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title: 'Parents’ recalled experiences of the child centred health dialogue in children
with overweight: a qualitative study'
authors:
- Malin Åsberg
- Mariette Derwig
- Charlotte Castor
journal: BMC Health Services Research
year: 2023
pmcid: PMC10045090
doi: 10.1186/s12913-023-09308-8
license: CC BY 4.0
---
# Parents’ recalled experiences of the child centred health dialogue in children with overweight: a qualitative study
## Abstract
### Background
Because overweight and obesity are still increasing and prevention of childhood obesity is more likely to be effective when initiated in preschool children, the Child Health Service in the south of Sweden developed a structured child-centred health dialogue model targeting all 4-year-old children and their families. The aim of this study was to describe parents’ recalled experiences of this health dialogue in children with overweight.
### Methods
A qualitative inductive approach with purposeful sampling was used. Thirteen individual interviews with parents (including 11 mothers and 3 fathers) were conducted and analysed with qualitative content analysis.
### Results
The analysis resulted in two categories: ‘A valuable visit with a subtle individual impact’ that described parents’ recalled experiences of the health dialogue and ‘*There is* a complex interaction between weight and lifestyle’ that reflected the parents’ perceptions of the relationship between their children’s weight and lifestyle.
### Conclusions
Parents recalled the child-centred health dialogue as important and described discussing a healthy lifestyle as one of the obligations of the Child Health Service. Parents wanted confirmation that their family lifestyle was healthy; however, they did not want to discuss the relationship between their family lifestyle and their children’s weight. Parents expressed that when their child followed the child’s growth curve, then this indicated healthy growth. This study supports using the child-centred health dialogue as a model to provide structure for discussing a healthy lifestyle and growth but highlights the difficulties of discussing body mass index and overweight, especially in the presence of children.
### Supplementary Information
The online version contains supplementary material available at 10.1186/s12913-023-09308-8.
## Background
Overweight and obesity are increasing among preschool aged children [1]. Obesity is associated with a range of physical and psychological health problems in children [2] and obesity in children often persists throughout adulthood [3]. Prevention of childhood obesity is more likely to be effective when interventions are initiated in preschool children or even earlier [4] and parents request interventions that can be applied in the preschool years, a period in which children’s behaviours and habits are shaped [5]. Both parents and professionals may have difficulty identifying preschool aged children with overweight and obesity [6]; therefore, body mass index (BMI) and the International Obesity Task Force (IOTF) standards a used to define ‘overweight’ and ‘obesity’ in growing children [7]. Swedish national data from 2018 based on 105,445 four-year-olds showed that the prevalence of overweight was $9\%$ and the prevalence of obesity was $2\%$ [8], which are comparable to the prevalence estimates of overweight and obesity among 2- to 7-year-olds (2006 to 2016) in other European countries (Netherlands, $10\%$; France, $11\%$; and Belgium, Finland and Hungary, $12\%$) [9].
In Sweden, the Child Health Service (CHS) reaches almost every child aged 0–5 years and their families. Nurses and physicians provide a package of healthcare visits to promote good health for all children during the early years, with extra visits according to need [10]. The 60-minute 4-year health visit includes measuring height and weight, calculating BMI, and testing vision, hearing, speech, motor skills and psychological development. The visit also involves a health dialogue and identifies overweight and obesity using the IOTF definitions [11]. However, nurses working within the CHS lack an evidence-based model to apply to children with overweight and obesity. Previous studies have shown that nurses described feelings of insecurity of the best approach to discussing overweight and obesity with children and their parents. They wanted appropriate guidance on how to raise the issue, and feared stigmatising children by linking them with childhood obesity [12, 13]. Discussing overweight with parents has been shown to be a delicate issue. Some parents find it difficult to believe that their child has overweight and dismiss the message [14], whereas other parents are concerned that talking to children about their weight might trigger low self-esteem or eating disorders [15]. Some studies have suggested that children with overweight, being labelled “as overweight” by their parents, may increase in BMI [16, 17]. Therefore, the Child Centred Health Dialogue (CCHD) has been developed as a structural approach that is designed to engage all family members in health promotion using sensitive non-judgmental communication skills and age-appropriate interactive, objective, and visual health promotion material. The CCHD consists of two parts: [1] a 10-minute universal part for all children and [2] a targeted part for families in which a child was identified with overweight. The universal part of the CCHD was implemented as part of the 4-year health visit and included a structured dialogue and eight illustrations that showed different aspects of a healthy lifestyle. A second tool, the BMI chart, was used to monitor each child’s growth and development and to identify overweight or obesity. At the end of the visit, each child received a storybook to read at home that had all the illustrations. The targeted part of the CCHD, the 45-minute ‘family guidance,’ was implemented 1–3 weeks after the universal 4-year health visit and was offered to children identified with overweight or obesity and their parents. This family guidance is inspired by the Standardized Obesity Family Therapy guidelines [18] and includes low-intensity treatment with a solution-focused approach that builds on family interactions as a basis for implementing and maintaining lifestyle changes.
A randomised controlled trial (RCT) that evaluated the CCHD’s effectiveness on weight gain in children with overweight produced a trend towards decreasing zBMI but was not statistically conclusive ($$p \leq 0.07$$) [19]. However, several core elements should be considered when performing intervention research in complex clinical settings, such as incorporating users’ experiences [20]. CHS nurses noted that involving children identified as having overweight was challenging, but that the CCHD training provided a structure that made it easier to guide children and their parents towards a healthier lifestyle [21]. Four-year-old children enjoyed participating in the health dialogue and were able to play an active role in the process, although their interpretations of the health messages sometimes differed from those of the adults [22]. Parents of children with normal weight reported that the universal part of the CCHD created supportive conditions for family members to actively participate, and they considered the health dialogue important and rewarding [23]. The aim of this study was to describe parents’ recalled experiences of the CCHD in children with overweight.
## Study design
A qualitative inductive approach using semi-structured interviews with parents of children with overweight at the 4-year health visit. The Consolidated Criteria for Reporting Qualitative Studies (COREQ) were followed [24]. This study was part of an RCT that evaluated the effectiveness of the CCHD in promoting healthy weight, registered at ClinicalTrials.gov (2016721LUC3).
## Setting and participants
Thirty-five child health centres in southern Sweden were included and randomised and stratified according to the Care Need Index (CNI), which measures an individual’s need for care based on socioeconomic factors [25]. Nurses randomised to the intervention group were trained to use the CCHD approach, the relevant tools, the illustrations that increase child participation, and the BMI growth chart [21]. Nurses were taught to discuss the child’s weight in a non-judgmental manner when overweight was identified, focusing on the child’s health and clarifying the importance of weight stabilisation [19]. A total of 238 children with overweight, according to the IOTF definition [7] who had been born between January 2013 and August 2014 were included in the intervention arm of the RCT [19].
The inclusion criterion for this study was parents of a child with overweight who participated in the intervention arm of the RCT. To achieve optimum variation within the sample, parents of enrolled children were selected strategically. First, one child from each centre allocated to the CCHD was randomly assessed: seven children from a centre in an area with high socioeconomic status and eight children from a centre in an area with low socioeconomic status, generating nine boys and six girls. Second, a letter was sent to the parents of these children explaining the purpose of the study and how the study would be performed. Thereafter, the first author (MÅ) contacted the parents, offered additional information and, for parents willing to participate, scheduled the date and location of the interview. Of the fifteen parents contacted by telephone, seven parents agreed to participate in the study, one declined, and seven did not answer repeated phone calls. To recruit more parents and ensure an even balance in CNI and child gender among the group, eight more children were selected. These children had participated in the intervention towards the end of the study period; therefore, their experience of the intervention was more recent. We followed the same procedure as before, and six parents responded and consented to participate.
## Data collection
Due to the pandemic, all interviews took place by video conference (Lund University Zoom, Lund University, Lund, Sweden) or by telephone, in accordance with the parents’ wishes. The interviews were carried out by the first author (MÅ) during November 2020 and April 2021. The interviews began by requesting background information; when an initial relation had been established, interviews continued using a semi-structured interview guide (Appendix 1). The interview guide includes opportunities for questions and suggestions for prompting more detailed responses when necessary. The first interview was conducted as a pilot interview and evaluated with the last author (CC). The interview guide fulfilled its purpose and remained unchanged; the pilot interview was included in the analysis. Interview durations were 10–35 min (median, 22 min). All interviews were recorded with the parents’ approval and transcribed verbatim.
## Analysis
Qualitative latent content was analysed using a structured stepwise method [26]. Two researchers (MÅ and CC) read the material several times to become familiar with the content. Meaning units were identified and thereafter condensed and coded based on their content. Similarities and differences among the codes were identified, and the codes were integrated into subcategories. In the latent analysis, the underlying meaning of the content was formulated into two categories (Table 1). All three authors were involved in the final evaluation of the results.
Table 1Profile of the parents and children ParentsChildrenN = 14 $$n = 13$$Female115Age (years)33–46 (mean, 40.7)6.7–7.9 (mean, 7.2)University10 (2 missing)Born in Sweden12CNI * ≥ 0.937Timespan between 4-year health visit and interview (years)2.5–3.9 (mean, 3.2)* CNI, Care Need Index ≥ 0.93 indicates living in an area with low socioeconomic status
## Results
Parents of 13 children were included in the study (Table 1). Ten interviews were performed with the mother, two with the father and one with both parents. During two interviews, the other parent was present, prompting at times. Participants had different ages and educational levels. They were born in Sweden, Europe or outside Europe. Some parents lived in areas with high socioeconomic status (CNI < 0.93), whereas others lived in areas with low socioeconomic status (Table 2).
Table 2Overview of meaning units, condensed meaning units, codes, subcategories and categories Meaning units Condensed meaning units Codes Subcategories Categories It might be good if the child is there, if you do it in the right way and have this with weight, the focus on weight I mean, that you do that in the right way so it does not become something dramatic, shameful, I do not think that is good. Child participation can be good but important not to focus on weight as this could be dramatic and shamefulChild participation without focus on weightOptimal child participation is complicatedA valuable visit with a subtle individual impactConsidering what I have read over the last few years; yes, it is literature describing the weights of adults, BMI is not a very good valuation… it is not widely representative of weights because circumstances can be so different. I have read that BMI is not a good valuation. Mistrust BMIBMI is neither adequate nor relevantA complex interaction between weight and lifestyle Seven subcategories in two categories were identified. One category, ‘A valuable visit with a subtle individual impact,’ described parents’ recalled experiences of the health dialogue and the other category, ‘A complex interaction between weight and lifestyle,’ reflected the parents’ perceptions of the relationship between their child’s weight and lifestyle (Table 3).
Table 3Subcategories and categoriesSubcategoriesCategoriesOne of many valuable health visitsIllustrations as tools to involve the childOptimal child participation is complicatedHigh expectations of the nurseA valuable visit with a subtle individual impactFollowing one’s growth curve is desirableBMI is neither adequate nor relevantA healthy lifestyle is natural but challenging to maintainA complex interaction between weight and lifestyle
## A valuable visit with a subtle individual impact
Parents reported that visiting the CHS during their child’s early years was a valuable experience. Discussing a healthy lifestyle was perceived as a logical part of both the CHS visit during the child’s early years and the 4-year health visit that included the CCHD. The parents recalled that the illustrations were simple and easy for most children to understand. Knowing the nurse prior to the dialogue helped parents and children to take part in the conversation and to make changes to improve the family’s health. Changes that were made could initially go unnoticed but were discovered after observing changes in the child’s health.
## One of many valuable health visits
Parents considered visiting the CHS as valuable and regarded the visits as checks to ensure the child was doing well. Parents expressed their overall gratitude and satisfaction with the CHS, and they were happy that the importance of a healthy lifestyle was highlighted. Sometimes, the 4-year health visit was recalled as a visit that focused on lifestyle and weight. At other times, it was difficult to distinguish the 4-year health visit from the other CHS visits because a healthy lifestyle had been discussed at several visits.
Parents reported that visits to the CHS seldom led to marked changes in their own family’s everyday life. They regarded change as unnecessary because they already had a healthy lifestyle and did not feel that the visits altered their behaviour. At the same time, parents recalled that the issues discussed during the visits were useful reminders for discussing lifestyle at home both between the parents and with the child. The parent could ask or remind the child what the nurse had said. Sometimes, this led to the parents eventually noticing changes. For example, the child stopped being constipated, even though they did not recall a specific alteration in lifestyle. We have different ways of doing things and different abilities but you want to do your best; so, if you’re given good advice, you try to follow it, and if the same advice comes from other sources, you are more likely to eventually make a change. ( Mother in interview no. 3, 7-year-old boy)
## Illustrations as tools to involve the child
Parents recalled that the illustrations both facilitated and complicated the dialogue about a healthy lifestyle. When listening to their child discussing the illustrations with the nurse, the parents were impressed that their child knew so much about a healthy lifestyle and was able to reflect on it. At times, parents thought that the illustrations could also impede the conversation as the child struggled to understand the message that was illustrated or had trouble interpreting the broader meaning of an illustration. Parents hypothesised that making the illustrations more fun and richer in content might help to involve the child even more, although they knew that the simple layout was designed to be easily understood by all children.[The illustrations] were quite simple, weren’t they? But maybe that’s because they should participate, the 4-year-olds, so it’s important that [the illustrations] are easy to understand. ( Mother in interview no. 8, 7-year-old boy)
## Optimal child participation is complicated
Parents expressed mixed feelings about involving the child in the conversation on a healthy lifestyle, especially if weight was discussed. They felt that the child listened more closely to the nurse than to the parent, even if both said the same thing. Furthermore, parents recalled that the child sometimes told the truth about less flattering aspects of family life, such as eating habits, which the parents were reluctant to talk about. At times, the parents recalled that involving the child in the discussions created difficulties. For example, the child may not focus on the issue that the adults were concerned about, or they may become uncomfortable if they felt that too much focus was on them. However, parents reported that after the visit their child was pleased that they were able to participate and was motivated by the fact that someone had listened to what they had said.
Parents worried that focusing on weight might generate feelings of guilt or even increase the risk of the child developing eating disorders. These worries could make it difficult for parents to talk freely in the presence of their child if the child was considered mature enough to understand what was said but not mature enough to understand the meaning of the conversation. Many kids simply accept their situation, so if someone actually asks them questions and allows them to express themselves, they might find this empowering: ‘if I say something, someone listens and it has an influence’ and then they will continue with that; so, there the illustrations were very good… however, these questions at the end about BMI, there you might not talk to the child. At that age they shouldn’t think about themselves in that way…in the end it’s judging their body. ( Mother in interview no. 3, 7-year-old boy)
## High expectations of the nurse
Dialogue with parents regarding a healthy lifestyle was considered a basic and important part of the CHS’s role and a good method of social education. Parents expected the nurse to provide comprehensive and specific information on healthy living, with a particular focus on each family’s lifestyle. This was facilitated when parents became familiar with their CHS nurse, and changing a family’s CHS nurse was considered counterproductive.
Parents recalled being grateful for information that had been prepared by the nurse so that they could focus on assimilating the advice. Parents recalled that they were attentive to the CHS nurse and expected the advice provided to be accurate and up to date. Parents wanted the nurse to confirm that their own lifestyle was healthy and if the nurse did not suggest any changes, parents assumed that everything was in order.
Parents emphasised the importance of the nurse being able to assess each family’s lifestyle within the appropriate cultural context and provide useful information to those who needed it. Parents preferred to receive information via dialogue with the nurse or as specific instructions. The parents also asked for written information because they did not remember everything that was said during the visit and some parents experienced language barrier difficulties with the spoken word. Given our interest, I wanted the information provided to be comprehensive and up to date. I did not want to settle for what we have known for 40 years about children’s diets. ( Mother in interview no. 10, 7-year-old girl)
## A complex interaction between weight and lifestyle
Parents recalled being suspicious and mistrustful of discussions about weight because they did not think their children had overweight. The relevance of measuring BMI in young children was questioned, as was the usefulness of labelling young children as having overweight. The parents preferred the regular growth chart to see whether their child followed the appropriate growth curve. They wanted confirmation that they already had a healthy lifestyle but did not want to talk about lifestyle in relation to weight.
## Following one’s growth curve is desirable
When parents referred to the growth chart, they stated that when their child followed the appropriate growth curve everything was okay. Parents thought that at some ages children were allowed to be over the growth curve on the growth chart. Often the child was referred to as large at birth, a little above their growth curve, or not having overweight anymore. At times, parents used expressions such as chubby, robust or sturdy, or said that the child did not look overweight or that the child was overweight but that this was only noticeable when they were compared with other children. He has always been a chubby child you might say, but he has always followed his growth curve; he has always been shorter and weighed a bit more [than some other children], but not to a worrying extent. ( Mother in interview no. 11, 7-year-old boy) Parents did not recall nurses using the word overweight at the 4-year health visit but instead recalled that the nurse had said that there was nothing to be concerned about and that the child was of normal weight. They described that this made them feel that there was nothing to worry about.
## BMI is neither adequate nor relevant
Despite their wish to focus on a healthy lifestyle rather than weight, parents said they recalled wanting to know whether their child had overweight and suggested the height and weight curve as a basis for these conversations. At the same time, parents expressed a general mistrust of the concept of BMI and recalled being surprised and upset when the CHS measured a child’s BMI, either during their own visit or when this was reported by other parents. Using BMI was experienced as problematic. Parents understood that BMI was used to determine whether an individual had overweight but believed that individuals had different preconditions and muscle masses, and that these factors should be taken into account. To illustrate, parents described themselves as having a high BMI without having overweight because they had an appropriate balance between muscle and fat. Therefore, parents stated that while their child was growing, there was no need to measure BMI.To put a BMI growth chart on a child is a little bit too much, a child develops all the time, they shoot up in height, stop growing, and then all of a sudden your child is overweight, obese maybe and then you need to put your child on a diet? No, you should not put a child on a diet! The child should be allowed to follow the growth chart. ( Mother in interview no. 2, 7-year-old boy)
## A healthy lifestyle is natural but challenging to maintain
Parents considered a healthy lifestyle to be about finding a balance in their everyday family life. They recalled trying to focus on aspects that promote good health, such as what to eat and what sports the children could participate in rather than discussing weight in front of their children. Various factors affected parents’ perceptions of a healthy lifestyle and the best ways to achieve this. Bad memories and body shaming experiences from a parent’s childhood could have negative effects, as could their own experience of having overweight, having an eating disorder, or having a preoccupation with weight or dieting. Parents recalled often trying to conceal these thoughts because they did not want their children to develop similar problems or perhaps provoke eating disorders. At home, we are really cautious, we do not want the child to lose confidence (...) We try to never compare them at home. I am overweight, I must rethink, I must change my eating habits, I must start exercising; so the kids come along, they want to be like their parents, but you never say these things to the child. ( Father in interview no. 7, 7-year-old girl) One difficulty in maintaining a healthy lifestyle was that parents were not always able to control their child’s environment. For example, grandparents may not adhere to family rules and may give the child cookies without the parents’ permission.
Parents thought they had healthy lifestyles, and they wondered what they were doing wrong and what they could have done differently if their child was identified as having overweight. They found it difficult to understand why their child’s BMI was greater than normal when the nurse had confirmed that they were doing everything right. They compared their child with his/her siblings who had normal weight and shared the same lifestyle. This was used to justify continuing with the current lifestyle. She and her sister have gained a lot of weight and we’re working on it, but you can’t make drastic changes with kids and you don’t want to put them on a diet. I feel we can hardly have candy on Saturdays or take a cake in the middle of the week and I think you should be able to do that… I grew up with a bad attitude towards my body, but I have managed to deal with it. ( Mother in interview no. 4, 8-year-old girl)
## Discussion
This study describes parents’ recalled experiences of the CCHD for children with overweight. One significant finding was that parents of children with overweight did not have specific recollections regarding the CCHD. Specific memories of each visit had faded and none of the parents recalled feeling upset or being questioned about their lifestyle during their visits; however, the parents retained positive impressions of the visits.
A possible explanation for this observation is that the nurses trained in CCHD might have tailored discussions regarding each child’s weight and each family’s lifestyle to suit each family. The use of positively framed messages, such as the CCHD illustrations, is considered a neutral method for discussing sensitive topics such as lifestyle and can tailor dialogue to meet a family’s needs [21, 27]. The CCHD trained nurses noted that deciding how and when to raise the issue of overweight was difficult. Nurses felt responsible for helping the child and family to achieve a healthier lifestyle, but on the other hand, they wanted to be sensitive to the perceived needs of the child and the family [21]. Parents appreciated the importance of talking about a healthy lifestyle during their visits to the CHS. They thought that discussing lifestyle was one of the obligations of the CHS. However, the parents stated that they already had healthy lifestyles. Therefore, they believed that the health messages from the CHS were most applicable to other families, as described in an *English focus* group study among parents of 4- and 5-year-old children who received feedback on their child’s weight [14].
Overall, parents were positive about including their child in the CCHD and were impressed with their child’s ability to participate in the discussion and reflect upon the health messages. In other words, the illustrations improved the children’s health literacy, allowing them to understand and reflect upon the messages and make healthy choices for themselves. This observation is consistent with a recent systematised review of research literature in which storytelling, visual materials and reflection were described as core elements in supporting health literacy development and providing motivation to make healthy choices [28]. Sometimes, parents expressed that their children misinterpreted the health messages associated with the illustrations and believed that the illustrations hindered their children’s participation in the health conversation. That adults and children interpreted the illustrated health messages in different ways has been confirmed by a study elucidating children’s experiences of the CCHD [22]. The study was based on observations and interviews with children who had recently taken part in the CCHD; it showed that children’s and adult’s interpretations of the illustrations sometimes differed and that children may become preoccupied with their own interpretations and do not focus on the messages that the nurses wanted to discuss.
Similar to a Norwegian study involving parents of children aged 2.5–5.5 years who had been identified as having overweight [29], we found that parents were reluctant to include their children in the health dialogue if the word overweight was being used, due to the risk of eliciting feelings of guilt or stigmatising the children. This is corroborated by another Swedish study involving parents of 3- to 7-year-old children with overweight or obesity [15], which stated that some parents did not wish to discuss the topic of overweight in the presence of their children to protect their children from weight conversations with negative connotations. However, previous research has shown that children ask for age-appropriate information on their own health status and according to the United Nations Convention on the Rights of the Child, children are entitled to such information. A study in which children with overweight who were aged 8–13 years participated in a health course suggested that participation in a non-judgmental health dialogue could help children to improve their health. These children articulated that the course helped them to develop strategies to cope with challenges and improve health behaviours in their everyday lives [30]. Further studies will be needed to determine whether very young children with overweight should be involved in such discussions. This is particularly important because children are end users of interventions to prevent childhood obesity and should be involved in the early stages of intervention development as much as possible [22].
Moreover, parents thought that measuring a child’s BMI was unhelpful, and they wanted to use a regular growth chart instead. There was a mistrust of measuring BMI in general and especially of using BMI to identify children with overweight. However, parents did want to know whether their child had overweight. Some parents considered BMI a complex measurement, rather than a means of highlighting the relationship between a child’s height and weight. Other studies have indicated that parents have difficulty understanding BMI charts [31, 32]. Parents in this study communicated that children who followed their growth curves on the growth chart were exhibiting healthy growth and could not have overweight, regardless of the relationship between height and weight. This may be an important insight for CHS nurses who could implement the parents’ confidence in their children’s growth curves by illustrating each child’s growth not only using the weight and height growth charts but also the BMI growth chart from an early age, when parents visit the CHS.
Over the last few decades, there has been a prevailing assumption that making parents aware that their child has overweight is a necessary step in initiating appropriate changes in lifestyle [33, 34]. However, some studies have found that parents’ awareness of their children having overweight does not create positive changes and that the children’s BMIs may actually increase [16, 17]. The parents in this study did not consider their children overweight and did not remember the nurses telling them that their children had overweight. One explanation might be that the nurses did not use the word overweight but discussed the child’s weight development in a positive manner, engaging the child and the parents in a non-judgmental dialogue about health and health behaviours, in accordance with the CCHD guidelines. There is evidence that healthy behaviours do not automatically develop when unhealthy behaviours are reduced but instead require positive reinforcement [35, 36]. For example, public health media messages may be motivating when they are formulated in a positive manner and focus on making healthy behavioural changes [37]. Another explanation is that nurses did not raise the issue of overweight in the presence of the child because they, like the parents, feared exacerbating the stigma of childhood obesity [12, 13]. These observations emphasise the need to train health professionals how to communicate weight-management messages and the need for initiatives that help to end weight stigma and discrimination on the societal level [38].
This study had both strengths and limitations. There was variation in the ages, gender, educational levels and CNIs of parents recruited, which enhanced the richness of our data. However, including background data on the parents’ weights and lifestyle factors could have improved the credibility of our findings further. All parents were contacted several times and all of those who responded wished to participate in the study, except one parent who did not remember their health visit.
Because several years (2–4 years) had passed between each child’s 4-year health visit and our study, our results highlight the long-term effects of the CCHD on parents.
All authors have extensive clinical experience of conversations with parents and children in various healthcare situations and are well acquainted with the CHS. The first (MÅ) and last (CC) authors were not involved in the RCT or in conversations on lifestyle or weight with families within the CHS. To increase confirmability, our analysis was performed with frequent reference to the study aims and the interview guide, and the method described by Graneheim and Lundman was followed [26]. The second author, who was the principal investigator in the RCT, was not involved in the primary analysis of the interviews, to minimise the risk of bias. The authors discussed the analysis until they agreed completely on the final categories. Quotations from parents’ statements are included in the results to help the reader to assess the study [39].
## Conclusions
Parents recalled the CCHD as important and described discussing a healthy lifestyle as one of the obligations of the CHS even if they believed this was not always relevant for their own family. Parents considered their children’s participation in the CCHD as valuable and were impressed at their children’s ability to reflect on their own health. In this way, the CCHD aligns with the aims of the CHS in promoting child health and with the United Nations Convention on the Rights of the Child, which states that children have the right to actively participate in their own healthcare. This study is consistent with previous studies that found parents wanted confirmation that their own family lifestyle was healthy, but preferred not to discuss the relationship between their own family lifestyle and their children’s weight. BMI and overweight were considered potentially stigmatising concepts that were not conducive to promoting a healthy lifestyle and should not be discussed in the presence of children. Parents believed that if their child followed the child’s growth curve on the growth chart, then this indicated healthy growth. This insight may inform weight related conversations. This study indicates that the CCHD can be used to provide a structure for discussing a healthy lifestyle and growth, but more research is needed to understand the best methods for broaching the topic of overweight with parents in the presence of the child recognising the rights of the child.
## Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary Material 1
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|
---
title: Implementation fidelity to a behavioral diabetes prevention intervention in
two New York City safety net primary care practices
authors:
- Avni Gupta
- Jiyuan Hu
- Shengnan Huang
- Laura Diaz
- Radhika Gore
- Natalie Levy
- Michael Bergman
- Michael Tanner
- Scott E. Sherman
- Nadia Islam
- Mark D. Schwartz
journal: BMC Public Health
year: 2023
pmcid: PMC10045092
doi: 10.1186/s12889-023-15477-2
license: CC BY 4.0
---
# Implementation fidelity to a behavioral diabetes prevention intervention in two New York City safety net primary care practices
## Abstract
### Background
It is critical to assess implementation fidelity of evidence-based interventions and factors moderating fidelity, to understand the reasons for their success or failure. However, fidelity and fidelity moderators are seldom systematically reported. The study objective was to conduct a concurrent implementation fidelity evaluation and examine fidelity moderators of CHORD (Community Health Outreach to Reduce Diabetes), a pragmatic, cluster-randomized, controlled trial to test the impact of a Community Health Workers (CHW)-led health coaching intervention to prevent incident type 2 Diabetes Mellitus in New York (NY).
### Methods
We applied the Conceptual Framework for Implementation Fidelity to assess implementation fidelity and factors moderating it across the four core intervention components: patient goal setting, education topic coaching, primary care (PC) visits, and referrals to address social determinants of health (SDH), using descriptive statistics and regression models. PC patients with prediabetes receiving care from safety-net patient-centered medical homes (PCMHs) at either, VA NY Harbor or at Bellevue Hospital (BH) were eligible to be randomized into the CHW-led CHORD intervention or usual care. Among 559 patients randomized and enrolled in the intervention group, $79.4\%$ completed the intake survey and were included in the analytic sample for fidelity assessment. Fidelity was measured as coverage, content adherence and frequency of each core component, and the moderators assessed were implementation site and patient activation measure.
### Results
Content adherence was high for three components with nearly $80.0\%$ of patients setting ≥ 1 goal, having ≥ 1 PC visit and receiving ≥ 1 education session. Only $45.0\%$ patients received ≥ 1 SDH referral. After adjusting for patient gender, language, race, ethnicity, and age, the implementation site moderated adherence to goal setting ($77.4\%$ BH vs. $87.7\%$ VA), educational coaching ($78.9\%$ BH vs. $88.3\%$ VA), number of successful CHW-patient encounters (6 BH vs 4 VA) and percent of patients receiving all four components ($41.1\%$ BH vs. $25.7\%$ VA).
### Conclusions
The fidelity to the four CHORD intervention components differed between the two implementation sites, demonstrating the challenges in implementing complex evidence-based interventions in different settings. Our findings underscore the importance of measuring implementation fidelity in contextualizing the outcomes of randomized trials of complex multi-site behavioral interventions.
### Trial registration
The trial was registered with ClinicalTrials.gov on $\frac{30}{12}$/2016 and the registration number is NCT03006666.
### Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-023-15477-2.
## Background
The NationalInstitutes for Health recommends fidelity measurement in health behavior studies because without the knowledge of implementation fidelity, it may be impossible to draw correct inferences about the effectiveness of or to replicate an intervention [1]. Erroneous inferences may lead to invalid conclusions about the relationships between the intervention components and outcomes, especially in pragmatic studies of complex behavioral interventions [2, 3]. However, most pragmatic trials do not report systematic assessment of implementation fidelity and very few assess how participant and contextual factors may influence fidelity. For example, a review found that only $3.5\%$ of complex behavioral interventions for drug abuse adequately addressed intervention fidelity to planned core intervention components [4].
CHORD (Community Health Outreach to Reduce Diabetes), launched in 2017, is a cluster-randomized, pragmatic trial that tests a Community Health Worker (CHW) driven intervention to promote healthy lifestyle changes to reduce the incidence of Type II diabetes mellitus (DM) among pre-diabetic patients cared for in two safety-net primary care sites that serve veterans, or uninsured and Medicaid populations [5]. We sought to improve the understanding of subsequent CHORD trial results, as well as to learn about how contextual factors affected implementation of the CHORD intervention, by assessing fidelity to its four core components across the study’s two participating sites.
By reporting on the fidelity of the CHORD study implementation, our study attempts to fill a gap in systematic documentation and reporting of implementation processes of complex behavioral interventions [4, 6]. In addition to clarifying causal mechanisms, assessment of implementation fidelity can provide critical information to guide future implementation of the intervention [4, 7–9]. Examining implementation fidelity is particularly necessary for multicomponent, complex behavioral interventions because of their higher likelihood of deviation from the protocol [9]. Few studies conduct concurrent fidelity assessment as opposed to retrospective. Concurrent process evaluations are important as they can capture implementation experiences in real time [9]. By building in the collection of fidelity measures and moderating factors in CHORD implementation, this study seeks to address this gap in the literature. Moreover, the study responds to the general calls for conducting quantitative evaluations of fidelity in intervention studies [9].
Figure 1 shows the logic model for the CHORD intervention. Evidence supports engagement of CHWs by safety net primary care practices for improving health, knowledge, behaviors and outcomes for underserved communities [10, 11]. The CHORD CHWs deliver evidence-based lifestyle interventions known to prevent DM among people with prediabetes [12–14]. CHWs are trusted members of the community who share lived experience and are familiar with community resources and norms [5, 10, 15]. Culturally congruent CHWs can bridge gaps between communities and health care systems to facilitate positive behavioral and lifestyle changes [12–14]. The evidence-based lifestyle interventions implemented in CHORD were based on guidelines from the National Diabetes Prevention Program (DPP) with a focus on healthy eating and physical activity [16]. People with prediabetes who participated in such a structured lifestyle change program reduced their risk of DM by $58\%$ [16].Fig. 1Logic Model and the Theory of Change of the CHORD Intervention CHORD is a complex behavioral intervention, where CHWs facilitate patients’ adoption of guideline-based lifestyle changes by using four behavioral intervention components: patient goal setting; education topic coaching; facilitating primary care (PC) visits; and referrals to address social determinants of health (SDH) [17]. We assessed fidelity to these four behavioral intervention components and examined factors affecting implementation fidelity using the Conceptual Framework for Implementation Fidelity (CFIF) [6, 7]. The overarching purpose of this analysis is to inform researchers and program implementors about the level of fidelity achievable of an intervention such as CHORD in the context it was implemented.
## Trial participants and description
The CHORD trial’s priority population was patients with prediabetes receiving care at two PC clinics, the *Manhattan campus* of the VA NY Harbor Healthcare System (VA), and Bellevue Hospital Center (BH) of New York City’s municipal hospital system [5]. Protocol details have been described previously [5]. This study was approved by the New York University Langone Health and the Veterans Affairs Institutional Review Boards and was registered with clinicaltrials.gov (NCT03006666) on $\frac{30}{12}$/2016. Informed consent was obtained from all the participants in the study. All the procedures were followed in accordance with the relevant guidelines (eg. Declaration of Helsinki) along with the rest of the ethical declarations. Findings were reported in accordance with the StaRI checklist for implementation studies [18].
Briefly, all PC clinicians within each site were randomized to intervention or usual care. Eligible patients were seen by one of the study clinicians (at least 1 PC visit in the past 2 years at the VA or at least 3 PC visits in the past 2 years at BH), were between ages 18–75 years, had ≥ 1 glycosylated hemoglobin (HbA1c) between 5.7–$6.4\%$ at baseline, no prior DM diagnosis, and ability to communicate in English or Spanish. Two CHWs, members of the study team assigned to each site, consented and enrolled eligible intervention patients, who then completed an intake survey, and began a 12-month intervention during which at least monthly encounters were planned between the CHW and patient. The two CHWs at each site made up to ten attempts to call and enroll each intervention group patient. A successful encounter was defined as when the CHW was able to speak with the patient in-person or by phone, or when a letter or a text message was delivered (no evidence of failure to deliver was apparent). During these encounters, CHWs delivered one or more of four core intervention components.
## Implementation of CHORD behavioral components
In the first component, CHWs established individualized goals with each patient and completed a 6-item, Patient Activation Measure (PAM) [19, 20]. These goals were then translated into a health action plan (HAP) tailored to each patients’ goals, PAM score, and preferences. Second, using the HAP, CHWs chose among 22 educational topics organized into 5 modules (prediabetes, healthful eating, MyPlate [21] and plate portions, physical activity, and stages of change) to conduct education sessions with patients, and provide information packets. Third, CHWs called or met patients before and/or after PC visits to encourage them to discuss diabetes prevention with their clinician or to review their after-visit summaries regarding diabetes. Finally, CHWs facilitated referrals as needed to hospital or community-based programs to help support behavioral change or address identified social needs.
## CHW training and fidelity monitoring
To facilitate and standardize the implementation of the intervention, CHWs received comprehensive training and then ongoing feedback during weekly team meetings and case review sessions. To address behavioral components, CHWs completed training on coaching competencies, motivational interviewing, mental health and nutrition needs, weight management and healthy lifestyle programs, multicultural competence, diabetes and diabetes prevention, elderly and loneliness, and technical trainings on using Excel, Outlook, and REDCap (Research Electronic Data Capture).
## Data collection
Figure 2 shows the modified version [6] of the Conceptual Framework for Implementation Fidelity (CFIF) [7] which guided our data collection and analyses. The key indicator of implementation fidelity according to CFIF is adherence, defined by Consolidated Framework of Implementation Research (CFIR) as “whether a program service or intervention is being delivered as it was designed or written.” [ 7] We measured adherence as coverage(“what proportion of target group participated in the intervention”) [6], content(“was each of the intervention components implemented as planned”) [6], and dosage, which includes duration and frequency(“amount of an intervention received by participants” [7], or “were the intervention components implemented as often and for as long as planned”) [6]. We also measured two factors that could moderate fidelity: Context(“what factors at the political, economic, organization, and work group levels affected the implementation”) [6], and participant responsiveness (“how were the participants engaged with the intervention”).Fig. 2The Modified Version of the Conceptual Framework for Implementation Fidelity that guided Fidelity Assessment of the CHORD intervention (adapted from Carroll et al. and Hasson et al.) Data on the CFIR implementation fidelity elements identified above were collected from the start of the CHORD trial (December 2017) until October 2019, using standardized Research Electronic Data Capture (REDCap) [22] forms completed by CHWs for each patient to record their demographics, information on outreach, enrollment, and intake, and weekly logs on encounters. Electronic Health Records (EHR) from VA and BH provided descriptive data on study participants and their healthcare utilization.
## Measures of fidelity and fidelity moderators
Table 1 shows the data sources for measures of fidelity and fidelity moderators. Coverage was the percent of patients who completed an intake and hence were able to receive the intervention. Content adherence was the percent of patients who received each of the four intervention components. Dose frequency was how much of the four components was received measured as an average or median across all intervention patients and dose duration measured for how long the intervention was delivered. Table 1Study measures and their data sources mapped to the framework constructsFramework constructReported measure from the CHORD trialCorresponding CHORD intervention core component if applicableData SourceFidelity CoveragePercent of outreached patients who were enrolledN/AOutreach formPercent of enrolled patients who completed intakeN/AIntake formPercent of intake patients who completed the first core component of establishing at least one goal or a Health Action Plana1Goal Setting Form Content adherencePercent of intake patients who established at least one goal or a Health Action Plana1Goal Setting FormPercent of intake patients who received coaching on at least one education topic2Encounter FormPercent of intake patients who received coaching on all education modules2Encounter FormPercent of intake patients who had at least 1 PC visit3Electronic Health RecordPercent of intake patients who received at least one referral4Encounter and Referral FormsPercent of intake patients who received at least one successful encounterN/AEncounter FormPercent of intake patients who received all four core components in some capacity1–4Goal Setting, Encounter and Referral Forms Dose- frequencyMedian number of goals established1Goal Setting FormMedian number of goals completed1Goal Setting FormMedian number of education sessions delivered2Encounter FormMedian number of education modules discussed2Encounter FormMedian number of PC visits3Electronic Health RecordMedian number of referrals4Encounter and Referral FormsMedian number of successful encountersN/AEncounter Form Dose- durationMedian duration (days) of follow-up timebN/AEncounter FormModerating factors Participant responsivenessBaseline Patient Activation Measure Score (< median vs. ≥ median)N/AIntake Form ContextClinical site (VA vs. BH)N/AStudy FormaPercent of intake patients who established at least one goal or completed establishing a Health Action Plan was operationalized as a measure of two fidelity constructs – content adherence and coverage – because this component was the first component that patients were required to complete in order to proceed with other components of the interventionbDuration of follow-up is the time from beginning of outreaching till the last successful encounter Measures of hypothesized moderators:Participant responsiveness, measured as the baseline Patient ActivationMeasure (PAM) score, which measures the extent to which patients are activated for participating in managing their health and healthcare including seeking health information and readiness to change [23–25]. According to Hasson et al., “ the uptake of the intervention depends on the responsiveness of those receiving it” (page 2). [ 6] We hypothesized that people with higher PAM score (indicating higher activation to participate in health) will be more responsive and motivated to participate and receive the intervention. Context, measured as the two clinical sites. As the intervention components were designed to be delivered by CHWs to patients, the clinical site was selected to capture systematic differences in the sociodemographic and economic context of patient populations at the two sites. It should be noted that, organizational differences between the two sites were not directly hypothesized to moderate fidelity measures of CHORD intervention which relied on individual encounters between CHWs and patients. Therefore, clinical site reflects differences in patients’ social profiles at the two sites. We did not assess the role of other specific patient characteristics that are not explained by their chosen site of healthcare.
## Analysis
Fidelity measures of coverage, content and dose were reported using applicable descriptive statistics including percentage for categorical variables or median with inter-quartile ranges (IQRs) for continuous or count variables. To evaluate fidelity moderation, we computed unadjusted p-values from Chi-square or Mann–Whitney U test and adjusted p-values from regression models that controlled for patient gender, language, race, ethnicity and age. To assess moderation by PAM score, we dichotomized the score as above or below the median score. As a sensitivity analysis, we also compared patients with a total maximal score of 24 vs. < 24. The first regression models treated PAM score as the primary independent variable, and the second set treated clinical site as the primary independent variable. Each set of models included separate models for each fidelity measure as the dependent variable. Logistic regression models were used for binary measures of coverage and content adherence (received or not received the intervention component). Linear regression models were used for fidelity measures of dosage that were continuous, and negative binomial regression models were used to model the fidelity measure of dosage that was a count variable.
Among patients who completed intake ($$n = 444$$), the denominator for our fidelity assessment, 32 patients ($7.2\%$) with missing PAM scores were excluded from fidelity moderation analysis by PAM score. Chi-square test or Mann–Whitney U test, as appropriate, were used to compare two population groups—how eligible/outreached patients differed by their enrollment status and how enrolled patients differed by their intake completion status – on their gender, language, race, ethnicity, age at outreach and PAM score. All quantitative analysis was conducted in the R statistical software environment [26], and statistical significance required an alpha < 0.05.
## Coverage
Among 1449 eligible patients assigned to CHWs for outreach, we excluded 471 patients with incorrect/no contact information or who could not be reached after ten phone calls, 416 who declined to participate, and another three found to be ineligible. Of the remaining 559 patients who enrolled in the intervention arm, 444 ($79.4\%$) completed an intake survey and were eligible to receive the intervention, hence comprised the analytic sample for fidelity assessment (Fig. 3). The 559 enrolled and the 890 unenrolled patients differed in their primary language, race, ethnicity, implementation site and median age at outreach. Those who enrolled were more likely to be Spanish speaking, Black and Hispanic (Supplemental Table 1). However, among those enrolled, patients completing intake vs. those not completing intake were similar (Supplemental Table 2). Among intake patients, 362 ($81.5\%$) established a HAP, the first core component. Fig. 3CONSORT Flow Diagram for the Intervention ArmTable 2Implementation fidelity (Content Adherence) for each intervention componentMeasureRelevant core componentNumber completing the component% Completing the component($$n = 444$$)Percent of intake patients who established at least one goal or a Health Action Plan$136281.5\%$Percent of intake patients who received coaching on at least one education topic a$236782.7\%$Percent of intake patients who received coaching on all education modules$210640.0\%$Percent of intake patients who had at least 1 PC visit$335379.5\%$Percent of intake patients who received at least one referral$420045.0\%$Percent of intake patients who received at least one successful encounter bN/A$35479.7\%$Percent of intake patients who received all four core components in some capacity1–$415534.9\%$aThe number of patients who received coaching on at least one education topic were more than the number of patients who established at least one goal (or a Health Action Plan) because although not designed to, 5 patients received an educational coaching session before they established a goal (or a Health Action Plan)bA successful encounter between a patient and a CHW was defined as an encounter (after the completion of the intake survey) where the CHW was able to speak with the patient either in-person or by phone, or when a letter or a text message was delivered (that is, when no evidence of failure to deliver was apparent). The number of patients with a successful encounter is less than the number of patients who completed at least one goal or the number of patients who received coaching on at least one education topic because although not designed to, for some patients, after a patient completed an intake, goal establishment or education sessions happened without a successful encounter
## Content adherence
Eighty percent of patients had ≥ 1 successful encounter with the CHW (Table 2). About $80\%$ of the patients completing an intake established ≥ 1 goal for their HAP, received coaching on ≥ 1 education topic or had ≥ 1 PC visit, indicating high content adherence to these three core components. Forty percent received coaching on all five education modules. Forty-five percent received a SDH referral, most of which were for a healthcare visit, with other referrals to facilitate healthy lifestyle, employment/workforce training, social security benefits, or mental health services. Overall, $34.9\%$ received all four core components in some capacity.
## Dose – frequency and duration
Among the 362 patients who established a HAP, more than half established three goals (median 3; IQR: 2, 3), more than half completed ≥ 1 goal, and $25\%$ completed three goals (median:1; IQR: 0, 3). The median number of education sessions delivered was 18 (IQR: 8, 33) and the median number of education modules covered was four of five (IQR: 2, 4). Median number of referrals was one (IQR: 1, 3), with $25\%$ receiving ≥ 3. The median number of PC visits was three (IQR: 2,5). A total of 4,072 encounters with patients were documented by CHWs, of which $55.6\%$ were successful. The median number of successful encounters per patient was five (IQR: 3, 8) (Table 3). Among them, $9.9\%$ had 12 successful encounters. The median duration of follow-up was 411 days [IQR: 341, 446], as we extended the overall intervention period to > 12 months for some patients. Table 3Implementation fidelity (frequency and duration) for each intervention componentMeasureRelevant core componentMedian [IQR]Frequency Median number of goals established13 [2,3] Median number of goals completed11 [0, 3] Median number of education sessions delivered218 [8,33] Median number of education modules discussed24 [2,4] Median number of PC visits33 [2,5] Median number of referrals41 [1,3] Median number of successful encountersN/A5 [3,8]Duration Median duration (days) of follow-up timeaN/A411 [341, 446]aDuration of follow-up is the time from beginning of outreaching till the last successful encounter
## Patient activation
The median PAM score was 18 of a maximal score of 24. None of the fidelity measures were moderated by PAM score when dichotomized at the median (Supplemental Table 3) or at the highest score of 24 versus < 24 (results not presented).
## Context
The implementation of the CHORD intervention was moderated by clinical site, with $60\%$ of patients from BH and $40\%$ from VA. VA patients had higher coverage and overall content adherence than BH. But a greater percentage of BH patients received coaching on all education modules and received all four core components. Three content adherence measures, including percent of patients who received ≥ 1 referral, ≥ 1 successful encounter and ≥ 1 PC visit, were similar at the two sites. Three dose-frequency measures, including median number of PC visits (4.0 VA vs. 4.0 BH), number of education modules covered (4.0 VA vs. 4.0 BH), and the number of successful encounters (4.0 VA vs. 6.0 BH), differed between the two sites (Supplemental Table 4).
## Discussion
In the CHORD study, we hypothesized that trained CHWs, through individualized goal setting, educational coaching, and facilitated referrals, would support positive lifestyle changes and prevent the onset of diabetes among patients with prediabetes. However, an intervention may not affect lifestyle change if it deviates from its protocol during implementation. In this concurrent process evaluation of the CHORD intervention, we examined implementation fidelity and fidelity moderators. Our analysis demonstrated moderate to high (depending on intervention component) rates of implementation fidelity of CHORD, and moderation by implementation site. The level of implementation fidelity achieved in this intervention is likely to be sufficient to justify inferences drawn about the impact of the intervention on the outcomes. However, with less than $100\%$ adherence and the variability observed in these components, as is likely common in complex behavioral interventions, the analysis of CHORD outcomes will provide an opportunity to explore the relative importance and impact of each of these components, accounting for their degree of implementation fidelity. Our use of quantitative methods for fidelity assessment will allow us to use these measures in outcome data analyses to determine the role of fidelity in observed outcomes [1, 27].
We found that CHWs completed an intake with nearly $80\%$ of the patients enrolled in the intervention arm, and three of the four core components (goal setting, education and PC visits) were delivered to nearly $80\%$ of the patients. Even though coverage and content adherence were moderate to high, there was high variability in the dosage. While the fourth core component in our intervention, referrals for social determinants of health and promoting access to healthy lifestyle choices, was delivered to only $45\%$ of the patients, a quarter received 3 or more referrals. As referrals were designed to be tailored to each patient’s circumstance, the dosage of referrals cannot be directly associated with outcomes as more referrals are not necessarily better. Further, we do not know if the remaining $55\%$ patients who did not receive a referral needed one.. We strived to deliver all core components for each patient, but we had not established, a priori, thresholds for adherence for core components among study participants. Our analysis explores the extent to which we attained implementation success as measured by percent of patients for which the core components were delivered. An implementation fidelity analyses of a randomized trial delivering a complex care continuum intervention for frail elderly people in Sweden also reported high variability in the adherence to intervention components. On a 4-point scale (never, seldom, sometimes, often, always), while most components were reported to be ‘always’ delivered, several were only ‘seldom’ delivered [28]. In another study implementing a program to promote care aide involvement in formal team communications about resident care, the adherence was comparable to our study. Nearly $63\%$ of the units participated in all three workshops and nearly $80\%$ of the units participating were delivered the inter-team activities [9]. However, some measures were higher than our study – $93\%$ of the units in this trial completed goal setting [9]. In another trial implementing a complex behavior change intervention to enable participants living with long-term musculoskeletal pain to improve their quality of lives, although the median score on adherence to components ranged from 1.67 to 2.00 on a scale of 0 to 2.00, overall course score of 2.00 showed $100\%$ adherence to these components [29]. Higher fidelity in interventions such as those targeting pain can be explained by the nature of the intervention. According to CFIR, the relative advantage of the intervention plays a key role in implementation success: [30] “If users perceive a clear, unambiguous advantage in effectiveness or efficiency of the innovation, it is more likely the implementation will be successful….benefits of the innovation must be clearly visible (observable) to assess relative advantage” [31]. The benefits of our intended outcome, diabetes prevention in patients with pre-diabetes, are more intangible and hence could have reduced patients’ motivation to participate fully in the intervention components.
We assessed the role of patient motivation in our study by examining moderation of fidelity measures by PAM score. Null findings on moderation by PAM score was unexpected because patient activation measured by PAM scores has been found to be positively associated with engaging in healthy lifestyle behaviors and exhibiting readiness to change [25]. PAM score at intake might be limited in its representation of the concept of ‘participant responsiveness’ as defined in the CFIF [6, 7]. Patient activation might not be directly associated with the perception of patients about the effectiveness of an intervention in improving health, even though they value health. Finally, using an adapted, shortened version of the PAM [19, 20], may not have fully measured this construct of activation.
The pragmatic nature of the CHORD trial permitted and promoted continuous adaptations. While this improved the meaningfulness of our intervention, it resulted in deviations from the original intervention protocol, decreasing fidelity. We adapted implementation in response to ongoing developments and situations. For example, the recruitment and follow-up process changed significantly after BH adopted a new EHR system in the second year of the CHORD trial. Provider communication and follow-up was adapted to align with their work schedule. In five cases, CHWs delivered education sessions before establishing goals as an engagement strategy to demonstrate how the intervention could be useful and encourage patients to set goals. In addition, the number of patients with a successful encounter was less than the number of patients who completed at least one goal or the number of patients who received coaching on at least one education topic. This occurred because for some patients, CHWs completed intake, established goals and provided some education in the same intake visit, but were unable to follow-up with the patient after repeated attempts, resulting in patients with goals and education but few successful encounters. The median number of successful encounters was 5 and about $10\%$ patients had 12 or more successful encounters. As the CHORD protocol planned at least monthly contacts between a CHW and patient, these findings suggest that CHWs divided their time between meeting motivated patients less frequently and checking-in more frequently with patients who perhaps had more complex social needs. All these adaptations could have impacted our fidelity. Future analysis will focus on sharing these adaptations or natural deviations in implementation of a pragmatic trial.
Our finding of moderation by the implementation site underscores the need to account for site-based differences in patient characteristics such as their social risk profiles, when implementing evidence-based interventions. Although BH and VA are both safety-net settings, they differ in terms of their patient populations. BH is the flagship of New York City’s large, municipal hospital system, and serves a diverse, multicultural and multilingual population with high numbers of poor and racial/ethnic minorities, many of whom are uninsured or on Medicaid. VA NY *Harbor is* smaller, and provides care to veterans (mostly older, White, male, and English speakers) and is funded federally. Variation in the complexity of patient populations have historically necessitated innovation, and the differences in fidelity at the two sites could be reflecting such adaptations by CHWs to meet the needs of their patient populations. Earlier studies have found different implementation fidelity across different organizations [32, 33], without any impact on outcome differences at patient-level [27]. These findings, including ours, suggest that an effective implementation fidelity might be based on the local organization’s conditions and therefore might require implementors to consider local adaptations when scaling-up evidence-based behavioral interventions. It is also important to note that, while our use of implementation site to measure ‘context’ reflects different healthcare ecosystems in terms of the patients served, neither of these clinical sites nor the scope of our analysis fully measures ‘context’ as conceptualized in the CFIF. A comprehensive assessment of patients’ social environments is an important consideration in a CHW-led intervention such as CHORD, which relies on patients’ achieving behavior change in the conditions of their everyday lives.
These differences in patient populations at the two sites could also explain the different participation rates at the two sites. Utilizing CHWs as a healthcare workforce is an equity-oriented approach to improving healthcare access and health outcomes among underserved populations [34]. Given their purpose, training and demographic composition (belonging to racial-ethnic minority groups), it is not surprising that the patients who enrolled in our CHW-led intervention were more likely to be Spanish speaking, Black, Hispanic, and seeking care at Bellevue hospital – these population subgroups have historically been excluded or marginalized from healthcare systems and face challenges in accessing resources to live a healthy life. Our CHWs were also either black or Hispanic, and those at the VA were veterans.
## Study limitations
First, as a pragmatic trial, the CHORD implementation did not start or end on fixed days, because CHWs maintained continued contacts with their patients. As a result, some interventions, such as referrals, were delivered outside of the intervention period. We included them in this analysis if they were recorded by CHWs. Second, fidelity measures can be intervention specific. Therefore, the measures used in this study might not directly translate to other complex interventions. Third, one important aspect of implementation is how well the participants engage with the intervention. In our study, while we measured the delivery of core components from the perspective of CHWs, we could not assess the extent to which delivered interventions were received by patients. Fourth, with two CHWs per site, differences in approach and skill by the CHWs, despite their uniform training and monitoring, may have contributed to the differences by site. Fifth, with four CHWs, we did not have enough variation in race/ethnicity to track patient enrollment by the concordance of their race/ethnicity with that of CHWs’. Sixth, we report fidelity measures across the three waves of CHORD implementation, but do not examine changes in fidelity over time. Finally, while we report on fidelity delivery, our study did not measure fidelity receipt or fidelity enactment [9], or assess qualitative aspects of fidelity, such as the quality of goal setting or the comprehensiveness of education sessions beyond the coverage of the required education modules.
## Study strengths and contributions
Our study adds to the limited literature with systematically reported concurrent evaluation of implementation processes of multicomponent complex behavioral interventions [4, 6]. Moreover, the study responds to the general calls for conducting quantitative evaluations of fidelity in intervention studies [9]. Use of real time data reported by the key implementors, the CHWs, adds to the validity of our analysis. Lastly, our study empirically tested the CFIF and found that the framework is a useful tool for conceptualizing and organizing measures of fidelity and their moderators. However, our process evaluation suggests that to standardize quantitative fidelity assessments, the field will benefit from further guidance on “how-to” quantitatively measure fidelity moderators.
## Conclusion
Our concurrent quantitative, implementation evaluation of a complex pragmatic trial to prevent diabetes in safety-net settings, found moderate-to-high adherence to the core components of the intervention, as well as moderation of several fidelity measures by implementation site, with no impact of the baseline patient-activation measure on fidelity measures. Analyses of implementation fidelity of complex interventions such as this trial, advances the field of implementation science. This implementation evaluation will inform our analyses of the study outcomes and may be useful for other researchers conducting complex behavioral interventions.
## Supplementary Information
Additional file 1: Supplement Table 1. Characteristics of Patients Who Were Determined Eligible for the Intervention Arm (and were Outreached by CHWs), by Their Enrollment Status. Supplement Table 2. Characteristics of Patients Who Were Enrolled in the Intervention Arm, by their Intake Completion Status. Supplement Table 3. Moderation of Fidelity Measures by PAM Score Among Intervention Patients Completing the Intake Survey. Supplement Table 4. Moderation of Fidelity Measures by Clinical Site* Among Intervention Patients Completing the Intake Survey.
## Authors’ information
Not applicable.
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|
---
title: Exploring the Long-Term Tissue Accumulation and Excretion of 3 nm Cerium Oxide
Nanoparticles after Single Dose Administration
authors:
- Lena M. Ernst
- Laura Mondragón
- Joana Ramis
- Muriel F. Gustà
- Tetyana Yudina
- Eudald Casals
- Neus G. Bastús
- Guillermo Fernández-Varo
- Gregori Casals
- Wladimiro Jiménez
- Victor Puntes
journal: Antioxidants
year: 2023
pmcid: PMC10045098
doi: 10.3390/antiox12030765
license: CC BY 4.0
---
# Exploring the Long-Term Tissue Accumulation and Excretion of 3 nm Cerium Oxide Nanoparticles after Single Dose Administration
## Abstract
Nanoparticle (NP) pharmacokinetics significantly differ from traditional small molecule principles. From this emerges the need to create new tools and concepts to harness their full potential and avoid unnecessary risks. Nanoparticle pharmacokinetics strongly depend on size, shape, surface functionalisation, and aggregation state, influencing their biodistribution, accumulation, transformations, and excretion profile, and hence their efficacy and safety. Today, while NP biodistribution and nanoceria biodistribution have been studied often at short times, their long-term accumulation and excretion have rarely been studied. In this work, 3 nm nanoceria at 5.7 mg/kg of body weight was intravenously administrated in a single dose to healthy mice. Biodistribution was measured in the liver, spleen, kidney, lung, brain, lymph nodes, ovary, bone marrow, urine, and faeces at different time points (1, 9, 30, and 100 days). Biodistribution and urinary and faecal excretion were also studied in rats placed in metabolic cages at shorter times. The similarity of results of different NPs in different models is shown as the heterogeneous nanoceria distribution in organs. After the expectable accumulation in the liver and spleen, the concentration of cerium decays exponentially, accounting for about a $50\%$ excretion of cerium from the body in 100 days. Cerium ions, coming from NP dissolution, are most likely excreted via the urinary tract, and ceria nanoparticles accumulated in the liver are most likely excreted via the hepatobiliary route. In addition, nanoceria looks safe and does not damage the target organs. No weight loss or apathy was observed during the course of the experiments.
## 1. Introduction
In the past years, immunometabolism has raised a genuine interest in the scientific community as a tool to control the immune system responses [1]. The immunomodulation concept emerges from noticing that immune cells have different energetic demands depending on the required biological response. *In* general terms, the faster the energy is required, at higher power, the more free radicals (reactive oxygen species, ROS) are generated, and ATP production is enhanced, as it happens during inflammation [2]. This increased ROS production, enhances the chemical potential of cells to sustain their defensive response and consequent energy consumption in biosynthesis (cytokines and chemokines) and phagocytosis, led by fast and inefficient oxidation of glucose in the cytoplasm (anaerobic glycolysis) [2]. However, this increased ROS production is toxic, causing oxidative stress that results in the oxidation of proteins, lipids, DNA, and ultimately cell death [3]. Therefore, the modulation of immune cell metabolism is emerging as a tool to regulate deranged inflammatory immune responses. This can be achieved either by using antioxidants to control ROS and therefore cellular REDOX potential [4], or by cutting out fuel supply, as in ketogenic diets [5,6] or the use of metformin [7].
Indeed, the need to protect the organism from excess ROS has driven the interest in antioxidants for decades. In 1970, Linus Pauling published a book titled: “Vitamin C and the common cold” [8], describing the protective and anti-inflammatory properties of natural antioxidants. Since oxidative stress is intrinsic when homeostasis is broken, which occurs during disease, numerous epidemiological and mechanistic studies have shown the remarkable benefits of antioxidants in a wide variety of fields, such as auto-immune diseases [9], chronic inflammation [10], neurodegeneration [11], cancer [12], and infections [13]. Unfortunately, the benefits of antioxidants have not been harnessed yet for clinical use, despite the thorough clinical trials since then, which has been attributed to the poor drug-likeness of current available substances (instability, unspecific reactivity, and low bioavailability at the site of action), and consequently their poor pharmacokinetics (PK) profiles [14,15].
In this context, nanotechnology has shown us how mineral antioxidants, such as metal oxide nanoparticles, especially cerium oxide (CeO2) nanoparticles (NPs), and nanoceria are safe and powerful anti-inflammatory substances [16,17,18] and seem to overcome these previous antioxidant PK limitations. Nanoceria is well known for its ability to scavenge ROS in biological systems, acting as an effective antioxidant and consequently anti-inflammatory substance [19]. It has been demonstrated to be highly soluble in biological media, present high bioavailability, disperse well in tissues, have therapeutic action at 50 to 250 micrograms/gram, and more importantly, while its chemical specificity is very low, scavenging different types of ROS (and reactive nitrogen species and reactive sulphur species) only in the case when an abnormally high (pathological) concentration of free radicals nanoceria is active, acting as a REDOX buffer [2]. Finally, as an inorganic catalyst, it can be used many times without being consumed, which allows it to work rather permanently at very low doses, offering chronic protection with a single administration. Accordingly, nanoceria efficacy has successfully been tested in a wide variety of disease models, mainly in inflammatory-related pathologies such as cardiac diseases [20], brain ischemia [21,22,23], diabetes [24], retinal dysfunction [25,26], liver inflammation [27,28], cancer [29], anaphylactic shock [30,31,32], acute [33] and chronic glaucoma [34], radiation-induced injuries [35,36], and neurodegeneration [37,38]. This ability of nanoceria to reduce ROS is crucial, because it avoids the direct damage derived from free radicals. In addition, it also has an important immunomodulatory effect, advocating for its use in medicine via its pharmaceutical development [39].
Despite these appealing therapeutic observations, there is still a fundamental open question: nanoceria’s end of life inside the body and in the environment. To some extent, inorganic NPs are supposed to be non-biodegradable and known to accumulate in different tissues and remain there for a long time. It is well known that slow and inefficient clearance rates are displayed by inorganic matter, leading to long-term toxicity concerns due to accumulation. An example is the case of the so-called frustrated phagocytosis where inorganic matter induces chronic inflammation preluding cancer, as in the cases of silicosis or asbestosis, where hundreds of micrometre inorganic particles cause chronic granulomatosis [40]. Even if the inorganic matter causing these diseases is orders of magnitude larger than the currently employed NPs, this raises concerns about NP accumulation, aggregation, and excretion from the organism in extended periods.
Nanoparticle fate belongs to NP PK, the branch of pharmacology that studies drug administration, distribution, metabolization, and excretion. Nanoparticle PK significantly differs from the traditional small molecule PK, and thus emerges the need to create new tools and concepts to assess NP evolution and fate inside the body. Nanoparticle PK strongly depends on size, shape, surface state, and aggregation state. All these features influence nanoceria biodistribution, degradation, and excretion profile, and hence their therapeutic potential and safety.
Today, there are plenty of short-term NP biodistribution studies in the literature, but there is a lack of fate and excretion studies. Excretion is paramount in the development of a medicine. The primary natural excretion pathways from the body are via the liver to faeces, and kidneys to urine. Regarding kidney clearance, several studies show how very small NPs, smaller than 6 nm (in hydrodynamic diameter), can be readily cleared from the body via the urinary tract [41,42]. Note that glomerular filtration not only depends on size, but it also depends on molecule charge [43]. Kobayashi and co-workers [44] showed that glomerular filtration depended on whether the charge was positive or negative, showing enhanced filtration for cationic molecules. Other researchers reported similar observations on NP charge and size effects [42]. Clearance from the liver is more complex, leading to a slower elimination rate than urine excretion. This slow clearance rate is mediated by the hepatobiliary route. The clearance of NPs from the blood into the liver, and from the liver into faeces has been well described in the studies of Pr. Warren Chan [45,46].
*In* general, as expected, administrated nanoceria ended up accumulating mainly in the liver and spleen (around $90\%$ of the injected dose) with smaller fractions accumulating in the kidneys and lungs, while the hepatobiliary route was the more often proposed excretion route [46]. It is important to understand that when administered, NPs must overcome different biological barriers before reaching their final destination. In short, the first natural barrier that NPs need to cross is the biological fluids, such as blood or lymph, sweat or tear, and the corresponding extracellular matrix, consisting of macromolecules (protein, vitamins), biological molecules (as saccharides) and minerals, that change in different tissues and compartments, and health status [47], which may promote NP aggregation and/or corrosion. The second natural barrier the NPs will encounter, in contrast to small molecules, is the immune system, which evolved to recognize molecular patterns from foreign substances and commensal organisms [48], labelling them with opsonins, and enhancing their uptake by phagocytic cells, such as splenic macrophages, or Kupffer cells in the liver. If NPs are recognized as foreign substances when entering the body, the immune response will reduce their plasma half-life, decreasing their efficiency in targeting different organs. As a third barrier, the microstructure of blood vessels and tissue also strongly determine NP biodistribution. Generally, NPs with hydrodynamic radii smaller than 6 nm are rapidly excreted through the urine while NPs with hydrodynamic radii between 6 and 200 nm are readily filtered in the liver. Larger ones are directly managed by the immune system in blood/lymph, and also tend to accumulate in the liver or other organs such as the lung or spleen [49].
In further detail, to study NP biodistribution, accumulation and excretion, the processes affecting NPs dispersion in the physiological medium have to be considered first [50]: aggregation, protein corona formation, and corrosion. NP aggregation and corrosion will affect NP quality, safety, and efficacy. First, blood and physiological media are highly saline. Hence, if NPs are stabilized by electrostatic repulsion, they will rapidly aggregate as soon as they enter in the highly electrolytic media. As a result, large aggregates (hundreds of nm) form and sediment, and they are not distributed further. These cases are not addressed in this work. Second, proteins in the media will interact with the NP surface. In this case, protein concentration is critical as high protein concentrations will lead to steric stabilization of NPs, while low concentrations will lead to agglomeration and aggregation of NPs and proteins [50]. Finally, NPs can also undergo chemical transformations, as in the common case of corrosion (reactive chemical dissolution), leading to NP dissolution and the corresponding release of NP constituents. These three events usually coexist, and their rates depend on both NP characteristics and medium composition [51].
Regarding the encounter of NPs with the immune system, it is important to note that the immune system can detect molecular and cellular structures with a spatial resolution of a few nm, which allows for detecting molecular patterns expressed in a great variety of pathogens, including viral and bacterial proteins, and bacterial nucleic acid sequences [52], ranging from a few nm to a few hundred nm, as colloidal NPs, which suggests an intense interaction between both [53]. Thus, NPs can be recognized or pass undetected by the immune system. Once detected, they can be tolerated or induce defensive (pro-inflammatory) or anti-inflammatory responses. The different immune responses induced by NPs have been recently reviewed [53]. Basically, poor solubility, large sizes, and cationic charges at the surface or hydrophobic moieties are rather immunogenic, while small, negatively charged, and highly soluble NPs are relatively undetected and tolerated. *In* general, when needed, surface PEGylation helps to escape from immune detection [54,55]. Ideally, NPs should be designed to evade the immune system, allowing for penetration into the different body tissues unless the NP target is the immune system [53].
Finally, when considering intravenous (IV) administration, which is likely the most employed nanoceria administration route, it is essential to note that the main blood vessels and capillaries in the body have a continuous lining of endothelial cells with pores of 6 nm. In such conditions, small drug molecules, the vast majority of drugs, can diffuse in and out from the blood vessels into the lymph and vice versa, while the passive transport of large objects, such as proteins and NPs, through these pores, is negligible. Besides, fenestrated capillaries found in the intestine and endocrine and exocrine glands present 50–60 nm pores, while discontinuous capillaries, such as those found in the liver, spleen, and bone marrow, display pores ranging from 100 to 1000 nm, which are where NPs are commonly found [56]. Tight junctions deserve special attention, including the blood-brain barrier (BBB), placenta, retinal, and testis barriers, where pores smaller than 1 nm (400 Da) have been reported, preventing NP passive accumulation [57]. It is worth noting here that blood vessel and tissue permeability is altered during the course of diseases, facilitating the passive accumulation of NPs in the disease areas. This altered permeability can increase the concentration of NPs in those tissues by one order of magnitude [58]. This is the case of the enhanced permeability and retention (EPR) effect in solid tumours [59], where defective angiogenesis results in defective blood vessels with large endothelial pores (a few hundred nanometres) nurturing the tumour, which together with the absence of a functional lymphatic drain facilitates NP accumulation in the tumour [60]. Similarly, blood vessels and tissue porosity increase during inflammation, allowing NPs to accumulate in the inflamed area [37]. It is also important to note that functionalization with directing vectors may significantly change the nanoceria distribution, apparently more than size and aggregation state. Thus, nanoceria conjugated to fluorescein isothiocyanate [61] or edaravone [62] has been observed to cross the BBB. Here it is important to note that during neuroinflammation, caused by many brain diseases, together with growing tumours or traumatic brain injury, will allow NPs to permeate the BBB, allowing for the translocation of NPs, as in the case of Amyotrophic Lateral Sclerosis [63].
This study aims to explore 3 nm nanoceria long-term accumulation and excretion in healthy mice after a single IV administration and compare it with the related experiments. We also studied shorter-term accumulation and renal and faecal excretion in model rats, IV, and orally administered with nanoceria.
## 2.1. Model of the Effects of Protein Corona on Nanoceria Internalization and Intracellular Trafficking
The results reported by Mazzolini J. et al. [ 64] led them to speculate a model in which, in the presence of serum in the environment, the protein corona that formed around the nanoceria contains the proteins involved in cell adhesion and endocytic pathways. Among these adsorbed proteins, transferrin promotes nanoceria internalization through transferrin receptor clathrin-mediated endocytosis, followed by their storage in vesicles and the endosomal compartment. Under these conditions, cell division, viability, and metabolism are preserved, whereas in serum-free media, the absence of a protein corona around nanoceria induces plasma membrane disruption and metabolism changes.
## 2.2. CeO2NPs Adsorption by Human Hepatocyte Cancer Cells
In a recent study, we reported that HepG2 cells, a human-derived cell cancer line, can internalize nanoceria [29]. In vitro experiments confirmed the uptake and retention of nanoceria by human hepatocyte cancer cells, mostly in endosome-like bodies. Human hepatocytes were exposed to CeO2NPs (10 μg/mL) for 24 h and subjected to TEM analysis. NPs were strongly attached to the outer leaflet of the plasmatic membrane, free in the cytoplasm, and mostly inside numerous endosome-like bodies of diverse morphology.
## 2.3. Nanoceria Synthesis
Nanoceria was synthesized using a wet chemistry method based on the basic precipitation of cerium (III) nitrate hexahydrate (Ce(NO3)3 • 6 H2O) in the presence of sodium citrate (SC). In detail, a TAMAOH solution (50 mL, 81 mM) was added to a 100 mL solution containing Ce(NO3)3 • 6 H2O (30 mM) and SC (60 mM). The final concentration was: 27 mM TMAOH, 10 mM Ce(NO3)3 • 6 H2O, and 20 mM SC. The reaction mixture was left under stirring overnight at room temperature. Later, the mixture was transferred to a three-necked round-bottomed flask (250 mL) and left under refluxing at 100 °C for 4 h. The resulting mixture was a stable, well-dispersed solution of 3 nm nanoceria at a concentration of 1.72 mg/mL CeO2.
Before use, the NPs solution was purified with 3 kDa centrifugal filter units (Amicon-Ultra-15 3K, Merck, Germany), and re-suspended in SC 2.2 mM.
## MSA Conjugation
To prevent aggregation of the NPs in the bloodstream, and to avoid hypotonic shock, nanoceria was conjugated with albumin from mouse serum (MSA, Merck, Germany) in phosphate buffer (PB), 10 mM at 4 °C for 24 h before injection.
## 2.5.1. Bacterial Endotoxin (LAL) Test
Both synthesis and purification of NPs were performed under sterile conditions and with non-pyrogenic material. To ensure safe NPs for animal administration, nanoceria was tested for LPS levels at *Echevarne analysis* laboratory (Barcelona, Spain).
## 2.5.2. Transmission Electron Microscopy (TEM)
Nanoceria was visualized using HRES-TEM (Tecnai F20 S/TEM). Ten µL of the as-synthesized solutions were drop-casted onto a carbon coated 200 mesh copper grid and left to dry for at least 24 h in the air at room temperature. The samples’ average size and distribution were measured using Image J Analysis software by counting at least 2000 particles.
## 2.5.3. UV-Visible Spectra
UV-vis spectra were acquired with a Cary 60 spectrophotometer (Agilent Technologies, Santa Clara, CA, USA) in the 250–800 nm range, using 1.5 mL plastic cuvettes.
## 2.5.4. Dynamic Light Scattering (DLS) and ζ-Potential
Malvern ZetaSizer Nano ZS (Malvern instruments, Malvern, UK) operating at a light source wavelength of 532 nm and fixed scattering angle of 173° was used to measure NPs hydrodynamic size and ζ-Potential value. Measurements were conducted in 1 cm path cell and 25 °C. Three independent measures were performed.
## 2.5.5. X-ray Diffraction
XRD diffraction experiments were performed on a Malvern Panalytical Xpert Pro diffractometer, with Cu-Kα X-rays of wavelength (λ) = 1.5406 Å. The patterns were collected in the angle region between 20° and 95° (2θ).
## 2.6. In Vivo Study Design
All experimental procedures were conducted in strict accordance with the European (Directive $\frac{2010}{63}$/UE) and Spanish laws and regulations (Real Decreto $\frac{53}{2013}$; Generalitat de Catalunya Decret $\frac{214}{97}$) on the protection of animals used for experimental and other scientific purposes, approved by the Vall d’Hebron Research Institute (VHIR) Ethical Experimentation Committee, and further validated by the authorized body of Generalitat de Catalunya (ref. n. 11357).
The experimental procedures conducted in Wistar rats were approved and performed according to the criteria of the Investigation and Ethics Committee of the Hospital Clínic Universitari (Barcelona, Spain), and validated by the authorized body of Generalitat de Catalunya (ref. n. 7907).
Animals received humane care according to the criteria outlined in the “Guide for the Care and Use of Laboratory Animals”.
## 2.6.1. Long-Term Biodistribution in Healthy Mice
For long-term biodistribution study, 30 adult female BALB/C mice (Charles River Laboratories), of 25 g of body weight and 7 months-old at the time of NP administration, were housed 3 to 4 per cage with ad libitum access to food and water during a 12 h light/dark cycle. Mice were randomly divided into four groups. On day 0, four groups of six mice were IV (retro-orbital injection) administered in the ophthalmic venous sinus, under general anaesthesia using Isoflurane ($5\%$ for the induction phase and $2\%$ for the maintenance phase), with a single dose of 5.7 mg/kg of body weight (bw) nanoceria conjugated with MSA in PB 10 mM, corresponding to the maximal volume that can be administered IV. Animals were sacrificed at different times after nanoceria injection: 1, 9, 30, and 100 days. The liver, spleen, kidneys, lung, brain, lymph nodes, ovaries, bone marrow, faecal content, and urine (collected in tared Eppendorfs) were collected and stored at −20 °C before elemental Cerium analysis.
## 2.6.2. Nanoceria Excretion in CCl4-Treated Rats
The study was performed in male Wistar rats (Charles-River, Saint Aubin les Elseuf, France) with hepatic fibrosis induced by repetitive CCl4 inhalation, as previously described [65]. The rats were fed ad libitum with standard chow and water containing phenobarbital (0.3 g L−1) as the drinking fluid. The animals were exposed to CCl4 vapor atmosphere twice a week for 16 weeks. Nanoceria (0.1 mg/kg bw) was injected twice a week for two consecutive weeks, starting at the seventh week after beginning CCl4 administration. Nanoceria was dispersed in saline solution containing TMAOH ammonium salts (0.8 mM) and was administered as a bolus (500 μL) through the tail vein. After the last dose of nanoceria, the animals were placed in metabolic cages and 24 h urine and faeces measurements were performed at 3, 21, 42, and 56 days after nanoceria administration.
## 2.6.3. Confocal Imaging of Nanoparticles in Mice Liver
Adult female BALB/cAnNRj mice (Janvier) were 19–22 g and 6–7 weeks old at the time of NP administration. They were housed three to four per cage with ad libitum access to food and water during a 12 h light/dark cycle. Nanoparticles for IV injections were conjugated with MSA in PB buffer 10 mM at 4 °C, 24 h before injection in order to prevent aggregation in the bloodstream.
Experimental procedure—Optical Microscopy of Tissue sections (see Supplementary Materials, SM).
## 2.6.4. Organ Distribution of Fe3O4NPs in CCl4-Treated Rats
Please see the details of procedure in Supplementary Materials (SM).
## 2.6.5. Organ Biodistribution after Oral Administration in Healthy Rats
In this study, CeO2NP mixed with polyethylene glycol were administered to healthy Wistar rats daily by intragastric gavage administration (3 mg/mL; 10 mg CeO2/Kg of bw) for 14 consecutive days ($$n = 3$$). Nanoceria was administered mixed with PEG as a standard excipient for oral administration, and thus prevented strong nanoceria aggregation once SC was protonated in the acidic pH of the stomach. The cerium concentration was measured by ICP-MS, and the major organs and serum were collected 72 h after the last administration.
## 2.7. Cerium Content Determination
Digestions were carried out in Ethos™ Easy (Millestone, Sorisole, Italy), an advanced microwave digestion system. First, samples were defrosted and mixed in the digestion solution containing one part of concentrated nitric acid and two parts of water. Subsequently, the digestions were performed under a 200 °C cycle for 1.5 h. Thereafter, elemental cerium in tissue were analysed using ICP-MS (7900 ICPMS, Agilent, Santa Clara, CA, USA), in *Chemical analysis* service (UAB, Barcelona, Spain).
## 3. Results
We have been working with nanoceria in disease models for over 15 years. According to our experience and the current literature, nanoceria accumulates largely (close to 85–$95\%$ of the injected dose) in the liver and spleen. Interestingly, this occurs both in healthy and liver-diseased models, as in hepatocellular carcinoma [29] or liver steatosis [66]. Indeed, liver accumulation of NPs has been extensively described in the scientific literature. An extended work can be found in Ref. [ 45], where the clearance of the NPs from blood to the liver is reported. In all those cases, the administered nanoceria was given at different doses and administration schedules, and although the NPs derived from similar synthesis, they had different formulations (mainly surface state and aggregation state) and ended up in similar places. Here, an important point to keep in mind is that biodistribution inside the organs is heterogeneous. It often seems assumed that NPs are homogeneously distributed and only a fraction of the organs are employed for elemental analysis. However, organs are complex and host different tissues and cell types, and therefore biodistribution inside the organs is heterogeneous. In model cirrhotic rats, injected nanoceria (5 nm aggregated in 30 nm clusters as described in Ref. [ 66]), was found heterogeneously distributed in the liver, as shown in Figure 1A, indicating that organs have to be homogenized before a fraction is digested for elemental analysis. There is a quite interesting study [45] where the blood clearance mechanisms were examined in relation to the flow dynamic and cellular phenotype in addition to the vessel’s microstructure. Here, the slower blood flow within the organs enhances the possibility of NP retention, which can help predict the accumulation regions inside an organ.
Besides, the NPs can be processed by different types of cells. A clear example is the processing of NPs in the liver either by hepatocytes, described as the main responsible cells during hepatic filtration [67], or Kupffer cells, the resident macrophages in the liver, responsible for the elimination of apoptotic bodies, protein aggregates, and foreign matter [46]. However, we once observed selective capture of NPs by hepatic stellate cells in the mice liver after a single IV injection (Figure 1B). In this work, we employed 50 nm AuNPs so they could be observed in reflectance mode in the confocal microscope without the need for labels at the NP surface, which could affect their biodistribution. This is not expected to be a general trend or applicable to nanoceria, but this selective NP uptake illustrates a most likely widespread event.
Next, the fate of very small 3 nm non-aggregated nanoceria IV administered in healthy mice was assessed. Size is one of the parameters that has been the focus of understanding NPs biodistribution, accumulation, and clearance. As a first observation, it has been postulated that the bigger the NPs are, the narrower their organ distributions [49]. Size may also have a substantial impact on NP integrity. Cerium ions are made insoluble by oxidation at basic pH, and once nanoceria is dispersed at neutral pH, in the REDOX conditions of living systems, its thermodynamic fate is to reduce back and dissolve in the form of Ce3+ ions (see the Pourbaix diagram in Suplemmentary Materials [68]. *This* generally does not happen due to a remarkably high activation energy for cerium oxide crystal dissolution [69]. However, this activation energy decreases with size, ultra-small NPs being prone to dissolution, facilitating biodegradation. Indeed, the curvature radii of NPs with a diameter 30 nm or below become progressively unstable [70]. Therefore, the smaller the NP, the faster its degradation would be. Note that the estimated minimal thermodynamically stable nanoceria crystal size is about 1.9 nm in diameter [69], which leaves 3 nm NPs on the verge of dissolution. Indeed, rapid nanoceria dissolution has been reported inside late endosomes and endolysosomes [71], and at acidic pH during colorimetric detection of analytes [72].
Nanoceria was synthesized in sterile conditions by basic precipitation of cerium nitrate using a classical hydrothermal approach. Sodium citrate (SC) was used as a complexing and stabilizing agent, and TMAOH was used as a base. A stable colloidal solution of ~3 nm non-aggregated naked surface NPs was obtained [25] and described in Figure 2. Note that a precise description of NP features is critical in controlling the interactions at the nano–bio interface [73]. Morphology and size distribution analysed by high-angle annular dark-field scanning transmission microscopy (HAADF-STEM) and High-Resolution transmission electron microscopy (HRES-TEM) (Figure 2A) indicates the formation of non-aggregated 2.5 ± 0.5 nm quasi-spherical nanoceria particles of high uniformity and narrow size distribution (Figure 2A, insert). The X-ray diffraction patterns of the NPs confirm that the sample displays a pure fluorite single-phase (face-cantered cubic, fcc) crystal structure (Figure 2D). The broadness of the diffraction peaks indicates an ultra-small crystal size, where the Scherrer equation confirms the NP size of ~3 nm. The UV-visible spectrum of nanoceria shows a distinct absorption band at 283 nm with a characteristic bandgap of 3.11 eV (the bulk is 3.19 eV) (Figure 2B and inset). This reduced bandgap manifests the oxygen vacancies that nanoceria accumulates at its surface as it decreases in size. These oxygen vacancies determine nanoceria catalytic behaviour (oxygen vacancies are active sites) and nanocrystal stability (the more oxygen vacancies, the closer to dissolution). The zeta potential indicates that after purification and re-dispersion of nanoceria in 2.2 mM SC, particles are negatively charged (−38.9 ± 16.7 mV, at pH = 9.23 and a conductivity of 0.33 mS cm−1) (data not shown). Hydrodynamic diameter and stability in simulated physiological media (DMEM, $10\%$ FBS, pH 7.4) were measured by dynamic light scattering (DLS) and shown in Figure 2C, where as-synthesized nanoceria shows monomodal distribution peaking at 3.96 ± 0.89 nm (PDI = 0.35). As expected, the results show nanoceria aggregation within 24 h in DMEM due to surface charge screening because of the high ionic strength of the media. Nanoceria conjugation with albumin prevented NP aggregation, and a slightly increased hydrodynamic diameter, peaking at 6.28 ± 1.6 nm (PDI = 0.47), was observed. Interactions of nanoceria with proteins in physiological media were previously well described [74]. Because of that, we recommend NPs stabilization in the serum before inoculation, murine or rat serum in case of mice and rats, respectively, normally at a final 1 to 10 mg/mL protein concentration, which also prevents rapid renal clearance of NPs < 6 nm.
In order to determine the biodistribution of the nanoceria, 4 groups of 5 mice each were IV administered with 5.7 mg/kg of body weight (bw) single dose of nanoceria and they were euthanized at different times after injection: 1, 9, 30, and 100 days. Although the most employed vein for administration is the lateral tail vein, we here chose retro-orbital injection in the ophthalmic venous sinus in the back of the eye socket. The reason is that administration in the secondary vein network improves the biocompatibility and prevents adverse infusion reactions. Thereafter, ICP-MS was used to determine cerium concentrations in the liver, spleen, kidney, lung, brain, lymph nodes, ovaries, bone marrow, urine, and faeces. During the experiments, all animals showed a healthy weight and appearance, and normal activity without lethargy or apathy after NP administration (see Figure S1).
As expected, the results showed the main accumulation of nanoceria in the liver, and spleen ($82\%$, and $5\%$ of the injected dose (ID), respectively) (Figure 2, Table S1). Cerium was not detected in the brain and showed extremely low levels in the other organs, although the presence could be observed in the kidneys, lungs, lymph nodes, ovaries, and bone marrow. With time, Ce concentration in the different organs progressively diminished. The most significant elimination was observed in the liver with a reduction from $82\%$ to $40\%$ of ID between day 1 and day 100. The spleen was the second organ with more accumulation, but the clearance rate was slower (see the excretion rates for the different organs in Figure S2). In the kidney, lung, bone marrow, and ovaries there was low accumulation, and slow clearance rates could also be observed. The striking difference between the liver and the rest may indicate that while there exists a ready mechanism for NP excretion in the liver, NP macrophage accumulation in the same liver or other organs leads to much slower excretion. Interestingly, on day 30, cerium concentration increased in the lymph nodes, which may indicate some re-distribution at longer times. This rebound effect is also observed shortly after initial kidney accumulation (W. Jiménez, unpublished observations). Traditionally, the spleen has attracted little attention in pharmacology, because of its minor role in “classical” drug disposition and/or excretion, but this is changing for “new” generation drugs (nanoparticles, recombinant proteins, and monoclonal antibodies) [75]. For example, Demoy et al. demonstrated the pivotal role of spleen marginal zone macrophages in the uptake of polystyrene NPs [76]. We hypothesize then that in our case, a small portion of nanoceria could have been retained in spleen macrophages, which are known to be a slower clearance route, as discussed below.
The results suggest that the main clearance route is hepatobiliary elimination, showing a ≈ $60\%$ decrease of nanoceria in the liver and ≈ $50\%$ inside the body 100 days after injection. This hypothesis is also supported by the observed cerium content in the faecal samples. Interestingly, the excretion is enhanced in the first 24 h after injection, also showing the highest peak of cerium content in the collected faeces. With time, cerium is also detected in urine. Due to nanoceria’s hydrodynamic diameter (Figure 2C), surface charge, and core density, it is highly improbable that particles undergo renal clearance. Besides, in other studies, no significant urine excretion was reported [77]. For this reason, these traces could be ionic cerium coming from nanoceria dissolution. All in all, this suggests elimination by the two main described mechanisms: (i) renal excretion of cerium ions and (ii) hepatobiliary elimination of CeO2 NPs.
Despite the reduced number of time points in Figure 3, we fitted the evolution of cerium content inside the liver, or in all measured organs (AMO) vs. time to standard PK models, where small drugs diffuse rather passively through the body following a first-order reaction kinetics that can be described by an exponential decay of cerium concentration with time. We here use one exponential term for one model compartment and two exponential terms for two model compartments (see Suplemmentary Materials) [78,79]. As peripheral distribution is not expected to be significant with NPs, one would expect monomodal exponential decay behaviour. Divergence from this behaviour indicates how the system eliminates cerium in a more active form (Figure 4). In addition, it appears that after the ninth day and ahead, there is a rather monotonous decrease in the cerium concentration, which could be due to a slow excretion of slowly generated cerium ions. On one side, different nanoceria fractions may coexist, and some nanoceria may stay permanently in the body captured inside tissue macrophages or blood monocytes. On the other side, nanoceria should completely dissolve with time in biological conditions regardless of location, accounting for the slow monotonous ceria concentration decrease observed at long times. A physiologically based pharmacokinetic modelling of nanoceria systemic distribution in rats [80] showed similar results, especially the different NP fate depending on admin route, surface, size, and physicochemical properties.
In another study, to compare if biodistribution was different in healthy or diseased pre-clinical models, we set rats in metabolic cages where cerium was also recovered in the urine and faeces during the experimental timeline. The experimental time in the metabolic cages was reduced for animal welfare. This study used Wistar rats with hepatic fibrosis induced by repetitive CCl4 inhalation and water containing phenobarbital as the drinking fluid. The animals were injected through the tail vein with nanoceria (0.1 mg/Kg bw) twice a week for two consecutive weeks, starting in the seventh week after the beginning of CCl4 administration [66]. After the last dose of nanoceria, animals were placed in metabolic cages to measure cerium concentration for 24 h urine and faeces deposition at 3, 21, 42, and 56 days. As shown in Figure 5, while the cerium faecal content decreases exponentially, a rather monotonous cerium concentration was observed in urine, supporting a slow and progressive nanoceria dissolution into cerium ions and its corresponding renal excretion [81]. As commented before, ultra-small ceria, close to the thermodynamic crystal stability limit, at neutral or acidic pH, is prone to dissolution.
These results are supported by other studies, where after IV injection of NPs with similar size and surface coating they were localized in both Kupffer cells and hepatocytes [82]. Note that both cells have phagocytic capacities, although hepatocytes are directly implicated in the pathway for biliary excretion (NPs found here will be potentially excreted to the bile), whereas Kupffer cells can only eliminate nanoceria via intracellular degradation. Importantly, the Kupffer cells uptake of nanoceria is often accompanied by a mild and transient activation of the immune system [82], calling for a careful examination of the immunogenic properties of designed NPs.
Regarding long-term accumulation of nanoceria, we would like to highlight the studies of Yokel et al. [ 83,84], where a large dose of 30 nm cubic nanoceria (87 mg/Kg bw) was IV administered to rats, and thereafter an exhaustive accumulation and excretion study was reported on days 1, 7, 30, and 90. In this case, nanoceria was again primarily accumulated in the spleen, liver, and bone marrow. Interestingly, NPs clearance from blood was studied for two weeks and it showed that less than $1\%$ of the nanoceria was removed, and there was a small decrease of particles in any tissue over 90 days. Besides, while we have never observed significant NP in blood a few hours after injection (data not shown), in this study there is a significant cerium blood content after 90 days, which could indicate particle endocytosis by blood cells. This difference among the results is most likely due to the divergence between the physicochemical properties of the used nanoceria (large vs. small size, aggregated vs. non-aggregated, and spherical vs. cubic). Interestingly, although biodistribution and target organs are similar, excretion profiles seem to differ widely. Here, one could hypothesize that NPs that reach the liver and are processed by hepatocytes will be shuttled outside of the body via the hepatobiliary route while NPs that are phagocytosed by resident macrophages, Kupffer cells in the liver, will stay in the macrophages permanently (and if the macrophage dies, another macrophage will engulf the remains) while NPs may slowly dissolve generating Ce3+ ions that are excreted via the urinary tract (Figure 6).
We also explored oral administration. In this regard, nanoceria dispersed in a polyethene glycol solution were delivered to healthy Wistar rats daily by intragastric administration (10 mg CeO2/Kg bw) for 14 days ($$n = 3$$). While most of the cerium was found in faeces, some of it entered the body and was observed in the same organs but at different concentrations than in the case of parenteral administration (Figure 7). Here we realised, that although PEG coating, exposure to rat gastrointestinal fluid promotes the rapid dissolution of the NPs into Ce3+ ions, which have been reported to act as Ca2+, and can be absorbed in the body without long-term accumulation and therefore being excreted through the urine [85]. Dispersion of nanoceria in simulated acidic solution (pH 1.7) showed both NP aggregation due to the protonation of the SC at stomach pH and dissolution of the NPs. If we estimate the average time of residence in the stomach to be about two hours, it seems that after a rapid agglomeration, nearly half of the nanoceria dissolves and the rest remains as aggregates (see Figure S3). Gastric capsules for mice and rat models are difficult to acquire and administrate, thus, we are exploring lipid NP encapsulation for stomach crossing. Besides, the dissolution of particles to ions could explain the elimination through kidneys and its prominent accumulation in the lung, where Ce3+ (CeCl3) IV administered to mice has been reported to accumulate [81] before renal excretion. There is a case report where a woman accidentally ingested about 1000 mL of a nanoceria-containing solution while working in an industrial setting where nanoceria (aggregated 20–40 nm NPs) was used as a polishing agent [86]. Cerium was detected both in blood and urine. The only symptoms that she presented were transient scattered red petechial, mainly in her face, and decreased plasma coagulation factors. Indeed, anticoagulant properties have been attributed to cerium ions and other rare earth metals [81,87], but not to their nanoscale counterparts, as far as we know.
Finally, despite the numerous evidence, there is still the question if different NPs or different analytical techniques would confirm these generalities of NP biodistribution, including procedures, and experimental and conceptual approximations. Therefore, we employed the CCl4-treated rats to observe the biodistribution of 8 nm NPs by magnetic resonance imaging (MRI), a technique displaying a high potential to localize NPs in vivo because of their high spatial resolution. Since nanoceria NPs lack paramagnetic properties, this protocol was performed using 8 nm Fe3O4NPs, which are somewhat similar, considering size, shape, and surface state, and a similar dose. We obtained sufficient resolution and contrast to assess Fe3O4NPs-induced signal intensity changes. The most pronounced changes, presented as an increase in signal intensity, were observed in the liver and spleen. These changes were apparent at the first image time point of 30 min after NPs injection (image not shown) and thereafter showed a progressive increase over 90 min (Figure S5), followed by a progressive decrease in signal intensity. Of note was that the brain image analyses revealed no changes during the observational period. Eight weeks after NPs administration the signal intensity was indistinguishable from that obtained in control rats (image not shown) (meaning that the iron concentration was below the limit of detection expected to be at $50\%$ of the administered dose). These findings coincided with those obtained by analysing ICP-MS tissue Ce accumulation following nanoceria IV injection in fibrotic rats [66].
## 4. Conclusions
In conclusion, while it seems universal that a major capture of NPs happens in the liver and spleen, regardless of their difference in dose, morphology, aggregation, and surface state, or if they are taken by immune or filtering cells, the final tissue/cellular distribution and clearance rate from the body seems extremely dependent on those NP characteristics. In this model, NPs that will escape the immune system can be eliminated through the hepatobiliary route, whereas nanoceria captured by circulating monocytes or resident macrophages can dissolve and the cerium ions are excreted through the urine tract. The fact that it is slowly excreted from the body is promising for nanoceria medical development; however, the excretion rates are low and repeated dosing could lead to toxic accumulation [39]. Interestingly, in toxicity studies, no adverse effects were reported at concentrations much higher than the therapeutic ones, as reported after nanoceria oral administration of 1000 mg/Kg bw for 14 days [88], providing some room for repeated administration despite the slow excretion. Accumulation in the spleen also deserves special attention since much slower clearance rates have been observed. This could be related to cell type interaction and to having monodisperse well characterized NPs that can be degraded. It is remarkable how, until now, nanoceria was reported to stay a long time inside the body and not be excreted, and has also been associated with mild pro-inflammatory activation. However, in this work, we demonstrate that non-immunogenic ultra-small highly soluble non-aggregated nanoceria is indeed excretable and biodegradable, paving the progress towards converting nanoceria into an active pharmaceutical ingredient.
All this data and considerations should help to better understand the PK of nanoceria to enable its successful translation to clinical use. Today, few inorganic NPs have reached clinical use: magnetite, Fe3O4, and amorphous silica, SiO2, which is generally regarded as safe (GRAS) by the FDA [89]. Interestingly, both slowly dissolve in vivo into Fe2+ ions and salicylic acid, respectively. We expect that many other NPs will join the future pharmacopoeia, where nanoceria will play a significant role.
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|
---
title: Identification of Prognosis-Related Oxidative Stress Model with Immunosuppression
in HCC
authors:
- Zhixuan Ren
- Jiakang Zhang
- Dayong Zheng
- Yue Luo
- Zhenghui Song
- Fengsheng Chen
- Aimin Li
- Xinhui Liu
journal: Biomedicines
year: 2023
pmcid: PMC10045103
doi: 10.3390/biomedicines11030695
license: CC BY 4.0
---
# Identification of Prognosis-Related Oxidative Stress Model with Immunosuppression in HCC
## Abstract
For hepatocellular carcinoma (HCC) patients, we attempted to establish a new oxidative stress (OS)-related prognostic model for predicting prognosis, exploring immune microenvironment, and predicting the immunotherapy response. Significantly differently expressed oxidative stress-related genes (DEOSGs) between normal and HCC samples from the Cancer Genome Atlas (TCGA) were screened, and then based on weighted gene coexpression network analysis (WGCNA), HCC-related hub genes were discovered. Based on the least absolute shrinkage and selection operator (LASSO) and cox regression analysis, a prognostic model was developed. We validated the prognostic model’s predictive power using an external validation cohort: the International Cancer Genome Consortium (ICGC).*Then a* nomogram was determined. Furthermore, we also examined the relationship of the risk model and clinical characteristics as well as immune microenvironment. 434 DEOSGs, comprising 62 downregulated and 372 upregulated genes ($p \leq 0.05$ and |log2FC| ≥ 1), and 257 HCC-related hub genes were recognized in HCC. Afterward, we built a five-DEOSG (LOX, CYP2C9, EIF2B4, EZH2, and SRXN1) prognostic risk model. Using the nomogram, the risk model was shown to have good prognostic value. Compared to the low risk group, HCC patients with high risk had poorer outcomes, worse pathological grades, and advanced tumor stages ($p \leq 0.05$). There were significant increases in LOX, EIF2B4, EZH2, and SRXN1 expression in HCC samples, while CYP2C9 expression was decreased. Finally, Real-time PCR (RT-qPCR) confirmed the mRNA expressions of five genes (CYP2C9, EIF2B4, EZH2, SRXN1, LOX) in HCC cell lines. Our study constructed a prognostic OS-related model with strong predictive power and potential as an immunosuppressive biomarker for HCC leading to improving prediction and providing new insights for HCC immunotherapy.
## 1. Introduction
Globally, primary liver cancer is the sixth-most common malignant tumor with ∼900,000 newly diagnosed patients annually, and is the third-most major cause of cancer-related mortality [1]. Approximately $75\%$ to $85\%$ of primary liver cancer cases are HCC, which are difficult to diagnose early and have a poor long-term prognosis [2]. For early HCC patients, radical surgery and transplantation are still the main radical therapies. The fact remains that a large number of HCC patients do not receive a diagnosis until they are in advanced stages and thus miss out on curative treatment due to the lack of apparent symptoms in the early stages [3,4]. Targeted molecular therapies, including sorafenib, lenvatinib, regorafenib, and immunotherapy have shown promising results in treating HCC [5,6,7]. Despite this, HCC patients continue to have dismal clinical outcomes in consequence of the emerged resistance. Consequently, many studies were performed to explore more effective models to precisely predict the prognosis and response to treatment of HCC patients for providing more evidence for precision therapy. Regardless of these explorations, rare models have been used in the clinic application of HCC patients. Consequently, finding new validated prognostic biomarkers and developing new models to predict HCC patients’ prognosis and treatment are crucial.
Oxidative stress (OS) occurs from the overproduction of reactive oxygen species (ROS) and reactive nitrogen species (RNS) [8], and is associated with the generation and progression of various physiological events or diseases, such as cancer, obesity and diabetes [9,10]. It has been found that increased ROS and RNS stimulate cell proliferation and angiogenesis in cancer cells and contribute to cancer progression [11]. ROS and RNS production are increased by hypoxia-inducible factors (HIFs) through upregulation of NADPH oxidases (NOXs) and nitric oxide synthases (NOSs) by binding to the hypoxic response element (HRE) in their promoter regions, respectively [12]. Accumulating evidence suggests that ROS, including superoxide free radicals, nitric oxide free radicals, hydroxyl free radicals, and uncharged substances, are significantly increased in HCC [13,14]. Recent studies have shown that the contribution of ROS to HCC is a complicated and varied process that involves their interacting directly with proteins and regulating gene expression or transcription factors to regulate multiple signal transduction pathways, while the overproduction of RNS causes protein damage in HCC [15,16]. Intracellular ROS accumulation can significantly promote tumor formation and growth, and induce drug resistance in HCC [13]. Moreover, several therapeutic approaches targeting OS have been proposed as possible therapies for HCC [15]. However, to our best knowledge, whether OS-related genes can accurately predict HCC prognosis and immunotherapy response has not yet been systematically evaluated, and the underlying mechanisms need to be further investigated.
The tumor microenvironment plays an important role in the development of tumors, especially in HCC [17]. As a typical inflammation driven tumor, HCC can promote immune tolerance through its immunosuppressive microenvironment. The dynamic balance of oxidative stresses not only orchestrate complex cell signaling events in cancer cells, but also affect other components in the tumor microenvironment (TME) [18]. Immune cells, such as M2 macrophages, dendritic cells, and T cells, are the major components of the immunosuppressive TME from the ROS-induced inflammation. As cancer treatment advances, immunotherapies are emerging as the next frontier, and HCC’s immunobiology is an area that will need further research. Immune checkpoint molecules contribute to HCC immunosuppressive through suppressing the anti-tumor immune response [19]. Immune checkpoint inhibitor (ICI) is one of the most rapidly developed immunotherapy strategies of HCC in recent years. ICI can block tumor-induced immunosuppression, thereby enhancing the anti-tumor immune response. ICI targets mainly include PD-1, PD-L1, and cytotoxic T lymphocyte antigen-4 (CTLA-4) [20]. The emergence of ICI has brought new research directions to researchers, and we look forward to better development of immune checkpoint inhibitors in the future.
In our study, by using publicly data from the Liver Hepatocellular Carcinoma database of The Cancer Genome Atlas (TCGA-LIHC), we identified 434 significantly differently expressed oxidative stress related genes (DEOSGs) in HCC. To discover the underlying mechanisms, protein-protein interaction (PPI) network and enrichment analysis were subsequently employed on DEOSGs [21,22,23]. Subsequently, the WGCNA analysis of 434 DEOSGs identified 257 hub genes related to HCC, and 146 prognostic DEOSGs were then recognized using univariate cox analysis. Furthermore, the prognostic risk model was determined by using LASSO analysis and multivariate cox regression analysis [24]. In addition, the correlation of the prognostic model and clinical characteristics, immune microenvironment, and immunotherapy response of HCC was explored in TCGA-LIHC cohort. Based on our information, this is the novel prognostic OS-related risk model for HCC patients leading to improved prediction of HCC prognosis and personalized treatment management for HCC immunotherapy.
## 2.1. Data Processing and DEOSGs Identification
From the TCGA and ICGC databases, defined respectively as the TCGA-LIHC cohort and ICGC cohort, transcriptomic, genomic mutation, and clinical messages were extracted. From the GeneCards Database, a list of 1399 OS genes with a relevance score ≥7 was obtained. The limma package in R was utilized to compare OS genes expression between normal tissues and HCC tissues for the purpose of screening DEOSGs, as the following standard: |log2 fold change| (|log2FC|) > 1 and adjusted p value < 0.05. This yielded 434 DEOSGs for subsequent analysis.
## 2.2. PPI Network Construction
A significant association of the PPI network in DEOSGs was created by employing the STRING database. We also employed Cytoscape software (version 3.7.2, Seattle, WA, USA) for the visual exploration of interaction networks. Molecular Complex Detection (MCODE) was operated as a Cytoscape plugin to identify critical PPI network modules [23].
## 2.3. Functional Enrichment Analysis
We conducted Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses for these DEOSGs by employing the clusterProfiler package to determine their main biological and underlying mechanisms [21,22]. Adjusted p value < 0.05 was regarded as statistically significance.
## 2.4. Identification of HCC-Related Hub Genes by WGGCNA
The “WGCNA” R package was performed to build a co-expression network based on 434 DEOSGs in the TCGA database [25,26]. Using hierarchical clustering, 434 DEOSGs were analyzed among normal and tumor tissues. Next, a suitable soft thresholding parameter (β) was applied to emphasize gene connections and penalize weak connections. Afterward, we converted the adjacencies into topological overlap matrices (TOMs). By using the TOM-based dissimilarity assessment, the DEOSG dendrogram was clustered with a minimum module size of 25 and the dissimilarity between modules was measured. Furthermore, the modules most relevant to tumor tissues were found by two parameters (gene significance (GS) and module eigengenes (MEs)). In functional terms, hub genes are nodes within modules that have a high degree of interconnection [27]. This study defined genes in the significant module as HCC-related hub genes.
## 2.5. Establish and Validation of Prognostic Risk Model
In the TCGA-LIHC cohort, we carried out the univariate cox analysis among hub genes to determine DEOSGs closely related to overall survival (OS) via the “survival” R package, and genes were recognized as prognostic DEOSGs with $p \leq 0.05.$ Afterwards, the LASSO regression analysis was conducted using the glmnet package in R software [24]. Finally, the prognostic risk model was created by multivariate cox analysis. For evaluating HCC risk scores, the following formula was used: risk score = ∑ni = vi × ci (where vi means gene’s expression and ci means gene’s corresponding coefficient). In the ICGC cohort, the risk model was confirmed. Each patient’s risk score was determined using the formula above. With the median value as the cut-off point, patients were stratified into high and low risk groups. The prognostic value of the model was assessed by Kaplan–Meier survival curves (K–M curves). Specificity and sensitivity of our risk model was validated by creating receiver operating characteristic (ROC) curves using the survivalROC and timeROC R packages.
## 2.6. Construction of Nomogram
On the TCGA cohort, univariate and multivariate analyses were conducted to assess if the risk model could be regarded as an independent risk factor. An evaluation of the clinical usefulness of the model at different risk thresholds was also conducted using the decision curve analysis (DCA) function in the “ggDCA” R package [28]. Comprised of gender, pathological grade, age, tumor stage, and risk group, a prognostic nomogram was established. A concordance index (C-index) and calibration curve were constructed for verifying the predicting discriminative value and accuracy of the nomogram. The construction of the nomogram, C-index, and calibration plots were completed using the “RMS” R package [29,30].
## 2.7. Calculation of Tumor Mutation Burden
Tumor mutational burden (TMB) is measured by the number of mutations per million bases in a tumor sample, including nonsense mutations, frameshift mutations, missense mutations, etc. Based on 38 million human exons, we calculated the TMB values using Perl scripts. In order to visualize the relationship among the TMB and risk group, we generated waterfall plots with the “maftools” package in R [31].
## 2.8. Investigation of HCC Immunity
We analyzed immune subtype proportions between the two risk groups based on UCSC-Xena database (https://xenabrowser.net//datapages//, accessed on 25 August 2022) using the “RColorBrewer” package [32]. Furthermore, to further confirm the connection between the risk and HCC immunity, the immune cell infiltration levels were quantified with ssGSEA. By using the Wilcoxon test of two samples, the levels of immune cells and the function of the two groups were compared. A comparison was also made between different groups regarding the expression of immune checkpoint genes and HLA (human leukocyte antigen) genes.
To predict immunotherapy response, we obtained immunophenoscores (IPS) for HCC patients using the Cancer Immunome Atlas (TCIA, https://tcia.at/, accessed on 25 August 2022) website [33]. Wilcoxon rank-sum tests were used to investigate the relationship between IPS and risk model. An increase in IPS score reflects higher immune reactivity, and a lower IPS score indicates lower immune reactivity.
## 2.9. Expression and Genetic Alteration Analyses of DEOSGs of Risk Model in HCC
TCGA-LIHC dataset was utilized to analyze the mRNA expression of five DEOSGs of risk model in HCC, and the Human Protein Atlas (HPA) (https://www.proteinatlas.org/, accessed on 25 August 2022) was applied to determine protein expression of five DEOSGs [34]. Prognostic evaluation of five DEOSGs was completed using the Kaplan–Meier Plotter website (https://kmplot.com/analysis/, accessed on 25 August 2022). In addition, to detect the copy-number alterations and mutation of above genes, the online database cBioPortal was employed [35].
## 2.10. Cell Culture
The human normal liver cell line, THLE-2, was obtained from Shanghai Academy of Life Science (Shanghai, China). Human hepatoblastoma cell line HepG2 (catalog No. ZQ0022), human HCC cell lines, (HCCLM3 (catalog No. ZQ0023), Hep3B (catalog No. ZQ0024), and Huh7 (catalog No. ZQ0025) were purchased from Zhong Qiao Xin Zhou Biotechnology (Shanghai, China). All cell lines were inoculated into culture dishes and added to Dulbecco’s Modified Eagle’s Medium (DMEM) containing $10\%$ fetal bovine serum (FBS) to maintain growth. The cell culture medium was also supplemented with $1\%$ penicillin/streptomycin. The growth environment temperature was maintained at 37 °C with $5\%$ CO2. The culture dishes were purchased from Guangzhou Jet Biofiltration (Guangzhou, China). FBS, and penicillin/streptomycin were purchased from BI (BI, Ridgefield, CT, USA).
## 2.11. RNA Extraction and Quantitative Reverse Transcription PCR
Using the total RNA isolation kit (Foregene, Chengdu, China) and the PrimeScript RT kit (Takara Biomedical Technology, Beijing, China), RNA was extracted from the cells and reverse transcribed into cDNA. TB Green Premix Ex TaqII (Takara Biomedical Technology, Beijing, China) was used for real-time PCR. The relative expression was compared with the expression of GAPDH, and was calculated by 2−ΔΔCt. The qPCR primers are listed in Supplementary Table S4. [ 36]
## 2.12. Chemotherapeutic Drug Analysis in Different Groups
Since there are no biomarkers that predict HCC chemotherapy drug sensitivity; through 10-fold cross-validation, the half-maximal inhibitory concentrations (IC50) of several chemotherapy drugs among two risk groups were calculated and compared. The calculation process was carried out by ridge regression using the “pRRophetic” R package [37], which can predict tumor chemotherapy response based on gene expression levels. A comparison of IC50 among the two groups was processed by the Wilcoxon signed-rank test.
## 2.13. Statistical Analysis
Perl language and R language were applied to carry out all statistical analyses. The differences in measurement data were compared by Student’s t-test. Using the log-rank test, the Kaplan–Meier curve was established for identifying survival of HCC patients. To determine independent predictors of HCC survival, Cox regression analyses were further executed. The Chi-squared test was used to compare data from categorical variables between two groups. All statistical analysis were executed with R software (version 4.1.0, https://www.r-project.org/, accessed on 25 August 2022). Two-tailed significance tests were performed, with $p \leq 0.05$ regarded as statistically significant. * $p \leq 0.05$; ** $p \leq 0.01$; *** $p \leq 0.001$; **** $p \leq 0.0001.$
## 3.1. Analysis of DEOSGs in HCC Samples
In the TCGA-LIHC cohort, expressions of 1399 OS genes were compared between 50 normal and 374 HCC samples. Of these, 434 oxidative stress related genes (OSGs) were identified as DEOSGs in HCC, comprising 62 downregulated and 372 upregulated genes (Supplementary Table S1, $p \leq 0.05$ and |log2FC| ≥ 1). As shown in Figure 1A,B, a hierarchical cluster heatmap and volcano plot were employed to visualize the DEOSGs.
To explore the interrelationship of DEOSGs, by employing the STRING dataset and Cytoscape software, we created a PPI network with 416 vertices and 6280 links (Figure 1C). As shown in Figure 1D, the MCODE plugin was further used, and the top 3 substantial modules (with 45 vertices and 498 links, 50 vertices and 466 links, and 40 vertices and 132 links) were identified as the potential key modules in the network.
Figure 1E–H shows the major 30 enriched pathways recognized by KEGG pathway analysis, including lipid and atherosclerosis, cellular senescence, MAPK signaling pathway, hepatitis B, and other KEGG pathways. As shown in Figure 1I–L, the leading 10 enriched GO terms for DEOSGs included oxidative stress, aging, and response to hypoxia. The functional enrichment analysis discovered that the DEOSGs were connected to cellular senescence, MAPK pathway, aging, and cancer.
## 3.2. Identification of HCC-Related Hub DEOSGs for by WGCNA
After that, WGCNA of 50 normal and 374 HCC samples from the TCGA database was performed based on the expression of 434 DEOSGs (Figure 2A). A soft threshold of 4 was chosen for the scale-free networks (Figure 2B,C); and three co-expressed modules were identified (Figure 2D). Each module was colored differently in order to determine the one most closely related to HCC. In particular, the turquoise module was chosen (Cor = 0.23, $p \leq 0.0001$) (Figure 2E). In total, 257 genes in turquoise module were identified as hub DEOSGs of HCC (Figure 2F).
## 3.3. Construction of a Prognostic Risk Model of DEOSGs
A univariate cox regression analysis was applied on 257 hub DEOSGs in order to identify prognosis-associated DEOSGs, and 146 DEOSGs with $p \leq 0.05$ were recognized as HCC prognostic DEOSGs (Supplementary Table S2). Furthermore, the LASSO algorithm was used for calculating the collinearity and following refinement (Figure 3A,B), and 5 DEOSGs, including lysyl oxidase (LOX), cytochrome P450 family 2 subfamily C member 9 (CYP2C9), eukaryotic translation initiation factor 2B subunit delta (EIF2B4), enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2), and sulfiredoxin 1 (SRXN1) were selected to form a prognostic risk model (Figure 3C, Supplementary Table S3). The prognostic risk score were calculated as follows: risk score = 0.246 × LOX + (−0.083) × CYP2C9 + 0.551 × EIF2B4 + 0.356 × EZH2 + 0.353 × SRXN1.
HCC patients were categorized into low and high risk groups based on their median risk scores in both the TCGA-LIHC and ICGC cohorts. In both the TCGA-LIHC cohort (Figure 3D) and ICGC cohort (Figure 3H) ($p \leq 0.001$), HCC patients with higher scores had worse overall survival. Notably, with an increased risk score, the death events were significantly increased (Figure 3E,I). Besides, time-dependent ROC curves showed the prognostic risk model to be quite reliable with the area under the ROC (AUC) of 0.790 in the TCGA-LIHC cohort (Figure 3F) and 0.743 in the ICGC cohort (Figure 3J) at 1 year. More interesting, in the TCGA-LIHC cohort, compared to other clinical characteristics, such as age, gender, pathological grade, tumor stage, T, M, and N, AUC over 1 year demonstrated that the model had an higher prognostic accuracy (Figure 3G). Moreover, the model showed good predictive ability in the ICGC cohort (Figure 3K). Taken together, this prognostic risk model had sufficient specificity and sensitivity.
## 3.4. Independent Prognostic Value of the Model and Establish of the Nomogram
Moreover, to determine the independence the risk model for HCC patients, independently prognostic analysis was achieved using univariate and multivariate cox regression analysis. In the TCGA-LIHC cohort (Figure 4A,B) and the ICGC cohort (Figure 4C,D), the risk model maybe an independently prognostic factor of HCC patients ($p \leq 0.001$). In the TCGA-LIHC cohort, as shown by the DCA curve (Figure 4E), the model outperformed other clinicopathological characteristics.
The survival probabilities for HCC at 1, 3, and 5 years were estimated using a nomogram plot containing the risk scores and clinical characteristics of the TCGA-LIHC cohort (Figure 4F). Moreover, the C-index of the risk score was higher than other clinicopathological characteristics (Figure 4G). The calibration plots indicated great consistency between prediction and actual risk in the TCGA-LIHC cohort at 1, 3, and 5 years (Figure 4H). Overall, the prognostic risk model showed good prognostic value in HCC samples.
## 3.5. Comparison of Risk Model and Other Models
We compared our risk model with three established prognosis-related risk models, namely 4-gene signature (Peng) [38], 8-gene signature (Qu) [39], and 8-gene signature (Cao) [40]. Based on the corresponding genes and coefficients, risk scores were calculated for each HCC patient using the three models. The median risk scores were used to classify HCC patients into high and low risk groups. The three models showed different prognoses of HCC in the high and low risk groups (Figure 5A–C, $p \leq 0.001$). However, our model had higher 1, 3, and 5-year AUC values (Figure 5D–F) and a higher C-index (Figure 5G) than these models, highlighting that our model has more reasonable and effective results.
## 3.6. Connections between Prognostic Risk Model and Clinical Characteristics of HCC Patients
In the TCGA–LIHC cohort, the distribution of clinical characteristics, including survival state, pathological grade, and tumor stage, among the two risk groups was significantly different (Figure 6A, $p \leq 0.05$). Additionally, HCC patients with higher risk scores had the worst pathological grades and advanced tumor stages (Figure 6B–D) of HCC patients.
According to the different clinical parameters, we further divided patients into several subgroups (Figure 6E–N). In this study, the clinical stratifications contained gender (female vs. male) (Figure 6E,F), pathological grade (G1 vs. G2 vs. G3–4) (Figure 6G–I), age (≥60 vs. <60) (Figure 6J,K), and tumor stage (I vs. II vs. III–IV) (Figure 6L–N). According to the K–M curves, for all of these parameters, with the exception for stage II, high-risk patients had worse outcomes than low-risk patients.
## 3.7. Functional Analyses Based on the Risk Model
Gene function analyses among the two groups were conducted by 2195 DEGs identified between the subgroups ($p \leq 0.05$ |log2FC| ≥ 1). GO enrichment analysis revealed that DEGs tended to be enriched in “nuclear division”, “positive regulation of cell activation”, “B cell activation”, and “mitotic nuclear division” in the biological process (Figure 7A–C). DEGs were primarily concentrated in the PI3K-Akt signaling pathway, cell cycle, cytokine-cytokine receptor interaction, ECM-receptor interaction, and *Fc gamma* R-mediated phagocytosis, according to the KEGG pathway analysis (Figure 7D–F). The functional annotations from GO and KEGG were further validated and complemented by gene set enrichment analysis (GSEA). A GO enrichment analysis of the high risk group identified the following biological processes as the most enriched: activation of immune response, B cell activation, adaptive immune response, and B cell mediated immunity (Figure 7G). In contrast, drug catabolic process, high density lipoprotein particle, and aromatase activity were the majority concentrated pathways in the low risk group (Figure 7H). Additionally, based on KEGG analysis, the high risk group’s enriched pathways included cell adhesion molecules (CAMs), ECM-receptor interaction, and cytokine-cytokine receptor interaction (Figure 7I), while fatty acid metabolism, butanoate metabolism, and primary bile acid biosynthesis were the most concentrated pathways in low risk group (Figure 7J).
## 3.8. Analysis of Tumor Mutation Burden
TMB, or non-synonymous variation, plays a significant role in immune cell infiltration [41]. As shown in Figure 8A, the waterfall plot indicated the mutation rate of 146 prognostic DEOSGs in the TCGA cohort. According to Spearman’s correlation analysis, the risk score and mRNAsi score are positively correlated (Figure 8B). Since TMB may have a significant role in clinical practice, the relationship of TMB and the model was investigated. TMB was higher in the high risk group, and was positively correlated with risk score (Figure 8C,D). Furthermore, the TMB and risk score combined to influence survival outcomes in HCC patients (Figure 8E). Using waterfall plots, different risk groups were shown to have different mutation characteristics (Figure 8F,G). In the high risk group, mutation frequency was higher, in line with the TMB score. Increased mutation frequencies of TP53, CTNNB1, TTN, and MUC16 were found in the high risk group, but the ALB mutation frequency was noticeably greater in the low risk group. The majority of the mutations were missense mutations and frameshift deletions.
## 3.9. Associations between Prognostic Risk Model and HCC Immunity
According to Figure 9A, the proportion of HCC immune subtypes varied between risk groups. In Figure 9B,C, differences between two risk groups are shown in terms of immune cell and immune function scores. Furthermore, two groups were compared regarding HLA gene expression and immune checkpoint gene expression. The results showed that high risk patients had higher expressions of the majority of HLA genes and immune checkpoint genes (Figure 9D,E), indicating an exhausted immune microenvironment in patients with higher risk scores. Furthermore, Figure S1 revealed the detailed information of several immune checkpoint genes’ expression in the high and low risk groups: patients in the high risk group had higher expressions of PD-1 ($p \leq 0.001$) (Figure S1A), CTLA4 ($p \leq 0.001$) (Figure S1B), TIM3 ($p \leq 0.001$) (Figure S1C), TNFSF4 ($p \leq 0.001$) (Figure S1D), TNFSF9 ($p \leq 0.001$) (Figure S1E), TNFSF18 ($p \leq 0.001$) (Figure S1F), TNFRSF4 ($p \leq 0.001$) (Figure S1G), TNFRSF9 ($p \leq 0.001$) (Figure S1H), TNFRSF18 ($p \leq 0.001$) (Figure S1I), CD276 ($p \leq 0.001$) (Figure S1J), VTCN1 ($p \leq 0.001$) (Figure S1K), and TIGIT ($p \leq 0.001$) (Figure S1L). A high risk score in the risk model was significantly positively associated with PD-1 ($R = 0.27$, $p \leq 0.001$), CTLA4 ($R = 0.33$, $p \leq 0.001$), TIM3 ($R = 0.33$, $p \leq 0.001$), TNFSF4 ($R = 0.3$, $p \leq 0.001$), TNFSF9 ($R = 0.32$, $p \leq 0.001$), TNFSF18 ($R = 0.25$, $p \leq 0.001$), TNFRSF4 ($R = 0.38$, $p \leq 0.001$), TNFRSF9 ($R = 0.37$, $p \leq 0.001$), TNFRSF18 ($R = 0.3$, $p \leq 0.001$), CD276 ($R = 0.45$, $p \leq 0.001$), VTCN1 ($R = 0.26$, $p \leq 0.001$), and TIGIT ($R = 0.2$, $p \leq 0.001$). In addition, Figure S1M revealed that SRXN1, LOX, EZH2, and EIF2B4 were positively correlated with immune checkpoint genes, while CYP2C9 were negatively correlated with immune checkpoint genes.
Figure 9F revealed the correlation between five genes in models and immune cells infiltration. Further evaluation was conducted to determine if the model could predict HCC patients’ response to immunotherapy. As shown in Figure 9G–J, the value of CTLA4− PD1−-IPS and CTLA4+ PD1+-IPS in the low risk group was higher than in the high risk group ($p \leq 0.05$), indicating that HCC patients in the low risk group showed significant therapeutic effects with anti-CTLA4 therapy and anti-PD1 therapy.
## 3.10. Expression of DEOSGs in Prognostic Risk Model in HCC
Furthermore, we explored the expression of five DEOSGs as a prognostic risk model for HCC. In the TCGA database, the mRNA level of LOX, EIF2B4, EZH2, and SRXN1 were significantly upregulated in HCC samples, while CYP2C9 was significantly downregulated compared with normal liver tissues (Figure 10A). The K–M curves revealed that the high expression of LOX, EIF2B4, EZH2, and SRXN1 presented a poor OS. In contrast, high CYP2C9 expression predicted better OS (Figure 10B). Similarly, from the HPA dataset, the protein expression pattern of these five genes demonstrated a consistent trend in mRNA expression (Figure 10C); unfortunately, there is no LOX and SRXN1 information in this database. As shown in Figure 10D, the frequencies of gene alterations, containing amplifications, deep deletions, missense mutations, and truncating mutation for these five genes ranged from $0.2\%$ to $1.7\%$ in the cBioPortal database.
## 3.11. RT-qPCR Validation of Five Genes in HCC Cell Lines
We used RT-qPCR to further verify the expressions of model genes (CYP2C9, EIF2B4, EZH2, SRXN1, and LOX) in the HCC cell lines. The results showed that the expressions of EIF2B4, EZH2, SRXN1, and LOX were upregulated in most HCC cell lines, and the expressions of CYP2C9 was downregulated, which was consistent with gene expressions in the TCGA database (Figure 10E–I).
## 3.12. Drug Sensitivity Analysis of the Model
To measure whether the model could be applied to personalized treatment of HCC, we compared the IC50 values of several chemotherapy drugs between two groups by the Wilcoxon signed-rank test. A low IC50 indicates a sensitive response. Interestingly, a curious finding was that compared to the low risk group, patients with high risk had lower IC50 values of sorafenib ($p \leq 0.0001$), sunitinib ($p \leq 0.0001$), dasatinib ($p \leq 0.0001$) gemcitabine ($p \leq 0.0001$), rapamycin ($p \leq 0.0001$), roscovitine ($p \leq 0.0001$), paclitaxel ($p \leq 0.0001$),mitomycin C ($p \leq 0.0001$), and bleomycin C ($p \leq 0.0001$), suggesting that the above chemotherapies may benefit patients with high risk (Figure 11).
## 4. Discussion
HCC, as a malignant neoplasm, is the third common cause of cancer death, globally accounting for almost 75–$85\%$ of primary liver cancer deaths. Although targeted molecular therapies and immunotherapy have demonstrated encouraging treatment benefits for HCC patients recently, and atezolizumab and bevacizumab are used as first-line treatment for advanced HCC [42], the overall clinical prognosis of HCC patients are far from satisfactory as a consequence of drug resistance [1,4]. Many studies were performed to explore effective models to precisely predict the prognosis and response to treatment of HCC patients, in the hope of providing more evidence for precision therapy [43,44,45]. Therefore, it is imperative to detect novel validated prognostic biomarkers and construct new models to predict the precise treatment for HCC patients.
An increase in ROS and RNS causes oxidative stress [46], which plays a key factor in the progression of liver carcinogenesis [47]. The presence of elevated ROS levels causes damage to DNA, RNA, lipids, and proteins. ROS imbalance promotes cellular proliferation, apoptosis evasion, angiogenesis, invasion, and metastasis [48]. When ROS are highly expressed, immature myeloid cells (IMC) produce MDSCs that suppress the immune system. Therefore, the clinical significance, biological role, and immune infiltration of OS genes can be extensive analyzed to provide a new direction in the research and treatment on HCC.
In our study, based on the TCGA database, 434 DEOSGs were determined. Of these, we regarded 257 genes in the turquoise module identified by WGCNA as HCC-related hub genes. Then, 146 prognostic DEOSGs were found by univariate cox analysis, and five DEOSGs (LOX, CYP2C9, EIF2B4, EZH2, and SRXN1) were selected to develop a risk model of HCC patients by LASSO and multivariate cox analysis.
Afterwards, this prognostic model had a superior forecast accuracy than the usual clinical characteristics, including pathological grade, tumor stage, age, and gender, as indicated by the ROC curve. More importantly, we revealed that the risk model was remarkably connected with advanced tumor stage, and worse pathological grade. Taken together, our results demonstrate this DEOSGs-related risk model can improve the prediction of prognosis and supply a novel perspective for assessing the survival in HCC patients.
We observed that the low risk group was mainly enriched in metabolism-related pathways, while the high risk group was primarily related to immune pathways. Furthermore, we found that TMB and the risk score can effectively distinguish the prognosis of HCC patients. Additionally, we displayed the different gene mutations frequency between subgroups.
More interestingly, C1 (wound healing) and C2 (IFN-g dominant) subtypes were more prevalent in the high risk group, whereas C3 subtypes (inflammatory) were less prevalent. The expression of immune checkpoint genes enable tumor cells to evade immune surveillance, resulting in immunosuppression in the TME. The expression of almost all immune checkpoint genes were upregulated in patients with high risk scores, and correlation analyses showed significant positive association between checkpoint genes and risk score, as well as the five OS genes comprised in the risk model, suggesting that patients with higher risk scores have severer exhausted immune microenvironments. In addition, the low risk group patients respond better to anti-PD-1 and anti-CTLA4 therapies, showing that immunotherapy can benefit HCC patients in the low risk group.
The TCGA and HPA datasets showed that expression of LOX, EIF2B4, EZH2, and SRXN1 were significantly upregulated in HCC tissues, while CYP2C9 was significantly downregulated. The K–M curves of these five genes showed that the upregulation of LOX, EIF2B4, EZH2, and SRXN1 presented poor OS. However, a higher expression of CYP2C9 predicted better OS. Umezaki et al. discovered that high expression of LOX is associated with EMT markers, early recurrence, and poor survival in HCC patients [49]. Research has also reported that decreased levels of CYP2C9 in HCC tissues [50,51], indicating the involvement of CYP2C9 in detoxification, may play an important role in the initiation of HCC. There is evidence that EZH2 is elevated in HCC and promotes proliferation, migration, and invasion of HCC cells, acted as a negative prognostic biomarker associated with immunosuppression, and is associated with sorafenib resistance in HCC [52,53,54,55]. SRXN1, an antioxidant molecule, was significantly upregulated in HCC and its increasement might lessen BTG2 expression, resulting in an increase in HCC cell proliferation. These findings are broadly consistent with the expression patterns we detected in this study. Notably, the function of EIF2B4 in HCC have not been reported yet and need to be further investigated.
It should be noted that HCC is relatively insensitive to chemotherapeutic drugs because of drug resistance mechanisms and heterogeneity, so that chemotherapeutics have limited effect. Several chemotherapy drugs showed different responses in the two groups, suggesting that the model could also help in selecting chemotherapy drugs for HCC patients.
Although we discovered a risk model composed of five DEOSGs that proved to be related to immunosuppression, there are limitations to this work. Further studies are needed to validate its reliable prognostic value in clinical practice. Meanwhile, the study was a retrospective analysis and conducted by bioinformatics analysis, which was not powerful enough and requires further prospective research and experimental verification. In addition, a number of laboratory experiments, including in vivo and in vitro studies, need to be performed to determine the underlying mechanism of these genes in HCC progression.
In our study, we constructed a prognosis-related oxidative stress model with strong predictive power for HCC patients. The phenotypes of HCC patients can be quantified and individualized using the risk score calculated by the model. The model may have important implications for the selection of ICIs and chemotherapy for HCC. Taken together, our model has great potential as a novel biomarker of HCC. As far as we know, this is the first prognostic OS-related risk model for HCC patients leading to improving prediction of HCC prognosis and providing new insights for HCC immunotherapy.
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|
---
title: Pre-treatment with IL-6 potentiates β-cell death induced by pro-inflammatory
cytokines
authors:
- V. R. Oliveira
- C. C. Paula
- S. Taniguchi
- F. Ortis
journal: BMC Molecular and Cell Biology
year: 2023
pmcid: PMC10045109
doi: 10.1186/s12860-023-00476-3
license: CC BY 4.0
---
# Pre-treatment with IL-6 potentiates β-cell death induced by pro-inflammatory cytokines
## Abstract
### Background
Type I *Diabetes mellitus* (T1D) is characterized by a specific destruction of β-cells by the immune system. During this process pro-inflammatory cytokines are released in the pancreatic islets and contribute for β-cells demise. Cytokine-induced iNOS activation, via NF-κB, is implicated in induction of β-cells death, which includes ER stress activation. Physical exercise has been used as an adjunct for better glycemic control in patients with T1D, since it is able to increase glucose uptake independent of insulin. Recently, it was observed that the release of IL-6 by skeletal muscle, during physical exercise, could prevent β-cells death induced by pro-inflammatory cytokines. However, the molecular mechanisms involved in this beneficial effect on β-cells are not yet completely elucidated. Our aim was to evaluate the effect of IL-6 on β-cells exposed to pro-inflammatory cytokines.
### Results
Pre-treatment with IL-6 sensitized INS-1E cells to cytokine-induced cell death, increasing cytokine-induced iNOS and Caspase-3 expression. Under these conditions, however, there was a decrease in cytokines-induced p-eIF2-α but not p-IRE1expression, proteins related to ER stress. To address if this prevention of adequate UPR response is involved in the increase in β-cells death markers induced by IL-6 pre-treatment, we used a chemical chaperone (TUDCA), which improves ER folding capacity. Use of TUDCA increased cytokines-induced Caspase-3 expression and Bax/Bcl-2 ratio in the presence of IL-6 pre-treatment. However, there is no modulation of p-eIF2-α expression by TUDCA in this condition, with increase of CHOP expression.
### Conclusion
Treatment with IL-6 alone is not beneficial for β-cells, leading to increased cell death markers and impaired UPR activation. In addition, TUDCA has not been able to restore ER homeostasis or improve β-cells viability under this condition, suggesting that other mechanisms may be involved.
### Supplementary Information
The online version contains supplementary material available at 10.1186/s12860-023-00476-3.
## Background
Type I *Diabetes mellitus* (T1D) is an autoimmune disease characterized by a genetic predisposition associated with environmental factors, that results in an autoimmune attack against insulin-producing β-cells, leading to its dysfunction and death [1–6].
This specific attack against β-cells occurs through a process known as insulitis, in which cells of the immune system infiltrate pancreatic islets and secret pro-inflammatory cytokines, such as Interleukin (IL)-1β, Interferon (IFN)-γ and Tumoral Necrosis Factor (TNF) [3, 7]. Leading, among others, to the expression of Inducible Nitric Oxide Synthase (iNOS), with consequently production of nitric oxide (NO) and of Endoplasmic Reticulum (ER) stress induction, triggering β-cells death [1–3, 8–11]. The activation of ER stress induces a cell survival response known as Unfolded Protein Response (UPR), which has the function of recovering homeostasis of ER. However, if the ER homeostasis is not recovered, pro-apoptotic pathways are activated [9, 12–14], as we observe for cytokine-exposed β-cells [9, 13–16].
T1D patients treatment consists of administration of exogenous insulin combined with the practice of physical exercise, which helps to restore glycemic control [17–19] and increase glucose uptake independent of insulin [20–22]. Beside this effect, it has being reported that physical exercise has an anti-inflammatory effect, leading to improvement in insulin secretion and β-cells protection [23–25]. However, the mechanism and pathways involved in this protection are not yet well defined. In the last years, attention has been focused on Interleukin 6 (IL-6) [26, 27], which when is released by skeletal muscles, it can stimulate the release of anti-inflammatory factors such as Interleukin 10 (IL-10) and inhibit the production of pro-inflammatory cytokines such as TNF [20, 28–30].
The protective anti-inflammatory effect of IL-6 in pancreatic β-cells was shown by Paula and collaborators [24, 25], in which islets of human and trained animals were resistant to cell death induced by pro-inflammatory cytokines, with a decrease in Caspase-3 and iNOS expression. Moreover, serum from physical trained subjects protected human and rodent β-cells against ER stress and apoptosis [25]. In addition, blocking of IL-6 partially prevented these beneficial effects [24, 25].
Since IL-6 is a pleiotropic cytokine, that is described to have pro- and anti-inflammatory effects [31], it is important to understand the specific pathways that could be modulated by IL-6 in β-cells, to prevent the deleterious effect of pro-inflammatory cytokines. This knowledge may help to design therapeutic protocols for T1D treatment or even prevention. Thus, here we pre-exposed the rat β-cell line, INS-1E, to IL-6 and then treated these cells with a combination of pro-inflammatory cytokines, to mimetic the insulites environment. We then investigate the effects of this pre-treatment on the expression of pro-apoptotic markers involved in cytokine induced β-cells death.
## Pre-treatment with IL-6 increases cytokine-induced pancreatic β-cells death markers
Exposure of INS-1E cells to pro-inflammatory cytokines (IL-1β + IFN-γ) leads to cell death, mainly by apoptosis, with increase of Caspase-3 (the active form) and iNOS expression [3, 11], as observed here (Fig. 1).Fig. 1IL-6 increases IL-1β and IFN-γ induced Caspase-3 and iNOS expression in INS-1E cells. Cells were exposed to IL-6 (IL6) or untreated (Ctrl). After 24 h cells were exposed to IL-1β and IFN-γ in the absence (Cyto) or in the presence of pre-treatment with IL-6 (IL6 + Cyto) or continuous treatment of IL-6 (IL6 + IL6 + Cyto). A Western blot for Caspase-3 and α-Tubulin. B The barplot showing the means values obtained in six independent experiments corrected by the housekeeping protein α-Tubulin. One-way ANOVA followed by Sidak’s correction. * $p \leq 0$,05, **$p \leq 0$,001 vs Ctrl, &$p \leq 0$,05 vs Cyto. C Western blot for iNOS and α-Tubulin. D The barplot showing the mean values obtained in four independent experiments corrected by the housekeeping protein GAPDH. One-way ANOVA followed by Sidak’s correction. ** $p \leq 0$,001 vs Cyto Pre-exposure of these cells to IL-6 increased cytokines-induced Caspase-3 expression (Fig. 1 A-B), although IL-6 alone had no effect on Caspase-3 expression. Similarly, induction of iNOS expression by cytokines was increased by IL-6 pre-exposure, with no effect of IL-6 alone on iNOS expression (Fig. 1 C-D). Of note, the same effect was observed when IL-6 was only used during the pre-exposure time, 24 h before cytokines exposure, or was kept also after this period together with the cytokine mix.
## Pre-treatment with IL-6 protect β-cells against cytokine-induced UPR protein expression
Cytokine-induced iNOS in rat β-cells leds to NO production and ER stress activation, which contribute to β-cells death [3, 13, 16]. Thus, we evaluate expression of phosphorylated form of eIF2-α (p-eIF2-α) and IRE1 (p-IRE1), two ER stress markers induced by cytokines in β-cells [13, 14, 16].
As expected, exposure of β-cells to cytokines increase expression of p-eIF2-α and p-IRE1 (Fig. 2 A-B and C-D, respectively). Although IL-6 alone did not modulate expression of this ER stress marker, it prevented induction of p-eIF2-α by cytokines (Fig. 2).Fig. 2IL-6 decreases IL-1β and IFN-γ induced p-eIF2-α and p-IRE1 expression in INS-1E cells. Cells were exposed to IL-6 (IL6) or untreated (Ctrl). After 24 h cells were exposed to IL-1β and IFN-γ in the absence (Cyto) or in the presence of pre-treatment with IL-6 (IL6 + Cyto) or continuous treatment of IL-6 (IL6 + IL6 + Cyto). A Western blot for p-eIF2-α and α-Tubulin (note that α-Tubulin image is the same used in Fig. 1A, since they are from the same blot where caspase 3 and eiF2α were evaluated). B The barplot showing the mean values obtained in five independent experiments corrected by the housekeeping protein α-Tubulin. One-way ANOVA followed by Sidak’s correction. * $p \leq 0$,05 vs Ctrl. C Western blot for p-IRE1 and α-Tubulin. D The barplot showing the mean values obtained in four independent experiments corrected by the housekeeping protein α-Tubulin
## The deleterious effect of IL-6 on pancreatic β cells is not prevented by increasing of ER protein folding capacity
We next used a chemical chaperon, TUDCA, that was previously shown to improve ER protein folding and rescue cells from ER stress [14, 32, 33], to evaluate if this would help to protect β-cells against IL-6 pre-treatment leading to cytokine-induced cell death worsening.
Our results showed that TUDCA addition to condition of pre-treatment with IL-6 and exposure to cytokines seems to further increase Caspase-3 expression (Fig. 3 A-B), in spite of not being able to modulate the expression of p-eIF2-α (Fig. 3 C-D) or BiP mRNA (Fig. 4A) in this conditions. In addition, TUDCA did not prevent increased mRNA expression of CHOP (Fig. 4B) neither of Bax/Bcl-2 ratio (Fig. 4C).Fig. 3TUDCA increases Caspase-3 but decreases p-eIF2-α expression in INS-1E cells. Cells were exposed to IL-6 (IL6) or untreated (Ctrl). After 24 h cells were exposed to TUDCA in the absence (TUDCA) or in the presence of pre-treatment with IL-6 (IL6 + TUDCA) and IL-1β and IFN-γ (TUDCA + Cyto) or pre-treatment with IL-6 and IL-1β and IFN-γ (IL6 + TUDCA + Cyto). Cells also were exposed to IL-1β and IFN-γ in the absence (Cyto) or in the presence of pre-treatment with IL-6 (IL6 + Cyto). A Western blot for Caspase-3 and α-Tubulin. B The barplot showing the mean values obtained in six independent experiments corrected by the housekeeping protein α-Tubulin. One-way ANOVA followed by Sidak’s correction. ** $p \leq 0$,001 vs Ctrl. C Western blot for p-eIF2-α and α-Tubulin. D The barplot showing the mean values obtained in five independent experiments corrected by the housekeeping protein α-Tubulin. One-way ANOVA followed by Sidak’s correction. * $p \leq 0$,05, ***$p \leq 0$,0001 vs CtrlFig. 4TUDCA prevent increase in BiP expression induced by cytokines + IL6 but not CHOP expression and Bax/Bcl2 ratio in INS-1E cells. Cells were exposed to IL-6 (IL6) or untreated (Ctrl). After 24 h cells were exposed to TUDCA in the absence (TUDCA) or in the presence of pre-treatment with IL-6 (IL6 + TUDCA). Cells also were exposed to IL-1β and IFN-γ (Cyto) or not [-]. Expression of BiP A and CHOP B and Bax/Bcl-2 C was evaluated by RT-qPCR. The bar plot shows the mean values obtained in three independent experiments normalized by Rn18s and control by method 2-ΔΔCT. One-way ANOVA followed by Sidak’s correction. ** $p \leq 0$,001 vs Ctrl
## Discussion
Physical exercise is an important tool in the treatment of numerous diseases, including T1D. Particularly, in the T1D the exercises have been argued as a beneficial factor, closely associated with the increase of β-cells viability and its physiological functions [23–25]. It is known that during physical exercise myokines are produced by skeletal muscle that can result in beneficial effects, among them, IL-6 has been shown to stimulate anti-inflammatory factors release and inhibit of pro-inflammatory cytokines production [20, 28–30]. However, most of these findings are based on the use of serum from exercised animals, which can induce the activation of several pathways in addition to IL-6, leading to a combined beneficial effect to the β-cells in the pro-inflammatory insult that occurs during T1D [23–25]. Therefore, it is important to evaluate the effects of IL-6 alone in pancreatic β-cells exposed to pro-inflammatory cytokines.
It is known that the cytokine-induced nitric oxide production, through NF-κB induced iNOS, is associated with the blocking of the ER calcium pump (SERCA2b) [16, 34] and causes stress in the ER, contributing to β-cells death [3, 13, 16]. Our data showed that pre-treatment with IL-6 leads to a higher sensitivity of INS-1E cells to death induced by pro-inflammatory cytokines, inducing increased iNOS and Caspase-3 expression. These data show us that pre-treatment with IL-6 alone does not have a beneficial effect on INS-1E cells viability exposed to pro-inflammatory cytokines. This apparently contradiction of our results and the beneficial effects of pre-treatment with IL-6 observed by Paula [24] may be due to the different cytokine combination used here. Paula used a combination of IL-1β and IFNγ, here added also TNF, since these three are major cytokines players during insulites [3]. This may indicate that TNF may induce other deleterious pathways that would lead to a pro-apoptotic effect of IL-6 in these cells.
It has recently been shown serum from exercise human or mouse prevent the death of human and rat β-cells exposed to tapsigargin or CPA (inhibitors of the SERCA2b pump), showing an effect of myocins in the ER stress pathways [25]. Our data shows that the pre-treatment of INS-1E cells with IL-6 alone decreases IL-1β and IFN-γ-induced expression of p-eIF2-α and p-IRE1, two important UPR markers, which are induced during ER stress provoked in β-cells exposed to cytokines [14, 16, 35].
Although pre-treatment with IL-6 decrease partially UPR response it still increases expression of Caspase-3 and iNOS expression, indicating increase of β-cells death in this condition. One possible hypothesis is that IL-6 could be decreasing the β-cells ability to activate UPR pathways, losing the ability to improve ER homeostasis, precipitating β-cells demise. It is known that although the activation of UPR in response to IL-1β and IFN-γ contributes to the death of β-cells [3, 9, 13, 14, 16], these pathways are primarily cellular responses to recover function and maintain cell viability [12, 13]. Thus, ER stress is characterized by a cellular response to the accumulation of poorly folded proteins within this organelle, however, it can lead to cell death if fails to restore homeostasis in the ER [12]. Of note, exposure of β-cells to cytokines induces a deficient UPR, which leads to activation of cell death pathways in this cells [7, 11–14, 16, 35, 36].
To solve the problem of poorly folded proteins, one of UPR mechanisms is to increase the expression of chaperones, that bind to unfolded proteins preventing them from aggregating [33, 37, 38]. The use of chemical chaperones to restore ER homeostasis have being reported, with beneficial results in protecting β-cells from ER-stress induced conditions [14, 32, 39]. Administration of TUDCA, a chemical chaperone, has been shown to reduce apoptosis of β-cells in a TD1 mice model and restore ER homeostasis [24], in addition, this protection has also been shown in human β-cells against cytokine-induced apoptosis [14].
Thus, we used TUDCA to assess whether an increase in the folding capacity of poorly folded proteins in the ER could improve the viability of INS-1E cells exposed to IL-6 and IL-1β + IFN-γ. The treatment with TUDCA did not prevent β-cells death under these conditions, indicating that perhaps other pathways may be involved in this process. Furthermore, there was an increase in Bax/Bcl2 mRNA ratio under these conditions, corroborating with lack of cell death prevention. We also observed that under control conditions, administration of TUDCA decrease expression of BiP (Fig. 4A), which could be due to TUDCA working as a chemical chaperone, decreasing the need for BiP expression. However, since BiP is an important chaperone for maintaining ER homeostasis and its decrease can lead to ER stress activation [13, 14], this could contribute for the deleterious effects when these cells are exposed to cytokines in combination with IL-6, since this treatment also lead to impaired ER stress responses, preventing activation of p-eIF2α.
Taking together, this data may indicate that the positive effects by IL-6 on β-cells, observed by other authors, may involve negative modulation of the ER stress, which, together with the activation of additional pathways, induced by other regulators, such as other myocines present in the serum of trained animals, may prevent β-cells death.
## Conclusions
Our data indicate that IL-6 pre-treatment sensitizes INS-1E cells death induced by pro-inflammatory cytokines IL-1β and IFN-γ. Increased iNOS expression in this condition, indicates involvement of NF-κB activation. This pre-treatment, however, prevented cytokine-induced important UPR pathways, namely p-eIF2-α, which may negatively interfere in ER folding capacity and cell viability. Use of the chemical chaperone TUDCA showed that the deleterious effect of pre-treatment with IL-6 may not seem to be related only to a worsening of the protein folding capacity in the ER, but to other mechanisms not yet demonstrated in the literature.
## Cell culture
INS-1E cell line, an efficient model to study β-cells, because of their similarity to primary mouse β-cells in both gene expression and insulin secretion in the glucose response [40, 41], was used in this work. This rat insulinoma cells, kindly provided by Prof. Dr. Claes B. Wolheim and Prof. Dr. Pierre Maechler (University of Geneva, Switzerland), was grown in RPMI 1640 culture medium (Gibco/Invitrogen, Carlsbad, CA, USA) supplemented with $5\%$ fetal bovine serum (FBS), 10 mM HEPES, 100U/mL penicillin, 100 µg/mL streptomycin, 1 mM sodium pyruvate and 50 µM 2-mercaptoethanol. The cultures of these cells were kept in an incubator (Autoflow IR Water-Jacketed CO2 Incubator, NuAire) at 37ºC, in a humidified atmosphere at $5\%$ CO2.
## Cell treatment
The cells were plated (100.000 cells/ condition in 24 wells plate) and cultured for 48 h before any treatment, to guarantee their adherence to the plaque and reduce the effects of stress due to trypsinization. After 48 h, cells were exposed to IL-6 at a concentration of 100 ng/mL (Life Technologies, Grand Island, NY, USA) for 24 h and then exposed to cytokine mix of IL-1β (Promega) at a concentration of 10U/mL and IFN-γ (Promega) at a concentration of 14U/mL, for additional 24 h. This additional exposure was performed in the presence or absence of IL-6 and/or TUDCA (Calbiochem), at a concentration of 300 µM. Unexposed cells were used as a control.
## Western blot
Total protein extracts were fractionated on sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS-PAGE) gel at concentrations of 8 or $14\%$. The proteins were transferred by electrophoresis to nitrocellulose membranes and the detection of specific bands was done using specific primary antibodies for the iNOS protein (#IO117), Caspase-3 (#9662, Cell Signaling), p-eIF-2α (#9721, Cell Signaling), p-IRE1 (#MABC742, Millipore), and as loading control α-Tubulin (#9026, Sigma-Aldrich) and GAPDH (#25,778, Santa Cruz Biotechnology). The membranes were incubated with secondary antibodies (horseradish peroxidase-labeled anti-IgG) anti-mouse IgG (#170–5046, Bio-Rad) or anti-rabbit IgG (#170–5047, Bio-Rad). The chemiluminescence (Ameersham ECL Plus Western Blotting Detection Reagents (GE Healthcare Life Sciences) and the detection of specific bands were made using the image documenter ImageQuant™ LAS 4000 (GE Healthcare Life Sciences). Quantification was performed by densitometry using the ImageQuant™ TL 8.1 (GE Healthcare) and Image Lab 6.1 (Bio-Rad) program and the values were normalized by the internal control densitometry values (α-Tubulin and GAPDH).
## Two-step RT-qPCR
Total RNA was isolated with TRIzol™ Reagent according to the manufacturer’s protocol. Two μg of DNase-treated total RNA (A$\frac{260}{280}$ ≥ 1,8), was used for cDNA synthesis, performed with SuperScript™ IV according to the manufacturer’s protocol. Quantitative PCR was performed in triplicates with 10 ng of cDNA and 300 nM of specific primers for the reference gene rat (Rn)18 s (F: 5’-TTCCCAGTAAGTGCGGGTCAT-3’ and R: 5’-AGTCAAGTTCGACCGTCTTCTCA-3’), CHOP (F: 5’-CCACACCTGAAAGCAGAAACC-3’ and R: 5’- GCTAGGGATGCAGGGTCAAG-3’), BiP (F: 5’-GCTAGGGATGCAGGGTCAAG-3’ and R: 5’- AAGGGTCATTCCAAGTGCGT-3’), Bax (F: 5’-AGCTGCAGAGGATGATTGCT-3’ and R: 5’-AGCCACCCTGGTCTTGGAT-3’) and Bcl2 (F: 5’- GGCCTTCTTTGAGTTCGGTG-3’ and R: 5’- ATATAGTTCCACAAAGGCATCCCAG) with PowerUp™ SYBR™ Green according to the manufacturer’s protocol in the Rotor-Gene Q. Data was analyzed with the 2-ΔΔCT method, as described previously [42].
## Statistical analysis
The results are presented as means ± SEM of the indicated number of independent experiments and were analyzed statistically, using GraphPad Prism 7 program (La Jolla, CA, USA), by ANOVA followed by Sidak’s correction, as indicated. A < 0.05 p value was considered statistically significant.
## Supplementary Information
Additional file 1. Additional file 2.
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|
---
title: A Meta-Analysis Study to Infer Voltage-Gated K+ Channels Prognostic Value in
Different Cancer Types
authors:
- Beatrice Angi
- Silvia Muccioli
- Ildikò Szabò
- Luigi Leanza
journal: Antioxidants
year: 2023
pmcid: PMC10045123
doi: 10.3390/antiox12030573
license: CC BY 4.0
---
# A Meta-Analysis Study to Infer Voltage-Gated K+ Channels Prognostic Value in Different Cancer Types
## Abstract
Potassium channels are often highly expressed in cancer cells with respect to healthy ones, as they provide proliferative advantages through modulating membrane potential, calcium homeostasis, and various signaling pathways. Among potassium channels, Shaker type voltage-gated Kv channels are emerging as promising pharmacological targets in oncology. Here, we queried publicly available cancer patient databases to highlight if a correlation exists between Kv channel expression and survival rate in five different cancer types. By multiple gene comparison analysis, we found a predominant expression of KCNA2, KCNA3, and KCNA5 with respect to the other KCNA genes in skin cutaneous melanoma (SKCM), uterine corpus endometrial carcinoma (UCEC), stomach adenocarcinoma (STAD), lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC). This analysis highlighted a prognostic role of KCNA3 and KCNA5 in SKCM, LUAD, LUSC, and STAD, respectively. Interestingly, KCNA3 was associated with a positive prognosis in SKCM and LUAD but not in LUSC. Results obtained by the analysis of KCNA3-related differentially expressed genes (DEGs); tumor immune cell infiltration highlighted differences that may account for such differential prognosis. A meta-analysis study was conducted to investigate the role of KCNA channels in cancer using cancer patients’ datasets. Our study underlines a promising correlation between Kv channel expression in tumor cells, in infiltrating immune cells, and survival rate.
## 1. Introduction
Potassium channels that allow the selective flux of K+ ions through biological membranes down their electrochemical gradient comprise more than 70 proteins that display diverse regulation, functions, and tissue distribution. Among them, the eight Kv1 Shaker subfamily members (Kv1.1-Kv1.8 encoded by KCNA1, KCNA2, KCNA3, etc (KCNA10 for Kv1.8)) of the voltage-gated potassium channels (Kv channels) https://www.guidetopharmacology.org/GRAC/FamilyIntroductionForward?familyId=81 (accessed on 18 January 2023) [1] have been extensively studied during the past decades for the important roles they exert in the regulation of cell cycle progression, apoptosis, and migration in both healthy and pathological cells. Several studies found a correlation between the activity and expression of various potassium channels and the progression of different kinds of cancers [recently reviewed in [2]. However, to our knowledge, no systematic study using publicly available databases obtained from patient samples examined whether the expression of the Shaker-type potassium channels was altered and whether it correlated with prolonged or decreased survival rate. Given the availability of specific pharmacological modulators of the *Shaker potassium* channels [1] and considerable promising in vitro and in vivo preclinical data, such information might be useful in understanding whether pharmacological targeting of these ion channels may be of benefit.
Previous data pointed out that Kv1.1 was expressed in the breast cancer cell line MCF-7, and its blockade by Dendrotoxin (DTX) (10 nM) could reduce proliferation by $30\%$ [3]. A high expression of the channel was observed in cervical cancer patients, correlating with poor prognosis and Kv1.1 silencing, which decreased the proliferation of HeLa cells [4]. DTX suppressed lung adenocarcinoma growth in vivo [5] and reduced the proliferation of even chemo-resistant non-small cell lung cancer (NSCLC) cells both in vitro and in vivo [6]. The specific inhibition of Kv1.1 by KAaH2 toxins repressed the proliferation of glioblastoma [7]. Interestingly, aberrant hypermethylation in the KCNA1 promoter region was observed in more than 200 colorectal cancer patients who held biomarker potential [8].
As to Kv1.2, much less information is available since this channel has been studied mainly in the context of pain. Its expression was barely detectable in a panel of gastric cancer cell lines [9]. However, this O2-sensitive channel was found to play a critical role in the hypoxia-induced depolarization of pheochromocytoma PC12 cells [10], but no follow-up studies were reported.
An important role for the ROS-modulated Kv1.3 [11] was instead well documented, both in cancer cells (for reviews see, e.g., [12,13]) and in some of the immune cells constituting the tumour microenvironment (TME) and actively modulating tumour progression [14]. The injection of Margatoxin (MgTx), an inhibitor of Kv1.3 (but also of Kv1.1 and Kv1.2 [15]), directly into the xenograft of the A549 human lung adenocarcinoma cell line at 1 nM concentration, inhibited tumor growth in a nude mice model [16]. Blockade of Kv1.3 by the most specific toxin inhibitor; Shk blunted the activation-induced proliferation of malignant T cells in Sezary syndrome, which express high levels of functional Kv1.3 [17]. An enhanced expression of Kv1.3 has also been observed in resected human pancreatic ductal adenocarcinoma [18] and in primary B cells from chronic lymphocytic leukemia patients [19]. In both cases, the modulation of Kv1.3 significantly decreased the tumor burden. Notably, Shk has recently become available orally as an engineered probiotic [20]. The study underlined its efficacy against autoimmune disease, but it would be worthwhile to explore whether such an administration route of Shk may have beneficial effects in the context of cancer. On the other hand, the modulation of the channel by pharmacological means in the TME immune cells might also be useful. For example, the cajanine derivative LJ101019C was shown to increase Kv1.3 activity and expression, leading to the proliferation and activation of natural killer (NK) cells, which are so important for anti-tumour immunity [21].
Regarding Kv1.4, the KCNA4 methylation pattern increased along with tumor grade progression and the predicted poor survival of glioma patients [22]. KCNA4 methylation was also enhanced in gastric cancer patients [23]. Whether KCNA4 hypermethylation correlates with high expression of the channel and the effects of altered expression/functions in cancer cells still await clarification.
As to Kv1.5, this O2-sensitive channel [24] has been shown to be upregulated in many types of tumors, where it promotes proliferation and metastatic tissues. High expressions of Kv1.5 correlated with leiomyosarcoma proliferation and aggressiveness [25] and were found in gastric and colorectal carcinoma specimens [26,27]. However, the expression of Kv1.5 shows an inversed correlation with malignancy in some gliomas and non-Hodgkin’s lymphomas [13,28]. Silencing Kv1.5 expression significantly inhibited proliferation and induced cell cycle arrest at the G0/G1 phase in osteosarcoma [29] but supported *Ewing sarcoma* cell proliferation [30]. Similarly to Kv1.3, Kv1.5 is also expressed in macrophages and is likely also in the tumor-associated macrophage population [31].
Kv1.6 was found to be expressed in prostate cancer cells [32], although to a lesser extent than Kv1.3. To our knowledge, studies regarding Kv1.7 and Kv1.8 expressions in cancer have not yet been performed.
Altogether, a conclusive general picture regarding the involvement of Shaker-type channels in promoting cell proliferation in cancer cells is still lacking. In addition, it has to be underlined that Kv1.1, Kv1.3, and Kv1.5 are present not only in the plasma membrane but also in mitochondria in several types of cells [33,34,35,36]. When the channel is found in the plasma membrane, usually it is expressed also in the mitochondria [33]. While the plasma-membrane channels modulate proliferation, the mitochondrial ones are linked to apoptosis regulation [37]. We also have to point out that Kv1.3 (and possibly other Shaker channels as well) can apparently also promote proliferation independently of its ion-conducting properties (see, e.g., [38,39]).
In the present study, we explored the publicly available TCGA database in order to systematically investigate the correlation between Shaker-type potassium channels in some types of cancers (with the highest Shaker channel mutational load) and patients’ survival.
## 2.1. cBioPortal
The cBioPortal for Cancer Genomics (http://www.cbioportal.org, accessed on 18 January 2023) is a repository of cancer genomics datasets [40,41]. We investigated genetic alteration frequencies of KCNA genes using the TCGA Pan-Cancer Atlas dataset, collecting data from 32 human cancers (10967 samples in total).
## 2.2. Gene Expression Profiling Interactive Analysis (GEPIA)
GEPIA (gene expression profiling interactive analysis) (http://gepia.cancerpku.cn/, accessed on 18 January 2023) is an interactive web application for gene expression analysis based on 9736 tumors and 8587 normal samples [42]. This platform was also used to analyse the expression of KCNAs in selected tumours and their effects on overall survival by means of the Kaplan–*Meier analysis* tool. Samples were divided between high and low KCNAs expression groups according to the quartile KCNAs mRNA levels to analyse survival rate (group cutoff selected quartile, cutoff-high (%): 75; cutoff-low (%): 25).
## 2.3. Survival Genie
To assess tumour infiltration according to KCNAs expression, Survival Genie software was employed (https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/, accessed on 18 January 2023). Survival *Genie is* an open source that contains 53 datasets of 27 distinct malignancies from 11 different cancer programs relating to adult and pediatric cancers [43].
## 2.4. UALCAN Database Analysis
To determine the clinical value of KCNA3 and KCNA5 expression levels, we used the UALCAN database (http://ualcan.path.uab.edu, accessed on 18 January 2023). UALCAN is an interactive and user-friendly web source that helps in analyzing cancer OMICS data and correlates them with clinicopathological features [43]. UALCAN was employed to evaluate the co-expression between KCNA3 and KCNA5 transcript levels with several clinical signatures or risk factors such as the absence or presence of tumor metastasis, nodal metastasis status, age, sex, weight, tobacco consumption, and H. pylori infections in cancer patients. The cancer stage was stratified between healthy tissues (“Normal”) and tumor stage (Stage 1 to stage 4). Patients’ weight was ranked based on BMI (body mass index): Normal weight (18.5 ≤ BMI ≤ 25), Extreme weight (25 ≤ BMI ≤ 30), Obese (30 ≤ BMI ≤ 40), and Extreme obese (BMI ≥ 40).
## 2.5. LinkedOmics
The LinkedOmics database (http://www.linkedomics.org/login.php, accessed on 18 January 2023) is a web tool that is useful for conducting cancer-associated multi-dimensional analyses deriving data from the TCGA datasets within and across 32 cancer types [44]. The LinkFinder module of LinkedOmics was used to study differentially expressed genes in correlation with KCNA3 and KCNA5 in the TCGA SKCM ($$n = 371$$), LUAD ($$n = 515$$), LUSC ($$n = 501$$), and STAD ($$n = 415$$) Firehorse cohorts perform pathway and network analyses. The results were statistically analyzed using Spearman’s correlation coefficient. GO enrichment analysis was used to perform GO analyses for the biological processes (BP). Graphs to analyze the correlation between gene expressions were also retrieved employing LinkedOmics.
## 2.6. Tumor Immune Estimation Resource (TIMER)
TIMER (tumor immune estimation resource) is an in silico web platform to analyze interactions between gene expression in tumors and infiltrating immune cell-types [45]. This tool collects data from 32 different tumor-types retrieved from the TCGA dataset, gathering gene expression profiles measured with RNA-seq or microarray to evaluate the abundance of the different immune infiltrates within the tumor microenvironment. KCNA3 mRNA levels and their association with infiltrated immune cells (B cells, CD4+T cells, CD8+T cells, Neutrophils, Macrophages, and Dendritic Cells) were assessed in overall SKCM, LUAD, and LUSC.
## 2.7. Statistical Analysis
Statistical analysis was performed using the CbioPortal, GEPIA, UALCAN, LinkedOmics, SurvivalGenie, and TIMER databases. Differences were examined for significance as per the figure legend specifications. Data were normalized as transcripts per kilobase million (TPM) values. Data were shown as the mean ± standard deviation. Statistical analyses were conducted using a t-test. Error bars represent SD. *, **, *** indicated p-value < 0.05, 0.01, 0.001, respectively. Kaplan–Meier analyses were plotted based on Fisher’s exact test (F-test). Values were normalized as TPM. Statistics of the survival analyses were performed using an F-test. The top 50 positively KCNA3 and KCNA5 correlating genes were mapped using the TCGA SKCM, LUAD, LUSC, and STAT dataset on the LinkedOmics database, according to their ranking and based on their Z-score through Spearman’s correlation analysis. The top 1000 KCNA3 and KCAN5 positively co-expressed genes were used for GO analysis obtained through Gene Ontology Enrichment Analysis performed on LinkedOmics, based on their p-values. Two Pearson correlation analyses between KCNA3 transcript levels and immune activation markers were retrieved from LinkedOmics using the SKCM, LUAD, and LUSC datasets. Data were plotted as scatter plots based on the Spearmans’ correlation coefficient (* $p \leq 0.05$; ** $p \leq 0.01$; *** $p \leq 0.001$). On the other hand, a correlation between the KCNA3 level of expression and immune infiltration of cell types was obtained overall by SKCM, LUAD, and LUSC datasets.
## 3.1. KCNAs Alterations and Expression in Human Cancers
The abnormal expression of potassium channels has been documented in many tumours and can be caused by the presence of mutations at the genomic level [46]. We evaluated the overall genetic alterations in all KCNA genes (KCNA1, KCNA2, KCNA3, KCNA4, KCNA5, KCNA6, KCNA7, KCNA10) using the TCGA Pan-Cancer Atlas dataset, collecting data from 32 human cancers (10,953 patients in total). Using the cBioportal Database, genomic alterations were classified into five categories per mutation (truncating mutations, in-frame mutations, or missense mutations), deep deletions (homozygous deletions for non-aneuploidy cases), gene amplification, structural variants, and multiple alterations [40]. The Cancer type summary representation revealed the distribution of KCNAs genomic alterations in the TCGA PanCancer cohorts (Figure 1A). Mutations in KCNA genes were present in $12\%$ of queried patients. Results showed that the five cancer types with the highest alteration frequencies were skin cutaneous melanoma (SKCM), uterine corpus endometrial carcinoma (UCEC), stomach adenocarcinoma (STAD), lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC), in which the overall mutation frequency was ranging from $25.01\%$ for SKCM to $19.51\%$ for LUSC. In particular, most of the genetic alterations in KCNA genes were determined through the presence of truncating mutations, in-frame mutations, or missense mutations, whereas amplifications, multiple alterations, or deep deletions were much less frequent. From the analysis of the single mutations on all KCNA genes, it was not possible to reveal any correlation between the presence of a certain mutation and the incidence of a specific cancer type. Likewise, these high-frequency mutations are not expected to change channel functions based on our current knowledge regarding the structure–function relationship of Kv channels.
Given this background, we explored the expression profile of KCNAs in five tumour types that showed higher KCNA mutation rates using the publicly available GEPIA database (gene expression profiling interactive analysis) [42]. The multiple gene comparison analysis showed that SKCM, UCEC, STAD, LUAD, and LUSC were overall characterized by a predominant expression of KCNA2, KCNA3, and KCNA5 with respect to the other KCNA genes (Figure 1B). Interestingly, KCNA3 is the most abundantly expressed KCNA gene in SKCM, STAD, LUSC, and LUAD.
With KCNA2, KCNA3, and KCNA5 being the most abundant transcripts of the *Shaker* gene family in SKCM, UCEC, STAD, LUSC, and LUAD, we compared their expression levels in both tumour and normal samples. The KCNA2 mRNA level does not significantly differ in controls compared to tumoral samples in any of the considered cancer types (Figure S1A). On the contrary, KCNA3 mRNA levels were significantly reduced in LUSC samples with respect to normal controls. No significant difference in KCNA3 expression can be observed instead in UCEC, STAD, LUAD, and SKCM (Figure S1B). As regards the KCNA5 transcript, UCEC, LUAD, and LUSC tumours displayed a statistically significant decrease in the expression of this gene with respect to normal controls, while no differences were present for SKCM and STAD (Figure S1C).
Overall, these data highlighted SKCM, UCEC, STAD, LUSC, and LUAD to be the five cancers with the highest KCNAs mutation frequency and revealed KCNA2, KCNA3, and KCNA5 to be the most expressed KCNA family genes in these tumours.
## 3.2. KCNA3 and KCNA5 Expression Impacts on Patients’ Survival
To explore the prognostic significance of KCNA2, KCNA3, and KCNA5 expression in cancer patients, we took advantage of the Kaplan–*Meier analysis* by sorting samples for high and low KCNAs expression according to the quartile KCNAs mRNA level. This analysis revealed a prognostic value for KCNA3 in SKCM, LUAD, and LUSC (Figure 2B) and of KCNA5 in STAD (Figure 2C). Indeed, high KCNA3 expression correlated with increased overall survival in SKCM patients (long-rank $$p \leq 6.3$$ × 10−6 and in LUAD patients (long-rank $$p \leq 0.0026$$) (Figure 2F,I). On the contrary, a high KCNA3 mRNA level was associated with decreased survival in LUSC patients (long-rank $$p \leq 0.015$$) (Figure 2J). It is worth mentioning that LUSC was the only tumour analysed in which the KCNA3 transcript significantly differed between the tumour and normal samples (Figure S1B). In STAD and UCEC patients, KCNA3 expression showed no clear correlation with overall survival (Figure 2G,H). High KCNA5 expression correlates with decreased survival rates in STAD patients (long-rank $$p \leq 0.023$$) (Figure 2M), while it has no association with survival in SKCM, UCEC, LUAD, and LUSC cancers (Figure 2K,L,N,O). Contrary to KCNA3 and KCNA5, KCNA2 has no prognostic value for any of the considered cancers (Figure 2A–E). Taken together, these data show the prognostic role of KCNA3 and KCNA5 in SKCM, LUAD, LUSC, and STAD, respectively.
However, the level of KCNAs transcripts in the different tumours and the difference in KCNAs expression between normal and tumour tissues do not provide an explanation for the effect that these genes play on survival. This indicates that other factors, rather than gene expression, need to be considered.
## 3.3. Clinical Features and Prognostic Value of KCNA3 and KCNA5 in Cancer
To better understand the prognostic function of KCNAs channels that are significantly related to survival in the tumors considered in Figure 2 (SKCM, LUAD, and LUSC for KCNA3 and STAD for KCNA5, respectively), we decided to investigate the relationship between channel expression and the pathological-clinical features of malignancies. To this end, we determined whether the expression of KCNA3 and KCNA5 correlated with tumor stage progression, age, sex, and some specific cancer risk factors (Figure 3A–P).
Considering KCNA3, it is interesting to note that its expression tends to significantly decrease with tumor stage progression compared to normal tissues in both lung tumor types which it associates with patient prognosis (Figure 3E,I). In these cases, the KCNA3 mRNA level is three-fold lower at LUAD stage 4 and over 16-fold lower at LUSC stage 4 compared to the channel’s expression in healthy tissues (“Normal”).
It is well known that the incidence of all types of cancer steadily increases with advancing age (National Cancer Institute). Indeed, aging is considered a generic risk factor for all types of cancers [47]. Noticeably, KCNA3 expression displays an increase with advancing age both in LUAD and LUSC (Figure 3F,J). The same is not true for SKCM, where there is no clear correlation with age, probably since the channel’s expression levels in melanoma are significantly lower than those in lung cancer in terms of transcripts per million (tpm), so differences in expression may not be appreciable.
KCNA3 expression also does not correlate to sex, except for LUAD, in which it is more expressed in females (Figure 3G). Numerous pieces of evidence underline the crucial role of obesity in tumor development and progression. Recently, multiple sources have demonstrated a close association between body weight gain and melanoma incidence [48]. Interestingly, the expression of KCNA3 shows a growing trend, although not significantly, correlating with the rise in body mass index (BMI) (Figure 3D).
Nevertheless, smoking represents the main risk factor for the onset of lung cancer [49,50]. Still, no relevant correlation between KCNA3 expression and smoking habits has been reported (Figure 3H,L).
As for KCNA5, the expression of the ion channel in STAD patients drastically and significantly decreases in the different tumor stages compared to healthy tissues (Figure 3M). However, no correlations were found between KCNA5 expression levels and other risk factors, including H. pylory infection (Figure 3P): one of the main risk factors for determining the onset of gastric tumors [51].
## 3.4. Expression of Known Interactors of Plasma-Membrane-Located Kv1.3 Do Not Correlate with KNCA3 Expression in Cancer
Next, since Kv1.3 is the channel mostly affecting patients’ survival in the considered malignancies, we investigated the correlation between KCNA3 expression and its known interactors. Indeed, Kv1.3 has been shown to interact with different proteins that are involved in signaling pathways that are linked to proliferation and migration. Therefore, we checked whether the expression level of KCNA3 correlated with that of its interactors to eventually associate the co-expression level with patients’ survival. The tested interactors are β1-integrin encoded by ITGB1 [52], cortactin (CTTN) (an SH3 domain-containing F-actin binding protein) [53], the PDZ family proteins DLG4 and DLG1 (also called PSD95 and SAP97, respectively) [54,55], the regulatory protein KCNE4 [56] as well as caveolin (CAV1) [57], and Sec24A from COPII [58]. As shown in Table 1, although a significant correlation between the expression of KCNA3 and of some of the interactors could be observed in all three types of cancers, the only protein whose expression negatively correlated with KCNA3 in SKCM and LUAD but not in LUSC, was cortactin. The knockdown of cortactin was shown to decrease the actin-based immobilization of Kv1.3 [53]. Interestingly, in melanoma patients, high levels of cortactin expression are correlated with poor disease-specific survival [59]; this is possibly because cortactin phosphorylation is a key step during invadopodia maturation and migration. Whether and how Kv1.3 expression regulates CTNN expression is unknown.
## 3.5. Identification and Analysis of the KCNA3 Differentially Expressed Genes (DEGs) in Cancer
Intrigued by the dual role played by KCNA3 in tumors, which is associated with positive prognosis in SKCM (Figure 2F) and LUAD (Figure 2I) but not in LUSC (Figure 2J), we sought to identify KCNA3 differentially expressed genes (DEGs) to clarify the functions with which it is involved (Figure 4A,C,E). To this end, genes positively correlated with KCNA3 in SKCM, LUAD, and LUSC were identified from their respective TCGA datasets by classifying Z-scores and mapping them using the LinkedOmics database. Interestingly, several of the DEGs were common to at least two of the TCGA-tumor datasets taken into consideration. Furthermore, most of them were linked to immune activation mechanisms that take an active part in the fight against carcinogenesis. For example, IKZF1 [60], SLAMF1 [61,62], ITGAL [63,64], C16orf54 [65], and CYTIP [66] are among the top 50 genes that are positively related to KCNA3 and are present in all three types of tumors (Figure S2). *These* genes have all been reported to play a role in the regulation and/or recruitment of immune cells in tumors.
By classifying the top 1000 positively KCNA3 co-expressed genes and listing them by gene ontology (GO) categories, we confirmed that KCNA3-positively related genes were involved in immune processes (Figure 4B,D,F). Indeed, some categories of biological processes (BPs) such as “T cell activation”, “B cell activation”, and “Adaptive immune response” were consistently found in all three datasets, suggesting a correlation between KCNA3 expression and immune system regulation in cancer. Additionally, this role seems to be peculiar to KCNA3 since KCNA5-related DEGs categories are not involved in these kinds of processes, as reported in Figure S3A,B.
## 3.6. KCNA3 Expression Correlates with Increased Immune Infiltration
To evaluate the possible involvement of KCNA3 signaling in the regulation of the immune system, we decided to analyze the degree of immune cell infiltration in SKCM, LUAD, and LUSC tumors as a function of the ion channel expression (Figure 5A). In particular, we first employed the TIMER dataset to correlate KCNA3 expression with the infiltration rate of different cell types when collected inside the TCGA cohorts, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. The analysis showed that the degree of infiltration for the immune subtypes always positively and significantly correlated with the level of KCNA3 (Figure 5A). Tumor “purity” refers to a key element affecting the genomic analysis of immune infiltrates: noticeably, all the screened conditions showed negative correlations with such parameters.
Nevertheless, as observed in Figure 2, the prognostic role of KCNA3 varied between the three examined tumors and was associated with a better prognosis in SKCM and LUAD only but not in LUSC. Considering the correlation with immune infiltrates, we hypothesized that KCNA3 could exert a distinct immune recruitment function in the different tissues where it was expressed, thus representing an advantage or not for the tumor progression. To verify this hypothesis, we took advantage of the SurvivalGenie tool to analyse the positive or negative correlations between the immune cell subtypes and their active/resting forms and the expression of KCNA3 (Figure 5B). Interestingly, in SKCM, a high level of KCNA3 mRNA positively correlated with the elevated infiltration of CD8+ T cells, the immune cell type most associated with a greater immune response against the tumor and considered a positive biomarker of prognosis in melanoma (Figure 5B) [67]. Conversely, increased KCNA3 transcript levels inversely correlate with M2 macrophage infiltration: a known marker of immune suppression (Figure 5B). Additionally, in LUAD, the expression of KCNA3 seemed to be positively associated with the infiltration of immune subtypes that promote the anti-tumor response (Monocytes, CD4+ T cells, Mast cells, Dendritic cells) and are inversely related to M2 macrophages (Figure 5C).
Interestingly, in LUSC, where KCNA3 correlates with a poor prognosis, the immune cell infiltration profile differs from the previous two cases (Figure 5D). For instance, high levels of KCNA3 correlate with an increase in the infiltration of Tregs (Regulatory T cells): one of the main cell types linked to immune suppression. Moreover, elevated KCNA3 levels were inversely correlated with the presence of dendritic cells (both active and resting), natural killers (NKs), CD4+ T cells, and mast cells (Figure 5D), which were all able to favor recognition, antigen presentation, and killing of tumor cells. These results suggest that the different composition of the KCNA3-related immune microenvironment in LUSC may favor mechanisms of immune evasion that could partially account for the different prognostic values of the gene in this tumor type.
## 4. Discussion
In recent years, ion channels have been studied intensively in the context of cancer since several pieces of evidence have appointed them as oncological targets [68,69]. In this paper, for the first time, we aimed to recapitulate all the available information collected in the publicly available databases concerning voltage-gated potassium channels and different types of cancers. In detail, our meta-analysis highlighted a possible correlation between KCNA potassium channels’ expression and cancer patients’ survival. We initially investigated KCNA gene alterations in several tumor types, demonstrating that SKCM, UCEC, STAD, LUSC, and LUAD are the five cancers with the highest KCNA mutation frequency. We further revealed that KCNA2, KCNA3, and KCNA5 as the most expressed KCNA family genes in these tumors. In addition, we were able to show a prognostic role for KCNA3 expression in SKCM, LUAD, and LUSC and for KCNA5 in STAD. Conversely, no correlation between KCNA2 expression and patients’ survival has been observed in the analyzed cancer types. Therefore, we focused our observations on identifying a possible relation between KCNA3 and KCNA5 expression and patients’ clinical features and tumor risk factors, such as age, sex, obesity, and smoking. Some previous evidence suggested that KCNA3 plays a regulatory role in the processes of regulating body weight, fat absorption, and insulin sensitivity [70,71,72,73]. Although the reported data were controversial, it would be worth investigating these relationships in the context of melanoma, considering that KCNA3 associates with a better prognosis in this tumor type (Figure 2F). Recent evidence demonstrates that tobacco consumption strongly affects gene expression in smokers compared to non-smokers. Interestingly, among the genes whose expression was found to be altered, there was KCNA3 [74]. For this reason, a better assessment of the KCNA3 role in lung cancer should be carried out to investigate the difference in the positive prognostic role played by this ion channel in LUAD (Figure 2I) but not in LUSC (Figure 2J).
Nowadays, it is worldwide accepted that cancer development is supported by the tumor microenvironment (TME) [75]. In particular, TME cells (e.g., immune cells, CAFs, mesenchymal cells) interact with primary cancer cells and promote their ability to become invasive. Our data clearly show that a possible explanation of the differential prognostic role of KCNA3 could be related to its capability to contribute to the recruitment of immune cells in the TME. Indeed, we observed that in the tumor where KCNA3 exerts a positive role in increasing the survival rate when it is highly expressed (SKCM and LUAD), KCNA3 mRNA expression is related to an elevated infiltration of anti-tumor immune cell sub-populations (e.g., CD8+ and CD4+ T cells, monocytes, dendritic cells), while the presence in the tumor microenvironment of M2 pro-tumorigenic macrophages was reduced. Conversely, in LUSC, where high KCNA3 expression is associated with poor prognosis, channel expression is correlated to higher pro-immune suppressive Tregs cell infiltration and a reduced presence of the anti-tumor immune cell sub-populations.
On the capability of potassium ions to modulate immune cell infiltration, Eil and colleagues have recently demonstrated that the increased extracellular potassium concentration due to the release from necrotic cancer cells plays a role in suppressing T cell functions within the tumor [76]. Do other immune cells have a similar checkpoint that modulates their function? Might cancer cells upregulate their levels of K+ channels to extrude potassium and survive in the potassium-rich extracellular fluid? These are important questions that need to be answered. On this line, according to our data, it would be important to understand how Kv1.3 could be modulated both in its expression and in its function. A possible signaling pathway that can act both on KCNA expression as well as regulating their activity could be linked to a burst in ROS [77]. The incomplete transfer of electrons to a specific target, along with the malfunction of antioxidant systems, could result in ROS production, which could lead to oxidative damage: a common phenomenon in most immune disorders. ROS are highly reactive molecules that can interact with various cellular constituents, such as DNA, lipids, and proteins, and therefore trigger cellular damage. In addition, the activation of mild oxidative stress may function as a second messenger in a signaling cascade promoted by alterations in the ion channel activity in response to hormones and neurotransmitters. Indeed, low oxidative stress is important for correct cell function [78]. Finally, it has also been demonstrated that openings or closures of mitochondria-located ion channels frequently lead to the modification of organelle functions that promote ROS release, for example, as observed with the inhibition of mitochondria-located Kv1.3 [35,79]. As for the immune system, hypoxia can impair the voltage-gated potassium channel (also Kv1.3) activity and expression, perhaps explaining the complications in proliferating of normally highly Kv1.3 expressing T-cells in hypoxic TME [80,81]. Similar to T-cells, the inhibition of Kv1.3 in macrophages leads to membrane depolarization and, in turn, the reduction in chemotactic migration [82] alongside the inhibition of stimulated proliferation and of the inducible nitric oxide synthase expression [83]. In addition, ROS are important mediators of pro-inflammatory signaling pathways, which modulate the expression of important transcription factors such as NF-kB and AP-1, that can support the up-regulation of pro-inflammatory chemokines/cytokines and adhesion molecules, which are also able to activate endothelial cells. In turn, endothelial cells can attract monocytes, which can then differentiate into macrophages [84]. On the other hand, ROS are also produced by immune cells to kill pathogens, but during long-lasting inflammation, this ROS-induced oxidative stress can damage endothelial cells [85]. In a scenario where the modulation of ROS could be beneficial to regulate immune responses to fighting cancer cells, a possible method of regulating ROS levels and antioxidant response is physical exercise, which can promote the release of stress hormones such as catecholamines and cortisol, resulting in the production of various cytokines, leading to either immune activation or immune suppression [85].
## 5. Conclusions
In conclusion, for the first time, we analyzed in detail the possible correlation of KCNA gene expression with patients’ survival in several tumors. Moreover, we demonstrated that a possible correlation in the case of Kv1.3 and Kv1.5 expression and some cancers’ prognosis exists. Finally, we observed a possible link between the prognostic role of Kv1.3 expression and its ability to recruit immune cells. *In* general, it is important to be aware of the limitation that by analyzing data obtained by datasets, we cannot discriminate between the KCNA3 expression either in tumors or in the immune cells. Therefore, further work is necessary to dissect and clarify whether the observed KCNA3 expression affects prognosis by relating to cancer cell behavior or to the increased presence of Kv1.3 expressing immune infiltrates. In addition, the elucidation of the possible role of the redox state in tuning on one side ion channels expression and activity and on the other side immune cells proliferation and activation could point to an interesting molecular pathway that can be studied in cancer biology.
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|
---
title: 'RU-Net: skull stripping in rat brain MR images after ischemic stroke with
rat U-Net'
authors:
- Herng-Hua Chang
- Shin-Joe Yeh
- Ming-Chang Chiang
- Sung-Tsang Hsieh
journal: BMC Medical Imaging
year: 2023
pmcid: PMC10045128
doi: 10.1186/s12880-023-00994-8
license: CC BY 4.0
---
# RU-Net: skull stripping in rat brain MR images after ischemic stroke with rat U-Net
## Abstract
### Background
Experimental ischemic stroke models play a fundamental role in interpreting the mechanism of cerebral ischemia and appraising the development of pathological extent. An accurate and automatic skull stripping tool for rat brain image volumes with magnetic resonance imaging (MRI) are crucial in experimental stroke analysis. Due to the deficiency of reliable rat brain segmentation methods and motivated by the demand for preclinical studies, this paper develops a new skull stripping algorithm to extract the rat brain region in MR images after stroke, which is named Rat U-Net (RU-Net).
### Methods
Based on a U-shape like deep learning architecture, the proposed framework integrates batch normalization with the residual network to achieve efficient end-to-end segmentation. A pooling index transmission mechanism between the encoder and decoder is exploited to reinforce the spatial correlation. Two different modalities of diffusion-weighted imaging (DWI) and T2-weighted MRI (T2WI) corresponding to two in-house datasets with each consisting of 55 subjects were employed to evaluate the performance of the proposed RU-Net.
### Results
Extensive experiments indicated great segmentation accuracy across diversified rat brain MR images. It was suggested that our rat skull stripping network outperformed several state-of-the-art methods and achieved the highest average Dice scores of $98.04\%$ ($p \leq 0.001$) and $97.67\%$ ($p \leq 0.001$) in the DWI and T2WI image datasets, respectively.
### Conclusion
The proposed RU-*Net is* believed to be potential for advancing preclinical stroke investigation and providing an efficient tool for pathological rat brain image extraction, where accurate segmentation of the rat brain region is fundamental.
## Background
Stroke is the leading cause of serious long-term disability and the major cause of mortality worldwide [1]. Of all strokes, the majority are the ischemic type resulting from the occlusion of a cerebral artery by a blood clot. Cerebral ischemia can induce many injuries including energy failure, intracellular calcium overload, and cell death, which eventually lead to the loss of neurological functions and permanent disabilities [2]. Experimental ischemic stroke models are crucial to understand the mechanism of cerebral ischemia and to evaluate the development of the pathological extent. Among the models in a variety of species, rodent stroke models have been broadly employed in experimental ischemia studies for decades [3].
In particular, the transient middle cerebral artery occlusion (tMCAO) model in rats is one of the closest simulations of human ischemic strokes, which has been frequently utilized to induce infarction at the basal ganglion and cerebral cortex [4, 5]. To noninvasively disclose stroke regions and the associated tissue, one popular manner is through the use of magnetic resonance imaging (MRI), where diffusion-weighted imaging (DWI) and T2-weighted MRI (T2WI) exhibits complementary visualization of ischemic lesions [4]. A fundamental task of the preclinical MRI studies associated with tMCAO models is the skull stripping in rat brain MR images. Skull stripping, also known as brain extraction or intracranial segmentation, is a process to remove nonbrain tissues and separate brain regions in MR images. The extracted rat brain is critical to succeeding processes such as hemisphere segmentation, lesion segmentation, tissue classification, and volume measurement in preclinical stroke investigation [6–8].
Unfortunately, computer-aided tools for rat brain extraction have been lacking. Manual delineation of the rat brain region on numerous MR images has been widely adopted in many preclinical studies [3, 8, 9], which is a time-consuming and laborious work with low reproducibility [10, 11]. In consequence, an accurate and reliable image segmentation tool for the brain extraction in MR image volumes is essential in experimental stroke rat analysis. Automatic skull stripping in rat brain MR images is quite challenging as typical magnetic fields are higher (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ge 7\text{T}$$\end{document} commonly) with a larger degree of radiofrequency inhomogeneity, which results in susceptibility artefacts and field biases [12]. Nevertheless, several attempts have been made to address the brain extraction problems in rat MR image volumes. For example, Li et al. [ 13] presented an automatic rat brain extraction method called the rat brain deformation (RBD) model, which made use of the information on the brain geometry and the T2WI image characteristics of the rat brain.
A fully automatic skull stripping method in an atlas-based manner was proposed for rat MRI scans [14], which was founded on an iterative, continuous joint registration algorithm. Lancelot et al. [ 15] developed a multi-atlas based method for automated anatomical rat brain MRI segmentation in such a way that MR images are registered to a common space, where a rat brain template and a maximum probability atlas were constructed. Delora et al. [ 16] presented a template-based brain extraction scheme called “SkullStrip” to segment the whole mouse brain in T1-weighted and T2-weighted MR images. Huang et al. [ 17] built a statistic template of the rodent brain, which was adopted to predict the location of the brain in MR images. Alternatively, Zhang et al. [ 18] combined deformable models and hierarchical shape priors, which constrain the intermediate result for rodent brain structure segmentation. Oguz et al. [ 19] introduced a rapid automatic tissue segmentation (RATS) algorithm based on grayscale morphology with initial surface extraction followed by graph search. Liu et al. [ 10] described an automatic brain extraction method, entitled SHape descriptor selected Extremal Regions after Morphologically filtering (SHERM), which extracted the brain tissue in both rat and mouse MR images.
With recent advances in artificial neural networks, many researchers have demonstrated their effectiveness in human brain image segmentation [20–22]. However, few studies have applied this strategy for rodent brain extraction comparing to human brain investigation [23]. The major difference between the human and rodent brain extraction results from the inherent brain dissimilarity in many aspects including the brain tissue geometry, brain-scalp distance ratio, tissue contrast around the skull, partial volume effect with respect to image resolution, and more noise due to a stronger magnetic field in rat brain MRI. One example is the automatic cropping scheme based on the pulse coupled neural network (PCNN) with a slice-by-slice fashion, which was proposed to segment the rat brain in T2WI image volumes [24]. Afterward, Chou et al. [ 25] described an automatic rodent brain extraction method by extending the PCNN algorithm into 3-D, which operated on the entire rodent brain MR image volume. Recently, deep learning-based approaches have shimmered the field of computer vision in that convolutional neural networks (CNNs) have been successfully applied in many image processing tasks, e.g., classification of the ImageNet database [26]. To handle semantic segmentation problems, the fully convolutional network (FCN) [27], which is an end-to-end and pixel-to-pixel network, has shown its outstanding performance over the CNN. In contrast to the CNN models, the FCN framework exploits an upsampling tactic instead of the fully-connected layer to recover the intermediate image back to the original image dimension.
One particular type of FCN architectures, U-Net [28], has been shown valuable in biomedical image segmentation and it has become the foundation of many segmentation methods. For example, an end-to-end learning algorithm for medical image segmentation was proposed [29], which introduced a category attention boosting module into the 3D U-Net segmentation network. A stacked U-Net scheme was applied to computed tomography image reconstruction that generated high-quality images in a short time with a small number of projections [30]. An automatic hemorrhagic stroke lesion segmentation approach in computed tomography scans was described, which is based on a 3D U-Net architecture incorporating the squeeze-and-excitation blocks [31]. For preclinical studies, Hsu et al. [ 32] employed the U-Net to automatically identify the rodent brain boundaries in MR images, which was trained and evaluated using rat and mouse datasets. De Feo et al. [ 33] presented a multi-task U-Net (MU-Net) framework that was designed to accomplish both skull stripping and region segmentation in large mouse brain MRI datasets. In light of the U-Net architecture, the final block of the decoder branch bifurcates into two different output maps corresponding to the two tasks. A unique CNN, called MedicDeepLabv3+ [34], was introduced to simultaneously segment intracranial brains and cerebral hemispheres in rat brain MR image volumes. By incorporating spatial attention layers and additional skip connections into the decoder, the network was able to attain more precise segmentation.
Stimulated by the demand of the preclinical ischemia studies, this paper develops an automatic skull stripping framework in rat brain MR images after stroke based on a deep learning network. The proposed architecture takes advantage of U-Net [28], residual network [35], and batch normalization [36] to perform efficient end-to-end segmentation in rat brain images, which is named Rat U-Net (RU-Net) and publicly available at https://github.com/lvanna/RU-Net. With the same U-shape like structure, two different skull stripping networks are individually trained and validated using two different MRI modalities of DWI and T2WI images. Due to the deficiency of public rat brain MR images after ischemic stroke, two in-house datasets corresponding to DWI and T2WI have been established. Skull stripping in the two MRI modalities using the proposed RU-*Net is* fairly compared with the state-of-the-art methods. The main contributions of the current work are summarized as follows: A new skull stripping system, referred to as RU-Net, specifically designed for handling pathological rat brain MR images after stroke was developed. On the foundation of a U-shape like architecture, a batch normalization associated with residual network strategy was investigated for extracting the rat brain characteristics. A pooling index transmission mechanism between the encoder and decoder was introduced to tackle large intensity variations in ischemic rat brain MR images. Two in-house datasets containing pathological rat brain DWI and T2WI image volumes were established.
The remainder of this paper is organized as follows. In Sect. 2, we describe the acquired datasets followed by the deep learning architecture for effective feature extraction and elaborate the proposed RU-Net for rat skull stripping. Section 3 presents experimental results and performance analyses regarding both modalities of DWI and T2WI image data. Section 4 discusses our investigation pertaining to the segmentation outcome. Finally, we draw the conclusion in Sect. 5.
## Ischemic stroke model
An ischemia-reperfusion model of rats based on the tMCAO with a silicon-coated nylon filament was carried out. Supplied by BioLASCO Taiwan Co., male Sprague-Dawley rats with ages of 7–9 weeks old and body weights of 181–336 g were employed as experimental subjects. Different ischemic durations of 0.5, 0.75, 1, 1.5, 2, and 3 h were performed to develop a wide range of infarction. Before the operation, the rats were kept under standard conditions and supplied with water and food ad lib. Under inhalation anesthesia with isoflurane (induction dosage: $4\%$, maintenance dosage: $2\%$), anterior neck incision at the right paramedian line (5 mm from the midline) was executed to disclose the right carotid artery. After serial ligations of the right common carotid artery (CCA), external carotid artery, and internal carotid artery (ICA), a silicon-coated filament was inserted into the right CCA and deliberately advanced towards the right ICA until a light resistance encountered. The filament sizes were determined in accordance with the body weight of each individual rat. The rats were allowed to regain consciousness after fixation of the filament on ICA followed by closure of the neck wound. Toward the end of the ischemic period, the rats received anesthesia again for removing the filament to accomplish reperfusion. In accordance with the principles of the Basel Declaration, the protocol was approved by the Animal Committee of National Taiwan University College of Medicine.
## Image acquisition
This study was dedicated to the skull stripping of pathological rat brain MR images with cerebral ischemia. Since there is no public image dataset that is appropriate for our investigation, we have established two in-house preclinical stroke rat MRI datasets. Each stroke rat experienced DWI and T2WI examination for unveiling ischemic regions in the brain. All rat MR images were acquired using the 7T MRI machine (Bruker PharmaScan, Ettlingen, Germany) at National Taiwan University, Taipei, Taiwan. The parameters of the DWI sequence were as follows [37]: b-value 1000 s/mm2, repetition time (TR) 4500 ms, echo time (TE) 30 ms, coronal section thickness 1 mm with 15 slices, field of view (FOV) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2.56\times 2.56$$\end{document} cm2, and matrix size \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$128\times 128$$\end{document}. The parameters of T2WI were as follows: 15 contiguous, coronal slices (thickness: 1 mm) acquired with an FOV of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2.56\times 2.56$$\end{document} cm2, matrix size \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$256\times 256$$\end{document}, TR 3000 ms, and TE 50 ms. Altogether, there were 55 rat subjects captured with DWI and T2WI for this study. After the MRI scanning, the rats were sacrificed for in vitro staining experiments. All rats were euthanized by intracardiac infusion of $1\%$ sodium nitrite under inhalation anesthesia of isoflurane at $5\%$ through a vaporizer in a dedicated euthanasia chamber.
## Data preprocessing
*To* generalize the proposed algorithm when handling heterogeneous image data, a least possible preprocessing step was first executed. Specifically, the standard score (or z-score) normalization [38] was exploited to reduce the intensity variation while maintaining the detailed structures of the input rat brain MR images. The standard score is the signed fractional number of standard deviations that is frequently utilized to standardize scores on the same scale by dividing a score’s deviation in a dataset. Mathematically, the input rat brain MR image scan \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$I$$\end{document} is normalized with1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\widehat{I}(x,y)=\frac{I(x,y)-{\mu }_{I}}{{\sigma }_{I}}$$\end{document} where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mu }_{I}$$\end{document} is the mean intensity of the images in the dataset, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\sigma }_{I}$$\end{document} is the corresponding standard deviation in the image dataset, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\widehat{I}$$\end{document} is the standardized rat brain MR image.
An essential role to deep learning-based investigation is the use of tremendous image data in the model training phase. For biological image processing applications as in our scenario, the number and scope of images are substantially limited comparing to many famous image databases such as ImageNet. In consequence, data augmentation, which is a strategy to expand the amount of data by generating modified copies or newly created images from existing data, has been commonly adopted as a regularizer to lessen overfitting [26, 39]. To increase the scale and diversity of the acquired rat brain MR image data, we employed four distinct forms of data augmentation, which allowed transformed images to be generated from the original data. The transformation consists of shears (within 0.3 rad), rotations (within 30 degrees), zooming (within $20\%$ of brain regions), and horizontal reflections, which are randomly created to increase the size of our training dataset by a factor of 1000 through all epochs in both DWI and T2WI images.
## RU-Net for rat brain extraction
Our RU-*Net is* a special deep learning framework that takes advantage of the decoupling utility in batch normalization [36], the skip connection in residual network [35], and the feature concatenation in U-Net [28] for skull stripping in pathological rat brain MR images. We introduce the batch normalization and residual network into our encoder-decoder U-Net like architecture to accelerate the convergence speed while reducing the gradient vanishing and explosion problems. As illustrated in Fig. 1, our RU-Net consists of 33 convolutional layers, 5 maximum pooling layers, and 5 upsampling layers. In the encoding path, there are 14 convolutional layers and 5 maximum pooling layers. Each individual rat brain MR image \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\widehat{I}$$\end{document} with a dimension of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N\times N$$\end{document} is fed into the network in the input layer, followed by a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\times 3$$\end{document} convolution process to boost the channel number to 64 in the convolution layer. This \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N\times N\times 64$$\end{document} output provides two functions: input for the subsequent block and input for the residual addition. The block consists of three consecutive layers, namely, batch normalization (BN), activation, and convolution. By normalizing each mini-batch, the BN layer enables us to be less cautious concerning parameter initialization and adopt higher learning rates, which also helps stabilize the network. The rectified linear unit (ReLU) function is utilized in the activation layer followed by a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\times 3$$\end{document} convolution layer for feature extraction. The same \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N\times N\times 64$$\end{document} structure is constructed through the entire block, i.e., all three layers. After one additional block with the same architecture, the immediate output and the preserved convolution output are joined together to establish the residual learning network in the addition layer.
Subsequently, the output from the addition layer serves as both the input of the following maximum pooling layer and the concatenation in the decoder phase. The maximum pooling is executed using a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2\times 2$$\end{document} neighborhood with stride 2 that reduces the output to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(N/2\right)\times \left(N/2\right)\times 64$$\end{document}. To tackle large intensity variation in ischemic rat brain images, a pooling index transmission mechanism is introduced so that the corresponding maximum value indices are also stored for recovering the feature locations in the decoding path [40]. The maximum pooling result and its output after two equivalent block processes are united to build a deeper residual learning scheme again in a second addition layer. These encoding procedures of one maximum pooling, three block processing, and one residual addition steps are repeated until the image dimension is scaled down to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(N/16\right)\times \left(N/16\right)$$\end{document}. After an additional maximum pooling operation, the decoder phase starts from a contrary \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2\times 2$$\end{document} maximum upsampling layer with stride 2 to produce enlarged features for concatenation. In the deepest concatenation layer, the upsampled result and the output from the deepest addition layer in the encoder phase are integrated into a double channel structure with a dimension of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(N/16\right)\times \left(N/16\right)\times 128$$\end{document}. In the following block processing, the output architecture reduces to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(N/16\right)\times \left(N/16\right)\times 64$$\end{document} after the convolution layer. This output and the outcome after three successive blocks are added up to produce the deepest residual learning network in the decoding path. The subsequent maximum upsampling layer again combines the addition result with the output from the corresponding maximum pooling layer in the encoder phase, which expands the outcome to a dimension of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(N/8\right)\times \left(N/8\right)\times 64$$\end{document}. This outcome is then concatenated with the output of the matching addition layer in the encoding path to generate a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(N/8\right)\times \left(N/8\right)\times 128$$\end{document} resulting structure.
These procedures associated with upsampling, concatenation, convolution, and residual learning are duplicated until the network dimension grows back to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N\times N\times 64$$\end{document}. In the last block, after the BN layer, the sigmoid function is employed in the activation layer to produce output values between 0 and 1 for segmentation prediction. A final \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1\times 1$$\end{document} convolution layer is utilized to consolidate all channels to a single \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N\times N$$\end{document} probability map, which completes the decoder phase with 19 convolutional layers and 5 upsampling layers. The loss function \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Lambda }$$\end{document} is defined in terms of the Dice metric [41] using2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Lambda }\left({{\Omega }}_{sp},{{\Omega }}_{gt}\right)=1-{\kappa }_{D}\left({{\Omega }}_{sp},{{\Omega }}_{gt}\right)$$\end{document} where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Omega }}_{sp}$$\end{document} represents the segmentation prediction (SP) mask, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Omega }}_{gt}$$\end{document} represents the ground truth (GT) mask, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{D}$$\end{document} represents the Dice coefficient, which is defined as 3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{D}\left({{\Omega }}_{sp},{{\Omega }}_{gt}\right)=\frac{2\left|{{\Omega }}_{sp}\bigcap {{\Omega }}_{gt}\right|}{\left|{{\Omega }}_{sp}\right|+\left|{{\Omega }}_{gt}\right|}=\frac{2{\theta }_{TP}}{{2\theta }_{TP}+{\theta }_{FN}+{\theta }_{FP}}$$\end{document} Fig. 1Illustration of the proposed RU-Net architecture
where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{TP}$$\end{document} represents true positives, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FN}$$\end{document} represents false negatives, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FP}$$\end{document} represents false positives associated with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Omega }}_{sp}$$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Omega }}_{gt}$$\end{document}. To find the best parameters in the proposed RU-Net, the Adam optimizer [42] is employed due to its great effectiveness on computational complexity and memory usage. Varying learning rates with decaying values during the training process are employed to further accelerate the convergence speed.
## Performance evaluation
In addition to the Dice metric as described in Eq. [ 3], some other evaluation measures are exploited to reveal the correlation between the segmentation and GT masks. Specifically, two similarity metrics of sensitivity \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{st}$$\end{document} and sensibility \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{sb}$$\end{document} [43] are adopted to evaluate the degree of under-segmentation and over-segmentation with4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{st}\left({{\Omega }}_{sp},{{\Omega }}_{gt}\right)=\frac{{\theta }_{TP}}{{\theta }_{TP}+{\theta }_{FN}}$$\end{document} and5\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{sb}\left({{\Omega }}_{sp},{{\Omega }}_{gt}\right)=1-\frac{{\theta }_{FP}}{{\theta }_{TP}+{\theta }_{FN}}$$\end{document} , respectively. The Hausdorff distance metric [44], which measures the largest distance of a point set to the nearest point in another, is utilized to signify how close the segmentation and GT contours are in a Euclidean space with 6\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{array}{l}{\delta _h}\left({{\Gamma _{sp}},{\Gamma _{gt}}} \right) = \\{\rm{max}}\left({\mathop {{\rm{max}}}\limits_{s \in {\Gamma _{sp}}} \mathop {{\rm{min}}}\limits_{g \in {\Gamma _{gt}}} \left\| {s - g} \right\|,\mathop {{\rm{max}}}\limits_{g \in {\Gamma _{gt}}} \mathop {{\rm{min}}}\limits_{s \in {\Gamma _{sp}}} \left\| {g - s} \right\|} \right)\end{array}$$\end{document}
where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\delta }_{h}$$\end{document} represents the Hausdorff distance, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left\| {\, \cdot \,} \right\|$$\end{document} symbolizes the norm, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Gamma }}_{sp}$$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Gamma }}_{gt}$$\end{document} indicate the point sets of the contours corresponding to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Omega }}_{sp}$$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\Omega }}_{gt}$$\end{document}, respectively. A robuster measure of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\delta }_{h}$$\end{document} is the average Hausdorff distance that computes the average distance instead of the maximum distance in Eq. [ 6], which is employed in this study and denoted as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\delta }_{ah}$$\end{document}. A paired t-test is used to compare the evaluation scores of the proposed framework with those from other methods. A two-tailed P-value < 0.05 is considered statistically significant.
## Implementation
Our proposed RU-Net framework for rat brain extraction in two different modalities of DWI and T2WI was implemented and programmed in Python 3.5 using Keras 2.1.6 [45]. All experiments were executed on an Intel® Xeon(R) CPU ES-2620 v3 @ 2.40 GHz\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times 24$$\end{document} workstation running 64-bit Linux Ubuntu 16.04. The machine was equipped with a NVIDIA Tesla K40c GPU of 12GB RAM [46]. The percentages of the training, validation, and testing sets were 6: 2: 2, which were randomly selected from the acquired image datasets. The input image dimensions are \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$128\times 128$$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$256\times 256$$\end{document} for DWI and T2WI images, respectively. The training phase was executed using a mini-batch size of 8 with a total number of 100 epochs. The learning rates were initialized with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$5{\text{e}}^{-4}$$\end{document}, which gradually decreased to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$1{\text{e}}^{-4}$$\end{document} when the epoch number was larger than 20. The same RU-Net architecture was employed for both DWI and T2WI images but trained individually. There were two different sets of the GT masks corresponding to the DWI and T2WI datasets, which were independently delineated by experienced neurologists in our team. This was mainly because the infarct regions exhibited in DWI and T2WI images were not identical due to different resolution abilities. On the basis of the GT, our skull stripping results were compared with traditional methods including the BSE [47], rBET [48], and RATS [19] as well as the network-based approaches such as the 3-D PCNN [25], DeepMedic [49], and U-Net [32]. For deep-leaning methods of DeepMedic and U-Net, their models were retrained using the same protocols as our RU-Net.
Fig. 2Plots of the accuracy and loss functions using the RU-Net in the training and validation datasets. Top row: DWI subjects. Bottom row: T2WI subjects
## Network cross validation
To understand the effectiveness of the proposed RU-Net skull stripping network, five-fold cross validation was exploited in the training phase. Figure 2 plots the accuracy and loss functions for the training and validation datasets in both DWI and T2WI images. Each fold had two curves that represented the training and validation subjects with respect to the epoch number. All of the five folds exhibited quite similar accuracy and loss trace patterns. For the DWI image scenario, the training curves climbed relatively slowly than the validation curves up towards the same high segmentation accuracy. While the training curves gradually raised their accuracy in T2WI images, the corresponding validation curves reached a plateau and maintained their high accuracy towards the end of the epoch. It was obvious that our RU-Net achieved high skull stripping accuracy with tiny loss in the DWI and T2WI rat brain image datasets, which indicated the robustness of our developed network. Further validation on the RU-Net segmentation performance was presented in Table 1 in comparison with different architecture variants using \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\times 3$$\end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4\times 4$$\end{document} maximum pooling, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$7\times 7$$\end{document} convolution, and 4 level U-shape network structure. It was apparent that the proposed RU-Net architecture exhibited the best evaluation scores with the narrowest standard deviations in terms of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{D}$$\end{document}, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{st}$$\end{document}, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{sb}$$\end{document}.
Table 1Segmentation performance comparison between different network architecture settingsNetwork architectureEvaluation metricΚD(%)Κst(%)Κsb(%)Maximum pooling:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\times 3$$\end{document}95.20 ± 2.5396.32 ± 3.2393.77 ± 4.36Maximum pooling:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4\times 4$$\end{document}95.18 ± 2.6196.24 ± 3.2993.82 ± 4.55Convolution filter:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$7\times 7$$\end{document}95.96 ± 2.4296.92 ± 2.9794.88 ± 2.98U-shape structure depth: 498.01 ± 1.5097.78 ± 1.8598.06 ± 1.87RU-Net 98.04 ± 0.33 97.94 ± 0.75 98.15 ± 0.68
## DWI skull stripping
Figure 3 illustrates qualitative skull stripping results in a sequence of DWI images using the proposed scheme along with the corresponding GT masks. The segmented brain regions (yellow) were observed to be well conformed to the GT contours (red). Performance measures of the skull stripping results using the Dice, sensitivity, and sensibility metrics based on five-fold cross validation were depicted in Fig. 4. It was noted that the proposed RU-Net produced the highest average Dice and sensibility scores with the narrowest standard deviations over the DeepMedic and U-Net methods. While the average sensitivity scores of the three methods were somewhat overlapped, the U-Net was slightly higher than other two methods. Representative skull stripping results using the abovementioned seven methods were qualitatively illustrated in Fig. 5. All approaches more or less encompassed the rat brain regions but the BSE, rBET, RATS, 3-D PCNN, and DeepMedic methods revealed apparent false positive regions. Both U-Net and RU-Net produced accurate segmentation results with the U-Net contours more smooth and the RU-Net contours deformed into the fissures, which better resembles the GT. Figure 6 demonstrates visual skull stripping results of two different subjects with DWI in 3-D view. Obvious over-segmentation and under-segmentation outcomes were generated by the traditional methods of BSE, rBET, RATS, and 3-D PCNN. More precise results were obtained using the deep learning-based methods. While the segmentation masks provided by the DeepMedic and U-Net methods were with excess components, our RU-Net scheme generated clean rat brain regions. Table 2 summarizes statistical analyses of the skull stripping results in the DWI image dataset in terms of the four evaluation metrics. The proposed RU-Net framework achieved the highest average evaluation scores of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{D}=98.04\%$$\end{document} (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$$p \leq 0.001$$$\end{document}) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{sb}=98.15\%$$\end{document} (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$$p \leq 0.001$$$\end{document}) with the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{st}$$\end{document} score slightly smaller than the maximum value received by the U-Net method. Our segmentation performance was further validated by the smallest average value of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\delta }_{ah}=0.1161$$\end{document}mm (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$$p \leq 0.001$$$\end{document}) compared with all competitive methods.
Fig. 3Illustration of DWI (Subject 39) skull stripping results using the proposed RU-Net framework. Yellow: Prediction. Red: GT Fig. 4Performance analyses of DWI skull stripping results based on five-fold cross validation Fig. 5Visual comparison of DWI skull stripping results using different methods. Top row: slices 7 and 8 of Subject 10. Bottom row: slices 9 and 10 of Subject 21 Fig. 6Visual comparison of DWI skull stripping results in 3-D view using different methods. Blue: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FP}$$\end{document}. Red: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FN}$$\end{document}. Top row: Subject 16. Bottom row: Subject 40
Table 2Quantitative comparison of rat skull stripping results in DWI image volumes between different methodsMethodEvaluation metricΚD(%)Κst(%)Κsb(%)δah(mm)BSE81.71 ± 2.4372.49 ± 2.3189.97 ± 2.342.4219 ± 0.8785rBET82.69 ± 2.7697.21 ± 2.9163.28 ± 7.822.2802 ± 0.6547RATS86.12 ± 3.5191.56 ± 2.8777.89 ± 3.861.7673 ± 0.78913DPCNN88.87 ± 5.2496.74 ± 1.5378.57 ± 3.311.6485 ± 0.8637DeepMedic95.88 ± 1.4398.24 ± 0.6293.27 ± 3.050.9896 ± 0.7955U-Net95.87 ± 0.97 98.76 ± 1.00 92.71 ± 2.430.9298 ± 0.6795RU-Net 98.04 ± 0.33 97.94 ± 0.75 98.15 ± 0.68 0.1161 ± 0.0754 Fig. 7Illustration of T2WI (Subject 31) skull stripping results using the proposed RU-Net framework. Yellow: Prediction. Red: GT Fig. 8Performance analyses of T2WI skull stripping results based on five-fold cross validation
## T2WI skull stripping
In the scenario of T2WI image segmentation, the proposed RU-Net scheme also performed well. As illustrated in Fig. 7, the segmented brain regions (yellow) were decently similar to the corresponding GT masks (red) in all instances. Figure 8 shows quantitative evaluation of the skull stripping results in the T2WI dataset based on five-fold cross validation. The average Dice and sensibility scores provided by our RU-Net architecture were higher and with smaller standard deviations than the DeepMedic and U-Net methods. The overlapping phenomena of the average sensitivity scores between the three methods in the T2WI subjects were more evident than the DWI subjects. We visually compared our skull stripping framework with the seven methods in Fig. 9, where two randomly selected subjects were presented. Similar to the DWI segmentation scenario, there were noticeable false positive regions in some slices using the BSE, rBET, RATS, 3-D PCNN, and DeepMedic methods. The U-*Net* generated smooth contours that approximately circumscribed the rat brain surfaces, whereas the proposed RU-Net achieved more accurate contours that were better compatible with the GT. Figure 10 compares the whole skull stripping outcomes of Subjects 3 and 37 in 3-D view between different methods. Apparent segmentation errors were observed using the BSE, rBET, RATS, 3-D PCNN, and DeepMedic methods. Both U-Net and RU-Net schemes produced more precise segmentation results with fewer flaws. Nevertheless, our RU-Net achieved higher Dice scores of $97.25\%$ and $98.08\%$ for Subjects 3 and 37, respectively. Statistical analyses of the rat brain segmentation results in T2WI image volumes in Table 3 indicated our advantage over other methods with the highest average values of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{D}=97.67\%$$\end{document} (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$$p \leq 0.001$$$\end{document}) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{sb}=97.42\%$$\end{document} (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$$p \leq 0.001$$$\end{document}). Lastly, the smallest average score of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\delta }_{ah}=0.1406$$\end{document}mm (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$$p \leq 0.001$$$\end{document}) attained by the RU-Net further confirmed our skull stripping efficacy.
Fig. 9Visual comparison of T2WI skull stripping results using different methods. Top row: slices 6 and 7 of Subject 9. Bottom row: slices 8 and 9 of Subject 33 Fig. 10Visual comparison of T2WI skull stripping results in 3-D view using different methods. Blue: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FP}$$\end{document}. Red: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FN}$$\end{document}. Top row: Subject 3. Bottom row: Subject 37 Table 3Quantitative comparison of rat skull stripping results in T2WI image volumes between different methodsMethodEvaluation metricΚD(%)Κst(%)Κsb(%)δah(mm)BSE82.44 ± 2.4073.13 ± 2.2789.99 ± 2.312.3127 ± 0.8563rBET83.51 ± 3.56 98.93 ± 0.26 65.04 ± 8.632.0538 ± 0.6435RATS87.31 ± 4.1293.16 ± 2.7778.97 ± 7.681.6806 ± 0.76113DPCNN89.06 ± 4.1897.25 ± 2.8178.69 ± 8.061.6132 ± 0.8527DeepMedic90.20 ± 2.7498.23 ± 0.7480.20 ± 6.901.5440 ± 0.6359U-Net96.43 ± 0.6598.35 ± 1.1794.38 ± 1.660.6850 ± 0.4451RU-Net 97.67 ± 0.46 97.90 ± 1.00 97.42 ± 0.97 0.1406 ± 0.1357
## Discussion
A new skull stripping framework for pathological rat brain MR images in light of deep learning networks has been introduced. The development of this RU-Net was inspired by the demand for preclinical stroke investigation associated with both DWI and T2WI image volumes. As the U-Net [28] has been successfully employed in many medical image segmentation applications [28, 32, 33], our network took advantage of the U-shape architecture from the U-Net. To handle the nonuniform intensity distribution and blurred brain boundaries in the ischemic rat MR images, a series of BN layers conceived from the batch normalization scheme [36] constituted the block structure in the encoding and decoding paths. Enhancement learning was accomplished by a residual network [35] that connects the input with the output features of each block in both encoder and decoder. A common disadvantage of deep learning-based approaches for medical image processing is the limited number of image data comparing to the scale of natural image databases such as the ImageNet. We tackled this issue by augmenting existing image data through different spatial transformations to diversify the training data. Based on the five-fold cross validation with the rat brain MR image datasets, we updated and finalized the system parameters to achieve the optimal architectures. Different evaluation metrics associated with the paired t-test were employed to compare our segmentation outcome with the state-of-the-art methods.
As presented in Tables 2 and 3, comparable skull stripping results were obtained in both the DWI and T2WI image datasets using the traditional methods of BSE, rBET, RATS, and 3-D PCNN. Developed for human brain image segmentation, the BSE method produced acceptable skull stripping results around the middle slices of the rat brain image volumes. However, notable segmentation errors appeared roughly in the first and last three slices, which deteriorated the overall performance. Modified from the BET scheme, the rBET method also adopted an active contour model that was evaluated in rat brain T1-weighted and T2-weighted MR images. Obvious over-segmentation outside the rat brain boundaries reduced its segmentation accuracy due to the abnormity in the DWI and T2WI image datasets, leading to the poorest sensibility scores in both scenarios. Originally validated on normal rat brain MR images similar to the rBET method, the RATS algorithm was unable to efficiently separate the ischemic rat brain regions from the surrounding tissues, particularly for DWI images. Extended from the 2-D PCNN model and verified in mouse brain T2WI images, the 3-D PCNN algorithm generated unstable skull stripping results so that some slices exhibited apparent false positive regions in the ischemic rat image datasets as illustrated in Figs. 5 and 9.
Fig. 11Visual skull stripping results using the original MU-Net (top row) and MedicDeepLabv3+ (bottom row) without retraining. Left columns: DWI Subjects 10 and 21. Right columns: T2WI Subjects 9 and 33 Different from the traditional approaches, the deep learning-based models exploited an end-to-end network, which usually provide better outcomes. As can be realized from the evaluation scores, the DeepMedic, U-Net, and RU-Net schemes exhibited higher skull stripping accuracy with smaller \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\delta }_{ah}$$\end{document} values in both DWI and T2WI scenarios. Equipped with the efficient multiscale 3-D CNN and fully connected conditional random field model, the DeepMedic scheme adequately captured the rat brain surfaces. Likewise, the skull stripping results using the U-Net method decently enclosed the rat brains in all demonstrated instances. Due to the large \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\theta }_{FP}$$\end{document} regions, the U-Net exhibited low \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{sb}$$\end{document} scores, which in turn produced higher \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{st}$$\end{document} scores than our RU-Net. To segment the rat brain MR images with ischemia, both DeepMedic and U-Net models were retrained using the same protocols as our RU-Net to fine-tune their system parameters. All three deep learning-based frameworks were evaluated according to the five-fold cross validation in the DWI and T2WI image datasets as revealed in Figs. 4 and 8, respectively. Statistical analyses using the Dice, sensitivity, and sensibility metrics indicated convergent characteristics of the three networks. This was mainly because the deep learning mechanisms were refreshed to adapt the systems to new image data. Without the retraining process for parameter adjustments, the segmentation to unfamiliar image data could be improper. To illustrate this, Fig. 11 depicts the skull stripping results of the same slices and subjects in Figs. 5 and 9 using the original models of the MU-Net [33], which was originally developed for large mouse brain segmentation in T2WI images, and the MedicDeepLabv3+ [34]. Their average \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\kappa }_{D}$$\end{document} scores were $31.01\%$ and $34.72\%$ for the DWI dataset, and $55.46\%$ and $48.28\%$ for the T2WI dataset, respectively.
One inevitable shortage of deep learning-based strategies for medical image segmentation is that the outcome may exhibit disconnected components with broken pieces and interior holes. This is mainly due to the natural characteristics of pixel-to-pixel partition based on the feature maps at different scales and depths. Although the consecutive convolution processes include neighboring information, the involvement is too shallow and limited mostly to adjacent pixels. For natural images, this partition scheme will not cause serious issues as the color information of three channels is involved and the intensity variation is relatively subtle. For medical images as in our scenario, the single gray scale image is the only input to the system and inhomogeneous intensities are obviously presented. As shown in Figs. 6 and 10, noticeable false positive regions apart from the brains were produced using the DeepMedic and U-Net methods. Thanks to the unique network architecture, the proposed RU-Net faithfully delineated the rat brain boundaries and achieved accurate skull stripping results with minor over-segmentation errors compared to other networks. This is not only because our architecture contains the BN layer associated with the residual network but also because the salient feature locations in the encoder are transmitted to the corresponding upsampling procedures in the decoder to strengthen the spatial correlation. From the perspective of practical applications, the outcome from deep learning-based approaches can be improved by appropriate morphological operations to acquire clean and complete brains. For example, the average sensibility scores of the DeepMedic and U-Net schemes in the DWI image dataset increased to $97.50\%$ and $93.11\%$, respectively, and they advanced to $97.14\%$ and $94.59\%$ in the T2WI image dataset. Lastly, our RU-Net can be extended for multimodal learning by feeding, say, two different modalities of DWI and T2WI images to the corresponding network and integrating the intermediate results through an extra concatenation structure to generate the ultimate prediction.
## Conclusion
In this paper, we investigated an automatic skull stripping framework in pathological rat brain MR images in light of a deep learning architecture, namely RU-Net. Motivated by the demand of segmenting rat brain MR images after ischemic stroke, the proposed scheme was established on an efficient U-shape like network with embedded BN layers reinforced by the residual network. A variety of ischemic rat brain images in two different DWI and T2WI datasets were employed to evaluate the capability of our rat brain segmentation network. Comparable performance with high evaluation scores in terms of Dice, sensitivity, and sensibility was observed in both image datasets. Our RU-Net outperformed the state-of-the-art methods either traditional mathematics models or deep learning networks in extracting clean rat brain regions with a nonuniform intensity distribution in the acquired MR image volumes. We believe that the proposed skull stripping network is of great potential for advancing preclinical stroke investigation as well as providing an efficient tool for abnormal rat brain MR image extraction, where accurate segmentation of the brain region is fundamental.
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|
---
title: Taurine as Antioxidant in a Novel Cell- and Oxygen Carrier-Free Perfusate for
Normothermic Machine Perfusion of Porcine Kidneys
authors:
- Laura Zarnitz
- Benedict M. Doorschodt
- Lisa Ernst
- Aisa Hosseinnejad
- Eileen Edgworth
- Tamara Fechter
- Alexander Theißen
- Sonja Djudjaj
- Peter Boor
- Rolf Rossaint
- René H. Tolba
- Christian Bleilevens
journal: Antioxidants
year: 2023
pmcid: PMC10045130
doi: 10.3390/antiox12030768
license: CC BY 4.0
---
# Taurine as Antioxidant in a Novel Cell- and Oxygen Carrier-Free Perfusate for Normothermic Machine Perfusion of Porcine Kidneys
## Abstract
Donor organ-shortage has resulted in the increased use of marginal grafts; however, normothermic machine perfusion (NMP) holds the potential for organ viability assessment and restoration of marginal grafts prior to transplantation. Additionally, cell-, oxygen carrier-free and antioxidants-supplemented solutions could potentially prevent adverse effects (transfusion reactions, inflammation, hemolysis), associated with the use of autologous packed red blood cell (pRBC)-based perfusates. This study compared 6 h NMP of porcine kidneys, using an established pRBC-based perfusate (pRBC, $$n = 7$$), with the novel cell- and oxygen carrier-free organ preservation solution Ecosol, containing taurine (Ecosol, $$n = 7$$). Despite the enhanced tissue edema and tubular injury in the Ecosol group, related to a suboptimal molecular mass of polyethylene glycol as colloid present in the solution, functional parameters (renal blood flow, intrarenal resistance, urinary flow, pH) and oxygenation (arterial pO2, absence of hypoxia-inducible factor 1-alpha) were similar to the pRBC group. Furthermore, taurine significantly improved the antioxidant capacity in the Ecosol group, reflected in decreased lactate dehydrogenase, urine protein and tubular vacuolization compared to pRBC. This study demonstrates the feasibility of 6 h NMP using a taurine containing, cell- and oxygen carrier-free perfusate, achieving a comparable organ quality to pRBC perfused porcine kidneys.
## 1. Introduction
The only curative treatment modality for end stage renal disease, reducing all-cause mortality, remains kidney transplantation [1,2]. According to Eurotransplant data, 4002 kidneys were transplanted in 2021, whilst 10,269 patients were enrolled on active waiting lists to receive a kidney graft at the end of 2021 and 706 people died awaiting kidney transplant [3]. To increase the pool of kidneys suitable for transplantation, expanded criteria for donation after brain death (ECD-DBD) as well as donation after circulatory death donors (DCD) are more often being employed. However, the organs from these donor categories are associated with higher incidences of primary non-function (PNF), delayed graft function (DGF) and graft loss [4,5,6], and thus defined as marginal grafts.
Over the last decade, normothermic machine perfusion (NMP) is increasingly investigated in preclinical as well as clinical studies since it holds a true potential of increasing the viability of marginal grafts. NMP also offers the possibility of viability assessment and pharmaceutical intervention prior to transplantation, in contrast to static cold storage (SCS) or hypothermic machine perfusion (HMP) [7,8]. As shown previously in cohort studies, NMP is capable of reducing PNF and DGF and improving immediate kidney function [9,10,11,12,13].
The adequate supplying of the kidney with nutrients and oxygen is vital to maintain the metabolism and organ function during NMP. The optimal composition of perfusion solutions for NMP remains to be defined. Although a standard NMP protocol is lacking, perfusates derived from whole blood or packed red blood cells (pRBC) combined with a buffer solution are most commonly applied [14,15]. As perfusion with whole blood or pRBC’s bears the risk of transfusion reactions through increased immunogenicity, inflammation, and hemolysis due to perfusion using systems with artificial surfaces, alternatives are the focus of experimental studies. In an attempt to replace pRBCs in our established NMP perfusate, we recently described the use of Hemoglobin-Based Oxygen Carrier-301 (HBOC-301, HBO2 Therapeutics, Souderton, PA, USA) [16] showing HBOC-301 to be inferior to pRBC’s in a 6 h porcine kidney NMP setting. Cell free solutions, such as Lifor, Aqix RS-I, University of Wisconsin solution (UW) and Steen solution have recently been described as alternative NMP perfusates in experimental studies [17,18,19,20]. It was shown that neither cells nor artificial oxygen carriers are required for adequate tissue oxygenation during 2 h NMP [17,20].
In the current study, we aimed to investigate the use of Ecosol organ preservation solution (TX Innovations B.V., Gulpen, The Netherlands), originally developed for kidney SCS, as an alternative to our previously established pRBC-based NMP perfusate [16,21,22]. In contrast to HBOC-301, *Ecosol is* an acellular and oxygen carrier-free solution. For DBD and DCD kidney SCS with subsequent normothermic reperfusion as well as for venous systemic oxygen persufflation and HMP, Ecosol showed an improved preservation quality compared to Histidine-Tryptophan-Ketoglutarate solution (HTK) [23,24].
As inflammatory mediators are upregulated during NMP, reactive oxygen species (ROS) are formed, resulting in tissue damage [25]. Ecosol contains taurine, a potent antioxidant, to minimize oxidative damage. Taurine supplementation to perfusion solutions previously demonstrated effectiveness in oxygenated liver preservation, reducing lipid peroxidation and vascular resistance [26,27]. It was also shown to preserve the renal function [28] and ameliorate liver injury in a rat cholestasis model [29].
This study aims to show the beneficial effects of a cell- and oxygen carrier-free, taurine-containing perfusate compared to the widely used pRBC-based perfusate in a porcine model of DCD kidney NMP.
## 2.1. Experimental Protocols
The experimental protocol was approved by the Institutional Animal Care and Use Committee of the RWTH Aachen University Hospital and performed in accordance with German legislation governing animal studies following the “Guide for the care and use of Laboratory Animals” (NIH publication, 8th edition, 2011) and the Directive $\frac{2010}{63}$/EU on the protection of animals used for scientific purposes (Official Journal of the European Union, 2010).
Kidneys were retrieved and either perfused with Ringer’s Solution for Infusion (B. Braun Melsungen AG, Melsungen, Germany) based perfusion solution mixed with autologous pRBCs or with Ecosol. The two experimental groups were defined as perfusion with one of the perfusates, and henceforward will be referred to as pRBC and Ecosol. Kidney pairs were perfused simultaneously for 6 h with perfusate and urine sample collection at regular time points. Biopsies and tissue samples were taken before and after perfusion for histology and molecular biology analysis.
## 2.2. Preparation of Kidney Grafts
Seven German landrace pigs, 56.3 ± 2.7 kg (MW ± SEM) body weight, from a disease-free barrier breeding facility, were housed in fully air-conditioned rooms (22 °C room temperature, $50\%$ relative humidity). For a minimum of seven days, they were allowed to acclimatize to these conditions and fasted for 12 h prior to surgery with free access to water. The animals were premedicated with 15 mg/kg BW ketamine (Ceva GmbH, Duesseldorf, Germany), 8 mg/kg BW azaperone (Stresnil®, Janssen-Cilag GmbH, Neuss, Germany), and 10 mg atropine (1 mL/$1\%$ atropine sulfate, Dr. Franz Köhler Chemie GmbH, Bensheim, Germany) administrated intramuscularly. Euthanization was performed using 1 mL/kg BW pentobarbital (Narcoren, Merial GmbH, Hallbergmoss, Germany), cardiac arrest was testified, and a midline laparotomy was performed. Immediately after cardiac arrest, the vena cava was cannulated and 450 mL of venous blood were collected into sterile blood bags (Composelect®, Fresenius Kabi Austria GmbH, Graz, Austria) each and prepared for pRBC production as described previously by our working group [16]. Kidneys were explanted simultaneously and weighed. For washout, 250 mL of warm (37 °C) Ringer’s solution or Ecosol were supplemented with 5000 IU heparin (B. Braun Melsungen AG, Melsungen, Germany). Directly after explantation, 100 mL of the flushing solution were administered, the other 150 mL after cannulation of the renal artery (Retrograde Cardioplegia Catheter, 14 Fr., Edwards Life Sciences, RC014; Unterschleißheim, Germany). Cannulation of the renal vein (Thomafluid® Luer Lock Tubing Adapter Female together with a flexible tube, ID 6.4 mm ($\frac{1}{4}$′′), Reichelt Chemietechnik GmbH + Co., Heidelberg, Germany) and ureter (Suction Catheter ProFlo straight tip with a funnel, 14 Ch., ConvaTec GmbH, Munich, Germany) were performed to enable sample collection. In accordance with the 3R principle in experimental animal sciences (Refine, Reduce, Replace), all remaining organs and tissues of the experimental animals were used by other in-house institutes and groups.
## 2.3. Normothermic Machine Perfusion
Kidneys were perfused simultaneously for 6 h at a mean arterial pressure (MAP) of 75 mmHg and at a temperature of 36.5 ± 0.1 °C, according to our established protocol [16,21,22].
The perfusion circuits (Figure 1a) consisted of a custom-made container for the kidneys, wherein the kidney was emersed in the effluent instead of a humid chamber, a centrifugal blood pump (Affinity CP, Medtronic GmbH, Meerbusch, Germany), an oxygenator (Newborn A.L.ONE ECMO, Eurosets GmbH, Gröbenzell, Germany), and a pediatric arterial filter (AffinityTM, Medtronic GmbH, Meerbusch, Germany).
Kidneys were connected to the circuit via the renal artery, with the effluent draining freely from the renal vein into the container, which served as a reservoir for the perfusion loop. The centrifugal blood pump was driven by a custom-designed pump controller (Informatik 11-Embedded Software, RWTH Aachen University, Aachen, Germany) automatically adjusting the rotations per minute (RPM) according to a preset arterial blood pressure. Within the first five minutes, starting at 25 mmHg, the MAP was continuously increased to the target MAP of 75 mmHg and held throughout the 6 h NMP. The perfusate was oxygenated through a heated oxygenator and ventilated with 0.5 L/min carbogen ($95\%$ O2/$5\%$ CO2). The temperature was maintained at 36.5 °C by a water bath thermostat connected to the oxygenator. The MAP and temperature were monitored (IntelliVue MX500, Royal Philips Electronics, Amsterdam, The Netherlands) continuously, and the arterial renal blood flow (RBF) was recorded through an ultrasonic flow meter (SonoTT, em-tec GmbH, Finning, Germany).
According to Weißenbacher et al., the urine was recirculated for improved metabolic homeostasis and to keep the perfusate volume within the circuit constant [30].
## 2.4. Perfusion Solutions
In both experimental groups, a total perfusate volume of 1000 mL was provided by using either 500 mL autologous pRBC and 500 mL of a Ringer’s solution-based buffer as previously described by our working group [16], or 1000 mL Ecosol. In the Ecosol group, 0.058 g of dissolved creatinine (Sigma Aldrich Chemie GmbH, Taufkirchen, Germany) was added, matching the concentration in the pRBC group to enable creatinine clearance (CrCl) determination.
Both groups were supplemented with 750 mg cefuroxime (Dr. Friedrich Eberth Arzneimittel GmbH, Ursensollen, Germany), 5000 IU heparin, 8 mg dexamethasone (Fortecortin inject, Merck KgaA, Darmstadt, Germany), and sodium bicarbonate $8.4\%$ (Deltamedica GmbH, Reutlingen, Germany) titrated until a pH of 7.318 ± 0.009 was reached (12.7 ± 0.6 mL).
Syringe pumps continuously administered a nutritive solution at a rate of 22.4 mL/h to pRBC, consisting of 44 mL Nutriflex (B. Braun Melsungen AG, Melsungen, Germany), 0.4 mL Cernevit (Baxter Deutschland GmbH, Unterschleißheim, Germany) and 20 IU insulin glulisine (Apidra, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany). Since Ecosol contains a unique mixture of additives and nutrients [24], the nutritive solution added to the pRBC group was not added to the Ecosol group. Instead, 44.4 mL Ecosol supplemented with 20 IU insulin was infused at the same rate, to match the volumes added to the pRBC group.
## 2.5. Biochemistry
As a baseline sample, 1 mL of the initial perfusate was taken before the kidneys were attached to the primed circuit (0 min). Arterial, venous and urine samples were collected at 8 distinct time points (5, 30, 60, 120, 180, 240, 300, and 360 min). The urine output was collected between these time points, and as soon as 100 mL was produced, $1\%$ of the volume was collected. The remaining amount was recirculated into the reservoir container.
Blood gas analysis was performed by using an in-line blood gas analyzer (ABL 800Flex, Radiometer GmbH, Krefeld, Germany). Arterial, venous and urine samples were analyzed for pH, partial pressure of oxygen (pO2), partial pressure of carbon dioxide (pCO2), saturation of oxygen (sO2), concentration of total hemoglobin (ctHb), electrolytes, glucose, and lactate.
Arterial samples were centrifuged at 10,000 rpm, 4 °C, for 10 min. Aliquots of the supernatant were stored at −80 °C for biochemistry analysis of aspartate aminotransferase (AST), lactate dehydrogenase (LDH), total protein, urea, creatinine, and iron. Urine samples were stored alike and analyzed for creatinine, urea, and total protein concentrations. Biochemistry analysis was performed by the local ISO 9001:2015-certified laboratory at the Institute of Laboratory Animal Science and Experimental Surgery.
Kidney weights were recorded before and after perfusion. Temperature, pump rpm, MAP, RBF, and total urine output were documented for each time point. Intrarenal resistance (IRR) was calculated as MAP/RBF/100 g and CrCl as urine creatinine × urinary flow/plasma creatinine/100 g.
## 2.6. Molecular Biomarkers
After perfusion, tissue samples of the renal cortex (RC), inner stripe (IS) and inner medulla (IM) were snap-frozen and stored at −80 °C for molecular biology (Figure 1b).
Serum and tissue concentrations of Hypoxia Inducible Factor-1alpha (HIF-1α, Porcine HIF-1α ELISA Kit; MBS263046, San Diego, CA, USA), and serum levels of Interleukin-6 (IL-6, Porcine IL-6 Quantikine ELISA Kit, P6000B, R & D Systems, Inc., Minneapolis, MN, USA) were analyzed through enzyme-linked immunosorbent assays (ELISA) by preparing 40 mg of tissue according to the manufacturer’s instructions. All samples were diluted 1:2 and plates were read at 450 nm with the iMark™ Microplate Absorbance Reader (Bio-Rad Laboratories GmbH, Feldkirchen, Germany).
For Western Blot (WB) analysis, Radioimmunoprecipitation Assay buffer (RIPA, Lysis Buffer, 10×, Merck KGaA, Darmstadt, Germany) was supplemented with $1\%$ Sodium dodecyl sulfate solution (BioUltra for molecular biology, Sigma-Aldrich Chemie GmbH, Taufkirchen, Germany), PhosSTOP (Roche GmbH, Grenzach-Wyhlen, Germany) and complete Mini (Roche GmbH, Grenzach-Wyhlen, Germany). Then, 40 mg of tissue was lysed with 800 µL of the prepared RIPA buffer. After homogenization on ice, samples were loaded onto QIAshredder columns (QIAGEN GmbH, Hilden, Germany) and centrifuged at 2000 rpm at 4 °C for 2 min. Lysates were stored at −80 °C until analysis.
Next, 5 µL lysate was mixed with 5.5 µL Laemmli buffer (4x Laemmli Sample Buffer, #1610747, Bio-Rad Laboratories GmbH, Feldkirchen, Germany), 2.2 µL dithiothreitol and 9.3 µL aqua destillata, respectively. Prepared samples were boiled at 100 °C for 5 min. Then, 15 comb $12\%$ gels (TGX Stain-Free™ FastCast™ Acrylamide Kit, $12\%$, #1610185, Bio-Rad Laboratories GmbH, Feldkirchen, Germany) were loaded with 20 µL of the sample per lane. Proteins were then separated through sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). Using the ChemiDoc™ MP Imaging System (Bio-Rad Laboratories GmbH, Feldkirchen, Germany), stain-free shots were visualized. With the Trans-Blot® Turbo™ Transfer System (Bio-Rad Laboratories GmbH, Feldkirchen, Germany), proteins were transferred onto Polyvinylidenfluorid (PVDF) membranes and then blocked with $5\%$ bovine serum albumin for 1 h at room temperature. Membranes were incubated with primary antibodies (Caspase-3: #14220; phosphorylated Erk$\frac{1}{2}$: #9101; Erk$\frac{1}{2}$: #9102; pAkt: #9271; Akt: #4691; Cell Signaling Technology, Leiden, The Netherlands; Vinculin: V9131, Sigma-Aldrich Chemie GmbH, Taufkirchen, Germany) for 2 h at room temperature or overnight at 4 °C, followed by appropriate secondary antibodies (anti-rabbit: #7074, Cell Signaling Technology, Leiden, The Netherlands; anti-mouse: GENXA931-1ML, Sigma-Aldrich Chemie GmbH, Taufkirchen, Germany). Bands were visualized by use of ECL (ECL™ Prime Western-Blot-System, GERPN22332, Sigma-Aldrich Chemie GmbH, Taufkirchen, Germany). Integrated density values (IDV) for each protein band were calculated using the Image Lab software (Bio-Rad Laboratories GmbH, Feldkirchen, Germany), and normalized to the total protein amount using Stainfree technology, as described previously [31].
## 2.7. Oxidative Stress
Serum samples were tested for oxidative stress by measuring the static oxidation-reduction potential (ORP) and the antioxidant capacity (AC) using the RedoxSYS Diagnostic SystemTM (Aytu BioScience, Inc., Englewood, CO, USA). This method was previously established by our group [16,22].
## 2.8. Histology
Needle biopsies were taken using a 14G Tru-Cut needle (Merit Medical Systems, South Jordan, UT, USA) before perfusion, fixed in $4\%$ buffered formalin for 7 days, and embedded in paraffin. Tissue samples from renal cortex and medulla, collected after 6 h NMP (Figure 1b), were processed similarly. Four-micron sections were stained with periodic acid–Schiff reaction (PAS).
All analyses were performed by a senior pathologist, blinded for timepoint and group. The tubular injury was assessed on a scale of 0–3 as follows: [0] no injury; [1] slight tubular injury; [2] prominent tubular injury; [3] and necrotic cell injury. Tubular vacuolization was determined dependent on the percentage of vacuolization-affected tubules on a scale of 0–4; [0] 0–$1\%$; [1] 2–$15\%$; [2] 16–$50\%$; [3] 51–$75\%$; and [4] 76–$100\%$.
## 2.9. Characterization of Ecosol before and after Perfusion
During perfusion, gel formation occurred on kidneys perfused with Ecosol, therefore, the composition of Ecosol and the structure of the formed gel after 6 h NMP using Ecosol were characterized by Fourier Transform Infrared (FTIR) spectroscopy with Thermo Nicolet Nexus 470 FTIR spectrometer (Thermo Fisher Scientific Inc., Waltham, MA, USA) on Attenuation Total Reflection (ATR) mode using silicon crystal. Data were analyzed using the Origin Pro (version 9.5.5) software.
Gel Permeation Chromatography (GPC) measurements were further used to analyze the molecular weights of the aqueous Ecosol components, which were taken on one precolumn (8 × 50 mm) and three Suprema-Lux gel columns (8 × 300 mm) at 40 °C at a flow rate of 1.0 mL min−1 using an Agilent 1200 system. The diameter of the gel particles measured 5 μm, where the nominal pore widths were 30, 1000, and 1000 Å. An aqueous solution of 0.05 wt% sodium azide (NaN3) was used as an eluent. Calibration was achieved using narrow-distributed polyethylene glycol (PEG) standards. The GPC data were analyzed using the WinGPC UniChrom program (version 8.3.2).
Prior to analysis, Ecosol was purified by dialysis against distilled water for a day and freeze-dried. Likewise, the formed gel mass was thoroughly washed with distilled water followed by freeze-drying before the measurement.
## 2.10. Statistical Analysis
Statistical analysis was performed using GraphPad Prism 9.4.1 software package (GraphPad Software Inc., San Diego, CA, USA). After Kolmogorov–Smirnov normality test, two-way analysis of variance (ANOVA) for multiple comparisons was used followed by Šídák post-test correction for all measurements of perfusion, oxygenation, kidney injury, and oxidative stress markers. For kidney weights, WB and ELISA data, one-way ANOVA-test was carried out. Data are presented as mean ± standard error of the mean (SEM) and p-values < 0.05 were considered significant.
## 3.1. Perfusion Parameters
The pH was similar in both perfusates prior to connection of the kidney (pRBC; 7.309 ± 0.014 vs. Ecosol; 7.327 ± 0.012) (Figure 2a), after which the pH in the pRBC group increased significantly over time, reaching 7.526 ± 0.016 at $t = 360$ min and remaining significantly higher than the Ecosol group from 60 min ($p \leq 0.0002$). In contrast, the pH in the Ecosol group remained stable during 6 h perfusion, except at 5 min after the start of perfusion.
Arterial flow (Figure 2b) remained stable in both groups throughout 6 h NMP and did not differ at any timepoint.
Intrarenal resistance in both groups did not differ, except at $t = 5$ min, where Ecosol was higher compared to the pRBC group ($$p \leq 0.0275$$).
Urinary flow (Figure 2d) differed between the groups only at the start of perfusion ($t = 5$ min) with 2.4 ± 1.2 mL/min vs. 7.9 ± 3.5 mL/min (pRBC vs. Ecosol resp., $$p \leq 0.01$$). Peak urinary flow was reached in both groups at 30 min (9.8 ± 2.3 mL/min in pRBC and 13.4 ± 2.2 mL/min in Ecosol).
## 3.2. Oxygenation
During NMP, supraphysiological pO2 values were achieved in both groups with average values of 473.1 ± 9.4 mmHg in pRBC and 451.9 ± 7.6 mmHg in Ecosol (Figure 3a).
HIF-1α was used as an indicator for hypoxic conditions, as it is an important regulator for downstream processes in cells suffering from hypoxia. No significant correlation could be found between HIF-1α levels and the perfusion groups (Figure 3b,c). In RC and IS samples, HIF-1α levels were comparable, but significantly higher than those in IM tissue samples ($p \leq 0.05$).
## 3.3. Markers of Kidney Injury
For a rough estimation of kidney damage, perfusate concentrations of lactate, AST, LDH, and urine protein were evaluated. Lactate levels (Figure 4c) increased significantly, from 0.9 ± 0.07 to 6.57 ± 0.85 mmol/L (pRBC) and from 0.07 ± 0.02 to 7.06 ± 0.42 mmol/L (Ecosol). Within the initial 30 min of perfusion, lactate levels were significantly higher in pRBC, and in Ecosol from 240 to 300 min. Similarly, AST (Figure 4a) and LDH (Figure 4b) levels rose in both groups over time. There were no differences in AST levels; however, LDH levels were higher in pRBC from 60 min until the end of perfusion ($p \leq 0.04$). Urine protein concentrations (Figure 4d) were higher in pRBC compared to Ecosol at $t = 5$ ($p \leq 0.01$), $t = 300$ and $t = 360$ ($p \leq 0.01$). IL-6 levels did not differ between the groups (Figure 4e).
## 3.4. Antioxidative Properties of the Perfusates
The antioxidant capacity (Figure 5a) was higher in the Ecosol group than in the RBC group ($p \leq 0.001$). It remained stable until the end of perfusion in the Ecosol group, whereas it increased over time in the RBC group. The oxidation-reduction potential (Figure 5b) was lower in Ecosol perfused kidneys in contrast to pRBC during perfusion ($p \leq 0.001$); however, it constantly increased, as opposed to a decrease seen in the RBC group.
## 3.5. Electrolytes and Glucose
Electrolyte and glucose levels during 6 h perfusion, compared to standard values are displayed in Table 1. In both groups, K+ levels during 6 h perfusion were higher than the standard value (Table 1), which can partly be explained by the protocol for sacrificing experimental animals using sodium pentobarbital and potassium (782 mg) mixture. Overall, no physiological ranges of electrolytes or glucose levels were sustained for the duration of perfusion.
## 3.6. Macroscopic Kidney Appearance and Perfusate Composition
Kidney function was approximated by creatinine clearance rates (Figure 6d). In the pRBC group, CrCl was shown to peak at 60 min with 24.98 ± 4.53 mL/min followed by a constant decrease and was higher than in Ecosol in the first 3 h of perfusion ($p \leq 0.03$). However, perfusate as well as urinary creatinine concentrations were lower in Ecosol perfused kidneys, suggesting loss of creatinine, as added concentrations were similar.
Additionally, formation of a gel-like mass appeared around the hilus in Ecosol perfused kidneys. After removing the mass from the kidney samples, it still maintained its gel-like properties and was insoluble in water or any other standard organic solvents at room temperature, implying an irreversible fully cross-linked structure of the mass. Since the colloidal component of Ecosol preventing extravasation of the solution is polyethylene glycol (PEG), the formation of the gel mass was hypothesized to result from the accumulation of a lower Mw PEG than the specified PEG 35 kDa in the Ecosol solution supplied by the manufacturer.
As shown in Figure 6a, the structure analysis of the Ecosol prior to perfusion measured by FTIR spectroscopy mainly revealed the characteristic signals of a typical non-functionalized PEG as a base component; however, the FTIR analysis of the Ecosol after perfusion (the formed gel) shows some structural changes. Particularly the presence of an additional carbonyl bond (−C=O) at 1737 cm−1 is evident. Furthermore, the evaluation of the Ecosol molecular weight analyzed by GPC confirmed the presence of different molecular weights with a Mw of 1–10 kDa and the absence of higher Mw PEG (Figure 6b).
The inhomogeneous composition of the Ecosol due to the wrong-sized polymers or any other polymer impurities might explain the unexpected behavior of PEG leading to crosslinking (gelation). Possibly, creatinine was further intercepted by the formed Ecosol gel as the presence of carbonyl in the gel structure can be correlated to the interaction with creatinine. Therefore, it led to the lack of efficient creatinine clearance in the Ecosol group.
Kidney weights (Figure 6c) did not differ in both experimental groups prior to perfusion. However, after perfusion kidney weights increased significantly compared to the initial weights ($p \leq 0.0001$). Moreover, kidney weights after perfusion differed significantly between the groups, with a significantly higher weight gain in the Ecosol group ($p \leq 0.001$).
## 3.7. Apoptosis in Different Areas of the Kidney after NMP
For the determination of apoptosis, uncleaved Casp 3, phosphorylated ERK to ERK (pERK/ERK) and phosphorylated AKT to AKT (pAKT/AKT) ratios were measured (Figure 7a–d).
Overall, the levels of uncleaved Casp 3 were higher in the Ecosol group than in the pRBC group. Levels of Casp 3 in RC and IS samples were significantly lower in pRBC compared to Ecosol kidneys ($p \leq 0.03$). Significantly less Casp 3 was found in IM than in RC and IS samples of the Ecosol group ($p \leq 0.05$). Cleaved Casp 3 could not be found in any sample.
The levels of pERK/ERK showed no difference between the Ecosol and pRBC groups. Within Ecosol, pERK/ERK was significantly higher in IM compared to RC as well as IS tissue samples ($p \leq 0.01$).
In samples of IM, pAKT/AKT was significantly higher in pRBC kidneys than in Ecosol kidneys ($$p \leq 0.0005$$). RC and IS samples showed a tendency for pAKT/AKT being higher in pRBC, which could not be confirmed by statistical significance.
## 3.8. Tissue Damage as Observed through Pathology
All kidneys showed diffuse and prominent acute tubular damage with different extents of tubular vacuolization (Figure 8a,b). The most common finding was tubular dilatation, loss of brush borders, as well as flattening of tubular cells. Some tubules demonstrated cell swelling and vacuolization. Kidneys perfused with pRBC depicted the anisometric vacuolization of tubular cells, with more flattened tubules and some single large vacuoles. Interstitial hemorrhages, thrombi or vascular injuries were not observed. Necrosis was only observed in some single spots in Ecosol perfused kidneys. The tubular injury severity score did not differ significantly between the groups before perfusion (0.75 ± 0.5 in pRBC vs. 0.75 ± 0.5 in Ecosol). However, kidneys in the Ecosol group scored significantly higher than kidneys in the RBC group after 6 h perfusion (Figure 8c; $$p \leq 0.0152$$) with a mean tubular injury severity score of 2.57 ± 0.45 compared to 2.00 ± 0.00. The extent of tubular vacuolization was comparable between the groups (0.75 ± 0.5 in pRBC vs. 1 ± 0.63 in Ecosol) before perfusion and higher ($p \leq 0.0001$) in pRBC after perfusion, with a mean score of 4.00 ± 0.00 compared to Ecosol.
## 4. Discussion
Scientific efforts regarding preservation and conditioning techniques for organ transplantation are increasing. Among working groups, a wide spectrum of different and complex perfusion protocols exists, demanding simpler solutions. Considering the opportunity of organ conditioning during NMP, perfusion solutions aiming to ameliorate tissue damage, such as Ecosol, could offer a great benefit in restoring organ viability.
Here, we compared Ecosol, a cell- and oxygen carrier-free preservation solution, containing the potent antioxidant taurine, to the clinically applied pRBC-based buffer solution for 6 h NMP of porcine kidneys. The major and novel finding is that Ecosol was able to provide stable perfusion parameters, such as RBF, pH, and constant urine production during 6 h of NMP. Most importantly, oxygenation was sufficient even without an oxygen carrier, preventing the shift to hypoxic conditions. This was indicated by comparable perfusate pO2 levels and HIF-1α levels in both groups. The overall kidney damage in the Ecosol group was, as represented by AST and lactate perfusate levels, comparable to the pRBC group, and better with regard to LDH and urine protein concentrations. The antioxidative potential of Ecosol, provided via taurine, was better than the pRBC-based perfusate, as expressed by a higher antioxidative capacity (AC) and lower oxidation-reduction potential (ORP). The formulation of Ecosol could be improved for NMP, since electrolyte and glucose levels were outside physiological ranges and an insufficient colloid-osmotic pressure was present due to a lower than specified PEG Mw. This led to extensive tissue edema, the formation of gel deposits on the kidney surface and high IRR, potentially causing aggravation of kidney damage and an increase of apoptosis as shown in WB analysis. Nevertheless, the overall performance of the kidneys after 6 h of NMP was still comparable between the two experimental groups.
NMP has been increasingly employed over the last decades for investigating kidney viability and the restoration of graft function. NMP provides a unique opportunity for functional organ assessment and predicting short-term transplantation outcome [7,8]. However, the variety of different perfusion protocols and lack of established, objectifying parameters impede prediction of long-term transplantation outcomes. Kaths et al. found that perfusate AST might be an important marker of renal graft function, as post-transplantation outcomes correlate with AST levels during NMP [32] and Hosgood et al. implemented a simple scoring system for functional assessment based on macroscopic appearance, arterial blood flow and urine flow [33]. Unifying NMP protocols could facilitate the search for more reliable parameters to assess organ viability. A step towards that goal might be the use of an elementary and ready to use perfusion solution for NMP procedures, such as Ecosol.
Cell free perfusion mediums have been tested previously in various NMP settings and have been proven to be feasible for kidney perfusion [17,18,19]. Minor et al. demonstrated that an Aqix RS-I cell free solution allowed for 2 h end-ischemic machine perfusion, rewarming grafts in a controlled fashion prior to NMP [17]. The Lifor solution was shown to protect rat kidneys from warm ischemia reperfusion injury in situ as well as from cold storage injury [18]. Additionally, beneficial effects of perfusion at room temperature were observed in a porcine DCD kidney model [19]. In line with these findings, an Ecosol perfusate performed comparable to a pRBC-based perfusate for 6 h NMP of DCD kidneys.
The impact of an insufficient colloid-osmotic pressure due to a too low Mw of the PEG component in the Ecosol solution used for this study, as demonstrated by FTIR and GPC analysis, was not only expressed by extensive tissue edema and significant weight gain. The soluble creatinine in the perfusate accumulated within the PEG containing gel mass found on the organ grafts, resulting in a lower CrCl compared to the pRBC group. Nevertheless, at 6 h of NMP, the CrCl rates were comparable between the two groups. PEG weights lower than 20 kDa lack the colloidal capacity required for successful NMP and prevention of extravasation of the perfusate. The detrimental effects of MW were demonstrated by Neuzillet et al. [ 34]. Additionally, the use of higher PEG MW > 10 kDa between 1 g/L to 30 g/L preserves the graft integrity and reduces antigen allorecognition, as shown by Giraud et al. [ 35]. All these findings are in line with morpholigical changes observed in kidneys with Ecosol in our study.
A main concern of using an oxygen carrier-free solution is the ability to sufficiently provide the kidney graft with oxygen. Due to the use of carbogen over a clinically employed oxygenator, supraphysiological pO2 levels were achieved in both pRBC and Ecosol kidneys, resulting in comparable perfusate HIF-1α levels. HIF-1α is a transcription factor regulating oxygen-dependent cell responses. Under hypoxic conditions, the oxygen-sensitive HIF-1α is not ubiquitinated, hence avoiding proteasomal degradation. This leads to accumulation of the transcription factor and binding to specific DNA sequences in hypoxia-regulated genes [36,37,38]. Comparable levels of HIF-1α in Ecosol and pRBC are therefore suggestive of sufficient oxygen supply by the cell- and oxygen carrier-free Ecosol solution. It could be argued that 6 h of NMP may not be long enough for regulating mechanisms to become apparent. However, Rosenberger et al. found that following hypoxic conditions, HIF-1α upregulation becomes evident within approximately 2 h [39], thus in our setting, changes in HIF-1α should have been seen.
The proinflammatory cytokine IL-6 plays an important role in inflammatory processes during reperfusion. It is upregulated in the kidney in response to ischemic injury and correlates with adverse transplantation outcomes [40,41]. However, IL-6 levels need to be interpreted cautiously, as it has both pro- and anti-inflammatory properties [40,41,42]. Recently, De Beule et al. found that the cytokine levels between kidneys perfused with whole blood and those perfused with pRBCs did not differ significantly [43]. As pRBCs are deprived of leukocytes, one would assume that the inflammatory response is milder in comparison to whole blood. As that assumption cannot be confirmed by De Beule et al. ’s findings, the question is raised if the cytokine expression measured in NMP studies, is not influenced by different perfusates. Accordingly, we did not observe differences, suggesting that IL-6 expression is rather associated with intrinsically available leukocytes than with those added by blood products. Nevertheless, perfusion with Ecosol did not aggravate inflammatory processes more than perfusion with pRBCs.
Acute kidney injury (AKI), as emerging during NMP, is not only associated with inflammation, but with reactive oxygen species (ROS) formation as well [44]. ROS, generated by nicotinamide adenine dinucleotide 3-phosphate oxidase 4 (Nox4), were shown to be crucial in the generation of contrast-induced AKI in in vivo and in vitro models [45]. Ecosol contains taurine as an antioxidant to reduce ROS formation during NMP. To quantify the effect of taurine on oxidative stress in our NMP setting, AC and ORP were measured, according to Rael et al. and Panighrani et al. [ 46,47]. In the pRBC group, the AC increased almost linearly over time. This finding is explainable by the constant administration of Cernevit, containing antioxidants such as vitamin C, to the pRBC perfusate. The higher AC and decreased ORP in Ecosol compared to pRBC might be due to taurine, only present in Ecosol.
Taurine is a semi-quantitative beta-amino acid and in taurine transporter knockout mice, its antioxidative, antiapoptotic properties were shown [48]. Taurine also proved to be organoprotective in cardiovascular, nervous, retinal, and renal tissues in preclinical and clinical studies [28,29,49,50,51]. Thus, taurine plays a crucial, cytoprotective role in various conditions, such as reperfusion injury [52]. In models of myocardial ischemia and reperfusion injury after coronary bypass surgery, taurine supplementation prior to the intervention showed beneficial effects on the injury size and heart function [49]. Two main arguments led to supplementing kidney NMP with taurine. [ 1] The renoprotective properties of taurine are well-established [29,53,54]. [ 2] The supplementation of a preservation solution with taurine and glutathione (GSH) reduced lipid peroxidation and vascular resistance in liver oxygen persufflation preservation models [26,55]. All the components necessary to synthesize GSH are incorporated in Ecosol: glutamate, cysteine, and glycine. In comparison to taurine, the concentrations of GSH components are much lower, so that the effect strength of GSH is postulated to contribute to a much lesser extent to Ecosol’s antioxidative characteristics.
Contrary to expectations, the antioxidative properties were not able to directly mitigate tissue damage and initiation of apoptosis, as shown by the higher tubular injury score and Casp 3 levels in Ecosol compared to pRBC. Similarly, normothermically perfused kidneys did not derive benefits from the addition of vitamin C to the perfusate, as shown by a preceding study [16]. The tubular vacuolization observed mainly in the pRBC group could be linked to hyperglycemia occurring in the pRBC-based perfusate, thus being a sign of osmotic nephropathy. Inducing renal hypoxia, volume depletion and ultimately ROS formation via osmotic diuresis hyperglycemia directly causes renal injury [56,57]. This could have contributed to the lower AC and higher ORP in the pRBC group.
On the protein level, the addition of taurine to Ecosol was reflected by a slightly favorable antiapoptotic status observed in Ecosol kidneys. Casp 3, pAkt/Akt, and pERK/ERK signaling were analyzed in renal tissue samples collected after 6 h NMP. High Casp 3 levels would have been expected to be reflected in more extensive tissue damage. Opposingly, neither the beneficial antioxidant capacities in the Ecosol group, nor the better histological tubular injury score in the pRBC group could be explained by the high Casp 3 levels in the Ecosol group. Cleaved Casp 3 was not detected in WB analysis, although the antibody is specific for both full-length and cleaved Casp 3. Consequently, upregulation of caspase 9 is likely missing, as it is responsible for Casp 3 cleavage [58]. As we did not find effector fragments in neither of the groups, no statement can be made on the apoptotic status of the analyzed renal tissue. However, a better-preserved cell status in Ecosol perfused kidneys could be assumed, as taurine potentially has a predominant role in this mechanism [59]. This leads to the assumption that Ecosol as an acellular perfusate in its present formulation (including low Mw PEG), is not superior in terms of cellular damage, but still not inferior to the pRBC-based perfusion in NMP settings, with the potential to be an efficient NMP solution in a modified version. In good agreement with this, no significant differences in pAkt/Akt and pERK/ERK signaling were observed between the groups.
Our study is limited in several aspects. First, the relatively small number of kidney grafts in the experimental groups ($$n = 7$$) as well as the use of porcine kidneys calls for the careful interpretation of results. Additionally, our study only assessed kidney function during NMP, and the kidneys were not transplanted. The performance of Ecosol was impaired by containing PEG with a lower Mw than specified by the manufacturer, making only general statements to its feasibility possible. The euthanasia protocol probably influenced the perfusate electrolyte concentrations. Lastly, whether kidney function during NMP with a cell- and oxygen carrier-free perfusion will translate into long-term graft function remains to be explored. Although all findings suggest that the use of Ecosol in our NMP setting leads to comparable perfusion outcomes, the relevance of these findings should further be investigated into extended NMP periods and transplantation of the perfused graft.
## 5. Conclusions
The cell- and oxygen carrier-free Ecosol preservation solution has the potential to become an effective NMP perfusate if the colloid-osmotic pressure can be improved by increasing the Mw of PEG.
Further studies involving transplantation models are required to elucidate the influence of perfusates and antioxidants used for NMP in relation to post-transplant outcomes.
Taken together, the findings of this study support the aim to optimize a cell- and oxygen carrier-free perfusion solution, since the general feasibility of oxygen carrier-free NMP was demonstrated.
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|
---
title: Radiation-Induced Nephropathy in the Murine Model Is Ameliorated by Targeting
Heparanase
authors:
- Alexia Abecassis
- Esther Hermano
- Kim Sheva
- Ariel M. Rubinstein
- Michael Elkin
- Amichay Meirovitz
journal: Biomedicines
year: 2023
pmcid: PMC10045137
doi: 10.3390/biomedicines11030710
license: CC BY 4.0
---
# Radiation-Induced Nephropathy in the Murine Model Is Ameliorated by Targeting Heparanase
## Abstract
Agents used to reduce adverse effects common in cancer treatment modalities do not typically possess tumor-suppressing properties. We report that heparanase, an extracellular matrix-degrading enzyme, is a promising candidate for preventing radiation nephropathy. Heparanase promotes tumor development and progression and is upregulated in tumors found in the abdominal/pelvic cavity, whose radiation treatment may result in radiation nephropathy. Additionally, heparan sulfate degradation by heparanase has been linked to glomerular and tubular/interstitial injury in several kidney disorders. In this study, heparanase mRNA levels were measured in HK-2- and HEK-293-irradiated kidney cells and in a murine radiation nephropathy model by qRT-PCR. Roneparstat (specific heparanase inhibitor) was administered to irradiated mice, and 24 h urinary albumin was measured. Kidneys were harvested and weighed 30 weeks post-irradiation. Clinically relevant doses of ionizing radiation upregulated heparanase expression in both renal cells and mice kidneys. A murine model of abdominal radiation therapy revealed that Roneparstat abolished radiation-induced albuminuria—the hallmark of radiation nephropathy. Given the well-documented anti-cancer effects of heparanase inhibition, our findings attest this enzyme to be a unique target in cancer therapy due to its dual action. Targeting heparanase exerts not only direct anti-tumor effects but protects against radiation-induced kidney damage—the backbone of cancer therapy across a range of malignancies.
## 1. Introduction
Radiation nephropathy (RN) is a significant side effect of radiation therapy when used in the treatment of pelvic malignancies such as gastrointestinal cancers, gynecologic cancers, lymphomas, sarcomas of the upper abdomen and total body irradiation [1]. The underlying mechanisms of RN pathogenesis as well as the mediators responsible for the deterioration of kidney function have not been fully elucidated. The notion that RN is mediated solely by DNA damage-related cell loss at division, and therefore is potentially unavoidable, has been transformed. This is due to the recognition that radiation-induced injury also involves complex and dynamic interactions between various cellular components (i.e., glomerular, tubular and interstitial) as well as the extracellular matrix (ECM) of renal tissue [2,3].
Heparanase is the sole mammalian endoglycosidase capable of degrading heparan sulfate (HS)—the principal polysaccharide of the ECM and cell surfaces in a wide range of tissues. HS chains play an important role in ECM integrity, barrier function and cell–ECM interactions, providing a structural framework for proper tissue organization and architecture. The heparanase-mediated cleavage of HS is best studied in the context of malignant tumor progression, where the enzyme has been shown to promote tumor growth and therapy resistance through multiple mechanisms. Heparanase overexpression (driven in human cancers by numerous molecular pathways [4,5,6,7,8]) is closely associated with enhanced aggressiveness and a poorer prognosis in several types of tumors, notably gastric [9]; colon [4]; ovarian [5] and cervical [6] carcinoma and retroperitoneal sarcoma [10]. These are precisely the tumor types where radiotherapy may lead to kidney damage and RN. These findings have highlighted the potential of heparanase to be a promising drug target, and heparanase-inhibiting compounds are currently being evaluated in clinical trials as anti-cancer drugs [11,12].
More recent studies have highlighted the pathogenic role of heparanase-mediated HS cleavage in renal disorders. In the kidney, HS contributes to the integrity and barrier functions of the basement membrane and glycocalyx, regulation of inflammatory responses and control of the availability of HS-binding chemokines, cytokines and growth factors sequestered in the ECM [13,14]. The degradation of HS by heparanase therefore has a significant effect on the development and progression of numerous kidney pathologies associated with both glomerular and tubular/interstitial injury [14,15,16]. The pathogenic action of heparanase involves damaging the glomerular filtration barrier function, fostering inflammation-mediated renal injury and promoting vessel destabilization and tubulo-interstitial fibrosis [14,15,16,17]. The induction of heparanase expression and enzymatic activity has been demonstrated in animal models of glomerulonephritis (i.e., puromycin amino–nucleoside-induced nephrosis and passive Heymann nephritis), adriamycin nephropathy, anti-glomerular basement membrane nephritis, diabetic nephropathy and acute kidney injury, as well as in patients with diabetic nephropathy, IgA nephropathy, minimal change disease, C3 nephropathy, lupus nephritis, membranous glomerulopathy, nondiabetic nephrotic syndrome and chronic kidney diseases, and kidney-transplanted patients. Moreover, heparanase deficiency eliminated the development of albuminuria and renal damage in mouse models of diabetic nephropathy and glomerulonephritis, while the neutralization of enzyme activity by specific inhibitors resulted in reduced proteinuria in animal models of diabetic and non-diabetic proteinuric kidney diseases [14,15,16]. Based on mounting evidence implicating heparanase in renal dysfunction, along with observations of clinically relevant doses of ionizing radiation (IR) inducing heparanase expression in certain cell types [18], we hypothesized that heparanase mediates the kidney-damaging effect of IR and could therefore serve as a potential therapeutic target for RN.
## 2. Materials and Methods
In vitro irradiation: HK-2 human proximal tubule epithelial cells [17] and HEK-293 human embryonic kidney cells (ATCC, Manassas, VA, USA) were routinely maintained in DMEM supplemented with 1 mM glutamine, 50 µg/mL streptomycin, 50 U/mL penicillin and $10\%$ fetal calf serum (FCS) at 37 °C and $7.5\%$ CO2. Prior to irradiation, cells were maintained for 16 h in serum-free medium and then irradiated using a 60Co Picker unit irradiator (1.56 Gy/min).
In vivo irradiation and murine radiation nephropathy model: Based on previous murine RN models [19,20,21], eleven-week-old female C3H/HeNHsd mice were housed under SPF conditions and received regular chow and water ad libitum. A dose of 10 Gy radiation (previously reported to induce radiation nephropathy in murine models [22]) was delivered to the anaesthetized mice via a brachytherapy afterloader (I192 Nucletron microSelectron HDR, Veenendaal, The Netherlands) using a bronchial sleeve applicator. On the bronchial sleeve, 1 cm dwell points were marked 1 cm apart with a 10 cm distance between each set of markers. Up to 5 sets were placed on each sleeve. These markers corresponded to the location of the kidneys inside the mice. The dose was calculated based on a 1.0 cm isodose line, with a 0.5 cm width silicon bolus placed above and below the sleeve to ensure dose homogeneity. The treatment field was designed to cover a specific banded area across the abdomen that included both kidneys, while shielding the rest of the body. The prescribed radiation dose was confirmed by film dosimetry. Variation in the dose within the kidneys was estimated to be within ±$10\%$ of the prescribed dose.
Subcutaneous injections of Roneparstat (kindly provided by Alessandro Noseda, Leadiant Biosciences S.p. A, Rome, Italy) were administered to mice in the experimental group (300 µg in 100 µL saline/mouse/injection, twice a day). Mice in the control group were injected with saline alone. For urine collection at indicated time points, mice were placed in metabolic cages for 24 h. Urinary albumin was measured using an ELISA kit (Bethyl Laboratories Inc, Montgomery, TX, USA).
Reverse transcription and quantitative RT-PCR (qRT-PCR): RNA isolation from both the cultured cells and the snap-frozen kidney tissue samples, and qRT-PCR, were performed as previously described [18]. The following primers were used: Human heparanase: Sense 5′-GTTCTAATGCTCAGTTGCTCCT-3′, Antisense 5′-ACTGCGACCCATTGATGAAA-3′; Mouse heparanase: Sense 5′-GGAGCAAACTCCGAGTGTATC-3′,
Antisense 5′-CAGAATTTGACCGTTCAGTTGG-3′; and Human Egr1: Sense 5′-GAGCAGCCCTACGAGC-3′ Antisense 5′-AGCGGCCAGTATAGGT-3′.
Ethical approval: All animal experiments were approved by and performed in accordance with the Hebrew University of Jerusalem’s Institutional Animal Care and Use Committee.
## 3. Results
IR induces the expression of heparanase in cells of kidney origin in vivo. HK-2 and HEK-293 cells either remained untreated or were treated with clinically relevant doses of IR, after which heparanase mRNA levels were determined by qRT-PCR. As shown in Figure 1, a significant increase in heparanase expression was detected following cell exposure to IR.
The early growth response (Egr1) transcription factor has been previously shown to upregulate the expression of the heparanase gene by binding specifically to its regulatory region [23]. Additionally, IR has been reported to induce Egr1 in tumor-derived cells [24,25]. Interestingly, using qRT-PCR, we detected that IR upregulates Egr-1 levels in both HK-2 and HEK-293 cells (Figure 1C,D), suggesting that an Egr-1-dependent mechanism is responsible for radiation-induced heparanase expression in kidney cells.
IR upregulates renal heparanase expression in vivo. The above findings prompted an examination of the effect of IR on renal heparanase expression in vivo. For this purpose, experimental mice either remained untreated or were treated with bilateral kidney irradiation, as described in the methods section. Forty-eight hours post irradiation, the mice were sacrificed, their kidneys were excised, and heparanase expression in the renal cortex was assessed by qRT-PCR. As can be seen in Figure 2, a significant increase in heparanase expression was readily detected in the renal cortex of irradiated mice as compared to age-matched, non-irradiated, control mice. This confirms the ability of radiation to induce renal heparanase expression.
The inhibition of heparanase abolishes radiation-induced albuminuria in a murine model of RN. Next, we investigated the effect of the specific heparanase inhibitor Roneparstat (SST0001) on the development of proteinuria in irradiated mice. To investigate the effect of heparanase inhibition on RN, we utilized a well-characterized C3H/HeNHsd mouse model [22]. RN was induced using bilateral kidney irradiation (10 Gy) for a relatively conformal radiation dose with minimal exposure and damage to the bowel, which is crucial for long-term survival of the mice as well as clinical relevance of the experiment. Age-matched, non-irradiated mice were used as a control. Irradiated mice were treated with either Roneparstat or the vehicle control (saline) and 24 h albumin excretion was assessed at weeks 10, 20 and 30 of the experiment. As shown in Figure 3, at week 20, a marked and statistically significant increase in 24 h albumin excretion was noted in saline-treated irradiated vs. non-irradiated mice ($$p \leq 0.032$$). Interestingly, the administration of Roneparstat diminished this increase, where corresponding values of 24 h albumin excretion did not increase significantly in irradiated Roneparstat-treated mice as compared with the basal levels observed in non-irradiated mice (Figure 3). A significant difference in 24 h albumin excretion between saline-treated irradiated and non-irradiated control mice, but not between Roneparstat-treated and control mice, was maintained on week 30 of the experiment (Figure 3). Kidney irradiation also resulted in an absolute renal weight reduction of $10.5\%$ in saline-treated mice as compared to IR-untreated mice at 30 weeks (although the differences between these groups did not reach statistical significance) (Figure 3).
## 4. Discussion
Radiation therapy forms one of the cornerstones of anticancer treatment modalities for a range of malignancies. Currently, more than $60\%$ of cancer sufferers undergo radiation therapy either as a monotherapy or, more commonly, in combination with either chemotherapy or surgery [26,27]. Although ionizing radiation is highly effective in controlling tumor growth and prolonging overall survival, the exposure of healthy tissue to the radiation field results in unavoidable adverse effects. Despite advances in radiation delivery techniques, limiting ionizing radiation exposure to only cancerous tissues remains a major challenge [28]. Due to the proximity of the pelvic region to the kidneys, RT for the treatment of any pelvic malignancies carries the risk of inducing radiation nephropathy (RN). RN is a kidney injury caused by exposure to ionizing radiation that usually presents as chronic kidney disease a few months post-RT, which has the potential to evolve into end-stage renal disease. The damaging features of RN have been found histologically in the vascular, glomerular and tubulointerstitial regions of the kidney [29]. There is a critical need to not only improve RT delivery techniques to limit the exposure of healthy tissue to IR, but also to reveal new potential therapeutic targets for novel treatment options for RN.
The radiation-induced expression of heparanase has been found in cancerous cells [18] and it was, therefore, of interest in this study to investigate whether a similar mechanism exists in cells of kidney origin. A significant increase in heparanase expression was, in fact, found in vitro using HK-2 and HEK-293 kidney cells following clinically relevant doses of exposure to IR. Among several factors controlling heparanase expression, the early growth response (Egr1) transcription factor acts as an activator for the expression of the heparanase gene in several cell types, including kidney cells, where it binds to the heparanase promoter and activates heparanase expression [23]. Notably, Egr1 is rapidly induced in response to IR in several cancerous cell lines [24,25]. The present study confirmed this notion, whereby IR was found to upregulate Egr-1 levels in kidney cells, implicating an Egr-1-dependent mechanism in radiation-induced heparanase expression. These results were confirmed in vivo in mice using bilateral kidney irradiation, where a significant increase in heparanase expression was seen in the renal cortex.
The induction of heparanase expression by IR in kidney cells both in vitro and in vivo, together with the known contribution of heparanase to the pathogenesis of several kidney disorders other than RN [14,15,16], led us to hypothesize that the inhibition of heparanase may prevent the progression of RN. To validate this hypothesis, the specific heparanase inhibitor known as Roneparstat was administered to irradiated mice and the resultant effect on the development of proteinuria was assessed. Roneparstat, a 15–25 kDa N-acetylated and glycol split heparin, is one of the most potent and widely studied heparanase inhibitors that effectively inhibits heparanase enzymatic activity in vitro and is devoid of the anticoagulant activity of unmodified heparin. The effectiveness of Roneparstat in inhibiting the pathologic action of heparanase in vivo has been demonstrated in heparanase-driven processes other than RN, including malignant tumor progression and numerous non-malignant conditions [30]. In this study, Roneparstat successfully reduced both radiation-induced 24 h albuminuria as well as kidney weight loss, showcasing not only its ability to slow RN progression, but also the prominent role of heparanase in this disease. These findings are in agreement with previous observations in mouse models of RN [31], as well as in clinical studies where a progressive decrease in kidney size was documented in patients that had undergone abdominal radiation therapy [32]. Importantly, the administration of Roneparstat diminished renal weight loss, further implicating heparanase in RN and validating the inhibition of this enzyme as a promising approach to mitigate renal radiation injury. A limitation of the present study is that possible differences in RN occurrence and response to heparanase inhibition based on sex were not addressed in the in vivo model.
It should be noted that the heparanase enzyme was previously linked to the development and progression of essentially all tumor types found in the abdominal/pelvic cavity whose radiation treatment may lead to RN (i.e., gastric [9]; colon [4]; ovarian [5] and cervical [6] carcinoma, pancreatic cancer [7,33], retroperitoneal sarcoma [10] and hepatobiliary tumors [34]). Moreover, in these tumor types, inhibitors of heparanase have exerted anti-cancer effects in preclinical models and are currently being tested clinically [34,35,36]. In the setting of the above-mentioned cancer types, our findings highlight heparanase as a unique target among the extracellular matrix molecules. Due to the dual action of heparanase, the inhibition of this enzyme, when administered concomitantly with radiation therapy, is expected to exert not only direct anti-tumor effects [8] but also to protect against kidney damage induced by radiation—the backbone of cancer therapy across a broad range of abdominal/pelvic malignancies. Further studies are warranted to validate this heparanase-based therapeutic approach and to optimally investigate its potential.
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|
---
title: 'The impact of preloaded intraocular lens implantation system (TECNIS iTec®)
in routine cataract surgery in China: a time-motion analysis'
authors:
- Xudong Song
- Jian Zhou
- Guangbin Zhang
- Songbai Jia
- Jun Yuan
- Ke Hu
- Xinhua Liu
- Mingbing Zeng
- Zhenyu Wang
- Baoying Tan
- Xingwei Lu
- Ailing Lin
- Xiaohan Hu
- Jianwei Xuan
journal: BMC Ophthalmology
year: 2023
pmcid: PMC10045151
doi: 10.1186/s12886-023-02858-9
license: CC BY 4.0
---
# The impact of preloaded intraocular lens implantation system (TECNIS iTec®) in routine cataract surgery in China: a time-motion analysis
## Abstract
### Objective
To evaluate the impact on surgical efficiency and labor time cost of preloaded intraocular lens (IOL) implantation system compared with manual IOL implantation system in age-related cataract surgery in China.
### Methods
This study was an observational, multicenter, prospective time-motion analysis. IOL preparation time, operation time, cleaning time, number and cost of cataract surgeries in eight participating hospitals were collected. The linear mixed model was used to explore factors associated with the difference in operation time between the preloaded IOL implantation system and the manual IOL implantation system. A time-motion model was constructed to convert the operation time cost saved by using preloaded IOL into economic benefits from hospital and social perspective, respectively.
### Results
There were 2,591 cases included in the study (preloaded IOL: 1,591 cases; manual IOL: 1,000 cases). The preloaded IOL implantation system was significant time-saving in both preparation time and operation time compared to the manual IOL implantation system (25.48s vs. 47.04s, $P \leq 0.001$ and 353.84s vs. 367.46s, $$P \leq 0.004$$, respectively). An average total of 35.18s can be saved by using preloaded IOL per procedure. The results of linear mixed model showed that the type of IOL was the main factor leading to the difference in preparation time between preloaded IOL and manual IOL implantation system. By switching from manual IOL to preloaded IOL, the model projected additional 392 surgeries can be performed each year and an increase in revenue of $565,282 per hospital, a $9\%$ increase from hospital perspective. And the annual productivity loss saved by using preloaded IOL was $3,006 in eight hospitals from perspective of society.
### Conclusion
Compared with manual IOL implantation system, the preloaded IOL implantation system reduces lens preparation time and operation time, which increases potential surgical volume and revenue, and reduces the loss of work productivity. This study provides real-world evidence to support the advantages of the preloaded IOL implantation system in improving efficiency of ophthalmic surgery in China.
## Introduction
Age-related cataract is an age-related lens opacity disease, which ranks first in the world as a major cause of blindness. With the increase of age, the number of patients with age-related cataract continues to grow as currently observed in China [1, 2]. Findings from a recent meta-analysis showed that the prevalence of age-related cataracts in Chinese males increased from $3.23\%$ at the age of 45 ~ 49 to $65.78\%$ at the age of 85 ~ 89, while the prevalence in females rose from 4.72 to $74.03\%$ in the corresponding age categories [3]. If left untreated, age-related cataract would eventually progress into severe visual impairment or blindness. At present, surgery is the only effective modality to treat cataract, and more than $75\%$ of patients can improve their visual acuity to more than 0.3 after surgery [4, 5].
Cataract surgery refers to the process of removing the opacified lens and then implanting a new intraocular lens (IOL). Successful cataract surgery is reflected in the safety, efficiency, long-term stability of the intraocular lens after implantation, and significant improvement in visual acuity. To achieve these goals, high-quality surgical equipment and IOL are needed. Traditional manual IOL need to be installed under a microscope or naked eyes using tools, such as folding clips and implants, before implantation. A study showed that when using manual IOL, the mean number of IOL physical touch of surgery equipment in each cataract surgery was 4 to 5 [6]. When physician’s assistant or nurse is not skillful in the preparation, wrong installation may occur. At the same time, the loading process increases the time of operation [7] and the risk of IOL contamination, which may lead to various complications, including anterior segment toxicity syndrome, endophthalmitis, severe intraocular tissue injury and severe vision loss or even blindness [8–10]. Conversely, the preloaded IOL implantation system is a non-contact and disposable IOL preloaded system, which avoids exposure to ambient air or physical touch of surgery equipment, minimizing the risk of infection and inflammation caused by contamination. A prospective, multicenter, parallel, single-blind, randomized controlled study in the United States showed that compared with manual IOL implantation system, patients with preloaded IOL implantation system had a smaller corneal incision size and a lower incidence of astigmatism caused by surgery [11].
Time-motion analysis, which is pioneered and developed by American industrial engineers [12], is one of the methods to study scientific management and benefits, and it is a research tool to improve and upgrade the working system. It was used to analyze each action involved in the study and its time in industrial processes in order to find out inefficient links and improve them. Time-motion analysis has also been employed by medical and health organizations to improve their operational efficiency and optimize the use of medical resources. A prospective observational study conducted in the United States, France, and Canada showed that compared to manual IOL implantation system, the preloaded IOL implantation system reduced total procedure time, total surgeon lens time and surgeon delays. The reduced operation time increased the surgical volume and reduced the possibility of IOL contamination and postoperative complications [6]. In China, there is no similar data on the time and motion of preloaded IOL implantation system for age-related contact surgery and the implications of adoption of preloaded IOL implantation system remain to be demonstrated.
This study is based on the time-motion analysis method to evaluate the effects of preloaded IOL implantation system (Product name: The TECNIS 1-Piece IOL with the TECNIS iTec®Preloaded Delivery System; Manufacturer: Johnson & Johnson Surgical Vision, Inc. China) and manual IOL implantation system on surgical efficiency and labor time cost for age-related cataract surgery in China. The study also quantified economic benefits associated with the time saved by using preloaded IOL system in terms of potential increased revenue and labor cost savings of the hospitals.
## Study design
This study was an observational, multicenter, prospective time-motion analysis. It compared the time spent of using preloaded IOL implantation system (TECNIS iTec®) with that of manual IOL implantation system in age-related cataract surgery. The numbers of operations and the cost of cataract surgery were collected through expert surveys. This study was conducted in 8 participating hospitals in 8 provinces in China from May 15, 2020 to June 30, 2021, including Beijing Tongren Hospital (Hospital A), Xijing Hospital (Hospital B), Xiamen Eye Center (Hospital C), The Second Xiangya Hospital of Central South University (Hospital D), Zhengzhou Second Hospital (Hospital E), the First Affiliated Hospital of Chongqing Medical University (Hospital F), Shenzhen Eye Hospital (Hospital G) and Hainan Branch of Zhongshan Ophthalmic Hospital (Hospital H). The study protocol was approved by the hospital ethics committee of the principal investigator (Beijing Tongren Hospital) and informed consent was obtained from all patients.
## Study population
The inclusion criteria were as follows: [1] patients undergoing phacoemulsification with IOL implantation for age-related cataract and [2] the preloaded IOL product used for the operation was The TECNIS1-Piece IOL with the TECNIS iTec® Preloaded Delivery System.
The exclusion criteria were as follows: [1] patients with glaucoma, diabetic fundus disease or other eye diseases or the manual intraocular lens used in surgery which was a disposable intraocular lens implantation system. [ 2] Abnormal time were screened based on InterQuartile Range [13] (IQR) principle. Abnormal time greater than the sum of the upper quartile and 1.5 times IQR were excluded.
## Data collection and linear mixed model
This study collected the IOL preparation time, operation time and cleaning time of each procedure. The preparation time of the IOL referred to the time when the IOL package was torn open until the IOL was successfully loaded into the implanter. The operation time referred to the time between surgeon’s first cut and completion of the watertight incision. The cleaning time referred to the time required for disinfection of the surgical instruments of a single operation after operation. The total procedural time included IOL preparation time and operation time. In addition, the operation-related information was collected, such as credentials of IOL preparation and cleaning staff (surgeon, surgical assistant, nurse, professional cleaning specialist) and Emery nuclear hardness grading (grade I, II, III, IV, V). Observers recorded the time spent in each step of the operation using a timer. Before conducting the study, the observers were trained on time measurement and use of measurement tools to ensure the reliability of data.
Through a survey of 8 experts from 8 participating hospitals, data on number of age-related cataract surgery performed each year and the procedure cost were collected.
Based on the potential confounding factors suggested by clinical experts, the linear mixed model (LMM) was employed to test whether there was a statistically significant difference in time between the preloaded IOL and the manual IOL implantation systems. In the model, each center was considered a random effect variable and other factors were considered fixed effect variables to identify factors that were significantly associated with the time difference between the preloaded IOL and the manual IOL implantation systems. Fixed effect parameters for preparation time included preparers and type of IOL, and for operation time included nuclear grade and type of IOL.
\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{array}{c}\log (time) = Y = {\beta _0} + {x_1}{\beta _{type\,\,of\,\,IOL}} + {x_2}{\beta _{preparation\,\,staff}}\\+ {x_3}{\beta _{nuclear\,\,grade\,}} + {u_4}{\gamma _{hospital}} + \in \end{array}$$\end{document} where β is fixed effect parameter, γ is random effect parameter.
## Time-motion model
A time-motion model (Fig. 1) was constructed to convert the operation time saved by using preloaded IOL into economic benefits. The Chinese currency was converted to US dollars (exchange rate 1 USD = 6.5249 CNY; 31 December 2020). From perspective of hospital, the potential increase in surgical volume attributed to preloaded IOL in the participating hospital was evaluated. Under the assumption that operation efficiency remains unchanged, if the total time saved per operation day exceeds the operation time by using the preloaded IOL, one or more operations is projected to be performed on that day.
From perspective of society, the increase in work productivity of medical staff by using preloaded IOL was evaluated under the condition of constant surgical volume.
Fig. 1Time-motion model structure
## Statistical analysis
Descriptive results were presented as mean and standard deviation for continuous variables. For categorical variables, frequencies and percentages were calculated. Statistical comparisons were performed using Student’s t-test or Wilcoxon rank-sum test for continuous variables as appropriate and Pearson χ2 test or Fisher exact test as appropriate for categorical variables. All tests were 2-sided and performed at a $5\%$ α-level. Statistical analysis was performed using the R software (Version 3.5.3).
## Results
In this study, a total of 2,857 cases using preloaded IOL implantation system and manual IOL implantation system were collected from eight participating centers. Upon excluding 266 cases which were deemed to be outliers per pre-determined criteria, 2,591 cases were included in the final analysis, including 1,591 cases using preloaded IOL implantation system and 1,000 cases using manual IOL implantation system (Fig. 2).
Fig. 2Inclusion and exclusion flow chart of age-related cataract surgery
## Preparation time and operation time
The mean total procedural time of each procedure using preloaded IOL implantation system and manual IOL implantation system were 379.32 and 414.50 s, respectively. Compared with manual IOL implantation system, an average of 35.18s were saved by using preloaded IOL implantation system, with $8.54\%$ reduction (Fig. 3). Owing to high heterogeneity in the processes and methods of cleaning IOL by different hospitals, the cleaning time was not included in the total time as a whole but analyzed separately as a subgroup.
There was a significant difference in the mean preparation time between the preloaded IOL implantation system and the manual IOL implantation system (25.48s vs. 47.04s, $P \leq 0.001$), with $45.83\%$ reduction in IOL preparation time using preloaded IOL implantation system. The preloaded IOL implantation system was significant time-saving in the part of preparation time compared to the manual IOL implantation system. Across participating hospitals, the preparation time shortened by using preload IOL system varied from 19.20 to $65.09\%$ (Table 1).
Fig. 3Preparation time and operation time by hospitalsA Preload and manual IOL preparation time by hospitals. B Preload and manual IOL operation time by hospital. * $P \leq 0.05$; **$P \leq 0.001$ Table 1Preload and manual IOL preparation time by hospitalsHospitalPreload (s)Manual (s)DifferenceaP-value N Mean ± SD N Mean ± SDOverall159125.48 ± 11.03100047.04 ± 14.72-$45.83\%$< 0.001**Hospital A25319.59 ± 5.4930856.11 ± 12.26-$65.09\%$< 0.001**Hospital B29522.12 ± 8.519833.15 ± 11.73-$33.27\%$< 0.001**Hospital C18618.86 ± 2.5011937.92 ± 2.31-$50.26\%$< 0.001**Hospital D15135.95 ± 4.6514947.70 ± 6.17-$24.63\%$< 0.001**Hospital E23026.64 ± 10.516048.81 ± 15.22-$45.42\%$< 0.001**Hospital F14124.60 ± 8.3713841.03 ± 17.69-$40.04\%$< 0.001**Hospital G18443.19 ± 8.196053.45 ± 8.31-$19.20\%$< 0.001**Hospital H15117.08 ± 6.916845.44 ± 20.47-$62.41\%$< 0.001**aDifference: Preload IOL vs. Manual IOL no bold*$P \leq 0.05$; **$P \leq 0.001$ Overall, there was also a statistically significant difference in the mean operation time between the preloaded IOL implantation system and the manual IOL implantation system (353.84s vs. 367.46s, $$P \leq 0.004$$). Using the preloaded IOL implantation system shortened the operation time by $3.71\%$. Across participating hospitals, Hospital B/Xijing Hospital showed no significant differences in the mean operation time comparing preload IOL with manual IOL, while other hospitals had shorter operation time with preloaded IOL implantation system varying from 2.10 to $28.11\%$ reduction (Table 2).
Table 2Preload and manual IOL operation time by hospitalHospitalPreload (s)Manual (s)DifferenceaP-value N Mean ± SD N Mean ± SDOverall1591353.84 ± 110.281000367.46 ± 126.82-$3.71\%$0.004*Hospital A253229.17 ± 55.64308253.86 ± 52.30-$9.73\%$< 0.001**Hospital B295456.65 ± 89.8198452.37 ± $97.880.95\%$0.690Hospital C186277.15 ± 22.00119286.02 ± 10.17-$3.10\%$< 0.001**Hospital D151493.79 ± 75.10149508.76 ± 76.07-$2.94\%$0.087Hospital E230298.57 ± 68.5960342.91 ± 73.51-$12.93\%$< 0.001**Hospital F141385.67 ± 55.50138410.33 ± 74.16-$6.01\%$0.002*Hospital G184332.82 ± 26.8760339.97 ± 55.74-$2.10\%$0.184Hospital H151396.46 ± 93.3168551.49 ± 127.63-$28.11\%$< 0.001**foraDifference: Preload IOL vs. Manual IOL no bold*$P \leq 0.05$; **$P \leq 0.001$ *In this* study, the cleaning time was analyzed by subgroup analysis and only the Hospital C and F were included because of their standardized cleaning protocols for both the preloaded IOL and manual IOL systems. Compared with the manual IOL system, the cleaning time of preloaded IOL system was significantly shorter in both hospitals ($P \leq 0.001$); For hospital C, the cleaning time of preloaded IOL and manual IOL was 113.27 and 142.34 s and for Hospital F, the cleaning time was 20.25 and 26.88 s for the respective IOL system.
## Linear mixed models for IOL preparation time and operation time
The results of linear mixed model showed that in the overall analysis, the type of IOL was the significant factor leading to the difference in preparation time between preloaded IOL implantation system and manual IOL implantation system. And nuclear hardness grading and IOL type were the significant factors leading to the difference in operation time between preloaded IOL implantation system and manual IOL implantation system. Compared with manual IOL implantation system, preloaded IOL implantation system saved more preparation time and operation time, and the difference was statistically significant (Tables 3 and 4).
Table 3Linear Mixed Model for IOL preparation timeParameterCoefficientStd. ErrorP-valuePreparer: Nurse0.00NANAPreparer: Surgical assistant0.180.160.270Preparer: Surgeon0.250.160.129Manual IOL System0.00NANAPreloaded IOL System-0.640.01<0.001** Represents statistically significant Table 4Linear Mixed Model for operation timeParameterCoefficientStd. ErrorP-valueGrade II nuclear0.00NANAGrade I nuclear0.030.040.383Grade III nuclear0.050.01<0.001*Grade IV nuclear0.210.01<0.001*Grade V nuclear0.320.03<0.001*Manual IOL System0.00NANAPreloaded IOL System-0.070.01<0.001** Represents statistically significant
## Annual potential increase in surgical volume and revenue
The mean annual cataract surgical volume per hospital was 6,883, of which age-related cataract surgery accounted for $61\%$. The average revenue of each age-related cataract surgery was $1,442.
From hospital perspective, assuming that all age-related cataract surgeries in each hospital are to be carried out with preloaded IOL onward, additional 392 procedures can be performed and an increase in annual revenue of $565,282 can be generated, i.e., an increase of $9\%$ (Table 5).
The average annual salary of medical staff in public hospitals was $16,690 in 2020 [14], and the number of working days in 2020 was 251 days. From perspective of society, it is assumed that all age-related cataract operations in eight hospitals used manual IOL, and the productivity loss attributed to the use of manual IOL was $0.081 per procedure. The aggregated annual productivity loss associated with use of manual IOL was $3,006 in eight hospitals.
Table 5Annual potential increase in surgery volume and revenueEconomic benefits from hospital perspectiveValuePotential increase in operationsAge-related cataract surgery volume with all using manual IOL: per year (cases)4,231Age-related cataract surgery volume with all using preloaded IOL: per year (cases)4,623Preloaded IOL vs. manual IOL: potential annual increase of surgery volume (cases)392Preloaded IOL vs. manual IOL: potential annual increase rate (%)$9\%$ Potential increase in revenue Senile cataract surgery revenue with all use manual IOL: per year ($)6,101,542Senile cataract surgery revenue with all use preloaded IOL: per year ($)6,666,824Preloaded IOL vs. manual IOL: potential annual increase of revenue ($)565,282Preloaded IOL vs. manual IOL: potential annual increase rate (%)$9\%$
## Discussion
Cataract is one of the major causes of blindness. With increasing age of global population, the number of patients with visual impairment caused by cataract may have reached 50 million by 2020 [15, 16]. Surgery remains the effective intervention to restore vision. In recent years, the improved materials, design and function of IOLs further drive the demand of cataract replacing surgeries [17–19].
The preloaded IOL has been demonstrated for its safety and effectiveness, long-term stability and excellent visual quality [6, 11, 20]. Surgeons and surgical technicians are more satisfied with the use of preloaded IOL, especially for the ease of lens preparation, the number of steps required and the total implantation time [20–23]. Additionally, the preloaded IOL offers several benefits over reusable, manual IOL, including a reduced chance of IOL damage during loading, shortened surgery time, the need for fewer surgical instruments, lower risk for contamination, and elimination of other manual setting errors, reduced incision size and quicker recovery [11, 20, 24]. At the same time, the particularities of preloaded IOL reflected in two aspects. On the one hand, it takes time for surgeons to learn and master how to use this preloaded IOL. On the other hand, the pushers of preloaded IOL are disposable and non-sterilizable, which is not in line with the sustainability concept.
As the population ages at an accelerated rate in China and worldwide, the number of cataract patients is projected to double within the next 30 years, presenting significant challenges for healthcare systems and limited resources. For a typical cataract surgery, the typical operation duration is as brief as 10–20 min. As a result, even minor improvements in surgical procedures and operating methods can quickly lead to substantial improvements in the number of cataract surgeries performed and the overall efficiency of the healthcare system. The personnel and operating room are both valuable and costly. Maximizing the efficiency of staff and operating rooms could allow for more patients to receive medical care. In this research, the effects on efficiency and revenue of adopting a preloaded IOL (TECNIS iTec® Preloaded Delivery System) were analyzed to determine the impact on the number of cataract surgeries performed and hospital revenue of transitioning from manual IOL to preloaded IOL. This study showed that application of the preloaded IOL significantly reduced the preparation time and operation time. The linear mixed model analysis indicated that the key factor affecting preparation time and operation time was the type of IOL. And it was estimated that switching from manual IOL to preloaded IOL could increase the surgery volume and revenue without additional staffs.
To our knowledge, this is the first study to evaluate the time savings and economic benefits from a hospital revenue perspective and a social productivity perspective of preloaded IOL in China with a large sample size. Our results were consistent with previous findings. A single-center, prospective and observational study in northwest China showed that the surgeon lens time was 0.7 min using preloaded IOL, which was a $46.2\%$ reduction compared with manual IOL (1.3 min) [25]. By switching from manual IOL to preloaded IOL, annual cataract surgery volume would increase by $5.2\%$, accompanied by an increase in revenue by $284,352 [25]. A study conducted in the United States, France and Canada found that the use of preloaded IOL can reduce mean total procedure time by 6.2-$12\%$ [6]. The annual surgical volume would increase by $9.9\%$ when switching from manual IOL to preloaded IOL [6]. Another study conducted in France and Spain showed that the implantation time of preloaded IOL was similar to that of manual IOL (12.9s vs. 12.2s), but the preparation time of preloaded IOL was shorter than that of manual IOL with a $49.3\%$ reduction (30.3s vs. 59.8s) [21]. A study conducting in New Zealand and Australia found that the mean estimated time-savings per procedure was 54.9s compared with non-preloaded delivery systems [20]. The preloaded IOL has the design advantages for elimination of the need for loading IOL into the introducer and combining the introducer with the pusher, which reduced number of preparation steps and improves intraoperative efficiency. In contrast to previous studies, our study also showed that the preloaded IOL significantly saved more preparation time and operation time compared to manual IOL upon controlling for effects of preparer type, surgery staff type, and patient nuclear hardness grade on time. Other potential influential factors, such as surgeons with varying levels of ophthalmic surgical experience, adhesion between haptics and optics will be collected in the future study. In addition, our study also measured the labor loss of surgeons and surgical technicians from the perspective of society.
In the current study, the calculated potential increase in revenue was derived by three factors: the time saved by preloaded IOL system, the cost per age-related cataract surgery, and volume of age-related cataract surgery. As the preparation process and surgical procedure may vary by sites, we used average time saved in eight participating study sites to estimate the potential increased revenue, which likely is more representative of typical clinical settings in China. Clinical experts survey indicated that there was no difference in surgical costs between preloaded IOL and manual IOL, with no additional instrumentation costs and less pushers used for preloaded IOL surgery. The surgical volume from participating hospitals was also obtained from the clinical experts’ survey, which was based on the real-world data from their respective hospital electronic information system. Taken together, the results of our study appeared to be robust.
Potential limitations should be taken into consideration when interpreting the findings of this study. This study was an observational, non-interventional study, which was not possible to control for unobserved external factors in participating hospitals (e.g., surgical procedure flow, cataract case mix, patient characteristics, etc.). The implication on surgical volume and hospital revenue was projected based on historical record not a direct observation. In fact, the annual surgical volume of 8 hospitals from July 2020 to July 2021 was significantly lower compared to the years prior due to the impact of the COVID epidemic. As a result, the potential increase in revenue and loss of labor costs may have been underestimated. Finally, this study only focused on the economic impact of the application of preloaded IOL system without follow-up on clinical and patient-centered outcomes, such as patient quality of life and satisfaction with preloaded or manual IOL before and after the implementation of cataract patients. However, these limitations did not affect the conclusions of this study which focused on the surgical efficiency comparing the preloaded IOL system with manual IOL system.
## Conclusion
Compared with manual IOL implantation system, the preloaded IOL implantation system reduces lens preparation time and operation time, which is projected to significantly increase potential surgical volume and revenue, and reduces the loss of work productivity. This study provides real-world evidence to support the advantages of the preloaded IOL implantation system in improving the efficiency of ophthalmic surgery in China.
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|
---
title: 'ACTIVE YOU: Teacher Attributes and Attitudes Predicting Physical Activity
Promotion'
authors:
- Erin E. Centeio
- Yeonhak Jung
- Darla M. Castelli
journal: Behavioral Sciences
year: 2023
pmcid: PMC10045155
doi: 10.3390/bs13030210
license: CC BY 4.0
---
# ACTIVE YOU: Teacher Attributes and Attitudes Predicting Physical Activity Promotion
## Abstract
Background: Based on the Health Belief Model, this study examined preservice teacher attributes and attitudes toward providing physical activity opportunities for children in school. Methods: A quasi-experimental design was used to collect proof of concept and feasibility data for the ACTIVE YOU intervention as part of teacher education. Conclusions: Examination of a diverse sample of preservice teachers during their fieldwork revealed that those who engage in healthy behaviors and had positive attitudes toward physical activity in schools are more likely to take action and promote physical activity for their students.
## 1. Introduction
Among children, single bouts of physical activity [1] and regular participation [2] positively relate to selective academic outcomes, as healthier children are more ready to learn [3]. Although the specific physical activity characteristics, such as the type and intensity that directly influence academic achievement may be debatable, the health-protective benefits of improved mental and social-emotional health of children justify its inclusion in the school curriculum [4]. Movement integration (MI), the integration of physical activity into classroom learning activities, is generally positively perceived by teachers [5,6]. When MI or physical activity is implemented effectively, it can improve student behaviors, increase time on task during academic learning [7], and increase the likelihood of having a positive class climate [8]. Schools provide an opportunity for children to learn the importance of physical activity in a structured and safe environment where knowledge and skills can be developed.
Although schools are an ideal place to promote physical activity, few teachers are prepared by their teacher education programs to do so. Novice teachers have many responsibilities, including their role as health promoters [9,10]. Even with training, teacher rankings of the importance of health promotion are low [11,12], and the influence of personal health behaviors influence attitudes, biographical characteristics, and self-efficacy toward leading physical activities in school has only been cross-sectionally examined among a few samples of preservice teachers [13,14] or as cohort research [15,16]. As the baseline assessment in a children’s movement course, we administered a standardized health-related fitness assessment to 133 individuals in their third year who were majoring in education. The assessment was valid for ninth-grade students [17]. The mean score for the preservice K-6 teachers was $54\%$ correct responses, thus demonstrating the lack of health-related fitness knowledge among future teachers.
In response to such concerns, we developed an intervention, ACTIVE YOU, to address the gaps in teacher education. Specifically, we sought to inspire cues to action and build self-efficacy to provide physical activity opportunities for children in schools. This study seeks to confirm the feasibility and proof of concept of the teacher education intervention, ACTIVE YOU, which focuses on developing health promotion skills among preservice teachers during their fieldwork.
## 1.1. Theoretical Framework: Health Belief Model
The Health Belief Model (HBM; Figure 1) links multiple constructs to explain why humans embrace some healthy behaviors while avoiding others [18]. In this study, we have applied the constructs of HBM to the lives of teachers, who must simultaneously consider their health and wellness and that of their students. The HBM is grounded in the constructs of perceived susceptibility, perceived severity, perceived benefits/barriers, cues to action, and self-efficacy. A teacher’s personal beliefs surrounding their health risk (e.g., a sedentary lifestyle, obesity, or poor eating habits) typically intensify with age [19]. Teachers must be aware of their own habits to conscientiously reduce personal health risks, considering that health is a continual work in progress affected by daily behaviors. Therefore, the perceived severity or the seriousness of a potential health condition would also play a role in a teacher’s attitudes and actions.
## 1.2. Teacher Education: Beliefs and Self-Efficacy
According to Bandura’s Social Cognitive Theory [1997], self-efficacy is the “belief in one’s capacity to organize and execute the course of action required to produce given attainments” [20] (p. 3). Teacher education encourages preservice teachers to be efficacious in their ability to enhance student learning because we know that past experiences in physical education and physical activity shape preservice teachers’ beliefs and influence what and how they teach [21]. The professional socialization process is designed to build self-efficacy through mastery experiences, vicarious experiences, verbal persuasion from teacher educators, and verbal persuasion from cooperating teachers [22].
The formulations of such beliefs through this contemplation can trigger actions. As presented in Figure 1, an event or cue (e.g., vicarious experiences—watching a fourth-grade teacher model how they integrate MI into a lesson; mastery experiences—the preservice teacher integrating MI into a lesson with fourth-grade students) can often initiate a behavioral response. Specific experiences in teacher education are designed as a source of cues to action [9]. For example, the mastery experience included in ACTIVE YOU are authentic case studies. When the case studies focus on personal health-protective behaviors, such as participation in physical activity, the reflective practice can build preservice teacher efficacy toward their capacity to model health practices for their students. Ultimately, the teacher must have the confidence to assert their actions. Those who believe they can influence the events, such as improving their health or that of their students, will behave in a goal-directed manner [23].
## 1.3. Teachers as Health Promoters in Schools
Targeting multiple points of intervention, the Comprehensive School Physical Activity Programs (CSPAP) framework creates a culture of consistent messaging, promoting opportunities for all to engage in positive and healthy physical activity during physical education, before and after school, during the school day, and with family and community members on school grounds [24]. A classroom teacher plays a pivotal role in implementing the school day portion of the CSPAP, partly by modeling but also by facilitating and supervising physical activity opportunities. Therefore, teacher education learning activities that introduce classroom educators to effective ways to incorporate MI and physical activity across the school day may benefit students and teachers [24,25].
Whether formally a school champion or simply a teacher who understands that healthier children learn better, positive attitudes and self-efficacy are valuable dispositions that influence the effectiveness of such initiatives [26,27]. Accordingly, this study sought to identify the relationship between preservice teacher attitudes and self-efficacy related to promoting physical activity within the school environment from an HBM perspective.
If teacher education programs are to effectively prepare teachers as health promoters who are likely to model and offer physical activity opportunities for their students, the learning experiences should be aligned with best practices and the theoretically and empirically supported literature [28]. As such, this study examined the association between preservice teacher characteristics, such as Body Mass Index (BMI) and daily physical activity participation, and their likelihood of offering physical activity opportunities in the school setting. Uniquely positioned in a preservice teacher education program at one US university, these future teachers were enrolled in a required course focused on children’s movement content. The state where this study took place has mandated courses for preservice teachers to provide physical education subject matter content and to introduce the whole-of-school approach using models such as CSPAP. Accordingly, this study sought to determine the feasibility and proof of concept of the ACTIVE YOU intervention to meet this state mandate and increase the likelihood that future teachers would provide physical activity opportunities during the school day for their students.
## 2. Materials and Methods
Using a quasi-experimental design in a 16-week teacher education course, we examined the relationships between personal attributes of BMI and daily physical activity participation on attitudes and self-efficacy toward providing physical activity opportunities for children among preservice teachers. We also examined the predictors of physical activity promotion. Findings from this study could provide proof of concept and support for continued development and full integration of the ACTIVE YOU curriculum, which has been organized into the Template for Intervention Description and Replication (TIDieR checklist [29], see Table 1). To date, the protocol has not yet been registered as a clinical trial.
## 2.1. Participants
After an Institutional Review Board approval was secured, 265 preservice teachers enrolled in a teacher education certification program volunteered to share their assignments completed during the university course. The researchers collected the data from the courseware and wearable device software after completing the course, with grades posted and course credit awarded. One student declined to provide the requested information for research purposes.
## 2.2. Instruments and Measures
Data were collected using wearable technology, self-reported perceptions, lesson reflections, fieldwork, and coursework artifacts over 16 weeks of fieldwork by preservice teachers. Two sets of valid, reliable surveys were administered at the beginning and end of the course: (a) past perceptions and experiences and (b) perceptions about fieldwork and working with children in schools.
## 2.2.1. Daily Physical Activity Measures of Self
The personal daily physical activity level of the preservice teachers enrolled in the course was objectively measured using accelerometers and subjectively measured through logs and reflections. Step counts were assessed using an ActiGraph GT3X (ActiGraph, Pensacola, FL, USA), which uses a solid-state triaxial accelerometer to measure motion data on multiple axes. The accelerometers were initialized to collect data using 5-s epoch lengths to capture the sporadic, intermittent nature of participant physical activity [30]. The participants were also required to keep a physical activity log that reflected their daily participation. Both measurements were integrated into the ACTIVE YOU intervention as course requirements intended to increase physical activity participation.
## 2.2.2. Biographical Questionnaire of Physical Self and Self-Perceptions of Ability
Self-reported biographical information, including participants’ age, gender, race, height, weight, and year in the teacher education program, was attained via survey through the campus courseware. BMI was calculated by dividing one’s weight in kilograms by the square of one’s height in meters. Participant’s perceptions of physical activity competence and past physical activity experiences were assessed with five items and four items, using two valid, reliable, 4-point Likert scales (1 = strongly disagree to 4 = strongly agree) with acceptable internal consistency (>0.82 and >0.86) [31]. Example items include “I am capable of participating in multiple sport activities” and “I enjoyed my physical education experience when I was in school”.
## 2.2.3. School Physical Activity Promotion Competence (SPAPC)
The School Physical Activity Promotion Competence (SPAPC) [9,10] is a valid, reliable instrument used to determine self-efficacy toward promoting physical activity in a school setting. The instrument contains 15 items and uses an 8-point Likert scale (0 = no skills to 7 = many skills) with acceptable internal consistency (>0.95). Example items include “I am comfortable integrating physical activity into classroom lessons”.
## 2.2.4. School Physical Activity Promotion Attitudes (SPAPA)
The School Physical Activity Promotion Attitude (SPAPA) [13,14] was used to measure attitudes toward promoting physical activity in a school setting with nine items using a 4-point Likert scale (1 = strongly disagree to 4 = strongly agree) with acceptable internal consistency (>0.83). Example items include “Elementary classroom teachers should provide physical activity for students daily as part of the school day”. The sum of each instrument was included in the statistical analysis.
## 2.2.5. Power Analysis
A priori power analysis was computed using G*Power to estimate the sample size needed for calculating hierarchical and logistical regression analyses based on the correlations and effect size reported in a meta-analytic review [32]. The calculation was based on a medium effect size ($f = 0.25$), six groups, and four covariates. Results showed that a total of 179 participants were required to achieve $80\%$ statistical power at α = 0.05. However, the final decision for sample size was $$n = 200$$ in consideration of potential attrition.
## 2.3. Data Collection Procedures
Participants were recruited from six course sections offered by a teacher education program after permission for intervention was obtained from the IRB and course instructors. Among the sections, three were randomly assigned to treatment groups and three were assigned to serve as control groups over one academic year. As part of the planned learning experiences within the course, participants were provided with formal instruction on the benefits of physical activity participation, which included familiarization with the instruments (e.g., accelerometer). All participants received a daily physical activity log and an accelerometer, which they were asked to wear for 14 days (7 days early in the semester and 7 days later in the semester). Before delivering physical activity content, the participants were asked to complete the online surveys before the end of the first week of the course. The treatment fidelity was confirmed through weekly lesson content observations, lesson artifacts review (e.g., presentation slides and assignments on courseware), and having one teacher deliver the intervention content to all course sections. All lessons were aligned with the HBM constructs (Figure 1), with the likelihood of action being measured as participation in and promoter of physical activity.
## 2.4. Statistical Analysis
This study used SPSS 25.0 software to analyze and process the data. Data screening was conducted before any statistical analyses were performed. For survey instruments, skewness and kurtosis values were used to confirm the normality assumption, while *Cronbach alpha* coefficients were used to assess internal consistency for validity [33]. Descriptive statistics were also calculated, including means (M), standard deviations (SD), and relative frequencies for continuous and categorical data. Based on two groups, including the healthy BMI group and the unhealthy BMI group, continuous variables (i.e., age, BMI, daily physical activity level) were compared using independent t-tests. The relationships between the BMI classifications, daily physical activity levels, and survey scores were examined using correlations. A hierarchical regression analysis was conducted to determine the likelihood of having positive attitudes and self-efficacy toward promoting physical activity in a school setting. The hierarchical regression analysis was selected to account for modifiable (e.g., attitudes, self-efficacy) and non-modifiable (i.e., year in teacher education program and race) variables. The hierarchical regression model was selected over other regression analyses because it examines the relationships between independent variables and a dependent variable after controlling for the effects of some non-modifiable variables. Logistic regression was used to predict the likelihood of having daily physical activity levels and perceived physical activity competence between the healthy BMI group and the unhealthy BMI group. Logistic regression was selected for two reasons: (a) the dependent variable was categorical and (b) the researchers wanted to estimate an odds ratio for these variables. The statistical significance level of all indicators was set as $p \leq 0.05.$
## 3. Results
A total of 265 participants were enrolled in the study over the academic year; however, only 233 participants were included in the final statistical analysis because they provided 14 days of physical activity measures and had completed all survey instruments. Thirty-two participants were excluded due to the absence of physical activity measures, incomplete surveys, or excessive missing data (i.e., missing more than $50\%$ of the total values).
Table 2 displays the participant demographic characteristics. A total of 233 preservice teachers ($$n = 211$$ females; Mage = 20.17, SD = 2.60) met the inclusion criteria. The participants were $55\%$ White, $31\%$ Hispanic, $8\%$ Asian, $4\%$ Black, and $2\%$ who reported multiple races/ethnicities. The sample’s experience classifications demonstrated $17\%$ first-year, $35\%$ second-year, $28\%$ third-year, $13\%$ fourth-year, and $7\%$ fifth-year preservice teachers in the teacher education program. For assessment of health behavior, steps per day ($M = 7880.32$, SD = 2861.66) fell below the daily standard of 10,000 steps [34], while the BMI ($M = 22.38$, SD = 3.68) fell within a healthy standard for this age group [35]. According to the BMI classification, participants were identified as underweight ($$n = 21$$; $9\%$), healthy ($$n = 168$$; $72\%$), overweight ($$n = 36$$; $16\%$), and obese ($$n = 8$$; $3\%$). In the subgroup comparison, 168 participants were classified in the healthy BMI group (MBMI = 21.42, SD = 1.72) and 65 participants were classified in the unhealthy BMI group (MBMI = 24.86, SD = 5.74). In addition, 188 participants were classified in the low active group (MSteps = 6930.83, SD = 1794.43) and 45 participants were classified in the high active group (MSteps = 12234.12, SD = 2812.02). When considering daily steps by the BMI classification, and BMI by the active classification, there was no significant difference in daily physical activity level, including steps ($$p \leq 0.19$$), between the unhealthy BMI group and healthy BMI group, and no significant difference in BMI levels ($$p \leq 0.52$$) between the low physically active group and the high physically active group.
## 3.1. Correlation Table Participant Characteristics, BMI, and Physical Activity Level
Table 3 reports a negative correlation between BMI and attitudes toward promoting physical activity in a school setting (r = −0.17, $$p \leq 0.009$$). At the same time, there was a significantly positive relationship between daily physical activity levels and perceived physical activity competence ($r = 0.28$, $p \leq 0.001$) and attitudes ($r = 0.15$, $$p \leq 0.04$$) toward physical activity. Attitudes toward physical activity were significantly correlated with past physical activity experience ($r = 0.33$, $p \leq 0.001$) and perceived competence ($r = 0.29$, $p \leq 0.001$). Self-efficacy toward physical activity was significantly related to past physical activity experiences ($r = 0.21$, $p \leq 0.001$) and perceived physical activity competence ($r = 0.24$, $$p \leq 0.003$$).
## 3.2. Hierarchical Regression Analysis
The hierarchical regression model examined personal characteristics on attitudes and self-efficacy toward promoting physical activity in school (Table 4). Regarding attitudes, the hierarchical regression analysis revealed that perceived previous physical activity experience and physical activity competence in the first step and predictors of daily physical activity level and BMI level in the second step accounted for $13\%$ and $16\%$ of the variance and were statistically significant, F [4,229] = 17.56, $p \leq 0.001$, η2 = 0.13 and F [6,227] = 8.82, $p \leq 0.001$, η2 = 0.16, respectively. Controlling for the year in the program and race, previous physical activity experiences (β = 0.24, $$p \leq 0.01$$), perceived physical activity competence (β = 0.17, $$p \leq 0.001$$), and daily physical activity level were positive predictors (β = 0.15, $$p \leq 0.042$$) of teachers’ attitudes toward physical activity promotion, while BMI was a negative predictor (β = −0.15, $$p \leq 0.015$$).
Additionally, analysis of self-efficacy toward physical activity using hierarchical regression, controlling for the year in the teacher education program and race, revealed that perceived physical activity competence and previous physical activity experience in the first step and predictors of daily physical activity levels and BMI in the second step accounted for $7\%$ and $8\%$ of the variance, which were significant, F [4,229] = 5.21, $$p \leq 0.002$$, η2 = 0.07 and F [6,227] = 2.98, $$p \leq 0.008$$, η2 = 0.07, respectively. Only perceived physical activity competence in the first step (β = 0.18, $$p \leq 0.012$$) and the second step (β = 0.19, $$p \leq 0.014$$) was a predictor of self-efficacy toward physical activity. No other significant predictors of self-efficacy toward promoting physical activity existed. Participants with higher perceived physical activity competencies and positive previous physical activity experiences were more likely to have positive attitudes and higher self-efficacy toward promoting physical activity in the school setting. Further, those with higher BMI or lower physical activity levels were less likely to have positive attitudes.
## 3.3. Logistical Regression Analysis
The logistic regression model compared teachers’ characteristics according to the BMI classification (i.e., healthy BMI group versus unhealthy BMI group) and active classification (i.e., high active or low active group) while controlling for covariates, including race and year in the program (Table 5). Significant predictors of BMI classification in the model were daily step counts (β = −0.01, $p \leq 0.001$) and perceived physical activity competence (β = −0.18, $$p \leq 0.017$$). Although participants in the unhealthy BMI group were only $1\%$ less likely to have daily step counts (OR = 0.99; $95\%$ CI = 0.99–0.99), they had $17\%$ less likely to have perceived physical activity competence (OR = 0.83: $95\%$ CI = 0.71–0.96) compared to the participants who were in the healthy BMI group. In addition, only perceived physical activity competence was a significant predictor for active classification (β = −0.37, $p \leq 0.001$). Participants in the low active group were $31\%$ less likely to have perceived physical activity competence (OR = 0.69: $95\%$ CI = 0.58–0.82) than those in the high active group. The results indicated that the participants in the unhealthy BMI group or the low active group were less likely to have their physical activity competencies related to teachers’ attitudes and self-efficacy toward promoting physical activity in school settings.
## 4. Discussion
We hypothesized that several well-established psychosocial determinants, such as attitudes and self-efficacy toward promoting physical activity, would be related to teachers’ health behaviors, such as personal BMI and daily physical activity levels. This study identified the personal health behaviors influencing teachers’ attributes to promote physical activity engagement for their future students in the school environment. In the present study, a higher BMI level was negatively related to teachers’ attitudes toward promoting physical activity, while a higher daily physical activity level was positively related to teachers’ attitudes. These findings indicated that preservice teachers who had a high prevalence of healthy behaviors would likely positively influence their physical activity promotion in schools. This study found that just under one-third of the individuals entering into the field of teaching were at risk for health issues according to the classification of their BMI [34] and $80\%$ of them were at risk of health issues because of the number of days not meeting the recommended daily step count [35]. Such unhealthy behaviors could be exacerbated over time, possibly due to reduced physical activity and increased sedentary activity levels related to employment as a full-time teacher [36]. Given the decline in physical activity participation in later life, other health risks, and the risk of developing as overweight/obese, the findings raise concerns regarding the potential influences of teachers’ health behavior and their perception of their future students.
These are valuable findings for two reasons. First, teachers’ health and well-being are essential, as healthier teachers are more likely to provide ample physical activity to produce academically successful students [37,38]. Additionally, there is a direct relationship between the amount of physical activity educators participate in and their willingness to promote physical activity for their students [39]. Second, the findings confirmed a bi-directional relationship between health; healthier teachers teach better and healthier students to learn better [40] because unhealthy behavior increases health problems (i.e., obesity and diabetes), which might play a significant role in interfering with children’s ability to learn in a school setting [3]. Furthermore, teachers, staff, and community members should work collaboratively to create a school setting to ensure that each student is emotionally and physically healthy.
## 4.1. Teacher Education and Preservice Teachers’ Health
Since unhealthy behavior (i.e., higher BMI level and lower physical activity participation) was negatively related to a teacher’s attitudes toward providing physical activity opportunities, teacher education needs to include coursework addressing health risks and strategies to promote physical activity in schools. Although preservice teachers with better health behaviors were more likely to have positive attitudes toward promoting physical activity in school, they lacked self-efficacy as a sense of confidence in personal physical activity skills and knowledge [41]. Low self-efficacy can decrease physical activity participation and reduce the teachers’ likelihood to promote physical activity with the students [42]. Our findings also confirmed that self-efficacy was significantly correlated with perceived physical activity competence and previous physical activity experience. The logistic regression model showed that preservice teachers in the unhealthy behavior group (i.e., BMI and active classification) had lower perceived physical activity competence than those in the healthy group, suggesting that those preservice teachers might have less confidence in promoting physical activity in their future students than those who are more active.
Findings from this study suggest that teacher education coursework in the United States should holistically integrate lessons that consider student and teacher health and wellness, similar to current global efforts [40]. Without an awareness of the potential impacts, including personal health behavior (i.e., physical activity and BMI), teachers’ attitudes, and self-efficacy, educators cannot create a healthy learning environment for students. As the present study indicated, preservice teachers who regularly engaged in physical activity had positive attitudes toward offering similar experiences to children in school. Therefore, ensuring that future educators are aware of how personal habits and competency may later influence student habits is essential.
## 4.2. Teacher Education and Preservice Teachers’ Physical Activity Promotion
Teachers are ideal health promoters, as healthier students are more ready to learn. However, few teachers are directly prepared with strategies first to develop a life-work balance and routines for their own well-being but second to also apply specific strategies for the physical activity promotion of their students. Accordingly, the field experience during the course where these data were collected was predicated on the notion that schools should provide opportunities to personally engage in physical activity, as well as to acquire content knowledge about movement concepts and motor skills, and to have exposure to instructional methods to deliver safe physical activity opportunities for children. The course content did not exclusively promote physical activity over motor skill development, both were equally endorsed. Further, the preservice teachers in this study were required to participate in a weekly field experience in an elementary school setting for approximately ten hours while assisting physical education and classroom teachers. It appeared that such experiences contributed to helping preservice teachers identify their own level of competence, efficacy, and attitudes toward facilitating student physical activity.
This study found that participation in physical activity related to preservice teacher attitudes and there was carry-over into the field experiences; therefore, this study suggests that individuals should be afforded opportunities to increase content knowledge within the classroom during teacher education. Moreover, applying this learning in an authentic context is essential to increase their perceived competence and engagement in physical activity. Since most preservice teachers in this sample exhibited positive attitudes and higher self-efficacy toward physical activities, it is probable that they will increase the likelihood of participating in and promoting health-enhancing behaviors, such as physical activity, when presented with authentic, in-school experiences.
## 5. Conclusions
Although the next step is an efficacy trial, sufficient evidence exists to include wearable devices, acknowledgment of previous physical activity experiences, teacher case studies, and specific strategies for physical activity promotion in schools (e.g., the CSPAP model). This study discovered that some individuals entering the teaching field have health risks, given the classification of their BMI and physical activity level. Preservice teachers with health risks may assume that health is an unimportant or devalued topic in schools. Given their sedentary, inactive lifestyles, today’s children are also at risk for health issues that can influence their health in relation to their academic achievement [43]. Since schools are an ideal place to offer physical activity opportunities, teachers need to be prepared and have positive attitudes and self-efficacy toward promoting physical activity. Further investigation is needed to evaluate the sustainability potential of this intervention, ACTIVE YOU, by following the preservice teacher to their full-time employment. Only then will we understand the effects of the teacher education coursework.
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|
---
title: Hirsutidin Prevents Cisplatin-Evoked Renal Toxicity by Reducing Oxidative Stress/Inflammation
and Restoring the Endogenous Enzymatic and Non-Enzymatic Level
authors:
- Faisal Imam
- Preeti Kothiyal
- Samiyah Alshehri
- Muhammad Afzal
- Muzaffar Iqbal
- Mohammad Rashid Khan
- Abdulrazaq Ahmed Hattab Alanazi
- Md. Khalid Anwer
journal: Biomedicines
year: 2023
pmcid: PMC10045162
doi: 10.3390/biomedicines11030804
license: CC BY 4.0
---
# Hirsutidin Prevents Cisplatin-Evoked Renal Toxicity by Reducing Oxidative Stress/Inflammation and Restoring the Endogenous Enzymatic and Non-Enzymatic Level
## Abstract
Recent research has shown that phytocomponents may be useful in the treatment of renal toxicity. This study was conducted to evaluate the renal disease hirsutidin in the paradigm of renal toxicity induced by cisplatin. Male Wistar rats were given cisplatin (3 mg/kg body weight/day, for 25 days, i.p.) to induce renal toxicity. Experimental rats were randomly allocated to four different groups: group I received saline, group II received cisplatin, group III received cisplatin + hirsutidin (10 mg/kg) and group IV (per se) received hirsutidin (10 m/kg) for 25 days. Various biochemical parameters were assessed, oxidative stress (superoxide dismutase (SOD), glutathione transferase (GSH), malonaldehyde (MDA) and catalase (CAT)), blood-chemistry parameters (blood urea nitrogen (BUN) and cholesterol), non-protein-nitrogenous components (uric acid, urea, and creatinine), and anti-inflammatory-tumor necrosis factor-α (TNF-α), interleukin-1β(IL-1β). IL-6 and nuclear factor-kB (NFκB) were evaluated and histopathology was conducted. Hirsutidin alleviated renal injury which was manifested by significantly diminished uric acid, urea, urine volume, creatinine, and BUN, compared to the cisplatin group. Hirsutidin restored the activities of several antioxidant enzyme parameters—MDA, CAT, GSH, and SOD. Additionally, there was a decline in the levels of inflammatory markers—TNF-α, IL-1β, IL-6, and NFκB—compared to the cisplatin group. The current research study shows that hirsutidin may act as a therapeutic agent for the treatment of nephrotoxicity induced by cisplatin.
## 1. Introduction
Nephrotoxicity is a condition when harmful substances and medications cause the kidneys to excrete less toxic metabolic waste [1] and it can be identified by nuclear chromatin condensation, tubular dilatation, vacuolization of tubular cells, and microvilli loss [2]. In cases of severe renal injury, tubular degradation may involve solely the loss of the epithelial cell brush edge. The main histopathological characteristics of nephrotoxicity are apoptosis and necrosis of tubular epithelial cells [3,4]. Drug accumulation causes renal proximal tubule cells to exhibit significant toxicity, which ultimately results in tissue damage, poor perfusion, and renal failure [5]. The primary clinical characteristics of chronic kidney disease (CKD) are the sequential loss of vital functionalities, which, finally, results in chronic renal failure and requirement of kidney dialysis or transplants to preserve quality of life [6]. Acute kidney disease (AKD) is linked to a high prevalence of CKD, and people whose CKD is made worse by AKD have a higher death risk, according to earlier research [7]. A previous study indicates that a significant factor in about $60\%$ of AKD cases in healthcare settings is drug-induced nephrotoxicity [8]. Cisplatin is used as a chemotherapy drug in treating different cancers, including testicular, ovarian, bladder, and lung cancers [4,9,10]. It works by interfering with the DNA in cancer cells, which prevents them from dividing and spreading [4,11,12]. Cisplatin is often used in combination with other chemotherapy drugs with significant side effects, including kidney injury and hearing loss [13,14]. The principal dose-limiting effect of cisplatin is nephrotoxicity, even though its remarkable anticancer activity is coupled with multiple toxicities including ototoxicity, gastrotoxicity, myelosuppression, and allergic responses [15,16,17]. The predominant location of impairment in cisplatin nephrotoxicity is the proximal tubules [17,18]. In addition to eliminating endogenous and external wastes, including medications, the kidney also retains some of these compounds in the proximal tubular region [19]. During cisplatin therapy, renal tissue accumulates cisplatin more quickly than other tissues and organs. The accumulation of cisplatin in these cells can lead to several pathophysiological consequences that contribute to its nephrotoxicity [20,21,22]. Cisplatin quantity in renal proximal tubule epithelial cells was found to be approximately five times higher than in serum [23].
The impact of cisplatin on DNA synthesis and repair, which inhibits cell proliferation as a result, is recognized as a contributing component to cisplatin toxicity [22,24,25]. An important factor in the acute renal failure induced by cisplatin is mitochondrial abnormality [25,26]. The accession of cisplatin inside the mitochondria turns into the production of reactive oxygen species (ROS), which then triggers oxidative stress and nephrotoxicity as well as renal damage [25,27]. Recent research suggests that oxidative stress significantly contributes to the proximal tubule injury caused by cisplatin, increasing the oxidation of lipids, proteins, and nucleic acids while decreasing the activity of enzyme-based antioxidants such as superoxide dismutase (SOD), glutathione peroxidase (GSH), and catalase (CAT) [17,28,29]. Low renal perfusion ultimately dictates the fate of the renal tissue by being indicative of nephrotoxicity and the necrosis of the proximal tubule’s terminal part. Renal failure brought on by cisplatin is indicated by a decreased rate of glomerular filtration along with increased levels of blood urea nitrogen (BUN)and plasma creatinine [22,30,31]. It was previously reported that the tumor-suppressor protein p53 is induced by cisplatin and, through the connection between the receptor and tumour necrosis factor, this impacts apoptosis. Cisplatin can also induce inflammation within the kidney, which can contribute to nephrotoxicity. This occurs when cisplatin stimulates the production of pro-inflammatory cytokines and chemokines, which recruit immune cells to the site of injury and can lead to tissue damage [32]. Therefore, the protective effects of various chemical and natural compounds with antioxidant activity against cisplatin-induced nephrotoxicity have been investigated [16,17]. The potential negative effects of cisplatin can be mitigated by several anti-inflammatory and antioxidant agents [33].
Therapeutic data and diagnostic data indicate that oxidative stress in the kidneys is generated by cisplatin administration resulting in the damage of tubules [34]. The reactive species of oxygen and nitrogen (ROS and RNS) have been proven to change the structural and functional integrity of membranes during mitochondrial respiration [35,36]. Furthermore, the build-up of these types of proteins in lysosomes and kidneys was used to elucidate the underlying cisplatin-induced acute nephropathy mechanism [37]. Numerous factors, including oxidative stress, inflammation, apoptosis, and dysfunctionality of mitochondria are symptomatic of cisplatin-induced nephropathy. However, the exact cause of the dysfunction is not fully understood [7].
Polyphenols called anthocyanins, present in fruits, vegetables, and flowers, are responsible for their pigmentation. It has been demonstrated that the flavonoid pigment of anthocyanin is naturally occurring and possesses antioxidant properties [38]. ROS are thought to be the cause of a wide variety of disorders; hence, it is hypothesized that this capacity serves as a defense mechanism. Consuming a diet high in anthocyanin-rich foods has been linked to a reduced risk of cancer [39], diabetes [40], obesity [40], bacterial infection [41], neurotoxicity [42], cardiovascular disease [43] and eye disease [44].
A member of the anthocyanin family, hirsutidin is an O-methylated anthocyanidin. It can be found in callus cultures and *Catharanthus roseus* (Madagascar periwinkle), where it is the most prevalent component in the petals. The review of the available literature reveals that the biological activities of the hirsutidin-plant flavonol glycoside, particularly its kidney protective capabilities, have received relatively little attention from scientific studies. The objective of the current study was to demonstrate the role of hirsutidin in the protection of the kidney in cisplatin-induced rats.
## 2.1. Animals
Male Wistar rats with a weight of 180 ± 20 g ($$n = 6$$ per group) were kept under standard laboratory conditions, including a 12 h–12 h light–dark cycle, humidity level of 40–$50\%$, and room temperature of 23–28 °C. The animals were provided with regular feed and water prior to conduction of the experiment. Rats should have assimilated over the course of seven days while adhering to accepted laboratory procedures. The rodent experimentation was given final approval by the Institutional Animal Ethics Committee (IAEC/TRS/PT/$\frac{022}{018}$).
## 2.2. Drugs and Chemicals
Cisplatin was procured from Sigma (St. Louis, MO, USA). Hirsutidin was collected as a gift sample from SRL, India. Interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and nuclear factor-kB (NF-κB) were determined by rat enzyme-linked immune-sorbent assay (ELISA) kit (MyBioSource, St. Louis, MO, USA).
## 2.3. Experimental Design
This proposed investigation was carried out according to the previous studies [45], with slight modifications. Four groups were divided randomly with 6 rats in each group.
To test for nephrotoxicity in rodents, the rats received cisplatin (3 mg/kg body weight/day) in the solution of saline ($0.9\%$) which was injected every five days (total of four injections) until 25 days [7,46].
## 2.4.1. Kidney Tissue Homogenate and Preparation of Biological Samples
Using metabolic cages, a sample of urine from 24 h was collected on the 25th day. At the endpoint, blood was collected using the retro-orbital technique. Approximately 200 μL to 1 mL of blood was taken and the separation of serum was performed by centrifugation for the duration of 20 min at the speed of 1000× g. A sample of serum and urine was taken to assess the various biochemical markers. After the rats were sacrificed, their kidneys were taken out and cleansed using normal saline solution and $10\%$ w/v homogenates of tissue were prepared with the buffer of Tris-HCl (pH 7.5) with the molarity of 0.1 M and centrifuged at the speed of 3000× g for a time period of 15 min [7] to obtain supernatant. The kidney homogenates were used for the determination of oxidative stress and inflammatory markers.
## 2.4.2. Estimation of Uric Acid, Urea, Creatinine, BUN, and Cholesterol
Using commonly accessible diagnostic kits (Meril life diagnostic kit, Gujarat, India), the serum at the absorbance of 254 nm and urine at the absorbance of 340 nm was evaluated spectrophotometrically to determine the uric acid (IFU/URCFSR$\frac{01}{01}$), urea (IFU/UREFSR$\frac{01}{00}$), levels of creatinine (IFU/CREFSR$\frac{03}{01}$), blood urea nitrogen (IFU/UREFSR$\frac{01}{00}$) and cholesterol (IFU/CHOFSR$\frac{01}{00}$) [7].
## 2.4.3. Estimation of Biomarkers of Oxidative Stress
GSH activity was determined by the method involving the oxidation of NADPH into NADP+ in the presence of oxidizedglutathione [47] and the results were represented in µmol/g of protein. SOD activity was estimated through the inhibition of the formation of autocatalyzed adrenochrome in the presence of tissue homogenate at 480 nm and SOD was expressed as U/g protein [46]. The activity of catalase was determined by measuring hydrogen peroxide (H2O2) decomposition at 254 nm in the presence of CAT using the method used by Aebi et al. [ 48] and was expressed as U/g protein. Malondialdehyde (MDA) levels were determined as an index of the extent of lipid peroxidation in kidney tissue using standard method [49] and the results were represented in nmol/g of protein.
## 2.4.4. Estimation of Inflammatory Markers
The supernatant was collected and used to measure levels of inflammatory markers, i.e., TNF-α (MBS175904), IL-1β(MBS732184), and NF-κB (MBS453975). The levels of TNF-α, IL-1β, and NF-κB in kidney tissue homogenate were quantitated using an ELISA assay according to the manufacturer’s instructions (My BioSource, St. Louis, MO, USA) [50].
## 2.4.5. Estimation of Histopathological Investigations
For microscopic examination, histopathologic samples were collected from the renal tubules of rats in various groups and fixed in $10\%$ formalin for 24 h. After washing in xylene, tissue samples were embedded in paraffin for 24 h at 56° in a hot-air oven. Using a sledge microtome, paraffin beeswax epithelial slabs were prepared for sectioning at a four-micron width. For microscopic examination, epithelial sections were positioned on the glass slides, deparaffinized, and stained with eosin stain and hematoxylin [51,52].
## 2.5. Statistical Analysis
Graph Pad Prism software (San Diego, CA, USA) version 8.0 was used to perform the analysis statistically for the current investigation. Results of statistical analysis were abridged in terms of standard error mean (SEM). Data were analyzed using one-way analysis of variance (ANOVA)followed by Tukey’s post-hoc test and values at $p \leq 0.05$ were considered statistically significant.
## 3.1. Effects of Hirsutidinon Uric Acid, Urea, Creatinine, Urine Volume, BUN, and Cholesterol
Figure 1A–H shows the effect of hirsutidin on uric acid, urea, creatinine, urine volume, BUN, and cholesterol in Wistar with renal dysfunctionality induced by cisplatin administration. The serum levels of urea, uric acid, and creatinine in group II were remarkably higher compared to group I, indicating that group II experienced a notable change in the excretion of the aforementioned parameters. Similarly, the present study concurrently evaluated the parameters of urine such as creatinine, uric acid, and urine volume to identify the unsafe levels of the stated elements as an outcome of nephrotoxicity in rats induced by cisplatin. Group II showed a notable downregulation in urine creatinine, urine uric acid, and urine volume, with increased serum levels of urea, uric acid, and creatinine as compared with group I. Tukey’s post-hoc test revealed that group III significantly restored the raised level of urea in serum (F [3, 20] = 48.49, ($p \leq 0.0001$)), serum uric acid (F [3, 20] = 13.69, ($p \leq 0.0001$)), and serum creatinine level (F [3, 20] = 96.43, ($p \leq 0.0001$)) as compared to group II. Similarly, notable variations in group III were detected in the urine parameters such as creatine (F [3, 20] = 33.92, ($p \leq 0.0001$)), uric acid (F [3, 20] = 9.094, ($p \leq 0.0001$)), and urine volume (F [3, 20] = 7.118, ($p \leq 0.0001$)), as compared with group II. Group IV did not show any significant changes. We found that group II showed a substantial elevation in the levels of certain serum chemistry parameters such as BUN and cholesterol levels as compared to group I. Group III showed notable changes in the serum chemistry parameters with BUN (F [3, 20] = 167.2, ($p \leq 0.0001$)), and cholesterol (F [3, 20] = 12.39, ($p \leq 0.0001$)), in comparison to group II, as evidenced by Tukey’s post-hoc test. Group IV experienced no statistically significant changes compared to group I.
Effects of hisutidin on oxidative-stress parameters Hirsutidin effects on rat levels of non-enzymatic and enzymatic parameters against nephrotoxicity induced by cisplatin administration are depicted in Figure 2A–D. In the current analysis, group II exhibited substantial changes in several enzymatic activities along with levels of a range of non-enzymatic oxidative-stress biomarkers, which are linked to nephrotoxic events in the kidney tissues. Group II rats showed a remarkable decline in enzymatic activities, such as CAT and GSH, as well as the nonenzymatic biomarker level of SOD, which is regarded as a key biomarker for ROS, in the tissues of a kidney when compared with group-I rats. In addition, group II showed significantly increased levels of MDA, a crucial oxidative biomarker, in kidney tissue ($p \leq 0.05$). Tukey’s post-hoc test indicated that group III significantly restored the activities of several antioxidant enzymes parameters as compared to group II i.e., CAT (F [3, 20] = 16.73, ($p \leq 0.0001$)), GSH (F [3, 20] = 27.72, ($p \leq 0.0001$))and SOD(F [3, 20] = 41.96, ($p \leq 0.0001$))along with the normalized levels of oxidative stress indicators MDA (F [3, 20] = 57.31, ($p \leq 0.0001$)), which shows the significant variations related with nephrotoxicity induced in the models of animal for experimentations. The rats did not show significant changes in group IV compared to group I.
## 3.2. Effects of Hrisutidin on Inflammatory Markers
Figure 3A–C depict the impact of hirsutidin on anti-inflammatory markers in rats against the nephrotoxicity induced by cisplatin administration. Group II exhibited noticeably elevated tissue pro-inflammatory levels of cytokines, i.e., TNF-α, IL-1β, and NF-kB. Tukey’s post-hoc test revealed that group III rats showed a significant decline in the levels of inflammatory markers, i.e., TNF-α (F [3, 20] = 218.5, ($p \leq 0.0001$)), IL-1β (F [3, 20] = 59.06, ($p \leq 0.0001$)), and NF-kB (F [3, 20] = 119.9, ($p \leq 0.0001$)) in comparison to the group-II rats. Furthermore, group IV did not show any significant changes compared to group I.
## 3.3. Effects of Hirsutidin on Histopathological Investigations
Figure 4A–D displays the histopathological modifications caused by the administration of cisplatin and hirsutidin to kidney tissues. Group I and group IV showed that the glomerulus and tubules are normal with normal architecture. As a result, the kidneys of the group-II rats displayed extensive degeneration, acute tubular necrosis, hyaline casts, interstitial edema, and inflammatory cell infiltration with the disruption of normal architecture. In contrast, group-III rats showed less histopathologic damage than group I.
## 4. Discussion
Cisplatin is the most widely used drug in the treatment of different cancers and solid tumors. However, the main obstacle to the widespread clinical use of this drug as a long-term treatment is the fact that it causes nephrotoxicity [30,53,54]. The nephrotoxicity caused by cisplatin is well-known to be caused, in part, by oxidative stress and inflammation, both of which play a significant role in the development of nephrotoxicity [55,56,57]. This study was conducted to reveal whether hirsutidin can be used to prevent the development of kidney damage by cisplatin-induced nephrotoxicity.
ROS are produced as a result of the inhibition of anticancer medication for the respiratory complex of mitochondria in renal tubular cells, which leads to tissue and organ damage [22,58,59]. Lipid peroxidation, as well as modifications to the enzymatic and nonenzymatic antioxidant systems along with alterations in gene expression, have been brought on by oxidative stress arising in renal tissue and the production of ROS [30,60]. It is considered that oxidative stress and inflammation are linked to abnormalities in the structure and functioning of renal tissue. Chemokines such as TNF-α were responsible for causing inflammation. Apoptosis is involved in nephrotoxicity caused due to cisplatin administration, as evidenced by the previous literature [61,62].
Past research has shown that cisplatin is recognized by most people to induce acute renal impairment [30]. This is the cellular process underlying kidney injury etiology [7,63]. Additionally, clinical concepts are advanced that contend that any structural and functional anomalies found in renal tissues are related to the emergence of inflammatory and oxidative stress. The current study looked at the potential nephroprotective effectiveness of hirsutidin against cisplatin-induced renal damage in rats. Cisplatin-induced neurotoxicity has been associated with damage to mitochondria and nuclei. In the current study, the experimental animal paradigm was used to examine the nephrotoxicity caused by cisplatin. As per the results of a previous study, several biomarkers are produced during the pathology of chemically induced nephrotoxicity. The changed amounts in non-protein-nitrogenous substances such as serum levels of urea, uric acid, and creatinine in the blood were also hypothesized by prior evidence [60].
Additionally, it was discovered that the levels of creatine in urine, the volume of urine, and the level of urine uric acid in experimental animal models were altered [64]. In the current study, we considered the kidney homogenate’s nonprotein-nitrogenous component levels. In the 25-day exploratory procedure, the administration of cisplatin significantly changed the amounts of the aforementioned non-protein components, elaborating upon the harmful impact of cisplatin on physiological activities. On the contrary, rats treated with hirsutidin (10 mg/kg) restored levels of all the biological components.
As high cholesterol levels might contribute to the onset of kidney disease, evaluating cholesterol levels is crucial for determining renal (kidney) function [65,66]. The filtering of waste from the bloodstream and the control of many chemicals, including cholesterol, are important functions of the kidneys [67,68]. The risk of cardiovascular disease increases when the kidneys are not working correctly because high cholesterol levels can cause plaque to accumulate in the arteries [69,70]. Numerous evidence-based studies point to the importance of blood chemistry in clinical signs of nephrotoxicity induced chemically [45]. According to previous research, changes in kidney function are linked to considerable variations in the level of several blood nephrotoxicity indicators, including BUN and serum cholesterol [71]. In this investigation, we found that the serum level of BUN and serum cholesterol were significantly impacted by the injection of cisplatin. The sensitive filters in the kidneys can also be harmed by an excess of cholesterol, which over time will result in a reduction in renal function [72,73]. Examining cholesterol levels can also reveal additional risk factors for kidney disease such as diabetes, high blood pressure, and a family history of kidney issues [74,75]. In line with this, we found in our study that doses of hirsutidin over the course of a protocol favorably improved their blood-chemistry profiles, indicating that hirsutidin may be a product of the nephroprotective effect in cisplatin-induced kidney damage.
These biochemical indicators have also notably highlighted the importance of non-protein-nitrogenous component estimation, blood-chemistry analysis, along with the concentrations of significant non-enzymatic and enzymatic biomarkers. With a primary emphasis on antioxidant enzymes such as CAT, GSH, MDA, and SOD in the tissues of the kidney, earlier investigations clarified the relevance of oxidative parameters in the etiology of nephrotoxicity. Furthermore, earlier research demonstrated that the activity of GSH, CAT, and SOD in the kidney tissues significantly decrease in cisplatin-induced nephrotoxicity. When examining the kidney profiles, however, dramatically increased amounts of MDA were discovered. In this study, we revealed that the kidney homogenate of the rat group that ingested cisplatin showed remarkable changes in the activity of GSH, CAT, and SOD together with higher levels of MDA. Post-treatment with hirsutidin for 25 days showed the restoration of the entire activity along with the levels of biomarkers, which is an indication of hirsutidin’s protective effects in the rats against cisplatin-induced nephrotoxicity.
Inflammatory markers play a very crucial role in the pathogenesis of nephrotoxicity induced by cisplatin administration [52]. The effect of the number of chemokines and inflammatory cytokines is elevated in the kidney after cisplatin ingestion [45]. Nuclear transcription factor NF-kB is mainly triggered by the cytokines IL-1β and TNF-α. The reduced NF-kB levels in the following study can perhaps be explained by the theoretical means: that cisplatin tends to cause NF-kB inhibition by binding the regions of “kB” that are the binding regions of NF-kB [51]. The expression of COX-2 which is linked to the proliferation of cells is mediated by the activated NF-kB [76]. The levels of TNF-α, IL-1β, and NF-kB were upregulated in cisplatin-treated rats in the present study. TNF-α triggers the receptor-dependent cascade of apoptosis after binding to its receptors through the activation of caspase-3. An administration of hirsutidin decreased the expression of TNF-α, IL-1β, and NF-kB. Hirsutidin improved renal histology with only mild swelling and vacuolations of epithelial lining renal tubules. The administration of hirsutidin revealed a relative improvement in the condition of histopathological damage induced by cisplatin [77,78]. In rats with warm renal injury, hirsutidin reduced acute tubular necrosis. Additionally, it reduced degeneration, hyaline casts, tubular necrosis, interstitial edema, and inflammatory cell infiltration in rats with contrast-induced nephropathy [78,79]. In our study, hirsutidin treatment significantly protected against nephrotoxicity caused by cisplatin treatment. Based on biochemical evidence and histological evidence, hirsutidin might be beneficial in reducing cisplatin toxicity due to its antioxidant and active ingredient properties. The present study showed that hirsutidin prevented cisplatin-induced kidney injury by modulating oxidative stress and marker enzymes. Furthermore, hirsutidin has been shown to reduce biochemical changes in the kidneys, such as increased levels of creatinine, urea, uric acid, and BUN. By reducing oxidative stress, hirsutidin helps to protect cells from damage caused by the harmful effects of ROS. Hirsutidin has been found to regulate the activity of marker enzymes involved in cellular metabolism, such as transaminases, inflammatory markers, and NF-kB, which can also play a role in preventing kidney injury. Long-term exposure to hirsutidin can provide a more comprehensive understanding of its effects and its mechanism of action. By conducting additional studies using techniques such as Western blotting, cell-based assays, and gene expression analyses, researchers can obtain a better idea of how hirsutidin impacts cellular processes and molecular mechanisms. Use of a small number of animals in the study is one of the limitations and makes it difficult to detect rare or indirect effects of hisutidin on the nephrological parameters.
## 5. Conclusions
The present study evaluated the data referring to the effect of hirsutidin’s potential nephroprotective activity, for the first time, to evaluate its ability to restore some biochemical indicators of oxidative stress with alter enzymatic and non-enzymatic components and change blood-chemistry profile information in cisplatin-induced neurotoxic effects. Additionally, hirsutidin might exhibit nephroprotective effects, as evidenced by its ameliorative efficacy in non-protein-nitrogenous components along with restoration of inflammatory markers altered as an outcome of induced nephrotoxicity. According to the aforementioned data, the natural supplement hirsutidin may have the potential to be an effective treatment for drug-related nephrotoxic side effects.
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|
---
title: Dieckol, Derived from the Edible Brown Algae Ecklonia cava, Attenuates Methylglyoxal-Associated
Diabetic Nephropathy by Suppressing AGE–RAGE Interaction
authors:
- Chi-Heung Cho
- Guijae Yoo
- Mingyeong Kim
- Ulfah Dwi Kurniawati
- In-Wook Choi
- Sang-Hoon Lee
journal: Antioxidants
year: 2023
pmcid: PMC10045168
doi: 10.3390/antiox12030593
license: CC BY 4.0
---
# Dieckol, Derived from the Edible Brown Algae Ecklonia cava, Attenuates Methylglyoxal-Associated Diabetic Nephropathy by Suppressing AGE–RAGE Interaction
## Abstract
The formation of advanced glycation end products (AGE) is linked to the pathogenesis of diabetic nephropathy. The aim of this work was to assess the therapeutic potential and underlying mechanism of action of dieckol (DK), isolated from Ecklonia cava, on renal damage induced by methylglyoxal (MGO) in mouse glomerular mesangial cells. The antiglycation properties of DK were evaluated using ELISA. We conducted molecular docking, immunofluorescence analysis, and Western blotting to confirm the mechanism by which DK prevents AGE-related diabetic nephropathy. DK treatment exhibited antiglycation properties through the inhibition of AGE production, inhibition of cross-linking between AGE and collagen, and breaking of its cross-linking. DK pretreatment exhibited protective effects on renal cells by suppressing MGO-induced intracellular reactive oxygen species (ROS) formation, intracellular MGO and AGE accumulation, activation of the apoptosis cascade and apoptosis-related protein expression, activation of receptor for AGE (RAGE) protein expression, and suppression of the glyoxalase system. Furthermore, DK exhibited a stronger binding affinity for RAGE than AGE, which was confirmed as exerting a competitive inhibitory effect on the AGE–RAGE interaction. These results demonstrated that DK is a potential natural AGE inhibitor that can be utilized to prevent and treat AGE-induced diabetic nephropathy.
## 1. Introduction
Diabetes mellitus (DM) is a chronic metabolic disorder that causes long-term damage to various organs by promoting secondary complications. Although diabetes is exacerbated by various factors, abnormally elevated synthesis and accumulation of advanced glycation end products (AGEs) in patients with chronic hyperglycemia is considered a trigger in the pathogenesis of chronic diabetic complications. AGEs are complex heterogeneous compounds that are naturally synthesized during the glycation reaction through several phases [1]. Increased accumulation of AGE in chronic hyperglycemic conditions leads to diverse diabetic complications, including retinopathy, neuropathy, and diabetic nephropathy. Diabetic nephropathy occurs in approximately 35–$45\%$ of patients with diabetes [2]. Particularly, intracellular glycation reaction, cross-linking with collagen, and AGE–RAGE (receptor for AGEs) interactions are known to be key mechanisms leading to AGE-related diabetic nephropathy. Therefore, AGEs are considered key biomarkers in patients with chronic hyperglycemia because they are responsible for the pathogenesis of diabetic complications [3,4]. Consequently, inhibiting AGE formation or aberrant accumulation, suppressing AGE–RAGE interaction, and regulating RAGE protein expression have been proposed as effective strategies for preventing or delaying AGE-induced diabetic complications.
Methylglyoxal (MGO), an α-dicarbonyl compound, is naturally produced by various metabolic pathways, including glycolysis. Moreover, MGO-derived AGE directly reacts with lysine and arginine residues in proteins, resulting in protein denaturation and dysfunction [5]. Furthermore, dicarbonyl stress by MGO increases oxidative damage to proteins, intracellular ROS generation, and renal cell apoptosis [6,7]. In addition, increased production of MGO and MGO-protein adducts is associated with the pathogenesis of diabetic nephropathy. Particularly, MGO accumulates in the kidneys and causes renal dysfunction, such as decreased glomerular filtration rate due to hypertrophy of the glomerular basement membrane [2,8]. MGO is converted to nontoxic D-lactate by the detoxification of glyoxalase-1 (Glo-1) in the kidney and is excreted. Since nuclear factor erythroid-2-related factor 2 (Nrf2) is involved in regulating the mRNA, protein, and activity of glo-1, Glo-1 enzyme activity is closely related to Nrf2 expression. Nrf2 is a transcription factor that mediates the antioxidant response element (ARE)-dependent activation of antioxidant enzymes, which play a critical role in protecting cells from oxidative stress-induced damage [2]. Therefore, upregulating Nrf2 not only promotes MGO detoxification through glo-1 activation, but also increases the expression of antioxidant enzymes, which can help suppress MGO-induced kidney dysfunction.
Ecklonia cava (E. cava) is an edible brown alga found along the Pacific coast around Jeju Island in Korea and is used as a food, cosmetic, and medicinal ingredient. E. cava is rich in bioactive components with various biological activities, such as fucoidans, phlorotannins, minerals, polysaccharides, dietary fiber, peptides, and carotenoids, and is used as a major ingredient in industrial applications in pharmaceuticals, cosmetics, and functional foods. Among the bioactive components found in E. cava, phlorotannin with a phloroglucinol structure has been demonstrated to exhibit diverse physiological activities such as anti-inflammatory, whitening, anticancer, antioxidant, and antibacterial properties [9,10]. Furthermore, E. cava and E. cava-derived phlorotannins have been shown to have antidiabetic activities by reducing human umbilical vein endothelial cell damage by hyperglycemia-induced glucotoxicity, activating both the AMPK/ACC and PI3K/Akt signaling pathways and inhibiting α-glucosidase and α-amylase activity, both in vitro and in vivo [2,9].
In this study, the therapeutic potential of dieckol isolated from E. cava on AGE-induced renal damage was evaluated through its antiglycation properties, AGE–RAGE interaction inhibitory ability, RAGE protein regulating ability, and antiapoptotic properties in mouse glomerular stromal cells.
## 2.1. Chemicals
Dieckol (DK) isolated from *Ecklonia cava* were kindly provided by Prof. You-Jin Jeon (Jeju Notional University, Republic of Korea) [11]. MGO and aminoguanidine (AG) were ordered from Sigma-Aldrich (St. Louis, MO, USA). Reagents used in all experiments were purchased in analytical grade. Information on the antibody used for Western blot is presented in Supplementary File (Table S1).
## 2.2. Antiglycation Property
To evaluate the antiglycation effect of DK, the inhibitory effect on AGE formation was evaluated by partially modifying the method of Kiho et al. [ 12]. Bovine serum albumin (10 mg/mL), glucose (2 M), and fructose (2 M) were dissolved in 50 mM phosphate-buffered saline (PBS, pH 7.4) containing $0.02\%$ (w/w) sodium azide and mixed with DK (1, 5, and 20 μM). Mixture was reacted at 37 °C for seven days. As a positive control, 50 mM PBS was added instead of DK, and aminoguanidine (AG, 0.5 mM) was used. AGE formation was measured using a fluorescence microplate reader (Molecular Devices, Sunnyvale, CA, USA) at 350 nm (excitation)/450 nm (emission).
To further evaluate the antiglycation ability of DK, the cross-link generation inhibitory effect between AGE and collagen was measured by slightly modifying the method of Do et al. [ 13]. Horseradish peroxidase-labeled (HRP) AGE (5 μg/mL) was mixed with DK (1, 5, and 20 μM), transferred to a collagen-coated 96-well plate, and cross-links formed between AGE and collagen at 37 °C for 18 h. AG (0.5 mM) was used as a positive control. Then, TMB substrate solution was added the reaction for 3 min.
To evaluate the breaking ability of DK on the cross-links formed between AGE and collagen, HRP-labeled AGE was reacted in a collagen-coated 96-well plate at 37 °C for 4 h to form a cross-link. Then, DK was added and reacted at 37 °C for 18 h. Alagebrium (ALT-711, 0.5 mg/mL), a cross-link breaker, was used as a positive control. After incubation, TMB substrate solution was added, the reaction was allowed to proceed for 3 min. The inhibiting and breaking abilities were measured using a microplate reader (Molecular Devices, Sunnyvale, CA, USA) at 450 nm.
## 2.3. Cell Culture
The mouse glomerular mesangial cells lines were obtained from the American Type Culture Collection. The mesangial cells were cultured DMEM/F12 medium containing $5\%$ (v/v) fetal bovine serum, 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES; 14 mM), penicillin (100 U/mL), and streptomycin (100 μg/mL) and was cultured under conditions of $5\%$ CO2, $95\%$ humidity, and 37 °C.
## 2.4. Cell Viability
The ability of DK to protect renal cells from MGO-induced oxidative stress was evaluated by MTT assay. Mesangial cells were seeded (3 × 104/well) in a 96-well plate and the plates were incubated under culture conditions (37 °C for 6 h). After treatment with DK (1, 5, and 20 μM) and incubation for 1 h, MGO (1 mM) was added and incubated at 37 °C for 23 h. AG (0.5 mM) was used as a positive control. After removing the supernatant, the MTT reagent was allowed to react for 3 h to form formazan The resulting formazan products from cells were dissolved with the addition of DMSO. The amount of MTT formazan was determined by measuring absorbance using a microplate reader (Infinite M200; Tecan Austria GmbH, Grödig, Austria) at 570 nm.
## 2.5. Intracellular ROS Production
The effect of DK on intracellular reactive oxygen species (ROS) production by MGO was performed by DCFH-DA assay with a modification of the method of Cho et al. [ 14]. Mesangial cells were seeded (3 × 104/well) in a 96-well plate and the plates incubated under culture conditions (at 37 °C for 6 h). After treatment with DK (1, 5, and 20 μM) and incubation for 1 h, MGO (1 mM) was added and incubated at 37 °C for 23 h. AG (0.5 mM) was used as a positive control. After removing the supernatant, the DCFH-DA reagent was allowed to react for 30 min. The intracellular ROS production was determined using a fluorescence microplate reader (Infinite M200; Tecan) at an excitation and emission wavelength of 485 and 530 nm, respectively.
## 2.6. In Silico Molecular Docking Study
Molecular docking studies were performed according to the CDOCKER protocol in Discovery Studio Software (BIOVIA Corp., CA, USA). CDOCKER is a molecular dynamics model based on the Chemistry at Harvard Macromolecular Mechanics (CHARMm) algorithm. The high-resolution crystal structure of RAGE (PDB code: 2MOV) was retrieved from the Protein Data Bank PDB (http://www.rcsb.org/pdb, access date: 16 April 2021). The RAGE was prepared by the “Clean protein” module in software. Incomplete amino acid residues were supplemented, hydrogens were added to the protein, and energy minimization was performed using the CHARMm force field. The RAGE substrate ligand methylglyoxal-derived hydroimidazolone-1 (MG-H1), AGE inhibitor AG (positive control), and DK were docked in a flexible manner to achieve a more realistic view of the possible protein–ligand interactions. The result was obtained from the calculated –CDOCKER energy (protein–ligand interaction, and the ligand strain energy). The score of the substrate ligand is one of the criteria for choosing a docked pose, with higher values indicating more favorable binding.
## 2.7. Intracellular MGO Concentration
To evaluate the inhibitory effect of DK on MGO accumulation in renal cells, ELISA was performed using Methylglyoxal Competitive kit (OxiSelect™; Cell Biolabs Inc. San Diego, CA, USA). Mesangial cells were seeded (1.0 × 106/well) in a 6-well plate and cultured for 6 h. To induce the intracellular MGO accumulation, MGO (1 mM) was added for 23 h after treatment with DK (1, 5, and 20 μM) for 1 h. AG (0.5 mM) was used as the positive control. The supernatant was removed, the cells were collected using trypsin-EDTA, and cell lysis was performed using PRO-PREP™ Protein Extraction Solution (iNtRON Biotechnology, Seongnam, Korea). The experiment was conducted as per the kit’s manual.
## 2.8. Intracellular AGEs Accumulation
To evaluate the inhibitory effect of DK on AGE accumulation in renal cells, AGE antibody/DAPI double-immunofluorescence analysis was performed. Mesangial cells were seeded (2.0 × 105/well) in a chamber slide and cultured for 6 h. To induce the intracellular accumulation of AGE, MGO (1 mM) was treated for 23 h after treatment with DK (1, 5, and 20 μM). AG (0.5 mM) was used as the positive control. After removing the supernatant, the cells were fixed using $4\%$ (v/v) formalin solution at 23 °C for 15 min. Then, $0.1\%$ (v/v) Triton X-100 was treated for 5 min. Blocking was performed using $1\%$ (v/v) BSA for 30 min. Thereafter, the cells were treated with AGE antibody and incubated at 4 °C for 24 h, followed by Alexa 288 secondary antibody at 23 °C for 2 h. Finally, after treating the cells with a mounting solution containing DAPI, AGE in renal cells was observed using a fluorescence microscope (Zeiss Axio Observer A1, ZEISS, Jena, Germany).
## 2.9. Apoptosis Analysis
The inhibitory effect of DK on MGO-induced renal cell apoptosis was evaluated using a MUSE flow cytometry system (Merck Millipore, Sydney, Australia). Mesangial cells were seeded (1.0 × 106/well) in a 6-well plate and cultured for 6 h. To induce cell apoptosis, MGO (1 mM) was treated for 23 h after treatment with DK (1, 5, and 20 μM). AG (0.5 mM) was used as the positive control. The supernatant was removed, and cells were collected using trypsin-EDTA and Muse™ Annexin V & Dead Cell reagent (Luminex, TX, USA). The inhibitory effect of DK on apoptosis induced by MGO-induced caspase $\frac{3}{7}$ activation was evaluated using the MUSE caspase $\frac{3}{7}$ assay kit. Total apoptotic cells (early and late apoptotic cells) and caspase $\frac{3}{7}$ activation were analyzed using a MUSE cell analyzer.
To visually confirm the inhibitory effect of DK on MGO-induced renal cell apoptosis, we used Hoechst 33342/PI double staining. Mesangial cells were seeded (2.0 × 105/well) in chamber slides and cultured for 6 h. To induce cell apoptosis, MGO (1 mM) was treated for 23 h after treatment with DK (1, 5, and 20 μM). AG (0.5 mM) was used as the positive control. After removed the supernatant, the cells were fixed in $4\%$ (v/v) formalin solution at 23 °C for 10 min. The cells were treated with $0.2\%$ (v/v) Triton X-100 for 10 min. Finally, the cells were stained with Hoechst 33342 (2 μg/mL) and PI (10 μg/mL) for 30 min. Renal cell apoptosis was observed using a fluorescence microscope (Zeiss Axio Observer A1, ZEISS, Jena, Germany).
## 2.10. Western Blot
The pretreated cells were scraped and proteins were extracted using PRO-PREP containing $1\%$ (v/v) protease and phosphatase. Protein samples were adjusted to the same amount by protein quantification and loaded onto gel (Any kD Mini-PROTEAN TGX Stain-Free Gel; Bio-Rad, Hercules, CA, USA); electrophoresis was performed at 200 volts. Proteins were then transferred to polyvinylidene difluoride membranes using the Transfer Kit (Trans-Blot Turbo RTA Mini 0.2 μm Nitrocellulose; Bio-Rad). After blocking the polyvinylidene difluoride membrane with $5\%$ (w/v) skim milk at 23 °C for 2 h, it reacted with primary antibodies at 4 °C for 24 h. Information on the antibody used for Western blot is presented in Supplementary File (Table S1). After sufficient washing of the membrane, it was reacted with a secondary antibody (HRP-labeled goat anti-rabbit IgG or goat anti-mouse IgG) at 23 °C for 2 h. Protein bands were measured using the ChemiDoc XRS + imaging system (Bio-Rad, CA, USA), and quantification of the measured proteins was performed using Image Lab software.
## 2.11. Statistical Analysis
All experiments were performed independently at least three times. The calculated results were expressed as mean ± standard deviation values. GraphPad Prism version 9.0 (GraphPad Software, Inc., San Diego, CA, USA) was used to statistically analyze and draw graphs. One-way analyses of variance followed by Tukey’s honestly significant difference test ($p \leq 0.05$) were applied to determine the significance of the differences among the means.
## 3.1. Antiglycation Property of DK
In this study, we evaluated the in vitro antiglycation properties of DK using a fluorescence-based AGE formation inhibitory assay. As shown in Figure 1A, incubation with DK (1, 5, and 20 μM) or AG (0.5 mM) significantly (*** $p \leq 0.001$) decreased AGE formation to 69.15 ± $0.47\%$, 42.49 ± $0.16\%$, 23.35 ± $0.36\%$, and 34.14 ± $0.58\%$, respectively, compared to the nontreated group.
To investigate the formation of AGE-collagen cross-link inhibitory properties of DK, we used ELISA. Treatment with DK (1, 5, and 20 μM) dose-dependently suppressed cross-linking (Figure 1B). Moreover, cotreatment with DK (20 μM) or AG (0.5 mM) significantly (*** $p \leq 0.001$) suppressed AGE-collagen cross-linking formation to 65.34 ± $2.35\%$ and 45.83 ± $1.44\%$, respectively.
We used ELISA to determine the strength of cross-link breaking to investigate AGE-collagen cross-link-breaking ability of DK. As shown in Figure 1C, treatment with AGE-BSA markedly increased AGE-collagen cross-linking, while treatment with DK at concentrations of 1, 5, and 20 μM dramatically decreased AGE-collagen cross-links to 87.57 ± $2.84\%$, 19.52 ± $1.45\%$, and 4.62 ± $0.51\%$, respectively. In particular, 20 μM DK treatment exhibited a more effective breaking ability than ALT-711, a representative cross-link breaker used as a positive control.
## 3.2. Protective Effect of DK against MGO-Induced Renal Damage
The viability of mouse glomerular mesangial cells was not significantly different from that of the control group after treatment with DK (1, 5, and 20 μM) for 24 h, indicating that DK was not toxic to mesangial cells under treatment conditions. Exposing mesangial cells to MGO induced an approximately $50\%$ decrease in cell viability (Figure 2A). However, pretreatment with DK exhibited a concentration-dependent effect on protecting mesangial cells from MGO-induced dicarbonyl stress, and 20 μM DK increased the viability to $63.6\%$ (### $p \leq 0.001$).
DCFH-DA is oxidized to the fluorescent compound DCF by oxidative stress in cells, which indirectly reflects the ROS levels in mesangial cells. MGO treatment induced overproduction of intracellular ROS to 427.43 ± $17.29\%$ in mesangial cells compared to the normal group (*** $p \leq 0.001$), while pretreatment with DK at concentrations of 1, 5, and 20 μM significantly suppressed MGO-induced intracellular ROS generation to 364.42 ± $3.80\%$, 284.27 ± $17.39\%$, and 154.63 ± $9.88\%$ (### $p \leq 0.001$), compared to the normal group (Figure 2B).
Treatment with 1 mM MGO increased the intracellular MGO cross-linked protein concentrations up to 75.55 ± 1.03 μg/mL in mesangial cells (*** $p \leq 0.001$) (Figure 2C). However, pretreatment with DK at concentrations of 1, 5, and 20 μM significantly decreased MGO-induced intracellular MGO accumulation to 28.28 ± 0.04, 20.84 ± 2.79, and 11.86 ± 1.74 μg/mL (### $p \leq 0.001$) in mesangial cells. AG (0.5 mM), used as the positive control, reduced the intracellular MGO concentration to 2.46 ± 0.04 μg/mL.
## 3.3. Molecular Docking Analtsis and Effect of DK on AGE/RAGE Axis in Renal Cells
RAGE is an AGE specific receptor that binds to AGEs and MGO, ultimately contributing to long-term oxidative damage and promoting diabetic nephropathy. Molecular docking estimates the ligand-receptor binding energy by exploring the 3D structure of the ligand employed within the active site of the receptor and evaluating key phenomena involved in the intermolecular recognition process [15]. In the present study, docking was performed for the three ligands (MG-H1, AG, and DK) identified in the literature to confirm the interaction of these ligands at the RAGE binding site. The residues involved in MG-H1-RAGE interactions were LYS32, CYS79, ASN92, ALA3, SER91, SER2, LYS90, and ARG78 (Figure 3A). AG bound to LYS32 and CYS79 of RAGE (Figure 3B). The amino acid residues involved in DK-RAGE were ARG78, LYS90, ARG94, SER91, CYS79, GLN80, ALA3, and LYS32 (Figure 3C). The binding energy of the ligand-RAGE interaction from the lowest to the highest was DK-RAGE, MG-H1-RAGE, and AG-RAGE, with energies of −27.8524 kcal/mol, −25.7807 kcal/mol, and −15.5972 kcal/mol, respectively. Interestingly, DK had relatively stable binding energy levels with RAGE at values of –CDOCKER energy lower than that of MG-H1. This result indicated that DK was able to compete with MG-H1 for binding to the active site of RAGE.
To confirm the mechanism of MGO-induced renal damage in mesangial cells, MGO-mediated RAGE protein expression was determined using western blotting (Figure 3D). RAGE protein expression was increased approximately 8.4 times by MGO treatment compared to the normal group. (*** $p \leq 0.001$). However, DK pretreatment dramatically decreased the expression levels of RAGE in mesangial cells 24 h after MGO stimulation compared to the MGO-treated group (### $p \leq 0.001$) (Figure 3E). The MGO-induced upregulation of RAGE expression was reduced in mesangial cells pretreated with DK (20 μM) or AG (0.5 mM) by 84.36 ± $1.65\%$ or 65.02 ± $0.87\%$, respectively, compared to the MGO group. To further confirm the effects of DK on the inhibition of intracellular AGEs accumulation, we performed immunofluorescence analysis using an AGEs antibody. AGEs were increased in mesangial cells cultured with 1 mM MGO, while pretreatment with DK (1, 5, and 20 μM) suppressed intracellular AGEs accumulation (Figure 3F).
These results demonstrate that DK has a competitive advantage over MGO in binding to the active site of RAGE, which may attenuate the AGE-RAGE interaction by suppressing the AGE-RAGE axis. Moreover, DK not only reduced the intracellular AGEs accumulation caused by MGO, but also decreased the downstream apoptosis cascade by suppressing the expression of RAGE protein in mesangial cells. Therefore, our results indicate that DK possesses strong potency to suppress AGE-mediated diabetic nephropathy.
## 3.4. Preventive Ability of DK against MGO-Induced Apoptotic Cell Death
The induction of apoptosis after treating the cells with MGO was determined using the Muse ™ Annexin V & Dead Cell Kit and flow cytometry (Figure 4A). MGO treatment (1 mM) induced abnormal apoptosis in mesangial cells, and the number of apoptotic cells dramatically increased to 65.03 ± $3.80\%$, compared with that of the normal group (5.12 ± $0.70\%$) (*** $p \leq 0.001$). Furthermore, we found that DK pretreatment significantly reduced the number of apoptotic cells in a dose-dependent manner compared to the MGO-treated group (### $p \leq 0.001$). All test concentrations of DK (1, 5, and 20 μM) had a significant preventive effect on MGO-induced mesangial cell apoptosis, compared with the MGO-treated group (### $p \leq 0.001$) (Figure 4B). In particular, 20 μM of DK was the most effective at protecting mesangial cells from MGO-induced toxicity, and the total apoptotic cell ratio (20.17 ± $1.56\%$) was close to that of the 0.5 mM AG group (positive control, 18.5 ± $2.52\%$).
The apoptotic cascade of cells is known to induce protein substrate cleavage and apoptotic cell death. Quantitative measurement of apoptotic cells by casepase-$\frac{3}{7}$ activation was performed using flow cytometry with the Muse™ Caspase $\frac{3}{7}$ assay kit (Figure 4C). Similar to the Annexin V assay, caspase-$\frac{3}{7}$ mediated apoptotic cell death was in-duced by MGO treatment, and the apoptotic cell ratio was significantly increased to 37.05 ± $1.84\%$ compared to that of the normal group (2.38 ± $0.33\%$) (Figure 4D) (*** $p \leq 0.001$). However, all the test concentrations of DK (1, 5, and 20 μM) dramatically decreased caspase-mediated apoptosis in a dose-dependent manner, compared to the MGO-treated group (### $p \leq 0.001$). Particularly, it was confirmed that 20 μM DK pretreatment suppressed the MGO-induced apoptotic cascade in mesangial cells, thereby maintaining a level of live cells comparable to that seen in the control group. Moreover, the total apoptotic cell ratio (6.90 ± $0.43\%$) in the 20 μM DK pretreatment group was close to that in the AG group (6.87 ± $0.20\%$).
To further confirm the inhibitory effects of DK on MGO-induced apoptotic cell death, mesangial cells were double stained with Hoechst 33258/PI. It was confirmed that MGO-treated cells showed increased characteristics of a typical apoptotic body. However, DK pretreatment dramatically reduced the number of apoptotic cells (Figure 4E). These results suggested that DK is a potential inhibitor of MGO-induced apoptosis in renal cells.
## 3.5. Effect of DK on the Apoptosis-Related Protein Expression
Flow cytometric analysis revealed that MGO treatment induced apoptosis in mouse glomerular mesangial cells, whereas DK pretreatment inhibited MGO-induced renal cell apoptosis. To further confirm the mechanism of the protective effects of DK on MGO-induced renal cell apoptosis, the expression of antiapoptotic (Bcl-2 and Bcl-xL), pro-apoptotic (Bax), cleaved caspase-3, and cleaved caspase-7 proteins was measured (Figure 5A). As shown in Figure 5B–F, MGO treatment resulted in a significant increase in Bax, cleaved caspase-3, and cleaved caspase-7 protein expression and a significant de-crease in Bcl-2 and Bcl-xL protein expression in mesangial cells (*** $p \leq 0.001$). In contrast, pretreatment with DK (1, 5, and 20 μM) reduced the expression of Bax, cleaved caspase-3, and cleaved caspase-7 and significantly increased the antiapoptotic protein expression (Bcl-2 and Bcl-xL), thereby exerting the effect of DK on suppressing apoptotic cell death of MGO-induced mesangial cells (### $p \leq 0.001$).
## 3.6. Effect of DK on Nrf2/Glo-1/ARE Signaling Pathway
Because MGO-induced oxidative stress is one of the major contributors to diabetic complications, increasing the expression of ROS-related proteins, such as Nrf2/Glo-1/ARE, is a promising strategy for alleviating/preventing AGE-induced nephropathy. To further confirm the protective effect of DK under MGO-treated conditions, we investigated the protein expression levels of ROS-related signaling pathways, such as Nrf2, Glo-1, HO-1, NQO1, CAT, and SOD1 in mesangial cells by Western blotting. Figure 6A shows that treatment with MGO markedly decreased the expression of Nrf2 protein in mesangial cells, while preincubation for 1 h with DK (1, 5, and 20 μM) and then stimulation with MGO (1 mM) for 23 h significantly increased the expression of Nrf2 compared to that in the MGO-treated group (# $p \leq 0.05$, ### $p \leq 0.001$) (Figure 5B). MGO treatment dramatically downregulated Glo-1 expression in mesangial cells, whereas pretreatment with DK significantly upregulated the MGO-induced reduction in Glo-1 protein expression at a concentration of 1–20 μM (### $p \leq 0.001$) (Figure 5C). The activation of Nrf2-regulated genes by DK pretreatment was further confirmed through the alteration of downstream gene expression, such as HO-1, NQO1, CAT, and SOD1 (Figure 6D–G). MGO treatment dramatically decreased the protein expression levels of HO-1, NQO1, CAT, and SOD1, while DK (1, 5, and 20 μM) pretreatment significantly reversed this trend compared to the MGO-treated group (### $p \leq 0.001$). These results indicate that DK can suppress MGO-induced Nrf2, Glo-1, and ARE reduction, which may be part of its cytoprotective mechanism in mesangial cells.
## 3.7. Effect of DK on MAPKs’ Phosphorylation
The phosphorylation-induced activation of MAPKs by MGO in mesangial cells is associated with an apoptotic cascade. Considering this, we further assessed the effect of DK on MAPK signaling phosphorylation, including ERK, p38, and JNK, during MGO-induced apoptosis using Western blotting (Figure 7A). As shown in Figure 7B–D, MGO treatment dramatically increased the levels of phosphorylated forms of ERK, p38, and JNK (*** $p \leq 0.001$). In contrast, pretreatment with DK (1, 5, and 20 μM) significantly decreased the phosphorylation of ERK, p38, and JNK in a dose-dependent manner (### $p \leq 0.001$).
## 4. Discussion
Advanced glycation end products (AGE) are yellow-brown compounds that are naturally formed by the glycation process, a nonenzymatic browning event in which the carbonyl groups of reducing sugars, such as glucose and fructose, as well as the amino group of proteins, form Schiff bases and Amadori products [3]. Furthermore, the heat treatment of food is an exogenous factor that generates AGE. Particularly, the production and accumulation of AGEs are promoted in diabetic patients who are continuously in a chronic hyperglycemic state, because blood glucose is the major source of carbonyl groups required for glycation reactions [16,17]. AGEs formed in the body have a strong affinity for long-lived proteins such as collagen. The formation of an irreversible bond by AGE-protein cross-linking not only accelerates the accumulation of AGEs in organs, but also directly causes aberrant protein structural modification. Furthermore, AGE-protein cross-linking induces diverse organ dysfunction through interfering with extracellular matrix–matrix and matrix–cell interactions in addition to AGE receptor-mediated mechanisms [18,19]. Many studies have revealed that the production and accumulation of AGEs in the basement membrane and endothelial and mesangial cells of the kidney are closely associated to the pathogenesis and progression of diabetic nephropathy (DN) [20]. Therefore, numerous researchers have postulated that inhibiting AGE formation, inhibiting AGE-collagen cross-links, and disrupting existing AGE-collagen cross-links are effective strategies for preventing AGE-associated DN. MGO is a dicarbonyl compound formed as a by-product of glycolysis and is one of the precursors required for AGE formation. Consequently, the MGO trapping reaction is regarded to be one of the mechanisms capable of effectively inhibiting AGE production. Several previous studies have demonstrated the antiglycation activity of terrestrial plant resources and bioactive compounds (phenolic and flavonoid compounds) derived from terrestrial plants [21,22]. Flavonoid compounds, in particular, are well known for their inhibitory effects on AGE generation via the MGO trapping reaction. Chlorogenic acid, quercitrin, and rutin isolated from *Houttuynia cordata* demonstrated a minimizing effect on AGE formation by creating mono- or di-MGO-conjugated adducts via the MGO trapping reaction [21]. Several studies have demonstrated that flavonoid compounds with specific structures, such as pyrocatechol, phloroglucinol, pyrogallol, and resorcinol, are more efficient than others at inhibiting AGE formation via MGO trapping [23,24,25]. Seaweed has traditionally been consumed, mostly in Asian coastal areas, and utilized as a traditional herbal medicine for a variety of ailments because it contains an abundance of physiologically active substances, such as polyphenols and polysaccharides. Recently, many scholars have been conducting research on the various physiological activities of seaweeds and their bioactive components. In particular, it has been demonstrated that polysaccharides (especially fucoidan), phlorotannins, and protein hydrolysates contained in seaweed can perform various biological functions, such as antidiabetic, anti-inflammatory, anticancer, antiviral, immunomodulatory, anticoagulant, antioxidant, antiobesity, and antiallergy [9,10]. Despite the abundance of bioactive substances in seaweed, little research has been conducted on its antiglycation activity. In a recent study, we revealed that seaweed has a strong antiglycation ability. Seaweed extracts exhibit antiglycation ability and brown algae have been proven to have a higher potential than red and green algae. Moreover, the antiglycation activity of seaweed was positively correlated with the content of phenolic and tannin substances among the bioactive components [26]. We reported that *Ecklonia cava* (edible brown algae; E. cava) extract, among seaweeds, is a rich source of bioactive substances that are effective in preventing DN caused by MGO-induced oxidative stress, as well as antiglycation reaction [27]. Because dieckol isolated from E. cava has a resorcinol structure, it is considered to have an inhibitory effect on AGE production through MGO trapping.
MGO, a highly reactive dicarbonyl intermediate metabolite among the precursors of AGE, has been linked to the development of diabetic microvascular complications, such as DN. The detoxifying processes of the body, such as the glyoxalase system, balance the AGEs produced in the body. Glo-1 overexpression not only suppresses intracellular MGO or MGO-derived AGE accumulation by improving the detoxifying ability in various cells, but it also promotes MGO conversion into nontoxic D-lactate [28]. Furthermore, stimulation of Glo-1 expression prevents the development of diabetic complications that are closely associated to microvascular complications by providing an enzymatic defense against MGO-mediated glycation. The accumulation of MGO and MGO-adducts induces toxicity in vascular endothelial cells and mesangial cells, triggering intracellular ROS production, apoptosis, and inflammation, ultimately leading to renal dysfunction [8,29]. MGO-induced RAGE protein expression triggers downstream signaling pathways, specifically promoting apoptosis via ROS-mediated MAPK phosphorylation, as well as apoptosis-related proteins such as Bax, Bcl, and cleaved caspase-3 [19,30]. Furthermore, when cells are subjected to oxidative stress caused by MGO, the interaction of the Nrf2-Keap1 complex in the cytoplasm is disrupted, and Nrf2 translocates to the nucleus, activating ARE-dependent genes such as HO-1, SOD, CAT, and NQO1. In the present study, MGO treatment not only reduced Nrf2 protein expression and the expression of Glo-1/ARE, a downstream signaling pathway, but also triggered an apoptotic cascade that caused renal cell damage [31,32].
The receptor for AGE (RAGE), a member of the immunoglobulin superfamily and an AGE-specific receptor, is closely implicated in diabetic complications caused by AGE. RAGE has been shown to be expressed in vascular cells, various types of epithelial cells, Müller cells in the retina, and almost all cell types in the kidney. A large body of evidence implies that DN is triggered by RAGE protein expression [3]. In particular, DN occurs in 35–$45\%$ of patients with diabetes and oxidative stress caused by AGE accumulation induces endothelial cell dysfunction, interstitial extracellular matrix deposition, and glomerular basement membrane thickening, resulting in glomerulosclerosis [19,33]. Moreover, various in vitro and in vivo studies have demonstrated that AGE–RAGE interaction stimulates intracellular ROS production and induces various signaling pathways, such as inflammation, fibrosis, and apoptosis [3]. Therefore, several researchers have attempted to elucidate the mechanisms involved in preventing or delaying the development of AGE-related DN. The inhibition of RAGE protein activation is considered the most important biomarker for the prevention of AGE-associated DN. Moreover, inhibition of AGE accumulation in renal cells and suppression of AGE–RAGE interactions are thought to be major mechanisms for DN prevention [19]. It was demonstrated that pretreatment of mesangial cells with E. cava extract not only suppressed MGO-induced AGE accumulation in renal cells, but also lowered RAGE protein expression [27]. In this study, molecular docking analysis demonstrated that the DK contained in E. cava had a comparative advantage over MG-H1 in the AGE–RAGE interaction and had competitive inhibitory potential. Moreover, DK pretreatment not only suppressed RAGE protein overexpression in mesangial cells caused by MGO treatment, but also protected kidney cells by stimulating the production of Glo-1, a detoxification enzyme. These results not only prove that DK can inhibit AGE-associated DN through various mechanisms, but also imply that DK is highly competitive in developing natural AGE inhibitors with low risk of side effects.
## 5. Conclusions
AGE is a complex and heterogeneous compound naturally produced by the glycation reaction of glucose and amino acids without the involvement of enzymes in the process of glucose metabolism. However, in the case of diabetic patients whose blood glucose concentration, a major component of AGE production, is continuously maintained at a high level, the production of AGE is accelerated and its accumulation in the body increases. *Excessive* generation of AGE beyond the level of detoxification in the body forms irreversible cross-links with long-lived proteins, such as collagen, and accumulates in the kidney, promoting the pathogenesis of AGE-associated DN. This study aimed to clarify the main mechanisms by which DK isolated from E. cava prevents AGE-related DN. Interestingly, molecular docking analysis demonstrated that DK has the potential to act as a competitive inhibitor of AGE–RAGE interaction, a key biomarker for the induction of AGE-mediated DN. Furthermore, DK was shown to protect renal cells from oxidative stress through the regulation of downstream signaling pathways, such as Nrf2/Glo-1/ARE, and apoptosis-related proteins regulated by the activation of RAGE expression in mouse glomerular mesangial cells. Consequently, we demonstrated that DK could prevent AGE-induced DN through various mechanisms and possesses potential as a therapeutic agent. However, this study evaluated the potential of DK for the prevention of diabetic nephropathy at the in vitro level using mouse glomerular mesangial cells, and it is considered necessary to verify it through in-depth research at the in vivo level.
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|
---
title: 'The Interaction between Circulating Cell-Free Mitochondrial DNA and Inflammatory
Cytokines in Predicting Human Mental Health Issue Risk in Adolescents: An Explorative
Study'
authors:
- Arto Alatalo
- Izaque de Sousa Maciel
- Nina Kucháriková
- Sweelin Chew
- Irene van Kamp
- Maria Foraster
- Jordi Julvez
- Katja M. Kanninen
journal: Biomedicines
year: 2023
pmcid: PMC10045177
doi: 10.3390/biomedicines11030818
license: CC BY 4.0
---
# The Interaction between Circulating Cell-Free Mitochondrial DNA and Inflammatory Cytokines in Predicting Human Mental Health Issue Risk in Adolescents: An Explorative Study
## Abstract
Adolescence is often a challenging time in which psychiatric issues have a strong connection to mental health disorders later in life. The early identification of the problems can reduce the burden of disease. To date, the effective identification of adolescents at risk of developing mental health problems remains understudied. Altogether, the interaction between circulating cell-free mtDNA (ccf-mtDNA) and inflammatory cytokines in adolescents is insufficiently understood regarding experienced mental health difficulties. Our study selected the participants based on the Strength and Difficulty Questionnaire (SDQ) score using the cut-off points of 3 and 18 for the low and the high score groups, respectively. The answers of the SDQ at the age of 12.2–15.7 years contributed to the investigation of (i) whether ccf-mtDNA units are associated with cytokines, and (ii) if an interaction model for predicting risk of mental health issues is observed. We discovered a sex-specific correlation between the screened markers associated with mental health problems in the low and high SDQ score groups among the male participants and in the low SDQ score group among the female participants. The mitochondrial MT-ND4 and MT-CO1 genes correlated significantly with interleukin-12p70 (IL-12p70) in males and with monocyte chemoattractant protein-1 (MCP-1) in females. Due to the nature of the explorative study, the studied markers alone did not indicate statistical significance for the prediction of mental health problems. Our analysis provided new insight into potential plasma-based biomarkers to predict mental health issues.
## 1. Introduction
The development of the brain is critical between the ages of 12 and 20 [1]. Due to the rapid development of the central nervous system and cortical control regions, excessive risk-taking behavior and psychiatric issues experienced in early adolescence have a strong link to mental health problems in adult life [2]. Prior to the COVID-19 pandemic, global statistics estimated the general prevalence of diagnosed mental health disorders to cause death or disability in the case of $13.5\%$ of 10-14-year-old (early) adolescents after diagnosis [3]. The pandemic further increased mental health problems due to social and physical restrictions—a study by Graupensperger et al. indicated significant increases in depression symptoms ($p \leq 0.01$) and loneliness ($p \leq 0.001$) during the initial phase of the COVID-19 pandemic [4]. Early identification of mental health problems is central to reducing the number of individuals that suffer from mental illness, improving the quality of life of affected individuals, and reducing socioeconomic costs. Approximately $50\%$ of young adults with the long-term NEET (not in education, employment, or training) status have been diagnosed with a psychiatric disorder in adolescence [5]. Hormone levels and the onset age of puberty have been widely studied as contributing factors to brain development between the sexes. Increased testosterone and dehydroepiandrosterone (DHEA) levels in males and estradiol levels in females are associated with physical changes as an indicator of puberty [6]. In particular, the development of psychiatric disorders around the time of the increased sex hormone levels may be sex-specifically implicated with brain development. Furthermore, biological, cognitive, and emotional differences can precede the expression of cognitive problems that are found to vary between males and females [7].
To date, a model combining psychiatric and molecular methods for the effective identification of individuals at heightened risk of developing mental health problems in adolescence does not exist. In psychiatric studies, the SDQ is used as a tool to determine a general score of problem behavior and to generate separate scores for emotional symptoms, conduct problems, hyperactivity, peer relationship problems, and prosocial behavior [8,9]. The low and high SDQ score groups can be categorized using a summary mental health index (the p-factor), which is described as a single-factor indicator that predisposes people to psychopathology [10]. The SDQ total scale is a commonly used general psychopathology measure [11]. A high p-factor score indicates larger life impairment, and poorer developmental histories [10]. Furthermore, the internalizing and externalizing sides of the p-factor measure observable symptoms of anxiety and disruptive behaviors of conduct disorder, respectively [11]. Detailed information on the SDQ scores is described in Materials and Methods.
The immune-inflammatory biomarker alterations are constantly associated with psychiatric conditions and negative clinical outcomes. Recent studies reported blood-based markers, including mitochondrial and cytokine contents, of major depressive disorder, bipolar disorder, and schizophrenia in adults [12,13]. In detail, mitochondria regulate energy production, lipid metabolism, and redox status as a part of maintaining cellular homeostasis. During cellular states of dyshomeostasis, mitochondrial respiration generates increased levels of reactive oxygen species (ROS), a phenomenon known to disturb cellular function and pathological conditions [14,15]. Excessive mitochondrial ROS (mtROS) also damages and fragments mitochondrial DNA (mtDNA) [15,16]. mtDNA has been described as an agonist of the immune system, via damage-associated molecular patterns (DAMPs) where dying cells release endogenous molecules into the extracellular environment [17]. The mtDNA fragments from the damaged mitochondria are released into the cytosol by autophagy. Cell-free mitochondrial DNA (cf-mtDNA) is recognized by the DAMP-specific receptors, including Toll-like receptors (TLRs), leading to the activation of immune cells, and the triggering of an inflammatory reaction [16,18]. Comprehensively, cytokines in plasma have been broadly identified as the prominent diagnostic biomarkers. For example, activated macrophages are a major source of cytokines and inflammatory mediators, of which interleukin-1 (IL-1) is produced early in the activation phase [19,20]. Along with the plasma samples, significant alteration of cytokines IL-1β, IL-6, IL-10, and IL-1RA was detected in the prefrontal cortex of depressed individuals who died by suicide compared with nonpsychiatric controls [21]. A correlation between cf-mtDNA levels and interleukin-4 (IL-4) produced by T-helper 2 (Th2) cells has previously been reported [13].
Cf-mtDNA becomes ccf-mtDNA when entering the extracellular fluids. Studies focusing on ccf-mtDNA unit alterations postulated this phenomenon as a potential indicator and diagnostic tool in early-stage screening and prognosis of mental disorders [13,22,23]. Kageyama et al. showed ccf-mtDNA levels to be significantly reduced in adults suffering from major depressive disorder (MDD) and bipolar disorder (BD) [13]. Similarly, Gonçalves et al. reported higher levels of plasma ccf-mtDNA are associated with later-life depression in individuals over the age of 60 [24]. Conversely, little information is known about the ccf-mtDNA levels in young individuals suffering from a mental disorder or psychological stress. Jeong et al. reported an increased but not significant difference in the ccf-mtDNA levels between the diagnostic groups of BD and the healthy controls at a mean age of 17.0 and 15.5 years old, respectively [25]. Therefore, the consensus on the potential of ccf-mtDNA as a predictive biomarker for mental health dysfunction is controversial. Furthermore, existing studies have not assessed how the sex of participants influences the ccf-mtDNA level.
Based on the reports that (i) childhood trauma is associated with elevated levels of pro-inflammatory cytokines [26], (ii) interleukin-10 (IL-10) is decreased in symptomatic adolescents with BD compared to healthy controls [27], and (iii) the reported nominal correlation between IL-4 and ccf-mtDNA level in adults with MDD [13], we hypothesized that there is a connection between ccf-mtDNA and inflammatory cytokines in adolescents experiencing internalized or externalized mental health outcomes. We investigated whether ccf-mtDNA levels are associated with inflammatory cytokines and can be used as biomarkers for predicting mental health issues in adolescents. Plasma levels of ccf-mtDNA and cytokines were measured in adolescents in the low and high SDQ groups. Here we report a sex-dependent correlation of the ccf-mtDNA unit with inflammatory cytokine levels in relation to the risk for mental health dysfunction. We summarize that the ccf-mtDNA unit is connected to IL-12p70 levels in males and MCP-1 levels in females. Together, these findings indicate novel biomarker panels for mental health risks in adolescents.
## 2.1. Cohort and Samples
Walnuts is a regional, controlled, randomized clinical Spanish cohort originally used for studies on the role of selected fatty acids from walnut intake associated with neuropsychological and physical health. For the current study, the SDQ-based subsamples were selected from the baseline population before the walnut intervention, as described in the next section. The study participants were from Barcelona, Spain, and none of them were taking medication at the time of participating in the study. The peripheral blood collection from all the participants was performed by following a standardized protocol during the school day in 2016–2018 [28]. Fasting samples were not included in the study. Blood was collected to EDTA Plus tubes (BD Biosciences, San Jose, CA, USA), inverted 6 times, and centrifuged at 2500 rcf for 20 min at 4 °C. The plasma layer was separated from the red blood and the buffy coat layers and collected to sterile tubes for storage at −80 °C prior to analyses.
## 2.2. Strengths and Difficulties Questionnaire and Eligibility Criteria
Approximately coincidentally with the collection of blood (Table 1), the participants filled out a self-reported version of the SDQ test. The questionnaire measured a general score of problem behavior and five subscales aimed to assess emotional symptoms, conduct problems, hyperactivity, peer relationship problems, and prosocial behavior [9]. The cut-off point of 18 for the high SDQ score group followed the recoded categorization of the SDQ score [8]. In the case of the low SDQ group, the cut-off point of 3 was selected manually to balance the size of each group (Table 1). The proportions of specific SDQ scores in the low and high groups are shown in Figure 1. The total SDQ score was calculated as a measure psychopathology index, summing hyperactivity, emotional symptoms, conduct problems, and peer problems [8,11]. SDQ is a well-established and widely used index to provide a score ranging from 0–40 (0–14 = low, 15–17 = borderline, 18–40 = high) [8,29].
## 2.3. Extraction and Quantification of Plasma ccf-mtDNA
Circulating cell-free genomic DNA was extracted from 200 μL of plasma by using the QIAamp MinElute Virus Spin Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. The final volume of the eluted ccf-mtDNA was 50 μL, from which the DNA concentration was measured with the NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). We focused on two mitochondrial genes that code for separate complexes of the electron transport chain. ND4 codes for complex I and CO1 codes for complex IV. TaqMan assays (Thermo Fisher, Carlsbad, CA, USA) were used to quantify two regions of human mtDNA in two replicate runs of qPCR. The ND4 and CO1 genes were quantified with TaqMan(R) Gene Expression assays Hs02596876_g1 and Hs02596864_g1, respectively (Table S1). The total reaction volume was 10 μL containing 5.0 μL of Maxima Probe/ROX qPCR Master Mix (Thermo Scientific, Carlsbad, CA, USA), 2.9 μL of the DNA template, 0.5 μL of primer, and 1.6 μL of nuclease-free water (Thermo Scientific, Carlsbad, CA, USA). The genomic DNA template was diluted to a concentration of 7.0 ng/μL with sterile water (Baxter, Mississauga, ON, Canada).
*The* gene quantification was performed using the StepOnePlus™ Real-Time PCR System (Applied Biosystems™, Carlsbad, CA, USA) for preparing the standard curves and running the extracted gDNA samples. The standard protocol for quantification included initial denaturation and holding steps at 50 °C for 2.0 min and 95 °C for 10 min followed by cycling steps at 95 °C for 15 s and 60 °C for 1.0 min for a total length of 40 cycles. All steps were performed as recommended by the manufacturer.
A standard curve was prepared to calculate and validate the unit of each mitochondrial gene by using commercially manufactured mtDNA plasmids according to the protocol of Applied Biosystems [30]. The plasmids for the standard curve were synthesized commercially (Azenta Life Sciences, Suzhou, China). The inserts of ND4 (233 nt) and CO1 (177 nt) genes were ligated into the pUC-GW-Amp plasmids during the manufacturing process (Figure S1). The concentration range of the standard curve was 3.0 × 108 to 3.0 × 104 unit/μL. The coefficient of determination had to be above 0.99 before the curve was approved. The unit level of plasma ccf-mtDNA was based on the standard curves of each quantified mtDNA region. Values are expressed in plasmid units per microliter of plasma.
## 2.4. Cytokine Bead Array
The secreted levels of cytokines in human plasma samples were measured using the Cytometric Bead Array (BD Biosciences, San Jose, CA, USA) along with Human Soluble Protein Master Buffer Kit (BD Biosciences, San Jose, CA, USA) according to the manufacturer´s protocol. IL-12p70 and monocyte chemoattractant protein-1 (MCP-1) were selected from the potential cytokines after screening. Cytokine measurement was performed with the CytoFLEX S Flow Cytometer (Beckman Coulter, Indianapolis, IN, USA). Acquired cytokine data were analyzed in the FCAP ArrayTM v2.0.1 software (Soft flow Inc., New Brighton, MN, USA).
## 2.5. Statistical Analyses
The ccf-mtDNA units were reported as mean ± standard deviation. The t-test along with inter-assay coefficients of variation was used to analyze differences between ND4 and CO1 unit levels. Unpaired Mann–Whitney U-test was used to compare means between the SDQ-based groups. All tests were two-tailed and a p-value ≤ 0.05 indicated a significant difference in means. A nonparametric Spearman’s Rho was used to analyze the correlation between SDQ scores, cytokine levels, and ccf-mtDNA unit. The ccf-mtDNA unit data were tested to confirm the usage of Spearman’s Rho by quantile–quantile plot (QQ plot), which indicated that the data are not following a Gaussian distribution. In the correlation analysis, 0.0 ≤ |r| ≤ 0.2 referred to no correlation, 0.2 < |r| ≤ 0.4 to the low correlation, 0.4 < |r| ≤ 0.6 to the moderate correlation, 0.6 < |r| ≤ 0.8 to the high correlation, and 0.8 < |r| ≤ 1.0 to the very high correlation. The absolute value of effect size was calculated using Cohen’s d. The values were divided into a small effect (d > 0.2), a medium effect (d > 0.5), and a large effect size (d > 0.8) [12]. All analyses were carried out in GraphPad Prism 9.1.1 (GraphPad Software, San Diego, CA, USA) or Microsoft Excel version 2122 (Microsoft, Redmond, WA, USA)
## 3.1. Ccf-mtDNA Unit Level Does Not Correlate with SDQ Scores or Sex in Adolescents
We first tested the difference in the unit levels between the mitochondrial CO1 and ND4 genes and no significant difference was observed ($$p \leq 0.185$$). Additionally, to verify a need for two ccf-mtDNA markers, we calculated $33.0\%$ and $37.8\%$ inter-assay coefficients of variation in the unit levels of ND4 and CO1 in the cases of the low SDQ score group and the high SDQ score group, respectively.
Next, we evaluated the relationship of the self-reported SDQ score and sex with the expression of the mitochondrial ND4 gene in plasma samples. There was no significant difference in ND4 levels between the low and high SDQ score groups (Figure 2a) or sexes (Figure 2b). The absolute value of effect size d was 0.424 and 0.047, as shown in Figure 2a,b, respectively. The correlation of ND4 unit levels and SDQ score did not indicate a significant correlation (Figure 2c; r = −0.177, $$p \leq 0.302$$). Subsequently, we analyzed the effects of the SDQ score and sex on the expression of the mitochondrial CO1 gene. There was no significant difference in CO1 gene expression between the low and high SDQ groups (Figure 2d) or sexes (Figure 2e). The absolute value of effect size d was 0.326 and 0.109, as shown in Figure 2d,e, respectively. CO1 unit levels and the SDQ score did not indicate significant correlations (Figure 2f; r = −0.252, $$p \leq 0.132$$).
## 3.2. Cytokine Levels Are Not Related to SDQ Scores or Sex in Adolescents
To assess whether cytokines were a potential indicator of the increased risk for mental health disorders in adolescents, we analyzed plasma levels of IL-12p70 and MCP-1. Both cytokines were described as the downstream cytokines of IL-1β in a DAMP-associated inflammation [31,32].
The effect of the self-reported SDQ score and sex on the cytokine level of IL-12p70 was studied using the cytokine bead array. There was no significant difference in IL-12p70 levels between the low and high SDQ score groups (Figure 3a), or between males and females (Figure 3b). The absolute value of effect size d was 0.624 and 0.219, as shown in Figure 3a,b, respectively. There was no significant correlation of IL-12p70 concentration and SDQ scores (Figure 3c; $r = 0.213$, $$p \leq 0.243$$). Similarly, MCP-1 levels were not affected by the SDQ score (Figure 3d) or sex (Figure 3e). The absolute value of effect size d was 0.237 and 0.160, as shown in Figure 3e,f, respectively. The correlation of MCP-1 concentration and the SDQ score was not significant (Figure 3f; r = −0.014, $$p \leq 0.934$$).
## 3.3. Mitochondrial Genes Correlate with IL-12p70 or MCP-1 in a Sex-Specific Fashion
We next analyzed the correlation between the ccf-mtDNA markers, ND4 and CO1, and inflammatory cytokines, IL-12p70 and MCP-1, separated by sex. In males, IL-12p70 correlated moderately with both ND4 (Figure 4a; $r = 0.476$, $$p \leq 0.122$$) and with CO1 (Figure 4b; $r = 0.518$, $$p \leq 0.089$$). Additionally, there was a low correlation between MCP-1 and ND4 (Figure 4c; $r = 0.306$, $$p \leq 0.288$$) and CO1 (Figure 4d; $r = 0.306$, $$p \leq 0.288$$). In females, only a low correlation between IL-12p70 and ND4 (Figure 4e; r = −0.230, $$p \leq 0.344$$) or CO1 (Figure 4f; r = −0.254, $$p \leq 0.280$$) was observed. Additionally, we found MCP-1 correlated moderately with both ND4 (Figure 4g; r = −0.593, $$p \leq 0.008$$) and CO1 (Figure 4h; r = −0.522, $$p \leq 0.018$$) in females.
Subsequently, we tested the interaction of the mitochondrial genes and inflammatory cytokines as described by Kageyama et al. [ 13]. The correlation between the ccf-mtDNA units and cytokine levels separated by sex were assessed by the Spearman’s Rho (Figure 4i). In male subjects, a very high positive correlation of both mitochondrial ND4 ($r = 0.600$, $$p \leq 0.242$$) and CO1 ($r = 0.829$, $$p \leq 0.058$$) with IL-12p70 were observed in the high SDQ score group. Additionally, a high positive correlation of both mitochondrial ND4 ($r = 0.691$, $$p \leq 0.069$$) and CO1 ($r = 0.762$, $$p \leq 0.037$$) with hMCP-1 was observed in males of the low SDQ score group. In females, a very high negative correlation of both mitochondrial ND4 (r = −0.917, $$p \leq 0.001$$) and CO1 (r = −0.800, $$p \leq 0.014$$) with MCP-1 was observed in the low SDQ score group. No significant correlations between mitochondrial genes and cytokines were observed in females with a high SDQ score. Furthermore, IL-12p70 was not significantly correlated to the mitochondrial genes of females in either the low or high SDQ score group.
## 4. Discussion
Here, we measured the correlation between ccf-mtDNA and cytokine markers, implicating a potential connection where the extracellular mtDNA may trigger an immune-inflammatory reaction in subjects at risk of psychopathology. The results indicate, on the whole, the existence of a specific correlation between the levels of ccf-mtDNA markers (ND4 and CO1) and inflammatory markers (IL-12p70 and MCP-1) to predict an increased risk for mental health issues compared with low-risk controls. Together, these findings indicate proposing novel biomarker panels for mental health risks in adolescents. Conversely, our study did not unveil the potential of using single ccf-mtDNAs or cytokines as predictive markers. Next, it is important to complete our predictive model by analyzing the role of other potential cytokine markers in the inflammatory pathway. To the best of our knowledge, this study reports for the first time how the risk of mental health issues in adolescents is connected to plasma ccf-mtDNA unit level, an indicator of oxidative stress, and cytokine levels, indicators of inflammation. Along with the analysis of the adolescent samples, we also provided insight into the inflammation process triggered by ccf-mtDNA, which is not affected by aging or chronic diseases. Our results suggest that inflammatory cytokine changes can potentially be associated with ccf-mtDNA markers in adolescents, but the association is sex-specific.
*The* genes of mitochondrial complex I (ND1-ND6) are the most studied genes of ccf-mtDNA associated with mental health disorders [12,13,25,33]. To date, little research has been conducted on the role of the genes encoding other mitochondrial complexes. Therefore, we decided to also perform quantitative analysis for the CO1 gene, part of complex IV, to discover whether the location of the gene can affect the results. The calculated inter-assay coefficient of variation in the ccf-mtDNA unit level was above $30\%$ to indicate the importance of measuring the unit level of both genes. Conversely, the t-test did not indicate significant differences between the unit levels of CO1 and ND4 ($$p \leq 0.185$$). However, the results from the coefficient of variation test provided a reason to test the expression of both genes in the plasma samples. Our results did not indicate significant variation in the unit levels of ND4 and CO1 between sexes or between the SDQ score groups (Figure 2), which emphasizes the reliability of the process. It also suggests that endogenous differences do not impact the quantification of the studied ccf-mtDNA genes. Additionally, a relatively small sample number affected the effect size of this study. The absolute value of effect size d was 0.33–0.42 between the low SDQ and high SDQ score groups in the quantification of mtDNA unit levels.
Previously, Lindqvist et al. and Kageyama et al. reported ccf-mtDNA units among adults with a diagnosed mental health disorder when compared to healthy controls. However, the Kageyama et al. paper reported a decrease, while the Lindqvist et al. study showed an increase in ccf-mtDNA level in individuals suffering from a mental disorder [12,13]. Moreover, Jeong et al., studied serum ccf-mtDNA unit levels in adolescents with a diagnosis of BD without finding significant differences when compared to healthy individuals [25]. Their findings on adolescents with an actual mental health disorder are in line with the results of our study, which indicated that ccf-mtDNA unit levels are not significantly altered in adolescents that are at risk of mental problems, as indicated by the results of the self-reported SDQ test. Based on these findings, we postulated that the SDQ score has utility in studies that focus on the risk of mental health, prior to an actual disease diagnosis. Along with our studies, the SDQ scores have also been used in earlier biomarker analyses to assess the risk of emotional and behavioral difficulties among children or adolescents [34,35]. Goodman and Goodman showed in their studies that children with higher total difficulty SDQ scores have greater psychopathology, which can be predictive of a disorder status three years later [36].
We investigated whether plasma ccf-mtDNA could trigger an inflammatory response, which may occur via the activated Toll-like receptor 9 (TLR9) [16]. Our study focused on measuring two pro-inflammatory cytokines (IL-12p70 and MCP-1) in the plasma samples. The heterodimeric IL-12p70 cytokine connects innate and adaptive immunity to stimulate T and natural killer (NK) cells [37]. Furthermore, interferon gamma (IFN-γ) serves as a signal to activate IL-12p70 production followed by the formation of a positive-feedback loop with IFN-γ [38,39]. On the other hand, IL-12p70 can be induced by pathogenic DNA [40]. Based on our results, both IL-12p70 and MCP-1 levels are associated with an increased risk of mental health issues, which has previously been highly understudied in the plasma samples. In addition, earlier studies indicated that excessive MCP-1 production can potentially favor Th2-specific immune responses [31]. When analyzing the plasma-based cytokines, we did not observe statistically significant differences between the low and high SDQ groups in the levels of IL-12p70 or MCP-1 in adolescents (Figure 3a,d). Additionally, plasma IL-12p70 and MCP-1 levels did not correlate significantly with the self-reported SDQ scores and, therefore, are not, on their own, sufficient biomarkers to predict an increased risk for mental health problems.
At this point, no studies have been conducted to point out straightforward correlations between ccf-mtDNA genes and IL-12p70 or MCP-1 in plasma. Nishimoto et al. indicated with animal studies that activation of the cfDNA-TLR9 pathway increases the expression of MCP-1 in macrophages [41]. A similar result was observed in the case of IL-12 production in dendritic cells [42]. Interestingly, our study revealed a sex-related difference in the results. We observed a clear effect of sex on the interaction of oxidative (ccf-mtDNA) and inflammatory (cytokine) markers. The direction of correlation was positive among the boys and negative among the girls. Surprisingly, the correlation was moderately high between the ccf-mtDNA markers and IL-12p70 among the boys (Figure 4a,b) but not among the girls (Figure 4e,f). Opposite results were found in the correlation analysis of MCP-1 with the ccf-mtDNA markers where the correlation was moderately high among the girls (Figure 4g,h) but not among boys (Figure 4c,d). When analyzing only the effect of the high SDQ score on the results, the units of ND4 and CO1 were highly or very highly positively correlated with the level of IL-12p70 but not with MCP-1 in male adolescents (Figure 4i). Among the female participants in the high SDQ score group, the correlation was negative and less significant between ND4 or CO1 and IL-12p70 or MCP-1 (Figure 4i) than in the male group. One possible explanation for the different results could be the contribution of the sex hormones and the stage of puberty. The mean ages for the blood sampling were 13.7 and 14.0 years for the male and female participants, respectively. In the case of the female participants, $85.7\%$ reported having their first periods before taking the SDQ test, while in males, only $16.7\%$ reported having started to develop facial hair before taking the SDQ test. Based on these reports, it is possible that the female participants were at a more advanced puberty stage at the time of testing, although their biological age was similar to the male participants. The sex-specific effect from hormones associated with the divergent oxidative stress and inflammatory pathway profiles between the male and female groups cannot be ruled out. Sex differences have previously been associated with mitochondrial- or mtDNA-related processes such as antioxidant defense, reactive oxygen species production, and immune response [43,44]. Pubertal hormonal (testosterone or estradiol) activity begins to increase cortical volumes earlier in girls than in boys [45]. Additionally, there are sex-specific differences in oxidative markers such as 8-oxoguanine (8-oxoG), GSH, and H2O2 associated with reactive oxygen species [46,47,48]. The role of pubertal hormones is most likely one of the main reasons why we observed a positive correlation between ccf-mtDNA markers and cytokines among boys and a negative correlation among girls (Figure 4). The hypothesis about the effect of sex hormones is supported by Carrascosa et al. in their Spanish longitudinal growth study, where the calculated mean onset age for the pubertal growth spurt was 11.97–12.96 years in boys and 9.91–10.90 years in girls [49]. Thus far, there have been very limited numbers of sex-specific studies to emphasize the difference of sex in the unit level of ccf-mtDNA associated with the risk of mental health issues or mental disorders in adolescents. However, Trumpff et al. reported higher serum ccf-mtDNA levels in middle-aged men than women in response to stress [33].
Despite the finding of a sex-specific significant correlation between biomarkers, a relatively small number of samples ($$n = 18$$–21 per group) together with unequal numbers of samples in the low and high SDQ groups and relatively low effect size are potential limitations of this explorative study. Therefore, we cannot exclude that the used n number could influence the statistical power of the analyses and conclusions. Kageyama et al. used 87–107 samples per group and Jeong et al. analyzed 105 samples [13,25]. Lindqvist et al. analyzed 37 plasma samples per group in their study with an effect size d of 2.55–4.01 [12]. Additionally, the sample preparation method including the duration and speed of centrifugation for plasma are described as affecting the ccf-mtDNA specificity by isolating different forms of ccf-mtDNA [23]. In our study, the same preparation method was used for all the plasma samples. We also quantified the nuclear DNA (nDNA) housekeeping gene levels in our plasma samples in order to eliminate possible contamination of different DNA material other than mtDNA. Furthermore, this study did not account for confounding factors such as mechanical tissue injuries or exercising, which have previously been linked to immediate and significant increases in ccf-mtDNA [50,51]. For example, an increase in the ccf-mtDNA level immediately after physical exercise was observed by Stawski et al. [ 52] and Beiter et al. [ 53] in men. Further studies could also focus on assessing the relationship between physical exercise and ccf-mtDNA in adolescents. Because the regular psychotropic medication is known to affect ccf-mtDNA levels [54], the participants of this study did not take any medication before donating the blood sample.
Our data about the interaction of the quantified ccf-mtDNA markers and the screened inflammatory cytokines (Figure 4) give, for the first time, an indicator of a potential pathway model to predict the risk of mental health issues in adolescents. The suggested framework for the interaction model is sex-specific, and it proposes that ccf-mtDNA triggers TLR9 followed by the activation of pro-inflammatory cytokines. However, based on the analyzed data, the correlation between ccf-mtDNA and cytokine markers is positive among boys and negative among girls. We believe that the observed sex-dependent changes are related to sex hormones and the stage of puberty. More studies are needed to verify the model and its function as a potential diagnostic tool.
## 5. Conclusions
In conclusion, our explorative study provides a new insight into potential plasma-based biomarkers to predict increased risk for mental health problems in children or adolescents. Our suggested model for connecting oxidative stress markers with pro-inflammatory cytokines is based on a relatively small number of samples used in this study. Further studies with a greater n number and specific information about the health issues and other lifestyle factors of participants are needed to validate the correlation analyses. A larger n number would also empower the effect size, which is smaller in our study than in other mtDNA-focused mental health issue studies. In addition, we were not able to assess the effect of sex-specific hormone levels on the observed results. However, studying blood-based markers in adolescents, without chronic diseases or long-lasting medication, which could affect the results, can be beneficial to limit the variation often observed with samples derived from adults. Further molecular level studies are needed to verify our suggested model, and to assess the role of sex hormones (testosterone or estradiol) in relation to ccf-mtDNA and cytokine levels in adolescents. We believe that our current findings can be used as a baseline for bigger cohort studies to set out detailed and comprehensive diagnostic models between oxidative and immune-inflammatory biomarkers associated with mental health issues.
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|
---
title: 'Flowers of Allium cepa L. as Nutraceuticals: Phenolic Composition and Anti-Obesity
and Antioxidant Effects in Caenorhabditis elegans'
authors:
- Cristina Moliner
- Sonia Núñez
- Guillermo Cásedas
- Marta Sofía Valero
- Maria Inês Dias
- Lillian Barros
- Víctor López
- Carlota Gómez-Rincón
journal: Antioxidants
year: 2023
pmcid: PMC10045179
doi: 10.3390/antiox12030720
license: CC BY 4.0
---
# Flowers of Allium cepa L. as Nutraceuticals: Phenolic Composition and Anti-Obesity and Antioxidant Effects in Caenorhabditis elegans
## Abstract
Allium cepa L., commonly known as onion, is one of the most-consumed vegetables. The benefits of the intake of its bulb are well studied and are related to its high polyphenol content. The flowers of onions are also edible; however, there are no studies about their biological properties. Our aim was to determine the polyphenolic profile and assess the antioxidant and anti-obesity capacity of an ethanolic extract from fresh flowers of A. cepa. The phenolic constituents were identified through LC-DAD-ESI/MSn. For the anti-obesity potential, the inhibitory activity against digestive enzymes was measured. Several in vitro assays were carried out to determine the antioxidant capacity. A Caenorhabditis elegans model was used to evaluate the effect of the extract on stress resistance and fat accumulation. For the first time, kaempferol and isorhamnetin glucosides were identified in the flowers. The extract reduced fat accumulation in the nematode and had a high lipase and α- glucosidase inhibitory activity. Regarding the antioxidant activity, the extract increased the survival rate of C. elegans exposed to lethal oxidative stress. Moreover, the activities of superoxide dismutase and catalase were enhanced by the extract. Our results demonstrate, for the first time, the antioxidant and anti-obesity activity of onion flowers and their potential use as functional foods and nutraceuticals.
## 1. Introduction
Bioactive compounds or extracts from plants have been used for health maintenance, control, and prevention of diseases since the earliest times. An example of this can be found in the management of overweight and obesity.
According to a report from the World Health Organization (WHO), overweight and obesity affect $60\%$ of adults and are also the leading risk factors for disability [1]. They are linked to an increased risk for many non-communicable diseases, such as metabolic syndrome, osteoarthritis, or respiratory disorders, which make them a major concern for public health. Pathogenic pathways of comorbidities associated with obesity are interconnected by different factors. Especially important is oxidative stress [2]. Thus, attenuating oxidative stress is a potential therapeutic target for obesity-associated diseases.
The current approach to counteract overweight and obesity comprises lifestyle modification (nutritional and exercise interventions), and, if it is necessary, it can also include the use of drugs and bariatric surgery. Even so, in most cases, the long-term results are modest. In this context, the use of functional foods and nutraceuticals has arisen as complementary to the classic therapeutical strategy [3,4].
The patterns of food consumption are changing during the last few years. An interest in ingredients and dietary supplements that are beneficial to well-being in a manner beyond a normal healthy diet has emerged [5]. The pursuit of new functional ingredients is very challenging due to the difficulty of carrying out clinical trials to prove health benefits [6]. Therefore, several in vivo systems are used for the study of efficacy and the mechanisms involved. Caenorhabditis elegans has emerged as a convenient model in nutrition research. In addition to its ease of handling, there is molecular conservation in signaling pathways between invertebrates and vertebrates, making this nematode species a powerful model organism [7].
Edible flowers are promising candidates for being used as nutraceuticals or functional foods due to their rich content of bioactive compounds. Flowers are a source of polyphenols, alkaloids and carotenoids, which are non-nutritive health-promoting compounds [8]. Despite this, their use is not widespread among the general population [9], although more and more are being consumed.
Allium cepa, popularly called onion, is one of the most-consumed species worldwide. Several studies have been carried out to determine the composition and biological activities of the bulb and other plant parts of this species, while their flowers remain poorly studied, even though they are also edible. Different plant parts of this species have demonstrated positive results in the treatment and prevention of obesity and associated disorders, such as diabetes, hypertension and hyperlipidemia [10,11,12].
For this reason, the present study aims to determine the polyphenolic composition of A. cepa flowers and provide an assessment of its anti-obesity and antioxidant capacity by exploring the effect on fat accumulation and protection against oxidative stress in C. elegans for the first time.
## 2.1. Standards and Reagents
Acetonitrile ($99.9\%$) was of HPLC grade and obtained from Fisher Scientific (Lisbon, Portugal). Phenolic compound standards (isorhamnetin-3-O-glucoside, kaempferol-3-O-glucoside, and quercetin-3-O-glucoside) were obtained from Extrasynthèse (Genay, France). Formic acid, bovine serum albumin (BSA), 2,2-diphenyl-1-picrylhydrazyl (DPPH), trolox, 2-2′-azobis(2-methyl-propionamidine)-di-hydrochloride (AAPH), 2,4,6-Tris(2-pyridyl)-1,3,5-triazine (TPTZ), xanthine, ferrous sulfate (FeSO4), CuSO4, α-glucosidase from Saccharomyces cerevisiae, 4-nitrophenyl α-D-glucopyranoside (pNPG), lipase from porcine pancreas, 4-nitrophenyl butyrate (NPB), and bicinchoninic acid were purchased from Sigma-Aldrich (St. Louis, MO, USA). A superoxide dismutase (SOD) assay kit and catalase (CAT) assay kit were purchased from Invitrogen (Barcelona, Spain), while RIPA buffer lysis was obtained from Thermo Scientific (Madrid, Spain). 5-hydroxy-1,4-naphthoquinone (juglone) was obtained from Alfa Aesar (Ward Hill, MA, USA), and Folin–Ciocalteu reagent was purchased from Chem-Lab (Zeldelgem, Belgium). The cOmplete Protease Inhibitor Cocktail, nitroblue tetrazoluzium (NBT) and xanthine oxidase were acquired from Vidrafoc (Barcelona, Spain). All other general laboratory reagents were purchased from Panreac Química S.L.U. (Barcelona, Spain). Water was treated in a Milli-Q water purification system (TGI Pure Water Systems, Greenville, SC, USA).
## 2.2. Plant Material and Soxhlet Extraction
Fresh flowers of A. cepa were harvested from an organic garden in the region of Zaragoza (Spain). A total of 50 g of sample were extracted in a *Soxhlet apparatus* using 1 L of ethanol for 4 h. After extraction, the solvent was removed with a rotatory evaporator, and the resulting extracts were stored in the dark at −20 °C.
## 2.3. Analysis of Phenolic Compounds
The phenolic profile was determined by LC-DAD-ESI/MSn (Dionex Ultimate 3000 UPLC, Thermo Scientific, San Jose, CA, USA). These compounds were separated using a Waters Spherisorb S3 ODS-2 C18 (3 μm, 4.6 mm × 150 mm, Waters, Milford, MA, USA) column thermostatted at 35 °C and identified as previously described [13].
The obtained extracts were re-dissolved at a concentration of 10 mg/mL with the methanol:water (80:20, v/v) mixture. A double online detection was performed using a DAD (280, 330, and 370 nm as preferred wavelengths) and a mass spectrometer (MS). The solvents used were: (A) $0.1\%$ formic acid in water and (B) acetonitrile. The elution gradient established was isocratic $15\%$ B (5 min), $15\%$ B to $20\%$ B (5 min), 20–$25\%$ B (10 min), 25–$35\%$ B (10 min), 35–$50\%$ B (10 min), and re-equilibration of the column, using a flow rate of 0.5 mL/min. The MS detection was performed in negative mode, using a Linear Ion Trap LTQ XL mass spectrometer (Thermo Finnigan, San Jose, CA, USA) equipped with an ESI source.
The identification of the phenolic compounds was performed based on their chromatographic behavior and UV-vis and mass spectra by comparison with standard compounds, when available, and data reported in the literature giving a tentative identification. Data acquisition was carried out with the *Xcalibur data* system (Thermo Finnigan, San Jose, CA, USA). For quantitative analysis, a calibration curve for each available phenolic standard was constructed based on the UV-vis signal. For the identified phenolic compounds for which a commercial standard was not available, the quantification was performed through the calibration curve of the most similar available standard. The results were expressed as mg/g of extract.
## 2.4.1. Inhibition of Pancreatic Lipase Assay
The ability of the extract to inhibit lipase was measured in 96-well plates [14]. The enzyme was diluted at a concentration of 2.5 mg/mL in 0.1 M TRIS base buffer with 5 mM CaCl2 (pH 7.0) and centrifugated at 2000× g for 7 min. A total of 40 µL of extract solution diluted in buffer, 40 µL of the enzyme, and 20 µL of buffered-substrate solution (10 mM of p-NPB) were mixed and incubated for 15 min at 37 °C. The range of extract concentrations was from 2000 to 62.5 µg/mL. Control wells were prepared by adding all reaction reagents using buffer instead of extract. Orlistat was used. Orlistat was first dissolved in ethanol at a concentration of 20 mg/mL, and afterward, serial dilutions were made in the buffer at the concentrations 1000, 100, 10, 1 and 0.1 µg/mL. Absorbance was read at 405 nm using Synergy H1 Hybrid Multi-Mode Reader (Winooski, VT, USA), and enzyme inhibition was calculated as percentage using the following Equation [1]. [ 1]Inhibition (%)=[(Abs control−Abs sample)Abs control]×100
## 2.4.2. Inhibition of α-Glucosidase Assay
α-glucosidase inhibition was assessed following the procedure of Cásedas et al. [ 15] in a 96-well microplate reader at 405 nm. Extract and acarbose (standard) were dissolved in buffer (12.5 mM Na2HPO4 and 3.3 mM NaH2PO4; pH = 6.9) in a range of concentrations between 1000 and 31.25 µg/mL. Each well contained 50 µL of sample and 100 µL of enzyme (1 U/mL in buffer). After 10 min, 50 µL pNPG 3 mM in buffer was added and incubated at 37 °C for 20 min. Control wells contained 50 µL of buffer. Acarbose was used as positive control. Absorbance was read, and inhibition was calculated using Equation [1].
## 2.5.1. Determination of Folin–Ciocalteu Reducing Capacity
The Folin–Ciocalteu reducing capacity was determined with the Folin–Ciocalteu method in a 96-well microplate as described by Zhang [16] with minor modifications. Briefly, Folin–Ciocalteu reagent (201 μL) was mixed with diluted extract (2.5, 5, and 10 μg/mL) in ethanol (9 μL) for 5 min in the dark at room temperature. Thereafter, $10\%$ Na2CO3 (90 μL) was added drop by drop to the mixture. The reaction was allowed to proceed for 40 min at room temperature in darkness. The absorbance of the solution was measured at 752 nm. Pyrogallol, dissolved in ethanol, was used as the standard to prepare a calibration curve (1–0.008 mg/mL); therefore, results were expressed as mg of pyrogallol equivalents (PE)/g extract.
## 2.5.2. DPPH Scavenging Activity
A DPPH assay was carried out following the description of Lopez [17]. The range of concentrations tested was 1000–31.25 μg/mL for the extract and 50–0.048 for ascorbic acid (standard solution). Both samples were dissolved in methanol. The reaction was initiated by adding 150 μL of DPPH dissolved in methanol (0.04 mg/mL) to 150 μL of sample dilutions. Control wells contained 150 μL of DPPH solution and 150 μL of solvent. The absorbance values were measured at 518 nm after 30 min of incubation in darkness at room temperature. The radical scavenging activity was determined as percentages according to Equation [1].
## 2.5.3. Superoxide Radical Scavenging Activity Assay
The superoxide (O2−) radical was produced by the xanthine/xanthine oxidase system. This assay was performed according to the procedure described in the literature adapted to 96-well microplates [18]. The extract and Trolox, used as standard, were dissolved in phosphate buffer (pH = 6.9) and diluted using a twofold dilution within a final concentration range of 500–15.62 μg/mL and 100–1.56 μg/mL, respectively. A total of 30 μL of the sample were mixed with 240 μL of 22.8 µM nitroblue tetrazolium (NBT), 90 µM xanthine, and 16 mM Na2CO3 in phosphate buffer. The reaction was initiated by adding 30 μL of xanthine oxidase (168 U/L). The mixture was allowed to stand for 5 min at 37 °C, and the absorbance was measured at 560 nm. The inhibitory xanthine oxidase activity of the extract was also assayed at 295 nm. The radical scavenging activity was calculated using Equation [1].
## 2.5.4. Ferric-Reducing Antioxidant Power (FRAP) Assay
This ferric-reducing ability of the extract was evaluated using a FRAP assay as described by Pulido [19] with minor modifications. The FRAP reagent was prepared daily and contained 10 mmol of TPTZ solution in 40 mmol/HCl, 20 mmol/L FeCl3·6H2O, and sodium acetate buffer (300 mmol/L, pH 3.6). A total of 30 μL of aqueous sample (1 mg/mL) was mixed with 90 μL of distilled water and 900 μL of FRAP reagent. The mixture was allowed to stand for 30 min at 37 °C. The absorbance was measured at 595 nm. A calibration curve was made with FeSO4·7H2O. FRAP value was expressed as μmol Fe2+/g extract.
## 2.5.5. Oxygen Radical Antioxidant Capacity (ORAC) Assay
The peroxyl radical scavenging activity of the extract was estimated by ORAC assay [20]. The ORAC assay was conducted using 96 black bottom well microplates using the Synergy H1 Hybrid Multi-Mode Reader (Winooski, VT, USA). In each well, 120 μL of fluorescein (70 mM), 20 μL of a dilution of extract, methanolic Trolox (standard), or phosphate-buffered saline (PBS; blank) were placed. The reaction was started by adding 60 μL of 2,2′-Azobis(2-amidinopropane) dihydrochloride (AAPH) 12 nM. The fluorescence was measured every 70 s for 93 min at 37 °C. The area under the curve (AUC) was calculated, and the ORAC value was obtained by interpolation in a calibration curve made with Trolox (0.002–0.0016 μmol). The results were expressed as μmol Trolox equivalent (TE)/mg extract.
## 2.6.1. Strains and Maintenance Conditions
The wild-type C. elegans strain (N2) and *Escherichia coli* OP50 were obtained from Caenorhabditis Genetics Center (CGC, Minnesota). C. elegans were propagated at 20 °C on Petri dishes containing nematode growth medium (NGM) with a lawn of E. coli OP50 as a food source. The synchronization of worms was achieved by preparing eggs from gravid adults using an alkali-bleaching method [21].
## 2.6.2. Assessment of Acute Toxicity
This assay was carried out following the method of Donkin and Williams with minor modifications [22]. After synchronization, wild-type worms were allowed to develop in NGM agar plates until larva stage 4 at 20 °C. At this moment, the plates were washed with K-medium (32 mM KCl, 51 mM NaCl), and the worms were re-suspended at a concentration of 80–120 worms/mL. Then, 200 μL of the worm/K-medium solution was transferred into each well of a 96-well plate. The extract was dissolved using K-medium. Fifty microliters of extract dilutions in K-medium (control) were added to the well. The survival of the worms was recorded after 24 h, and the results were expressed as a percentage of the survival rate. Approximately 40 worms per condition were tested in each assay.
## 2.6.3. Analysis of Body Fat Accumulation in C. elegans Obesity Model
An obese C. elegans model was designed after exposing the wild-type N2 worms to an excess of $5\%$ glucose in NGM. The conditions studied were: $5\%$ glucose as a positive control, $5\%$ glucose and 250 µg/mL of A. cepa flower extract, and plates without adding glucose as control. As a negative control substance, orlistat was used at 6 µg/mL [23]. The fat reduction obtained by this drug compared to the obese worm (positive control) was considered the maximum effect ($100\%$ reduction).
The effects of the extracts on C. elegans fat storages were studied by Nile Red staining and fluorimetry on the L4 stage. Synchronized L1 C. elegans (at least 300 individuals per condition) were grown for 48 h at 20 °C under different dietary conditions, as previously described. Total fat content was measured in nematodes by quantifying Nile Red staining images according to the previously described method [24]. This dye emits fluorescence when exposed to ultraviolet light (Nikon Intensilight C-HGFI), allowing the observation of lipids accumulated in intracellular droplets in worms. A total of 30–40 worms per condition were captured with a *Nikon camera* attached to an inverted Nikon Eclipse TS100 microscope after exposure to UV lightning using a GFP filter that captures 395 nm excitation and 508 nm emission wavelengths. All worms were photographed at 100× magnification and 20 s of exposure time. Images were analyzed using the image processing program ImageJ to obtain the relative fluorescence per area value of each worm.
## 2.6.4. Evaluation of Resistance to Oxidative Stress
The oxidation stress resistance assay was based on the method described by Surco-Laos with modifications [25], using juglone to induce lethal oxidative stress. In brief, synchronized L1 worms were transferred to Petri dishes containing different concentrations of flower extract (0, 50, 100, 250 and 500 μg/mL) and were cultivated for 48 h at 20 °C. After the exposure period, the worms were washed twice with sterile water and were transferred into new wells containing 150 μM of juglone. After 24 h, the survivors were scored. At least 120 worms per condition were evaluated in each assay.
## 2.6.5. Endogenous Antioxidant Enzymes
L1 larvae (50 nematodes/condition) were incubated in the presence of a range of concentrations of the extract (50–500 μg/mL) or in the absence of it at 20 °C. In addition, 48 h later, the nematodes were directly lysed or subjected to sublethal oxidative stress (juglone 150 μM in NGM, 1 h or 3 h) and were subsequently lysed. In order to carry out lysis, nematodes were washed twice with M9 and then mixed with RIPA buffer and cOmplete protease inhibitor cocktail. Then, the worms were disrupted by two cycles of freezing/thawing and centrifugated at 14,000× g 10 min at 4 °C. After centrifugation, the protein content of the supernatants was determined by the bicinchoninic acid (BCA) assays.
SOD and CAT activities were measured spectrophotometrically using commercially available kits. The activities of SOD and catalase were expressed as U/mg protein.
## 2.7. Statistical Analysis
All data come from three independent replicates. The results are reported as mean ± standard error of the means (SEM). IC50 values were estimated by using non-linear regression. A one-way ANOVA, Tukey’s multiple comparisons and unpaired Student’s t-tests were used to analyze statistical significance using GraphPad Prism version 6.0c (San Diego, CA, USA). Differences with p ≤ 0.05 were considered statistically significant.
## 3.1. Polyphenolic Composition of A. cepa Flowers
The extract was prepared from fresh flowers of A. cepa with a yield of $7.14\%$ (mass of extract/mass of fresh flowers).
The phenolic composition of the ethanolic extract of fresh flowers of A. cepa was performed using an LC-DAD-ESI/MSn, and the tentative identification and quantification are presented in Table 1. Seven phenolic compounds were identified, all identified as flavonols, mainly kaempferol and isorhamnetin glycoside derivates. Peaks 5 (kaemperol-3-O-glucoside), 6 (isorhamnetin-3-O-glucoside), and 1 (kaemperol-O-dihexoside) were the major compounds found in the extract. The phenolic profile of this part of the sample is slightly different from those reported for the bulb and peel, in which the main compounds present were quercetin glycosides [26,27]. The quantity of kaempferol and isorhamnetin derivatives found in the extract was higher than other species of flowers, such as Viola cornuta, Viola × wittrockiana, or Sambucus nigra, but less than the value reported for *Cytisus multiflorus* [28,29].
## 3.2. In Vitro Inhibition of α-Glucosidase and Pancreatic Lipase
The antiobesogenic potential was first evaluated through the in vitro inhibition of the lipase and α-glucosidase enzymes. IC50 values of samples and control substances (acarbose and orlistat) are presented in Table 2.
A. cepa flower extract showed α-glucosidase inhibition and pancreatic lipase inhibition; the percentages of inhibition were not as high as the control substances, but this activity should be taken in consideration.
Through the targeting of these digestive enzymes, the absorption of sugars and lipids can be reduced or controlled and therefore be useful in the management of parameters related to obesity, cardiovascular diseases, and diabetes. As stated by the European Medicines Agency [30], A. cepa has been seldom traditionally used to treat diabetes, but there are reports of its antihyperglycemic activity, cardiovascular benefits, and lipid-lowering effects.
Various studies have shown that onion extracts can exhibit inhibitory activity against the enzymes connected to metabolic syndrome and oxidative stress [31,32,33,34]. There are precedents for the inhibition of lipase and α-glucosidase by diverse parts of A. cepa, such as leaves [35], skin [34], and pulp [36], but to the best of our knowledge, this is the first time that these bioactivities have been proven in the flower extract. For lipase inhibition, the obtained IC50 value was lower than those described for the skin extract (53.70 mg/mL) or bulb juice (9.5 mg/mL) [31,35]. The IC50 value for α-glucosidase inhibition was higher; Nile et al. found an IC50 of 55.2 μg/mL for an ethanolic extract of solid onion waste (basal and apical trimming and outer skin parts) [33]. Our results suggest that A. cepa flower extract may serve as a potential source of natural lipase and α-glucosidase inhibitors.
## 3.3. In Vitro Antioxidant Activity
A. cepa flower extract was first tested in vitro through several antioxidant assays. The results are summarized in Table 3.
DPPH and O2− assays were used to assess the radical scavenging activity of the extract. A. cepa extract exhibited moderate activity in the DPPH assay. The maximum percentage of inhibition of DPPH was $94\%$ ± 1 at 1000 μg/mL. A higher power was found to neutralize the superoxide radical. This is an important fact because this radical is one of the most prevalent ROS in biological systems [37].
Beyond scavenging oxidants, the ability to perform reduction, especially of Fe2+, is also considered an important antioxidant mechanism [38]. To evaluate this, FRAP and Folin–Ciocalteau assays were carried out. The FRAP value was 6 ± 2 mmol Fe2+/g extract, while the reducing capacity quantified by the Folin–Ciocalteau method was 17 ± 2 mg PE/g extract. This method is known as a measure of the total phenolic content; however, due to the non-specificity of the reaction, it is more valuable to assess the total antioxidant-reducing activity. The Folin–Ciocalteau reagent is not only reduced by phenolic compounds, such as flavonoids; other compounds can also react against it, such as vitamins or proteins [39]. As a consequence, there is an overestimation of the total phenolic content compared with the value obtained with LC-DAD-ESI/MSn.
ORAC is one of the main assays to assess the hydrogen atom transfer of extracts. The ORAC value of the flower extract was 1 ± 0.1 μmol TE/mg extract. Xiong et al. determined the ORAC value of acetone extracts from 10 common edible flowers, and most of them showed a lower value than our data [40].
The comparison of our results with others reported in the literature about other parts of A. cepa is difficult due to the use of different units and methods for the antioxidant activity evaluation. These studies have shown a strong antioxidant activity of the skin, pulp and essential oil [41,42,43,44]. Our findings show promising activity also for the flowers of this species.
## 3.4. C. elegans Assays
In order to better understand the biological effects of this extract, the antioxidant and anti-obesity activity was assessed in C. elegans, as this nematode offers the possibility of detecting phenotypic changes.
## 3.4.1. Assessment of Acute Toxicity of Fresh Flowers
Initially, the effect of the extract on the viability of C. elegans N2 was carried out to evaluate its acute toxicity and to establish the range of non-toxic concentrations (Figure 1).
The range of concentrations of 50–750 μg/mL for 24 h did not affect viability as compared to the control group. However, the higher concentrations tested (1000 and 2000 μg/mL) had a negative impact on the viability of the nematodes ($p \leq 0.0001$). The mortality rate was increased by $19\%$ (1000 μg/mL) and $37\%$ (2000 μg/mL) with respect to the control without reaching the lethal dose 50 (LD50).
The nematicide power of the flower extract is scarce. This is the first time that the impact on C. elegans viability of A. cepa flowers has been described. No other studies have been found that evaluate this activity in other nematode species; however, there are two studies about the nematicidal action. One of them was carried out using onion oil, while the other one tested two purified oligosaccharides from onion bulb extract [45,46]. As commented previously, there is a difference in the phytochemicals present in different parts of the plant, and these differences also depend on the extraction technique.
## 3.4.2. A. cepa Flower Extract Decreased Fat Accumulation
C. elegans is a great model for exploring lipid metabolism because the regulatory pathways of energy homeostasis are highly conserved between mammals and this nematode. Numerous studies have shown that C. elegans is an excellent tool in the search for bioactive compounds that allow modulating lipid metabolism, contributing to the control of obesity [47,48,49].
As can be seen in Figure 2, glucose supplementation increases fat deposits in obese control worms by $31.8\%$ compared to control animals ($p \leq 0.001$), validating the designed in vivo model. On the other hand, our results show that treatment with orlistat, the reference drug, or the extract of A. cepa flowers effectively reverses this effect. The dietary addition of 250 μg/mL of A. cepa flower extract reduced the fat deposits in the treated worms by $18.2\%$ compared to the obese control without treatment ($p \leq 0.05$). A similar effect was observed in the group treated with orlistat, the reference drug, which produced a reduction in lipid content of $34.6\%$ ($p \leq 0.0001$). For both treatments, no statistical differences were achieved in the non-obese worms (control group), which suggests that onion flower extract, as orlistat, allows the reduction of fatty deposits to physiological levels in the C. elegans N2 strain.
Energy homeostasis is a highly complex phenomenon whose regulation is influenced by numerous factors. In C. elegans, more than 400 genes involved in the maintenance of body reserves have been described. Many of these pathways are highly conserved in humans, so in recent years, a considerable number of authors have used this model in the study of fat metabolism and obesity [48]. Recent research has shown that phenolic compounds can reduce fatty deposits in C. elegans by increasing lipolysis or reducing lipogenesis through different mechanisms controlled by several genetic pathways. The in vivo obesity model used in this study does not allow the identification of a specific mechanism of action for the decrease in total fat observed in worms treated with A. cepa. However, the identification in the extract of kaempferol and isorhamnetin derivates as major components suggests that these compounds, whose anti-obesity effect has been previously described, could be responsible for the observed activity [47,48]. Thereby, Farrias-Pereira et al. showed that isorhamnetin reduces fat accumulation in C. elegans by increasing fat oxidation [48]. This effect was dependent on the nhr-49 pathway, which is involved in fatty acid β-oxidation and lipolysis. As is well known, fat accumulation increases oxidative stress damage, and on the contrary, an increase in ROS production leads to an excessive accumulation of fat [50]. The clear antioxidant effect shown by the extract could contribute to the observed anti-obesity effect.
## 3.4.3. Onion Flower Extract Attenuates the Oxidative Stress Toxicity Induced by Juglone
The protective activity of the extract of A. cepa flowers against oxidative stress was evaluated by exposing C. elegans to a lethal dose of juglone. Juglone is a powerful pro-oxidant, which increases the generation of intracellular superoxide radicals that can damage cellular components [51]. As shown in Figure 3, the pre-treatment with A. cepa significantly increased the survival rate of nematodes, protecting them from oxidative stress. The best response was found in the group treated with 500 µg/mL of flower extract, for which the survival rate was increased from $0.4\%$ ± 0.3 (control group) to $13\%$ ± 3.
Our results reveal a protective potential for A. cepa flowers against oxidative stress, which is in concordance with the in vitro assays described above and the phenolic composition. To the best of our knowledge, this is the first study of the antioxidant potential of A. cepa using C. elegans. The polyphenols present in the extract have shown a protective effect against oxidative stress on this model organism. Kampkötter et al. showed that kaempferol decreases the accumulation of ROS and oxidative stress [52]. Similar findings were also made in assays performed with isorhamnetin, which increased the survival rate of nematodes after juglone exposure by around $15\%$ [53].
## 3.4.4. Impact of the Extract on Endogenous Antioxidant Enzyme Activities
The antioxidant enzymes catalase (CAT) and superoxide dismutase (SOD) are the main defense system against oxidative injury. The inductions of these antioxidant enzymes are potential pharmacology targets to attenuate ROS-induced damage related to cardiovascular or neurodegenerative disorders [54]. Both enzymes are highly conserved in the nematode C. elegans [55].
The effect of A. cepa extract on SOD and CAT activities was determined on C. elegans (Figure 4). After 48 h of treatment with the extract, the results revealed a significant increase in the activity of both enzymes with respect to the control group. The best response was found in the group treated with 500 µg/mL leading to a 4.3 and 2.3-fold increment for SOD and CAT activity compared to the control worms, respectively. The 250 µg/mL group also increased SOD activity (3.8-fold) without having a significant effect on the CAT activity against the control group.
To deepen the protective effect of the extract against juglone damage, the activity of these endogenous antioxidant enzymes was determined after inducing a sublethal oxidative stress. In order to observe the differences over time, worms were exposed to juglone 150 μM for 1 h or 3 h, and the results are shown in Figure 5. In both cases, the exposition to juglone for 1 h causes a significant increase in their activity to counteract the free radicals generated by juglone. However, after 3 h of exposure, the assessment showed a significant reduction in SOD and CAT. This fact was not observed in the nematodes treated with the extracts, in which no statistical differences in enzymatic activity between the different times were found. CAT and SOD levels remained constant. This could be related to the positive effect on the survival rate of nematodes exposed to a lethal oxidative stress. However, no statistical differences were found between the different groups in the same exposure time.
Previous studies found similar effects in SOD and CAT activities of other parts of the plant using cell cultures, rats, and rabbits [56,57,58]. These enzymes are biomarkers of antioxidant defenses of the organisms.
A. cepa flowers exhibit a protective effect against juglone toxicity supported by in vitro assays. However, the results obtained from the endogenous enzymes are insufficient to explain the implied antioxidant mechanism, which should be further clarified in the future.
The use of functional foods and nutraceuticals as non-pharmacological interventions has a great potential for reducing obesity, oxidative stress, and associated comorbidities. Certain clinical trials are using A. cepa as a dietary intervention, such as the study performed by Jeon et al.; in this study, overweight South Korean patients received supplementation with steamed onion, which caused a decrease in total body fat and an improvement in metabolic parameters [12]. These encouraging results support the need to continue the research on the different edible parts of onions and related vegetables.
## 4. Conclusions
We demonstrated, for the first time, the potential use of onion flowers as a functional food due to the presence of polyphenols and their antioxidant and anti-obesity activities exhibited in vitro and in vivo. A. cepa flowers are a rich source of kaempferol and isorhamnetin glycoside derivatives. The extract has demonstrated lipase and α-glucosidase inhibiting properties, as well as the ability to mitigate the fat accumulation and toxicity induced by oxidative stress in C. elegans. This work put forward the idea of using certain flowers of plant foods as edible, healthy ingredients with health-promoting properties.
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|
---
title: Assessment of Metabolic Parameters in Female Triathletes with Hashimoto’s Thyroiditis
in Poland
authors:
- Marcin Gierach
- Roman Junik
journal: Biomedicines
year: 2023
pmcid: PMC10045185
doi: 10.3390/biomedicines11030769
license: CC BY 4.0
---
# Assessment of Metabolic Parameters in Female Triathletes with Hashimoto’s Thyroiditis in Poland
## Abstract
Background: *Hypothyroidism is* a complex disorder characterized by an increase in body weight. About 15–$30\%$ of hypothyroid patients are reported to be overweight. The triathlon is an endurance combination sport that comprises a sequential swim, cycle, and run. Triathletes must withstand high training loads with various combinations of intensity and volume. Adequate body structure, the ratio of fat and muscle tissue, and adequate hydration play a huge role. The aim of our study was to show the potential differences in metabolic parameters assessed by medical Body Composition Analyzer before the initiation of treatment with L-thyroxine and after 3 and 6 months of treatment in females who practiced triathlon and who were newly diagnosed with Hashimoto’s thyroiditis. Methods: The study group included 32 females practicing triathlon. They were recruited for 10 months from March to December 2021. Analysis of anthropometric measurements was performed using a seca device mBCA 515 medical Body Composition Analyzer. Results: We observed significant differences in FM and VAT before and after L-thyroxine treatment. We also noticed lower BMI levels after treatment, along with significant differences in thyroid function tests (TSH and fT4) carried out during the recruitment period and after 3 and 6 months of treatment. Conclusion: Due to their higher daily energy consumption, further research is needed into the treatment of Hashimoto’s thyroiditis in athletes who practice triathlon. Frequent bioelectrical impedance analysis of body composition during treatment can be very helpful.
## 1. Introduction
In Poland, up to $22\%$ of the population may have thyroid problems. This mainly applies to women [1]. Hypothyroidism is one of the most common thyroid disorders and is often caused by chronic autoimmune inflammation—affecting approximately 4–$10\%$ of the population—characterized by the production of anti-thyroid peroxidase antibodies (TPOAb) and anti-thyroglobulin antibodies (TgAb) [2]. Hashimoto’s thyroiditis (HT) is a polygenic disease with still not fully defined etiopathogenesis. In Poland, we observe a constant increase in the incidence of this disease in the female population of all ages, but especially in young women of childbearing age. Women are about eight times more likely to develop HT than men.
Thyroid dysfunction (hypothyroidism) not only alters the appetite and makes it difficult to maintain normal body weight, but it also affects body composition, regardless of physical activity.
Thyroid hormones (triiodothyronine-T3, thyroxine-T4) are considered to be strong modulators of thermogenesis, and their deficiency predisposes to the development of central obesity [3,4,5]. Even subclinical hypothyroidism may affect weight gain, so it can be a risk factor for overweight and obesity.
Many studies concerning the association between thyroid dysfunction and changes in body weight are based on the analysis of elementary indicators, for example, body weight or body mass index (BMI) [6,7,8,9]. There is a need for a more thorough analysis of these parameters, to enable information to be obtained on the content of muscle tissue, water, and fat in the body.
Triathlon is a combined endurance sport that involves sequential swimming, transition from swimming to cycling (T1), cycling, transition from cycling to running (T2), and running various “long” or “short” distances [10]. Triathletes have to endure high training loads with various combinations of intensity and volume [11]. Adequate body structure, the ratio of fat and muscle tissue, and adequate hydration play a huge role.
The aim of our study was to show the potential differences in the metabolic parameters assessed by medical Body Composition Analyzer (mBCA) before the initiation of treatment with L-thyroxine and after 3 and 6 months of treatment in females with newly diagnosed Hashimoto’s thyroiditis (HT), who were practicing triathlon.
## 2.1. Participants
The study group included 32 females practicing triathlon. They were recruited for 10 months from March to December 2021 by the Cardiometabolic Center Gierach-Med in Bydgoszcz, Poland and the Department of Endocrinology and Diabetology Collegium Medicum University of Nicolaus Copernicus in Bydgoszcz, Poland. All the patients provided verbal consent to participate in the study. The mean age of the women studied was 33 years, and standard deviation was ±4.76 years. The average height of the triathletes was 169.6 ± 4.7 cm, body weight was 68.05 ± 4.83 kg, and BMI was 23.78 ± 1.02 kg/m2. The average number of hours a week spent on training by the participants was 8.71 ± 1.26 h.
Exclusion criteria for the study were patients using drugs which could affect thyroid functions, such as lithium, amiodarone, steroids, beta blockers, or interferon; patients using drugs which could affect body water–lipid homeostasis, such as diuretics or oral contraceptives; smoking, chronic renal failure, hepatic failure, congestive heart diseases, malnutrition, malignant diseases, pregnant women, and patients with other known endocrine disorders.
## 2.2. Body Composition Analysis
Analysis of the anthropometric measurements was performed using a seca device mBCA 515 medical Body Composition Analyzer. The measurements were taken three times (during recruitment, then at 3 and 6 months after initiation of L-thyroxine treatment) in the morning on an empty stomach. There was no training the day before the study. Participants were also informed not to consume alcohol 24 h before the measurements, and not to consume caffeine, including beverages, 4 h before the measurements, in accordance with the manufacturer’s instructions. All participants wore light clothing, and earrings, rings, bracelets, and any metal which could influence the results, were removed before the measurements were taken.
The device measures the composition of the body by bioelectrical impedance analysis (BIA), using a pair of electrodes for each hand and foot. The performance and accuracy of every BIA device depends directly on its validation and reference data, and seca mBCA passed an extensive scientific validation process [12,13,14,15]. We assessed the following parameters: body mass index (BMI); fat mass (FM); fat-free mass (FFM); skeletal muscle mass (SMM); total body water (TBW); extracellular water (ECW); resistance (BIWA); visceral adipose tissue (VAT).
Patients were then started on L-thyroxine supplements. The dose of the drug was increased periodically (every 4–6 weeks) stepwise, based on TSH estimations, until the patients were rendered euthyroid, that is, had a TSH level between 0.5 and 4.5 µIU/l. The mean dose during the study was 65.5 µg per day with a standard deviation (SD) ± 12.3 µg. The subjects were advised not to change their dietary and exercise habits. The characteristics of the study group are presented in Table 1.
## 2.3. Thyroid Gland Ultrasonography
The measurement of the thyroid gland was performed using an ultrasound scan (US) with a 10 MHz linear probe using the Vivid S60N. The US was performed in a darkened room in a lying position with the head tilted back. The structure of the thyroid gland and its dimensions were assessed by one endocrinologist.
## 2.4. Biochemical Analyses
Venous blood samples were collected from fasting patients for biochemical analyses (TSH, fT3, fT4, TPOAbs, TgAbs). The diagnosis of Hashimoto’s thyroiditis (HT) was based on the presence of a hypoechogenic thyroid structure on US examination and elevated serum concentration of thyroid peroxidase antibodies (TPOAbs) and/or antibodies against thyroglobulin (TgAbs) [16]. HT was diagnosed on the basis of typical clinical symptoms (tiredness, weakness, dry skin, feeling cold, etc.), decreased fT3 and/or fT4 and decreased TSH and, additionally, the presence of anti-thyroid antibodies. All the tests were performed at the Department of Laboratory Medicine, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland using a Horiba ABX Pentra 400 analyzer (Horiba ABX, Montpelier, France).
## 2.5. Statistical Analyses
Statistical analysis was performed using the Statistica 10.0 software (Statsoft, Bydgoszcz, Poland). The results were expressed as mean of ± standard deviation (SD). The Kruskal–Wallis test for independent variables was used for the comparison of the groups, followed by the ANOVA test. The results were considered statistically significant when $p \leq 0.01.$
## 2.6. Ethic Approval
All the procedures used in the present study were performed in accordance with the 1964 Helsinki declaration and its later amendments and other relevant guidelines and regulations. The research protocol was reviewed and approved by the Ethics Committee at the University Hospital in Bydgoszcz (Permission number KB/$\frac{224}{2022}$). All subjects granted their informed consent for participation in the study.
## 3. Results
We observed significant differences in FM and VAT before and after L-thyroxine treatment. We also noticed lower BMI levels after treatment (23.78 vs. 23.22 vs. 23.14, respectively), and higher levels of SMM (21.2 vs. 21.5 vs. 21.6, respectively), but there were no significant differences. We did not find any differences in FFM or BIVA (Table 2).
We also observed significant differences in thyroid function tests (TSH and fT4) carried out during the recruitment period and after 3 and 6 months of treatment (TSH: 4.84 vs. 2.31 vs. 1.93, respectively, and fT4: 9.26 vs. 11.23 vs. 12.87, respectively). There were no significant differences related to TPOAbs and TgAbs (Table 3).
The results of correlation analysis between serum thyroid hormone levels (TSH, fT4) and metabolic parameters in participants are shown in Table 4.
We found no obvious associations between serum thyroid hormone levels (TSH, fT4) and FM, FFM, SSM, and TBW. There was a significant negative correlation of serum FT4 levels with BMI and VAT among participants with HT (r = −0.087, $p \leq 0.01$; and r = −0.125, $p \leq 0.01$, respectively). Serum TSH levels were also positively correlated with BMI and VAT ($r = 0.236$, $p \leq 0.01$; and $r = 0.324$, $p \leq 0.01$, respectively) (Table 4).
After 3 months of treatment with L-thyroxine we also found that serum FT4 levels showed a negative correlation with BMI and VAT (r = −0.065, $p \leq 0.01$; and r = −0.088, $p \leq 0.01$, respectively), and serum TSH levels showed a positive correlation with BMI ($r = 0.202$, $p \leq 0.01$) and also a positive correlation with VAT ($r = 0.277$, $p \leq 0.01$) in the participants with HT. Similarly, there were no significant associations between FFM, FM, SSM, and TBW (Table 5).
After 6 months of treatment with L-thyroxine we observed an association between TSH levels and BMI and VAT. There was a positive correlation ($r = 0.255$, $p \leq 0.01$; and $r = 0.223$, $p \leq 0.01$, respectively). We also found that serum FT4 levels showed a negative correlation with BMI and VAT (r = −0.125, $p \leq 0.01$; and r = −0.123, $p \leq 0.01$, respectively). Similarly, there were no significant associations between FFM, FM, SSM, and TBW (Table 6).
## 4. Discussion
Hypothyroidism is a complex disorder characterized by an increase in body weight. About 15–$30\%$ of hypothyroid patients are reported to be overweight. In their study, Malczyk et al. [ 17] observed that women with HT were characterized by significantly higher values of body weight, and thus BMI index, than healthy women (73.64 kg vs. 64.36 kg, $p \leq 0.0001$; 27.65 kg/m2 vs. 23.95 kg/m2, $p \leq 0.001$, respectively). In our group, the initial BMI in triathletes was normal (23.78 ± 1.02 kg/m2), which is probably due to their previous high level of physical activity (8.71 ± 1.26 h per week), and it decreased, although statistically insignificantly, during L-thyroxine treatment. However, Okan et al. did not observe a decrease in body weight and body fat percentages, in spite of the fact that the participants achieved euthyroidism with adequate L-thyroxine replacement [18]. In other studies, obesity also seems to persist, even after established euthyroidism via levothyroxine (LT4) replacement therapy [19,20].
Hypothyroidism is known to lead to an increase in weight and fat content in the body. Sanyala and Raychaudhuri, in their study, noticed that hormonal disorders connected with Hashimoto’s disease affected not only the change in body weight, but also its composition, regardless of physical activity [5]. As reported by Malczyk et al., the problem of body fat excess affected women with HT more often than healthy women ($44.7\%$ vs. $13.8\%$, $p \leq 0.001$) [17], and accounted for the decrease in thermogenesis, fat tissue metabolism, and fluid retention [3]. Adipose tissue is an active internal endocrine organ, but it is also responsible for energy storage. It consists of different types of cells, such as fat cells, fibroblasts, and immune cells, and it is divided into two types—brown and white. Brown adipose tissue (BAT) plays a key role in the process of thermogenesis and also in maintaining normal body weight. It has been observed that the amount of BAT decreases with increasing body mass. Thus, the right amount of active BAT can prevent obesity in adults [21]. Adipose tissue, as an endocrine organ, secretes various biologically active substances [22,23], one of which is leptin, which can play an important role in the interaction between the composition of the body and thyroid hormones [24]. There are studies which show that leptin may stimulate TSH secretion and influence peripheral conversion of T4 to T3, and it may be associated with thyroid gland autoimmunity [25,26].
The bioelectrical impedance analysis system (BIA) is an easy and a cheap method which helps to identify different body compartments: body lipid percentage, fat-free body mass, and total body fluid [27]. In our study we used a seca device mBCA 515 medical Body Composition Analyzer for analysis of anthropometric measurements. We observed significant differences in FM and VAT before and after 6 months of treatment with L-thyroxine. In hypothyroid patients, body fat content is shown to increase in parallel with body weight. This effect is attributed to the reduction of lipid metabolism in hypothyroidism [28,29]. In their study, Malczyk et al., observed that the problem of excess of fat in the body affected women with HT more often than healthy women ($44.7\%$ vs. $13.8\%$, $p \leq 0.001$) [18]. Nevertheless, in a few other studies, no significant reduction in body fat was observed with L-thyroxine therapy [30,31]. Ruhla et al. also reported that L-thyroxine therapy is associated with an increase in BMI independent from the level of TSH [20]. Karmisholt et al. observed that weight loss in hypothyroid subjects treated with L-thyroxine resulted mainly from the excretion of excess body water associated with myxedema, and not from a change in adipose tissue [32].
There was a significantly positive correlation of serum TSH levels with BMI and VAT among participants with HT ($r = 0.236$, $p \leq 0.01$; and $r = 0.324$, $p \leq 0.01$, respectively) in our study. Many authors have attributed this relationship to the adipokine leptin. Leptin regulates thyrotropin-releasing hormone (TRH) gene expression in the paraventricular nucleus, and TSH, in turn, increases leptin production from adipose tissue. Leptin also regulates the conversion of T4 to T3 [4,33]. The strongest correlation was established between TSH and BMI ($r = 0.23$). These findings are compatible with some previous studies [34,35,36,37]. In a study by Yasar et al., which correlated thyroid function with obesity in a cohort of polycystic ovary syndrome subjects, the correlation of TSH with BMI was also significant (r: 0.122; p: 0.02) [36]. A review by Amanda de Moura Souza published in 2011 analyzed data from 29 studies. Some of these studies demonstrated a positive correlation between body mass index and TSH, but approximately half of the studies showed no such correlation [7]. The hypothesis for correlation was that TSH is involved in the differentiation of pre-adipocytes and induced adipogenesis. Another hypothesis is the leptin hypothesis. Some studies have demonstrated a positive correlation between leptin and TSH [33].
In our study, there was also a significantly negative correlation of serum FT4 levels with BMI and VAT among participants with HT (r = −0.087, $p \leq 0.01$; and r = −0.125, $p \leq 0.01$, respectively). Kim B et al. reported that FT4 was positively associated with blood pressure, FPG, HDL, and triglyceride levels, and negatively associated with waist circumference in euthyroid subjects [38]. Pratz-Puig et al. also demonstrated that a free thyroxine level (FT4) close to the lower limit is related to increased body mass index, visceral fat, and insulin resistance [39].
## 5. Limitation of Our Study
The main limitation of the study was the small numbers recruited and the limited duration of follow-up. Diet, supplementation, and modifications in training used by triathletes were not taken into account. Throughout the study, patients were advised not to change their dietary and exercise habits.
## 6. Conclusions
The problem of treating Hashimoto’s thyroiditis in athletes who practice triathlon requires further research due to the higher daily energy consumption caused by heavy physical exertion, adequate supplementation, and diet. Frequent bioelectrical impedance analysis of body composition analysis during treatment can be very helpful.
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|
---
title: 'Psychosocial determinants of consistent condom use among university students
in Sudan: findings from a study using the Integrated Change Model'
authors:
- Husameddin Farouk Elshiekh
- Ciska Hoving
- Hein de Vries
journal: BMC Public Health
year: 2023
pmcid: PMC10045195
doi: 10.1186/s12889-023-15466-5
license: CC BY 4.0
---
# Psychosocial determinants of consistent condom use among university students in Sudan: findings from a study using the Integrated Change Model
## Abstract
Unprotected sex is common among university students in Sudan, thus increasing risks for sexually transmitted diseases (STDs) and human immunodeficiency virus (HIV). As little is known about the psychosocial determinants of consistent condom use among this population, this study was designed to identify them. The Integrated Change Model (ICM) was applied in a cross-sectional design to identify in 218 students (aged 18–25 years) from Khartoum which items distinguish condom users from non-condom users. Condom users differed significantly from non-condom users in having more HIV and condom use-related knowledge, higher perception of susceptibility to HIV, reporting more exposure to condom use cues, having a less negative attitude towards condom use (attitude cons), experiencing social support and norms favouring condom use and having higher condom use self-efficacy. Binary logistic regression showed that peer norms favouring condom use in addition to HIV-related knowledge, condom use cues, negative attitude and self-efficacy were the factors uniquely associated with consistent condom use among university students in Sudan. Interventions seeking to promote consistent condom use among sexually active students could benefit from increasing knowledge about HIV transmission and prevention, raising HIV-risk perception, using condom use cues, addressing perceived condom disadvantages and enhancing students` self-efficacy to avoid unprotected sex. Moreover, such interventions should raise students` perceptions of their peers` beliefs and behaviours favouring condom use and seek health care professionals` and religious scholars` support for condom use.
## Introduction
In 2010, the global HIV response aimed to achieve three zeros by 2030; zero new HIV infections, zero AIDS-related deaths and zero discrimination against people living with HIV/AIDS (PLWHA). To achieve these goals, measurable targets were set and interim 2020 milestones were articulated by the United Nations (UN) General Assembly in the 2016 Political Declaration on Ending AIDS. These milestones included reducing new HIV infections to fewer than 500,000 by 2020 through ensuring access to combination prevention options, including pre-exposure prophylaxis, voluntary medical male circumcision, harm reduction and condom promotion. However, the progress towards these goals is off track in the Middle East and North Africa (MENA), where HIV infections have increased by $22\%$ since 2010 [1]. Sudan is among the countries with the highest HIV prevalence in MENA. In 2013, it was estimated that around $21\%$ of PLWHA in MENA were from Sudan [2].
Sudan has a total population of about 35 million people. The number of people living with HIV in Sudan in 2019 was estimated at 46,000 and the estimated HIV prevalence was $0.2\%$ [3]. Although this is considered a low prevalence compared to the generalized epidemic in some sub-Saharan countries such as South Sudan ($2.5\%$) [4], the prevailing lack of knowledge, increasing poverty and political instability in the country raise the concerns as these conditions could further fuel the epidemic in Sudan [5]. The HIV epidemic in *Sudan is* spread mainly via unprotected heterosexual and among men who have sex with men [6]. In Sudan, all types of extramarital sex are religiously forbidden and socially unaccepted; social norms expect sexual abstinence and virginity at the time of marriage remains a virtue. Therefore, condom promotion programs are difficult to implement in the country and previous attempts to promote condom use among university students were resisted by the religious leaders who believe that condom promotion will promote immorality and promiscuity.
University students are targeted by HIV prevention interventions in many countries because they are believed to be at a higher risk of acquiring HIV compared to the general population in these countries [7–9]. This has also been observed in many countries in the MENA region, where increasing numbers of university students become involved in risky sexual behaviours [10–12]. Engagement of university students in sexual risk behaviours can be attributed to several factors, including the university lifestyle with diminished parental control and monitoring and the poor comprehensive knowledge about HIV/AIDS [13–15]. In addition, poor access to HIV counselling and sexual health services is also a determinant of high-risk sexual behaviours among this population [16]. Alcohol and drug use among university students are also associated with increased high-risk behaviours, including unprotected sex with multiple sex partners [16, 17].
Similarly, university students in Sudan are at high risk of contracting HIV because of a relatively high prevalence of engagement in condomless sex. Based on a survey conducted by the Sudan National AIDS Program (SNAP) in 2002, it was estimated that about $6.5\%$ of university students in Sudan were sexually active (unpublished report). In 2010, a study conducted by SNAP among higher education institutions` students and staff in Sudan revealed an increase in sexual activity among university students to more than $12.5\%$. Moreover, only $20\%$ of the sampled university students reported using condoms during their first-ever sexual encounter and only $32\%$ of them used a condom during their latest sexual intercourse (unpublished report). In another study conducted among visitors to voluntary counselling and testing (VCT) centers in Khartoum, only $12\%$ of the respondents reported using condoms consistently, $41.5\%$ used them sporadically and $46.3\%$ were nonusers. According to this study, knowledge about AIDS transmission, knowing someone infected with or had died of AIDS, experiencing condom problems, type of sexual partners, purchase embarrassment and education were the main predictors of condom use [18]. However, this study included only male participants.
Considering the importance of the psychosocial determinants of condom use, several behavioural change theories have been used to promote condom use through addressing these determinants [19, 20]. The Integrated Change Model (I-Change Model) is one of these theories used to explain a variety of types of health behaviour, including consistent condom use [21, 22]. The I-Change Model, which is derived from the Attitude – Social influence – Self-Efficacy Model, integrates the ideas of Ajzen’s Theory of Planned Behavior, Bandura’s Social Cognitive Theory, Prochaska’s Transtheoretical Model, the Health Belief Model, and goal setting theories [23]. The I-Change Model distinguishes three phases in the process of behavioural change: a pre-motivational (awareness), motivational and post-motivational (action) phase. Each of these three phases has its relevant determinants [24]. The pre-motivational or awareness phase is determined by knowledge, risk perceptions, cues to action and cognisance about one`s own behaviour. In relation to this study, the model assumes that condom use pre-motivational awareness phase is determined by a person`s cognisance of his/her sexual behaviour and whether it meets the recommendations, accurate knowledge about HIV and condom use, and a person’s perception of the seriousness of HIV (risk severity) and how likely it is to get HIV if practised condomless sex (risk susceptibility). This phase is also determined by the cues that prompt a person to use condoms consistently such as the death of a relative with AIDS. Once they become aware of the health problem (HIV) and its risk behaviours (condomless sex), individuals can proceed to the motivational phase in which they will consider taking up a health-promoting behaviour (e.g. consistent condom use). According to the I-Change Model, the determinants of this motivational phase include attitude, social influence and self-efficacy. In relation to this study, a person`s attitude towards condom use is his or her perception of the cognitive and emotional advantages and disadvantages of using condoms consistently [21]. The social influence on an individual`s condom use behaviour refers to the support that he or she receives from others to use condoms (social support), the perception of what others in his community believe about condom use (social norm) and the individual`s perception of condom use behaviour among the community members (social modelling) [25]. Self-efficacy refers to a person’s perception of his capability to carry out a type of behaviour (consistent condom use) in a variety of situations and how difficult a person regards realising the desired healthy behaviour [26]. These motivational factors together are assumed to predict the intention to use condoms consistently. The translation of this intention into behaviour is the third and post-motivational phase which is determined by a person’s level of intention, action plans such as the plans required to prepare oneself and initiate condom use and the coping plans needed to overcome barriers and plan enactment. This phase is also determined by a person`s self-efficacy, skills and the level of barriers that are encountered [27]. Finally, as a psycho-social-ecological model, the I-Change model indicates that these factors are influenced by predisposing factors such as psychological factors (e.g. personality), behavioural factors (e.g. lifestyles), social and cultural factors (e.g. policies, cultural norms, religion), biological factors (e.g. gender, genetic predisposition) and information factors (the quality of messages, channels and sources used) [21].
The above-described determinants have been poorly studied in Sudan. To the best of our knowledge, these determinants have been only recently explored by a qualitative study we have conducted among university students in Khartoum using the I-Change Model. Regarding the pre-motivational determinants, the study revealed several misconceptions about condoms and their use among male and female students and most of the participants reported a lack of knowledge about how to use condoms. Regarding risk perception, most of the participants perceived the high risk of getting HIV if they practised condomless sex. They also reported a high perception of HIV severity and indicated that HIV is a serious disease with severe impacts on health and social life. The cues reported by the consistent condom users as encouraging cues included having previous experience with PLWHA and having easy access to condoms. Concerning the motivational determinants, the findings suggested that negative attitude was a determinant of condom use as non-condom users of both sexes perceived several physical and emotional disadvantages associated with condom use. Regarding the role of social influence on the students’ condom use, the study suggested that lack of social support was a barrier and pointed to the role of religious values and social norms against condom use. Most of the participants also pointed to the influential role of their peers in their condom use behaviour. Low self-efficacy was also identified as a possible determinant of condom use as most of the consistent users reported higher confidence in their ability to overcome the challenging situation than non-condom users. Finally, regarding the post-motivational determinants, the study suggested that poor action planning was a barrier as most of the participants reported a lack of action and coping plans [14].
Although the previous study provided important insights into the psychosocial determinants of consistent condom use among university students in Sudan, the study was limited by its qualitative design and the small sample of only 30 students. Therefore, this study was conducted to complement the previous study and further assess these determinants quantitatively. For this purpose, the I-CHANGE model (Fig. 1) was used as a theoretical framework.
Fig. 1The integrated behavioural change (I-CHANGE) model
## Design
A quantitative cross-sectional study was used among university students in Khartoum.
## Recruitment and participant selection
The target group of this study was the sexually active undergraduate university students in Khartoum state. From a list of 35 universities in Khartoum, including 16 public and 19 private universities, three public and three private universities were randomly selected. The deans of students` affairs in these selected universities were visited by the principal researcher to explain the objectives of the study and seek their approval. Following approvals, invitation letters were distributed among the students in randomly selected lecture rooms in each university. The invitation letters provided to the students described the study and its objectives and shared how to access the study questionnaire online. Additionally, some sexually active students identified by the HIV counsellors were asked to invite their sexually active friends, who were also university students, to fill the online questionnaire (snowball recruitment).
## Procedures
As it is culturally sensitive to talk about sexual behaviour outside marriage in Sudan openly, data collection occurred online. The online questionnaire was in Arabic and accessible by smartphones, laptops and computers. The questionnaire started with an introduction presenting the study and explaining its objectives. This was followed by a section to inform the students that their participation was voluntary, and their confidentiality and privacy were assured. Participants’ identifiers such as their names, address, phone numbers or universities were not included in the questionnaire.
## Measurement
Questionnaire development was inspired using findings of an earlier qualitative study [14] and previous studies about sexual health behaviours using the I-Change Model [27, 28]. The instrument was piloted with ten university students other than those who participated in the study; no extensive changes were required. To assess the validity of the questionnaire for each construct of the I-Change model, factor analysis was conducted. Cronbach’s alpha was calculated to ensure the internal consistency of each construct items [29].
## Knowledge
Knowledge was assessed by 16 statements about HIV, its transmission, prevention and treatment and five statements about condom use such as “condoms have expiry dates” and “condoms could affect the muscles of the penis”. Participants could respond to each statement with yes, no or not sure. Participants` responses to knowledge questions were coded as [1] for correct answers and [0] for incorrect or not sure responses.
## Cues to action
Cues to consistent condom use were assessed by five items; knowing someone infected with or died of HIV, previously attending a talk regarding living with HIV/AIDS, previously attending a peer education program about HIV and knowing someone who could provide condoms. Participants could answer with yes [1] or no [0] for each item. All of these factors were combined together as cues to consistent condom use.
The participants reported low exposure to the cues about condom use. Less than $20\%$ of them knew someone infected or who had died of HIV/AIDS. Only $31\%$ had attended a peer education program about HIV prevention and only $36\%$ of them knew somebody who could provide them with condoms confidentially. Generally, consistent condom users reported higher exposure to condom use cues than non-consistent condom users (Hotelling’s $T = 0.550$; F [5,212] = 23.307; $p \leq .001$). When looking at the items separately, consistent condom users had significantly higher exposure to all of these cues than non-consistent users (Table 2).
## Risk perception
Risk perception was assessed by five items. Three items assessed the participants` perception of the risk of severe HIV-related health problems, social problems and psychological distress (-2 (totally disagree) to + 2 (totally agree); Cronbach’s alpha = 0.74). To assess participants` perception of susceptibility to HIV, they were asked how likely they would be infected with HIV if they practised unprotected vaginal sex and how likely they would be infected with HIV if they practised unprotected anal sex (-2 (very unlikely) to + 2 (very likely); Cronbach’s alpha = 0.83).
The participants generally had high perceptions of the severe health, social and psychological consequences of HIV infection. MANOVA showed no overall difference between the two groups in their perception of HIV severity (Hotteling`s $T = 0.019$; F [3,214] = 1.382; $$p \leq .249$$). In contrast, the perception of susceptibility to HIV was relatively low among the study participants; however, consistent condom users scored significantly higher to the overall perception of susceptibility than non-consistent condom users (Hotelling’s $T = 0.086$; F [5,212] = 9.245; $p \leq .001$). In addition, compared to non-consistent condom users, consistent users showed higher perceptions of susceptibility to HIV if they practised unprotected vaginal ($p \leq .01$) and anal sex ($p \leq .001$), as shown in Table 3.
Table 3Differences between groups for HIV risk perception, attitude, social influence, self-efficacy and intentionConstruct itemsOverall meanNon- consistent condom users(Mean score)Consistent Condom users(Mean score) F P Risk perception (Risk severity) If I would contract HIV, this would be a serious health problem for me.1.581.511.724.090 < 0.05 If I would contract HIV, I would have serious social problems.1.591.541.671.4300.233If I would contract HIV, I would suffer from serious psychological distress.1.511.461.591.0220.313 Risk perception (Risk susceptibility) How likely that you will get HIV infection if you practice unprotected vaginal intercourse.0.450.300.726.883 < 0.01 How likely that you will get HIV infection if you practice unprotected anal intercourse.0.430.180.8818.294 < 0.001 Attitude (pros condom use) If I use condoms during sexual intercourse:I will be protected against HIV and other STIs1.241.231.260.1020.750This will indicate that I care about my partner`s health.1.151.181.110.2680.605I don’t have to worry about pregnancy1.321.371.211.7070.193This will help me to have more sexual partners.− 0.05− 0.140.122.5570.111It will delay ejaculation and let me enjoy sex0.660.630.720.5170.473Attitude (cons condom use) If I use condoms during sexual intercourse:This will indicate that I do not trust my partner.− 0.42− 0.32− 0.612.7370.100It will decrease sexual pleasure0.220.77− 0.80114.946 < 0.001 I will have health problems due to semen stagnation0.130.23− 0.053.5730.060I will become sex addicted0.470.620.189.182 < 0.01 It will feel unnatural to me− 0.51− 0.43− 0.661.9230.167 Social influence (Peer norm) Most of my friends believe that I should use condoms during sexual intercourse.0.270.160.473.5070.062Most of my sexual partners believe that I should use condoms during sexual intercourse− 0.08− 0.180.123.7800.053 Social influence (Peer support & modelling) Most of my friends support me to use condoms during sexual intercourse0.18− 0.050.6215.652 < 0.001 Most of my sexual partners support me to use condoms during sexual intercourse− 0.16− 0.380.2515.986 < 0.001 How many of your friends use condoms during sexual intercourse?− 0.15− 0.300.128.282 < 0.01 Social influence (Others influence) My parents believe that I should use condoms during sexual intercourse0.320.300.360.1130.737Health professionals believe that I should use condoms during sexual intercourse0.850.731.099.676 < 0.01 Religious scholars believe that I should use condoms during sexual intercourse.0.410.270.677.209 < 0.01 My parents support me to use condoms during sexual intercourse.0.370.320.450.7020.403Health professionals support me to use condoms during sexual intercourse.0.850.681.1615.771 < 0.001 Religious scholars support me to use condoms during sexual intercourse.0.390.250.647.429 < 0.01 Self-efficacy I would find it difficult to use condoms if my sexual partners refuse it.− 0.76− 0.91− 0.479.325 < 0.01 I would find it difficult to use condoms in case of high sexual arousal.− 0.38− 0.650.1323.447 < 0.001 I would find it difficult to use condoms because it is difficult for me to get it.− 0.50− 0.68− 0.1710.180 < 0.01 I would find it difficult to use condoms when I feel that it reduces pleasure.− 0.44− 0.63− 0.0911.651 < 0.01 I would find it difficult to use condoms with my steady partner.− 0.64− 0.72− 0.482.0190.157I would find it difficult to use condoms since I do not know how to use it properly.0.270.060.6616.490 < 0.001 Intentions I have the intention to use condoms during the next sexual intercourse0.930.801.178.763 < 0.01 I have the intention to use condoms consistently during future sexual intercourse0.860.731.119.002 < 0.01 I have the intention to discuss condoms use with my sexual partner the next time I have sex1.060.891.3816.771 < 0.001 Risk perception (severity), Attitude, social influence and intentions items: (-2 (totally disagree) to + 2 (totally agree)) Risk perception (susceptibility) items: (-2 (very unlikely) to + 2 (very likely)); Self-efficacy items: (-2 (totally agree) to + 2 (totally disagree)
## Attitude
To assess attitude towards condom use, five items were used for the advantages (pros) of using condoms such as “If I use condoms during sexual intercourse, I will be protected against HIV and other STIs” and another five items for the disadvantages (cons) of using condom such as “If I use condoms during sexual intercourse, this will indicate that I do not trust my partner.,” ( Cronbach’s alpha = 0.64 and 0.78, respectively). Response options for all attitude items ranged from − 2 (totally disagree) to + 2 (totally agree).
The comparison between consistent and non-consistent condom users in their perception of the advantages of using condoms revealed no significant difference (Hotteling`s $T = 0.026$; F [5,212] = 1.121; $$p \leq .350$$). Among the items that assessed the positive attitude towards condom use (condom use pros), protection against pregnancy, prevention of HIV/STIs and indicating caring about partner’s health were the most important perceived advantages of consistent condom use among the study population.
On the other hand, a high perception of condom use disadvantages (condom use cons) was observed, with a significantly higher perception of condom use disadvantages among non-consistent users (Hotteling`s $T = 0.608$; F [5,212] = 25.795; $p \leq .001$). For instance, non-consistent condom users were more convinced than consistent condom users that condom use would decrease sexual pleasure ($p \leq .001$) and lead to sex addiction ($p \leq .01$). The perceptions that consistent condom use would indicate lack of trust in the sexual partner, cause semen stagnation or feel unnatural were all very low among both consistent and non-consistent condom users with no significant differences between the two groups (Table 3).
## Social influence
Social influence was assessed with eleven items such as “Most of my friends believe that I should use condoms during sexual intercourse” and “Most of my sexual partners support me to use condoms during sexual intercourse.” For all social influence items, participants could reply on a five-point Likert scale ranging from − 2 (totally disagree) to + 2 (totally agree). Based on factor analysis, the social influence 11 items were grouped into three categories: peer norm (two items; Cronbach’s alpha = 0.68), peer support and modelling (three items; Cronbach’s alpha = 0.71) and others (parents, religious scholars and health professional) influence (six items; Cronbach’s alpha = 0.82).
Generally, the participants had a very low perception of peer norms favouring consistent condom use. Consistent condom users had a relatively higher perception of friends and sexual partners` norms favouring consistent condom use; however, this difference was not statistically significant ($$p \leq .062$$ and 0.053, respectively). In addition, no difference in overall peer norm influence was identified between consistent and non-consistent condom users (Hotteling`s $T = 0.022$; F [2,215] = 2.403; $$p \leq .093$$). Overall, consistent condom users reported more peers to use and support condom use (Hotteling`s $T = 0.102$; F [3,214] = 7.3; $p \leq .001$). In-depth analysis revealed that most of the participants received little support from their friends and sex partners, but consistent condom users did report relatively more support from their friends ($p \leq .001$) and sexual partners ($p \leq .001$). They also believed that condoms were more commonly used by their peers as compared to non-consistent condom users ($p \leq .01$).
Consistent condom users also reported to experience more influence from parents, religious leaders and health professionals than non-consistent condom users (Hotteling`s $T = 0.111$; F [6,211] = 3.901; $$p \leq .001$$). When looking at the items separately, consistent condom users were more convinced that health professionals ($p \leq .01$) and religious leaders ($p \leq .01$) favoured consistent condom use than non-consistent condom users. Consistent condom users also perceived greater support to use condoms consistently from health professionals ($p \leq .001$) and religious leaders ($p \leq .01$) than non-consistent condom users. Both groups perceived greater support from health professionals than religious leaders. Parents` influence on consistent condom use, including both parents` support and norms, was not statistically significant (Table 3).
## Self-efficacy
Self-efficacy was assessed with six statements such as “I would find it difficult to use condoms if my sexual partners refuse it”. Participants could reply to self-efficacy items on a five-point Likert scale ranging from − 2 (totally agree) to + 2 (totally disagree). ( Cronbach’s alpha = 0.78) Students’ self-efficacy to use condoms consistently was generally very low. Partner refusal to use condoms, practising sex with steady partners and facing difficulty in obtaining condoms were the most difficult barriers affecting students` self-efficacy. Overall, consistent condom users reported higher self-efficacy than non- consistent condom users (Hotteling`s $T = 0.182$; F [6,211] = 6.388; $p \leq .001$). In-depth analysis reveals that consistent condom users showed significantly higher self-efficacy for most difficult situations except when practising sex with steady partners (Table 3).
## Intention
Intention to use condoms consistently was assessed with three statements using a five-point Likert scale regarding respondents’ intention to use condoms during the subsequent sexual intercourse, to use it consistently during future sexual intercourse and to discuss condom use with the sexual partner during the following sexual intercourse (-2 (totally disagree) to + 2 (totally agree); Cronbach’s alpha = 0.84).
*In* general, participants had a slightly positive intention to use condoms during the following sexual intercourse, use it consistently during future sexual intercourse and discuss condom use with their sexual partners the next time they have sex (overall mean scores 0.93, 0.86 and 1.06, respectively). These intentions to use condom were significantly higher for consistent users compared to non-consistent condoms users (Hotteling`s $T = 0.081$; F [3,214] = 5.783; $p \leq .01$). Consistent condom users had significantly higher intentions to use condoms during the next sexual intercourse ($p \leq .01$) and to use it consistently during future sexual intercourse ($p \leq .01$). They also had higher intentions to discuss condom use with their sexual partners the next time they had sex ($p \leq .001$) (Table 3).
## Consistent condom use
Consistent condom use as a behavioural outcome variable was measured by asking the participants whether they used a condom during their last sexual intercourse (yes, no) and how frequently they use condoms during sexual intercourse (always, often, sometimes, rarely, never). Only those who stated that they used condoms during their last sexual activity and always used condoms during sex were considered consistent condom users. Accordingly, non-consistent condom users were coded as [0] and consistent condom users [1].
## Data analysis
Data analysis was performed in SPSS version 24. A descriptive analysis was undertaken to describe the study sample. Multivariate analysis of variances (MANOVA) was conducted to assess the difference between consistent and non-consistent condom users per psychosocial construct and for each individual construct item. Finally, forward binary logistic regression analysis (forward LR) was performed to identify the potential predictors of consistent condom use. Results with p values < 0.05 were considered significant.
## Description of the sample
Initially, about 415 students responded, but only 304 of them completed the whole questionnaire. The remaining 111 participants answered less than $70\%$ of the questions; therefore, they were excluded from the study. Among those who completed the online questionnaire, 98 were sexually active. An additional 120 sexually active participants were recruited by some sexually active students (snowball recruitment). Two hundred and eighteen sexually active male and female university students were included in the study. The sample included 76 consistent condom users ($35\%$). Most participants were Sudanese ($94.5\%$) and Muslim ($94\%$). Table 1 summarises the demographic characteristics of the study participants.
Table 1Description of the study sample ($$n = 218$$)CharacteristicsTotal N (%)Non-consistent condom usersConsistentCondom users χ 2 P-value Consistent condom use 218 ($100\%$)142 ($65\%$)76 ($35\%$)Age (range 18–25)Mean21.0621.121 Age group < 20 years80 ($37\%$)50 ($62.5\%$)30 ($37.5\%$)0.390.53> 20 years138 ($63\%$)92 ($66.7\%$)46 ($33.3\%$) Gender Male137 ($63\%$)93 ($67.9\%$)44 ($32.1\%$)1.220.27Female81 ($37\%$)49 ($60.5\%$)32 ($39.5\%$)Nationality group*Sudanese206 ($94\%$)134 ($65\%$)72 ($35\%$)1.0Non-Sudanese12 ($6\%$)8 ($66.7\%$)4 ($33.3\%$) Religious group* Muslims205 ($94\%$)131 ($63.9\%$)74 ($36.1\%$)0.23Non-Muslims13 ($6\%$)11 ($84.6\%$)2 ($15.4\%$) Family income Low income51 ($24\%$)28 ($54.9\%$)23 ($45.1\%$)3.090.21Middle income99 ($45\%$)68 ($68.7\%$)31 ($31.3\%$)High income68 ($31\%$)46 ($67.6\%$)22 ($32.4\%$) Type of university Public university118 ($54\%$)76 ($64.4\%$)42 ($35.6\%$)0.060.81Private university100 ($46\%$)66 ($66\%$)34 ($34\%$)Academic year*Early academic years (1st − 3rd years)106 ($49\%$)66($62\%$)40 ($38\%$)0.750.39Late academic years (4th - 6th years)112 ($51\%$)76 ($68\%$)36 ($32\%$)* Fisher`s exact test was used instead of Chi-squared test
## Knowledge about HIV/AIDS
The overall percentage of correct answers to each of the 16 items used to assess knowledge about HIV/AIDS ranged between 27 and $85\%$. The vast majority of the participants correctly answered items on HIV transmission. Nevertheless, misconceptions existed among the students. Many of them believed that HIV could be transmitted by mosquito bites or through hugging people living with HIV/AIDS (PLWHA) ($43\%$ and $45\%$ respectively). More than $70\%$ also believed that HIV transmission could be prevented by pre-ejaculation withdrawal. Additionally, more than $60\%$ had the misconception that most people know they are infected with HIV soon after being infected.
MANOVA results showed that the overall knowledge about HIV/AIDS (the total score of all knowledge items) was higher among consistent condom users as compared to non-consistent condom users (Hotelling’s $T = 0.282$; F [16,201] = 3.539; $p \leq .001$). When looking at the separate HIV knowledge items, significant differences were observed between consistent and non-consistent condom users with higher knowledge about HIV/AIDS among consistent condom users in almost all items, as shown in Table 2.
Table 2Differences between groups for knowledge and cuesKnowledge about HIV/AIDSOverall meanNon- consistent condom usersConsistent Condom users F P Anyone can get infected with HIV if he practices condomless vaginal intercourse with infected persons0.830.750.9615.66 < 0.001 Anyone can get infected with HIV if he practices condomless anal intercourse with infected persons0.780.720.9110.95 < 0.01 Anyone can get infected by getting injections with a needle that has already been used by infected persons.0.840.810.892.650.105 A pregnant woman who is infected with HIV can transmit the virus to her baby.0.710.650.805.29 < 0.05 Anyone can get infected with HIV from a mosquito bite.0.530.470.635.14 < 0.05 Anyone can get infected with HIV through hugging with people living with HIV.0.550.440.7521.35 < 0.001 Someone who looks healthy can be infected with HIV.0.680.630.785.15 < 0.05 You can protect yourself against HIV by abstaining from sexual intercourse before marriage.0.850.820.913.210.075You can protect yourself against HIV by using a condom correctly every time you have sexual intercourse.770.680.9522.56 < 0.001 People can reduce the risk of getting HIV by reducing the number of their sexual partners.0.660.560.8316.50 < 0.001 Having sexually transmitted infection put you at higher risk of getting infected with HIV.0.710.630.8612.38 < 0.01 Most people do know they are infected with HIV soon after getting infected0.320.260.426.00 < 0.05 Getting the penis out just before ejaculation, is a safe method of preventing HIV transmission0.270.260.280.060.803HIV treatments help HIV infected people to live normally for longer time.0.610.560.715.02 < 0.05 HIV infected people on treatment are less likely to transmit HIV to others.0.560.470.7414.98 < 0.001 *Early diagnosis* of HIV infection can prevent development of AIDS.0.660.620.722.380.125 Knowledge about condom use Condoms could affect the muscles of the penis0.370.290.5312.55 < 0.01 Condoms protect only male partner against HIV and sexually transmitted infections (STI)0.610.570.682.700.102Consistent use of condoms can cause loss of sexual desire.0.290.200.4616.74 < 0.001 Consistent condom use provides only $50\%$ protection against HIV0.410.320.5814.01 < 0.001 Condoms have expiry dates0.800.750.918.39 < 0.01 Condom use cues Do you know someone who is infected with HIV/AIDS0.180.130.265.74 < 0.05 Do you know someone who died of AIDS0.140.100.215.31 < 0.05 Have you ever listened to someone living with HIV/AIDS telling his experience of living with HIV0.210.110.3926.29 < 0.001 Have you attended any peer-education program on HIV prevention0.310.170.5846.71 < 0.001 Do you know somebody who can provide you with condoms confidentially0.360.150.75115.83 < 0.001 Knowledge items: (correct = 1, incorrect = 0), Cues items: (yes = 1, no = 0)
## Knowledge about condom use
The results reveal several misconceptions about condoms and their use prevalent among the total study population. For example, the majority of the students believed that consistent condom use could affect the muscles of the penis and cause loss of sexual desire ($68\%$ and $73\%$, respectively). In addition, about $59\%$ also underestimated the protective role of consistent condom use against HIV transmission. Besides, $39\%$ of the participants believed that condoms protect only male partners against HIV and sexually transmitted infections (STI).
When comparing consistent and non-consistent condom users using MANOVA, overall knowledge about condom use was higher among consistent condom users (Hotelling’s $T = 0.163$; F [5,212] = 6.927; $p \leq .001$) with significantly higher knowledge about condom use among consistent condom users in almost all items (Table 2).
## Regression analysis
Table 4 summarizes the results of the forward binary logistic regression, which showed that HIV knowledge, condom use cues, attitude cons, peer norms and self-efficacy were all uniquely associated with consistent condom use. The odds of consistent condom use were higher among those with higher HIV knowledge (OR: 1.27, $95\%$ CI: 1.22, 144, $p \leq .001$), higher exposure to condom use cues (OR: 1.74, $95\%$ CI: 1.38, 2.19, $p \leq .001$) and higher perception of peer norms favoring consistent condom use (OR: 1.65, $95\%$ CI: 1.099, 2.47, $p \leq .05$). Conversely, the odds of consistent condom use were much lower among those with a higher perception of condom use disadvantages (attitude cons) (OR: 0.15, $95\%$ CI: 0.07, 0.32, $p \leq .001$). Self-efficacy was found to be strongly associated with consistent condom use. The odds of consistent condom use were more than two times more among those with higher self-efficacy (OR: 2.115, CI: 1.255, 3.566, $$p \leq .005$$). The logistic regression model was statistically significant, χ2 (5, $$n = 218$$) = 111.691, $p \leq .001.$ The model explained $55.3\%$ (Nagelkerke R2) of the variance in consistent condom use and correctly classified $81.2\%$ of cases.
Table 4Binary logistic regression analysis for condom useVariables in the equationOdds ratio$95\%$ confidence intervalSig. LowerUpperBLOCK 2Step 1Condom use cues1.8221.4982.216 < 0.001 Step 2Knowledge about HIV/AIDS1.2811.1431.436 < 0.001 Condom use cues1.7471.4222.147 < 0.001 BLOCK 3Step 1Knowledge about HIV/AIDS1.2821.1351.449 < 0.001 Condom use cues1.7891.4322.237 < 0.001 Attitude cons0.1980.1010.386 < 0.001 Step 2Knowledge about HIV/AIDS1.2781.1301.446 < 0.001 Condom use cues1.7081.3622.142 < 0.001 Attitude cons0.1810.0890.368 < 0.001 Self-efficacy2.1881.3083.660 < 0.01 Step 3Knowledge about HIV/AIDS1.2711.1221.440 < 0.001 Condom use cues1.7381.3782.191 < 0.001 Attitude cons0.1500.0700.320 < 0.001 Peer norm1.6481.0992.470 < 0.05 Self-efficacy2.1151.2553.566 < 0.01 *In block 1, both included variables (age and gender) were not retained in the equation
## Discussion
This study aimed to identify the psychosocial determinants of condom use among university students in Khartoum, using the I-Change Model as a theoretical framework. The findings of the analyses of variance clearly indicated that condom users differed significantly from non-condom users in having more HIV and condom use-related knowledge, higher perception of susceptibility to HIV, reporting more exposure to condom use cues, having a less negative attitude towards condom use (attitude cons), experiencing social support and norms favouring condom use and having higher condom use self-efficacy. These outcomes suggest that, in order to promote condom use, these items should be clearly addressed in condom promotion programs among this at-risk population in Sudan.
The results of the regression analysis also supported the importance of knowledge about HIV/AIDS as a factor uniquely related to consistent condom use among the study population, a finding consistent with results of previous studies [18, 30–32]. Despite being university students, serious knowledge gaps and misconceptions about HIV transmission and prevention as well as condom use misconceptions were revealed by this study. Hence, it is important to design health education messages to address these misconceptions and fill the knowledge gaps. However, holding mass educational campaigns to promote condom use among university students in *Sudan is* challenging. A recent study has also identified peers as the main source of knowledge about HIV and condom use for university students in Sudan [14]. Therefore, it is essential to select the most appropriate channels to deliver these messages to disseminate HIV knowledge among the students.
The perception of HIV severity was not associated with consistent condom use among this study participants, which contradicts the findings of some previous studies [33–35]. This lack of association could be explained by the high level of social stigma associated with HIV in Sudan that led all the students to perceive the severe social and psychological consequences of contracting HIV as observed in this study and previously reported [14]. However, an association between the perception of susceptibility to HIV and consistent condom use was revealed by this study as well as several previous studies [35–37]. The regression analysis of our study data showed no unique association between HIV-risk perception and consistent condom use although a previous study showed that the influence of risk perception as a pre-motivational factor on behaviour may be mediated by motivational factors as assumed by the I-Change model [38]. Previous match-mismatch studies indicated that people in the pre-motivational phase benefit more from interventions that target their current motivational status [39, 40]. Therefore, it seems important to address HIV-risk perception in condom promotion intervention to raise the awareness of those in the pre-motivational phase.
Regarding the cues to condom use and similar to what was observed in some previous studies [14, 18, 41], knowing someone who was infected with HIV or who died of AIDS was associated with consistent condom use. However, some conditions need to be considered before including this cue in future interventions aiming to promote consistent condom use. Firstly, students’ exposure to such cues may be limited since HIV infected persons in Sudan tend to hide their infection due to the high social stigma and discrimination against PLWHA [42]. Secondly, it has been suggested that fear appeal messages may increase the stigma and discrimination against PLWHA [43]. Besides, previous research suggested that using fear appeal to change the high-risk behaviours among people with low self-efficacy may result in a defensive behaviour to avoid the fear appeal messages [44]. Our study also found an association between knowing somebody who could provide condoms confidentially and consistent condom use, which was also found by previous studies that identified purchase embarrassment as a barrier to consistent condom use [18, 45, 46]. In a conservative community like Sudan, purchasing condoms is usually associated with embarrassment because of the social stigma associated with premarital sex. To cope with this embarrassment, some sexually active students used to ask someone they knew to buy condoms for them or go to pharmacies in remote areas to purchase condoms [14, 18].
Concerning the attitude towards condom use, our study revealed that the participants’ perception of condom disadvantages (cons) was uniquely associated with consistent condom use. Similar to previous research [47, 48], the perceived negative effect of condom use on sexual pleasure was associated with inconsistent condom use among this study population. It should be acknowledged that latex condoms represent mechanical barriers that reduce sensation and physical contact, which could affect sexual pleasure and this represents an important barrier to consistent condom use [47, 49]. However, the effect of condoms on sexual pleasure could be minimised by promoting the use of high-quality condoms and emphasising the pleasure-enhancing aspects of condom use [47].
Regarding social influence on condom use, our study highlighted some important contextual differences between the Islamic and non-Islamic communities that should be considered. According to our study participants, parents` norms and support seemed to play no role in condom use in Sudan due to the *Islamic religious* values and prevailing social norms prohibiting all types of extramarital sex and discouraging open discussions about sex among family members [14]. This finding contradicts with results obtained from study findings from some non-Islamic cultures [50–52], but maybe explained by the fact that our participants were university students and thus have or want to become less dependent from their dependents. More qualitative in-depth research on this matter may be wanted to understand this finding better. Our study pointed to an interesting result regarding the positive role of *Islamic religious* scholars in promoting and supporting condom use by sexually active students. Again, this result is not in line with findings from previous studies identifying *Islamic religious* leaders as opponents to condom use [14, 53]. Nevertheless, other studies also revealed that religious scholars might support condom use by sexually active Muslims considering the Islamic values of preventing harm and disease [54, 55]. Although peer support, modelling and norms favouring consistent condom use were all associated with consistent condom use, only peer norms were uniquely associated with consistent condom use in this study. The importance of peer norms favouring condom use was also reported in other studies [56, 57]. A recent study has identified peers as the only social group among this population with whom sexual practices are discussed and recommended their involvement in condom promotion interventions to facilitate their implementation and maximise their benefits [14].
Self-efficacy was identified by the regression analysis as an important factor with a unique association with consistent condom use in this study, which is in agreement with what has been suggested by a recent qualitative study among the same populations [14], and previous studies [58–60]. Condom use self-efficacy is a multidimensional construct [60]. Previous research reported some gender-specific differences in these self-efficacy dimensions [61], which may necessitate further research to identify such differences among this population to facilitate the design of more gender-specific condom promotion interventions.
Although the association between consistent condom use and the awareness about HIV and the perceived severity and susceptibility to HIV was thoroughly assessed in this study, it should be acknowledged that in such a conservative community the fear of getting unwanted pregnancy could be very influential in students’ intentions to use condoms consistently. Therefore, future research should assess this association to inform future interventions aiming to promote consistent condom use.
## Practice implications
Promoting consistent condom use requires comprehensive interventions that address the different barriers. This study identified the salient psychosocial determinants of consistent condom use to be considered in future condom promotion interventions in Sudan and provided some suggestions on how to deliver such interventions.
HIV-related knowledge, especially HIV transmission and prevention, should be raised. The study identified some of the prevalent misconceptions and HIV-knowledge gaps to be targeted. Future research may investigate if videos of HIV infected persons talking about their experience could be used as cues to promote condom use among Sudanese students with high self-efficacy provided that carefully designed non-discriminatory messages are used. Suitable cue -reminders can also be used to complement interventions and augment their effectiveness [62]. Condom promotion interventions should also address the negative perceptions and emphasise the pleasure-enhancing aspects of condom use. This could be achieved by combining both emotional and factual messages [63].
Moreover, interventions should aim to change students` perception of their peers` beliefs (peer norm) and how they behave (modelling) concerning condom use. Norm-based interventions with strategies such as social norms marketing, personalised normative feedback and focus group discussions could be used for this purpose [64]. Finally, enhancing the students` self-efficacy to use condoms consistently is of paramount importance. All dimensions of condom use self-efficacy must be enhanced using the appropriate techniques such as verbal persuasion, condom use skills, condom negotiation and affect regulation skills [65–67].
A recent randomised control trial has shown that internet-based interventions are effective in behavioural change programs targeting HIV risk behaviour, including condomless sex [68]. This approach has several advantages: maintaining participants privacy, message tailoring, reaching the most at-risk population (MARPs) and saving time and resources [69]. Being the first study using an online questionnaire to study sexual behaviours among this population and considering the sensitive data obtained thorough this approach, our study suggested the suitability, feasibility and acceptability of this approach among university students in Sudan. However, RCT studies to investigate the effectiveness of web-based HIV interventions among this population are highly needed.
## Strengths and limitations
This is the first study focusing mainly on the psychosocial determinants of condom use among university students in Sudan. To the best of our knowledge, it is also the first study that used an online questionnaire to collect data about the sensitive issues around sexual practices among youth in the conservative community of Sudan. This was expected to be more comfortable and popular among university students and assumed to enable researchers to collect more valid data. Using a behavioural change theory, the I-Change model, as a theoretical framework for the study is also one of the strengths as this could help understand the students` condom use behaviour and identify its psychosocial determinants.
Despite these strengths, the study is not free of limitations. Firstly, being a cross-sectional study, a cause-effect relationship could not be established. Secondly, some of the participants were recruited through snowball sampling, which may question the representativeness of the sample and generalizability of the study results. Thirdly, the role of action planning and plan enactment as post-motivational mediators of the association between intention and behaviour and how the interaction between these determinants could influence the students` condom use were not assessed because these are better assessed with longitudinal studies rather than cross-sectional studies [70]. Finally, the limited number of participants prevented the gender analysis of the data to identify differences between male and female students to develop more gender-sensitive interventions.
## Conclusion
Unprotected sex is common among university students despite the attempts to promote condom use in Sudan. HIV-related knowledge, exposure to condom use cues, attitude towards condom use, peer norms favouring condom use and condom use self-efficacy are all associated with consistent condom use among university students in Sudan. Interventions seeking to promote consistent condom use among sexually active students should increase knowledge about HIV transmission and prevention, address perceived condom disadvantages and foster peer norms favouring condom use. Moreover, such interventions should enhance students` self-efficacy to avoid unprotected sex. Increasing students’ exposure to condom use cues may also help them use condoms consistently.
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---
title: Effects of Citrus kawachiensis Peel in Frailty-like Model Mice Induced by Low
Protein Nutrition Disorders
authors:
- Toshiki Omasa
- Satoshi Okuyama
- Atsushi Sawamoto
- Mitsunari Nakajima
- Yoshiko Furukawa
journal: Antioxidants
year: 2023
pmcid: PMC10045201
doi: 10.3390/antiox12030779
license: CC BY 4.0
---
# Effects of Citrus kawachiensis Peel in Frailty-like Model Mice Induced by Low Protein Nutrition Disorders
## Abstract
“Frailty” caused by a decline in physiological reserve capacity, chronic inflammation, and oxidative stress in the elderly has recently become a major social issue. The present study examined the effects of the peel of *Citrus kawachiensis* (CK), which exhibits anti-inflammatory, antioxidant, and pro-neurogenesis activities in frailty-like model mice. Male C57BL/6 mice (15 weeks old) were fed an $18\%$ protein diet (CON), a $2.5\%$ protein diet (PM), and PM mixed with $1\%$ dried CK peel powder for approximately 1 month. Mice were euthanized 2 or 8 days after a single intraperitoneal administration of lipopolysaccharide (LPS) and tissues were dissected. Among peripheral tissues, muscle weight, liver weight, and blood glucose levels were significantly higher in the PM–LPS–CK group than in the PM–LPS group. In the behavioral analysis, locomotive activity was significantly lower in the PM–LPS group than in the PM group. The reduction in locomotive activity in the PM–LPS–CK group was significantly smaller than that in the PM–LPS group. The quantification of microglia in the hippocampal stratum lacunosum-moleculare revealed that increases in the PM–LPS group were significantly suppressed by the dried CK peel powder. Furthermore, the quantification of synaptic vesicle membrane proteins in the hippocampal CA3 region showed down-regulated expression in the PM–LPS group, which was significantly ameliorated by the administration of the dried CK peel powder. Collectively, these results suggest that CK inhibits inflammation and oxidative stress induced by PM and LPS in the central nervous system and peripheral tissue. Therefore, C. kawachiensis is highly effective against “frailty”.
## 1. Introduction
Lifespans have been increasing worldwide with advances in health care and better diets, and many countries are now experiencing population aging. Aging is associated with an increased risk of a few diseases due to chronic inflammation, oxidative stress, and a decline in physiological reserve capacity. Aging decreases physical activity and food intake, resulting in protein-energy malnutrition, and has a negative impact on immunity and muscle strength. An increased susceptibility to stress, chronic inflammation, oxidative stress, and other factors may lead to a decline in the activities of daily living, the need for nursing care, and even death, and this is called “frailty” [1,2,3]. The repetition of these conditions leads to a vicious cycle, referred to as the “frailty cycle”, which has become a major social issue. Frailty includes physical frailty, such as sarcopenia and locomotive syndrome, and mental and psychological frailty related to cognitive dysfunction and depression-like symptoms, both of which may exacerbate the frailty cycle and, thus, must be carefully managed [1,2,3]. Moreover, oxidative stress caused by inflammatory cytokines and free radicals due to chronic inflammation has been implicated in various chronic diseases, such as autoimmune diseases, cancer, neurological diseases, and lifestyle-related diseases [4,5,6]. It is an important factor that accelerates the frailty cycle by creating an internal environment in which compensatory mechanisms are impaired. Furthermore, the propagation of inflammation not only to the periphery but also to the central nervous system has been suggested to accelerate brain aging and is also associated with mental disorders and neurodegenerative-related diseases, including Alzheimer’s disease [7], in which neuronal damage due to microglial activation and decreased brain-derived neurotrophic factor (BDNF) production are prominent features.
Citrus fruits contain a variety of bioactive components, especially polyphenols and flavonoids. In recent years, several citrus components have been reported to have a potential to prevent or treat not only peripheral diseases, but also central nervous system degenerative diseases caused by inflammation and oxidative stress [8]. Our laboratory extracted functional components from various citrus peels and screened them using cultured neurons, and we found that the components in *Citrus kawachiensis* peel were highly active in terms of brain-protective effects [9]. Therefore, our research has been focusing on the effects of peel components of Citrus kawachiensis, a specialty citrus fruit in Japan [10], on the suppression of central nervous system dysfunction induced by chronic inflammation or oxidative stress. The peel of C. kawachiensis contains larger amounts of bioactive components, such as 3,5,6,7,8,3′,4′-heptamethoxyflavone (HMF), auraptene (AUR), and naringin (NGI), than other citrus varieties [10,11], which are expected to exert ameliorative effects on the functional decline of the central nervous system and peripheral tissue. We previously reported that C. kawachiensis exhibited various anti-inflammatory, antioxidant, and brain-protective activities, such as the suppression of microglial activation and reductions in glutathione levels in the brain, in global cerebral ischemia model mice [12]. It also inhibited microglial activation and tau phosphorylation and enhanced neurogenesis in the brains of hyperglycemia model mice [13] and aging-accelerated model mice [14].
A protein malnutrition model has been reported, and the experiment was conducted by feeding a low-protein diet for four weeks [15]. The model showed hippocampal protein thiols decrease with a low protein diet and dramatic reactive gliosis accompanied by extensive neuronal loss following ischemia [15]; in addition, protein malnutrition has also been reported to decrease antioxidant capacity in the brain and may lead to increased oxidative stress [16], so a low protein diet impairs functional outcomes. Lipopolysaccharide has also been reported to induce oxidative stress and exacerbate inflammation in the body in animal models [17], suggesting that protein malnutrition and lipopolysaccharide administration-induced chronic inflammation reproduce frailty in the body. In the present study, we investigated the effects of dried C. kawachiensis peel powder on the central nervous system and peripheral tissues of frailty-like model mice induced by low-protein nutritional disorders.
## 2.1. Animals
All animal experiments were conducted in accordance with the guidelines of Matsuyama University (protocol # 18-008). Nine-week-old male C57BL/6N mice were purchased from Japan SLC (Hamamatsu, Japan). Mice were kept at 23 ± 1 °C with a light/dark cycle of 12 h (light period 8:00–20:00, dark period 20:00–8:00). Animals were kept with free access to water and food for the duration of the experiment.
## 2.2. Sample Treatment
The control group (CON) was fed an $18\%$ protein control diet, the protein malnutrition (PM) group a $2.5\%$ low-protein diet, and the PM–CK group a PM diet mixed with $1\%$ dried C. kawachiensis (CK) peel powder for the four-week feeding period. Then, the PM–LPS and PM–LPS–CK groups were intraperitoneally administered lipopolysaccharide (LPS) once (1 mg/kg of mouse), and mice were dissected either 2 or 8 days later. The group not administered LPS was treated with saline.
## 2.3. Food Intake
Mice were housed four per cage, and food consumption was measured each week. The amount of food consumed by one mouse was estimated by dividing the total food intake each day by the number of mice.
## 2.4. The Y-maze Test
Mice were placed at the tip of one of three arms (each arm was designated as A, B, or C) of a Y-shaped Y-maze device (length of 35 cm/width of 8.5 cm/height of 15 cm) and allowed to freely explore for 8 min. Mouse behavior was analyzed for the total distance travelled and immobility time using the ANY-maze Video Tracking System (Stoelting, Wood Dale, IL, USA) connected to a USB digital camera. A behavioral analysis was performed in a dark place with indirect illumination, feces and urine were processed for each test, and the apparatus was disinfected with alcohol each time to keep the inside clean.
## 2.5. Dissection
Blood was collected from the heart under anesthesia and followed by the transcardial perfusion of heparinized phosphate-buffered saline. The brain was removed and halved according to the cerebral longitudinal fissure. One half of the brain was soaked in $4\%$ of paraformaldehyde for 2 days and then in 15 and $30\%$ sucrose solutions for 1 day each. Brains were embedded in OCT compound, and 30 µm thick frozen brain sections (sagittal plane) were prepared using a cryostat (CM3050; Leica Microsystems, Heidelberger, Germany). The liver and gastrocnemius muscle were also collected. Blood samples were left to stand at room temperature for 30 min and then centrifuged at 1200× g at 4 °C for 20 min.
## 2.6. Blood Glucose Measurement
LabAssay™ Glucose (Mutarotase-GOD method; Wako, Osaka, Japan) was used to measure blood glucose levels. The experimental procedure was performed using the protocol in this kit, which involved measuring the absorbance of the sample and standard solutions at 570 nm with a microplate reader (Thermo Fisher, Tokyo, Japan).
## 2.7. Immunohistochemistry for Optical Microscopy
Thirty-micrometer-thick brain sections were immersed in $3\%$ hydrogen peroxide solution for 20 min to remove endogenous peroxidase and then blocked in $2\%$ skim milk for 60 min followed by $5\%$ normal goat serum solution for 60 min. Sections were incubated with a rabbit polyclonal antibody against ionized calcium-binding adaptor 1 (Iba1, 1:1000; Wako, Osaka, Japan), which is specifically expressed in microglia, with shaking at 4 °C overnight. Brain sections were reacted with an Envision-plus system-HRP-labeled polymer as a secondary antibody for 60 min. The DAB substrate was used to develop staining, followed by $95\%$ ethanol, $100\%$ ethanol, and xylene × 2 in that order, and then sealed with a cover glass. Images of stained brain sections were captured with an optical microscope (CX21; Olympus, Tokyo, Japan). Multiple brain sections from each mouse were stained.
## 2.8. Immunofluorescence for Confocal Microscopy
Thirty-micrometer-thick brain sections were immersed in HistoVT One (Nacalai Tesque, Kyoto, Japan) and heated at 70 °C for antigen retrieval. Sections were then cooled to room temperature and blocked with $2\%$ skim milk for 30 min followed by $5\%$ normal goat serum solution for 60 min. Sections were incubated with a mouse monoclonal antibody against a synaptic vesicle membrane protein (synaptophysin, 1:1000; Sigma-Aldrich, St. Louis, MO, USA) as the primary antibody with shaking at 4 °C overnight. The next day, sections were reacted with Alexa Fluor 488 goat anti-mouse IgG (H + L) (1:300; Invitrogen, Carlsbad, CA, USA) as a secondary antibody and shaken for 60 min in the dark. Brain sections were placed on glass slides using mounting medium with DAPI (Vectashield; Vector Laboratories, Burlingame, CA, USA). Stained brain sections were then observed, and images were captured using a confocal fluorescence microscopy system (LSM800, Zeiss, Oberkochen, Germany). Multiple brain sections from each mouse were stained.
## 2.9. Image Analysis
A quantitative analysis of immune-positive signals in the images was performed using ImageJ software (NIH, Bethesda, MD, USA). The particle analysis tool was used for the analysis, and the pixels of the immune-positive signals were accumulated.
## 2.10. Statistical Analysis
Data for individual groups are expressed as means ± SEM. Data were statistically analyzed between two groups using the t-test. A value of $p \leq 0.05$ was significant.
## 3.1. Changes in Body Weight and Food Intake in Different Experimental Groups
Body weight showed normal increases in the CON diet group but decreased in the PM group (Figure 1a). However, food intake was significantly higher in the PM group than in the CON group (Figure 1b–d; *** $p \leq 0.001$). Furthermore, a comparison of food intake in the fourth week showed that intake was slightly higher in the PM–CK group than in the PM group (Figure 1d; $p \leq 0.09$).
## 3.2. Percent Weight Loss 2 or 8 Days after the Administration of LPS
Comparisons of the CON and PM groups treated with saline showed that weight loss was significantly greater in the PM group than in the CON group 2 and 8 days after the administration of LPS (Figure 2a,b; ** $p \leq 0.01$, *** $p \leq 0.001$). Two days after the administration of LPS, weight loss was significantly greater in the PM–LPS group than in the PM group (Figure 2a; *** $p \leq 0.001$) and was not ameliorated by the dried C. kawachiensis peel powder (Figure 2a). Eight days after the administration of LPS, weight loss was significantly greater in the PM–LPS group than in the PM group (Figure 2b; *** $p \leq 0.001$). Body weight loss was significantly lower in the PM–LPS–CK group than in the PM–LPS group (Figure 2b; ** $p \leq 0.01$).
## 3.3. Ameliorative Effects of C. kawachiensis on Peripheral Dysfunction 8 Days after the Administration of LPS
We collected gastrocnemius muscle, liver, and serum samples to examine the peripheral effects of the PM diet and inflammation. Gastrocnemius muscle weight was significantly lower in the PM group than in the CON group (Figure 3a; *** $p \leq 0.001$) and significantly lower in the PM–LPS group than in the PM group (Figure 3a; *** $p \leq 0.001$). However, gastrocnemius muscle weight loss was significantly lower in the PM–LPS–CK group than in the PM–LPS group (Figure 3a; ** $p \leq 0.01$). Liver weight was significantly lower in the PM group than in the CON group (Figure 3b; *** $p \leq 0.001$) but was similar in the PM–LPS group and PM group. On the other hand, liver weight loss was significantly lower in the PM–LPS–CK group than in the PM–LPS group (Figure 3b, ** $p \leq 0.01$). Blood glucose levels were also significantly lower in the PM group than in the CON group (Figure 3c; *** $p \leq 0.001$). Furthermore, the decrease observed in the PM–LPS group was significantly lower in the PM–LPS–CK group (Figure 3c; *** $p \leq 0.001$).
## 3.4. Ameliorative Effects of C. kawachiensis on Spontaneous Behavior
We performed the Y-maze test to assess behavioral activity. The total distance traveled in 8 min did not significantly differ between the CON and PM groups 2 days after the administration of LPS (Figure 4a); however, it was significantly shorter in the PM–LPS group than in the PM group (Figure 4a; *** $p \leq 0.001$). Additionally, reductions in the total distance traveled were not attenuated by the dried C. kawachiensis peel powder. No significant differences were observed in immobility times 2 days after the administration of LPS between the CON and PM groups (Figure 4c), whereas it was significantly longer in the PM–LPS group than in the PM group (Figure 4c; *** $p \leq 0.001$). In addition, the immobility time in the PM–LPS–CK group was not suppressed (Figure 4c), as in the previous results. Eight days after the administration of LPS, no significant differences were noted in the total distance traveled between the CON and PM groups (Figure 4b); however, it was significantly shorter in the PM–LPS group than in the PM group (Figure 4b; * $p \leq 0.05$). The reduction observed in the total distance travelled in the PM–LPS group was significantly smaller in the PM–LPS–CK group (Figure 4b; * $p \leq 0.05$). Furthermore, no significant differences were noted in immobility times between the CON and PM groups (Figure 4d), whereas they were significantly longer in the PM–LPS group than in the PM group (Figure 4d; * $p \leq 0.05$). The longer immobility time observed in the PM–LPS group was reduced in the PM–LPS–CK group (Figure 4d; * $p \leq 0.05$).
## 3.5. Suppressive Effects of C. kawachiensis on Microglial Activation
The quantification of microglia in the stratum lacunosum-moleculare of the hippocampus revealed no significant differences between the CON and PM groups (Figure 5a,b); however, the total area of activated microglia was significantly higher in the PM–LPS group than in the PM group (Figure 5b; ** $p \leq 0.01$). This increase was significantly smaller in the PM–LPS–CK group (Figure 5b; * $p \leq 0.05$).
## 3.6. Protective Effects of C. kawachiensis on Neuronal Cell Function in the Hippocampus
Synaptophysin as an indicator of synaptic vesicle membrane proteins in neurons was examined and quantified in the stratum lucidum of the hippocampal CA3 region. As shown in Figure 6, a significantly stronger synaptophysin signal was observed in the CON group than in the PM group (Figure 6a,b; *** $p \leq 0.001$). Although there was no significant difference between the PM and PM–LPS groups (Figure 6b), synaptophysin signaling was significantly stronger in the PM–LPS–CK group than in the PM–LPS group (Figure 6a,b; * $p \leq 0.05$).
## 4. Discussion
The peel of C. kawachiensis has been shown to exert protective effects on the brains of various pathological mouse models, including global cerebral ischemia, type 2 diabetes, and senescence-accelerated models, through anti-inflammatory, antioxidant, and neuroprotective activities [10,12,13,14]. HPLC and NMR analyses have revealed that the peel of C. kawachiensis contains larger amounts of bioactive components, such as HMF, AUR, and NGI, than other citrus varieties [11]. A previous study reported that the dried peel of C. kawachiensis contained 0.27 mg/g of HMF, 4.07 mg/g of AUR, and 44.02 mg/kg of NGI [10]. Furthermore, these components exert various effects. HMF exhibits anti-inflammatory activity, inhibits neuronal cell death, promotes BDNF production, stimulates neurogenesis, improves memory impairment, and exerts antidepressant effects [18,19,20,21,22,23,24]; AUR exhibits anti-inflammatory activity, inhibits neuronal cell death, promotes neurogenesis, and suppresses tau phosphorylation [25,26,27,28,29]. NGI also exhibits anti-inflammatory activity, inhibits neuronal cell death, promotes neurogenesis, suppresses tau phosphorylation, and exerts antioxidant effects [28,29,30].
Frailty is the result of the interplay of various factors, including chronic inflammation and oxidative stress associated with aging, which reduces physiological reserve capacity and increases vulnerability to stress [1,2,3]. Many patients with frailty have a poor nutritional status, particularly protein-energy malnutrition. These factors contribute not only to sarcopenia and locomotive syndrome, but also to diseases of the central nervous system, such as cognitive dysfunction and mental disorders. However, frailty is a reversible disease because improvements in any of these factors may lead to recovery; therefore, appropriate interventions are needed [1,2,3]. Protein malnutrition alters various parameters of oxidative stress [15,16]; furthermore, inflammation caused by LPS administration aggravates the pathology and produces a frailty model. This may replicate the chronic disease conditions in the body of the elderly.
In the present study, food intake was slightly higher in the group fed dried C. kawachiensis peel than in the PM group (Figure 1d). These results are consistent with the effects of “Chinpi”, the dried peel of C. unshiu, an herbal medicine with stomachic effects. Chinpi is a component of the Kampo medicines Rikkunshito and Ninjin’yoeito, both of which enhance digestive function and are effective against anorexia. Previous studies suggested that the flavonoids present in citrus peels increase the level of ghrelin, an appetite-stimulating hormone [31,32,33]. Furthermore, the peel of C. unshiu contains HMF, which enhances appetite through 5-HT2 receptor antagonism, and HMF in dried C. kawachiensis peel powder has also been suggested to increase food intake [34]. Various mechanisms for age-related sarcopenia have been reported, including anorexia, a decrease in anabolic hormones such as growth hormone and insulin-like growth factor, and damage caused by inflammatory cytokines [35]. An increased food intake may ameliorate the losses in liver and muscle weights caused by a PM diet, and the HMF-induced increase in ghrelin levels also stimulates growth hormone secretion via the growth hormone secretagogue receptor [32,33,36]. Ghrelin has also been reported to exert anabolic effects on protein and suppress inflammatory cytokines [32,35,37], and these combined effects may have prevented muscle and liver weight losses in the PM–LPS–CK group (Figure 3a,b). Blood glucose levels are maintained by glycogenolysis and glycogenesis in the liver even during fasting. In the present study, endogenous glucose production may have been reduced in the PM group due to a decrease in glycogen storage, a smaller liver volume, and a lack of the amino acids needed for glycogenesis [38,39]. In contrast, the repair of peripheral tissue function by C. kawachiensis as described above may have increased blood glucose levels (Figure 3c).
In the behavioral analysis, inflammation caused by LPS decreased activity 2 days after its administration, which may have been due to sickness behavior during the acute phase of inflammation (Figure 4a,c), consistent with previous findings [40]. The decrease observed in behavior in the PM–LPS group 8 days after the administration of LPS was attributed to the previously reported spread of inflammation from the periphery to the brain, which led to brain dysfunction and depression-like symptoms [40,41]. On the other hand, muscle and brain improvements associated with anti-inflammatory, antioxidant, neuroprotective, and anti-depressive effects in peripheral tissues and the central nervous system in the PM–LPS–CK group may have contributed to the recovery of behavioral activity (Figure 4b,d, Figure 5 and Figure 6) [12,14,19]. In the brain tissue analysis, the quantification of microglia in the acute inflammatory phase showed no significant inflammation in the PM group; however, inflammation was confirmed after the administration of LPS. This result also demonstrated that peripheral inflammation propagates to the central nervous system [40,41]; however, the administration of the dried peel of C. kawachiensis significantly suppressed microglial activation in the brain, which is consistent with previous findings on the effects of the peel in the brain (Figure 5a,b) [12,14]. In addition, the quantification of synaptic vesicle membrane proteins, a marker of neuronal cell function, showed low immunoreactivity signals in the PM group. In spite of our expectations, no further deterioration was observed with the administration of LPS. These results suggest that malnutrition due to protein deficiency alone may induce significant damage to the central nervous system, which is regarded as a major factor accelerating frailty [1,2,3,42]. However, the dried peel of C. kawachiensis significantly inhibited neuronal cell dysfunction induced by the PM diet and administration of LPS (Figure 6a,b), suggesting that it maintained brain function.
Nobiletin, which is structurally similar to HMF and a polymethoxyflavone found in C. unshiu and C. depressa, was recently shown to ameliorate memory impairment by reducing Aβ in the brain of animal models of Alzheimer’s disease and has anti-inflammatory and antioxidant effects [43,44]. Furthermore, AUR was found to exert antidepressant effects by lowering malondialdehyde (MDA) and nitrite concentrations in the brain, thereby enhancing antioxidant capacity [27]. Furthermore, NGI suppressed cognitive impairment and oxidative stress by reducing MDA and glutathione levels in the brain [30]. It has been also reported that many polyphenols as ingredients of citrus and other plants, including naringin, could increase PPAR-gamma, which works as an antioxidant [28,45]. The anti-inflammatory, antioxidant, and neuroprotective effects of dried C. kawachiensis peel powder, which is rich in these bioactive components, have been confirmed and other effects are expected [12,13,14].
## 5. Conclusions
Dried C. kawachiensis peel powder has the potential to attenuate peripheral tissue and central nervous system dysfunctions under frailty-like conditions caused by protein-deficient malnutrition. Furthermore, it may be an effective food material for physical and psychosomatic frailty. We have confirmed the effect of the dried peel of C. kawachiensis in various disease model mice, and we were able to confirm the effect of the dried peel of C. kawachiensis in this frailty-like model as well.
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|
---
title: Environmental Enrichment and Metformin Improve Metabolic Functions, Hippocampal
Neuron Survival, and Hippocampal-Dependent Memory in High-Fat/High-Sucrose Diet-Induced
Type 2 Diabetic Rats
authors:
- Teh Rasyidah Ismail
- Christina Gertrude Yap
- Rakesh Naidu
- Narendra Pamidi
journal: Biology
year: 2023
pmcid: PMC10045208
doi: 10.3390/biology12030480
license: CC BY 4.0
---
# Environmental Enrichment and Metformin Improve Metabolic Functions, Hippocampal Neuron Survival, and Hippocampal-Dependent Memory in High-Fat/High-Sucrose Diet-Induced Type 2 Diabetic Rats
## Abstract
### Simple Summary
Type 2 diabetes can lead to catastrophic complications, including neurodegeneration and memory impairment. Therefore, it is essential to identify effective therapeutic strategies to improve blood glucose levels and prevent the onset of complications. This study evidently showcases environmental enrichment as an effective therapy for preserving mental health in diet-induced type 2 diabetic rats. The outcomes of this study can be translated to clinical trials in diabetic patients. Environmental enrichment can be introduced as one of the alternative therapies for preventing diabetes in pre-diabetic individuals and in established diabetes alongside metformin or other hypoglycemic pharmacotherapy.
### Abstract
Background: The Western-style diet-induced type 2 diabetes mellitus (T2D) may eventually trigger neurodegeneration and memory impairment. Thus, it is essential to identify effective therapeutic strategies to overcome T2D complications. This study aimed to investigate the effects of environmental enrichment (EE) and metformin interventions on metabolic dysfunctions, hippocampal neuronal death, and hippocampal-dependent memory impairments in high-fat/high-sucrose (HFS) diet-induced T2D rats. Methods: Thirty-two male rats (200–250 g) were divided into four groups: C group (standard diet + conventional cage); D group (HFS diet + conventional cage); DE group (HFS diet + EE cage/6hr daily); and DM group (HFS diet + metformin + conventional cage). Body weight was measured every week. T-maze tasks, anthropometric, biochemical, histological, and morphometric parameters were measured. The expression changes of hippocampal genes were also analyzed. Results: The anthropometric and biochemical parameters were improved in DE and DM groups compared with the D group. DE and DM groups had significantly higher T-maze percentages than the D group. These groups also had better histological and morphometric parameters than the D group. The interventions of EE and metformin enhanced the expression of hippocampal genes related to neurogenesis and synaptic plasticity (BDNF/TrkB binding, PI3K-Akt, Ras–MAPK, PLCγ–Ca2+, and LTP). Conclusion: Environmental enrichment (EE) and metformin improved metabolic functions, hippocampal neuron survival, and hippocampal-dependent memory in HFS diet-induced T2D rats. The underlying mechanisms of these interventions involved the expression of genes that regulate neurogenesis and synaptic plasticity.
## 1. Introduction
Type 2 diabetes mellitus (T2D) contributes to the worldwide disease burden, and devastatingly, the global prevalence of T2D is projected to increase to 7079 individuals per 100,000 by 2030 [1]. T2D is often initiated by obesity, a disease caused by the overconsumption of a Western-style diet [2]. The most representative examples of Western-style diets are fast foods, high-fat foods, and sugar-sweetened desserts and beverages. Studies on the effects of western-style diets on animals were performed using modified or enriched diets consisting of high percentages of fat and sucrose [2].
Over time, T2D can trigger a critically long-lasting impact on the hippocampus and its role in memory formation. The pathophysiology linking T2D with hippocampal impairments involved the combination of several factors. These factors include but are not limited to hyperglycemia, insulin resistance, adipose tissue dysfunction, and oxidative stress [3]. For this reason, effective therapeutic strategies are essential to overcome T2D-related hippocampal impairments. Some studies even emphasized the medicine-free approach for the interventions of these impairments [4]. In animal models, investigations on the medicine-free approach can be conducted using environmental enrichment (EE).
Environmental enrichment (EE) refers to complex motor stimulation and sensory and cognitive enhancement that provides animals with physical exercise opportunities, entertaining activities, various learning experiences, and complex social interactions [5]. EE cage is a large-space cage equipped with rotating or running wheels, toys, tubes, and tunnels. The accessibility of rotating or running wheels results in more voluntary exercise. Simultaneously, repeated exposures to novel items, such as toys, tubes, and tunnels, increase the opportunity to experience new sensory information [6]. Previous studies showed that EE enhanced learning and memory [7]. Some reports demonstrated that EE increased hippocampal neurogenesis and enhanced the expression of neurotrophic factors [8].
Biguanide metformin is a safe, oral anti-hyperglycemic drug of choice to treat T2D in obese and non-obese patients. Furthermore, it is inexpensive and has a good safety profile. Metformin has antioxidant properties that are capable of reducing oxidative stress and neuroinflammation. Thus, it has also recently attracted much attention due to its possible beneficial effects on the learning and memory [9].
The EE effects on various disease models are well-documented, and the anti-diabetic effect of metformin is well-known. However, the impact of EE and metformin against hippocampal impairments in HFS diet-induced T2D models are limited. Therefore, the present study was designed to investigate the effects of EE and metformin interventions on metabolic dysfunctions, hippocampal neuronal death, and hippocampal-dependent memory impairments in high-fat/high-sucrose (HFS) diet-induced T2D rats.
## 2.1. Animals and Ethics Statement
Thirty-two healthy male Wistar albino rats (200–250 g body weight) were obtained from the Jeffrey Cheah School of Medicine and Health Sciences Animal Facility, Monash University, Malaysia. All animal experiments were approved by the Monash University Animal Ethics Committee (AEC No. MARP/$\frac{2016}{109}$). Rats were acclimatized (1 week) before the study started. Rats were kept in conventional polypropylene cages (length: 460 mm × width: 300 mm × height: 160 mm) and were placed in a temperature-maintained (22–25 °C) and light-controlled (12-h/12-h light/dark phase) room. Rats had ad libitum access to standard chow pellets and tap water.
## 2.2. Diets
Standard and HFS diets were used in this study. A standard chow pellet diet comprised $20\%$ protein, $59.4\%$ carbohydrate, $4.8\%$ fat, and $4.8\%$ crude fiber with a caloric density of approximately 3.34 kcal/g (Specialty feeds, Glen Forrest, WA, Australia). The T2D was induced in the rats by feeding them a high-fat diet and a high-sucrose solution drink (HFS). The high-fat diet was composed of $20\%$ protein, $20\%$ carbohydrate, and $60\%$ fat, with a caloric density of approximately 5.24 kcal/g (D12492; Research Diets, New Brunswick, NJ, USA). The $10\%$ w/v sucrose solution in tap water was made fresh daily to drink ad libitum. The HFS diet mimicked the Western-style diet consisting of high-fat food and sweetened drinks [2].
## 2.3. Experimental Design
An illustration of the timeline of the experimental design is shown in Figure 1. Following one week of acclimatization, baseline parameters, such as body weight, BMI, biochemical parameters, and spatial learning and memory T-maze tasks, were measured. After completing the T maze tasks, eight rats were randomly allocated to the control group (C group, $$n = 8$$) on week two. These rats were placed in conventional polypropylene cages and were maintained on an ad libitum standard chow pellet diet and tap water. In contrast, the remaining twenty-four rats were fed the HFS diet to induce T2D. The HFS diet feeding procedure lasted ten weeks, followed by fasting blood glucose (FBG) measurement. Rats with fasting blood glucose above 6.7 mmol/L suggested that T2D was successfully induced and were kept in the study [10]. These rats were randomly subdivided into three groups of eight rats (D, DE, and DM groups) and were continuously fed the HFS diet until the end of the study. As interventions, rats in the DE group were placed in EE cages for 6 h/day, and rats in the DM group were given the anti-diabetic drug metformin by gavage feeding at a dose of 250 mg/kg body weight once daily. Bodyweight measurement was taken every week, and the T-maze tasks were conducted again in week 38. Moreover, biochemical parameters, including fasting blood glucose (FBG), C-peptide, triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), free oxygen radicals testing (FORT), free oxygen radicals defense test (FORD), and serum brain-derived neurotrophic factor (BDNF), were measured in week 42. Finally, rats were humanely sacrificed, and several organs, such as adipose tissues, pancreas, and brains, were collected for further analyses.
## 2.4. Environmental Enrichment (EE) Cages
The EE cages (length: 500 mm × width: 500 mm × height: 300 mm) were equipped with nesting material, a rotating wheel, plastic tubes, and toys (Figure 2). A maximum of three rats can be accommodated in each EE cage. Rats (group DE) were placed in the EE cages for six hours during their dark phase when they were naturally active and had free access to the HFS diet. The EE cages were cleaned, and the EE equipment was changed daily throughout the experimental period [11].
## 2.5. T-Maze Tasks: Spontaneous Alternation and Rewarded Alternation
T-maze apparatus was used to evaluate spatial learning and memory function, and rats were subjected to two tasks, spontaneous alternation and rewarded alternation [12]. The T-shaped apparatus was made up of black acrylic that consisted of a start alley (66 cm L × 16 cm W × 40 cm H) and two arms (50 cm L × 16 cm W × 40 cm H). Guillotine doors were used to close all arms manually (Figure 3). All tasks were carried out in a sound-attenuated room during the dark phase. Rats were adapted to the T-maze environment for two days by placing them in the maze for 30 min daily before commencing any T-maze tasks.
## 2.6. Spontaneous Alternation Task
The spontaneous alternation task was conducted for four days, with six runs performed daily. In each run, a rat was placed at the start arm and allowed to locomote down the start alley and choose either maze arm (all rat’s limbs had to be in the chosen arm). The rat was returned to its home cage for 3 min before the next run. The chosen arms and the total number of alternations made by the rat were recorded. The percentage of spontaneous alternation was calculated as follows: spontaneous alternation % = (total number of alternated arm visits/total number of arm visits) × 100.
## 2.7. Rewarded Alternation Task
This task was performed after the spontaneous alternation task was completed. Food intake was restricted (12 g/rat/day; provided between 8 to 10 a.m.) for two days before the task sessions to maintain high motivation during the T-maze exploration for the food reward. The rewarded alternation task was performed for four days, consisting of six trials daily, with a 3 min inter-trial interval. Each trial had two runs, viz. forced run and choice run. Food reward was placed at the end of the T-maze arms before the trial started. In the forced run, one arm was blocked, and a rat was forced into the open rewarded arm. After the rat ate the food reward, it was returned to its home cage for 3 min before the choice run was carried out. The guillotine door was removed in the choice run, and the rat was free to locomote both arms. If the rat entered the rewarded novel arm, the response was recorded as a correct response. However, if the rat reentered the same arm during the forced run, it was recorded as a wrong response. The percentage of correct responses was calculated as follows: correct response % = (total number of correct responses/total number of trials) × 100.
## 2.8. Measurement of Anthropometric Parameters
The body weight, percentage of weight gain (PWG), body mass index (BMI), and adiposity index (AI) were measured as indicators of obesity in rats. All rats’ body weight was measured every week, whereas PWG, BMI, and AI were measured at the end of the experiment. The total weight gain was determined by subtracting the initial body weight from the final body weight. The percentage of weight gain (PWG) was calculated using the following formula: PWG = total weight gain/initial body weight × 100 [13]. The body mass index (BMI) was calculated as follows: BMI = final body weight/final body length squared (g/cm2). The body length was measured between the tip of the nose and the anal region. The BMI for normal adult rats ranged between 0.45 ± 0.02 and 0.68 ± 0.05 g/cm2 [14]. The adiposity index (AI) was calculated as follows: AI = (weight of excised white adipose tissues/final body weight) × 100 [15]. The excised white adipose tissue comprised retroperitoneal, epididymal, and mesenteric parts.
## 2.9. Measurement of Fasting Blood Glucose (FBG)
The fasting blood glucose (FBG) samples were collected via the tail vein of the overnight fasted rats and were immediately measured using a glucometer (B/BRAUN omnitest® 3).
## 2.10. Measurement of C-Peptide
Serum C-peptide level was determined using the ELISA kits Elabscience E-EL- R0032. Instead of measuring insulin levels, we measured the serum C-peptide levels for evaluating insulinemia. Similar to insulin, C-peptide is also a good indicator of pancreatic beta-cell function. C-peptide is co-secreted with insulin in equal amounts by pancreatic beta-cells following glucose stimulation [16].
## 2.11. Measurement of the Lipid Profile
Ten microlitres of lateral tail vein blood samples were collected and were instantly analyzed using a handheld CardioChek PA® analyzer (Polymer Technology Systems, Inc., Indianapolis, IN, USA). The triglyceride (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) levels were recorded.
## 2.12. Measurement of Oxidative Status
The systemic oxidative status was assessed by quantitating reactive oxygen species (ROS), antioxidant capacity level, and redox (reductive–oxidative) balance. The ROS was determined using free oxygen radicals testing (FORT). Meanwhile, the free oxygen radicals defense test (FORD) determined the antioxidant capacity level. Both FORT and FORD levels were used to determine the redox balance. These oxidative status analyses were measured using a free oxygen radical analyzer (CR3000 FORM® plus, Callegari, Parma, Italy) according to the manufacturer’s (Callegari, Parma, Italy) instruction [17]. The FORT and FORD results are expressed as mmol H2O2 Eq/L and mmol/L of Trolox Eq/L, respectively. The reference values of FORT are <2.36 mmol H2O2 Eq/L with linearity ranging from 1.22 to 4.56 mmol H2O2 Eq/L. The reference values for FORD are 1.07–1.53 mmol/L of Trolox Eq/L, with the linearity ranging between 0.25 to 3.0 mmol/L of Trolox Eq/L. Redox balance was defined as the ratio of FORD (mmol Trolox Eq/L) to FORT (mmol H2O2 Eq/L) [18]. Low values of redox balance indicate oxidative stress.
## 2.13. Measurement of Serum BDNF
The serum BDNF was used as an indicator for learning and memory function, as BDNF can cross the blood–brain barrier resulting in a correlation in blood and brain BDNF concentrations [19]. The serum BDNF was determined using the ELISA kits Cusabio Biotech CSB-E04504r.
## 2.14. Tissue Preparation
All rats were euthanized by cervical dislocation at the end of the experiment. The splenic portion of the pancreas, retroperitoneal white adipose tissue (WAT), interscapular brown adipose tissue (BAT), and the brains (right hemispheres) were collected and fixed in $10\%$ neutral buffered formalin for 48 h for further histopathological study. On the other hand, the hippocampi (from the left hemispheres) were immediately removed, placed in cryotubes, and frozen in liquid nitrogen. The hippocampi were stored at −145 °C until gene expression analysis.
## 2.15. Histology
The post-fixed specimens were trimmed accordingly and were individually placed into the labeled histological cassette. The specimens were processed in an automatic tissue processor. Then, the specimens were embedded in a paraffin block and were cut serially at five μm thickness with a rotary microtome. Subsequently, the sections were mounted on microscope slides, and three consecutive sections were stained with haematoxylin and eosin (H&E).
## 2.16. Image Morphometry
Microscopic images were digitally photographed at ×100 and ×200 magnifications using an Olympus BX41 microscope equipped with a microscope camera and imaging software AnalySIS LS Report 2.6. Image processing and morphometric analyses were carried out independently by two blinded observers using computer-aided image analysis software Fiji/ImageJ (Fiji2.3.0) (NIH, Bethesda, MD, USA; http://rsbweb.nih.gov/ij/, accessed on 16 March 2023).
## 2.17. Morphometric Measurement of Adipose Tissue
The retroperitoneal white adipose tissue (WAT) size was measured using the Analyze Particles macro of (Version 1.53t) The average values were obtained from 100 white adipocytes per rat [20]. On the other hand, the percentage of lipid droplet content in the interscapular brown adipose tissue (BAT) was measured using the Measure macro of ImageJ [21]. The average percentage values were obtained from five non-overlapping interscapular sections per rat.
## 2.18. Morphometric Measurement of Pancreatic Islets
The pancreatic islets’ area and circularity index were measured in ten non-overlapping pancreatic fields per rat and were determined using the Analyze Particles macro of ImageJ. The circularity index reports the degree of roundness, where 1.0 corresponds to a perfect circle [22,23].
## 2.19. Morphometric Measurement of Hippocampal Neurons
The hippocampal neurons in CA1 and CA3 regions were quantified in three non-overlapping visual fields per rat. The surviving neuron had a triangular body with a basophilic rim of the cytoplasm. It also has a vesicular nucleus and prominent nucleoli. In contrast, a damaged neuron appeared as a dark and shrunken cell [24]. The percentage of surviving neurons was calculated by dividing the number of surviving neurons by the total number of neurons ×100.
## 2.20. RNA Extraction
Briefly, RNA was isolated from the hippocampal tissues using the RNeasy Mini Kit (catalog no. 74104; Qiagen GmbH, Hilden, Germany). The total RNA concentration was determined by Nanodrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). A ratio of absorbance of approximately 2.0 at 260 and 280 nm was acceptable. The extracted total RNA was stored at −80 °C for subsequent use.
## 2.21. Analysis of Gene Expression by the Real-Time PCR
The real-time PCR was performed to evaluate the expression of seventeen genes related to neurogenesis and synaptic plasticity. The analysis was performed in five biological replicates with each technical triplicate (per group).
Following RNA extraction, the total cDNA was synthesized using RT2 First Strand Kit (catalog no. 330401; Qiagen). Next, the cDNA was diluted with RNase-free water and mixed with 2xT2 SYBR Green qPCR Mastermix (catalog no. 330503; Qiagen). This mixture was aliquoted onto the custom RT2 Profiler PCR Array (catalog no. 330171; Qiagen). The custom RT2 Profiler PCR array contained four sets of 21 designed, optimized, and verified RT2 qPCR primer assays, including four reference genes (Actb, Pgk1, Hprt1, and Tbp), a proprietary control panel to monitor genomic DNA contamination (GDC), the first strand synthesis (RTC) and real-time PCR efficiency (PPC) (Table 1). The cDNA was used as the PCR template and was amplified using the Applied Biosystems Step One Plus™ Real-Time PCR system (Life Technologies™ Waltham, MA, USA) under the following thermal cycling conditions: 10 min at 95 °C, followed by 40 cycles of 15 s at 95 °C and 1 min at 60 °C.
*The* generated cycle threshold (CT) values from each reaction were exported to the Expression Suite version 1.3 (Life Technologies/Applied Biosystems, Waltham, MA, USA) to rapidly and accurately quantify relative gene expression across many genes and samples. The relative gene expression was calculated using the 2−ΔΔCt method [25]. Four reference genes (Actb, Pgk1, Hprt1, and Tbp) were used to normalize the reactions, and the C and D groups were used as calibrators. Changes in gene expression were analyzed with the Student’s t-test followed by Benjamini Hochberg correction.
The fold-change values were expressed LOG2 fold-changes (calibrator groups set to 0). The fold changes lower than 1 (decreased gene expression) were converted to a negative number, and fold changes greater than 1 (increased gene expression) were converted to a positive number. Genes were identified as differentially expressed if FDR q < 0.05 and LOG2 fold-change of value > 1.0-fold.
## 2.22. Statistical Analysis
Statistical analysis for the lipid panel and morphometric analyses were performed using the non-parametric Kruskal–Wallis test, followed by Dunn’s multiple comparison test. Data were reported as medians with interquartile ranges. Other parameters were measured using the one-way analysis of variance (ANOVA) with the Bonferroni post-hoc test and were reported as mean ± standard deviation (SD). All statistical analyses were carried out using a GraphPad Prism version 8.0 (GraphPad Software, Inc, San Diego, CA, USA) except for the gene expression analysis, which was performed using Expression Suite software described in the methodology. p of <0.05 was considered statistically significant.
## 3. Results
There were no significant differences in the baseline parameters between all rats.
## 3.1. Effects of EE Exposure and Metformin Treatment on Fasting Blood Glucose (FBG), Serum C-Peptide, Histological Features, and Morphometric Measurement of Pancreatic Islets in HFS Diet-Induced T2D Rats
Previous studies proved the association between overconsumption of the HFS diet and T2D. Typically, T2D is characterized by hyperglycemia and hyperinsulinemia. To investigate the possible anti-diabetic effects of EE and metformin interventions in HFS diet-induced T2D rats, we measured two T2D indicators, FBG, and serum C-peptide.
As expected, the D group had higher FBG and serum C-peptide levels than the C group ($p \leq 0.05$), whereas the DM group had lower FBG and serum C-peptide levels than the D group ($p \leq 0.05$). Surprisingly, the DE group had a similar outcome to the DM group ($p \leq 0.05$). ( Table 2). This critical finding implied that EE exposure triggered anti-hyperglycemic and anti-hyperinsulinemic effects in HFS diet-induced T2D rats.
Next, we determined the effects of EE and metformin interventions on the histology and morphometry of pancreatic islets in HFS diet-induced T2D rats. Our result (Figure 4) showed that the D group had oversized and irregular islets. Furthermore, some parts of the islets in the D group exhibited vacuolated cells with pyknotic nuclei. The EE and metformin interventions remarkably prompted islet recovery. The DE and DM groups had smaller and partially irregular islets than the D group. Although these islets were moderately rescued, vacuolated cells were almost undetected.
The morphometric analysis significantly validated these histological observations (Figure 4). The mean area confirmed the size of the pancreatic islets. In contrast, the mean circularity confirmed the shape of the pancreatic islets, respectively. These results indicated that EE and metformin interventions promoted recovery and preserved pancreatic islets in HFS diet-induced T2D rats.
## 3.2. Effects of EE Exposure and Metformin Treatment on Serum Lipid Profile, Anthropometric Parameters, Histological Features, and Morphometric Measurement of Adipose Tissue in HFS Diet-Induced T2D Rats
Other than T2D, the HFS diet is also induced dyslipidemia and obesity. Dyslipidemia is characterized by an odd combination of high TG and TC levels and low HDL-C levels [26]. Hence, we measured the serum lipid profile to investigate the possible anti-dyslipidemic effects of EE and metformin interventions in HFS diet-induced T2D rats.
By the end of this study, we found that the D group had higher levels of TG and TC and lower levels of HDL-C than the control ($p \leq 0.05$). Meanwhile, DE and DM groups had lower levels of TG and TC than the D group ($p \leq 0.05$), but their HDL-C levels were insignificant (Table 3). These results indicated that the interventions of EE and metformin promoted the anti-dyslipidemic activities in HFS diet-induced T2D rats.
Furthermore, we measured the anthropometric parameters to investigate the possible anti-obesity effects of EE and metformin interventions in HFS diet-induced T2D rats. Based on Table 3, the anthropometric parameters, including final body weight, PWG, and BMI of the D group, were higher than the C group ($p \leq 0.05$). On the contrary, both DE and DM groups had lower anthropometric parameters than the D group ($p \leq 0.05$). This finding implied that the interventions of EE and metformin promoted bodyweight reduction in HFS diet-induced T2D rats.
Next, we determined whether the body weight reduction was due to adipose tissue loss. For this purpose, we analyzed the AI, histological features, and morphometric measurement of adipose tissue. Our results showed that the D group’s AI was higher than the C group’s ($p \leq 0.05$), while both DE and DM groups had lower AI than the D group ($p \leq 0.05$) (Table 4). Moreover, the histological analysis revealed that the WAT in the D group was more extensive than in the C group. In contrast, the WAT in DE and DM groups was less extensive than in the D group. As for the lipid droplets in BAT, the D group had larger droplets than the C group. Meanwhile, DE and DM groups had smaller droplets than the D group (Figure 5). Furthermore, the results of the morphometric analysis confirmed these observations (Table 5). These outcomes indicated that EE and metformin interventions in HFS diet-induced T2D rats promoted adipose tissue loss.
## 3.3. Effects of EE Exposure and Metformin Treatment on Oxidative Status in HFS Diet-Induced T2D Rats
Overconsumption of the HFS diet leads to T2D, which is also linked to the increment of oxidative stress [27]. This study also determined whether EE and metformin interventions have the anti-oxidative capacity to overcome the oxidative stress induced by HFS diet-induced T2D. It was performed by assessing serum FORT, FORD, and redox balance levels.
Our results (Table 4) revealed that the serum FORT level was higher in the D group than in the C group ($p \leq 0.05$) and exceeded the threshold of 2.36 mmol H2O2 Eq/L. It indicated that the HFS diet initiated the reactive oxygen species (ROS) and increased oxidative stress. Although the serum FORT levels in DE and DM groups exceeded the threshold, they were significantly lower than in the D group. Nevertheless, all groups had normal serum FORD levels, indicating that all groups had normal antioxidant levels. The FORT and FORD levels were used to calculate the redox balance ratio. As a result, the D group had a lower redox balance ratio than the C group ($p \leq 0.05$), indicating the oxidative stress state. More importantly, the redox balance ratio of the DE ($p \leq 0.05$) and DM ($p \leq 0.05$) groups was higher than the D group. Overall, these results indicated that EE and metformin interventions alleviated oxidative stress in HFS diet-induced T2D rats.
## 3.4. Effects of EE Exposure and Metformin Treatment on Spatial Learning and Memory Function, Serum BDNF, Histological Features, and Morphometric Measurement of Hippocampal Neurons in HFS Diet-Induced T2D Rats
A recent study has proved that T2D is significantly associated with hippocampal neuronal death and hippocampal-dependent memory impairments [28]. Herein, we investigated whether EE and metformin interventions improve hippocampal neuron survival and hippocampal-dependent memory function in HFS diet-induced T2D rats. For this purpose, we evaluated the T-maze tasks, serum BDNF levels, histology, and morphometry of hippocampal neurons.
In this study, the T-maze tasks (spontaneous alternation and rewarded alternation) were performed to evaluate the effects of EE and metformin interventions on spatial learning and memory function in HFS diet-induced T2D rats. Table 5 shows that the D group had lower percentages of correct response and spontaneous alternation than the C group ($p \leq 0.05$). Contrarily, DE and DM groups had a higher correct response and spontaneous alternation percentages than the D group ($p \leq 0.05$). These results indicated that diabetes caused spatial learning and memory deficits, but more importantly, the EE and metformin interventions significantly ameliorated these deficits in HFS diet-induced T2D rats.
Next, we investigated the serum BDNF levels in all rats. We found that the D group’s serum BDNF levels were lower than the C group ($p \leq 0.05$). On the contrary, DE and DM groups had higher serum BDNF levels than the D group ($p \leq 0.05$) (Table 5). The increment of the serum BDNF in HFS diet-induced T2D rats that received either EE or metformin indicated that these interventions improved hippocampal neuron survival and hippocampal-dependent memory function.
As learning and memory relate to the hippocampus, we evaluated the histological features of the pyramidal neurons in the hippocampus subregions CA1 and CA3 that are important in memory formation. Many CA1 and CA3 pyramidal neurons in the D group were dark-stained and shrunken. On the other hand, most of the pyramidal neurons (in both subregions) in the DE and DM groups were healthy and appeared as triangular bodies. They had basophilic rims of the cytoplasm, vesicular nuclei, and prominent nucleoli (Figure 6).
The results of the morphometric analysis confirmed these histological findings. The D group had less surviving neuron percentage in CA1 and CA3 subregions than the C group ($p \leq 0.05$). In contrast, DE and DM groups had more surviving neuron percentages than the D group ($p \leq 0.05$) (Figure 6). These outcomes indicated that HFS diet-induced T2D triggered hippocampal neuronal death. More importantly, EE and metformin interventions enhanced hippocampal neuron survival in HFS diet-induced T2D rats.
## 3.5. Effects of EE Exposure and Metformin Treatment on Gene Expression in the Hippocampus of HFS Diet-Induced T2D Rats
In addition to mentioned parameters, we also investigated the expression of the hippocampal genes in all rats. The real-time PCR was performed to evaluate the expression of seventeen hippocampal genes related to neurogenesis and synaptic plasticity. We first investigated the expression of candidate genes of group D relative to the C group. Our results revealed that the expressions of Bdnf, Irs1, Pik3ca, Bcl2, and Atf4 were significantly decreased (downregulated) in the D group compared to the C group. In contrast, the expression of Gsk3b was significantly increased (upregulated) in the D group compared to the C group (Figure 7). These results suggested that HFS diet-induced T2D impairs neurogenesis mediated through the altered expression of these genes.
For the last part of this study, we investigated the expression of candidate genes of group DE and DM groups relative to the D group. Interestingly, we found that the expressions of Bdnf, Ntrk2, Irs1, Bcl2, Atf4, Map2k1, Mapk1, Camk2g, Grin1, and Gria2 were significantly increased (upregulated) in the DE group compared to the D group. Meanwhile, the expression of Gsk3b was significantly decreased (downregulated) in the DE group compared to the D group (Figure 8). These results suggested that EE exposure promotes neurogenesis and synaptic plasticity by altering the expression of these genes in HFS diet-induced T2D rats. In addition, the metformin treatment also promotes neurogenesis and synaptic plasticity by altering the expression of Ntrk2, Irs1, Gsk3b, Bcl2, Map2k1, and *Grin1* genes in HFS diet-induced T2D rats.
## 4. Discussion
Extensive studies revealed the correlation between a Western-style diet with obesity and T2D. Eventually, individuals with T2D may develop neurodegeneration and memory impairment. Such impairments are due to direct or indirect T2D consequences such as hyperglycemia, insulin resistance, adipose tissue dysfunction, and oxidative stress [29,30,31]. Therefore, it is crucial to identify effective therapeutic strategies for these impairments, and the medicine-free approach remains a priority.
*In* general, this study provides rodent model evidence that EE and metformin interventions improved hippocampal neuron survival and hippocampal-dependent memory function in HFS diet-induced T2D. In addition, our study also shows that EE has similar anti-diabetic properties to metformin by alleviating metabolic dysfunctions in HFS diet-induced T2D rats.
Environmental enrichment (EE) with ample space and various stimulators provides physical exercise opportunities, entertaining activities, learning experiences, and complex social interactions [5]. Studies proved that EE promotes hippocampal neurogenesis and memory function. In addition, EE also enhances the expression of neurotrophic factors [7]. Previous studies also suggested that exercise (such as in EE) is beneficial in treating the metabolic dysfunctions of the T2D [32,33]. In the following paragraphs, we will discuss the findings of this study, the similar anti-diabetic effects of EE to metformin, and, more importantly, the neuroprotective effects of the individual intervention of EE and metformin.
The benefit of metformin use in T2D is well acknowledged. Still, many studies explored alternative strategies for treating T2D and its complications. In our study, the medicine-free EE shows similar anti-diabetic medicinal effects to metformin, including anti-hyperglycemia, anti-hyperinsulinemia, anti-dyslipidemia, and anti-oxidative stress. In addition, EE and metformin interventions also preserved pancreatic islets and promoted adipose tissue loss in our rat model of HFS diet-induced T2D.
In our study, the EE exposure reduced the serum glucose in the HFS diet-induced T2D rats. We believe that the exercise component of EE plays a crucial strategy in glycemic control. Exercise promotes energy expenditure and induces muscular contraction-mediated glucose uptake, which facilitates the removal of excess glucose from blood circulation (hypoglycemic effect) [34]. Our findings also showed that EE exposure alleviated the oversecretion of insulin in the HFS diet-induced T2D rats. Although we measured the serum C-peptide in our study, its level is proportionate to the insulin level. The C-peptide is part of proinsulin, cleaved prior to co-secretion with insulin by the pancreatic beta-cells [16]. The histology and morphometry of pancreatic islets were also investigated, and our study showed that the EE exposure preserved the structure of the pancreatic islets in the HFS diet-induced T2D rats. We assume that the decreased serum C-peptide and the preserved pancreatic islet morphology were possibly due to the alleviation of the glycemic control in the HFS diet-induced T2D rats. It eventually inhibits the overstimulation of pancreatic islets and the over secretion of the insulin [34].
Our study also showed that EE exposure promoted weight loss and alleviated BMI, AI, and dyslipidemia in the HFS diet-induced T2D rats. Again, we believe that exercise in EE plays a vital role in these changes. Although our EE setting lacks intense resistance or endurance exercises, we believed the exercise was sufficient to promote energy expenditure and enhance the lipolysis [35]. The exercise generates a negative energy balance that triggers body weight loss and improves BMI [36]. The EE mechanisms responsible for alleviating dyslipidemia and AI may relate to the increased lipoprotein lipase activity that mediates triglyceride hydrolysis and hepatic cholesterol excretion [37]. The histology and morphometry of WAT and BAT confirmed these findings. The exercise alleviates WAT and BAT in the HFS diet-induced T2D rats. It may involve the elevation of mitochondrial activity, adipokine secretion alteration, glucose uptake, and lipidome reductions [38,39].
Identical to metformin, the EE exposure also reduced the oxidative stress in the HFS diet-induced T2D rats. However, the underlying mechanism of the anti-oxidative activity of EE and metformin is not fully understood. Few studies revealed that metformin increased the expression of the nuclear factor E2-related factor 2 (Nrf2) protein. The increment of Nrf2 protein activated antioxidant defense systems such as superoxide dismutase (SOD) [9]. Meanwhile, a recent study proposed that EE can eliminate oxidative stress by altering the detoxifying metabolism. The detoxifying metabolism has three phases that modify toxins into active metabolites, catalyze the active metabolites into hydrophilic products with transferase enzymes, and excrete the final products via various transporter systems. The EE regulates enzymes participating in the detoxification metabolism, such as cytochrome P450 family 1 subfamily A member 2 (Cyp1a2) and carbonyl reductase2 (Cbr2) [40]. The anti-oxidative activities of EE and metformin might be responsible for anti-diabetic and neuroprotective effects in the HFS diet-induced T2D rats.
The main findings of this study indicated that individual intervention of EE and metformin improved the serum BDNF, hippocampal-dependent memory function (T-maze tasks), and hippocampal neuron survival in the HFS diet-induced T2D rats. In conjunction with these pieces of evidence, the individual intervention of EE and metformin also improved the expression of hippocampal genes related to neurogenesis and synaptic plasticity in the HFS diet-induced T2D rats.
T-maze is an animal-friendly procedure and a valuable tool for validating spatial learning and memory functions. This procedure is based on the natural tendency of animals to explore and memorize their environment to obtain food. The present study showed that the individual intervention of EE and metformin increased the correct response and spontaneous alternation percentages. These results indicated that these interventions improved hippocampal-dependent memory functions in the HFS diet-induced T2D rats. Brain-derived neurotrophic factor (BDNF) is one of the possible mediators responsible for improving these rats’ learning and memory function [19].
The BDNF is a vital neurotrophin involved in neuronal development, survival, maintenance, learning, and memory function. It is widely expressed throughout the central nervous system and released into the blood circulation by the brain. The availability of the serum BDNF is another piece of evidence that indicates the hippocampal learning and memory functions are preserved [41]. In our study, the individual intervention of EE and metformin significantly increased the serum BDNF in the HFS diet-induced T2D rats. We proposed that the possible mechanisms of EE and metformin involved the alteration of BDNF secretion and expression.
Hippocampus is a brain structure with several critical subregions, the cornu ammonis (CA: CA1, CA2, and CA3) and the dentate gyrus. These regions are composed of pyramidal neurons that support cognitive function, including but not limited to learning and memory response [42]. Our results revealed that the individual intervention of EE and metformin significantly enhanced hippocampal neuron survival in the HFS diet-induced T2D rats. We found that the T2D rats that received either the EE or metformin interventions had a higher percentage of surviving neurons (in the CA1 and CA3 subregions) than the non-treated T2D rats. We suggested that EE and metformin’s anti-diabetic and anti-oxidative stress activities are the possible mechanisms involved in hippocampal neuron survival enhancement.
We also proposed that the EE and metformin promote the expression of hippocampal genes related to neurogenesis and synaptic plasticity in the HFS diet-induced T2D rats. *These* genes regulate the binding of BDNF/TrkB and its downstream signaling, including PI3K-Akt and Ras–MAPK pathways. The BDNF binds to tyrosine receptor kinase B (TrkB) and activates three main intracellular signaling cascades. The BDNF/TrkB-signalling promotes neuron survival by activating the phosphatidylinositol 3 kinase pathway (PI3K-Akt) and cellular proliferation by the Ras–mitogen-activated protein kinase pathway (Ras–MAPK). Moreover, BDNF also promotes memory formation by regulating the phospholipase Cγ pathway (PLCγ–Ca2+) [43]. Thus, we assessed the hippocampal expression of seventeen hippocampal genes involved in these signaling pathways to investigate the mechanisms responsible for these improvements.
The Bdnf, Irs1, Pik3ca, Atf4, and Bcl2 were downregulated, and the Gsk3b was upregulated in the HFS diet-induced T2D rats. The altered gene expressions may cause impairments of neurogenesis, synaptic plasticity, and memory formation in these rats. The downregulation of Bdnf, the gene that encodes the neurotrophin BDNF, directly disrupts the BDNF/TrkB binding, PI3K-Akt, Ras–MAPK, and PLCγ–Ca2+ pathways [44]. In particular, the downregulation of Irs1, the gene that encodes the insulin receptor substrate-1 (IRS-1), inhibits the signaling cascade of PI3K-Akt [45]. Other than cognitive dysfunction, the abnormal expression of IRS1 is also related to T2D and hippocampal insulin resistance [46]. Meanwhile, the downregulated Pik3ca disrupts the availability of phosphoinositide-3-kinase, which interferes with the binding and activation of protein kinase Akt. This interference leads to the deactivation of anti-apoptotic cytokines, thereby impeding the hippocampal neuron survival [45]. The Gsk3b upregulation promotes pro-apoptotic proteins, whereas the Bcl2 downregulation inhibits anti-apoptotic proteins. The alteration of the expression of these genes decreases hippocampal neuron survival (neurogenesis) [47]. The *Atf4* gene encodes cyclic AMP-responsive element-binding protein (CREB) that mediates the transcription of essential prosurvival genes and other downstream targets involved in neural plasticity. Thus, the downregulation of the Atf4 promotes neuron death, glutamatergic synaptic dysfunction, and memory deficits [48].
The EE exposure given to the HFS diet-induced T2D rats resulted in the upregulation of Bdnf, Ntrk2, Irs1, Bcl2, Atf4, Map2k1, Mapk1, Camk2g, Grin1, and Gria2, and the downregulation of Gsk3b. The Ntrk2 encodes the tyrosine kinase receptor, TrkB, a neurotrophin receptor activated by BDNF. Thus, the upregulations of Bdnf and Ntrk2 improve the binding of BDNF/TrkB and its downstream signaling [43]. Next, the upregulation of Irs1 promotes the activation of the PI3K-Akt signaling cascade. This finding also suggested that EE exposure may ameliorate insulin resistance in the hippocampus. The EE exposure also resulted in the downregulation of Gsk3b and the upregulation of Bcl2. These alterations inhibit the pro-apoptotic proteins and promote anti-apoptotic proteins, which enhance hippocampal neuron survival. The Map2k1 encodes the dual specificity mitogen-activated protein kinase kinase 1, and the Mapk1 encodes the mitogen-activated protein kinase 1. Both kinases are essential components of the Ras–MAPK pathway. Therefore, the upregulations of Map2k1 and Mapk1 indicate that EE exposure promotes hippocampal neuron survival. The Camk2g encodes the calcium/calmodulin-dependent protein kinase type II subunit gamma, one of the components of the PLCγ–Ca2+ pathway. Hence, the upregulation of Camk2g promotes synaptic plasticity, long-term potentiation (LTP), and memory formation. Grin1 encodes the component of NMDA glutamate receptor complexes, whereas Gria2 encodes the AMPA glutamate receptor. These two glutamate receptors mediate LTP at CA3–CA1 synapses. Therefore, the upregulations of Grin1 and Gria2 promote long-term potentiation (LTP) and memory formation.
Our study also indicated that the metformin treatment successfully enhances hippocampal neuron survival and promotes hippocampal-dependent learning and memory in the HFS diet-induced T2D rats by altering the expression of Ntrk2, Irs1, Gsk3b, Bcl2, Map2k1, and *Grin1* genes. Previous studies revealed that metformin might help inhibit neuronal cell death through the p53 signal-induced apoptosis [9,49]. However, our study revealed that metformin improves neuron survival by altering the expression of genes related to the BDNF/TrkB and its downstream signaling, including PI3K-Akt and Ras–MAPK pathways. Our study also showed that metformin promotes hippocampal-dependent memory by altering genes related to LTP (Grin1).
## 5. Conclusions
In summary, our study revealed that the overconsumption of the Western-style diet instigated T2D in rats. These rats had hyperglycemia, hyperinsulinemia, dyslipidemia, and histological alterations in pancreatic islets and adipose tissue. These rats also had high levels of systemic oxidative stress. Nevertheless, the EE had similar anti-diabetic properties to metformin by alleviating metabolic dysfunctions and histological features in the HFS diet-induced T2D rats. Like metformin, the EE also reduced the systemic oxidative stress in the HFS diet-induced T2D rats.
Chronically, hippocampal neuronal death and hippocampal-dependent memory impairment were triggered in the HFS diet-induced T2D rats. These rats had low percentages of T-maze tasks, low serum BDNF and low percentages of hippocampal neuron survival in CA1 and CA3. We also found that the expressions of hippocampal genes related to neuron survival were altered in these rats.
The highlight of this study is the investigation of the neuroprotective effects of EE and metformin in HFS-induced T2D rats with hippocampal neuron and memory impairments. The interventions of EE and metformin significantly improved hippocampal neuron survival and hippocampal-dependent memory functions in the HFS-induced T2D rats. Our findings revealed that the HFS diet-induced T2D rats either exposed to EE or treated with metformin had high percentages of T-maze tasks, high serum BDNF and high percentages of hippocampal neuron survival in CA1 and CA3. Although the underlying mechanisms of EE and metformin were not fully understood, we believed that the anti-oxidative activities of these two interventions might be responsible for both anti-diabetic and neuroprotective effects in the HFS diet-induced T2D rats. Specifically, we proposed that the underlying mechanisms of these interventions involved the expression changes of hippocampal genes related to neurogenesis and synaptic plasticity. The EE exposure improved the expressions of genes that regulate the BDNF/TrkB binding and its downstream signaling, including PI3K-Akt, Ras–MAPK, and PLCγ–Ca2+ pathways. Our study also showed that EE enhanced the expression of genes related to LTP. Meanwhile, the metformin treatment only improved the expressions of genes that regulate the BDNF/TrkB binding, PI3K-Akt, Ras–MAPK, and LTP.
In conclusion, environmental enrichment (EE) and metformin improved metabolic functions, hippocampal neuron survival, and hippocampal-dependent memory in HFS diet-induced T2D rats. The underlying neuroprotective mechanisms of these interventions involved the expression of genes that regulate the BDNF/TrkB binding, PI3K-Akt, Ras–MAPK, PLCγ–Ca2+, or LTP. The details of these mechanisms should be further verified in future studies.
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|
---
title: Development and validation of a risk prediction model for frailty in patients
with diabetes
authors:
- Fan Bu
- Xiao-hui Deng
- Na-ni Zhan
- Hongtao Cheng
- Zi-lin Wang
- Li Tang
- Yu Zhao
- Qi-yuan Lyu
journal: BMC Geriatrics
year: 2023
pmcid: PMC10045211
doi: 10.1186/s12877-023-03823-3
license: CC BY 4.0
---
# Development and validation of a risk prediction model for frailty in patients with diabetes
## Abstract
### Background
Frailty is the third most common complication of diabetes after macrovascular and microvascular complications. The aim of this study was to develop a validated risk prediction model for frailty in patients with diabetes.
### Methods
The research used data from the China Health and Retirement Longitudinal Study (CHARLS), a dataset representative of the Chinese population. Twenty-five indicators, including socio-demographic variables, behavioral factors, health status, and mental health parameters, were analyzed in this study. The study cohort was randomly divided into a training set and a validation set at a ratio of 70 to $30\%$. LASSO regression analysis was used to screen the variables for the best predictors of the model based on a 10-fold cross-validation. The logistic regression model was applied to explore the associated factors of frailty in patients with diabetes. A nomogram was constructed to develop the prediction model. Calibration curves were applied to evaluate the accuracy of the nomogram model. The area under the receiver operating characteristic curve and decision curve analysis were conducted to assess predictive performance.
### Results
One thousand four hundred thirty-six patients with diabetes from the CHARLS database collected in 2013 ($$n = 793$$) and 2015 ($$n = 643$$) were included in the final analysis. A total of 145 ($10.9\%$) had frailty symptoms. Multivariate logistic regression analysis showed that marital status, activities of daily living, waist circumference, cognitive function, grip strength, social activity, and depression as predictors of frailty in people with diabetes. These factors were used to construct the nomogram model, which showed good concordance and accuracy. The AUC values of the predictive model and the internal validation set were 0.912 ($95\%$CI 0.887–0.937) and 0.881 ($95\%$ CI 0.829–0.934). Hosmer–Lemeshow test values were $$P \leq 0.824$$ and $$P \leq 0.608$$ (both > 0.05). Calibration curves showed significant agreement between the nomogram model and actual observations. ROC and DCA indicated that the nomogram had a good predictive performance.
### Conclusions
Comprehensive nomogram constructed in this study was a promising and convenient tool to evaluate the risk of frailty in patients with diabetes, and contributed clinicians to screening the high-risk population.
### Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-023-03823-3.
## Background
There are more than 140 million people with diabetes in China, which is the highest in the world. The number is expected to reach 174 million by 2045 [1]. Frailty has become the third major complication of diabetes after macrovascular and microvascular complications [2], and it is an independent risk factor for death and disability in people with diabetes [3, 4]. Frailty, defined as loss of fitness associated with age and disease, is a fragile state with poor homeostasis resolution after stress and a consequence of the decline of multiple physiological systems [5].
The prevalence of frailty in people with diabetes is up to $48\%$, and the probability of developing frailty is three to five times higher than that in people without diabetes [6]. Frailty not only increases the risk of adverse events, such as fractures, falls, disability, and hospitalization in people with diabetes [7, 8], but also increases medical and health expenditure [9]. Additionally, diabetics with frailty due to diabetes have a higher mortality rate than those without frailty [10]. An increase in frailty score by one unit results in a $93\%$ increased risk of long-term mortality in patients with diabetes, and people with both diabetes and frailty have a 2.62 times higher risk of complication than non-frail diabetic patients [4].
The development of frailty in patients with diabetes is a consequence of the combined effects of multiple factors. A previous study indicated that gender, age, and socioeconomic status are all independently associated with the development of frailty [7]. Another study further revealed that hyperglycemia, hypoglycemia, low hemoglobin A1c (HbA1c), insulin resistance, cardiovascular disease, low physical activity, and malnutrition increase the risk of frailty among patients with diabetes [11]. Yakabe and Ogawa found that chronic conditions, such as visual impairment, diabetic complications, comorbidities, and depression, may also contribute to frailty in patients with diabetes [12].
The development of frailty is dynamic and reversible [13]. Early screening for the high-risk population is important for early intervention to delay the onset and progression of frailty. Risk prediction models are a tool that can be used to assess the risk of frailty occurring among patients with diabetes. Most previous studies have focused on investigating the status of frailty and its influencing factors, while few have attempted to develop risk prediction models to screen subjects at high risk of frailty. For example, Dong and associates [14] developed and validated a frailty prediction model in community-living older adults. The study indicated that age, marital status, physical exercise, baseline frailty state, and diabetes were independently associated with frailty. Li and colleagues [15] constructed a dynamic simulation model to predict frailty and concluded that older age, working in a professional or technical role before 60 years old, poor economic status, and poor oral hygiene were independent risk factors for frailty.
Nevertheless, the present models were based only on healthy populations, and no predictive model for frailty in patients with diabetes has been reported. This study aimed to identify factors associated with frailty and incorporate them into a nomogram constructed based on a model for predicting frailty in patients with diabetes.
## Study design
We used data from the China Health and Retirement Longitudinal Study (CHARLS), which was publicly available at http://charls.pku.edu.cn. The project was approved by the Biomedical Ethics Committee of Peking University (Beijing, China). The data is of high quality and has the nature of a large sample, thus providing real and effective data support for the analysis of this paper. Data from CHARLS 2013 and 2015 were selected for analysis in this study. After excluding participants with missing data, one thousand four hundred thirty-six patients were included in the analyses. Our research has been performed in accordance with the Declaration of Helsinki. The original CHARLS was approved by the Ethical Review Committee of Peking University (IRB00001052–11,015), and all participants signed the informed consent at the time of participation.
## Frailty
The definition of frailty was originally proposed by Fried et al. [ 16] and includes unintentional weight loss, self-reported exhaustion, weakness, slow walking speed, and low physical activity. Based on the above criteria, and combined with the information available from the CHARLS database and previous research, modified criteria have emerged and the previous study has justified that the criteria are equally valid for frailty [17]. This study refers to the diagnostic criteria of frailty from the previous study.
It includes exhaustion, weakness, low physical activity, weight loss, and slowness. In this study, frailty was treated as a binary outcome indicator and the specific assessment is as follows:1. Weakness was measured using the self-reported item “having difficulty in lifting or carrying weights over 5 kg” [18].2. Slowness was considered present if a participant had difficulty walking 100 m or climbing several flights of stairs without resting, which was similar to that used in previous studies [18].3. Exhaustion was present if the participant answered “Most or all of the time” or “Occasionally or a moderate amount of the time”, in response to either of the Chinese version of the Center for Epidemiologic Studies-Depression scale (CES-D) questions: “I felt everything I did was an effort during last week” or “I could not get going during last week.” This variable was constructed identically to the originally proposed by Fried et al. [ 16].4. Low physical activity was considered to be present if the participants did not undertake physical activity or walk at least 10 min at a time during a usual week. This variable is different from that proposed by Fried et al. [ 16], but a similar study has previously used this variable to determine frailty [19].5. Weight loss was defined as unintentional loss of 5 or more kg in the last year or current body mass index (BMI) ≤ 18.5 kg/m2 [17]. It has been proved that weight loss was a better indicator of frailty than body mass index and energy intake [20].
Frailty was defined as the presence of three or more of the above five components.
## Socio-demographic factors
Socio-demographic factors included age, gender, education level, marital status, permanent address, insurance, and financial support. Gender was defined as either male or female. Education level was categorized as “less than lower secondary”, “upper secondary or vocational training”, or “tertiary”. Marital status was defined as married if the participant was currently married and living with a spouse, and unmarried if the participant was currently separated, divorced from a spouse, widowed, or never married. The permanent address was defined either as urban or rural. Insurance and financial support were classified as either “Yes” or “No.”
## Behavioral factors
Behavioral factors included the history of alcohol consumption, smoking, the number of cigarettes smoked each day, social activities, poor sleep quality, and nighttime sleep duration. History of alcohol consumption, smoking, and social activities was classified as either “Yes” or “No”. Poor sleep quality was assessed according to the response “my sleep was restless”, and divided into four groups according to the amount of time this statement was true during a week. Total nighttime sleep duration data was obtained from the question ‘‘During the past month, how many hours of actual sleep did you get at night (average hours for one night)?’’.
## Health status
According to previous research and our professional knowledge [21–25], the factors selected as potentially predictive for frailty were a history of chronic disease (hypertension, dyslipidemia, cancer, heart disease, chronic lung disease, stroke, mental disease, arthritis or rheumatism, liver disease, kidney disease, digestive disease, or asthma), waist circumference, grip strength, self-perceived health status, ADL score, medication, vision, hearing, pain, and cognitive function.
Chronic disease and pain were based on self-reported diagnoses and defined as “Yes” or “No”. Self-perceived health status, vision, and hearing were categorized as “good”, “fair”, and “poor”. Activities of daily living were measured using The Katz Index of Independence in Activities of Daily Living (Katz ADL) [26], and six items were included in the CHARLS questionnaire: feeding, dressing, transferring, going to the toilet, bathing, and continence; 1 point was assigned for “No, I don’t have any difficulty” and “I have difficulty but can still do it”, and 0 points were assigned for “Yes, I have difficulty and need help” and “I cannot do it”; thus, total Katz ADL score indicates the degree of dependency, with lower scores indicating a higher level of dependency.
Cognitive functions include visuospatial skills, memory, orientation and attention. Visuospatial skills were assessed by redrawing a picture of two overlapped pentagons; those who redrew the picture correctly scored one point, while those who failed scored zero points. Memory was measured as the mean score for immediate and delayed recall of ten Chinese words; one point was given for each word correctly recalled. Orientation and attention were measured by the Telephone Interview of Cognitive Status (TICS-10), which calculates a score based on answers to questions regarding the year, month, day, day of the week, season, and serial subtraction of 7 from 100 (up to five times), with one point for each correct answer, and a total score of 0–10. The sum total of the above dimensions was the total cognitive function score, and ranged from zero to 21, with higher scores representing better cognitive function [27].
## Mental health factors
Mental health factors included depression and life satisfaction. Depression was assessed in the questionnaire using the Center for Epidemiologic Studies Depression Scale (CES-D) [28], which is widely used as a measure of mental health status and has a total score for 10 items of 30 points, a score of 10 points or more are defined as depression. Life satisfaction was categorized as “good”, “fair” and “poor”.
## Statistical methods
Data from the CHARLS database for 2013 and 2015 were selected for analysis in this study. Measures are expressed as median and interquartile range, and comparisons between groups were analyzed using the rank sum test. Categorical variables are expressed as percentages, and comparisons between groups were analyzed using the χ2 test or Fisher’s exact test. Data were randomly divided into training ($$n = 1005$$) and validation ($$n = 431$$) sets, according to a ratio of 7:3 [29].
A nomogram was used to illustrate the risk of frailty in individuals with diabetes, and the least absolute shrinkage and selection operator (LASSO) regression analysis was used to develop and validate the model. First, training set data were analyzed by LASSO regression [30, 31] to select predictors of frailty in people with diabetes. Then, tenfold cross-validation was applied to confirm the appropriate tuning parameters (λ) for LASSO regression analysis and the most significant features were screened with the LASSO algorithm. Finally, the selected predictors were included in multifactor logistic regression analysis, and those with P values < 0.05 were included in the nomogram model. Maximum missing values for all variables extracted did not exceed $20\%$, and multiple imputation was used to handle missing data [32].
Discrimination, accuracy, and clinical validity were used to validate the prediction model. In this study, the area under the receiver operating characteristic (ROC) curve (AUC) was used to determine the discrimination ability of the model. Calibration curves were used to determine the degree of agreement between predicted probabilities and observed outcomes. Decision curve analysis (DCA) was used to assess clinical validity.
R software (version 4.1.0) was used for all analyses in this study. All tests were two-tailed, and $P \leq 0.05$ was considered statistically significant.
## Participant characteristics
In total 1436 people with diabetes were included in this study. The demographic and clinical characteristics of participants are listed in Table 1. There were 586 male patients ($40.8\%$), 850 female patients ($59.2\%$), and $8.3\%$ of patients were ≥ 75 years old. The internal validation cohort consisted of 431 patients, an additional file shows this in more detail (see Additional file).Table 1Baseline characteristics of the study populationVariableTotalNon-frailFrailPn = 1436n = 1291n = 145ADL score6.00 [5.00, 6.00]6.00 [6.00, 6.00]4.00 [3.00, 6.00]< 0.001Cognitive function11.00 [7.50, 13.50]11.50 [8.00, 13.50]7.00 [4.00, 11.00]< 0.001Grip strength (kg)28.65 [22.00, 36.00]29.50 [23.00, 37.00]21.50 [16.00, 26.90]< 0.001Waistline (cm)91.80 [85.00, 99.00]92.00 [85.40, 99.00]88.70 [80.00, 95.00]< 0.001Nighttime sleep duration (h)6.00 [5.00, 8.00]6.00 [5.00, 8.00]6.00 [4.00, 7.00]< 0.001Smoking per day0.00 [0.00, 0.00]0.00 [0.00, 0.00]0.00 [0.00, 0.00]0.149Medications2.00 [1.00, 3.00]2.00 [1.00, 3.00]2.00 [1.00, 3.00]< 0.001Age, years (%)< 0.001 < 55315 (21.9)297 (23.0)18 (12.4) 55–64613 (42.7)561 (43.4)52 (35.9) 65–74389 (27.1)338 (26.2)51 (35.2) ≥ 75119 (8.3)95 (7.4)24 (16.5)Gender (%)< 0.001 Male586 (40.8)553 (42.8)33(22.8) Female850 (59.2)738 (57.2)112 (77.2)Education (%)0.024 Less than lower secondary1243 (86.6)1107 (85.7)136 (93.8) Upper secondary or vocational training154 (10.7)146 (11.3)8 (5.5) Tertiary39 (2.7)38 (3.0)1 (0.7)*Marital status* (%)0.003 Married1239 (86.4)1126 (87.2)113 (77.9) Unmarried197 (13.6)165 (12.8)32 (22.1)Permanent address (%)0.036 Urban718 (50.0)658 (51.0)60 (41.4) Rural718 (50.0)633 (49.0)85 (58.6)Self-perceived health status (%)< 0.001 Good190 (13.2)183 (14.2)7 (4.8) Fair721 (50.2)680 (52.7)41 (28.3) Poor525 (36.6)428 (33.1)97 (66.9)Hypertension (%)787 (54.8)693 (53.7)94 (64.8)0.014Cancer (%)33 (2.3)31 (2.4)2(1.4)0.627Chronic lung disease (%)207 (14.4)175 (13.6)32 (22.1)0.008Heart disease (%)428 (29.8)372 (28.8)56 (38.6)0.019Stroke (%)106 (7.4)92 (7.1)14 (9.7)0.349Mental disease (%)33 (2.3)27 (2.1)6 (4.1)0.205Arthritis or rheumatism (%)607 (42.3)513 (39.7)94 (64.8) < 0.001Dyslipidemia (%)611 (42.5)549 (42.5)62 (42.8)1Liver disease (%)117 (8.1)107 (8.3)10 (6.9)0.674Kidney disease (%)182 (12.7)144 (11.2)38 (26.2)< 0.001Digestive disease (%)423 (29.5)364 (28.2)59 (40.7)0.002Asthma (%)102 (7.1)82 (6.4)20 (13.8)0.002Alcohol consumption (%)378 (26.3)359 (27.8)19 (13.1)< 0.001Smoking (%)542 (37.7)508 (39.3)34 (23.4)< 0.001Insurance (%)1367 (95.2)1232 (95.4)135 (93.1)0.3Social activities (%)826 (57.5)779 (60.3)47 (32.4)< 0.001Financial support (%)1089 (75.8)970 (75.1)119 (82.1)0.081Poor sleep quality (%)< 0.001 Rarely or none of the time679 (47.3)639 (49.5)40 (27.6) Some or a little of the time219 (15.2)193 (14.9)26 (17.9) Occasionally or a moderate amount of the time217 (15.1)191 (14.8)26 (17.9) Most or all of the time321 (22.4)268 (20.8)53 (36.6)Depression (%)1089 (75.8)970 (75.1)119 (82.1)< 0.001Life satisfaction (%) < 0.001 Good475 (33.1)439 (34.0)36 (24.8) Fair787 (54.8)715 (55.4)72 (49.7) Poor174 (12.1)137 (10.6)37 (25.5)Vision (%)0.001 Good253 (17.6)235 (18.2)18 (12.4) Fair636 (44.3)585 (45.3)51 (35.2) Poor547 (38.1)471 (36.5)76 (52.4)Hearing (%)< 0.001 Good512 (35.7)478 (37.0)34 (23.4) Fair711 (49.5)642 (49.7)69 (47.6) Poor213 (14.8)171 (13.3)42 (29.0)Pain (%)536 (37.3)438 (33.9)98 (67.6)< 0.001
## Prevalence of frailty and related variables
The prevalence of frailty was $10.1\%$ ($\frac{145}{1436}$). Several factors, including ADL, cognitive function, grip strength, and waistline differed significantly ($P \leq 0.05$) between patients with and without frailty. Of patients with diabetes, 1005 ($70\%$) and 431 ($30\%$) were randomly assigned to the training and validation sets, respectively. Comparisons between the training and validation sets are presented in the additional file, and no significant differences were detected between the two groups ($P \leq 0.05$).
## LASSO and logistic regression of patients with diabetes
In the LASSO regression model, this study has chosen non-zero coefficients as potential predictors of frailty (Fig. 1A and B). And then, we further used the ‘rms’ package in ‘R’ software to incorporate these potential factors related to frailty into the multivariate logistic regression model. Ultimately, marital status ($$P \leq 0.003$$), ADL ($P \leq 0.001$), waistline ($$P \leq 0.017$$), cognitive function ($$P \leq 0.008$$), grip strength ($P \leq 0.001$), social activity ($$P \leq 0.003$$), and depression ($P \leq 0.001$) were associated with the development of frailty in patients with diabetes (Table 2).Fig. 1Demographic and clinical feature selection using the LASSO regression model. A According to the logarithmic (lambda) sequence, a coefficient profile was generated, and non-zero coefficients were produced by the optimal lambda. B The optimal parameter (lambda) in the LASSO model was selected via tenfold cross-validation using minimum criteria. The partial likelihood deviation (binomial deviation) curve relative to log (lambda) was plotted. A virtual vertical line at the optimal value was drawn using one SE of minimum criterion (the 1-SE criterion)Table 2The prediction model with multivariate logistic regressionVariableMultivariate analysisOR ($95\%$CI)PADL score0.44(0.37–0.53)< 0.001Waist circumference0.98(0.96–1.00)0.017Cognitive function0.92(0.86–0.98)0.008Grip strength0.95(0.92–0.97)< 0.001Marital status MarriedReference Unmarried2.67(1.40–5.02)0.003Social activities Yes0.44(0.25–0.75)0.003 NoReferenceDepression Yes5.40(3.14–9.57)< 0.001 NoReference
## Predictive model development
LASSO regression analysis was used to screen the variables for the best predictors of the model based on a 10-fold cross-validation. Multivariate logistic regression was conducted to establish a predictive model. The variance inflation factor (VIF) test was performed, and VIF values for all variables were < 4. There was no covariance and the model fit was good. The prediction model was composed of variables with P values that were less than 0.05 in the multivariate logistic regression. These variables included marital status, ADL, waistline, cognitive function, grip strength, social activity, and depression as predictors. The predictive model was presented using a nomogram, which can be used to quantitatively predict the risk of frailty in patients with diabetes (Fig. 2).Fig. 2Nomogram
## Discrimination
AUC values were calculated to assess the discrimination of the predictive model by examining the occurrence of frailty in patients with diabetes in the training and validation sets. As shown in Fig. 3A and B, the predictive model yielded an AUC value of 0.912 ($95\%$ CI = 0.887–0.937), with a specificity of 0.786 and sensitivity of 0.915, in the training set, and AUC = 0.881 ($95\%$ CI = 0.829–0.934), with a specificity of 0.796 and sensitivity of 0.821, in the validation set. These data indicate that the nomogram has good discriminatory ability and predictive value, and can correctly identify frail and non-frail patients. Fig. 3A Nomogram ROC curves generated from the training dataset. B Nomogram ROC curves generated using the validation dataset
## Calibration of the predictive model
The nomogram was evaluated using a calibration plot and the Hosmer–Lemeshow goodness-of-fit test ($P \leq 0.05$ indicates that the model exhibits a very good degree of fit). The test results showed that the model had a very good fit for both the training (χ2 = 4.3518, df = 8, $$p \leq 0.8241$$) and validation (χ2 = 6.3492, df = 8, $$p \leq 0.6082$$) sets. Calibration plots for the training and validation sets, based on the multifactorial logistic regression model, are shown in Fig. 4A and B. Calibration curves for the nomogram showed high uniformity between the predicted and actual probabilities of frailty in the training (Fig. 4A) and validation (Fig. 4B) sets. Fig. 4A Calibration plot for the training dataset. B Calibration plot for the validation dataset
## Evaluation of clinical validity
The clinical validity of the model was evaluated using the DCA method, and the results are shown in Fig. 5A and B. From the decision curves, the net benefits of the predictive model for the internal validation set were significantly higher than those of the two extreme cases, indicating that the nomogram model had the superior net benefit and predictive accuracy. Fig. 5A DCA curves for the training dataset. B DCA curves for the validation dataset
## Discussion
The occurrence of frailty in patients with diabetes in the present study was $10.1\%$, which is consistent with previous reports of the prevalence of frailty, which range from $3.9\%$ to $17.1\%$ [33, 34]. Frailty is closely related to the occurrence of falls, fractures, and death [35]. Hence, the identification of individuals at high risk is important to prevent frailty and associated adverse outcomes, especially in the early stages of diabetes.
The pathogenesis of frailty is complex and associated with multiple factors.
This study revealed that marital status was a predictor of frailty in patients with diabetes. The results showed that unmarried individuals with diabetes (including those who were divorced, widowed, and never married) were more likely to develop frailty than those who were married, which is consistent with previous findings [36, 37]. Unmarried people usually live alone and lack psychological and social support in the face of stressful events, then they are more likely to experience a sense of social isolation and loneliness, which further aggravate the development of frailty [16]. Married people are more accessible to family or social support to help with their diabetes self-management, then they are often at a lower risk of frailty. Therefore, unmarried patients deserve more attention from professionals to protect them from frailty and help them to maintain a high quality of life.
Our predictive model showed that low ADL scores were also associated with frailty. Diabetics with impaired ADL were more likely to develop frailty. A previous cross-sectional study also proved the relationship between functional incapacity and frailty and further confirmed that ADL score is a predictor of frailty [34]. ADL reflects an individual’s self-care ability. Patients with impaired ADL generally also experience reduced self-care ability, which may further influence their eating habits and can result in malnutrition. Additionally, reduced physical function leads to reduced activity levels, which may result in decreased muscle strength and bone density, leaving patients susceptible to sarcopenia and osteoporosis, which can further lead to a high risk of frailty [38]. Therefore, the inclusion of ADL in the routine assessment of patients with diabetes could help healthcare providers to conduct risk stratification and to develop interventions with positive effects in reducing frailty and other adverse health outcomes.
This study also found that hand grip strength and waist circumference were independent predictors of frailty. Patients with diabetes with low maximal hand grip strength in the main hand were more likely to develop frailty. Hand grip strength usually reflects muscle force level, which reflects physical function and physiological reserve capacity to some extent [39]. A decrease in hand grip strength represents a decrease in muscle mass and density, which will lead to loss of muscle force and motor coordination, thereby accelerating the onset of frailty [40]. Additionally, an important pathophysiological feature of frailty is skeletal muscle loss [41, 42], which is an important underlying physiological mechanism that supports our findings. Similarly, we also found that a smaller waist circumference was associated with a higher risk of developing frailty. This differs from the findings of previous studies that focus on healthy populations, indicating that abdominal obesity, presenting as a large waist circumference, is a risk factor for frailty [43–46]. Diabetes mellitus is a chronic wasting disease that causes weight loss or emaciation that can result in reduced waist circumference, which predisposes to malnutrition and sarcopenia [47]. Sarcopenia and chronic malnutrition are strongly associated with the development of frailty and both increase the risk of its development [48]. Additionally, weight loss is one of the criteria for frailty. Our data suggest that early nutritional intervention and muscle exercises should be provided for those at risk of malnutrition or reduced muscle strength to reduce the risk of frailty.
Moreover, this study found that frailty is closely associated with cognitive function. The cognitive function of the frail group was significantly lower than that of the non-frail group in the present study. Lower cognitive function was associated with a higher risk of frailty. This is consistent with the results of a previous study, indicating frailty was associated with subjective cognitive decline [49]. The relationship between cognitive function and frailty could be explained by pathogenic mechanisms common to them both, such as chronic inflammation and oxidative stress [50]. The common pathogenic mechanisms allow them to interact and contribute to one another. Besides, diabetes, as an important risk factor for Alzheimer’s disease, can accelerate cognitive decline [51]. The cognitive decline will reduce patients’ self-management ability and compliance with diabetes treatment, which further aggravates the disease progression and contribute to a higher risk of frailty. Thus, the cognitive function should be taken seriously in patients with diabetes and those with cognitive decline should take cognitive training as early as possible to slow the decline of cognitive function and help to prevent frailty.
The present study also found that depression and social activity were associated with frailty in patients with diabetes, which is supported by previous studies [52]. Some studies have proved that depression and frailty have the same pathophysiologic mechanisms [53]. Additionally, depressive symptoms can adversely affect psychological conditions and aggravate the onset of frailty by reducing social activity. The prevalence of depression in patients with diabetes is as high as $15\%$, which is approximately twice as high as in non-diabetics [54]. Our study indicated that social activity is a protective factor against frailty. Patients who were socially active had a lower risk of frailty than those who never or rarely socialized. These findings are supported by previous studies, showing that social activities can reduce loneliness and social isolation, and are associated with a reduced prevalence of frailty [55, 56]. Furthermore, social activities can enable patients to acquire disease knowledge and management skills, build confidence to overcome the disease, improve self-management ability and self-efficacy, and prevent the occurrence of diabetes complications [57]. It is helpful in slowing down the process of frailty development. Hence, more experience-sharing and various forms of social activities should be organized for patients with diabetes. Healthcare professionals should pay attention to the mental health of these patients and be alert to negative emotions to prevent depression and the development of frailty.
The nomogram is a commonly used prediction model used in research in many clinical fields. Nomograms are quantitative analysis diagrams that represent the functional relationship between variables using planar coordinates connected by disjointed line segments, which can be applied to predict the probability of a clinical outcome event by adding up the scores of each predictor to obtain a total score [58]. No nomograms for predicting frailty in patients with diabetes based on population-based data have been reported previously. In this study, we found that marital status, ADL, waist circumference, cognitive function, grip strength, social activity, and depression were the main factors predicting frailty in patients with diabetes. Our predictive model, constructed based on these seven factors influencing the development of frailty, demonstrated good discrimination, calibration, and clinical validity, indicating that the prediction model is valuable for the effective identification of individuals with diabetes at high risk of developing frailty. The nomogram can specifically quantify the hazard ratio in the form of a score, the probability of a patient developing a certain outcome can be obtained by simple calculation, and it can provide personalized risk assessment for each individual, which is highly relevant and accurate. Therefore, the establishment of a predictive model for frailty in patients with diabetes is a novel achievement of this study. As an efficient and accurate assessment tool, our predictive model can assist medical practitioners in screening for individuals with diabetes at high risk of developing frailty and provides a theoretical basis and entry point for the development of early prevention and intervention measures. The predictive model demonstrated good clinical applicability and it was helpful in screening patients at high risk for frailty.
There are some limitations in the present study. First, some potential predictors, including diet habits, hypoglycemia, and some diabetes complications, were not provided in the CHARLS database. Second, the nomogram was developed based on data from China, and whether the results of this study can be extended to other regions and countries requires further verification using data from external cohorts. Third, this was a retrospective study and the patients with diabetes were not followed up, hence data from more patients who have undergone long-term follow-up should be analyzed to improve the current nomogram model.
## Conclusion
This study established and verified a nomogram model that can predict frailty in patients with diabetes. Our nomogram model, which combines marital status, ADL, waist circumference, cognitive function, grip strength, social activity, and depression, was verified internally as a useful tool for risk assessment. The developed predictive model will be valuable in screening patients with diabetes at high risk for frailty.
## Supplementary Information
Additional file 1. Comparison between variables in the training and validation datasets.
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|
---
title: The NGF R100W Mutation, Associated with Hereditary Sensory Autonomic Neuropathy
Type V, Specifically Affects the Binding Energetic Landscapes of NGF and of Its
Precursor proNGF and p75NTR
authors:
- Sonia Covaceuszach
- Doriano Lamba
journal: Biology
year: 2023
pmcid: PMC10045213
doi: 10.3390/biology12030364
license: CC BY 4.0
---
# The NGF R100W Mutation, Associated with Hereditary Sensory Autonomic Neuropathy Type V, Specifically Affects the Binding Energetic Landscapes of NGF and of Its Precursor proNGF and p75NTR
## Abstract
### Simple Summary
A point mutation in the Nerve Growth factor gene (leading to the amino acid substitution R100W), causing Hereditary Sensory and Autonomic Neuropathy type V, a condition that primarily affects the sensory nerve cells, whose principal function is to transmit information about sensations, such as pain. Indeed, NGF not only mediates the development and survival of sensory neurons by binding TrkA and p75NTR receptors, but it also plays a role in pain sensation. It is worth noting that the NGF precursor is known to be a biologically active ligand with opposite physiological functions to those of its mature counterpart, and that NGF R100W mutation has been shown to determine an unbalance in the proNGF/NGF levels. Thus, the aim of this work is to elucidate the impact of the R100W mutation on the interactions of p75NTR with the precursor and the mature NGF to unveil the molecular determinants that trigger their different physiological and pathological outcomes. Computer simulations of these complexes allowed us to portray the energetic landscapes and the conformational plasticity, gaining insights into the structural basis of the molecular mechanisms beyond the clinical manifestations of HSAN V patients.
### Abstract
Nerve Growth Factor (NGF), the prototype of the neurotrophin family, stimulates morphological differentiation and regulates neuronal gene expression by binding to TrkA and p75NTR receptors. It plays a critical role in maintaining the function and phenotype of peripheral sensory and sympathetic neurons and in mediating pain transmission and perception during adulthood. A point mutation in the NGFB gene (leading to the amino acid substitution R100W) is responsible for Hereditary Sensory and Autonomic Neuropathy type V (HSAN V), leading to a congenital pain insensitivity with no clear cognitive impairments, but with alterations in the NGF/proNGF balance. The available crystal structures of the p75NTR/NGF and 2p75NTR/proNGF complexes offer a starting point for Molecular Dynamics (MD) simulations in order to capture the impact of the R100W mutation on their binding energetic landscapes and to unveil the molecular determinants that trigger their different physiological and pathological outcomes. The present in silico studies highlight that the stability and the binding energetic fingerprints in the 2p75NTR/proNGF complex is not affected by R100W mutation, which on the contrary, deeply affects the energetic landscape, and thus the stability in the p75NTR/NGF complex. Overall, these findings present insights into the structural basis of the molecular mechanisms beyond the clinical manifestations of HSAN V patients.
## 1. Introduction
Nerve Growth Factor (NGF), the prototype of the neurotrophin family, was originally identified as a key survival factor necessary for the development and differentiation of sympathetic and sensory neurons during embryogenesis. It was eventually shown to play pleiotropic functions in several neural and non-neural populations during adulthood, including differentiation, neuronal survival, synaptogenesis, and modulating synaptic plasticity [1]. NGF exerts these activities by binding to two different classes of receptors, the specific Tropomyosin Receptor Kinase A (TrkA) and the low-affinity p75 NeuroTrophin Receptor (p75NTR) [2,3].
NGF is initially synthesised as a longer precursor, known as proNGF [4], with the pro-domain acting as an intramolecular chaperone to guarantee the proper folding of the mature part, and is then further cleaved by specific intracellular proteases [5] giving rise to the C-terminal mature part [6].
Although NGF is essential for the development of nociceptive primary neurons, it also plays a pivotal role in inflammatory hyperalgesia, modulating nociception in adulthood even in conditions with no apparent inflammatory signs. The intracellular mechanisms so far proposed for heat sensitization are direct phosphorylation and membrane trafficking of TRPV1 by TrkA. Long-lasting sensitizing effects are mediated both by changed expression of neuropeptides and ion channels (Na channels, ASIC, and TRPV1) in primary afferents and by spinal NMDA receptors [7]. Moreover, it has been shown that mechano-hypersensitivity from peripheral NGF involves the sphingomyelin signalling cascade activated via p75NTR, and that a peripheral aPKC is essential for this sensitization [8]. p75NTR contributes to cancer-induced bone pain by upregulating mTOR signalling [9], modulates small fiber degeneration in diabetic neuropathic pain [10], and promotes rheumatoid arthritis and inflammatory response by activating the proinflammatory cytokines [11].
The physiological relevance of the NGF system for pain mediation and modulation [12] is supported by significant genetic evidence in humans. To this respect, Hereditary Sensory and Autonomic Neuropathy type V (HSAN V) is an autosomal recessive genetic disorder associated with a point mutation in exon 3 of the NGFB gene, leading to the substitution C661T, i.e., a basic arginine (CGG), into an aromatic tryptophan (TGG) at the position corresponding to residue 100 in mature NGF (R100W) [13]. This mutation leads to a severe reduction of pain perception and is associated with a consequent propensity to multiple body lesions. It is worth noting that this genetic disorder is not associated with mental retardation or cognitive impairment [14], contrary to HSAN IV disorder, which is characterized by mutations in the gene coding for TRKA [15,16] that leads to congenital insensitivity to pain accompanied by anhidrosis and intellectual disability. The partly overlapping clinical features of HSAN IV and V are in agreement with the general finding that the NGF–TrkA signalling pathways play a crucial role not only in the development, but also in the adult function, of the nociceptive system [7].
These clinical features suggest that the dysfunction of NGF [13] results in a less severe phenotype than the dysfunction of its receptor, TrkA, does [15]. This is most likely the result of a mutated NGF that is still able to bind and activate TrkA, albeit in a defective manner [17,18], whereas HSAN IV-related mutations in TrkA lead to a more dramatic loss of function [16].
In this contest, it is worth noting that also the NGF precursor, proNGF, was shown to be secreted as a biologically active form, exerting opposite functions in nervous system physiology (such as neuronal survival and synaptic plasticity) with respect to those of the mature counterpart [19]. proNGF binds simultaneously to p75NTR and sortilin receptors; the latter one a member of Vps10p-domain receptors [20]. Interestingly, proNGF, unlike NGF, is unable to support physiological pain sensitization [17]. The NGF R100W mutation has been shown to determine an unbalance in the proNGF/NGF levels [21]. Therefore, it is likely that the increased proNGF levels in humans carrying the HSAN V mutation might trigger an endogenous analgesic, suppressing pain perception. In addition, in vitro binding studies of a panel of R100 mutants highlighted that R100 mutations preserve the interaction of NGF with TrkA, but disrupt the interaction with p75NTR [18]. Intriguingly, this effect takes place only in the context of the mature NGF, since the affinity of proNGF R100 mutants to p75NTR does not differ to that of proNGF WT.
From a structural point of view, the X-ray crystal structures of p75NTR complexes with NGF and proNGF, respectively, show a similar 3D architecture, but they surprisingly differ in their stoichiometries [22,23]. The p75NTR/NGF complex (1:2) is asymmetric with two different binding sites. The observed structural asymmetry of the complex [22] has been ascribed to the flexibility of the NGF loop II (highlighted in pink in Figure 1) [24] that disables NGF’s symmetry-related second p75NTR binding site through an allosteric conformational change.
The symmetric 2p75NTR/proNGF [22] is characterized by the presence of an extra binding site located on the mature part, while the electron density corresponding to the entire pro-domain was poorly traceable. The pro regions of proNGF are mostly disordered, and two hairpin loops II at the top of NGF dimer have undergone more conformational changes in comparison to those of the mature NGF structures, suggesting possible interactions with the pro-peptide.
It is worth nothing that this intrinsically disordered pro-peptide does not show any structural effect on p75NTR, and therefore the formation of the symmetrical complexes is mainly due to the pro-domain effect on the mature part, with the conformation of the loop II being the main difference between these complexes [23]. In this respect, Molecular Dynamics (MD) simulations allowed to examine the energetics and the structural characteristics of these two complexes, as well as of the two forms of NGF upon the removal of p75NTR [25].
We now report explicit water MD simulations of the native, as well as of the R100W mutated 2p75NTR/proNGF and p75NTR/NGF complexes, respectively, aiming to unveil the likely structural rearrangements ascribable to the R100W mutation. The results highlight the structural determinants underlying the discriminating functional impact of the HSAN V mutation on the affinity and on the stability of NGF R100W and proNGF R100W complexes with p75NTR.
## 2. Materials and Methods
The PDBePISA server (Proteins, Interfaces, Structures and Assemblies) [26] allowed us to explore the macromolecular surfaces and interfaces of the crystallographic complexes p75NTR/NGF (PDB_ID 1SG1) and 2p75NTR/proNGF (PDB_ID 3IJ2). The structural and physicochemical properties, i.e., hydrogen bonds and salt bridges, Accessible Surface Area (ASA), Buried Surface Area (BSA), and Solvation energy effect (ΔiG) were thoroughly analysed.
Coot [27] model building tools were used for processing the crystal structures of the 2p75NTR/proNGF and p75NTR/NGF complexes and to mutate the R residue to W at position 100 in both protomers of hNGF 1SG1 (PDB ID 1SG1 chain A: aa 11–115; chain B: aa 9–116) and mouse proNGF (PDB ID 3IJ2 chain A and B: aa 8–117). The missing residues of hNGF, i.e., loop III (aa 61–66), in the crystallographic structure PDB ID 1SG1 were modelled as previously reported [28].
In either of the crystal structures of the 2p75NTR/proNGF and p75NTR/NGF complexes, the residues R100 are localized at the surface in both the NGF or proNGF protomers, and they are exposed. In the p75NTR/NGF structure (PDB ID 1SG1), the ASA values for the R100 residues in the NGF A and B protomers are of 65.4 Å2 and 35.8 Å2, respectively.
In the 2p75NTR/proNGF structure (PDB ID 3IJ2), the ASA values for the R100 residues in the proNGF A and B protomers are 73.13Å2 and 73.16 Å2, respectively. Therefore, the R100W mutation did not cause any steric hindrance.
Prior to molecular dynamics simulations, the mutated structures of the complexes were energy minimized.
We further evaluate and discuss the effects of this mutation on the unbound proteins (see below).
MD simulations were performed on the four complexes each solvated in a water box using the GROMACS 4.5 (Groningen Machine for Chemical Simulation) package [29] in conjunction with the Amber99SB force field. The simple point charge model was used to represent the water molecules. The protonation state of the ionizable groups of both the p75NTR and proNGF/NGF proteins was chosen according to a pH of 7.0, and an appropriate number of counter ions were added to achieve charge neutrality in the system. After energy minimization by using a steepest descent algorithm, during the equilibration dynamic period, the system was thermostated to a temperature of 300 K and maintained at a pressure of 1 bar. Starting with these equilibrated structures, MD production runs of 100 ns in duration were performed. All the simulations were performed at 1 atm and 300 K by coupling them to an external heat and an isotropic pressure bath. The impact on the main structural features of the complexes after the emergence of the R100W mutation were analysed by calculating: [1] the root-mean-square deviations (RMSD), [2] the radii of gyration (Rg), and [3] the distance between the p75NTR—proNGF/NGF centres of mass (COMs) by using GROMACS “gmx rmsd”, “gmx gyrate”, and “gmx distance” tools, respectively.
The GROMACS “gmx rmsf” command line tool allowed us to estimate the individual backbone root-mean-square fluctuation (RMSF) of each protein. The Solvent Accessible Surface Area (SASA) using the GROMACS “gmx sasa” script allowed us to estimate the global stability of the protein–protein complexes. The number of hydrogen bonds and pairs within 0.35 nm were analysed by the GROMACS “gmx hbond” tool.
A descriptive statistical analysis, as implemented in Microsoft Office Excel 10 (Microsoft Corporation, Redmond, WA, USA), was employed to calculate the mean of the obtained values of the analysed parameters as a measure of central tendency, and the standard deviations of the former values were computed as a measure of dispersion. The same software was used to produce all the graphs.
## 3.1. Impact on the Main Structural Features of the p75NTR/NGF and 2p75NTR/proNGF Complexes after the Emergence of the R100W Mutation
In order to disclose the impact of the R100W pathological mutation on the stability and dynamical behaviour of the complexes of NGF and proNGF with p75NTR, all the p75NTR complexes with WT and mutant NGF or proNGF were used in the 100 ns all-atom MD simulation runs.
At first, the effects of the HSAN V mutation were evaluated by a series of 100 ns all-atom MD simulation runs of the unbound states of NGF and proNGF, both WT and R100W. As shown in Figures S1 and S2, by comparing the root-mean-square fluctuations of the two protomers of each molecule, the R100W mutation does not introduce steric hindrance and does not affect the structural features of the neighbouring residues.
The stability of the complexes was explored in terms of the RMSD over the simulation frame. Typically, RMSD is used as a standard measurement for the structural distances between coordinates in order to infer the extent of deviation for a group of atoms relative to their reference structures [30]. The RMSD values display how much the conformations of these groups of atoms change during the simulation, providing a good indication of complex stability [31]. Thus, we calculated the RMSD plots both for the two complexes and the individual subunits.
By comparing the RMSD profiles of the p75NTR/NGF complex (Figure 2a), the R100W mutation induces huge variations in the RMSD values during the 100 ns MD simulation that resulted in an increased mean value (RMSD = 3.69 ± 0.63 Å) compared to that of the complex with the WT protein (RMSD = 2.81 ± 0.47 Å), as reported in Table 1. The same behaviour is shown by both the NGF (Figure S3a) and p75NTR (Figure S4a). In details, the mean value for the NGF increases from 1.77 ± 0.19 Å for the WT protein to 2.52 ± 0.19 Å for the R100W mutant and, in accordance, the mean value of p75NTR in the complex with NGF WT is 3.77 ± 0.46 Å, while the corresponding value for p75NTR in the complex with NGF R100W is 4.68 ± 0.64 Å (Table 1).
These findings point to a decreased stability of the asymmetric p75NTR/NGF WT complex as a consequence of the R100W mutation. On the contrary, the RMSD profiles of the symmetric 2p75NTR/proNGF WT complex (Figure 2b) do not show significant differences, with RMSD variations that are more similar to the ones observed for the asymmetric p75NTR/NGF WT complex, with them being 3.34 ± 0.42 Å and 3.43 ± 0.40 Å for the p75NTR complexes with proNGF WT and proNGF R100W, respectively (see Table 2). In accordance, the subunits do not show variations also, with the mean values for proNGF WT and R100W being 1.79 ± 0.24 Å and 1.81 ± 0.18 Å, respectively (Figure S3b). Regarding the two subunits of p75NTR, while the mean values of the chains X of the complex with proNGF WT and R100W are very similar, i.e., 3.77 ± 0.46 Å and 3.76 ± 0.42 Å, respectively (Figure S4b), the value of chain Y of the complex with the mutants slightly decreases respect to that of the complex with the WT, with them being 3.53 ± 0.36 Å and 3.78 ± 0.37 Å for p75NTR_Y in the complexes with proNGF R100W and WT, respectively (Figure S4c).
Therefore, the R100W mutation deeply affects the p75NTR/NGF complex, whereas it does not have an impact on the stability of the 2p75NTR/proNGF complex.
These findings are further confirmed by the resulting Rg values and the COM-COM distances of the complexes of NGF and proNGF with p75NTR throughout the duration of the simulation.
Generally, low Rg values imply sustained stability and compactness of the investigated complexes during the MD simulation. This parameter is defined as the mass-weighted RMSD for a group of atoms relative to their common mass centre. Thus, the structure stability within a valid MD simulation is correlated to Rg tones, reaching a plateau around the average values [32].
In the presented study, the *Rg analysis* appears to ensure the preferential stability of the p75NTR/NGF WT complex that was previously investigated by the RMSD trajectory analysis.
In detail, the profile of the Rg of the p75NTR/NGFR100W complex is characterized by an increasing trend with consistent variations and a mean value of 26.63 ± 0.22 Å. The mean Rg value of the p75NTR/NGF WT complex is significantly lower (i.e., 26.16 ± 0.13 Å) and slightly differs from the value at the start of the simulation (Figure 3a). Conversely, the 2p75NTR/proNGF WT and 2p75NTR/proNGF R100W complexes (Figure 3b) show a similar trend in their Rg profiles that oscillate around very close mean values of 30.13 ± 0.21 Å and 30.00 ± 0.18 Å, respectively.
A similar opposite behaviour can be observed comparing the COM-COM distances of the WT and R100W mutants in the p75NTR/NGF and 2p75NTR/proNGF complexes (Figure 4).
Indeed, the COM-COM distances of the p75NTR/NGF WT complex became smaller during the simulation, with small variations and a mean value of 18.38 ± 0.75 Å, which is significantly lower than the mean COM-COM distances of the complex between p75NTR and NGF R100W (i.e., 20.16 ± 0.58 Å), whose profile shows remarkable oscillations (Figure 4a). Instead, the COM-COM distances in the p75NTR/proNGF complexes show similar behaviours for the WT and the R100W mutant, with there being mean values of 18.78 ± 0.83 Å and 18.55 ± 0.56 Å between the chain X of p75NTR and proNGF WT and R100W, respectively, and 18.59 ± 0.52 Å and 19.16 ± 0.50 Å between the chain Y of p75NTR and proNGF WT and R100W, respectively. It is also interesting to note that the fluctuations shown in the COM-COM distances between proNGF WT and both chains of p75NTR (Figure 4b,c) seem to be slightly more pronounced compared to those of the proNGF R100W complexes.
All of these analyses support the hypothesis of a differential impact of the R100W mutation on the stability of p75NTR/NGF and p75NTR/proNGF complexes, resulting in the destabilization of the p75NTR/NGF interaction, while proNGF binding to p75NTR seems to be affected to only a small extent.
## 3.2. Variations in Conformational Flexibility and Their Effect on the Interface Surfaces of the p75NTR/NGF and 2p75NTR/proNGF Complexes after the Emergence of the R100W Mutation
In order to gain a deeper insight into the stability of the complexes after the emergence of the R100W mutation, the RMSF was estimated for each complex throughout the whole MD simulation. RMSF estimates the time evolution of the average deviation for each residue from its reference position within the minimized starting structures [33]. Adopting an ∆RMSF cut-off value of 0.1 Å was relevant in order to estimate the significant change within the structural movements, where residues with >0.1 ∆RMSF values are considered to show significant variations in their mobility [34,35].
When we were analysing the RMSF of each chain of the two complexes (Figure 5), it is worth noting that the flexible regions of the two protomers composing NGF were quite different (Figure 5a,c), while in proNGF (Figure 5b,d) and p75NTR (Figure 5f,g) the RMSF profiles were quite similar.
The highly flexible regions in both the proNGF WT and NGF WT complexes with p75NTR are mainly mapped at the level of the four loops and at the amino and carboxy termini. Loop V of the chain B of NGF in the p75NTR/NGF WT complex shows an increased RMSF with respect to that of chain A, as well as with respect to those of both the proNGF chains in the 2p75NTR/proNGF WT complex. Loop II is less flexible in the chain A of the p75NTR/NGF WT complex with respect to that of chain B, characterized by a higher RMSF, and those of both the proNGF chains in the 2p75NTR/proNGF WT complex, confirming its role in the different binding modes of NGF and proNGF to p75NTR.
The R100W mutation induces an overall increased RMSF along both chains of NGF in the p75NTR/NGF R100W complex, with the only exception being loop II. A similar behaviour characterized the two protomers of proNGF in the 2p75NTR-proNGF R100W complex. A stabilization effect by the R100W mutation can be highlighted in some portions of loop I and loop II in the 2p75NTR-proNGF R100W complex.
A related effect can also be seen in the RMSF profile of p75NTR in the complex with NGF, with only two small patches that seem to be stabilized by the R100W mutation, i.e., residues 6–12 and 27–33 (Figure 5e). A quite different behaviour is observed for the two chains of p75NTR in the 2p75NTR/proNGF complex (Figure 5f,g). Overall, the RMSF in the complex with proNGF WT and R100W are closer along both p75NTR chains and in several regions the mutation seems to stabilize the complex decreasing the RMSF of p75NTR residues. Regarding the NGF, all the contact residues of the two protomers, except for a couple of amino acids (aa) at the end of loop II of chain B, show a significantly higher RMSF after the emergence of the R100W mutation. On the contrary, the RMSD values of both protomers of proNGF do not dramatically change after the emergence of the mutation, and in addition, a stabilizing effect nearby the mutation can be seen in loop V of both the proNGF protomers.
Moreover, focusing on the residues that are involved in the contact interfaces according to [26], and thus responsible for the stability of the complexes (highlighted by violet dots in Figure 5), it can be noted that the RMSF for all the contact residues of p75NTR with NGF show an increase after the emergence of the R100W mutation. Instead, the RMSFs of both the p75NTR chains are very similar to those of the WT and the R100W in the 2p75NTR/proNGF complexes, with some contact regions that are stabilized as result of the mutation.
To investigate this opposite behaviour, we took into account the variation in the RMSF values of the contact residues after the emergence of the R100W mutation (Supplementary Tables S1–S4). We focused on the residues involved in hydrogen bonds and salt bridges formation and on those that are the major determinant of the formation of the two complexes on the basis of the related ∆iG.
Overall, the R100W mutation caused a significant increase in the RMSF of the majority of NGF and p75NTR contact residues (Tables S1 and S2), namely 25 aa, with higher RMSF on a total of 25 aa for both NGF protomers and 37 aa out of 43 aa for p75NTR, respectively. In detail, in the p75NTR/NGF complex R100W mutation caused increased fluctuations in five out of the seven residues involved in hydrogen bonds and salt bridges (Table S1); only W21 and Y52 show a slight decrease in the RMSF, even if none of them contribute significantly to the ∆iG (being 0.89 kcal/mol and 0.54 kcal/mol, respectively). From a thermodynamic point of view, the 14 residues (with only one exception) that mainly contribute to the binding energy with negative values of ∆iG are all characterized by a significant increase in their RMSF values after the emergence of the R100W mutation. In accordance, the RMSF values of all 12 contacting residues of p75NTR involved in hydrogen bonds and salt bridges (Table S2) increase because of the R100W mutation, and all the 16 residues carrying negative ∆iG show larger fluctuation after the emergence of the mutation. Regarding the impact on the total binding energy (being −3.77 kcal/mol and −2.45 kcal/mol for the NGF protomers and p75NTR, respectively), residues with higher fluctuations after the emergence of R100W account for −3.71 kcal/mol and −2.37 kcal/mol for the NGF and p75NTR, respectively, making the contribution negligible to the binding energy by the few residues, with a reduced RMSF for both the binding partners (i.e., −0.06 kcal/mol and −0.08 kcal/mol for NGF and p75NTR, respectively). All these considerations are in agreement, pointing to a destabilizing effect of this interaction due to the R100W mutation.
As the global effect of the R100W mutation on the 2p75NTR/proNGF complex (Supplementary Tables S3 and S4) is of concern, a significant decrease was observed in the RMSF values of the key residues involved in stabilizing non-covalent interactions and that are mainly responsible of the strength of the interaction. In particular, lower RMSF values are associated with the R100W mutation in 10 of the 14 residues involved in hydrogen bonds and salt bridges of the two chains of p75NTR, while on the side of the two proNGF protomers, only 3 residues out of a total of 13 show a significant increase in the RMSF values. As a result, 21 residues on 34 p75NTR that contribute to the overall binding energy are characterized by a reduction of their RMSF values, while 12 residues on 25 of the proNGF protomers show higher fluctuations. Regarding the contribution on the total binding energy (being −7.50 kcal/mol and −4.77 kcal/mol for proNGF protomers and the two chain of p75NTR, respectively), those residues with decreased RMSFs after the emergence of the R100W mutation account for −3.96 kcal/mol and −3.11 kcal/mol for the NGF and the two chains of p75NTR, respectively. Therefore, the residues showing increased fluctuations influence only for $47.2\%$ and $34.8\%$ of the total ∆iG for proNGF and for the two chains of p75NTR, respectively, with a possible compensatory effect of the contact residues with decreased RMSFs. Indeed, they account for the majority of the binding energy contributors in both the binding partners. These data strongly suggest that HSAN V mutation has an opposite impact on the 2p75NTR/proNGF complex with respect to that on the p75NTR/NGF complex, increasing the strength of the former one, while promoting the destabilization of the latter one.
## 3.3. Global Stability Analysis of the Interacting Surfaces
Solvent Accessible Surface Area (SASA) estimates the molecular surface area accessible to solvent molecules, providing a quantitative measurement of the extent of the protein/solvent interactions [36]. Decreased SASA tones generally imply relative molecular surface shrinkage of the protein–protein complexes by altering the solvent exposed surface charges, yielding, in turn, more compact and stable conformations.
Aiming to investigate the impact of R100W mutation on the p75NTR/NGF complex, the total SASA trajectories of the two complexes were monitored (Figure 6a).
The p75NTR/NGF WT complex showed significantly lower SASA trajectories (i.e., 2280.23 ± 159.15 Å2) with respect to those of the p75NTR/NGF R100W complex (i.e., 2657.02 ± 177.08 Å2), suggesting a reduction of the intermolecular interaction surface due to the R100W mutation, which is quite a stable effect, taking into account the small fluctuations in the total SASA profile of both complexes (Figure 6a). Analogously, the R100W mutation causes an increase in the hydrophobic SASA from 1086.15 ± 122.35 Å2 to 1253.44 ± 106.87 Å2 (Figure 7a), as well as of the hydrophilic SASA from 1194.16 ± 109.44 Å2 to 1403.65 ± 97.10 Å2 (Figure 8a).
Even if the fluctuation in both the hydrophobic and hydrophilic SASA values are larger than those observed for the respective total SASA, this finding confirms the destabilizing effect of the R100W mutation on the p75NTR/NGF complex.
Conversely, the total SASA tones of both the 2p75NTR-proNGF WT and R100W complexes were comparable with a slight decrease in the SASA values for the 2p75NTR-proNGF R100W complex. The total SASA values were 2758.12 ± 283.04 Å2 and 2542.33 ± 221.51 Å2 for proNGF WT in the complex with the two chains of p75NTR and 2842.15 ± 181.19 and 2558.79 ± 201.21 Å2 for proNGF R100W in the complex with the two chains of p75NTR (Table 2), respectively. This finding points to the similar stability of the two complexes, even if there were significant fluctuations in the SASA values during the simulation. The profiles, nevertheless, are shared by all the analysed complexes (Figure 6b). The analysis of the both hydrophobic (Figure 7b) and hydrophilic SASA (Figure 8b) agrees well with the dynamic behaviour of the total SASA (Table 2), even if the decrease in their tones after the mutation emerged is less pronounced.
## 3.4. Analysis of the Evolution of Intermolecular Hydrogen Bonding Network after the Emergnce of the HSAN V Mutation
The stability of the hydrogen bond network interactions between the engaged core protein residues were investigated during the MD simulation. The time-dependent variations in the number of the hydrogen bonds and in the interacting pairs within 3.5 Å were observed, together with their stability during the MD simulation window for calculating the corresponding percentage of time persistence (Figure 9 and Figure 10, respectively).
Regarding the p75NTR/NGF complex, the number of hydrogen bonds (Figure 9a) and of the interacting pairs within 3.5 Ă (Figure 10a) apparently did not seem to be influenced by the R100W mutation (Table 1), with the number of hydrogen bonds being 10.06 ± 3.31 and 11.13 ± 2.28 for the complexes with NGF WT and R100W, respectively. The number of interacting pairs within 3.5 Ă are 5.47 ± 2.66 and 5.78 ± 2.31 for the complexes with NGF WT and the mutant, respectively. It is worthy of note that both the trajectories are characterized by large variations, suggesting that beside the mean number of hydrogen bonds or of interacting pairs, a more significant parameter to be compared is their time persistence, expressed by calculating the percentage of time during the entire simulation. In details, the number of hydrogen bonds covers a range between $0\%$ and $20\%$ and shows a large fluctuation mainly in the first 50 ns of the simulation, especially in the case of the p75NTR-NGF R100W complex. This behavior is reflected by comparing the percentage of time persistence of the number of hydrogen bonds in the p75NTR complexes with NGF WT and R100W, respectively. The corresponding plots show Gaussian profiles with a peak maximum height that is shifted to a lower number and a lower percentage of time persistence after the emergence of the R100W mutation (i.e., 11 hydrogen bonds. lasting for a percentage around $18\%$ of time for the p75NTR/NGF WT complex, compared to 9 hydrogen bonds, lasting for a percentage around $15\%$ of time for the p75NTR/NGF R100W complex).
On the other hand, the number of the interacting pairs within 3.5 Ă also spans over a broad range (between $0\%$ and $19\%$) and shows large fluctuation during the entire simulation window. Both plots are characterized by an almost overlapping Gaussian profile that has lower peaks after the emergence of the R100W mutation, with a maximum of six interacting pairs within 3.5 Ă, lasting for a time persistence around $17\%$ for the p75NTR/NGF WT complex, compared to seven interacting pairs within 3.5 Ă, lasting for a persistence time around $14\%$ for the p75NTR/NGF R100W complex. All of these findings point to a weakened hydrogen bond interactions network induced by the HSAN V mutation in the p75NTR/NGF complex.
Concerning the symmetric 2p75NTR/proNGF complex, as observed in the case of the asymmetric p75NTR/NGF complex, the R100W mutation does not affect the number of hydrogen bonds (Figure 9b,c) and of the interacting pairs within 3.5 Ă (Figure 10b,c). Indeed, the numbers of hydrogen bonds with p75NTR chain X are 10.94 ± 2.55 and 9.05 ± 2.35 and with p75NTR chain Y 7.46 ± 2.24 and 8.23 ± 2.15 for the p75NTR complexes with proNGF WT and proNGF R100W, respectively. The numbers of interacting pairs within 3.5 Ă with p75NTR chain X are 6.68 ± 2.65 and 5.68 ± 2.27 and with p75NTR chain Y 5.18 ± 2.23 and 5.56 ± 2.07 for the complexes with proNGF WT and the proNGF mutant, respectively (Table 2).
By analyzing the corresponding trajectory of the number of hydrogen bonds for the p75NTR_X/proNGF complex, the plot is characterized by slightly reduced fluctuations compared to those of the asymmetric p75NTR/NGF WT complex. The Gaussian profiles of the corresponding plots of the percentage of persistence time have a peak height maximum that is shifted towards a lower number of hydrogen bonds, but show a higher percentage of time persistence as result of the R100W mutation (i.e., 11 hydrogen bonds, lasting for a persistence time around $16\%$ for the p75NTR_X complex/proNGF WT, compared to 8 hydrogen bonds, lasting for a persistence time of around $20\%$ for the p75NTR/proNGF R100W complex). In the case of p75NTR_Y/proNGF WT complex, the fluctuations are even more reduced, while for the complex with the mutant, an increase in the number of hydrogen bonds can be observed in the last 20 ns of the simulation. The corresponding plots of the percentage of time are characterized by a symmetric Gaussian profile for the p75NTR_Y/proNGF WT complex with a maximum of eight hydrogen bonds, lasting for a persistence time of around $17\%$ as in the case of the p75NTR_Y complex/proNGF R100W. The profile of the latter one is broader and asymmetric, spanning to the range of 9–11 hydrogen bonds and lasting for a persistence time between 17 and $12\%$.
Concerning the trajectories of the interacting pairs within 0.35 nm, the plots of the complexes with p75NTR_X show a similar range of fluctuations to those of the asymmetric p75NTR/NGF complex. Both the plots display a broad and an almost overlapping Gaussian profile, which peak height increases after the emergence of the R100W mutation, with a shared maximum of five pairs within 3.5 Ă, lasting for a higher percentage of persistence time for the p75NTR_X/proNGF R100W complex with respect to that of p75NTR_X/proNGF WT (26 and $15\%$, respectively). Instead, the trajectories of the complexes with p75NTR_Y exhibit a narrower range of fluctuations compared to those of the p75NTR/NGF complex. The Gaussian profiles of the percentage of persistence time display a peak height maximum that is shifted to a higher number and to a higher percentage of persistence time after the emergence of the R100W mutation (i.e., six pairs within 3.5 nm, lasting for a persistence time around $19\%$ for the p75NTR_Y/proNGF R100W complex, compared to five pairs within 3.5 Ă, lasting for a persistence time around $18\%$ for the p75NTR_Y/proNGF WT complex). Thus, these observations suggest that the HSAN V mutation not only does not negatively affect the hydrogen bond interaction network in the symmetric 2p75NTR/proNGF complex, but it might, on the contrary, strengthen the non-covalent interactions that mediate the formation of this complex.
## 3.5. Dynamics Analysis of the p75NTR/NGF and 2p75NTR/proNGF Complexes after the Emergence of the R100W Mutation
We finally compared the 10 most populated poses of each simulation, obtained by GROMACS “cluster.com” command line tool, to gain information on the relevant collective motions characterizing the asymmetric p75NTR/NGF and symmetric 2p75NTR/proNGF complexes after the emergence of the R100W mutation. As shown in Figure 11, the motions of both NGF and p75NTR increase after the emergence of the R100W mutation, not only at the level of the interaction surface comprising position 100, as expected (Figure 11, lower panel), but also at the level of the second main contact surface that involves the domain at the C-terminal of the extracellular domain of p75NTR.
This unexpected dynamic behavior suggests that R100W mutation is also able to destabilize the asymmetric p75NTR/NGF complex by long range cooperative effects that significantly contribute to disrupt this interaction.
On the contrary, the dynamics analysis of the symmetric 2p75NTR/proNGF complex (Figure 12 and Figure 13) show that, even if the overall motions of both proNGF and p75NTR slightly increase after the emergence of the R100W mutation, the interaction surfaces are not affected especially in the regions involving position 100 (Figure 12 and Figure 13, lower panel).
In conclusion, the present in silico study of the NGF and proNGF complexes with p75NTR after an HSAN V mutation emerges proves that the main effect of this mutation is to lower NGF affinity toward the p75NTR receptor, not only by means of a direct destabilization of the interaction surface at the level of position 100, but also by long range cooperative effects. This it takes place only in the context of the asymmetric p75NTR/NGF complex, whereas the R100W mutation does not interfere with the stability of the interaction between p75NTR and proNGF, providing a structural basis of the molecular mechanisms beyond the clinical manifestations of HSAN V patients.
## 4. Discussion
In this paper, we used water MD simulations to gain insights into the structural determinants underlying the discriminating functional impact of the HSAN V mutation on the affinity and on the stability of NGF complex with p75NTR.
HSANs are a heterogeneous group of eight phenotypically diverse forms of inherited peripheral neuropathies, characterized by mainly sensory, but also variable motor and minimal autonomic dysfunctions [37]. Among them, HSAN V is characterized by the loss of pain perception without any mental retardation. This is the result of the substitution of C to T at nucleotide position 661 (661C > T) in exon 3 of the NGF gene located on chromosome 1p11.2-p13.2, resulting in a missense mutation of tryptophan (W) for arginine (R) at position 221 in the proNGF polypeptide corresponding to residue R100W in mature NGF [13]. At first, aiming to elucidate the functional impact of NGF and proNGF binding to TrkA and p75NTR receptors, we focused on the structural analysis of the X-ray crystal structures of the complexes that were available in the Protein Data Bank. We have previously highlighted [18] that R100 does not participate in the interacting symmetric protein–protein molecular surface with the TrkA receptor (2:2) (PDB_ID 2IFG) [38], and above all, that R100 is buried ($90\%$) in the asymmetric complex p75NTR/NGF complex and is engaged in a salt-bridge protein–protein interaction with residue D75 of p75NTR (PDB_ID 1SG1) [22], largely contributing to the binding affinity of the complex. Due to the negligible yields obtained in attempting the production of recombinant human NGF R100W in an E. coli heterologous expression system, the characterization of the in vitro receptor binding properties toward NGF receptors by Surface Plasmon Resonance (SPR) (Table 3) was performed on a panel of single mutants in position 100 (R-> K, E, Q, A, and V) [18], proving that TrkA binding affinity is unaffected, while the R100 mutations greatly reduce the interaction between NGF and p75NTR. In this work, we confirmed that this finding also applies to the NGF R100W mutant (Table 3 and Figure S2). Interestingly, the R100 mutations display only a minor impact on p75NTR binding affinity in the context of the unprocessed hproNGF R100 muteins [17].
proNGF, unlike NGF, is unable to support pain sensitization [17], and taking into account that patients suffering with HSAN V show an imbalance between the NGF and proNGF levels [21], it has been postulated that proNGF might suppress pain perception by acting as an endogenous analgesic.
The unaffected in vitro binding affinity of p75NTR to proNGF cannot be easily reconciled only on the basis of the so far available crystallographic structure of the symmetric p75NTR/NGF complex (PDB_ID 3iJ2) [23]. Indeed, the interaction surfaces of this complex almost completely recapitulate the one of the asymmetric p75NTR/NGF complex with the involvement of R100 residues in the interacting protein–protein molecular surfaces.
To clarify this apparent paradox, we pursued an in silico computational approach previously exploited by Pimenta et al., 2014 [25], which employed a series of 100 ns MD simulations to elucidate the structural features and the binding energetics of p75NTR complexes with NGF and proNGF with (1:2) and (2:2) stoichiometries, respectively. Indeed, MD simulations are widely considered to be an efficacious approach to exploit the stability of intermolecular protein–protein complexes, as well as to investigate their relative dynamic nature, providing detailed information on the energetics of binding interactions and the impact of mutations on protein–protein interactions [39]. Therefore, we first reproduced the previous results [25] to validate our system. Then, we produced MD simulations for the same complexes in which the R100W mutation has been included. The comparative analysis of the resulting trajectories highlighted the postulated differential impact of the HSAN V mutation on the asymmetric p75NTR/NGF and symmetric 2p75NTR/proNGF in terms of (i) the behaviour of all the structural parameters (RMSD, Rg, and COM-COM distance), (ii) the dynamics of the interacting protein–protein surfaces deciphering the interaction hydrophobic and hydrophilic fingerprints, (iii) the time-persistence of the hydrogen bond networks, and (iv) the overall energetic landscapes (∆iG). Indeed, as previously hypothesised, the R100W mutation deeply destabilises p75NTR/NGF (1:2) asymmetric complex, whose RMSD, Rg, and COM-COM distances increase, but most importantly, the hydrogen bond network is disrupted, and as a consequence, the interacting molecular protein–protein surface is significantly shrunken, and the binding energy highly reduced. Surprisingly, instead, proNGF interaction with p75NTR in the (2:2) symmetric complex with the R100W mutation positively improve the binding affinity.
## 5. Conclusions
In conclusion, all of the outcomes of the present MD simulation are in agreement, pointing to a destabilization effect of the HSAN V mutation, which specifically affect the asymmetric p75NTR/NGF (1:2) complex alone, while the symmetric 2p75NTR/proNGF (2:2) complex is strengthened, allowing us to reconcile the apparent discrepancy between the crystallographic information and the in vitro experimental SPR data. Moreover, elucidating the differential dynamics of the two complexes after the emergence of the R100W mutation allows us to gain novel insights into the differential biological outcomes observed between the mature and proforms of neurotrophins in pain transmission and perception, providing the structural basis for clarifying the molecular determinants triggering the clinical manifestations in patients affected by HSAN V.
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|
---
title: Antioxidant Characterization of Six Tomato Cultivars and Derived Products Destined
for Human Consumption
authors:
- Anna Rita Bianchi
- Ermenegilda Vitale
- Valeria Guerretti
- Giancarlo Palumbo
- Isabella Maria De Clemente
- Luca Vitale
- Carmen Arena
- Anna De Maio
journal: Antioxidants
year: 2023
pmcid: PMC10045220
doi: 10.3390/antiox12030761
license: CC BY 4.0
---
# Antioxidant Characterization of Six Tomato Cultivars and Derived Products Destined for Human Consumption
## Abstract
The consumption of fresh tomatoes and processed tomato products is widespread in the Mediterranean diet. This fruit is a valuable source of antioxidants and plays an important role in preventing oxidative stress. This study aimed to investigate the content of antioxidants and measure the total antioxidant capacity (ABTS and DPPH assays) in the peel, pulp, and seed fractions of six tomato cultivars. Finally, some bioactive compounds and total antioxidant activity were also determined in homemade tomato purees, since such homemade production is commonplace in Southern Italy. The level of antioxidants and total antioxidant capacity in each fraction were also calculated based on their actual fresh weight in the whole tomato. The overall results indicated that the peel and seeds of all analysed tomato cultivars contribute significantly to the antioxidant charge of the fruits. Consequently, consuming tomatoes without peel and seeds results in a substantial loss of compounds beneficial for human health. Our results also showed that phenolic and lycopene content, as well as antioxidant activities in all purees are higher than in fresh tomatoes. Based on this evidence, producing homemade tomato puree is a good practice, and its consumption helps prevent oxidative stress damage.
## 1. Introduction
The tomato berry is a versatile fruit that is eaten both fresh and as processed products. It is a staple ingredient of the Mediterranean diet, mainly because of its beneficial properties. It provides good levels of dietary fibre and varying amounts of all essential minerals and vitamins [1,2,3].
The nutritional content of tomato berries depends on biotic and abiotic factors. In addition, the physiological state of the plant, the moisture and salinity level of the substrate, the light quality and intensity, the ripening stage, temperature, presence of heavy metals, cultivar type, post-harvest conditions, and processing and storage conditions significantly influence the biosynthesis and concentrations of the substances present in the tomato [4].
The elevated consumption of fresh and processed tomatoes confers on this fruit the role of the primary source of antioxidant molecules (ascorbic acid, vitamin E, carotenoids, flavonoids, phenolic acids) involved in preventing a wide range of diseases [5].
The vitamin most commonly found in tomato berries is vitamin C, which benefits the immune system and promotes the absorption of iron and calcium [6,7]. In addition, tomato berries also contain: considerable amounts of vitamin K, which is necessary for proper coagulation [8]; vitamin A, which is essential for the immune system as well as cell regeneration and healthy skin [9]; vitamin E, which protects polyunsaturated membrane lipids from free radical attack and promotes enhanced humoral and cellular immune responses [10]; and finally, all the B-complex vitamins, which are essential for normal appetite, good vision, healthy skin, the nervous system, and red blood cell formation [11].
Among all the carotenoids in ripe tomatoes, lycopene is the most abundant [12] and is responsible for the red colour of this fruit. However, although tomatoes are a significant source of dietary lycopene, most of this compound contained in fresh tomatoes is present as trans isomers, whose bioavailability is very low [13].
Lycopene bioavailability depends on many factors, such as cis–trans isomerization and tomato processing [14]. For example, temperature and processing time increase the isomerization of lycopene to the cis isomer in processed tomato products. As a result, these products have higher lycopene bioavailability: thanks to the cis isomer’s shorter chain length, it is more soluble and more easily absorbed by human intestinal cells [13,15].
Tomato processing methods also increase lycopene bioavailability as they weaken the binding forces between lycopene and the tissue matrix [12,13]. Interestingly, lycopene has been widely shown to protect against a wide range of diseases, such as obesity and diabetes [16], Alzheimer’s disease [17], and several types of cancer [18].
Epidemiological evidence suggests that tomato is a potential factor in reducing serum levels of oxidative stress biomarkers. In support of lycopene’s role in preventing oxidative stress-related diseases, it has been demonstrated that daily consumption of 160 g of tomato sauce rich in lycopene produces a decrease in oxidized LDL cholesterol levels [19]. Lycopene reduces the risk of cardiovascular disease [20,21], breast cancer in postmenopausal women [22], ovarian cancer in premenopausal and postmenopausal women [23], and prostate cancer in men [24].
Lycopene seems to also play a skin protective role after exposure to UV irradiation [25], and higher serum levels of lycopene have been associated with reduced mortality in individuals with metabolic syndrome [26].
Toor and Savage [27] have compared the main antioxidants and total antioxidant activity in the peel, pulp, and seed fractions of three commercially grown New Zealand tomato cultivars. They have demonstrated that the peel of tomatoes contains significantly higher concentrations of phenols, flavonoids, lycopene, ascorbic acid, and antioxidant activity than the pulp and seeds.
It has also been reported that processed tomato products’ antioxidant capacity and antioxidant content, as well as their resulting health value, directly depend on industrial processing techniques (cold cracking, evaporation, pasteurization, etc.) [ 28,29]. To date, several studies have been conducted to examine the impact of processing techniques on the content of carotenoids and their isomerization [30], while few data are available on the content of ascorbic acid, total phenols, and tocopherols [29,31,32]. In any case, results are often conflicting because the content of bioactive compounds depends on the different processing techniques and conditions, and their processing sensitivity and stability also depend on the cultivar [5,33,34,35].
Based on what has been reported so far, the present work aimed to determine hydrophilic and lipophilic phenols, lycopene, and ascorbic acid content, and the total water-soluble and fat-soluble antioxidant capacity in six tomato landraces (Cherry tomato, “Ciliegino”; Smooth round tomato, “Pomodoro tondo liscio”; Round tomato sauce, “Pomodoro tondo da sugo”; “Datterino” tomato; “S. Marzano” tomato; and “Piccadilly” tomato). In detail, the antioxidant content and activities were determined in the peel, seed, and pulp fractions of each cultivar to assess whether removing the peel and the seeds may cause a significant loss of measured antioxidants.
The concentration of antioxidants and total antioxidant capacity level in each fraction was measured based on their actual fresh weight in the whole tomato. In addition, hydrophilic and lipophilic phenols, ascorbic acid, and lycopene concentrations and antioxidant capacities were also evaluated in homemade tomato purees.
## 2.1. Sample Preparation
Tomato fruit. Six varieties of healthy, ripe tomatoes (Cherry tomato, CT “Ciliegino”; Smooth round tomato, ST “Pomodoro tondo liscio”; Round tomato sauce, RTS “Pomodoro tondo da sugo”; “Datterino” tomato, DT; “S. Marzano” tomato, SMT; “Piccadilly” tomato, PT) were purchased from a supermarket near Naples. Each tomato’s seeds, pulp, and peel were carefully separated with a sharp knife. The peel was the outer epidermis; the seed fraction of the tomatoes consisted of the seeds and the jelly portion; the pulp consisted of the portion of the tomato that remained after the peel and seed fractions were removed. The fresh weight of the whole fruit, seeds, pulp, and peel were reported in Table 1. All fractions and whole tomatoes were stored at −20 °C until analysis.
Tomato puree. Tomato puree was obtained by pressing fresh, ripe whole tomatoes (2 kg). After washing them for 5 min with water and blanching at 85–100 °C for 3 min, each of the six tomato varieties was refined through a tomato press to obtain a traditional puree without seeds and peel. Glass jars (500 g) were filled with the tomato puree and then sealed. The filled jars were heated at 100 °C for 40 min in water and then cooled. The tomato purees were subjected to subsequent analysis after several days of storage.
## 2.2. Extraction of Water-Soluble and Fat-Soluble Antioxidants
The extraction of water-soluble and fat-soluble antioxidants from each cultivar’s peel, pulp, and seed fractions and tomato purees was conducted as described in Arena et al. [ 36], with some modifications. Hydrophilic extracts were obtained using absolute ethanol, while absolute acetone was used to extract fat-soluble antioxidants. All described procedures were performed on ice and in the dark. First, the whole samples were homogenized with a Polytron Ultra Turrax T8 (IKA-WERKE) and then 0.3 g of each homogenate was resuspended in 1.5 mL absolute ethanol. After shaking in the dark for 16–18 h, the samples were centrifuged at 8500 rpm for 30 min at 4 °C using an Eppendorf 5417 R centrifuge (Bio-Rad, rotor F 45-30-11). The first supernatant (hydrophilic extract) was transferred into new tubes; the pellet was extracted as previously described and the second supernatants were added to the first.
Finally, 1.5 mL of absolute acetone was added to the precipitates to obtain the fat-soluble extracts. The following experimental procedures are the same as described above.
## 2.3. Water-Soluble and Fat-Soluble Antioxidant Capacity
The free radical scavenging capacity of the water-soluble and fat-soluble extracts of fresh tomato fractions and purees was determined using the 2,2′ azino-bis (3-ethylbenzthiazoline-6-sulphonic acid) (ABTS•+) radical cation decolourization assay as described by Ariano et al. [ 37]. The ABTS•+ radical cation was generated by a reaction between 2.45 mM and 7 mM ABTS, in the dark, for 16 h at room temperature. The reaction mixture was diluted with ethanol to obtain an absorbance of 0.800 ± 0.050 at 734 nm and was utilized within two days. A volume of 15 µL of extracts were mixed with 1 mL of diluted ABTS•+ solution and then incubated at room temperature for 10 min. The decolouration resulting from cation reduction by antioxidants in the sample was measured at 734 nm using an LLG uniSPEC 2 UV/VIS-Spectrometer (Labware). Assays were performed with three dilutions of each extract, in duplicate. Trolox (6 hydroxy-2,5,7,8-trimethyl-chroman-2-carboxylic acid) (0–15 µM) was used to plot the standard curve. Antioxidant capacity was expressed as micromolar Trolox equivalents (TEAC) per 100 g fresh weight (FW).
Water-soluble and fat-soluble antioxidant capacity of whole fresh tomatoes and purees were also determined by DPPH assay [37]. A solution of 60 µM of DPPH• in ethanol was prepared daily in the dark. Then, 50 µL of the extract was mixed with 1.95 mL of DPPH• solution and incubated for 15 min. The decrease in absorbance at 517 nm was recorded using a spectrophotometer (uniSPEC 2 UV/VIS, Lab Logistics Group GmbH Labware, Germany). A standard curve was prepared by measuring the scavenging activities of the DPPH• solution at different concentrations of Trolox (6.25, 12.5, 18.8, and 25 µM). The results were expressed as µM Trolox/100 g fresh weight.
## 2.4. Total Phenolic Content
Total phenolic content was determined in both hydrophilic and lipophilic extracts of fresh tomato fractions and purees by the Folin-Ciocalteu assay [38]. Briefly, 0.1 mL of hydrophilic extract was mixed with 2.5 mL of 10-fold diluted Folin-Ciocalteau reagent, and the reaction was neutralized by adding 2.0 mL of $7.5\%$ (w/v) sodium carbonate (Na2CO3). After incubation for 2 h at room temperature, the absorbance of the reaction mixtures was measured at 760 nm spectrophotometrically (uniSPEC 2 UV/VIS-Spectrometer, Lab Logistics Group GmbH Labware, Meckenheim, Germany). Gallic acid was used as a standard, and the total phenolic content of the hydrophilic extracts was expressed in milligram gallic acid equivalents (mg GAE) per 100 g fresh weight (FW).
## 2.5. Lycopene
Lycopene concentration was extracted in the dark from 0.3 g of seeds, pulp, peel, and tomato purees with a mixture of 15 mL hexane:acetone:ethanol (2:1:1), as described in Periago et al. [ 39], with slight modifications. The total lycopene content was measured at 472 nm spectrophotometrically. Lycopene was used to prepare the standard curve, and the results were expressed as milligrams per 100 g fresh weight (FW).
## 2.6. Ascorbic Acid
The ascorbic acid (AsA) in the peel, pulp, and seed fractions and tomato purees of each cultivar was measured using the Ascorbic Acid Assay Kit (MAK074, Sigma-Aldrich, St. Louis, MO, USA), following the procedure reported by Costanzo et al. [ 40]. Briefly, 10 mg of sample was homogenized in 4 volumes of cold AsA buffer and then centrifuged at 13,000 rpm for 10 min at 4 °C to remove insoluble material. Next, the supernatant was mixed with AsA assay buffer to a final volume of 120 μL. The assay reaction was performed by adding the kit reagents to the samples. The ascorbic acid was determined by a coupled enzyme reaction, which developed a coloured (570 nm) product proportional to the amount of ascorbic acid in the sample. A standard calibration curve was used to quantify the ascorbic acid content, and the results were expressed as milligrams per 100 g fresh weight (FW).
## 2.7. Statistical Analysis
Statistically significant differences were assessed by one-way analysis of variance (ANOVA), followed by Holm-Sidak’s multiple comparisons test using the GraphPad Prism 8 Software. The results of total water-soluble and fat-soluble antioxidant capacities, as well as the phenolic, lycopene, and ascorbic acid contents, were reported as the mean ± standard deviation (SD), and the minimum level of acceptable significance was $p \leq 0.05.$ The different letters in the figures indicate the significant differences ($p \leq 0.001$) observed when comparing the values of each fraction belonging to one variety with those measured in the others. The tables show the p-values ($p \leq 0.05$; $p \leq 0.01$; $p \leq 0.001$) obtained by multiple comparisons between the three fractions (peel vs. seeds, peel vs. pulp, and seeds vs. pulp).
## 3.1. Antioxidant Capacity and Content in the Seeds, Pulp, and Peel Fractions of Different Cultivars
In all the cultivars, the highest levels of water-soluble and fat-soluble activities were found in the peel compared to both seeds and pulp. Moreover, the seeds showed higher values than the pulp.
In detail, regarding the peel, the highest levels of total water-soluble and fat-soluble antioxidant capacity were measured in Cherry, while the lowest were found in Smooth round tomato, Round sauce, and Piccadilly. In the seeds, the highest values of both antioxidant activities were observed in Cherry and the lowest in Piccadilly. Finally, concerning the pulp, Cherry and Datterino showed the highest water-soluble and fat-soluble activities, while the lowest levels were in Piccadilly (water-soluble antioxidant capacity), and San Marzano and Piccadilly (fat-soluble antioxidant capacity) (Figure 1a,b, respectively).
The multiple comparisons among the three fractions showed a significant difference ($p \leq 0.001$) between both water-soluble and fat-soluble antioxidant capacities measured in peel vs. seeds, peel vs. pulp, and seeds vs. pulp.
The highest content of hydrophilic and lipophilic phenols was found in the peel compared to both seeds and pulp. Moreover, within each variety, the phenolic content in the seeds was always higher than in the pulp (Figure 2a,b, respectively).
In particular, in the peel, the highest content of hydrophilic and lipophilic phenols was found in Cherry, while the lowest was found in Smooth round, Round sauce, San Marzano, and Piccadilly tomatoes. Comparing the seeds of all cultivars, the highest and lowest levels of phenols were measured in Cherry and Piccadilly, respectively. Furthermore, the highest phenolic content was determined in the Cherry pulp, while the lowest was in all other cultivars except Datterino (Figure 2a,b).
The content of hydrophilic and lipophilic phenols in the three fractions of each cultivar was always statistically different ($p \leq 0.001$).
All cultivars showed the highest lycopene concentration in the peel compared to the seeds and pulp. Lycopene levels were higher in the seeds than in the pulp of Datterino ($p \leq 0.001$), S. Marzano ($p \leq 0.05$), and Piccadilly ($p \leq 0.01$) varieties. Conversely, in the other cultivars, lycopene was more concentrated in the pulp fraction. In detail, in the seeds, the highest concentration of lycopene was found in Cherry tomato and the lowest in all the other cultivars except Datterino tomato. In the pulp, the highest content was measured in Cherry tomato and the lowest in Piccadilly. Finally, in the peel, the highest concentration of lycopene was found in Cherry tomato and the lowest in Smooth round and Piccadilly tomatoes (Figure 3).
The p-values in Table 2 indicate a significant difference between the lycopene content measured in seeds vs. pulp, seeds vs. peel, and pulp vs. peel because they are always lower than 0.05.
Finally, regardless of the cultivar, the peel showed the highest ascorbic acid content compared to the seeds and pulp fractions, while no significant differences were observed between seeds and pulp.
In the peel, the highest concentration of ascorbic acid was measured in Datterino and the lowest in Piccadilly tomatoes. In seeds and pulp, the highest content was in Cherry tomato and the lowest in Piccadilly (Figure 4).
No significant differences were observed among the three fractions of each tomato cultivar (Table 3).
## 3.2. Antioxidant Capacity and Content in Tomato Purees
The total antioxidant capacity of fresh and pureed tomatoes was determined by ABTS and DPPH assays. The total antioxidant capacity levels were consistently higher in the purees than in the fresh tomatoes with both methods. Furthermore, the measured values showed no significant differences (Table S1). Finally, total phenolic and lycopene content in tomato purees was also higher than those measured in whole fresh tomatoes of each cultivar. On the contrary, ascorbic acid concentration was always lower (Table 4).
In detail, the maximum phenolic (1.4 times) and lycopene (12.7 times) content were found in Cherry tomato, while the lowest were found in Piccadilly (1.24 times total phenolic content and 6.36 times lycopene content). The highest decrease of ascorbic acid concentration was determined in Cherry tomato (5.00 times), while the lowest (3.33 times) was determined in Piccadilly.
## 3.3. Percent Contribution of the Peel, Pulp, and Seeds Fractions to the Total Antioxidant Content in Whole Tomatoes
The results referring to 100 g FW of each tomato evidenced that antioxidant content and capacities were always higher in the peel than in the pulp and seeds. As the quantification of the peel and seeds fractions present in a whole fresh tomato was lower than the pulp (Table 1), it was necessary to determine the amount of antioxidants in each fraction based on their actual weights. Thus, the percentage contribution of the peel, pulp, and seeds fractions to the total antioxidant content in whole tomatoes was calculated, and the results were reported in Table 5.
The lowest contribution ($51\%$) of the peel and seeds fractions to total antioxidant capacity was found in Datterino tomatoes, while the highest ($63\%$) was found in S. Marzano and Piccadilly tomatoes. Conversely, the most significant contribution to the total phenolic content was observed in the Smooth round tomato ($65\%$), while the lowest ($56\%$) was found in the Cherry tomato. Furthermore, the peel and seeds provided the lowest contribution ($38\%$) to lycopene in the Smooth round tomato and Round tomato sauce, and the highest ($51\%$) in Datterino. Finally, the less consistent contribution of the peel and seed fractions to ascorbic acid was found in the Cherry tomato ($41\%$), while the highest contribution was observed in the cultivar Datterino ($47\%$).
## 4. Discussion
Fruits and vegetables are rich in bioactive compounds beneficial for human health. However, they are not always consumed entirely and they are often subjected to processing to separate the valuable product from other plant constituents [41]. It has been estimated that many vegetables and fruits produce 25–$30\%$ of inedible products [42], but the inability or impossibility to recover waste materials such as peels, seeds, and stones determines a considerable loss of antioxidants from natural sources [43].
In particular, the peel is widely reported to be richer in antioxidants than other fruit components. For instance, phenolic compounds and ascorbic acid are more concentrated in the peel than in the pulp of citrus fruits [44]. The phenolic content of the edible pulp of bananas (Musa paradisiaca) is about $25\%$ of that in the peel [45]. The peel and other residues and by-products of star fruit (*Averrhoa carambola* L.), pomegranate (Citrus paradise M., *Punica granatum* L.), banana (*Musa acuminata* Colla), and citrus are evaluated as relevant sources of antioxidants [46,47,48,49,50]. Moreover, Wolfe, Wu, and Liu [51] demonstrated that phenol concentration, antioxidant activity, and antiproliferative activity measured in apple peel are significantly higher than in the pulp. For this reason, they hypothesize that daily consumption of apple peels reduces the risk of cardiovascular disease and cancer.
In addition to the concentration of antioxidants, the antioxidant activity of many fruits (guava, kiwifruit, purple mulberry, strawberry, white pomegranate) is also higher in the peel and seed fractions than in the pulp [52].
In the past, great attention was paid to the antioxidant content in tomatoes, which represent the main component of the Mediterranean diet. Consuming fresh tomato berries or tomato puree offers significant health benefits, as they are rich in antioxidant compounds essential in preventing various diseases associated with oxidative stress [53,54,55,56].
The lycopene, phenols, flavonoids, ascorbic acid, and vitamin E in tomatoes are mainly responsible for the antioxidant capacity due to their ability to quench free radicals, which are responsible for oxidative changes in the human body [57,58,59].
Several studies have already shown that the peel and seeds are often removed in the daily consumption of tomatoes and the preparation of their derivatives, despite being a valuable source of bioactive compounds and minerals [12,27,60,61].
More recently, a study on 12 field-grown tomato genotypes reported that, on average, lycopene levels in the tomato peel are 2.5 times higher than in the pulp [62]. The same authors also noted that the tomato peel contains many phenols and ascorbic acid.
Significant differences in the antioxidant content of the seeds, pulp, and peel fractions have been measured in different Indian tomato cultivars developed at high altitudes and in the lowlands. In all the tested cultivars, the highest antioxidant levels and free radical scavenging activities were found in the peel. In detail, the highest lycopene content was found in high-altitude cultivars, and the highest ascorbic acid and phenol levels were detected in plain region cultivars [63].
Based on this knowledge, our study evaluated the effect of peel and seeds removal on ascorbic acid, phenol, and lycopene content and antioxidant capacity in tomato fruits of six typical varieties cultivated in Campania, a region in Southern Italy.
Data reported in the literature (on 100 g of analysed fractions) indicate that the peel is the tomato fruit component with the highest concentration of antioxidants, namely water-soluble and fat-soluble antioxidant capacity, phenolics, lycopene, and ascorbic acid, followed by the seeds and pulp. Furthermore, the antioxidant content measured in the seeds and peel, and calculated taking into account the tomato weights (Table 5), confirms the considerable contribution of these components to the scavenging properties of tomato fruits (i.e., antioxidant capacity from 51 to $63\%$; total phenolic content from $56\%$ to $65\%$; lycopene content from $38\%$ to $51\%$; ascorbic acid content from $41\%$ to $47\%$). Since for all studied tomato cultivars the peel represents a precious sink of bioactive compounds, it is noteworthy that peeling is the most detrimental procedure before consuming tomatoes, especially for Cherry and Datterino varieties, which are considered the healthiest cultivars.
It is well known that domestic and industrial food processing significantly affects the structural integrity of fruits and vegetables [64]. In particular, industrial processing often involves many thermal processes, which may positively or negatively impact food. More specifically, they can inactivate food-borne enzymes and pathogens, increase foodstuff’s digestibility and bioavailability, extend the shelf life of fruits, or lead to the loss of some desirable nutrients [65].
Several factors have already been demonstrated to influence the capacity and content of antioxidants during industrial tomato processing [31,66,67,68]. However, to date, no information is available on the effects of processing during the production of homemade tomato puree, a common practice in Campania (Southern Italy) in the summer, from July to September.
Therefore, we evaluated for the first time whether and to what extent the antioxidant capacity and the content of phenols, lycopene, and vitamin C could change in homemade tomato puree compared to unprocessed tomatoes. Although San *Marzano is* usually the most commonly used for homemade passata, we prepared purees with the six available tomato cultivars.
Our data show that home processing positively affects phenols and lycopene content. We hypothesize that heating glass jars filled with tomato puree at 100 °C for 40 min could have promoted the extractability and release of (bound) phenols [31] and lycopene from tissues. The heating process could have also: induced lycopene isomerization from all-trans to cis configuration, increased its bioavailability [69,70,71], and deactivated endogenous oxidative enzymes responsible for the degradation of antioxidant compounds [72].
In addition, the mechanical treatment (sieving) during tomato processing could have favoured phenolics’ bioaccessibility, extractability, and bioavailability [72].
Finally, the evidence that total antioxidant capacity is always higher in purees than in fresh tomatoes suggests that the increased phenols and lycopene phenols compensates for the significant reduction in ascorbic acid (around $70\%$) (Table S1 and Table 4), probably due to oxidation processes [73]. Furthermore, in puree, the formation of polymeric phenols, which are more potent antioxidants than their simple counterparts [66], could be a further reason to explain the increase in antioxidant activity.
## 5. Conclusions
This study focused on the antioxidant characterization of six Italian tomato cultivars and evaluated the antioxidant content of homemade puree for the first time.
The first analysis highlights that consuming fresh and unpeeled berries is preferable because removing the peel and seed fractions significantly reduces the content of antioxidants and total antioxidant activities.
The second finding concerns the antioxidant properties of tomato purees. To date, the only data available in the literature refer to industrial purees. As a novel aspect, we have proven, for the first time, that homemade tomato purees, because of their high antioxidant content which is not lost during the preparation procedure, are strongly recommended in the human diet. All cultivars, especially Cherry tomatoes, provide purees rich in antioxidant capacity, and lycopene and phenol content. Such compounds, which become more available following the heating process, represent an added value in the diet, effectively preventing oxidative stress.
As a final consideration, our study provides encouraging results that valorise local products and support the consumption and reutilization of waste products in view of the circular economy designed to benefit the environment.
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|
---
title: Inflammatory Blood Signature Related to Common Psychological Comorbidity in
Chronic Pain
authors:
- Bianka Karshikoff
- Karin Wåhlén
- Jenny Åström
- Mats Lekander
- Linda Holmström
- Rikard K. Wicksell
journal: Biomedicines
year: 2023
pmcid: PMC10045222
doi: 10.3390/biomedicines11030713
license: CC BY 4.0
---
# Inflammatory Blood Signature Related to Common Psychological Comorbidity in Chronic Pain
## Abstract
Chronic pain is characterized by high psychological comorbidity, and diagnoses are symptom-based due to a lack of clear pathophysiological factors and valid biomarkers. We investigate if inflammatory blood biomarker signatures are associated with pain intensity and psychological comorbidity in a mixed chronic pain population. Eighty-one patients ($72\%$ women) with chronic pain (>6 months) were included. Patient reported outcomes were collected, and blood was analyzed with the Proseek Multiplex Olink Inflammation Panel (Bioscience Uppsala, Uppsala, Sweden), resulting in 77 inflammatory markers included for multivariate data analysis. Three subgroups of chronic pain patients were identified using an unsupervised principal component analysis. No difference between the subgroups was seen in pain intensity, but differences were seen in mental health and inflammatory profiles. Ten inflammatory proteins were significantly associated with anxiety and depression (using the Generalized Anxiety Disorder 7-item scale (GAD-7) and the Patient Health Questionnaire (PHQ-9): STAMBP, SIRT2, AXIN1, CASP-8, ADA, IL-7, CD40, CXCL1, CXCL5, and CD244. No markers were related to pain intensity. Fifteen proteins could differentiate between patients with moderate/high (GAD-7/PHQ-9 > 10) or mild/no (GAD-7/PHQ-9 < 10) psychological comorbidity. This study further contributes to the increasing knowledge of the importance of inflammation in chronic pain conditions and indicates that specific inflammatory proteins may be related to psychological comorbidity.
## 1. Introduction
Chronic pain is a challenging disorder to study given the complexity of the underlying mechanisms, which include the immune system, and the high psychological comorbidity [1,2]. Many neuroimmune and psychological mechanisms [3,4] have been identified that seem to play a role in the development and maintenance of pain that persists without a corresponding peripheral sensory input. Chronic pain diagnoses are rarely distinct entities. The diagnostic criteria were recently revised by the International Association for the Study of Pain (IASP) to reflect modern findings and facilitate an adequate distinction between functionally different types of chronic pain. In the ICD-11, pain syndromes are divided into mechanistic groups that encompass nociceptive pain (actual tissue damage and nociceptor activation), neuropathic pain (lesions to the somatosensory nervous system), and nociplastic pain (altered pain perception despite no discernable damage) [5,6]. Many pain syndromes do, however, include a mixture of these processes. Importantly, individuals with chronic pain commonly present with psychological comorbidities, including anxiety, depression, fatigue, disturbed sleep, and cognitive deficits [3,4]. These comorbidities can often affect the person’s quality of life and functioning as much as the pain intensity itself [7] and may negatively influence the effects of treatment. In turn, pain is one of the most common comorbid problems in illness in general and is one of the most significant problems accounting for years lived with disability, according to WHO [8]. Chronic pain encompasses many fundamental problems that characterize non-communicable, complex disorders. It is profoundly costly for society and often devastating for the individual [5]. It affects a large part of the population, but increasing age and female sex increase the risk [7]. Several treatment options may be helpful for many individuals suffering from pain, but often, no complete cure can be offered [5].
The understanding of chronic pain has increased in the last few decades, and modern pain treatment incorporates psychological aspects of the disorder [5], acknowledging that pain is not solely a dysfunction of the nervous system but a multisystem problem. Lately, the focus has been on the immune system, highlighting neuroimmune interactions and inflammatory mechanisms in chronic pain conditions [1,2,3,4,9,10,11,12,13]. This line of research suggests that the immune system is involved in both central and peripheral sensitization of pain neurons [2], in the development and priming of the pain system [1], in sex differences in prevalence [12,13], and in the bidirectional interplay between pain and psychological wellbeing [3,4]. Systemic low-grade inflammation has been indicated in several pain diagnoses [14,15,16,17,18], similar to the findings for inflammation and depression [19,20,21,22]. Pain diagnoses are generally symptom-based due to a lack of clear pathophysiological factors and reliable and relevant biomarkers. Challenges in identifying target molecules for pharmacological treatments of chronic pain have led to system-based enquiries, such as proteomics studies or larger targeted multiplex analyses, to study networks of expressed proteins in different chronic pain conditions. Gomez-Varela et al. suggest the term protein disease signature (PDS) to describe networks or groups of proteins related to chronic pain in general, to specific chronic pain syndromes, or phases or aspects of persistent pain [23]. For now, no PDS specific enough to serve as a biomarker for diagnosis or progression of chronic pain has been identified. In PDS studies, many markers are studied in an exploratory and data-driven fashion. Such studies may reveal the biological underpinnings of this common and severe disorder that are unknown to date and can subsequently be investigated in directed, experimental studies. Most pain studies using this approach have been cross-sectional, comparing defined pain populations with healthy controls, assuming that the differences between groups reflect a specific pattern in the chosen biological fluid related to that particular pain disorder [24,25,26,27,28,29,30,31,32,33]. The focus is usually on pain intensity, as pain research ultimately aims to eradicate the pain [34,35,36,37,38]. Some have pointed to correlations between PDS and pain severity, but most have not. The few studies investigating psychological comorbidity in pain with a proteomic approach indicate that the related PDS differ for pain sensitivity (pressure pain thresholds), clinical pain (pain intensity), or psychological distress (anxiety and depression using total HADS) in pain disorders of widespread pain [32,38,39]. Wåhlén et al. show that distinct protein networks largely do not overlap and are related to pain or psychological distress, respectively, in fibromyalgia and chronic widespread pain. This exemplifies the complexity of pain syndromes regarding the relationship between biological networks and clinical outcomes.
In this study, we make assumptions that influence analyses and interpretations. The first is that chronic pain is multifaceted. Pain intensity is the primary treatment outcome, but the disorder encompasses levels of suffering beyond pain intensity, such as depression and anxiety. The second is that some mechanisms will be specific for certain pain disorders (e.g., mechanisms accompanying the damage of nerves in neuropathic pain), but some are potentially overarching, such as immune dysfunction, and involved in several pain disorders. We thus focus on proteins belonging to the inflammatory system from an easily accessible tissue (blood). We also proceed from the broad knowledge assimilated in the past decade on inflammation-driven mood changes in experimental [40,41,42,43] and clinical settings and in population studies [19,44,45,46,47]. These studies suggest that an activated immune system may drive depressive mood and anxiety, as well as heightened pain sensitivity. While inflammatory effects have been intensely investigated for depression [19,21,22], it should be noted that higher levels of common inflammatory markers (e.g., CRP and IL-6) in clinical anxiety diagnoses are inconsistent, most consistently represented in post-traumatic stress disorder [48,49,50]. For chronic pain, PDS research has increased in recent years (e.g., [32,51]). Thus, this study attempts to explore the relationship of 77 inflammatory markers from a well-established and well-used protein marker panel and explore potential subgroups of a chronic pain patient sample. This study is an exploratory assessment within a project designed to investigate the effects of ongoing inflammation in pain, pain comorbidity, and behavioral treatment (https://openarchive.ki.se/xmlui/handle/$\frac{10616}{48067}$ (accessed on 8 January 2023)) [52]). The sample consists of mixed pain for pragmatic reasons and to optimize ecological validity, i.e., a clinically representative pain population. We asked which inflammatory markers were related to the pain itself versus common psychological comorbid problems in a clinically representative pain population and if some markers can distinguish patient subgroups based on their pain and/or psychological comorbidity. This investigation aims to add to the growing literature on the involvement of inflammation in chronic pain and problematize the different subcomponents of this complex disorder.
## 2.1. Study Participants and Procedure
Participants were recruited between 2016 and 2018 as patients at the Behavioral Pain Medicine Treatment Services at the Karolinska University Hospital (Sweden) or via advertisements (self-referral). The inclusion criteria for the study were men and women ≥ 18 years of age; pain duration > 6 consecutive months; unresponsiveness to general treatments; stable medication the last two months; and must understand/read fluent Swedish. Exclusion criteria were pregnancy, breastfeeding or having given birth within the previous year, and hemophilia. Further, patients participating in a concurrent cognitive behavioral therapy (CBT)-based treatment, such as acceptance and commitment therapy (ACT), as well as patients who presented with severe psychiatric comorbidity that required immediate assessment or treatment (e.g., high risk of suicide, psychotic symptoms), were excluded. Finally, if a spontaneous improvement in their pain could be expected, participants were also excluded (see [52] using the same cohort). The initial screening processes resulted in 113 participants. After evaluation of eligibility according to the inclusion and exclusion criteria, 81 subjects (women $$n = 58$$ ($72\%$), men $$n = 23$$ ($28\%$)) with chronic pain (>6 months) were included in the study. For an overview of the recruitment process and reason for exclusion, see the flow chart in Figure 1.
## 2.2. Patient-Reported Outcomes (PROMs)
Self-reported Swedish questionnaires, including several validated measures, were used to record patient-reported outcomes and were filled out digitally by each participant in connection to blood sampling.
## 2.2.1. Anthropometric Parameters
Sex, age (years), weight (kg), and height (cm) were recorded via self-assessment, and body mass index (BMI) was calculated (kg/m2).
## 2.2.2. Pain Parameters
Each subject self-reported their present pain intensity (whole body) with the numeric rating scale (NRS). The NRS scale ranges from 0 to 10, where 0 equals no pain and 10 equals the worst imaginable pain. To characterize what type of pain was present, each subject reported present pain (yes or no) in the following area: head, facial, teeth/jaw, neck, back, chest, abdomen, genital, hands, legs, feet, and entire body. These scores were used to determine whether the pain was of local or of a more widespread origin. A score of reported pain in ≥3 areas was regarded as widespread pain. Local pain was classified if the pain was present in only one area or two areas in the same body part, e.g., leg and feet. Mean painful areas were calculated and reported as the variable pain area number.
Pain duration (years) for each area was reported and calculated as mean pain duration over all sites.
The Pain Disability Index (PDI) consists of 7 items and assesses how much impact the perceived pain has regarding hindering everyday life activities [53]. Each item is summarized into a total score ranging from 0 to 70, where a higher score indicates greater disability due to pain.
The Pain Interference Index (PII) measures how pain influences functioning. It consists of 6 items, where the total score is summarized, ranging from 0–36 [54]. A higher score indicates more pain interference.
The Pain Catastrophizing Scale (PCS) measures catastrophizing thoughts and consists of 13 items divided into three subscales that measure rumination, helplessness, and magnification. Each subscale is summarized to a total score ranging from 0 to 52, where a higher value indicates worse catastrophizing thoughts [55].
## 2.2.3. Psychological Parameters
The Patient Health Questionnaire-9 (PHQ-9) was used to assess present depressive symptoms. The questionnaire consists of nine items, with each item scoring 0–3 points. The total sum score (maximum 27) was calculated, and cutoff values for depressive symptoms were set to: 0–4 = none, 5–9 = mild, 10–15 = moderate, and 15–27 = moderate/severe [56].
The Generalized Anxiety Disorder 7-item scale (GAD-7) was used to assess symptoms of anxiety. The GAD-7 consists of 7 items, with each item scoring 0–3 points. The total sum score (maximum 21) of all seven items was calculated, and cutoff values for anxiety symptoms were set to: 0–4 = none, 5–9 = mild, 10–14 = moderate, and 15–21 = severe [57].
## 2.2.4. Other Clinical Parameters
Self-rated health (SRH-5) was used to evaluate how the participants rated their general health status. The questionnaire consists of a single item and is scored from 0 to 5. For facilitating the interpretation, the score was reversed when summarized so that 0 = poor health and 5 = good health [58].
The Insomnia Severity Index (ISI) was used to assess insomnia problems. It consists of seven items, with a total score ranging from 0 to 28 [59]. A higher score indicates greater insomnia problems.
The Perceived Stress Scale (PSS) was used to evaluate general perceived stress levels. It consists of 10 items, with each item scoring 0–4. The total score from all items is summarized to generate a score ranging from 0 to 40 [60]. The higher the score, the larger the perceived stress level.
Short Form-12 Health Survey (SF-12) is a shorter form of the SF-36 questionnaire measuring health-related quality of life summarized in two dimensions; a physical component score (PCS-12) and a mental component score (MCS-12) [61]. PCS-12 and MCS-12 consist of several questions with different scoring, which generate a total sum score ranging from 0 to 100. The higher the score, the better the patient’s physical and mental wellbeing.
## 2.3. Blood Sampling
Non-fasting venous blood sampling using EDTA tubes was performed between 8 and 12 a.m., and samples were processed within two hours. No more than 50 mL of blood was drawn. Routine analysis measures of C-reactive protein (hs-CRP), erythrocyte sedimentation rate (sr-ESR), and cortisol in blood were performed at Karolinska University Hospital. If elevated CRP values (>10 mg/L) were detected, the patients were informed of the results by a physician. Plasma samples were further aliquoted and stored in Karolinska University Hospital Biobank at −80 °C and went through one thawing cycle before analysis. For further details, see [52].
## 2.4. Inflammatory Cytokine Panel Analysis
Plasma samples from each participant were analyzed on the Proseek Multiplex Olink Inflammation Panel using the Proximity Extension Assay technology provided by OLINK (Bioscience Uppsala, Sweden) according to the manufacturer’s instructions (for information on all cytokines included in the panel, see www.olink.com/products/inflammation/ (accessed on 8 January 2023)) [62,63]. The inflammatory panel included 92 cytokines, chemokines or growth factors. Eighteen proteins were excluded due to missing values in >$60\%$ of the samples (IL-17C, IL-20RA, IL-2RB, IL-1 alpha, IL-2, FGF-5, IL-22RA1, Beta-NGF, IL-24, IL-13, ARTN, IL-20, IL-33, IL-4, LIF, NRTN, IL-5, and TSLP), resulting in 77 proteins from the OLINK panel included in the downstream statistical analysis. *The* generated data are expressed as normalized protein expression (NPX), and values of NPX are acquired by normalizing Cq values against extension control, interplate control and a correction factor. The dataset can be used for statistical multivariate analysis and expresses relative quantification between samples but is not an absolute quantification.
## 2.5. Statistical Analysis
Univariate and descriptive statistics were performed in GraphPad Prism version 7.0.5 for Windows (GraphPad Software, San Diego, CA, USA). For comparison between subgroups (PROMs and specific protein markers), the Kruskal–Wallis test followed by post hoc Dunn’s multiple comparison tests were applied. No further correction for multiple testing was performed for univariate statistics. All analyses used a p-value ≤ 0.05 as the significance level. Multivariate data analysis (MVDA) was performed in SIMCA version 16 (Sartorius Stedim Biotech, Umeå, Sweden). The procedure for computing MVDA has been described in detail elsewhere [24,30,32,33,64]. MVDA is often used when large omics panels are investigated and multivariate correlation between variables exists. Since MVDA accounts for the internal correlation structures of a dataset (analyzing all variables simultaneously), no further correction for multiple testing is needed, as is often necessary using other type of tests such as mixed models or univariate comparison. Before starting the MVDA, NPX data were log2 transformed and scaled with unit variance, following principal component analysis (PCA) in combination with hierarchical clustering analysis (HCA), orthogonal partial least-square analysis (OPLS), and based on the subgroups identified in the HCA, OPLS–discriminant analyses (OPLS-DA).
## 2.5.1. Principal Component Analysis (PCA)
PCA is an unsupervised dimensional reduction method used to investigate correlation structures among several variables (e.g., inflammatory proteins) and a set of observations (each individual subject). In this study, we have used inflammatory proteins as x-variables ($$n = 77$$) and included 81 observations (subjects) consisting of chronic pain patients. Initially, the PCA was used to detect potential outliers in the dataset using Distance to model X (DModX) and Hotelling’s T2 in SIMCA [64,65]. If an observation is flagged in both DmodX and Hotelling’s T2 as a moderate and strong outlier, it should be excluded. No observation was flagged as a severe outlier, and all observations were thus kept for further downstream statistical analysis.
Beyond the detection of outliers, PCA was used to discover correlation patterns and other similarities in the dataset, including subgroups. The results are displayed in two plots; the score plot and the loading plot. The score plot consists of the first two principal components (PC), and each observation is displayed as an individual point referred to as a score. The loading plot shows each x-variable as a loading weight, and these weights (or loadings) are displayed as individual points in the loading plot. Furthermore, the loading plot shows how each x-variable is related to each other, including if they are positively correlated and contain similar information (located close/grouped), which ones are negatively correlated (located opposite to each other in diagonal quadrants), and variables that are poorly explained by the model (variables located close to zero) [65]. The proteins with the highest loadings have the most influence on the model, and proteins located close to zero do not influence the model output. By combining the score and loading plot, interpretations of associated patterns and correlation structures between variables and observations can be made. Complementary to PCA, the built-in hierarchical clustering analysis (HCA) in SIMCA was used to explore potential subgroups [65]. The resulting dendrogram, based on inputted x-variables (proteins) and all detected components in the PCA, suggested three subgroups. The available clinical variables were explored and compared between subgroups to find potential clinical differences.
## 2.5.2. Orthogonal Partial Least Square Analysis (OPLS)
OPLS modeling was used to investigate a specific clinical variable (set as the Y-variable) and correlations to x-variables (proteins). OPLS separates the systemic variation in X into two parts, one related or correlated to Y and one uncorrelated to Y. Based on our a priori findings and assumptions, the clinical variables PHQ-9 (depression) and GAD-7 (anxiety) were investigated. Due to an age difference between groups, age was also investigated.
## 2.5.3. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA)
OPLS-DA is a supervised method used to identify variables, such as proteins, that are most important for discriminating between two groups. In this study, OPLS-DA was applied based on the clustered subgroups from the HCA/PCA, where two chronic pain subgroups were set as Y-variables at a time (group belonging) and protein data were set as predictors (x-variables). In the OPLS-DA model, chronic pain patients with moderate/high or mild/no psychological comorbidities were compared. The patients were classified as having moderate or high psychiatric comorbidity if they scored > 10 or mild or no psychological comorbidity if they scored < 10 in the self-reported PHQ-9 and/or GAD-7 scale questionnaires.
The OPLS and OPLSA-DA modeling was performed in two steps, as described in previous studies [32,33]. A number of parameters should be taken into consideration to describe the model quality when using the SIMCA software [64]. Overall model prediction and performance for PCA, OPLS, and OPLS-DA are represented by the variables R2 and Q2. The goodness of fit is how well the model fits the data or explains the dataset and is described by R2. The goodness of prediction, or how well a model predicts the dataset, is explained by Q2. These two parameters can vary between 0 and 1, where 1 means a $100\%$ fit and prediction of data. Working with biological data, an R2 or Q2-value of >0.3 indicates a good model. To evaluate if a model is significant, a cross-validated analysis of variance (CV-ANOVA) is used, where a p-value < 0.05 is considered a significant model. To evaluate which x-variables (proteins) are regarded as significant in each model (OPLS and OPLS-DA), the variable influence on projection (VIP)-value is used. VIPpred (VIP value for the first predictive component) is related to the loading of each variable and describes the importance of each variable and its contribution to the model output. The higher the VIP value, the more important the variable for the model is. A VIPpred value > 1.0 is regarded as significant. p(corr) is the correlation coefficient, originating from the loadings and ranging from −1 to 1. A higher p(corr) indicates a higher correlation of a specific variable in OPLS and OPLS-DA models [64,65].
## 3.1. Cohort Characteristics
In total, 81 subjects with chronic pain were included in this study. Overall, females were overrepresented ($71.6\%$), and the patients reported moderate pain intensity (mean (SD): 6.2 (1.9)) and pain in different areas of the body. The back ($70.4\%$) and neck ($58\%$) were the most reported painful areas (Table 1). Based on the self-reported pain areas, $32.1\%$ were grouped as having local pain, and $67.9\%$ were grouped as having widespread pain (Table 1). An overview of background data, pain, and other clinical characteristics are further described in Table 1.
## 3.2. PCA Investigating Patient Subgroups Based on Inflammatory Protein Profile
In the primary analysis, a PCA was created to investigate correlation structures among inflammatory proteins and potential chronic pain subgroups. In this unsupervised model including 81 observations and 77 proteins, three subgroups of chronic pain patients were identified using HCA included in the SIMCA software. The significant model had four principal components with an R2(cum) = 0.420 and a Q2(cum) = 0.222 (Figure 2).
The PCA score plot shows each observation (represented by a square, circle, or triangle) and the results from the HCA as three groups marked in the colors green (group 1 = squares), blue (group 2 = circles), and red (group 3 = triangles) (Figure 2A). The complementary PCA loading plot shows each variable (proteins) and is represented by a colored dot (Figure 2B). The different proteins are clustered, correlated, and associated with the three groups. The results from the PCA show a higher inflammatory profile is present in subgroups 2 and 3 compared to subgroup 1 (Figure 2B). Several proteins are intercorrelated and associated with individual subgroups (Supplementary Table S1).
To obtain an overview of the clinical picture of the identified three subgroups in the PCA, a descriptive overview of the variables sex, pain intensity, age, BMI, anxiety, and depression scores are presented in Supplementary Table S2 and Supplementary Figures S1–S6. In summary, women and men were evenly distributed in the score plot and within each detected subgroup (Supplementary Figure S1). The self-reported pain intensity was also similar among the three subgroups (Supplementary Figure S2). A tendency of higher age was noted in subgroup 2 (Supplementary Figure S3), which was confirmed by statistical analysis showing an increased age in subgroup 2 compared to subgroup 3 (Supplementary Table S2). No statistical differences were found between the groups when comparing BMI (Supplementary Table S2 and Figure S4). A tendency for higher anxiety and depression scores was noted in subgroup 3 (Supplementary Figures S5 and S6). A statistically significant difference in self-reported anxiety score was noted between groups, specifically in subgroup 1 compared to subgroup 3 (Supplementary Table S2). For the other clinical measures, we saw no difference in sleep, stress or self-rated health between groups, nor was there a difference in pain-related aspects or physical wellbeing (Supplementary Table S2). However, mental wellbeing (MCS-12) differed significantly between groups, with group 2 showing higher overall mental wellbeing as assessed by the SF-12. In summary, the identified groups based on inflammatory markers tended to differ in age, BMI, anxiety, and depression in visual distribution plots (Supplementary Figures S1–S6) and statistically differed in age, anxiety, and mental wellbeing (Supplementary Table S2).
## 3.3. Correlation of Inflammatory Proteins with Pain Intensity, Psychological Comorbidity, and Age
No significant model was obtained when performing an OPLS regression on pain intensity and inflammatory proteins (R2 = 0.23, Q2 = 0.002, CV-ANOVA p-value = 0.91). Since there was a significant difference in self-reported anxiety score (GAD-7) between subgroups 1 and 3, an OPLS model regressing this variable was performed, including all groups. A significant model was obtained with a low explained variation of $14.0\%$ (1 PC, R2 = 0.140, Q2 = 0.110, CV-ANOVA p-value = 0.017) (Supplementary Figure S7A,C). Ten proteins were associated with anxiety and regarded as significant with a VIP-value > 1.0 and p(corr)> 0.80. These proteins were (ordered after the highest VIP-value): STAMBP, SIRT2, CD40, AXIN1, CASP-8, IL-7, CXCL1, CXCL5, CD244, and ADA (Supplementary Figure S7C). As shown in the score plot (Supplementary Figure S7A), these ten proteins were associated with a higher self-reported anxiety score, where groups 2 and 3 cluster around these proteins, while subgroup 1 does not.
Visualization of the self-reported PHQ-9 scores, reflecting depressive symptoms, in the PCA score plot (Supplementary Figure S6) indicated a difference in this score among our three subgroups. Therefore, and due to our initial interest in anxiety and depression and comorbidities in pain, an OPLS model using PHQ-9 as a regressor was performed. The significant model had a low explained variation of $14.4\%$ (1 PC, R2 = 0.144, Q2 = 0.106, CV-ANOVA p-value = 0.020), and 11 proteins were regarded as significant and associated with higher self-reported depression scores (VIP-value > 1 and p(corr) > 0.70) (Supplementary Figure S7B). These proteins were (ordered in highest VIP value): STAMBP, SIRT2, AXIN1, CASP-8, ADA, IL-7, CD40, CXCL1, CXCL5, CD244, and ST1A1 (Supplementary Figure S7D).
Ten of the eleven significant proteins were important regressors in both OPLS models of self-reported anxiety and depression scores. Comparing the mean NPX values of these 11 proteins between the 3 subgroups clearly showed that subgroup 1 had lower levels than subgroups 2 and 3 of the 11 cytokines (Figure 3), which was confirmed with univariate statistics (Supplementary Table S3).
## 3.4. Inflammation and Age in Chronic Pain
Since there was a significant difference in age between subgroups 2 and 3 (Supplementary Table S2), we wanted to control for the possibility that the correlations with psychological comorbidity were not merely an effect of aging. Therefore, an OPLS model using age as an individual y-variable and proteins as regressors (x-variable) was performed to elucidate which proteins correlated to age. For age, a model with high explained variation and predictivity (R2 = 0.863, Q2 = 0.730, CV-ANOVA p-value = <0.001) was found. Twenty-two proteins had a VIP >1.0 and were regarded as significantly correlated to age. Out of the 22 proteins, only the protein ADA was found in the OPLS model of anxiety and depression (Supplementary Table S4).
## 3.5. OPLS-DA Modeling of Chronic Pain Patients with a Higher Psychiatric Profile (Anxiety or Depression) Versus Chronic Pain Patients with no Psychiatric Comorbidity
To elucidate if there was a difference in inflammatory profile among chronic pain patients with psychological comorbidities, the cohort was divided into two larger groups, one with moderate/high and one with mild/no psychological comorbidities based on GAD-7 and PHQ-9 scores. The OPLS-DA model was significant (1 PC, CV-ANOVA p-value = 0.028) with a fairly good explained variation (R2 = 0.279) but with low predictivity (Q2 = 0.097) (Figure 4). Several proteins were associated and upregulated in chronic pain patients with the presence of moderate/high psychiatric comorbidity and had high VIP-values (proteins with a VIP > 1.52); IL-7, LAP TGF-beta-1, AXIN1, CXCL1, TNFSF14, CXCL5, CXCL6, 4E-BP1, SIRT2, CD40, CASP-8, ST1A1, STAMBP, ADA, and CD244). Other proteins were more associated with and upregulated in chronic pain patients with mild or no psychiatric comorbidity (proteins with a VIP > 1.0; CDCP1, CXCL9, CXCL10, CCL28, and IFN-gamma). Hence, five of these proteins were also found in the OPLS model of age (ADA, CXCL9, CCL28, CDCP1, and CXCL10). After removing the proteins that were found in the model by age, 15 proteins were left significant and able to separate the two groups (SIRT2, STAMPB, AXIN1, IL-7, CASP-8, CXCL1, CD-40, CXCL5, ST1A1, CD244, TNFSF14, 4E-BP1, CXCL6, LAP TGF-beta-1, and IFN-gamma) (Table 2).
To further elucidate the widespread pain component in this chronic pain cohort, the patients were divided according to their reported pain areas and if they were of a widespread origin or local, if they had back pain or no back pain, and if they had neck pain or neck pain. Surprisingly, no significant OPLS-DA models were retrieved after the division of pain location (data not shown).
## 4. Discussion
In this study, we used an exploratory approach to investigate a set of inflammatory markers in the blood that covary with important aspects of pain syndromes. As a first step, we investigated if the inflammatory markers were related to subgroups in a data-driven approach, i.e., the subgroups were defined according to inflammatory protein aggregation. The data suggest that the studied proteins clustered the participants into three groups. Group 1 had a less pronounced inflammatory profile compared to the other two groups (Figure 2 and Supplementary Table S1). The grouping pattern from the PCA is not entirely clear concerning the function of the markers’ biological function. What can be said is that the classical proinflammatory cytokines that are mostly studied in similar research, such as IL-6, IL-8, IFN-gamma, IL-10 and CRP, tend to fall into group 2, except for TNF, which clustered in group 1. To further understand the subgroups identified through the PCA, we compared clinical characteristics between the groups. The identified groups based on inflammatory markers showed a tendency to differ in age, BMI, anxiety, and depression in visual distribution plots (Supplementary Figures S1–S6), but only age and anxiety distinguished them statistically (Supplementary Table S2). Looking at crude mean levels, group 2 distinguished itself by having a higher mean age and BMI and statically significantly better mental health as assessed by SF-12. Group 3 was slightly younger and had the highest anxiety and depression scores. Group 1 had the lowest mean scores for psychological comorbidity and did not stand out in age or BMI. Interestingly, pain intensity and other pain-related measurements did not differ between the identified groups, other than that the older group 2 consequently had suffered from pain for a longer mean time. Sex was evenly distributed in the groups, so we do not believe the identified clustering patterns are sex-dependent. This means that within our PCA, the defining aspects of the groups, other than different inflammatory markers profiles, were age and mental health (Supplementary Table S2).
As a next step, we investigated if some markers are specifically related to the three main outcomes of interest, i.e., pain intensity, anxiety, and depression. First, we concluded that no inflammatory markers were related to pain intensity. This was somewhat contrary to our expectations, given prior research on inflammatory markers in pain populations. However, previous research is incongruent regarding the correlation of protein markers with pain intensity [34,35,36,37,38,66,67]. The lack of correlation to pain intensity was perhaps also not surprising, given that the PCA did not show any differences in pain measures in the identified groups. In contrast, 11 proteins were associated with higher depression scores. The same proteins, except for ST1A1, were also significantly correlated to higher anxiety scores. Group 1 had significantly lower mean levels of these markers compared to the other two groups (Figure 3). Unfortunately, we could not find any articles studying pain and depression or anxiety using this inflammatory panel for comparison. However, Sundquist et al. [ 68] showed altered levels of 36 cytokines/chemokines in patients with mild to moderate depression and anxiety after 8 weeks of psychological treatment using the same inflammatory panel. Among their top 10 most significant proteins that were altered after treatment were the same proteins that we found in our OPLS and OPLS-DA models for depression and anxiety (CXCL6, STAMPB, CXCL1, SIRT2, AXIN1, CXCL5, ST1A1, and IL-7). Even though they did not find any correlation of the cytokines/chemokines to reported symptom severity (using MADRS-S) before the start of the intervention, these proteins decreased after the intervention, and the authors suggest a potential involvement of these inflammatory markers in depression, anxiety, and stress and adjustment disorders. Our subgroup analysis partly supports that there might be specific inflammatory protein networks potentially related to self-reported higher anxiety and/or depressive mood in chronic pain patients.
To investigate if the correlations were primarily driven by age, given the significant age difference of one group, we identified the proteins that correlated with age (Supplementary Table S4). From these 22 age-related markers, only 1 (ADA) overlapped with the markers related to OPLS models of anxiety and depression. We thus tentatively argue that the correlations suggest a relationship between some immunomarkers and psychological comorbidity in this pain cohort. Taking this reasoning a step further, we divided the patients into two groups, pain with high psychological comorbidity vs. pain with low psychological comorbidity, and tested if some markers were predictive for this division. When excluding the markers that were related to age (CXCL9, CXCL10, CDCP1, CCL28, and ADA), 15 markers had some prognostic capacity (Figure 4 and Table 2), of which the 11 from the OPLS were overlapping. Interestingly, several of the markers associated with the patients in our cohort who also suffer from comorbid psychological problems have been associated with the presence of comorbid pain in patients groups with a different primary diagnosis, including diabetes [24] and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) [69], and have been shown to add inflammation in the form of periodontal problems in rheumatoid arthritis [70]. Several of these markers have also been suggested as markers for a specific pain disorder [71,72,73], such as AXIN1, CXCL1, TNFSF14, CD40, and particularly ST1A1 (all three studies). Additionally, Fineschi et al. [ 74] showed in a recent study of fibromyalgia patients that among 19 increased inflammatory proteins, AXIN1, SIRT2, and STAMPB were among the highest elevated in FM compared to controls. They also identified a subgroup of FM patients presenting a “high inflammatory profile” based on inflammatory protein levels in their serum. This FM subset reported significantly higher FM severity scores compared to the FM subset with a less pronounced inflammatory protein profile. However, no correlation between inflammatory proteins and depression or anxiety scores was assessed [74]. Some of these markers are reoccurring in several studies, and it remains to be understood what their presence in the blood in complex disorders signifies. AXIN1, for example, a regulator molecule of the Wnt signaling pathways [75], has been shown to correlate with disease severity in endometriosis [76]. SIRT2 has a wide range of regulatory functions ranging from neuronal to immunological and metabolic homeostasis [77,78]. Our study, together with other protein disease signature (PDS) studies, shows the importance of analyzing multiple inflammatory markers and comorbidities to explore a more complete picture of a disease. Our type of analysis strategy has the potential to reveal markers that would not have been studied in a classical hypothesis-driven setting.
Interestingly, all 15 markers that, in our OPLS-DA model, were related to the presence of anxiety or depression were also part of a highly discriminative PDS for fibromyalgia proposed by Bäckryd et al. [ 79]. In our study, post hoc analyses did not show a difference between patients with localized versus widespread pain. Speculatively, in a complex disorder such as chronic pain, any disease-related PDS that is identified may not be specific for the disease characteristics of primary interest but with characteristic comorbidity. This would require a new approach when comparing groups and controlling for covariates. The markers in the mentioned studies above were identified in between-group analyses of a particular pain population and healthy control or between two pain populations. In such comparisons, it seems to be assumed that the identified markers are distinct for the pain syndrome at hand, while psychological comorbidity is rarely taken into the equation. Our results suggest that these markers may, in fact, be related to pain syndromes but perhaps not to pain-related aspects specifically or to specific pain syndromes. PDS exploration needs to take psychological comorbidity into account to a higher degree, e.g., with positive controls with psychiatric disorders or grouping based on mental health or other common comorbidities compared to disease-specific severity.
Our study has several limitations. The PDS was assessed in a mixed chronic pain population representative of patients attending this clinic working with behavioral interventions for chronic pain. The group appears typical for similar clinical settings [33,80], with a mean age of around 50 years, around $70\%$ women, and common comorbidities (Table 1), with the majority of patients having low back and neck pain and pain in more than one body part. This may give the results some ecological validity but introduces variance in the sample, and the results must be interpreted keeping this in mind. We lack a healthy control group for comparison, and a positive control group, such as a group of depressed patients. The design is cross-sectional, and the variables are self-reported. The chosen analysis panel is inflammatory, which constricts the exploratory effort, and the values are relative. We have not included several variables that may be of importance for the relationships at hand, such as medication, socioeconomic situation, and comorbidities other than anxiety and depression. Furthermore, the blood is not the optimal target tissue from a mechanistic point of view, but it is the most accessible sample for clinicians. Cerebrospinal fluid (CSF) may be more relevant mechanistically [81], and there is not a clear correlation between peripheral and central cytokine expression [82]. However, CSF is more challenging to retrieve, and collection may pose a risk for the participants that need to be weighed against the benefits and scientific merit. From a psychoneuroimmunological point of view, however, one may argue that peripheral activity may indeed affect the central nervous system and, consequently, emotions and behaviors [83]. Finally, correlations are not informative for causation, but such relationships can give an indication of which systems may covary and what active networks characterize the studied patient group. Despite these limitations, there are some clear overlaps between our findings and those of prior studies using the same panel in pain populations or populations with comorbid pain, which may suggest that there are overarching biological networks that need to be identified to be able to specify disease-related networks.
In our sample, the Olink panel only gives relative relationships, but the CRP levels suggest that none of our included patients had severe inflammation, and most of them had normal levels. The term that is often used for non-communicable complex disorders is “low-grade inflammation”, but this term needs to be further problematized. Within a population defined as having low-grade inflammation, relationships and characteristics in subgroups of patients with higher or lower inflammation may differ. Furthermore, ongoing inflammatory activity may not be harmful but a part of the body’s attempt to heal. Recently, we showed that in pelvic pain, women had an inverse relationship between the widespreadness of the pain and blood IL-8 levels, whereas no association was seen for men [84]. Interestingly, a very similar pattern was shown for depressed patients [85], with an inverse relationship between blood IL-8 levels and depression severity scores, but no association was found for men. Furthermore, the key to immune-driven ill health may not be systemic or localized inflammation per se but dysfunctional immunoregulation. Regarding pain specifically, some recent data show a stronger association between pain development and immunoreactivity [86,87], as gauged by toll-like receptor stimulation of whole blood/white blood cells, than with ongoing inflammatory activity (cytokine plasma levels). We did not have the logistic capabilities to collect and stimulate white blood cells in this study, but it is possible that immune priming and second-hit regulation [1] may be of greater importance for persistent pain than the commonly measured inflammatory markers assessed in blood.
Our results should be seen as a complement to ongoing neuroimmune research in pain and potentially hypothesis-generating rather than mechanistically exploratory. We argue that the pain and PNI research communities need to move beyond the traditional inflammatory markers to understand complex disorders, consonant with beliefs about multifaceted and interacting bodily processes involved in health and disease. IL-6 and CRP have repeatedly been shown to correlate with self-rated health [88,89], psychological wellbeing [19,21], and pain sensitivity [39,90]. These findings have taught us that low-grade inflammation is important, but from a treatment perspective, such general markers are not particularly useful. Treatment strategies targeting, e.g., IL-6 in these populations would do more harm than good. While anti-cytokine treatment has been successful for many patients with inflammatory pain, such as in rheumatoid arthritis [14], similar successes for musculoskeletal and generalized pain have not been achieved. It is likely that other proteins that interact and regulate the (neuro)immune system will be better candidates to treat pain with no clear inflammatory origin and may influence the large variability in treatment outcomes.
## 5. Conclusions
This study further contributes to the increasing knowledge that inflammation seems to be involved in the underlying mechanisms of chronic pain conditions. Our results show that there are potential subgroups of chronic pain patients with different inflammatory profiles and that specific proteins might be associated with higher psychological comorbidity. In future research, inflammatory blood signature exploration needs to consider psychological comorbidity to a higher degree to further understand its involvement in different chronic pain conditions.
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|
---
title: Inflammation, Microcalcification, and Increased Expression of Osteopontin Are
Histological Hallmarks of Plaque Vulnerability in Patients with Advanced Carotid
Artery Stenosis
authors:
- Ioan Alexandru Balmos
- Emőke Horváth
- Klara Brinzaniuc
- Adrian Vasile Muresan
- Peter Olah
- Gyopár Beáta Molnár
- Előd Ernő Nagy
journal: Biomedicines
year: 2023
pmcid: PMC10045225
doi: 10.3390/biomedicines11030881
license: CC BY 4.0
---
# Inflammation, Microcalcification, and Increased Expression of Osteopontin Are Histological Hallmarks of Plaque Vulnerability in Patients with Advanced Carotid Artery Stenosis
## Abstract
Background: severe carotid artery stenosis is a major cause of ischemic stroke and consequent neurological deficits. The most important steps of atherosclerotic plaque development, leading to carotid stenosis, are well-known; however, their exact timeline and intricate causal relationships need to be more characterized. Methods: in a cohort of 119 patients, who underwent carotid endarterectomy, we studied the histological correlations between arterial calcification patterns and localization, the presence of the inflammatory infiltrate and osteopontin expression, with ulceration, thrombosis, and intra-plaque hemorrhage, as direct signs of vulnerability. Results: in patients with an inflammatory infiltrate, aphasia was more prevalent, and microcalcification, superficial calcification, and high-grade osteopontin expression were characteristic. Higher osteopontin expression was also correlated with the presence of a lipid core. Inflammation and microcalcification were significantly associated with plaque ulceration in logistic regression models; furthermore, ulceration and the inflammatory infiltrate were significant determinants of atherothrombosis. Conclusion: our results bring histological evidence for the critically important role of microcalcification and inflammatory cell invasion in the formation and destabilization of advanced carotid plaques. In addition, as a calcification organizer, high-grade osteopontin expression is associated with ulceration, the presence of a large lipid core, and may also have an intrinsic role in plaque progression.
## 1. Introduction
Ischemic vascular brain disease, manifesting as brain infarction and white matter lesions (WMLs), is highly prevalent in the elderly, being the second leading cause of death globally, and can lead to permanent disability due to irreversible neurological and cognitive deficits [1]. It is most commonly caused by severe carotid stenosis or embolization from a high-risk carotid plaque resulting in a stroke. Atherosclerotic plaque development is driven by systemic and local factors that ultimately determine where plaques form and how they progress. Local susceptibility to plaque formation depends on the arterial microenvironment, including arterial mechanics, matrix remodeling, and lipid deposition through the regulation of vascular cell function [2].
The pathophysiology of atherosclerosis is well documented, considered a chronic, insidious lipid-driven inflammatory process with several potential contributors, which lead to ischemia of target tissues through narrowing of the large- and medium-sized arteries’ lumen. This process is initiated by endothelial dysfunction, followed by a cascade of cellular, functional, and molecular events, which imply the activation of inflammatory pathways [3]. Lipid deposition in the arterial wall causes an influx of macrophages to remove the lipid deposits, but the continuous increase in plasma cholesterol and the ineffective removal result in extracellular lipid accumulations, along with macrophage necrosis, leading to the formation of a necrotic core. This intimal inflammatory response activates smooth muscle cells in the underlying medial layer, which shift their phenotype and migrate into the neointima. Through fibroproliferative remodeling, smooth muscle cells contribute to the growing plaque size and lumen occlusion. However, this fibroproliferative response also forms a protective fibrous cap, rich in smooth muscle cells and collagen, which ensures the mechanical stability of the plaque and prevents plaque rupture [3].
Before the era of the inflammatory theory, vascular calcification was thought to be a passive process and a late manifestation of atherosclerosis. In the coronaries, calcification is a predictor of future cardiovascular events [4]; less is known about its causal relationships in the case of carotids. Recent histological evidence from human cerebral artery specimens has demonstrated that calcification may affect two different layers of the wall: the intima and/or the media. Calcification of the media is often associated with diabetes and chronic kidney disease. Intimal calcification is a typical feature of advanced atherosclerosis and manifests as two sub-types: micro- or spotty, early-stage calcification or macro-, sheet-like, and late-stage calcification [5]. Evidence from histopathological analyses and clinical imaging studies has confirmed that intimal calcification is more associated with plaque vulnerability. In contrast, medial calcification, particularly of the inner elastic lamina, contributes to artery stiffness rather than lumen stenosis [6].
Microcalcification develops due to activated macrophages and smooth muscle cells, which first form matrix vesicles and then crystallizing mineral deposits [4]. These can be identified by PET-CT imaging or optical coherence tomography; functionally, they increase the mechanical stress between the fibrous cap and lipid core, resulting in plaque rupture [7]. Several analyses have associated the late-stage “macrocalcification” with the presence of more differentiated smooth muscle cells and a more organized extracellular matrix, conferring plaque stability [8,9]; however, other recent studies have suggested that superficial, multiple calcifications and ulceration are associated with intra-plaque hemorrhage, and may represent higher-risk lesions [10]. Conversely, intraplaque hemorrhage and erythrocyte extravasation may stimulate osteoblastic differentiation and intralesional calcium phosphate deposition [11]. Osteopontin (OPN), a phosphoglycoprotein expressed in many tissues, consistently co-localizes with ectopic calcification. The molecule is a pro-inflammatory cytokine and can be further induced by reactive oxygen species, interleukin-1β (IL-1β), and tumor necrosis factor α (TNFα) [12]. Due to the density of glutamic and aspartic acid residues, OPN can fix a significant amount of calcium [13]. It was suggested that acute increases in OPN might have a protective role because it reduce calcification and assist in wound healing and neovascularization. However, its sustained elevation confers a high cardiovascular risk [12]. According to these data, the risk of a cerebrovascular event due to a vulnerable atheromatous plaque depends on the severity of vascular stenosis and plaque morphology and composition.
Taking these considerations, we studied the relationships between calcification patterns, the presence of inflammatory cell infiltrates, and histological signs of vulnerability: ulceration and thrombosis on arterial specimens of a cohort of patients who underwent carotid endarterectomy due to severe atherosclerosis.
## 2.1. Patients and Tissue Fragments
Carotid plaque specimens were collected by carotid endarterectomy from patients diagnosed with symptomatic carotid artery stenosis hospitalized between January 2020 and December 2022 in the Vascular Surgery Clinic—County Emergency Clinical Hospital and the Cardiovascular Surgery Clinic—Cardiovascular Disease and Transplantation Emergency Institute of Târgu Mureș (Romania).
A total of 119 cases were selected for the histopathology study (plaques collected during carotid endarterectomy from 82 males and 37 females, all of them with severe carotid stenosis) based on strict criteria: patients with complete clinical documentation and the written informed consent of enrollment in the study, and last but not least, tissue samples with adequate quantity and quality for histological evaluation (Figure 1). Indication for carotid endarterectomy (CEA) was made on the clinician’s decision according to the European Society for Vascular Surgery and European Stroke Organization guidelines which recommend CEA for asymptomatic patients with carotid stenosis between 60–$99\%$ and for symptomatic patients with carotid stenosis between 50–$99\%$. Prior to surgery, imaging tests (CT angiography and a Doppler ultrasonography) were performed to diagnose, localize, and grade the stenosis. The exclusion criteria consisted of patients with carotid near occlusion, which refers to severe carotid stenosis with distal vessel collapse and no significant improvement in stroke prevention within the first 5 years following endarterectomy [14,15], those who had experienced a major stroke, those with a second stenotic lesion in the intracranial segment of the internal carotid artery, and those who had previously undergone carotid endarterectomy on the same side [16]. Figure 1 shows the study flowchart with the main exclusion steps at the clinical and histopathological levels.
## 2.2. Patients Data Collection
Demographic information (age and sex) and clinical data (neurological symptoms at the time of admission, history of hypertension, diabetes mellitus, hypercholesterolemia, coronary heart disease, presence of atherosclerotic disease involving more than one vascular bed, current history of smoking, use of antiplatelet or anticoagulant, hypolipidemic, and anti-hypertensive drugs and previous stroke/transient ischemic attack history) were collected and checked against medical records. Hypertension, diabetes mellitus, and hypercholesterolemia have been defined according to recent guidelines [17,18,19]. A history of stroke was based on the definition in the World Health Organization criteria, including a syndrome of rapidly developing symptoms, with no apparent cause other than of vascular origin, of focal or global cerebral dysfunction lasting 24 h or longer, or leading to death [20]. From the laboratory examination results, we have noted recent data on absolute neutrophil and lymphocyte count and neutrophil/lymphocyte ratio. Our group’s epidemiological, clinical imagistic, and laboratory characteristics are summarized in Table 1, which also shows the data broken down to subgroups with and without an inflammatory cellular infiltrate.
This study was conducted according to the principles of the Helsinki Declaration. It was approved by the Ethical Committee of the George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures (no$\frac{.906}{2020}$) and the institutional review board of County Emergency Clinical Hospital of Targu Mures (no. $\frac{29496}{2019}$) and of Cardiovascular Disease and Transplantation Emergency Institute of Târgu Mureș (no. $\frac{1680}{2020}$). Written informed consent was obtained from each patient involved in this study.
## 2.3. Histological Processing
After surgery, the tissue samples were immediately fixed in $10\%$ neutral buffered formalin and sent for histological analyses. Following decalcification in ethylene-diamine-tetra-acetic acid (EDTA) solution pH 7, all fragments were processed according to the standard methodology. For immunohistochemistry, consecutive histological sections were prepared. Morphological features of carotid plaques were examined in 4–5 µm sections stained with hematoxylin and eosin (H&E) by a senior pathologist (EH) blinded to the patient’s characteristics. Atherosclerotic plaques were classified accordingly to the Modified American Heart Association Classification in type IV-VII [21]. After establishing the grade, based solely on visual estimation of histological features without quantitative measurements, detection of characteristic signs of plaque vulnerability for each case was proposed, as follows: active mononuclear cells infiltration (macrophages and lymphocytes) within the atherosclerotic plaque, neovascularization within the lipid core, pattern of calcification (type, position, and extension), structure of lipid core (lipid-rich large necrotic core or hyaline rich core), intra-plaque hemorrhage, and fibrous cap damage (with or without parietal thrombus fragments) [22], each scored as being present or absent. Plaque rupture was identified by the presence of fibrous cap discontinuity with an endothelial defect of at least 1000 µm in width or a clear cavity formed inside the plaque [4], with or without thrombus, intra-plaque hemorrhage. The lipid core was categorized into large necrotic if cellular detritus predominated in its structure, along with macrophages with foamy cytoplasm and cholesterol crystals. In addition, we considered being fulfilled the criteria for an active mononuclear inflammatory infiltrate when macrophages and lymphocytes were observed around the core regardless of their quantity. The presence or absence of new vessels within the lipid core was also noted.
Focusing on their calcification type, plaques were included in four categories depending on the calcified patch distribution, size, and shape: (a) microcalcification (defined as a punctate pattern of numerous small micronodules/scattered small mineral foci), (b) nodular calcification (single/multiple stratified mineral deposits with a nodular aspect), (c) confluent/large calcification (a conglomerate of mineral material with irregular edges in collagen-rich plaque), and (d) osteoid metaplasia (mature bone with lamellar structure and bone marrow in a mineral mass of fibrocalcific plaque). Although there is no conventional standard of size, the consensus was taken into account that categorizes microcalcifications and macrocalcifications based on nodules of <50 and ≥50 μm, respectively [23]. Regarding position/location of calcification, we established two categories: superficial calcifications as calcified nodules located at the intimal–luminal interface or close to the lumen [10] and deep calcifications located in the thickness of the media or closer to the adventitia than to the lumen [4]. Extension of mineral mass was quantified depending on the occupied area from the total surface of the examined material and scored from 1 to 4, namely grade 1: less than $25\%$; grade 2: between 25–$50\%$; grade 3: between 50–$75\%$ and grade 4: over $75\%$.
## 2.4. Investigation of the Osteopontin (OPN) Expression within the Atherosclerotic Plaque by Immunohistochemistry
Immunohistochemical staining was performed using Osteopontin (OPN) polyclonal antibody (pab73623) purchased from Covalab (Villeurbanne, France) in combination with EnVision FLEX/HRP (Agilent, Dako, Santa Clara, CA, USA) as secondary antibody and 3,3′-diaminobenzidine chromogen (DAB), respectively, according to the manufacturer’s instructions. Nuclei were counterstained by hematoxylin. For negative control, normal serum was substituted for the primary antibody. According to the extension of the brown color reaction product, plaques were categorized in low-grade (score 1), mild-grade (score 2), and high-grade (score 3) OPN expression. Score 1 was considered as few positive cells (<25 cells in no more than two areas of the plaque examined with 20× magnification). Score 2 was represented by immunolabelled cells in slightly increased numbers, not exceeding 50 elements in no more than two areas of the plaque examined with 20× magnification. When the number of positive cells exceeded 50 in number in the examined areas, samples were labeled as score 3.
## 2.5. Statistical Analysis
Categorical variables and transformed continuous variables were assessed for absolute and relative distribution frequency. Analysis of 2 × 2 or 3 × 2 contingency tables has been performed with the Fisher’s exact test and the Pearson χ2 test. Nonlinear logistic regression models were set for the prediction of ulceration and atherothrombosis. In all tests, p-values < 0.05 were considered statistically significant. Data processing was performed using Microsoft Excel 2016 (Microsoft Corporation, Redmond, WA, USA) and GraphPad Prism 9.5.0 (GraphPad Software LLC., San Diego, CA, USA).
## 3.1. Study Group Characteristics
A total of 119, out of which 82 were male and 37 female patients, were enrolled in the study group, with a median age of 67 (61–72). All patients had severe carotid artery stenosis over $70\%$ (mean ± SE 81.3 ± 0.7). A total of 84 individuals showed unilaterally, and 35 possessed bilateral involvement of the carotids. Seventeen patients suffered from various forms of sensory or motor aphasia, and hemiparesis/hemiplegia occurred in 13 study group members. A previous stroke history was confirmed in 76 subjects. The vast majority of cases were hypertensive ($92.4\%$), and $27.7\%$ were diabetic (type 1 and type 2). Eighty of them showed only carotid atherosclerosis; in 28 patients, two arterial bed involvement (carotids and limbs or coronary), and in 11 cases, three arterial bed involvement (carotids, limbs, and coronary arteries) was established. A total of $48.7\%$ of the cohort were smokers, and except for four subjects, the rest presented hypercholesterolemia. No significant differences in the absolute neutrophil count, the absolute leucocyte count, and the neutrophil/lymphocyte ratio were observed (Table 1).
## 3.2. Histopathogical Features of Carotid Atherosclerotic Plaques
First, we investigated the plaque architecture and histological features by light microscopy. These plaques, some unstable, others advanced, showed a varied histological composition. Characteristic signs of plaque vulnerability for each case were reported. A lipid-rich large necrotic core (Figure 2a) was detected in $58.8\%$ of specimens. An active mononuclear cell component (macrophages and lymphocytes) was found in $63.02\%$ of cases surrounding the necrotic core or extending to the hyalinised zones (Figure 2b). Accumulation of erythrocyte aggregates in the plaque structure (intra-plaque hemorrhage) (Figure 2c) was present in $32.8\%$ of cases. Many plaques showed neovascularization by the proliferation of small, thin-walled microvessels with a collapsed lumen ($66.4\%$), in most cases coexisting with inflammation and intra-plaque hemorrhage (Figure 2d). Ulcerated plaques with irregular and discontinuous fibrous caps ($43.7\%$) led to thrombus formation in 16 cases (Figure 2e,f).
Because all examined plaques showed signs of calcification, the next step was to characterize the pattern, extent, and location of calcification. Regarding the intra-plaque calcification patterns, microcalcification, as numerous micronodules/scattered small mineral foci forming a calcification front within fibrosis (Figure 3a), was present by itself or in predominance in association with other types of calcification in $45.4\%$ of cases. Seventy-one plaques ($59.7\%$) showed a predominance of nodular calcification, as well-shaped single/multiple stratified mineral deposits with a nodular aspect (Figure 3b). Extensive (confluent) calcification (a conglomerate of mineral material with irregular edges (Figure 3c) dominated $34.5\%$ of cases, and osteoid metaplasia (mature bone with lamellar structure and bone marrow (Figure 3d) was present in only 33 cases ($27.7\%$). Depending on the location of the calcified foci in the thickness of the plaque, we observed a slight predominance in favor of superficial calcification over deep calcification 65 ($54.6\%$) vs. 54 ($45.4\%$). Mineral mass with grades 0–2 ($54.6\%$) exceeded grades 3–4 ($45.4\%$).
## 3.3. Osteopontin Expression
After the characterization of carotid atherosclerotic plaque morphology, the ensuing investigation has focused on the role of OPN in plaque instability. We examined by immunohistochemical technique whether OPN expression is only cell-associated or is also present at the extracellular level in the plaque. In Figure 4, endothelial cells of the intima and neoformed vessels, macrophages, those transformed into foam cells, and fibroblasts are intensively cytoplasmic stained for OPN (Figure 4a). Vascular smooth muscle cells, other significant constituents of the atherosclerotic plaque and capable of transformation into foam cells, were also OPN positive (Figure 4b–d). In plaque structure without addition to the cells mentioned above, OPN staining of an extracellular component can also be observed. Details are shown on Figure 4.
This result indicates that extracellular OPN is an active component of atherosclerotic plaque, but to clarify if it interacts with proteins involved in the plaque structure requires further immunohistochemical studies. Because the immunohistochemical results showed that osteopontin is produced by multiple cells, we hypothesized that the amount of OPN in situ influences plaque instability. Based on the scoring system applied to quantify the OPN expression, we found that a low-grade OPN expression (score 1) is significantly associated with the absence of an inflammatory infiltrate ($63.1\%$ vs. $36.9\%$). In contrast, in those with mid-grade (score 2) and high-grade (score 3) OPN expression, the incidence of the infiltrate was $80.5\%$ and $96.1\%$, respectively ($p \leq 0.001$). The low-grade OPN expression was present in $59\%$ of plaques without a lipid core, but the high-grade OPN was characteristic for $84.6\%$ of plaques with a lipid core ($p \leq 0.001$). The OPN score 3 was also significantly correlated with plaque ulceration ($53.8\%$), whereas the OPN score 1 case in $70.2\%$ showed no ulcers ($$p \leq 0.021$$). Moreover, in patients with polyvascular atherosclerotic disease affecting 3 arterial beds, 10 had an OPN score of 1, and only 1 had an OPN score of 3. In cases with one arterial bed involvement, the expression of OPN was more equilibrated ($41.2\%$ OPN score one vs. $23.7\%$) ($$p \leq 0.037$$). No relationship was observed with age, gender, neovascularization, thrombosis, intra-plaque hemorrhage, hypertension, aphasia, hemiparesis/hemiplegia, or bilateral carotid involvement. Microcalcification strongly correlated with osteopontin expression: its absence was observed in $73.7\%$ of the cases with an OPN score of 1. On the contrary, its presence was documented in $80.7\%$ of those with an OPN score of 3 ($p \leq 0.001$). Out of 65 cases with calcification of the superficial vessel wall layers, 22 had an OPN score of 1, and 19 had an OPN score of 3. However, in those with deep layer (media and adventitia) calcification, the distribution was unequal: 35 cases showed low, whereas only 7 cases showed high OPN expression ($$p \leq 0.003$$).
The extent of calcification, the nodular, the extended/confluent patterns, metaplasia, and the cumulated calcification pattern did not have significant associations. The distribution of OPN expression scores is indicated in Supplementary Table S1.
## 3.4. Comparison of the Inflammatory Infiltrate Positive (INF+) and Negative (INF−) Groups
Seventy-five patients possessed atheromatous plaques with a significant inflammatory infiltrate (INF), whereas 44 showed no elements of inflammation. Table 1 synthesizes the distribution of different variables in these two groups. The demographic parameters were similar in the two groups. The occurrence of aphasia was significantly lower in the inflammatory infiltrate negative (INF−) subgroup: $4.5\%$ compared to $20\%$ in the positive (INF+) subgroup ($$p \leq 0.027$$). In addition, the frequency of hemiparesis/hemiplegia was lower ($4.5\%$ vs. $14.7\%$) but without significance. The grade of carotid stenosis showed a borderline difference between the groups ($$p \leq 0.06$$). There were no essential differences concerning the incidence of diabetes, hypertension, bilateral carotid involvement, or previous stroke history. Polyvascular atherosclerotic disease with three arterial beds involvement was represented in $20.5\%$ of cases in the INF− group vs. $2.7\%$ in the INF+ group, whereas solitaire carotid artery involvement equaled $50\%$ in the INF− and $77.3\%$ in the INF+ group ($p \leq 0.001$).
## 3.5. The Distribution of Atheroma Calcification Patterns
Fifty-four plaques presented extended calcification (grades 3 and 4), out of which 30 ($40\%$) were classified in the INF+ and 24 ($54.5\%$) in the INF− group. In addition, 54 specimens showed microcalcification from the overall group, with a significantly biased distribution between the groups: 42 ($56\%$) in the INF+ group and only 12 ($27.2\%$) in the INF−. Regarding the localization, the calcification was superficial in 54 and affected the deep layers in 65 cases. Superficial calcification characterized more ($64\%$) INF+ plaques and less ($38.4\%$) of those INF− ($$p \leq 0.008$$). Among the calcification patterns, the nodular pattern was more frequent in the overall group than in the extended/confluent form ($59.7\%$ vs. $34.5\%$). The distribution of these patterns was significantly biased in the latter case: $26.7\%$ of the INF+ group had extended/confluent calcification, compared to $47.4\%$ of the INF− cases ($$p \leq 0.027$$). Osteoid metaplasia was detected at 33 plaques in the entire group, being more frequent in those INF− ($40.9\%$ vs. $22.6\%$), but this difference did not reach the significance threshold.
## 3.6. Treatment Correlations
Anti-hypertensive medication has been administered to all hypertensive patients ($$n = 110$$). A small subgroup was treated with anticoagulants ($$n = 7$$) preoperative (p.e.), and the majority of subjects received postoperative (p.o.) anti-coagulants ($$n = 95$$). Lipid-lowering treatment was administered to all, with the exception of three cases.
## 3.7. Correlations of Calcification Extent, Localization and Patterns with Ulceration, Thrombosis and Hemorrhagic Rupture of the Plaque
Ulceration occurred in a significantly higher proportion of plaques showing microcalcification: 34 of 54 vs. 18 of 65 ($p \leq 0.001$). Ulceration was relatively more frequent in those with superficial layer calcification than in plaques with deep layer involvement ($$p \leq 0.064$$). The nodular, the extended/confluent patterns, and the presence of metaplasia were not significantly associated with the ulcerative complication, neither as solitaire correlates nor in cumulative patterns (we classified in this group the occurrence of co-existing patterns, each component with a minimum weight of approximately $25\%$).
The presence of thrombosis was not correlated with calcification extent, localization, or patterns, as seen in Table 2.
The hemorrhagic rupture had a higher incidence in plaques with superficial calcification (27 of 65) than in those with deep layer calcification (12 of 54, $$p \leq 0.031$$). Further, the extended/confluent pattern was significantly associated with the lack of hemorrhagia ($$p \leq 0.019$$). No other calcification parameters or cumulative patterns correlated with the hemorrhagic rupture of the atheroma (Table 2).
## 3.8. Predictors of Plaque Ulceration
Univariate regression analysis revealed significant associations between plaque ulceration, the presence of single arterial bed involvement ($$p \leq 0.042$$), and morphological characteristics of the plaque: the lipid core ($$p \leq 0.004$$), micro-calcification ($p \leq 0.001$), and the presence of inflammatory infiltrate ($p \leq 0.001$). No significant relationships could be observed with diabetes, hypertension, a positive stroke history, unilateral vs. bilateral carotid involvement, age, gender, smoking, or hypercholesterolemia. A tendency for a lower odds ratio was registered in the presence of extended/confluent calcification pattern and in the highest vs. the lowest quartile of stenosis grade ($$p \leq 0.079$$ and $$p \leq 0.091$$). No other calcification patterns were correlated with ulceration (Table 3).
We constructed non-linear multiple logistic regression models to predict the ulceration of the plaques. In a model adjusted for the absence of polyvascular disease, a greater stenosis extent, hypertension, the presence of superficial and an extended/confluent pattern of calcification, and the presence of a lipid core, microcalcification ($$p \leq 0.003$$), and the presence of an inflammatory infiltrate ($$p \leq 0.007$$) remained significant predictors (Table 4). However, when we also adjusted for osteopontin expression, this abolished the significant influence of microcalcification and lipid core.
## 3.9. Predictors of Atherothrombosis
In univariate regression models, ulceration proved to be a strong predictor of thrombosis ($p \leq 0.0001$). The inflammatory infiltrates were also significantly associated ($$p \leq 0.046$$), whereas revascularization and the lipid core showed a borderline significance ($$p \leq 0.074$$ and $$p \leq 0.064$$, respectively). The other factors did not correlate, as shown in Table 5.
In univariate regression analysis, ulceration was strongly associated with plaque thrombosis ($p \leq 0.0001$). Further, the presence of inflammatory infiltrate was also significantly more frequent in those with thrombosis, ($$p \leq 0.046$$), whereas revascularization ($$p \leq 0.074$$) and the presence of the lipid core ($$p \leq 0.064$$) showed a tendency to significance. Age, gender, diabetes, hypertension, and smoking could not be associated, and no relationship has been revealed with the presence of polyvascular disease, unilateral involvement, and the grade of vascular stenosis. Furthermore, none of the calcification patterns could be correlated to the atherothrombotic complication (Table 6). In a multiple logistic regression model, ulceration and inflammation remained significant predictors, when adjusted for revascularization and the presence of the large lipid core ($$p \leq 0.002$$ and $$p \leq 0.007$$).
## 4. Discussion
Carotid endarterectomy and carotid stenting are two treatment modalities for patients with severe carotid stenosis. Histopathological processing of endarterectomy specimens provides useful information, which, together with clinical data and imaging investigation, contributes to the efficient secondary prevention of cerebrovascular events.
Carotid plaques have a complex morphology and composition, consisting of both extracellular (necrotic core, lipids, extracellular matrix proteins, lipids, and free cholesterol recognized as clefts) and cellular components dominated by inflammatory cells, smooth muscle cells, and fibrous tissue, which explains the existence of considerable differences in vulnerability between plaques with identical degrees of stenosis. In this context, histopathological assessment of plaque characteristics is one of the “gold standards” used to classify plaques as stable or unstable, first proposed by Lovett et al. in 2004 [22,24].
Although the precise sequence of lesion progression leading to plaque vulnerability is poorly elucidated, the morphological signs of instability as a potential indicator of stroke risk are well known. This hallmark includes a large lipid core, macrophage-mediated inflammatory changes, intraplaque neoangiogenesis/hemorrhage, ulceration, and microcalcification [25]. In this context, histological identification of these signs in endarterectomy specimens may provide valuable data concerning underlying plaque morphologies and should guide the treatment strategy to prevent further cerebral events.
Arterial plaques contain macrophages (MFs) involved in all steps of atherosclerosis. They are influenced by several cytokines and chemokines in the vessel wall and interact with local microenvironmental factors, which drive their differentiation into variable functional phenotypes. MFs can take up oxidized LDL and low-density lipoprotein (LDL)-derived cholesterol as lipid droplets and transform them into foam cells. These are significant players in the initiation and progression of atherosclerosis. The debris of macrophage-derived foam cells provides the major source of the necrotic core in the atherosclerotic plaque [26]. The liponecrotic tissue in atheroma with necrotic core appears to be developed by the structural collapse of the lipid core of atheroma due to the loss of elastic and collagen fibers; MFs are organically involved in this mechanism [27]. Matrix metalloproteinases synthesized by infiltrating macrophages are mainly responsible for their intra-plaque elastolytic and collagenolytic activity. Genetic deficiency of MMP-1a strongly suppresses atherogenesis in the aorta of apo E −/− mice [28]. Interestingly, collagen structure, along with synthesis, degradation, and remodeling of vascular wall elastin, proteoglycans, and glycosaminoglycans, modulate the phenotype of infiltrating inflammatory, but also of the resident cells [29].
In our case, histopathological examination of 119 endarterectomy specimens revealed the presence of a lipid-rich, large necrotic core (Figure 1a) in $58.8\%$ of specimens. This core was associated with an active mononuclear cell component (macrophages and lymphocytes) that surrounded the necrotic core in $63\%$ of cases. In patients without a high inflammatory component in their carotid plaques, the occurrence of cerebrovascular events such as aphasia, hemiparesis, or hemiplegia was significantly lower compared to the INF-positive subgroup. These results suggest that MF-mediated inflammation, initiated by the lipid content, destabilizes atherosclerotic plaques through the degradation of their cross-linked structural proteins. Increases in the size of the necrotic core may happen as a consequence of two factors, MF death, and impaired efferocytosis. In addition, necrosis contributes to forming an inflammatory microenvironment, enhanced oxidative stress, and thrombogenicity [3].
Fissuration and ulceration, landmarks of destabilization, are also the result of MF-released enzymatic activity. Tomas et al., in 159 carotid specimens obtained by endarterectomy, identified an altered metabolomic signature of unstable carotid plaques, comprising increased glycolysis and amino acid utilization along with low fatty-acid oxidation. A series of pro-inflammatory cytokines, like interleukins IL-1b, IL-6, IL-15, IL-17, and IL-18, are abundantly expressed in homogenates of the cluster characterized by the signature mentioned above [25,30]. Chemokines synthesized by MFs, like monocyte chemoattractant protein-1 (MCP-1) and MF inflammatory protein-1b (MIP-1b) were also up-regulated in unstable vs. stable plaques [30].
Our study defines ulceration, thrombosis, and intra-plaque hemorrhage as major morphological manifestations of atherosclerotic plaque vulnerability. Clinical findings support this assumption: the presence of ulceration, as the sole sign, is predictive of neurological symptoms and, together with advanced-grade stenosis, represents a high risk for stroke [31]. Sixty-one subjects were investigated by multi-detector computed tomography, and in 16 ulcerated plaques, no correlation was observed with the plaque volume. In contrast, ulcerative lesions were strongly associated with the presence of a lipid-rich content [31].
In univariate logistic regression models, we observed that the sizeable necrotic lipid core, but not hypercholesterolemia, was significantly associated with ulceration. However, this association was abolished in a multiple logistic regression model focused on ulceration, inflammation, revascularization and the lipid core. Regarding the infiltrating inflammatory elements of the atherosclerotic plaques and the circulating neutrophil count, or neutrophil/lymphocyte ratio, no correlation was found, even though several studies report higher neutrophil counts along the presence of microemboli detected by transcranial Doppler ultrasound in symptomatic patients [32]. Instead, the presence of the inflammatory cellular infiltrate, consisting predominantly of MFs, and microcalcification proved to be the strongest predictors of ulceration, which remained significant after adjustments for the stenosis grade, the presence of the lipid core, and superficial layer calcification. Further, ulceration and the inflammatory infiltrate, but not calcification extent or pattern, were defined as significant determinants of atherothrombosis, another important sign of plaque vulnerability.
An MF-rich inflammatory infiltrate was present in almost $\frac{2}{3}$ of cases, so we investigated its histological correlates and compared it in INF+ and INF– groups. We showed that there were no essential differences between these groups in terms of the incidence of diabetes, hypertension, bilateral carotid involvement, or previous stroke history. In contrast, atheroma calcification patterns and location showed a significantly biased distribution of microcalcification and superficial calcification in favor of the INF+ group. Even though the effect of calcification is considered biphasic, from pro-inflammatory properties of “microcalcification” to anti-inflammatory properties of “macrocalcification,” in our study, the distribution of extended/confluent pattern was almost twice less frequent in the case of the INF+ group (See Table 1). This result may suggest that extensive calcification, even if not a direct predictor of plaque ulceration and thrombosis, is less associated with inflammation and intra-plaque hemorrhage and might be considered a sign of plaque stability.
As reported in the literature, the calcification of atheromatous plaque is a remarkable feature of advanced atherosclerosis. It is triggered by inflammation, emerges as microcalcification, and develops through a spectrum of events to macrocalcification, with the formation of bone-like structures within the plaque. The release of matrix vesicles from macrophages and the death of VSMC initiates the calcification process of the plaque. Other factors are also involved in the process, including reduced levels of mineralization inhibitors or increased osteogenic transdifferentiation (VSMC pericytes) [3]. In our study, a part of the plaques showed mixed calcification patterns, containing foci with both microcalcification and different types of macrocalcification. In this case, the dominant patterns were considered, and for macrocalcification, cumulative patterns also were investigated. Our results demonstrated the presence of ulceration and intra-plaque hemorrhage in a significantly higher proportion of plaques with microcalcification. Furthermore, they showed dominance in plaques with superficial layer calcification compared to those with deep layer damage. No significant influence of the macrocalcification patterns was observed; no other single calcification parameters or cumulative patterns correlated with the hemorrhagic rupture of the plaque (See Table 2).
The role of calcification in the development of plaque progression is a controversial topic in the literature. The promoting role of microcalcification-induced stress on thin fibrous caps has been demonstrated in plaque rupture both by a three-dimensional blood-vessel modeling [33] and by imaging, histological and morphometric analysis [4,34]. Imagistic studies revealed some interesting aspects of calcification linkage with arterial wall inflammation: higher calcium scores appear along multiple sites in arteries in aging [35]. Carotid artery calcification was investigated in 130 patients included in the dal-PLAQUE study with 18F-labeled fluorodeoxyglucose positron emission tomography and computed tomography at entry and six months. The study revealed a poor overlap between vascular inflammation and calcification on multiple arterial beds. However, those with some calcification content at baseline showed more calcification progression than patients without. These arterial segments with progressive calcification showed a high [18F] FDG-PET signal, which highlights the putative causal role of inflammation in the progression of calcified lesions [35]. Macrocalcification is easily detected and quantified (calcium scores as predictive value for cardiovascular incidence) using the CT scan method. By contrast, microcalcification-the early stage of plaque calcification, is observed only with Positron Emission Tomography (PET)/CT Imaging and Optical Coherence Tomography (diagnostic methods that are not used in daily practice) [36]. However, the CT analysis of calcium subtypes is limited by the resolution and blooming artifacts. In this context, the histopathological examination of the endarterectomy specimens provides helpful information to the clinician to develop a treatment strategy. Molecular imaging of macrophages highlighted enhanced proteolytic activity via matrix metalloproteinases MMP-2, MMP-9, and MMP-13 [37]. MMP-9 is up-regulated by osteopontin, cleaves collagen and elastin substrates in the extracellular matrix, and determines hydroxyapatite crystal deposition [38]. In experimental conditions, the cysteine protease-activatable NIRF-imaging revealed that vascular calcification evolves parallel with bone osteolysis and might be driven by shared inflammatory driver mechanisms [37].
Several cytokine-type soluble regulators were described, which interact with different steps of calcification. For example, osteoprotegerin is elevated in the serum of patients with polyvascular atherosclerotic disease [39,40] and, in animal models, inhibits arterial calcification without affecting the development of the number and volume of atherosclerotic lesions [41]. Another regulator is osteopontin (OPN), a pro-inflammatory glycophosphoprotein involved in bone morphogenesis, a multi-faceted regulator of biomineralization, calcification, and tissue remodeling. Five isoforms of OPN may be expressed due to alternative splicing, which is a possible reason why it shows a diverse linkage with cardiovascular events in the population. OPN increases dramatically in acute stroke, and it is presumed that its early role is protective, attenuates vascular calcification, and promotes post-ischemic neovascularization. Paradigmatically, in chronic inflammatory pathways involving the vessel wall, OPN is probably harmful. It may be expressed in infiltrating macrophages, differentiating myofibroblasts, and endothelial cells of the vessel wall [42]. Wolak T. et al., in a study focusing on carotid atherosclerosis in hypertensive patients, demonstrated that none of the OPN “family members” have anti-inflammatory properties. OPN-N terminal fragment is associated with increased plaque inflammation [43].
In our tissue sections, a rather diverse cell population was stained for OPN. Morphologically, most of the OPN+ cells were macrophage-derived foam cells, VSMCs, and endothelial cells. We found that in our cohort, low-grade OPN expression was significantly associated with the absence of an inflammatory cell infiltrate. Furthermore, microcalcification was significantly correlated with OPN expression. Higher OPN scores were associated with plaque ulceration and the presence of a lipid core, and lower expression was observed in plaques without ulceration. Additionally, low OPN scores were observed in patients with polyvascular disease with three arterial bed involvement. These data converge with those obtained by Strobescu–Ciobanu in a recent study: the authors described in 49 carotid specimens a significant association of higher OPN with ulceration and inflammation of the atherosclerotic lesions [44]. However, no significant association could be defined with calcification; this discrepancy might lie in the applied methodology as calcium content was determined by carotid arteries’ ultrasonography based on plaque echogenicity.
## 5. Limitations
The results from the histological processing of the 119 specimens characterize the CA plaques at a well-determined moment (the occurrence of neurological complications) without the possibility of following the disease progression.
We considered that the semi-quantitative evaluation of plaque complexity accurately characterizes the most important histological features of the plaque and may predict the behavior of the plaque at the time of examination. Although it has been based solely on visual estimation and might have been limited by subjectivity and variability between observers, we chose this method for the properties of the specimens; in contrast to autopsy and experimental study subjects, the fragmented aspect of the specimens does not allow the accurate evaluation of the components and their ratio by morphometric methods. It may have affected our sensitivity to detect relevant associations.
## 6. Conclusions
In a previous morphometric study, we demonstrated that femoral and carotid plaques show different morphology and the tendency for calcification, suggesting that the mechanism is site-specific and vessel wall structure dependent [45]. In the current study, we focused on the carotid plaque’s intimate structure, with a particular emphasis on inflammation, as an important correlate and histological signs of vulnerability: ulceration, atherothrombosis, and hemorrhage.
Our results highlight the following critical issues related to carotid atherosclerotic plaques linked to severe carotid stenosis: [1] considerable differences in vulnerability signs between plaques with identical degrees of stenosis are due to complex morphology and composition; [2] in patients with carotid plaques with low/mild inflammatory components, the occurrence of cerebrovascular events (aphasia, hemiparesis/hemiplegia) is significantly lower compared to those with high degrees of inflammation, suggesting the role of pro-inflammatory MFs in atheroma vulnerability; [3] the presence of the inflammatory infiltrate and of the large necrotic lipid core increase the probability of ulceration; [4] ulceration and intra-plaque hemorrhage have appeared in a significantly higher proportion of specimens with microcalcification and dominated in plaques with superficial layer calcification compared to those with deep layer damage; and [5] our data suggest a potential role for OPN in the development of vulnerability: expression of OPN significantly correlated with microcalcification, and at the same time, higher OPN scores were associated with plaque ulceration and the presence of a sizeable necrotic lipid core.
Based on our results, we hypothesize that the lesions described are characteristic of advanced stages of atherogenesis; clarifying how plaque composition changes from apparent early lesion formation to clinically significant vascular stenosis require further longitudinal, multidisciplinary studies.
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|
---
title: 'The association between comorbidities and self-care of heart failure: a cross-sectional
study'
authors:
- Kyoung Suk Lee
- Debra K. Moser
- Kathleen Dracup
journal: BMC Cardiovascular Disorders
year: 2023
pmcid: PMC10045230
doi: 10.1186/s12872-023-03166-2
license: CC BY 4.0
---
# The association between comorbidities and self-care of heart failure: a cross-sectional study
## Abstract
### Background
Because heart failure (HF) is a debilitating chronic cardiac condition and increases with age, most patients with HF experience a broad range of coexisting chronic morbidities. Comorbidities present challenges for patients with HF to successfully perform self-care, but it is unknown what types and number of comorbidities influence HF patients’ self-care. The purpose of this study was to explore whether the number of cardiovascular and non-cardiovascular conditions are associated with HF self-care.
### Methods
Secondary data analysis was performed with 590 patients with HF. The number of cardiovascular and non-cardiovascular conditions was calculated using the list of conditions in the Charlson Comorbidity Index. Self-care was measured with the European HF self-care behavior scale. Multivariable linear regression was performed to explore the relationship between the types and number of comorbidities and self-care.
### Results
Univariate analysis revealed that a greater number of non-cardiovascular comorbidities was associated with poorer HF self-care(β=-0.103), but not of more cardiovascular comorbidities. In the multivariate analysis, this relationship disappeared after adjusting for covariates. Perceived control and depressive symptoms were associated with HF self-care.
### Conclusion
The significant relationship between the number of non-cardiovascular comorbidities and HF self-care was not independent of perceived control and depressive symptoms. This result suggests a possible mediating effect of perceived control and depressive symptoms on the relationship between HF self-care and the number and type of comorbidities.
## Introduction
Because heart failure (HF) is a debilitating chronic cardiac condition and increases with age, most patients with HF experience a broad range of coexisting chronic morbidities including cardiac and non-cardiac diseases [1–3]. In Tisminetzky and colleagues’ study [2018] with 114,553 community dwellers with HF, patients had six chronic conditions, on average, with $17.4\%$ having nine or more of 26 possible chronic conditions [2]. In their study, the most frequently observed chronic conditions were, in descending order, hypertension, dyslipidemia, visual impairment, and chronic kidney disease.
Self-care is conceptualized as a naturalistic decision-making process to maintain physiological stability, facilitate symptom perception, and take action to improve symptoms when symptoms are changed [4]. However, comorbidities present unique challenges for patients with HF to perform self-care, as they may deal with overlapping symptom profiles between HF and other chronic conditions. For example, shortness of breath and fatigue, typical symptoms of HF, are also common symptoms of chronic obstructive pulmonary disease. Thus, patients with comorbid conditions may find it difficult to interpret their symptom experiences and respond appropriately [5, 6]. Because patients are also asked to simultaneously adhere to multiple self-care regimens for their comorbidities and HF, they need to develop strategies for a variety of therapeutic regimens for multiple conditions. For HF patients with other cardiovascular conditions, adhering to recommended self-care regimens can be relatively uncomplicated because some recommended regimens (e.g., low sodium diet) are common across those conditions. Thus, it may be that engaging HF self-care is less difficulty for HF patients with cardiovascular comorbidities compared to those with non-cardiovascular comorbidities.
Although it is evident that comorbidity complicates HF patients’ self-care, little is known about who may be at risk for poor HF self-care when they also have comorbid conditions. Kerr and colleagues first classified comorbidities in patients with diabetes into “concordant” conditions, which represented condition with an identical overall pathophysiologic risk profiles to diabetes, and “discordant” conditions, which were not directly related to diabetes in either their pathogenesis or management and did not share underlying risk factors (predisposing factors)[7]. They found that types of comorbidities were associated with self-care ability of patients with diabetes in addition to the number of comorbid conditions [7]. Their findings stimulated further research related to comorbidities of diabetes. Similar to the diabetes population, considering the types and number of conditions is also important for patients with HF. Therefore, the purpose of this study was to enhance our understanding of the impact of the number of cardiovascular and non-cardiovascular conditions on HF self-care. We hypothesized that patients with more cardiovascular comorbidities would have better HF self-care than those with fewer cardiovascular comorbidities, and that patients with more non-cardiovascular comorbidities would have poorer HF self-care than those with fewer non-cardiovascular comorbidities.
## Study design and sample
The present study is a secondary analysis of the baseline data in a randomized, clinical trial designed to study the effects of an educational intervention on the prognosis and quality of life for patients with HF who lived in rural areas in the United States from March, 2007 to January, 2013 (www. ClincalTrials.gov-NCT00415545) [8]. Patients were eligible if they were older than 18 years old, and had a confirmed diagnosis of HF, history of hospitalization due to HF within the last six months before enrollment, and intact cognition. Exclusion criteria included having life-threatening comorbid conditions such as active cancer treatment, were non-English speaking, or were living in a nursing home or assisted living facility. The parent study was approved by the Institutional Review Boards of all three participating institutions and conformed to the ethical principles outlined in the Declaration of Helsinki. Participants provided signed, written informed consent. The approval of the secondary data analysis was approved by the Institutional Review Boards at the affiliated institute (IRB # 84922).
## Procedures
The detailed study procedure of the parent study is described elsewhere [8]. After giving written, signed informed consent, patients completed structured questionnaires to gather sociodemographic data and information on self-care, perceived control, and depressive symptoms. Clinical information (e.g., left ventricular ejection fraction) was collected through a medical record review and patient interview. The Charlson Comorbidity Index [9] was used to assess comorbid conditions, and was completed based on patients’ self-report. For the current study, we examined HF self-care of 590 patients who provided data on all of the variables of interest out of 602 patients enrolled in the parent study. There were no significant demographic or clinical differences in patients who were included and those who were excluded in this study.
## Self-care
Self-care was measured with the European HF self-care behavior scale (EHFScB-9) [10]. This scale consists of 9 items, which are rated on a five-point scale from 1 (“completely agree”) to 5 (“do not agree at all”). Total scores can range from 9 to 45, with higher scores indicating poorer self-care. However, for ease of interpretation, a new scoring method was suggested and validated by Vellone and colleagues [2014] [11]. The new scoring method includes standardizing the scores ranging from 0 to 100, with higher scores representing better self-care. The standardized score is computed by subtracting nine from the item total and multiplying by 2.7777 after reverse-scoring. We used the standardized scores of the EHFScB-9.
## Comorbid conditions
Patients’ comorbid condition profiles were expressed as the number of cardiovascular and non-cardiovascular conditions. Medical record reviews were performed to collect the data on comorbid conditions listed in the Charlson Comorbidity Index [9]. However, of the 19 conditions included in Charlson Comorbidity Index, dementia and AIDS/HIV were excluded because dementia was the exclusion criterion of the parent study, and no one reported having AIDS/HIV. A total of 16 conditions were categorized into cardiovascular (4 conditions) and non-cardiovascular (12 conditions) conditions. Cardiovascular conditions included myocardial infarction, peripheral vascular disease, cerebrovascular disease, and hemiplegia. Non-cardiovascular conditions included the following: renal diseases, diabetes with and without end organ damage, chronic pulmonary disease, peptic ulcer, connective tissue diseases, mild liver disease, moderate to severe liver disease, solid tumor with and without metastasis, leukemia, and lymphoma.
On average, patients had two comorbid conditions (SD: 1.45), with a range of 0 to 7 (Table 2). About half of the patients ($49.3\%$) had both cardiovascular and non-cardiovascular comorbid conditions. Of the cardiovascular comorbid conditions, myocardial infarction ($50.5\%$) was most frequently reported, followed by peripheral vascular disease ($32.3\%$), cerebrovascular disease ($14.6\%$), and hemiplegia ($1.2\%$). Of the non-cardiovascular comorbid conditions, frequently reported conditions were chronic pulmonary disease ($33.9\%$), diabetes without end organ damage ($33.1\%$), and peptic ulcer ($14.4\%$).
Table 2Description of the comorbid conditions ($$n = 590$$)TotalNumber of total comorbid conditions, mean (SD)2.1 (1.45)Number of cardiovascular conditions, mean (SD)0.98 (0.87) Myocardial infarction298 ($50.5\%$) Peripheral vascular disease190 ($32.2\%$) Cerebrovascular disease86 ($14.6\%$) Hemiplegia7 ($1.2\%$)Number of non-cardiovascular conditions, mean (SD)1.2 (0.99) Chronic pulmonary disease200 ($33.9\%$) Diabetes without end organ damage195 ($33.1\%$) Peptic ulcer85 ($14.4\%$) Diabetes with end organ damage52 ($8.8\%$) Connective tissue diseases41 ($6.9\%$) Solid tumor without metastasis29 ($4.9\%$) Renal dysfunction27 ($4.6\%$) Mild liver disease13 ($2.2\%$) Lymphoma7 ($1.2\%$) Solid tumor with metastasis7 ($1.2\%$) Moderate to severe liver disease1 ($0.2\%$) Leukemia1 ($0.2\%$)Note. SD = standard deviationValues are n (%), otherwise being indicated
## Perceived control
Perceived control was measured using the 8-item Control Attitudes Scale-Revised [12]. Patients were asked to rate their sense of control over their cardiac problems on a 5-point scale (1 = totally disagree, 5 = totally agree). Total scores range from 8 to 40, with a higher score indicating greater levels of perceived control.
## Depressive symptoms
The Patient Health Questionnaire-9 was used to measure depressive symptoms [13, 14]. The items of this measure correspond to the 9 diagnostic criteria for major depressive disorders in the Diagnostic and Statistical Manual of Mental Disorder IV. Patients were asked to rate each item from 0 (not at all) to 3 (nearly every day) points. Total scores can range from 0 to 27, with higher scores indicating higher levels of depressive symptoms. Scores of 10 or greater indicate a clinically significant levels of depressive symptoms [13].
## Demographic and clinical variables
A self-reported questionnaire was used to collect data on sociodemographic information. The New York Heart Association functional class was determined by trained research nurses based on careful patient interviews. Medical record reviews were also conducted to collect clinical information. Patients’ left ventricular ejection fraction was defined as reduced ($40\%$ or below), mid-range (40–$49\%$), and preserved left ventricular systolic function ($50\%$ or above).
## Statistical analyses
Descriptive statistics were used to summarize the characteristics of our sample. After performing the univariate linear regression, multivariate linear regression was conducted to examine the relationship between the number of cardiovascular and non-cardiovascular comorbid conditions and self-care after adjusting for covariates (i.e., age, gender, race, living arrangement, employment status, education level, etiology of HF, reduced left ventricular systolic function, perceived control, and depressive symptoms).
Three additional analyses were also conducted with the three aims. The first aim was to explore the relationship between HF self-care and the types of comorbid conditions (i.e., cardiovascular and non-cardiovascular comorbid conditions) without considering the number of conditions. For this analysis, patients were grouped as either having or not having cardiovascular and non-cardiovascular comorbid conditions. The second aim was to explore the relationship between HF self-care and the number of comorbid conditions regardless of the types. The third aim was to explore the association between HF self-care and the Charlson Comorbidity Index scores, which are the sum of the weights of each condition. Data were analyzed with IBM SPSS version 25 (IBM Corporation, Armonk, NY). The significance level was set at p-value < 0.05.
## Sample characteristics
A total of 590 patients were included in this study. The average age of the patients was 66 years (SD: 0.31), and more than half of the patients were 65 years or older ($57.0\%$) (Table 1). The majority of the patients were male, white, non-employed or retired, lived with someone, and had less than a high school education level. About one-third of the patients ($35.4\%$) were in New York Heart Association functional class III/IV, and less than a half of the patients ($47.7\%$) had ischemic etiology of HF. Slightly less than one-third of the patients ($30.8\%$) had the Patient Health Questionnaire-9 scores of 10 or above, indicating clinically significant depressive symptoms. The average scores of EHFScB-9 were 69.7 (SD: 19.2).
Table 1Sample characteristics ($$n = 590$$)TotalAge, years66.0 (13.0)Female241 ($40.8\%$)White525 ($89.0\%$)Living alone137 ($23.2\%$)Employed86 ($14.6\%$)High school above education284 ($48.1\%$)New York Heart Association function class III/IV209 ($35.4\%$)Categories of heart failure Reduced ejection fraction (< $40\%$ of LVEF)301 ($51.0\%$) Mid-rage ejection fraction (40–$49\%$ of LVEF)108 ($18.3\%$) Preserved ejection fraction (≥ $50\%$ of LVEF)181 ($30.7\%$)Ischemic etiology of heart failure ($$n = 589$$)281 ($47.7\%$)Medications ($$n = 589$$) ACEI or ARB439 ($74.4\%$) Beta blockers474 ($80.3\%$) Diuretic495 ($83.9\%$)Perceived control29.4 (5.0)Depressive symptoms7.3 (6.4)Self-care69.7 (19.2)Note. LVEF = left ventricular ejection fraction, ACEI = angiotensin-converting enzyme inhibitor, ARB = angiotensin receptor blockerValues are n (%) or mean (Standard deviation)
## Relationship between the comorbid conditions and self-care
In the univariate linear regression model, the number of non-cardiovascular comorbid conditions was statistically significantly associated with self-care, but not the number of cardiovascular comorbid conditions (Table 3). Patients with a greater number of non-cardiovascular comorbid conditions were more likely to have poorer self-care (standardized coefficient: -0.103; $95\%$ confidence interval=-3.593 – -0.405; p-value = 0.014).
Table 3The association between comorbid conditions and heart failure self-care ($$n = 590$$)Bβp-value$95\%$ confidence intervalUnivariate analysis Number of cardiovascular comorbid conditions0.0980.0040.915-1.719, 1.915 Number of non-cardiovascular comorbid conditions-1.999-0.1030.014-3.593, -0.405Multivariate analysis Number of cardiovascular comorbid conditions0.5630.0260.549-1.281, 2.407 Number of non-cardiovascular comorbid conditions-0.992-0.0510.233-2.625, 0.641 Age-0.040-0.0270.543-0.168, 0.088 White-4.822-0.0790.053-9.7, 0.057 Living alone-0.0220.0000.991-3.651, 3.607 Employed-3.323-0.0610.159-7.956, 1.31 High school above education0.0630.0020.968-3.013, 3.14 New York Heart Association functional class III/IV-1.578-0.0390.350-4.895, 1.738 Categories of heart failure Reduced ejection fraction (< $40\%$ of LVEF), reference group1 Mid-rage ejection fraction (40–$49\%$ of LVEF)-2.921-0.0590.169-7.091, 1.249 Preserved ejection fraction (≥ $50\%$ of LVEF)-2.413-0.0580.192-6.042, 1.215 Perceived control0.5570.1460.0010.22, 0.895 Depressive symptoms-0.493-0.165< 0.001-0.767, -0.219Note. LVEF = left ventricular ejection fractionModel p-values for univariate and multivariate models 0.045 and < 0.001, respectively In the multivariate linear regression model, neither the number of cardiovascular nor non-cardiovascular comorbid conditions was statistically significantly associated with self-care after adjusting for covariates. Among the covariates entered in the model, perceived control and depressive symptoms care (standardized coefficient: 0.146 and − 0.165; $95\%$ CI = 0.22–0.895 and − 0.767 – -0.219; p-value = 0.001 and < 0.001 respectively) were statistically significantly associated with HF self-care.
## Additional analyses
In the both univariate and multivariate linear regression models, types of comorbid conditions were not statistically significantly associated with self-care. Identical results were found when the number of total comorbid conditions regardless of their type was entered in the both univariate and multivariate linear regression models. When Charlson Comorbid Index scores were entered to explore the relationship between this score and self-care in the univariate and multivariate linear regression model, self-care was not related to the Charlson Comorbid Index scores.
## Discussion
We explored the relationship between HF self-care and comorbid conditions with the underlying assumption that both the types and the number of comorbid conditions could influence patients’ adherence to HF self-care activities. Our findings showed that a greater number of non-cardiovascular comorbidities was associated with patients’ adherence to HF self-care activities, but not the number of cardiovascular comorbidities. Our assumption was further supported by the results of our additional analyses. Neither the number of total comorbid conditions or the types of comorbid conditions were associated with HF self-care. However, the significant relationship between self-care and the types and number of comorbidities disappeared when the covariates were entered in the model. Our results imply that perceived control and depressive symptoms may be mediators of the relationship between comorbidities and HF self-care.
The presence of multiple comorbid conditions can substantially increase patients’ treatment burden because patients are required to manage a variety of self-care activities for both HF and comorbidities (e.g., medication management, clinic appointments, and lifestyle modifications), reconcile information from multiple clinicians, and monitor and distinguish between HF symptoms and those of other conditions. Several studies have indicated that patients’ day-to-day decisions related to HF self-care are complicated when multiple conditions co-exist with HF, as some comorbid conditions may present competing demands for performing HF self-care activities [6, 15, 16]. Our findings expand previous findings because our study showed the importance of considering the types and number of comorbid conditions in HF self-care, which goes beyond a simple count or burden of comorbidities.
The univariate analysis revealed a significant relationship between the number of non-cardiovascular comorbidities and HF self-care, and the non-significant association between the number of cardiovascular comorbidities and HF self-care. To the best of our knowledge, our study is the first to explore the relationship between self-care and the types and number of comorbid conditions in HF, which makes it difficult to compare our study findings with previous findings. The relationship between individual comorbidities (e.g., peripheral artery disease, diabetes, and renal disease) and self-care has been explored in a limited number of the studies. However, consistent relationships between individual comorbidities and self-care were not found across the studies [17, 18].
Because of the lack of relevant previous studies, it was difficult to interpret our results. However, we may be able to explain the significant association between self-care and the number of non-cardiovascular comorbidities based on three reasons. One reason for this finding could be related to patients’ limited capacity to simultaneously deal with HF and non-cardiovascular conditions. To successfully engage in self-care, patients need a comprehensive understanding of comorbidities and HF. However, because recommended therapeutic regimens for non-cardiovascular conditions can vary widely from that of HF, patients with HF and non-cardiovascular conditions may be confused and have challenges understanding the variety of self-care activities in a coherent manner. For example, in a previous qualitative study, one patient with HF and diabetes did not weigh himself because the patient believed that monitoring weight daily was harmful to losing weight for his diabetes [6].
The second reason may be that patients give lower priority to HF self-care than to self-care for non-cardiovascular comorbidities, although we did not directly ask patients what priority they gave to HF self-care versus their other comorbidities. Patients with diabetes as well as more cardiac comorbidities and discordant comorbidities (conditions that are not directly related to diabetes) were likely to give lower priority to diabetes self-care [7], which is in line with our finding. In a previous review, various internal and external factors were reported to affect the prioritization process [19]. One of the internal factors was how well the disease was controlled, and if well-controlled conditions were given lower priority. Because the majority of our sample was in New York Heart Association functional class I/II, indicating no or mild symptoms that minimally interfered with their daily activities, most patients in our study may have believed that HF was under control so other comorbidities were given higher priority than HF. However, we did not have evidence that non-cardiovascular comorbidities were given higher priority than cardiovascular comorbidities as we did not collect this information.
The last reason may be the fragmented care for patients with multiple chronic conditions. Some comorbidities are addressed in the HF management guidelines (e.g., stroke, diabetes, and kidney diseases) [3, 20, 21]. However, the depth of the recommendations and comorbid conditions included in the guidelines are not consistent, and the AHA/ACC/HFSA guideline for the management of HF noted the difficulty of suggesting specific recommendations for some comorbid conditions, including most non-cardiovascular conditions, due to the lack of current evidence [3]. Therefore, it would be difficult for HF specialists including physicians and nurses to explain HF self-care in relation to patients’ non-cardiovascular comorbidities. Similarly, specialists of other discordant conditions may not address HF and may give conflicting information about HF management and the other conditions.
Although we found a significant association between the number of non-cardiovascular conditions and HF self-care in the univariate regression model, this relationship did not remain when covariates were included in the multivariate regression model. Of the covariates, perceived control and depressive symptoms were significantly related to HF self-care. This result has been consistently reported in numerous HF studies [22–24]. Studies have reported that patients with a greater number of chronic conditions were at risk for lower levels of self-efficacy (which is a related concept to perceived control), and higher levels of depressive symptoms in patients recruited in primary care settings or the community [25–27]. From these findings, we suspect that the relationship between the types and number of comorbidities and HF self-care is mediated by patients’ perceived control and depressive symptoms. However, some investigators have suggested a moderating role of comorbidities on the relationship between HF self-efficacy and HF self-care [6, 28], but the findings in previous studies have been inconsistent. Thus, further research is needed to clarify the role of perceived control (or self-efficacy) and depressive symptoms on the relationship between self-care and comorbidities.
## Limitations
Although this study highlights the importance of considering the types and number of comorbidities when investigating HF self-care, our study has several inherent limitations to be noted by using the existing data. The data collection for comorbidity using the Charlson Comorbidity Index was performed to suite the primary purpose of the original investigators. The list of chronic conditions included in the Charlson Comorbidity Index may not be comprehensive. Although the Charlson Comorbidity *Index is* one of the most popular instruments to measure comorbidities[29] and includes some of the prevalent comorbidities in the HF population [1], the instrument was originally developed to estimate one-year mortality of hospitalized patients and was validated with women receiving treatment for breast cancer [9]. Thus, some authors have raised concerns about using the Charlson Comorbidity Index for this area of research [6]. Our study sample was limited to patients with HF living in rural areas with a majority of white ethnic background, which limits the generalizability of our findings.
## Conclusion
Comorbidities have become increasingly common in patients with HF. Thus, it is important to understand how comorbid conditions influence patients’ decisions about HF self-care. Previous studies have shown that patients with HF and comorbid conditions face challenges with HF self-care because each comorbid condition presents competing demands. Our study expands previous findings. We found that patients with a greater number of non-cardiovascular comorbidities were at risk for poorer HF self-care, but not for those with a greater number of cardiovascular comorbidities. We also found that this significant relationship did not hold when perceived control and depressive symptoms were considered. Our results suggest the potential mediating effect of perceived control and depressive symptoms on the relationship between HF self-care and comorbidities. However, further research is needed to increase our understanding of these relationships. Studies are also needed to examine whether number and types of comorbidities affect changes in self-care to understand the impact of comorbidities on self-care.
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---
title: The Soft Prefabricated Orthopedic Insole Decreases Plantar Pressure during
Uphill Walking with Heavy Load Carriage
authors:
- Hsien-Te Peng
- Li-Wen Liu
- Chiou-Jong Chen
- Zong-Rong Chen
journal: Bioengineering
year: 2023
pmcid: PMC10045236
doi: 10.3390/bioengineering10030353
license: CC BY 4.0
---
# The Soft Prefabricated Orthopedic Insole Decreases Plantar Pressure during Uphill Walking with Heavy Load Carriage
## Abstract
This study aimed to investigate the effect of varying the hardness of prefabricated orthopedic insoles on plantar pressure and muscle fatigue during uphill walking with a heavy backpack. Fifteen healthy male recreational athletes (age: 20.4 ± 1.0 years, height: 176.9 ± 5.7 cm, weight: 76.5 ± 9.0 kg) wore prefabricated orthopedic insoles with foot arch support; a heel cup with medium (MI), hard (HI), and soft (SI) relative hardnesses; and flat insoles (FI). They performed treadmill walking on uphill gradients with 25 kg backpacks. The plantar pressure and surface electromyographic activity were recorded separately, in 30 s and 6 min uphill treadmill walking trials, respectively. The HI, MI, and SI significantly decreased peak plantar pressure in the lateral heel compared to FI. The MI and SI significantly decreased the peak plantar pressure in the fifth metatarsal compared to FI. The MI significantly reduced the pressure–time integral in the lateral heel compared to FI. The HI significantly increased the peak plantar pressure and pressure–time integral in the toes compared to other insoles, and decreased the contact area in the metatarsal compared to SI. In conclusion, a prefabricated orthopedic insole made of soft material at the fore- and rearfoot, with midfoot arch support and a heel cup, may augment the advantages of plantar pressure distribution during uphill weighted walking.
## 1. Introduction
Mountaineering is a popular recreational activity that requires carrying heavy backpacks during long-term uphill walking [1]. The added external load and uphill gradient can increase the stress on the bones, ligaments, and muscles [2]. Therefore, this type of activity has always been highly strenuous and fatiguing for mountain climbers. It also induces biomechanical changes, including increased-propulsion vertical and anterior ground reaction force [1], increased frontal ankle range of motion [1], increased plantar pressure [3,4], and increased low-limb muscle activity [2]. These biomechanical changes cause a potential risk for metatarsal stress fractures [4], blister development [1,5], ankle sprain [1], and muscle fatigue [2]. These risks of injury suggest that neuromuscular and skeletal systems are unable to accommodate the demands of load carriage during uphill walking.
Injuries to the foot are commonly prevented using prefabricated orthopedic insoles, which are inexpensive and convenient [5,6]. Prefabricated orthopedic insoles are generally designed based on features and characteristics including arch support, heel cups, and cushion properties [7,8]. Two studies have shown a decrease in plantar pressure and the risk of foot injury using these devices while carrying a heavy backpack during level walking [5,9]. Peduzzi de Castro, Abreu, Pinto, Santos, Machado, Vaz, and Vilas-Boas [9] designed a plantar pressure relief insole and found that it was effective in reducing foot plantar pressure in the little toes (second to fifth toe), medial midfoot, lateral midfoot, and forefoot. Melia, Siegkas, Levick, and Apps [5] reported that a soft orthopedic insole attenuated plantar pressure of the lateral and medial forefoot and increased the contact area over the whole foot. However, to date, there appears to be a gap in the literature regarding the effect of prefabricated orthopedic insoles on plantar pressure during uphill walking while carrying a heavy backpack.
A previous study found that the muscle activity of the erector spinae, vastus medialis, soleus, and gastrocnemius increased when carrying a load during uphill walking compared with unloading during level walking [2]. The author suggests that muscles require more effort to overcome external loads and uphill gradients, resulting in muscle overexertion, muscle fatigue, and injury. In addition, muscle fatigue may increase the risk of falls and endanger the lives of mountain climbers. Therefore, resisting muscle fatigue and assisting in improving the biomechanical efficiency of walking are critical issues. Previous studies have found that a custom-made orthopedic insole could decrease muscle fatigue during level walking [10], which is associated with improving the mechanical energy that is stored and returned at each step [11]. However, it is unclear whether prefabricated orthopedic insoles help with resistance muscle fatigue while carrying a load during uphill walking.
Prefabricated orthopedic insoles are made of varying materials which induce different biomechanical effects. The stiff orthopedic insole slightly deforms when bearing weight, which results in less impact attenuation and greater plantar pressure; however, a method to control abnormal foot motion is better, such as overpronation of the foot [12,13,14]. Conversely, the soft orthopedic insole can fit the geometrical shape of the plantar because of the characteristics of the material, which is likely to contribute to attenuating impact and foot pressure [5,12,15]. This hypothesis was confirmed by Melia, Siegkas, Levick, and Apps [5], who found that low-density shoe insoles (soft) were better at decreasing plantar pressure than high-density shoe insoles (hard), as they produced more contact area under the whole foot. However, overdeformation of the insole occurs if the material of the insole is too soft, which negatively influences the impact absorption and plantar pressure attenuation [5]. Therefore, the effect of carrying a heavy backpack during uphill walking while wearing prefabricated orthopedic insoles with different hardness values should be considered, because this issue is critical to developing an appropriate prefabricated orthopedic insole for mountaineering activity.
This study aimed to investigate the effect of varying the hardness of a prefabricated orthopedic insole on plantar pressure and muscle fatigue during uphill walking while carrying a heavily loaded backpack. It was hypothesized that a soft prefabricated orthopedic insole may decrease plantar pressure and muscle fatigue.
## 2.1. Subjects
The institutional review board of the Jianan Psychiatric Center, Ministry of Health and Welfare (IRB No. 21-027) approved all experimental procedures for this study. Fifteen healthy male recreational athletes participated in this study (Table 1). The inclusion criteria were that they had practiced back squats with a loaded barbell (greater than 15 kg) or had participated in heavy-loaded carriage (greater than 15 kg) trail walking. Exclusion criteria were a history of asthma, heart disease, or hypertension; any physical illnesses; an injury to the upper or lower limbs within the experimental period; or an injury 6 months prior to the experiment. A priori sample size calculation was performed using a free online tool, G*Power (www.gpower.hhu.de accessed on 1 April 2021), with a power level of $80\%$ and an α level of 0.05 [16]. The expected effect size was calculated using the means (294.1 and 407.7) and standard deviations (172.0 and 250.0) of the average contact pressure of the hallux during uphill walking [7]. This revealed that a sample size of 13 participants would be sufficient for the analysis. All subjects were required to read and sign an informed consent form prior to the experiment.
## 2.2. Insoles
The prefabricated insoles of flat and thin shoes (FI) were used as a control group. Three commercially available prefabricated insoles with medium, hard, and soft relative hardnesses (MI, HI, and SI, respectively) were selected as the experimental groups in this study (Figure 1). These prefabricated orthopedic insoles had the same features as foot arch support and heel cups. The hardness of the prefabricated orthopedic insole was examined in the forefoot, mid-foot, and rear foot areas using a hardness tester (Figure 1) (Teclock GS-709N Type A, Teclock Co., Nagano, Japan). Both hands held the hardness tester and pushed down vertically at the selective area five times during the hardness testing [7].
## 2.3. Experimental Protocol
Participants visited the laboratory 1 day before the experimental session for familiarization and anthropometric measurements. Anthropometric data for each participant, including height, weight, foot type, foot length, and leg type, were collected by the same tester. Foot type was calculated using the Chippaux and Smirak index (CSI) [17,18,19,20], and leg type (knock knee, bow knee, or normal knee) was examined by subjective judgment [21].
This was a randomized single-blind study. The participants completed the experimental sessions in 1 day. At the start of the experimental session, participants were informed to wear the same brand of socks (Footdisc, Inc., Taipei, Taiwan) and shoes (Maximizer16, Mizuno Inc., Taipei, Taiwan) to prevent sock and shoe characteristics from influencing the results. They performed a warm-up consisting of 5 min of dynamic and static stretches and 5 min of riding a stationary bike at a selected speed. After the warm-up, all participants performed 4 uphill walking trials in 4 prefabricated orthopedic insole conditions while carrying a pack frame of 25 kg [22,23], with 15 min of static rest between trials. All trials were performed on a treadmill (NordicTrack X7i, Sydney, Australia) at the same speed and gradient (2.57 km/h and $24\%$ gradient). Each trial was divided into two parts. The first consisted of collecting plantar pressure data for 30 s; the second of collecting surface electromyography data (EMG) for 6 min.
Plantar pressure data were collected at 100 Hz using the Tekscan system (Wireless Tekscan Device, Boston, MA, USA) and analyzed using the F-Scan software (F-Scan Research 4.5) [9,24,25,26]. The footprint was divided into 13 plantar foot regions to analyze the plantar pressure data. The following variables were analyzed for the 13 plantar foot regions of the dominant leg: peak pressure, pressure–time integral, and contact area. The outcome of these variables was the mean of a complete gait cycle, excluding the first and last step of the 30 s plantar pressure data collection trial. The dominant leg was defined as the leg regularly used to kick a ball [27,28,29,30,31,32].
The EMG was recorded at 2000 Hz using wireless surface electromyography (Trigno, Delsys Inc., Boston, MA, USA) [33,34,35,36,37] from the following muscles of the dominant leg: rectus femoris, tibialis anterior, biceps femoris, and gastrocnemius. Before sensor attachment, the hair on the skin’s surface was shaved using a razor and wiped with alcohol. Four electrodes were affixed using kinesiology tape to the selected muscle areas. Raw EMG data were band-pass filtered from 20 to 450 Hz using a fourth-order zero-lag Butterworth filter. To examine the fatigue effect, the raw EMG data were clipped in the first 1 min as pre-fatigue data and in the last 1 min as post-fatigue data. Fast Fourier Transformation of the raw EMG data was used to calculate the power spectral density (PSD). The PSD was set as follows: window length (0.125 s); window type (Hanning); window overlap (0.0625 s). The median frequency (MF) was calculated using Equation [1]. The participant wearing the control insole performed 1 min of uphill walking (no external load), which was used to normalize the MF data to be expressed as a percentage [38,39]. [ 1]MF=∫0MFPSDfdf=∫MF∞PSDfdf=12∫0∞PSDfdf MF: median frequency; PSD: power spectral density.
## 2.4. Statistics
All statistical analyses were performed using the SPSS version 18.0 software (SPSS Science Inc., Chicago, IL, USA). Descriptive statistics (mean ± SD) are presented for all outcome measurements. To assess differences between the four prefabricated orthopedic insole conditions in plantar pressure and hardness of the insole, one-way repeated measures ANOVA, followed by Bonferroni’s post hoc test (p ≤ 0.05), were performed. A two-way ANOVA (insole condition × pre- and post-fatigue) was performed on the MF of the four muscles. A post hoc test was conducted using the Bonferroni test (p ≤ 0.05). The effect size (ES) was calculated using partial eta squared (η2). The partial eta squared was considered the η2 of 0.01 small, 0.06 medium, and above 0.14 large [9,40,41,42,43,44]. Statistical power was calculated using SPSS software.
## 3.1. Hardness of Insole
The hardness values of the insoles are presented in Table 2. The HI was the stiffest, and the SI the softest insole compared with the rest of the insoles in the forefoot, mid-foot, and rear-foot regions. The MI presented greater hardness in the mid-foot and lower hardness in the forefoot and the rear foot than FI.
## 3.2. Peak Plantar Pressure
The peak plantar pressure data for the subject’s dominant leg are presented in Table 3. The HI presented greater peak plantar pressure in the hallux, second, third, fourth, and fifth toes than the other insoles, and showed greater peak plantar pressure in the mid-foot than the SI. The FI presented greater peak plantar pressure in the fifth metatarsal than the MI and SI, and presented greater peak plantar pressure in the lateral heel than the other insoles.
## 3.3. Pressure–Time Integral
The pressure–time integral data of the subject’s dominant leg are presented in Table 4. The HI presented a greater pressure–time integral in the hallux, third, fourth, and fifth toes than the other insoles, and presented a greater pressure–time integral in the second toe than the MI and SI. The FI presented a greater pressure–time integral in the lateral heel compared to the MI.
## 3.4. Contact Area
The contact area data for the dominant leg of the subject are presented in Table 5. The SI had a greater contact area in the first, second, third, and fourth metatarsals than the HI. The HI had a greater contact area in the hallux than FI.
## 3.5. Median Frequency of EMG
The median frequency of the EMG data of the subject’s dominant leg is presented in Table 6. A significant main effect of pre- and post-fatigue was noted on the tibialis anterior ($$p \leq 0.003$$, ES = 0.474, power = 0.910). Post-fatigue presented a lower median frequency of EMG than pre-fatigue in all insoles.
## 4. Discussion
The major findings of the current study were that both MI and SI, with lower hardness values in the fore- and rear-foot regions, significantly reduced the peak plantar pressure in the fifth metatarsal and lateral heel, and MI significantly reduced the pressure–time integral in the lateral heel compared with FI. The HI, with the hardest hardness in the fore-, mid-, and rear-foot regions, significantly increased the peak plantar pressure and pressure–time integral in the toes, but decreased the contact area in the metatarsal compared with the other insoles with lower hardness values. The MI, HI, and SI, which were prefabricated orthopedic insoles with foot arch support and heel cups, significantly decreased the peak plantar pressure in the lateral heel compared with the FI. No difference was found among all insoles in terms of reducing muscle fatigue. Thus, these results partially support our hypothesis that the soft prefabricated orthopedic insole decreases plantar pressure, but cannot reduce muscle fatigue.
Previous studies have indicated that soft orthopedic insoles could contribute to reducing plantar pressure during loading gait and level walking [5]. The results of this study further confirmed that soft, prefabricated orthopedic insoles can reduce plantar pressure, specifically in the fore- and rear-foot regions, during loading gait and uphill walking. Based on the obtained plantar pressure data, Peduzzi de Castro, Abreu, Pinto, Santos, Machado, Vaz, and Vilas-Boas [9] used finite element analysis to develop insoles for obese and weight-bearing individuals, and found that insoles configured with soft cork gel in the forefoot and heel can redistribute the plantar pressure in these areas. For example, the pressure of the rearfoot of the weight-bearing person is transferred from the lateral to the medial heel, and the pressure of the forefoot and the lateral mid-foot of an obese person is decreased. The relatively reduced plantar pressures observed in the toes and forefoot during weight-bearing walking may decrease the risk of foot blisters [25,45], metatarsalgia, and stress fractures in these foot regions [46], as well as plantar fasciitis [47]. Nevertheless, softer is not always better, as the MI significantly reduced the pressure–time integral in the lateral heel, but the SI did not. The MI showed greater hardness in the fore- and midfoot regions than the SI did. This could partly contribute to the stiff arch support of the midfoot MI.
Wearing MI, HI, and SI was shown to decrease peak plantar pressure in the lateral heel compared with FI during weight-bearing uphill walking in this study. The prefabricated orthopedic insoles used herein featured arch support and deep heel cups. Previous research has shown that a flat foot wearing a custom-made arch support insole can reduce the average pressure and peak pressure in the rearfoot by $9.6\%$ and $17\%$, respectively [48], which is similar to the results of a study that achieved reduced peak pressure in the rear foot. The outcome of the current study was not in accordance with previous studies reporting that orthopedic insoles cannot decrease plantar pressure in the rearfoot during weight-bearing level walking [5,9]. This could be attributed mainly to the different features, such as the presence of arch support and deep or shallow heel cups of the orthopedic insoles, rather than the hardness of the insoles.
This study demonstrated that the SI showed a greater contact area in the metatarsal compared with the HI during weight-bearing uphill walking. Previous research has indicated that insoles with high hardness values are mainly used for foot realignment, while insoles with low hardness values are mainly used for foot shock absorption [49]. Low-density materials can easily reduce peak plantar pressure, and their soft and compliant properties allow the foot to better adapt to the load on the plantar geometry and produce a more uniform pressure distribution [50]. The use of insoles can increase the contact area and reduce the peak pressure on the foot [51]. The SI, with soft material in the forefoot, was considered to fit the geometry of the metatarsal, causing uniform pressure distribution. Moreover, the increased contact area was subjectively considered to increase the comfort of the insoles [5].
This study found that tibialis anterior fatigue significantly increased after weight-bearing uphill walking in all insoles. This result is consistent with those of previous studies [39,52]. Previous studies have indicated that the tibialis anterior can ensure adequate space between the foot and ground during the swing phase; correctly align ankle and calcaneus at initial heel contact; and eccentrically drop the mid- and forefoot to the ground during the stance phase, thus avoiding tumbling and falling during weight-bearing uphill walking [39]. Moreover, there was a trend toward decreased tibialis anterior fatigue in the MI ($1.87\%$) after weight-bearing uphill walking compared with the HI, SI, and FI ($2.58\%$, $4.12\%$, and $6.99\%$, respectively). The slight decrease in tibialis anterior fatigue while wearing the MI may imply that there is a decreased demand for absorption of impact forces of the muscles of the hip and knee [39].
The current study had some limitations. This study was a short-term test and was only performed on a treadmill indoors, which may not be sufficiently similar to the outdoor environment. A pack frame with only one loading weight (25 kg) was used, and the results may not be applicable to other weights. Nonetheless, all participants’ perceptions of effort in carrying out the tests using a 25 kg load reached the hard/heavy level on the Borg rating of perceived exertion scale (15.4 ± 0.6). The subjects were healthy male recreational athletes; thus, the results may not apply to other populations.
## 5. Conclusions
The prefabricated orthopedic insoles with lower hardness values demonstrated benefits in the form of decreased plantar pressure at the toes, fifth metatarsal, and lateral heel, as well as increased contact area at the metatarsal during uphill walking while carrying a heavily loaded backpack. However, the prefabricated orthopedic insole was unable to significantly decrease muscle fatigue. It was suggested that the prefabricated orthopedic insole made of soft material at the fore- and rearfoot with midfoot arch support and heel cups may augment the advantages of plantar pressure distribution during uphill walking with a heavy load. These results recommend that mountain climbers wear prefabricated orthopedic insole with lower hardness values during mountaineering when carrying a heavily loaded backpack, as this will decrease the risk of foot injuries, including metatarsal stress fractures, blister development, and sprained ankles.
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|
---
title: 'Many Facets of Eating Disorders: Profiling Key Psychological Features of Anorexia
Nervosa and Binge Eating Disorder'
authors:
- Alessandro Alberto Rossi
- Giada Pietrabissa
- Andrea Tagliagambe
- Anna Scuderi
- Lorenzo Montecchiani
- Gianluca Castelnuovo
- Stefania Mannarini
- Laura Dalla Ragione
journal: Behavioral Sciences
year: 2023
pmcid: PMC10045239
doi: 10.3390/bs13030276
license: CC BY 4.0
---
# Many Facets of Eating Disorders: Profiling Key Psychological Features of Anorexia Nervosa and Binge Eating Disorder
## Abstract
Objective. The present study employs a profile analysis to identify and compare psychological features and core eating disorder (ED) symptoms in clinical samples of patients with anorexia nervosa (AN) and binge eating disorder (BED) and the general population (GP). Methods. A sample comprising 421 participants (142 patients with AN; 139 patients with BED; and 140 participants from the GP) was surveyed with the Eating Disorder Inventory-3 (EDI-3). Individuals with AN and BED were recruited and tested during their first week of a multidisciplinary inpatient program for weight loss and rehabilitation at the ‘Rete DCA USL Umbria 1′ (Eating Disorders Services), Italy. Results. The findings suggest distinct patterns of symptom presentation between the three samples across all the EDI-3 dimensions—with both the AN and BED groups scoring significantly higher than the GP. Patients with AN registered greater scores in all the psychological trait scales and the drive for thinness ED-specific dimension of the EDI-3 compared with their BED counterpart—which, instead, scored higher in the bulimia and body dissatisfaction subscales. These data support the transdiagnostic nature of the main risk factors for the onset and maintenance of EDs—which would vary in severity levels—and the existence of disease-specific pathways giving rise to AN and BED. Conclusion. This study for the first time compares patients with AN and BED with a non-clinical sample on main ED psychological features. This might inform classification approaches and could have important implications for the development of prevention and early intervention programs.
## 1. Introduction
Feeding and eating disorders (EDs) are mental health conditions characterized by abnormal patterns of eating behavior and negative thoughts and feelings about food and one’s body [1].
International epidemiological research in Western countries indicated a lifetime prevalence of EDs as follows: anorexia nervosa (AN) at $0.16\%$; bulimia nervosa (BN) at $0.63\%$; and binge eating disorder (BED) at $1.53\%$ [2,3].
AN is characterized by an intense fear of gaining weight or becoming fat and distorted perceptions of weight or body shape, which motivates severe dietary restriction or other weight-loss conducts despite starvation (i.e., purging, fasting, or over-exercising) leading to abnormally low body weight [1]. BN is marked by distorted body image and an obsessive desire to lose weight, in which uncontrolled episodes of overeating are followed by self-induced vomiting, misuse of laxatives, and other methods designed to compensate for the effects of binge eating. Similarly, people with BED consume large amounts of food and feel unable to stop eating but in absence of compensatory behaviors. This commonly leads the persons to experience negative emotions—including guilt, shame, or depression—and to gain weight as a result of restrained eating because of over-compensatory overeating during lapses [4,5].
Despite the diagnostic need to define the various manifestations of dysfunctional eating behaviors as discrete categories that are qualitatively different from one another, taxonometric research—designed to classify the latent structure of phenomena—showed that changes in eating behavior designed to control body weight are often observed to varying degrees in all individuals. It also documented that EDs hallmarks can manifest themselves across different diagnoses rather than only in distinct categories [6,7,8].
Still, the existence of a dimensional latent structure of EDs had already been proposed in earlier research using discriminant function analysis [9], and, more recently, a meta-analysis conducted by Markon et al. [ 2011] found adequate empirical and theoretical evidence sustaining that a dimensional view of psychopathology is more reliable and valid than a categorical one [10].
Indeed, longitudinal studies showed that individuals with an ED might move between diagnostic states over time.
For example, Tozzi et al. [ 2005] showed that 32 out of 88 individuals diagnosed with a restricting-type AN developed BN—$91\%$ of which within the first 5 years. Additionally, in a sample of 350 subjects with BN, $27\%$ developed AN, binge-eating/purging type—$77\%$ of which within the first 5 years [11]. Similarly, a subsequent investigation found that most women diagnosed with AN experienced diagnostic crossover to BN: during 7 years, over half of them oscillated between the restricting and binge eating/purging AN subtypes; one-third crossed over to BN [12].
Furthermore, in a study examining the course of the full range of EDs across 3 time points over 30 months was observed that only one-third of a total sample of 192 women (55 with AN, 108 with BN, and 29 suffering from an eating disorder not otherwise specified) retained their original diagnosis [13]. Diagnostic instability also characterized a large clinical sample of patients with various EDs ($$n = 793$$) whose symptomatologic course was evaluated in a 6-year follow-up study. The presence of mood disorders was found to be a significant cause of crossover between the diagnoses, and shape concern severity was a significant modifier outcome [14].
Taken together, these findings suggest that EDs may not be distinct but are rather overlapping and interrelated, and that common processes might be involved in their etiopathogenesis and persistence over time.
This is in line with the transdiagnostic conceptualization of EDs [15], according to which four core maintaining mechanisms would operate across all EDs diagnostic categories. These include [1] extreme perfectionism, defined as the over-evaluation of the striving for and achievement of personally demanding standards despite adverse consequences; [2] the difficulty of coping with intense mood states; [3] the impact of low self-esteem that motivates individuals to pursue achievement in the valued domain of weight and shape control to increase feelings of self-worth; and [4] marked interpersonal difficulties, which may lead to increased dietary restraint to control weight and shape and achieve the perceived socially valued ideal. The transdiagnostic theory has received empirical support [16,17,18]. Additionally, Olatunji, Kim, and Wall [2015] [19] proposed an important extension of this model by recognizing body thinness, body perfectionism, and body awareness as common symptom dimensions across diagnostic categories.
Focusing on common symptom dimensions across eating disorder diagnoses, rather than specific diagnoses, could advance current knowledge on mechanisms of etiology and maintenance of EDs. It would also help to improve their treatment and to inform the selection of more reliable and valid symptom measures [20,21].
Given these considerations, the present study made use of a profile analysis to compare symptoms and psychological features of EDs between two clinical samples of inpatients with AN and BED and the general population.
Indeed, while several studies assessed and compared samples of patients with AN and BN [12,22,23,24,25] or BN and BED presentations [26,27,28,29,30,31,32,33], no research to our knowledge has yet compared psychological features of individuals diagnosed with AN with those presenting BED psychopathology [34]. Further, studies have also been usually conducted on clinical samples and do not, therefore, provide rigorous empirical comparisons of psychological characteristics between individuals with an ED and a community sample.
To extend research on EDs, the current study for the first time provides a direct assessment and comparison of the Eating Disorder Inventory-3 (EDI-3) dimensions between inpatients with AN and BED and respondents from the general population to identify distinct patterns of symptom profiles that may inform the development of early intervention programs.
## 2. Methods
A cross-sectional design has been employed for this study.
## 2.1. Procedures
A survey containing a socio-demographic report form and the EDI-3 was administered to each participant.
Individuals with AN and BED were recruited at the ‘Rete DCA USL Umbria 1′ (Eating Disorders Services), Italy, during the first week of a multidisciplinary inpatient program for weight and psychological rehabilitation. The survey was administered individually in a dedicated room by a clinical psychologist working in the clinic and independent of the study as part of the routine clinical assessment.
In line with previous studies [35,36], participants from the GP were enrolled using the snowball sampling technique, personal invitations, and advertisements placed in the Universities of Padua and Milan, cafés, and libraries.
Each participant voluntarily agreed to participate in the study and signed the written informed consent.
The research project was previously approved by the Ethics Committee of the Azienda Ospedaliera di Perugia (CER Umbria): protocol n°: $\frac{22877}{21}$/ON.
## 2.2. Sample Size Determination
The minimum sample size required for this study was computed a priori by using the G*Power software [37]. Given the main analysis of the study (see dedicated section), the multivariate analysis family of statistics was chosen—specifying 3 independent groups of patients (AN vs. BED vs. GP) and 12 different psychological scales as response variables (see ‘instruments’ section) [38,39,40,41,42]. According to guidelines [43], a priori statistics were set to small values (small effects): Pillai’s trace (V) was set to 0.2 (effects provide a minimum contribution [44])—resulting in a small effect size: f2(V) = 0.11 [43,45]. Additionally, according to general guidelines [43], the Type I error (α) rate was set at 0.05 (two-sided), and the Power (1—β) was set at 0.95. Results showed that there is more than a $95\%$ chance of correctly rejecting the null hypothesis of no significant effect of the interaction with an overall sample of 159 subjects—53 participants per group.
## 2.3. Participants
Patients referring to the ‘Rete DCA USL Umbria 1′ (Eating Disorders Services), Italy, were consecutively recruited and screened for admission into the study within the first week of a multidisciplinary inpatient program for weight and psychological rehabilitation.
Inclusion criteria were [1] being a native Italian speaker; [2] being 18 years or older; [3] being diagnosed with an ED (AN or BED) within the last 6 months according to the DSM-5 criteria [1,45] by clinical professionals; and [4] providing signed informed consent.
Unlike the clinical sample, participants enrolled from the general population (GP) were required to have never been diagnosed with an ED (AN, BED, BN, etc.).
Participants were excluded from the study if [1] unable to complete the assessment procedure due to cognitive or vision impairments and/or illiteracy; [2] provided missing data responses.
## 2.4. Measures
Demographics and clinical information included age, gender, weight (in kg), height (in meters)—used to calculate the individuals’ body mass index (BMI), familiarity with EDs, previous psychological treatments, and previous hospitalizations for EDs, Moreover, the Italian version of the Eating Disorder Inventory-3 (EDI-3) was administered to the participants in the study. The EDI-3 is one of the most used self-report questionnaires for a clinical evaluation of the presence and intensity of psychological traits and symptomatology associated with EDs [20,21]. The EDI-3 is composed of 91 items rated on a six-point Likert scale ranging from A (=“always”) to F (=“never”). Higher scores reflect higher levels of the specific measured construct. The EDI-3 is organized into 12 primary scales, consisting of 3 eating disorder-specific scales (Drive for Thinness—DT; Bulimia—B; and Body Dissatisfaction—BD) and 9 general psychological scales that are highly relevant to but not specific to EDs (Low Self-Esteem—LSE; Personal Alienation—PA; Interpersonal Insecurity—II; Interpersonal Alienation—IA; Interoceptive Deficits—ID; Emotional Dysregulation—ED; Perfectionism—P; Asceticism—A; Maturity Fears—MF). These 12 scales yield 6 composite scores: 1 specific Eating Concerns Composite (ECC) and 5 general integrative psychological constructs (Ineffectiveness Composite—IC; Interpersonal Problems Composite—IPC; Affective Problems Composite—APC; Overcontrol Composite—OC; and Global Psychological Maladjustment—GPM). In this study, the 12 primary scales were considered.
## 2.4.1. Drive for Thinness (DT)
Drive for thinness (DT) is one of the main features of ED—especially for AN and BN but also for BED—and it has been considered an essential criterion for a diagnosis of EDs. The DT scale assesses an extreme desire to be thinner, concern with dieting, preoccupation with weight, and an intense fear of weight gain. The DT scale is composed of seven items. In this study, the DT scale showed good internal consistency: Cronbach’s alpha = 0.915; McDonald’s omega = 0.917.
## 2.4.2. Bulimia (B)
The Bulimia (B) scale evaluates the predisposition to think about and engage in binge eating episodes. The B scale assesses worries about overeating and eating in response to being emotionally upset. The tendency to engage in uncontrollable overeating is common in individuals with a diagnosis of BED and BN, but it is also recurrent (but less severe) in individuals who do not meet the criteria for a diagnosis of an ED. The B scale is composed of eight items. In this study, the B scale showed good internal consistency: Cronbach’s alpha = 0.873; McDonald’s omega = 0.878.
## 2.4.3. Body Dissatisfaction (BD)
The Body Dissatisfaction (BD) scale measures discontent with both the shape and the size of those regions of the body such as thighs, hips, stomach, etc. Even in this case, body dissatisfaction is common in individuals with a diagnosis of ED but it is also frequent (but less severe) in individuals who do not meet the criteria for a diagnosis of an ED. The B scale is composed of 10 items. In this study, the BD scale showed good internal consistency: Cronbach’s alpha = 0.861; McDonald’s omega = 0.864.
## 2.4.4. Low Self-Esteem (LSE)
The Low Self-Esteem (LSE) scale assesses self-devaluation (namely, negative self-evaluation), which has a major role in the development and maintenance of EDs. The LSE scale evaluates feelings of insecurity, inadequacy, ineffectiveness, and lack of personal worth. The LSE scale is composed of six items. In this study, the LSE scale showed good internal consistency: Cronbach’s alpha = 0.907; McDonald’s omega = 0.910.
## 2.4.5. Personal Alienation (PA)
The Personal Alienation (PA) scale assesses a pervasive sense of poor self-understanding, emotional emptiness, and solitude. Moreover, the PA scale evaluates the desire to be someone else and the feeling of being out of control of things in one’s own life. The PA scale is composed of seven items. In this study, the PA scale showed good internal consistency: Cronbach’s alpha = 0.844; McDonald’s omega = 0.846.
## 2.4.6. Interpersonal Insecurity (II)
The Interpersonal Insecurity (II) scale evaluates embarrassment, uneasiness, and reticence in social situations—focusing on difficulties expressing personal thoughts and feelings in a social context as well as the tendency to withdraw and isolate from others. The II scale is composed of seven items. In this study, the II scale showed good internal consistency: Cronbach’s alpha = 0.834; McDonald’s omega = 0.838.
## 2.4.7. Interpersonal Alienation (IA)
The Interpersonal Alienation (IA) scale measures detachment, discontent, estrangement, and lack of trust in others. The IA scale evaluates the propensity to feel imprisoned in relationships as well as the sense that there is a lack of understanding and love from others. The IA scale is composed of seven items. In this study, the IA scale showed good internal consistency: Cronbach’s alpha = 0.769; McDonald’s omega = 0.772.
## 2.4.8. Interoceptive Deficits (ID)
The Interoceptive Deficits (ID) scale assesses two important characteristics of those who develop EDs: (a) the distress triggered by too strong and/or uncontrollable emotions (namely, ‘fear of affect’) and (b) the difficulty in correctly recognizing emotional states (namely, ‘affective confusion’). The ID scale is composed of nine items. In this study, the ID scale showed good internal consistency: Cronbach’s alpha = 0.898; McDonald’s omega = 0.899.
## 2.4.9. Emotional Dysregulation (EmoD)
The Emotional Dysregulation (EmoD) scale measures the propensity to impulsivity, mood instability, anger, self-destructiveness, and recklessness. The predisposition toward reduced impulse regulation and mood intolerance has been identified as poor prognostic signs in EDs. The EmoD scale is composed of eight items. In this study, the EmoD scale showed good internal consistency: Cronbach’s alpha = 0.807; McDonald’s omega = 0.843.
## 2.4.10. Perfectionism (P)
The Perfectionism scale (P) assesses the degree to which an individual gives importance to reaching high standards of personal accomplishment through severe personal standards for performance and/or pressure from parents and teachers. Perfectionism is considered a fundamental feature for the development and maintenance of EDs—mainly for AN. The P scale is composed of six items. In this study, the P scale showed good internal consistency: Cronbach’s alpha = 0.759; McDonald’s omega = 0.733.
## 2.4.11. Asceticism (A)
The Asceticism (A) scale measures the propensity to pursue virtue through the striving for spiritual ideals such as self-discipline, self-denial, self-control, self-sacrifice, and control of bodily impulses. The A scale is composed of seven items. In this study, the A scale showed good internal consistency: Cronbach’s alpha = 0.766; McDonald’s omega = 0.776.
## 2.4.12. Maturity Fears (MF)
The Maturity Fears (MF) evaluates the desire to return to the safety of childhood, avoiding the confusion, conflict, and developmental expectations associated with adulthood—which can stimulate fears related to role changes for which the person feels unprepared. The MF scale is composed of eight items. In this study MF scale showed good internal consistency: Cronbach’s alpha = 0.833; McDonald’s omega = 0.839.
## 2.5. Statistical Analyses
Data analysis was performed by using R software and the following packages: ‘esvis’ [46], ‘ggplot2′ [47], ‘profileR’ [38,48], ‘psych’ [49], and tidyverse [50].
First, according to the guidelines [40], the normality, linearity, multicollinearity, and homogeneity of covariance matrices were inspected.
Second, a profile analysis was performed. Profile analysis (a special case of MANOVA) allows to both determine, quantify, and interpret the extent to which the three groups of individuals (independent variable) revealed different profiles on variables implied in EDs (dependent variables)—quantifying the degree of dissimilarity between profiles [38,48,51,52,53]. According to the guidelines, before performing profile analysis, all dependent variables were rescaled into z-scores [38,40]. Profile analysis is a multivariate approach to test mean differences toward three specific statistics: (I) parallelism; (II) level equality, and (III) flatness [39,40,53,54]. ( I) Parallelism assesses whether the shape of two profiles is analogous and symmetrical (parallel) between different groups—between-subject general statistics. To assess for parallelism, 11 segments were artificially created: [1] DT vs. B; [2] B vs. BD; [3] BD vs. LSE; [4] LSE vs. PA; [5] PA vs. II; [6] II vs. IA; [7] IA vs. ID; [8] ID vs. EmoD; [9] EmoD vs. P; [10] P vs. A; and [11] A vs. MF. Each segment represents the slope of the line among the means of two close variables, and slopes are used to test whether the difference between two segments is the same across groups. Wilks’ lambda (Λ) was chosen to test the multivariate effect. ( II) Level equality refers to the degree of similarity in means of scores across all of the dependent variables across all groups—general between-subject statistic. To test level equality, several focused comparisons between groups were performed [55]. Finally, (III) Flatness aimed to determine whether (within each profile) each variable score yielded a similar response to the following variable—general within-subjects statistic [40]. To test flatness, several focused repeated measures comparisons were also performed for each group to assess within-group effects.
Bonferroni’s correction was applied. Partial eta-square (η2p) and Cohen’s d were used to quantify the difference in multiple and pairwise comparisons, respectively—with the following benchmarks: small (η2p: 0.011 to 0.059; d: 0.20 to 0.49), moderate (η2p: 0.060 to 0.139; d: 0.50 to 0.79), and large (η2p > 0.140; d > 0.80) [40,42].
## 3.1. Sample Characteristics
The final sample comprised 421 participants. Patients with AN were 142 [5 males ($3.5\%$) and 137 females ($96.5\%$)], were aged from 18 to 65 years (mean = 27.96, SD = 10.64), and had a BMI ranging from 11.40 to 18.42 Kg/m2 (mean = 15.21, SD = 1.63). Additionally, $80\%$ of them had no familiarity with a diagnosis of ED and reported no previous treatments or hospitalizations for an ED. Patients with BED were 139 [33 males ($23.7\%$) and 106 females ($76.3\%$)], were aged from 18 to 70 years (mean = 44.65, SD = 15.21), and had a BMI ranging from 23.00 to 71.47 Kg/m2 (mean = 41.54, SD = 9.53). Furthermore, $77.4\%$ of them had no familiarity with a diagnosis of ED, and $80.4\%$ of the respondents reported no previous treatments or hospitalizations for an ED. Participants from the GP were 140 [33 males ($25\%$) and 105 females ($75\%$)], were aged from 18 to 70 years (mean = 42.30, SD = 14.35), and had a BMI ranging from 15.24 to 65.79 Kg/m2 (mean = 23.70, SD = 5.51). None of them had familiarity with a diagnosis of ED, previous treatments, or hospitalizations for an ED.
## 3.2. Preliminary Analyses
First, univariate normality was assessed. As reported in Table 1, the raw score of each dependent variable was almost normally distributed. Second, the linearity of bivariate relationships among dependent variables was observed using a scatter matrix that revealed no curvilinear relationships. Multicollinearity among dependent variables was assessed using Pearson’s bivariate correlation coefficients, tolerance, and variance inflation factor (VIF) statistics—which revealed the absence of multicollinearity (Table 1). Finally, the homogeneity of variance–covariance matrices was tested through the Box’s M test—which resulted to be statistically significant ($M = 466.788$, $F = 2.873$, $p \leq 0.001$); however, it should be noted that this statistic is overpowered when groups have equal size—as in this case [40]. Thus, considering these results, a profile analysis was performed [40,55].
## 3.3. Profile Analysis: Parallelism
A statistically significant interaction effect between the three groups (AN vs. BED vs. GP) and the selected EDs-related variables was found—showing an absence of parallelism among profiles: Wilks’ Λ = 0.549, $F = 12.983$, $p \leq 0.001$, η2p = 0.259 (large effect size). This revealed that segments were different across conditions. Figure 1 graphically represents the absence of parallelism.
## 3.4. Profile Analysis: Level Equality—Between-Group Differences
A statistically significant between-groups effect was found: $F = 93.47$, $p \leq 0.001$; η2p = 0.309 (large effect size). This outcome further confirmed that the three groups (AN vs. BED vs. GP) were different, on average.
Multivariate pairwise focused contrast between the AN group and the GP showed a statistically significant multivariate effect [Wilks’s Λ = 0.798, $F = 6.248$, $p \leq 0.001$, η2p = 0.202 (large effect size)] and a statistically significant between-groups difference [$F = 179.446$, $p \leq 0.001$, η2p = 0.391 (large effect size)]. Moreover, multivariate pairwise focused contrast between the GP and the BED group presented a statistically significant multivariate effect [Wilks’s Λ = 0.670, $F = 11.968$, $p \leq 0.001$, η2p = 0.330 (large effect size)] and a statistically significant between-groups difference [$F = 105.410$, $p \leq 0.001$, η2p = 0.276 (large effect size)]. Lastly, a multivariate pairwise focused contrast between the AN and BED conditions exhibited a statistically significant multivariate effect [Wilks’s Λ = 0.560, $F = 19.194$, $p \leq 0.001$, η2p = 0.440 (large effect size)] and a statistically significant between-groups difference [$F = 12.894$, $p \leq 0.001$, η2p = 0.044 (small effect size)].
Considering the DT, MANOVA revealed statistically significant differences between the three groups: $F = 59.045$, $p \leq 0.001$, η2p = 0.220 (large effect size)—Figure 2, Panel A. Considering the B scale, MANOVA showed statistically significant differences between the three conditions: $F = 87.590$, $p \leq 0.001$, η2p = 0.295 (large effect size)—Figure 2, Panel B. Considering the BD scale, MANOVA revealed statistically significant differences between the three groups: $F = 75.269$, $p \leq 0.001$, η2p = 0.265 (large effect size)—Figure 2, Panel C. Considering the LSE scale, MANOVA showed statistically significant differences between the three conditions: $F = 66.434$, $p \leq 0.001$, η2p = 0.241 (large effect size)—Figure 2, Panel D. Considering the PA scale, MANOVA revealed statistically significant differences between the three groups: $F = 87.374$, $p \leq 0.001$, η2p = 0.295 (large effect size)—Figure 2, Panel E. Considering the II scale, MANOVA showed statistically significant differences between the three conditions: $F = 44.740$, $p \leq 0.001$, η2p = 0.176 (large effect size)—Figure 2, Panel F. Considering the IA scale, MANOVA revealed statistically significant differences between the three groups: $F = 34.337$, $p \leq 0.001$, η2p = 0.141 (large effect size)—Figure 2, Panel G. Considering the ID scale, MANOVA showed statistically significant differences between the three conditions: $F = 70.248$, $p \leq 0.001$, η2p = 0.252 (large effect size)—Figure 2, Panel H. Considering the EmoD scale, MANOVA revealed statistically significant differences between the three groups: $F = 45.551$, $p \leq 0.001$, η2p = 0.179 (large effect size)—Figure 2, Panel I. Considering the P scale, MANOVA showed statistically significant differences between the three conditions: $F = 14.842$, $p \leq 0.001$, η2p = 0.066 (moderate effect size)—Figure 2, Panel J. Considering the A scale, MANOVA revealed statistically significant differences between the three groups: $F = 45.294$, $p \leq 0.001$, η2p = 0.178 (large effect size)—Figure 2, Panel K. Considering the MF scale, MANOVA showed statistically significant differences between the three conditions: $F = 43.909$, $p \leq 0.001$, η2p = 0.174 (large effect size)—Figure 2, Panel L. Bivariate comparisons are reported in Table 2.
## 3.5. Profile Analysis: Flatness—Within-Group Differences
A statistically significant within-groups effect was found: $F = 17.691$, $p \leq 0.001$, η2p = 0.078 (moderate effect size). This result confirmed that there were overall differences in the average values of the dependent variables.
Considering patients with AN, a statistically significant multivariate effect [Wilks’s Λ = 0.585, $F = 8.460$, $p \leq 0.001$, η2p = 0.415 (large effect size)] and a statistically significant within-group differences [$F = 11.947$, $p \leq 0.001$, η2p = 0.075 (moderate effect size)] were found. Considering participants enrolled from the GP, a statistically significant multivariate effect [Wilks’s Λ = 0.670, $F = 5.787$, $p \leq 0.001$, η2p = 0.330 (large effect size)] and a statistically significant within-group differences [$F = 6.438$, $p \leq 0.001$, η2p = 0.044 (small effect size)] were found. Considering patients with AN, a statistically significant multivariate effect [Wilks’s Λ = 0.483, $F = 12.463$, $p \leq 0.001$, η2p = 0.517 (large effect size)] and a statistically significant within-group differences [$F = 16.072$, $p \leq 0.001$, η2p = 0.104 (moderate effect size)] were found.
Detailed results—bivariate comparisons—are reported in Table 3.
## 4. Discussion
The present study employs profile analysis to investigate similitudes and differences in core ED symptoms and general psychological constructs as assessed by the EDI-3 among samples of patients with AN and BED and respondents from the GP.
Results support previous research in suggesting that distinct patterns of symptom presentation exist between the three samples across all the EDI-3 dimensions, but for the first time, clinical samples of patients with AN and BED are directly compared here.
Not surprisingly, both the AN and BED groups separately showed significantly higher scores across the majority of the EDI-3 dimensions than the community sample. Moreover, statically significant differences in specific symptom presentations were observed between the two clinical samples (AN vs. BED).
Of note, higher scores across all the psychological trait scales were detected in the AN group compared to their counterpart, together with significantly higher scores in the drive for thinness ED-specific dimension. Patients with BED showed, instead, a greater tendency to engage in uncontrollable overeating (bulimia) and higher (but not statistically different) scores in the body dissatisfaction dimension compared to the AN group.
Indeed, dissatisfaction with body shape and weight is a key indicator and risk factor for the development of AN and BN [56]; the Diagnostic and Statistical Manual of Mental Disorders, 5th ed. ( DSM-5) [1] does not contain a body image-related criterion for BED [3]. Results from this study support those from previous research in which patients with BED showed remarkable concerns about weight and body shape [57], extreme body dissatisfaction, [58] as well as body checking and avoidance behaviors [59]. Additionally, studies exploring the presence of altered body perception in patients with BED concluded that they may either over- [60,61] or underestimate [62,63] their body size. Despite leading to inconsistent conclusions, these findings further indicate a link between distorted body image and its related constructs (i.e., body dissatisfaction) and BED symptomatology. Therefore, the application of body dissatisfaction as a diagnostic indicator seems reasonable but—given the results of this study—only considering other variables associated with higher levels of ED pathology including lower self-esteem.
Indeed, it is unquestionable that low self-esteem is linked with EDs, and a decrease in self-esteem is correlated with poorer body image [64,65], perfectionism [66,67,68], and bulimic symptoms [69,70,71]. However, how these variables are related is not entirely well-defined: is it low self-esteem that makes an individual more susceptible to an ED, or is it the presence of disordered eating patterns that impacts the individual’s self-esteem?
In a review of the literature, Ghaderi [2010] concluded that low self-esteem, along with other factors, not only puts an individual at greater risk for the development of an ED but also serves as a maintaining factor [72]. Indeed, individuals with higher levels of disordered eating behaviors displayed higher levels of overall dissatisfaction with themselves, their appearance, and their family relationships in many studies [73,74].
Self-esteem is «a sense of contentment and self-acceptance that results from a person’s appraisal of their worth, attractiveness, competence, and ability to satisfy their aspirations» [72].
Given this definition, it is clear to see that self-esteem is multifaceted. Similarly, the development and maintenance of EDs are complex and involve factors such as family and cultural environments, history of dieting and/or food addiction, developmental stage, and relational, emotional, and spiritual factors [74,75,76].
The research found that the development of AN and BN is predicted by perfectionistic tendencies and body dissatisfaction only among women with low self-esteem, whereas women showing higher self-esteem did not develop anorexic and/or bulimic symptoms [66,77,78].
The results from this study support the occurrence of low self-esteem in both clinical samples and partially support the cognitive-behavioral theorization of eating behaviors as driven and maintained by attempts to adhere to extreme dietary rules; the results also seem to reflect similar—albeit different—tendencies in AN and BED.
The ideal thinness—a noticeable trend in society—would drive those individuals that also scored significantly higher in the EDI-3 perfectionism dimension to cope by striving to become the thinnest they can—thus anticipating the onset of AN. Furthermore, if these factors are buffered by low self-esteem, an intense drive for thinness would follow—functioning as maintaining factors.
Instead, individuals showing less perfectionistic attitudes but still engaging in restrained eating would develop BED symptoms if unable to adhere to extreme dietary rules, and concerns about their ability to control their eating, shape, and weight matched with perceived poor self-control and personal weakness, further encouraging dietary restraint.
Despite coming to interesting conclusions, the present study has a few limitations. First, a single psychometric measure has been used, and its self-report nature may also have affected the reliability of the tool due to the socially desirable response tendency. Moreover, since the EDI—and particularly its body dissatisfaction subscale—was originally designed for underweight to normal-weight populations of individuals with AN and BN, it might fail to detect differences in samples of overweight or obese participants with BED. Second, although this study was based on a solid literature background, the research design was cross-sectional, and, therefore, it is not possible to assess the incidence or make a causal inference. Thus, future research should fill this gap by conducting longitudinal studies or employing stronger methodologies (i.e., randomized control trials) aimed at exploring these constructs over time. Third, while subjects meeting the BED criteria in the present study are distinguishable from patients with AN based on their bulimia subscale scores, the absence of a sample of participants with BN—or patients with obesity without BED—prevents drawing further considerations and research hypotheses for future studies on the etiopathogenesis and maintenance of overeating tendencies. Fourth, the data presented are collected from patients attending a specialist ED rehabilitation program, but there is a plethora of evidence that the majority of those suffering from EDs are not receiving active treatment.
The results from this study are useful for helping clinicians assess target variables while working with patients with EDs, therefore furthering knowledge and enhancing treatment strategies for AN and BED. Specifically, an intervention targeting self-esteem seems particularly helpful to prevent the worsening of the clinical presentation of patients with dysfunctional eating habits. Furthermore, baseline assessment of the presence of body image disturbance in both individuals with AN and higher weight might help support the development of effective treatment to reduce ED symptoms. However, in light of the above limitations, findings from this study must be taken with caution and inspire further research in the field. Future studies might indeed use different, additional self-report measures to corroborate the above-mentioned conclusion. Models of predictive/protective factors for the onset of AN and BED might be also tested in longitudinal research.
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|
---
title: CXCL12 and CXCR4 as Novel Biomarkers in Uric Acid-Induced Inflammation and
Patients with Gouty Arthritis
authors:
- Seong-Kyu Kim
- Jung-Yoon Choe
- Ki-Yeun Park
journal: Biomedicines
year: 2023
pmcid: PMC10045243
doi: 10.3390/biomedicines11030649
license: CC BY 4.0
---
# CXCL12 and CXCR4 as Novel Biomarkers in Uric Acid-Induced Inflammation and Patients with Gouty Arthritis
## Abstract
The aim of this study was to evaluate the expression of chemokine receptor CXCR4 and its ligand CXCL12 in patients with gout and uric acid-induced inflammation. A total of 40 patients with intercritical gout and 27 controls were consecutively enrolled. The serum levels of interleukin-1β (IL-1β), IL-18, CXCL12, and CXCR4 were assessed using an enzyme-linked immunosorbent assay. *The* gene and protein expressions for these target molecules were measured in human U937 cells incubated with monosodium urate (MSU) crystals using a real-time reverse transcription polymerase chain reaction and Western blot analysis. Patients with intercritical gout showed higher serum IL-1β, IL-18, and CXCL12 levels, but not the serum CXCR4 level, than in the controls. The serum CXCR4 level in gout patients was associated with the serum IL-18 level, uric acid level, and uric acid/creatinine ratio ($r = 0.331$, $$p \leq 0.037$$; $r = 0.346$, $$p \leq 0.028$$; and $r = 0.361$, $$p \leq 0.022$$, respectively). U937 cells treated with MSU crystals significantly induced the CXCL12 and CXCR4 mRNA and protein expression in addition to IL-1β and IL-18. In cells transfected with IL-1β siRNA or IL-18 siRNA, the CXCL12 and CXCR4 expression was downregulated compared with the non-transfected cells in MSU crystal-induced inflammation. In this study, we revealed that CXCL12 and CXCR4 were involved in the pathogenesis of uric acid-induced inflammation and gouty arthritis.
## 1. Introduction
Gout is a chronic inflammatory disease triggered by an excessive deposition of monosodium urate (MSU) in articular and extra-articular structures, usually in subjects with hyperuricemia [1]. It initially manifests as acute inflammatory arthritis and progresses to chronic synovitis, accompanied by tophi depositions and joint damage. Although the pathogenesis of gout has not been determined, the activation of the NLRP3 inflammasome triggered by uric acid is considered to be a key pathogenic mechanism in the acute inflammatory response of gout, which leads to the production of proinflammatory cytokines, including interleukin-1β (IL-1β) and IL-18 [2,3].
Chemokines are a family of small, secreted chemotactic cytokines that play a crucial role in the stimulation of leukocyte migration and adhesion to inflammatory lesions through interactions with G protein-coupled chemokine receptors. They are involved in cellular homeostasis, immune system activation, and inflammatory responses [4]. Chemokines and their receptors have been implicated in the pathogenesis of inflammation of diverse joint diseases and have also been considered as potential therapeutic targets [5]. In addition, the enhanced production of chemokines—including IL-8 (C-X-C motif chemokine ligand 8 (CXCL8)) [6], macrophage inflammatory protein (MIP)-1α (C-C motif chemokine ligand (CCL3)) [7], MIP-2/CXCL2 [7], monocyte chemoattractant protein-1 (MCP-1) [8], and CXCL16 [9]—has been found to be associated with the pathogenesis of uric acid-induced inflammation in gouty arthritis.
CXCL12, formerly known as stromal-derived factor-1 (SDF-1), is produced in a broad variety of human tissues (including skin, kidney, colon, and joint tissues) as well as in various cell types (including stromal cells, monocytes, and synovial cells) [10,11]. C-X-C chemokine receptor 4 (CXCR4) is a chemokine receptor in the G protein-coupled receptor (GPCR) superfamily [10,11]. CXCR4 binds to its ligand CXC chemokine CXCL12 and plays a role in the induction of the recruitment of inflammatory cells, including leukocytes and endothelial cells [12]. The CXCL12/CXCR4 axis has been implicated in the pathogenesis of several types of inflammatory arthritis and autoimmune diseases, including rheumatoid arthritis (RA) [13,14], osteoarthritis (OA) [15,16], systemic lupus erythematosus (SLE) [17], and ankylosing spondylitis (AS) [18]. Evidence of the pathogenic role of CXCR4 and CXCL12 in uric acid-induced inflammation has not been presented. Thus, the aim of this study was to compare the CXCR4 and CXCL12 levels between gout patients and controls and to determine the role of these molecules in uric acid-induced inflammation.
## 2.1. Study Population
In this study, we consecutively enrolled male patients with intercritical gout ($$n = 40$$) who were older than 18 years and met the classification criteria of gout proposed by the American College of Rheumatology/European League Against Rheumatism [19]. Patients with gout were those who continued to receive uric acid-lowering agents and who had no history of gout attacks in the previous month. Age- and gender-matched controls ($$n = 27$$) also were recruited. We excluded those with any medical history or treatment for other inflammatory arthritis or autoimmune disease-related arthritis (including RA, AS, pseudogout, psoriatic arthritis, SLE, or Sjögren’s syndrome) through a review of the medical records or an interview with each subject. The clinical data (including the age, gender, blood urea nitrogen, creatinine, estimated glomerular filtration rate (eGFR), uric acid, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR)) of the gout patients were collected at the time of study enrollment (Table 1). The estimated glomerular filtration rate (eGFR) was calculated by the original Modification of Diet in Renal Disease (MDRD) equation using the serum creatinine, age, and gender, as follows: MDRD eGFR (mL/min/1.73 m2) = 175 × (serum creatinine)−1.154 × (age)−0.203. The current medication of the gout patients was identified, and included febuxostat, allopurinol, benzbromarone, colchicine, steroids, non-steroidal anti-inflammatory drugs, and diuretics.
We collected venous blood samples from the gout patients and controls, placed them in tubes for the serum separation, and centrifuged them at 2500 rpm for 5 min (NeoGenesis Co., Ltd., Seoul, Korea) to obtain the supernatant. Each supernatant was collected into an Eppendorf tube and stored in a freezer at −80 °C until the ELISA analysis.
## 2.2. Cell Culture and Preparation of MSU Crystals
Cells from the human monocytic leukemia cell line U937 were obtained from the Korean Cell Line Bank (KCLB, Seoul, Korea) and maintained in an RPMI 1640 medium (Gibco Laboratories, Grand Island, NY, USA) supplemented with $10\%$ fetal bovine serum (FBS) and PenStrep (100 U/mL penicillin and 100 μg/mL streptomycin) at 37 °C in a $5\%$ CO2 humidified incubator. The U937 cells were differentiated by 100 ng/mL of phorbol 12-myristate 13-acetate (PMA, Sigma-Aldrich, St. Louis, MO, USA) and allowed to adhere for 24 h. After this, the adherent cells were treated with MSU crystals.
The MSU crystals were prepared as described in our previous study [20]. The endotoxin assay for the MSU crystals was performed using a ToxinSensorTM Chromogenic LAL endotoxin assay kit (Genscript, Piscataway, NJ, USA).
## 2.3. Enzyme-Linked Immunosorbent Assay (ELISA)
The serum concentrations of IL-1β, IL-18, and CXCL12 were measured by an ELISA kit, according to the assay instructions (R&D Systems, Minneapolis, MN, USA). Briefly, 96-well plates were coated with 100 μL of each captured antibody and kept at room temperature overnight. The plates were washed three times in a wash buffer ($0.05\%$ Tween 20 in phosphate buffered saline (PBS)) and blocked with 300 μL per well of blocking reagents ($1\%$ bovine serum albumin (BSA) in PBS) for 1 h at room temperature. After washing, the serum and standards were added to each well and incubated for 2 h at room temperature. The serum IL-1β, IL-18, and CXCL12 levels were visualized with a biotin-conjugated detection antibody, followed by horseradish peroxidase-labelled streptavidin. The reaction was stopped by the addition of 2N H2SO4 to each well, and the optical density was determined on a microplate reader set to 450 nm. The serum level of CXCR4 was measured by ELISA kits (MyBioSource, San Diego, CA, USA), according to the manufacturer’s instructions.
The sera were pre-coated onto 96-well plates and incubated for 2 h at 37 °C. The plates were aspirated and a biotin antibody was added to each well and incubated for 1 h at 37 °C. After 3 washes, 100 μL of HRP-avidin (1X) was added to the wells and incubated for 1 h at 37 °C. A tetramethyl benzidine substrate was added to each well and incubated at 37 °C in the dark for 15–30 min. The reaction was stopped by the addition of 50 μL of a stop solution to each well, and the absorbance was measured at 540 nm using an ELISA plate reader (BMG Lab Technologies, Offenburg, Germany).
## 2.4. Real-Time Reverse Transcription Polymerase Chain Reaction (RT-PCR)
The cells (2 × 104) were seeded in 24-well plates and treated with various concentrations of MSU crystals (0.1, 0.2, and 0.3 mg/mL) for 24 h. The total RNA was extracted using a TRIzol reagent, and complementary DNA (cDNA) was synthesized using a ReverTra Ace-α-reverse transcriptase kit (Toyobo, Osaka, Japan). The cDNA was then analyzed by real-time RT-PCR (Bio-Rad iQ5 Real-Time PCR System, Bio-Rad, Hercules, CA, USA) using an SYBR Green Mix kit (Toyobo, Osaka, Japan). The PCR amplification consisted of an initial denaturation at 95 °C for 15 min, followed by 40 cycles of 9 °C for 5 s, 55–65 °C for 30 s, and 72 °C for 15 s. The relative expression of each gene was analyzed using the ΔΔCT method.
## 2.5. Western Blot Analysis
The cells (2 × 106) were seeded on 100 mm culture dishes and treated with MSU crystals (0.1, 0.2, and 0.3 mg/mL) for 24 h. The total proteins were extracted from the cells with a radioimmunoprecipitation assay buffer containing a protease inhibitor cocktail (Thermo Fisher Scientific, Rockford, IL, USA), incubated on ice for 10 min, and centrifuged at 13,000 rpm for 10 min at 4 °C. The protein concentration of the supernatant was measured with a Pierce™ BCA Protein assay kit using a microplate reader at 562 nm. Equal amounts of protein (50 μg) were separated with 10–$13\%$ SDS-PAGE gel electrophoresis and transferred to nitrocellulose membranes (Bio-Rad, Hercules, CA, USA).
After blocking with $5\%$ BSA, the samples were probed with appropriate primary antibodies and incubated overnight at 4 °C. The membranes were subsequently reacted with the appropriate HRP-conjugated secondary antibodies (Santa Cruz Biotechnology, Santa Cruz, CA, USA) for 1 h at room temperature. The proteins were enhanced with ECL chemiluminescent detection system reagents. Images were obtained using a ChemiDoc TM XRS system (Bio-Rad).
## 2.6. Transfection of siRNA
The cells (1 × 104 cells/well) were seeded in 24-well plates and transfected with 50 nM human IL-1β siRNA (HSS105299) and human IL-18 siRNA (HSS105407) using a lipofectamine RNAi MAX reagent (Invitrogen, Waltham, MA, USA) in Opti-MEM media (Gibco Laboratories). After 48 h of transfection, the cells were harvested for the real-time RT-PCR and Western analysis.
## 2.7. Statistical Analysis
The data were presented as the median and interquartile range (IQR) for the quantitative variables and numbers with percentages for the qualitative variables. The normality of the data not showing a normal distribution was verified using the Kolmogorov–Smirnov test. The comparison of IL-1β, IL-18, CXCL12, and CXCR4 between the gout patients and the controls was performed using the Mann–Whitney U test. The correlation among IL-1β, IL-18, CXCL12, CXCR4, and the laboratory variables was evaluated by Spearman’s correlation analysis. The comparison of the mRNA expression in IL-1β, IL-18, CXCL12, and CXCR4 between the cells treated with MSU crystals and the non-treated cells was assessed by a Mann–Whitney U test. A p-value < 0.05 was considered to be statistically significant. The statistical analysis was performed using SPSS version 19.0 (SPSS Inc., Chicago, IL, USA). The curve generation for the figures in this study was performed using GraphPad Prism 5.0 (GraphPad Software, Inc., San Diego, CA, USA).
## 3.1. Comparison of Expression of CXCR4, CXCL12, IL-1β, and IL-18 between Patients with Gout and Controls
The baseline characteristics of the study population are shown in Table 1. The gout and controls were all male subjects. The median values of age between the two groups had no statistical difference ($$p \leq 0.349$$) (Table 1). IL-1β and IL-18 are crucial proinflammatory cytokines that play a role in the pathogenesis of gout [2,3]. First, we compared the levels of the two proinflammatory cytokines in the serum of the gout patients and controls (Figure 1A). The serum IL-1β and IL-18 levels in the gout patients were significantly higher than in the controls (7.31 ± 11.84 vs. 0.46 ± 0.91, $$p \leq 0.004$$ and 100.51 ± 47.63 vs. 68.49 ± 32.55, $$p \leq 0.002$$, respectively). In a comparison of CXCR4 and its ligand CXCL12, the gout patients showed a larger increase in the expression of the serum CXCL12 level compared with the controls (392.27 ± 247.54 vs. 243.90 ± 184.03, $$p \leq 0.010$$). However, there was no difference in the serum CXCR4 level between the two groups (45.45 ± 18.46 vs. 47.45 ± 8.35, $$p \leq 0.550$$).
**Table 1**
| Variables | Gout (n = 40) | Controls (n = 27) |
| --- | --- | --- |
| Sex, male (n, %) | 40 (100.0) | 27 (100.0) |
| Age (years) | 63.0 (54.3, 70.0) | 65.0 (51.8, 70.0) |
| Blood urea nitrogen (mg/dL) | 19.4 (12.8, 27.1) | |
| Creatinine (mg/dL) | 1.0 (0.8, 1.4) | |
| eGFR (mL/min/1.73 m2) | 77.7 (52.4, 100.1) | |
| Erythrocyte sedimentation rate (mm/h) | 11.5 (7.0, 21.8) | |
| C-reactive protein (mg/L) | 0.9 (0.6, 1.9) | |
| Uric acid (mg/dL) | 4.8 (4.2, 6.6) | |
| Uric acid/creatinine | 5.12 (3.65, 6.59) | |
| Medication (n, %) | | |
| Febuxostat | 30 (75.0) | |
| Allopurinol | 3 (7.5) | |
| Benzbromarone | 5 (12.5) | |
| Colchicine | 16 (40.0) | |
| Steroids | 6 (15.0) | |
| Non-steroidal anti-inflammatory drugs | 8 (20.0) | |
| Diuretics | 2 (5.0) | |
## 3.2. Correlations of IL-1β, IL-18, CXCL12, and CXCR4 with Laboratory Variables in Gout Patients
We evaluated the relationship among IL-1β, IL-18, CXCL12, CXCR4, and the laboratory variables in the patients with gout. The serum IL-1β level was not statistically associated with the serum CXCR4 and CXCL12 levels (Figure 1B). The serum IL-18 level was positively correlated with the serum CXCR4 level ($r = 0.331$, $$p \leq 0.037$$), but not the serum CXCL12 level.
There was a significant correlation between the serum CXCR4 level and uric acid ($r = 0.346$, $$p \leq 0.029$$) (Figure 1B). After an adjustment of uric acid with creatinine, the significance of the correlation between the serum CXCR4 level and uric acid persisted ($r = 0.361$, $$p \leq 0.022$$). In addition, the serum uric acid level was not associated with the serum CXCL12 level. However, we could not discover the correlations between acute phase reactants such as CRP and ESR and the serum CXCR4, CXCL12, IL-1β, and IL-18 levels (data not shown).
## 3.3. Expression of IL-1β, IL-18, CXCL12, and CXCR4 in MSU Crystal-Stimulated U937 Cells
We then evaluated whether U937 macrophages treated with MSU crystals induced the mRNA and protein expression of IL-1β, IL-18, CXCL12, and CXCR4. MSU crystals significantly induced the mRNA expression of proinflammatory cytokines IL-1β and IL-18 in human U937 cells in a dose-dependent manner (Figure 2A). In addition, the CXCL12 and CXCR4 mRNA expression markedly increased in the macrophages treated with MSU crystals compared with the non-treated cells.
Consistently, the U937 cells incubated with MSU crystals induced cleaved forms of IL-1β and IL-18 from inactive pro-IL-1β and pro-IL-18 in a dose-dependent manner (Figure 2B). In addition, the expression of CXCL12 and CXCR4 proteins was significantly increased by a stimulation with MSU crystals.
## 3.4. Expression of CXCR4 and CXCL12 by Downregulation of Either IL-1β or IL-18 in MSU Crystal-Stimulated U937 Cells
The U937 cells transfected with IL-1β siRNA suppressed the IL-1β, CXCL12, and CXCR4 mRNA expression compared with the non-transfected cells ($p \leq 0.001$, $p \leq 0.01$, and $p \leq 0.05$, respectively) (Figure 3A). The activation of pro-IL-1β was markedly blocked in the U937 cells transfected with IL-1β siRNA compared with the cells transfected with the negative control (NC) siRNA (Figure 3B). The macrophages transfected with the IL-1β siRNA significantly suppressed the CXCL12 and CXCR4 expression.
Consistently, the IL-18, CXCL12, and CXCR4 mRNA expression was significantly downregulated in the U937 cells transfected with the IL-18 siRNA relative to the non-transfected cells ($p \leq 0.01$, $p \leq 0.05$, and $p \leq 0.05$, respectively) (Figure 3C). The U937 cells transfected with the IL-18 siRNA inhibited the activation of pro-IL-18 to IL-18, respectively, and attenuated the CXCL12 and CXCR4 expression (Figure 3D).
## 4. Discussion
The NLRP3 inflammasome is an intracellular multi-protein signaling complex that is induced through stimulations with various endogenous and exogenous pathogens such as LPS, nigericin, MSU, silica, or alum [21,22]. Accumulating evidence suggests that MSU crystals induce the recruitment and assembly of NLRP3, ASC, and pro-caspase-1, triggering NLRP3 inflammasome activation and resulting in the activation of proinflammatory cytokines (including IL-1β, IL-18, tumor necrosis factor-α (TNF-α), and IL-6), which ultimately generates uric acid-induced intra-articular inflammation in the pathogenesis of gouty arthritis [2,3,23]. In addition to these inflammatory cytokines, chemokines that play a role in the ability to recruit and infiltrate leukocytes into the intra-articular space are involved as potent mediators of the inflammatory response of gouty arthritis [5]. Previous studies have found an increased expression of various chemokines (including CXCL8, CCL3, CXCL2, and MCP-1) in stimulations with MSU crystals in experimental models of gout or in the serum of gout patients [6,7,8,9]. Based on these observations, novel chemokines and their receptors might play a crucial role in the pathogenesis of gout and may also be potent therapeutic targets.
The CXCL12/CXCR4 axis is one of the most studied C-X-C chemokine/chemokine receptor subfamilies and is implicated in a broad variety of physiological and pathological conditions, including autoimmune or inflammatory diseases, tissue regeneration, and cancerous diseases [10,11,12]. The activation of GPCRs by binding ligands induces the expression of multiple genes involved in proinflammatory cytokine activation, chemotaxis, adhesion molecules, and tissue repair [24]. There are multiple complex downstream signal transduction pathways activated by the binding of CXCL12 to CXCR4. Upon binding to the ligand, CXCR4 activation induces a dissociation of heterotrimeric G protein subunits bound to the intracellular loop of CXCR4 to lead to the activation of multiple signaling pathways. Heterotrimeric G protein subunits dissociate into Gi and Gβγ subunits. The Gβγ subunit induces intracellular calcium mobilization and triggers the production of phosphatidyl-inositol-3-kinase (PI3K), which results in the activation of the ARK and ERK$\frac{1}{2}$ pathways and finally stimulating NF-κB, an inducible transcription factor of inflammatory genes [25]. In addition, the Gβγ subunit is involved in the conversion of phosphatidylinositol 4,5-bisphosphate (PIP2) into IP3 and diacylglycerol (DAG) [26]. IP3 regulates the calcium release from the endoplasmic reticulum, modulating numerous downstream signaling transduction targets. Previous studies have implicated the CXCL12/CXCR4 axis in the pathogenesis of diverse autoimmune, inflammatory, or non-inflammatory rheumatic diseases, including RA [13,14], OA [15,16], SLE [17], and AS [18]. Considering the interactions between gout and the downstream pathways in the CXCL12/CXCR4 axis, many studies have suggested that the uric acid-induced inflammatory response with activation by NF-κB might be related to the GPCR downstream signaling pathway [27,28]. Our study first identified an increased expression of CXCR4 and CXCL12 mRNA and protein under a stimulation with MSU crystals in human U937 macrophages and also a higher level of serum CXCL12 in the gout patients compared with the controls, although the serum CXCR4 level was similar between the two groups. In contrast, Murakami et al. demonstrated that the knockdown of the Gβ subunit, a downstream molecule of GPCRs, significantly enhanced caspase-1 activation and IL-1β release by an ATP treatment, indicating that the Gβ subunit negatively regulated NLRP3 inflammasome activation by the inhibition of ASC oligomerization [29]. Nevertheless, the CXCL12/CXCR4 axis plays a critical role in immune-mediated or inflammatory diseases (including gouty arthritis) as a therapeutic target by modulating the inflammatory and immune response and regulating the recruitment of leukocytes.
Considering the clinical significance of CXCR4 and CXCL12 in inflammatory or autoimmune rheumatic diseases, previous studies have analyzed the relationship between disease activity or severity in patients with each disease and those biomarkers. Active RA patients showed a higher CXCR4 and CXCL12 expression in the serum and joint fluid compared with patients in remission and control groups [14]. In addition, these biomarkers were significantly associated with the ESR, CRP, and DAS28 score. Qin et al. demonstrated that the activation of the SDF-1/CXCR4 axis induced subchondral bone deterioration and articular cartilage degeneration that aggravated joint destruction in anterior cruciate ligament transection OA mice models [16]. These results suggest that CXCR4 and CXCL12 might contribute to the activity and severity of OA. In the assessment of the role of chemokines in the pathogenic process of SLE, the expression level of CXCR4 in circulating B cells from peripheral blood mononuclear cells (PBMCs) in active SLE patients was significantly higher than those in inactive patients and healthy controls [17]. Consistently, the chemotactic response of CD19+ B cells to CXCL12 was also markedly increased in active SLE patients compared with those with inactive SLE and the controls ($$p \leq 0.004$$ and $$p \leq 0.001$$, respectively). Aeberli et al. evaluated the regulatory effect of infliximab in patients with AS on the chemokines MCP-1 and CXCL12 and their receptors CCR2 and CXCR4 in purified CD11b+CD14+ monocytes [18]. An infliximab treatment significantly decreased the serum SDF-1 level at day 84 and day 168 in both AS and RA patients. However, the downregulation of the percentage of CXCR4+ monocytes was not detected during the infliximab treatment for 6 months. In the present study, we could not identify the associations between the serum CXCR4 and CXCL12 levels and acute phase reactants, including ESR and CRP. However, IL-18, one of the main proinflammatory cytokines related to the pathogenesis of gout, was significantly associated with the CXCR4 level. The weak correlation with the inflammatory markers was presumed to be partially related to selection of intercritical gout patients with a low disease activity. Due to the limited clinical data of the effects of these chemokines and their receptors on the long-term prognosis and severity of inflammatory rheumatic diseases, it is necessary to evaluate the clinical significance of these biomarkers in prospective studies.
The relationship between inflammatory cytokines and chemokines is considered to be complex. In the present study, we confirmed that the IL-1β and IL-18 expression was increased by a stimulation with MSU crystals as well as in the blood of gout patients, together with CXCR4 and CXCL12. Human U937 cells transfected with IL-1β siRNA or IL-18 siRNA showed a downregulated CXCR4 and CXCL12 mRNA and protein expression, indicating that the tight control of proinflammatory cytokines may have had an additive therapeutic effect by inhibiting the action of the activated chemokines in the inflammatory response. An IL-1β pretreatment improved the homing efficacy of mesenchymal stem cells on liver failure through an increased CXCR4 expression [30]. Binding CXCL12 to CXCR4 induces the activation of mitogen-activated protein kinase (MAPK) and NF-κB, resulting in the stimulation of a diverse gene transcription [10]. Conversely, the CXCR4 knockdown of RAW 264.7 cells showed a decreased expression in proinflammatory cytokines such as IL-6 and TNF-α by the attenuation of the MAPK and NF-κB signaling pathways [31]. Based on these observations, CXCL12 and CXCR4 might be regulated by proinflammatory cytokines such as IL-1β and IL-18.
Uric acid is the main pathogenic trigger in the pathogenesis of gout through NLRP3 inflammasome activation [2,3]. In addition, there is a well-established close relationship between uric acid and cardiovascular diseases (CVDs) [32]. The pathogenic mechanism of uric acid on CVDs has not clearly defined. Oxidative stress, insulin resistance, and impaired endothelial dysfunction induced by uric acid play a role in the development of atherosclerosis. Thus, uric acid is considered to be a crucial predictor for CVD-mediated outcomes such as CV mortality and morbidity. The activation of the CXCR4/CXCL12 axis was found to play an important role in angiogenesis as well as the homing and mobilization of progenitor cells; this then results in the development of CVDs, including myocardial ischemia and infarction [33]. Considering the relationship between uric acid and the CXCR4/CXCL12 axis presented in our study, the CXCR4/CXCL12 axis may be an important mediator in the development of uric acid-induced CVD. Ultimately, the acquisition of sufficient knowledge on CXCR4/CXCR12 is expected to be useful in the prevention and treatment of CVD.
There are a few limitations to the interpretation of our results in this study. First, the size of the study population, including the gout patients and controls, was relatively small to clarify the differences between CXCL12 and CXCR4. As the expression of CXCL12 and CXCR4 was cross-sectionally analyzed, the study was limited in its ability to longitudinally confirm the change pattern of these molecules associated with medication or other inflammatory factors. Second, the expression of CXCL12 and CXCR4 was measured in the serum extracted from whole blood. It would be more convincing to confirm the expression of these target molecules from PBMCs. However, this weakness was overcome by verifying the expression of inflammatory cytokines and chemokines through experiments using human U937 macrophages treated with MSU crystals. Third, most of the gout patients had intercritical gout without an acute gout attack. The intercritical phase in gout may be clinically important for a reduction in the risk of an acute gouty flare-up [1]. As shown in Table 1, a few patients in the intercritical phase without an acute gout attack still used anti-inflammatory drugs, including colchicine, steroids, or NSAIDs. This could suggest that the patients had an inflammatory response, even at the intercritical phase. It is, therefore, necessary to identify the extent of the inflammatory response in the intercritical phase. Finally, this study was cross-sectionally designed to define the role of CXCL12 and CXCR4 in the intercritical phase. Therefore, changes in the CXCL12 and CXCR4 expression during an acute attack could not be confirmed. Therefore, a prospective longitudinal study with a larger study population and more reasonable selection criteria is needed to produce more robust results on the significance of CXCL12 and CXCR4.
## 5. Conclusions
We found that gout patients showed a higher expression of CXCL12 and proinflammatory cytokines, including IL-1β and IL-18, than members of the control group. Additionally, this study found that the expression of CXCL12 and CXCR4 could be regulated during NLRP3 inflammasome activation stimulated by MSU crystals in U937 macrophages (Figure 4). Therefore, chemokine CXCL12 and its receptor CXCR4 might be considered to be potent therapeutic targets in uric acid-induced NLRP3 inflammasome activation in gout patients.
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|
---
title: Antibacterial and Phytochemical Screening of Artemisia Species
authors:
- Maria-Evelina Bordean
- Rodica Ana Ungur
- Dan Alexandru Toc
- Ileana Monica Borda
- Georgiana Smaranda Marțiș
- Carmen Rodica Pop
- Miuța Filip
- Mihaela Vlassa
- Bogdana Adriana Nasui
- Anamaria Pop
- Delia Cinteză
- Florina Ligia Popa
- Sabina Marian
- Lidia Gizella Szanto
- Sevastița Muste
journal: Antioxidants
year: 2023
pmcid: PMC10045255
doi: 10.3390/antiox12030596
license: CC BY 4.0
---
# Antibacterial and Phytochemical Screening of Artemisia Species
## Abstract
Taking into account the increasing number of antibiotic-resistant bacteria, actual research focused on plant extracts is vital. The aim of our study was to investigate leaf and stem ethanolic extracts of *Artemisia absinthium* L. and *Artemisia annua* L. in order to explore their antioxidant and antibacterial activities. Total phenolic content (TPC) was evaluated spectrophotometrically. Antioxidant activity was evaluated by DPPH and ABTS. The antibacterial activity of wormwood extracts was assessed by minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) in Escherichia coli, Staphylococcus aureus, Listeria monocytogenes, and *Salmonella enteritidis* cultures, and by zone of inhibition in Klebsiella carbapenem-resistant enterobacteriaceae (CRE) and *Escherichia coli* extended-spectrum β-lactamases cultures (ESBL). The *Artemisia annua* L. leaf extract (AnL) exhibited the highest TPC (518.09 mg/mL) and the highest expression of sinapic acid (285.69 ± 0.002 µg/mL). Nevertheless, the highest antioxidant capacity (1360.51 ± 0.04 µM Trolox/g DW by ABTS and 735.77 ± 0.02 µM Trolox/g DW by DPPH) was found in *Artemisia absinthium* L. leaf from the second year of vegetation (AbL2). AnL extract exhibited the lowest MIC and MBC for all tested bacteria and the maximal zone of inhibition for Klebsiella CRE and *Escherichia coli* ESBL. Our study revealed that AbL2 exhibited the best antioxidant potential, while AnL extract had the strongest antibacterial effect.
## 1. Introduction
There is an increasing interest in the antibacterial activity of herbal extracts, as they have been shown to be effective even on multidrug-resistant bacterial strains [1].
In 2015, the Nobel Prize for Physiology/Medicine was won by a doctor who discovered artemisinin (sesquiterpene lactone endoperoxide) to be an efficient treatment for malaria [2]. Artemisinin is a semisynthate found in all Artemisia plants in varying concentrations and is the most important active substance in *Artemisia annua* L. (A. annua L.) [3].
A. annua L., known as sweet wormwood, is a plant in the Asteraceae family that grows wild in Asia (primarily China, Japan, and Korea). It was imported to other countries such as Poland, Brazil, Spain, France, Italy, Romania, the United States, and Austria, where it was domesticated [4]. Since ancient times, Chinese herbalists have utilized it to treat a variety of ailments [5]. The mechanisms of action of A. annua L. and of artemisinin’s antimalarial effects is a current focus of research [6]. Furthermore, over the past few decades, research on A. annua L.’s effects on a variety of diseases, including inflammatory and cancerous conditions, and viral, bacterial, and parasite-related infections, has been performed [7,8].
Artemisia absinthium L. (A. absinthium L.), colloquially called wormwood, also belongs to the family Asteraceae (Compositae), of the tribe Anthemideae. It is a perennial, herbaceous, mesothermal, aromatic medicinal plant that has been used in traditional medicine from ancient times. The leaf and stem of wormwood, a very bitter-tasting plant, have traditionally been employed as a bitter tonic in appetite loss [9]. A. absinthium L.’s utility in gastrointestinal diseases is associated with its capacity to reduce the growth of microorganisms involved, due to its phenolic content [10].
There is an increasing interest in treating various degenerative diseases with different herbs and herbal extracts. Compounds with antioxidant activity, such as phenolic acids and flavonoids, are of interest to scientists as they can be further exploited [11]. Once elucidated, these compounds could be used in the pharmaceutical, cosmetic, and food industries [11,12].
The major bioactive antioxidant phenolic compounds found in Artemisia species are gallic acid, catechin, vanillic acid, caffeic acid, epicatechin, ferulic acid, sinapic acid, rutin, quercetin, luteolin, gentisic acid, chlorogenic acid, isoquercitrin, quercetol, kaempferol, and apigenin [13,14,15]. Phenolic compounds are widely distributed in plants, and they are associated with the prevention of several diseases in which oxidative stress plays an important role [16,17]. The amount of phenolic and flavonoid compounds in wormwood is positively correlated with its antioxidant capacity [18,19]. The health benefits of Artemisia include its antioxidant [20,21,22,23,24], neuroprotective [25], hepatoprotective [26], anti-inflammatory [27], renoprotective [28], and gastroprotective effects, and its digestive [29] and antibacterial activities [30,31,32]. The antibacterial activity of plants is a topic of interest for researchers because of the increasing antibacterial resistance to medications designed to kill them.
The objective of the current study was to investigate the phytochemical and antibacterial activities of leaf and stem ethanolic extracts of A. absintium L. and A. annua L. in different growing years.
## 2.1. Herb Samples and Ethanolic Extraction
The plant materials used in this study were the aerial parts (the stem and leaf) of A. absinthium L. and A. annua L. plants, from wild flora, collected at the end of June 2021, during the flowering period, from the outskirts of Blaj, Alba County, Romania. The samples were taxonomically authenticated at the University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca, Romania. The plants were dried naturally at room temperature in a dark room without light (11 days). After drying, they were ground to powder. Ethanolic extracts from wormwood leaf and stem were obtained according to the method of Marțiș et al., 2021 [33], with some modifications. The dried material (1 g) was mixed with 50 mL of $96\%$ ethanol for 24 h at 3–6 °C. Both samples were filtered through Whatman filter paper No. 4 and concentrated under reduced pressure at 35 °C, using a rotary evaporator (Rotavap Laborata 4010 Digital, Heidolph, Schwabach, Germany). The dried extract was recovered with 10 mL ethanol and stored at −18 °C until use. Three different replicates were performed for each extract’s extraction and all experiments were run in duplicates.
## 2.2. Reagents
Merck (Darmstadt, Germany) provided ethanol (HPLC grade), and Alpha Aesar, ThermoFisher provided 2,2′-Diphenyl-1-picrylhydrazyl radical (DPPH•, $95\%$) and 2,2′-Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS, $98\%$). ( ThermoFisher Kandel GmbH, Kandel, Germany). TCI supplied 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox, $98\%$). ( Portland, OR, USA). A Milli-Q Ultrapure water purification system was used to obtain analytical grade water (Millipore, Bedford, MA, USA).
## 2.3. Total Phenolic Content (TPC)
TPC was determined spectrophotometrically using the UV-Vis Specord 205 spectrophotometer (Analytik Jena GMbH, Jena, Germany) and Folin-Ciocalteu (FC) reagent, as previously published with minor changes [34]. In a 10 mL calibration flask, 0.4 mL of ethanol plant extract and 2 mL of FC reagent (diluted 1:1) were added. After shaking the mixture for 3 min, 1.6 mL of sodium carbonate solution ($7.5\%$) was added. Water was used to bring the solution to volume. The solutions were cooled after having been exposed at 50 °C for 10 min, and the absorbance at 760 nm was measured against a reagent blank (0.4 mL water + 2 mL FC reagent + 1.6 mL sodium carbonate solution). TPC was estimated using the basis of the gallic acid calibration curve and reported as gallic acid equivalents (GAE) per gram of sample. TPC was also calculated in mg GAE/mL.
## 2.4. Assessment of the Antioxidant Activity
Assay for radical scavenging with DPPH. The antioxidant activity of plant extracts was assessed using the modified DPPH technique [35]. The extracts’ free radical scavenging activity was assessed in comparison to the effects of standard solutions of ethanol Trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid) (0.02–0.1 mol/mL) or plant extracts on DPPH radical production, as follows: To 2 mL of ethanol and 0.5 mL of DPPH solution, 0.5 mL of each Trolox solution (or extract) was added. Then, 2.5 mL of ethanol was mixed with 2 mL of DPPH solution to make a control sample. The reactant mixture was vortexed for 30 s before being left to react in the dark for 30 min at room temperature. Each sample’s absorbance was recorded at 517 nm against a blank of ethanol. The antioxidant activity was calculated using the Trolox calibration curve and represented in micromoles per gram of material. Gallic acid was used as positive control.
Assay for radical scavenging ABTS•+. The antioxidant activity of plant extracts was determined using ABTS•+ in accordance with a previously established method [36] with adjustments. The procedure is based on the percentage inhibition of this radical’s peroxidation, which is visible as a darkening of a blue-green solution in an alkaline media at a wavelength of 734 nm. Amounts of 7 mM ABTS•+ solution and 2.45 mM potassium persulfate solution were included in the stock solutions. The working solution was then prepared by mixing equal parts of the two stock solutions and allowing them to react for 17 h at room temperature in the dark. After that, the solution was diluted by combining 1 mL of ABTS•+ solution with ethanol to obtain an absorbance between 0.700 and 0.800.
## 2.5. Quantitative Determination of Phenolic Compounds
The experiments of HPLC method [37] were conducted on a Jasco Chromatograph (Jasco International Co., Ltd., Tokyo, Japan) outfitted with a smart HPLC pump, an intelligent column thermostat, an intelligent UV/VIS detector, a ternary gradient unit, and an injection valve with a 20 µL sample loop (Rheodyne, Thermo Fischer Scientific, Waltham, MA, USA). The ChromPass® software was used to process the experimental data (version v1.7, Jasco International Co., Ltd., Tokyo, Japan).
At 22 °C, a Lichrosorb® RP-C18 column (25 × 0.46 cm) was used for separation, and UV detection was performed at 270 nm. The mobile phase was a solution of $0.1\%$ formic acid and ethanol (A, HPLC grade). At a flow rate of 1 mL/min, the mobile phase was a mixture of ethanol (A, HPLC grade) and $0.1\%$ formic acid solution (Millipore ultrapure water), and a gradient method was used: 0–10 min, linear gradient 10–$25\%$ A; 10–25 min, linear gradient 25–$30\%$ A; 25–50 min, linear gradient 35–$50\%$ A; 50–70 min, isocratic $50\%$ A. The injection volume was constantly 20 µL. The compounds were identified by comparing their elution periods to the ones of the standard compounds examined under the same HPLC circumstances.
Standards solutions. In ethanol, a stock standard solution (1 mg/mL of each) was produced and kept at 4 °C. The calibration curves were generated with four concentration levels ranging from 120 g/mL to 11.25 g/mL, with R2 values greater than 0.998.
## 2.6.1. Determination of the Minimum Inhibitory Concentration (MIC)
Escherichia coli ATCC 25922, *Staphylococcus aureus* ATCC 25923, *Salmonella enteritidis* ATCC 13076, and *Listeria monocytogenes* ATCC 19114 were examined as standard strains. They were cultivated for 24 h at 37 °C in a test tube containing 10 mL of sterile nutritional broth (Oxoid Ltd., Basingstoke, Hampshire, England). TBX agar was used for E. coli, BP agar for S. aureus, XLD agar for S. enteritidis (Oxoid Ltd., Basingstoke, Hampshire, England), and Palcam agar base enhanced with Listeria Palcam antimicrobic supplement (Oxoid Ltd., Basingstoke, Hampshire, England) for L. monocytogenes. Plates were incubated at 37 °C for 24 h. Optical microscopy was used to confirm bacterial morphology. Several colonies of each strain were distributed into sterile saline solution and corrected to match the turbidity of the McFarland 0.5 standard (1.5 × 108 CFU/mL) grown on Mueller–Hinton agar (Oxoid Ltd., Basingstoke, Hampshire, England). Then, for each microplate well, a 1.5 × 106 CFU/mL bacterial suspension was produced [38]. The MIC was obtained using a microtiter plate-based antibacterial test based on resazurin [39]. A 96-well microplate was filled with 100 µL of sterile nutritional broth (Oxoid Ltd., Basingstoke, Hampshire, England). The material was then added to the first well in 100 µL increments, and serial 11-fold dilutions were made in the remaining wells of each row by moving 100 µL from well to well. The excess 100 µL in the row’s final well was discarded. Then, in each well, 10 µL of inoculum (1.5 × 106 CFU/mL) was introduced. The positive control was gentamicin (0.04 mg/mL in saline solution), while the negative control was ethanol $96\%$. The microplates were incubated for 20–22 h at 37 °C, then 20 µL of 0.2 mg/mL resazurin aqueous solution was added into each well. The microplates were subsequently incubated for 2 h at 37 °C. After this period, resazurin (a blue nonfluorescent dye) was oxidized to resorufin (fluorescent pink) wherever viable bacterial cells were present. As a result, the concentration in the last well remained blue in each row and was considered to totally block bacterial growth and represented the MIC. For each sample, two replicates were performed.
## 2.6.2. Assessment of the Minimum Bactericidal Concentration (MBC)
The MBC was determined by plating a 10 µL aliquot on solid culture Mueller–*Hinton medium* from the last three wells that demonstrated inhibition of bacterial growth in the MIC assay (Oxoid Ltd., Basingstoke, Hampshire, England). The plates were incubated at 37 °C for 24 h. The MBC was defined as the lowest concentration that stopped bacterial growth (no colonies on the plate). For each plate, three separate biological replicates were performed, and all experiments were run in duplicate.
## 2.7. Bacterial Samples
Isolation of the bacterial strains was performed using selective chromogenic media CHROMID® ESBL (bioMérieux, Marcy-l’Étoile, France) and CHROMID® OXA-48 (bioMérieux, Marcy-l’Étoile, France). To identify the colonial morphology, the isolated strains were inoculated into the following media: Columbia blood agar (bioMérieux, Marcy-l’Étoile, France) and MacConkey agar (bioMérieux, Marcy-l’Étoile, France). The biochemical tests used for identification were as follows: TSI (triple sugar iron), MIU (motility indole urea), SIM (sulfide indole motility), citrate, PAD (phenylalanine deaminase), and OF (oxidation–fermentation). Only the strains that matched the colonial morphologies and biochemical profiles of Klebsiella spp. and E. coli were used later in this experiment. The antibiotic susceptibility profiles were determined using the Kirby–Bauer disk diffusion method. Moreover, the CRE (carbapenem-resistant enterobacteriaceae) phenotype was identified using the Diatabs™ (Rosco Diagnostica) disk diffusion synergy test on Mueller–Hinton agar. A total of 15 strains were used in this study: 5 strains of Klebsiella spp. ESBL, 5 strains of Klebsiella spp. CRE, and 5 strains of E. coli ESBL. Pathogens were obtained from the Department of Microbiology collection (Iuliu Hatieganu University of Medicine and Pharmacy Cluj-Napoca).
To test the antibacterial effects of the studied extracts, antibiograms were performed using the Kirby–Bauer disk diffusion method [1,40]. Mueller–*Hinton media* were inoculated with 0.5 McFarland bacterial suspensions using the spread plate technique. Sterilized filter paper disks, 5.49 mm in diameter, imbued with 5 microliters of the studied extracts, were used to evaluate the antibacterial activity. The media were incubated at 37 °C for 24 h, and the zones of inhibition were measured thereafter.
## 2.8. Statistical Analysis
The ANOVA analysis of variance was used to compare the average mean values, with a confidence interval of $95\%$ or $99\%$, using SPSS 19.0 statistical analysis (IBM, New York, NY, USA) and Tukey’s honestly significant differences (HSD) test. A p-value of less than 0.05 was deemed statistically significant.
## 3.1. Total Phenolic Content of Different Tissues of Artemisia Extracts
Table 1 is a summary of the phenolic content found in the different tissues of the A. annua L. and A. absinthium L. samples. It is striking that these components were higher in the leaf from the second year of vegetation than in all the other parts examined in this study. For the A. annua L. leaf (AnL), we measured 518.09 ± 0.01 mg GAE/mL.
## 3.2. Antioxidant Activity
Two different chemical methods, namely, DPPH and ABTS assays, were used to assess the antioxidant activity of the studied wormwood extracts (Table 1). The leaf and stem of A. absinthium L. extracts from the second year of vegetation had higher values as compared to the leaf extract from the first year. The values obtained using ABTS were higher than those obtained using DPPH. As expected, the levels of antioxidant capacity were significantly different ($p \leq 0.001$) among different plant tissues for both Artemisia species.
The intensity of relationships between the TPC, DPPH, and ABTS was determined with Pearson’s correlation with a $95\%$ confidence interval. Statistically significant correlations were established (p ≤ 0.05) between the DPPH free radical scavenging activity and TPC values in the leaf of both Artemisia species ($r = 0.967$) using Pearson’s correlation test (Table 2).
## 3.3. Phenolic Compound Profile by HPLC
Phenolic compounds from plants such as rutin, catechin, and ferulic acid have received increasing interest due to their potential antioxidant activity. Eleven phenolic compounds were found in the Artemisia species (Table 3, Supplementary Materials using a chromatographic analysis of the ethanolic extracts). Two phenolic acids, i.e., vanillic acid and p-coumaric acid, were present in both the leaf and stem.
From the flavan-3-ols, epicatechin was the dominant compound in A. annua L. and A. absinthium L.
## 3.4. Antibacterial Activity of Different Tissues of Artemisia
The results of the antibacterial assay are presented in Table 4. The following standard strains were tested: *Escherichia coli* ATCC 25922, *Staphylococcus aureus* ATCC 25923, *Salmonella enteritidis* ATCC 13076, and *Listeria monocytogenes* ATCC 19114. The ethanolic extract of the A. annua L. leaf exhibited antibacterial activity against all the bacterial strains tested. The MIC of the ethanolic extract of AnL ranged from <2.00 ± 0.014 mg/mL (against S. aureus ATCC 25923) to 375.00 ± 0.014 mg/mL AbS1 (against E. coli ATCC 25922 and S. enteritidis ATCC 13076). The MBC of the A. annua L. ethanolic extract ranged from 5.00 ± 0.014 mg/mL (against S. aureus ATCC 25923 and L. monocytogenes ATCC 19114) to 375.00 ± 0.014 mg/mL AbS1 (against S. aureus ATCC 25923, E. coli ATCC 25922, S. enteritidis ATCC 13076, and L. monocytogenes ATCC 19114).
The antibacterial effects exhibited by wormwood were significant as compared to the ethanol $96\%$ controls ($p \leq 0.05$) (Table 5). Our findings show that the ethanolic extracted from A. annua L. and A. absinthium L. possessed significant antibacterial effects against Klebsiella ESBL, Klebsiella CRE, and E. coli ESBL.
## 4.1. Phytochemical Characteristics of Extracts
The antioxidative effects of plants in the *Artemisia genus* are most probably due to the high amounts of phenolic compounds.
The polyphenolic profiles of the extracts from the leaf and stem of Artemisia species were assessed as a source of natural antioxidants.
The highest values of TPC were found in AnL (518.09 ± 0.01 mg GAE/mL) and in AbL2 (487.36 ± 0.08 mg GAE/mL). Intermediate values were determined for AbL1 (229.68 ± 0.16 mg GAE/mL) and AnS (135.34 ± 0.08 mg GAE/mL). The lowest values were found in AbS2 (60.59 ± 0.20 mg GAE/mL) and in AbS1 (51.73 ± 0.11 20 mg GAE/mL). In our study, ethanolic extracts of leaves had higher TPC than ethanolic extracts of stems, regardless of the species and year of vegetation.
Lee proposed three other extraction methods for A. absinthium L. leaf from South Korea: ethyl acetate, methanol, and water [41]. The best TPC extraction rate was found for the aqueous leaf extract at 134.47 ± 0.016 mg/100 g DW. Since the values obtained in the present study are higher (Table 1), we believe ethanol extraction to be more efficient than the solvents listed above. Similar results were recently communicated by Sembirin, who showed that the amount of antioxidant compounds extracted from A. annua L using an ethanol solvent was higher than the amount of antioxidant compounds extracted by a methanol solvent [42]. A higher value was also observed for the hydroalcoholic extract of A. absinthium L. from India, obtained from the aboveground parts of the plant (9.29 ± 0.51 mg GAE/g DW), as compared to hexane (0.43 ± 0.07 mg GAE/g DW) and methanol (3.55 ± 0.39 mg GAE/g DW) extracts [43].
In previous studies, it was shown that the strength of antioxidant activity was influenced by the content of phenolic compounds and total flavonoids [8,34,35].
In our study, the antioxidant activity was not directly proportional to the TPC from the leaf and stem ethanolic extracts of each individual species of Artemisia. Only in the global analysis of the leaf extracts was a high positive correlation found between TPC and antioxidant activity for both types of determinations, DPPH and ABTS (Table 2). Among the analyzed extracts, AbL2 had the highest antioxidant capacity for both determination methods (ABTS and DPPH). We found that the decreasing order of antioxidant activity among the different extracts from the aerial parts of wormwood was the following: AbL2 (735.77 ± 0.02 µM Trolox/g DW) > AnL (250.51 ± 0.01 µM Trolox/g DW) for DPPH method; AbS1 (1314.38 ± 0.01) > AnS (659.57 ± 0.02 µM Trolox/g DW) for the ABTS method. Previously published studies also found that the antioxidant capacity was not necessarily directly proportional to the amount of active compounds from the plant. Minda showed that Artemisiae annue herba had an antioxidant activity (DPPH method) of 24.14 ± $0.6\%$ at a 50 µg/mL concentration and reached only 90.04 ± $2.25\%$ at a 1000 µg/mL concentration [15].
Concerning the growing year of the A. absinthium L. leaf, there was an approximate 12-fold increase in the antioxidant activity in the second year as compared to the first year (the DPPH method).
Comparing the two varieties of wormwood in the first year of growth, the antioxidant activity was significantly higher in A. annua L. as compared to A. absinthium L. for both methods used (DPPH and ABTS). However, for the stem in the first year of vegetation, the order of the varieties changed in favor of A. absinthium L. (AbS1 > AnS). Moreover, the antioxidant activity of the A. absinthium L. stem extract was slightly higher than that of the A. absinthium L. leaf extract in the first year of vegetation. These results are consistent with the study of Moacă [9].
Sengul obtained the highest total phenolic content in A. absinthum (9.79 µg GAE/mg), followed by A. santonicum (15.38 µg GAE/mg) and *Saponaria officinalis* (6.57 µg GAE/mg), with a positive correlation ($r = 0.819$) between the antioxidant activity and the TPC of the plant samples [44].
Many studies reported a strong relationship between the TPC and the antioxidant activity in certain plant products [19,21,33,44,45,46]. In our study, we found a positive and extremely high correlation ($r = 0.959$, $$p \leq 0.0001$$) between the TPC and the antioxidant activity (DPPH) when all plant extracts were taken into account. When leaf and stem extracts were individually assessed, the correlation coefficient between TPC and DPPH was $r = 0.967$ ($$p \leq 0.0001$$) for the wormwood leaf samples. Unexpectedly, an extremely high negative correlation (r = −0.949, $$p \leq 0.001$$) was found between the TPC and DPPH for the stem.
On the basis of the HPLC analysis and the calibration curves of the standard samples, the phenolic compound content was determined in all extracts (Table 3). The leaf extract of A. annua L. was found to be the richest in bioactive compounds (AnL > AnS), and it had high levels of sinapic acid (285.694 ± 0.002 µg/mL), p-coumaric acid (51.267 ± 0.002 µg/mL), vanillic acid (46.863 ± 0.002 µg/mL), and rutin (17.320 ± 0.000 µg/mL).
Sinapic acid (3,5-dimethoxy-4-hydroxycinnamic acid) is the most representative phytochemical hydroxycinnamic acid of the flavonoid compounds identified. In accordance, the results of Baiceanu also indicated high levels of sinapic acid in other herbal extracts of the *Artemisia genus* (A. abrotanum L. 79.95 µg/mL) [47]. Sinapic acid is a natural compound with various potential health benefits, including antibacterial [48], antioxidant [49,50], anti-inflammatory [51,52], antihypertensive, cardioprotective [53], anxiolytic [54], and antiaging effects [55].
Quercetin, which is a flavonol, was identified in only two extracts. The highest amount was found in AbS1 (8.492 ± 0.002 µg/mL), and the lowest in AnL (1.653 ± 0.003 µg/mL). Quercetin possesses antioxidant, anti-inflammatory, neuroprotective, cardioprotective, antiobesity, anticancer, and antimicrobial activity. Quercetin antimicrobial activity against Gram-positive and Gram-negative bacteria, including various drug-resistant microorganisms, could be explained by its capacity to damage microbial cell membrane, to inhibit nucleic acids and proteins synthesis, to reduce expression of virulence factors and to prevent biofilm formation [56].
Epicatechin possesses antioxidant, anti-inflammatory, vasoprotective, neuroprotective, anticancer, and antimicrobial activity [57]. In a previous study, epicatechin demonstrated an inhibitory effect on *Helicobacter pylori* growth [58]. In our study, the highest content of epicatechin was recorded in the AbS2.
Gallic acid is another hydroxybenzoic acid that modulates the immune response and antimicrobial natural defense. Due to its antimicrobial activity, gallic acid is used to synthesize trimethoprim, an antimicrobial agent [59]. In our study, gallic acid was found in a higher amount in AnL (1.132 ± 0.001 µg/mL) and in a lower amount in AnS (0.086 ± 0.004 µg/mL), but it was not detected in the A. absinthium L. extracts. In contrast, in a study focused on the chemical compounds in the aerial part of Romanian A. absinthium extracts, a small amount of gallic acid (0.092 ± 0.005 mg/g DW) was observed [46]. In an A. absinthium leaf extract from South Korea, Lee found the amount of gallic acid to be 63.99 ± 0.827 µg/g [41].
Vanillic acid is an antioxidant monohydroxybenzoic acid with antimicrobial activity against S. aureus and E. coli [60]. The highest amount of vanillic acid was identified in AbL2 (66.777 ± 0.002 µg/mL) and the lowest was recorded in AbS1 (2.420 ± 0.002 µg/mL). The decreasing order of samples for vanillic acid was as follows: AbL2 >AnL > AbL1 > AbS2 > AnS > AbS1.
Caffeic acid was not detected in any sample from the stem or leaf from either variety. The antioxidant activity of certain phenolic acids indicated the following order: caffeic acid > sinapic acid > ferulic acid > p-coumaric acid.
p-Coumaric acid has antioxidant and bactericidal activity based on DNA and bacterial cell membrane damages [61]. In the present study, the highest amount of p-coumaric acid was found in the AnL (51.267 ± 0.002 µg/mL). Another p-coumaric acid value reported for wormwood leaf extracts was 9.10 ± 0.141 µg/g [41].
Ferulic acid acts as a superoxide scavenger, similarly to superoxide dismutase [62]. It also exhibited anti-inflammatory, antidiabetic, and anticancer effects and antimicrobial activity [63]. In our study, the ferulic acid amount in the analyzed samples was low, in accordance with the findings of other studies [41,46].
The differences between the phenolic compound values in the leaf and stem of A. absinthium L. were evident for the wormwood extracts in the first year of growth. The amounts of phenolic compounds were higher in AbL1 (42.241 ± 0.001 µg/mL for vanillic acid, 13.488 ± 0.001 µg/mL for epicatechin, and 2.565 ± 0.002 µg/mL for p-coumaric acid) than in AbS1. The exception was catechin, whose value was higher in the stem extract than in the leaf extract (2.438 ± 0.002 µg/mL in AbS1, 1.262 ± 0.002 µg/mL in AbL1), indicating a higher antioxidant activity in the stem.
Differences between the phenolic profile of the leaf and the stem ethanolic extracts of A. absinthium L. were also observed in the second year of growth. The amounts of phenolic compounds were higher in AbL2 (66.777 ± 0.002 µg/mL for vanillic acid and 1.375 ± 0.002 µg/mL for p-coumaric acid) than in AbS2. Epicatechin was found in high amounts in AbS2 (21.123 ± 0.001 µg/mL).
Flavonoids, such as rutin, quercetin, epicatechin, and catechin, involved in free-radical scavenging activity were also reported in other studies focused on wormwood extracts. Some additional phytocompounds were identified in other studies, including gentisic acid, chlorogenic acid, caffeic acid, isoquercitrin, quercetol, kaempferol, and apigenin [15]. Free-radical scavenging activity and anti-inflammatory activity was demonstrated for these pharmacophores [64,65,66,67,68].
## 4.2. Antibacterial Effects
The inhibitory activity of herbal extracts against Gram-positive bacteria, especially S. aureus, has been widely reported in the literature [69]. Wormwood’s significant antibacterial activity against surgical wounds infected with S. aureus (the most common cause of surgical wound infections) in a rat model was reported by Moslemi [31]. In our study, the highest antibacterial activity (MIC = 2.00 ± 0.014 mg/mL and MBC = 5.00 ± 0.014 mg/mL) against S. aureus was recorded for AnL extract. The AnL antibacterial activity could be attributed to the sinapic acid (285.694 ± 0.002 mg/mL). Previous in vivo studies conducted on Gram-positive and Gram-negative bacteria found that sinapic acid exhibited significant antibacterial activity against various microorganisms [55].
AbL2 extract was found to be in the second place with its efficacy against S. aureus, with MIC = 25.00 ± 0.002 mg/mL and MBC = 54.00 ± 0.014 mg/mL. For AnS, with MIC = 54.00 ± 0.002 mg/mL and MBC = 114.00 ± 0.014 mg/mL, the antibacterial activity was also shown to be satisfactory.
The antibacterial activity against S. aureus for AbL2, in which the phenolic compounds gallic acid, caffeic acid, ferulic acid, sinapic acid, rutin, quercetin, and luteolin were not detected, could be due to vanillic acid. In a previous study, Keman showed the importance of vanillic acid for treatment in methicillin-resistant S. aureus infections [70].
The antimicrobial effects against S. aureus found for AbS2 (MIC = 114.00 ± 0.014 mg/mL, MBC = 114.00 ± 0.014 mg/mL), AbL1 (MIC = 89.50 ± 0.028 mg/mL, MBC = 255.00 ± 0.014 mg/mL), and AbS1 (MIC = 85.00 ± 0.002 mg/mL, MBC = 375.00 ± 0.014 mg/mL) were low.
The chemical composition of A. absinthium L. differs according to geographical area [71], the physiological part of the plant [72], the temperature [73], and the degree of senescence [74]. For this reason, there is no standard chemical composition and antibacterial activity.
Valdes studied the antibacterial activity of Cuban medicinal plants, wormwood ethanolic extract included, and found no antibacterial activity related to the wormwood extract for the concentrations tested (64 µg/mL to 0.25 µg/mL) [75]. In another study, Fiamegos also demonstrated that chloroform extracts from A. absinthium L. leaf (in a concentration range of 150–500 mg/mL), tested on pathogenic bacteria, had no antibacterial activity against E. coli but inhibited S. aureus [30].
Another pathogenic bacterium used to test the efficacy of the wormwood extracts in our study was E. coli. We noticed similarities between the activity against the two pathogenic bacteria: S. aureus and E. coli. The most pronounced antibacterial activity against E. coli was identified for the AnL extract, with MIC = 5.00 ± 0.014 mg/mL and MBC = 12.00 ± 0.014 mg/mL. It has to be noted that this extract contains a wide range of phenolic compounds. Thus, the extract’s antibacterial effect could be correlated to them. We also found significant antibacterial activity in AbL2 (MIC = 54.00 ± 0.014 mg/mL and MBC = 54.00 ± 0.002 mg/mL) and in AnS (MIC = 54.00 ± 0.014 mg/mL and MBC = 114.00 ± 0.014 mg/mL). A low E. coli inhibition activity was recorded for AbL1 (MIC = 255.00 ± 0.014 mg/mL and MBC = 255.00 ± 0.014 mg/mL), similarly with AbS2 (MIC = 240.00 ± 0.014 mg/mL and MBC = 240.00 ± 0.014 mg/mL). The extract with the weakest antibacterial activity was that from AbS1 (MIC = 375.00 ± 0.014 mg/mL, MBC = 375.00 ± 0.014 mg/mL).
A lot of other researchers identified the antibacterial activity of different wormwood species. In his research, Baykan Erel demonstrated the moderate effect of A. absinthium L. methanolic extract on E. coli ATCC29998 and on E. coli ATCC11230, with 10 mm and 7 mm inhibition zones, respectively [76]. Sengul also reported antibacterial activity for two types of extracts: aqueous and methanolic, from the aerial parts of A. absinthium L. The inhibition zones reported for S. aureus ATCC29213 were 12 mm for the aqueous extract and 15 mm for the methanolic extract; meanwhile, for E coli 1328, the inhibition zones were weaker: 7 mm for the aqueous extract and 11 mm for the methanolic extract [44].
Mihajilov-Krstev demonstrated that the MIC of A. absinthium L. essential oil ranged from <0.08 mg/mL for S. aureus isolated from the wound to 0.30 mg/mL against S. aureus ATTC 25923. The MBC of A. absinthium L. essential oil ranged from <0.08 mg/mL for S. aureus isolated from the wound to 0.61 mg/mL against S. aureus ATTC 25923. The same author showed that the MIC of A. absinthium L. essential oil ranged from 1.21 mg/mL for E. coli isolated from stool and against E. coli. ( ATTC) 8739 to 0.39 mg/mL for E. coli isolated from wounds. The MBC of A. absinthium L. essential oil ranged from 2.43 mg/mL for E. coli isolated from stool to 2.43 mg/mL for E. coli isolated from wounds and against E. coli ATTC 8739. In the same study, the MIC of A. absinthium L. essential oil against L. monocytogenes was 0.30 mg/mL and the MBC was 38.80 mg/mL [77]. Sultan demonstrated the antibacterial activity against E. coli and S. aureus bacteria for a reaction mixture prepared by dissolving hot methanolic extract A. absinthium L. leaf in Milli-Q water [78]. Lopes-Lutz demonstrated that A. absinthium L. essential oil was one of the most active agents against Staphilococcus strains and that it also had antibacterial activity against E coli. The zone of inhibition expressed in millimeters for S. aureus was high (25 ± 1.4 mm), confirming our results, while it was significantly lower (5 ± 0.0 mm) for E. coli [79]. Msaada studied the antibacterial activity of A. absinthium L. essential oil from four different areas of Tunisia. The highest antibacterial activity was recorded against S. aureus 25923 for the essential oil from Kairouan (25 ± 1.13 mm diameter of inhibition), followed by those from Jerissa (diameter of inhibition of 20.66 ± 0.65 mm), Boukornine (diameter of inhibition 20.66 ± 2.61 mm) and Bou Salem (18 ± 1.13 mm diameter of inhibition) [71]. On the other hand, Joshi, who also studied the activity of A. absinthium L. essential oil from India, did not identify any antibacterial activity for S. aureus and E. coli [80]. Likewise, Jouteau, tested the antibacterial activity of A. absinthium L. essential oil against S. aureus (CIP 53154) and E. coli (CIP54127) using the liquid diffusion method and found no effect at the tested concentrations [81].
The antibacterial activity of the extracts against S. enteritidis ATCC 13076 was also investigated. As compared to the other bacteria assessed in this study, poor antibacterial activity against this bacterium was evident. We observed that the AnL extract exhibited a good action against all bacteria, and S. enteritidis was no exception, with MIC = 5.00 ± 0.014 mg/mL and MBC = 12.00 ± 0.014 mg/mL. Moreover, AbS1 had the weakest antibacterial activity against all bacteria considered, with MIC = 375.00 ± 0.014 mg/mL and MBC not detected for S. enteritidis ATCC 13076. A moderate antibacterial activity was identified for AbL2, with MIC = 54.00 ± 0.002 mg/mL and MBC = 54.00 ± 0.002 mg/mL. Low antibacterial activity was also identified for AbL1, with MIC = 255.00 ± 0.014 mg/mL and MBC not detected. On the other hand, Kordiali found no antibacterial activity against S. enteriditis ATCC 13076, S. aureus ATCC 29213, or E. coli for the essential oil obtained from aerial parts of A. absinthium L. from Turkey [18]. Based on our research and the aforementioned studies, we can state that the plant origin area and the type of extract used (ethanolic, methanolic, aqueous, etc.) can cause differences in the antimicrobial activity of wormwood extracts.
In order to support the above mentioned findings, Msaada studied the antibacterial activity of A. absinthium L. essential oil from four different areas of Tunisia against L. monocytogenes ATCC 19195 and found different inhibitory areas: 20.00 ± 1.13 mm and 20.00 ± 1.95 mm were recorded for the essential oil from the Bou Salem and Kairouan areas (the highest values), 18.66 ± 2.35 mm for the essential oil from Boukornine, and 17.33 ± 1.72 mm for the essential oil from the *Jerissa area* [71].
In our study, the best antibacterial activity against L. monocytogenes ATCC 19114 was found in AnL, with MIC = 5.00 ± 0.014 mg/mL and MBC = 5.00 ± 0.014 mg/mL. The MIC against L. monocytogenes ATCC 19114 of the ethanolic extract of A. absinthium ranged from 54.00 ± 0.002 mg/mL (AbL2) to 178.00 ± 0.014 mg/mL (AbS1). The year of vegetation positively influenced the MIC and MBC values of A. absinthium L. The leaf and stem of A. absinthium L. from the second year of vegetation had better mean MIC and MBC values than those from the first year (e.g., MIC = 54.00 ± 0.002 mg/mL for AbL2 and MIC = 121.00 ± 0.014 mg/mL for AbL1). As compared to MIC (0.3 mg/mL) and MBC (38.80 mg/mL) against L. monocytogenes ATCC 7644 of the essential oil from the A. absinthium family harvested from Serbia, the value was higher in our sample [77].
L. monocytogenes ATCC 19114 was differently influenced by the ethanolic stem extracts of the plants included in this study. Thus, the A. annua L. and A. absinthium L. stem samples from the second year of vegetation exhibited better antibacterial activity than those from the first year (AnS = AbS2 > AbS1). This could be explained by the fact that there was approximately twice the amount of polyphenols and flavonoids in the leaf vs. stem (Table 5), which is in accordance with other studies [82].
In an A. annua L. leaf studied until senescence, Lommen found the maximum amount of artemisinin in the leaf after the onset of senescence [74]. In our study, the amount of vanillic acid, ranging from 66.777 ± 0.002 mg/mL in the second year to 42.241 ± 0.001 mg/mL in the first year, was responsible for the antibacterial activity, which was significantly higher for the second year of vegetation in the AbL2 extract on all strains tested (S. aureus ATCC 25923, E. coli ATCC 25922, L. monocytogenes ATCC 19114, and S. enteritidis ATCC 13076).
Antibacterial activity against carbapenem-resistant enterobacter hormaechei (CREH) as mediated by vanillic acid was studied by assessing variations in the intracellular ATP concentration, intracellular pH, and membrane potential [83]. Moreover, the addition of vanillic acid (500 µg/mL vanillic acid $65\%$) to the growth medium of S. marcescens ATCC 14756 and MG1 significantly affected biofilm production and virulence in a concentration-dependent manner [84]. Vanillin, ethyl vanillin, and vanillic acid may be useful for controlling Cronobacter spp. in food during preparation and storage, and disrupting the cell membrane of CREH [85]. Various Artemisia species were shown to produce metabolites with antibacterial activity. Furthermore, in the ethanolic extract, a high level of chlorogenic acid was found in a tall species of the genus Asteraceae (A. gmelinii). Recent studies show that chlorogenic acid bonds to the outer membrane, disrupts it, depletes the intracellular potential, and releases macromolecules from the cytoplasm, leading to cell death [14].
Artemisia extracts exhibited potent antibacterial activity against selected clinically-important pathogenic bacteria as judged by the low MIC values. The results of the present study demonstrate the significant antibacterial activity of wormwood ethanolic extract against Klebsiella spp. ESBL, Klebsiella spp. CRE, and E. coli ESBL (Table 5).
Our findings indicate that AnL, AbL1, and AbS1 from the first year of vegetation had significant activity against Klebsiella ESBL (10.863 ± 0.308 mm for AnL; 10.110 ± 1.68 mm for AbL1; 11.246 ± 1.71 mm for AbS1). The vanillic acid and epichatechin found in the aforementioned samples conferred antibacterial properties to the extracts. It is well-established that flavonoids have multiple hydroxyl groups and, therefore, have a pronounced potential to bind proteins. The inhibition of the binding affinity of KpDnaB to dNTPs (deoxyribonucleoside triphosphate) in *Klebsiella pneumonia* by flavonols could explain their antibacterial activity [86].
Significant antibacterial action against Klebsiella CRE was found in samples of A. annua L., both in the leaf and stem, with sinapic acid well-represented in the extracts (12.756 ± 0.993 mm for AnL; 9.843 ± 0.945 mm for AnS). AnL and AnS extracts appeared to have the best effect against E. coli ESBL (8.610 ± 1.861 mm, 5.67 ± 0.682 mm, respectively). The antibacterial activity of sinapic acid was demonstrated in various studies on both plant and human pathogens [87], including E. coli [88]. As a result of their capacity to form hydrogen bonds with amino-acid residues of theactive site of the NorA efflux pump, sinapic acid exhibits a significant antibacterial activity against the NorA-bearing Gram-positive and Gram-negative bacteria, S aureus, and E. coli. Moreover, they can be safely administered orally and can penetrate the cell wall to reach the NorA active site [89].
## 4.3. Limits of the Study
In addition to the methods used by us (DPPH for stable radicals and ABTS for cation radicals), other methods for determining the antioxidant activity of wormwood extract should also be used, such as chemical-based methods (the cupric ions reducing power assay and ferric reducing antioxidant power) or biological assays (cellular antioxidant activity assay) [90].
In order to draw firm conclusions concerning the influence of the vegetation year, both Artemisia species should be analyzed in the first and in the second year.
## 5. Conclusions
The year of vegetation, the part of the plant, and the species influenced the TPC of the wormwood extract. The highest value was obtained for the leaf sample in the second year of vegetation. As regards the species, A. absinthium L. registered the highest TPC, with leaf superior to stem. Sinapic acid was abundant in A. annua leaf/stem extracts. In all ethanol leaf samples, vanillic acid was present in significant amounts. Concerning the activity of wormwood extracts against S. aureus, the results showed that the leaf, rich in phenolic compounds, had a higher antibacterial activity than the stem.
The antibacterial activity against S. aureus depended on the growing year of the plants. A. absinthium extracts from the first year of vegetation exhibited a weaker antibacterial activity than A. absinthium extracts from the second year. The A. annua L. species, rich in polyphenolic compounds, mainly in the leaf, was proven to have antibacterial activity against Salmonella enteritidis. From all the Artemisia extracts studied, AnL and AnS exhibited significant activity against Klebsiella spp. CRE and E. coli spp. ESBL. Thus, on the basis of our results and the recent literature, the application of new therapeutic protocols for resistant infectious diseases based on the use of natural extracts of *Artemisia is* a real possibility and should be further studied.
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|
---
title: Ginger (Zingiber officinale) Root Capsules Enhance Analgesic and Antioxidant
Efficacy of Diclofenac Sodium in Experimental Acute Inflammation
authors:
- Ioana Boarescu
- Raluca Maria Pop
- Paul-Mihai Boarescu
- Ioana Corina Bocșan
- Dan Gheban
- Adriana Elena Bulboacă
- Anca Dana Buzoianu
- Sorana D. Bolboacă
journal: Antioxidants
year: 2023
pmcid: PMC10045259
doi: 10.3390/antiox12030745
license: CC BY 4.0
---
# Ginger (Zingiber officinale) Root Capsules Enhance Analgesic and Antioxidant Efficacy of Diclofenac Sodium in Experimental Acute Inflammation
## Abstract
Our study aimed to evaluate the analgesic and antioxidant effects of ginger (Zingiber officinale) root capsule extract (GRCE) in addition to diclofenac (D) sodium treatment in carrageenan-induced acute inflammation (AI). Seven groups of eight Wistar-Bratislava white rats were included in the study. One group was the control (C), and AI was induced in the other six groups. The following treatments were applied: saline solution for C and AI groups, D for the AID group, GRCE for two groups and GRCE and D for another two groups. The GRCE was administered by gavage in two doses (100 mg/Kg b.w. or 200 mg/kg b.w.), while D was administered intraperitoneally in a dose of 5 mg/kg b.w. The association of GRCE with this low dose of diclofenac reduced pain threshold and improved mobility with the best results for the dose of 200 mg/kg b.w. Moreover, this combination reduced, better than D alone, the serum levels of the evaluated pro-oxidant parameters (malondialdehyde, the indirect assessment of NO synthesis, total oxidative status and oxidative stress index) up to $78\%$, especially oxidative stress index ($p \leq 0.0001$). GRCE alone slightly improved the antioxidant parameters (total antioxidant capacity and total thiols), but when associated with, D the results were better, especially for total thiols as their plasma levels increased up to $50\%$ ($p \leq 0.0010$), with the best results obtained for the 200 mg/kg b.w. dose of GRCE. In conclusion, ginger root capsules associated with diclofenac might offer additional antioxidant and analgesic effects in a dose-dependent manner in acute inflammation.
## 1. Introduction
The carrageenan-induced paw edema is the most commonly used animal model of acute inflammation [1]. Moreover, it is a well-defined model used to evaluate the anti-inflammatory and anti-edematous potential of pharmacological substances, as there is a variety of inflammatory mediators involved in its development [2,3,4,5].
Acute inflammation has two main components: vascular changes associated with cellular events. Carrageenan is a natural linear sulfated polysaccharide and the sulfated sugars present in carrageenan are responsible for the production of vascular and cellular events of inflammation due to the activation of inflammatory mediators [6]. Oxidative has a major impact in the pathophysiological mechanisms of acute inflammation, as it can activate various transcription factors, leading to differential expression of some genes involved in the inflammatory pathways [4]. Oxidative stress is defined as an imbalance between the production of reactive oxygen species (ROS) and their neutralization by the antioxidant system. Moreover, this imbalance can be responsible for damaging cellular molecules such as deoxyribonucleic acid (DNA), lipids or proteins [7].
Medications such as nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly used in the management of acute inflammation. Diclofenac (2-[(2,6-dichlorophenyl)amino] benzenacetic acid), a well-known NSAID drug, exerts its anti-inflammatory effects through the inhibition of the arachidonate metabolites synthesis secondary to cyclooxygenase (COX) inhibition [8]. Diclofenac was observed to possess dose–response relationships for COX-2 and COX-1 inhibition, with greater COX-2 selectivity [9]. Moreover, it was observed to significantly reduce the production of pro-inflammatory cytokines, such as Tumor Necrosis Factor-α (TNF-α) and Interleukin-6 (IL-6) in acute inflammation [10]. Administration of NSAIDs may cause side effects such as hypertension, acute renal failure, gastrointestinal ulcers, serious cardiovascular events and even worsen preexisting heart failure. Limitation of NSAIDs’ side effects can be achieved by a reduction in dosage and treatment duration [11].
Medicinal plants have been used throughout history as a popular method of therapy for pain relief [12]. Zingiber officinale roscoe (Z. officinale), commonly known as ginger, is a member of the Zingiberaceae family and has been widely used as a spice [13,14]. Major biologically active compounds, such as gingerols, shogaols and paradols can be found in Zingiber officinale, but the chemical analysis shows that it contains more than 400 different compounds [15]. In experimental studies conducted in rodents, Zingiber officinale was reported to have various therapeutic effects such as anti-emetic in cancer chemotherapy, hypoglycemic in and streptozotocin-induced diabetes mellitus model and anti-inflammatory in egg albumin-induced pedal edema [16,17,18]. Moreover, it was observed to attenuate muscle pain significantly [19] and to reduce injury-induced neuropathic pain [20,21] and oxaliplatin-induced neuropathic pain [22].
Various in vivo and in vitro tests have explored the anti-oxidative properties of ginger and its components [23,24,25,26]. In an animal model study, it was shown that ginger significantly raised the levels of antioxidant enzymes, together with serum glutathione and lowered induced lipid peroxidation [24]. Among its components, 6-Shogaol was observed to exhibit the most potent antioxidant and anti-inflammatory properties in ginger, these effects being attributed to the presence of the alpha, beta-unsaturated ketone moiety [25]. Another component, 6-gingerol, might have an enhanced antioxidant effect in protection from oxidative damage caused by free ROS, as a result of its free radical-scavenging ability [26].
Gingerol, shogaol and other structurally-related compounds in ginger express their anti-inflammatory effects through inhibition of the prostaglandin and leukotriene biosynthesis, as a result of 5-lipoxygenase or prostaglandin synthetase suppression [23]. The inhibition of the pro-inflammatory cytokines such as Interleukin-1 (IL-1), TNF-α and Interleukin-8 (IL-8) was described as another anti-inflammatory mechanism observed for ginger [27,28]. Moreover, it was already reported that shogaol can down-regulate inflammatory inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) gene expression in macrophages [29].
Our study aimed to evaluate the analgesic and antioxidant effects of ginger (Zingiber officinale) root capsule extract in addition to diclofenac sodium in carrageenan-induced acute inflammation.
## 2. Materials and Methods
The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Iuliu Hațieganu University of Medicine and Pharmacy Cluj-Napoca (approval no. $\frac{25}{3}$ February 2021) and by the Sanitary-Veterinary and Food Safety Directorate from Cluj-Napoca (approval no. $\frac{252}{17}$ March 2021).
## 2.1. Chemicals and Drugs
Saline solution ($0.9\%$) and diclofenac sodium injection were purchased from a local pharmacy in Cluj-Napoca.
## 2.2. Plant Material
Ginger root capsule extract (GRCE) (Solaray, Park City, UT, USA) was purchased from a local pharmacy where the capsules were commercialized as a food supplement. As stated in the pamphlet, the 250 mg capsules have the following ingredients: ginger (Zingiber officinale) (root extract) (guaranteed 12.5 mg ($5\%$) gingerols), ginger (Zingiber officinale) (root) 100 mg, magnesium carbonate, vegetable cellulose capsule, maltodextrin, magnesium stearate, silica and croscarmellose sodium.
## 2.3. Extraction of Ginger Root Capsules
The content of 10 ginger root capsules was extracted with 20 mL ethanol on a magnetic stirrer for 1 h. Afterward, the mixture was kept in dark conditions at 4 °C for 24 h, followed by filtration (Whatman filter paper no.3). The pellet was resuspended again in 10 mL ethanol and the mixture was sonicated for 30 min at room temperature and filtered (Whatman filter paper no.3). The ginger root capsule extract (GRCE) was further analyzed for its phytochemicals compounds, total polyphenols content and total antioxidant capacity.
## 2.4. Total Polyphenol Content
Total polyphenols content (TPC) was evaluated using Folin–Ciocalteu as previously described by Pop et al. [ 30]. Ginger root capsules extract (25 μL of) was mixed with Folin–Ciocalteu reagent (125 μL; 0.2 N) and sodium carbonate (Na2CO3) solution (100 μL; $7.5\%$ w/v), homogenized, put in 96-well plates and incubated at room temperature in dark conditions. After 2 h of incubation, the plates were read at 760 nm using the Microplate Reader Synergy HT Multi-Detection (BioTek Instruments, Inc., Winooski, VT, USA). The results were expressed as gallic acid equivalents (GAE) using a gallic acid calibration curve (r2 = 0.9946). The analysis of GRCE was performed in triplicate and expressed as mean values (mg/g dry weight (d.w.) of extracts) ± standard deviations.
## 2.5. Radical-Scavenging Capacity Antioxidant Capacity Test
The radical-scavenging capacity (DPPH) of GRCE was performed following the Brand-Williams method [31]. Accordingly, 250 μL of GRCE sample was mixed with 1750 μL of 0.02 mg/mL DPPH solution and incubated at room temperature (30 min). The absorbance was recorded by a 96-well plates Synergy HT Multi-Detection Microplate Reader (BioTek Instruments, Inc., Winooski, VT, USA) at 517 nm. The control was performed with methanol. A standard calibration curve with Trolox (r2 = 0.9985) was used for the interpretation of the results, which were expressed as Trolox equivalents (TE) per 100 g dry weight (d.w.). The experiments were performed in triplicates.
## 2.6. High-Performance Liquid Chromatography-Diode Array Detection–Electro-Spray Ionization Mass Spectrometry Analysis of Ginger Root Capsule Extract
The High-Performance Liquid Chromatography–Mass Spectrometry (HPLC-MS) analysis of GRCE was performed as described by Pop et al. [ 30]. Agilent 1200 HPLC with DAD detection was coupled to Agilent 6110 single quadrupole mass spectrometer. The column used was Eclipse XDB C18 (4.6 × 150 mm, 5 m particle size) from Agilent Technologies, Santa Clara, CA, USA. The separation was performed at room temperature using a gradient by mixing mobile phase A ($0.1\%$ acetic acid in distilled water (99:1) (v/v)) and mobile phase B ($0.1\%$ acetic acid in acetonitrile (v/v)) [32]. The elution gradient is presented in Table 1.
The spectra were registered at 280 nm and further injected into the MS equipped with an ESI source and scanned between 100 and 1000 m/z. The compound’s ionization was performed in the (+) mode at 350 °C. The nitrogen flow was set at 8 L/min and the capillary voltage at 3000 V. Agilent Chem-Station Software (Rev B.04.02 SP1, Palo Alto, CA, USA) was used for data analysis. The tentative compound identification was performed considering mass spectra, UV−visible spectra, retention time and the literature data.
## 2.7. Animals
Sixty-two [62], ten-week-old, white male Wistar-Bratislava rats (300–320 g) were included in the study. They were all purchased from the Animal Department of the Faculty of Medicine, Iuliu Haţieganu University of Medicine and Pharmacy. They were acclimatized to standard environmental conditions of 22–25 °C, $30\%$ humidity and 12 h/12 h light/dark cycle, having free access to water and food.
## 2.8. Toxicity Testing
Six rats were used to evaluate the toxicity of ginger root capsules (GRCE) according to the recommendations of the guideline for testing chemicals issued by the Organization for Economic Co-operation and Development (OECD) [33].
The content of GRCE was dissolved in saline solution and administrated orally by gavage. Initially, a dose of 50 mg/kg b.w. ( body weight) was administered to 3 rats. Each rat was observed individually after administration of the ginger solution at least once in the first 30 min and periodically in the first 24 h, with special attention given in the first 4 h. Afterwards, all rats were observed daily for 14 days. Possible changes in the skin and fur, eyes and mucous membranes, as well as the cardiac, respiratory and nervous system, as well as behavioral disorders, were monitored. Close attention was paid in order to observe whether the rats exhibited tremors, convulsions, excessive salivation, diarrhea, lethargy or drowsiness. The weight of the rats was determined before the administration of the extract and thereafter once every 7 days up to 14 days. At the end of the experiment (day 14), under local anesthesia with xylazine and ketamine, blood samples were collected from each rat and toxicity tests consisted of evaluating the serum levels of alanine aminotransferase (ALT), total bilirubin (TB), creatinine and urea. The rats were sacrificed and their liver and kidneys were taken, fixed in $10\%$ formalin. After fixation in paraffin, stained with hematoxylin and eosin, a pathologist examined the tissue fragments under a light microscope. Since no rat died, another 3 rats and the same steps were followed to test the 300 mg/kg b.w. GRCE dose for another 14 days, and afterward another 3 rats for the 2000 mg/kg b.w. dose for another 14 days.
## 2.9. Experimental Design
Since there were no significant differences between their weights, the fifty-six [56] rats were randomly divided into eight groups of seven animals each and treated as follows:[1]C, the control group, rats had no intervention and were treated with saline solution;[2]Acute inflammation (AI) group, acute paw inflammation was induced and rats were treated with saline solution;[3]AI treated with diclofenac sodium (AI-D) group, acute paw inflammation was induced and rats were treated with diclofenac sodium (5 mg/kg b.w.);[4]AI treated with GRCE in the lower dose (AI-GRCE100) group, acute paw inflammation was induced and rats were treated with GRCE in a dose of 100 mg/kg b.w.;[5]AI treated with GRCE in the higher dose (AI-GRCE200) group, acute paw inflammation was induced and rats were treated with GRCE in a dose of 200 mg/kg b.w.;[6]AI treated with GRCE in the lower dose and D (AI-GRCE100-D) group, acute paw inflammation was induced and rats were treated with GRCE in a dose of 100 mg/kg b.w., and D in a dose of 5 mg/kg b.w.;[7]AI treated with GRCE in the higher dose and D (AI-GRCE200-D) group, acute paw inflammation was induced and rats were treated with GRCE in a dose of 200 mg/kg b.w. and D in a dose of 5 mg/kg b.w.
Acute inflammation was induced using 100 μL of $1\%$ freshly prepared carrageenan solution, on day 0 of the experiment. Carrageenan solution was injected sub-plantary into the right-hind paw [34].
Only one dose of diclofenac sodium of 5 mg/kg b.w. was administered intraperitoneal (i.p.) right after AI induction. C and AI groups received 1 mL of saline solution i.p. The reduced dose of 5 mg/kg b.w. of diclofenac sodium was used as it was previously observed to reduce paw edema in carrageenan-induced AI [35,36]. The GRCE was dissolved in saline solution and administrated orally by gavage right after diclofenac administration. Control and AI groups received 1 mL of saline solution by gavage. A dose of 100 mg/kg b.w. was chosen as this dose of Zingiber officinale was proven to have antioxidant and anti-inflammatory effects [37] and the dose of 200 mg/kg b.w. was proven to have analgesic effects [38].
## 2.10. Outcome Measurements
The physical tests described in Table 2 (paw pressure, hot plate and motility tests) were performed at 1, 3, 5, 7 and 24 h after carrageenan administration.
The animal care staff, those who administered the treatment and those who collated data during motility, paw pressure and hot plate tests were unaware of allocation groups. Neither the persons involved in blood sample collection, biochemical and histological analysis, nor the person who did the statistical analysis were aware of the treatment received by each rat.
## 2.11. Blood Samples and Biochemical Assays
Under light anesthesia with xylazine and ketamine, the blood samples were collected from the retro-orbital plexuses of each rat, at 24 h after AI induction, in heparinized tubes (Startstedt AG and Co., Nümbrecht, Germany). Plasma was obtained by centrifugation at 4 °C for 20 min at 16,200× g, transferred in Eppendorf tubes and kept at −80 °C until further analysis.
The serum levels of ALT, TB, urea and creatinine were determined using an automatic analyzer Applied Biosystem (Costa Brava, Barcelona, Spain) through a spectrophotometric method.
Five oxidative stress parameters were assessed from plasma with a Jasco V-530 UV–Vis spectrophotometer (Jasco International Co. Ltd., Tokyo, Japan), using the methods previously described: malondialdehyde (MDA) [42], the indirect assessment of NO synthesis (NOx) [43], total oxidative status (TOS) [44], total antioxidant capacity (TAC) [45], total thiols (SH) [46] and oxidative stress index (OSI) [47].
## 2.12. Statistical Methods
Means and standard deviations were used as descriptive statistics in reporting the primary outcomes, namely the serum levels of the evaluated markers (MDA, NOx, TOS, TAC, total thiols and OSI). The same descriptive statistics indicators were used for secondary outcomes, namely paw pressure and hot plate tests while for the motility test, we reported percentages associated with the scores. Student t-test for independent groups was used to test the induction of AI comparing the C group with the AI group as well as the effects of the low D dose on evaluated markers and signs comparing the AI group with the AIC group. The anti-inflammatory and antioxidant effects of the GRCE with or without D were compared with an ANOVA test followed by post hoc analysis using the Scheffe test (at a significance level of 0.008) whenever data proved statistical differences on a two-tailed test at a significance level of $5\%$. The distribution of raw data of the evaluated serum markers was graphically represented using a variability plot that shows individual values along with the median. The results of the paw pressure and hot plate tests were graphically represented using the mean and $95\%$ confidence interval for each group. The distribution of the motility test was represented with a $100\%$ stacked bar per group.
Statistical analysis was conducted blinded so that the treatment group was not identifiable during the analysis. The correspondence between the code and the group’s name was conducted when the article was written. Data analysis was conducted with Statistica software (v. 13.5, StatSoft, St Tulsa, OK, USA).
## 3.1. Ginger Root Capsules Extract Phytochemical Analysis
The GRCE total polyphenols content (TPC) was 3757.45 ± 58.57 mg GAE/100 g d.w. plant material, while the total antioxidant capacity was 0.918 ± 0.01 mM Trolox Equivalents/100 g d.w. The HPLC-DAD-ESI MS identified significant concentrations of gingerols and gingerol derivatives, gingerdiols, gingerdiones and shogaols, the principal classes of ginger compounds (Table 1 and Figure 1). Figure 1HPLC chromatogram of ginger root ethanol extract registered at 280 nm. The identification of the main compounds is listed in Table 3.
## 3.2. Ginger Root Capsules Extract Toxicity
No changes in the skin and fur, eyes or mucous membranes were observed in rats who received the dose of 50 mg/kg b.w., 300 mg/kg b.w. or 2000 mg/kg b.w. of GRCE. Neither heart rate, respiratory rate or neurological/behavioral disorders were observed in all 3 doses. A slight increase in weight was observed in all three groups after 2 weeks. No significant variations were observed in any liver or kidney evaluated serum markers, at the tested doses, as shown in Table 4.
Histological examination revealed the normal architecture of the liver and kidneys of each rat used for toxicity testing, as shown in Figure 2.
## 3.3. Effects of Acute Inflammation on the Evaluated Oxidative Stress Serum Markers and the Effects of Diclofenac on These Markers
The MDA, NOx and TOS values significantly increased and TAC and total thiols significantly decreased after AI induction (Table 5). Diclofenac significantly decreased (MDA, NOx and TOS) and, respectively, increased the TAC serum values showing antioxidant efficacy (Table 5). No significant changes in the AI-D group than in AI were observed on serum values of total thiols (Table 5).
Without any exception, the rats walked easily without any difficulties on the motility test in the control group (score = 2). Diclofenac exhibits its effect on motility, with $50\%$ of rats walking without any motility difficulties at 24h after AI induction (Figure 3).
## 3.4. Ginger Enhancement of the Diclofenac Analgesic and Antioxidant Efficacy
The AI-GRCE200-D group obtained the closest serum values of the evaluated markers to the control group, with statistically significant differences between groups (Table 6, Figure 4).
The better results on paw pressure tests were obtained by AI-GRCE100-D and AI-GRCE200-D groups, with the closest values to the control group and slightly better results compared to the AI-D group (Figure 4). The AI-GRCE200-D group shows better results on the hot plate test, with the closest values to the control group (Figure 5).
The best motility is observed in the rats in the AI-GRCE200-D group (Figure 6). Normal motility at 24 h was observed on $\frac{6}{8}$ rats in the AI-GRCE200-D group, while half of the rats in the AI-GRCE200 and AI-GRCE100-D groups showed normal motility at the same measurement.
## 4.1. Ginger Root Capsules Extract Phytochemical Analysis and Toxicity
Phytochemical analysis of GRCE revealed significant concentrations of 6-gingerol, 8-gingerol, 10-gingerol and 6-shogaol (Table 3) similar to the capsules evaluated by Zick et al. in healthy human subjects [48].
No clinical signs of toxicity nor biochemical or histological abnormal results were observed for the three doses of the GRCE (50mg/kg b.w., 300 mg/kg b.w. or 2000 mg/kg b.w.). Toxicity testing of ginger (Z. officinale) powder capsule performed by Zick et al. [ 48] in healthy human subjects reported no adverse events for the dose of 100 mg. Higher doses of 1000 mg or 2000 mg were associated with minor gastrointestinal symptoms, including eructation, heartburn and indigestion, but no toxicities greater than the National Cancer Institute Common Toxicity Criteria (version 2.0) grade 1 were reported [48].
## 4.2. Ginger Root Capsule Extract Enhancement of the Diclofenac Analgesic and Antioxidant Efficacy
The results of the present study demonstrate that the association of ginger with diclofenac sodium provides dose-dependent analgesic and additional antioxidant effects in carrageenan-induced acute inflammation (Figure 4, Figure 5 and Figure 6, Table 6). To the best of our knowledge, this is the first study focused on evaluating the additional analgesic and antioxidant efficacy of ginger (Zingiber Officinale) root capsule extract to diclofenac sodium in experimental acute inflammation.
The administration of GRCE alone slightly improved the motility score but when it was associated with D, this combination better improved the motility score (Figure 6) more than D alone, most probably due to the fact that GRCE offers supplementary analgesic and anti-inflammatory effects. It was already observed that ginger injected intraperitoneally can effectively decrease disease incidence, joint temperature and swelling, and ameliorate clinical scores in rats with collagen-induced arthritis, with the best results for the dose of 200 mg/kg b.w. [ 49]. The anti-inflammatory effects of ginger are the result of the inhibition of the induction of several genes involved in the inflammatory response (e.g., genes encode the inducible cyclo-oxygenase-2 enzyme, chemokines and cytokines) [50].
The paw pressure test is a useful method for evaluating nociceptive thresholds, often used to test the effectiveness of different analgetics by observing the reaction to gradually increasing pressure on the inflamed paw [51]. Ginger administration was observed to provide a reduced analgesic effect (Table 6, Figure 5); moreover, it was already suggested that on mechanically induced pain the analgesic effects of ginger are dose-dependent [52]. In our study, the best analgesic effect was obtained after the association of GRCE in the dose of 200 mg/kg b.w. with D. Diclofenac administration was already demonstrated to increase the withdrawal threshold in paw pressure tests and, therefore, to provide analgesic effects [35]. Diclofenac, as a nonsteroidal anti-inflammatory drug (NSAID), reduces the inflammation process and therefore the associated pain [10]. Our results suggest that the 5 mg/kg b.w. dose of diclofenac sodium might have limited anti-nociceptive effects (Table 6, Figure 5) because it offers a reduced dose of the active substance. Ginger antinociceptive activity might be related to the inhibition of arachidonic acid synthesis, a metabolite that is mediated by COX inhibition [12].
The hot plate test is a thermoanalgesic method useful to evaluate the central activity of different analgesic drugs, since, in this test, the response reflex is mediated by supraspinal centers [53]. Our results show that GRCE administration was observed to provide a slight thermoanalgesic effect compared to D. Better results were observed after the combination of GRCE with D (Table 6, Figure 5). Diclofenac is an NSAID, so it has analgesic effects proved by the elevation of time to paw withdrawal to thermal stimuli, a behavior observed as well as in previous studies [54,55]. Zingiber officinale dried rhizomes ethanol extract produced dose-related, significant analgesic effects against thermally induced nociceptive pain of the rat hind paw, in the fresh egg albumin-induced AI [17]. In our study, the ginger root capsule aqueous extract prolonged latency in the hot plate test (Table 6, Figure 5), so ginger might also be acting centrally.
In the present study, the inflammation induction after carrageenan administration led to increased plasma levels of pro-oxidant parameters such as MDA, NOx, TOS and OSI and decreased plasmatic levels of the antioxidant parameters such as TAC and SH. Ginger root capsule extract administration provided a reduced antioxidant effect as the two doses slightly reduced the plasmatic levels of the above-mentioned pro-oxidant parameters and slightly improved the plasmatic levels of the evaluated antioxidant parameters. Diclofenac sodium administration was associated with a reduction of all the evaluated pro-oxidant parameters and elevation of all studied antioxidant parameters, more than GRCE alone. The association of GRCE with diclofenac sodium had an additional dose-dependent beneficial effect on all studied oxidative stress parameters (Table 5 and Table 6, Figure 4).
The release of neutrophil-derived free radicals is responsible for oxidative stress imbalance, which is specific to the second phase of edema induced by carrageenan [56]. Lipids are the biomolecules most involved in oxidative stress, as lipid peroxidation gives rise to several secondary products. Malondialdehyde is considered the principal and most studied product of polyunsaturated fatty acid peroxidation as it is regarded as a highly toxic molecule [57]. Diclofenac administration reduces serum lipid peroxidation [58], reduced the MDA plasma levels in a rat adjuvant arthritis model [59], and on carrageenan-induced paw edema [60]. Ginger has a similar effect as it inhibits lipid peroxidation and reduces MDA levels [61].
Nitric oxide (NO) is another major product of oxidative stress that plays a key role in the pathogenesis of inflammation. Under normal physiological conditions, it has beneficial effects in modulating vascular tone, as a vasodilator [62]. It can contribute to inflammatory damage if overproduced (by iNOS) together with excess superoxide anion, thus giving rise to harmful peroxynitrite (the so-called nitroxidative stress) [63]. Nitric oxide was observed to be involved in the pathogenesis of inflammatory disorders of the joints, gut and lungs. Therefore, NO inhibitors could represent an important therapeutic advance in managing inflammatory diseases, as different selective NO inhibitors might be helpful in treating NO-induced inflammation [64,65]. Diclofenac reduces inducible nitric oxide synthases (iNOS) expression in macrophages, decreasing NOx levels [66]. Inhibition of iNOS expression was suggested as a possible mechanism for NOx reduction after ginger powder supplementation [67].
Total oxidant status (TOS) is another pro-oxidant marker often used to estimate the overall oxidation state of the body [68], while TAC is an antioxidant marker used to evaluate the antioxidant capacity of the body [69]. It was already observed that diclofenac administration reduces TOS and increases TAC in carrageenan-induced paw edema inflammation in rats [70]. Ginger was observed to reduce TOS on renal ischemia/reperfusion injury in rat kidneys due to reduced oxidant substances excretion [71]. Ginger (Zingiber officinale Roscoe) administration was observed to increase TAC as a result of antioxidant defending capacity and decrease oxidative stress [72]. Moreover, ginger can be considered a storehouse of antioxidants as its bioactive ingredients such as gingerols, shogaols and zingerone were observed to have antioxidant activity by inhibiting oxidase enzymes such as xanthine oxidase [73].
A more precise biomarker reflecting oxidative stress is the OSI pro-oxidant marker, which can reflect an imbalance between antioxidants and pro-oxidation levels as it is defined as the ratio of the TOS level to the TAC level [74]. Ginger can influence the TAC and TOS ratio and therefore reduce the OSI index through the prevention of oxidation and nitration reactions induced by peroxynitrite, inhibition of xanthine oxidase responsible for the generation of reactive oxygen species, such as superoxide anion or inhibition of NO synthesis [75].
Thiols are a group of antioxidant molecules regarded as a useful defense system against biochemical alterations produced by oxidative stress [76]. Total thiol levels were increased after ginger administration as ginger was observed to possess high levels of biological thiols [77].
The low bioavailability and extensive phase II metabolism might be a limitation for the use of ginger in different pathologies and therefore new pharmaceutical forms for delivering ginger’s bioactive compounds are currently being developed [78]. For example, nanocarriers may further improve the beneficial effects of natural-based bioactive compounds as they protect the active compound from external injuries and internal pH variations [79,80].
## 4.3. Limitations of the Study and Call for Future Studies
No evaluations of the anti-inflammatory effects of GRCE associated with D were performed in this study since such measurements were out of our aim. Analyzation of the anti-inflammatory effects of GRCE in combination with diclofenac in acute inflammation is of real interest. Additional tests focused on the antinociceptive actions of ginger could be included in future studies. Moreover, the encapsulation of gingers’ active compounds in nanocarriers for targeted drug delivery represents a topic for future research.
## 5. Conclusions
Ginger root capsule extract in doses of 50 mg/kg b.w., 300 mg/kg b.w. or 2000 mg/kg b.w. were observed not to be toxic. Ginger root capsules associated with diclofenac might offer additional antioxidant and analgesic effects, in a dose-dependent manner in acute inflammation. The association of ginger root capsule extract with a low dose of diclofenac sodium might be a useful option to decrease diclofenac sodium doses used, as this combination seems to be helpful for oxidative stress and pain reduction, and mobility improvement in acute inflammation. Additional studies are needed to achieve clinical evaluation not only for the antioxidant but also for the anti-inflammatory and antinociceptive effects of ginger.
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|
---
title: Association of Cognitive Deficit with Glutamate and Insulin Signaling in a
Rat Model of Parkinson’s Disease
authors:
- Ana Knezovic
- Marija Piknjac
- Jelena Osmanovic Barilar
- Ana Babic Perhoc
- Davor Virag
- Jan Homolak
- Melita Salkovic-Petrisic
journal: Biomedicines
year: 2023
pmcid: PMC10045263
doi: 10.3390/biomedicines11030683
license: CC BY 4.0
---
# Association of Cognitive Deficit with Glutamate and Insulin Signaling in a Rat Model of Parkinson’s Disease
## Abstract
Cognitive deficit is a frequent non-motor symptom in Parkinson’s disease (PD) with an unclear pathogenesis. Recent research indicates possible involvement of insulin resistance and glutamate excitotoxicity in PD development. We investigated cognitive performance and the brain glutamate and insulin signaling in a rat model of PD induced by bilateral intrastriatal injection of 6-hydroxydopamine (6-OHDA). Cognitive functions were assessed with Passive Avoidance (PA) and Morris Water Maze (MWM) tests. The expression of tyrosine hydroxylase (TH) and proteins involved in insulin (insulin receptor - IR, phosphoinositide 3 kinase - pI3K, extracellular signal-regulated kinases-ERK) and glutamate receptor (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptos-AMPAR, N-methyl-D-aspartate receptor - NMDAR) signaling was assessed in the hippocampus (HPC), hypothalamus (HPT) and striatum (S) by immunofluorescence, Western blot and enzyme-linked immunosorbent assay (ELISA). Three months after 6-OHDA treatment, cognitive deficit was accompanied by decreased AMPAR activity and TH levels (HPC, S), while levels of the proteins involved in insulin signaling remained largely unchanged. Spearman’s rank correlation revealed a strong positive correlation for pAMPAR-PA (S), pNMDAR-pI3K (HPC) and pNMDAR-IR (all regions). Additionally, a positive correlation was found for TH-ERK and TH-pI3K, and a negative one for TH-MWM/errors and pI3K-MWM/time (S). These results suggest a possible association between brain glutamate (but not insulin) signaling dysfunction and cognitive deficit in a rat PD model, detected three months after 6-OHDA treatment.
## 1. Introduction
Parkinson’s disease (PD) is the second most common age-related neurodegenerative disorder after Alzheimer’s disease (AD), with over 6 million people affected worldwide [1]. The main symptom of PD is motor deficit (bradykinesia, tremor, rigidity and gait difficulties [2]), but approximately 20–$40\%$ of PD patients suffer from cognitive impairment in the early stage, while more than 75–$80\%$ of them will eventually develop dementia, making PD the third most common form of dementia [3,4]. At the molecular level, PD is associated with degeneration of the nigrostriatal dopaminergic neurons [5] and the appearance of Lewy bodies with alpha-synuclein as the major protein associated with protein deposits [6].
Increasing evidence suggests that AD and PD share monoamine and alpha-synuclein dysfunctions, often beginning years before the onset of clinical manifestations [7]. The triggers for these impairments and the causes leading these early neurodegenerative processes to develop further in the form characteristic of AD or PD remain unclear [7]. Currently, the background of cognitive dysfunction in PD is not fully understood and is still a matter of an ongoing debate [8]. Latest research indicates a possible connection between insulin resistance in the brain and the development of dementia in PD [9] and suggests that metabolic dysfunction might be an important player in the pathophysiology of PD [10,11,12,13,14]. Moreover, recent research indicates a possible link between type 2 diabetes (T2DM) and PD: (a) they may have a common pathological mechanism and (b) presence of T2DM increases the risk for PD [15].
As with AD, there is a possibility that glutamate excitotoxicity is also involved in the development of PD [16]. Previous studies have shown that glutamate excitotoxicity may induce degeneration of the dopaminergic neurons and concomitant motor dysfunction in PD [17,18]. Several clinical results have revealed slight alterations in glutamate content in the brain of PD patients post mortem that indicate increased glutamate neurotransmission [19]. The excitotoxic glutamate cascade in PD is triggered by excess extracellular glutamate, which can ultimately lead to cell injury and death. With the excessive activation of N-methyl-D-aspartate (NMDA) receptors, the increased influx of Ca2+ ions worsens further the level of reactive oxygen compounds, leads to mitochondrial damage and increases susceptibility to cell death. In addition, excessive activation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors causes Na+ ion overload, resulting in high intracellular permeability and acute cell swelling [19]. Data concerning the interconnection of the glutamate and insulin signaling, in regards to cognitive and motoric deficit, and in relation to the affected brain regions, are missing. Therefore, to further explore this aspect of PD pathophysiology, it is necessary to use animal models.
There are two leading approaches to non-transgenic models of PD generated by exogenous toxins; administration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) or 6-hydroxydopamine (6-OHDA) [20]. The most commonly used rat model in preclinical research of PD is based on the central application of 6-OHDA, directly into the target brain region. In the brain, 6-OHDA has the ability to induce degeneration of dopaminergic and noradrenergic neurons. These types of neurons are particularly sensitive to 6-OHDA because their membrane transport proteins have a high affinity for this molecule [21]. Once absorbed, 6-OHDA accumulates in the neuronal cytosol, where it leads to progressive neuronal deterioration due to oxidative stress-induced cytotoxicity [22,23]. The usual locations of 6-OHDA administration are the substantia nigra pars compacta (SNpc), the medial forebrain bundle (MFB) or the striatum [24]. Unilateral administration of 6-OHDA into the SNpc or MFB causes a quick and vast degeneration of dopaminergic cell bodies (and anterograde progression of neurodegeneration), while injection into the striatum primarily affects the dopaminergic terminals (with further retrograde progression of degeneration) [25]. Intrastriatal administration of 6-OHDA causes a full array of premotor Parkinsonian symptoms, including cognitive deficit, with incomplete nigrostriatal cell loss and partial striatal dopamine depletion similar to early stages of the disease, and gradual SN cell loss, thus representing PD more closely [25,26,27,28].
The aim of this research was to clarify the connection between degeneration of dopaminergic neurons, motor and cognitive deficits with glutamate and insulin signaling in relation to the brain regions involved in cognition (hippocampus), motor function (striatum) and metabolism (hypothalamus) in an animal PD model induced by bilateral intrastriatal 6-OHDA application.
## 2.1. Animals
The research was conducted on adult, 3-month-old (equivalent to young adults [29]), male Wistar rats, (University of Zagreb, School of Medicine, Department of Pharmacology). All animals were housed (2–3 rats per cage) from 1 month of age and during the whole experiment (in total 5 months) in a licensed animal facility at the Department, kept on standardized food pellets and tap water ad libitum and maintained under a $\frac{12}{12}$ h light/dark cycle.
## 2.2. Ethics
All procedures involving animals, their care, administration of drugs, in vivo tests and sacrifice were carried out in accordance with institutional guidelines that comply with national and international laws: [1] Directive of the European Parliament and the Council for the Protection of Animals Used for Scientific Purposes; [2] Croatian Law on Animal Welfare (NN $\frac{135}{06}$); [3] Act on Changes and Amendments to the Croatian Animal Welfare Act (NN $\frac{37}{13}$); [4] Croatian Law on Animal Protection (OG $\frac{102}{17}$); [5] Guidelines for the care of animals in laboratory procedures or for other scientific purposes (NN$\frac{55}{13}$); [6] Guidelines for laboratory animal anesthesia procedures. In vivo experiments on animals, cognitive testing and animal sacrifice were approved by the Ethics Committee/Committee for Animal Welfare of the School of Medicine, University of Zagreb, as well as by the Ministry of Agriculture (CLASS: UP/1-322-$\frac{01}{18}$-$\frac{01}{57}$; NUMBER: 525-$\frac{10}{0255}$-18-5). The animals were bred and housed in a registered animal facility at the Department of Pharmacology, School of Medicine, University of Zagreb. Procedures performed on animals were carried out in compliance with the 3R principle. The persons who handled the animals were officially trained to work with laboratory animals.
## 2.3. Experimental Rat Model of Parkinson’s Disease
*Under* general anesthesia (ketamine 70 mg/kg/xylazine 7 mg/kg ip), rats were administered with 6-OHDA bilaterally into the striatum (caudate putamen, coordinates: AP-0 mm; ML-3 mm; DV-7 mm) in a total dose of 16 µg (dissolved in $0.02\%$ ascorbic acid; 8 µg in 2 µL per brain hemisphere; OHDA; $$n = 14$$) [21,30]. An equal volume of solvent ($0.02\%$ ascorbic acid) was applied intrastriatally to control animals using the same procedure (CTRis; $$n = 14$$) and a third group of animals was not treated (intact group; CTRint; $$n = 9$$).
## 2.4. Cognitive Testing
Three months after 6-OHDA administration, the animals were subjected to cognitive and motor tests. Cognitive functions of learning and memory were tested with two standard tests: the Morris Water Maze Swimming Test (MWM) and the Passive Avoidance Test (PA) and the motor ability of the animals was tested using the rotating cylinder test (results on the motor ability published in preprint [31], currently under review).
## 2.5. MWM
The Morris Water Maze Swimming Test (MWM) was conducted [32] in a 180 cm diameter pool with water at a standard temperature of 25 °C. The testing itself was performed using the Ethovision XT animal monitoring software (Version 11.5, Noldus, Wageningen, the Netherlands), with a cut-off time of 1 min. The pool was divided into 4 equal quadrants: NW—northwest, NE—northeast, SW—southwest, SE—southeast. A hidden underwater platform was located in the NW quadrant. Testing was conducted over 6 consecutive days. The time required to find the platform over 5 consecutive days (4 tests per day) and the number of entries (errors) into quadrants without the platform (learning phase) were measured. On the last day of testing, the platform was removed and the time spent in search of the platform in the correct quadrant and the number of entries/errors into other compartments were recorded in the probe trial.
## 2.6. PA
The Passive Avoidance Test (PA) apparatus (Ugo Basile, Gemonio, Italy) is divided into 2 compartments, a light and a dark one, with a sliding door between them. The time required for the animal to enter the dark compartment was measured one day after the animal was subjected to an electric shock of 0.5 mA for 2 s. On the first day, habituation to the new environment was carried out—the animals explored both compartments without being subjected to any electric shock, and after entering the dark compartment, they were taken out of the apparatus after 15 s. The next day, the animals were subjected to an electric shock after entering the dark compartment, in order to learn to avoid the dark chamber. On the third day, the time required for the animal to enter the dark compartment was measured with a cut-off time of 5 min [33].
## 2.7. Tissue Preparation
After cognitive testing, the animals were sacrificed under deep anesthesia (thiopental 70 mg/kg/diazepam 7 mg/kg). The animals were decapitated and their brain removed. The hippocampus (HPC), hypothalamus (HPT) and striatum (S) were isolated from half of the brain, for protein analysis by Western blotting (WB) and enzyme-linked immunosorbent assay (ELISA) analysis. The samples were stored at −80 °C. For protein isolation and subsequent measurement of protein levels, HPC, HPT and S were homogenized using an ultrasonic homogenizer (Microson Ultrasonic Cell Disruptor XL; Misonix, Farmingdale, NY, USA) in cell lysis buffer solution (1 M Tris (tris(hydroxymethyl)aminomethane) pH 8.0; 1 M NaCl; 0.005 M EDTA; 1 M DTT; 0.01 M sodium vanadate; $1\%$ NP-40) with protease (Roche Holding AG, Basel, Switzerland; Cat.#04693132001) and phosphatase (Roche Holding AG, Basel, Switzerland; Cat.#4906837001) inhibitors. Homogenates were centrifuged for 10 min at 12,500 rpm at 4 °C (Biofuge Fresco Heraeus, Hanau, Germany), and supernatants were stored at −80 °C [34]. The protein concentration was measured using the Lowry protein assay [35]. The remaining brain halves were washed in cold saline and immersed in $4\%$ buffered paraformaldehyde (PFA) for 2 days. After fixation, animal brains were cryopreserved with serial sucrose solutions ($15\%$ and $30\%$). Then, the brain was embedded in Tissue-Tek solution using Tissue-Tek Cryomolds (Sakura Finetek USA, Torrance, CA, USA). Brains were sliced using a cryostat (Leica CM1850; Wetzlar, Germany) (16 μm), mounted on slides and dried overnight at 37 °C before the immunofluorescence procedure.
## 2.8. Immunofluorescence
Previously sliced and dried sections were washed 3 times for 5 min in phosphate buffer (PBS). Non-specific binding sites were blocked with $10\%$ normal goat serum (NGS) in PBST ($0.25\%$ Triton X-100 in PBS) for 1 h at room temperature and incubated overnight at 4 °C with the primary anti-tyrosine hydroxylase (TH) antibody (Merck Millipore, Burlington, MA, USA; Cat.#AB152) diluted in $1\%$ NGS in PBST at a concentration of 1:1000. After the incubation, slides were washed in PBS (3 × 5 min) and incubated with the appropriate secondary fluorescent antibody (1:500) for 2 h in the dark (anti-rabbit Alexa Fluor 555; Cell Signaling Technology, Danvers, MA, USA; Cat.#4413). After incubation, the sections were washed and slides were again incubated with the primary antibody NeuN (1:1000) (Merck Millipore, Burlington, MA, USA; Cat.#MAB377) and the next day with the appropriate secondary fluorescent antibody (anti-mouse Alexa Fluor 488; 1:600; Cell Signaling Technology, Danvers, MA, USA; Cat.#4408). The sections were then washed again in PBS 3 times, allowed to dry for a short period and coverslipped with Fluoroshield mounting medium with DAPI (Sigma-Aldrich, St. Louis, MI, USA; Cat.#F6057). Slides were viewed and analyzed using the Olympus BX51 microscope and the CellSense Dimension software (Version 1.6, Olympus Corporation, Shinjuku City, Tokio, Japan) [36].
## 2.9. Insulin Concentration Measurement
Insulin concentration in the brain was determined by commercially available enzyme immunoassay (Rat/Mouse Insulin ELISA, Merck Millipore, Burlington, MA, USA, Cat.#EZRMI-13K) in strict compliance with the manufacturer’s protocol and analyzed by colorimetric analysis using a multimodal microplate reader Infinite F200 PRO (Tecan, Männedorf, Switzerland). Rat brain samples were added to the corresponding wells for insulin measurement. Absorbance was measured at 450 nm, subtracted for absorbance at 590 nm using a microplate reader. The concentration of insulin was calculated using the absorbance curve of the standard and was expressed in ng/mL.
## 2.10. Western Blot Analysis
Samples for electrophoresis were prepared by mixing equal amounts of homogenate and buffer (2 mL glycerol; 6 mL $10\%$ SDS; 2.5 mL 1 M tris buffer pH 6.7; 2–4 mg bromophenol blue) and $10\%$ β-mercaptoethanol was added. Samples were briefly heated at 95 °C for 5 min and centrifuged afterwards for 60 s at 13,000 rpm (Mikro 120; Hettich, Westphalia, Germany). Equal amounts of protein (40 µg for HPC and 30 µg for HPT and S) were separated by sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS-PAGE) using $12\%$ TGX Stain-Free gels (TGX Stain-Free FastCast acrylamide kit; Bio-Rad Laboratories, Hercules, CA, USA; Cat.#1610185). After electrophoresis, gels were visualized using the ChemiDoc Imaging System (Bio-Rad Laboratories, Hercules, CA, USA) and transfer efficiency was checked after transfer using the same technology. All the proteins in the sample were used for normalization and analysis. Following visualization, proteins were transferred to nitrocellulose membranes which were then blocked for 1 h at RT in $5\%$ non-fat milk in a low-salt washing buffer (LSWB; 10 mM Tris, 150 mM NaCl, pH 7.5 and $0.5\%$ Tween 20). After blocking, the membranes were incubated overnight at 4 °C with primary antibodies to detect the enzyme involved in dopamine synthesis (anti-TH), insulin receptor (IR, anti-IR; Merck Millipore, Burlington, MA, USA; Cat.#07-724) as well as two types of glutamate receptors (anti-total-AMPAR/tAMPAR/, Cat.#AB1504, anti-phospho-AMPAR/pAMPAR/, Cat.#AB5849, anti-phospho-NMDAR/pNMDAR, Cat.#ABN99; Merck Millipore, Burlington, MA, USA) and IR-signaling downstream elements (anti-phosphoinositide 3 kinase p85 (PI3K, Cat.#4257), anti-extracellular signal-regulated kinases (ERK, Cat.#4695; Cell Signaling Technology, Danvers, MA, USA; 1:1000 dilutions). After incubation, membranes were washed 3x with LSWB and incubated for 1 h at RT with the appropriate secondary antibody solution (anti-rabbit or anti-mouse, 1:2000; Cell Signaling Technology, Danvers, MA, USA), washed in LSWB and incubated with chemiluminescent reagent (Super Signal West Femto; Thermo Fisher Scientific, Waltham, MA, USA; Cat.#34095). The signals were captured and visualized with a MicroChemi video camera system (DNR Bio-Imaging Systems MicroChemi, Jerusalem, Israel). The ImageJ software (ImageJ; U.S. National Institutes of Health, Bethesda, MD, USA) was used to analyze the bands obtained by the Western blotting method. Total proteins were used as a control of the procedure, and protein intensities were expressed in proportion to the signal of total proteins in the same sample on the corresponding membrane [34].
## 2.11. Statistics
Protein levels and PA test results were presented as box and whiskers (min to max) plots with between-group differences tested by two-tailed Kruskal–Wallis one-way analysis of variance, followed by the Mann–Whitney U-test, with $p \leq 0.05$ considered statistically significant, using the GraphPad Prism 5 statistical software. MWM test results for learning trials were expressed as mean ± SD and analyzed by two-way ANOVA for repeated-measures with Bonferroni post-hoc correction, with $p \leq 0.05$ considered statistically significant, using the GraphPad Prism 5 statistical software. Principal component analysis was used for multivariate exploratory data analysis following data normalization using the Jamovi software (Version 2.3, Sidney, Australia). The results were presented as coordinates of individuals in respect to the biplot, and vectors of variables indicating contributions to the first two principal components (PC). Monotonic associations were analyzed by calculating Spearman’s rank correlation coefficients (ρ) for pairs of measured variables. Correlations were reported as heatmaps visualized in the JASP software (Version 0.15, Amsterdam, The Netherlands).
## 3.1. 6-OHDA Administration Induced Learning and Memory Deficit
In the MWM test, animals in the OHDA group spent a longer time to find the platform during the learning trials (Figure 1A), compared to both controls (CTRint and CTRis; +$65.4\%$–+$503.6\%$; $p \leq 0.001$). In addition, animals in the OHDA group entered the wrong quadrants (non-target entries) more often (Figure 1A), in comparison to both controls during the fourth (+$107.4\%$ vs. CTRis; $p \leq 0.05$, +$175.3\%$ vs. CTRint; $p \leq 0.01$) and fifth (+$131.2\%$ vs. CTRint; $p \leq 0.05$, +$142.8\%$ vs. CTRis; $p \leq 0.01$) day of the learning trial. Cumulative trajectories of animals separated by treatment depicted in heatmaps (Figure 1B) point to one more observation between control animals and OHDA-treated ones: the tendency of OHDA animals to stay in the proximity of the MWM pool walls, indicating possible anxious behavior.
Although there is no statistically significant difference in the latency time between the groups in the PA test, there is a tendency of OHDA animals to spend less time in the light compartment compared to controls (Figure 1C). In the probe trial, OHDA rats spent less time in search of the platform compared to both control groups: CTRint (−$69.9\%$, $$p \leq 0.0221$$) and CTRis (−$61.2\%$, $$p \leq 0.0352$$) (Supplement S1 (Supplementary Materials)) and had less non-target entries compared to CTRis (−$47\%$, $$p \leq 0.0096$$) (Supplement S1).
In addition, and as expected, the 6-OHDA model was characterized by a relatively large dropout rate throughout the experiment while no fatal outcomes were observed in either of the two control groups. Rotarod performance showed pronounced motor deficits in the 6-OHDA group. The results of motor findings are presented in the previously published manuscript [31].
## 3.2. 6-OHDA Administration Induced Dopaminergic Neurodegeneration (Reduced TH Levels) in the Cortex, HPC, HPT and S, while Dopaminergic Nuclei in the Substantia Nigra Were Found Preserved
Levels of TH determined by Western blot were found decreased in all observed regions (Figure 2A–C) compared to CTRis (in HPC −$59.8\%$, $$p \leq 0.0028$$; in HPT −$52.7\%$, $$p \leq 0.0076$$; in S −$82.1\%$, $$p \leq 0.0004$$) and compared to the intact controls (in HPC −$70.4\%$, $$p \leq 0.0016$$; in S −70.9 %, $$p \leq 0.0048$$) except in the HPT, where there was significant data dispersion in the CTRint group. Three months after intrastriatal vehicle administration (CTRis), striatal TH levels were found increased in comparison to intact controls (Figure 2C) (+$68.8\%$, $$p \leq 0.0040$$). Immunofluorescent analysis confirmed decrement of TH positive signal (red) in the cortex (Figure 2E) and hippocampus (Figure 2D) compared to both controls. Contrary to the observed decrease in TH levels, intrastriatal administration of 6-OHDA did not induce the loss of TH positive cells in the substantia nigra, compared to both control groups (Figure 2F).
## 3.3. A Total of 3 Months after 6-OHDA Administration, No Changes Were Observed in the Level of Proteins Involved in Insulin Signaling
The administration of 6-OHDA did not induce statistically significant changes in insulin concentration measured by ELISA compared to intact rats (CTRint) and rats that received vehicle only (CTRis) in all observed regions (Figure 3A–C). However, a tendency towards a decrease in insulin concentration after intrastriatal administration of OHDA was noticed in HPT (−$9\%$ vs. CTRint, $$p \leq 0.0593$$; Figure 3B) and S (−$4\%$ vs. CTRint, $$p \leq 0.0829$$; −$9\%$ vs. CTRis, $$p \leq 0.0509$$; Figure 3C). Statistically significant decrement of insulin concentration was observed after intrastriatal administration of vehicle only compared to intact controls in the HPC (−$21.8\%$, $$p \leq 0.0244$$; Figure 3A) and HPT (−$11.5\%$, $$p \leq 0.0206$$; Figure 3B). The analysis of protein levels involved in insulin signaling (IR, pI3K, ERK) did not show statistically significant changes in the HPC (Figure 3D) and HPT (Figure 3E). Intrastriatal administration of vehicle only induced increase in pI3K (+$31.5\%$ vs. CTRint, $p \leq 0.0001$; +$39.9\%$ vs. OHDA, $$p \leq 0.0028$$) and ERK (+$18.6\%$ vs. CTRint, $$p \leq 0.0315$$) levels in the striatum (Figure 3F).
## 3.4. 6-OHDA Induced Decrement of Phosphorylated AMPAR Levels in the HPC and S
Western blot analysis showed a statistically significant decrease in pAMPAR levels 3 months after 6-OHDA treatment compared to controls in the HPC (−$49.2\%$ vs. CTRint, $$p \leq 0.0008$$; −$36.3\%$ vs. CTRis, $$p \leq 0.0176$$; Figure 4A) and S (−$49.9\%$ vs. CTRint, $$p \leq 0.0047$$; −$42.4\%$ vs. CTRis, $$p \leq 0.0823$$; Figure 4C). Intrastriatal administration of vehicle only induced decreases in the pAMPAR levels in the HPC (−$20.3\%$, $$p \leq 0.0188$$; Figure 4A) and tAMPAR levels in the HPT (−$37.5\%$, $$p \leq 0.0464$$; Figure 4E) compared to the intact control group, while tAMPAR levels were found increased in the OHDA group compared to CTRis in the HPT (+$166.3\%$, $$p \leq 0.0048$$; Figure 4E). There was no statistically significant change of pNMDAR levels in all of the observed regions 3 months after the 6-OHDA injection (Figure 4G–I).
## 3.5. 6-OHDA Induces Regionally Specific Correlations
Spearman’s rank correlation was performed to analyze monotonic associations of the behavioral results’ parameters and measured parameters in the HPC (Figure 5C), HPT (Figure 6C) and S (Figure 7C). Regarding the behavioral parameters, there was a strong positive correlation between time needed to find platform (MWM/time) and non-target entries (MWM/errors) (ρ = +0.533, $$p \leq 0.007$$) and strong negative correlation between MWM/time and Rotarod (RR) results (ρ = −0.558, $$p \leq 0.008$$) (Figure 5, Figure 6 and Figure 7; Supplement S2). In all of the observed regions, there was a strong positive correlation between pNMDAR and IR levels (ρ = +0.614 in HPC, $$p \leq 0.005$$/Figure 5C/; ρ = +0.709 in HPT, $p \leq 0.001$/Figure 6C/; ρ = +0.651 in S, $$p \leq 0.001$$/Figure 7C/). In both HPC (Figure 5C) and S (Figure 7C), there was a strong positive correlation between TH levels and RR results (ρ = +0.652, $p \leq 0.001$ and +0.584. $$p \leq 0.003$$, respectively). In the HPC, pNMDAR was found positively correlated with pI3K (ρ = +0.583, $$p \leq 0.008$$). In the S (Figure 7C), TH was found strongly negatively correlated with MWM/errors (ρ = −0.601, $$p \leq 0.002$$), while positively with ERK (ρ = +0.563, $$p \leq 0.005$$) and pI3K (ρ = +0.594, $$p \leq 0.003$$). Additionally, in the S (Figure 7C), pAMPAR was found positively correlated with PA (ρ = +0.582, $$p \leq 0.009$$) and RR (ρ = +0.579, $$p \leq 0.009$$), and pI3K was found negatively correlated with MWM/time (ρ = −0.610, $$p \leq 0.002$$). Other moderate associations (ρ =0.4–0.53) are indicated in Figure 5C, Figure 6C and Figure 7C and Supplement S2. Principal component analysis was used for multivariate exploration separately in the HPC (Figure 5), HPT (Figure 6) and S (Figure 7). Plots in Figure 5A, Figure 6A and Figure 7A represent coordinates of individuals in respect to the first and second PC for each region (HPC, HPT and S) and behavioral data. In the HPC, the first two components explain $31.99\%$ and $20.58\%$ of the variance, respectively, with RR, MWM/time and errors, TH and ERK being the largest contributors to the first PC and IR, pAMPAR and pNMDAR to the second one (Figure 5A,B; Supplement S2). Clustering of the groups, OHDA vs. CTRint and CTRis was most prominent in respect to the first PC in the HPC (Figure 5A). In the HPT, two components explained $29.38\%$ and $19.33\%$ of the variance, with MWM/time, IR, pNMDAR, TH and ERK being the largest contributors to the first PC and AMPAR and PA to the second one (Figure 6A,B; Supplement S2). The 6-OHDA treatment showed the most pronounced effect in respect to the both first and second PC in the HPT (Figure 6A). In the S, the first two components explain $31.75\%$ and $18.39\%$ of the variance with MWM/time and errors, TH, pI3K and RR as the largest contributors to the first PC and IR and AMPAR and ERK to the second one (Figure 7A,B; Supplement S2). Both intrastriatal administrations 6-OHDA (OHDA) and vehicle (CTRis) had pronounced opposite effects in respect to the first PC (Figure 7A).
## 4. Discussion
Bilateral intrastriatal 6-OHDA administration triggers dopaminergic degeneration in both hemispheres, which is important for the appearance of the entire spectrum of behavioral symptoms of the disease [30,37,38,39]. Given that dopamine is a key neurotransmitter involved in motivation, stimulus-reward learning process and preserving neuronal plasticity, its malfunction can lead to changes in synaptic transmission as well as cognitive disorders [40]. The occurrence of memory and learning disorders is expected and registered in animals treated with 6-OHDA toxin [41,42]. In addition, the 6-OHDA model displays the broader spectrum of non-motor symptoms (emotional and cognitive deficit) in comparison to the genetic PD model [41].
The results confirm that the bilateral 6-OHDA injection causes motor symptoms characteristic for PD [31], as well as dysfunctions in spatial–visual memory and learning (Figure 1). Many authors associate the described changes with a decrease in the number of TH-positive neurons in the SNpc and striatum [43]. As TH is crucial in the synthesis of dopamine in the brain [44,45], it is expected that the depletion of dopaminergic neurons will lead to a decrease in TH positive neurons in the observed parts of the brain. Moreover, dopaminergic signaling has important role in the hippocampus-dependent learning and memory [46] and the hypothalamic control of energy metabolism [47] and they can receive dopamine projections from the ventral tegmental area (VTA) and SNpc [48,49,50,51]. Reduction in the TH positive signal was seen in all of the observed regions (HPC, HPT, S and CTX; Figure 2), and dopaminergic nuclei in the substantia nigra were found preserved 3 months after 6-OHDA bilateral injection, pointing towards incomplete depletion of dopaminergic cells. Tadaiesky and colleagues noticed, in SN, a cell number decrement with 6-OHDA bilateral injection (12 µg per injection) even 1 week after surgery, although the reduction persisted until the third week, it was diminished [25], suggesting a partial depletion and time-dependent recuperation of dopaminergic neurons in SN. There is a possibility that due to the longer time after 6-OHDA treatment and/or lower 6-OHDA dosage than in previous research [25,26], preservation of dopaminergic nuclei observed 3 months after 6-OHDA treatment might occur. Moreover, as we have already mentioned in our preprint, there was a pronounced drop-out rate in the 6-OHDA-treated group of animals ($57\%$ fatality rate) which may have introduced attrition bias—e.g., the animals with the most pronounced response to the 6-OHDA administration, and possibly more rapid spreading of the 6-OHDA-induced damage from the striatal terminals to SN [31]. The levels of TH in hypothalamus, in comparison to other observed regions, were found the most preserved, showing only a slight decrement. There was an increase in TH activity in S of sham operated group, suggesting a compensational response due to invasive procedure of intrastriatal application. PCA and correlation analysis were used to determine in which brain region the TH signal could be associated with behavioral changes (Figure 5, Figure 6 and Figure 7). Strong correlation between motoric performance and TH signal in HPC and S suggests involvement of dopaminergic signaling on motoric performance not only in striatum, as expected, but also in HPC. In addition, TH, RR and MWM are one of the most important parameters that can explain the difference between control groups and OHDA in HPC and S. It seems that spatial learning and memory does not correlate with dopaminergic signaling, but only in HPC, while there was some correlation in both HPT and S suggesting better performance in MWM with increment of TH levels. In spatial navigation tasks, the role of the hippocampus has been classically juxtaposed with the role of the dorsal striatum, the latter of which has been characterized as a system important for implementing stimulus–response and action–outcome associations [52]. It is possible that dopamine depletion in the striatum induced by 6-OHDA administration is responsible for learning and memory deficit, and that dopamine does not play an important role of aforementioned memory in HPC. There is also a possibility of simple direct action of 6-OHDA toxicity in HPC, which caused reduction in TH levels or reduced input of dopaminergic projections to this brain region. In addition, dopamine levels were found not altered in HPC after 6-OHDA treatment in the research of Tadaiesky and colleagues [25], and they also suggest that HPC is not involved in the behavioral impairments. However, decrement of TH can also be found in HPC after 6-OHDA injection in SN [53], this type of lesioning (in SN) is sometimes not adequate to develop non-motor symptoms. Striatal 6-OHDA injections are better at reproducing the early stages of PD, so this approach is well suited to the study of non-motor symptoms, since these ailments often appear during the prodromal phase of PD [54], and once again indicate the importance of striatum in spatial learning and memory. The administration of 6-OHDA leads to damaging noradrenergic neurons as well, which can be associated with both central (cognitive impairment, depression, anxiety, olfactory deficit) as well as peripheral (cardiovascular, gastrointestinal) non-motor symptoms [55]. Interestingly, only in HPT, the parameter measuring fear-conditioned memory, in addition to MWM, is one of the important ones that explains the difference between CTR and OHDA groups. Research on fear conditioning has traditionally focused on brain areas such as the amygdala and hippocampus, in contrast, the role of the hypothalamus has remained relatively underexplored. Recently, Concetti and colleagues found that inappropriate, learning-resistant fear results from disruption of brain components: hypothalamic melanin-concentrating hormone-expressing neurons [56], confirming the importance of HPT in memory disorders. In addition, sleep disorders appear in the early stages of PD and this can be due to degeneration of orexinergic neurons in HPT [57], as it was also noted in rat PD model after striatal 6-OHDA injection [58].
The importance of insulin in the metabolism of glucose in the brain has gained attention in the last few decades through research into the pathogenesis of neurodegenerative diseases such as AD and PD. Insulin via the PI3K/Akt signaling pathway enhances long-term memory in hippocampus-related tasks, reduces alpha-synuclein accumulation and neurotoxicity and reduces neuroinflammation and apoptosis [59]. In addition, insulin normalizes the production and functionality of dopamine and ameliorates motor impairments in 6-OHDA-induced rat PD models [59]. Although insulin resistance is increasingly associated with PD, this mechanism has not yet been fully investigated. Interestingly, PD patients show increased autoimmune reactivity to insulin that may reflect the neurodegenerative brain-damaging processes and impaired insulin homeostasis occurring in PD [60]. Moreover, in PD patients, the death of dopaminergic neurons in the SNpc is often associated with a marked loss of IR mRNA and an increased level of IRS phosphorylation at serine residues, with an inhibitory effect on insulin signaling and subsequently increased insulin resistance [61]. Signs of insulin resistance were found in the rat striatum 6 weeks following the unilateral administration of 6-OHDA into the MFB [12]. In rats with severe depletion of dopamine (90–$99\%$), the most prominent signs in the brain were increased serine phosphorylation of IR substrate-2 (IRS2) and decreased phosphorylation of AKT as well as reduced expression of GSK-3α, while no significant changes in peripheral glucose and insulin were found. While unilateral intrastriatal 6-OHDA administration has been shown to affect serum insulin levels (early increase in glucose tolerance test) and striatal insulin signaling, it has not induced peripheral insulin resistance, at least not at the 6-week post-lesion time point. [ 62]. However, induction of peripheral insulin resistance by a diet high in fat may lower the threshold for developing experimental PD following 6-OHDA treatment [63]. Insulin binding to IR was found decreased by $25\%$ in the arcuate nucleus 7 days after 6-OHDA icv treatment [64], but the dose that was used was fairly high. A dysfunctional IR signaling cascade in the 6-OHDA model was reported in the striatum; reduction in PI3K and AKT phosphorylation was found after 2 [65] and 6 weeks [12]. Similarly, increased levels of phosphorylated IRS at serine residues, the marker of insulin resistance, are seen in the dopamine-depleted striatum, in the 6-OHDA toxin model of PD and transgenic mice overexpressing alpha-synuclein [12,66]. Contrary to these findings, our results do not show marked changes in levels of proteins in insulin cascade pathway 3 months after 6-OHDA administration, with a slight tendency for insulin concentration decrement in the hypothalamus and striatum (Figure 3). As we have already mentioned, this discrepancy could be related to lower dose administration and partial depletion of dopaminergic neurons. There is a possibility that changes in the insulin signaling pathway protein expression would be observed at earlier and/or later time points after 6-OHDA administration than the time point used in this study, where a compensational response could happen. Conversely, PCA and correlation analysis suggested involvement of IR levels in hypothalamic CTR and OHDA distinguishment: IR being the largest contributor to the first dimension (Figure 6, Supplement S2), suggesting a connection between dopaminergic depletion (induced primarily in striatum) with IR signaling in HPT. As was expected, the strong positive correlation in all of the observed regions was found between levels of IR and pNMDAR, confirming their signaling pathway interconnection [67,68]. Interestingly, in the striatum, TH was found positively correlated with ERK and pI3K, suggesting the importance of MAPK/ERK and PI3K/AKT signaling pathways in catecholamine synapses not necessarily connected with IR pathway (Figure 7). Summarizing the results, we can assume that disturbed dopamine signaling may be, to a lesser extent, transduced to insulin signaling and its downstream targets, as a secondary, collateral damage [55] such as the one seen in HPT, but it probably depends on the 6-OHDA dose and the location of administration. In addition, intranasal insulin improves mitochondrial function, alleviates motor deficits and protects against substantia nigra dopaminergic neuronal loss in 6-OHDA rat model [69,70], suggesting a neuroprotective insulin action.
Glutamate, as an important central neurotransmitter, is closely related to the occurrence and development of PD [16], and impaired glutamate homeostasis in the striatum is emerging as a key feature of PD pathology [19]. It has been proven that glutamate AMPA receptors participate in the modulation of neuronal excitability and long-term synaptic plasticity [71] and are associated with altered neurotransmission in PD [72]. By analyzing the protein levels of the AMPA receptor and its phosphorylated form, we observed significant changes in all three regions of the brain. A decrease in phosphorylated AMPA receptor in the HPC and S was observed 3 months after bilateral intrastriatal administration of 6-OHDA, which indicates reduced glutamate signaling in these brain regions. PCA analysis indicated the importance of glutamate signaling in HPT, where increased pNMDAR levels and decreased AMPAR levels distinguish control animals from OHDA group. If we include the finding that reduced pNMDAR levels are correlated with reduced IR levels in the HPT of OHDA group, increased AMPAR could be a compensational response to decreased glutamatergic signaling. Interestingly, increased levels of pAMPAR in S are associated with better results in RR and PA tests (Figure 7). Previous studies have shown that α-synuclein is closely associated with glutamate excitotoxicity and that the aforementioned α-synuclein increases the release of glutamate [16]. Additionally, overexpression of α-synuclein increases the phosphorylation of NMDARs, and some studies indicate that α-synuclein can also enhance glutamate excitotoxicity by accelerating AMPAR signaling [16]. The 6-OHDA model shares a common failing with many other animal models of PD as it does not lead to the formation of the pathological hallmark of PD, the Lewy body, that contain ubiquitinated proteins such as α-synuclein [73]; therefore, the change in glutamate receptor levels in our research, especially AMPA receptors, is associated with dopaminergic degeneration seen as positive correlation between TH and pAMPAR levels. In their work, He and his co-workers [74] showed that direct administration of 6-OHDA in the SNpc reduces the expression of AMPA receptors, including its subunits GluR1, GluR2 and GluR3, but not GluR4 and this could be related to the reduction in TH positive neurons, considering that in the study the expression of the AMPA receptor, GluR1 subunit, was decreased together with the appearance of lesions and the reduction in TH positive neurons after the administration of 6-OHDA [74]. Recent studies suggest that selective potentiators of AMPA receptors may be useful for protection against SNc degeneration and motor deficits after establishment of SNc lesion caused by 6-OHDA in rats [75]. There is a possibility that the decrement of pAMPAR levels is a consequence of synapse weakening following glutamate excitotoxicity that occurred earlier after dopaminergic degeneration by 6-OHDA injection. Dopaminergic and glutamatergic neurons are interconnected. The striatum circuitry is mainly composed of inhibitory spiny projection neurons (SPNs) that receive DA innervation from SNpc and glutamatergic inputs from the cerebral cortex and thalamus. The coordinated activity of these pathways becomes impaired in PD due to the progressive loss of nigral DA neurons. A decreased stimulation of the DA receptors affects the direct pathway (striatopallidal neurons project to neurons of the internal segment of the globus pallidus directly) leading to a reduced inhibition of the output signals while the lack of DA receptor-mediated stimulation of the indirect pathway (striatopallidal neurons communicate with the external segment of the globus pallidus and the subthalamic nucleus (STN) through glutamate release) results in a disinhibition of the STN causing a glutamatergic overstimulation of the output signals [19]. Excessive activation of NMDARs induces excessive influx of Ca2+ and further exacerbates ROS levels and oxidative damage. Overactivation of AMPARs induces Na+ overload, which leads to increased cellular permeability and results in cellular swelling and neuronal death [16]. If this was the course of events, we should also see a decrease in the level of total receptors AMPARs, as well as NMDARs, but that is not the case. Reduced pAMPAR levels can be a sign of synapse weakening. In HPC, long term depression is dependent on NMDARs and its induction can lead to the depression of synaptic strength via removal of AMPARs [71]. This can lead to exaggeration of motoric and cognitive deficit, especially since there is a correlation between striatal pAMPAR levels and cognitive and motor performance in this research. In addition, sham operation caused decrement of insulin concentration and pAMPAR level in HPC compared to intact control, which indicates chronic changes (3 months after the surgery) after striatal syringe lesioning.
To conclude, bilateral intrastriatal administration of 6-OHDA can induce cognitive deficit, beside motoric one and substantial reduction in TH levels in the brain, but with incomplete depletion of dopaminergic SN cells. This partial depletion could be due to the too low 6-OHDA dose or time-dependent recuperation of dopaminergic neurons in SN. The effects of 6-OHDA injection on rodent brain are known in general and the novelty of this research is that it provides the novel findings on the region-specificity in the particular signaling pathways (comparison between insulin and glutamate signaling) and the correlation of these changes with behavioral patterns and dopaminergic depletion, which originated in the striatum. Even though the levels of proteins involved in insulin signaling were not found markedly changed, PCA and correlation analysis suggested some association such as in the case of: (a) IR being one of the largest contributors to the first PC in HPT (CTRs and OHDA group distinguishment), suggesting a connection between dopaminergic depletion with IR signaling in HPT; and (b) a positive correlation between striatal TH and ERK and pI3K. Further studies are needed to evaluate the involvement of insulin signaling, especially regarding transcriptional changes and their correlation to protein expression. The most pronounced change in glutamatergic receptor levels was the decrement of pAMPAR in S and HPC and its positive association with better performance in motoric and cognitive tests. Decrement of glutamatergic signaling can be due to synapse weakening and can lead to exaggeration of motoric and cognitive deficit. Further studies are needed to clarify the exact role and the involvement of striatal glutamatergic signaling in motoric and cognitive functions.
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|
---
title: Entomotherapeutic Role of Periplaneta americana Extract in Alleviating Aluminum
Oxide Nanoparticles-Induced Testicular Oxidative Impairment in Migratory Locusts
(Locusta migratoria) as an Ecotoxicological Model
authors:
- Esraa A. Arafat
- Doaa S. El-Sayed
- Hussein K. Hussein
- Justin Flaven-Pouchon
- Bernard Moussian
- Lamia M. El-Samad
- Abeer El Wakil
- Mohamed A. Hassan
journal: Antioxidants
year: 2023
pmcid: PMC10045266
doi: 10.3390/antiox12030653
license: CC BY 4.0
---
# Entomotherapeutic Role of Periplaneta americana Extract in Alleviating Aluminum Oxide Nanoparticles-Induced Testicular Oxidative Impairment in Migratory Locusts (Locusta migratoria) as an Ecotoxicological Model
## Abstract
In this study, we shed light for the first time on the usage of migratory locusts (Locusta migratoria) as an insect model to investigate the nanotoxicological influence of aluminum oxide (Al2O3) nanoparticles at low doses on testes, and evaluate the capacity of a whole-body extract of American cockroaches (Periplaneta americana) (PAE) to attenuate Al2O3 NPs-induced toxicity. Energy dispersive X-ray microanalyzer (EDX) analysis verified the bioaccumulation of Al in testicular tissues due to its liberation from Al2O3 NPs, implying their penetration into the blood–testis barrier. Remarkably, toxicity with Al engendered disorders of antioxidant and stress biomarkers associated with substantial DNA damage and cell apoptosis. Furthermore, histopathological and ultrastructural analyses manifested significant aberrations in the testicular tissues from the group exposed to Al2O3 NPs, indicating the overproduction of reactive oxygen species (ROS). Molecular docking analysis emphasized the antioxidant capacity of some compounds derived from PAE. Thus, pretreatment with PAE counteracted the detrimental effects of Al in the testes, revealing antioxidant properties and thwarting DNA impairment and cell apoptosis. Moreover, histological and ultrastructural examinations revealed no anomalies in the testes. Overall, these findings substantiate the potential applications of PAE in preventing the testicular impairment of L. migratoria and the conceivable utilization of locusts for nanotoxicology studies.
## 1. Introduction
Nanoparticles (NPs) are particles with at least one dimension less than 100 nm that have been identified as key elements of nanomaterials, which could be further modified for implementation in various sectors in terms of nanotechnology [1]. NPs are classified into different categories following their morphological features, size, and chemical characteristics. Furthermore, NPs can be put into predominant groups based on their physical and chemical properties, such as metal, ceramic, carbon-based, lipid-based, and polymeric NPs [2]. Given their outstanding and versatile properties, NPs, particularly metal NPs, have been receiving immense attention for applications in multiple fields, including industrial, environmental, biomedical, and electronic sectors [2,3]. Along with this extensive growth and revolution, the exposure of living organisms to these metal NPs is inevitable due to their high discharge into the ecological system, raising critical questions about their potential deleterious consequences [4]. Recent reports have launched discussions about the toxicological impacts of metal NPs, such as Al2O3 NPs and Ag NPs, on the reproductive system, demonstrating some evidence about their conceivable mechanisms, which have not been fully comprehended [5,6,7]. Among these metal NPs, Al2O3 NPs are one of the most widely utilized, and account for about $20\%$ of the global nanoparticle market, since they could be exploited in coating, textile functionalization, and medicine for drug delivery application, and are substantially implemented as aluminum-based adjuvants in vaccines to modulate the immune response while boosting human immunization [8,9]. Previous studies have demonstrated that the accumulation of Al2O3 NPs inside biological tissues could disturb biological pathways, inducing critical toxicological episodes [10,11].
This is principally due to the discharging of Al from the nanoparticles within the respective tissues, generating surpluses of reactive oxygen species (ROS) and mutations of DNA, which provoke the dysfunction of cells and the substantive disruption of the antioxidant defense system and other metabolic mechanisms [5,11]. These detrimental events could be easily instigated due to the infiltration of Al2O3 NPs throughout different tissues, including the blood–testis barrier in terms of the reproductive system, inciting oxidative stress alongside its complications, which breaks up cellular homeostasis and further leads to the impairment of testicular tissues [10]. The study of the harmful effects of metal NPs on the reproductive system using insects as bioindicators has recently come to light in order to evaluate environmental pollution and comprehend critical biological problems [12,13]. Recently, migratory locusts, *Locusta migratoria* (Linnaeus, 1758), have received a lot of attention for their use in environmental toxicity assessments because they have inherent advantages, such as a short life cycles and non-specific living demands [12,14,15]. Significantly, the immune system of L. migratoria comprises humoral-based and cell-mediated immune reactions, including the synergy of hemocytes, fat bodies, and circulating hemolymph peptides for the elimination or deactivation of xenobiotics [15]. Furthermore, multiple actions could be performed by insects to counteract oxidative damage, including enzymatic and non-enzymatic antioxidants; for instance, carboxylesterase (CarE), and glutathione S-transferase (GST) are important detoxifying enzymes in insects. Moreover, they can metabolize a large number of toxins to maintain their physiological activities [16].
To hinder the toxicological effects, in particular the oxidative stress engendered by Al2O3 NPs, many endeavors have been dedicated to discovering natural products with intrinsic antioxidant capacities. The major studies focused on antioxidant-derived plants that contain bioactive polyphenolic compounds such as quercetin to reduce oxidative damage in hepatic cells after treatment with Al2O3 NPs [17,18,19]. So far, very little attention has been paid to antioxidant-derived insects to tackle the deleterious consequences of the metal NPs. Traditional Chinese medicine has widely used an insect-derived whole-body extract of the cockroach *Periplaneta americana* [20]. It has been reported that it has remarkable antimicrobial [21,22] and anti-inflammatory properties [23].
Even though there is a lot of attention given to appraising the toxicological influences of nanoparticles in relation to testicular tissues, no reports to date have comprehensively probed the deleterious effects of Al2O3 NPs at low doses. Moreover, to the best of our knowledge, no studies have evaluated the prophylactic activity of *Periplaneta americana* extract (PAE) against any types of metal NPs in order to thwart various disturbances of biological pathways within the testicular tissues of L. migratoria. Herein, we extensively study the deleterious effects of Al2O3 NPs in the testicular tissues of locusts through evaluating physiological characteristics, DNA impairment, and cell apoptosis. Furthermore, the histopathological and ultrastructural features of the testicular sections of locusts subjected to Al2O3 NPs were inspected. On the other hand, comparable tests were conducted to assess the efficacy of PAE as a protective extract for male locusts before being exposed to the Al2O3 NPs to counteract the harmful effects caused by the nanoparticles.
## 2.1. Collection of Insects
Adult migratory locusts, L. migratoria (Linnaeus, 1758) (Orthoptera, Acrididae), were collected from an organic field cultured with corn in Giza governorate, Egypt, before being identified and housed in the Entomology laboratory at the Faculty of Science, Alexandria University, Egypt, in standard wood cages with ten individuals in each, of which $50\%$ were males. They were maintained under standard conditions (temperature: 29.4 ± 3.5 °C; photoperiod: light:dark 12:12 h; humidity: 46.5 ± $9.4\%$) with unlimited access to water and food.
## 2.2. Al2O3 NPs Characterization
To probe the morphology and particle size of Al2O3 NPs (Nanotech Egypt for Photo-Electronics, Giza, Egypt), three samples were examined by a scanning electron microscope (SEM, JEOL JSM-5300, Tokyo, Japan) at an accelerating voltage of 20 kV and a transmission electron microscope (TEM, JEM-1400 Plus, Tokyo, Japan) at an acceleration voltage of 80 kV. Fourier transform infrared spectroscopy (FT-IR, Shimadzu 8400S, Kyoto, Japan) was also used to characterize the Al2O3 NPs.
## 2.3. Preparation of Al2O3 NPs Suspension and PAE Solution
To prepare a stock suspension of Al2O3 NPs, 1 mg/mL Al2O3 NPs were suspended in saline solution, followed by sonication using a Branson 450 sonicator (Branson Ultrasonics Crop, Danbury, CT, USA). The working solution was then prepared, and the final volume of each dose was adapted to the mass of each insect. PAE (Citeq Biologics, Groningen, Netherlands) stock solution was prepared by dissolving in a $0.9\%$ NaCl solution according to the manufacturer’s instructions.
## 2.4. Experimental Design
Prior to commencing the experiments, the weights of male migratory locusts were estimated at an average of 1.03 g in order to adapt the injection dose. To determine the dose of Al2O3 NPs for treating the migratory locusts, six groups of the migratory locusts were randomly established (10 insects/group) and designated from Al-G1 to Al-G6; these were injected with different doses at final concentrations of 0.01, 0.02, 0.03, 0.04, 0.05, and 0.06 mg/g body weight, respectively. On the other hand, to evaluate the toxicity of PAE and select the safest dose for locusts, three groups of insects (10 insects/group) termed PAE1, PAE2, and PAE3 were injected with PAE at doses of 0.01, 0.03, and 0.05 mg/g body weight, respectively. The control groups of insects in both investigations were injected with saline solution. The locusts were monitored for 10 days, and the mortality and behavior of insects were perceived and reported on a daily basis. According to mortality and behavior evaluations of male locusts, 60 locusts were randomly divided into three groups (20 insects/group): the control group, which was injected with a saline solution; the second group was injected with a single dose of Al2O3 NPs (0.03 mg/g body weight), and the third group was injected with a single dose of PAE (0.05 mg/g body weight) before being injected after 24 h with a dose of Al2O3 NPs (0.03 mg/g body weight). The injections were carried out in the intersegmental membrane between the 3rd and 4th abdominal sternites by means of a 0.5 mL BD hypodermic syringe (27 gauge, ½ inch needle).
## 2.5. Dissection Procedures
Adult locusts were cooled for 10 min at 4 °C. The testicular tissues were dissected from adult male locusts of the three groups mentioned above on ice under the microscope after being injected with 0.02 mL of $4\%$ formaldehyde:$1\%$ glutaraldehyde (4F:1G) buffer (pH 7.2) in the abdominal region as the fixative solution, comprising 10 mL of formaldehyde ($40\%$), 4 mL of glutaraldehyde ($25\%$), 1.16 g of monobasic sodium phosphate, and 0.27 g of NaOH, completed to 100 mL by Milli-Q water as previously described [24], for scanning electron microscope–energy dispersive X-ray microanalyzer (SEM-EDX), histological, and ultrastructural analyses. The collected testicular tissues used for biochemical assays were preserved at −80 °C until use.
## 2.6. X-ray Detection of Al in the Testes of L. migratoria
To assess the levels of Al accumulated in the testicular tissues of adult L. migratoria, three samples from each group were examined by means of SEM (Jeol JSM-5300, Tokyo, Japan) linked with a Link-Isis EDX at an accelerating voltage of 20 kV. The identity of each peak was figured out automatically using the EDX software on the basis of the intensity of each element in comparison to reference elements.
## 2.7.1. Determination of Protein Content in Hemolymph and Total Hemocyte Count
Hemolymph and hemocyte isolations were performed using a modified protocol from Bergin et al. [ 25]. Adult locusts were anesthetized by cooling for 10 min at 4 °C. Afterward, hemolymph was collected by making a small puncture under the hind leg in the abdominal region [26]. The hemolymph was collected into heparin tubes and pooled (0.5 mL) from four locusts for hemocyte counting, with the remainder was pooled in a cold Eppendorf tube (0.5 mL) for total protein analysis. The collected hemolymph was diluted in 1:20 ratio with acidified physiological saline. The acidified physiological saline was prepared by mixing acetic acid with saline solution at a ratio of 0.1:$2\%$. Hemocytes were separated from hemolymph by centrifugation at 1500× g for 5 min at 4 °C, washed twice, and then resuspended in a cold acidified physiological saline. The total hemocyte count was assessed using a hemocytometer by counting three independent samples from each group. Moreover, the total protein content of the hemolymph was evaluated using a commercial total protein kit (Spinreact, Girona, Spain).
## 2.7.2. Biochemical Assays in Testicular Tissues
The dissected testicular tissues were homogenized in a phosphate buffer (pH 7.0) using a homogenizer (Kimble® 885300-0002, Sigma-Aldrich Chemie GmbH, Maryland, USA) then centrifuged at 16,100× g at 4 °C for 20 min, and the supernatant was then collected for biochemical assays.
The total proteins of testicular homogenates (mg/mg tissue) were assessed as described by Lowry et al. [ 27]. To appraise the lipid peroxidation, the malondialdehyde (MDA) level was determined following the protocol of Ohkawa et al. [ 28]. The assay is based on a reaction between 2-thiobarbituric acid (TBA) and MDA at 95 °C, resulting in the production of 2-thiobarbituric acid-reactive substance (TBARS) with a pink color, which was measured at 532 nm using a spectrophotometer. A reaction mixture free of a testis sample served as a control.
Alanine transferase (ALT) and aspartate transferase (AST) activities were quantified in the testicular homogenates utilizing BioSystems assay kits (Madrid, Spain), according to the manufacturer’s protocols. Furthermore, the performance of creatine kinase (CK) was assayed using a kit purchased from Spinreact Co. (Girona, Spain) following the manufacturer’s protocols.
To determine the activities of detoxifying enzymes, the activity of β-carboxylesterase (CarE) in the testicular tissue homogenates was measured following the protocol described by Thompson [29], and the activity of glutathione S-transferase (GST) was estimated according to the method reported by Carmagnol et al. [ 30].
Furthermore, the total antioxidant capacity (TAC) was evaluated using an assay kit supplied by Abcam Company (ab65329, Abcam Co., Berlin, Germany), while the activity of superoxide dismutase (SOD) was estimated utilizing the EliteTM SOD Activity Assay Kit (MBS433565, MyBioSource Co., San Jose, CA, USA) following the manufacturer’s procedures. Additionally, glutathione peroxidase (GPx) activity was assessed following the method of Flohé and Günzler [31] and the activity of catalase (CAT) was determined following the procedures reported by Aebi [32].
To assess the index of inflammation in the testicular homogenates, the level of nitric oxide (NO) was assayed by a nitric oxide assay kit (ab65328, Abcam Co., Berlin, Germany) according to the manufacturer’s instructions.
## 2.7.3. Molecular Docking and Computational Studies
Based on the findings of a previous study [20], some PAE compounds were chosen for molecular docking analysis in order to predict the antioxidant capacity implicated in our studied extract. The compounds, 7a-Methyl-1,2,3,6,7,7a-hexahydro-5H-inden-5-one (MHI), Methyl 4,8,12-trimethyltridecanoate (MTTD), Methylenebis (2,4,6triisopropylphenylphosphine) (MTP), Propanoic acid-ethyl ester (PAE) and oleic acid- methyl ester (OAM) were subjected to molecular docking analysis using two crystal macromolecular structures and 1AR5 and 8CAT targets to probe the antioxidant activity of these ligands. In the current study, a molecular docking simulation analysis was accomplished using Autodock software (version 4.2) (accessed on 1 December 2022) with the preparation of binding sites, then several energetic conformations’ production. The Discovery Studio program (https://www.3ds.com/products-services/biovia/) (accessed on 1 December 2022) was used for some visualization. The crystal macromolecular target proteins used in this study were downloaded from the protein data bank (https://www.rcsb.org/) (accessed on 1 December 2022). Grid parameters were located with box dimensions 60 × 44 × 56 Ǻ3 for 1AR5 and 62 × 54 × 60 Ǻ3 for 8CAT; the specified spaces included a large number of active macromolecular amino acid sites for best conformation prediction.
## 2.7.4. Assessment of HSP70 and HSP90 mRNA Expressions
Three testicular tissues of L. migratoria were randomly selected for total RNA isolation utilizing the TRIzol™ Plus RNA Purification Kit (Invitrogen, USA) following the manufacturer’s instructions. The integrity and purity of the isolated RNA were evaluated by means of agarose gel electrophoresis and a spectrophotometer at $\frac{260}{280}$ nm, respectively. The relative expression levels of HSP70 and HSP90 in testicular tissues of locusts were analyzed using a one-step RT-PCR reaction. The primers used in the RT-qPCR reactions were (Forward) 5′-AAA ATG AAA GAA ACG GCA GAG G-3′ and (Reverse) 5′-TAA TAC GCA GCA CAT TGA GAC C-3′ for HSP70, (Forward) 5′-GAT ACA TCC ACA ATG GGC TAC A-3′ and (Reverse) 5′-CTT GTC ATT CTT GTC CGC TTC A-3′ for HSP90, and (Forward) 5′-AAT TAC CAT TGG TAA CGA GCG ATT-3′ and (Reverse) 5′-TGC TTC CAT ACC CAG GAA TGA-3′ for housekeeping gene β-actin [33,34]. The RT-qPCR reactions were conducted using the Qiagen Rotor-Gene SYBR Green PCR Kit (QIAGEN, Hilden, Germany) in a 25 μL mixture containing 1 μg of RNA, 12.5 μL of SYBR Green, 2.5 μL of each primer and 9 μL of H2O. The RT-qPCR program consisted of an initial step at 95 °C for 5 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 10 s. The assays were performed by means of the Rotor-Gene Q using Rotor-Gene Q-Pure Detection version 2.1.0 (Qiagen, Montgomery, MD, USA). The quantification of the transcript levels of HSP70 and HSP90 mRNA was accomplished in accordance with the comparative 2-ΔΔCT method [35].
## 2.8. Cells Viability Assessment by Flow Cytometry
Flow cytometric analysis of testicular tissues was carried out using the TACSTM Annexin-V-FITC apoptosis detection kit (TA4638, Germany) following the manufacturer’s instructions. Briefly, the cell suspension was obtained from the testicular tissues by homogenizing the tissues in cold phosphate-buffered saline (PBS, pH 7.4) at 4 °C. The cells were harvested and washed twice in PBS before being resuspended in 195 μL of binding buffer. Following this, 5 μL of Annexin-V-FITC conjugate reagent was added to the cell suspensions prior to being maintained in the dark for 10 min. After washing the cells, they were resuspended in 190 μL of binding buffer, followed by the addition of 10 μL propidium iodide solution. The states of different cells were then ascertained employing flow cytometry (Becton Dickinson, Franklin Lakes, NJ, USA) and the findings were assessed by means of Cell Quest Pro software version 5.2.1, 2005 (Becton Dickinson, San Jose, CA, USA).
## 2.9. Assessment of DNA Damage
The genotoxicity of the cells obtained from the testicular tissues of adult L. migratoria was evaluated by means of the comet assay according to Tice et al. [ 36]. The tissues were chopped using small dissecting scissors before being homogenized in a chilled buffer consisting of 0.075 M NaCl and 0.024 M Na2EDTA. The cell suspension was centrifuged at 700× g and 4 °C for 10 min, washed twice using the same buffer, and the cell pellet was then obtained. After that, cells were mixed with molten low-melting point (LM) agarose, followed by the spreading of the mixture over a frosted slide. The slides were immersed in lysis solution for 60 min before commencing the electrophoresis at a high pH (pH 13). Next, the slides were immersed in a neutralization buffer for 15 min. Afterward, the samples were dried, stained with ethidium bromide, and viewed by a Leitz Orthoplan epi-fluorescent microscope equipped with an excitation filter of 515–560 nm and a barrier filter of 590 nm. The microscope was connected to a computer-based image analysis system (Comet Assay V software, Perspective Instruments). To determine comet cells, 50 to 100 randomly selected cells per slide were used, and DNA damage was evaluated as tail length, % tail DNA, and tail moment accordingly.
## 2.10. Scanning Electron Microscope (SEM) Analysis of Testes
The testicular tissue samples were prepared for surveying by SEM as previously described [4]. Briefly, testicular tissues from each group were fixed in cold 4F:1G, which was prepared as described above (Section 2.5) in 0.1 M phosphate buffer solution (pH 7.2) for 3 h, followed by postfixation in $2\%$ osmium tetroxide for 2 h at 4 °C. The samples were washed in PBS for 2 h at 4 °C, dehydrated in an increasing series of ethanol concentrations for 15 min each, and sectioned to 0.06 mm before being mounted on an aluminum stub. The samples were coated with gold palladium in a sputter-coating unit (JFC-1100 E), followed by inspection by means of an SEM.
## 2.11. Histological and Ultrastructural Analyses of Testicular Tissues
To examine the histological differences between the different groups of locusts, the testicular tissues were fixed, post-fixed, and dehydrated through the ethanol series as mentioned above in the SEM analysis. Subsequently, specimens were immersed in an Epon–Araldite mixture, and the tissues were sectioned (0.5 μm thick) by means of an LKB ultramicrotome (LKB Bromma, 2088 Ultrotome, Mississippi, USA) before being stained with toluidine blue. The slides were investigated employing a light microscope (Olympus CX31, Tokyo, Japan).
For the ultrastructural investigations, the prepared testicular tissues were sectioned (60 nm thick) on an LKB ultramicrotome and then picked up on 200 mesh naked copper grids. Following this, the testicular sections were stained with uranyl acetate and lead citrate before being scanned employing a transmission electron microscope (TEM, JEM-1400 Plus, Tokyo, Japan) at an acceleration voltage of 80 kV.
## 2.12. Statistical Analysis
All investigations were accomplished with 3–5 replicates for statistical analysis. To evaluate the significant differences in the results, statistical analyses of the raw data were carried out by means of GraphPad Prism (Version 8, GraphPad Software Inc., San Diego, CA, USA). For mortality analysis, the log-rank (Mantel-Cox) test was performed, and the Chi square was calculated. As regards the biochemical results, the normal (Gaussian) distribution of the data was assessed using the Shapiro–Wilk test, followed by one-way analysis of variance (ANOVA) with Tukey’s analysis for multiple comparisons between groups. All results are represented as mean ± SD, and they were considered significant at p ≤ 0.05.
## 3.1. Characterization of Al2O3 NPs
We have characterized the Al2O3 NPs used in this study by SEM, TEM, and FT-IR analyses, as depicted in Figure 1. It is apparent from the SEM and TEM images that Al2O3 NPs are spherical in nature with an average particle size of 62 nm, which correlates with the data supplied by the manufacturer. The results reveal that Al2O3 NPs less than 100 nm should be considered nanomaterials in accordance with the International Organization for Standardization (ISO).
Figure 1c delineates the FT-IR spectra of Al2O3 NPs, showing peaks below 1000 cm−1, which are distinct features of the studied nanoparticles. We also observed vibration peaks at 598 and 792 cm−1, which are attributed to Al–O stretching. Furthermore, the peaks at 3501, 3458, and 3391 cm−1 are assigned to the O–H stretching of the hydroxyl group. Additionally, the emergence of the peak at 1399 cm−1 is ascribed to Al=O, while the peak at 1092 cm−1 could be imputed to AL–O–H.
## 3.2. Survival and Mortality Analyses of L. migratoria Male after Injection with Al2O3 NPs and PAE
The survival rates of male locusts after treatment with a single dose of Al2O3 NPs were appraised by monitoring six groups named Al-G1 to Al-G6 for ten days after administration with different concentrations of the nanoparticles. The Kaplan–Meier survival analysis was used to decipher the survival probability assays, as shown in Figure 2a, exposing significant differences between the insects injected with nanoparticles at concentrations of 0.03 and 0.04 mg/g body weight in comparison to the control locusts. Nevertheless, the group injected with 0.03 mg/g body weight of Al2O3 exhibited the highest mortality rate compared to the other groups of locusts, implying that this dose penetrated the most tissues and blood barriers, provoking deleterious impacts on the locust and possibly leading to death. Thus, we determined a dose of 0.03 mg/g body weight of Al2O3 NPs as a deleterious dose with regard to L. migratoria, for further investigations. On the other hand, we tested the toxicity of the PAE toward male locusts using three groups labeled from PAE-G1 to PAE-G3, which were injected with varying amounts of the extract, alongside the control group to determine the safe dose that could be used to alleviate the detrimental influences of Al2O3 NPs. It could be extrapolated from the data in Figure 2b, following the Kaplan–Meier survival analysis for PAE, that the results exhibited no significant differences in the mortality rate between various concentrations of the extract compared to the control insects. Therefore, we determined the highest concentration (0.05 mg/g body weight) of the extract as the potential protective dose in this work.
## 3.3. Evaluation of Al Accumulated in Testicular Tissues of Locusts
The testicular tissues of male locusts dissected from the group treated only with Al2O3 NPs and the group co-treated with Al2O3 NPs and PAE were examined by EDX to evaluate the accumulation of Al compared to the control group as shown in Figure 3. Considering the EDX analysis of testicular tissues harvested from the control locusts, different peaks could be detectable, which are correlated with carbon (C), nitrogen (N), oxygen (O), sodium (Na), phosphorus (P), and sulfur (S). On the other hand, the EDX for the group of locusts treated only with Al2O3 NPs exhibited the substantial agglomeration of Al, reporting 0.25 ± $0.04\%$ alongside comparable elements observed in the control insects with different amounts, as presented in Table 1, which could be elucidated by the anticipated physiological disturbance as a consequence of the exposure to Al2O3. By contrast, the locust group pretreated with PAE as a protective dose before being exposed to the Al2O3 NPs revealed a significant decrease in the level of Al accumulated in the testes, recording 0.07 ± $0.03\%$. Moreover, similar elements could be perceived in the latest group with concentrations close to the control group, except for sulfur, which could be estimated at high concentrations. This is most likely related to the sulfur contents of the PAE extract, since the most antioxidant and bioactive compounds possess sulfur, endowing them with favorable bioactivity.
## 3.4. Impact of Al2O3 NPs and Combinatorial Treatment of Al2O3 NPs and PAE on the Physiological Properties of L. migratoria
The density of hemocytes in the hemolymph was surveyed in the different experimental groups, as portrayed in Figure 4a. The total hemocyte count (THC) of the control insects was determined to be 3613 ± 65 hemocytes/µL. Compared to the control locusts, the THC significantly increased in the Al2O3 NPs-treated insects, reporting 5350 ± 70 hemocytes/µL. Noticeably, locusts that received combinatorial treatment with PAE (0.05 mg/g body weight), followed by Al2O3 NPs (0.03 mg/g body weight), exhibited a remarkable diminution (3767 ± 134 hemocytes/µL) in hemocyte density compared to those doped only with Al2O3 NPs. These findings suggest that injection with Al2O3 NPs induced inflammatory responses in L. migratoria that could be markedly mitigated by pretreatment with PAE.
In comparison to control locusts, the MDA levels were significantly promoted (Figure 4b), while the GST and CarE were remarkably diminished with regard to the testes of Al2O3 NPs-injected insects, as given in Figure 4c,d. Furthermore, considerable reductions in the TAC and GPx activities were observed in Al2O3 NPs-treated insects (Figure 4e,f), whereas the activities of CAT and SOD were significantly increased compared with the control insects (Figure 4g,h). Moreover, the activities of metabolic enzymes, including ALT, AST, and CK, were significantly enhanced in Al2O3 NPs-treated locusts compared to those of the control group (Figure 4i,j,k). Locusts pre-administered with a prophylactic dose of PAE, followed by Al2O3 NPs, manifested significant restoration of most of the studied biomarkers compared to insects receiving Al2O3 NPs alone. Taken together, these findings point out that the oxidative stress and toxicity induced by Al2O3 NPs could be significantly alleviated by PAE pretreatment.
From the data in Figure 5a, it is evident that the single application of Al2O3 NPs (0.03 mg/g body weight) in male locusts provoked a noticeable lessening in the total protein content in both testicular tissues and the hemolymph compared to the control insects (Figure 5a). In contrast, the pre-exposure of male locusts to PAE improved the protein content of the hemolymph. Moreover, the pre-treatment of male locusts with PAE ameliorated the total protein contents in the testis, with no significant difference compared to the control locusts, as shown in Figure 5b.
To delve into the expression of important stress factors, we investigated the impacts of Al2O3 NPs on the expression of HSP 70 and HSP 90 in the locust testes, as depicted in Figure 5c. The results reveal a significant upregulation in both HSP 70 and HSP 90 genes in Al2O3 NPs-treated locusts compared to control insects. By contrast, the locust group co-treated with PAE + Al2O3 NPs demonstrated significant downregulations of both genes as a result of pre-treatment with PAE. These results clearly indicate that PAE could modulate the Al2O3 NPs-induced stress response, which supports the previous biochemical assays.
Besides this, the NO level in the testicular tissues of the Al2O3 NPs-injected locusts was significantly raised in comparison with the control group, whereas the pre-exposure of locusts to PAE prior to being doped with Al2O3 NPs significantly lowered this effect by $45\%$, as illustrated in Figure 5d. The reduction in NO levels in the testes of locusts treated with PAE emphasizes the antioxidant and anti-inflammatory properties of the PAE, implying that the PAE compounds may have the capacity to scavenge nitric oxide.
## 3.5. Evaluation of DNA Impairment by Comet Assay
The biochemical findings clearly point out that several metabolic pathways were affected by Al2O3 NPs. In addition, they reveal that the pretreatment with PAE could be remarkably effective in counteracting the adverse effects of Al2O3 NPs, restoring the major metabolic activities of the cells. We thus investigated the capacity of the PAE to reinstate the dominant functions of cells alongside the impact of exposure to Al2O3 NPs in the testicular tissues of locusts on the DNA integrity of the testicular cells. To assess DNA integrity in testicular tissues of L. migratoria after Al2O3 NPs intoxication, we conducted a comet assay (Figure 5e–g). Three parameters were estimated: percentage of DNA in comet tail, length of comet tail, and tail moment. As anticipated, the administration of Al2O3 NPs instigated genotoxic consequences in the testes of L. migratoria. Specifically, the level of DNA impairment was substantially higher in the testicular tissues of locusts that were only treated with the Al2O3 NPs, compared to both the control and PAE + Al2O3 NPs groups. Besides this, the amount of DNA in the comet tail was noticeably higher in the testicular tissues of the group exposed only to Al2O3 NPs, compared to the control and the PAE + Al2O3 NPs locusts. Moreover, the mean DNA percentage in the comet tail of the testicular tissue of the Al2O3 NPs-injected locusts was about three times higher than in the control ones, while PAE treatment resulted in a significant reduction of $40\%$ compared to the Al2O3 NPs-injected locusts. Collectively, these outcomes show a prominent protective influence of PAE against Al2O3 NPs-induced genotoxicity, verifying our biochemical analyses.
## 3.6. Assessment of Cell Viability by Flow Cytometric Analysis
The Annexin-V-FITC assay has shown that a single application of Al2O3 NPs provoked a substantial disturbance of live, dead, and apoptotic cells in the testicular tissues of migratory locusts, as illustrated in Figure 5h and Figure 6. Evidently, we discerned a significant reduction of $40\%$ in living cells, associated with remarkable rises in apoptotic (early and late) cells in the Al2O3 NPs-injected locusts compared to the control insects. In contrast to these findings, PAE treatment counteracted this effect by increasing viable cells and decreasing apoptotic cells. These findings along with those obtained from the comet analysis demonstrate the effectiveness of PAE as a counteractive dose to rescue cell viability and their ideal characteristics in L. migratoria testicular cells.
## 3.7. Molecular Docking Analysis
To rationalize the previous experimental activities as antioxidant behaviors, molecular docking data analysis predicted the inhibition of protein active sites. The best conformers and protein–ligand binding states generated from docking are ranked with higher (with negative values) binding energies. Table 2 presents the ligands with binding energy (Ebinding) and intermolecular energy (EIntermol.) values, where the more negative values of binding energy explain the stability of the protein–ligand complex. According to the investigated energy parameters, related to binding energy, it was predicted that MHI is more stable (−5.79 kcal/mol) in complexing with the target protein 1AR5, and also forms a more stable complex (−6.03 kcal/mol) with the target protein 8CAT. This may be attributed to the heterocyclic rings that strongly interact with amino acids independent of their number and type of interaction. As regards other intermolecular interactions, MTTD manifested several interaction types with 1AR5 (−8.24 kcal/mol), while in 8CAT, one type of unfavorable interaction destabilized the ligand–protein complex (12.56 kcal/mol). In both target proteins, MTP yielded a highly unstable bio-complex due to the large steric hindrance and unfavorable bumps that were formed. PAE and OAM with 1AR5 showed a similar binding-stabilization effect (−3.79 and −3.73 kcal/mol, respectively), with larger interaction types in only OAM (−8.56 kcal/mol), while for 8CAT, the protein–PAE complex was found to be more stable than OAM. Based on the data resulting from docking with the two target proteins 1AR5 and 8CAT, the five ligands with a successful pose score interacted with several amino acids. Figure 7 and Figure 8 show the best docking scores at the same protein active sites, with some differences in the mode of interaction. Due to the large variety of structural functional bio-species, Figure 9 and Figure 10 show several non-covalent interaction types present between the bio-macromolecule and the studied ligands, such as Van der Waals, alkyl, π-alkyl, conventional hydrogen and carbon–hydrogen bonds, and the π-donor hydrogen bond. Large unfavorable bumps are distributed in the protein–MTP complex (Figure 8c and Figure 10c), and are also slightly present in the 8CAT-MTTD complex (Figure 10b).
## 3.8. SEM Analysis
Scan electron micrographs of the Al2O3 NPs-injected locusts reveal anomalies in the morphology of the testicular tissues, with remarkable impairment in the testicular follicle (TF). Additionally, Al2O3 NPs exposure resulted in significant diminutions in the TF width compared to the control and pre-treated with PAE tissues (Figure 11a, a` and a``). Moreover, abnormalities in spermatozoa (Sz) heads and flagella structures were observed in the Al2O3 NPs-injected insects compared with the control group and the locusts pre-administered with PAE (Figure 11b–b``). The spermatozoa of locusts exposed only to Al2O3 NPs emerged with abnormal morphologies, with double-head spermatids and spermatids agglutinated tail-to-tail (Figure 11b`), whereas those from locusts exposed to PAE + Al2O3 NPs had regular morphological structures and a long flagellum without any abnormalities (Figure 11b``). The spermatozoa bundles in the Al2O3 NPs-injected locusts appeared with an irregular arrangement compared to the control insects (Figure 11c,c`). It is evident that the spermatozoa bundles in the PAE-treated locusts emerged with regular arrangements similar to those in the control group, and exhibited no signs of agglutinations or structural abnormalities, as illustrated in Figure 11c``. Overall, these findings suggest that PAE may be useful in preventing the testicular structural anomalies caused by Al2O3 NPs.
## 3.9. Histological Analysis
Histological analysis of the TF of locusts treated with Al2O3 NPs has shown severe morphological and structural aberrations, including remarkable shrinkage in TF size compared to the control insects (Figure 12a–a``). Typical cysts within the TFs and parietal cells in between were discerned in the control and the PAE + Al2O3 NPs-treated groups. By contrast, ruptured cyst walls and numerous vacuolations within cysts were observed in Al2O3 NPs-treated locusts, which could not be detected in the controls or the insects treated with PAE + Al2O3 NPs (Figure 12b–b``).
In the PAE + Al2O3 NPs locust group, the TF showed various cysts at different developmental stages of the spermatogenic elements, including primary spermatocytes, secondary spermatocytes, and spermatids with typical cyst morphology, intact cyst walls, regular parietal cells, and typical global organization, indicating normal spermiogenesis development (Figure 12c). By contrast, morphologically altered spermatogonia, showing signs of disintegration and necrosis with anomalous staining, dense vesicles, dense particles, and vacuolated cysts without any germ cells, were discernible in Al2O3 NPs-injected locusts. The severe shrinkage within the TF of Al2O3 NPs-injected locusts resulted in a distinct separation between the follicular wall and the cyst content, which led to the presence of an empty area throughout the contour of the follicle. This empty area revealed the rupture of the follicular or cyst walls, as depicted in Figure 12c`. Interestingly, the normal organization of the secondary spermatocyte, the short spermatids, and the long spermatids within the cysts was discernible in the locusts pre-exposed to PAE (Figure 12c``).
## 3.10. Ultrastructural Analysis
To further substantiate the previous findings, we inspected the ultrastructure of the testicular tissues using TEM analysis. The control insects had normal spermatogenic structures, with the mitochondrial nebenkern associated with the early spermatid stage (Figure 13a). However, Al2O3 NPs-injected locusts showed several aberrations in the spermatogenic elements, including a degenerated nebenkern with vacuoles and Al2O3 NP accumulation within it (Figure 13a`). Remarkably, despite the presence of a few nanoparticles within the cyst and mitochondrial nebenkern in insects treated with PAE + Al2O3 NPs, the TF ultrastructure manifested with normal characteristics and no malformations (Figure 13a``).
It could be observed that the short spermatid stage in the control group had a typical structure, as shown in Figure 13b. Conversely, a nuclear dense vesicle of aggregated nanoparticles and agglutinated head-to-head spermatids could be observed in Al2O3 NPs-exposed group (Figure 13b`). We presume that the black spots observed in this section are likely related to the cluster of nanoparticles, since they were not detected in the control insects, but the exact nature of the spots is not adequately assessable with TEM analysis. On the other hand, a normal short spermatid was perceived in the group pretreated with the PAE (Figure 13b``). Additionally, transversal sections across the flagella revealed a typical axoneme in the middle, surrounded by two mitochondrial derivatives (Figure 13c). On the other hand, locusts exposed only to Al2O3 NPs emerged with various structural anomalies in the flagella, including a degenerated axoneme and malformed mitochondrial derivatives. Furthermore, agglutination is implied by three axonemes in the same section (Figure 13c`). However, pretreatment with PAE resulted in the emergence of normal flagella with a typical axoneme and mitochondrial derivatives (Figure 13c``). The TEM analysis confirms our previous findings, emphasizing the vital role of PAE as a prophylactic extract in attenuating the toxicity induced by Al2O3 NPs.
## 4. Discussion
Recently, a considerable amount of literature has proliferated around the importance and broad applications of aluminum nanoparticles. In light of this event, it is becoming extremely problematic to disregard the incidence and bioaccumulation of these nanoparticles in living organisms. Thus, several authors have attempted to investigate the deleterious influences of Al NPs on mammals and in vitro using cell lines. They reported that Al NPs can induce oxidative stress in different types of cells, which could further engender adverse consequences for the metabolic pathways and the functions of several organs [10,37]. However, no reports have comprehensively studied the impacts of Al NPs on testicular tissues of migratory locusts. On the other hand, previous investigations sought to discover antioxidant agents derived from plants, particularly those containing polyphenolic compounds, to curtail the toxicity of the nanoparticles and treat the oxidative testicular injury triggered by their indirect influence on cells existing in testes [18,19]. However, the antioxidant compounds extracted from the insects have received scant attention in empirical research. In this work, we extensively studied the influence of Al2O3 NPs on the testicular tissues of L. migratoria as an insect model and sought to suppress their harmful effects through the pre-treatment of locusts with PAE as a prophylactic agent.
## 4.1. Size and Bioaccumulation of Al2O3 in the Testicular Tissues
Admittedly, the size of nanoparticles makes a decisive contribution to the degree of their harmfulness, since it affects their infiltration throughout the tissues [3]. The SEM and TEM analyses revealed that Al2O3 NPs have an average size of 62 nm, indicating the facile translocation of the nanoparticles throughout the locust’s tissues.
EDX examination of the testicular tissues harvested from the control group of locusts revealed the incidence of C, N, O, Na, P, and S, while the locust group exposed to Al2O3 NPs demonstrated the agglomeration of Al in addition to the previous elements. The pretreatment of locusts with PAE resulted in a significant lessening of the Al accumulated in the testes. This is likely related to the chelating activity of PAE, due to the presence of several compounds with high antioxidant features along with chelation properties in relation to the nanoparticles [20].
## 4.2. Impact of Alumina and PAE on Hemocytes
Hemocytes are predominantly assumed to play a crucial immune role in animals with regard to cellular and humoral responses [38]. Thus, an increase in hemocytes is likely stimulated to promote the detoxification process of pollutants and other toxic substances [39]. Our findings have demonstrated that a single administration of Al2O3 NPs resulted in hemocyte activation and an increase in THC. Previous studies revealed that exposure to CuO NPs and ZnO NPs increased THC levels in the hemolymph of *Galleria mellonella* and Bombyx mori, respectively [40,41]. In accordance with our findings, studies on G. mellonella have suggested that this growth may be attributed to the enhancement of hematopoiesis or the immune response on account of the activation of the mitotic division of hemocytes in response to the accumulation of Al NPs [39,40]. In contrast to these findings, the THC was lessened as a result of pre-administration with PAE, implying the capacity of the extract to govern the inflammation provoked by Al2O3 NPs.
## 4.3. Al-induced Oxidative Stress in the Locust Testes
In the current study, in the testicular tissues from the Al2O3 NPs group, we reported augmentations of MDA, SOD, and CAT levels, whereas the activities of TAC, GPx, CarE, and GST were substantially decreased. ErbaŞ and AltuntaŞ [42] proposed that the increase in CAT and SOD activities in G. mellonella could be attributed to an adaptive response to the oxidative damage provoked by xenobiotics. In the same manner, we suggest that the increased levels of CAT and SOD in the Al2O3 NPs may arise as a spontaneous metabolic reaction to acclimatize to the agglomeration of Al inside the testicular tissues.
Furthermore, the MDA level was heightened in the testes as a result of exposure to a single dose of Al2O3 NPs, implying high lipid peroxidation. It is worth mentioning that previous investigations demonstrated that GPx functions to enhance the detoxification of lipid hydroperoxides, which stem from lipid peroxidation (LPO), and it could even hamper the instigation of LPO [42]. Therefore, the decreased levels of the antioxidant enzymes (TAC and GPx) in the testicular tissues could be explained by a rise in LPO activity that may be related to the reduction in antioxidant enzymes implicated in the detoxification of ROS in these tissues, to sustain the antioxidant defense system. By contrast, the pretreatment of locusts with PAE promoted the performances of TAC and GPx, which explains the antioxidant characteristics of the extract. In addition, the remarkable inhibition of CarE and GST activities in the Al2O3 NPs-treated group indicates their deficiency in repelling the oxidative stress, which further gives rise to the impairment of the testicular tissues. However, the amplification of TAC capacity in the PAE-treated group discloses that the antioxidant defense system was immensely active in modulating the oxidative stress derived from the discharge of ROS. Therefore, the improved enzymatic activities in the PAE treated animals were probably due to the protective role of PAE against Al2O3 NPs-mediated toxicity.
It is being recognized that metabolic enzymes play a vital role in preventing the oxidative damage resulting from xenobiotic agents. Thus, it was reported in the locusts exposed to Al2O3 NPs that the activities of ALT and AST were significantly enhanced, while the protein contents were markedly diminished. These findings are in agreement with those observed in the ground beetle as a result of soil pollution with heavy metals [43,44]. Previous studies have suggested that a decrease in total protein could be considered a strong sign of the dysregulation of enzyme activities and expressions, as elaborated above [45]. It is well known that heat shock proteins (HSPs) play a paramount role in insects and mammals to maintain cellular homeostasis [46]. In our previous work, we found a noticeable upregulation of specific protective proteins, such as HSPs, as a defense strategy to govern oxidative stress [47]. Our findings demonstrate that the expressions of HSP70 and HSP90 were highly upregulated in the Al2O3 NPs-exposed animals compared to the controls. However, significant inhibition of their expression was observed in the insects pretreated with PAE. Previous studies reported an increase in HSP70 levels in A. domesticus after exposure to nanodiamonds [48] and to nanographene oxide [49]. On the other hand, the increase in the NO level in the locusts treated only with Al2O3 NPs clearly indicates the unfavorable stress inside the cells, which was significantly abated in the group treated with PAE. Prior studies have posited that nitric oxide has the ability to react with superoxide, producing peroxynitrite. Given the intense oxidative capacity of peroxynitrite, it could interact with the molecules in the biological system, which further thwarts the activity and functions of imperative metabolic enzymes, disrupting the integrity of mitochondria [19,50]. Nevertheless, the remarkable diminution in the NO in locusts pretreated with PAE points to the capacity of the antioxidant compounds in PAE to scavenge the NO, impeding the other adverse effects. To explain the deleterious consequences of Al2O3 NPs on the basis of these findings, we presume that the interaction of these nanoparticles is comparable to that of other counterparts, such as AgNPs [6,7]. Thus, we could postulate that the toxicity of Al2O3 NPs could be instigated through the surface oxidation of the nanoparticles by oxygen and other oxidized agents, which predominate in living organisms, stimulating the discharge of free Al inside the cells. This could result in an excess of ROS, which could lead to other severe complications, such as inflammation and cell cycle disorders.
Surplus ROS could impair the integrity of the lipid membrane and augment membrane permeability [51]. This leads to protein impairment, including modifications of amino acids, the disintegration of peptide chains, critical aggregation, and uncontrolled cross-linking reactions, and indeed, these cause the considerable production of non-functionalized proteins and enzymatic deactivation [51,52].
From these findings, it could be deduced that the toxicity of Al2O3 NPs could result in the dysfunction of the reproductive system by inciting oxidative injury in the testicular tissues. On the other hand, the pre-administration with PAE efficiently attenuated the direct and indirect deleterious effects of Al2O3 NPs through the amelioration of the antioxidant defense mechanism, which further impedes oxidative stress. Based on recent studies, the antioxidant activity of PAE may be mainly attributed to the existence of various antioxidant compounds in the PAE, since the authors have demonstrated the presence of sixty compounds with different structures and properties, such as dopamine, coumarin, aminoacids, dipeptide, and organic compounds, which make crucial contributions to controlling the overproduction of ROS, leading to an improvement of the antioxidant enzymes and other oxidative parameters [20,23]. Overall, the molecular docking analysis and the in vivo studies emphasized the antioxidant competency of the PAE.
## 4.4. Apoptotic Analysis and DNA Damage of Testicular Tissues
It is assumed that oxidative stress caused by an overflow of ROS disrupts the antioxidant metabolic system of the cells, provoking apoptosis, which is predominantly associated with DNA damage. Moreover, the unregulated ROS impair the DNA by oxidizing deoxyribose, fragmenting the DNA strand, altering bases, and further leading to critical mutations in the expressed proteins [51,53,54]. On the other hand, previous studies postulated an alternative interaction of nanoparticles, such as Ag and Al, with DNA that depends on the infiltration of nanoparticles into the nucleus through nuclear pores and binding to the DNA of the cells, modifying the structure of the DNA and leading to either DNA damage or unanticipated mutations [7,55]. Furthermore, the integrity and functions of mitochondria are prone to critical disorders due to the overproduction of ROS, which is usually modulated by the antioxidant mechanism of mitochondria. However, the accumulation of Al results in an overabundance of ROS, causing oxidative stress associated with a disturbance of ATP synthesis. Accordingly, the anticipated fate of cells triggered by these critical dysregulations includes DNA injury and apoptosis. According to our data, Al2O3 NPs induced DNA impairment, which is consistent with previous reports that showed an increase in DNA damage in A. domesticus after the administration of nanodiamond [48] and graphene oxide [55]. Although the Al2O3 NPs accumulated within the testicular tissues, the group pretreated with PAE showed a reduction in DNA damage compared to the group treated only with Al2O3 NPs. Consequently, our results demonstrate that PAE can protect DNA from the genotoxic effect of alumina NPs. Regarding the health status of locust cells in our study, several investigations have reported an elevation in apoptotic and necrotic cells due to metal NPs’ toxicity [7,56]. Importantly, the PAE-treated group exhibited improved cell survival, as a higher percentage of viable cells combined with reduced percentages of apoptotic and necrotic cells were observed. However, the complete restoration of the cell’s viability requires a longer time after eradicating the major deleterious influences of Al2O3 NPs. Altogether, the pre-treatment of locusts with PAE may protect cells from the negative effects of Al2O3 NPs by suppressing DNA damage and inhibiting cell apoptosis.
## 4.5. Histological and Ultrastructural Analyses of Testicular Tissues
To provide more evidence on the protective influence of PAE in relation to attenuating the hazardous episodes provoked by the toxicity of the testicular tissues with Al2O3 NPs, we inspected the histological and ultrastructural characteristics of the testes compared to the testicular tissues exposed to a single application of Al2O3 NPs and those from control locusts. Prior investigations have evidenced that treatment with either Ag NPs or NiO NPs incited various anomalies in the testicular tissue of beetles, including deformed spermatogenic elements and agglutinated spermatids, in addition to axonemal and mitochondrial deformations [4,47,57]. Furthermore, Wang et al. [ 58] reported that exposure to nanoparticles such as TiO2, gold alloys, nickel NPs, and Ag NPs had serious effects on the male reproductive system. In this study, histological, SEM, and TEM analyses demonstrated different aberrations in testicular tissues from locusts treated with Al2O3 NPs, particularly a substantial degradation of the mitochondria. The disintegration of mitochondrial structures and their derivatives conceivably disrupts the ATP supply for sperm motility, leading to infertility [4,47]. These observations imply the alarming toxicity of Al2O3 NPs connected with bioburden toward cells, even if they are administered in low doses. Kheirallah et al. [ 47] elucidated that the secondary fusion of the spermatogenic elements during mitosis could be the underlying cause behind the appearance of bi- and tetra-flagellated sperms. In contrast to these findings, the testicular tissues of the group pretreated with PAE showed the ameliorative capacity of PAE and its role in protecting testicular tissues, with no manifestations of sperm cell agglutination. Given this fact, the treatment of locusts with PAE could sustain the integrity of sperms against the adverse effects of Al2O3 NPs, and we could therefore presume that the behavior of sperms would return to normal with regard to motility and the fertilization process accordingly. In a similar fashion, different plant extracts, such as curcumin [59] and *Aloe vera* gel [60], exhibited ameliorative and protective effects against the Al- and AlCl3-induced reproductive toxicity of Wistar rats. This research raised many questions in need of further investigation. Despite the widespread application of PAE in traditional Chinese medicine [61] and previous studies demonstrating its safe and effective application to accelerate diabetic wound healing [62,63], the mortality test of adult locusts using different concentrations of PAE revealed a mortality rate of $20\%$. Therefore, further investigations are required to understand the underlying mechanisms and interactions of PAE within cells of different organs. Future studies on the purification of the PAE compounds are therefore recommended, since it would be interesting to ascertain the compounds with high antioxidant and anti-inflammatory capacities. Moreover, the antagonistic and synergistic effects of the compounds could be evaluated to explore the potential candidates for promoting their biomedical applications while minimizing their side effects. Notwithstanding these limitations, our findings substantiate the prophylactic effect of PAE against Al2O3 NPs-induced reproductive toxicity in the testicular tissue of the locust model as an animal model, maintaining the structure and function of the testicular tissues. These findings emphasize the results obtained from the biochemical, DNA damage, and apoptotic analyses.
## 5. Conclusions
To sum up, our work offers comprehensive insights into the deleterious effects instigated by exposure to Al2O3 NPs at a low dose in the testicular tissues of L. migratoria, along with the extent of the influence of P. americana extract (PAE) as a prophylactic. Our results demonstrate that the release of Al as a result of Al2O3 NPs oxidation caused disruption of the antioxidant defense system in the testes, resulting in DNA injury, cells apoptosis and alterations in mitochondria and other organelles in the testicular tissue. In contrast, pretreatment with PAE precluded all the harmful effects of Al accumulation at all levels, including the activity of enzyme and non-enzymatic antioxidant factors, the expression of stress biomarkers, DNA impairment, and cell apoptosis. Besides this, no anomalies were perceived in the histological and ultrastructural sections of testicular tissues pretreated with PAE. These findings suggest the potential implementation of PAE to attenuate the oxidative stress and other consequences originating from the toxicity of metal NPs toward the male reproductive system.
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|
---
title: Effects of Particle Size of Curcumin Solid Dispersions on Bioavailability and
Anti-Inflammatory Activities
authors:
- Chihiro Kato
- Mayuko Itaya-Takahashi
- Taiki Miyazawa
- Junya Ito
- Isabella Supardi Parida
- Hiroki Yamada
- Akari Abe
- Mika Shibata
- Keita Someya
- Kiyotaka Nakagawa
journal: Antioxidants
year: 2023
pmcid: PMC10045274
doi: 10.3390/antiox12030724
license: CC BY 4.0
---
# Effects of Particle Size of Curcumin Solid Dispersions on Bioavailability and Anti-Inflammatory Activities
## Abstract
The delivery of curcumin (CUR) using the solid dispersion system (CUR solid dispersions; C-SDs) has been shown to improve CUR bioavailability. However, it is unclear how different particle sizes of C-SDs affect the bioavailability and biological activities of CUR. Hence, we prepared C-SDs in different sizes using food-grade excipients and evaluated their bioavailability and biological activities. By pulverizing large particle sizes of C-SDs using zirconia beads, we successfully prepared C-SDs I-IV (particle size: (I) 120, (II) 447, (III) 987, (IV) 1910 nm). When administrated orally in rats, the bioavailability of CUR was increased with decreasing C-SDs size, most likely by improving its solubility in micelles. When administrated intravenously in rats, blood concentrations of CUR were increased with increasing particle size, suggesting that larger C-SDs presumably control the metabolic conversion of CUR. In RAW264 cells, more CUR was taken up by cells as their sizes reduced, and the more potent their anti-inflammatory activities were, suggesting that smaller C-SDs were taken up through a number of cellular uptake pathways. Altogether, the present study showed an evident effect of C-SDs size on their bioavailability and anti-inflammatory activities—information that serves as a basis for improving the functionality of CUR.
## 1. Introduction
Curcumin (CUR) is one of the principal lipophilic polyphenols in turmeric (*Curcuma longa* L.). While it has various physiological benefits, including anti-inflammatory, antioxidant, and lipid-lowering activities [1,2], these functions are often limited due to the low bioavailability of CUR [3,4]. Efforts have been made to improve the bioavailability of CUR [5]; among these, delivery strategies using solid dispersion techniques (i.e., CUR solid dispersions; C-SDs [6,7,8]) have gained increasing attention due to their promising efficiency.
In C-SDs, CUR is encapsulated in micro/nanoscale vehicles and dispersed in water with the aid of surfactants. Compared to bare CUR, this system improves CUR bioavailability, most likely by enhancing its solubility in bile salt micelles. In fact, our previous findings demonstrated that the delivery of CUR using poly-(lactic-co-glycolic acid) (PLGA)-based nanoparticle dispersions improved its oral bioavailability in rats by about 10-fold [9]. In another study, the delivery of CUR in solid dispersions consisting of solid lipid or D-α-tocopheryl polyethylene glycol 1000 succinate improved the oral bioavailability of CUR in rats by about 9.5-fold and about 65-fold, respectively [10,11]. Even when administered via the intravenous route, polymeric particle-based C-SDs showed beneficial curative properties in the mouse model of acute inflammation [12]. Despite the compelling results, it is important to note that these previous reports used excipients that are tailored for pharmaceutical products, aiming for disease treatments. In recent years, however, measures to prevent diseases through the consumption of functional foods have gained increasing interest, and, thus, we should consider using food-grade excipients in formulating the C-SDs to facilitate their applications in food products.
*In* general, the particle sizes of the encapsulated lipophilic compounds affect their biological activities when administered via oral and intravenous routes [13,14]. For food-grade C-SDs, it was unclear how their particle sizes may affect the bioavailability of CUR. Hence, it is vital that we understand the effect of particle sizes on the bioavailability of food-grade C-SDs in the first place. Some studies have provided salient examples of the significance of compound particle sizes on their biological activities. For instance, previous studies have demonstrated the increasing bioaccessibility of some lipophilic compounds (i.e., β-carotene, coenzyme Q10, and raloxifene) after oral administration, with decreasing particle sizes in dispersions comprised of bile acids or surfactants [15,16,17]. Furthermore, even for intravenous administration, optimizing particle size is known to be important (e.g., for blood profiles) [18]. Considering the above points, we aimed to formulate C-SDs using food-grade excipients with a strictly controlled particle size, which is expected to optimally enhance the bioavailability of CUR for a wide range of applications, including disease prevention and treatment.
To achieve our objective, we attempted to prepare four C-SDs with different particle sizes ((I) 120, (II) 447, (III) 987, (IV) 1910 nm) using food-grade excipients. Once we successfully prepared the C-SDs, we determined how their particle sizes affect their functional potencies by investigating: [1] their oral bioavailability based on the plasma level of CUR and its metabolites (e.g., curcumin glucuronide (CURG)) post-oral administration in rats, [2] their blood profile after intravenous administration in rats, and [3] their cellular uptake and anti-inflammatory activity through cell experiments (Figure 1). The findings from the present study will hopefully be useful in efforts to improve the functionalities of bioactive food compounds such as CUR and formulate functional food products.
## 2.1. Reagents
Lipopolysaccharide (LPS), N-(1-naphthyl) ethylenediamine, sodium nitrite, and sulfanilamide were purchased from Wako Pure Chemical Industries, Ltd. (Osaka, Japan). All other chemicals and reagents used in the study were of analytical grade or higher.
## 2.2. Preparation of C-SDs
We started by determining suitable materials for preparing C-SDs I-IV under optimized conditions. To prepare the excipient emulsion, 5.0 g of glycerin, 3.5 g of decaglycerol monoester, 2.0 g of lysolecithin, and 0.2 g of sodium chloride were dispersed in 83.8 mL of water then heated at 70 °C for 30 min. Into the emulsion, 5.5 g of the CUR powder (Vidya Japan K. K, Tokyo, Japan) was gradually added over 30 min with constant stirring at 6000 rpm using a homomixer (Homomixer mark II; PRIMIX Corp., Hyogo, Japan), and 1.3 mL of ethanol was mixed at room temperature to obtain C-SDs IV. To obtain C-SDs III, 80 mL of C-SDs IV was transferred to a planetary mill (Pulverisette 6; Fritsch Japan Co., Ltd., Kanagawa, Japan) and pulverized with zirconia beads (mean diameter: 0.3 mm) at 350 rpm for 2.5 min. C-SDs II was obtained by further pulverizing 60 mL of C-SDs III in a planetary mill for 15 min, and C-SDs I was obtained by pulverizing 40 mL of C-SDs II in a planetary mill using smaller zirconia beads (average diameter: 0.03 mm) at 600 rpm for 180 min. C-SDs I-IV were stored at room temperature and shielded from light until use in experiments. The range of particle size was determined based on a previous study [19].
## 2.3. Characterization of C-SDs I-IV
To determine the particle size and zeta potential of C-SDs I-IV, 20 µL of C-SDs I-IV were diluted with water to appropriate concentrations and analyzed using dynamic light scattering and laser Doppler anemometry (ELS-Z; Otsuka Electronics Co., Ltd., Osaka, Japan).
To observe the shape of C-SDs I-IV, 20 µL of C-SDs I-IV were diluted 1000-fold with water and photographed using a transmission electron microscope (TEM, H-7650 ZeroA; Hitachi, Ltd., Tokyo, Japan).
To measure the CUR concentration in C-SDs I-IV, 100 µL of C-SDs I-IV were dissolved in 30 mL of methanol and passed through a filter to remove insoluble components (GL Chromatodisc, 0.45 µm; GL Science, Tokyo, Japan). One hundred microliters of the solution were diluted with 900 µL of methanol, and a 10 µL aliquot was subjected to analysis using high-performance liquid chromatography with ultraviolet detection (HPLC-UV; JASCO, Tokyo, Japan). Chromatographic separation was performed using a ProC18 column (4.6 × 150 mm, 5 µm; YMC Co., Ltd., Kyoto, Japan) with a binary gradient consisting of solvent A ($0.05\%$ formic acid) and solvent B (acetonitrile). The gradient profile was as follows: 0–17 min, 30–$50\%$ B linear; 17–22 min, 50–$100\%$ B linear; 22–32 min, $100\%$ B. The flow rate was adjusted to 1.0 mL/min, and the column temperature was maintained at 40 °C. CUR was detected at 420 nm, and its concentration was determined using the standard curve of CUR (Nagara Science Co., Ltd. (Gifu, Japan)).
## 2.4. Bioavailability of C-SDs after Oral Administration in Rats
Seven-week-old male Sprague Dawley (SD) rats weighing 220–240 g were purchased from CLEA Japan Inc., (Tokyo, Japan). The rats were group-housed (two rats per cage) and placed in the animal experimental room with a 12 h light/dark cycle and controlled temperature of 24 °C. Prior to the experiment, rats were acclimated for one week with ad libitum access to water and commercial rodent chow (CE-2; CLEA Japan Inc., Tokyo, Japan).
For oral administration, acclimated rats were fasted overnight and randomly divided into four groups (C-SDs I-IV, $$n = 4$$). Each group received an oral administration of C-SDs I-IV by a gastric tube equivalent to 100 mg CUR/kg BW (380–504 µL depending on BW). The dose of C-SDs was determined based on a previous study [9] and the preliminary experiment. Blood was collected from the tail vein in heparinized tubes at 0, 1, 3, 6, 12, and 24 h following oral administration and centrifuged at 3600 rpm for 5 min at 4 °C to obtain plasma (MX-307; TOMY SEIKO Co., Ltd., Tokyo, Japan). Plasma samples (100 µL or less) were then stored at −80 °C until analysis.
One hundred microliters of plasma was mixed with 500 µL of acetonitrile, vortexed, and centrifuged at 7400 rpm for 5 min at 4 °C (MX-307; TOMY SEIKO Co., Ltd., Tokyo, Japan). The supernatant was collected, 400 µL of water was added, and it was filtered to remove insoluble components (GL Chromatodisc, 0.45 µm; GL Science, Tokyo, Japan). The same ratio of acetonitrile and water was used for plasma volumes less than 100 µL. Ten microliters of the filtrate were loaded into a high-performance liquid chromatography-tandem mass spectrometry machine (HPLC-MS/MS, 4000 QTRAP; Sciex, Redwood City, CA, USA). Chromatographic separation was performed using an Xbridge™ C18 column (2.1 × 150 mm, 3.5 µm; Waters, Milford, MA, USA) with a binary gradient consisting of solvent A ($0.05\%$ formic acid) and solvent B (acetonitrile). The gradient profile was as follows: 0–20 min, 15–$100\%$ B linear. The flow rate was adjusted to 0.2 mL/min, and the column temperature was maintained at 40 °C. CUR and CURG were detected using electrospray ionization (ESI) MS/MS in negative ionization mode using the following multiple-reaction monitoring (MRM) transitions: CUR, m/z 367 > 217 (collision energy (CE), −18 V; declustering potential (DP), −60 V); CURG, m/z 543 > 134 (CE, −72 V; DP, −85 V). The following MS setting was used for the optimal detection of CUR and CURG: turbo gas temperature, 500 °C; spray voltage, −4500 V; ion source gas 1, 60 psi; ion source gas 2, 50 psi; curtain gas, 30 psi; collision gas, 3.0 V. Concentrations of CUR and CURG were determined according to the standard curves of CUR (Wako Pure Chemical Industries, Ltd., Osaka, Japan) and CURG (Therabiopharma, Ltd., Kanagawa, Japan), respectively.
## 2.5. Blood Profile of C-SDs after Intravenous Administration in Rats
Preliminary feeding was carried out using the same protocols as mentioned in Section 2.4. For intravenous administration, acclimated rats were randomly divided into three groups (C-SDs I-III, $$n = 4$$). Each group received intravenous doses of C-SDs I-III (diluted 5-fold with saline) equivalent to 5 mg CUR/kg BW (104–138 µL depending on BW) via the tail vein. The dose of C-SDs was determined based on the preliminary experiment. From the viewpoint of animal ethics, C-SDs IV, which easily aggregates, was not administered intravenously. Two hours after the intravenous administration of C-SDs I-III, rats were sacrificed, and blood was drawn by cardiac puncture using a heparinized syringe, after which the rats were perfused with saline. Plasma was obtained from blood using the same method as previously mentioned in Section 2.4. To measure the concentrations of CUR and CURG in plasma, 100 µL of plasma underwent extraction and quantification protocols as previously mentioned in Section 2.4.
All animal studies were conducted in accordance with the Committee on the Ethics of Animal Experiments and carried out in accordance with the Animal Experiment Guidelines of Tohoku University (Sendai, Japan). The permit number for this animal experiment is 2021–AgA–011.
## 2.6. Cellular Uptake and Anti-Inflammatory Activity of C-SDs
Mouse leukemic monocyte macrophage (RAW264) cells were obtained from Japan Food Research Laboratories (Tokyo, Japan) and maintained in Dulbecco’s modified *Eagle medium* (DMEM D-6429; 4500 mg/L glucose, high pyruvate; Sigma-Aldrich, St. Louis, MO, USA) supplemented with $10\%$ fetal bovine serum (FBS) and antibiotics (100 U/mL penicillin and 100 µg/mL streptomycin) in 100 mm plastic Petri dishes at 37 °C and $5\%$ CO2. Cell lines were determined based on a previous study [20].
To measure the cellular uptake of CUR after exposure to C-SDs I-IV, RAW264 cells (1.0 × 10⁴ cells) were seeded in 35 mm glass bottom dishes (Matsunami Glass Industries, Osaka, Japan) and grown in 3 mL of medium. After overnight incubation, the medium was replaced with 3 mL of medium containing C-SDs I-IV (final concentration of 10 µM CUR). After another round of incubation for 15 min, cells were washed with phosphate-buffered saline, and CUR in C-SD I-IV-treated cells was observed using confocal laser microscopy (LSM 710; Carl-Zeiss, Baden-Wurttemberg, German). An excitation wavelength of 488 nm and emission wavelength of 519 nm were used to detect the fluorescent of CUR itself.
To measure nitric oxide (NO) production, RAW264 cells (1.0 × 10⁴ cells/well, $$n = 6$$) were seeded in a 96-well plate in 100 µL medium. After a 24 h incubation, 20 µL of medium containing LPS and C-SDs I-IV was added into each well. The final concentration of LPS in the medium reached 100 ng/mL, and the addition of C-SDs I-IV resulted in the final concentration of CUR being 0–15 µM. After further incubation for 24 hours, 80 µL of the supernatant was transferred to another 96-well plate and NO levels were measured through a colorimetric assay as described in a previous study [20].
To measure the expression of genes related to inflammatory response, we performed the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). For RT-qPCR analysis, RAW264 cells were seeded in 60 mm dishes in a 5 mL medium at a density of 1.0 × 10⁶ cells ($$n = 3$$). For ELISA, RAW264 cells were seeded in 60 mm dishes in a 5 mL medium at a density of 1.0 × 10⁶ cells (for IL-1β, $$n = 3$$) and 2.5 × 10⁵ cells (for IL-6 and MCP-1, $$n = 3$$). After incubation for 24 h, the medium was replaced with 5 mL of medium containing LPS (100 ng/mL) and C-SDs I-IV to reach a final concentration equivalent to 10 µM of CUR. After another 24 h of incubation, cells were harvested to prepare RNA extract for RT-qPCR assay, while the mediums were collected for ELISA. Total RNA was extracted from cell lysates, and cDNA was synthesized according to methods previously described [21]. *The* gene expressions of pro-inflammatory markers (Il-1β, Cox-2, Il-6, Mcp-1, Inos, Tnf-α, Nf-κb, Tgf-β, Ho-1, Cat, and Nrf-2) were evaluated through RT-qPCR as described in a previous study [21], and the sequences of primers used in the present study are listed in Table 1. For the detection of Il-1β, Mcp-1, Inos, Tnf-α, Cox-2, Ho-1, Tgf-β, and Nrf-2, samples were subjected to the following amplification condition using an RT-qPCR machine (C1000™ Thermal Cycler; BIO-RAD, Hercules, CA, USA): 30 s at 95 °C, 5 s at 95 °C (40 cycles), and 30 s at 60 °C. The annealing temperature was set at 63.3 °C for Cat and 64.5 °C for Il-6 and Nf-κb, while the rest of the parameters remained similar. The relative expression of each target gene was determined using the 2−ΔΔCt with housekeeping gene Gapdh as the reference gene. The inflammatory cytokines (IL-6, MCP-1, and IL-1β) in the collected mediums were measured using ELISA kits (ELISA MAX Deluxe Set; BioLegend ltd., San Diego, CA, USA) as described in a previous study [20]. The concentration of CUR was determined based on preliminary experiments.
## 2.7. Statistical Analysis
Data are expressed as mean ± standard deviation (SD) or mean ± standard error (SE). Differences between multiple groups were determined using one-way analysis of variance (ANOVA) and Tukey’s posthoc test with $p \leq 0.05$ considered statistically significant. For comparison between two treatment groups, ANOVA and Dunnett’s posthoc test was performed, with $p \leq 0.05$ and $p \leq 0.01$ considered statistically significant. All statistical analyses were performed using the statistics software (EZR; Jichi Medical University Saitama Medical Center, Saitama, Japan) [22].
## 3.1. Characterization of C-SDs
Previous reports have shown an increase in the biological activities of CUR delivered by various nanoparticle systems, either through oral or intravenous routes [5,23]. However, most available reports on C-SDs used pharmaceutical excipients in one particular size. Hence, in the present study, we prepared C-SDs with varying particle sizes at the submicron level using food-grade excipients; the physicochemical properties of C-SDs were characterized, and their bioavailability and efficacy were evaluated.
To prepare the C-SDs, we incorporated lecithin and decaglycerol monoester in C-SDs matrices as they are widely used as food-grade excipients and considered safe for oral administration [24,25]. The formation of C-SDs or any encapsulation process, in general, consists of two main steps: the emulsification of polymer substances containing encapsulated compounds using high-pressure homogenization [26] and the hardening of the nanoparticle surface through solvent evaporation [8,27,28]. However, these methods were not suitable for producing C-SDs in multiple particle sizes, especially using the same excipients, as CUR tends to form aggregates. To overcome this problem, we instead pulverized the homogenized dispersion using zirconia beads; by adjusting the size of beads and grinding time, we generated C-SDs I-IV with particle sizes ranging from submicron to micron using the same food-grade excipients. Using dynamic light scattering, we determined the particle diameter of C-SDs as follows: C-SDs I, 122 nm; C-SDs II, 448 nm; C-SDs III, 991 nm; and C-SDs IV, 1910 nm (Table 2). These were in line with their TEM images (Figure 2). C-SDs I-IV had negative zeta potentials, suggesting that they are properly encapsulated in lecithin and decaglycerol monoester [29,30]. Using the HPLC-UV, we found the following concentration of CUR in C-SDs: 176.7 mM in C-SDs I; 202.5 mM in C-SDs II; 163.6 mM in C-SDs III; and 172.0 mM in C-SDs IV. This showed that almost all CUR was dispersed in water without undergoing oxidation or degradation. In addition to CUR, the HPLC-UV chromatogram of C-SDs I-IV showed peaks of bisdemethoxycurcumin (BDMC) and demethoxycurcumin (DMC) (Figure S1) [4], which are the analogs of CUR commonly present in turmeric products along with CUR itself. Overall, CUR serves as the major active constituent in C-SDs, with BDMC and DMC present at $\frac{1}{40}$ and $\frac{1}{8}$ of the amount of CUR, respectively. This level of CUR is sufficient for evaluating the biological activities of C-SDs in the following experiments. C-SDs I-IV were well-dispersed through sonication before the experiment.
## 3.2. Oral Bioavailability of C-SDs
To examine how the particle sizes of C-SDs affect the oral bioavailability of CUR, we measured the changes in plasma levels of CUR and its metabolites in rats within 24 h of oral administration of C-SDs I-IV (=100 mg/kg BW of CUR per administration). Initially, CUR and its metabolites were not detected in rat plasma prior to C-SDs I-IV administration. Irrespective of the particle sizes of C-SDs, CURG was detected as the predominant constituent in plasma, followed by CUR, within 24 h post-loading (Figure 3). Other metabolites were also detected, although to a lesser extent (Figure S2), and the highest area under the plasma concentration–time curve (AUC) level of CURG was exhibited by the C-SDs I group (Figure 4). Thus, these results suggest that reducing the particle size of C-SDs does improve the bioavailability of CUR, but the differences in particle sizes may not affect CUR metabolism, which commonly occurs in the intestine, liver, and kidney [31]. The relationship between particle sizes and oral bioavailability has been reported for compounds other than CUR. For example, β-carotene in smaller particle sizes (120 nm, 190 nm, 14,000 nm) showed better solubility in micelles [15]. Furthermore, an ex vivo study reported how bovine serum albumin (BSA) in small particles (100 nm) penetrated rat intestinal submucosa at a higher rate compared to large particles (500 nm, 1 μm, and 10 μm) [32]. Therefore, we infer that C-SDs I increased the oral bioavailability of CUR by improving its solubility in bile acid micelles (as described in the Introduction) and/or increasing its penetration into the intestinal submucosa; future studies should focus on elucidating the effect of C-SDs size on these aspects. Additionally, the AUC of CURG in the C-SDs I administered group was consistent with our previous study using C-SDs with PLGA [9], a pharmaceutical excipient [33]. All things considered, our data showed that the small particle size of C-SDs prepared from food-grade excipients improves the bioavailability of CUR to the same extent as the ones made with pharmaceutical excipients.
## 3.3. Blood Profile of C-SDs after Intravenous Administration
C-SDs are often used not only for oral administration but also for intravenous use [12]; thus, we evaluated the effect of particle sizes on the CUR blood profile following the intravenous administration of C-SDs I-III (=5 mg/kg BW of CUR per administration). Similar to the results from oral administration (Section 3.2), CUR and CURG were not detected in rat plasma prior to intravenous administration. At two hours post-loading, we detected CURG as the predominant constituent in plasma, followed by CUR (Figure 5). Other metabolites were also detected, though in lesser amounts. This suggests that even when administered intravenously, a relatively large amount of CUR is metabolized into CURG, an event that is likely to take place in the liver and kidney instead of the intestinal tract [31]. It is interesting to note that while the blood concentration of CURG remained unaffected, the concentration of CUR increased with increasing particle size (Figure 5), thereby suggesting that we can control the metabolic conversion of CUR to CURG by adjusting the particle size of C-SDs. Thus, by increasing the particle size of C-SDs and inhibiting the metabolic conversion of CUR to CURG, we are more likely to increase the in vivo activities of CUR as it is generally more potent compared to CURG [34]. It should be pointed out that a considerable accumulation of CUR was found in the lungs and liver of rats given the larger size C-SDs (II and III) (Figure S3), so future evaluation should also look out for any potential side effects due to this deposition. While some questions have yet to be answered, our results suggest that the intravenous administration of C-SDs with optimized particle size affects the metabolism rate of CUR into CURG, a phenomenon that is not achievable through oral administration.
## 3.4. Cellular Uptake and Anti-Inflammatory Activities of C-SDs
From Section 3.2 and Section 3.3, it appears that the particle size of C-SDs affects CUR bioavailability when administered via the oral route, and presumably affects its metabolism when given via the intravenous route. Previous studies have reported C-SDs interaction with immune cells and anti-inflammatory activities after intravenous administration [12]; hence the present study assessed the effect of C-SDs particle sizes on their cellular uptake and anti-inflammatory activities in the RAW264 macrophage cell line. First, RAW264 cells were incubated in a medium containing C-SDs I-IV, and CUR fluorescence was detected through confocal laser microscopy. The smaller the particle sizes, the higher the fluorescence intensity that is considered to be derived from CUR (Figure 6). Then, the effect of C-SDs particle sizes on their anti-inflammatory activities was assessed based on NO production, gene expression, and secretion of inflammatory cytokines. We found that NO production was inhibited in a dose-dependent manner (5–15 µM) in C-SDs I-IV-treated cells, with smaller particle sizes leading to greater inhibition (Figure 7). There were no significant differences in the cell viability between groups, confirming that cell death did not affect NO production (Figure S4). Along with the aforementioned changes, the expression levels of some pro-inflammatory genes (Il-1β, Cox-2, and Il-6) were reduced by C-SDs treatment, particularly in the C-SDs I and II-treated groups (Figure 8A–C). In addition, the secretion levels of inflammatory cytokines (IL-1β, IL-6, and MCP-1) were markedly suppressed as the particle size decreased (Figure 9). Altogether, our data showed that the smaller the particle sizes, the more efficiently CUR was transferred into the cells and the more potent the anti-inflammatory activities. Small-sized particles can be taken up by cells via multiple pathways, such as clathrin-mediated endocytosis, caveolae-mediated endocytosis (for nanoscale particles), and phagocytosis (nano- to micro-scale particles) [35]. The efficiency of these pathways depends on the particle sizes of the transported particles, which likely explains why smaller C-SDs were taken into cells at a higher rate. To identify the mechanisms involved in the cellular uptake of CUR encased in C-SDs, it may be necessary for future studies to assess C-SDs uptake in the presence of the inhibitors of each pathway. In addition, our previous data showed that piperine increases the cellular uptake of CUR by competitively inhibiting the binding of CUR to BSA [20], and, therefore, we are interested in creating C-SDs containing CUR and piperine as this is likely to further increase its cellular uptake.
## 4. Conclusions
In the present study, C-SDs with different particle sizes were successfully prepared using the same food-grade excipients by pulverizing large-sized C-SDs using zirconia beads. When administered orally, our small-sized C-SDs were able to improve CUR bioavailability to the same extent as the ones made with pharmaceutical excipients (AUC of CURG, 21,364.8 ± 3048.8 nM-hours). When administered intravenously, larger-sized C-SDs appeared to inhibit the metabolic conversion of CUR to CURG about 1.6 times more than smaller sized C-SDs. Cell experiments showed higher cellular uptake of CUR when delivered in smaller-sized C-SDs, and accordingly, their anti-inflammatory activities were more potent. From these findings, it is inferred that we can modify the bioavailability and biological activities of CUR by adjusting the particle sizes of food-grade C-SDs according to the intended purposes. Altogether, this study provides a basis for improving the functionality of CUR and developing new food products containing CUR. For this purpose, it would be essential for future research to conduct short- and long-term pharmacokinetic studies in humans and identify any potential side effects from C-SDs intake (e.g., on bodyweight change and psychokinetic behaviors).
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|
---
title: Overcoming Barriers to Wound Healing in a Neuropathic and Neuro-Ischaemic Diabetic
Foot Cohort Using a Novel Bilayer Biodegradable Synthetic Matrix
authors:
- Frank P. Guerriero
- Robyn A. Clark
- Michelle Miller
- Christopher L. Delaney
journal: Biomedicines
year: 2023
pmcid: PMC10045282
doi: 10.3390/biomedicines11030721
license: CC BY 4.0
---
# Overcoming Barriers to Wound Healing in a Neuropathic and Neuro-Ischaemic Diabetic Foot Cohort Using a Novel Bilayer Biodegradable Synthetic Matrix
## Abstract
Diabetes-related foot ulceration presents an increasing risk of lower limb amputation globally, driving the search for new treatment technologies. Our single-centre prospective observational study reports on the impact of bilayer biodegradable synthetic matrix technology (NovoSorb® BTM) on the healing and amputation rates of a diabetic foot ulceration cohort. Consecutive patients with a diabetes-related foot ulceration treated with NovoSorb BTM, between December 2019 and October 2021, were followed for 12 months. Complete wound healing and amputation outcomes were observed. Amputation risk was stratified using the Wound, Ischaemia and foot Infection (WIfI) classification system. Study outcomes were compared with recently published meta-analysis data to evaluate the impact of the synthetic matrix. In total, 25 NovoSorb BTM applications to 23 wounds in 22 patients were observed. Complete wound healing was observed in 15 of the wounds, 3 retained chronic wounds, 3 required minor amputation and 2 required major limb amputation. Further, 12-month WIfI amputation risk analysis saw 18 patients stratified to WIfI stage 4, 4 to WIfI stage 3 and 1 to WIfI stage 1. Our observed 12-month major amputation rates were $11.1\%$ ($$n = 2$$) for stage 4 and $0\%$ for stages 3 and 1. Our early experience suggests that NovoSorb BTM is a safe and effective treatment for moderate to severe diabetes-related foot ulceration. While larger-scale data are required, NovoSorb BTM may represent a promising new addition to the armamentarium of clinicians, who strive to achieve limb salvage in this complex cohort of patients.
## 1. Introduction
Lower limb amputation is a complication of foot ulceration in patients with diabetes and/or peripheral arterial disease. The annual incidence of foot ulceration in patients with diabetes is reported to be between $2\%$ and $5\%$, with a lifetime risk of $15\%$ to $20\%$. With the global prevalence of diabetes is reported to be 415 million [1], with conservative estimates placing the global incidence of diabetes-related foot ulceration at around 8.3 million. Furthermore, observational studies place rates of amputation in patients with diabetes-related foot ulceration between $6\%$ and $43\%$ [2]. Up to 3.5 million amputations may, therefore, be required globally on an annual basis. In fact, throughout the world, it is estimated that every 30 s, a leg is amputated, and $85\%$ of these amputations are the result of a foot ulcer [3].
It is, therefore, understandable that the concept of amputation prevention has become a growing focus of vascular surgical practice. While advances in endovascular revascularisation techniques have provided improvements in treating macrovascular ischaemia, the associated micro-ischaemia and compromised immuno-cellular environment remain, which stand as barriers to wound healing [4]. Despite radiologically optimal outcomes, many patients do not reach the perfusion pressure threshold for adequate wound healing.
The combination of ischaemia, neuropathy, and immuno-compromise in diabetes-diseased tissue presents a significant challenge to wound healing, often limiting the success of traditional surgical approaches for assisted wound closure, such as split thickness skin grafting and autologous flaps. Use of emerging augmentative wound closure technologies, such as exografts, allografts and acellular dermal matrices, in the treatment of diabetes-related foot ulceration continues to be evaluated and evidence concerning long-term outcome data is lacking [5]. The current limitations of assisted wound closure options for vascular disease patients expose this cohort to extended healing time frames, higher risk of infection and, subsequently, a higher risk of limb amputation.
The proliferative properties of a novel bilayer biodegradable synthetic matrix product (NovoSorb® BTM, PolyNovo Biomaterials Pty Ltd., Port Melbourne, VIC, Australia) are suitable for application over exposed deeper structures, such as tendon and bone [6,7,8], and may be a new alternative for assisted wound closure in patients with diabetes-related neuropathic and neuro-ischaemic foot wounds. BTM is a 2 mm-thick biodegradable polyurethane foam matrix, which houses a pre-fenestrated non-biodegradable sealing membrane on the outward-facing surface (Figure 1a). The sealing membrane serves to physiologically close the wound and protect the underlying matrix during the proliferation of tissue into the open structure foam matrix (integration) during formation of a vascularised neo-dermis (Figure 2). As cellular migration begins into the foam matrix, the chambers are infiltrated by a variety of cell types with the interconnecting pores, allowing for the exchange of nutrients and waste (Figure 1b). Most critically, the chambers compartmentalize the wound response, minimizing the foreign body response and creating a microwound that the body can heal through regeneration. Once tissue proliferation throughout the foam matrix is complete, the sealing membrane is removed to allow epithelialisation to occur [7]. NovoSorb® BTM (BTM) is fully synthetic, contains no biological molecules and retains its structure while it is slowly broken down by hydrolysis within the integrating tissue [7].
This single-centre prospective observational study reports on the impact of bilayer biodegradable synthetic matrix technology (NovoSorb® BTM) on the healing and amputation rates of a complex diabetic foot ulceration cohort.
## 2.1. Study Design
This single-centre prospective observational study investigated the impact of BTM on the proliferation of tissue for the purpose of wound healing and limb salvage in a neuropathic and neuro-ischaemic diabetic foot wound cohort.
## Ethics
The study was approved by the by the Ethics Committee of Southern Adelaide Local Health Network Office for Research (approval number HRE$\frac{0214}{2021}$).
## 2.2. Participants
Consecutive patients treated between December 2019 and October 2021 were prospectively observed if they met the following criteria:A confirmed diagnosis of diabetes, as determined by blood glycosylated haemoglobin (HbA1C) >$6.5\%$ (48 mmol/mol) or as represented by pre-existing prescription of diabetes medication (e.g., insulin or oral hypoglycaemics) within 12 weeks of admission;Who were 18 years or older;*Hosted a* wound in the foot, distal to malleoli, arising from either surgical amputation or debridement of a chronic wound;Who were treated with BTM for the purpose of tissue reconstruction, treatment of tissue deficit or exposed deeper structures, such as bone and tendon, were included.
## 2.3. Study Outcome
Complete wound healing, defined as $100\%$ epithelialisation with no exudate from the site of original BTM application, was established as the primary outcome. Secondary outcomes were time (days) to complete wound healing, occurrence of wound infection post-BTM application and major and minor amputation post-BTM application. Outcome data were collected prospectively and evaluated at 12 months post-date of surgical application of BTM.
## 2.4. Technique
Patients undergoing BTM application were optimised with maximal revascularisation prior to application. The supervising clinician would determine that the wound was clinically free from infection prior to BTM application. BTM was applied in an operating theatre environment. The wound bed was surgically debrided to healthy bleeding tissue, removing any non-viable tissue from the wound bed prior to application. Although pre-fenestrated, additional fenestrations (5–10) were made to the BTM prior to application using the tip of a scalpel on an inverted kidney dish, to ensure adequate extraction of wound exudate through the sealing membrane. The BTM was cut to match the size of the wound bed using scissors and pressed against the bleeding tissue to visibly moisten the foam with blood from the wound. The BTM was secured to the wound bed using either surgical staples or sutures to facilitate apposition of the product with the wound bed (Figure 1).
Intraoperatively, the BTM was further bolstered into the wound bed utilising polyurethane foam dressing (Granufoam™, 3M/KCI San Antonio, USA) and secured in place with clear polyurethane adhesive drape and Negative Pressure Wound Therapy (NPWT) applied (VAC™, 3M/KCI San Antonio, TX, USA) with a continuous pressure of −75 mmHg for an initial 5–7 days.
After initial post-surgery review (5–7 days), NPWT was reapplied for a further 7 days as per the above method, to further bolster the BTM into the wound bed and manage wound exudate. There was no contact of the Granufoam™ with the wound bed—it sits atop the BTM sealing membraned for all NPWT applications.
Post the initial 14 days of NPWT, management of the in situ BTM continued using topical antimicrobial wound dressings (povidone iodine and paraffin-impregnated gauze) bolstered with sterile gauze and a sterile composite absorbent dressing, secured with hypoallergenic fixation tape or crepe bandage. Wound dressings were replaced a minimum of 3 times a week, more frequently in the event of high volumes of wound exudate.
The sealing membrane and surrounding skin were sprayed with a topical hypochlorous acid (Microdacyn® TeArai Biofarma, Herne Bay, Aukland, New Zealand) post-removal of previous dressing, at each dressing change, to reduce risk of infection.
Delamination of the BTM was performed once the sealing membrane layer could be easily separated from the underlying integrated tissue. Securing medium (staples or sutures) was left in situ until day of delamination.
Post-BTM delamination management was facilitated through conventional wound management practice, utilising principles of wound bed preparation [9], infection prophylaxis [10] and biomechanical offloading [11]. Assisted wound closure through split thickness skin grafts is not typically employed for diabetic foot ulcers in our surgical unit due to higher risk of post-operative complications, delayed healing times and additional exposure to anaesthetic [5,12].
Patients received a collaborative mixture of community, podiatric and vascular surgery outpatient follow-up, with a minimum of monthly attendance to a multidisciplinary vascular surgery outpatient service.
## 2.5. Safety
Patients were monitored for adverse events related to application of BTM.
## 2.6. Data Collection
Demographics, including patient age and sex, were obtained from the medical record. Pre-procedural HbA1C was also collected.
## 2.7. Primary Outcome Data
Wound healing outcomes were observed at 12 months post the nominated inclusion period (December 2019 through October 2021).
Cases where complete wound healing was not observed were classified as chronic wounds (not healed).
## 2.8. Secondary Outcome Data
Time (days) to complete wound healing was calculated using the difference between date of BTM application and documented date of complete epithelialisation with no exudate, taken from the follow-up visit date where complete epithelialisation was observed.
Those who underwent amputation post-application of BTM were stratified into minor and major amputations, defined as per the International Working Group of the Diabetic Foot (IWGDF) ‘definitions and criteria for diabetic foot disease’ document [13].
Data concerning wound infection pre- and post-BTM application were collected via medical record documentation for the admission where BTM application occurred. For this study, infection was classified using the Society for Vascular Surgery (SVS) adaptation of the Infectious Diseases Society of America (IDSA) and IWGDF Guidelines on the diagnosis and treatment of foot infection in persons with diabetes [10,14]. All confirmed wound infections were systemically treated with appropriate antibiotic regime and the wound determined clinically free from infection by the treating clinician, prior to BTM application.
Pre-BTM application toe pressures were obtained post-revascularisation procedures and prior to BTM application. A toe pressure >50 mmHg was established as a predictor of wound healing [15]; however, this did not serve as a cut-off for determining application of BTM but helped to inform ischaemia severity.
## 2.9. Data Analysis
Continuous data were reported as mean (SD) or median (IQR) according to normality and categorical data as n (%). Differences within groups for continuous data were tested using paired samples t-test. Differences between groups for categorical data were tested using χ2 test. A statistical significance level of $p \leq 0.05$ was utilised. IBM SPSS was utilised for statistical testing (IBM Corp. Released 2016. IBM SPSS Statistics for Windows, Version 24.0. IBM Corp, Armonk, NY, USA).
## 2.10. Predicted Amputation Risk in the Observed Cohort
To illustrate the severity of the wounds treated with BTM, the predicted 12-month risk of amputation, prior to BTM application, was determined using the validated Wound, Ischaemia and foot Infection (WIfI) classification system [14]. The score was calculated with wound severity and infection severity grading based on pre-procedural clinical photography, pre-procedural perfusion tests (after revascularisation) (i.e., toe pressures), pre-procedural signs of infection as per IDSA guidelines and clinical documentation. Patient lower limb 12-month amputation risks were stratified into Very Low (stage 1), Low (stage 2), Moderate (stage 3) or High (stage 4) categories, as per the WIfI classification system [14].
The assigned WIfI classification grading was employed to compare wound healing outcomes and 12-month amputation rates of BTM-treated patients with expected rates of amputation based on the widely validated global WIfI data in a recently published meta-analysis [16]. WIfI classification was also used to compare outcomes between wounds originating from either surgical amputation or pre-existing chronic wounds, treated with BTM.
## 3. Results
During the nominated study period (December 2019 to October 2021), we observed a total of 25 BTM applications to 23 wounds amongst 22 patients treated for diabetic foot wounds. Out of the 22 cases, 4 underwent more than one application of BTM—3 who underwent repeat application to their originally treated wound bed and 1 who had a new wound on the opposite foot that was also treated with BTM (Table 1).
The majority was male ($$n = 19$$, $86\%$), with a mean age of 67.3 years (SD 10.2) (Table 1).
## 3.1. Wound Healing and Amputation Outcomes
A total of 15 ($65.3\%$) of 23 wounds progressed to complete wound healing post-BTM application (Table 2). Of the remaining eight non-healed wounds, three retained a chronic wound, three required minor amputation at the site of BTM application and two required major amputation of the BTM-treated limb, both secondary to wound deterioration and significant calcaneal bone loss related to refractory osteomyelitis (Table 2).
Of the three patients with a chronic wound, two experienced a greater than $60\%$ reduction in wound surface area, observed during the follow-up period. The remaining patient passed away due to cancer-related illness prior to complete wound closure.
Of the three patients who underwent minor amputation of the BTM-treated area, two progressed to complete wound healing and one retained a chronic wound.
## 3.2. Time to Complete Wound Healing
Of the 15 wounds that achieved complete wound healing, average time to complete wound healing was 158 days (median 126, IQR 81).
## 3.3. Pre- and Post-BTM Application Wound Infection
Out of the 23 wounds, 12 ($52.1\%$) were classified as hosting signs of infection, ranging from mild through to severe, within 14 days prior to BTM application. All 12 wounds received treatment for wound infection prior to BTM application. Of these, six progressed to complete wound healing, three progressed to minor amputation, two to major amputation and two patients retained a chronic wound at the end of the observation period.
A total of three ($13\%$) wounds developed a wound infection post-BTM application. Two of these patients were treated for pre-existing infection, prior to BTM application—one progressed to major amputation and the other retained a chronic wound. The remaining patient progressed to complete wound healing within 182 days post-BTM application.
## 3.4. Pre-BTM Application Toe Pressures and Wound Healing Outcomes
Of the 13 patients with pre-BTM application toe pressures >50 mmHg, complete wound healing was observed in 11 ($84\%$) patients, compared with the pre-BTM cohort with toe pressures of <50 mmHg (despite maximal revascularisation), where a lower proportion of patients (4 out of 10) completely healed their wounds.
There was a total of seven patients treated with BTM with severe refractory ischaemia post-maximal revascularisation (toe pressures < 30 mmHg). Of these seven patients, three ($43\%$) progressed to complete wound healing, two ($29\%$) retained chronic wounds and one ($14\%$) progressed to minor amputation and one ($14\%$) to major amputation within the observed period.
## 3.5. WIfI Stratification of 12-Month Amputation Risk
All 23 wounded limbs in 22 patients were successfully staged using the WIfI 12-month amputation risk. In total, 18 ($78\%$) wounded limbs were scored a stage 4 (high) risk of amputation, 4 ($17\%$) were assigned stage 3 (moderate) and 1 ($5\%$) assigned a stage 1 (very low) score (Table 2). There were no patients assigned WIfI stage 2.
## 3.6. Post-BTM Application Wound Healing Outcomes and WIfI Stratification
Analysis of the wound healing outcomes in the 18 wounds assigned WIfI stage 4 observed complete wound healing in $61.1\%$ ($$n = 11$$), with $11.1\%$ ($$n = 2$$) retaining a chronic wound, $16.7\%$ ($$n = 3$$) requiring minor amputation and $11.1\%$ ($$n = 2$$) progressing to major amputation (Table 2).
There were four ($17\%$) wounds stratified to WIfI stage 3. Complete wound healing was observed in $75\%$ ($$n = 3$$) of this group, with the remaining wounded foot ($25\%$) retaining a chronic wound. There were no amputations in this group (Table 2).
The single WIfI stage 1 wounded foot progressed to complete wound healing (Table 2).
Stratification of time to complete wound healing to WIfI stage revealed averages of 166 days (SD 92.6) for WIfI stage 4 and 141 days (SD 25.5) for WIfI stage 3 patients. The single WIfI stage 1 patient healed their wound in 142 days (Table 1).
## 3.7. Surgical Amputation and Chronic Wound Debridement Outcomes Stratified by WIfI Stage
The majority ($69.5\%$) of wounds treated with BTM were existing chronic wounds ($$n = 16$$), with the remaining portion of wounds originating from surgical amputations ($$n = 7$$) (Table 3). All WIfI stages were represented in the chronic wound cohort, with the majority stage 4 ($$n = 11$$) followed by stage 3 ($$n = 4$$) and stage 1 ($$n = 1$$), respectively. Major amputation was undertaken in one ($6\%$) and minor amputation in three ($19\%$) of the sixteen patients in the chronic wound cohort, and all were classified WIfI stage 4 (Table 3). Wound healing was observed in $100\%$ of WIfI stage 1 cases, and a majority of both WIfI stage 3 ($75\%$) and stage 4 ($63.3\%$) BTM-treated chronic wounds. Of the chronic wound patients treated with BTM, only one patient, classified as WIfI stage 3, retained an unhealed chronic wound at the 12-month observation period (Table 3).
All patients treated with BTM following surgical minor amputation were classified as WIfI stage 4, four ($57\%$) were observed to progress to complete wound healing, two ($29\%$) retained chronic wounds and only one ($14\%$) required major amputation (Table 3).
## 3.8. Pre-BTM Application Glycosylated Haemoglobin
The average pre-procedural HbA1C of the 22-patient cohort was $9.0\%$ (Median $8.5\%$, IQR $2.45\%$). Mean HbA1c values for patients with healed wounds ($$n = 15$$) were $9.5\%$ (SD 2.5) compared with non-healed wounds ($$n = 8$$), which was $8.1\%$ (SD 1.4). No significant difference in HbA1C was observed between the healed and non-healed groups ($$p \leq 0.17$$) (Table 1).
## 3.9. Safety
There were no adverse events related to BTM application reported during the observation period.
## 4. Discussion
Ulceration in the setting of diabetes-related foot disease (neuropathy, structural deformity and peripheral arterial disease) has been established as a major contributing factor to lower limb amputation [4].
A wide variety of studies exist detailing the use of various augmentative wound healing technologies for the treatment of diabetic foot ulceration, including dermal matrices (exogenous and human-derived), allografts, xenografts and autologous grafts [5]. Reported outcomes from these studies vary, with ulcer healing rates spanning from $30\%$ to as high as $85\%$ in their experimentally treated groups; however, many of these studies exclude patients with severe lower limb peripheral arterial disease, tissue or bone infection or exposed underlying structures, such as tendon or bone [17,18,19,20,21,22,23,24]. With a majority of WIfI stage 4 patients in our observational cohort, our use of BTM was employed to treat moderate to severe diabetic foot ulcerations and should be taken into account when evaluating the reported effectiveness of this technology. Despite the high severity, we observed overall healing rates of $65.3\%$ and 12-month major amputation rates of $11.1\%$ in our WIfI stage 4 cohort, comparable with those previously reported by Mathioudakis, Hicks [25], who, in their single-centre prospective observational study of diabetic foot wounds treated in a multidisciplinary setting, observed a $70\%$ wound healing rate and $6\%$ 12-month major amputation rate in their WIfI Stage 4 cohort. This comparison should be made in the context that under half ($44\%$) of those WIfI stage 4 patients reported by Mathioudakis, Hicks [25], required surgical wound coverage (xenograft/allograft application), which is arguably a more accurately comparable cohort—however, outcome data for this subgroup were not reported. Further comparison of BTM efficacy can be drawn with our observed mean time to complete wound healing for WIfI stage 4 (166 days, SD 92) and stage 3 (141 days, SD 25), which were favourable when compared with previously published, single-centre prospective observational study data by Mathioudakis, Hicks [25] (stage 4, 190 days, and stage 3, 125 days), and Zhan, Branco [26] (stage 4, 264 days, and stage 3, 163 days).
When we consider that reported systematic review data suggest 12-month major-amputation risk of WIfI stage 3 and 4 patients to be $11\%$ and $38\%$ and we have shown amputation rates to be $0\%$ and $11.1\%$, respectively, this highlights the potential future role that BTM has to play in the paradigm of such patients who may otherwise face amputation [16].
The higher rate of wound healing observed in the patient cohort with toe pressures >50 mmHg aligns with previously reported experiences [15]; however, this should not detract from the high severity of wounds treated with BTM, represented in this subgroup (Table 1), with $92\%$ of those with a toe pressure >50 mmHg containing wounds scored as a WIfI wound category two or greater (extensive/deep ulcer, with exposed bone joint or tendon) (Table 1). Whilst severe refractory ischaemia (toe pressures < 30 mmHg post-maximal revascularisation) was prevalent in only $30\%$ ($$n = 7$$) of the study cohort, with a majority ($$n = 6$$) of these cases hosting severe wounds (WIfI wound severity of 3), 12-month amputation-free survival was $70\%$ ($$n = 5$$), suggesting BTM offers some capacity to facilitate amputation prevention in the setting of ischaemia not amendable to further revascularisation. These data highlight that the WIfI classification of our observed cohort was predominantly driven by high wound severity and, therefore, retain a high risk of wound healing failure, irrespective of perfusion status, reinforcing the positive context of our patient outcomes for which BTM offered a non-autologous off-the-shelf reconstruction solution.
Adding further support to the value of BTM is the fact that it is dry storage, non-refrigerated, low cost and does not result in donor site creation, which overcomes many of the current criticisms of skin grafts and tissue replacements, including high cost in the context of operating theatre time, creation of a second wound in a patient with established wound healing difficulties and variance in availability (in context of allografts/exografts) [5].
The reported rates of surgical site infection post-BTM application, while seemingly high, are in keeping with reported experiences of higher-than-normal infection rates in diabetic foot and ankle surgery (reported as $7.7\%$ to $13.6\%$) [27]. Our observed cohort also had a considerably high number of pre-existing infections diagnosed prior to BTM application (Table 1). Despite this, our amputation rates were considerably lower than those reported in the published systematic review data [16].
It is also acknowledged that all patients who progressed to amputation, post-BTM application, were amongst those treated for infection pre-application of BTM. Although the sample size does not allow for multivariate analysis in this cohort, infection source control through aggressive debridement and antibiotics is, therefore, recommended prior to BTM application.
While WIfI provides a vehicle for describing neuroischaemic disease burden, glycaemic control is also a key influence in wound healing. Pre-procedure HbA1C failed to establish a significant link between those wounds that healed and those that failed to heal within the follow-up time frames. This crudely suggests an equal distribution of diabetes disease severity amongst the observed population—however, this conclusion could have been further strengthened through the gathering of additional data, such as type of blood-glucose-regulating medication, as additional indicators of diabetic disease severity. While our findings do not align with emerging evidence associating elevated HbA1C with increased amputation risk and decreased rates of wound healing, this is more likely a reflection of the low case volume and/or other comorbid factors not yet identified [28,29].
This prospective study presents encouraging results, with respect to limb salvage and wound healing, for patients with moderate to severe diabetic foot ulceration treated with BTM. This extent of diabetic foot ulceration being successfully treated with dermal substitutes is scarcely reported in the literature and reinforces a major role for BTM in this cohort. Furthermore, our observational study presents a real-world pragmatic experience of the use of BTM in treating very advanced diabetic foot disease and overcomes the criticisms of many such papers who do not report on such advanced disease [16,17,22,23,24].
It is noted that one limitation of BTM application relates to the need for apposition of the foam with all surfaces of the wound bed and, therefore, some wound geographies, such as deep narrow cavities, exclude the use of BTM in its current format.
While early experience with BTM in human studies suggests that the product facilitates neovascularisation into the foam scaffold to allow for integration and proliferation of a neodermis, including coverage of exposed deeper tissue structures [7,8], its specific action in diabetic foot disease is not established and requires further investigation. Our early experience reinforces the ability for BTM to provide coverage of deep tissue structures in complex diabetic foot wounds in whom the alternative option may only be major limb amputation.
Direction for future adaptation of this technology would be best informed through linking wound healing outcomes with tissue-level laboratory-based investigation of the impact of BTM on the cellular milieu of diabetic foot ulcers and our institution is currently undertaking this work.
## 5. Conclusions
The results from this observational study serve as encouraging early data for the use of BTM as a safe and accessible treatment of neuroischaemic diabetic foot wounds, including those that are moderate or severe. While larger-scale data are required, BTM may represent a promising new addition to the armamentarium of clinicians, who strive to achieve limb salvage in this complex cohort of patients.
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|
---
title: Tissue and Serum Biomarkers in Degenerative Aortic Stenosis-Insights into Pathogenesis,
Prevention and Therapy
authors:
- Alkistis Kapelouzou
- Styliani Geronikolou
- Irene Lidoriki
- Christos Kontogiannis
- Loukas Kaklamanis
- Loukas Tsourelis
- Dennis V. Cokkinos
journal: Biology
year: 2023
pmcid: PMC10045285
doi: 10.3390/biology12030347
license: CC BY 4.0
---
# Tissue and Serum Biomarkers in Degenerative Aortic Stenosis-Insights into Pathogenesis, Prevention and Therapy
## Abstract
### Simple Summary
We found higher levels of six biomarkers significantly involved in cardiovascular pathology, i.e., irisin, periostin, osteoglycin, interleukin 18, high mobility group box 1 and proprotein convertase subtilisin/kexin type 9 in the serum at the protein level, and in the tissue at both the protein and mRNA levels of patients with AS ($$n = 60$$). Higher levels of all factors were found in DAS patients’ serum than in normal C (Ν = 22). All biomarkers were seen in the aortic valve cusps with DAS, but no trace of PCR mRNA was found in the five transplantation valves.
### Abstract
Background and Aim. Degenerative Aortic Stenosis (DAS) is a common disease that causes substantial morbidity and mortality worldwide, especially in the older population. Our aim was to further investigate novel serum and tissue biomarkers to elucidate biological processes involved in this entity. Material and Methods. We evaluated the expression of six biomarkers significantly involved in cardiovascular pathology, i.e., irisin, periostin, osteoglycin, interleukin 18, high mobility group box 1 and proprotein convertase subtilisin/kexin type 9 in the serum at the protein level, and in the tissue at both the protein and mRNA levels of patients with AS ($$n = 60$$). Five normal valves obtained after transplantation from hearts of patients with idiopathic dilated cardiomyopathy were also studied. Serum measurements were also performed in 22 individuals without valvular disease who served as controls (C). Results. Higher levels of all factors were found in DAS patients’ serum than in normal C. IHC and PCR mRNA tissue analysis showed the presence of all biomarkers in the aortic valve cusps with DAS, but no trace of PCR mRNA was found in the five transplantation valves. Moreover, periostin serum levels correlated significantly with IHC and mRNA tissue levels in AS patients. Conclusion. We showed that six widely prevalent biomarkers affecting the atherosclerotic process were also involved in DAS, suggesting a strong osteogenic and pro-inflammatory profile, indicating that aortic valve calcification is a multifactorial biological process.
## 1. Introduction
The interest in degenerative aortic stenosis (DAS) remains unabated, since it is an increasingly frequent cause of cardiac morbidity and mortality [1,2]. In a U.S. population study, its prevalence was $2.8\%$ for peoples aged > 75 years [3]. It is correlated to atherosclerotic vascular disease, with many factors being prevalent in both conditions [1,2]. However, Ortlepp et al. [ 4] point out, that the predictive power of risk factors is not equal for the two entities. It is currently being accepted that DAS is not a passive process, but involves many mechanisms, such as lipoprotein profile derangement, oxidation, inflammation and valvular cell apoptosis [5,6,7]. All these are compounded by hemodynamic factors, since the initial valve sclerosis causes flow turbulence and nonlinear flow promoting further progress of the sclerosis/calcification process [1,6].
Livia Passos et al. [ 8] argue that cardiovascular calcification is an inflammatory disease, through crosstalk between innate and adaptive immune cell components.
A great number of biomarkers has been studied in DAS.
The purpose of our study is to identify additional serum and tissue biomarkers involved in patients with DAS, and also to investigate the correlation between their tissue and serum levels. Since 2015 we have been investigating tissue and serum biomarkers in this entity. We have shown that patients with DAS express more pro-inflammatory, calcification, fibrosis, proliferation and apoptosis biomarkers. We have also shown that Toll-like receptors and interleukin-37 are differentially expressed in aortic compared to mitral valves, indicating a higher pro-calcific and pro-inflammatory process in the aortic valve [7], in addition to the hemodynamic factors and the turbulent aortic flow.
Trying to obtain further insight in the calcification process we measured six biomarkers in the tissue of stenotic aortic valves excised at surgery for aortic valve replacement and compared them to normal aortic valves obtained at cardiac transplantation.
These six biomarkers were also measured in the serum of patients and controls without any cardiovascular disease; the reasons for their inclusion are explained below.
## 1.1. Irisin Levels
The myokine irisin, which is cleaved from the plasma membrane FNDC5, is more highly expressed in cardiac muscle than in skeletal [9]. It is also highly elevated in patients with heart failure and preserved ejection fraction (EF) more than in those with reduced EF; in the former, it correlated with total antioxidant capacity [10]. Irisin is increased in acute heart failure and is an independent factor for 1 year all-cause mortality [11]. However, it is decreased in myocardial infarction, both clinical and experimental [12,13]. It is correlated negatively to coronary artery disease severity [14]. Patients in the higher SYNTAX score levels were older and had lower irisin levels than younger ones. However, it has also been reported to be cardioprotective [15].
Irisin has been found to promote osteoblast proliferation and differentiation via the MAP kinase pathways by Qiao et al. [ 16] who postulated its possible use in osteopenia. It increases sclerostin expression in osteocytes to induce bone resorption. It mediates this effect via αV integrin receptors [17]. In our previous study we have found sclerostin to be increased in DAS [5]. Irisin administration has been proposed for treatment of osteoporosis by Colaioanni et al. [ 18].
## 1.2. Periostin
Hakuno et al. [ 19] found PN to be increased in degenerative or rheumatically affected heart valves. The same authors also found that in wild type mice a high fat diet markedly increased its expression in both AV and MV together with the fibrotic markers MMP2 and MMP13. It is associated with myocardial fibrosis in human heart failure [20]. It was increased together with MMP2 activity. It is increased in hypertrophic mice hearts together with interstitial fibrosis [21]. It decreases together with a reduction in myocardial fibrosis in hearts unloaded both clinically (LVAD) and experimentally in mice (aortic arch de-banding) [22]. It is also a potential marker biomarker for coronary artery disease with acute heart failure [23]. Furthermore patients with CAD had higher levels than controls at similar ages (around 63 y).
## 1.3. Osteoglycin
The same pattern for PN was found for OGN, which is implicated in matrix homeostasis. It modulates fibrosis and inflammation. Deckx et al. [ 24] found that its levels were higher in patients with AS with less severe myocardial fibrosis, in whom it was negatively correlated with collagen content in the myocardium, but they did not measure it in the valves. Van Aelst et al. [ 25] found that it prevents cardiac dilation and dysfunction after myocardial infarction through infarct collagen strengthening. Zuo et al. [ 26] have found that osteoglycin attenuates cardiac fibrosis; it could be an antifibrotic, but is also pro-calcific by suppressing myofibroblast proliferation. Circulating osteoglycin and NGAL/MMP9 complex concentrations predict 1 y MACE after coronary arteriography [27]. It was statistically slightly higher in CAD patients aged 70 vs. 65 y [28] Tanaka et al. have stated that it is a humoral bone anabolic factor [28]
## 1.4. Interleukin 18
IL-18 is a dominant pro-inflammatory cytokine. In the heart, it is produced by infiltrating neutrophils, resident macrophages, endothelial cells, smooth muscle cells and cardiomyocytes [29]. In the non-rheumatic aortic valve, increased tissue levels have been found as compared to controls [30], and are correlated to advanced clinical severity. It promotes myofibroblast activation of porcine valvular interstitial cells [31]. Interestingly, the administration of increased doses of IL-18 upregulated the expression of osteopontin [32] which we have found to be pro-osteogenic [5]. It is prospectively and independently associated with CVD risk [33] in patients of similar ages (52.5 y).
## 1.5. HMGB1
The high mobility group box 1 (HMGB1) which is also a pro-inflammatory factor has been implicated in the pathogenesis of DAS. It has been found to be increased in the calcific regions; the same was found in regard to TLR by Shen et al. [ 34], who postulate that TLR4 may function as an essential mediator of HMGB1-induced calcification and in the activation of p38 and NFkB. Wang et al. [ 35] found that HMGB1 protein and TLR4 are upregulated in vitro by HMGB1 in aortic valvular interstitial cells. We have described in detail the role of TLRs in aortic and mitral valve stenosis [7]. Its increase in the serum is related to severity of coronary artery stenosis [36].
## 1.6. PCSK9
Recent experimental studies have demonstrated that PCSK9 might directly promote inflammation, apoptotic cell death and endothelial dysfunction in the atherosclerotic process and plaque formation [37] and is associated with the severity of CAD [38] in hypercholesterolemia, cardiovascular inflammation and diabetes [39,40,41].
Wang et al. [ 42] and Poggio et al. [ 43] found lower calcium content in aortic valves of PCSK9−/− mice than wild type animals. The former were resistant to production of aortic calcification with two pro-calcification diets (β-glycero–phosphate and ascorbic acid). The same authors found that human calcified aortic valves expressed higher PCSK9 than non-calcified ones. Interestingly, Salaun et al. [ 44] found that elevated plasma levels of PCSK9 were a risk factor for hemodynamic deterioration of surgically implanted bioprosthetic aortic valves. The same held true for LP-PLA2 and HoMA. PCSK9, apart from its action on LDL receptors, can promote apoptotic cell death of neurons [45].
## 2.1. Ethics Statement
This study was approved by the Ethics Committees of the Onassis Cardiac Surgery Center (OCSC) and conformed to the principles outlined in the Declaration of Helsinki. Written informed consent was obtained from all patients.
## 2.2. Study Population
The present, prospective, open-label study, extends the results of our previously published studies [5,7]. The age of the 60 DAS patients was 66.1 ± 12.5 years, $50\%$ were women. Echocardiography was obtained in all patients. Aortic valve area was 0.9 to 0.5 cm [2]. Patients were taking antihypertensive ($75\%$) and antilipidemic ($80\%$) drugs during the last two years. However, none had significant coronary artery disease necessitating concomitant aortocoronary bypass surgery. Patients with rheumatic cardiac disease, bicuspid aortic valve or connective tissue disorders were excluded. The excised valve cusps were harvested during surgery. Blood was collected from AS patients before valve surgery and from twenty-two [22] healthy subjects without any chronic cardiovascular or metabolic disease, and not receiving any long-term medication, who served as healthy control group (C), for comparison of serum biomarkers; mean age was 34.4 ± 7.5 years, $50\%$ were women. None were steadily employing radioactive drugs.
We also obtained 5 aortic valves from patients undergoing cardiac transplantation, 3 men and 2 women (min age 48.4), because of terminal heart failure due to idiopathic dilated cardiomyopathy, who did not show any sclerotic or calcific aortic valve changes.
## 2.3. Blood Analysis
Blood samples were collected by venipuncture after subjects were fasted overnight. Serum was collected and stored at −80 °C, analysis was performed in duplicate; dilution was assessed as per protocol. We used commercially available enzyme immunoassay kits for irisin (FNDC5) (EK-067-29, Phoenix Pharmaceuticals, California, CA, USA); periostin (PN) (EHPOSTN, Thermoscientific, Germany); osteoglycin (OGN) (CSB EL016314HU, Cusabio, Houston, TX, USA); IL-18 (DY318-05, R&D, Minneapolis, MN, USA); high-mobility group box 1, HMGB1 (LS-F11641, Lifespan Ltd., Seattle, DC, USA); PCSK9 (DPC900, R&D, Minneapolis, MN, USA) and quantified each protein according to the protocol of the manufacturer with an ELISA reader system (Spectramax 190; Molecular Devices, Sunnyvale, Calif, CA, USA).
## 2.4. Valve Cusp Immunohistochemistry and Quantitative Morphometrical Analysis
Aortic valve cusps were excised and one part of each valve tissue was placed in a container for immunohistochemistry (IHC) analysis at the pathology department of the OCSC and the Biomedical Research Foundation of Academy of Athens according to our previous protocol. The protocol of IHC has been described and validated in our lab [46]; FNDC-5 (PA5-62368, 5 μg/mL, Invitrogen, CA, USA); PN (PA5-82458, 5 μg/mL, Invitrogen, CA, USA); OGN (PA5-48255, 5 μg/mL, Invitrogen, CA, USA); IL-18 (PA5-79479, Invitrogen, CA, USA) HMGB1 (PA5-80691, 5 μg/mL, Invitrogen, CA, USA); PCSK9 (PA5-79789, 5 μg/mL, Invitrogen, CA, USA) were used for IHC. IHC was performed according to the manufacturer’s protocol by using the development kit (Zytochem Plus; Zytomed system, Germany). Appropriate isotype negative controls were performed at the same concentrations as the primary antibodies. Microscopic investigation of the IHC sections was performed with stereology upright Leica DMRA2 camera, and were analyzed by stereo-investigator 10 program (version 10.1, MBF Bioscience, Microbrightfield. Inc., Willinston, VT, USA) in order to quantify the extent of the tissue covered by each antibody.
## 2.5. RNA Isolation and qRT PCR Analysis
Total RNA was extracted using Trizol reagent (Sigma, Saint Louis, MO, USA) according to the manufacturer’s instructions [46]. The RNA quality was assessed with agarose gel electrophoresis and quantitated spectrophotometrically. cDNA was synthesized by RT (MMLV, reverse transcriptase; Sigma), and real-time quantitative polymerase chain reaction was performed by using SYBR Green (Invitrogen, Life Technologies, New York, NY, USA). The primers synthesized by Origine (Herford, Germany) were used as documented in Table 1. The thermal cycling protocol was performed according to our lab protocol [5,7].
We also measured the 6 biomarkers already discussed in the 5 aortic valves explanted from patients who had undergone cardiac transplantation by RNA isolation and qRT analysis.
All had idiopathic dilated cardiomyopathy without coronary artery disease at arteriography: 2 were women aged 28 and 56 years, and were 3 men aged 48, 54 and 58 years.
## 2.6. Statistical Analysis
Shapiro–Wilks test for normality showed that none of the variables had normal distribution. Thus, Univariate and Multivariate analysis, one-way ANOVA or t-test were inappropriate tests for the analysis. We performed non-parametric tests instead. The Mann–Whitney test for evaluating the patients versus control serum biomarkers showed significant differences between all serum markers. All correlations were performed with non-parametric Spearman’s rho. Alpha was set at 0.05. Statistics were performed with SPSS28.
## 3.1. Serum Findings
(a) The non-parametric Mann–Whitney test showed significant differences in all serum biomarkers between patients and the control group. ( Figure 1, Table 2).
(b) Positive correlations were found in HMGB1 with PCSK9 and PN vs. PSCK9. Negative correlations were observed in OGN with PN and IL-18.
Any other correlation was found insignificant ($p \leq 0.05$).
(c) Positive correlations were found in HMGB1 with PCSK9 and PN with PSCK9. Negative correlations were observed in OGN with PN and IL-18.
(d) Any other correlation was found insignificant ($p \leq 0.05$).
## 3.2. Tissue vs. Serum
(a) Of all biomarkers found significantly correlated only PN tissue levels correlate with the same marker’s levels detected in serum.
(b) For all other tissue markers described in Table 3, the correlations were found in non-identical markers: (positive) tissue HMGB1 with serum OGN, tissue PCSK9 with serum OGN, (negative) tissue IL-18 with serum PCSK9 and OGN, tissue HMGB1 with serum IL-18, tissue PCSK9 with serum HMGB1 and IL-18. ( Table 3) (c) The insignificant correlations were not included in Table 3.
## 3.3. Immunohistochemistry Biomarkers in Aortic Valve Cusps
Immunohistochemistry staining was performed (Figure 2). Biomarker tissue presence was confirmed in all AVC samples.
## 3.4. mRNA Expression of Inflammation and Calcification Biomarkers in AS Patients
Tissue mRNA levels of all biomarkers was present in AVC (Figure 3).
The highest expression was found for osteoglycin, while FNDC5 was only mildly elevated None of the valves from patients with cardiac transplantation had any expression of mRNA of the above biomarkers.
The five valves from the cardiac transplantation hearts showed no expression at all.
## 3.5. Tissue Biomarkers Correlations
We found significant correlations between most tissue biomarkers.
## 4. Discussion
In this study we continue the investigation of the calcification process through the novel body of biomarkers examined in DAS [5,7]. We investigated six factors, both in serum and valve tissue, of which some have been very scantily studied. All of them have also been involved in CAD. Thus, we did not consider it practical to add a comparison Group with CAD only and without DAS.
We obtained valves from five patients undergoing cardiac transplantation, which did not show any expression of RNA of these biomarkers. With regard to the serum biomarkers, it must be realized that the control individuals were younger. However, this difference reflects a real-life situation, that individuals develop DAS later in life. It must be realized that DAS and CAD co-exist in around $50\%$ of patients, as presented by Ortlep et al. [ 4]. However, none of our patients needed any concomitant surgery for CAD, thus excluding significant disease.
Our study may offer another biomarker, periostin, which may in the future provide prognostic information. Up to now, NT-proBNP [47] and BNP [48] have provided data with regard to intervention time because they reflect myocardial stress which would prompt information. A valve-specific marker such as periostin may provide means of following the course of sclerosis to stress.
Again, we must stress that we did not perform a population study so as to assess the importance of these biomarkers for predicting the presence of DAS.
Νew technologies to measure early calcification and inflammation are available. Dweck et al. have provided data from position emission tomography in vivo [49] in patents with DAS.
It must be noted that we did not find any microscopic evidence of changes in the normal aortic valves obtained at cardiac transplantation, nor by mRNA PCR, which is more reliable than immunohistochemistry [50].
Our findings confirm the association of PCSK9 with valve tissue calcification, and supports the postulations that PCSK9 inhibitors or drugs preventing its production by the liver could be a consideration for prevention of the course towards AS once aortic valve sclerosis has been diagnosed. In fact, in the FOURIER study, PCSK9 inhibition was associated with a lower hazard of new or worsening stenosis AS [51]. This is especially relevant since initial trials with statins have not been successful in preventing AS [52,53]. While there was some promise in a rosuvastatin trial with echo measurements [54], this was not validated in the ASTRONOMER TRIAL [55]. A reason might be that statins do lower cholesterol but increase PCSK9 levels [56]. Thus, well-controlled therapeutic trials with PCSK9 inhibitors are warranted.
In the coronary arteries statins actually promote calcification, while decreasing atherosclerotic plaque burden and fibrosis [57]. This action may explain their lack of influence on the progression of aortic calcification. We found that the PCSK9 receptor is strongly expressed in the aortic valve both by IHC and mRNA analysis and increased in the serum as compared to controls. This supports the population study of Perrot et al. [ 58] who found that AS was less frequent in carriers of the PCSK9 R461 loss-of-function variants. They also found increased expression of PCSK9 in calcified human valves.
The high interrelation between PCSK9 and aortic valve calcification has already been stressed [59]. Additionally, this family of drugs antagonizes apoptosis; [45,56] endothelial apoptosis [60] is found in endothelial cells in DAS.
PCSK9 inhibitors alleviate oxidation and inflammation [61].
Another candidate drug family would be SGLT2 inhibitors. Interestingly, they have been found to attenuate the secretion of IL1β and IL-18 [59] by repressing the HMGB1-TLR4 receptor axis [62]. They also antagonize many inflammatory interleukins [63,64,65]. They are also considered powerful antioxidants [66]. Possibly, if these families of drugs for PCSK9 and SGLT2 are given together they could exert a synergistic effect.
Another practical aspect of our finding is if serum levels could predict or follow the course of aortic valve sclerosis towards actual stenosis, by a set of easily measured biomarkers. This held true for periostin in our patients.
We tried to address the mechanisms of DAS. The fact that none of these biomarkers are found in the tissue of normal aortic valves in control patients undergoing cardiac transplantation of a similar age to those with AVR suggests that this is not a problem regulated only by age. As it regards serum levels, all our control patients had much lower levels than those with DAS, which is not surprising. Furthermore, biomarkers in DAS are legion and concern all aspects of inflammation, oxidative stress, pro-calcification effects and lipid metabolism.
It should also be stressed that they all have been associated with CAD as well, since approximately half of the patients with DAS have CVD as well. As already stated, coronary artery disease is strongly associated with DAS in many studies considering the age of our patients; its prevalence could be estimated between $41\%$ and $51\%$ [4,67].
Indeed, non-obstructive aortic valve calcification has become a window into significant coronary artery disease [68].
However, since as already stated, many biomarkers are being studied, we did not address any other correlations in the tissue which would create confusion, since it would be difficult to find practical explanations and promote far-fetched postulation.
We believe that our findings add impetus to the efforts towards preventing the progression of aortic sclerosis to frank DAS by drugs affecting causative factors, such as hyperlipidemia, inflammation, oxidation and endothelial apoptosis. This is a realistic goal in parallel to CAD, where, although interventional and surgical therapies have attained excellent results, efforts at prevention continue unabated.
## 5. Study Limitations
The lower serum levels of most markers in our controls may be because they are of younger age and there is an absence of comorbidities. However, we do not consider that we have a new diagnostic and pragmatic biomarker, but we have investigated the pathobiology of this entity.
## 6. Conclusions
Patients with stenotic aortic valves express higher pro-inflammatory, calcification, fibrosis, proliferation and apoptosis-expressing markers in their serum than normal controls. They are all strongly expressed in calcified, but not normal, valves. We found that PN concentration is an important finding that can lead us to a consideration of the prognostic role of serum biomarkers in the course of this pathological process. Our findings point toward a higher pro-calcification and pro-inflammatory profile in DAS patients. We believe that our findings provide interesting data for the diagnosis and prevention of aortic sclerosis, and possibly treatment of mild AS.
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|
---
title: Effect of Quercetin Nanoparticles on Hepatic and Intestinal Enzymes and Stress-Related
Genes in Nile Tilapia Fish Exposed to Silver Nanoparticles
authors:
- Mayada R. Farag
- Haitham G. Abo-Al-Ela
- Mahmoud Alagawany
- Mahmoud M. Azzam
- Mohamed T. El-Saadony
- Stefano Rea
- Alessandro Di Cerbo
- Doaa S. Nouh
journal: Biomedicines
year: 2023
pmcid: PMC10045288
doi: 10.3390/biomedicines11030663
license: CC BY 4.0
---
# Effect of Quercetin Nanoparticles on Hepatic and Intestinal Enzymes and Stress-Related Genes in Nile Tilapia Fish Exposed to Silver Nanoparticles
## Abstract
Recently, nanotechnology has become an important research field involved in the improvement of animals’ productivity, including aquaculture. In this field, silver nanoparticles (AgNPs) have gained interest as antibacterial, antiviral, and antifungal agents. On the other hand, their extensive use in other fields increased natural water pollution causing hazardous effects on aquatic organisms. Quercetin is a natural polyphenolic compound of many plants and vegetables, and it acts as a potent antioxidant and therapeutic agent in biological systems. The current study investigated the potential mitigative effect of quercetin nanoparticles (QNPs) against AgNPs-induced toxicity in *Nile tilapia* via investigating liver function markers, hepatic antioxidant status, apoptosis, and bioaccumulation of silver residues in hepatic tissue in addition to the whole-body chemical composition, hormonal assay, intestinal enzymes activity, and gut microbiota. Fish were grouped into: control fish, fish exposed to 1.98 mg L−1 AgNPs, fish that received 400 mg L−1 QNPs, and fish that received QNPs and AgNPs at the same concentrations. All groups were exposed for 60 days. The moisture and ash contents of the AgNP group were significantly higher than those of the other groups. In contrast, the crude lipid and protein decreased in the whole body. AgNPs significantly increased serum levels of ALT, AST, total cholesterol, and triglycerides and decreased glycogen and growth hormone (*** $p \leq 0.001$). The liver and intestinal enzymes’ activities were significantly inhibited (*** $p \leq 0.001$), while the oxidative damage liver enzymes, intestinal bacterial and Aeromonas counts, and Ag residues in the liver were significantly increased (*** $p \leq 0.001$, and * $p \leq 0.05$). AgNPs also significantly upregulated the expression of hepatic Hsp70, caspase3, and p53 genes (* $p \leq 0.05$). These findings indicate the oxidative and hepatotoxic effects of AgNPs. QNPs enhanced and restored physiological parameters and health status under normal conditions and after exposure to AgNPs.
## 1. Introduction
Thanks to nanotechnology, it has been possible to manage compounds with smaller dimensions (less than 100 nm) that facilitated their pickup by cells and made them effective in small doses. Recently, nanotechnology applications have increased in veterinary medicine [1,2,3] and particularly in aquaculture [4,5,6], ranging from nutrient and vaccine delivery to health management, water purification, pollution remediation, and fish breeding [4,7].
One of the highly demanded industrial materials are silver nanoparticles (AgNPs) [8]. AgNPs can be easily synthesized by different technologies, such as chemical, physical, and green or biological techniques [9]. Recently, AgNPs have been widely implemented in many industries, such as textiles, electronics, health care, and medical uses, because of their antimicrobial and antifungal activities [10,11]. AgNPs are used in aquaculture sectors for aquatic animal nutrition, disease control, and water treatments [12,13]. The extensive use of AgNPs in different industries increases the risk of environmental pollution as it may leak into natural water bodies during disposal, production, transportation, storage, and washing effect of the rain [14]. The aquatic ecosystem is highly sensitive to Ag+ ions, which dissociate from AgNPs, resulting particularly toxic [15]. The AgNPs can enter the animal bodies via endocytosis or diffusion and pass through the blood barriers affecting almost all the body organs of animals [16]. The toxicity of AgNPs has been claimed in various aquatic species, including *Daphnia magna* [17], algae [18], and fishes [19,20,21,22]. The AgNPs also altered the histological structure of the liver and gills of fish, impaired the functions of mitochondria, hampered the production of energy, induced apoptotic and oxidative damage with sublethal exposure [19,23,24,25].
Although alterations in organ histology may go unnoticed, remarkable mitochondrial changes were noticed after six months following nanoparticle exposure [26,27], suggesting long-term oxidative stress. Additionally, nanomaterials can cross the cellular membranes and, after reaching the nuclei, damage the genetic material [28], induce chromosomal aberrations and micronuclei onset in vitro and in vivo [29,30]. Exposure to AgNPs for 60 days caused high mortalities, reaching $50\%$ (LC50) at 5 mg L−1. This was accompanied by a low-growth rate and delayed metamorphosis of the tadpole, *Polypedates maculatus* [31].
Oxidative stress and immune impairment are major obstacles in aquatic farming [32,33]. Stress induces a set of physiological responses that are compensatory or adaptive to maintain normal homeostasis [33]. Under acute or chronic stress, living organisms may lose their adaptability and balance, leading to oxidative stress, increased susceptibility to diseases, and impaired growth and reproduction [34,35,36]. The fullerene and AgNPs induced disruption of the bacterial communities (pathogenic *Vibrio was* the most prevalent genus) and antioxidant capacity of the mucus of the polychaete *Laeonereis acuta* (Nereididae) [37]. Furthermore, the AgNPs altered fish immunity and performance and induced metabolic disorders, inflammation, and biochemical disturbances depending on the size and concentration of nanoparticles and the exposure duration [38,39]. Therefore, it is crucial to overcome AgNPs-associated toxicity.
AgNPs-associated toxicities can be hindered by means of the application of different natural antioxidant alternatives to inhibit oxidative damage and improve fish resistance and health.
Quercetin is a promising antioxidant polyphenolic flavonoid compound of various vegetables and fruits that can protect tissues from the oxidative damaging effect of free radicals [40]. It can effectively treat a wide array of allergies, metabolic disorders, inflammations, and cardiovascular disturbances owing to its antioxidant, antiviral, antimicrobial, antidiabetic, anticancer, and antiatherosclerotic properties [41]. In Nile tilapia, the use of quercetin as a dietary supplement could improve performance, health, antioxidant mechanisms, and immune system [42]. It can also lower serum and whole body lipids, and modulate heavy metal toxicities [42]. Moreover, it showed antibacterial activity against *Pseudomonas aeruginosa* [43], A. hydrophila in *Nile tilapia* [40], and common carp (Cyprinus carpio) [44]. Despite these effective activities, the use of quercetin is restricted because of poor bioavailability and instability. Thus, quercetin nanoparticles (QNPs) have been developed with effective characteristics and a higher bioavailability [40]. Consequently, the current study aimed at evaluating the impact of QNPs dietary supplementation, alone or combined with AgNPs aqueous exposure, on liver function markers, hepatic antioxidant status, bioaccumulation of silver residues in hepatic tissue, whole-body chemical composition, hormonal assay, intestinal enzymes’ activity, and gut microbiota. In addition, the relative mRNA levels of some stress and apoptosis-related genes were investigated in *Nile tilapia* (Oreochromis niloticus), the predominant and most commonly cultured species in many countries, especially for intensive aquaculture.
## 2.1. AgNPs and QNPs Preparation
To obtain AgNPs, the *Bacillus subtilis* MT38 isolate was inoculated in Luria Bertani broth (LB) medium and incubated at 35 °C for 24 h. Twenty milliliters of the bacterial suspension, obtained after centrifugation at 8000 rpm for 20 min, were added to 80 mL of AgNO3 (3 mM) at pH 6, 30 °C, and subjected to an agitation speed of 150 rpm for 24 h. All chemicals were purchased from Sigma-Aldrich International GmbH (St. Louis, MO, USA).
To obtain QNPs, a solution with 50 mL of ethanol containing 100 mg of quercetin was prepared. The internal organic phase solutions were quickly injected into a 150 mL external aqueous solution containing the appropriate amount of polyvinyl alcohol (PVA), and then the solutions were homogenized at 20,000 rpm for 30 min. The ethanol was evaporated using a rotary vacuum evaporator at 45 °C, and the obtained material was lyophilized using a freeze dryer.
The obtained AgNPs and QNPs were characterized using UV–Vis Spectrophotometer (UV–Vis; LaxcoTM dual-beam spectrophotometer, Lake Forest, Il, USA), dynamic light scattering (DLS, Malvern Hills, Worcestershire, UK), which is a technique used to study size and charge of suspended nanoparticles, and transmission electron microscopy (TEM, JEOL 1010, Tokyo, Japan) to measure the AgNPs size in colloidal solution. Zeta potential analysis was carried out to determine the surface charge of the nanoparticles.
## 2.2. Fish and Diet Formulations
Two hundred and forty O. niloticus (40 ± 0.45 g body weight) were purchased from a hatchery (El-Abbassa Fish Hatchery, El-Abbassa, Al-Sharkia, Egypt) and subjected to an acclimatization period of 14 days in dechlorinated tap water in glass aquaria.
Fish were fed 3 times daily a basal diet (without AgNPs or QNPs) corresponding to a $5\%$ of their biomass. The recommendations of the American Public Health Association regarding water quality parameters were followed [45]. The same rearing conditions were adjusted in all glass aquaria, including temperature, pH, ammonia, and dissolved oxygen, with a photoperiod of 10 h: 14 h (light: dark).
The QNPs (400 mg/kg) were mechanically mixed with the basal diet ingredients, pelletized, and left to dry at 25 °C for 24 h. The prepared diet was kept in the refrigerator at 4 °C until use. The composition of the basal diet was $32\%$ crude protein, $45.5\%$ fat, $42.50\%$ fiber, $73\%$ ash, and $518\%$ nitrogen-free extract.
Nile tilapias were allocated into four groups ($$n = 60$$/group), each with four replicates (fifteen fish/replicate). Fish were kept in glass aquaria (100 × 50 × 40 cm) containing 160 L of dechlorinated tap water. The first group (control) did not receive AgNPs or QNPs in the water or the diet. The second group was fed a basal diet supplemented with 400 mg QNPs per kg diet (QNPs-supplemented group). The third group was fed a basal diet and exposed to AgNPs (1.98 mg/L; corresponding to $\frac{1}{10}$th LC50). The fourth group (AgNPs/QNPs co-administered group) received QNPs and was exposed to AgNPs at the previously mentioned concentration. The daily feeding regime was performed three times at 7:00 a.m., 11:00 a.m., and 4:00 p.m. throughout the experimental period (60 days), and the amount of feed was adjusted every two weeks according to the body weight.
## 2.3. Chemical Composition of the Whole Body
On the 60th day of the experiment, five fishes were randomly selected ($$n = 5$$/replicate) from each group to estimate the proximate chemical composition of the whole body, represented as percentages of the wet weight [46]. The crude protein was estimated by the Kjeldahl method (Velp Scientifica, Usmate Velate, MB, Italy). The moisture was estimated by a natural convection oven (JSON-100, Gongju-City, Republic of Korea). Ash and fats were estimated by muffle furnace and Soxhlet extraction (Thermo Scientific, Greenville, NC, USA), respectively.
## 2.4. Blood and Tissue Sampling
Blood samples were collected from the caudal blood vein by sterile syringes and then placed in sterile tubes (free from anticoagulant). The samples were left to coagulate, centrifuged at 1075 g for 20 min to separate the serum, and then stored at −20 °C until physiological, biochemical, and hormonal analyses. Fish from the different groups were sacrificed by spinal cord sectioning, and the liver and whole intestine were collected. The collected organs (100 mg each) were homogenized in 10 mM phosphate/20 mM Tris-pH 7.0 using a mechanical homogenizer at 600× g for 3 min at 4 °C, and the supernatant was collected after centrifugation. Intestinal and liver enzymes’ activity was also analyzed.
Parts of livers were frozen until the determination of silver residues. Another set of liver tissue samples was quickly transferred to liquid nitrogen and then stored at −80 °C until RNA extraction. Other intestine samples were used for the bacterial count.
## 2.5. Serum Physiological Assays
The indices of hepatic injury, including aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP), as well as total cholesterol (TC) and triglycerides (TG), were determined according to their related literature protocols [47,48,49,50,51]. Liver glycogen was determined by commercial kits (Cayman Chemical Company, Ann Arbor, MI, USA) [30].
## 2.6. Oxidative Injury Assays and Antioxidant Status
The activities of the antioxidants catalase (CAT) and superoxide dismutase (SOD), the concentration of reduced glutathione (GSH), and the oxidative injury marker malondialdehyde (MDA) were assessed in the liver tissue using a colorimetric method [52,53,54,55]. The same method was also used to monitor the protein carbonyl (PC) content in hepatic tissue (Cayman Chemical Company, Ann Arbor, MI, USA).
## 2.7. Expression of Liver Apoptosis and Stress-Related Genes
RNA was extracted from the hepatic tissue, and its integrity and concentration were checked by $1\%$ agarose and spectrophotometry. First-strand cDNA was synthesized using a QuantiTect RT kit (Qiagen, Hilden, Germany). The primers of the tested genes (caspase3, casp3; heat shock protein 70, Hsp70; tumor suppressor protein, p53; the internal housekeeping gene β-actin) are presented in Table 1.
Real-time PCR was performed using a QuantiTect SYBR Green PCR kit (Qiagen, Hilden, Germany) and a Rotor-Gene Q apparatus. The thermocycler conditions were 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s, 60 °C for 30 s and 72 °C for 30 s. The relative expression of the studied genes was analyzed using the 2−ΔΔCt equation [60].
## 2.8. Intestinal Enzyme Activities
The intestinal lipase and α-amylase activities were estimated with a fast colorimetric kit (Spectrum Diagnostic Co., Cairo, Egypt) [61,62], according to the manufacturer’s directives. The intestinal protease activity was estimated according to the method proposed by Bezerra et al. [ 63].
## 2.9. Hormonal Assay
Fish GH, T3, T4, and glucagon were estimated in the serum using ELISA kits (catalog numbers MBS701414, MBS2700145, MBS701162, MBS034316, respectively; MyBioSource, San Diego, CA, USA).
## 2.10. Determination of Aeromonas Counts and Total Intestinal Bacteria
Intestine samples were taken from 5 fish/group to enumerate Aeromonas and total bacteria. The samples were homogenized in sterile saline peptone water (8.5 gL−1 NaCl and 1 gL−1 peptone), followed by serial dilution up to 107. The total bacteria and Aeromonas were counted after incubation at 37 °C for 24 h on plate count agar [64] and agar medium [65], respectively.
## 2.11. Determination of Silver Residues
The liver samples were exposed to digestion by acids [66]. One gram of each sample was transported to a screw-capped glass bottle and exposed to a 4 mL digestion solution of nitric and perchloric acid (1:1). The samples were left at room temperature for 24 h for an initial digestion and then heated for 2 h at 110 °C. After that, the samples were cooled, and deionized water was added. Then, the solutions were warmed in a water bath for 1 h to eliminate nitrous gases. The digestion products were filtered, and deionized water was added up to 25 mL. Silver residues were determined by flame atomic absorption spectrophotometer (FAAS).
## 2.12. Statistical Analysis
The obtained data were statistically analyzed by SPSS (version 16.0, SPSS Inc., Chicago, IL, USA). All data are presented as means ± standard deviation. One-way analysis of variance (ANOVA) with Tukey’s multiple comparison post hoc test was applied to compare means among groups (* $p \leq 0.05$).
## 3.1. AgNPs and QNPs Characterization (Surface Chemistry)
The results of the characterization of AgNPs are presented in Figure 1. UV–Vis spectroscopy results showed the maximum peak at 420 nm. TEM analysis revealed a spherical shape with an average size of 30–60 nm and a net surface charge of −22 mV. According to the DLS analysis, the exact size was 59 nm.
Regarding the QNPs, TEM analysis revealed a spherical shape absorbing UV at 310 nm, an average size of 45–65 nm, and a net surface charge of −23 mV. DLS analysis showed an exact size of 77 nm (Figure 2).
## 3.2. Whole-Body Chemical Composition
The moisture percent of fish that received AgNPs was significantly higher than that of the other groups by approximately $3.5\%$ (Table 2). The same trend was also observed in the ash, which recorded an increase of $1.8\%$ compared to the QNPs and control groups. Fish that received AgNPs and QNPs showed increased ash percentages; however, these increases were nonsignificant and lower than those in the AgNP group.
The crude lipid percentage showed significant changes among the treated groups; the lowest and highest values were observed in the AgNPs and control groups. The crude lipid percentage of groups that received AgNPs + QNPs or AgNPs was around $5\%$. AgNPs markedly reduced the crude protein percentage, and such a decrease remained significantly lower than those of the QNPs and control groups.
## 3.3. Serum Physiological Assays
AgNPs notably increased serum levels of ALT and AST, with values double to triple those of the control; while QNPs significantly reduced these close to those of the control (Table 3). The glycogen level was significantly low in the AgNP group; however, this effect was rescued in the AgNPs + QNPs group.
QNPs significantly reduced the levels of TG and TC in serum levels in the QNPs group and kept them at lower values than those of the control.
## 3.4. Antioxidant Status and Oxidative Injury Assays
The activities of CAT, SOD, and GSH were significantly inhibited in the liver of the AgNP group (Table 4). Notably, GSH recorded a very low activity in the AgNP group, which reached a third of the values of the control group. MDA and PC levels were increased in the liver in response to AgNPs exposure. QNPs improved the negative effect of AgNPs on the activities of SOD, CAT, and GSH and, to a reasonable extent, increased the activities of MDA and PC in the liver.
## 3.5. Expression of Apoptosis and Stress-Related Genes
The expression of the hepatic Hsp70, casp3, and p53 genes was significantly upregulated in the AgNP group, with values between five- and six-fold increases (Figure 3). The expression of these genes was unaffected by QNPs treatment. Interestingly, the expression levels of these genes returned to the normal range in the AgNPs + QNPs group, except for Hsp70, which decreased by two-fold and remained at higher levels than the control.
## 3.6. Intestinal Enzyme Activity
QNPs increased intestinal enzyme activities (i.e., amylase, lipase, and protease) (Table 5). QNPs preserved much of the reduced intestinal enzyme activities resulting from AgNPs challenge. QNPs showed a marked effect on intestinal lipase activity in the QNP and AgNP + QNP groups.
## 3.7. Hormonal Assay
The GH, T3, T4, and glucagon levels were lowered in the AgNP group; however, QNPs kept them at normal levels in the AgNP + QNP group (Table 6). The changes in GH were statistically significant, while those in T3, T4, and glucagon were not significant.
## 3.8. Total Intestinal Bacteria and Aeromonas Counts
Notably, AgNPs markedly increased the total intestinal bacteria and Aeromonas count in the AgNP group (Figure 4). However, QNPs significantly decreased the total intestinal bacterial and Aeromonas counts in the QNP and AgNP + QNP groups compared to the control and AgNP groups.
## 3.9. Silver Residues
The highest level of silver residues was detected in the liver of the AgNP group compared to other groups (Figure 5). QNPs lowered the silver residues in the liver.
## 4. Discussion
The rapid expansion in the applications of engineered nanomaterials showed environmental impacts that are gaining greater and greater attention, associated with their novel advantages and potential hazards to living creatures. The AgNPs’ toxicity was investigated and found to be dependent on the shape, coating material, size, dose, duration of exposure, and species differences [9,67].
Characterization of AgNPs showed a spherical shape with an average size of 30–60 nm under TEM. UV–Vis spectroscopy showed the maximum peak at 420 nm with −22 mV net surface charge by zeta potential analysis, while the DLS analysis showed the hydrodynamic size of 59 nm. AgNPs have been already characterized for size and dispersity using UV–Vis spectroscopy and TEM, showing a peak at 431 nm with the size distribution ranging from 60 to 80 nm, respectively [68]. Shaluei et al. [ 2013] reported an average nanoparticle size of 61 nm [69]. The morphological characteristics of AgNPs by TEM showed mono-dispersed, roughly spherical with average sizes from 80 to 90 nm without any agglomeration. The spherical configuration of AgNPs under TEM was also observed by Srinonate et al. [ 70]. The data of DLS analysis showed that the Z-average was 32.20 nm [71]. Sibiya et al. [ 2022] reported a typical high-pitched peak of absorbance recorded on UV–Vis spectrophotometer at 450 nm due to the absorption of AgNPs surface plasmon resonance which confirmed the reduction of silver nitrate [72]. The same authors examined the size, shape, and morphology of AgNPs using TEM proving that AgNPs were globular in shape. other studies reported spherical and scattered smaller-sized AgNPs with approximately 20 nm in size [73,74]. The variations among previous studies and the present one might be ascribed to the different method of AgNPs synthesis.
AgNPs significantly increased serum ALT and AST, with double to triple values compared to the control. Indeed, elevated serum ALT and AST levels are considered as liver injury and stress markers [75,76]. Indeed, both regulate the transamination process, particularly during stress, to fulfill the increased energy requirement of the body [77], and modulate the metabolism of carbohydrates and proteins [78,79,80]. Thus, the activities of ALT, AST, but also ALP are highly indicated to measure the fish toxicity and recovery pattern [81].
In accordance, the ALT and ALP activities in common carp and ALP and acid phosphatase in *Labeo rohita* were significantly enhanced following exposure to AgNPs [22,82]. This increased activity could be ascribed to disruption of hepatocyte membranes and leakage of such enzymes from the hepatic cells into the bloodstream [25]. At the same time, the liver is an early target of detoxification and accumulation of various toxic substances [21]. The exposure to AgNPs enhanced the reactive oxygen species (ROS) production in the hepatoma cell line derived from fish [83], which is also confirmed by the increased MDA and PC levels in our findings. This oxidative stress could disrupt the function of mitochondria and lead to toxic effects by decreasing the integrity of the cell membrane and oxidizing the constituents of the cell [84].
ALT serum levels have been shown to be associated with liver fat [85,86]. In fish and mammals, de novo lipogenesis plays a crucial role in glucose homeostasis, in which lipogenic enzyme activities are modulated by dietary carbohydrate intake [87,88,89] and thus modulate glycogen levels [90].
Since the liver appeared to be targeted by AgNPs, hepatic glucagon signaling seemed to be inhibited, leading to decreased serum glucagon, as seen in the present study. Glucagon receptor signaling is linked to the metabolism of lipids [91] and amino acids [92]. Blockade of the glucagon receptor decreased hepatic amino acid catabolism with increased serum amino acids in animal models, including zebrafish [92,93,94]. Knockdown of the glucagon receptor upregulated the expression of hepatic lipogenic genes, increased hepatic lipid contents, and enhanced de novo lipid synthesis [95]. Glucagon inhibits hepatic de novo lipogenesis by the cyclic AMP-responsive element-binding protein H-insulin-induced gene-2a signaling pathway [96]. In the AgNP group, the whole body’s crude lipid and protein percentages were lower than the control. Accordingly, AgNPs may modulate glucagon receptor signaling. Although QNPs decreased the crude lipid content compared to the control (i.e., by approximately $1\%$), they beneficially increased the protein content in the whole body. QNPs also increased the lowered levels of the crude lipid and protein percentages caused by AgNPs.
Glucagon is secreted to regulate blood glucose levels and is strongly suggested to promote ureagenesis to regulate amino acid metabolism [97,98,99].
Hepatic knockdown of the glucagon receptor increased total plasma cholesterol and increased triglycerides [95]. Quercetin inhibited the increases in plasma cholesterol and protected pancreatic β-cells from oxidative stress, mitochondrial dysfunction (e.g., decreased ATP levels), and lipid peroxidation induced by high cholesterol treatment in vivo and in vitro [100]. Quercetin facilitates cholesterol excretion and helps protect cells from excessive accumulation of cholesterol by enhancing reverse cholesterol transport through the upregulation of related protein expression [101]. Typically, our findings indicated that QNPs decreased the TC and TG in the QNP and AgNP + QNP groups to lower levels than in the control group.
AgNPs have a direct effect on SOD, CAT, GSH, MDA, and glutathione peroxidase (GPx), which can change the antioxidant capacity [102]; they also initiate the production of ROS [103]. These enzymes are responsible for the detoxification of ROS and normal homeostasis maintenance. If the antioxidant system cannot maintain safe levels of ROS, oxidative stress occurs, and cellular damage may develop [32]. Mansour et al. [ 2021] showed a depletion of the activities of antioxidant enzymes and significant MDA production, as an indicator of ROS, in fish exposed to AgNPs at high levels. Similarly, O. niloticus and *Tilapia zillii* exposed to AgNPs (4 mg/L) showed reduced gene expressions and activity of antioxidant enzymes and enhanced levels of MDA in the brain of treated fish [16]. The SOD, CAT, and GST activities were significantly reduced in different organs of *Labeo rohita* following the exposure to increasing AgNPs concentrations [82].
AgNPs from wastewater led to oxidative damage and reduction of SOD activity in rainbow trout [104]. Moreover, exposure of common carp (C. carpio) to AgNPs ($12.5\%$ of LC50) increased the activity of CAT and SOD while exposure to $25\%$ and $50\%$ of LC50 showed opposite effects [22].
Sibiya et al., [ 2022] showed that AgNPs induced oxidative stress by increasing the activity of PC and lipid peroxidation in the gills, and altered the antioxidants such as GPx, glutathione-S-transferase (GST), CAT, SOD and GSH in O. mossambicus [72]. Furthermore, the AgNPs can interfere with the synthesis of antioxidant enzymes [105].
Therefore, the decrease in antioxidant enzyme activity observed in the present study could be attributed to the depression of antioxidant genes expression and enzyme synthesis process leading to the weakening of the cell antioxidant capacity [84,106]. The mechanism behind this weakening is the nanoparticles’ metallic nature, and the existence of ionic forms of transition metals that encourage ROS production leading to oxidative stress [107]. Our results showed that QNPs have effective antioxidant activities against the oxidative damage induced by AgNPs in the liver. Earlier reports indicated that quercetin markedly protected against the decreased activities of SOD and GPx induced by high cholesterol supplementation in animal models and in vivo [100]. In zebrafish, nano-encapsulated quercetin maintained redox status after exposure to AgNPs [108]. QNPs had moderate but effective preservation of the MDA content; however, they could not restore the activity of MDA to physiological levels. This finding could be explained by the variable resistance of the antioxidant activities toward AgNPs, in which MDA showed less resistance to AgNPs and Ag+ [102]. However, the other antioxidant enzymes had variable resistance against AgNPs and Ag+, and SOD showed stronger resistance to both forms of silver [102].
Quercetin protects against inflammatory/oxidative stress responses by modulating 5’adenosine monophosphate-activated protein kinase (AMPK)/sirtuin 1 (SIRT1)/nuclear factor kappa B (NF-κB) signaling, which upregulates the expression of SIRT1 and downregulates NF-κB [109,110]. The induction of NF-κB prompts the expression of related stress genes (e.g., heat shock proteins) [111]. AgNPs upregulated Hsp70 and p53 (cell cycle checkpoint proteins that control cell division and apoptosis, respectively), inhibited the antioxidant GSH, and enhanced MDA and the apoptosis markers casp3 and casp9, indicating induced oxidative stress, nucleic acid damage, and apoptosis in the genetic model Drosophila melanogaster [112].
According to our results, AgNPs upregulated the expression of Hsp70, p53, and casp3. AgNPs were already shown to induce inflammatory response, oxidative stress and Hsp70 stress gene expression upregulation in *Nile tilapia* [8]. AgNPs toxicity also induced p53 expression in the liver tissue of adult zebrafish [74]. Moreover, p53 activation in response to DNA damage can lead to cell cycle arrest or apoptosis preventing cell proliferation [113,114]. However, this action was rescued by QNPs, with a lesser effect on Hsp70, which showed an antiapoptotic effect by suppressing casp3 and releasing cytochrome c [100].
In the present study, intestinal enzyme activities (i.e., amylase, lipase, and protease) and GH, T3, and T4 were checked to assess the physiological status of the digestion process and growth. The results of the exposure to AgNPs are consistent with the disrupted growth performance observed after increasing the concentration of AgNPs in the *Nile tilapia* [71].
The findings revealed improved intestinal enzyme activities by QNPs in both the QNP and AgNP + QNP groups. Importantly, QNPs exhibited a pronounced effect on intestinal enzyme activities in the QNP group. This could be attributed to the protection of quercetin against intestinal oxidative damage and the maintenance of intestinal barrier function [115,116]. Furthermore, total intestinal bacteria and Aeromonas counts were unexpectedly increased in the AgNP group owing to silver antibacterial activity [103]. A possible explanation of this observation is that a high concentration of AgNPs negatively modulated the intestinal microbiota and increased harmful bacteria such as Aeromonas. Earlier studies support this hypothesis, showing that AgNPs caused gut dysbiosis in animal models, including fish [117,118,119,120].
Silver residues were highly detected in the liver, and the current findings indicate a primitive role of the liver in the detoxification of silver and AgNP-induced liver cell injury. Similar results were observed in *Clarias gariepinus* and Indian major carp Labeo rohita, in which AgNPs were highly detected in the liver even after 15 days of recovery [121,122].
Additionally, AgNPs were massively accumulated in the liver of common carp (C. carpio) [22]. Further, silver residues showed the highest levels in gills compared to other tissues in common carp and African catfish (C. gariepinus) [22,123]. Such variations may depend on species-specific differences or variable experimental conditions. For instance, 15 days of exposure to silver led to its considerable accumulation in the liver of C. gariepinus [121,122]. Treatment of the freshwater rainbow trout with AgNPs resulted in the accumulation of great quantities of silver in the liver, intestine, muscles, and gills [124]. Moreover, 100 μg/L of AgNPs or AgNO3, individually or combined with 10 mg/L of humic acids, bioaccumulated Ag in gills and altered the antioxidant status of *Piaractus mesopotamicus* [125]. The ability of freshwater fish to accumulate AgNPs and AgNO3 may impair their biochemical and physiological parameters [126].
## 5. Conclusions
In conclusion, our findings showed that AgNPs (1.98 mg/L) have a deleterious effect on the physiological status and antioxidant system of Nile tilapia. They markedly increased serum levels of ALT, AST, TC, and TG. SOD, CAT, and GSH were significantly inhibited in the liver, and the expression of hepatic stress-related genes was upregulated after exposure to AgNPs. In addition, the intestinal enzyme activities and bacterial counts were disrupted. This indicates a hepatotoxic effect of AgNPs. QNPs showed promising protective action against the impact of AgNPs. Additionally, QNPs exhibited beneficial effects in enhancing the physiological and health status and growth parameters of *Nile tilapia* when used under normal conditions.
## 6. Limitations and Future Perspectives
Various reports documented the possible toxic effects of AgNPs in vitro and in vivo. Therefore, investigating the mechanism of interaction between biological cells and AgNPs to better understand their potential risks as antibacterial agents seems to become a significant issue. Moreover, transforming some natural polyphenolic compounds, such as quercetin, into QNPs may provide better physical insights, thus enhancing their pharmaceutical efficacy.
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|
---
title: Identification of Kinase Targets for Enhancing the Antitumor Activity of Eribulin
in Triple-Negative Breast Cell Lines
authors:
- Xuemei Xie
- Jangsoon Lee
- Jon A. Fuson
- Huey Liu
- Toshiaki Iwase
- Kyuson Yun
- Cori Margain
- Debu Tripathy
- Naoto T. Ueno
journal: Biomedicines
year: 2023
pmcid: PMC10045293
doi: 10.3390/biomedicines11030735
license: CC BY 4.0
---
# Identification of Kinase Targets for Enhancing the Antitumor Activity of Eribulin in Triple-Negative Breast Cell Lines
## Abstract
Background: Triple-negative breast cancer (TNBC) is the most aggressive molecular subtype of breast cancer, and current treatments are only partially effective in disease control. More effective combination approaches are needed to improve the survival of TNBC patients. Eribulin mesylate, a non-taxane microtubule dynamics inhibitor, is approved by the U.S. Food and Drug Administration to treat metastatic breast cancer after at least two previous chemotherapeutic regimens. However, eribulin as a single agent has limited therapeutic efficacy against TNBC. Methods: High-throughput kinome library RNAi screening, Ingenuity Pathway Analysis, and STRING analysis were performed to identify target kinases for combination with eribulin. The identified combinations were validated using in vivo and ex vivo proliferation assays. Results: We identified 135 potential kinase targets whose inhibition enhanced the antiproliferation effect of eribulin in TNBC cells, with the PI3K/Akt/mTOR and the MAPK/JNK pathways emerging as the top candidates. Indeed, copanlisib (pan-class I PI3K inhibitor), everolimus (mTOR inhibitor), trametinib (MEK inhibitor), and JNK-IN-8 (pan-JNK inhibitor) produced strong synergistic antiproliferative effects when combined with eribulin, and the PI3K and mTOR inhibitors had the most potent effects in vitro. Conclusions: *Our data* suggest a new strategy of combining eribulin with PI3K or mTOR inhibitors to treat TNBC.
## 1. Introduction
Triple-negative breast cancer (TNBC), which lacks the expression of estrogen receptor (ER) and progesterone receptor (PR) and has low or no expression of human epidermal growth factor receptor 2 (HER2), accounts for 15–$20\%$ of all breast cancers diagnosed worldwide [1]. Compared with patients with other subtypes of breast cancer, patients with TNBC have shorter survival; the 5-year mortality rate of patients with TNBC is $40\%$ [2]. TNBC is more aggressive than other subtypes of breast cancer and has a worse prognosis [3,4,5]. The poor outcomes of TNBC are attributed to its high rates of metastasis and relapse [3,4,5]. In addition, previous clinical trials have shown the limited efficacy of several small-molecule inhibitors and monoclonal antibodies against tumor-driving signaling pathways in TNBC [6,7,8]. The current U.S. Food and Drug Administration (FDA)-approved targeted drugs for TNBC treatment are poly(ADP-ribose) polymerase (PARP) inhibitors, an anti-PD-L1 immune checkpoint inhibitor, and an antibody-drug conjugate targeting trophoblast cell-surface antigen 2 (TROP2). However, the use of these drugs in patients with TNBC is limited because only some TNBC patients are eligible for these treatments, and resistance ultimately develops. As a reslult, cytotoxic systemic chemotherapy still has a significant role in TNBC treatment.
Another vulnerability in TNBC may lie in the PI3K/Akt/mTOR pathway, that plays a critical role in cell proliferation, survival, mobility, and chemotherapy resistance in breast cancer [9]. This pathway can be highly activated by multiple genomic alterations, including mutations in the oncogenes PIK3CA, AKT, and MTOR and inactivating mutations in the tumor suppressor genes PIK3R1, INPP4B, PTEN, TSC1, TSC2, and LKB1 (also called STK11) [10]. PIK3CA, an oncogene that encodes the p110α catalytic subunit of phosphatidylinositol-3-kinase (PI3K), is the second most commonly mutated gene after P53 in TNBC [11]. Mutations in PIK3CA can activate several signaling pathways in breast cancer, predominantly affecting the PI3K/Akt pathway [12,13]. PIK3CA mutations increase TNBC cell aggressiveness and confer resistance to chemotherapy in TNBC by inducing constitutive activation of PI3K/Akt/mTOR signaling and suppressing apoptosis [14]. This association with chemotherapy resistance is further supported by the association of PIK3CA mutations with a poor pathological complete response rate to neoadjuvant chemotherapy in TNBC [15,16]. PIK3CA mutations are detected in $37\%$ of ER+/HER2−, $22\%$ of HER2+, and $18\%$ of ER−/HER2− breast tumors and in $23.7\%$ of TNBC [17,18]. The higher rate of PIK3CA mutations in advanced TNBC relative to early-stage TNBC is likely due to ER expression loss in relapsed breast cancer that was initially positive for ER, a subtype that harbors a high rate of PIK3CA mutations [19]. For all these reasons, inhibitors targeting the PI3Kα subunit of PIK3CA have been tested in TNBC.
In the same pathway, mTOR is another possible therapeutic target for TNBC. mTOR, a serine–threonine kinase, forms two complexes, mTORC1 and mTORC2, and is mutated in $1.8\%$ of the primary breast cancer cases in The Cancer Genome Atlas, with a small minority of these mutations recognized as putative drivers [20,21]. In addition to genetic activation, mTOR can be activated by PI3K signaling, which has been associated with drug resistance, and mTOR inhibition re-sensitizes ER+ breast cancer cells to tamoxifen [22]. The FDA has approved the mTOR inhibitor everolimus for the treatment of advanced HER2− breast cancer that expresses either ER or PR.
A treatment that has shown activity in TNBC is eribulin (eribulin mesylate). Eribulin is a synthetic analog of halichondrin B, a natural product isolated from the marine sponge Halichondria okadai [23]. It functions as a non-taxane microtubule inhibitor [24]. The FDA has approved eribulin to treat patients with advanced or metastatic breast cancer who have received at least two chemotherapy regimens. Eribulin exerts its antitumor activity by binding to microtubule ends to prevent microtubule polymerization, leading to cell cycle arrest at the G2/M phase and subsequent apoptosis [24]. In addition, eribulin inhibits tumor progression or metastasis by reducing hypoxia [25], reversing epithelial–mesenchymal transition [26], suppressing migration and invasion [26], and preventing tumor vasculature remodeling [25]. Eribulin has been used to treat advanced or metastatic breast cancer, including TNBC [27,28,29], and has been used to overcome chemotherapy resistance. Eribulin produced regression of cisplatin-resistant tumors in a patient-derived xenograft model of triple-negative matrix-producing breast carcinoma [30]. The EMBRACE trial, a phase III study of eribulin in patients with HER2− advanced breast cancer, showed overall survival improvement after eribulin treatment in patients whose breast cancer was resistant to anthracycline-based regimens and taxane therapy [31]. However, the improvement of overall survival in eribulin-treated patients was only 2.5 months compared with the treatment of physician’s choice, and clinical resistance to eribulin developed after a median of 3.7 months [31].
To further enhance the anti-tumor efficacy of eribulin against TNBC, we aimed to identify potential synergistic partners for eribulin through a high-throughput kinome library RNA interference (RNAi) screening. We found that the PI3K/Akt/mTOR, MAPK, and JNK pathways are potential targets for eribulin-based combination treatment. We confirmed that targeting PI3K with copanlisib (a pan-class I PI3K inhibitor) and targeting mTOR with everolimus showed synergistic effects when combined with eribulin. Our data indicate that either of these kinase inhibitors combined with eribulin represent a promising combination therapy for TNBC.
## 2.1. Cell Lines and Reagents
BT-20, MDA-MB-157, MDA-MB-453, MDA-MB-468, MDA-MB-231, HCC70, HCC1187, HCC1806, BT-549, HCC1395, and MDA-MB-436 TNBC cells and MCF10A normal breast epithelial cells were purchased from American Type Culture Collection (Manassas, VA, USA). HCC2185 and HCC3153 TNBC cells were purchased from The University of Texas Southwestern Medical Center (Dallas, TX, USA). MFM-223, CAL51, and CAL120 TNBC cells were purchased from the DSMZ-German Collection of Microorganisms and Cell Cultures (Braunschweig, Germany). SUM159 (TNBC), SUM185 (TNBC), and SUM149 (triple-negative inflammatory breast cancer (TN-IBC)) cells were purchased from Asterand Bioscience (Detroit, MI, USA). The BCX-010 (TN-IBC) cell line was established at The University of Texas MD Anderson Cancer Center (Houston, TX, USA).
BT-20, HCC70, HCC1187, HCC1806, BT-549, HCC1395, HCC2185, and HCC3153 (TNBC) cells were maintained in Roswell Park Memorial Institute 1640 medium (#R8758; Sigma-Aldrich, St. Louis, MO, USA). MDA-MB-157, MDA-MB-453, MDA-MB-468, MDA-MB-231, and MDA-MB-436 (TNBC) cells were maintained in Dulbecco’s modified Eagle medium/F-12 medium (#D8062; Sigma-Aldrich). BCX-010, SUM149, and SUM159 (TN-IBC) cells were maintained in Ham’s F-12 medium (#11765054; Life Technologies Inc., Carlsbad, CA, USA) supplemented with 5 µg/mL insulin (#12-585-014; Thermo Fisher Scientific Inc., Waltham, MA, USA) and 1 µg/mL hydrocortisone (#H0888; Sigma-Aldrich). All media were supplemented with $10\%$ fetal bovine serum (FBS; #F0600-050; GenDEPOT, Katy, TX, USA) and $1\%$ antibiotic/antimycotic (#A5955; Sigma-Aldrich). MCF10A cells were maintained in Dulbecco’s modified Eagle medium/F-12 medium, supplemented with $5\%$ horse serum (#16050-122; Thermo Fisher Scientific), 5 µg/mL insulin, 1 µg/mL hydrocortisone, $1\%$ antibiotic/antimycotic, 100 ng/mL cholera toxin (#C8052; Sigma-Aldrich), and 20 ng/mL epidermal growth factor (#HZ-1326; Proteintech Group, Inc., Rosemont, IL, USA). All cell lines were validated by DNA typing at the MD Anderson Cancer Center Characterized Cell Line Core and confirmed to be free of mycoplasma using the MycoAlert Mycoplasma Detection Kit (#LT07-710; Lonza, Morristown, NJ, USA).
## 2.2. Small Molecules
Copanlisib (#204570) was purchased from MedKoo (Morrisville, NC, USA). Trametinib (#S2673), everolimus (#S1120) and JNK-IN-8 (#S4901) were purchased from Selleckchem (Houston, TX, USA). Eribulin was provided by Eisai Inc. (Nutley, NJ, USA).
## 2.3. Cell Proliferation Assay
The anti-proliferation effect of eribulin against TNBC and IBC cells was assessed using CellTiter-Blue Cell viability and sulforhodamine B staining assays. In brief, 3 to 6 × 103 cells/well were seeded in 96-well plates and treated the next day with eribulin alone or with eribulin combined with kinase inhibitors, including copanlisib, trametinib, everolimus, and JNK-IN-8, for 5 days. On day 5, following treatments, the CellTiter-Blue reagent (#PR-G8081; Promega Corporation, Madison, WI, USA) was added to the plates, and the optical density (595 nm) was determined using a Victor X3 plate reader (PerkinElmer, Waltham, MA, USA). The cells were then fixed with $5\%$ trichloroacetic acid (#T8657; Sigma-Aldrich) for 2 h at room temperature and then stained with $0.03\%$ sulforhodamine B solution (#230162; Sigma-Aldrich) for 30 min at room temperature. The stained cells were dissolved in 10 mM Tris buffer (#1610732; Bio-Rad, Hercules, CA, USA). The optical density was determined at 585 nm using the Victor X3 plate reader. Growth inhibition graphs were generated, and IC50 values were calculated using nonlinear regression to fit the data to the log (inhibitor) vs. response (variable slope) curve using GraphPad Prism software 9 (GraphPad Software, Inc., San Diego, CA, USA). To evaluate the synergistic anti-proliferation effects of eribulin in combination with kinase inhibitors, the combination index (CI) and fraction affected were determined using the CalcuSyn software (v2.1, Biosoft, Cambridge, United Kingdom). CI < 0.90 indicates a synergistic impact, 0.91 ≤ CI < 1.10 indicates an additive impact, and CI ≥ 1.11 indicates an antagonistic impact of the two-drug combination.
## 2.4. Soft Agar Colony Formation Assay
The impact of drug treatment on anchorage-independent growth was assessed using a soft agar assay, a standard method to predict in vivo carcinogenesis and a drug’s anti-tumor efficacy. Cells (2 to 5 × 103 cells/well) were suspended in 2 mL of $0.375\%$ agarose with DMSO or drugs and then overlaid onto 650 µL of $0.75\%$ agarose layer in six-well plates. The plates were incubated for 3 to 6 weeks. After treatment, the colonies were stained with 200 µL of MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide; 2 mg/mL; #M5655; Sigma-Aldrich) for 2 h. Stained colonies greater than 80 μm in diameter were counted using a GelCount system (Oxford Optronix Ltd., Milton, UK).
## 2.5. High-Throughput RNAi Screening
Pooled kinome siRNA, consisting of 3 unique siRNAs targeting 1 gene and a total of 2127 siRNAs targeting 709 kinase genes, was selected using Ambion Silencer Select Human Genome siRNA Library V4 (#4397926; Life Technologies Inc.) and placed into Greiner Bio-One Cellstar 384-well plates (Thermo Fisher Scientific). Seventy-five microliters of the three pooled siRNAs (2 µM) for one gene were dispensed per well in quadruplicate. For an internal control, Silencer Select Negative Control No. 1 siRNA (#4390844; Thermo Fisher Scientific), Silencer Select Positive Control PLK1 siRNA (#AM51331; Thermo Fisher Scientific), and no-siRNA control (Thermo Fisher Scientific) were included in each plate. The positive control (PLK1 siRNA) was used to assess transfection efficiency, and the no-siRNA control was used to calculate cellular sensitivity to eribulin. Lipofectamine RNAiMAX (0.05 µL/well; #13778030; Thermo Fisher Scientific) in 10 µL of serum-free Opti-MEM was added to the plates, and then the plates were incubated at room temperature for 45 min. After incubation, SUM149 (300 cells) in 20 µL of complete media without antibiotics was added. The plates were sealed and incubated at 37 °C with $5\%$ CO2 for 48 h. A total of 28 plates were prepared for kinome screening, with each plate containing pooled siRNAs targeting 26 genes. At 48 h after treatment with pooled siRNAs, eribulin at the final concentration of IC20 (0.3 nM) or vehicle (DMSO) in 30 µL of complete media was added to each well. The plates were then sealed and incubated at 37 °C with $5\%$ CO2 for 72 h. Following drug treatment, 35 µL of medium was aspirated from each well, followed by the addition of ATPlite 1step (25 µL/well; #6016731; PerkinElmer). The plates were sealed and incubated at room temperature for 10 min by shaking at 1000 rpm on an orbital shaker. Luminescence readings were used as an indicator of cell viability. Luminescence readings for each treatment were averaged and normalized to the mean of the DMSO-treated no-siRNA negative control in the same plate as relative viability. The median Z’-factor in each plate was calculated using the equation below. The median z’-factor was 0.58 for the SUM149 kinome screening. Z’factor = 1 − [3 × (σp + σn)]/(μp − μn) Here, σp is the standard deviation of the PLK1 positive control, σn is the standard deviation of the no-siRNA negative control, μp is the mean of the PLK1 positive control, and μn is the mean of the no-siRNA negative control.
To assess the impact of siRNA-induced gene knockdown on drug sensitivity, the sensitivity index was calculated for each gene after eribulin treatment to identify synergistic drug and gene combination hits, using the equation below [32]. Each drug and gene combination was then ranked according to this sensitivity index score with a cutoff of 0.15. Sensitivity index = (Rc/Cc × Cd/Cc) − Rd/Cc Here, *Rc is* the viability of cells treated with siRNA without the drug, *Cc is* the viability of cells treated with the no-siRNA no-drug control, *Cd is* the viability of cells treated with the drug, and *Rd is* the viability of cells treated with siRNA plus drug.
## 2.6. Western Blotting
Cells (3 × 105 cells/10 mL) were seeded in 6-cm plates overnight and were treated the next day with eribulin alone or in combination with everolimus, trametinib, JNK-IN-8, or copanlisib for 48 h at 37 °C. At 48 h following treatment, the total protein was extracted using a cold M-PER Mammalian Protein Extraction Reagent (#78501; Thermo Fisher Scientific) complemented with phosphatase and protease inhibitors (#B15001; Bimake.com, Houston, TX, USA). The protein samples were denatured by incubation at 70 °C for 10 min on a heat plate, resolved by running sodium dodecyl sulfate–polyacrylamide gel electrophoresis using NuPAGE 4–$12\%$ Bis-Tris Plus gel (#WG1403BOX, Thermo Fisher Scientific), and then transferred onto a polyvinylidene difluoride membrane (#1620177, Bio-Rad). Following blocking with $4\%$ bovine serum albumin, proteins of interest on the blots were probed using the following primary antibodies (in a 1:1000 dilution) purchased from Cell Signaling Technology (Danvers, MA, USA) or other suppliers as indicated: anti-XIAP (#14334), anti-phospho-AKT (#4060), anti-phospho-mTOR (#5536), anti-phospho-H2AX (#80312), anti-PARP (#9542), or anti-α-tubulin (#T9026, Sigma-Aldrich). The secondary antibodies used were horseradish peroxidase–conjugated immunoglobulin G (Life Technologies Inc.) for chemiluminescence signal detection. The intensity of target proteins on the blots was measured using ImageJ (National Institutes of Health, Bethesda, MD, USA).
## 2.7. Caspase 3/7 Activity Measurement
Caspase $\frac{3}{7}$ activity was measured using Caspase-Glo $\frac{3}{7}$ assay reagent (#G8091; Promega Corporation) according to the manufacturer’s instructions. In brief, cells (5 × 103 cells) were seeded into 96-well plates and cultured overnight. The next morning, the cells were treated with eribulin alone, everolimus alone, copanlisib alone, eribulin plus everolimus, or eribulin plus copanlisib for 24 h at 37 °C. At 24 h after treatment, the culture media were removed, and 100 µL of the Caspase-Glo $\frac{3}{7}$ assay reagent was added into the plates, which were incubated for 1 h at 37 °C. Luminescence intensity was determined using the Victor X3 plate reader (PerkinElmer), and the background signal from the control wells containing reagent only was subtracted.
## 2.8. Cell Cycle Analysis
Cells (3 × 105 cells) were seeded into 60-mm plates and cultured overnight. The next morning, the cells were treated with eribulin alone, everolimus alone, copanlisib alone, eribulin plus everolimus, or eribulin plus copanlisib for 72 h at 37 °C. At 72 h after treatment, the cells were collected, fixed in ice-cold $70\%$ EtOH (#111000200; Greenfield Global Inc., Toronto, ON, Canada), treated with 50 μg/mL RNase A (#12091021; Invitrogen), stained with propidium iodide (#P4864; Sigma-Aldrich), and subjected to flow cytometry analysis.
## 2.9. Cell Migration Assay
The migration assay was performed using a 24-well microchemotaxis chamber (Corning Inc., Corning, NY, USA). Cells (2 × 106) were seeded in 10-cm plates and the next morning treated with eribulin alone, everolimus alone, copanlisib alone, eribulin plus everolimus, or eribulin plus copanlisib for 2 h at 37 °C. At 2 h after treatment, the cells were resuspended in FBS-free medium (2.5 × 105 cells/250 µL) and then added into the upper chambers of transwells separated by inserts with 8-µm pores. The lower chambers were filled with complete medium (750 µL) containing $10\%$ FBS as an attractant. The cells were allowed to migrate for 6-8 h and then fixed and stained with hematoxylin and eosin. Migrated cells were scanned using the PathScan Enabler IV Pathology Slide Scanner (Meyer Instruments, Inc., Houston, TX, USA) and then quantified using National Institutes of Health ImageJ software (http://rsb.info.nih.gov/ij/ (accessed on 17 January 2023)).
## 2.10. Ex Vivo Determination of Drug Sensitivity
Fresh tissue slices (300 µm) were prepared from TNBC cell xenografts collected from humanized NSG-SGM3 mice (Jackson Laboratory, Bar Harbor, ME, USA) and cultured in an air/media interface on a membrane. Every 4 days, the media were discarded, and fresh media containing drugs were added. Viability was measured on day 8 or 12 using the luminescent viability assay.
## 2.11. Statistical Analysis
The cell proliferation rate was summarized with descriptive statistics (mean, median, and quartiles) and box plots for each treatment group. A two-tailed unpaired Student t-test was used for statistical analysis using GraphPad Prism software, with p ≤ 0.05 considered significant.
## 3.1. Eribulin Suppressed Proliferation of TNBC and TN-IBC Cells
To evaluate the antitumor efficacy of eribulin in vitro and to select proper cell lines for the further evaluation of eribulin’s antitumor efficacy in combinations ex vivo, we tested eribulin for its anti-proliferation effects against a panel of TNBC and IBC cells. As shown by a sulforhodamine B assay, eribulin effectively inhibited the proliferation of the 18 tested TNBC cell lines, which were BT-20, MFM-223, MDA-MB-157, MDA-MB-453, MDA-MB-468, MDA-MB-231, HCC70, HCC2185, CAL-120, HCC1187, CAL-51, HCC1806, SUM185, BT-549, HCC1395, HCC3153, MDA-MB-436, and SUM159 (Figure 1). Eribulin also effectively inhibited the proliferation of the two tested TN-IBC cell lines, which were SUM149 and BCX-010 (Figure 1). The IC50 values of eribulin against the tested TNBC and IBC cells ranged from 0.12 nM to 1.91 nM, except for CAL51, for which the IC50 was 8.1 nM. These results demonstrate that eribulin is highly effective at inhibiting the proliferation of both TNBC and TN-IBC cells, with IC50 values in the nanomolar range.
Despite this overall effectiveness, we observed variation in the TNBC cell lines’ responses to eribulin (Figure 1). These varying responses may be related to the differences in TNBC molecular subtypes and genomic alterations in the PI3K/Akt/mTOR pathway. TNBC is a heterogeneous disease with different molecular subtypes showing different responses to chemotherapy [33]. In addition, the mutations in MTOR, PIK3CA, TP53, PTEN, and/or other genes have a significant impact on responses to chemotherapy [9,14,15,16,22]. Indeed, based on TNBC molecular subtypes and genomic alterations in the PI3K/Akt/mTOR pathway, we noted that basal-like 1 (MDA-MB-468), basal-like 2 (SUM149), and luminal androgen receptor (MDA-MB-453) TNBC cells harboring more mutations in this pathway were less responsive to eribulin than the cells of the same subtypes harboring fewer mutations (Table in Figure 1). We also observed that, among the tested mesenchymal TNBC cell lines, the cells harboring mutations in PIK3CA and TP53 (CAL-51, SUM159) or PIK3CA and PTEN (BCX-010) were less responsive to eribulin than the cells harboring other mutations. Altogether, our results demonstrate that different TNBC molecular subtypes with different mutations in the PI3K/Akt/mTOR pathway have different responses to eribulin. This should be considered in the development of eribulin-based combination treatments.
## 3.2. PI3K/Akt/mTOR and MAPK/JNK Pathways Potentiate the Antitumor Efficacy of Eribulin in TNBC Cells
To identify potential synergistic partners to improve the antitumor efficacy of eribulin against TNBC, we performed a high-throughput RNAi screening using kinome library pooled siRNA, consisting of 2127 siRNAs targeting 709 kinase genes, in SUM149 cells; these cells are well characterized in preclinical models, are chemoresistant, and are relatively resistant to eribulin (Table 1) [34]. Based on a sensitivity index with a cutoff at 0.15, we identified 135 genes whose inhibition significantly enhanced the anti-proliferation effect of eribulin against SUM149 cells (Table 1). Furthermore, an ingenuity pathway analysis identified the PI3K/Akt/mTOR and MAPK/JNK pathways as the top candidates whose inhibition using siRNA significantly enhanced the anti-proliferation effect of eribulin against SUM149 cells (Figure 2). These results suggest that targeting the PI3K/Akt/mTOR or MAPK/JNK pathway may improve the antitumor efficacy of eribulin in TNBC.
## 3.3. Combination with Inhibitors of Target Kinases Enhanced Anti-Proliferation Activity of Eribulin
To validate the potential of targeting the PI3K/Akt/mTOR and the MAPK/JNK pathways to enhance the antitumor efficacy of eribulin in TNBC, we tested the synergistic effect of eribulin and kinase inhibitors, including everolimus (an mTOR inhibitor), copanlisib (a pan–class I PI3K inhibitor), trametinib (a MEK inhibitor), and JNK-IN-8 (a pan–JNK inhibitor) using MDA-MB-468, MDA-MB-436, SUM149, and BCX-010 TNBC cells. These cell lines can easily form tumors in mice and have either functionally normal PIK3CA (MDA-MB-436 and SUM149) or mutant PIK3CA (MDA-MB-468 and BCX-010). Therefore, these cell lines allow us to understand the impact of PIK3CA mutations on the synergistic effect of eribulin combined with everolimus or copanlisib.
As shown in Figure 3, the combination of eribulin and everolimus showed a strong synergistic anti-proliferation effect in MDA-MB-468, MDA-MB-436, and BCX-010 cells, with CIs ranging from 0.21 to 0.75. This combination also showed a moderate synergistic effect at low doses and a slight antagonism effect at high doses in SUM149 cells, with CIs ranging from 0.80 to 1.38. The combination of eribulin and copanlisib showed a strong synergistic anti-proliferation effect in MDA-MB-468 and BCX-010 cells, with CIs ranging from 0.42 to 0.84. This combination also showed a moderate synergistic effect in MDA-MB-436 cells, with CIs ranging from 0.14 to 0.93. No synergistic effect of eribulin and copanlisib was observed in SUM149 cells, with CIs ranging from 0.94 to 1.45. The combination of eribulin and trametinib showed a synergistic anti-proliferation effect in MDA-MB-468, SUM149, and BCX-010 cells, with CIs ranging from 0.35 to 0.95, and a moderate synergistic to moderate antagonistic effect in MDA-MB-436 cells, with CIs ranging from 0.69 to 1.37. The combination of eribulin and JNK-IN-8 showed a synergistic to nearly additive anti-proliferation effect in MDA-MB-436, SUM149, and BCX-010 cells, with CIs ranging from 0.43 to 0.96, whereas no synergistic effect was observed in MDA-MB-468 cells, with CIs ranging from 0.89 to 2.09.
Altogether, the combination of eribulin with everolimus had the most synergistic anti-proliferation effect, especially in MDA-MB-468, MDA-MB-436, and BCX-010 cells, followed by the combinations of eribulin with trametinib or copanlisib, with JNK-IN-8 showing the least synergy. This study indicates that inhibition of mTOR/PI3K signaling by everolimus or by copanlisib may improve the anti-tumor efficacy of eribulin in TNBC. Among the tested cell lines, BCX-010 cells, followed by MDA-MB-468 cells, showed the most synergistic response to all the tested combination treatments.
## 3.4. Combination with Inhibitors of the PI3K/mTOR Pathway Enhanced Growth Inhibition Activity of Eribulin in 3D Culture
The results from the 2D culture suggest that, compared with the inhibition of other pathways, the inhibition of the mTOR/PI3K pathway showed the most synergistic effect when combined with eribulin. Therefore, we further tested the synergistic antitumor effect of eribulin combined with everolimus or copanlisib by performing an anchorage-independent soft agar colony formation assay, that reflects the in vivo tumorigenicity of tumor cells and in vivo antitumor efficacy of therapeutic agents. Meanwhile, to evaluate the impact of PIK3CA and PTEN mutations on the synergistic effect of eribulin with everolimus or copanlisib, we used cell lines harboring mutations in PIK3CA (SUM159 and BCX-010) or PTEN (MDA-MB-468). As shown in Figure 4A and Supplementary Figure S1, compared to eribulin or everolimus monotherapy, combination therapy with eribulin and everolimus significantly suppressed colony formation 5.97-fold vs. eribulin ($p \leq 0.001$) and 13.66-fold vs. everolimus ($p \leq 0.001$) in MDA-MB-436 cells; 2.89-fold vs. eribulin ($p \leq 0.01$) and 5.51-fold vs. everolimus ($p \leq 0.001$) in SUM149 cells; 5.05-fold vs. eribulin ($p \leq 0.0001$) and 3.79-fold vs. everolimus ($p \leq 0.001$) in MDA-MB-468 cells; 5.76-fold vs. eribulin ($p \leq 0.001$) and 12.96-fold vs. everolimus ($p \leq 0.0001$) in SUM159 cells; and 11.04-fold vs. eribulin ($p \leq 0.001$) and 1.82-fold vs. everolimus ($p \leq 0.001$) in BCX-010 cells. Similarly, compared to eribulin or copanlisib monotherapy, the combination of eribulin with copanlisib significantly suppressed tumors 2.12-fold vs. eribulin ($p \leq 0.05$) and 3.43-fold vs. copanlisib ($p \leq 0.001$) in MDA-MB-436 cells; 2.65-fold vs. eribulin ($p \leq 0.001$) and 4.53-fold vs. copanlisib ($p \leq 0.01$) in SUM149 cells; 2.44-fold vs. eribulin ($p \leq 0.0001$) and 1.69-fold vs. copanlisib ($p \leq 0.0001$) in MDA-MB-468 cells; 3.84-fold vs. eribulin ($p \leq 0.001$) and 9.54-fold vs. copanlisib ($p \leq 0.001$) in SUM159 cells; and 3.09-fold vs. eribulin ($p \leq 0.001$) and 3.05-fold vs. copanlisib ($p \leq 0.001$) in BCX-010 cells. Furthermore, to assess the potential toxicity of the combination treatment to non-tumorigenic cells, we also examined the effect of the treatment on the growth of normal breast epithelial cell line MCF10A. As shown in Supplementary Figure S2A, no synergistic effects were observed in MCF10A cells when eribulin was combined with everolimus or copanlisib, suggesting that the synergistic effect is tumor cell specific.
Next, we examined the synergistic anti-proliferation effect of eribulin combined with everolimus or copanlisib in BCX-010 and SUM149 cells using an ex vivo (patient-derived xenograft fresh tumor slice) model. As shown in Figure 4B, compared to eribulin or everolimus monotherapy, combination therapy with eribulin and everolimus reduced the viability of BCX-010 cells by $69.87\%$ vs. eribulin ($$p \leq 0.0178$$) and by $53.47\%$ vs. everolimus ($$p \leq 0.1199$$); the combination therapy also reduced the viability of SUM149 cells by $31.36\%$ vs. eribulin ($$p \leq 0.0144$$) and by $11.10\%$ vs. everolimus ($$p \leq 0.0656$$). Similarly, compared to eribulin or copanlisib monotherapy, the combination of eribulin with copanlisib significantly reduced the viability of BCX-010 cells by $68.41\%$ vs. eribulin ($$p \leq 0.0213$$) and by $58.79\%$ vs. copanlisib ($$p \leq 0.0417$$); the combination therapy also reduced the viability of SUM149 cells by $32.93\%$ vs. eribulin ($p \leq 0.0001$) and by $5.38\%$ vs. copanlisib ($$p \leq 0.0233$$).
These results clearly demonstrate that the inhibition of the PI3K/mTOR pathway effectively enhances the anti-tumor efficacy of eribulin in vitro. Moreover, the cell lines harboring PTEN or PIK3CA mutations showed a similar synergistic response to that of the wild-type cell lines, indicating that these mutations do not impact this synergistic effect.
## 3.5. Combination of Eribulin with Inhibitors of Target Kinases Arrested Cell Cycle Progression and Induced Apoptosis in TNBC Cells
To define the mechanisms of synergy between eribulin and mTOR/PI3K inhibition, we first examined the effects of combination treatments on the expression of phosphorylated Akt (pAkt), a key mediator of the PI3K/Akt/mTOR pathway [35]. Treatment with copanlisib alone reduced the expression of pAkt (Figure 5A), but no further reduction in pAkt was observed following treatment with copanlisib combined with eribulin (Figure 5A). We also examined the effects of combination treatment on the expression of phosphorylated H2AX (pH2AX), a biomarker of DNA damage [36]. Treatment with eribulin or everolimus alone increased the expression of pH2AX (Figure 5A); however, no further increase in pH2AX was observed following treatment with eribulin combined with everolimus or with copanlisib (Figure 5A). These data suggest that the synergistic effects of the combination treatment of eribulin with everolimus or with copanlisib were independent of pAkt or pH2AX.
We next examined whether the synergistic anti-proliferation effect of combination treatment was a result of cell cycle arrest and further induction of apoptosis. As shown in Figure 5B, compared to eribulin alone or everolimus alone, the combination of eribulin with everolimus increased the sub-G1 population by $7.29\%$ and $12.96\%$, respectively, in SUM149 cells and increased the G2M phase by $22.62\%$ and $40.36\%$, respectively, in BCX010 cells. Similarly, compared to eribulin alone or copanlisib alone, the combination of eribulin with copanlisib increased the sub-G1 population by $15.08\%$ and $20.55\%$, respectively, in SUM149 cells and increased the G2M phase by $11.07\%$ and $30.44\%$, respectively, in BCX-010 cells. These results suggest that the synergistic anti-proliferation effects of the combination treatment of eribulin plus everolimus or copanlisib are a result of cell cycle arrest.
To determine whether this cell cycle arrest leads to apoptotic cell death, we examined the effect of combination treatment on apoptosis induction. As shown in Figure 5A, compared to eribulin, everolimus, or copanlisib monotherapies, the combination of eribulin with everolimus or with copanlisib increased the expression of cleaved PARP in both BCX-010 and SUM149 cells, indicating the induction of apoptosis. The induction of apoptosis by combination treatments was further confirmed by the increased caspase $\frac{3}{7}$ activity in the treated cells. As shown in Figure 5C, the combination of eribulin with everolimus significantly increased caspase $\frac{3}{7}$ activity 1.45-fold vs. eribulin ($p \leq 0.01$) and 2.16-fold vs. everolimus ($p \leq 0.0001$) in BCX-010 cells, and 1.23-fold vs. eribulin ($p \leq 0.05$) and 1.84-fold vs. everolimus ($p \leq 0.001$) in SUM149 cells. Similarly, the combination of eribulin with copanlisib significantly increased caspase $\frac{3}{7}$ activity 2.17-fold vs. eribulin ($p \leq 0.001$) and 2.53-fold vs. copanlisib ($p \leq 0.001$) in BCX-010 cells, and 1.61-fold vs. eribulin ($p \leq 0.01$) and 1.59-fold vs. copanlisib ($p \leq 0.01$) in SUM149 cells. To assess the potential toxicity of the combination treatment to non-tumorigenic cells, we also examined the effect of treatments on caspase $\frac{3}{7}$ activity in MCF10A cells. Compared to eribulin, everolimus, or copanlisib monotherapies, the combination of eribulin with everolimus or copanlisib did not enhance eribulin-induced caspase $\frac{3}{7}$ activation in MCF10A cells (Supplementary Figure S2B), suggesting that the combination does not enhance eribulin-induced apoptosis in non-tumorigenic cells. Furthermore, pre-treatment with Z-VAD-FMK (a pan-caspase inhibitor) completely inhibited the combination treatment–induced activation of caspase $\frac{3}{7}$ in both BCX-010 and SUM149 cells (Figure 5C). Our results suggest that the synergistic anti-proliferation effect of this combination treatment is a result of the induction of apoptosis, independent of pAkt and pH2AX.
## 3.6. Combination with Inhibitors of Target Kinases Enhanced Inhibitory Activity of Eribulin against Cell Migration In Vitro
In addition to assessing the synergistic anti-proliferation effect of eribulin combined with the inhibitors of the PI3K/mTOR pathway, we examined the synergistic impact of the combination treatment on the motility of TNBC cells using a Transwell assay. As shown in Figure 6, compared to eribulin or everolimus monotherapies, the combination of eribulin with everolimus reduced migration by $54.61\%$ ($p \leq 0.0001$) and $58.86\%$ ($p \leq 0.001$), respectively, in SUM149 cells and by $69.02\%$ and $55.00\%$, respectively ($p \leq 0.0001$ for both), in BCX-010 cells. Similarly, compared to eribulin or copanlisib monotherapies, the combination of eribulin with copanlisib reduced migration by $55.52\%$ ($p \leq 0.0001$) and $52.11\%$ ($p \leq 0.001$), respectively, in SUM149 cells and by $56.77\%$ and $54.07\%$, respectively ($p \leq 0.0001$ for both), in BCX-010 cells. This result suggests that, in addition to synergistically inhibiting cell growth, the combination of eribulin with everolimus or copanlisib also inhibits the motility of TNBC cells, indicating the potential applications of this approach in controlling both tumor growth and metastasis.
## 4. Discussion
On the basis of the findings of our high-throughput kinome library RNAi screening in SUM149 cells, we extended the findings to other TNBC and TN-IBC cells and found that the combination of eribulin with inhibitors targeting the PI3K/Akt/mTOR and the MAPK/JNK pathways showed a synergistic anti-proliferation effect in those cells in vitro. Among the kinase inhibitors, the agents targeting PI3K or mTOR signaling showed the strongest synergistic effect with eribulin by inducing apoptotic cell death. These data suggest that a novel combination treatment of eribulin with everolimus or copanlisib may be promising for patients with TNBC.
PI3K is highly expressed in $40\%$ of TNBC, and its expression is marginally higher in TNBC than in hormone receptor-expressing (HR+) breast cancer [37]. A high expression of PI3K is correlated with a larger tumor size, lymph node metastases, advanced tumor stage in TNBC [37], and unfavorable outcomes in various solid tumors [38,39,40,41]. The PI3K/mTOR pathway is also strongly activated in IBC tumors [42], and the PI3K/Akt and PI3K/mTOR pathways are crucial for IBC invasion [43,44]. In addition, PIK3CA is the second most commonly mutated gene after TP53 in both TNBC ($16\%$) and IBC ($29.5\%$) [11,45,46]. Dysregulation of the PI3K/Akt/mTOR pathway has been implicated in genomic instability, uncontrolled proliferation, metabolic reprogramming, and resistance to therapies [14,47,48,49]. Therefore, the PI3K/Akt/mTOR pathway has been considered one of the most attractive targets for cancer treatment.
Multiple PI3K inhibitors have been developed and tested in preclinical and clinical studies. However, their efficacy as therapeutic agents is far from what is expected because of the coexistence of various mutations, compensatory feedbacks, or treatment-associated toxicity [50]. Therefore, PI3K inhibitors have been tested in combination with other drugs. For instance, the combination of buparlisib, a pan-PI3K inhibitor, with hormonal therapy showed a modest response in advanced HR+/HER2− breast cancer but displayed significant toxic effects [51]. A PI3Kα-targeting inhibitor, alpelisib, with a better toxicity profile, has been developed and is being evaluated in clinical trials in patients with HR+/HER2− metastatic breast cancer [52,53]. In a phase III clinical trial, compared to treatment with fulvestrant and placebo, treatment with alpelisib and fulvestrant increased the response rate and prolonged progression-free survival (PFS) in patients with PIK3CA-mutated HR+/HER2− advanced breast cancer (hazard ratio for progression or death, 0.65; $95\%$ confidence interval, 0.50-0.85; $p \leq 0.001$) [53]. In the SOLAR-1 trial, the combination of alpelisib and fulvestrant increased the median overall survival of patients with PIK3CA-mutated HR+/HER2− advanced breast cancer compared to those treated with fulvestrant and a placebo (39.3 vs. 31.4 months; hazard ratio, 86; $95\%$ confidence interval, 0.64–1.15; $$p \leq 0.15$$), although the analysis did not cross the prespecified boundary for statistical significance [54]. However, in the phase II/III BELLE-4 trial, patients with TNBC who were treated with buparlisib plus paclitaxel had a shorter PFS than those treated with paclitaxel alone (5.5 vs. 9.3 months; hazard ratio, 1.86; $95\%$ confidence interval, 0.91–3.79) [55]. Moreover, patients with PIK3CA mutations did not show any survival benefit from the combination treatment (hazard ratio, 1.17; $95\%$ confidence interval, 0.63–2.17) [55]. Lehmann et al. reported that PIK3CA mutations were highly clonal and occurred more frequently in androgen receptor–positive (AR+, $40\%$) TNBC vs. AR− ($4\%$) TNBC [56], and patients with AR+ TNBC were less likely to benefit from chemotherapy. Therefore, the frequency of PIK3CA mutations in the TNBC molecular subtype may account for the inconsistent prognostic outcomes in clinical trials. Currently, the ongoing randomized EPIK-B3 trial is being conducted to assess the efficacy and safety of nab-paclitaxel combined with alpelisib for patients with advanced TNBC with either PIK3CA-activating mutations or PTEN loss (NCT04251533). Our results here demonstrate that the inhibition of PI3K signaling effectively enhances the anti-tumor efficacy of eribulin in vitro and ex vivo. However, the cell lines harboring PTEN or PIK3CA mutations showed a similar synergistic response to that of the wild-type cell lines, indicating that these mutations do not impact this synergistic effect.
mTOR is a key integrator of signals that control protein and lipid biosynthesis and growth factor–driven cell cycle progression [57]. mTOR was highly expressed in $44\%$ of TNBC, and the high expression of mTOR was correlated with a high pathological prognostic TNBC stage [37]. Expression levels of mTOR were significantly higher in TNBC than in HR+ tumors, and high mTOR expression was associated with advanced tumor stage [37]. Everolimus, a derivative of rapamycin (sirolimus), inhibits mTOR activity by binding to its intracellular receptor FKBP12 to prevent the downstream signaling required for cell cycle progression and cell proliferation [58]. In the BOLERO-2 phase III study, the combination of everolimus with exemestane improved outcomes of patients with ER+/HER2− metastatic breast cancer. At an interim analysis, the combination treatment improved PFS by 4 months compared to exemestane plus a placebo (6.9 months vs. 2.8 months; hazard ratio, 0.43; $95\%$ confidence interval, 0.35–0.54; $p \leq 0.0001$) [59]. At the final analysis after a median follow-up of 18 months, the median PFS was 7.8 for everolimus with exemestane vs. 3.2 months for exemestane plus placebo (hazard ratio, 0.45; $96\%$ confidence interval 0.38–0.54; $p \leq 0.0001$) [60]. Based on a central assessment, the median PFS was 11.0 months for the combination vs. 4.1 months for exemestane plus placebo ($p \leq 0.0001$); this translates into a $62\%$ risk reduction (hazard ratio, 0.38) [60]. The combination of everolimus with exemestane was approved by the FDA for the treatment of HR+/HER2− metastatic breast cancer. In a phase II study in patients with metastatic TNBC, the combination of everolimus and carboplatin demonstrated a clinical benefit rate of $36\%$ and a median PFS of 3 months [61]. However, in a recently completed phase II trial in patients with TNBC, the addition of everolimus to standard neoadjuvant combination chemotherapy did not provide the expected benefit, as no significant differences were found between the everolimus-treated and nontreated groups in terms of 12-week response rates ($47.8\%$ vs. $29.6\%$; $$p \leq 0.075$$) and pathological complete response ($30.4\%$ vs. $25.9\%$; $$p \leq 0.76$$) [62]. The different clinical outcomes of combinations of everolimus with different regimens underlines the need for the careful selection of patients who may benefit from such treatments. Not all patients will respond to this combination treatment, even when patients seem to have similar molecular characteristics of subtypes of breast cancer.
The suppression of apoptosis is one of the hallmarks of tumor progression and drug resistance [63,64]. An effective approach for cancer treatment is to reactivate apoptosis in cancer cells. Thus, apoptosis has emerged as a critical endpoint for cancer treatment. Moreover, in breast cancer, PI3K/Akt/mTOR pathway activation is one of the main causes of resistance to antitumor therapies [65] and thus is an important target for improving the sensitivity of tumors to antitumor therapies. Hu et al. found that PIK3CA mutations triggered the sustained activation of PI3K/AKT/mTOR signaling and led to the inhibition of apoptosis in TNBC [14]. They hypothesized that agents targeting PIK3CA mutations and other molecules downstream of the pathway might enhance chemotherapeutic sensitivity and accelerate tumor cell apoptosis. In support of their findings, our study showed that copanlisib, which targets PI3Kα and δ isoforms, and the mTOR-targeting agent everolimus enhanced the antitumor efficacy of eribulin in both PIK3CA-mutated and PIK3CA wild-type TNBC cell lines by inducing apoptotic cell death. The results obtained using cell lines were further confirmed with fresh tumor tissue slices of TNBC cell xenografts collected from humanized mice. Fresh tumor tissues represent a more accurate in vitro model for evaluating the antitumor efficacy of drugs because of several advantages, e.g., stable gene expression profiles [66], a high degree of correlation between genetic mutations and sensitivity to targeted therapies [67], and better reproducibility [68]. These results indicate that targeting PI3K/Akt/mTOR signaling may improve the efficacy of eribulin in patients with TNBC.
However, there are several limitations of this study. These include the lack of knowledge on the association of TNBC molecular subtypes with responses to eribulin in the clinic; the correlations between [1] TNBC cell sensitivity to the combination treatment of eribulin with everolimus or copanlisib and [2] TNBC molecular subtypes, as well as [3] the genomic alterations in the PI3K/Akt/mTOR pathway; and the molecular mechanisms underlying the antitumor synergy of eribulin combined with inhibitors of the PI3K/mTOR pathway in TNBC. Such studies are critical for the translation of the combination treatment to the clinic and for the selection of patients who would benefit from such a treatment.
## 5. Conclusions
TNBC is an aggressive set of diseases, and developing optimal combination therapies for these diseases is challenging. The PI3K/mTOR/AKT pathway has been identified as a potential target for the treatment of TNBC and for overcoming resistance to chemotherapies in these diseases. Our study demonstrates that targeting PI3K/mTOR/AKT signaling with PI3K inhibitors, such as copanlisib, or with mTOR inhibitors, such as everolimus, can increase sensitivity to eribulin treatment in TNBC. Future in vivo preclinical studies, ideally using a diversity of TNBC patient-derived xenograft models, are needed to confirm the synergistic effects of eribulin combined with drugs targeting PI3K/Akt/mTOR signaling in TNBC. The findings from these studies will lay a foundation for clinical trials testing the efficacy of this strategy in patients with TNBC.
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|
---
title: Glutamine Starvation Affects Cell Cycle, Oxidative Homeostasis and Metabolism
in Colorectal Cancer Cells
authors:
- Martina Spada
- Cristina Piras
- Giulia Diana
- Vera Piera Leoni
- Daniela Virginia Frau
- Gabriele Serreli
- Gabriella Simbula
- Roberto Loi
- Antonio Noto
- Federica Murgia
- Paola Caria
- Luigi Atzori
journal: Antioxidants
year: 2023
pmcid: PMC10045305
doi: 10.3390/antiox12030683
license: CC BY 4.0
---
# Glutamine Starvation Affects Cell Cycle, Oxidative Homeostasis and Metabolism in Colorectal Cancer Cells
## Abstract
Cancer cells adjust their metabolism to meet energy demands. In particular, glutamine addiction represents a distinctive feature of several types of tumors, including colorectal cancer. In this study, four colorectal cancer cell lines (Caco-2, HCT116, HT29 and SW480) were cultured with or without glutamine. The growth and proliferation rate, colony-forming capacity, apoptosis, cell cycle, redox homeostasis and metabolomic analysis were evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide test (MTT), flow cytometry, high-performance liquid chromatography and gas chromatography/mass spectrometry techniques. The results show that glutamine represents an important metabolite for cell growth and that its deprivation reduces the proliferation of colorectal cancer cells. Glutamine depletion induces cell death and cell cycle arrest in the GO/G1 phase by modulating energy metabolism, the amino acid content and antioxidant defenses. Moreover, the combined glutamine starvation with the glycolysis inhibitor 2-deoxy-D-glucose exerted a stronger cytotoxic effect. This study offers a strong rationale for targeting glutamine metabolism alone or in combination with glucose metabolism to achieve a therapeutic benefit in the treatment of colon cancer.
## 1. Introduction
Colorectal cancer (CRC), with 1.9 million new cases and 935,000 deaths in 2020, ranks third in incidence and second for mortality in both sexes worldwide [1]. Gene alterations [2] and some diseases, such as chronic inflammatory bowel disease [3] and type 2 diabetes [4], are predisposed to the development of CRC. In addition, some lifestyle habits have been recognized as risk factors for the onset of the disease, such as excess body weight [5], cigarette smoking [6], a sedentary lifestyle [7], the consumption of processed meats [8] and a low intake of dietary fiber [9,10]. The incidence in young adults under 50 has increased alarmingly in recent years, as reported by numerous studies [11,12,13,14]. The CRC stage notably influences survival at diagnosis: the 5-year survival rate ranges from $90\%$ if diagnosed in the early stages to $14\%$ if the cancer is already metastatic [14]. Therefore, a better understanding of the etiological mechanisms in order to improve prevention and early diagnosis has become necessary. The high proliferation rate of cancer cells leads to an increase in the demand for energy and bio-macromolecules. Most cancer cells rewire their metabolism to meet this increased requirement, and the reprogramming of energy metabolism has been recognized as a new hallmark of cancer [15]. Notably, several cancer cells become dependent on specific nutrients, including glutamine, and they exhibit glutamine addiction [16,17,18,19]. Glutamine is defined as a “conditionally” essential amino acid. Indeed, although it can be synthesized de novo by cells, it becomes essential in particular pathological conditions and highly proliferating cells, such as cancer cells [20]. Glutamine plays a pivotal role in numerous processes. In particular, it is important for mitochondrial metabolism as it fuels the tricarboxylic acid cycle (TCA) to produce energy [21,22,23]. Recently, glutamine addition has attracted attention as a therapeutic target to selectively affect cancer that depends on the availability of this amino acid to survive and grow, including colorectal cancer [19,24]. However, the overall metabolic deregulation underlying the effects induced by glutamine deprivation on colorectal cancer cells has not yet been clarified. Indeed, metabolomics could represent a promising approach for investigating the alterations implemented by the tumor to survive and grow, with the main goal of identifying early diagnostic biomarkers and therapeutic targets [25,26]. To contribute to this issue, the present work aimed to identify metabolic perturbations due to glutamine deprivation in colorectal cancer cells, exploring which metabolic pathways were modified and which strategies cancer cells put in place to overcome the glutamine deprivation. Moreover, the consequences on survival, proliferation and redox homeostasis caused by glutamine deprivation were highlighted.
## 2.1. Cell Culture
Caco-2 cells were kindly gifted by Prof. Monica Deiana (University of Cagliari, Cagliari, Italy). HCT116 cells were given by Dr. Giuseppina Sanna (University of Cagliari, Italy). HT29 cells were purchased from Elabscience®, Houston, TX, USA. SW480 cells were obtained from the cell bank ICLC (San Martino Polyclinic Hospital, Genova, Italy). *The* genetic background and the tumor of origin classification are reported in detail in Table 1. The cell lines were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) high glucose supplemented with $10\%$ heat-inactivated bovine serum (FBS, Life Technologies, Milan, Italy), 100 U/mL penicillin, 100 mg/mL streptomycin (Sigma-Aldrich, Milan, Italy), L-glutamine 4 mM (Euroclone, Milan, Italy) and sodium pyruvate 1 mM (Euroclone, Milan, Italy), and were maintained at 37 °C in a humidified $5\%$ CO2 atmosphere. Before being deprived of glutamine, the cells were grown for 4 days in a complete medium to reach an adequate number of cells in order to optimally perform all assays.
## 2.2. Growth Curves
The growth curves of CRC cells were obtained by performing MTT ((3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) tetrazolium) assay [32,33], which allows for identifying viable and metabolically active cells. Briefly, cells were seeded in 96-well plates (1 × 105 cells/mL; 100 μL/well) in a complete medium to allow for attachment. Subsequently, cells were deprived of glutamine. MTT assays were performed every day for a total of 4 days. Firstly, the medium was removed, and cells were rinsed twice with phosphate-buffered saline pH 7.4 (PBS, Euroclone, Pero, Italy). Thereafter, 50 µL of MTT solution (2 mg/mL in PBS) was added and left for 4 h at 37 °C. After that, the PBS was aspirated, and the derived blue-violet formazan was solubilized with 100 µL of DMSO (Sigma-Aldrich, Milan, Italy). The absorbance was measured at 570 nm, after 15 s of shaking, using a microplate reader (Infinite 200, Tecan, Salzburg, Austria). Data were expressed as absorbance at 570 nm ± standard deviation. All experiments were carried out in at least triplicate and repeated 3 times.
## 2.3. Colony Forming Assay
The proliferation capacity of CRC cells was evaluated through colony forming assay as described by Liang and colleagues [34]. Briefly, cells were seeded at low concentrations in 24-well plates, (1–2 × 103 cells/mL, 500 µL per well) in a complete medium and left to grow for 4 days. Then, cells were deprived of glutamine for a total of 6–10 days depending on cell lines. At this time, cells were fixed with 200 µL of ice-cold methanol for 20 min, rinsed with water and finally stained with a solution of $5\%$ crystal violet in $80\%$ methanol. After 5 min, cells were washed and air-dried overnight. Samples were solubilized with glacial acetic acid, and a microplate reader (Infinite 200, Tecan, Salzburg, Austria) was used to measure optical density at 570 nm, as reported by Wang and colleagues [35]. All experiments were carried out in at least triplicate and repeated 3 times.
## 2.4. Fluorescence-Activated Cell Sorting (FACS) Analysis
To investigate cell death, a flow cytometric analysis was performed. We used the cell apoptosis kit Annexin V/Propidium Iodide (PI) double staining uptake (Life Technologies, Monza, Italy). CRC cell lines (Caco-2, HCT116, HT29 and SW480) were seeded at 5 × 104 cells/mL in 6-well plates and cultured in a complete medium for 4 days. Subsequently, cancer cells were exposed to a complete medium or glutamine-deprived medium for additional 48 h. Next, they were washed with PBS and 100 μL of annexin binding buffer plus 5 μL of Annexin V and 1 μL of PI were added. After that, cells were incubated in the dark for 15 min at room temperature. Stained cells underwent flow cytometric analysis by measuring the fluorescence emission at 530 and 620 nm using a 488 nm excitation laser (MoFloAstrios EQ, Beckman Coulter, Brea, CA, USA) [33]. The evaluation of apoptosis was performed using Software Summit Version 6.3.1.1, Beckman Coulter, Brea, CA, USA. To explore the effect of glutamine starvation on the cell cycle, a flow cytometric analysis was performed using FxCycle™ PI/RNase Staining Solution kit (Life Technologies). The cells were seeded and left to grow for 4 days in 6-well plates (5 × 104 cells/mL) in a complete medium. Then, they were deprived of glutamine for 48 h. After trypsinization, the cells were washed with PBS and fixed in ethanol for 30 min. After that, the cells were collected and centrifuged. Pellet was washed with PBS, resuspended in a buffer containing PI and then incubated for 30 min. The DNA content was then detected using flow cytometry (MoFloAstrios EQ, Beckman Coulter, Brea, CA, USA) [36]. The analysis of cell cycle phase distribution was performed with Kaluza Flow Cytometry Analysis Software (Software Version 1.2, Beckman Coulter, Brea, CA, USA) by setting 3 gates in each single parameter histogram: G0/G1, S and G2/M.
## 2.5. Sample Preparation for Metabolomics Analysis
To evaluate metabolomics changes induced by glutamine starvation, intracellular metabolites of Caco-2, HCT116, HT29 and SW480 cells were extracted and analyzed using gas chromatography–mass spectrometry, as described by Santoru and colleagues [37]. Briefly, cells were seeded and left to grow for 4 days in 6-well plates (5 × 104 cells/mL) in a complete medium. Subsequently, cells were starved of glutamine for 48 h. After washing the cells twice with physiological solution, 500 µL of ice-cold $80\%$ methanol solution was used to extract hydrophilic metabolites. The extraction was carried out for 10 min on ice to limit the metabolic reactions and preserve the intracellular compounds. Afterward, cells were scraped and transferred in tubes. To ensure complete lysis of cell membranes, samples underwent 10 min of ultrasonication at 4 °C. Cell suspensions were centrifuged at 4500× g for 30 min at 4 °C. Thereafter, 400 μL of supernatant was aliquoted and dried overnight in an EppendorfTM Concentrator Plus. Next, 50 μL of a solution of methoxyamine in pyridine (10 mg/mL) (Sigma-Aldrich, St. Louis, MO, USA) was added to the dried pellet for 1 h at 70 °C. Subsequently, samples were derivatized with 100 μL of N-Methyl-N-(trimethylsilyl)-trifluoroacetamide, MSTFA, (Sigma-Aldrich, St. Louis, MO, USA) and incubated at room temperature for one hour. Finally, 50 μL of hexane was added to each sample and the solution was transferred to a vial for the GC-MS analysis.
## 2.6. Gas Chromatography-Mass Spectrometry Analysis
A 7890A gas chromatograph coupled with a 5975C Network mass spectrometer (Agilent Technologies, Santa Clara, CA, USA) equipped with a 30 m × 0.25 mm ID and fused silica capillary column, packaged with a 0.25 μM TG-5MS stationary phase (Thermo Fisher Scientific, Waltham, MA, USA), was exploited for metabolomic analysis. Samples were injected in splitless mode. The injector temperature was 250 °C whereas the transfer line was set at 280 °C. The carrier gas inside the column flowed at 1 mL/min rate. The programmed temperature was set as reported by Santoru and colleagues [37]: 60 °C for 3 min, then increased up to 140 °C at 7 °C/min and held at 140 °C for 4 min and finally raised to 300 °C at 5 °C/min and kept in isocratic mode at 300 °C for 1 min. Different sources were exploited for the identification of metabolites: NIST 08 (http://www.nist.gov/srd/mslist.cfm, accessed on 15 September 2022), GMD (http://gmd.mpimp/golm.mpg.de, accessed on 15 September 2022) mass spectra libraries and AMDIS software (Automated Mass Spectral Deconvolution and Identification System), freely available on www.amdis.net. Peak deconvolution, filtering, integration and normalization were performed using MassHunter Profinder Software from Agilent Technologies (La Jolla, CA, USA).
## 2.7. Glucose Uptake Assay
Glucose uptake was measured as previously described by Tronci et al. [ 33]. CRC cells were seeded in 96-well plates (1 × 105 cells/mL) in a complete medium and incubated at 37 °C in order for attachment. After 24 h, cells were cultured in the presence or absence of glutamine for 48 h. Then, cells were rinsed with PBS and treated with 100 µL of a 50 µM solution of the fluorescent glucose analog 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) amino]-2-deoxy-D-glucose (2-NBDG, N13195; ThermoFisher, Waltham, MA, USA) in PBS in the presence or absence of glutamine. After an incubation of 30 min, the excess of 2-NBDG was removed and replaced with 100 µL PBS. Emitted fluorescence proportional to glucose uptake was read with a microplate reader (Infinite 200, Tecan, Salzburg, Austria). An excitation wavelength of 485 nm and an emission wavelength of 530 nm was exploited. All experiments were carried out in at least triplicate and repeated 3 times.
## 2.8. GLUT1 Protein Expression by Immunofluorescence
CRC-derived cells were cultured on previously sterilized slides and placed in square tissue culture dishes (quadriPERM®, Sarstedt AG & Co, Nümbrecht, Germany) for 24 h in a complete medium and in a humidified incubator. Thereafter, the medium was replaced and cells were grown for 48 h in the presence or absence of glutamine. After that, cells were fixed with $4\%$ paraformaldehyde solution for 10 min at room temperature. As previously described [38], immunostaining was performed using rabbit polyclonal anti-GLUT1 (1:200; Abcam, CA, USA) antibody. The secondary antibody used was Alexa-conjugated (Alexa Fluor 488 or 594, Life Technologies) goat anti-rabbit IgG. To counterstain, nuclei 4′,6-diamidino-2-phenylindole (DAPI) was used. Images were obtained with an epifluorescence microscope (Olympus BX41) and charge-coupled device camera (Cohu), interfaced with the CytoVysion system (software 2.81 Applied Imaging, Pittsburg, PA, USA). Twenty randomly selected fields were acquired with a 20× objective for each cell line. The fluorescence intensity was determined by exploiting the Image J software (US National Institutes of Health, Bethesda, MD, USA).
## 2.9. 2-Deoxyglucose Treatment and MTT Viability Test
The inhibitory effect of 2-Deoxyglucose (2-DG) was evaluated in the presence or absence of glutamine using the MTT assay as follows. Briefly, cells were seeded at a density of 1 × 105 cells/mL in a 96-well plate and incubated to allow for attachment. Then, cells were grown in a medium deprived of glutamine or not for 48 h. After that, the medium was washed off and cells were treated with 2-DG (2.5 mM for Caco-2, HCT116 and HT29, 5 mM for SW480) in the presence or absence of glutamine for another 48 h. After incubation, cells were rinsed with PBS and 50 µL of MTT solution (2 mg/mL in PBS) was added and left for 4 h at 37 °C. The resulting formazan crystals were solubilized in 100 μL of DMSO. The absorbance was measured using a TECAN microplate reader (Infinite 200, Tecan, Salzburg, Austria) at 570 nm [33]. Viability was calculated as % of control (cells grown in complete medium) for each cell line. All experiments were carried out in at least triplicate.
## 2.10. Determination of Intracellular Aminothyol Levels
The ratio between the reduced and oxidized form of glutathione (GSH/GSSG) was determined with high-performance liquid chromatography coupled with an electrochemical detector (HPLC-ECD), as previously described [39]. Cells were grown 4 days in complete medium in 6-well plates (density of seeding of 1 × 105 cells/mL). After that, the medium was replaced, and cells were cultured in the presence or absence of glutamine for additional 48 h. Subsequently, cells were rinsed twice with PBS and extracted with 150 μL of $10\%$ meta-phosphoric acid and 150 μL of $0.05\%$ trifluoroacetic acid (Sigma-Aldrich, Milan, Italy) solution. The cell suspension was centrifugated and then the supernatant was injected into the HPLC system (Agilent 1260 infinity, Agilent Technologies, Palo Alto, Santa Clara, CA, USA) supplied with an electrochemical detector (DECADE II Antec, Leyden, The Netherlands) and an Agilent interface 35900E. A C-18 Phenomenex Luna with 5 μm particle size and 150 × 4.5 mm column was used. The mobile phase constituted $99\%$ water with $0.05\%$ TFA (v/v) and $1\%$ MeOH, with a flow rate of 1 mL/min. The oxidizing potential of the electrochemical detector was set at 0.74 V. GSH and GSSH standards were injected before and after the samples run to allow for identification.
## 2.11. Statistical Analysis
GC-MS data obtained from MassHunter Profinder were organized into data matrices, where the columns represent the variables (area of the chromatographic peak), and the rows represent the samples. To minimize the effects of variable dilution of the samples, the final dataset was normalized to the total area. Each feature underwent univariate statistical analysis using GraphPad Prism software (version 7.01, GraphPad Software, Inc., San Diego, CA, USA) to identify statistically significant variables. The statistical significance of all performed experiments was assessed using the Student t-test, and a p-value of <0.05 was considered to be statistically significant.
## 3.1. Glutamine Starvation Alters Growth Rate in Colorectal Cancer Cells
In order to investigate whether CRC cells were sensitive to glutamine deprivation, growth curves were evaluated. After seeding in a complete medium to allow for attachment, cells were grown in the presence or absence of glutamine, and viable cells were determined by an MTT assay every day. The results show that glutamine starvation significantly affected the growth rate in all studied CRC cell lines (Figure 1A–D). A significant decrease in viable cells was already highlighted on the first day of treatments in HCT116 and HT29 cells, whereas, in Caco-2 and SW480 cells, the statistical significance was reached after 48 h. After 3 days of starvation, the reduction in the growth in the glutamine deprivation condition was between approximately 40 and $50\%$ in comparison to the respective control for all CRC cell lines (Table 2). Based on these results, glutamine represents an important amino acid for growth and its deprivation reduces the proliferation rate of colorectal cancer cell lines.
## 3.2. Glutamine Starvation Reduces Proliferative Capacity in Colorectal Cancer Cells
The proliferation capacity during glutamine deprivation was evaluated with the colony-forming assay. Glutamine was essential for CRC cells to proliferate. Indeed, a significant reduction in the colony-forming ability was observed in all cell lines after starvation (Figure 2A–D). These results confirm that glutamine represented a pivotal amino acid, and its withdrawal altered the proliferation rate and growth capacity of colorectal cancer cells.
## 3.3. Glutamine Starvation Triggers Cell Death and G0/G1 Cell Cycle Arrest
Considering the decrease in the percentage of viable cells observed from the growth curves in the absence of glutamine, the influence of glutamine deprivation on apoptosis and necrosis was quantified using PI-Annexin V staining. In Caco-2 and HT29 cells, a significant decrease in the percentage of viable cells was observed upon glutamine deprivation (Figure 3A,C). In these cell lines, the necrotic percentage was higher in glutamine starvation than in the control condition, whereas only HT29 cells showed an increase in apoptotic cell death when cultured in the absence of glutamine (Figure 3C). In Caco-2, the mechanism of cell death by apoptosis was not involved, and, surprisingly, the apoptotic contribution was lower in the absence of glutamine compared to the control condition (Figure 3C). In SW480, the percentage of viable cells did not change when cells were deprived of glutamine; however, a significant increase in apoptotic percentage and a significant decrease in necrotic percentage were observed (Figure 3D). No effects of glutamine deficiency on the cell death of HCT116 cells were detected (Figure 3B). The percentage of viable, apoptotic and necrotic cells are detailed in Table 3. Because of these results, it was further investigated whether 48 h of glutamine starvation affected cell cycle progression by flow cytometry analysis. As shown in Figure 4A, 4B, 4C, 4D, glutamine withdrawal determined an accumulation of cells in the G0/G1 phase and a concomitant decrease in S and G2/M phases in all cell lines according to a significant decrease in the proliferation index (PI = (S + G2/M)/(G0/G1 + S + G2/M) *100) as reported in Table 4.
## 3.4. Metabolomic Alterations under Glutamine Deprivation
In order to investigate the metabolic alterations induced by glutamine deficiency, Caco-2, HCT116, HT29 and SW480 cells were grown in a complete or glutamine-deprived medium for 48 h. After this, hydrophilic intracellular metabolites were extracted and analyzed with GC-MS. Identified metabolites and statistical parameters are reported in Table 5. The metabolomic analysis showed a significant increase in D-glucose and D-galactose after glutamine starvation in all cell lines. Fructose and sorbose levels significantly increased in HT29 cells, whereas they decreased in Caco-2 cells. The glucose-6-phosphate level was higher in SW480 cells after starvation and ribose-5-phosphate was reduced in Caco-2, while mannose-6-phosphate decreased in Caco-2 and increased in SW480 cells. The GC-MS analysis showed a decrease in Krebs cycle intermediates. In particular, fumaric acid levels were lower in HCT116, HT29 and SW480 cells, while citric acid and malic acid concentrations were significantly lower in Caco-2 and HT29 cell lines. Lactic acid was reduced after glutamine starvation, especially in Caco-2, HCT116 and HT29 cells. The amino acidic pool was altered in glutamine withdrawal. In particular, glycine, phenylalanine, threonine and serine levels were significantly increased in all cell lines, whereas β-alanine, aspartic acid, glutamic acid and pyroglutamic acid amounts significantly decreased after starvation in all cell lines. Furthermore, aminomalonic acid and gamma-aminobutyric levels, tyrosine and valine were altered in Caco-2, HCT116 and SW480. Specifically, aminomalonic acid and gamma-aminobutyric acid decreased, whereas tyrosine and valine increased. Isoleucine, leucine and tryptophan levels increased after glutamine starvation in HCT116 and SW480 cells and creatinine was higher in Caco-2 and HCT116 cells, while alanine levels significantly decreased in Caco-2 and HT29 cell lines. The proline content was reduced only in HCT116 cells without glutamine. For polyols, a significant increase in myo-inositol was observed in all cell lines and the mannitol content was increased in Caco-2 cells and decreased in HCT116 cells, whereas the pantothenic acid content increased only in SW480 cells after starvation. The levels of some nucleosides or nitrogenous bases were reduced in glutamine withdrawal, especially adenosine monophosphate in Caco-2 and HT29, Uridine 5-monophosphate in HCT116 and 5′methylthioadenosine in Caco-2 cells. In addition, the glycerol-3-phosphate content increased after glutamine starvation in Caco-2, HCT116 and SW480 cells, while cholesterol levels increased in Caco-2 cells. Finally, the levels of beta-glycerophosphoric acid, myo-Inositol 1-phosphate, niacinamide and taurine showed no significant changes in glutamine-deprived conditions.
## 3.5. Glutamine Deprivation Altered Glucose Uptake and GLUT1 Expression
Considering the increase in sugar levels observed by the metabolomic analysis following glutamine deprivation, it was hypothesized that their increase could be due to an enhanced glucose uptake during starvation. Therefore, the glucose uptake was evaluated using a fluorescent analog, 2-NBDG. Furthermore, the expression GLUT1 glucose transporter was evaluated. A significant increase in 2-NBDG uptake was observed in Caco-2 and SW480 cells (Figure 5A,D), whereas only an increasing trend was detected in HCT116 and HT29 cell lines after 48 h of glutamine deprivation (Figure 5B,C).
Moreover, the GLUT1 was significantly over-expressed in Caco-2, HCT116 and SW480 cells after 48 h of glutamine starvation (Figure 6Ai,Bi,Di). Only HT29 cells showed a remarkable decrease in GLUT1 expression after glutamine starvation (Figure 6Ci). These results suggest that glutamine deprivation can alter glucose transport across the plasma membranes by inducing GLUT1 expression.
## 3.6. The Combined Treatment with Glutamine Deprivation and 2-Deoxy-D-Glucose Affected CRC Survival more than Glutamine Deprivation
Given the increased glucose avidity of cancer cells during glutamine starvation, it has been speculated that combining the starvation with a glycolysis inhibitor, 2-DG, could affect cancer cells’ survival and proliferation. The dose of 2-DG used is different for each cell line. Therefore, it was considered useful to use a concentration able to induce a decrease in vitality between 30 and $50\%$ compared to the control. For this purpose, the Caco-2, HCT116 and HT29 cells were treated with 2.5 mM 2-DG and SW480 cells with 5 mM 2-DG in the presence or absence of glutamine for 48 h. Cell viability was assessed using the MTT assay. Figure 7B–7D shows that the combination of the two treatments (2-DG and glutamine starvation) results in a significantly lower percentage of viable cells in comparison with both glutamine starvation and 2-DG treatment alone in HCT116, HT29 and SW480 cells. Only in Caco-2 cells does the combined treatment not show significant synergistic effects compared to glutamine deprivation alone. The result suggests that targeting glucose and glutamine metabolism simultaneously could represent a more effective strategy for suppressing the survival of colorectal cancer cells.
## 3.7. Glutamine-Deprivation-Induced Reduction in Antioxidant Defenses in CRC Cells
Glutamate synthesized from glutamine is one of the components of glutathione, an important cellular antioxidant [20]. Consequently, in order to evaluate the alterations in redox balance induced by glutamine starvation, the reduced and oxidized glutathione forms (GSH and GSSG, respectively) were evaluated by HPLC analysis. In all cell lines examined, a significant decrease in GSH/GSSG ratios was observed after 48 h of glutamine starvation compared with the respective control grown in a complete medium (Figure 8A–D). This observation highlights the role of glutamine in maintaining adequate antioxidant defenses.
## 4. Discussion
Glutamine fuels energetic and biosynthetic processes and ensures redox homeostasis in cells, playing a pivotal role, especially in high-proliferating cells [40,41]. In particular, cancer cells rewire glutamine metabolism and become addicted to this amino acid, such as CRC cells [16,17,42,43,44,45]. In this context, glutamine metabolism represents an intriguing target for investigation. Exploring and understanding how glutamine is involved in cancer cell survival, proliferation and redox homeostasis is essential for exploiting aberrant tumorigenic metabolism in the therapeutic field. In the present study, proliferation, survival, antioxidant species and the metabolic profile were investigated in four CRC cell lines. The results confirm that CRC cells were sensitive to glutamine starvation. Deprivation resulted in a marked antiproliferative effect, with a decrease in growth rate ranging from 40 to 50 percent in all cell lines. It has been demonstrated that glutamine deprivation can induce cell death or block cell proliferation depending on the cell line [40,45,46,47,48]. In this study, changes in the apoptosis and cell cycle of colon cancer cells grown in the absence of glutamine were examined. The results demonstrate that the depletion of glutamine inhibited cell proliferation in the colon cancer cells via apoptosis or necrosis, and induced cell cycle G0/G1 arrest. These observations are in agreement with previous data [40] and indicate that the anti-proliferative effects exerted by glutamine deprivation can be attributed to the induction of cell cycle arrest and cell death. Several mechanisms come into play in the activation of the apoptotic pathway following glutamine deprivation [49,50,51,52]. In our cells, cell death could be induced by the reduction in the reduced form of GSH, as observed through HPLC analysis. Moreover, in HCT116 cells, glutamine starvation does not induce cell death, but it is well-known that the absence of glutamine causes a distinct response in different cell types [53]. Instead, HCT116 cells reduced their proliferation rate by entering a quiescent state, as demonstrated by the augmentation of cells in the G0/G1 phase as demonstrated by others in different cell lines [54,55,56]. The decrease in the cell population in the synthetic and mitotic phases is consistent with the importance of glutamine in the overcoming of the G1 phase and the synthesis of nucleotides [54,57,58]. Overall, glutamine deprivation reduces proliferating cells, and, at the same time, the formation of cancer cell colonies is decreased in all cell lines. The results suggest an effort to overcome starvation by down-regulating cell cycle progression and avoiding cell death. Moreover, data demonstrated that cancer cells can adapt to overcome glutamine withdrawal through the adjustment of specific metabolic pathways. Moreover, the withdrawal of glutamine can induce a decrease in the levels of TCA cycle intermediates, as revealed by the GC-MS analysis. In particular, the level of citrate, fumarate and malate was significantly decreased in almost all cell lines after 48 h of glutamine deprivation. Moreover, the GC-MS analysis also displayed higher glucose levels in glutamine-deprived cells. To explain this increase, the glucose uptake was evaluated, as well as the expression of GLUT1, one of the most important glucose transporters. A strongly enhanced glucose uptake was observed in Caco-2 and SW480 cells, whereas, in HCT116 and HT29 cells, only an increasing trend was noted. Furthermore, the expression of GLUT1 was increased after glutamine starvation in Caco-2, HCT116 and SW480 cells. Surprisingly, GLUT1 expression was reduced in HT29 cells, despite increased intracellular glucose levels. This controversial result could be explained by the overexpression of GLUT3, another glucose transporter in the HT29 cell line as already observed by Kuo et al. [ 59]. Furthermore, it has been shown that cancer cell growth could be reduced by inhibiting both glucose transporters and glutamine metabolism, and this represents a successful strategy for cancer therapy [60,61]. Despite the higher glucose uptake, lactate levels were decreased after glutamine withdrawal. It is probable that the glycolytic rate, and, consequently, the energy production, were downregulated to exploit glucose for biosynthetic purposes. Moreover, glucose can be used to produce NAPDH through the pentose phosphate pathway [62], regenerate GSH from GSSG and counteract oxidative stress, as already proven by Cetinbas and colleagues [63]. In the pancreatic β-cell line during glutamine starvation, glucose’s carbons were used to synthesize glutamate, usually produced from glutamine [64,65]. As expected, the metabolomics analysis showed that the glutamate level and its cyclized form, pyroglutamic acid, were significantly decreased in glutamine deprivation conditions in all cell lines. Indeed, glutamate is directly produced from glutamine via deamination by GLS [66]. The threonine, tryptophan, tyrosine and valine levels were significantly higher in almost all studied cell lines after 48 h of glutamine starvation. Supposedly, glutamine absence triggered the uptake of exogenous amino acids, as observed by Chen and colleagues [67]. In addition, glycine and serine intracellular concentrations were markedly enhanced in all cell lines after glutamine withdrawal. This is in accordance with Tanaka and colleagues, who found a raised level of serine in glutamine-deprived glioblastoma cells [68]. Serine and glycine amino acids participate in several processes, including amino acids, purines, antioxidants synthesis and the folate cycle through one-carbon metabolism [69,70]. The enhanced levels of these amino acids could support cells in maintaining redox homeostasis in glutamine deprivation conditions. In addition, in our colon cancer cells, the level of beta-alanine is altered following glutamine deprivation; specifically, its concentration is significantly decreased in starved cells. The beta-alanine level was found to be significantly upregulated in human CRC tissues [71]. Furthermore, Hutschenreuther and colleagues correlated beta-alanine acid with lactate concentration and with glycolytic activity [72]. This is in agreement with the decrease in lactate production in all colon cancer cell lines. In addition, glutamine is mainly converted into alanine and lactate and then carried out in the extracellular space [73,74]. In glutamine absence, pyruvate or alanine refuels the Krebs cycle through an anaplerotic flux to compensate for glutamate deficiency. This process has been suggested as a resistant mechanism for pharmacological glutaminase inhibition in cancer cells [75,76,77]. These observations could underlie the pronounced decrease in alanine and lactate seen in our glutamine-deprived cells. Thereby, this mechanism could provide energetic and biosynthetic substrates, without, however, overcoming the inhibition caused by glutamine withdrawal. Moreover, the metabolomic analysis highlighted a significant decrease in myo-inositol levels in cells deprived of glutamine. Myo-inositol plays a crucial role in cell survival and proliferation [78]. This should be consistent with the lower proliferation capacity observed. As noted from metabolomic analysis and glucose uptake assay, cells deprived of glutamine uptook more glucose. Thus, it is possible to hypothesize that, during starvation, tumor cells put in place this strategy to overcome glutamine depletion and survive. As expected, glutamine deprivation combined with glucose metabolism inhibition with 2-DG exerted a greater cytotoxic effect than the treatments considered individually in all studied CRC cell lines. As reported by Le and colleagues, glutamine compensates for energetic and biosynthetic purposes when the tumor cells are glucose-deficient [79]. Conversely, glutamine depletion led to an increased glucose utilization [65]. At the same time, blocking both glucose and glutamine utilization markedly affected the cell viability [60]. Therefore, an imbalance of glutaminolysis and glucose metabolism could cause metabolic distress [80]. It is well known that glutamine is indirectly involved in maintaining cellular redox homeostasis. Indeed, glutamine represents the primary precursor of glutamate, which, in turn, is a component of glutathione, one of the major cellular antioxidant species [81]. The metabolomic analysis showed a significant decrease in glutamate content (and its cyclized form, pyroglutamic acid) after 48 h of glutamine withdrawal in all CRC cell lines. Moreover, a significant decrease in antioxidant species, as shown by the change in the ratio between GSH/GSSG, indicates an increased oxidative condition. The oxidative stress damage could be responsible for the decreased cell proliferation and apoptosis/necrosis induction, although the underlying mechanism is still unclear [82]. Overall, although the CRC cell lines studied harbor the common genetic mutations (APC, KRAS, PIK3CA and TP53 genes) associated with the different tumor stages [83], in our hands, glutamine starvation did not determine relevant differences in survival, proliferation, oxidative homeostasis and metabolism. These in vitro results suggest that colon cancer cells, independent of genetic and phenotypic features, implement a similar strategy to overcome the withdrawal of this nutrient. Nevertheless, in vivo studies are needed to confirm this hypothesis.
## 5. Conclusions
Glutamine represents a pivotal metabolite for tumor viability and proliferation by fulfilling the metabolic and biosynthetic request and by regulating the redox homeostasis counteracting the increase in oxidative species during rapid proliferation. Indeed, our results suggest that glutamine depletion deeply altered energy metabolism, the amino acid content and antioxidant defenses, and induced similar metabolic alterations in colon cancer cells. These metabolic perturbations could be responsible for the decreased cell proliferation and apoptosis/necrosis independently by genetic and phenotypic features of colon cancer. This suggests that tumor cells try to overcome starvation by putting in place a common metabolic rewiring. This offers a strong rationale for targeting glutamine and glucose metabolism and regulating the redox status to achieve significant therapeutic benefits in the clinic.
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|
---
title: Metallothionein 3 Inhibits 3T3-L1 Adipocyte Differentiation via Reduction of
Reactive Oxygen Species
authors:
- Yuankuan Li
- Sung Ho Lee
- Meiyu Piao
- Hyung Sik Kim
- Kwang Youl Lee
journal: Antioxidants
year: 2023
pmcid: PMC10045306
doi: 10.3390/antiox12030640
license: CC BY 4.0
---
# Metallothionein 3 Inhibits 3T3-L1 Adipocyte Differentiation via Reduction of Reactive Oxygen Species
## Abstract
Metallothionein 3 (MT3), also known as a neuronal growth-inhibitory factor, is a member of the metallothionein family and is involved in a variety of biological functions, including protection against metal toxicity and reactive oxygen species (ROS). However, less is known about the role of MT3 in the differentiation of 3T3-L1 cells into adipocytes. In this study, we observed that MT3 levels were downregulated during 3T3-L1 adipocyte differentiation. Mt3 overexpression inhibited adipocyte differentiation and reduced the levels of the adipogenic transcription factors C/EBPα and PPARγ. Further analyses showed that MT3 also suppressed the transcriptional activity of PPARγ, and this effect was not mediated by a direct interaction between MT3 with PPARγ. In addition, Mt3 overexpression resulted in a decrease in ROS levels during early adipocyte differentiation, while treatment with antimycin A, which induces ROS generation, restored the ROS levels. Mt3 knockdown, on the other hand, elevated ROS levels, which were suppressed upon treatment with the antioxidant N-acetylcysteine. Our findings indicate a previously unknown role of MT3 in the differentiation of 3T3-L1 cells into adipocytes and provide a potential novel target that might facilitate obesity treatment.
## 1. Introduction
Obesity has been gradually turning into a global epidemic with an increasing prevalence among adults and children [1,2,3]. By 2025, the incidence of obesity is predicted to be more than $21\%$ in women and $18\%$ in men [4]. Obesity is associated with an increased risk of developing various diseases, including several types of cancer [5,6,7], type 2 diabetes [8], and cardiovascular disease [9], which are the primary causes of death worldwide. Therefore, it is crucial to develop effective interventions for the prevention and treatment of obesity. Adipocyte differentiation, a critical event in the progression of obesity, is an intricate process tightly controlled by various transcription factors, including the members of the CCAAT/enhancer binding protein (C/EBP) family and peroxisome proliferator-activated receptor γ (PPARγ) [10,11]. C/EBPβ and C/EBPδ are important regulators of the initial phases of adipocyte differentiation; C/EBPβ allows the growth-arrested preadipocytes to reinitiate mitotic clonal expansion (MCE) [12,13]. Then, C/EBPβ and C/EBPδ synergistically promote the expression of C/EBPα and PPARγ upon stimulation with a differentiation cocktail [14]. PPARγ is considered to be the dominant inducer of adipocyte differentiation due to its indispensable role in adipogenesis; its absence is sufficient to inhibit adipocyte differentiation [15,16]. C/EBPα, a critical downstream effector of PPARγ, maintains the expression of PPARγ and functionally synergizes with PPARγ to induce the expression of adipogenic genes functioning in the late stages of adipocyte differentiation, such as adiponectin and fatty acid binding protein 4 (FABP4, also known as aP2) [17,18].
Metallothioneins (MTs) are metal-binding proteins of low molecular weight (6–7 kDa) with a high cysteine content ($30\%$). The four major MTs are MT1, MT2, MT3, and MT4 [19,20,21]. Among them, MT1 and MT2 are widely expressed in mammals, whereas MT3 is primarily found in the brain, and MT4 is expressed only in certain squamous epithelia [19,22]. MTs are associated with multiple physiological functions, including detoxification of heavy metals, maintenance of metal ion homeostasis (especially zinc and copper), and protection against DNA damage and oxidation [23,24,25,26]. MTs play key roles in signaling pathways relevant to several disease conditions, including cancer and neurodegenerative diseases [27,28]. Multiple studies have shown that MTs are also closely associated with obesity. MT$\frac{1}{2}$-knockout male mice fed a high-fat diet (HFD) displayed enhanced features of obesity (increased fat accumulation and obese (ob) gene expression) compared with wide mice [29]; this finding was further confirmed in the MT$\frac{1}{2}$-knockout female mice [30]. MT3-knockout male mice also exhibited elevated weight gain with aging compared with wild-type mice, which was associated with reduced levels of leptin receptors [31].
Reactive oxygen species (ROS) are essential mediators that are not only linked to aging and pathological conditions, such as cancer, diabetes, and obesity, but are also required for multiple physiological processes essential for life [32,33]. Previous studies have indicated that oxygen consumption and production of intracellular and mitochondrial ROS increase during 3T3-L1 adipocyte differentiation [34,35]. In addition, oxidative stress was found to induce the accumulation of lipid droplets through SREBP1c activation in HepG2 cells [36]. Moreover, ROS can promote adipocyte differentiation in 3T3-L1 preadipocytes, which is mediated by advancing MCE [37]. These observations indicate that ROS act as crucial factors in adipocyte differentiation. Intriguingly, the ROS scavenging activity of MT3, which is rich in cysteine residues with a high potential to interact with ROS, is considered to be one of its major functions [38], suggesting that MT3 may be closely related to adipocyte differentiation.
In this study, we first found that MT3 was downregulated in the process of 3T3-L1 adipocyte differentiation. To investigate the role of MT3 in this process, we overexpressed MT3 in 3T3-L1 cells. Our data revealed that MT3 can suppress 3T3-L1 adipocyte differentiation indirectly by inhibiting the transcriptional activity of PPARγ and by reducing ROS levels in the early stages of adipogenesis, thus providing a potential novel target for the prevention and treatment of obesity.
## 2.1. Cell Culture
Mouse preadipocyte 3T3-L1 cells and human embryonic kidney (HEK) 293T cells were obtained from the American Type Culture Collection. The 3T3-L1 cells were cultured in Dulbecco’s modified *Eagle medium* (DMEM, #12100046, Gibco™, Carlsbad, CA, USA) supplemented with $10\%$ bovine calf serum (BCS, Welgene Inc., Daegu, Republic of Korea) and $1\%$ antibiotic–antimycotic (#15240062; Gibco™). HEK 293T cells were maintained in DMEM containing $10\%$ fetal bovine serum (FBS, Welgene Inc.) and $1\%$ antibiotic–antimycotic at 37 °C in a humidified incubator with $5\%$ CO2.
## 2.2. 3T3-L1 Adipocyte Differentiation
After reaching confluence, the 3T3-L1 cells were maintained for 48 h. Then, the growth medium was replaced with the differentiation medium, consisting of DMEM supplemented with $10\%$ FBS and a differentiation cocktail with 0.5 mM 3-isobutyl-1-methylxanthine (Sigma, St. Louis, MO, USA), 10 μg/mL insulin (Sigma), and 1 μM dexamethasone (Sigma) on day 0. Two days after hormonal induction (on day 2), the differentiation medium was replaced with DMEM supplemented with $10\%$ FBS and 10 μg/mL insulin. The media was replaced every two days with DMEM supplemented with $10\%$ FBS. On day 8, the lipid droplets were observed in the cells, which were used for further experiments.
## 2.3. Plasmids and Transfection
The HA-tagged MT3 plasmid or Myc-tagged PPARγ plasmid were constructed in a CMV promoter-derived mammalian expression vector (pCS4+). For MT3 knockdown experiments, oligonucleotides for small hairpin RNA (shRNA) were generated by targeting a 19-base pair sequence of the mouse MT3 gene. shMT3#1: sense 5′-GAT CCC CCC AAG GAC TGT GTG TGC AAT TCA AGA GAT TGC ACA CACA GTC CTT GGT TTTTA-3′, antisense 5′-AGC TTA AAA ACC AAG GAC TGT GTG TGC AAT CTC TTG AAT TGC ACA CAC AGT CCT TGG GGG-3′; shMT3#2: sense 5′-GAT CCC CGC AAG TGC AAG GGC TGC AAA TTT CAA GAG AAT TTG CAG CCC TTG CAC TTG C TTTTTA-3′, antisense 5′-AGC TTA AAA AGC AAG TGC AAG GGC TGC AAA TTC TCT TGA AAT TTG CAG CCC TTG CAC TTG CGGG-3′. Sense and antisense oligonucleotides were annealed and ligated into a pSuper-retro vector (Oligoengine, Seattle, WA, USA). Both overexpression and knockdown experiments in the HEK 293T cells and 3T3-L1 cells were performed by using polyethyleneimine (PEI) (Polysciences, Inc., Warrington, PA, USA).
## 2.4. Oil Red O Staining
Oil Red O staining was performed to measure the extent of adipocyte differentiation. Briefly, cells were washed two times with phosphate-buffered saline (PBS) and fixed with $10\%$ formalin at room temperature for 30 min. Next, the cells were washed with PBS twice and incubated with $60\%$ isopropanol for 1 min. Then, 250 μL (for a 24-well plate) of $0.5\%$ Oil Red O staining solution (O0625; Sigma, St. Louis, MO, USA) was added to each well to cover the cell monolayer, and the cells were incubated at room temperature for 25 min on a shaker. The staining solution was carefully aspirated, and the cells were washed with PBS three times. An inverted microscope and NIS-Elements software (Niko Company, Fukuoka, Japan) were used to visualize lipid droplet accumulation. For the quantification of lipid accumulation, the stain was extracted in isopropanol, and the absorbance was measured at 510 nm using an Epoch microplate reader (BioTek Company, New Castle, DE, USA).
## 2.5. Triglyceride (TG) Colorimetric Assay
For cellular triglyceride determination, fully differentiated 3T3-L1 cells were washed twice with PBS and collected by cell scraper. They were centrifuged at 1000× g for 10 min, and then the supernatant was removed and the cell sediment was retained. The cells added isopropanol into the sediment according to the cell number (2 × 106) ratio: isopropanol (μL) = 1:200. Then, centrifuging was performed at 10,000× g for 10 min at 4 °C, and the supernatant was taken for detention. Cellular triglyceride content was determined by the TG Colorimetric Assay Kit (E-BC-K261-M; Elabscience Biotechnology Inc., Houston, TX, USA).
## 2.6. Luciferase Reporter Assays
HEK 293T cells were seeded in a 24-well plate and transfected with combinations of plasmids expressing indicated proteins (MT3 and PPARγ), luciferase reporters (aP2-Luc or PPRE-Luc), and CMV promoter-driven β-galactosidase (β-gal). PPRE-Luc includes the consensus PPAR response element (PPRE), and aP2-Luc contains a promoter region of adipocyte aP2 that includes PPREs [39]. A β-gal plasmid was used to monitor transfection efficiency. The cells were treated with the PPARγ agonist rosiglitazone 24 h after transfection and were lysed to determine the activities of luciferase reporters using a luciferase reporter assay kit (Promega, Madison, WI, USA).
## 2.7. Immunoblotting
Cells were lysed in an ice-cold lysis buffer ($1\%$ NP-40, 25 mM HEPES at pH 7.5, $10\%$ glycerol, $0.25\%$ sodium deoxycholate, 1 mM EDTA, 1 mM Na3VO4, 25 mM NaF, 150 mM NaCl, 10 mg/mL aprotinin, 10 mg/mL leupeptin, and 250 mM phenylmethanesulfonyl fluoride). For immunoblotting (IB), the samples (50–80 μg of total protein per sample) were run on sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred onto polyvinylidene fluoride membranes. Then, membranes were incubated with primary antibodies at 4 °C overnight. The primary antibodies used are shown in Table 1. After incubation with appropriate horseradish peroxidase-conjugated secondary antibodies, an Immobilon Western Chemiluminescent HRP Substrate (WBKLS0500, Millipore, Billerica, MA, USA) was used to visualize the protein bands, and the images were captured using an AmershamTM ImageQuantTM 800 system (GE Healthcare Life Sciences, Marlborough, MA, USA).
## 2.8. Immunoprecipitation
For immunoprecipitation, supernatants of centrifuged lysates were incubated with appropriate antibodies at 4 °C overnight on a shaker. Next, protein A-Sepharose beads (17096303, GE Healthcare) were added (40 μL per sample). The samples were incubated for 2 h at 4 °C, centrifuged (3000 rpm) to precipitate the beads, and washed with lysis buffer three times at 4 °C. Finally, the supernatant was removed, and 20 µL of 5× loading buffer (20 mL of glycerol, 25 mL of $10\%$ SDS, 5 mL of 1 M tris at pH 7.5, 100 µL of Bromo blue phenol, and 50 mL of double distilled water) was added to each sample. Then, the samples were boiled for 5 min at 100 °C. The immunoprecipitated proteins were subsequently subjected to SDS-PAGE and visualized by immunoblotting.
## 2.9. Reverse Transcription followed by Quantitative PCR (RT-qPCR)
The total RNA from the 3T3-L1 cells was extracted using an RNAiso Plus kit (TaKaRa, Tokyo, Japan), and cDNA was synthesized using Oligo (dT) primers with GoScriptTM Reverse Transcription System (Promega). Quantitative PCR was performed using a TB Green® Premix Ex Taq™ (Tli RNaseH Plus) Kit (TaKaRa) following the manufacturer’s protocol. The primer sequences for the target genes are summarized in Table 2.
## 2.10. Dihydroethidium (DHE) Staining
The DHE Assay Kit—Reactive Oxygen Species (Abcam, Cambridge, UK) was used to determine intracellular ROS levels in the 3T3-L1 cells. The cells seeded in 96-well plates were transfected with plasmids inducing MT3 overexpression or knockdown. Upon confluence, the cells were incubated with antimycin A or N-acetyl cysteine (NAC) for 12 h. Next, the 3T3-L1 cells were incubated with DHE buffer at 37 °C for 1 h, and images were captured using a fluorescence microscope and a digital camera.
## 2.11. Statistical Analysis
GraphPad Prism 8.0.2 was used for statistical analysis. One-way ANOVA followed by Tukey’s Test (to compare the mean of each group with the mean of every other group) or Dunnett’s Test (to compare the mean of each group with the control group) was used to evaluate the differences. All experiments were repeated at least three times. The data are expressed as the means ± SEM, and differences with p-values smaller than 0.05 were considered significant.
## 3.1. MT3 Is Significantly Downregulated during 3T3-L1 Adipocyte Differentiation
Previous studies in our lab have demonstrated that MT3 is important for osteoblast differentiation [40], and numerous in vitro studies have shown that osteogenic factors inhibit adipogenesis, while adipogenic factors hinder osteogenesis [41,42,43]. Therefore, to explore the role of MT3 in adipocyte differentiation, we induced 3T3-L1 adipocyte differentiation and examined the levels of Mt1, Mt2, and Mt3 by RT-qPCR. The induction of adipocyte differentiation was successful, as indicated by the expression of the early-stage marker C/EBPβ and the late-stage adipogenesis markers C/EBPα and PPARγ (Figure 1d–f and Figure 2a,c–e). We found that the mRNA levels of Mt1 and Mt2 peaked on day 2 and then gradually decreased afterward, while the mRNA levels of Mt3 dramatically decreased during the period of adipocyte differentiation (Figure 1a–c). The protein levels of MT3 were reduced in a similar manner (Figure 2a,b). These findings suggest that MT3 might play a role in 3T3-L1 adipocyte differentiation.
## 3.2. Mt3 Overexpression Inhibits Lipid Accumulation in 3T3-L1 Adipocytes
To further investigate the potential function of MT3 in 3T3-L1 adipocyte differentiation, we overexpressed Mt3 in 3T3-L1 preadipocytes before they reached confluence. The formation and accumulation of lipid droplets are considered the predominant characteristic of mature adipocyte differentiation; thus, Oil Red O staining was used to assess the extent of adipocyte differentiation. Microscopy images showed that the differentiated control group acquired the phenotype of mature adipocyte after 8 days of differentiation, and Mt3 overexpression significantly decreased the intracellular lipid accumulation, which was confirmed by quantitative analysis (Figure 3a,b). Furthermore, Mt3 overexpression also evidently decreased intracellular triglyceride content (Figure 3c). Taken together, these results demonstrate that MT3 can inhibit 3T3-L1 adipocyte differentiation.
## 3.3. Mt3 Overexpression Suppresses the Protein Levels of Adipogenic Transcriptional Factors in 3T3-L1 Cells
The sequential expression of genes associated with the specific characteristics of adipocytes takes place during adipocyte differentiation. Therefore, we investigated whether the decrease in the accumulation of lipid droplets in 3T3-L1 cells was due to a downregulation of adipogenic transcription factors. Immunoblotting analysis revealed that the protein levels of the early-stage marker C/EBPβ and the late-stage markers C/EBPα and PPARγ were all reduced in cells overexpressing Mt3 (Figure 4a–e). Adiponectin is an adipokine that regulates a variety of metabolic events, including fatty acid oxidation and glucose levels, and exhibits the highest mRNA expression levels in adipocytes [44]. In our study, the protein levels of adiponectin were also dramatically decreased by Mt3 overexpression compared with the differentiated group (Figure 4f). These data demonstrate that MT3 inhibits adipocyte differentiation by attenuating the expression of adipogenic transcription factors.
## 3.4. Mt3 Overexpression Reduces Adipogenesis-Related Gene Expression in 3T3-L1 Cells
As Mt3 overexpression resulted in a downregulation of the protein levels of adipogenic transcription factors, we further examined the mRNA levels of genes encoding these factors. Similar to the protein levels, Mt3 overexpression significantly inhibited the mRNA levels of adipogenesis-related genes, such as Pparg, Cebpa, Cebpb, and Adiponectin (Figure 5a–d). In addition, we assessed the expression levels of other adipogenesis-related genes associated with lipogenesis, fatty acid oxidation, and glucose homeostasis pathways [45,46]. Upon differentiation induction, the mRNA levels of fatty acid synthase (Fasn), Fabp4, and glucose transporter type 4 (Glut4) were highly elevated compared with the undifferentiated group, whereas Mt3 overexpression dramatically reduced these increases (Figure 5e–g).
## 3.5. MT3 Indirectly Suppresses PPARγ Transcriptional Activity
PPARγ is considered the most important regulator of adipocyte differentiation [15,16]. Thus, we investigated whether MT3 regulated the transcriptional activity of PPARγ by performing a luciferase reporter assay to measure the transcriptional activity of PPARγ in HEK 293T cells. As expected, PPARγ alone stimulated the activity of luciferase reporters, and MT3 did not affect the activity of luciferase reporters. However, we observed that Mt3 overexpression evidently inhibited the activity of luciferase reporters in the presence of Pparg overexpression, while this inhibitory effect was more pronounced following the incubation with rosiglitazone, an agonist of PPARγ (Figure 6a,b). These results suggested that Mt3 overexpression suppressed PPARγ transcriptional activity. Then, we examined whether there was an interaction between MT3 and PPARγ in HEK 293T cells by performing immunoprecipitation. However, we did not detect an interaction between MT3 and PPARγ (Figure 6c,d). Taken together, these data suggested that MT3 downregulated PPARγ transcriptional activity not by interacting with PPARγ but through an indirect mechanism.
## 3.6. MT3 Impedes ROS Production in the Early Stage of 3T3-L1 Adipocyte Differentiation
Given that Mt3 overexpression downregulated the levels of adipogenic transcription factors including PPARγ but indirectly regulated PPARγ transcriptional activity, we sought to identify the mechanism underlying the inhibitory effect of MT3 on 3T3-L1 adipocyte differentiation. MT3 is a powerful scavenger of ROS due to its particular structure [38]. In addition, the early stages of adipocyte differentiation are associated with elevated ROS levels [37], implying that ROS plays a role in adipocyte differentiation. Therefore, we hypothesized that MT3 might affect ROS generation during adipocyte differentiation. To test our hypothesis, we performed DHE staining to measure ROS levels in 3T3-L1 cells. We found that Mt3 overexpression decreased the elevated ROS levels induced by differentiation, while antimycin A treatment reversed the MT3-induced decreases in ROS levels (Figure 7a,c). Antimycin A is a mitochondrial respiratory chain inhibitor that is experimentally used to induce ROS generation [47]. To further examine the effect of MT3 on ROS levels, we knocked down MT3 expression by transfecting the cells with shRNA targeting Mt3. Compared with the differentiated control group, Mt3 knockdown dramatically elevated ROS levels. However, treatment with NAC, an ROS scavenger, attenuated the Mt3 knockdown-induced increases in ROS levels (Figure 7b,d). Taken together, these results indicate that MT3 can impede ROS production in the early stages of adipocyte differentiation.
## 4. Discussion
MTs are multipurpose proteins with essential roles in a variety of pathological conditions. Previous studies have demonstrated that MTs are potentially involved in obesity and its complications. MTs are secreted by white adipose tissue in mice [48], but their functions in the adipose tissue are not clear. Clinical studies have shown that MT1A and MT2A levels are upregulated in subcutaneous and visceral adipose tissues of patients with obesity or type 2 diabetes [49,50], implying that increased expression of MTs in human adipose tissues may be either a factor contributing to the development of obesity or a consequence of obesity. A recent study further reported the regulatory effect of MT$\frac{1}{2}$ on sex-specific differences observed in HFD-induced obesity. MTs can enhance the activity of androgens to promote fat storage and the function of estrogen in preventing excess fat accumulation [51]. In fact, Mt3-knockout mice fed an HFD were more susceptible to weight gain compared with Mt$\frac{1}{2}$-knockout mice fed an HFD [52]. However, there are no clear data on how MT3 is engaged in the development of obesity, especially in 3T3-L1 adipocyte differentiation; the underlying molecular pathways remain unclear.
A previous study showed that MTs are not secreted during the maintenance of fibroblast-like preadipocytes but are released after the induction of differentiation by exposure to a “differentiation cocktail”. Furthermore, the release of MTs into the culture medium precedes leptin expression [48], indicating that MTs may be potential markers of adipocyte differentiation. Yoshito Kadota et al. [ 53] also describe the expression patterns of MT1 and MT2 during 3T3-L1 adipocyte differentiation. In our study, we further examined the expression patterns of MT3 during 3T3-L1 adipocyte differentiation. We observed that MT3 expression was significantly decreased during differentiation, along with the upregulation of PPARγ and C/EBPα. The Oil Red O staining results demonstrated that MT3 repressed the accumulation of lipid droplets, suggesting that MT3 may inhibit adipocyte differentiation. This was further confirmed by the downregulation of the adipogenic transcription factors PPARγ and C/EBPα. Considering that adipocyte differentiation is a multi-step process, we examined the protein levels of related markers, including PPARγ, C/EBPα, and C/EBPβ, at different stages of differentiation to clarify the steps in which MT3 may significantly affect differentiation. We found that MT3 reduced the protein level of PPARγ and C/EBPα at specific times (day 2, day 4, day 6, and day 8) (Figure S1). The differentiation of mature adipocytes from preadipocytes is involved in the successive activation of a range of transcription factors, among which PPARγ is the most important one [54]. Considering the central role of PPARγ in adipocyte differentiation, we hypothesized that MT3 might mediate the PPARγ transcriptional activity. To this end, a luciferase reporter assay was performed to measure its transcriptional activity. As suspected, MT3 suppressed PPARγ transcriptional activity, and the inhibitory effect of PPARγ was more pronounced after treatment with the PPARγ agonist rosiglitazone. We considered the possibility that the inhibitory effect of MT3 on PPARγ transcriptional activity was due to a potential interaction between MT3 and PPARγ. However, immunoprecipitation assays indicated that MT3 did not bind PPARγ. Therefore, the mechanism through which MT3 regulates PPARγ transcriptional activity is still unclear; one possibility is that MT3 may interact with upstream factors of PPARγ, such as C/EBPβ, or another important factor, C/EBPα, which needs to be further investigated.
As in the case of other MT family members, ROS scavenging ability is the most important function of MT3 [55]. Both intracellular and extracellular MT3 protect neurons from oxidative damage under stress-induced conditions due to their function in the elimination of ROS [56,57], which plays a potential role in adipocyte differentiation. Elevated ROS levels during the initial stages of adipocyte differentiation are observed in both 3T3-L1 cells and mesenchymal stem cells (10T$\frac{1}{2}$), indicating that ROS generation is essential for adipocyte differentiation. In line with this idea, adipocyte differentiation is promoted by H2O2 treatment but inhibited by the antioxidant NAC [37,58]. ROS can originate from mitochondrial complex III and can regulate the differentiation process from the primary human mesenchymal stem cells into adipocytes, which is mainly dependent on mTORC1 signaling [59]. In adipose-derived stem cells, hypoxia ($2\%$ oxygen) enhances the differentiation through the generation of mitochondrial ROS [60]. Hence, we asked whether there was a relationship between MT3, ROS levels, and adipocyte differentiation. Here, we found that ROS were induced in the initial phase of 3T3-L1 adipocyte differentiation. We also observed that Mt3 overexpression could impede ROS generation during differentiation; on the contrary, Mt3 knockdown significantly elevated ROS production; importantly, these effects were largely reversed by treatments with the ROS inducer antimycin A and the antioxidant NAC, respectively. In addition, Mt3 overexpression could reduce the MDI-induced increase of ROS scavenging genes, such as Catalase, Gpx1, Sod1, and Sod2, while antimycin A treatment reversed this effect (Figure S2). To further elucidate whether MT3 could regulate adipocyte differentiation through its powerful antioxidant effect, we treated Mt3-overexpressing 3T3-L1 cells with or without antimycin A. The Oil Red O staining results showed that antimycin A could partially restore the inhibitory role of MT3 on 3T3-L1 adipocyte differentiation (Figure S3). Taken together, these results suggest that MT3 hinders 3T3-L1 adipocyte differentiation largely by attenuating the ROS levels during the early stages of adipocyte differentiation.
A previous study reported a partial relationship between ROS levels and C/EBPβ activity with the following observations: (i) the initial phase of adipocyte differentiation with elevated ROS levels corresponds to the S phase of MCE, when C/EBPβ is translocated into centromeres; (ii) antioxidant treatment not only blocks ROS production but also prevents the translocation of C/EBPβ. Therefore, this study [37] demonstrated that ROS is essential for the MCE of 3T3-L1 preadipocytes, which is closely linked to the DNA binding activity of C/EBPβ. Furthermore, there are some other studies showing that ROS levels can be reduced by PPARγ and its agonists [61,62,63]. However, we did not investigate the connection between the decreased ROS levels caused by MT3 and the adipogenic transcription factors C/EBPβ and PPARγ, which should be further studied in the future.
Adipocyte differentiation is a complex process regulated by various signaling pathways. For example, the mitogen-activated protein kinase (MAPK) signaling pathway plays a pivotal role in adipocyte differentiation [64]. Extracellular signal-regulated kinases (ERKs), c-Jun amino-terminal kinases (JNKs), and p38 MAPK are the three main important subfamilies of the MAPK signaling pathway [65]. ERKs can be activated by mitogens including growth factors or serum, and its activation is essential for MCE, which is indispensable for early adipocyte differentiation [66]. Conversely, phosphorylated Erk$\frac{1}{2}$ inhibits 3T3-L1 adipocyte differentiation through a reduction in PPARγ transcriptional activity [67]. These opposite effects of ERKs might be associated with the different stages of differentiation. JNK2 has a positive impact on 3T3-L1 adipocyte differentiation, and its activation specifically contributes to the initial stage of differentiation, as JNK inhibition cannot affect terminal differentiation [68]. p38 MAPK inhibitors function to block 3T3-L1 adipocyte differentiation during the early stage of differentiation [69]. This study also pointed out that C/EBPβ serves as a substrate for p38 MAPK in vitro due to its consensus site for p38 phosphorylation. In addition, the MAPK signaling pathway is closely linked to the ROS pathway. ERK$\frac{1}{2}$ has been reported as the potential downstream target of ROS in inflammation-related diseases [70,71]. ROS can induce the activation of the MAPK signaling pathway, and the decreased accumulation of ROS by antioxidants suppresses MAPK activation, implying that ROS play a vital role in the activation of MAPK pathways [72,73]. The phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway also plays a critical role in adipocyte differentiation [74]. The constitutively active form of Akt promotes 3T3-L1 adipocyte differentiation [75], and ROS are known to enhance Akt phosphorylation [76]. A previous study showed that mTORC1 signaling is required for the early increase in ROS during adipocyte differentiation of human mesenchymal stem cells [59]. In addition, ROS can activate AMP-activated protein kinase (AMPK) and further induce the DNA binding activity of C/EBPβ, leading to the promotion of adipogenesis [77].
Furthermore, the generation of complex III ROS in the mitochondria, which induces the PPARγ transcriptional machinery, is required for adipocyte differentiation [59]. On the basis of our finding that MT3 can suppress the expressions of PPARγ and its target genes, we assume that the inhibition of ROS generation by MT3 might suppress the PPARγ transcriptional machinery and consequently inhibit 3T3-L1 adipocyte differentiation. However, the detailed mechanism of how the decrease in ROS via MT3 regulates PPARγ transcriptional machinery remains elusive.
## 5. Conclusions
In conclusion, our findings suggest a new role for MT3 in the differentiation of 3T3-L1 cells into adipocytes (Figure 8). Our results indicate that MT3 acts as a novel inhibitor of adipocyte differentiation. MT3 can suppress the levels of adipogenic transcription factors such as C/EBP family members and PPARγ. MT3 also downregulates the transcriptional activity of PPARγ. Furthermore, the ability of MT3 to regulate adipocyte differentiation is largely dependent on its ROS scavenging activity. Although our findings are limited in vitro, this study might provide a potential target for the prevention and treatment of obesity.
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|
---
title: Isolation and Identification of Dihydrophenanthrene Derivatives from Dendrobium
virgineum with Protective Effects against Hydrogen-Peroxide-Induced Oxidative Stress
of Human Retinal Pigment Epithelium ARPE-19 Cells
authors:
- Pongsawat Panuthai
- Rianthong Phumsuay
- Chawanphat Muangnoi
- Porames Maitreesophone
- Virunh Kongkatitham
- Wanwimon Mekboonsonglarp
- Pornchai Rojsitthisak
- Kittisak Likhitwitayawuid
- Boonchoo Sritularak
journal: Antioxidants
year: 2023
pmcid: PMC10045308
doi: 10.3390/antiox12030624
license: CC BY 4.0
---
# Isolation and Identification of Dihydrophenanthrene Derivatives from Dendrobium virgineum with Protective Effects against Hydrogen-Peroxide-Induced Oxidative Stress of Human Retinal Pigment Epithelium ARPE-19 Cells
## Abstract
Oxidative stress is a significant factor in the development of age-related macular degeneration (AMD), which results from cell damage, dysfunction, and death in the retinal pigmented epithelium (RPE). The use of natural compounds with antioxidant properties to protect RPE cells from oxidative stress has been explored in Dendrobium, a genus of orchid plants belonging to the family Orchidaceae. Two new compounds and seven known compounds from the MeOH extract of the whole plant of *Dendrobium virgineum* were successfully isolated and structurally characterized. Out of all the compounds isolated, 2-methoxy-9,10-dihydrophenanthrene-4,5-diol [3] showed the highest protective effect against hydrogen peroxide (H2O2)-induced oxidative stress in human retinal pigment epithelial (ARPE-19) cells. Therefore, it was selected to evaluate its protective effect and mechanism on oxidative-stress-induced ARPE-19 cells. Cells were pre-treated with compound 3 at 25, 50, and 100 µg/mL for 24 h and then induced with 400 µM H2O2 for 1 h. The results demonstrated that compound 3 significantly ($p \leq 0.05$) increased cell viability by 10–$35\%$, decreased ROS production by 10–$30\%$, and reduced phosphorylation of p38, ERK$\frac{1}{2}$, and SAPK/JNK by 20–$70\%$ in a dose-dependent manner without toxicity. Furthermore, compound 3 significantly ($p \leq 0.05$) modulated the expression of apoptosis pathway proteins (cytochrome c, Bax and Bcl-2) by 20–$80\%$, and enhanced SOD, CAT, and GPX activities, and GSH levels in a dose-dependent manner. These results suggest that compound 3 protects ARPE-19 cells against oxidative stress through MAPKs and apoptosis pathways, including the antioxidant system. Thus, compound 3 could be considered as an antioxidant agent for preventing AMD development by protecting RPE cells from oxidative stress and maintaining the retina. These findings open up new possibilities for the use of natural compounds in the treatment of AMD and other oxidative-stress-related conditions.
## 1. Introduction
The abnormality of the eyes in the macular area causes irreversible blindness and retinal disease, the so-called age-related macular degeneration (AMD) [1]. The prevalence of AMD in Europe and Asia was around 200 million in 2020 and is expected to be a global health issue in 2040 [2,3,4,5]. AMD is primarily found in patients older than 60, with a loss of central vision that can disturb the patient’s daily life [6,7]. The pathogenesis of AMD is complex; however, it is divided into two types including dry or atrophic and wet or neovascular AMD [8]. The disease progression is associated with retinal pigment epithelium (RPE), which is necessary to maintain photoreceptor cells in the retina [7]. In elderly patients, RPE cannot maintain metabolic activity in the macula and clear the cellular waste and unusual proteins [7,9]. Eventually, it impairs the function of RPE, and overloaded waste is detected as drusen, a yellow spot in the retina, which is a vital sign of AMD [7,9,10]. Due to this imbalance, RPE loses function and affects the retina, which causes vision loss [11,12]. Various risk factors associated with AMD include genetic and exogenous factors such as aging, obesity, oxidative stress, and smoking [13,14]. According to the above risk factors, oxidative stress is the primary cause of the development of AMD [15].
Continuous exposure to blue light, which generates reactive oxygen species (ROS), is known to cause damage to RPE cells in the macula due to its ability to pass through the structures of the retina and induce photooxidation of lipofuscin to cytotoxic compounds [16]. RPE cells with abundant mitochondria exhibit elevated cellular metabolic rates in environments rich with endogenous reactive oxygen species, such as superoxide anions (O2−·) and hydroxyl radicals (OH·). ROS produced from mitochondria activity are also released into the cytoplasm and affect other cells, leading to an increase in ROS levels [17,18]. For the above reasons, high ROS production can be expected to lead to oxidative stress in RPE cells [19,20]. In various studies, ROS such as hydrogen peroxide (H2O2) cause the Fenton reaction, which is the chain reaction between iron in lysosomes and oxidants, resulting in more production of ROS, and are used to induce the oxidative stress condition in in vitro and in vivo [21,22].
Cellular dysfunction and abnormality of biomolecules, such as DNA damage and misfolding proteins, in cells are caused by the attack from ROS [23]. To survive, cells must remove the waste to maintain their function, especially in post-mitotic cells such as RPE cells [24]. The mitogen-activated protein kinases (MAPKs) signaling pathway, which controls the proliferation and cell death in RPE including Bax (pro-apoptotic) and Bcl-2 (anti-apoptotic), is activated by ROS [25,26]. Moreover, ROS can impact the mitochondrial outer membrane by altering the Bax and Bcl-2 proteins, which can lead to the release of cytochrome C into the cytoplasm, and activation of the apoptosis and caspase pathways, including caspase-3 and caspase-9 [27,28]. Such dysfunctions can cause damage to RPE cells and contribute to the development of AMD. Thus, the essential treatment for AMD focuses on the prevention of RPE cells from oxidative stress. Typically, RPE cells contain various endogenous antioxidants such as antioxidant enzymes including glutathione peroxidase (GPx), glutathione transferase (GST), catalase (CAT), superoxide dismutase (SOD), and the non-enzymatic antioxidant glutathione (GSH) for protection of the retina from oxidative damage [29]. A deficiency in antioxidant enzymes frequently accompanied by aging can contribute to the development of AMD [30].
Several studies on active compounds, such as kinsenoside from *Anoectochilus roxburghii* and herbal extracts such as *Emblica officinalis* (Amla) and bilberry anthocyanin extracts, have shown the existence of potent antioxidants for protective effects against AMD [31,32,33]. Dendrobium is a genus in the orchid family (Orchidaceae) with more than 1500 species worldwide [34]. These species have been proved to have therapeutic properties and have been used as folk medicines for more than 2300 years [35]. Dendrobium plants have been used as traditional medicine in China to treat fever, diabetes, stomach diseases, and lung and kidney disorders [36]. The natural exogenous non-enzymatic antioxidants such as polyphenols, carotenoids, flavonoids, and organosulfur compounds, which exhibited the preventive effects in AMD, have been reported in various studies [37,38,39,40,41,42,43,44,45]. Moreover, Dendrobium extract has been reported to improve vision [46]. Dendrobium virgineum Rchb.f. ( Figure 1A), known in Thai as “Ueang Nang Chi”, is usually founded in dry evergreen forests and mixed deciduous forests in Thailand’s east and north-east regions, and in Myanmar, Laos, and Vietnam. Its flower consists of white petals and a red lip, and it was first discovered by Reichenbach in 1884 [47].
In this study, we aimed to isolate and determine the protective effect against H2O2-induced oxidative stress in human retinal pigment epithelial (ARPE-19) cells of isolated compounds from the whole plant of Dendrobium virgineum. Among 9 isolated compounds, two new compounds (1 and 2) and seven known compounds (3–9) were identified. Compound 3, with the most potent antioxidant effect, was further investigated regarding its protective mechanism against H2O2-induced ARPE-19 cells.
## 2.1. Experimental
The Milton Roy Spectronic 3000 Array spectrophotometer (Rochester, Monroe, NY, USA) was used to record UV spectra, while IR spectra were obtained from the PerkinElmer FT-IR 1760X spectrophotometer (Boston, MA, USA). Mass spectra were determined using the Bruker MicroTOF mass spectrometer (ESI-MS) (Billerica, MA, USA). NMR spectra were recorded by the Bruker Avance DPX-300FT NMR spectrometer or the Bruker Avance III HD 500 NMR spectrometer (Billerica, MA, USA). Sigma Aldrich (Sigma-Aldrich, Dorset, UK) provided 2′,7′-dichlorofluorescein di-acetate (DCFH-DA), and Merck Millipore (Merck Millipore, Darmstadt, Germany) supplied fetal bovine serum (FBS). Invitrogen (Invitrogen Ltd., Paisley, UK) provided Dulbecco’s modified Eagle’s Medium/Nutrient Mixture F-12 Ham (DMEM/F-12), penicillin–streptomycin, H2O2, dimethyl sulfoxide (DMSO), and 3-[4,5-dimethyltiazol-2-yl]-2,5-diphenyl-tetrazolium bromide (MTT). Antibodies used in western blotting were obtained from Cell Signaling Technology (Danvers, MA, USA). Antioxidant enzyme assay test kits were obtained from Cayman Chemical (Cayman Chemical, Ann Arbor, MI, USA).
## 2.2. Plant Material
The whole plants of D. virgineum were obtained from Chatuchak Market (Bangkok, Thailand) in September 2015. Authentication was performed by the author (Boonchoo Sritularak). A voucher specimen (BS-DVir-2558) was deposited at the Department of Pharmacognosy and Pharmaceutical Botany, Faculty of Pharmaceutical Sciences, Chulalongkorn University.
## 2.3. Extraction and Isolation
The dried, powdered whole plant of D. virgineum (2.7 kg) was extracted in a stainless tank with 20 L of MeOH three times at room temperature to give a MeOH extract (297 g) after evaporation of the solvent. The MeOH extract was partitioned with 10 L of EtOAc and water to give an EtOAc extract (95 g) and an aqueous extract (200 g). The EtOAc extract was initially subjected to liquid chromatography under vacuum on silica gel (acetone–hexane, gradient) to yield 6 fractions (A-F). Fraction B (12.3 g) was separated by column chromatography (CC) over silica gel (acetone–hexane, gradient) to give 5 fractions (B−I to B−V). Fraction B−II (2.5 g) was fractionated by Sephadex LH-20 (MeOH) and then purified by CC (EtOAc–hexane, gradient) to yield 2-methoxy-9,10-dihydrophenanthrene-4,5-diol [3] (5 mg) and compound 1 (6 mg). Compound 1 (17 mg) and gigantol [4] (541 mg) were obtained from fractions B−III (553 mg) and B−IV (1.2 g), respectively, after purification on Sephadex LH-20 (MeOH). Fraction C (8.6 g) was separated by CC (silica gel, acetone–hexane, gradient) to give 9 fractions (C−I to C−IX). Fraction C−V (2.0 g) was fractionated by Sephadex LH-20 (MeOH) to give 4 fractions (C−V1 to C−V4). Fraction C−V2 (206 mg) was isolated by CC (silica gel, EtOAc–hexane, gradient) and further purified by Sephadex LH-20 (MeOH) to furnish compound 2 (6 mg). Fraction C−V3 (116 mg) was separated by CC (silica gel, EtOAc–hexane, gradient) and then subjected to repeated CC (silica gel, acetone–hexane, gradient) to yield 5-methoxy-7-hydroxy-9,10-dihydro-1,4-phenanthrenequinone [5] (4 mg). Fraction C−VI (1.3 g) was subjected to CC on silica gel (acetone–hexane) and then fractionated by Sephadex LH-20 (MeOH) to give 9 fractions (C−VI1 to C−VI9). Fraction C−VI2 (106 mg) was separated by CC (silica gel, EtOAc–hexane, gradient) to yield p-coumaric acid [6] (9 mg). Tristin [7] (101 mg) was obtained from fraction C−VI3 (237 mg) after purification on CC (silica gel, EtOAc–hexane, gradient). Purification of fraction C−VI5 (156 mg) by CC (silica gel, EtOAc–hexane, gradient) gave 2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene [8] (116 mg). Fraction C−VI6 (11 mg) was separated by CC (silica gel, EtOAc–hexane, gradient) to give 2,4,7-trihydroxy-9,10-dihydrophenanthrene [9] (5 mg) (Scheme 1).
Dendrovirginin [1]: *Brown amorphous* solid; UV (MeOH) λmax (log ε): 222 (4.49), 273 (4.15), 305 (3.94) nm; IR (film) νmax: 3166, 2936, 2837, 1616, 1463, 1435, 1250, 1152, 1104 cm−1; HR-ESI-MS: [M−H]− at m/z 271.0960 (calcd. for 271.0970, C16H15O4); 1H NMR (500 MHz, acetone-d6) and 13C NMR (125 MHz): see Table 1.
Dendrovirginone [2]: *Red amorphous* solid; UV (MeOH) λmax (log ε): 222 (4.39), 260 (4.07), 334 (3.79), 490 (3.53) nm; IR (film) νmax: 3416, 2939, 2922, 1722, 1658, 1605, 1560, 1349, 1213, 1160 cm−1; HR-ESI-MS: [M−H]− at m/z 285.0752 (calcd. for 285.0763, C16H13O5); 1H NMR (500 MHz, acetone-d6) and 13C NMR (125 MHz): see Table 1.
## 2.4. Culture of ARPE-19 Cells
ARPE-19 cells (ATCC, Rockville, MD, USA) were used as a representative model of human RPE cells and cultured in DMEM/F-12 with $10\%$ (v/v) heat-inactivated fetal bovine serum (FBS) and $1\%$ (v/v) penicillin–streptomycin (pen–strep). Standard 6-well or 96-well plates were used for all experiments, unless otherwise stated. Cells were seeded at 1.0 × 106 and 3.0 × 104 cells/well for 6- and 96-well plate experiments, respectively. The cells were allowed to grow until they reached over $90\%$ confluence before being utilized in subsequent experiments.
## 2.5. Cell Viability Assay
The viability of cells was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide tetrazolium (MTT) assay, which measures the conversion of MTT substrate to a purple-colored formazan product in viable cells. After cells reached their experimental time points, they were washed once with phosphate buffer saline (PBS) and incubated with MTT in PBS at 0.5 mg/mL for 4 h at 37 °C. After removal of the MTT solution, DMSO was added to dissolve the formazan crystals generated by viable cells. The absorbance was subsequently measured at 540 nm using a microplate reader (SPECTROstarNano, BMG LABTECH, Ortenberg, Germany).
## 2.6. Cytotoxicity Assay of Compounds 1–9
Following a 24 h incubation of ARPE-19 cells, the media was removed and cells were washed with serum-free media. Cells were then treated with varying concentrations (10, 50, and 100 µg/mL) of compounds 1–9 for 24 h, with a $0.5\%$ DMSO used as the control group. Cell viability was assessed using the MTT assay after the respective experimental time.
## 2.7. Determining the Optimal H2O2 Concentration for Cytotoxicity Induction
ARPE-19 cells in a 96-well plate were treated by removing the media and washing with serum-free media. Subsequently, cells were treated with serum-free medium containing various concentrations of H2O2 (200–1000 µM) for 30, 60, and 120 min at 37 °C. The control group consisted of cells cultured in serum-free medium without H2O2. Following the experimental treatment, cells were washed twice with PBS and evaluated for cell viability using the MTT assay.
## 2.8. Assessing the Effect of Compound 3 on ARPE-19 Cells Exposed to H2O2
ARPE-19 cells in 6-well and 96-well plates were washed one time with serum-free media and pre-incubated with compound 3 (25, 50, and 100 µg/mL) in serum-free media for 24 h. A $0.5\%$ DMSO served as the control group. After pre-treatment with compound 3, cells were washed with serum-free media and then treated with appropriate H2O2 concentrations in serum-free medium at 37 °C for 1 h. Cell viability was measured using the MTT assay in the 96-well plate setup, while the 6-well plate setup was used for non-enzymatic and enzymatic antioxidant assays, caspase-9 and caspase-3 activities, and western immunoblot analysis.
## 2.9. Evaluation of Reactive Oxygen Species (ROS) Production
To determine intracellular ROS, ARPE-19 cells were seeded at 3.0 × 104 cells/well in black 96-well, clear bottom plates and cultured for 24 h. After washing with serum-free media, cells were pre-incubated for 24 h with compound 3 (25, 50 and 100 µg/mL) in serum-free media, with $0.5\%$ DMSO as the control. Subsequently, cells were incubated with 10 µM DCFH-DA in serum-free media at 37 °C for 30 min, then treated with varying concentrations of H2O2 in serum-free media at 37 °C for 1 h. Following PBS washes, ROS production was measured using a fluorescence microplate reader with excitation/emission wavelengths of $\frac{485}{530}$ nm.
## 2.10. Western Blot Analysis
ARPE-19 cell lysates were prepared from a 6-well plate by centrifuging at 14,000 rpm at 4 °C for 10 min, and the protein concentrations were determined using the BCA protein assay kits. Equal amounts (40 µg) of protein samples were separated by $10\%$ SDS-PAGE, transferred to a nitrocellulose membrane, blocked with $5\%$ dry milk, and then incubated with anti-p-p38, anti-p-ERK$\frac{1}{2}$, anti-p-SAPK/JNK, anti-Bax, anti-Bcl-2, or anti-cytochrome c at a ratio of 1:1000 (v/v) in TBST overnight. The membrane was washed with TBST and incubated with a 1:2000 species-specific horseradish peroxide conjugated secondary antibody for 2 h. The protein levels were detected using an enhanced chemiluminescent detection kit, followed by imaging. The densitometry values of the phosphorylated forms of p38 (p-p38), ERK$\frac{1}{2}$ (p-ERK$\frac{1}{2}$), and SAPK/JNK (p-SAPK/JNK) were normalized to the band intensity of the respective total forms of p38, ERK$\frac{1}{2}$, and SAPK/JNK. Similarly, the densitometry values of cytochrome c, Bax, and Bcl-2 were normalized to the band intensity of β-actin.
## 2.11. Caspase-9 and -3 Activities
Following pre-treatment with compound 3 and H2O2 induction, as described in Section 2.8, the cells were homogenized in a hypotonic buffer to extract the supernatant. The supernatant was combined with a specific substrate (N-acetyl-Leu-Glu-His-Asp p-nitroanilide or N-acetyl-Asp-Glu-Val-Asp p-nitroanilide for caspase-9 or caspase-3, respectively) at a concentration of 100 µmol/L. The mixture was incubated at 37 °C for 1 h., and the absorbance was measured at 450 nm using a microplate reader to detect the activity of the caspases.
## 2.12. SOD, GPx, CAT, and GSH Determination
After treating ARPE-19 cells with compound 3 and H2O2, as described in Section 2.8, the cells were harvested by scraping and incubated with $0.5\%$ (v/v) Triton X-100 in cold PBS. The resulting cell solution was transferred to a 1.5-mL tube and subjected to sonication in an ultrasonic sonicator bath at 4 °C for 10 min. The cell lysate was then centrifuged at 14,000× g at 4 °C for 10 min, and the supernatant was collected to measure the levels of GSH and the activities of SOD, GPx, and CAT using assay kits.
## 2.13. Statistical Analysis
The results are expressed as mean ± standard deviation (SD) of at least three independent experiments. Statistical analysis was performed with SPSS software version 16.0 (SPSS inc., Chicago, IL, USA). The differences among groups were assessed by one-way analysis of variance (ANOVA). Statistical significance was set at $p \leq 0.05.$
## 3.1. Structural Characterization
Chromatographic separation of EtOAc extract from the whole plants of D. virgineum resulted in the isolation of two previously unknown phenanthrene derivatives (1 and 2), along with seven known compounds, which included 2-methoxy-9,10-dihydrophenanthrene-4,5-diol [3] [48], gigantol [4] [49], 5-methoxy-7-hydroxy-9,10-dihydro-1,4-phenanthrenequinone [5] [50], p-coumaric acid [6] [51], tristin [7] [52], 2,5,7-trihydroxy-4-methoxy-9,10-dihydrophenanthrene [8] [53], and 2,4,7-trihydroxy-9,10-dihydrophenanthrene [9] [54] (Figure 1B).
Compound 1 was purified as a brown amorphous solid. A molecular formula C16H16O4 was deduced from its [M−H]− at m/z 271.0960 (calcd for C16H15O4 271.0970). The IR spectrum exhibited absorption bands for hydroxyl (3166 cm−1), aromatic (2936, 1616 cm−1), and methylene (1463 cm−1) functionalities. The UV absorptions at 222, 273, and 305 nm indicated the characteristic of a dihydrophenanthrene nucleus [55]. This was confirmed by the presence of four methylene protons at δ 2.58–2.65 (4H, m, H2-9, H2-10), which showed correlations to the carbon atom at δ 23.0 (C-9) and δ 31.6 (C-10). The 1H NMR displayed four aromatic protons at δ 6.45–6.88 and two methoxy groups at δ 3.77 (3H, s, MeO-2) and 3.78 (3H, s, MeO-8). On ring A, the 1H NMR showed two doublet proton signals at δ 6.45 (1H, d, $J = 2.5$ Hz, H-3) and 6.49 (1H, d, $J = 2.5$ Hz, H-1). The assignment of H-1 was based on its HMBC correlation with C-10 (δ 31.6) and NOESY interaction with H2-10 (Figure 2). The first methoxy group was located at C-2 according to its NOESY correlations with H-1 and H-3. A comparison of 1H and 13C NMR of ring B of 1 with those of dendroinfundin B, a dihydrophenanthrene derivative previously reported from *Dendrobium infundibulum* [56], revealed their structural similarity by the presence of two doublet protons at δ 6.84 (1H, d, $J = 8.5$ Hz, H-7) and 6.88 (1H, d, $J = 8.5$ Hz, H-6), and a methoxy group at δ 3.78 (3H, s, MeO-8). The assignment of H-7 was according to 3-bond correlations of C-8a (δ 129.3) with H-7 and H2-10. The second methoxy group was substituted at C-8 based on its NOESY correlation with H-7 and H2-9 (Figure 2). Based on the above spectral evidence, 1 was characterized as 4,5-dihydroxy-2,8-dimethoxy-9,10-dihydrophenanthrene and named dendrovirginin.
Compound 2, a red amorphous solid, was analyzed for C16H14O5 from its [M−H]− at m/z 285.0752 (calcd for C16H13O5 285.0763). The IR spectrum showed absorption bands for hydroxyl (3416 cm−1), aromatic (2939, 1658 cm−1), and ketone (1722 cm−1) functionalities. The UV absorptions at 222, 260, 334, and 490 nm suggest a dihydrophenanthrenequinone nucleus [50]. This was supported by the presence of the 1H NMR signals for two pairs of methylene protons at δ 2.46 (2H, br s, H2-10) and 2.58 (2H, t, $J = 7.0$ Hz, H2-9), and the 13C NMR signals of carbonyl carbon at δ 180.7 (C-1) and 185.1 (C-4). Compound 2 showed 1H and 13C NMR resonances similar to those of 5-methoxy-7-hydroxy-9,10-dihydro-1,4-phenanthrenequinone [5], a dihydrophenanthrenequinone also isolated from this plant, except for the presence of a methoxy group (δ 3.82, 3H, s) at C-2 of 2. The substitution of this methoxy group was supported by the presence of a sharp singlet proton signal of H-3 (δ 5.95, 1H, s), which showed correlations with C-1 (δ 180.7) and C-4a (δ 142.1), and the NOESY interaction between MeO-2 and H-3 (Figure 2). The 1H NMR also showed two doublet protons at δ 6.41 (1H, d, $J = 2.0$ Hz, H-8) and 6.43 (1H, d, $J = 2.0$ Hz, H-6), and a methoxy group at δ 3.69 (3H, s, MeO-5). The HMBC correlation of H-8 with C-9 and the NOESY correlation of H-8 with H2-9 were also observed (Figure 2). The placement of MeO-5 was supported by its NOESY correlation with H-6. Therefore, compound 2 was identified as 7-hydroxy-2,5-dimethoxy-9,10-dihydro-1,4-phenanthrenequinone and given the trivial name dendrovirginone.
## 3.2. Evaluation of the Effects of Compounds (1–9) on Viability of ARPE-19 Cells
To measure their non-toxic concentrations, compounds 1–9 were tested on ARPE-19 cells before assessing their protection against oxidative stress. The treatment was conducted for 24 h at 25, 50, and 100 µg/mL. Compounds 1, 2, and 4 at 50 and 100 µg/mL, as well as compounds 8 and 9 at 100 µg/mL, exhibited cytotoxicity against ARPE-19 cells (Figure 3). To ensure efficient and continuous activity, the maximum concentration used in subsequent experiments was 25 µg/mL.
## 3.3. Evaluation of the Effect of H2O2 on Viability and ROS Production of ARPE-19 Cells
Various concentrations of H2O2 (200–1000 µM) were applied to ARPE-19 cells for 30, 60, and 120 min to determine the concentration required for a roughly $50\%$ reduction in viability. Results indicated that H2O2 treatment caused a concentration and time-dependent decrease in cell viability and an increase in ROS production (Figure 4A,B). Treatment with 400 µM of H2O2 for 60 min caused a $50\%$ reduction in cell viability (Figure 4A). As a result, 400 µM of H2O2 for 60 min was employed to generate oxidative stress in ARPE-19 cells.
## 3.4. Evaluation of the Effect of Compounds (1–9) on Cell Viability of Oxidative-Stress-Induced ARPE-19 Cells
To assess their protective effects against H2O2-induced oxidative stress in ARPE-19 cells, compounds 1–9 were evaluated by pre-incubating cells with each compound at 25 µg/mL for 24 h. After washing with serum-free media, cells were treated with serum-free media containing 400 µM of H2O2 for 60 min. Among the compounds, compound 3 showed the highest protective effect against oxidative stress in ARPE-19 cells (Figure 5A) without inducing toxicity in normal ARPE-19 cells (Figure 5B). Therefore, compound 3 was selected to evaluate its protective mechanism in oxidative-stress-induced ARPE-19 cells. As shown in Figure 3, the cytotoxicity results revealed that the maximum concentration of compound 3 at 100 µg/mL had no significant impact on viability of ARPE-19 cells compared with the control. Consequently, concentrations of 25, 50, and 100 µg/mL of compound 3 were chosen for the protective mechanism studies.
## 3.5. Evaluation of the Effect of Compound 3 on Cell Viability and ROS Production in Oxidative-Stress-Induced ARPE-19 Cells
The protective effects of compound 3 against oxidative-stress-induced cell death in ARPE-19 cells were investigated by pre-incubation with compound 3 at 25, 50, and 100 µg/mL for 24 h followed by induction of oxidative stress with 400 µM H2O2 for 60 min. The protective effect of compound 3 against H2O2-induced oxidative stress was supported by inverted microscopic analysis (Figure 6A). H2O2 treatment caused a $50\%$ decrease in cell viability compared with the control group (Figure 6B). However, compound 3 significantly ($p \leq 0.05$) protected the cell viability of ARPE-19 cells in a dose-dependent manner when compared with the H2O2 group (Figure 6B). In terms of ROS production, H2O2 significantly ($p \leq 0.05$) increased ROS production compared with the control group (Figure 6C). On the other hand, compound 3 significantly ($p \leq 0.05$) decreased ROS production in a dose-dependent manner when compared with the H2O2 group (Figure 6C). These findings suggest that compound 3 protects ARPE-19 cells against oxidative-stress-induced cytotoxicity by reducing ROS production dose-dependently.
## 3.6. Evaluation of the Effect of Compound 3 on MAPKs Protein Expression in Oxidative-Stress-Induced ARPE-19 Cells
The protective effects of compound 3 on ARPE-19 cells under oxidative stress were investigated to determine the underlying molecular mechanisms. Previous research indicated that phosphorylation of MAPK signaling pathways (p38, ERK$\frac{1}{2}$, and SAPK/JNK) promoted H2O2-induced apoptosis [57]. The current study explored whether the same pathway contributed to H2O2-induced cell damage and death. Immunoblotting was used to analyze protein expression and revealed that incubation of ARPE-19 cells with H2O2 at 400 µM for 1 h significantly increased the phosphorylation of p38 (p-p38), ERK$\frac{1}{2}$ (p-ERK$\frac{1}{2}$), and SAPK/JNK (p-SAPK/JNK) in comparison with the control group (Figure 7A–C). This finding suggests that H2O2-induced cell death occurs via the p-p38, p-ERK$\frac{1}{2}$, and p-SAPK/JNK pathways. Pre-incubation with compound 3 (25, 50, and 100 µg/mL) for 24 h reduced the expression of the phosphorylation form of p38, ERK$\frac{1}{2}$, and SAPK/JNK in comparison with the H2O2-induced ARPE-19 cell group ($p \leq 0.05$), indicating that compound 3 protects against oxidative stress via a dose-dependent modulation of the MAPKs signaling pathway.
## 3.7. Evaluation of the Effect of Compound 3 on Apoptosis Protein Expression in Oxidative-Stress-Induced ARPE-19 Cells
To understand how compound 3 protects against oxidative stress, we assessed its molecular mechanisms by analyzing the apoptosis pathway. Specifically, we evaluated the levels of downstream targets of the MAPK pathways, such as cytochrome c, Bax (pro-apoptotic), and Bcl-2 (anti-apoptotic) proteins [58,59]. We determined the expression of cytochrome c, Bax, and Bcl-2 through immunoblotting in ARPE-19 cells induced with oxidative stress (Figure 8A–C). Our results demonstrated that H2O2 incubation significantly increased cytochrome c and Bax levels and decreased Bcl-2 levels compared with the control group.
However, pre-incubating cells with compound 3 at concentrations of 25, 50, and 100 µg/mL for 24 h resulted in a significant dose-dependent decrease in the levels of cytochrome c and Bax proteins, and a significant dose-dependent increase in the level of Bcl-2 protein compared with the H2O2 group (Figure 8A–C). Thus, in a dose-dependent manner, the protective effect of compound 3 against oxidative-stress-induced cell death is mediated by regulating the cytochrome c, Bax, and Bcl-2 proteins in the apoptosis pathway.
## 3.8. Effect of Compound 3 on Caspase-9 and Caspase-3 Activities in ARPE-19 Cells under Oxidative Stress
To investigate the anti-apoptotic effect of compound 3 on oxidative-stress-induced ARPE-19 cells, we examined its impact on caspase-9 and caspase-3 activities. H2O2 exposure significantly ($p \leq 0.05$) increased the activity of both caspases compared with the control group (Figure 9A,B). However, pre-incubation with compound 3 at 25, 50, and 100 µg/mL for 24 h significantly decreased caspase-9 and caspase-3 activities in a dose-dependent manner compared with the H2O2 group (Figure 9A,B). These findings indicate that compound 3 can mitigate H2O2-induced apoptosis from oxidative stress by modulating the apoptosis pathway via caspase-9 and caspase-3 activities.
## 3.9. Evaluation of the Effect of Compound 3 on SOD, CAT, and GPx Activities as well as GSH Levels in ARPE-19 Cells under Oxidative Stress
To determine whether compound 3 modulates enzymatic antioxidants such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), as well as the non-enzymatic antioxidant glutathione (GSH), we examined their activities and levels in ARPE-19 cells under oxidative stress. Results showed that H2O2 incubation significantly decreased SOD, CAT, and GPx activities, and GSH levels compared with the control group ($p \leq 0.05$) (Figure 10A–D). However, pre-incubation of cells with compound 3 at concentrations of 25, 50, and 100 µg/mL for 24 h significantly improved SOD, CAT, and GPx activities, and GSH levels in a dose-dependent manner in ARPE-19 cells induced with oxidative stress (Figure 10A–D). Interestingly, incubation with only compound 3 at a concentration of 100 µg/mL significantly increased SOD, CAT, and GPx activities, and GSH levels compared with the control group (Figure 10A–D). These findings suggest that pre-treatment with compound 3 could enhance the antioxidant system in RPE cells and protect against potential oxidative stress inducers. The findings suggest that prior administration of compound 3 could enhance the antioxidant system of ARPE-19, thus providing protection against potential triggers of oxidative stress.
## 4. Discussion
Plants in the genus Dendrobium have been traditionally used for medicinal purposes, and one of the benefits of Dendrobium extract is vision improvement [46]. In this study, we initially investigated the protective effects of the MeOH extract from the whole plants of D. virgineum on H2O2-induced oxidative stress in ARPE-19 cells. Chromatographic isolation of this plant led to the isolation of two new compounds, dendrovirginin (compound 1) and dendrovirginone (compound 2), along with seven known compounds (compounds 3–9). The isolated compounds from the plant were subsequently evaluated for their cytotoxicity and protective effects on ARPE-19 cells under oxidative stress. Among the isolated compounds, only compound 3 showed the highest protective effect without inducing toxicity. Therefore, compound 3 could be a potential candidate for treating oxidative-stress-related eye diseases and was chosen for further protective effect and mechanism evaluation.
This study represents the first demonstration of the protective effects of the natural bioactive compound, compound 3, belonging to the dihydrophenanthrene group, isolated from D. virgineum, against oxidative stress in ARPE-19 cells. Compound 3 exhibited its protective effect by modulating the key apoptotic mitogen-activated protein kinases (MAPKs), namely p38, extracellular-signal-regulated kinases $\frac{1}{2}$ (ERK$\frac{1}{2}$ or p$\frac{44}{42}$), and stress-activated protein kinases/c-Jun N-terminal kinases (SAPK/JNK), as well as the apoptotic signaling pathway, encompassing Bax, Bcl-2, and cytochrome c. Furthermore, compound 3 could protect ARPE-19 under oxidative stress by enhancing the activities of enzymatic antioxidant systems, including SOD, CAT, and GPx, and the non-enzymatic antioxidant GSH. Previous studies have demonstrated that natural bioactive compounds belonging to the dihydrophenanthrene group possess direct antioxidant activities in 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and cupric ion reducing antioxidant capacity (CUPRAC) assays [60]. Hence, it is plausible that compound 3 may confer its protective effect on oxidative stress in ARPE-19 cells via direct antioxidant activity. Taken together, these findings emphasize the potential utility of compound 3 as a prophylactic agent for AMD.
Moreover, we found that compound 3 exerts a protective effect via the modulation of phosphorylation of MAPKs signaling, namely p38, ERK$\frac{1}{2}$, and SAPK/JNK. These MAPKs play essential roles in cellular functions such as apoptosis and proliferation [58,59]. Transient or acute stimulation of this pathway is crucial for normal cell survival, whereas sustained or chronic stimulation can lead to cell death. Such studies show that stimulating these MAPKs can cause downstream expression of apoptotic regulators, including Bax (pro-apoptotic), Bcl-2 (anti-apoptotic), and cytochrome c. In addition, the phosphorylation of MAPKs is strongly related to the promotion of H2O2-induced cell apoptosis and death in RPE cells [59,61,62]. Hence, assessing the activation of MAPK and the expression of downstream molecules such as Bax, Bcl-2, and cytochrome c provides insights into the mechanism of H2O2-induced apoptosis in ARPE-19. The treatment of H2O2 led to an increase in the phosphorylation of p38, ERK$\frac{1}{2}$, and SAPK/JNK in ARPE-19. As a result, there was an increase in Bax and cytochrome c expression, along with a decrease in Bcl-2 expression, indicating that cell death following H2O2 treatment occurred via the apoptotic signaling pathway. Pre-incubation with compound 3 prevented these changes, leading to increased cell viability under oxidative stress by H2O2. These findings highlight the potential of compound 3 as a preventive agent for oxidative-induced cell dysfunction and death in RPE cells, particularly in the case of AMD.
Additionally, pre-incubation with compound 3 increased the activities of key enzymatic antioxidants such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), as well as the levels of the non-enzymatic antioxidant glutathione (GSH). These results suggest that compound 3 can function indirectly as an antioxidant by enhancing the activities and levels of these critical antioxidants. Under oxidative stress conditions induced by incubation with H2O2, we observed a decrease in the activities of SOD, CAT, and GPx, as well as the levels of GSH. However, pre-incubation with compound 3 improved the activities of these enzymes and the level of GSH in comparison with the cells under oxidative stress. Furthermore, under normal conditions, where the cells were pre-incubated with compound 3 without H2O2, we observed a significant increase in SOD, CAT, and GPx activities, as well as GSH levels compared with the control group. These results indicate that the pre-treatment of compound 3 could support oxidative stress protection by enhancing the SOD, CAT, and GPx activities, and the levels of GSH. A previous study showed that bioactive compounds from the Dendrobium extract protected HaCaT keratinocytes cells from oxidative stress by activating non-enzymatic and enzymatic antioxidant systems, leading to reduced ROS production [63]. Another study showed that the bioactive compounds in the dihydrophenanthrene group increased enzymatic antioxidant activity in polymorphonuclear leukocytes [64].
The exact mechanisms by which compound 3 influences SOD, CAT, and GPx activities, as well as the GSH level, were not evaluated in this study. However, previous studies have reported that antioxidant compounds can protect RPE cells against oxidative stress by activating the signaling pathway of Akt/Nrf2 [65,66]. This pathway relates the translocation of Nrf2 into the nucleus, which leads to the expression of various non-enzymatic and enzymatic antioxidants. Numerous studies have reported that dihydrophenanthrene compounds, such as compound 3, exert protective effects against oxidative stress by activating the Nrf2 signaling pathway [67,68]. Therefore, it is likely that compound 3 can influence the levels of the non-enzymatic and enzymatic antioxidants through this pathway. Our findings suggest that compound 3 can protect RPE cells from oxidative stress by enhancing the activities of key enzymatic antioxidants, such as SOD, CAT, and GPx, and the level of GSH. Further studies are needed to elucidate the precise mechanisms by which compound 3 influences these antioxidants’ activities and levels.
## 5. Conclusions
In conclusion, the study shows that compound 3, a dihydrophenanthrene group compound isolated from Dendrobium virgineum, has a protective effect against oxidative-stress-induced damage in ARPE-19 cells by modulating key apoptotic signaling pathways and enhancing the activities of enzymatic and non-enzymatic antioxidants (Figure 11). These findings suggest that compound 3 has potential as a prophylactic agent for AMD and other oxidative-stress-related eye diseases. The study also highlights the importance of evaluating the activation of MAPKs and the apoptosis pathway to understand how oxidative stress induces apoptosis in RPE cells. The discovery of new natural bioactive compounds such as compound 3 provides opportunities for the development of novel therapeutic agents to prevent and treat oxidative-stress-induced diseases.
## Figures, Scheme and Table
**Figure 1:** *(A) *Dendrobium virgineum* (B) Chemical structures of compounds (1–9).* **Scheme 1:** *Extraction and isolation of compounds from Dendrobium virgineum.* **Figure 2:** *Selected HMBC and NOESY correlations of 1 and 2.* **Figure 3:** *Evaluation of the effect of compounds (1–9) on cell viability of ARPE-19 cells. Cells were treated with compounds (1–9) at 25, 50 and 100 µg/mL for 24 h. A $0.5\%$ DMSO was used as a control group. After incubation, cell viability was determined using an MTT assay. Results present average cell viability as mean ± SD ($$n = 4$$). The symbol * indicates significantly different from the control group ($p \leq 0.05$).* **Figure 4:** *Evaluation of the effect of H2O2 on cell viability and ROS production of ARPE-19 cells. Cells were treated at various concentrations of H2O2 (200–1000 µM) for 30, 60 and 120 min. (A) Cell viability and (B) ROS production were measured using MTT and DCFH-DA assays, respectively. Results present cell viability and relative fluorescence related to ROS production as mean ± SD ($$n = 4$$). The symbol * indicates significantly different from the control group ($p \leq 0.05$).* **Figure 5:** *Evaluation of the effect of compounds (1–9) on cell viability in oxidative-stress-induced ARPE-19 cells. (A) Cells were pre-treated with compounds (1–9) at 25 µg/mL for 24 h. After incubation, cells were induced with 400 µM H2O2 for 60 min. (B) Cells were treated with compounds (1–9) at 25 µg/mL for 24 h. Cell viability was determined using an MTT assay. Results present average cell viability as mean ± SD ($$n = 4$$). Different superscript letters (a–d) indicate significant differences between values in the column ($p \leq 0.05$).* **Figure 6:** *Evaluation of the effect of compound 3 on cell viability and ROS production in oxidative-stress-induced ARPE-19 cells. Cells were pre-treated with compound 3 at 25, 50 and 100 µg/mL for 24 h, followed by incubation with H2O2 at 400 µM for 60 min. (A) Cell morphology under all experimental conditions was observed by phase-contrast microscopy. Scale bar represents 100 µm; (B) viability of cells was determined using an MTT assay; (C) production of ROS was measured by a DCFH-DA assay. Results present average cell viability and ROS production as mean ± SD ($$n = 4$$). Different superscript letters (a–e) indicate significant differences between values in the column ($p \leq 0.05$).* **Figure 7:** *Evaluation of the effect of compound 3 on MAPK protein expression in oxidative-stress-induced ARPE-19 cells. Cells were pre-incubated with compound 3 at 25, 50 and 100 µg/mL for 24 h, followed by incubation with H2O2 at 400 µM for 60 min. The protein expression levels of phosphorylated p38 (A), ERK$\frac{1}{2}$ (B), and SAPK/JNK (C) were determined by immunoblotting from cellular lysates. The densitometry values of the phosphorylated forms of p38, ERK$\frac{1}{2}$, and SAPK/JNK were normalized to the total form bands of p38, ERK$\frac{1}{2}$, and SAPK/JNK, respectively. Results are presented as mean ± SD values ($$n = 4$$). Different superscript letters (a–d) indicate significant differences between values in the column ($p \leq 0.05$).* **Figure 8:** *Evaluation of the effect of compound 3 on apoptosis protein expression in oxidative-stress-induced ARPE-19 cells. Cells were pre-treated with compound 3 at 25, 50 and 100 µg/mL for 24 h, followed by incubation with 400 µM H2O2 for 60 min. Protein levels of (A) cytochrome c, (B) Bax, and (C) Bcl2 were examined by immunoblotting. Band densitometry values of cytochrome c, Bax and Bcl-2 were normalized to the band of β-actin. Results are expressed as mean ± SD values ($$n = 4$$). Different superscript letters (a–d) indicate significant differences between values in the column ($p \leq 0.05$).* **Figure 9:** *Effect of compound 3 on caspase-9 and caspase-3 activities in oxidative-stress-induced ARPE-19 cells. Cells were pre-treated with compound 3 at 25, 50 and 100 µg/mL for 24 h, followed by incubation with H2O2 at 400 µM for 60 min. The treated cells were homogenized in a hypotonic buffer to obtain the part of the supernatant. The supernatant was determined on (A) caspase-9 and (B) caspase-3 activities. Results are presented as mean ± SD values ($$n = 4$$). Different superscript letters (a–e) indicate significant differences between values in the column ($p \leq 0.05$).* **Figure 10:** *Evaluation of the effect of compound 3 on SOD, CAT, and GPx activities, and GSH levels in oxidative-stress-induced ARPE-19 cells. Cells were pre-treated with compound 3 at 25, 50 and 100 µg/mL for 24 h, followed by incubation with H2O2 at 400 µM for 60 min. (A) SOD, (B) CAT, and (C) GPx activities, and (D) GSH levels using the respective assay kits. Results are presented as mean ± SD values ($$n = 4$$). Different superscript letters (a–f) indicate significant differences between values in the column ($p \leq 0.05$).* **Figure 11:** *A schematic showed the proposed mechanism. (A) H2O2 induces oxidative stress in ARPE-19 cells, which leads to cell death via MAPKs signaling and apoptosis pathways. (B) The protective effect of compound 3 on oxidative-stress-induced ARPE-19 cells; pretreatment of compound 3 could protect RPE-19 cells against induced oxidative stress through its ability to scavenge ROS and enhance enzymatic (SOD, GPx, and CAT) and non-enzymatic (GSH) antioxidants.* TABLE_PLACEHOLDER:Table 1
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|
---
title: Ceruloplasmin Interferes with the Assessment of Blood Lipid Hydroperoxide Content
in Small Ruminants
authors:
- Stefano Cecchini Gualandi
- Raffaele Boni
journal: Antioxidants
year: 2023
pmcid: PMC10045310
doi: 10.3390/antiox12030701
license: CC BY 4.0
---
# Ceruloplasmin Interferes with the Assessment of Blood Lipid Hydroperoxide Content in Small Ruminants
## Abstract
Simple and inexpensive analytical methods for assessing redox balance in biological matrixes are widely used in animal and human diagnostics. Two of them, reactive oxygen metabolites (ROMs) and total oxidant status (TOS), evaluate the lipid hydroperoxide (LOOH) content of the sample and are based on iron-mediated mechanisms. However, these tests provide uncorrelated results. In this study, we compared these two tests in the blood serum of goat kids and lambs, together with an evaluation of ceruloplasmin (CP) oxidase activity. No significant correlation was found between ROMs and TOS, or between TOS and CP oxidase activity, in either species. Conversely, ROMs and CP oxidase activity were highly correlated in both kid and lamb samples ($p \leq 0.001$). A significant progressive reduction in the analytical signal in the ROMs assay was observed when sodium azide, an effective CP inhibitor, was added to the samples before the assay ($p \leq 0.001$). This decrease was related to sodium azide concentration ($p \leq 0.01$) and was not found when sodium azide was added at the same concentrations in the TOS assay. These findings suggest that ROMs, unlike TOS, may be affected by CP, which interferes with LOOH detection in blood samples.
## 1. Introduction
Redox status is a condition that is increasingly investigated in organisms for the evaluation of either physiological or pathological mechanisms. Redox homeostasis is the result of a delicate balance between the production of oxidants and antioxidants. Reactive oxidants, such as reactive oxygen and nitrogen species (ROS and RNS), when produced in small amounts as by-products of aerobic metabolism, play a pivotal role in many physiological functions, regulating many signaling pathways and activating the adaptation and protection behaviors of organisms under stress [1,2]. In this case, the potential harmful effects of these compounds are adequately counteracted by the antioxidant defense system [3,4]. When oxidant production exceeds cellular antioxidant capacity, organisms can experience oxidative stress (OS), with failure in the prevention and repair of oxidative damage to macromolecules that, in turn, affects their structure, causing dysfunction of their physiological activities [5,6].
Most ROS analytical assessments are complex and impractical for clinical or screening applications [7]. Furthermore, since ROS are unstable molecules, their quantification can lead to misleading results [8]. Some alternative analytical assays have been developed that are mainly based on evaluating lipid hydroperoxide (LOOH) content. LOOHs are unstable molecules and the primary oxidation products of polyunsaturated fatty acids (PUFAs); they generate new peroxyl and alkoxy radicals and decompose to form secondary products [9]. LOOH detection methods have been largely applied in both human and animal blood samples and are also available as commercial kits [10,11]. They are mainly based on two different methods: oxygen metabolites (ROMs) [12] and total oxidant status (TOS) [13]. Both methods are based on iron-mediated mechanisms, and the oxidant potential of a sample is measured as the content of substances able to oxidize a chemical compound in the test solution. However, their detection mechanisms are quite different. In fact, the ROMs test assumes that LOOHs generate alkoxyl (R-O●) and peroxyl (R-OO●) radicals following the release of iron ions from metalloproteins in an acidic buffered solution (Fenton reaction). These radicals oxidize an alkyl-substituted aromatic amine (N,N-diethyl-para-phenylenediamine, DEPPD), generating a pink-colored derivative, which is spectrophotometrically measured at 530 nm [12]. The TOS assay instead evaluates the content of oxidant molecules in a sample through the oxidation of ferrous (Fe2+)-o-dianisidine dihydrochloride complex to ferric (Fe3+) ions. The ferric ions form a colored complex with the chromogen xylenol orange in an acidic medium, which is spectrophotometrically measured at 550 nm [13].
Although both tests evaluate the total LOOH content in plasma or serum, when applied to the same samples, they return non-comparable and unrelated results in both human [13,14] and animal [15] analyses. Previous papers even reported LOOH values that were 100 times higher in goat kid sera using the ROMs test with respect to the TOS test [15,16]. Similar results have been obtained in human samples [13], in which the LOOH levels assessed using the ROMs test largely exceed the cytotoxicity threshold level [17].
The reason for the discrepancy between these two methods is likely due to the use, in the ROMs method, of the alkylamine chromogen DEPPD, which is also a substrate for the enzymatic analysis of ceruloplasmin (CP) [18]. CP is a glycoprotein and the major copper-carrying protein in the blood, and is also involved in iron metabolism. It acts as a ferroxidase enzyme by oxidizing ferrous to ferric ions with the reduction of molecular oxygen to water. The reactive ferrous ions are, therefore, unavailable to catalyze the decomposition of hydrogen peroxide to produce hydroxyl radicals [19]. Thus, CP may be considered an antioxidant. It is also a potent physiologic inhibitor of myeloperoxidase [20], an oxidative neutrophil enzyme responsible for protein and lipid modifications, as well as for the increase in LOOHs during inflammation [21]. Several studies found a strong positive correlation ($p \leq 0.001$) between ROMs-evaluated LOOH content and CP oxidase activity in both human [13] and animal [15] samples. This finding suggested low specificity of the ROMs test since part of its analytical value may be attributed to substances other than the OS-produced metabolites. In line with this, the addition of sodium azide, an effective CP inhibitor, to human serum extinguishes any relationship between ROMs and CP oxidase activity, and significantly decreases the analytical signal of the ROMs assay [13]. Additionally, Kilk et al. [ 18] showed a progressive reduction in the absorbance values of the ROMs assay when increasing concentrations of sodium azide were added to human and bovine sera. A reduction in the analytical signal was also observed when pure solutions of human and bovine CP replaced the serum samples, suggesting that the ROMs test mainly measures the CP oxidase activity, and that LOOHs work as potential interfering molecules. Moreover, these authors found that sodium azide did not inhibit CP oxidase activity in chicken and wild redpoll sera, highlighting that LOOHs’ contribution to the test outcome in avian species is higher than in mammals [18].
This study aimed to validate the ROMs test’s effectiveness in detecting the oxidant status of serum samples collected from healthy young small ruminants. The choice to use young animals for this study was based on the need to reduce the possible sources of oxidation, which is more frequent in adult animals and is associated with the rearing system, production/reproductive conditions, and a greater occurrence of diseases, even if this is not evident [22]. To achieve this goal, the ROMs test was compared to either a TOS test or a CP oxidase activity assay. To discriminate the LOOH analytical signal from any CP interference, serum samples were further treated with increasing molar concentrations of sodium azide.
## 2.1. Animals and Blood Sampling
Blood samples were collected from sixteen Camosciata delle Alpi goat kids and sixteen Italian Merino-derived lambs that were randomly chosen from a private farm in the Potenza district (Italy). Pre-weaning goat kids and lambs were aged about 60 and 40 days and weighed 12.8 ± 0.7 and 14.2 ± 1.3 kg, respectively. To deepen and confirm the results, a new group of animals reared on another private farm in the province of Potenza was enrolled for a second trial. This group consisted of Grigia Lucana kids ($$n = 5$$) and Italian Merino-derived lambs ($$n = 5$$), as well as Grigia Lucana goats ($$n = 5$$) and Italian Merino-derived ewes ($$n = 5$$) in lactation. All the animals were clinically healthy and free from internal and external parasites. Evaluation of the animals’ health status was based on rectal temperature, heart rate, respiratory rate, appetite, and fecal consistency. Blood samples were collected from the external jugular vein into tubes without an anticoagulant; after clotting, the sera were obtained via centrifugation (2200× g for 10 min at 4 °C) and stored at −80 °C until analyses were performed. All procedures were carried out in strict accordance with the European legislation regarding the protection of animals used for scientific purposes (European Directive $\frac{2010}{63}$), as recognized and adopted by Italian law (DL $\frac{2014}{26}$). No animal suffered as a consequence of blood sampling.
## 2.2. Analytical Methods
Unless otherwise indicated, all reagents and media were purchased from Sigma-Aldrich (Milan, Italy).
Reactive oxygen metabolites (ROMs) were assessed as described by Alberti et al. [ 12]. Briefly, 10 µL of each sample was added in duplicate to each well of a microtiter plate and, subsequently, filled with 200 µL of an analytical mixture containing 100 mM acetate buffer solution, pH 4.8, supplemented with 0.37 mM N,N-diethyl-para-phenylendiamine (DEPPD) and 2.8 mM iron (II) sulfate heptahydrate (FeSO4·7H2O). After incubation (30 min at 37 °C), the optical densities (ODs) were read at 530 nm against a blank, where phosphate buffer saline replaced the sample, using a microplate reader (model 550, BioRad, Segrate, Milan, Italy). The assay was calibrated with tert-butyl hydroperoxide (t-BHP) and the results were expressed in terms of t-BHP equivalents (mM).
Total oxidant status (TOS) was assessed as described by Erel [13]. Briefly, 35 μL of samples were added in duplicate to each well of a microtiter plate and mixed with 225 μL Reagent 1 (150 μM xylenol orange, 140 mM NaCl, and 1.35 M glycerol in 25 mM H2SO4 solution, pH 1.75) and the ODs were read at 550 nm against a blank (see above) using the microplate reader. After that, 11 μL Reagent 2 (ferrous ion 5 mM and o-dianisidine 10 mM in 25 mM H2SO4 solution) was added to the mixture. After 5 min at 37°C, the ODs were again read at 550 nm. The assay was calibrated with t-BHP and the results are expressed in terms of t-BHP equivalents (μM).
To discriminate the analytical LOOH signal due to possible CP interference, both tests were repeated on pooled serum samples. Each pool was obtained by mixing, at random, four serum samples of each species, thus generating four distinct samples for each species. Then, each pooled serum sample was treated with increasing (from 1 to 1000 µM) molar concentrations of sodium azide just before performing the assays.
The evaluation of CP was based on its oxidase activity using o-dianisidine dihydrochloride (ODD) as a substrate, as described by Schosinsky et al. [ 23]. Briefly, serum samples were incubated in duplicate at 37 °C in the presence of 7.88 mM ODD in 0.1 M acetate buffer, pH 5.0. The light absorption variation in relation to the color intensity of the sample was measured using a spectrophotometer (SmartSpec 3000 UV/Vis, Bio-Rad, Segrate, Italy) against a blank (see above) at 540 nm after 5 min and 15 min of incubation using 9 M H2SO4 to stop the enzymatic reaction. The CP oxidase activity was expressed in units per liter (U L−1) in terms of consumed substrate and calculated as the difference between the two absorbance values [23].
## 2.3. Statistical Analysis
The analytical data, presented as means ± standard deviation (SD), consisted of the averages of three analyses performed for each parameter. The Kolmogorov–Smirnov test was used to determine the normality of the distribution of the data ($p \leq 0.05$). Differences between species in the ROMs, TOS, and CP values, and the effect of sodium azide on the LOOH assessment, were analyzed via one-way analysis of variance (ANOVA). Bonferroni pairwise comparison was conducted to discriminate differences in the mean analytical values of the ROMs assay at different sodium azide concentrations in comparison with either the lowest or the highest sodium azide concentrations. Bland–*Altman analysis* was performed to describe the agreement between the ROMs and TOS assays [24]. In particular, the differences between these two analytical methods (y-axis) were plotted against the average of the two analytical method (x-axis) values using the open-source software Jamovi (The Jamovi project, Version 2.3.21.0). Linear regression analyses were performed to check for possible correlations among the assessed parameters. p-values lower than 0.05 were considered to be statistically significant. All these statistical analyses were performed using SigmaPlot software for Windows (Version 11.0, Systat Software Inc., San Jose, CA, USA). The IC50 values, defined as the concentration of sodium azide that caused $50\%$ inhibition of the analytical signal in the ROMs assay, were analyzed using Microsoft Excel software.
## 3. Results
In the ANOVA analysis, there is a significant difference in all the analyzed parameters between the two small ruminant species, as reported in Table 1, with a discrepancy between the two analytical assays for the LOOH content. In fact, in the ROMs test, significantly higher LOOH values were found in goat kids than in lambs, whereas a significantly inverse result was found with the use of the TOS test. CP oxidase activity was more than two times higher in kids than in lambs.
The regression analyses did not detect any significant correlations between the ROMs and TOS values in either goat kid (r2 = 0.011, $$p \leq 0.696$$) or lamb (r2 = 0.150, $$p \leq 0.161$$) samples, or between the TOS and CP oxidase activity values in either goat kid (r2 = 0.059, $$p \leq 0.363$$) or lamb (r2 = 0.180, $$p \leq 0.143$$) samples. Conversely, ROMs and CP oxidase activity levels were highly correlated in both kid and lamb samples (Figure 1).
The poor agreement between these two different assays, both measuring LOOH content, was assessed using the Bland–Altman plot, which shows that the difference between the two methods tends to become larger as the values increase (Figure 2). In addition, all differences, except one, fell within the limits of agreement (mean ± 1.96 standard deviation).
The analysis of the data of the second trial (Table 2) that was carried out on a smaller number of animals and, in the case of goats, on different breeds, confirms the differences in the ROMs, TOS, and CP values between kids and lambs, although the comparison does not allow us to express significant differences due to the high individual variability and the small number of animals used. Upon comparing the data according to age, regardless of the species, adults showed lower levels of ROMs than juvenile animals (0.384 ± 0.143 vs. 0.679 ± 0.151 mM, $p \leq 0.001$), whereas upon comparing the data without considering age, there is a higher level of TOS in the ovine than caprine species (34.30 ± 19.57 vs. 15.45 ± 6.15 µM, $p \leq 0.01$).
When sodium azide was added to the samples before the execution of the two LOOH assays, the ROMs test values showed a significant progressive decrease with increasing micromolar concentrations of sodium azide (Figure 3) in both goat kid (Figure 3A) and lamb (Figure 3C) sera ($p \leq 0.001$), whereas no changes were found in the TOS values following the same treatment (Figure 3B,D). The ROMs values were significantly affected by sodium azide at the lowest concentrations of 31.25 µM ($p \leq 0.001$) and 7.81 µM ($$p \leq 0.004$$) in goat kids (Figure 3A) and lambs (Figure 3C), respectively. On the other hand, the concentrations of sodium azide that ensured the highest reduction in the analytical signal were 250 µM ($p \leq 0.001$) and 125 µM ($$p \leq 0.003$$) in the goat kid (Figure 3A) and in lamb (Figure 3C) samples, respectively. Finally, the IC50 values of sodium azide were 98.51 µM and 72.91 µM in the goat kid and lamb samples, respectively. The same treatment with sodium azide also produced results similar to those observed in juveniles when conducted on blood serum from adult goats and sheep (Figure S1).
## 4. Discussion
In this study, LOOH levels, as a biomarker of oxidative status, were detected in the blood sera of both adult and juvenile small ruminants using two different methods: ROMs and TOS assays. In addition, in the same blood samples, CP oxidase activity was also evaluated. The analytical results obtained for these three assays are in line with those reported by other authors, as is the large variability that was found among individuals in their analytical data [15,25,26,27,28,29,30,31]. The differences that emerged between species, as detected in the first experimental dataset and confirmed by the data of the second trial, to which was also added a significant difference between ages, are not supported by the literature due to a lack of these types of comparative analyses between these species. The ROMs and TOS values were not significantly correlated in either goat kid or lamb sera, although both methods were designed to assess the LOOH levels, confirming results previously found in both human and goat serum samples [13,14,15]. Moreover, the poor agreement that emerged in the Bland–Altman plot indicates the existence of proportional bias and, hence, the two methods did not agree equally throughout the range of measurements.
A highly significant correlation was, however, found between ROMs and CP oxidase activity levels in both goat kid and lamb sera ($p \leq 0.001$). This finding is unexpected considering the role played by CP as a strong inhibitor of myeloperoxidase (MPO) [20]. In fact, since MPO is associated with an increase in LOOHs during inflammation [21], CP, as an MPO inhibitor, should decrease LOOH and, hence, ROMs and TOS levels [13]. In line with this, previous studies [15] detected a high positive correlation ($p \leq 0.001$) between TOS and MPO activity in the blood serum of goats kid. Moreover, in nitrosative stress, stable end-products of nitric oxide radicals (NO•), such as NOx, were found to be positively correlated with TOS values in goat kids [15], as well as in cattle [32] and humans [33,34]. This finding is of particular interest as the simultaneous evaluation of NOx and MPO activity can provide important indications of the role played by OS in human disorders [35,36]. Conversely, ROMs values, despite representing alternative assessments of LOOH content [12], were not found to be associated with oxidant and antioxidant biomarkers in human and goat sera [14,15], but only with the CP oxidase activity, as found in the present results and in other studies [13,15]. The relationship between ROMs and CP oxidase activity may bias the ROMs analytical method, making it poorly specific for LOOH assessment. In fact, the ROMs assay returns unrealistic LOOH levels in some mammalian species, which is attributable to analytical interference with CP and other serum components [13,18]. This assumption was demonstrated using either pure solutions of human and bovine CP or human and bovine sera that were treated with sodium azide, a strong CP inhibitor [13,18]. Based on these findings, Kilk et al. [ 18] speculated that a ROMs assay would mainly detect CP with potential interferences from LOOHs, iron level, thiols, and albumin in human and bovine samples. On the other hand, in some avian species, the ROMs assay represents a method of choice for the evaluation of LOOHs considering that in these species, CP does not seem to interfere with the ROMs assay, as demonstrated by the absence of an effect of sodium azide treatment on the outcomes of the analytical ROMs assay [18]. Therefore, a ROMs assay cannot discriminate between LOOHs and CP, biasing the results, at least in human and bovine serum samples [13,18]. However, Colombini et al. [ 37] did not find any significant correlations between ROMs and CP values or copper content in human sera, and thus, supported the analytical specificity of the ROMs assay. These conflicting results require further studies aimed at definitively clarifying the reliability of the ROMs test for the evaluation of the oxidative status of organic matrices.
To further support potential interference of the CP with the analytical results of a ROMs assay, however, different pH conditions are foreseen by the two methods under examination. Generally, pH variation has a marked effect on the rate of the enzymatic reaction; in fact, pH alters the charge of functional residues in substrate binding or in the catalysis process itself. Additionally, enzymes can also undergo changes in their conformation, together with changes in pH [38]. The reduction in CP oxidase activity at low pH may be due to the effect of the pH of the analytical mixture in ionic groups on the active site, or variation in the ionic state of the substrate or enzyme–substrate complex [39]. The optimum pH for CP oxidative activity assessment depends not only on the nature of the chemical substrate, but also on the different animal species. Thus, for example, in humans, the optimal pH is 5.4, but at pH 4.6, enzymatic activity is already inhibited by 50–$80\%$ [39]. In dogs, the best analytical condition is obtained at pH 5.2, whereas at pH 4.8, CP oxidase activity decreases by about 10–$20\%$ [40]. In pigs, Martínez-Subiela et al. [ 41], using o-dianisidine dihydrochloride as a substrate, showed that the optimal pH for detecting CP oxidase activity is 4.6 with a progressive decrease up to about zero at pH 4.2. In our study, the pH of the analytical mixtures was 4.8 and <2 in the ROMs and TOS assays, respectively. While at pH conditions foreseen by the ROMs assay, CP oxidase activity should be partially maintained, and at the very low pH of the TOS assay, complete enzymatic deactivation of CP is likely to occur. Hence, the results of the present study confirm, in young small ruminants, the low specificity of the ROMs assay in the detection of LOOH content, as well as the interference of CP in the analytical method.
The different concentrations of LOOH detected using these two methods is also worth reflecting on. While the analytical values of the TOS assay vary around a few µM t-BHP equivalents, the ROMs assay returns values about 100 times higher. This agrees with the values recorded in human samples [13], in which the LOOH levels assessed using a ROMs test were 350 times higher than those obtained using a TOS assay, and far beyond the cytotoxicity threshold indicated in the literature [4,17]. At the same time, ROMs-assessed LOOH values in livestock species are remarkably lower than in humans [25,26,28,42], whereas TOS-assessed LOOH values do not greatly differ between livestock species and humans [43,44,45,46]. This discrepancy may be attributable to the higher CP oxidase activity in humans than in animal species [23,47,48,49,50]. To support this hypothesis, our results found that TOS-assessed LOOH values were higher in lambs than in goat kids, whereas ROMs-assessed LOOH content was higher in goat kids than in lambs. Contextually, the CP oxidase activity in kids was about double that in lambs. Thus, the lower detection of LOOH content using the ROMs test in lambs could be attributable to the lower CP interference in the ROMs analysis, which is associated with lower CP plasma concentration in this species. Moreover, the treatment of the serum samples with a progressively increasing sodium azide concentration led to a progressive decrease in the analytical signal, which reached absorbance values close to those of the blank at the highest sodium azide concentration.
Another finding highlighted using the ROMs assay in young small ruminants is the progressive reduction in or eradication of the analytical signal with increasing sodium azide concentration. This demonstrates that, at least in our animal models, the ROMs assay was able to detect only the CP content. In human and bovine serum samples, Kilk and colleagues [18], despite detecting a reduction in the analytical signal due to sodium azide, observed a residual absorbance value, even at the highest sodium azide concentrations. This suggests that the ROMs assay is able to cumulatively detect LOOH and CP content without discriminating between these two molecules. The discrepancy that emerged between the results of the present study and those of Kilk et al. [ 18] may be attributed, together with species-specificity, to the young age of the animals enrolled in the present study. In fact, young animals usually have a lower oxidative status than adults, with the exception of the neonatal period [22]. Thus, although the ROMs assay was criticized as a simultaneous measurement of LOOH and CP in humans, our results demonstrate that, at least in young small ruminant specimens, it mainly reflects CP oxidase activity.
## 5. Conclusions
Oxidative status, measured as LOOH content, in the blood serum of lambs and goat kids, was assessed using two different methods, reactive oxygen metabolites (ROMs) and total oxidant status (TOS), together with ceruloplasmin (CP) oxidase activity. Although the ROMs and TOS tests are both designed to measure the LOOH content in clinical and experimental practice, and both are based on iron-mediated mechanisms, the present study demonstrated that these tests are not comparable to each other. In this regard, upon treating samples with sodium azide, a potent CP inhibitor, the analytical signal of the ROMs test was almost completely eradicated, but not that of the TOS test; this suggests that CP interfered with the ROMs assessment, as previously found in humans. Therefore, the present findings highlight the low diagnostic specificity of the ROMs test in measuring the LOOH content in blood serum because it mainly detects CP oxidase activity, at least in young small ruminants.
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|
---
title: 17β-Estradiol Suppresses Gastric Inflammatory and Apoptotic Stress Responses
and Restores nNOS-Mediated Gastric Emptying in Streptozotocin (STZ)-Induced Diabetic
Female Mice
authors:
- Jeremy Sprouse
- Chethan Sampath
- Pandu Gangula
journal: Antioxidants
year: 2023
pmcid: PMC10045314
doi: 10.3390/antiox12030758
license: CC BY 4.0
---
# 17β-Estradiol Suppresses Gastric Inflammatory and Apoptotic Stress Responses and Restores nNOS-Mediated Gastric Emptying in Streptozotocin (STZ)-Induced Diabetic Female Mice
## Abstract
Gastroparesis (Gp) is a severe complication of diabetes mellitus (DM) observed predominantly in women. It is characterized by abnormal gastric emptying (GE) without mechanical obstruction in the stomach. Nitric oxide (NO) is an inhibitory neurotransmitter produced by neuronal nitric oxide synthase (nNOS). It plays a critical role in gastrointestinal (GI) motility and stomach emptying. Here, we wanted to demonstrate the protective effects of supplemental 17β-estradiol (E2) on NO-mediated gastric function. We showed E2 supplementation to alleviate oxidative and inflammatory stress in streptozotocin (STZ)-induced diabetic female mice. Our findings suggest that daily administration of E2 at therapeutic doses is beneficial for metabolic homeostasis. This restoration occurs via regulating and modulating the expression/function of glycogen synthase kinase-3β (GSK-3β), nuclear factor-erythroid 2 p45-related factor 2 (Nrf2), Phase II enzymes, MAPK- and nuclear factor kappa-light-chain-enhancer of activated B cells (NFkB)-mediated inflammatory cytokines (IL-1β, IL-6, TNFα, IGF-1), and gastric apoptotic regulators. We also showed E2 supplementation to elevate GCH-1 protein levels in female diabetic mice. Since GCH-1 facilitates the production of tetrahydrobiopterin (BH4, cofactor for nNOS), an increase in GCH-1 protein levels in diabetic mice may improve their GE and nitrergic function. Our findings provide new insights into the impact of estrogen on gastric oxidative stress and intracellular inflammatory cascades in the context of Gp.
## 1. Introduction
Diabetic gastroparesis (DGp) is a gut motility disorder associated with abnormal gastric emptying (GE) when there is no mechanical obstruction along the gastrointestinal (GI) tract [1,2]. DGp is characterized by severe nausea, vomiting, bloating, early satiety, abdominal pains, nutritional deficiencies, and poor glycemic control [3]. DGp is a multifactorial condition caused by malfunction in the enteric nervous system (ENS) as well as the excitatory and inhibitory neurons [4,5]. Findings from recent studies suggest that patients with DGp lack functional coordination between these cell types [2,3,6]. Nitric oxide (NO) is an inhibitory non-adrenergic, non-cholinergic (NANC) neurotransmitter in the gut produced by neuronal nitric oxide synthase (nNOS) and secreted by inhibitory enteric neurons. It plays an important role in controlling gastrointestinal motility and transit time [4]. Therefore, DGp is associated with the dysregulation of gut–brain interaction.
Sex-related differences in the presentation of gastric motility disorders are well documented in both human and animal studies. Women and female rodents tend to experience more severe symptoms of Gp compared to their male counterparts due to naturally slower GE rates in females [7,8,9,10]. Young, healthy women are also more prone to experience Gp than age-matched men [7,8,9,10,11]. Various studies have demonstrated a positive correlation between Gp symptoms and menstruation, use of hormonal contraceptives, and use of hormone replacement in postmenopausal women [12,13]. Recent data from animal studies suggest that diabetes is more deleterious to the female ENS plexus and thus GI dysmotility [9,14,15]. Furthermore, our laboratory has demonstrated the role of ovarian hormone receptors and antioxidant activators in gastric motility in rodent models of type 2 diabetes mellitus (DM) [16,17,18,19]. These studies were key in identifying several roles that estrogen receptors and nuclear factor-erythroid 2 p45-related factor 2 (Nrf2) activators play in overcoming the insults of hyperglycemia, obesity, and inflammation on the oxidative stress response and gastric homeostasis. Particularly, we examined the systemic and gastrointestinal effects of a diet-induced hyperglycemia model in causing delayed and accelerated GE in the presence and absence of ovaries, respectively [16,17]. Through these models, we demonstrated gastric estrogen receptor influence in ovary-intact and ovariectomized rodent models that were exhibiting elevated circulatory estrogen. This study provides novel insight in evaluating the physiologic and therapeutic effects of estrogens on restoring gastric fitness in an STZ-induced diabetic mouse model mimicking type 1 DM. Here, we provide encouraging evidence of estrogenic effects on [1] Nrf2-mediated antioxidant protection and [2] gastric apoptotic markers, while further exploring [3] nuclear factor kappa B subunit 1 (NFκB) and 10 gut inflammatory cytokines in the context of alleviating the pathogenesis of gastric motility. Several studies have also identified elevated levels of estrogen and NO as the primary contributors to the observed slower GE in both pregnant and non-pregnant healthy rodents [8,20,21]. Although therapeutic options for Gp exist, many currently available drugs cause debilitating side effects and may not improve overall quality of life [6,22]. The influence of estrogens on the NO-mediated component of the gastric neuromuscular plexus is poorly understood. Understanding the role of estrogen in this aspect may be the key to explaining the sexual dimorphism observed in Gp and GE rates. This study further elaborates on the understanding of how supplemental estrogen, at physiologic and therapeutic levels, can also influence a disrupted nitrergic component of the gastric motility apparatus in an STZ-induced diabetic mouse model.
Animal studies have provided tremendous insight into the role of sex hormones in GE. Estrogens are known to mediate genomic and non-genomic biological actions through nuclear, cytoplasmic, and membrane-bound receptors [21,23]. Two estrogen receptors (ERs) are classically defined as ligand-activated transcription factors: Erα (alpha) and Erβ (beta). ERα and ERβ are expressed from two different genes and have various actions in different tissue systems of the gut. While ERs exist in the gastric and small intestinal mucosa, their presence is poorly documented in the gastrointestinal smooth muscle or ENS [24]. We have recently shown that ER activation restores glucose homeostasis, NO-mediated nitrergic relaxation, GE, and antioxidant and inflammatory responses to appropriate levels in high-fat diet-induced diabetic female mice [16].
Physiological estrogen levels fluctuate widely in humans and female rodents. Normal circulatory estrogen levels can range from very low in the diestrus stage to very high in the proestrus and estrus stages of the mouse reproductive cycle [25]. Estradiol (E2) has a myriad of effects on different organ systems when supplemented at different doses. It has been shown to exhibit dose-dependent responses at the cellular, tissue, organ, and whole-body levels [23,26,27,28]. In this study, we sought to demonstrate the benefits of supplemental E2 on NO-mediated gastric function, oxidative stress response machinery, and gastric apoptosis in diabetic female mice. We chose four different supplemental E2 doses that have been previously shown to mimic physiological, supraphysiological, and therapeutic concentrations in mice. The purpose of this study was to uncover the effects of E2 on diabetic Gp, NO-mediated gastric function, and the oxidative stress and inflammatory responses in female mice with STZ-induced diabetes.
## 2.1. Animals
All experiments were approved by the Institutional Animal Care and Use Committee (e-protocol no. 17-09-764 dtd $\frac{03}{05}$/2018) at Meharry Medical College (MMC). Adult female C57BL/6J mice aged 8–9 weeks were purchased from The Jackson Laboratory (Bar Harbor, ME, USA). All animals were housed in a vivarium under standard conditions and allowed access to food and water ad libitum.
## 2.2. Experimental Design and STZ-Induced Diabetes
All mice were randomized and divided into two groups: control mice and mice treated with streptozotocin (STZ) to induce DM [26]. After calculating crude power analysis for study significance, we employed a commonly used methodology to induce diabetes with STZ [29,30]. The control mice were injected with sodium citrate vehicle buffer (pH 4.5). Mice in the STZ group were injected intraperitoneally with 0.1 mmol/L STZ in sodium citrate buffer, pH 4.5 (S0130, Sigma Chemical Co., St. Louis, MO, USA) at 50 mg/kg once a day for five consecutive days to induce persistent hyperglycemia, as described previously [31]. Body weight and circulatory glucose levels were assessed weekly to confirm diabetes induction via tail vein blood and a standard glucometer. After diabetes had been established, the diabetic mice were randomly assigned to four E2 treatment groups: 0.001 mg/kg b.w. ( $$n = 6$$), 0.005 mg/kg b.w. ( $$n = 6$$), 0.25 mg/kg b.w. ( $$n = 6$$), or 1.0 mg/kg b.w. ( $$n = 6$$). These doses have been shown to mimic physiological (0.001 mg/kg b.w.), peak physiological (0.005 mg/kg b.w.), and therapeutic (0.25 mg/kg b.w. and or 1.0 mg/kg b.w.) doses of E2 [16,28,32,33]. Dosing injections were administered intraperitoneally once a day at the same time each day for six weeks. GE and organ bath studies were conducted the day after the final dosing regimen.
## 2.3. Measurement of Gastric Emptying
Solid GE studies were executed as previously described [16,17,34]. Briefly, each group of mice was fasted overnight and then fed the next morning with a known amount of food with water for 3 h. At the termination of the feeding period, the mice were placed in a fresh cage and fasted for 2 hr. The leftover food was weighed to calculate the amount of food consumed. After the 2 h fasting zone, the mice were sacrificed, and stomach weights were recorded prior to emptying the stomach contents and again after. The rate of GE was calculated as follows: GE (% in 2 h) = (1 − gastric content/food intake) × 100. Gastric antrum tissues were harvested, snap frozen, and stored at −80 °C.
## 2.4. Neuromuscular Recording with Electric Field Stimulation
NO-mediated gastric relaxation was measured as reported previously [35]. Circular muscle sections of the gastric antrum were suspended between L-shaped tissue hooks in 5 mL organ baths containing Krebs buffer (pH 7.4) at 37 °C and continuously bubbled with $95\%$ O2, $5\%$ CO2 (DMT-USA, Inc., Ann Arbor, MI, USA). Tension of the neuromuscular strip was monitored with an isometric force transducer and analyzed with a digital recording software. A total of 2 g of passive tension was applied to the strip over an hour-long equilibration period through incremental increases of 0.5 g at 15 min intervals. The gastric neuromuscular strips were then treated with atropine, phentolamine, and propranolol (10 µM each) for 30 min to inhibit adrenergic and cholinergic transmission. Following exposure and contraction with 5-HT (100 µM), the muscle strips were stimulated with EFS (1 ms pulses for 1 min at 2 Hz) to elicit NANC relaxation. The changes in muscle activity were measured. For confirmation, this response was mediated by NO, the relaxation was measured after incubation with NO inhibitor, Nω-Nitro-L-arginine methyl ester (L-NAME, 30 min; 100 µM, N5751, Sigma, St. Louis, MO, USA). Analysis of area under the curve (AUC) of EFS-induced relaxation (AUCR) for 1 min and the baseline for 1 min (AUCB) was used to compare groups using the equation: (AUCR-AUCB)/weight of the tissue (mg) = AUC/mg tissue.
## 2.5. Evaluation of 17β-Estradiol, Insulin, MDA, IL-6, TNFα, IGF-1, and Total Nitrite Concentrations in Mouse Serum
Blood was collected from euthanized mice via cardiac puncture. The serum was isolated and stored at −80 °C until use. ELISA kits for 17β-estradiol (K3830, BioVision, Inc., Milpitas, CA, USA), insulin (90080, Crystal Chem, Elk Grove Village, IL, USA), malondialdehyde (MDA), and serum cytokines (tumor necrosis factor (TNF)-α, interleukin (IL)-6, and insulin-like growth factor 1 (IGF-1)) (EA-1091, Signosis, Santa Clara, CA, USA) were used to measure the serum levels of these compounds. Systemic total serum nitrite was assessed using a standard colorimetric assay per manufacturer’s recommended methodology (K262, BioVision, Inc., Milpitas, CA, USA).
## 2.6. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) Analysis
Gastric antral neuromuscular tissues were harvested from mice and frozen in liquid nitrogen. Total RNA was extracted using TRIzol (Thermo Fisher Scientific, Waltham, MA, USA) per manufacturer’s protocol. The quality of RNA was determined by NanoDrop (Thermo Fisher Scientific), and the quantity was estimated by an Agilent 2100 bioanalyzer (Agilent Technologies, Houston, TX, USA). To eliminate any contaminating DNA, RNA was treated with RNase-free DNase (Invitrogen). One microgram of DNase-treated RNA was used for cDNA synthesis. The iScript cDNA synthesis kit (Bio-Rad, Hercules, CA, USA) was used to synthesize cDNA. One microliter of cDNA was used for each reaction together with the corresponding target primers. Primer sequences for target genes are listed in Table 1. Quantitative RT-PCR (qRT-PCR) was performed using the SYBR Green (Bio-Rad, Hercules, CA, USA) method. Cycling conditions were 95 °C for 3 min followed by 45 cycles of 95 °C for 30 s and 55 °C for 1 min. mRNA levels for target genes were normalized to mRNA levels for the β-actin gene, and threshold cycle (CT) numbers were calculated (i.e., 2−ΔΔCT, the Ct method) according to manufacturer’s instructions. All studies were performed in the MMC Molecular Core Laboratory.
## 2.7. Subcellular Fractionation
The tissue lysates were suspended in fractionation buffer (10 mM HEPES (pH 7.9), 10 mM KC1, 1.5 mM MgCl2, $0.1\%$ NP-40, 0.5 mM NaF, 200 mM Na3V04, and 1× protease inhibitor cocktail). The cells were incubated on ice for 15 min with shaking. Lysates were centrifuged at 2600× g at 4 °C, and supernatants representing cytosolic fraction were collected. The precipitates were then resuspended with the modified RIPA buffer containing 1× protease inhibitor cocktail and incubated on ice for 20 min with periodic vortexing. The lysates were then cleared by centrifugation at 10,000× g at 4 °C, and supernatants were used as the nuclear fractions.
## 2.8. Gel Electrophoresis and Western Blot Analysis
Gastric antrum samples were homogenized, and total protein level was estimated for each lysate via bicinchoninic acid (BCA) assay. Equal amounts of protein (30 µg) from each sample were separated on $6\%$ and $12\%$ SDS polyacrylamide gels. The gel was then transferred to nitrocellulose membranes in cold environment. Each membrane was incubated in $5\%$ dried non-fat milk in TBST for 1 h and then incubated overnight with respective primary polyclonal antibodies including: ERα, (sc-8005,1:500), ERβ (sc-390243, 1:500), GCH-1 (sc-271482, 1:500), GCLC (sc-390811, 1:1000), Nrf2 (sc-365949, 1:1000), GCLM (sc-55586, 1:1000), MAPK (sc-81621, 1:1000), NFκB (sc-8414, 1:1000), and NQO-1 (sc-376023, 1:1000) (each from Santa Cruz Biotechnology, Santa Cruz, CA, USA). nNOSα (N-terminal, ab76067, 1:1000) was purchased from Abcam (Cambridge, MA, USA). Following incubation, the membranes were washed three times for 5 min each time in $0.1\%$ TBS-Tween and then exposed to horseradish peroxidase-conjugated secondary antibody (Santa Cruz Biotechnology, Santa Cruz, CA, USA) (1:1000) for 1 hr at room temperature. The membranes were visualized using an ECL Western blotting detection reagent (GE Healthcare Bio-Sciences Corp., Piscataway, NJ, USA), and the optimal reactive bands were analyzed using ImageQuant 500 (GE Healthcare Bio-Sciences Corp., Piscataway, NJ, USA). Optical densitometry was measured using Image Lab software (BioRad, Hercules, CA, USA). Blots were stripped and blocked overnight in $5\%$ milk in TBST. Stripped blots were re-probed with β-actin polyclonal antibody (Sigma Chemical, St. Louis, MO, USA) for 30 min to enable normalization of luminescence signals between samples.
## 2.9. Statistical Analysis
All data are presented as mean ± standard error (SE). Statistical significance among groups was measured using Student’s t-test for homogeneity and the Tukey test after one-way analysis of variance (ANOVA). A p value of less than 0.05 was considered statistically significant.
## 3.1. E2 Supplementation Normalized Body Weight, Blood Glucose Levels, Oxidative Stress Response, and Levels of Circulatory Inflammation Markers in STZ-Induced Diabetic Female Mice
We measured the blood glucose levels and body weights of the mice weekly to first confirm the onset of STZ-induced DM and then to examine the response to E2 therapy during the six-week treatment regimen (Table 2). We also measured the circulatory concentrations of insulin, nitrite, E2, MDA, and inflammatory cytokines using commercially available ELISA kits (Table 2). We observed that STZ-treated female mice were highly susceptible to weight loss and hyperglycemia (STZ vs. CON) ($p \leq 0.05$). Interestingly, while E2 administration did not yield significant weight gain, mice that received therapeutic E2 dosages were marginally heavier than mice in the STZ-only group. Therapeutic doses of E2 also significantly decreased glycemia ($p \leq 0.05$), though not to pre-diabetic or healthy levels.
We found circulatory estrogen levels to be significantly reduced ($p \leq 0.05$) upon STZ treatment (CON: 33.4 ± 3.3 vs. STZ: 20.7 ± 2.8 ng/L). In addition, we also found E2 supplementation to significantly elevate serum estrogen levels in a dose-dependent manner. These observations suggest that E2 dosages used in this study could restore serum estrogen levels in diabetic mice up to levels comparable to those closer levels in control mice (Table 2).
The insulin levels in STZ-induced diabetic female mice were also decreased. Increasing doses of E2 supplementation did not significantly restore their insulin levels. Total serum nitrite levels are indicative of NO production in systemic circulation, whereas MDA levels are indicative of levels of reactive oxygen species and oxidative load. As shown in Table 2, total serum nitrate levels were diminished in STZ-induced diabetic mice. E2 supplementation at therapeutic doses (0.25 mg/kg b.w. and 1.0 mg/kg b.w.) substantially elevated their systemic nitrite levels. MDA concentrations were significantly elevated in STZ-induced diabetic mice. Similarly, E2 supplementation at therapeutic doses restored their MDA levels to levels comparable to those in healthy mice. Inflammation and oxidative stress are common sequela in DM [14]. We observed a substantial level increase for pro-inflammatory cytokines IL-6, TNFα, and IGF-1 in the diabetic mice. Daily E2 supplementation at the two highest doses (0.25 mg/Kg and 1.0 mg/Kg) resulted in a statistically significant reduction in the levels of these cytokines (Table 2).
Taken together, our data suggest that daily E2 supplementation influenced the blood glucose, as well as the inflammation and oxidative stress load in STZ-induced diabetic female mice.
## 3.2. E2 Supplementation Restored Gastric Emptying and Nitrergic Relaxation in STZ-Induced Diabetic Female Mice
As shown in Figure 1A, STZ-induced diabetic female mice displayed significantly delayed solid GE compared to control mice ($79\%$ for CON vs. $42\%$ for STZ, $p \leq 0.05$). E2 supplementation at 0.25 mg/kg restored GE to rates comparable to those in control mice ($p \leq 0.05$). E2 supplementation at other doses did not result in significant changes in the GE rates of the diabetic mice.
NO is the primary neurotransmitter fueling muscle relaxation in the gut. Low-frequency EFS (2 Hz) in an organ bath elicits inhibitory relaxation in the gastric antral neuro-musculature [35]. NANC inhibitory relaxation was severely impaired in STZ-induced diabetic mice, consistent with delayed solid GE. E2 supplementation restored NO-mediated relaxation in the gastric antrum of STZ-induced diabetic mice to levels comparable to those in healthy mice ($p \leq 0.05$, Figure 1B). Blockade of nNOS with L-NAME drastically diminished gastric relaxation in all mice (Figure 1B, grey bars). These results support the involvement of NO in this process. Taken together, our results show that E2 supplementation restored nitrergic function and GE in diabetic female mice to levels comparable to those in healthy mice.
## 3.3. E2 Supplementation Affected ERs and MAPK mRNA and Protein Levels in STZ-Induced Diabetic Female Mice
It is widely accepted that estrogen receptor signaling regulates many biological effects primarily via two receptor subtypes, ERα and Erβ [36]. These receptors function as ligand-activated transcription factors and intracellular signaling agents that perform the actions of estrogens [36]. We observed a reduction in the mRNA and protein levels for both receptors in STZ-induced diabetic mice. E2 supplementation in the diabetic mice at all doses used restored their mRNA and protein levels for these receptors to levels comparable to those in control mice (Figure 2A,B,D,E).
We have previously shown diabetic conditions and E2 to influence mitogen-activated protein kinase (MAPK) activation and signaling [33,34]. Here, our findings demonstrate marked decreases ($p \leq 0.05$) in p38/MAPK mRNA and protein levels in STZ-treated female mice (Figure 2C,F). E2 supplementation upregulated p38/MAPK mRNA and protein levels in the diabetic mice in a dose-dependent trend, with the highest doses exhibiting expression levels comparable to those observed in healthy control mice (Figure 2C,F).
## 3.4. E2 Supplementation Restored the Levels of GSK-3β, Cytosolic and Nuclear Nrf2, and Phase II Antioxidant Enzymes to Normal Levels in STZ-Treated Diabetic Female Mice
Emerging research suggests that glycogen synthase kinase-3β (GSK-3β) participates in oxidative stress homeostasis through its interaction with nuclear factor erythroid 2 p45-related factor 2 (Nrf2) [37,38]. Here, we observed elevated levels of GSK-3β in STZ-treated mice when compared to control mice (Figure 3A,C). E2 supplementation reduced GSK-3β levels in STZ-treated mice (Figure 3A,C). Nrf2 activation and its downstream effect on Phase II enzymes are crucial to combating cellular oxidative stress. Cytosolic Nrf2 is typically bound to Keap-1 in an inactive state. Active Nrf2 traverses the nucleus in a redox-rich state [39]. Here, we found the levels of cytosolic and nuclear Nrf2 in gastric antrum samples to be inversely proportional (Figure 3D,E). Supplementing STZ-treated mice with therapeutic doses of E2 normalized the Nrf2 levels in both cellular compartments, implying at least a partial restoration of Nrf2 activity in these mice.
Hyperglycemia is associated with increased oxidative stress. Although estrogens have been shown to possess antioxidant properties, not much is known about their role in co-regulating Phase II enzymes with Nrf2. Figure 3F–K depict the effects of estrogens on Phase II enzymes GCLC, GCLM, and NQO1 in diabetic mice. E2 supplementation increased the levels of gastric Phase II enzymes GCLC, GCLM, and NQO1 to various extents, bringing their levels closer to those in healthy mice (Figure 3F–K).
## 3.5. E2 Supplementation Normalized the Levels of Gastric nNOSα and GCH-1 Proteins in Diabetic Mice
NO-mediated relaxation has been reported as the predominant component that is severely compromised in female rodent models of diabetic Gp, specifically within the proximal regions of the stomach, colon, and intestinal smooth muscle [4,40,41]. Human and animal studies suggest that NO depletion due to nNOS dysfunction and expression may lead to delayed GE in diabetes and high oxidative stress conditions [4]. Since STZ-treated mice presented with depressed nitrergic relaxation in the gastric antrum, we measured their nNOS𝛼 levels in the presence and absence of E2 supplementation. We observed a marked decrease in nNOSα mRNA and protein levels in STZ-treated mice compared to control mice (Figure 4A,C). Interestingly, while nNOSα mRNA levels were elevated in the diabetic mice at all doses of E2 supplementation, nNOSα protein levels were significantly elevated ($p \leq 0.05$) only in diabetic mice receiving therapeutic doses of E2 (0.25 mg/kg and 1.0 mg/kg).
Tetrahydrobiopterin (BH4) is an essential cofactor for nNOS activity [42]. BH4 biosynthesis is chiefly regulated by two enzymes in converging pathways: GCH-1 (de novo) and DHFR (salvage). Our data demonstrate a decrease in GCH-1 expression in gastric antrum samples from STZ-induced diabetic female mice compared to control mice (Figure 4B,D). E2 supplementation significantly elevated GCH-1 protein expression ($p \leq 0.05$) in the diabetic mice, implying at least a partial restoration of BH4 biosynthesis (Figure 4D).
## 3.6. E2 supplementation Restored Levels of Nuclear NFκB and Gastric Pro-Inflammatory Cytokines in STZ-Treated Diabetic Mice to Levels Comparable to Those in Healthy Mice
Emerging evidence suggests that nuclear factor κB (NFκB) regulates the expression of various pro-inflammatory cytokines that influence gut function [43,44]. We observed a decrease in gastric IkkB and cytosolic NFκB levels in STZ-induced diabetic mice compared to healthy mice (Figure 5A,B). E2 treatment at 0.25 and 1.00 mg/kg restored the levels of gastric IkkB and cytosolic NFκB to levels comparable to those in healthy mice (Figure 5A–C). Conversely, nuclear NFκB levels were elevated in the gastric antrum of diabetic mice (Figure 5C). E2 treatment at therapeutic doses significantly reduced nuclear NFκB levels in diabetic mice to levels comparable to those in healthy mice. Furthermore, E2 restored the levels of several cytokines in diabetic female mice (Figure 5D) to levels comparable to those in healthy mice. Taken together, our observations suggest that E2 supplementation improved NFκB signaling and function in diabetic mice.
Next, we analyzed the levels of IL-1β and TNFα in the gastric antrum samples. Consistent with the increase in levels of nuclear NFκB, pro-inflammatory cytokines such as IL-1β and TNFα were also elevated in diabetic mice. E2 supplementation at therapeutic doses restored the levels of these cytokines in the diabetic mice to levels comparable to those in healthy mice (Figure 5E,F).
## 3.7. E2 Supplementation Affected the Expression of Apoptotic Markers Bax, BCL-2, and Caspase 3 in STZ-Induced Diabetic Female Mice
Excessive apoptosis of gastric cells is common in Gp patients with diabetic enteropathy [45]. B-cell lymphoma 2 (BCL-2) and Bcl-2-associated X protein (BAX) have been reported as pro- and anti-inflammatory regulators, respectively [46]. Here, we examined the protein levels of BCL-2, BAX, and caspase 3 in mouse gastric tissues. We observed a diminished level of BCL2 protein, the anti-apoptotic marker, in diabetic mice compared to healthy controls. E2 supplementation reversed this effect (Figure 6A). Conversely, the level for BAX protein, the pro-apoptotic marker, was elevated in diabetic mice compared to healthy controls. E2 supplementation at therapeutic doses reversed this effect (Figure 6A). Figure 6B illustrates the protein levels of gastric caspase 3. The level of cleaved caspase 3 was elevated in diabetic mice; E2 supplementation reversed this effect. Taken together, these observations indicate an increase in apoptosis in the gastric tissues of diabetic mice and that E2 supplementation at least partially reversed this effect.
## 4. Discussion
Gp is a chronic stomach motility disorder and common chief complaint among diabetic women [7]. It constitutes abnormal GE of solids and/or liquids in the absence of mechanical obstruction. Patients often suffer from debilitating symptoms, nutrition deficiencies, and overall decreased quality of life.
Diabetic women make up roughly $80\%$ of the diabetic Gp patient population [47]. Several proposed reasons for this phenomenon include intrinsically slower GE rates in females, elevated levels of sex steroid hormones, and the loss of nNOS expression and interstitial cells of Cajal (ICC); however, the molecular mechanism of disease occurrence and progression remains a mystery. The purpose of our present study was to elucidate the effects of E2 on nNOS-mediated gastric motility as well as the inflammation and apoptotic cascades in a mouse model of diabetic Gp. We demonstrated that daily E2 supplementation can improve metabolic and oxidative stress homeostasis as well as nNOS-mediated gastric motility in diabetic mice. Our findings suggest that E2 plays a protective role in diabetic gastric motility in female rodents.
DM is a metabolic disease associated with several intestinal disorders [48]. Rodent STZ-induced diabetic models have proven extremely useful in studying the DM pathology in mice and the potential effects of hormone supplementation [31,49,50,51]. STZ is an antibiotic that causes pancreatic islet β-cell destruction and is widely used experimentally to induce type 1 DM in rodents. These animals have been used extensively to demonstrate the effects of diabetes in several organ systems, including the stomach and GI tract [31]. In our study, we treated female mice with STZ to recapitulate several known metabolic characteristics in diabetes, including hyperglycemia, weight loss, depletion in insulin and estrogen levels, and elevation in the level of oxidative stress marker MDA [49,51,52,53]. Interestingly, women report several disruptions in sex hormone balance in diabetes [54,55]. Despite numerous findings that diabetes and hyperglycemia may influence estrogen levels in type 1 DM patients, very few studies evaluate circulating levels in rodent research models utilizing STZ. Our findings in female C57/BL6 mice suggest a significant decline in serum estradiol levels after diabetes induction with STZ, correlating with another study of diabetic nephropathy in Sprague-Dawley rats [56]. However, conflicting reports exist on the effects of STZ-induced diabetes on serum estradiol levels in rodents. Here, we provide our findings of this data in C57/BL6 mice that STZ-induced diabetes is consistent with a diminished serum estradiol level in mice, similar to the findings in human data [57]. Future studies geared towards nullifying the effects of ovarian hormones, estrogen and progesterone, and subsequent re-supplementation in the type 1 diabetic mouse gastric system will be important to our field.
Diabetic enteropathy causes GI autonomic nerve dysfunction, consequently disrupting ENS activity and function [45]. GE requires synchronous excitatory contractions and NO-mediated inhibitory relaxation of gastric musculature along the GI apparatus. NO is a crucial neurotransmitter that regulates the inhibitory plexus of gastrointestinal motility and transit time [58]. Here, we observed decreased NO-mediated nitrergic relaxation in gastric antrum specimens from diabetic mice that corresponded to delayed GE. Additionally, the levels of nNOSα and GCH-1 were diminished in STZ-treated mice compared to healthy mice. E2 supplementation restored levels of nNOSα and GCH-1 as well as nitrergic relaxation and GE in the diabetic mice. These observations align with our previous findings in mice with high-fat diet-induced type 2 diabetes [16]. Taken together, our results suggest that E2 can improve nNOS function via BH4 synthesis in both type 1 and 2 DM female mice.
Estrogen and its chief receptors are known to impact processes of the gastrointestinal tract in experimental animal models and in humans [21,36]. In the gastric and small intestinal mucosa, estrogen receptors facilitate genomic and non-genomic intracellular activity. In vitro studies have shown that estrogen can affect the contractile response and myoelectric activity of gastrointestinal smooth muscle [24]. Furthermore, E2 exerts both genomic and non-genomic effects on nNOS/NO abundance in vascular endothelium dilation [26,59,60]. The mechanisms responsible for these effects are not completely understood, and conflicting reports exist in the literature. Several studies have implicated increased pyloric ERβ in the development of GP in STZ-induced male diabetic rats [51]. Here, we demonstrated the effects of E2 supplementation on GE in STZ-induced diabetic female mice with Gp. Supplemental E2 at various doses improved GE in these mice by improving nitrergic relaxation. It is postulated that this system is often the most severely compromised in diabetic human patients.
We previously showed E2 to crosstalk with MAPK. The MAPK pathway bridges the switch from the receipt of extracellular signals to the initiation and progression of intracellular responses under both healthy and inflammatory conditions; the latter includes diabetes [61,62]. Previous studies have shown that p38/MAPK may interact with ER upon ligand binding to influence intracellular function. Here, we found the levels of gastric MAPK, ERα, and ERβ to be suppressed in diabetic mice, and E2 supplementation restored their levels to levels comparable to those in healthy mice. Furthermore, enhanced MAPK signaling has been shown to positively correlate with a depletion in inflammatory cytokines with elevated antioxidants, resulting in reduction of oxidative stress [18]. Our results corroborate with this finding because we found E2 supplementation to normalize the levels of oxidative stress marker MDA, Nrf2, Phase II enzymes (GCLC, GCLM, and NQO1), and serum and gastric inflammatory markers. It is noteworthy that E2 can also protect against oxidative stress in tissues expressing ERβ due to induction of GCLM. While the mechanism of the MAPK/E2 crosstalk is unclear, we have demonstrated their relationship in two animal models of diabetes [16]. Therefore, the potential role for both MAPK and E2 in regulating oxidative stress and inflammation warrants further investigation.
Oxidative stress is caused by imbalance between reactive oxygen species (ROS) and the antioxidant response system. It is a plausible etiologic factor that underlies the loss of nitrergic function in diabetic patients [17,39]. DM induces a state of high oxidative stress that affects various tissues. MDA is considered an indirect marker of oxidative stress [63]. Here, we observed the MDA levels to be significantly increased in diabetic mice, which was consistent with previously reported findings [64]. Nrf2 is an oxidative stress-sensitive transcription factor that regulates cellular protection against oxidative stress by activating an array of antioxidant response genes [65]. GSK-3β and Nrf2 have emerged as promising therapeutic targets for treating chronic diseases including several nervous system disorders and diabetes, due to their role in the cellular response to oxidative stress [37]. We have previously reported that Nrf2 loss in female mice resulted in elevated gastric GSK-3β levels, decreased tetrahydrobiopterin (BH4) levels, inhibition of neuronal NO (nNOSα, nitrergic neuron)-mediated gastric relaxation, and reduction in nitrite levels, subsequently leading to delayed GE [34]. Similarly, we found GSK-3β upregulation to cause delayed GE by reducing levels/activity of gastric PI3K/Akt/Nrf2, Phase II enzymes, and BH4-nNOSα in an obesity-induced diabetes mouse model [19]. It has been proposed that GSK-3β regulates Nrf2 translocation to the nucleus. Nrf2 phosphorylation by GSK-3β leads to nuclear exclusion and degradation, consequently derailing antioxidant stress response and Phase II enzyme induction. Studies from Pandy and colleagues suggest that estrogen supplementation inhibits GSK3 activity in the hippocampal neurons of ovariectomized rodents [63,66]. Interestingly, GSK-3β has also been shown to have a dual inhibition and activation effects on Nrf2 via NFκB [38,43]. Though several studies have reported diverging findings on the influence of estrogens on Nrf2 in various cell types, information on their manifestations in diabetic female mouse models is scant. Here, we observed an elevation in GSK-3β levels in diabetic female mice, which we could reverse with therapeutic doses of E2 supplementation. When GSK-3β levels were reduced in diabetic mice, so were the levels of cytosolic Nrf2 levels. We also found E2 supplementation to restore expression of Nrf2 and increase the levels of NQO1, GCLC, and GCLM in diabetic mice. NQO1 is a Nrf2-dependent quinone reductase enzyme that alleviates oxidative stress by acting as a superoxide reductase to modulate redox balance [67]. Another Nrf2-dependent Phase II enzyme is glutamate-cysteine ligase (GCL), a rate-limiting enzyme in glutathione synthesis composed of a catalytic subunit (GCLC) and a modifier subunit (GCLM) [68]. Our findings show the increase in nuclear Nrf2 levels upon E2 supplementation to positively correlate with the increase in the levels of these Phase II enzymes.
Importantly, our data show that E2 can repress hyperglycemia (HG), Nrf2 loss, and induction of apoptosis by decreasing levels of pro-inflammatory cytokines and reactive oxygen species (ROS). Recent studies have proposed the activation of NFκB signaling to be important in apoptosis of ICC in GI transit disorders [69,70,71,72]. NFκB represents a family of transcription factors that, when activated, regulates more than 400 various genes such as enzymes, cytokines, cell-cycle regulatory molecules, angiogenic factors, etc. These important transcription elements are normally held dormant in the cytoplasm by inhibitory molecules of the IκB family [43]. NFκB is activated by a wide variety of agents, including oxidative stress, inflammatory stimuli, cytokines, and endotoxins. When activated, NFκB regulates more than 400 various genes such as enzymes, cytokines, cell-cycle regulatory molecules, angiogenic factors, etc. [ 43,73]. NFκB has been linked to numerous human diseases, most notably diabetes. NF-κB is activated by IKK kinase, which phosphorylates and inhibits IKB-α, the endogenous inhibitor of NF-κB. Levels of IkkB and cytosolic NFκB were reduced in STZ-induced diabetic mice, whereas nuclear NFkB level was upregulated. E2 supplementation reversed these effects, corroborating data observed in starved MLO-Y4 cells [74]. Recent studies suggest Nrf2 and Phase II enzymes play a key part in inhibiting NFκB signaling. The Nrf2 and NFκB pathways have also been proposed to exert an inhibitory effect on each other at the transcription level [65,73]. Nuclear translocation of NFκB results in the secretion of pro-inflammatory cytokines, including tumor necrosis factor-a (TNF-α), interleukin 6 (IL-6), interleukin 10 (IL-10), and interleukin-1beta (IL-1β) [73,75,76]. Here, we found therapeutic doses of E2 supplementation restored the gastric and systemic levels of pro-inflammatory markers (IL-1β and TNFα) to healthy, pre-stress levels.
Inflammation overload, combined with oxidative stress, can activate intrinsic and extrinsic apoptotic pathways in various tissues and organ systems [77]. Diabetic autonomic neuropathy (DAN) is well-documented in the progression of long-term diabetes. This complication manifests in multiple symptoms that involve the gastrointestinal tract, including DGp, gall bladder atony, diabetic enteropathy, and colonic hypomotility [45]. The hallmark of DAN is rampant apoptosis in neurons throughout the body. The BCL-2 family consists of proteins that regulate apoptosis. Particularly, BCL-2 suppresses cell death while BAX promotes cell death [46]. Here, we observed diminished BCL-2 and exaggerated BAX expression levels in gastric antrum samples from diabetic female mice. Conversely, we observed higher BCL-2 expression and lower BAX expression in healthy mice and diabetic mice receiving pharmacological doses of E2. Our findings suggest a connection between ERs and the apoptotic machinery. We also found E2 supplementation to restore TNF-α levels in diabetic mice to healthy, pre-stress levels. TNF-α is involved in caspase-mediated apoptosis in ICC [78,79]. Therefore, while several mechanisms may govern the apoptotic response within the GI apparatus in our mouse model of diabetic GP, our findings suggest that E2 supplementation can modulate and at least partially restore the function of these mechanisms to healthy, pre-stress conditions.
The pathogenesis of DGp in men and women appears to be similar. However, women are consistently prone to be symptomatic due to the lower baseline kinetics of their stomachs, perhaps due to elevated levels of sex steroid hormones and inhibitory nitric oxide [10,13]. In this study, we showed E2 to influence apoptosis and oxidative stress in female mice with DGp.
Estrogen levels fluctuate in females, with physiological elevations and depressions occurring throughout the estrus cycle [25]. Furthermore, many hormones have tissue-specific functions and are most efficient at their optimal concentrations. In this study, we chose the supplemental E2 doses based on previous reports of circulating E2 levels in healthy mice [28,32,33,80]. We found the effect of physiological E2 doses (0.001 mg/kg b.w. and 0.005 mg/kg b.w.) to be largely minimal in restoring gastric function in diabetic mice. The depletion of endogenous estrogen was prevalent in STZ-induced diabetic mice, and physiological doses of E2 supplementation could not restore their estrogen levels (Table 2). On the other hand, pharmacologic doses of E2 (0.25 mg/kg b.w. and 1.0 mg/kg) normalized circulating estrogen levels in the diabetic mice to those observed in healthy mice. Thus, these E2 doses could alleviate some effects of oxidative stress, gastric apoptosis, and inflammation in order to improve GE in the diabetic mice. Interestingly, the pharmacologic doses of estradiol can be extrapolated to a human equivalent dose such as those contained in transdermal, oral, and ultra-low dose vaginal preparations [81,82,83]. Collectively, our findings indicate E2 supplementation at appropriate doses as a potential treatment regimen for diabetes-induced gastric dysmotility in women.
## 5. Conclusions
DGp is a debilitating condition with limited therapeutic options [15,80]. Current treatments for Gp include extreme dietary modifications, costly oral drug therapy, and invasive surgery [6]. As women are four times more likely to experience the debilitating symptoms of diabetic Gp, we hypothesize that this sex-related difference is due to the influence of female sex hormones on the gastro-motility milieu. Our current study uncovered new information that links the molecular underpinnings of inflammation, oxidative stress, and apoptotic response in Gp to E2-mediated activation of intracellular ER/MAPK/Nrf2/nNOSα signaling to improve GE. We conclude that changes in ER abundance and the downstream influence of target genes may precipitate the advancement and prognosis of Gp in female mice with type 1 DM. Due to the complexity of gut motility signaling in males versus females, further studies are needed to tease out the role of ERs, Nrf2, and inflammatory cytokines in experimental models of Gp.
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|
---
title: Characteristic Analysis of Featured Genes Associated with Cholangiocarcinoma
Progression
authors:
- Qigu Yao
- Wenyi Chen
- Feiqiong Gao
- Yuchen Wu
- Lingling Zhou
- Haoying Xu
- Jong Yu
- Xinli Zhu
- Lan Wang
- Lanjuan Li
- Hongcui Cao
journal: Biomedicines
year: 2023
pmcid: PMC10045321
doi: 10.3390/biomedicines11030847
license: CC BY 4.0
---
# Characteristic Analysis of Featured Genes Associated with Cholangiocarcinoma Progression
## Abstract
The noninvasive diagnosis of cholangiocarcinoma (CCA) is insufficiently accurate. Therefore, the discovery of new prognostic markers is vital for the understanding of the CCA mechanism and related treatment. The information on CCA patients in The Cancer Genome Atlas database was used for weighted gene co-expression network analysis. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied to analyze the modules of interest. By using receiver operating characteristic (ROC) analysis to analyze the Human Protein Atlas (HPA), the featured genes were subsequently verified. In addition, clinical samples and GSE119336 cohort data were also collected for the validation of these hub genes. Using WGCNA, we identified 61 hub genes that regulated the progression and prognosis of CCA. Eight hub genes (VSNL1, TH, PCP4, IGDCC3, RAD51AP2, MUC2, BUB1, and BUB1B) were identified which exhibited significant interactions with the tumorigenic mechanism and prognosis of CCA. In addition, GO and KEGG clarified that the blue and magenta modules were involved with chromosome segregation, mitotic and oocyte meiosis, the cell cycle, and sister chromatid segregation. Four hub genes (VSNL1, PCP4, BUB1, and BUB1B) were also verified as featured genes of progression and prognosis by the GSE119336 cohort data and five human tissue samples.
## 1. Introduction
Cholangiocarcinomas (CCAs) are epithelial tumors that arise from the intrahepatic bile duct or large bile ducts [1]. In addition, CCA is very common in digestive system tumors, and its incidence is second only to hepatocellular carcinoma [2]. Over the past 40 years, the global incidence rate of CCA has increased to approximately $18\%$ [3]. Early diagnosis of CCA remains challenging because most patients have no conspicuous symptoms during the early stages of disease [4]. Furthermore, highly desmoplastic, paucicellular tumors develop in the liver or large bile ducts, thereby limiting the sensitivity of pathological diagnosis [5]. Given the intertumoral and intratumoral heterogeneity of CCA, key therapeutic targets have not been defined for this disease [5,6]. Therefore, reliable biomarkers are needed for the early diagnosis of CCA, and important prognostic factors should be identified.
With the increasing popularity of next-generation sequencing technology, targeted or operable molecular changes in transcription levels can be identified [7]. Many cancers have been analyzed using this technique to detect novel biomarkers for tumor diagnosis, as well as to mitigate the recurrence and inhibition of drug resistance [8,9]. Based on public database findings or sequencing data from clinical samples, Li et al. elucidated nine hub genes highly related with the pathological T stage of hepatocellular carcinoma [10]. Similarly, utilizing weighted gene co-expression network analysis (WGCNA) to construct an endogenous competitive RNA regulatory network, Peng et al. identified six possible pivotal genes in metformin in the treatment of diabetes and colorectal cancer [11].
Common CCA screening indicators, such as carbohydrate antigen 199, cancer antigen 125, and cancer antigen −50, are not sensitive or specific enough [12]. For example, CA199 is also highly expressed in pancreatic cancer, hepatobiliary carcinoma, gastric cancer, and colorectal cancer [13,14]. Additionally, the levels of CA125 increase in patients with fallopian tube adenocarcinoma, ovarian cancer, pancreatic cancer, colorectal cancer, and breast cancer [15,16,17]. There are obvious genomic changes in the pathogenesis of CCA, and the study of CCA may be helpful in finding their potential diagnostic and prognostic value. For example, MRPS18A, CST1, and SCP2 were associated with the pathological stage, liver function, and overall survival in CCA patients [18]. The inhibition of HER2/neu was identified as a promising treatment target for patients with CCA [19]. In approximately $60\%$ of intrahepatic CCAs, the FGFR2 and the genes encoding isocitrate dehydrogenases might be suitable therapeutic targets [20]. Nevertheless, further research is needed concerning novel biomarkers for clinical decision making.
Here, patients with CCA in The Cancer Genome Atlas (TCGA) were used to perform WGCNA. WGCNA was applied to find the correlation between the clinical information and the genes in the microarray samples [21]. Additionally, correlation networks were used to analyze the candidate biomarkers with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein–protein interaction (PPI) networks. Overall, the identification of the modules and featured genes in CCA will help to build a precise approach to diagnosis and treatment.
## 2.1. Processing of Gene Expression Data
RNA sequencing data were collected by the Illumina HiSeq 2000 RNA Sequencing platform and then mean-normalized (per gene) across all TCGA cohorts. Phenotype information was also downloaded from UCSC Xena, accessed on 17 January 2021 (https://xenabrowser.net). The following inclusion criteria were used: [1] samples with RNA sequencing data available and [2] matched samples with adequate clinical data. Gene matrix profiles were cleaned and normalized using NetworkAnalyst, accessed on 22 February 2021 (https://www.networkanalyst.ca). A |log2fold change| > 1.0 and an adjusted p-value < 0.05 were set as the threshold for differentially expressed genes (DEGs). Ultimately, we included 36 bile duct cancer tissues and 9 matched normal tissues. Clinical characteristics were extracted, including age, albumin value, CA199 expression, cancer history in first-degree relatives, Child–Pugh grade, creatinine value, fetoprotein value, fibrosis score, neoadjuvant treatment history, neoplasm histological grade, pathological M, N, and T scores, perineural invasion, neoplasm cancer, platelet count, prothrombin time, family cancer history, vascular tumor cell type, survival, sex, ethnicity, vital status, prior malignancy, prior treatment, tumor stage, body mass index (BMI), height, and weight.
## 2.2. Gene Co-Expression Network Construction
In order to construct a co-expression network, the “WGCNA” package statistical software, accessed on 26 February 2021. ( version 4.0.2, https://www.r-project.org) was employed to calculate the similarities between the gene expression profiles [21]. Outlier samples were identified by the averaging method in the “hclust” function within the “WGCNA” package. These outliers were then removed. Scale-free networks were constructed using the WGCNA method. The scale-free network is defined as a network in which most nodes in the network connect with a few other nodes, but a few nodes connect with many nodes. These networks are more tolerant of unexpected faults compared with networks in which most nodes connect with many other nodes. Using hierarchical clustering, the adjacency matrix was changed into a topological overlap matrix (TOM); the dynamic tree cut method was then used to identify different modules. When setting the parameters, the minimum number of genes contained in the network module was set at 30 (min module size = 30); the threshold value of the gene reclassification between modules was set at 0 (reassign threshold = 0); and the degree of dissimilarity was set at 0.25 (merge cut height = 0.25).
## 2.3. Construction of CCA Modules with Clinical Relationships
Pearson correlation coefficients between the module eigengenes (MEs) and the clinical information were calculated. Following the calculation of the core modules, gene significance (GS) and module membership (MM) were used to measure the association levels of the genes with clinical traits and the MEs. Module core genes were considered to have MM > 0.8 and GS > 0.2.
Combined with the hub genes identified by MM and GS, a q-weighted cutoff < 0.01 was settled to find featured genes using the network screening function. The common hub genes were determined by two methods and then visualized using Venn diagrams.
## 2.4. Functional Annotations for DEGs
The clusterProfiler package (version: 3.16.1) was adopted for GO biological function and KEGG signaling pathway analysis for the DEGs. The GO function and KEGG pathway used the default parameters in the clusterProfiler package, and the cutoff threshold was set to $p \leq 0.0001.$
## 2.5. Hub Gene Validation
The R package “survival” and Gene Expression Profiling Interactive Analysis (http://gepia.cancer-pku.cn), accessed on 27 February 2021, were employed to identify the key prognostic genes by means of Kaplan–Meier analysis. The Human Protein Atlas database (https://www.proteinatlas.org), accessed on 22 February 2021, was employed to validate the immunohistochemistry results of the featured prognostic genes [22].
## 2.6. Identification of Hub Gene Functional Annotations
Using the GO function and KEGG pathway enrichment analysis, we mapped, integrated, and visualized the characteristic genes and related tumor progression mechanisms. The GOplot R package (version: 1.0.2) was employed for visualization.
## 2.7. Human Samples
All the patients with CCA gave their informed consent, and the experimental design met the ethical requirements, which were approved by the Ethics Committee of The First Affiliated Hospital of Zhejiang University (No. 2014-272). Tissues, including para-tumor and CCA samples, were sampled immediately in the First Affiliated Hospital, Zhejiang University School of Medicine.
## 2.8. Immunohistochemical Staining
Using xylene and alcohol, 5 µm thick human sample tissues were deparaffinized. The samples were then repaired with $3\%$ H2O2-CH3OH for 10 min. Subsequently, they were submerged in a pH 9.0 buffer for antigen retrieval and then incubated at 37 °C overnight with primary antibody, BUB1B (Abcam, ab183496, 1:100), BUB1 (Abcam, ab195268, 1:100), PCP4 (Proteintech, 14705-1-AP, 1:200), or VSNL1 (Proteintech, 67134-1-IG, 1:200). After the sections had been washed with phosphate-buffered saline three times, they were submerged with horseradish peroxidase-conjugated IgG, rabbit anti-mouse IgG (Abcam, ab6728), and goat anti-rabbit IgG (Abcam, ab6721) at 37 °C for 40 min. Finally, the sample sections were developed with a 3,3′-diaminobenzidine tetrahydrochloride detection system kit (Abcam, ab64238) and hematoxylin staining solution (Servicebio, G1004). Protein expressions in the sections were detected via and analyzed by NDP.view2 (version 2.6.8). Five visual fields were randomly selected to compare the protein expression levels between the CCA and para-tumor samples. Quantitative analyses were conducted by Image J software. Protein expressions that were specifically located within cholangiocarcinoma cells or bile duct cells were compared. Notably, staining areas within normal hepatocytes were excluded. Mean optical density was chosen as a comparative indicator and could be calculated as follows: Mean optical density = Integrated option density/Area.
## 2.9. Construction of PPI Network
Using the Search Tool for the Retrieval of Interacting Genes, we evaluated the correlation and biological function of related genes [23]. The cutoff criterion was regarded as a confidence score ≥ 0.4. Cytoscape is a visualization software platform (version: 3.7.1; https://cytoscape.org), accessed on 22 February 2021, which can help to visualize the PPI network [24].
## 2.10. Statistical Analysis
R (version 4.0.2) was used for data analysis. Wilcoxon and Kruskal–Wallis tests were used for gene difference analysis. In this study, overall survival analysis was evaluated by the Kaplan–Meier method and log-rank testing. In the absence of special labels, $p \leq 0.05$ was regarded as significant in all statistical analyses.
## 3.1. Data Collection and Processing
The overall flowchart of the study protocol is shown in Figure 1. The selected clinical information and mRNA were downloaded from UCSC Xena, including 36 bile duct cancer tissues and nine matched normal tissues (Figure S1A,B). After data cleaning and normalization (removal of samples with repetition or missing information), 544 up-regulated genes and 1069 down-regulated genes met the screening conditions (Figure 2A,B). t-Distributed stochastic neighbor embedding of the DEGs demonstrated that the tumor and nontumor tissues were clearly distinguished (Figure 2C). The threshold of the adjusted p-value was < 0.05 and the |log2fold change was | > 1.0 for WGCNA and the subsequent analyses (Figure 2D). The corresponding clinical information is shown in Table S1.
For WGCNA, the ‘hclust’ function clustered 45 samples and removed the outliers. As shown in Figure 2E, the parameters “cutHigh” and “minSieze” were set at 55 and 10, which ultimately yielded 28 samples.
## 3.2. Functional Annotations of Hub Genes
The clusterProfiler and enRichment packages were used to examine the biological function of the selected modules by GO analysis and KEGG pathway analysis (Tables S2 and S3). In the GO analysis, the top five GO terms were monooxygenase, passive transmembrane transporter, metal ion transmembrane transporter, channel activity, and ion channel (Figure S2A,B). In KEGG analysis, the top five biological pathways were neuroactive ligand–receptor interaction, chemical carcinogenesis, metabolism of xenobiotics by cytochrome P450, drug metabolism–cytochrome P450, and steroid hormone biosynthesis (Figure S3).
## 3.3. Weighting Coefficient β Selection
The most important co-expression networks are scale-free networks, such that P (k)∼k − 1 (Table S4) [25]. As the soft threshold (β) increases, the correlation coefficient of the network increases (R2 > 0.8) (Figure 3A), and the mean connectivity of the network subsequently decreases (Figure 3B). Therefore, β = 5 was selected to construct the co-expression network, such that log(k) was correlated with log[P(k)] (R2 = 0.87, slope = −1.33) (Figure 3C,D).
## 3.4. Co-Expression Network Construction
Adjacencies among the DEGs were evaluated, and then, the results were plotted in a TOM-based hierarchical gene clustering tree (Figure S4A). Initially, the MEs were determined by principal component analysis. The Dynamic Tree Cut package is a function used to analyze modules of interest; the parament of the minimum module size was defined as 30 and the deepSplit was defined as 2 (Figure S4B). Using the Dynamic Tree Cut Merged Dynamics package, the gene topological matrix was modified (Figure 4A). To reduce the complexity of the network, the MEs with a similarity > 0.75 were merged, and the numbers of modules were not changed. The eigengene dendrogram and heatmap were evaluated using the groups of correlated eigengenes and the dendrogram (Figure 4B).
## 3.5. Identification of Clinical Modules
As shown in Figure 4C, the clinical modules were clustered, and their correlations were analyzed with a sample dendrogram. With respect to the clinical data, red represents a high value, white means a low value, and gray means a missing value. Through the R value and p-value, the connection between the MEs and the clinical characteristics was continuously scored, and the 13 modules were related to the clinical characteristics given above, as shown in Figure 4D. The blue and magenta modules were significantly associated with tumor stage ($R = 0.38$, $$p \leq 0.05$$; $R = 0.47$, $$p \leq 0.01$$). The whole genes of the blue and magenta modules are shown in Table S5.
## 3.6. Identification of Hub Genes
The GS for the tumor stage and MM values for the genes in each module was calculated in order to identify the MM values associated with tumor differentiation, as shown in Figure 5A. The magenta module (correlation coefficient = 0.6, p-value = 5.1 × 10−9) and the blue module (correlation coefficient = 0.49, p-value = 3.6 × 10−11) were consistent with the adverse clinical characteristics of the CCA patients (Figure 5B,C). To identify the hub genes for tumor differentiation, a GS > 0.2 for the tumor stage and an MM > 0.8 were concurrently satisfied in two modules. This ruled out a total of 73 hub genes. Furthermore, the hub genes were required to meet the screening criteria (q-weighted < 0.01) of the ‘networkScreening’ function. In total, 61 featured genes were identified, as shown in the Venn plot (Figure 5E).
## 3.7. Functional Enrichment Analyses of the Hub Genes in Hub Modules
Applying GOplot packages, we investigated the biological significance of selected modules by using GO terms. In the whole genes of the blue and magenta modules, the top 10 biological processes in the GO analysis mainly focused on mitochondria (Figure 5D). Applying GOplot packages, we investigated the GO terms of the selected 61 hub genes, as well as the KEGG pathway analysis. The GO analysis results illustrated that the selected 61 hub genes were particularly enriched in chromosome segregation, mitotic sister chromatid segregation, and mitotic nuclear division (Figure 5F). According to the KEGG plot, the most important pathways were oocyte meiosis, cell cycle, dopaminergic synapse, alcoholism, and the Rap1 signaling pathway (Figure 5G). A co-expression network analysis was used to explore the degree of association among the 61 featured genes, with a coefficient of ≥0.53 (Figure S5). Next, we divided the two subgroups according to the correlation degree of the genes; the subgroups contained 23 and 33 genes, respectively (Figures S6–S8). Among them, we found that the correlation coefficient between CALML3 and ALPP was the highest at 0.99 (Figure 6A). Based on the pathways enriched, we established connections between the hub genes and the cell cycles (Figure 6B and Figure S9).
## 3.8. Construction of PPI Network and Verification of Hub Genes
A PPI network was constructed using 61 featured genes, which had three subgroups. The denser and bigger the nodes are, the more important the gene is. Additionally, the thicker the edge, the closer the connection between the genes. The biggest subgroup had 28 nodes and 246 edges (Figure 6C). The remaining two subgroups had three nodes and four nodes, and two edges and three edges, respectively (Figure 6D).
## 3.9. Survival Analysis
Survival analysis is one of the most important indicators of prognosis. After analyzing the survival curve of 61 featured genes, 27 featured genes were related to the overall survival rate of the CCA patients ($p \leq 0.05$) (Figure S10; Table S6).
## 3.10. Hub Gene Analysis and Validation
In order to further the potential mechanisms and roles of the 61 hub genes in CCA prognosis and tumor progression, receiver operating characteristic (ROC) analysis was employed. The results demonstrated that the area under the curve (AUC) of five of the hub genes in the 61 hub genes was >0.75, which could be used to distinguish CCA tumorigenic progression and prognosis (Figure 7A; Tables S7 and S8). In addition, five other hub genes (0.75 > AUC > 0.7) could be used to distinguish CCA tumorigenic progression (Figure S11).
In Figure 7B, by combining 61 hub genes, the selected 10 hub genes (AUC > 0.7) in the ROC analysis for tumor progression, and 27 hub genes ($p \leq 0.05$) in the Kaplan–Meier survival curve, a Venn plot was constructed to find the genes which affected tumor development, as well as the prognosis and survival of the tumor patients. Eight hub genes were identified: VSNL1, TH, PCP4, IGDCC3, RAD51AP2, MUC2, BUB1, and BUB1B. *These* genes affected tumor development, as well as the prognosis and survival of the tumor patients (Figure 7B). In addition, VSNL1, RAD51AP2, PCP4, and MUC2 were correlated with tumorigenic progression by staging plot levels in the Gene Expression Profiling Interactive Analysis database (Figure S12).
We selected VSNL1, PCP4, BUB1, and BUB1B for verification at the mRNA and protein levels. Compared with nontumor tissues, the mRNA expression levels of PCP4, BUB1, and BUB1B were strikingly higher in the CCA patients. Additionally, the mRNA expression level of VSNL1 was strikingly reduced in the CCA tissue (Figure 7C). These results are similar to those of other GEO datasets (Figure 7D). We then used immunohistochemical staining to identify protein expression in the human samples. Then, PCP4 was verified by the HPA database. Furthermore, the experimental results of the immunohistochemistry showed that BUB1, BUB1B, and PCP4 were darker brown in the CCA tissue than in the normal tissue, while VSNL1 was the opposite. The mean optical density of the expression of BUB1, BUB1B, PCP4 and VSNIL1 in the CCA and adjacent tissue samples showed that the protein levels of BUB1, BUB1B, and PCP4 in the CCA tissue were significantly increased, but the protein level of VSNL1 in the CCA tissue was significantly decreased (Figure 8).
## 4. Discussion
CCA is a highly heterogeneous and rapidly developing disease, which is difficult to find early and hard to resection [26]. CCA heterogeneity causes poor treatment responses in most patients; so, surgery remains the primary treatment option [27]. However, with the development of new immunotherapy and biomarker therapy, the therapeutic effect on patients with end-stage CCA has also been improved [28]. Biomarkers can be used for accurate diagnosis, prediction of prognostic effects, and improvement of clinical efficacy [29].
Our study used personalized bioinformatics to identify the mRNA related to clinical features; our hope was to find new therapeutic targets or prognostic markers. Thus, we used the WGCNA method to identify 1613 DEGs from 45 CCA samples and constructed 13 co-expression modules. Furthermore, WGCNA was employed to analyze the relationships between the co-expression modules and the clinical characteristics by means of correlation coefficients.
*The* genes in clinically relevant modules are presumed to be functionally associated with each other, and this may be helpful for subsequent detection or treatment. In addition, according to the requirements of WGCNA, the number of multiple samples should be more than 15 [21]. Therefore, our WGCNA network is reliable. From 13 co-expression modules, the magenta (cor = 0.6) and blue (cor = 0.49) modules were extracted because of their associations with tumor-stage diagnosis. Through Venn plot analyses, we selected 61 genes that were highly correlated with CCA progression and prognosis. Subsequently, GO and KEGG analyses were used to functionally annotate these 61 hub genes. The GO analysis showed that two modules were particularly focused on chromosome segregation, mitotic sister chromatid segregation, and mitotic nuclear division. Condensed chromosome outer kinetochore and protein kinase activity were enriched in the cellular component and molecular function processes. The related pathways were mainly concentrated in the oocyte meiosis, cell cycle, dopaminergic synapse, alcoholism, and Rap1 signaling pathways. Loss of mitotic regulation is an important feature of cell carcinogenesis which leads to abnormal mitosis and chromosome segregation. [ 30]. Our results indicated that mitosis, meiosis, and the cell cycle are key factors that influence the speed of tumor deterioration, the same as those of Du et al. [ 31].
Furthermore, we identified eight hub genes (VSNL1, TH, PCP4, IGDCC3, RAD51AP2, MUC2, BUB1, and BUB1B) that promoted tumor progression and were associated with prognosis according to the Kaplan–Meier and ROC curve analyses. TH, IGDCC3, RAD51AP2, and MUC2 are genes that were identified by WGCNA and are related to the clinical prognosis and survival of cholangiocarcinoma, but they have already been reported [5,32,33,34]. Therefore, VSNL1, PCP4, BUB1, and BUB1B were chosen for further verification.
VSNL1 is related to neuronal calcium sensor proteins which are highly expressed in the cerebellum [35]. The research concerning VSNL1 has mainly focused on neurological diseases such as Alzheimer’s disease and medulloblastoma [36,37]. VSNL1 has also been investigated in gastrointestinal tumors, where it promotes the rapid growth and metastasis of gastric cancer cells [38], lymph node metastasis, and the deterioration of colorectal cancer [39]. However, the VSNL1 function in CCA needs to be further analyzed. Considering that some studies have shown that the high expression of VSNL1 in colorectal cancer is related to the high degree of tissue differentiation, it is speculated that the function of VSNL1 may be related to the metastasis of cholangiocarcinoma.
PCP4 encodes a modulator of calmodulin-mediated calcium binding, mainly expressed in brain, kidney, colon, and thyroid tissue. The main function of PCP4 is believed to be related to the regulation of the calmodulin-mediated signal [40]. The role of PCP4 is under investigation in neurological and endocrine diseases, such as polycystic ovary syndrome and Alzheimer’s disease. In adrenal adenomas, the overexpression of Pcp4 may be related to DNA methylation and may affect aldosterone secretion [41]. PCP4 is rarely studied in gastrointestinal tumors. PCP4 participates in the calmodulin-dependent kinase signaling pathway to inhibit cell apoptosis, and CCA may promote cancer cell adhesion, migration, and invasion.
BUB1 and BUB1B encode the serine/threonine–protein kinases that greatly contribute to mitosis [42,43]. At present, it is believed that the function of BUB1 is to activate the related genes of the spindle checkpoint by phosphorylating the related members of the mitotic checkpoint complex so as to affect the process of cell proliferation [44]. BUB1B is a checkpoint which is similar to BUB1. Additionally, BUB1B triggers polyploid cell apoptosis and inhibits the activity of PLK1 in the mitotic interphase [45]. Overall, it participates in two crucial aspects of mitosis: the spindle assembly checkpoint signal and the cell chromosome arrangement in mitosis. BUB1 is reportedly overexpressed in pancreatic ductal adenocarcinoma, gastric cancer, and multiple myeloma [46,47,48]. BUB1B has been studied in multiple tumors, such as colorectal carcinoma, CCA, and breast cancer [49,50,51]. Qiu reported that BUB1B may promote the proliferation of liver cancer cells by raising the mTORC1 signaling pathway [52]. BUB1 and BUB1B mediate apoptosis in response to chromosomal aberration and inhibit the proliferation and metastasis of tumor cells. BUB1 and BUB1B may accelerate the process of cholangiocarcinoma by promoting the mitosis of cholangiocytes.
This study also has some shortcomings. First of all, despite the use of clinical samples and TCGA samples, the number of samples used was still small in general, and the sample size should be expanded in a follow-up study. Second, the CCA hub genes and their relationships with tumor progression and prognosis require experimental verification, both in vitro and in vivo. Third, CCAs are epithelial tumors which can be divided into three subtypes. Fourth, scoring these genes in the CCA library using the data in the single cell map or single cell portal will help to explore the changes in these hub genes in the tumor microenvironment. Therefore, our study results might be more convincing if the samples were divided into several subgroups. Therefore, additional clinical samples with detailed clinical data are needed to confirm our findings. Basic research concerning hub genes is important for accurate identification of the mechanisms underlying tumor progression and prognosis.
## 5. Conclusions
Through WGCNA, GO, and KEGG analyses, ROC analysis, and immunohistochemical staining, we identified eight hub genes (VSNL1, TH, PCP4, IGDCC3, RAD51AP2, MUC2, BUB1, and BUB1B) that may contribute to CCA progression and prognosis. Of these eight genes, VSNL1, PCP4, BUB1, and BUB1B may also serve as novel biomarkers for the determination of disease progression. Additional mechanistic research and clinical verification may contribute to individualized treatment in the future.
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|
---
title: 'Ability of a Polyphenol-Rich Nutraceutical to Reduce Central Nervous System
Lipid Peroxidation by Analysis of Oxylipins in Urine: A Randomized, Double-Blind,
Placebo-Controlled Clinical Trial'
authors:
- Raúl Arcusa
- Juan Ángel Carillo
- Begoña Cerdá
- Thierry Durand
- Ángel Gil-Izquierdo
- Sonia Medina
- Jean-Marie Galano
- María Pilar Zafrilla
- Javier Marhuenda
journal: Antioxidants
year: 2023
pmcid: PMC10045327
doi: 10.3390/antiox12030721
license: CC BY 4.0
---
# Ability of a Polyphenol-Rich Nutraceutical to Reduce Central Nervous System Lipid Peroxidation by Analysis of Oxylipins in Urine: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial
## Abstract
Isoprostanes (IsoPs) are lipid peroxidation biomarkers that reveal the oxidative status of the organism without specifying which organs or tissues it occurs in. Similar compounds have recently been identified that can assess central nervous system (CNS) lipid peroxidation status, usually oxidated by reactive oxygen species. These compounds are the neuroprostanes (NeuroPs) derived from eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and the F2t-dihomo-isoprotanes derived from adrenic acid (AdA). The aim of the present investigation was to evaluate whether the long-term nutraceutical consumption of high polyphenolic contents (600 mg) from fruits (such as berries) and vegetables shows efficacy against CNS lipid peroxidation in urine biomarkers. A total of 92 subjects (47 females, 45 males, age 34 ± 11 years old, weight 73.10 ± 14.29 kg, height 1.72 ± 9 cm, body mass index (BMI) 24.40 ± 3.43 kg/m2) completed a randomized, cross-over, double-blind study after an intervention of two periods of 16 weeks consuming either extract (EXT) or placebo (PLA) separated by a 4-week washout period. The results showed significant reductions in three AdA-derived metabolites, namely, 17-epi-17-F2t-dihomo-IsoPs (Δ −1.65 ng/mL; $p \leq 0.001$), 17-F2t-dihomo-IsoPs (Δ −0.17 ng/mL; $p \leq 0.015$), and ent-7(RS)-7-F2t-dihomo-IsoPs (Δ −1.97 ng/mL; $p \leq 0.001$), and one DHA-derived metabolite, namely, 4-F4t-NeuroP (Δ −7.94 ng/mL; $p \leq 0.001$), after EXT consumption, which was not observed after PLA consumption. These data seem to show the effectiveness of the extract for preventing CNS lipid peroxidation, as determined by measurements of oxylipins in urine through Ultra-High-Performance Liquid Chromatography triple quadrupole tandem mass spectrometry (UHPLC-QqQ-ESI-MS/MS).
## 1. Introduction
Oxidative stress (OS) is known as an imbalance between oxidizing and anti-oxidizing agents, affecting the physiological function of the organism [1] that could cause damage to lipids, proteins, and DNA structures, among others [2]. This imbalance could be caused by a low intake of antioxidants, depletion of endogenous antioxidants, or an increase in reactive species [3]. Whilst it is known that the organism synthesizes reactive oxygen species (ROS) and nitrogen species (NOS) in small enough quantities that it is capable of neutralizing, when this production is excessive and prolonged over time, it can cause damage to cell structures and functions and may lead to irreparable damage [4]. Lipid peroxidation of membranes can lead to impaired functions, inactivation of its receptors and enzymes, increased permeability to ions, decreased fluidity, and, ultimately, rupture [5].
Several problems arise in the assessment of OS, particularly in the determination of scientifically validated biomarkers [6]. In addition, for such biomarkers to be useful, they must meet certain criteria, such as showing specificity for a given disease, having prognostic value, correlating with disease activity, remaining reasonably stable, being easily accessible in tissues, and are cost-effective to measure on a large scale [1]. Despite the fact that it is common to assess the total antioxidant capacity in subjects’ blood plasma, this procedure may not provide accurate information on the organism’s state [7]. The scientific literature has described how numerous phytochemicals are fleetingly metabolized into molecules with altered biological properties [7]. In addition, it is of greater interest to evaluate the activity of the organism’s antioxidant enzymes [8], which support the main antioxidant defense load of the organism [9].
There are different pathways involved that explain the antioxidant capacity of polyphenols, highlighting the elimination of ROS, the attenuation in the synthesis of these radicals by inhibiting enzymes involved in their production, and the increase in endogenous antioxidant defenses [10]. Moreover, thanks to their structure and the presence of hydroxyl groups attached to the aromatic ring, they exert antioxidant activity to neutralize unpaired electrons from free radicals (FR), donating hydrogens, and chelating metallic ions [11]. For flavonoids, the hydroxyl of the B-ring appears to be responsible for scavenging ROS and NOS by hydrogen and electron donation to hydroxyl, peroxyl, and peroxynitrite radicals, giving rise to stable flavonoid radicals [12,13].
Oxylipins are oxygenated bioactive lipids [14], synthesized as metabolites from the oxidation of polyunsaturated fatty acids (PUFAs). The scientific literature describes how altered oxylipin signaling is associated with different types of cardiovascular diseases (CVDs) such as diabetes, hypertension, hemostasis, thrombosis, and hyperlipidemia [15]. Oxylipins originate after damage or stimulus; due to their short lifespan they are not stored, but are synthesized de novo in a tightly regulated manner [16]. Linoleic acid ((LA), omega-6 family) and alpha-linolenic acid ((ALA), omega-3 family) are the main precursors of oxylipins. In the LA metabolism pathway, dihomo-gamma-linolenic acid (DGLA) and arachidonic acid (AA) are synthesized, while in the ALA pathway, EPA and DHA are generated [17,18].
The different types of oxylipins, including IsoPs, were discovered by Morrow and collaborators in the 1990s [19]. IsoPs are prostaglandin-like eicosanoids, synthesized by a non-enzymatic pathway independent of cyclooxygenase (COX), via ROS-induced AA peroxidation [20,21]. IsoPs are fleetingly metabolized and excreted in urine, and their quantification is useful to assess the oxidative status at a particular time [22,23,24].
One of the limitations of IsoPs is that, despite revealing the oxidative status of the organism, it does not specify which organs or tissues it occurs in, unless the IsoP levels in the cerebrospinal fluid are directly assessed [25]. Nevertheless, recent compounds have been described as biomarkers of CNS lipid peroxidation, such as NeuroPs originating from EPA and/or DHA (which produce F3-IsoPs and F4-IsoPs, respectively) and F2t-dihomo-IsoPs, derived from AdA [26,27,28], as illustrated in Figure 1. These compounds can be assessed in different biological fluids, with plasma and urine being the methods of choice [29,30,31,32].
AA is evenly distributed in the brains’ gray and white matter, as well as inside glia and neurons [33]. Urine assessment of NeuroPs and F2t-dihomo-IsoP, which are both present in brain tissues, could be an additional and more reliable indicator of neuronal oxidative and myelin sheath damage, respectively, because DHA is abundant in the gray matter of the brain and AdA is abundant in the white matter [30,31].
Since the CNS is prone to ROS production and lacks an adequate antioxidant system, a constant increase in ROS and NOS can occur [34]. High oxygen consumption by the brain results in excessive ROS production since neuronal membranes are rich in PUFAs and therefore have increased vulnerability to FR attack to its high number of double bonds [35].
In this context, the aim of the present investigation was to evaluate whether the consumption of nutraceutical-based fruits (such as berries) and vegetables with a high polyphenol content was effective to prevent CNS lipid peroxidation by attenuating urine metabolites derived from EPA, DHA, and AdA.
## 2.1. Chemical and Reagent
Three NeuroPs (4(RS)-4F4t-NeuroP, 4-epi-4-F3t-NeuroP, 4-F4t-NeuroP) and three F2t-dihomo-IsoPss (17-epi-17-F2t-dihomo-IsoP, 17-F2t-dihomo-IsoP, Ent-7(RS)-7F2t-dihomo-IsoP) were synthesized by Durand’s team at the Institut des Biomolecules Max Mosseron (IBMM) (Montpellier, France). Table 1 shows the different NeuroPs and F2t-dihomo-IsPs molecules tested in this study.
The enzyme β-glucuronidase, type H2 from *Helix pomatia* and BIS-TRIS (bis-(2hydroxyethyl)-amino-tris(hydroxymethyl)-tris(hydroxymethyl)-methane) were obtained from Sigma-Aldrich (St Louis, MO, USA). All LC-MS-grade solvents were obtained from J.T. Baker (Phillipsburg, NJ, USA). Hydrochloric acid, hexane, trichloroacetic acid, and ethyl acetate were obtained from Panreac (Caste3llar del Vallés, Barcelona, Spain). Strata X-AW solid-phase extraction (SPE) cartridges, 100 mg per 3 mL, were purchased from Phenomenex (Torrance, CA, USA). Water was treated in a Milli-Q water purification system from Millipore (Bedford, MA, USA).
## 2.2. Clinical Trial Design
The study consisted of a randomized, double-blind, crossover, two-arm, placebo-controlled, sex-stratified, single-center clinical trial, which was described in detail and illustrated in a previous publication [36]. The intervention phase lasted for 36 weeks, divided into two phases of 16 weeks wherein subjects consumed either extract or placebo, separated by a 4-week washout period, after which subjects transitioned to the opposite arm of the study.
During the intervention, the subjects visited the laboratory four times, corresponding to the beginning and end of each 16-week phase. During these visits, in addition to checking adherence to treatment, urine was collected in the 24 h prior to the visit. Researchers recorded the total volume of urine and stored the different samples at −80 °C for subsequent analysis.
Prior to starting the intervention, the protocol was approved by the Institutional Ethical Committee Board of the Catholic University San Antonio of Murcia (UCAM), dated 24 November 2017, under the code: CE111072.
## 2.3. Participants
The subjects had to meet certain inclusion criteria: signing an informed consent form, not consuming more than three servings of fruit and vegetables per day, having a BMI between 18.5 and 35 kg/m2, and being aged between 18 and 65 years old. At the same time, the fulfillment of only one exclusion criterion was sufficient reason for not being a candidate for the study. These criteria include: changes in physical activity habits during the intervention; being pregnant or breastfeeding; being smokers; taking any medication or food supplements, nutraceuticals, multivitamins, etc.; being on a weight-loss, vegan, or vegetarian diet; typically consuming more than three glasses of alcohol (wine, beer) per day; having sleep problems; giving a blood donation (0.5 L) within the last month; and having undergone major surgery in the last three months.
## 2.4. Test Supplement
The product under investigation is a nutraceutical consisting of a mixture of 36 different sources of berries, vegetables, and dried fruits, which are explained in detail a previous publication [37]. In order to blind both researchers and subjects, a PLA of similar visual appearance was manufactured and provided by the same company. The daily dose consisted of six capsules, taken twice a day (three capsules in the morning and three in the afternoon).
Bresciani and collaborators previously characterize the product through UHPLC-QqQ-MS, and showed that this daily dose of the product offered a total of 600 mg of polyphenols, detecting a total of 119 different phenolic compounds [38]. The same research group performed a bioavailability study showing that of the 92 molecules monitored, 20 of them could be detected in the plasma of the subjects, all of them in the form of conjugates and at different times depending on the site of absorption from the gastrointestinal tract [39].
## 2.5. Extraction of Human Oxylipins in Urine Samples
The extraction of NeuroPs and F2t-dihomo-IsoPs was performed by solid-phase extraction as described in previous works [22,40,41,42] and whose methodology is detailed in [36].
## 2.6. UHPLC-QqQ-MS/MS Analysis of Oxylipins
NeuroPs and F2t-dihomo-IsoPs analysis was performed by chromatographic separation using UHPLC-QqQ-ESI-MS/MS following a previously published methodology [22,40,41,42]. The protocol is fully described elsewhere [36], employing a different type of column (C18 column (2.1 × 50 mm, pore size of 1.7 μm)) (Waters, MA, USA).
## 2.7. Statistical Analysis
Descriptive analysis was performed (mean and standard deviation (SD)) on all the quantitative study variables, for baseline conditions and in their evolution, using the Kolmogorov–Smirnov test to verify the normal distribution of the continuous data, both in the EXT and PLA consumption periods. At baseline, Student’s t-distribution comparisons were performed between the two arms of the study to verify if the groups were homogeneous. To analyze the evolution of the variables between groups, an analysis of variance for repeated measures was performed with an intrasubject factor (time manner: baseline and final for each study arm) and an intersubject factor (product: experimental and placebo). For the post hoc analysis, the Bonferroni test was used. Comparisons were made for those effects that were significant with the option of assuming or not assuming equality of variances. In the set of statistical tests, the significance level used was 0.05, and the statistical analysis was performed using SPSS Statistics 27 (SPSS, Inc., Chicago, IL, USA).
## 3.1. Study Population
As summarized in the flow diagram in Figure 2, after the recruitment and selection phase, a total of 117 subjects of both sexes were selected after verification of the inclusion and exclusion criteria, and they were randomly assigned to one of the two groups. Finally, 108 subjects were distributed across two homogeneous groups and started the intervention (Table 2). During this phase, and after losses due to lack of follow-up and dropouts, a total of 92 volunteers completed the treatment.
## 3.2. Oxylipins
Urine samples were collected at the beginning and end of the intervention and analyzed to evaluate lipid peroxidation in the CNS, through oxylipins derived from EPA, DHA, and AdA. Of the six oxylipins analyzed, we were able to quantify four: three derived from AdA and one from DHA, whose values are shown in Table 3.
## 3.2.1. Oxylipins Derived from Adrenic Acid
As shown in Figure 3, the 17-epi-17-F2t-dihomo-IsoP values were non-significantly reduced after the consumption of PLA (Δ −0.121), while after the consumption of EXT, they were reduced in a more pronounced and significant way (Δ −1.65 ng/mL). Furthermore, it is noteworthy that after comparing the evolution between groups at the end of the intervention, statistically significant differences were observed in the comparison of the final timepoint between PLA and EXT, which seems to confirm that the consumption of EXT may be effective in reducing 17-epi-17-F2t-dihomo-IsoP levels.
As shown in Figure 4, the values of 17-F2t-dihomo-IsoP remained stable after consumption of PLA (Δ 0), whereas after the consumption of EXT, they were significantly reduced (Δ −0.17 ng/mL). However, comparing the evolution between treatment groups at the end of the intervention, no statistically significant differences were observed. These data suggest that the consumption of EXT reduces 17-F2t-dihomo-IsoP levels compared to PLA.
As shown in Figure 5, the ent-7(RS)-7-F2t-dihomo-IsoP values started from disparate and non-homogeneous values at the beginning of the intervention, with higher values in the EXT group. Comparing the evolution in each group separately, it was observed that ent-7(RS)-7-F2t-dihomo-IsoP levels were not altered after the consumption of PLA (Δ 0.03), whereas after the consumption of EXT, they were significantly reduced (Δ −1.97 ng/mL). After comparing the evolution between the groups at the end of the intervention, statistically significant differences were observed, and when the comparison was made at the end of the study, significant differences from baseline were no longer observed. These results seem to show that EXT is effective in reducing ent-7(RS)-7-F2t-dihomo-IsoP levels. However, given that at the beginning of the intervention, the values were very variable, and the reason is yet known, caution should be exercised in interpreting these results.
## 3.2.2. Oxylipins Derived from Docosahexaenoic Acid
The only NeuroP quantified was 4-F4t-NeuroP, the most representative NeuroP (Figure 6), whose values did not vary significantly (Δ 0.38) after the consumption of PLA, while after the consumption of EXT, they were significantly reduced (Δ −7.94 ng/mL). Comparing the evolution between the groups at the end of the intervention, statistically significant differences were observed. Furthermore, to increase the statistical power size effect, the difference at the end of the intervention between PLA and EXT were analyzed, and statistically significant differences were also seen. Therefore, the consumption of EXT seems to be effective in reducing 4-F4t-NeuroP levels.
## 4. Discussion
The CNS is highly vulnerable to ROS-mediated injury due to the brain’s high oxygen consumption (given its high energy demands), high PUFA levels, and weak antioxidant defenses [26], leading to the overproduction of ROS [35]. Specifically, the brain uses more than $20\%$ of all oxygen consumed by mitochondrial respiration [43].
The brain demands high amounts of oxygen, which makes it prone to OS, with oxidative brain injury being a major cause of neurological disorders such as epilepsy [44]. DHA oxidation in the CNS is associated with various neurodegenerative disorders, including Rett syndrome, amyotrophic lateral sclerosis, Huntington’s disease, Parkinson’s disease, and Alzheimer’s disease [45,46].
In the present investigation, we considered evaluating three NeuroPs corresponding to series 4 and three F2t-dihomo-IsoPs corresponding to series 7 and 17 (Table 1) to assess DHA and AdA oxidation, respectively. Of the six compounds analyzed, four were quantified, one NeuroP and three F2t-dihomo-IsoPs, the results of which are shown in Table 3.
In the case of the only NeuroP quantified, 4-F4t-NeuroP, a significant reduction in its values was observed only after the consumption of EXT, which did not occur after the consumption of PLA. Furthermore, observing the differences at the end of the intervention between groups and comparing their evolution, significant differences were also observed, which reinforces the statistical power of the results.
Within the F4t-NeuroPs, 4-F4t-NeuroP and 10-F4t-NeuroP are the most frequently reported, being elevated in the plasma in a multitude of neurological diseases [47] and cognitive impairment disorders [48], as well as in the plasma and urine of smokers [49] and type 2 diabetic patients [50]. Signorini et al. conducted an investigation to evaluate the clinical relevance of 4-F4t-NeuroP and 10-F4t-NeuroP in four neurological diseases (Rett syndrome, Down syndrome, multiple sclerosis, and autism spectrum disorder) compared with a control group of age-matched subjects, and found that the levels of 10-F4t-NeuroP were elevated in all diseases, and 4-F4t-NeuroP only in Rett syndrome and multiple sclerosis [51]. These results seem to show the relationship of these molecules with these diseases, as has also been shown in this work.
For the F2t-dihomo-IsoPs derived from AdA, significant reductions were observed after EXT consumption in all three (17-epi-17-F2t-dihomo-IsoP, 17-F2t-dihomo-IsoP, and ent-7(RS)-7-F2t-dihomo-IsoP), but, as with 4-F4t-NeuroP, this was not observed after PLA consumption. In addition, the 17-epi-17-F2t-dihomo-IsoP levels presented significant differences, when comparing the study endpoint and in the evolution between groups. It should be noted that the ent-7(RS)-7-F2t-dihomo-IsoP values showed significant differences, but the cause is unknown.
Elevated values of F4-NeuroPs and F2t-dihomo-IsoPs are associated with neurodegenerative diseases as well as brain lesions, the former being a biomarker with higher reliability, which requires further investigation to assess whether it could be effective for the early detection of neurological disorders [27]. The F4-NeuroPs appear to be much more sensitive markers for oxidative damage to neurons than IsoPs because DHA has a greater sensitivity to oxidation than AA due to the presence of a larger number of methylene double bonds [52]. Meanwhile, the F2t-dihomo-IsoPs do appear to be an early marker of lipid peroxidation in Rett syndrome, a disorder that causes developmental delay, especially in areas controlling expressive language and hand movements [26,53].
Libia et al. observed how markers of CNS oxidation in urine samples correlated positively with age [25], which raises the efficacy of promoting polyphenol intake to prevent and not accentuate future problems at the neurological level. The same research group also observed how NeuroP and F2t-dihomo-IsoP values in urine samples were increased when comparing high-altitude training versus sea-level training in elite triathletes, which seems to be due to the phenomenon of hypoxia at high altitudes [54]. In another study conducted by the same research group, it was observed that the ingestion of 200 mL of aronia juice in elite triathletes for 45 days reduced markers of CNS lipid peroxidation in urine samples compared to placebo [55]. Consistent with the latter study are data observed in an intervention that evaluated DHA lipid peroxidation and the production of NeuroPs and F2t-dihomo-IsoPs in urine samples as markers of oxidative damage in the CNS; improvements were observed after red wine versus ethanol intake, probably due to the ability of melatonin and hydroxytyrosol to cross the blood–brain barrier (BBB) and are highly present in wine [56].
Polyphenols can alter brain function in three compartments: outside the CNS (by improving cerebral blood flow or modulating signaling pathways from peripheral organs to the brain), in the BBB (by altering the input and output mechanisms of several drug-resistant protein-dependent biomolecules), and within the CNS (by directly modifying neuronal and glial cell activity) [57,58,59]. Flavonoids, in particular, can influence the survival cascade and transcription factors by modulating the redox potential of neurons and glia, presenting a protective function against oxidative damage in the brain [60]. In addition, certain polyphenols have the ability to cross the BBB [61,62].
The BBB protects the brain and consists of endothelial cells with tight junctions between them, allowing a permeability in a narrowly selective manner [63]. This barrier modulates the exchange of molecules between the blood and neuronal tissue, regulating the access of nutrients and different compounds to the brain. The BBB is selectively permeable to polyphenols depending on their structural properties [64]. The physiology and state of the brain can be affected by the compounds that manage to cross the BBB, with the microbial metabolites of polyphenols showing higher permeability compared to their original compounds [65]. There are certain flavonoids that are able to cross the BBB [62], such as catechin, quercetin, cyanidin-3-glucoside [66], different anthocyanidins [67], and hesperetin, naringenin, and their derivatives, which all belonging to the subclass of flavones [61]. It is noteworthy that in the product under investigation, Bresciani and collaborators were able to identify quercetin sulfate, myricetin glucuronide, hesperetin sulfate, naringenin glucuronide, and hesperetin glucuronide, among others, in the blood plasma of their subjects [39]. These are compounds that, according to the scientific literature, could cross the BBB.
Polyphenols have a broad spectrum of molecular and cellular actions against neurological degeneration [68]. Brain function is mediated by molecules such as brain-derived neurotrophic factor (BDNF), a neurotrophin that influences the maintenance, survival, growth, and differentiation of neurons, which is more active in brain regions associated with cognition such as the cerebral cortex and hippocampus [69]. Low levels of BDNF are associated with increased neurodegenerative diseases [70]. It has been shown that foods rich in dietary polyphenols have antioxidant and anti-inflammatory activities at the brain level, in addition to being associated with increased BDNF expression [71]. In line with these observations, together with the reduction in NeuroPs and F2t-dihomo-IsoPs described in the present investigation, it seems that the EXT used could produce improvements at the brain level by decreasing oxidative damage due to the high polyphenolic content of this product.
The limitations of the study include the fact that a population without previous pathologies was chosen; we believe that the baseline values would have been higher in a pathological population and the results could have been more significant. Another limitation was that the subjects were not exposed to additional OS; it was decided not to do so due to the long intervention period, and to prevent a greater number of losses to follow-up. Another limitation was found in assessing the results of ent-7(RS)-7-F2t-dihomo-IsoP, where, despite significant reductions after EXT consumption, it was the only variable that began with non-homogeneous values at baseline.
In regard to future clinical trials, it would be appropriate to choose a population with certain previous pathologies, neurological disorders, or with a certain degree of inflammation, such as population with obesity, in order to determine whether there are improvements in these populations. Another possibility could be to subject the population to certain stresses such as physical activity, taking into account that physical exercise itself is capable of improving endogenous antioxidant capacity. On the other hand, stratification by different metabotypes could be carried out to identify, depending on the composition of the microbiota, which types of subjects could benefit more from a particular type of polyphenol.
## 5. Conclusions
The results of the present investigation suggest that the long-term consumption of a nutraceutical with a high polyphenol content is effective in reducing lipid peroxidation of the CNS by reducing different metabolites derived from AdA, which is present in the white matter of the brain, and from DHA, which is present in the gray matter. This may exert a protective effect against oxidative damage in the CNS.
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|
---
title: The Interrelationship of Reflexivity, Sensitivity and Integrity in Conducting
Interviews
authors:
- Abdulghani Muthanna
- Ahmed Alduais
journal: Behavioral Sciences
year: 2023
pmcid: PMC10045330
doi: 10.3390/bs13030218
license: CC BY 4.0
---
# The Interrelationship of Reflexivity, Sensitivity and Integrity in Conducting Interviews
## Abstract
By employing a thematic review of 74 relevant publications and our learning, teaching, and research experiences and expertise, we discussed the concepts of ‘reflexivity’, ‘sensitivity’ and ‘integrity’, and the factors that enhance or hinder their practice. We also categorized the levels of sensitivity according to the stages of conducting and interpreting interviews in qualitative research. By categorizing the three levels of sensitivity ‘i.e., high sensitivity during interviewing, higher sensitivity during transcribing data, and highest sensitivity and criticality during interpreting data’ with practical examples, we offer an approach that facilitates and supports the application of ethical interviews. We conclude that achieving sensitivity and reflexivity enhances the trustworthiness of the overall research and reflects the application of research ethics and integrity in practice.
## 1. Introduction
The rapid increase in the number of qualitative publications in almost all disciplines reflects the trustworthiness and robustness of the research methodology on the one hand, and the need for strengthening specific skills on the other. Among others, the focus is on critical thinking, interview construction and conduct, interaction, data analysis, synthesis, and interpretational skills.
In qualitative research, researchers develop interview guides that help collect in-depth data from research participants. In the conduct of interviews, researchers attempt to exercise empathy, transparency, and unconditional positivity to create an interviewing space [1,2] and interpersonal connection that allows them to establish a good rapport with participants [3]. However, there are moments when either interviewers or interviewees feel that something is not going well in their interaction. This might be attributed to the topic under discussion, which can be sensitive and demands many reflexive experiences on the part of interviewees. This, of course, demands the expertise of inquirers when dealing with sensitive topics.
The previous literature has attempted to differentiate between several types of reflexivity, including the interaction of the researcher with the social world, the sociology of knowledge, publishing and research politics, and using subjectivity to understand the social and psychological world [4]. Despite the trend toward developing a reflexive research paradigm, particularly in the social sciences [5], these benefits of practicing reflexivity have been critiqued for inflating the significance of reflexivity in research or its role in research as a methodological tool [6]. Given the importance of reflexivity in interviewing, researchers have long criticized the dominance of neo-positivism and romanticism paradigms in interviewing [7], and have advocated for the use of interviews as a means of interaction between the interviewer and the interviewee [8]. When researchers misuse reflexivity to selectively extract what serves their aims and fits their beliefs while ignoring the rest of the transcript, this is a tempting interpretation [9]. This argument was also addressed in another study seeking to demonstrate the difference between verbal interview and a verbatim transcript, and its influence on readers.
These days, there is a need to examine moral accountability and apply more practical ways of analyzing and reporting interviews that include more than just selecting specific phrases to address the researcher’s concerns [10]. In this setting, the researcher advocated for more participatory interview interpretation and presentation [11]. This viewpoint is backed up by initiative calls supporting hermeneutic approaches to conduct more meaningful interviews [12]. One idea to help with this stage is to integrate visual and textual information, allowing the researcher to be more reflexive while conducting, interpreting, and utilizing interview results [13]. Given the long debate over what constitutes reflexivity in interviewing and how reflexivity can increase sensitivity in interviews, what matters most is that researchers remain involved in these existing methodological tools [14], in order to gain a deeper understanding and improve their skills in conducting interviews [15] in real-life situations.
Dealing with participants in real-life situations and collecting an abundant number of words demand qualitative researchers to be reflexive and sensitive. In critical qualitative research, the concept of sensitivity is under-researched. Further, the concept of reflexivity differs from one field to another. We believe that the ethical application of both ‘sensitivity and reflexivity’ demands the practice of ‘integrity’. While there are publications on ‘reflexivity in qualitative studies’, there is a lack of studies on ‘sensitivity in qualitative studies’, interviews in particular, or how ‘integrity’ interrelates to the concepts of ‘sensitivity and reflexivity’. As a result, this paper attempts to answer these research questions: [1] What do ‘reflexivity, sensitivity and integrity’ mean in interviews? and [2] How do they interrelate in conducting interviews? Below we report the research procedures and methods.
## 2. Research Design and Methods
We assume that undergraduates, graduates, postgraduates and even academics could achieve a higher level of quality in qualitative research if they are equipped with the sufficient awareness and understanding of interviewees’ needs, interests, and preferences, that is, sensitivity. Further, we contend that this first step could proceed when they are transparent and reflexive, that is, reflexivity. Not only should they be sensitive and reflexive in interviewing, but they should also believe in research ethics and possess integrity, that is, moral development. Given this, we believe that these three work interactively to achieve quality conduct in interviews. It is significant that researchers need to consider conducting qualitative research that contributes to human development with humane, honest, practical, and professional practices.
The thematic analysis technique is useful for reducing researchers’ biases [16], and provides a systematic and thorough analysis of the examined topic [17]. Therefore, we employed the thematic analysis technique because the study integrates the researchers’ profound academic experiences in qualitative research and teaching undergraduate and graduate students, as well as a critical review of previous studies concerning sensitivity and reflexivity in interviewing.
The reviewed literature included publications (articles, book chapters and books), using the English language. We used several databases to explore relevant studies (ScienceDirect, Sage, Web of Science, and Scopus). The starting date was determined using the oldest available papers relevant to the study, and the ending date was determined using the day of the search. Because reflexivity is applied in all topic areas, all subject areas were considered. We used following terms in our search:Title contains sensitivity in qualitative researchOR contains sensitivity in researchOR contains reflexivity in researchOR contains reflexivity in qualitative researchOR contains sensitivity and reflexivity in qualitative researchOR contains sensitivity and reflexivity in researchOR contains adult moral development We added ‘adult moral development’ in our search keywords because we indicated that researchers might interview with sensitivity, while exercising reflexivity and contemplating integrity. The search resulted in 263 hits, of which 74 were included for review purposes. The rest were excluded due to their irrelevance to the questions of the study, not mentioning any of these targeted themes, or discussing them from different perspectives or contexts. Our list of references shows both the used and cited ones; those with an asterisk (*) refer to the one not used for review purposes.
In this thematic review, we established ‘trustworthiness’ by following four psychometric concepts: credibility, transferability, dependability and confirmability [18,19,20,21,22,23,24,25]. Table 1 details the following techniques used to enhance credibility, facilitate transferability decisions, audit confirmability, and check dependability.
## 3. Findings
In this section, we discuss the main themes and subthemes. Further, we highlight how interviewing with sensitivity by exercising reflexivity, while considering integrity, are interrelated.
## 3.1. Reflexivity in Interviewing
Reflexivity technically refers to the exercise of transparency in interviewing and “promotes an intuition-informed decision-making process as a means to achieve ethical practice and conduct interviews with sensitivity and proficiency” [26] (p. 747). Because reflexivity reflects the attainment of research ethics and quality, some researchers might practice uncomfortable reflexivity instead [27]. Below, we present a synthesis of reflexivity and how qualitative researchers can be sensitive by exercising reflexivity.
## 3.1.1. Defining Reflexivity
In lexicography, reflexivity is defined as “the fact of someone being able to examine his or her feelings, reactions, and motives…reasons for acting… and how these influence what he or she does or thinks in a situation” [28]. The technical meaning of this concept is not significantly different from the lexical meaning. In particular, the lexeme ‘reflexive’ originated from the theory of Coordinated Management of Meaning (CMM). Cronen and Pearce as cited in [29] introduced the CMM, which assumes that regulative and constitutive rules control human interaction. These rules interact reflexively to form meaningful human interactions. Building upon this theory, two other reflexivity types are generated: the strange and reflexive loops. While the former indicates a change in meaning, the other indicates stillness in meaning [30]. The same author proposed four questions to achieve effective interventive interviewing: lineal, circular, strategic, and reflexive. These affect the interviewer and interviewee(s): conservative, liberating, constraining, and generative effects. They also have different purposes, including explaining problems, behavior, leading and confrontation, and hypothetical future and perspective questions [29]. Regardless of all this conceptualization, the general meaning of reflexivity in interviewing relates to “reflecting on the speaker’s narrative, expressing the interviewer’s understanding of it” [31] (p. 3).
While reflexivity decreases subjectivity in conducting interviews [32], the use of the ‘reflexivity’ concept remains dissimilar according to the context and field of study: political and forensic science [33], health care and midwifery practice [34], supervisor–supervisee relationship [35], interviewing offenders [36], and indicating truth in the literature [37]. Most interestingly, some researchers in the field of psychology use psychoanalysis to reach the unconscious processes and gain knowledge from interviewing [38]. The concept of reflexivity in interviewing extends to folklore research [39], clinical psychology [40], surgery [41], and erotic reflexivity in sociology, where these emotions make the collected data more informative and productive [42].
## 3.1.2. A Brief Debate on Reflexivity
The practice of reflexivity is the essence of learning to conduct quality qualitative research [43]. With reflexivity, we understand the value of all the participating members in the research, including the researcher, interviewer, interviewees, society, and the surrounding environment and context [44]. However, some researchers have fashionably used it to claim trustworthiness [45], and the evidence concerning reaching reflexivity is still variable. For instance, some researchers argue that the use of audio and visual aids urges the interviewees to emphasize their identity, enhancing reflexivity [46]. There is also an argument that awareness of the difference between contextual and cognitive interests is the path to producing more reliable knowledge using interviews. This argument attempts to distinguish between the society as a whole and the researchers—making and creating knowledge [47]. Above all, we argue that ‘reflexivity’ is an ongoing part of the research process and is a tool that aids in enhancing the interpretation of the data.
The most debatable issue concerning qualitative research is ‘subjectivity’ [48]. The direct interference, and the interviewer’s influence and interpretation of data might reflect questionable reflexivity; we assume that practicing sensitivity helps bridge this gap by increasing the trustworthiness of the investigated knowledge. However, subjectivity is a plus when merged with the examined object or problem (i.e., objectivity) [49], and when merged with the expertise of the researcher to use the data [50]. Researchers argue that there is a possibility for the occurrence of both subjectivity and objectivity in interviewing; a complete picture of the investigated phenomenon can be better seen through this mixture of being subjective and objective during interviewing, transcribing, and interpreting [51].
## 3.1.3. Factors Enhancing and/or Hindering Reflexivity
Linking the interviewer, interviewees and the society to build up a social world [52] is a factor for enhancing reflexivity. The elicitation of prospective and retrospective reflections over time [53], writing about the personification while conducting research [54], the embodiment of the experiences of the researcher [55], and the interactions among the interviewer, interviewees, and context [56] are all factors that enhance reflexivity. The interaction between the researcher’s body and speech is also influential during interviewing [57]. Moreover, using different categories of knowledge (for example, experiential, clinical, cultural, and academic) strengthens the interview interaction [58]. Additionally, the bioecological systems theory considers space and time as reflexivity. In other words, the geographic location (macro-level) and the immediate surroundings (micro-level) are two factors that can improve the interview quality. Time, be it past, present, or future, improves the interview process even during the transcription and interpretation processes [36].
It is also possible that other factors hinder reaching reflexivity in interviewing. Such factors relate to, for example, touchy topics (e.g., intimacy) [57], losing the focus of the researched topic while interviewing and/or interpretation [32], and the researcher’s values, beliefs, experiences, and interests [59]. Other factors could be the nature of the topic itself, the level of the risk (e.g., the low-risk issue of rural living, gender, the high-risk case of alcohol use), and the trait of the interviewer (e.g., neutrality, self-disclosure) [60]. Further, the researcher’s positionality, be it static or fixed, insider or outsider, contributes either negatively or positively to the reflexivity of the interviewing process [61].
## 3.1.4. Levels and Categories of Reflexivity in Interviewing
Several researchers have attempted to create a three-level typology of ‘micro, meso, and macro’ levels, which are applicable at the individual, organizational, and societal levels. The use of these three levels leads to three types of reflexivity: self-critique, objective and methodological, and political or social [62]. Furthermore, there are three levels of talk during interviews: personal, interpersonal, and positional. While the personal level focuses on the participant’s specific, unique experiences and feelings, the interpersonal level considers the use of words, images, or metaphors, and how the interviewer and interviewee jointly construct the narrative. How people position themselves in the subject and what they talk about refers to the positional level [63] (p. 238).
While reflexivity in research methods and designs of interviewing is known as methodological reflexivity [40], we have found several other categories of reflexivity. For example, participant reflexivity, as a significant factor in decreasing the interviewer’s subjectivity [64], helps achieve trustworthiness in interviewing [65]. Additionally, participant reflexivity is more credible when using dialogic interviewing; this is supported by three strategies: probing questions (i.e., seeking deeper insights), participants’ reflections (discussing interviews, transcript, interpretation, and even findings with the participants), and counterfactual prompting (leading the participants towards a different perspective of thinking) [66]. The more the participants are engaged, the more the trustworthiness is reachable [67].
Another category is reflexive pragmatism; it is achieved by the “interplay between research design and research questions, interviewing and written product” through “the relationship between epistemology and method” [68] (p. 610). A further category is analytical reflexivity, which requires a thick description of all the processes and factors motivating the researcher to decide or conclude on the searched topic [69]. Moreover, the form of language, be it direct speech, reported speech, or enacted scenes, is also vital in establishing analytical reflexivity in interviewing [70].
Researchers in developed and stable countries face different types of challenges while conducting interviews. They, in best cases, view reflexivity as a procedure [71]. Because of the importance of the relationship between the researcher and the participants, and because the feelings of both the parties and the context are vital, emotional reflexivity is introduced as an essential category, referring “to the intersubjective interpretation of one’s own and others’ emotions and how they are enacted” [72] (p. 61). We conclude this part with a summary in Figure 1 of the concept of reflexivity, its enhancing factors, hindering factors, and levels.
## 3.2. Defining Sensitivity: Sensitivity vs. Criticality
The concept of sensitivity is used in medical sciences as a statistical measure for evaluating the accuracy of tests with a positive or negative outcome [73]. The measure of sensitivity becomes highly significant for the reliability of the test outcomes. For medical test results, high sensitivity means high reliability, while the opposite is also true.
In qualitative studies, researchers also exercise sensitivity but in a different way and at various levels. The researcher’s sensitivity includes ‘a host of skills that the qualitative researcher employs throughout all phases of the research cycle’ [74] (p. 780). In interviews, and based on our experiences, ‘sensitivity’ is the concept that deals with awareness and an understanding of interviewees’ needs, interests, and preferences. Being aware and understanding is the primary factor in persuading interviewees to conduct interviews and to engage in possible further interviews and observations. Sensitivity also means that a qualitative researcher needs to be careful in selecting words while interviewing or observing participants so that interviewees are not unintentionally offended. It also means that a researcher needs to be caring, especially when exploring issues that reflect the interviewees’ distressful, depressed, or critical situations. In this sense, sensitivity includes the features of awareness, understanding, carefulness, and caring.
We understand ‘criticality’ as being more relevant to the process of thinking. This critical thinking helps qualitative researchers understand texts, written texts in particular. This means that criticality allows researchers to explore the truth of texts (interview transcripts) while interpreting them. It also means that researchers should be qualified to rationally analyze/interpret and synthesize texts and provide logical conclusions. This criticality is, therefore, very important for all qualitative researchers. In short, sensitivity is applied during verbal interactions with participants, while criticality is implemented in analyzing and reporting texts and raw data.
## 3.3. Levels of Sensitivity While Conducting and Interpreting Interviews
Based on our experiences, we present the three primary levels of sensitivity concerning conducting and interpreting interviews.
## 3.3.1. High sensitivity: During Interviewing
During the verbal interactions with interviewees, in order to invite them for interviews and during the interviews, qualitative researchers need to have a high level of sensitivity, meaning that interviewers should pay attention to the interviewees’ words, facial expressions, and body gestures, and note them down. It also means that interviewers listen to the (audio-recorded) interactions of the interviewees as a unit, and write some notes regarding information that needs further investigations/questioning.
In in-depth interviews, follow-up questions (probes) derived from the answers of interviewees will occur. High sensitivity in this stage helps the continuity of the interaction in an exciting and rich data-obtaining manner. Showing a high sensitivity while exploring sensitive issues is also critical. It helps make interviewees feel at ease and ready to continue the interaction with trust.
## 3.3.2. Higher Sensitivity: Transcribing Data
In transcribing data, qualitative researchers must show higher sensitivity in protecting the anonymity of the participants and their interactions. Higher sensitivity should be applied in transcribing all words verbatim without additions or deletions. In the stage of transcribing data, higher sensitivity also includes profiling every interviewee’s interaction separately and with high confidentiality. In this sense, higher sensitivity application consists of the application of research ethics.
## 3.3.3. Highest Sensitivity and Criticality: Interpreting Data
In interpreting data, qualitative analysts need to have the highest sensitivity level, which indicates the reading of the entire transcripts of interviewees, the natural selection of participants’ quotes and interpreting them without any bias. In this sense, the implementation of criticality is crucial and cannot be separated from sensitivity. It helps conduct a systematic, logical, and reasonable analysis, synthesis, and interpretation of the transcripts/raw data.
## 3.3.4. Unconscious Development of Hyper-Sensitivity and Its Consequences
Qualitative researchers need to listen to the words of interviewees carefully and pay attention to the interviewees’ tones and intonations, facial expressions, and body gestures (that clearly or partially imply different meanings) for the sake of grasping a complete understanding of the verbal expression. However, they also need to pay further attention to their own words and behavior. This is important because some interviewers might show unhappy feelings (e.g., anger) toward their participants. Although they might not mean it, this shows a negative behavior that affects the flow of interaction, if it does not lead the participants to refuse to continue being interviewed immediately. Showing unhappy feelings during an interaction with interviewees might be attributed to the lack of training the interviewers have received or the presence of hypersensitivity as part of their personality. Both aspects are not favorable for a qualitative interviewer, who thus needs further training on how to employ a moderate or higher level of sensitivity when collecting or interpreting qualitative data. Training on the correct rise and fall of tones/voices is essential to any interviewer and interviewee. This is because such a tone or pitch change in the voice might be interpreted negatively, leading to ending a conversation.
In academic life, researchers interact with one another formally and/or informally. In both formal and informal situations, they need to be very sensitive towards selecting vocabulary and gestures or facial expressions. The arbitrary use of vocabulary, gestures or facial expressions might force others to react hyper-sensitively. Such incidents might put researchers in critical situations when it comes to collecting data through interviews. This is because hypersensitivity might be developed unconsciously.
Giving a first-hand example by the first author here helps understand hypersensitivity and its consequences. Two colleagues respected each other and used to discuss different topics at different times. One is religious, and the other one is not. It happened that they once started a discussion on a religious topic (the presence of God), which should be discussed with caution; here, careful vocabulary should be used and each should show respect to one another’s views.
While the discussion initially started well, scholar two’s laughter, the raising of the voice, and the utterance of ‘you both go to hell’ indicate that scholar 2 is not aware of the hyper-sensitivity action they have developed for no apparent reason. Although scholar 2 might attempt to exercise sensitivity when conducting interviews, hyper-sensitivity might appear during their conversation with interviewees, as shown in the above example. Scholar 1 ended the discussion respectfully. The consequence is that they have never discussed any topic since then. Indeed, they might not care for each other anymore. Further, and more seriously, the presence of hypersensitivity affects the reliability of collecting and protecting data, and affects one’s academic and personal life.
By considering our own experiences in conducting interviews, we underscore that conducting more interviews helps enhance researchers’ experiences and expertise, and enhances the application of the appropriate level of sensitivity consciously and unconsciously.
## 3.4.1. Sensitivity and Integrity
We attempt to relate sensitivity to adult moral development. This includes discussing the acquisition of sensitivity if we believe that it is acquired just as other elements in our life are (e.g., language). It also consists of the learnability of sensitivity if we assume that this element does not exist within our biological and/or developmental system. By doing so, we attempt to establish how the proposed levels of sensitivity in terms of conducting interviews (i.e., conducting, transcribing, and interpreting) and higher education levels (i.e., undergraduate, master, and (post)doctoral) are possibly acquired, learned, or structured, towards more ethical yet credible qualitative research.
When conducting an interview, moral development plays a vital role during the whole research process. Here, sensitivity in research will be a mixture of knowledge of personal ethics, social rules, and even country policies, regulations, and laws. We quote here the concept of ‘ethical sensitivity’ in order to introduce our concept of “qualitative sensitivity.” While ethical sensitivity refers to “the ability to recognize decision situations with ethical content” [75] (p. 361), our concept of ‘qualitative sensitivity’ indicates a researcher’s capacity to make the participants, readers, and involved society well-informed about how we conduct our research, interview our participants, collect and interpret data, and even inferred or reached our final findings.
## 3.4.2. Teaching and Learning of Research Ethics
Researchers agree about what could be considered questionable or unquestionable research practices [76,77]. These are usually policies, regulations, or laws, individually or collectively, issued by institutions or countries [78]; this is in order to achieve what we call the ‘academic order’ in knowledge production and science advancement.
Given that there is no concrete evidence regarding whether we acquire ethics or learn them, we believe that this is similar to language, which we acquire during our early childhood and when we move to the preschool level and onwards. Previous and current research on teaching ethics and integrity to students indicates that integrity is an independent variable related to personality, but other external factors could still influence it. For instance, a study on teaching ethics to medical students in Croatia indicates that reasoning relates to gender and Machiavellianism [79]. In the context of Turkey, it is reported that although students realize that it is unlawful to cheat, they still practice it [80]. Nevertheless, viewing sensitivity as ethics based on culture and religion is not enough; rules and laws are vital for implementation. This is evident in countries where higher education quality is low and questionable research practices are practiced [81].
Some researchers tend to practice irresponsible research or questionable research practice [82], including “thinking errors, poor coping with research pressures, and inadequate oversight” [83] (p. 320). However, be it an element of ethics, rules, or laws, the teaching of the responsible conduct of research for a researcher [84] should be promoted regardless of the used teaching methods [85]. These could be case study samples [86], active learning, experiential learning or task-based learning [87]. It could start as early as the undergraduate level and be upgraded based on higher education levels, or be promoted in future careers [88].
## 3.5. The Interrelationship of ‘Sensitivity, Reflexivity, and Integrity’ in Conducting Interviews: Practical Examples
Having introduced each of these three themes separately, we show in Table 2 how these three interact together to allow conducting interviews with higher quality in order to achieve better accountability for qualitative research. We divided the sensitivity levels according to the educational level into three main categories. Next, we provided three possible situations for the three levels of sensitivity when conducting an interview. Each situation shows how a researcher (undergraduate, graduate, or (post)doctorate) interviews, transcribes and interprets data. Criticality, part of sensitivity, is considered during each third level (third, sixth, and ninth). After that, reflexivity is presented, and in each situation, a different category or level of reflexivity is illustrated.
It should be noted that this is changeable according to the situation. This is followed by ‘the typical behavior’ column, which attempts to describe what happened and how it could be modified, benefitting from sensitivity and reflexivity in interviewing. When these two fail, as we illustrated, then moral development (integrity) plays a role. Given this, conducting interviewing requires being sensitive and having intrapersonal and interpersonal skills, being reflexive through transparency and other techniques, and having acquired and learned research ethics. In other words, while moral development is acquiring and learning the knowledge required to conduct interviews ethically, sensitivity and reflexivity are the means and techniques to conduct interviews professionally. It is important to note that the examples provided in the following table are imagined scenarios that help clarify the interrelationship between the ‘sensitivity, reflexivity and integrity’ concepts in conducting interviews.
## 4. Discussion and Conclusions
Our findings critically discuss the high significance of employing ‘reflexivity, sensitivity and integrity’ in conducting interviews and in transcribing and interpreting the collected data. In conducting interviews, reflexivity is useful in increasing the trustworthiness of the collected data. It also helps raise further awareness of the people engaged in the interaction.
Researchers’ reflexivity can be enhanced through eliciting prospective and retrospective reflections over time [53], writing about the personification while conducting research [54], embedding researchers’ experiences [55], allowing interaction between the interviewer, interviewees, and context [56] and using different categories of knowledge [58]. On the contrary, reflexivity can be hindered when discussing sensitive topics (e.g., intimacy) [57], or losing the focus of the researched topic [89], among others. Learning about and practicing the different types of reflexivity is important for interviewers. Methodological reflexivity [40], participant reflexivity [64], reflexive pragmatism [68], analytical reflexivity [69], contextual reflexivity [71] and emotional reflexivity are all important in the ethical and appropriate conduction of interviews. To increase the level of reflexivity, researchers need to also develop some sensitivity.
We argue that the concept of sensitivity deals with interviewers’ awareness and understanding of interviewees’ needs, interests, and preferences. Being aware and understanding is necessary for conducting interviews, in addition to the careful selection of words and showing care while discussing distressing or critical situations. In this sense, we state that sensitivity includes the features of awareness, understanding, carefulness, and care.
The application of our proposed three levels of sensitivity ‘i.e., high sensitivity during interviewing, higher sensitivity during transcribing data, and highest sensitivity and criticality during interpreting data’ are very important and should be learned and exercised by interviewers. By applying these levels of sensitivity, we believe that the ‘qualitative sensitivity’ of researchers is enhanced, leading to a strong application of ‘research integrity’. While teaching and learning research ethics differs from one context to another, it is important that teachers and learners develop a stronger awareness of ‘qualitative sensitivity’, which, if applied well, will lead to the attainment of research ethics and integrity. However, qualitative researchers need to consider not being hypersensitive, as this is not useful in interacting with other people. This demands being careful in our daily interactions, which might shape the way we interact when it comes to conducting interviews.
Finally, we contend that qualitative researchers might apply different levels of sensitivity and reflexivity in conducting and interpreting interviews. The application of a different level of sensitivity and reflexivity, the acquisition of intrapersonal and interpersonal skills, the exercise of reflexive transparency and other techniques, and the learning and teaching of research ethics are significant in conducting and interpreting interviews professionally.
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|
---
title: Sepsis-Induced Coagulopathy Phenotype Induced by Oxidized High-Density Lipoprotein
Associated with Increased Mortality in Septic-Shock Patients
authors:
- Yolanda Prado
- Pablo Tapia
- Felipe Eltit
- Cristian Reyes-Martínez
- Carmen G. Feijóo
- Felipe M. Llancalahuen
- Claudia A. Riedel
- Claudio Cabello-Verrugio
- Jimmy Stehberg
- Felipe Simon
journal: Antioxidants
year: 2023
pmcid: PMC10045333
doi: 10.3390/antiox12030543
license: CC BY 4.0
---
# Sepsis-Induced Coagulopathy Phenotype Induced by Oxidized High-Density Lipoprotein Associated with Increased Mortality in Septic-Shock Patients
## Abstract
Sepsis syndrome is a highly lethal uncontrolled response to an infection, which is characterized by sepsis-induced coagulopathy (SIC). High-density lipoprotein (HDL) exhibits antithrombotic activity, regulating coagulation in vascular endothelial cells. Sepsis induces the release of several proinflammatory molecules, including reactive oxygen species, which lead to an increase in oxidative stress in blood vessels. Thus, circulating lipoproteins, such as HDL, are oxidized to oxHDL, which promotes hemostatic dysfunction, acquiring prothrombotic properties linked to the severity of organ failure in septic-shock patients (SSP). However, a rigorous and comprehensive investigation demonstrating that oxHDL is associated with a coagulopathy-associated deleterious outcome of SSP, has not been reported. Thus, we investigated the participation of plasma oxHDL in coagulopathy-associated sepsis pathogenesis and elucidated the underlying molecular mechanism. A prospective study was conducted on 42 patients admitted to intensive care units, (26 SSP and 16 non-SSP) and 39 healthy volunteers. We found that an increased plasma oxHDL level in SSP was associated with a prothrombotic phenotype, increased mortality and elevated risk of death, which predicts mortality in SSP. The underlying mechanism indicates that oxHDL triggers an endothelial protein expression reprogramming of coagulation factors and procoagulant adhesion proteins, to produce a prothrombotic environment, mainly mediated by the endothelial LOX-1 receptor. Our study demonstrates that an increased plasma oxHDL level is associated with coagulopathy in SSP through a mechanism involving the endothelial LOX-1 receptor and endothelial protein expression regulation. Therefore, the plasma oxHDL level plays a role in the molecular mechanism associated with increased mortality in SSP.
## 1. Introduction
Sepsis syndrome is the main cause of mortality in patients admitted to intensive care units (ICU). Sepsis is an uncontrolled response to an infection and is characterized by severe systemic inflammation, which progresses to multiple organ dysfunction syndrome (MODS), which is associated with a high mortality rate [1,2,3]. During sepsis, several critical alterations occur, including a loss of hemostatic control, which promotes a procoagulant phenotype that is a central factor for inducing MODS and increasing mortality [3,4]. In fact, sepsis progression is characterized by disseminated intravascular coagulation (DIC) which generates detrimental effects in organ function and is associated with an increased mortality rate [4,5,6,7,8]. Indeed, rats with DIC induced by endotoxin lipopolysaccharide (LPS) administration, showed a decrease in organ failure after profibrinolytic protein tissue-type plasminogen activator (t-PA) injection and the administration of the anticoagulant heparin-reduced MODS [9,10]. The first diagnostic criteria of DIC were established by the International Society on Thrombosis and Haemostasis (ISTH) [11]. During sepsis, systemic coagulation appears in an early stage of sepsis, which compromises tissue circulation and generates MODS [12]. To obtain an early diagnosis of acute DIC, including sepsis-associated DIC, the Japanese Association for Acute Medicine (JAAM) designed the JAAM-DIC diagnostic criteria [13,14]. Thus, a few years ago, new diagnostic criteria were designed specifically for sepsis-based coagulation disorders, including sepsis-induced coagulopathy (SIC) [15,16].
High-density lipoprotein (HDL) is an accepted vascular protective factor that contributes to hemostatic control by providing protection against vascular diseases [17]. HDL is a lipoprotein that circulates in the bloodstream and exhibits both antithrombotic activity and enhances fibrinolysis, thus playing a significant role in regulating coagulation [18,19]. HDL promotes its protective effects by interacting with several tissues, including endothelial cells (ECs), to trigger several processes to maintain hemostatic balance [20]. ECs control hemostasis equilibrium via the regulation of protein expression, such as coagulation factors and adhesion proteins [21,22].
Sepsis-induced systemic inflammation is characterized by immune system overactivation, which produces several inflammatory molecules, including reactive oxygen species (ROS), generating increased oxidative stress in blood vessels [23,24,25,26,27,28]. This oxidative environment promotes oxidative modifications to several molecules in the plasma. Consequently, circulating lipoproteins, such as HDL, are oxidized through modifications mediated by enzymatic and non-enzymatic oxidative activity to generate oxHDL, the oxidized form of HDL [29,30]. Interestingly, it has been reported that HDL is more susceptible than other lipoproteins to oxidation [31]. It is noteworthy that oxHDL fails to maintain hemostasis control and acquires prothrombotic properties, possibly due to oxHDL-induced procoagulant activity via the impairment of EC functions [32,33]. Some evidence has been reported concerning the detrimental actions of oxHDL during coagulation regulation. The expression of plasminogen activator inhibitor-1 (PAI-1) is stimulated by HDL, which is oxidized by 15-lipoxygenase, causing procoagulant actions [34], suggesting that oxHDL leads to a decrease in fibrinolysis, affecting clot stability. Furthermore, previous evidence has shown that oxHDL plasma levels are inversely associated with D-dimer, fibrinogen plasma, plasmin–α2 plasmin inhibitor complex, and thrombin–anti-thrombin complex levels in diabetic patients [35,36], indicating that oxHDL has an impact on both blood coagulation and fibrinolysis. Thus, during an oxidative-stress-mediated inflammatory condition, native HDL is converted into oxHDL, which is dysfunctional and causes cells to acquire a procoagulant phenotype.
Plasma oxHDL levels are increased in several inflammatory pathological conditions, such as obesity, diabetes, renal failure, cardiovascular disease, rheumatoid arthritis and liver, among several others [37,38,39,40,41]. It has been reported that oxHDL correlates with organ failure severity in septic patients [42]. Congruently, recombinant HDL administration led to a decrease in organ dysfunction in endotoxemic rats [43]. In line with this finding, a decrease in HDL plasma level is a predictor of organ dysfunction in septic patients [44]. However, to the best of our knowledge, whether increased plasma oxHDL participates in hemostatic alterations via EC dysfunction, leading to SIC generation and increased mortality in septic-shock patients (SSP) has not yet been studied. Therefore, we focused on determining whether the plasma oxHDL level in SSP is associated with increased mortality in SSP, and demonstrating that oxHDL induces a procoagulant phenotype mediated by a molecular mechanism that involves changes in the endothelial protein expression associated with both SIC establishment and mortality in SSP.
Our results indicate that circulating oxHDL promotes a procoagulant phenotype, which is strongly associated with SIC and leads to the establishment of increased mortality and an elevated risk of death in SSP. The mechanism underlying this process indicates that circulating oxHDL promotes the endothelial protein expression reprogramming of both coagulation factors and procoagulant adhesion molecules, generating a prothrombotic environment. This process is mediated by the activation of the endothelial lectin-like low-density lipoprotein (LOX-1) receptor and the participation of the endotoxin receptor, Toll-like receptor 4 (TLR-4).
Taken together, the plasma oxHDL level emerges as an important factor involved in increased mortality in SSP.
## 2.1. Patients and Volunteers
The study was conducted in 42 ICU patients, 26 septic-shock patients (SSP) and 16 non-septic-shock patients (NSSP), admitted to ICU at Hospital Clínico Metropolitano La Florida located in Santiago, Chile. The patients were critically ill patients admitted to the ICU (septic and non-septic patients) with a distributive shock. The patients were classified as SSP when infection was detected. NSSP consisted of neurocritical, acute pancreatitis, and post-operative vascular surgery patients. The clinical and demographic features of the patients are provided in Supplemental Table S1. The mortality of SSP and NSSP was $46.2\%$ and $50.0\%$, respectively. As a control group, we recruited 39 healthy volunteers (HV). This study was approved by the local institutional Ethics and Bioethics Review Board (N°141008). Additionally, the Commission of Bioethics and Biosafety of Universidad Andres Bello also approved all experimental protocols (N°$\frac{002}{2020}$). The investigation conforms with the principles outlined in the Declaration of Helsinki. All participants or their surrogates signed an informed consent form prior to entry into the study.
Inclusion criteria for SSP and NSSP included being aged >18 y.o. without a limitation for resuscitation or suffering from shock defined operationally as a requirement for a norepinephrine (NE) dose of >0.1 g·kg−1·min−1 to maintain the mean arterial pressure between 65–80 mmHg and a lactate concentration of >4 mmol/L. Furthermore, patients had respiratory support with invasive mechanical ventilation and a C-reactive protein level of ≥15 mg/dL. These criteria had to be met 48 h after patients were admitted to the ICU.
Exclusion criteria for SSP and NSSP comprised the consumption of drugs that modify coagulation, fibrinolysis, and platelet aggregation in the previous 14 d. Additionally, we included solid cancer with a more advanced stage than carcinoma in situ, organ transplantation, leukemia, lymphoma, pregnancy, liver cirrhosis, nephrotic syndrome, chronic dialysis, congestive heart failure and red blood cell transfusion with >2 units within the last 48 h after ICU admission. In addition, SSP and NSSP with chemotherapy, hospitalization, or surgery within the last 3 months prior to ICU admission were also excluded. HV were enrolled from the outpatients in the hospital area and research facilities at Universidad Andres Bello. The abovementioned exclusion criteria were also applied to the HVs. The operational definition of a HV was people without any known chronic disease and explicitly without arterial hypertension, chronic allergic condition, diabetes, a body mass index of >30 kg/m2, smoking, pregnancy and coagulation dysfunction. In addition, those subjects with an episode of hospitalization or surgery in the last 3 months prior to enrollment in the study were excluded.
Demographic, clinical and laboratory data were carefully recorded and collected. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score was evaluated after admission to the ICU. The Sequential Organ Failure Assessment (SOFA) score was determined on the day of blood recollection. The management and treatment of patients was carried out by the attending physicians at the ICU without any specific intervention for the purpose of this study. Thirty-day mortality was also recorded.
## 2.2. Plasma HDL and oxHDL Measurements, Extraction, and Determination of HDL Oxidation Kinetics Parameters
Human blood samples were obtained after receiving informed consent from patients and volunteers. Samples were collected in a sodium citrate blood collection Vacutainer® tube. Native HDL and oxidized HDL (oxHDL) were measured using a Human OxHDL ELISA kit from MyBioSource, Inc. (San Diego, CA, USA). HDL fractions were obtained from blood samples by ultracentrifugation using sodium bromide. The HDL fraction was adjusted to 50 μg/mL in a phosphate buffer (10 mmol/L, pH 7.4). Next, 20 μL of 1 mmol/L CuSO4 was added and changes in absorbance at 234 nm were recorded to determine the oxidation capacity of lipoproteins. The oxidation kinetics parameters (lag time, slope and maximal oxidation) of oxidized HDL were measured, adapted from previously reported studies [40,45,46]. Lag time denotes the period required to start oxidation, detected by a change in baseline absorbance measured in seconds. Slope represents the oxidation velocity and Vmax indicates the maximal oxidation, measured as absorbance/seconds and maximal absorbance/seconds, respectively. Values were obtained by subtracting the baseline absorbance. Kinetic curves were fitted to a sigmoidal curve to obtain slope and maximal oxidation values.
## 2.3. Plasma Measurements of Coagulation Parameters and Secreted Proteins Determination
Human blood samples were obtained after receiving informed consent from patients and volunteers. Samples were collected in a sodium citrate blood collection Vacutainer® tube. Plasma platelet count was measured using a Sysmex k 1000 (Sysmex Inc., Kobe, Japan). Plasma levels of D-dimer and fibrinogen were measured using an ELISA kit (both from R&D Systems, Inc.) in accordance with the manufacturer’s instructions. INR was measured using a proper i-STAT cartridge. Plasma levels of tissue factor (TF), t-PA, tissue-factor pathway inhibitor (TFPI) (all from R&D Systems, Inc.), thrombin-activatable fibrinolysis inhibitor (TAFI), von Willebrand factor (vWF) and p-selectin (P-Sel) (all from Abcam, USA) were measured using ELISA kits, according to the instructions of the manufacturer.
## 2.4. Circulating Endothelial Cell (CECs) Separation and Protein Expression Determination Using Flow Cytometry
CECs, which are composed of circulating endothelial mature cells (CMECs) and circulating endothelial progenitor cells (CEPCs), were separated from blood samples obtained from SSP and NSSP, 48 to 72 h after admission to the ICU, and HV. Blood samples were collected in a 3 ml vacutainer tube containing liquid tripotassium ethylenediaminetetraacetic acid (EDTA) as anticoagulant. The collection of blood samples and the isolation of cells and their analysis were carried out by two personnel who were blinded to patient information, as well as clinical characteristics or the further outcomes of the patients. The CMECs and CEPCs were isolated using magnetic bead-based immunoseparation, as described previously [47,48]. Briefly, after blood samples were obtained, the total mononuclear blood cell fraction was isolated from the blood by Ficoll-Histopaque (Sigma Chemical Co., St. Louis, MO, USA) gradient separation. The mononuclear cell fraction was washed by centrifugation with phosphate-buffered saline solution. Then, the mononuclear blood cell fraction was subjected to immunomagnetic bead capture (IBC) using a bead-conjugated CD133 monoclonal antibody and magnetic cell separation system (Miltenyi Biotec, Bergisch Gladbach, Germany). The captured cells corresponded to an enriched CEPC sample (positive selection, CD133+), while the cells contained in the eluted solution contained CMECs (negative selection, CD133−). To directly isolate CMECs, eluted fluid was subsequently subjected to a second step of IBC positive selection using a bead-conjugated CD146 monoclonal antibody (Miltenyi Biotec), obtaining an enriched CMEC sample (CD146+ and CD133−). CMEC and CEPC quantification was performed using flow cytometry. Compensation particles (BD CompBeads) and amine polymer microspheres (Becton Dickinson) were used for compensation [47,48]. Fluorescent-conjugated antibodies against VE-Cadherin+ and CD31+ and against VEGFR-2+ and CD34+ were used for the detailed phenotype characterization of CMECs and CEPCs, respectively. Flow cytometry analysis was performed to determine the expression changes in TF, TAFI, t-PA, TFPI, vWF and P-Sel using the corresponding monoclonal antibodies (all from R&D Systems, Inc.), coupled to suitable secondary antibodies conjugated to fluorophores (all from ThermoFisher, Waltham, MA, USA). The labeled cells were then analyzed immediately via flow cytometry (BD FACS Fortessa, BD Biosciences, San José, CA). Color compensation matrices were calculated for each staining combination within each experiment using single-stained antibody. In all analyses, doublets and clusters were eliminated. A minimum of 10,000 events were analyzed.
## 2.5. Endothelial Cell Culture, mRNA Isolation and RT-qPCR
Human aortic endothelial cells (HAEC (Lonza, Chicago, IL) were cultured in EGM-2 medium supplemented with $5\%$ FBS. Experiments were performed in $1\%$ FBS. RT-qPCR experiments were performed to measure TF, TAFI, t-PA, TFPI, vWF and P-Sel mRNA levels in HAEC. Total RNA was extracted with Trizol according to the manufacturer’s protocol (Invitrogen, Carlsbad, CA, USA). DNAse I-treated RNA was used for reverse transcription using the Super Script II Kit (Invitrogen, Carlsbad, CA, USA). Equal amounts of RNA were used as templates in each reaction. Quantitative-PCR was performed using the SYBR Green PCR Master Mix (AB Applied Biosystems, Foster City, CA, USA). Assays were run using a RotorGene instrument (Corbet Research, Sydney, Australia). Data are presented as relative mRNA levels of the gene of interest normalized to relative levels of 28S mRNA and normalized against the control condition.
## 2.6. Generation of Oxidization of HDL
Native HDL (Sigma-Aldrich, St Louis, MO, USA) at a final concentration of 0.5 mg/mL was incubated at 37 °C for 16 h in the presence of 50 μM CuSO4 in PBS. The reaction was stopped by storing the oxHDL at 4 °C to prevent further oxidation. The extent of lipoprotein oxidation was monitored by measuring thiobarbituric acid reactive substance (TBARS) formation using the TBARS assay kit (Cayman Chemical Company, Ann Arbor, MI, USA), following the manufacturer’s instructions [49]. For oxHDL, a total of 17.55 ± 1.95 μM MDA was obtained versus 1.12 ± 0.57 μM from native HDL, in a total of seven independent experiments (p ≤ 0.001). To chelate copper from the reaction, oxHDL was incubated for 5 min with 100 mg/mL of CHELEX-100 (Bio-Rad Laboratories Inc., Hercules, CA, USA), centrifuged at 4 °C for 1 min at 500× g, and the pellet was discarded [50].
## 2.7. Reagents and Inhibitors
The following reagents and inhibitors were used: HDL (Sigma-Aldrich, St Louis, MO, USA), neutralizing anti-LOX antibody (1:50, Abcam) and CLI-095 (Invitrogen, USA). All inhibitors were added 1 h before and maintained throughout the treatment. Buffers and salts were purchased from Merck Biosciences.
## 2.8. Data Analyses
Results are presented as mean ± SD or mean ± $95\%$ confidence interval (CI) for the relative risk. Differences were considered significant at $p \leq 0.05.$ Statistical differences were assessed using the student’s t-test (or Mann–Whitney type), one-way analysis of variance (one-way ANOVA) (or Kruskal–Wallis type) followed by Dunn’s post hoc test and two-way analysis of variance (two-way ANOVA) followed by Tukey post hoc test. See the figure legends for the specific test used. The relationships between variables were assessed by means of correlation analysis using Spearman’s correlation coefficients and linear regression. Survival Kaplan–Meier curves were compared via a log-rank (Mantel-Cox) test and Gehan–Breslow–Wilcoxon test to determine survival rates. Contingency analyses with Fisher’s exact test were used to assess the relative risk of death. The ability of the oxHDL level or INDEX to predict death at 30 days was assessed using the area under the receiver operating characteristic curve (AUROC) with a $95\%$ confidence interval ($95\%$ CI). Statistical testing was two-sided and used the $5\%$ significance level. The data were analyzed with GraphPad Prism version 9.4 (GraphPad Software, LLC). Samples used in the study were defined to identify the mean magnitude effect of a >2-fold increase in the oxHDL level between HV and SSP and NSSP with standard deviations of $10\%$. Accordingly, a sample size of 39 HV, 26 SSP and 16 NSSP, considering the further separation into survival/non-survival and high/low plasma levels or INDEX ratio, would provide a $90\%$ statistical power to detect a >2-fold increase in the oxHDL level using a two-sided 0.05 significance level.
## 3.1. Increased oxHDL Plasma Level in SSP and NSSP
Blood samples from SSP and NSSP showed an increase in plasma oxHDL levels (Figure 1A), whereas the level of native HDL had decreased (Figure 1B) in comparison to HV. Considering the divergent change between oxHDL and HDL, we determined the oxHDL/HDL INDEX (called INDEX from this point) as a measure of the transition of native HDL to the oxidized form. As shown in Figure 1C, INDEX increased in SSP and NSSP, exhibiting a strong significance in the SSP group
## 3.2. Susceptibility to Oxidation of HDL from SSP
Considering that oxHDL is derived from the oxidation of native HDL, we investigated whether the HDL from patients was more susceptible to oxidation. To that end, the HDL obtained from HV, SSP, and NSSP were subjected to in vitro oxidation to determine the HDL oxidation kinetic parameters, including lag time, oxidation rate, and maximal oxidation. We observed that the lag time of HDL oxidation was similarly shortened in both SSP and NSSP (Figure 1D,E) compared to HV. Interestingly, the HDL oxidation rate measured as the slope of HDL oxidation showed a greater increase in values in SSP rather than NSSP (Figure 1D,F), denoting the susceptibility of HDL from SSP to oxidation. Additionally, the maximal oxidation of HDL in both SSP and NSSP increased, reaching similar maximal values (Figure 1D,G).
## 3.3. Plasma oxHDL Level and INDEX in Non-Survivor SSP
Next, we wondered whether levels of oxHDL and INDEX differentially increased in surviving and non-surviving SSP and NSSP. The results showed that oxHDL levels were higher in non-surviving than surviving SSP, whereas in NSSP, no difference was detected (Figure 2A). Similarly, INDEX was higher in non-surviving than surviving SSP, whereas no change was found in NSSP (Figure 2B). Interestingly, the oxHDL level correlated with a 30-day survival rate in non-surviving SSP, whereas in NSSP, no significant correlation with this survival rate was found (Figure 2C). Such a correlation was stronger ($$p \leq 0.0012$$ versus 0.0125) when INDEX was analyzed (Figure 2D), suggesting that INDEX correlates better than oxHDL level with the 30-day survival rates of non-surviving patients in the SSP group.
Considering that a higher oxHDL level could be more deleterious than lower ones, we analyzed the survival curves of SSP and NSSP grouped into high- and low-oxHDL levels. High- and low-oxHDL groups were determined using the median concentration depicted in Figure 1A as the threshold. The results showed a significant difference in the high-oxHDL group compared with the low-oxHDL group in SSP patients, as indicated by the log-rank (Mantel–Cox) test as shown in Figure 2E. To give more weight to deaths at early time points, the Gehan–Breslow–Wilcoxon test was used, and results showed that the high-oxHDL group had an increase in death incidence compared to low-oxHDL (Figure 2E). However, NSSP showed no differences between high- and low-oxHDL levels in the different groups of patients (Figure 2F). Next, whether a higher INDEX value reflected more deleterious conditions was assessed. To that end, high- and low-INDEX groups were determined using the median value depicted in Figure 1C as the threshold. Similarly, the high-INDEX survival curve showed significant differences compared to the low-INDEX group, as indicated by the log-rank (Mantel–Cox) test and Gehan–Breslow–Wilcoxon test, as shown in Figure 2G. In addition, NSSP showed no differences between the high- and low-INDEX levels in different groups of patients (Figure 2H).
## 3.4. High-INDEX Increases Relative Risk of Death in SSP
After considering the results showed above, we performed a contingency analysis to determine the relative risk of death between high- and low- oxHDL and INDEX groups in SSP and NSSP. The results showed that high-oxHDL exhibited an increased, although not significant, risk of death compared to low-oxHDL (Figure 2I). Similarly, NSSP showed no difference in the relative risk of death (Figure 2J). It is noteworthy that the results showed that high-INDEX SSP exhibited a significant increase in the risk of death compared to the low-INDEX group (Figure 2K), whereas NSSP showed no difference in relative risk of death (Figure 2L).
Taking the results in Figure 2 together, an association between increased oxHDL levels and INDEX with SSP but not NSSP is suggested. It is noteworthy that the INDEX shows a stronger potential than the oxHDL level for predicting mortality and risk of death in SSP.
## 3.5. High-oxHDL Level and High-INDEX Correlates with SIC Score in SSP
After considering the prominent role of the plasma oxHDL level and INDEX in SSP, but not in NSSP, we focused our investigation on SSP. Thus, we investigated whether the oxHDL level and INDEX are linked to coagulation parameters to generate a procoagulant phenotype in SSP. As shown in Figure 3A, the platelet count was reduced in SSP compared to healthy volunteers, a finding that is consistent with a platelet consumption phenotype. Interestingly, the high-oxHDL and high-INDEX groups of patients showed a reduced platelet count (Figure 3B) compared to the low-oxHDL and low-INDEX groups, respectively.
Correlation analyses showed that the high-oxHDL and high-INDEX groups correlate with platelet count (Figure 3C, upper panels), whereas low-oxHDL and low-INDEX (Figure 3C, lower panels) showed no significant correlations. D-dimer serves as a marker of coagulation, since it is a fibrin degradation product that increases as a result of fibrinolysis [45,51]. Our results demonstrated that SSP showed an increase in the plasma levels of D-dimer (Figure 3D). The high-oxHDL and high-INDEX groups of patients exhibited an increased plasma D-dimer level (Figure 3E). Additionally, correlation analyses showed that the high-oxHDL and high-INDEX groups correlate with D-dimer levels (Figure 3F, upper panels), whereas low-oxHDL and low-INDEX (Figure 3F, lower panels) showed no such correlation. Fibrinogen was used as a coagulation marker because it decreases as consequence of conversion to fibrin. SSP showed a decreased plasma fibrinogen level (Figure 3G). The high-oxHDL and high-INDEX groups of patients displayed a decreased plasma fibrinogen level (Figure 3H). A decreased plasma fibrinogen level correlated with the high-INDEX group (Figure 3I, upper-right panel). The high-oxHDL, low-oxHDL, and low-INDEX groups did not correlate with plasma fibrinogen levels (Figure 3I, upper-left and lower panels). Because prothrombin time (PT) is prolonged in the procoagulant phenotype, we measured this parameter. To standardize PT measurements, the international normalized ratio (INR) was chosen. The results indicate that SSP showed an increase in INR (Figure 3J). The high-oxHDL and high-INDEX groups of patients showed increased INR (Figure 3K). The correlation analyses showed that the high-oxHDL and high-INDEX groups correlated with INR (Figure 3L, upper panels), while low-oxHDL and low-INDEX (Figure 3L, lower panels) showed no correlations. We also measured the activated partial thromboplastin time (aPPT) since it is prolonged in coagulopathy during sepsis. The results indicate that SSP exhibited a prolonged aPPT (Supplemental Figure S1A), a finding that correlated with the high-INDEX group, whereas the high-oxHDL, low-oxHDL and low-INDEX groups did not correlate with plasma aPPT levels (Supplemental Figure S1B).
A plasma determination of platelet count, D-dimer, fibrinogen, and INR are frequently used to determine ISTH-DIC incidence based on DIC score calculations, whereas only platelet count, INR, and SOFA are needed for SIC determination. Thus, we determined the DIC score to evaluate its association with oxHDL and INDEX levels. To accomplish this task, the ISTH-DIC and SIC score algorithms were used [15,52,53] to determine coagulopathy occurrences as an ISTH-DIC score of ≥5 or SIC score of ≥4. The results showed that the calculated ISTH-DIC score from SSP patients ranged between 2 and 7. The high-oxHDL and high-INDEX groups of patients showed an ISTH-DIC score (Figure 3M,P upper panels, respectively). Correlation analyses showed that the high-oxHDL (Figure 3N upper panel) and high-INDEX (Figure 3Q upper panel) groups correlated with the calculated DIC scores, whereas low-oxHDL and low-INDEX (Figure 3O,R, upper panels, respectively) groups did not show significant correlations. Similarly, the high-oxHDL and high-INDEX groups showed correlating SIC scores (Figure 3M,P lower panels, respectively). Correlation analyses showed that the high-oxHDL (Figure 3N lower panel) and high-INDEX groups (Figure 3Q lower panel) correlated with the calculated SIC scores, whereas the low-oxHDL and low-INDEX groups (Figure 3O,R, lower panels, respectively) did not show significant correlations. These results showed similar results between ISTH-DIC and SIC scores, but the SIC score showed a major ability to detect a major proportion of patients undergoing SIC (score ≥ 4).
After taking into account that plasma oxHDL levels lead to the induction of a procoagulant phenotype and associate with a ≥4 SIC score, we determined whether oxHDL led to an increase in coagulation in blood vessels. A zebrafish model was used, which allowed us to observe in vivo coagulation in the vasculature due the vasculature’s transparency. To that end, 4 dpf wild-type zebrafish larvae were microinjected with saline solution, HDL, oxHDL, or not injected (control), and 24 h later, thrombus formation was analyzed by means of o-dianisidine staining in the caudal vein (Supplemental Figure S2A). The results showed that zebrafish larvae treated with oxHDL exhibited significant coagulation in the posterior part of the caudal vein compared to those treated with HDL, saline solution, or not treated (Supplemental Figure S2B–F). In addition, we determined if the existence of coagulation was coupled to changes in the blood flow. Thus, 4 dpf Tg(fli1:eGFP)y1 larvae, that have the vasculature and platelets fluorescently green labeled, were microinjected with saline solution, HDL, oxHDL, or not injected (control). After 24h, an in vivo determination of the number of platelets observed in 60 seconds via time-lapse analysis in a section of the caudal vein was performed (Supplemental Figure S2G). The results showed that zebrafish larvae treated with oxHDL exhibited a significant reduction in the platelet flow compared to those treated with HDL, saline solution, or not treated (Supplemental Figure S2H–L; and supplemental movies 1–4).
## 3.6. Plasma oxHDL Level and INDEX Are Associated with Increased Mortality in SSP
To evaluate the capacity to predict mortality through measuring the plasma oxHDL level and INDEX from SSP, we used an area under the receiver operating characteristic curve (AUROC) analysis. The plasma oxHDL level and INDEX from SSP showed a high predictive capacity (Figure 4) showing AUROC values superior to the diagonal nondiscrimination line, which denotes their statistical significance. The AUROC analysis performed in all SSP showed that the oxHDL level is a better predictor than INDEX (Figure 4A). Interestingly, when AUROC analysis was performed in high-oxHDL and high-INDEX SSP groups, INDEX was a better predictive marker than oxHDL level (Figure 4B). Notably, in both cases, the capacity to predict mortality outcomes based on oxHDL and INDEX was better when compared with the APACHE-II and SOFA scores, which are scores of severity and prognosis, respectively, and are widely used for critical patient evaluations (Figure 4A,B).
These findings indicate that plasma oxHDL levels and particularly the INDEX are associated with increased mortality in SSP.
## 3.7. Plasma oxHDL Level and INDEX Correlate with Coagulation Factors and Platelet Adhesion Proteins Level in SSP
Considering both the plasma oxHDL level and INDEX association between an increased oxHDL level and pro-coagulant coagulopathy parameters, the SIC score shown in Figure 3 and the finding that oxHDL treatment induced vascular coagulation in the zebrafish model (Supplemental Figure S2), we investigated the underlying mechanisms involved in oxHDL-induced coagulation. To that end, we detected several circulating coagulation factors and adhesion proteins involved in coagulation. SSP plasma showed increased prothrombotic TF levels, as shown in Figure 5A. Importantly, the high-oxHDL and high-INDEX groups of patients showed an increased TF plasma level (Figure 5B), compared to the low-oxHDL and low-INDEX groups, respectively. Correlation analyses showed that the high-oxHDL and high-INDEX groups correlated with TF level (Figure 5C, left panels). Interestingly, the SIC score from the high-oxHDL and high-INDEX patients were found to correlate with the TF level (Figure 5C, right panels). Additionally, plasma samples from SSP showed an increase in the levels of the antifibrinolytic factor TAFI, as shown in Figure 5D. Notably, the high-oxHDL and high-INDEX groups of patients exhibited an increased TAFI plasma level (Figure 5E).
Correlation analyses showed that the high-INDEX group and SIC scores from high-INDEX patients correlated with TF levels (Figure 5F, lower panels). The high-oxHDL and SIC score from high-oxHDL showed no significant correlation (Figure 5F, upper panels). Furthermore, the t-PA decreased in SSP (Figure 5G). The high-oxHDL and high-INDEX groups of patients showed a decreased t-PA plasma level (Figure 5H). Correlation analyses indicated that the high-INDEX group, and SIC score from the high-INDEX patients correlated with the t-PA level (Figure 5I, lower panels). The high-oxHDL and SIC scores from high-oxHDL groups showed no significant correlations (Figure 5I, upper panels). Furthermore, the antithrombotic molecule TFPI, as shown in Figure 5J, showed a decrease in plasma levels in SSP. The high-oxHDL and high-INDEX groups of patients displayed a decreased TFPI plasma level (Figure 5K). Correlation analyses showed that the high-INDEX group correlated with the TFPI level (Figure 5L, left-lower panel). Similarly, the SIC score from high-oxHDL and high-INDEX patients correlated with TFPI levels (Figure 5L, right panels). The high-oxHDL group showed no significant correlation (Figure 5L, left-upper panels). On the other hand, the plasma levels of soluble vWF and soluble p-selectin (svWF and sP-Sel, respectively), both of which promote platelet adhesion to the endothelium, were also evaluated. SSP plasma showed increased levels of svWF (Figure 5M), and the high-oxHDL and high-INDEX groups of patients displayed an increased svWF plasma level (Figure 5N). Correlation analyses showed that the high-oxHDL and high-INDEX groups correlated with the svWF level (Figure 5O, left panels). The SIC score from the high-oxHDL and high-INDEX groups of patients also correlated with the svWF level (Figure 5O, right panels). SSP plasma showed an increase in levels of sP-Sel (Figure 5P). The high-oxHDL and high-INDEX groups of patients showed an increased sP-*Sel plasma* level (Figure 5Q). Correlation analyses showed that the high-INDEX group (Figure 5R, left-lower panel), and SIC score from the high-oxHDL and high-INDEX patients were found to correlate with the sP-Sel level (Figure 5R, right panels). The high-oxHDL group showed no significant correlation with sP-Sel (Figure 5R, left-upper panel). The ISTH-DIC score showed similar results as those shown for the SIC score (Supplemental Figure S3). The results obtained from the low-oxHDL and low-INDEX groups of patients showed no significant correlations (not shown).
These data indicate that altered levels of coagulation factors and platelet adhesion proteins in SSP appear to be associated with the high-oxHDL and high-INDEX patients, and with the final event of coagulation, since an association with the calculated SIC scores in the high-oxHDL and high-INDEX groups was found.
## 3.8. Circulating Endothelial Cells from SSP Exhibited Modified Coagulation Factors and Platelet Adhesion Protein Expression, which Correlate with Plasma oxHDL and INDEX
Considering that the vascular endothelium regulates hemostasis via both coagulation factor production and platelet adhesion protein generation and that oxHDL induces procoagulant actions via the impairment of EC function, we investigated whether ECs from SSP showed these features. It has been reported that septic patients showed increased CECs, which are composed from CMECs, which are a suitable model for studying vascular ECs from patients, and also from CEPCs [47,48,54]. Thus, analyses were performed on CECs obtained from the high- and low-oxHDL groups and compared with those from healthy volunteers. Positive and negative magnetic bead-based immunoseparation was performed to successfully separate the CMECs (CD146+, CD133−) and CEPCs (CD133+) by means of appropriate markers, after which cells were subject to flow cytometry analyses to determine changes in the expression of coagulation factors and platelet adhesion proteins (Supplemental Figure S4). The CMECs from SSP showed an increase in TF expression (Figure 6A). The high-oxHDL and high-INDEX groups of patients showed increased TF expression (Figure 6B). Correlation analyses showed that the high-INDEX group correlates with TF expression (Figure 6C, left-lower panel). Similarly, the SIC score from the high-oxHDL and high-INDEX patients were found to correlate with TF expression (Figure 6C, left panels). The high-oxHDL group showed no significant correlation (Figure 6C, left-upper panel). CMECs from SSP showed an increase in TAFI expression (Figure 6D). The high-oxHDL and high-INDEX groups of patients exhibited an increased TAFI expression (Figure 6E). Correlation analyses showed that the high-INDEX group and SIC score from the high-INDEX patients were found to correlate with TAFI expression (Figure 6F, lower panels), whereas high-oxHDL and the SIC score from high-oxHDL showed no significant correlation with the SIC score (Figure 6F, upper panels). CMECs from SSP showed a decreased t-PA expression (Figure 6G). The high-oxHDL and high-INDEX groups of patients displayed a decreased t-PA expression (Figure 6H). Correlation analyses showed that high-INDEX and SIC score from high-INDEX groups correlated with t-PA expression (Figure 6I, lower panels), whereas high-oxHDL and the SIC score from the high-oxHDL groups showed no significant correlation (Figure 6I, upper panels). CMECs from SSP showed a decrease in TFPI expression (Figure 6J). The high-oxHDL and high-INDEX groups of patients showed a decreased TFPI expression (Figure 6K). Correlation analyses showed that the high-INDEX group and SIC score from the high-INDEX group of patients correlated with TFPI expression (Figure 6L, lower panel) whereas high-oxHDL and SIC score from high-oxHDL showed no significant correlation (Figure 6L, upper panel). CMECs from SSP showed an increase in vWF expression (Figure 6M). High-oxHDL and the high-INDEX groups of patients showed increased vWF expression (Figure 6N). Correlation analyses showed that high-oxHDL and high-INDEX and the SIC score from the high-oxHDL and high-INDEX groups of patients correlated with vWF expression (Figure 6O). CMECs from SSP showed an increase in P-Sel expression (Figure 6P). The high-oxHDL and high-INDEX groups of patients showed an increased P-Sel expression (Figure 6Q). Correlation analyses showed that high-oxHDL and high-INDEX (Figure 6R, left panels) and the SIC score from the high-INDEX group (Figure 6R, right-lower panel) of patients were found to correlate with P-Sel expression, whereas the SIC score from the high-oxHDL patients showed no significant correlation (Figure 6R, right-upper panel). Similar results were obtained after testing CEPCs (not shown). The ISTH-DIC score showed similar results as shown for the SIC score (Supplemental Figure S5). The results obtained from the low-oxHDL and low-INDEX groups of patients showed no significant correlation with P-Sel (not shown).
These results indicate that ECs from SSP express altered levels of coagulation factors and platelet adhesion proteins, both of which are associated with a high-oxHDL and high-INDEX level in addition with the calculated SIC score in the high-oxHDL and high-INDEX groups.
## 3.9. Endothelial Cells Exposed to Plasma from SSP Modified Coagulation Factors and Platelet Adhesion Protein Expression, Which Correlate with Plasma oxHDL and INDEX
After considering the previously mentioned results, we tested whether cultured ECs exposed to plasma extracted from SSP showed similar changes to those observed in CECs. To that end, plasma from high-oxHDL and low-oxHDL patient groups were extracted and added to cultured EC, after which the expression of coagulation factors and platelet adhesion proteins were measured (Supplemental Figure S6).
Cultured ECs exposed to plasma obtained from the high-oxHDL patients showed an increase in TF mRNA expression (Figure 7A). The high-oxHDL and high-INDEX groups of patients showed an increased TF mRNA expression (Figure 7B). Correlation analyses showed that high-oxHDL and high-INDEX (Figure 7C, left panels) and the SIC score from the high-INDEX (Figure 7C, right-lower panels) group of patients correlated with TF mRNA expression, whereas the SIC score from the high-oxHDL patients showed no significant correlation with TF mRNA expression (Figure 7C, right-upper panel). Cultured ECs exposed to plasma obtained from the high-oxHDL patients showed an increase in TAFI mRNA expression (Figure 7D). The high-oxHDL and high-INDEX groups of patients showed an increased TAFI mRNA expression (Figure 7E). Correlation analyses showed that high-oxHDL and high-INDEX (Figure 7F, left panels) and the SIC score from the high-INDEX (Figure 7F, right-lower panels) group of patients correlated with TAFI mRNA expression, whereas the SIC score from the high-oxHDL patients showed no significant correlation with TAFI mRNA expression (Figure 7F, right-upper panel). Cultured ECs exposed to plasma obtained from high-oxHDL patients showed a decrease in t-PA mRNA expression (Figure 7G). The high-oxHDL and high-INDEX groups of patients showed a decreased t-PA mRNA expression (Figure 7H). Correlation analyses showed that high-oxHDL and high-INDEX (Figure 7I, left panels) and the SIC score from the high-INDEX (Figure 7I, right-lower panels) group of patients correlated with t-PA mRNA expression, whereas the SIC score from high-oxHDL patients showed no significant correlation (Figure 7I, right-upper panel). Cultured ECs exposed to plasma obtained from the high-oxHDL patients showed a decrease in TFPI mRNA expression (Figure 7J). The high-oxHDL and high-INDEX groups of patients showed a decreased TFPI mRNA expression (Figure 7K). Correlation analyses showed that high-oxHDL and high-INDEX and the SIC score from the high-oxHDL and high-INDEX groups of patients correlated with TFPI mRNA expression (Figure 7L). Regarding vWF and P-Sel adhesion protein expression levels, the results showed that cultured ECs exposed to plasma obtained from high-oxHDL patients showed an increase in vWF mRNA expression (Figure 7M). The high-oxHDL and high-INDEX groups of patients showed an increased vWF mRNA expression (Figure 7N). Correlation analyses showed that high-INDEX and the SIC score from the high-INDEX groups were found to correlate with vWF mRNA expression (Figure 7O, lower panels), whereas high-oxHDL and the SIC score from the high-oxHDL patients showed no significant correlation (Figure 7O, upper panels). Cultured ECs exposed to plasma obtained from the high-oxHDL patients showed an increase in P-Sel mRNA expression (Figure 7P). The high-oxHDL and high-INDEX groups of patients showed increased P-Sel mRNA expression (Figure 7Q). Correlation analyses showed that high-INDEX (Figure 7R, left-lower panel) and the SIC score from the high-oxHDL and high-INDEX groups of patients correlated with P-Sel mRNA expression (Figure 7R, right panels), whereas the high-oxHDL group did not show correlation (Figure 7R, left-upper panel). The ISTH-DIC score showed similar results as shown for the SIC score (Supplemental Figure S7). The results obtained from the low-oxHDL and low-INDEX groups of patients showed no significant correlation with this parameter (not shown).
## 3.10. LOX-1 and TLR-4 Receptors Mediate Actions of SSP Plasma in Endothelial Cells
Although patients’ plasma contains lipoproteins, including HDL and oxHDL, several other molecules are also present. Considering that bacterial infection is the main difference between SSP and NSSP, circulating bacteria and bacterial endotoxin play a role in SSP pathogenesis. LPS is the main circulating endotoxin detected in SSP infected with Gram-negative bacteria.
Therefore, oxHDL and endotoxin are concurrently present in SPP plasma, and both elicit actions in tissues, including the endothelium. The actions of oxHDL and endotoxin in ECs are mediated by their endothelial receptors, LOX-1 and TLR-4, respectively [27,55,56]. Thus, we investigated the role played by these endothelial receptors in the actions of SSP plasma in terms of modifying coagulation factors and platelet adhesion protein expression. To that end, ECs exposed to plasma from high-oxHDL and high-INDEX patient groups were treated with a neutralizing antibody against LOX-1 and the TLR-4 specific inhibitor, CLI-095, after which mRNA expression of coagulation factors and platelet adhesion proteins were measured.
The results showed that both LOX-1 and TLR-4 inhibition caused a partial decline in the increase in TF mRNA expression (Figure 8A) and TAFI (Figure 8B) when ECs were exposed to high-oxHDL (Figure 8A,B, left panels) and high-INDEX (Figure 8A,B, right panels). Furthermore, LOX-1 inhibition led to a strong reduction in the decrease in mRNA expression of t-PA and TFPI (Figure 8C,D, respectively) in ECs that were exposed to high-oxHDL (Figure 8C,D, left panels) and high-INDEX (Figure 8C,D, right panels), whereas TLR-4 inhibition provoked a slight lessening in the increase in mRNA expression of t-PA and TFPI (Figure 8C,D, respectively). In terms of adhesion protein expression, the results showed that LOX-1 inhibition led to a strong reduction in the increase in mRNA expression of vWF, whereas TLR-4 inhibition provoked a minor decrease (Figure 8E) in ECs that were exposed to high-oxHDL (Figure 8E, left panel) and high-INDEX (Figure 8E, right panel). In the case of P-Sel, the results showed that both LOX-1 and TLR-4 inhibition caused a partial reduction in the increase in mRNA expression of P-Sel (Figure 8F) in ECs that were exposed to high-oxHDL (Figure 8F, left panel) and high-INDEX (Figure 8F, right panel).
These results indicate that oxHDL via activation of its receptor, LOX-1, lead to the promotion of an endothelial procoagulant phenotype by controlling the expression of t-PA, TFPI and vWF, whereas that the activation of the endotoxin receptor, TRL-4, showed only a slight tendency toward such a phenotype. Furthermore, TF, TAFI and P-Sel expression levels are controlled by the concomitant actions of oxHDL and endotoxin.
## 3.11. Endothelial Cells Exposed to Exogenous SSP Plasma Preparation Modified Coagulation Factors and Platelet Adhesion Protein Expression
Considering that SSP plasma elicit a prothrombotic phenotype in ECs, we hypothesized that cultured ECs exposed to an exogenous preparation of plasma-containing oxHDL and endotoxin, which mimics SSP plasma, would exhibit similar effects in protein expression profiles versus that observed in CECs from SSP as shown in Figure 6 and in cultured ECs exposed to SSP plasma as shown in Figure 7.
To that end, exogenous plasma samples were prepared by combining oxHDL and endotoxin. The exogenous plasma preparation of SSP high- and low-oxHDL was designed using the median concentration of oxHDL measured in plasma obtained from high- and low-oxHDL groups (SSP-oxHDLHIGH+Endo and SSP-oxHDLLOW+Endo, respectively). In addition, exogenous plasma preparations of SSP high- and low-INDEX were designed using the concentration of oxHDL and HDL measured in the median INDEX value determined in plasma obtained from high- and low-INDEX groups (SSP-INDEXHIGH+Endo and SSP-INDEXLOW+Endo, respectively). Endotoxin was added at a concentration used in a previous study by us for similar in vitro studies in ECs [57,58]. Additionally, the exogenous plasma preparation from the HV was designed by combining a suitable amount of HDL and oxHDL, but without endotoxin (HV-oxHDL and HV-INDEX), as shown in Supplemental Figure S8.
The results indicated that ECs exposed to an exogenous preparation of SSP-oxHDLHIGH+Endo and SSP-INDEXHIGH+Endo elicited an increase in TF and TAFI mRNA expression (Figure 9A and B, respectively). Furthermore, ECs exposed to SSP-oxHDLHIGH+Endo and SSP-INDEXHIGH+Endo showed a decrease in the expression of t-PA and TFPI mRNA expression (Figure 9C and D, respectively). In addition, ECs exposed to SSP-oxHDLHIGH+Endo and SSP-INDEXHIGH+Endo showed an increase in the mRNA expression of adhesion proteins vWF and P-Sel (Figure 9E,F, respectively). The treatment with exogenous SSP-oxHDLLOW+Endo and SSP-INDEXLOW+Endo yielded no significant effects compared to HV-oxHDL and HV-INDEX, respectively (not shown).
Taken together, these results indicate that SSP produces a procoagulant phenotype by modulating plasma coagulation factors and platelet adhesion protein levels. It is noteworthy that the oxHDL level and, principally, INDEX are strongly associated with the loss of hemostasis in SSP. The results indicated that oxHDL promotes procoagulant activity by means of changing the endothelial protein expression profile, mainly through LOX-1 endothelial receptors, and supported by TLR4. Notably, these findings indicate that the plasma oxHDL level and, mainly, its INDEX are associated with coagulopathy in SSP.
## 4. Discussion
The results from this study indicate that SSP and NSSP showed increases in both oxHDL and INDEX and decreases in HDL plasma levels. The HDL from SSP is more susceptible to oxidation than NSSP HDL, a finding that depicts an oxidation-mediated conversion of the HDL pool into oxHDL. Furthermore, the oxHDL level and INDEX correlate in non-surviving SSP but not in NSSP. Interestingly, the high-oxHDL level and high-INDEX groups of SSP showed increases in mortality and risk of death. In addition, the high-oxHDL level and high-INDEX groups of patients were found to be associated with higher ISTH-DIC and SIC scores in SSP. Notably, a plasma high-oxHDL level and high-INDEX showed significant AUROC analyses for predicting mortality in SSP, and both parameters were better for such a prediction than APACHE II and SOFA scores. The underlying mechanism indicates that oxHDL promotes an endothelial reprogramming in protein expression patterns. OxHDL-treated ECs and high oxHDL SSP samples show an increase in the expression and secretion of the procoagulant factors, TF and TAFI, as well as decreases in the anticoagulant molecules t-PA and TFPI, thus generating a prothrombotic environment. Additionally, the expression and secretion of the procoagulant adhesion proteins, vWF and P-Sel, were increased. Finally, the oxHDL-induced endothelial protein expression change was found to require the activation of the endothelial LOX-1 receptor, which is supported, but not required, by the action of the endotoxin receptor TLR-4.
The role of HDL as an antithrombotic factor has been widely demonstrated [17,18,19,20]. However, it is well known that during sepsis, a large amount of ROS is generated and interacts with HDL to generate oxHDL, which exhibits dysfunctional functions directly involved in pathophysiological processes [32,33]. Increased oxHDL and decreased HDL plasma levels in SSP are involved in other inflammatory diseases, including obesity and type 2 diabetes mellitus [35,36,59,60]. Additionally, increased levels of HDL have been associated with endothelial dysfunction [61,62,63].
After taking into account the results presented in this study, it is reasonable to hypothesize that the excess of HDL is converted into dysfunctional HDL, after which it promotes endothelial damage. Of note is that HDL from SSP is more susceptible to oxidation than is NSSP. This feature could be explained as based on the underlying infection-induced oxidative stress in SSP, which is absent in NSSP. This idea is supported by the notion that LDL oxidation is influenced by infection [64,65]. In fact, endothelial infections caused by the bacterium *Chlamydia pneumoniae* promote LDL oxidation [65]. Interestingly, the oxidation of HDL appears to be influenced further by serum lipids from the non-HDL fraction, which includes LDL and VLDL [66]. Similarly, in patients with renal failure, less resistance of LDL to oxidation related to the decrease in HDL was observed, suggesting that LDL oxidation depends on the presence of further lipids circulating in blood [67]. Additionally, structural differences between distinct HDL subclasses have no impact on their susceptibilities to oxidation [68], reinforcing the idea that changes in all lipoprotein levels circulating in the bloodstream could influence HDL oxidation. Importantly, it has been reported that the susceptibility of HDL oxidation is associated with age, after observing an increased capacity for HDL oxidation that is associated with aging, a process that has a crucial impact on thrombotic alteration in the elderly population [69].
The days of hospitalization at the ICU of non-surviving SSP correlated with the plasma oxHDL level, indicating that higher oxHDL levels are associated with mortality. Notably, the higher portion of oxHDL levels showed an increase in both mortality and risk of death compared to the lower half. This finding indicates that although all SSP exhibits increased oxHDL compared to HV, a mortality increase is linked only to higher oxHDL values. It is noteworthy that the high-INDEX value strongly associates with mortality and risk of death. Indeed, a high-INDEX value displayed a stronger association with several of the coagulation parameters evaluated throughout the experiments in this study. This finding agrees with those proposed by Guirgis et al., in which dysfunctional HDL (Dys-HDL) was found to be useful as a biomarker for early sepsis [42]. In contrast, in this study, it was hypothesized that early Dys-HDL levels would correlate with SOFA scores in the first 48 h, whereas in the present study, we showed a low correlation between both oxHDL level and INDEX values, and SOFA scores. Further experiments could be performed to understand this difference, which could be based on the different methods used for oxHDL and Dys-HDL determination. Furthermore, other articles have proposed oxHDL as a biomarker for human pathologies, including nonalcoholic fatty liver disease, pericoronary inflammation, cardiovascular risk and calcific aortic valve disease [70,71,72,73] Reaching high INDEX values is required for the concurrent generation of oxHDL and consumption of HDL. Thus, prothrombotic actions of oxHDL appear while protective HDL properties on the endothelium decrease [17,19,74], promoting the prothrombotic phenotype. Thus, it is possible to have a permanent conversion from HDL into oxHDL in SSP with a normal or high plasma HDL level upon ICU admission. Low-INDEX results from a slightly increased oxHDL level and marginally decreased or normal HDL levels. In this scenario, a competition between prothrombotic and protective actions could be generated, canceling each other out. Thus, it is possible to understand that despite the finding that low-oxHDL levels and low-INDEX values were higher than those observed in HV, the promotion of prothrombotic activity failed to occur. The plasma oxHDL level and INDEX in both SSP and the high-SSP group showed significant capabilities for predicting mortality. Remarkably, this capacity for predicting mortality was better than the widely used scores of gravity and organic failure, such as the APACHE-II and SOFA scores, respectively. These relevant findings suggest that plasma oxHDL levels and INDEX are accurate diagnostic tools for predicting mortality in SSP.
Endothelial tissue performs several crucial functions, including the control of hemostasis. However, EC becomes dysfunctional during sepsis, which is an early sign of the loss of hemostasis control in the severe systemic inflammation that triggers sepsis-associated MOD [75,76]. Endothelial dysfunction contributes to severity in dysfunctional coagulation and supports the pathogenesis of sepsis-induced coagulopathy and increasing mortality [77]. Since sepsis is a systemic inflammatory syndrome, several studies have reported that markers of inflammation are useful for diagnostic of sepsis-associated coagulopathy [78]. However, these strategies demand the evaluation of several inflammatory mediators, thus making such an evaluation unsuitable for transfer to a clinical setting. Along the same line, it has been reported that coagulation parameters are suitable biomarkers for predicting coagulopathy in septic patients [79,80], but again, several coagulation parameters need to be measured. Interestingly, ISTH-DIC also predicts mortality in non-septic patients [81].
Evidence indicates that the scavenger receptor class BI (SR-BI) is an HDL receptor that mediates its protective actions [82]. The results from this study indicate that oxHDL actions were mediated by the LOX-1 receptor. Conversely, evidence has been presented in which oxHDL interacts with SR-BI in platelets [83]. This finding suggests that HDL and oxHDL actions are mediated by different receptors, which is in agreement with different outcomes. Interestingly, LOX-1 is an LDL and oxLDL receptor [27,84], indicating that oxHDL elicits its deleterious actions because it interacts with the LDL receptor. On the other hand, oxHDL activates the nuclear factor kappa beta (NF-κB) transcription factor, a process mediated by LOX-1 activation, thus modulating protein expression [27,85]. Similar to the results reported in this study, the LOX-1 receptor mediates the oxHDL-induced expression regulation of coagulation factors and adhesion proteins. Further experiments must be performed to demonstrate whether NF-κB is involved in this transcriptional process.
Several lines of evidence indicate that endotoxin binds TLR-4 to mediate its inflammatory action in EC and other cell types [55,86,87]. This evidence suggests that endotoxin plays a key role in a dysfunctional endothelium. However, our results demonstrate that oxHDL triggers protein expression related to coagulation in the absence of TLR-4, but the complete expression of TF, TAFI and P-Sel requires the endotoxin-mediated TLR-4 activation. Interestingly, endotoxin binds to HDL, thus neutralizing the endotoxin’s properties [88], indicating that even when the plasma HDL level is maintained in a normal range, its actions could be blunted by its interaction with endotoxin.
The main strengths of our study are the monitoring of patients for 30 days or until death. The study design and experimental procedures were performed in a rigorous double-blind manner; thus, researchers performing benchtop experiments did not participate in patient management or the survival evaluation carried out by the medical personnel, and a non-survival outcome was significant in allowing successful discrimination between patients. However, our study also has some limitations, mainly regarding the capacity of the oxHDL level and INDEX to predict SSP mortality. Because we used a rigorous inclusion and exclusion criteria, patients were classified based on a restricted definition of septic shock. Thus, we used a low number of patients that is not high enough for our investigation to be considered as a clinical study or clinical trial. Additionally, we did not use a group without septic shock because this group of patients did not show any significant results. Further studies and a bigger sample size are required to extrapolate these findings to a general population of patients who are undergoing septic shock.
Taken together, the findings shown here indicate that the plasma oxHDL level and particularly its INDEX are correlated with coagulopathy in SSP, which is associated with increased mortality in SSP.
## 5. Conclusions
Increased plasma oxHDL levels and particularly the oxHDL/HDL INDEX are correlated with coagulopathy in SSP, with a severe impact on mortality and risk of death, which is mediated through an underlying molecular mechanism that involves changes in endothelial protein expression. Taken together, the findings shown here indicate that plasma oxHDL and the oxHDL/HDL INDEX levels are associated with increased mortality in SSP.
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|
---
title: Differential Roles of CD36 in Regulating Muscle Insulin Response Depend on
Palmitic Acid Load
authors:
- Jingyu Sun
- Yajuan Su
- Jiajia Chen
- Duran Qin
- Yaning Xu
- Hang Chu
- Tianfeng Lu
- Jingmei Dong
- Lili Qin
- Weida Li
journal: Biomedicines
year: 2023
pmcid: PMC10045334
doi: 10.3390/biomedicines11030729
license: CC BY 4.0
---
# Differential Roles of CD36 in Regulating Muscle Insulin Response Depend on Palmitic Acid Load
## Abstract
The possible role of fatty acid translocase (CD36) in the treatment of obesity has gained increasing research interest since researchers recognized its coordinated function in fatty acid uptake and oxidation. However, the effect of CD36 deficiency on intracellular insulin signaling is complex and its impact may depend on different nutritional stresses. Therefore, we investigated the various effects of CD36 deletion on insulin signaling in C2C12 myotubes with or without palmitic acid (PA) overload. In the present work, we reported the upregulated expression levels of CD36 in the skeletal muscle tissues of obese humans and mice as well as in C2C12 myotubes with PA stimulation. CD36 knockdown using RNA interference showed that insulin signaling was impaired in CD36-deficient C2C12 cells in the absence of PA loading, suggesting that CD36 is essential for the maintenance of insulin action, possibly resulting from increased mitochondrial dysfunction and endoplasmic reticulum (ER) stress; however, CD36 deletion improved insulin signaling in the presence of PA overload due to a reduction in lipid overaccumulation. In conclusion, we identified differential roles of CD36 in regulating muscle insulin response under conditions with and without PA overload, which provides supportive evidence for further research into therapeutic approaches to diabetes.
## 1. Introduction
Obesity is one of the most serious public health diseases in the world because it predisposes multiple diseases and shortens life expectancy. Obesity is considered an important link in type 2 diabetes and is likely caused by insulin resistance (IR) [1]. Skeletal muscle is responsible for glucose disposal and is essential to systemic glucose regulation [2]. Therefore, muscle (IR is a major feature of obesity and type 2 diabetes [3]. Phosphorylation of AKT is thought to be a critical step in intracellular insulin signaling [4,5]. Defective insulin-induced AKT phosphorylation is associated with obesity-related muscle insulin resistance [6,7].
CD36, as a transmembrane glycoprotein, is abundantly expressed in adipocytes, macrophages, muscle cells, and hepatocytes [8]. CD36 promotes the uptake and oxidation of long-chain fatty acids (LCFAs), which in turn regulate intracellular metabolic homeostasis [9]. Recently, the potential regulatory role of CD36 on insulin signaling has been increasingly investigated; however, the effect of CD36 on insulin signaling is complex [10,11]. Some studies have shown that upregulation of CD36 is associated with insulin resistance, suggesting that CD36 may be a negative mediator of insulin sensitivity [11]. However, other studies show that CD36 has an opposite regulatory effect on insulin sensitivity [12]. Collectively, the exact regulation of insulin sensitivity by CD36 is highly controversial and the underlying mechanisms remain uncovered. Interestingly, it has been shown that CD36-deficient mice clear glucose more rapidly on a chow diet; however, after switching to a high fructose diet, CD36-deficient mice exhibited significant glucose intolerance compared to wild-type (WT) mice [13], hypothesizing that the paradoxical role of CD36 in insulin signaling may depend on different nutritional stresses. Here, we investigated the effect of CD36 on insulin signaling in C2C12 myotubes under different nutritional conditions with or without PA overload.
Mitochondrial dysfunction is commonly observed in the skeletal muscle of mice with IR [14]. The presence of reduced mitochondrial protein expression, decreased oxygen consumption rates, impaired ATP synthesis, and reduced mitochondrial protein expression have been observed in people with obesity or IR [15,16]. Recent research also proposes that ER stress has emerged as a key player in the onset of insulin resistance [17]. Considering that CD36 regulates insulin action, mitochondrial dysfunction and ER stress may be key regulators of insulin signaling by CD36 [18].
In the present study, the role of CD36 in the skeletal muscle tissue of obese humans and mice and in C2C12 myotubes under PA stimulation was first examined. To further determine the effect of CD36 deficiency on insulin signaling under different nutritional conditions, the cultured C2C12 myotube models with or without PA overload were utilized. Finally, mitochondrial dysfunction and ER stress were highlighted as potential mechanisms by which CD36 may regulate insulin signaling.
## 2.1. Animal
Eight-week-old male C57BL/6 mice were provided by Charles River Laboratories (Beijing, China). All mice in the study were randomly divided into the following two groups: a normal diet group (ND) ($10\%$ fat, SLACOM, Shanghai, China) and a high fat diet group (HFD) ($40\%$ fat, SLACOM, Shanghai, China). Mice were housed in comfortable conditions with a 12:12 h light–dark cycle, at a temperature of 20–26 °C, and with free access to feeding and drinking. After 4 months of high-fat feeding, mice were euthanized and gastrocnemius muscle tissues were collected, rapidly frozen in liquid nitrogen, and stored at −80 °C for subsequent analysis. All animal experiments were approved by the Animal Care and Use Committee of Tongji University.
## 2.2. Cell Culture
Mouse skeletal muscle cell line (C2C12) was cultured with growth medium (high-glucose DMEM supplemented with $10\%$ FBS (#10270106, Thermo Fisher Scientific, Waltham, MA, USA) and L-glutamine (2 mmol/L, #25030081, Thermo Fisher Scientific, Waltham, Massachusetts, USA). C2C12 cells were differentiated in differentiation medium (low-glucose DMEM supplemented with $2\%$ horse serum (#C2510, VivaCell Biosciences, Shanghai, China)). Differentiated C2C12 myotubes were starved (16–18 h) in buffer A (low-glucose DMEM supplemented with 2 mmol/L L-glutamine, 100 mmol/L MEM nonessential amino acids (#11140050, Thermo Fisher Scientific, Waltham, MA, USA), 100 units/mL penicillin, and 100 mg/mL streptomycin (#25030081, YuanPei, Shanghai, China)). For PA treatment, the fatty acid (FA)-bovine serum albumin (BSA) conjugate was prepared as follows: firstly, PA was dissolved in sodium hydroxide solution at 95 °C to a final concentration of 100 mmol/L. Secondly, the 100 mmol/L PA solution was diluted to 10 mmol/L with BSA solution. The stock solution of PA or BSA were mixed into culture media at a final concentration of 200 μM. FA-free BSA was obtained from Equitech-Bio (#BAH66, Kerrville, TX, USA). Palmitate acid was obtained from Sigma–Aldrich (#O1383, St. Louis, MO, USA).
## 2.3. RNA Interference
siRNA duplexes that target mouse CD36 (siCD36-1: 5′-GGAUGACAACUUCACAGUUTT-3′; siCD36-2: 5′-GGAUUGGAGUGGUGAUGUUTT-3′) and negative control (siCont, 5′-UUCUCCGAACGUGUCACGUTT-3′) were synthesized by Sigma–Aldrich. Lipofectamine RNAiMAX (#13778075, Thermo Fisher Scientific, Waltham, MA, USA) was used to transfect C2C12 cells with siRNA at a final concentration of 20 nM according to the manufacturer’s protocol. All siRNA-transfected myotubes had normal morphology and were used 72 h after transfection. Western blot analysis confirmed the transfection efficiency.
## 2.4. CD36 Plasmids Construction
Wild-type mouse skeletal muscle RNA was extracted and reversed to cDNA; primers were designed to amplify the CD36 CDS sequence from cDNA. Then CD36 overexpression sequence was cloned into the PWPI vector to obtain CD36 overexpression plasmids. CD36 plasmid was packaged to lentivirus and transfected with C2C12 for the next analysis.
## 2.5. Transcriptome Sequencing
Total RNA from the two groups was extracted with TRIzol reagent (Invitrogen, Carlsbad, CA, USA). A cDNA library was constructed using the Illumina NovaseqTM 6000 sequence platform (LC Bio, Hangzhou, China). By using the Illumina paired-end RNA- sequencing approach, the transcriptome was sequenced, generating one million 2 x 150 bp paired-end reads from the sample, which were dependent on Illumina paired-end RNA- sequencing. Reads from all samples were compared to the reference genome by using the HISAT (version 2.0, Johns Hopkins University, Baltimore, MD, USA) software package. After calculation with StringTie software (Johns Hopkins University, Baltimore, MD, USA), FPKM values were generated to indicate the expression levels of the mRNAs. Genes were subjected to differential expression analysis by using edgeR software between two different groups. Differentially expressed genes (DEGs) were considered at p value < 0.05 and absolute log2 (fc) ≥ 1. Significantly, DEGs were enriched to KEGG pathways by using the OmicStudio tools (LC Bio, Hangzhou, China). The raw RNA-seq data has been uploaded to the public database of GSE under accession number: GSE204686. The KEGG pathways were identified as significantly enriched following a hypergeometric test (FDR < 0.05). For the reanalysis of public human transcription data, raw data were downloaded from the GSE database (no. GSE81965). After quality analysis with fastp (version 0.20.1, HaploX, Shenzhen, China), sample reads were mapped to the reference genome of humans (version GRCh38) using STAR (version 2.7.6a, NHGRI, National Institutes of Health, Bethesda, MD, USA). The reads count values after calculation with htseq (version 0.13.5) represent the expression level of CD36 between obese individuals and non-obese controls.
## 2.6. Oil Red O Staining
C2C12 myotubes were cultivated on coverslips in six-well plates with 200 μM PA for 16 h to stain intracellular lipid deposits. The cells were then stained with Oil Red O (#O0625, Sigma Aldrich, Shanghai, China) after being fixed with $4\%$ paraformaldehyde. A microscope was used to capture images.
## 2.7. Triglyceride (TG) Content Assay
Intracellular TG content in C2C12 myotube cells was determined with a Tissue TG Content Assay Kit (#E1013, Applygen, Beijing, China). 1 × 106 myotube cells were washed twice with DPBS and lysed with lysis buffer. The levels of TG released from myotube cells were analyzed according to the instructions of the kit and normalized by total protein quantity.
## 2.8. Reactive Oxygen Species (ROS) Measurement
ROS measurement was performed according to the protocol of the ROS assay kit (#E004-1-1, Nanjing Jiancheng Bioengineering Institute, Jiangsu, China). After treatment, the cells were placed in 96-well black opaque plates and incubated with 25 M DCFH-DA for 30 min in the dark in a 37 °C incubator. The fluorescence spectrum was recorded at an excitation wavelength of 488 nm and an emission wavelength of 525 nm (SpectraMax M5, Molecular Devices, Silicon Valley, CA, USA).
## 2.9. Adenosine Triphosphatase (ATPase) Activity Assay
The activity of ATPase was determined using corresponding microplate assay kits (#A070-1-1, Nanjing Jiancheng Bioengineering Institute, Jiangsu, China) according to the kits’ protocol. A TECAN microplate reader (TECAN, Sunrise, Mannedorf, Switzerland) was used to record the absorbance.
## 2.10. Transmission Electron Microscopy (TEM)
C2C12 cells were collected after centrifugation. The TEM fixative buffer containing $2\%$ glutaraldehyde, 0.1 M sodium cacodylate, $0.5\%$ polyformaldehyde, 3 mM CaCl2, and 0.1 M sucrose was used to fix the cell sample at 4 °C for 2–4 h. Then, the differentiated C2C12 cells were washed thrice with PBS for 15 min each, dehydrated in series concentration of ethanol and in acetone, and inserted into a mixture buffer of equal volume of acetone and EMBed 812 overnight at 37 °C. Pure EMBed 812 was held at 37 °C overnight. The slides were stained twice with $2\%$ uranium acetate saturated alcohol solution and $2.6\%$ lead citrate and examined at 80 kV by using Tecnai 10 TEM (TECNAI G2 F20 S-TWIN, FEI, Hillsboro, OR, USA). The ultrastructure of the mitochondria was observed using a Hitachi (HT7800) transmission electron microscope.
## 2.11. Quantitative RT-PCR
TRIzol (Invitrogen, Carlsbad, CA, USA) reagent was used to isolate the total RNA. The RNA was fully released after 5 min at room temperature and then added 100 μL of chloroform for RNA extraction. About 160 μL of the upper aqueous phase was aspirated after centrifugation at 12,000 rpm for 15 min at 4 °C. A total of 160 μL of isopropanol was added, and the solution was well-mixed for 10 min at room temperature. After the RNA pellet was washed and dissolved, nanodrop was used to determine the concentration and quality of the RNA sample. The quality RNA was reversed to cDNA according to the instructions (#KR106-02, TIANGEN, Beijing, China) and subjected to PCR reaction. The procedure of PCR was used to determine gene expression levels as previously reported [19]. The calculation formula of 2−△△Ct was used to assess the expression levels of target genes. We used GAPDH as the internal reference in this study. The sequences of primers are summarized in Table 1.
## 2.12. Western Blot Analysis
RIPA buffer ($1\%$ Triton, 20 mM Tris-HCl at pH 7.5, 150 mM NaCl, 1 mM Na3VO4, and 50 mM NaF) with proteases and a phosphatase inhibitors cocktail (Roche Diagnostics, Germany) was used to lyse the sample. A BCA test (Thermo Scientific, Waltham, MA, USA) was used to measure the concentration of protein. Protein samples were loaded in SDS-PAGE, and the gels were transferred to the polyvinylidene difluoride membranes (Millipore Corp., Bedford, MA, USA). The membranes were immersed in a blocking reagent ($5\%$ non-fat milk) for 1 h at room temperature. After washing with TBST, the membranes were incubated with primary antibodies, including rabbit antibody phospho-AKT (P-AKT, S473) (#4060), total AKT (T-AKT) (#ab187783), phospho-p$\frac{44}{42}$ MAPK (P-ERK, T202/Y204) (#4370), total ERK (T-ERK) (#4695), cytochrome c (Cyto-C, #4280), cytochrome c oxidase subunit 4 (COX-4, #4850T), glucose-regulated protein 78 (GRP-78, #3177), C/EBP homologous protein (CHOP, #2895T) purchased from Cell Signaling Technology (Danvers, MA, USA), goat antibody anti CD36 (CD36, #AF2519) purchased from R&D system (Minneapolis, MN, USA), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH, #AB0037) from Abways (Shanghai, China). The membranes were washed thrice after 1 h of incubation with peroxidase-conjugated secondary antibodies from Yeasen (Shanghai, China). Target protein bands were detected by ECL luminescence technique and analyzed using Image J software (V1.8.0, National Institutes of Health, Bethesda, MD, USA) for grayscale values.
## 2.13. Statistical Analysis
Data were presented as mean ± SEM. For multiple comparisons, statistical significance was established using paired Student t test or one-way ANOVA. The level of significance was set to $p \leq 0.05.$ SPSS 19.0 (Chicago, IL, USA) was used for data analysis.
## 3.1. CD36 Is Highly Expressed in Skeletal Muscle under the Condition of HFD and PA Treatment
CD36 is correlated with the progression of metabolic diseases [11]. To investigate the relevance of obesity and CD36 expression, this study processed and reanalyzed publicly available transcriptome sequencing data (GEO ID: GSE81965) from the human skeletal muscle of obese and non-obese controls. Bioinformatics analysis showed that CD36 expression was upregulated in skeletal muscles from obese individuals compared with non-obese controls (Figure 1A), which were also validated in an HFD-induced animal model. The results showed that the expression level of CD36 was increased in the skeletal muscle tissue of HFD-induced mice (Figure 1B). To further test the effect of obesity and its complications on CD36 expression in the skeletal muscle cells, we established a suitable culture condition by differentiating C2C12 cells with a PA-containing medium, which mimics HFD conditions in vitro. The result also showed an increase in CD36 protein expression in PA-stimulated C2C12 myotubes (Figure 1C). Hence, it is hypothesized that CD36 may be associated with metabolic disorders in the skeletal muscle of obese humans and mice as well as in PA-stimulated C2C12 myotubes.
## 3.2. Loss of CD36 Impairs Insulin Signaling in C2C12 Myotubes in the Absence of PA Loading
To investigate the role of CD36 in regulating the metabolic homeostasis of skeletal muscle cells, RNA-seq was performed in C2C12 myotubes with and without CD36 knockdown. Interestingly, the insulin signaling pathway was enriched by KEGG enrichment analysis (Figure 2A). Irs1, Irs2, and Pi3kr1 are key players in insulin signaling [20]. The expression levels of Slc2a4, Irs1, Irs2, and Pi3kr1 were downregulated in CD36-deficient C2C12 myotubes by qRT-PCR analysis (Figure 2B). Phosphorylation of AKT is thought to be a key step in insulin signaling in skeletal muscle [4,5]. The insulin-induced activation of AKT and ERK in CD36-deficient C2C12 myotubes was significantly lower than that of C2C12 myotubes (Figure 2C). Overall, CD36 deletion impairs insulin signaling in skeletal muscle cells in the absence of PA stimulation, suggesting its fundamental role in regulating insulin action.
## 3.3. Loss of CD36 Induces Mitochondrial Dysfunction in C2C12 Myotubes in the Absence of PA Loading
The underlying mechanism of CD36 on insulin signaling needs to be further explored. The overproduction of ROS can cause damage to the mitochondria and other cellular components, resulting in autophagy or apoptosis under high stress levels [21]. ROS content was measured to identify the function of CD36 deletion in ROS production. CD36 deletion significantly increased the ROS levels (Figure 3A), which might have impaired mitochondrial function. Mitochondrial function is expressed as changes in the protein level or the enzymatic activity of key mitochondrial components that promote oxidation, the mRNA levels of mitochondrial markers, and mitochondrial size and shape [22]. Reduced mitochondrial protein expression, a decreased oxygen consumption rate, and impaired ATP synthesis have been observed in people with obesity or IR [15,16]. ATPase is essential for mitochondrial function. Therefore, we investigated the possible role of CD36 deletion on ATPase activity. Results showed that ATPase activity was decreased in CD36-deficient C2C12 myotubes (Figure 3B). The expression levels of Cyto C and COX4 in CD36-deficient C2C12 myotubes were also significantly reduced compared to the controls (Figure 3C). A TEM was used to examine the effect of CD36 deficiency on mitochondrial ultrastructure. Significant damage was detected in the CD36-siRNA group, along with mitochondrial vacuolization, swelling, and mitochondrial crista rupture (shown by blue arrows in Figure 3D).
## 3.4. Loss of CD36 Enhances ER Stress in C2C12 Myotubes in the Absence of PA Loading
IR in skeletal muscle is linked to increased ER stress markers [23]. The expression of ER stress markers was examined to explore the role of CD36 deletion in ER stress. The results of real-time PCR revealed a significant increase in the mRNA levels of ATF6, IRE1α, PERK, CHOP, GRP78, and GRP94 after CD36 deletion in C2C12 myotubes compared to the control group (Figure 4A). The significant effect of CD36 deletion on the expression of proteins related to the ER stress pathway was confirmed by examining the expression of GRP78 and CHOP by western blot analysis. The protein expression of GRP78 and CHOP significantly increased in CD36-deficient C2C12 myotubes (Figure 4B). Therefore, CD36 expression may play a key role in ER stress, which is partly responsible for impaired insulin signaling.
## 3.5. Loss of CD36 Protects against Insulin Resistance in the Presence of PA Overload
It is hypothesized that, in contrast to the absence of PA loading, loss of CD36 protects against insulin resistance in the presence of PA overload due to a reduction in lipid accumulation [24]. Therefore, the effect of CD36 deficiency on lipid accumulation under PA conditions was investigated. siRNA against CD36 was used for transfection to inhibit the CD36 mRNA and protein expression levels, which decreased remarkably (Figure 5A). After silencing CD36, lipid accumulation was alleviated in CD36-deficient C2C12 myotubes under PA stimulation (Figure 5B,C). Excessive intracellular lipid deposition is closely associated with the development of IR in skeletal muscle [15], so we further investigated the effect of CD36 on insulin signaling in the presence of PA overload. Our study showed that insulin-stimulated phosphorylation of AKT and ERK was increased in CD36-deficient myotubes compared to controls in response to PA overload (Figure 5D). In contrast, insulin-stimulated phosphorylation of AKT and ERK was decreased in CD36-overexpressing myotubes with PA overload (Figure 5E). These results suggested that CD36 negatively affects insulin signaling in the presence of PA overload, possibly related to the effects of intracellular lipid accumulation.
## 4. Discussion
The over-deposition of intramuscular triacylglycerol (IMTG) is closely related to muscle IR [25]. Considering the strong association between muscle IR and IMTG, we focused on CD36, which contributed to regulating LCFA uptake and oxidation in a coordinated manner [9]. Therefore, the expression levels of CD36 in the skeletal muscle tissues of obese humans and mice were first identified. Our results showed that the CD36 expression levels were upregulated in the skeletal muscle tissues of obese humans and mice compared to non-obese subjects. PA at concentrations of 0.4–1.0 mM can induce IR models in cultured skeletal muscle cells [26]. Thus, we established an in vitro model of C2C12 myotubes cultured in a PA medium as a way to further confirm the results in vivo. The results showed that CD36 protein was highly expressed in PA-stimulated myotubes. Collectively, these results suggested that CD36 might be associated with metabolic dysregulation in myotubes under the condition of PA overload.
Interestingly, the role of CD36 in regulating insulin signaling is complex [9]. It has been reported that this regulation may depend on the cellular response to different nutritional stresses [10]. Therefore, we explored the differential effects of CD36 deficiency on insulin signaling in C2C12 myotubes in the absence and presence of PA load. In the absence of PA stimulation under basal conditions, insulin-induced AKT phosphorylation expression levels were reduced in CD36-deficient C2C12 myotubes, which was also confirmed by RNA-seq and RT-PCR analysis, suggesting that CD36 deficiency disturbs insulin action and impairs insulin signaling, possibly because the presence of CD36 is essential for maintaining intracellular metabolic homeostasis (Figure 2). Emerging evidence supports our results that skeletal muscle insulin signaling is impaired in CD36-deficient mice [10]. Nevertheless, in our study, the contradictory result was observed in the case of PA overload. The results showed that CD36 deletion protected myotubes from insulin resistance in the presence of PA overload (Figure 5), probably because CD36 deletion reduced the uptake of excess LCFAs and alleviated lipid overaccumulation, thus improving the insulin signaling pathway [14]. This result was also confirmed by other in vivo studies that CD36 deletion protects mice from HFD-induced IR, obesity, and hypoglycemia [27]. The differences in CD36 promotion or prevention of IR may be related to FA-loading status and tissue specificity [28,29]. In addition, based on genetic studies, the effects of partial CD36 defects [30] are different from those of complete CD36 defects [13]. Our results showed that complete CD36 deficiency in the absence of PA load, much like CD36 overexpression in the presence of PA overload, may lead to metabolic complications. Thus, there may be a “metabolic protection” range or threshold effect for CD36 expression. Further studies are necessary to determine the molecular regulation of CD36 expression under different FA loading conditions and its contribution to tissue-specific functions to understand how CD36 affects specific obesity-related phenotypes and complications.
ROS-induced mitochondrial dysfunction and ER stress cause IR [31]. It is critical for cellular function to maintain proper mitochondrial function [18]. Recently, research interest in skeletal muscle mitochondrial function has increased because of the discovery of mitochondrial dysfunction in type 2 diabetes, including decreased muscular ATP synthesis [32,33], reduction in the activity of mitochondrial enzymes and expression of the electron transport chain [34,35], and aberrations in mitochondrial morphology and density [36,37]. Despite the controversy regarding IR, CD36 emerges as a biomarker for patients with type 2 diabetes and related complications. The role of CD36 in the regulation of mitochondrial function in the treatment of IR and type 2 diabetes needs to be determined [38]. However, the contributions of CD36 deficiency to the modulation of mitochondrial function have not been established. Our results demonstrated that CD36 deficiency induces a reduction in ATPase and several markers of mitochondrial genes, such as COX4 and Cyto C, and an aberration in mitochondrial morphology, suggesting impairment of mitochondrial function. A strong structural and functional connection has been observed between the mitochondrial network and ER [39,40]. It is reported that ER stress upregulated in CD36-deficient mice [10], which is consistent with our results that CD36 negatively regulated ER stress. It is hypothesized that in the absence of PA overload, CD36 is necessary for maintaining muscle lipid metabolism and its deficiency disturbs intracellular metabolic homeostasis [37,38], leading to increased ER stress in myotubes. The role of CD36 in regulating skeletal muscle ER stress in vivo needs to be further investigated.
## 5. Conclusions
In summary, the effect of CD36 deficiency on insulin signaling is varied in C2C12 myotubes with or without PA overload. In the absence of PA load, CD36 deletion impairs insulin signaling, possibly by increasing mitochondrial dysfunction and ER stress. This suggests that CD36 is essential for the maintenance of physiological insulin action; however, CD36 deletion improves insulin signaling in the presence of PA overload due to a reduction in lipid accumulation (Figure 6). Although this work yielded a potential relationship between CD36 expression and insulin signaling in C2C12 myotubes, several limitations remain. First, additional key members of the insulin signaling pathway should be tested in the future and supplemented with physiological indicators to reflect the effects of CD36 more fully on insulin signaling activity. In addition, the dynamic impact of CD36 in the progression from IR to diabetes has not been elucidated. Finally, whether CD36 deficiency impairs insulin signaling by increasing mitochondrial dysfunction and ER stress lacks causal validation and requires further experimental proof. Uncovering these vital issues would be instrumental for designing novel CD36-targeted therapies, which would suppress or diminish IR and its harmful effects.
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|
---
title: 'Research on the Process and Influencing Factors of Online Diabetes Information
Users’ Avoidance Behavior: A Qualitative Study'
authors:
- Caiqiang Guo
- Li Si
- Yifan Sun
journal: Behavioral Sciences
year: 2023
pmcid: PMC10045335
doi: 10.3390/bs13030267
license: CC BY 4.0
---
# Research on the Process and Influencing Factors of Online Diabetes Information Users’ Avoidance Behavior: A Qualitative Study
## Abstract
Users’ avoidance behavior of health information has received growing attention recently, but research into users’ avoidance behavior of diabetes information remains limited. This paper aims to reveal the process and the factors of avoiding online diabetes information. The interview, conducted with the critical incident technique, and the diary methods were used to collect 40 true incidents of online diabetes information avoidance from 17 participants. Based on the thematic analysis method and grounded theory, the data were analyzed to identify the key phases of the avoidance process and obtain the factors influencing the occurrence of avoidance behavior. The results showed that the macro-process of online diabetes information avoidance comprised three phases: pre-encountering, encountering, and avoiding after encountering. First, browsing, searching, or social interaction provide the context for encountering; second, the encountering occurrence consists of three steps—noticing the stimuli, reacting to stimuli, and examining the content; and third, to avoid the online diabetes information encountered, users will adopt avoidance strategies, such as avoiding information sources, controlling attention, delaying access, forgetting information, and denying information, which is manifested as general avoidance and strong avoidance, and has positive, negative, or no effect on users. The 14 influencing factors of avoidance behavior obtained were divided into four clusters. User-related factors include demographic characteristics, health-behavior perception, perceived threat, perceived control, and information sufficiency; information-related factors include information quality, information overload, and information dissemination; environment-related factors include context type, behavior place, time pressure, and social factors, and emotion-related factors include the pre-encountering and post-encountering emotional states. These findings can guide the intervention of information avoidance behavior.
## 1. Introduction
According to the 10th edition of the International Diabetes Federation diabetes atlas, diabetes has become one of the fastest-growing global health concerns in the twenty-first century. Currently, 537 million adults worldwide have diabetes, with a prevalence rate of $10.5\%$ [1]. Diabetes complications affect multiple organs and lead to high disability and mortality rates. In 2021, about 6.7 million adults died of diabetes or its complications, accounting for $12.2\%$ of the global death toll [1]. China had about 140 million diabetics in 2021, ranking first in the world. Diabetes prevalence among adults increased from $4.2\%$ in 2002 to $11.2\%$ in 2017 [2,3]. Although the awareness, treatment, and control rate of diabetes improved in recent years, they remained low [2]. It is urgent to improve the ability of people with pre-diabetes to obtain appropriate and timely care, effectively preventing or delaying complications, avoiding premature death, and improving their quality of life. Access to online health information is an essential way for information consumers to improve their quality of life and meet their information needs.
Active access to health information helps individuals understand their health status and medical diagnosis, and maintain their health [4]. However, a large body of research has found that people do not always actively access health information and sometimes deliberately avoid it to maintain or increase their level of uncertainty [5,6]. “ Health information avoidance” is a prevalent issue. According to research on the information behavior of people with life-threatening diseases, such as breast cancer, prostate cancer, AIDS, etc., some individuals avoid learning about their health status [7,8,9]. Although some studies have confirmed that reasonable avoidance of health information can temporarily alleviate negative emotions such as anxiety and fear [10], in the long run, it affects people’s perception of their health status and may lead to missed opportunities to detect diseases early and improve lifestyle habits [11].
Online health information avoidance is the behavior presented by individuals of avoiding or delaying access to available online health information [11]. Some researchers put information avoidance behavior in the context of information seeking [12,13], and less in that of information encountering. The relevant research on the behavior of information encountering only considered the accidental discovery and active acquisition of unexpected information and ignored the instinct of human beings to generate avoidance motivation for external stimuli, thus paying less attention to the avoidance behavior after information encountering [14]. Online health information encountering is useful or interesting health information that users encountered while searching and browsing, which can help users solve past, present, or future health problems related to themselves or others [14]. Moreover, it plays an important role in disease prevention, diagnosis and treatment, can optimize health decisions for users, improve or change health behaviors, and better play the value of health information. Avoiding such information means that individuals would lose out on early detection of diseases and the correction of unhealthy lifestyles, which is not conducive to the flow of information and the realization of information value. Although there has also been research on whether individuals were willing to accept the detection of type 2 diabetes and diabetics’ avoidance behavior of health information [15,16,17], the avoidance of diabetes information received less attention. Therefore, it is necessary to explore users’ avoidance behavior of online diabetes information.
This study puts information avoidance in the context of information encountering, aiming to solve the following questions:
## 2. Literature Review
Health information avoidance research mainly focused on the content and influencing factors of information avoidance, and a few studies have explored the avoidance strategies and results.
## 2.1. Research on Influencing Factors of Health Information Avoidance
Relevant studies mainly focused on the avoidance of disease health information, including cancer [9,10], diabetes [15,16,17], and daily health information, such as skin damage [18] and physical exercise [19]. The respondents included patients [17], college students [15], females [9,20], pregnant women [21], elderly people [22], rural residents [23], and other different groups.
Researchers explored the factors that influenced users’ avoidance behavior of health information in three aspects: user-related factors, information-related factors, and context-related factors. [ 1] User-related factors: female, elderly, low-income, low-education, and low information literacy users tended to avoid health information related to subjects such as cancer, physical exercise, and epidemic [19,24,25]. Another study found that younger users were more likely to avoid information [26]. Negative emotions, such as fear, anxiety, worry, etc., led to users’ avoidance behavior of cancer information [10,22,27]. However, the direction of the relationship between worry and cancer information avoidance was inconsistent in China and the U.S. [28]. Perceived risk promoted users’ avoidance behavior of health information [6,23]. When users believed that the disease was controllable, they would avoid health information less [9]. Compared with people with more coping resources, people with fewer were more likely to avoid information [29]. Cognitive dissonance increased the willingness to avoid information [30], but self-efficacy decreased individuals’ willingness [31,32]. Individual self-affirmation helped reduce the avoidance of risk information, but increased users’ avoidance when information may force people to carry out unwanted behaviors and when information was related to the risk of an untreatable disease [33]. [ 2] Information-related factors: researchers found that information overload aggravated users’ cognitive burden, triggered negative emotions such as anxiety and fatigue, and led to avoidance behavior [13,25,34,35]. Source credibility, information utility and characteristics had an impact on users’ avoidance behavior [21,23,36]. In addition, the expression of health information titles affected users’ avoidance behavior. Compared with loss frame titles, gain frame titles attracted more and longer attention and more clicks [20]. [ 3] Context-related factors: health information avoidance was situational, relatively common, not necessarily unhealthy, and may be used to achieve multiple communication goals [37]. People avoided health information mainly to maintain hope or deniability, resist overexposure, accept limits of action, manage flawed information, maintain boundaries, and continue with life/activities [37]. Social norms, behavior changes, task driving, and society influenced users’ avoidance behavior [12,21,36].
## 2.2. Research on Avoidance Strategies
To achieve the purpose of avoiding information, people often adopted certain avoidance strategies, such as avoiding information sources, controlling attention, delaying access, forgetting information, and denying information. [ 1] Avoiding information sources. In real life, people often avoided unwanted information by avoiding specific information sources, including newspapers, books, websites, social networking platforms, television programs, and other people or institutions that may provide information [38]. [ 2] Controlling attention. Even if people had obtained information from information sources, they were often unable to focus on information. When information conflicted with their cognition and caused discomfort, people avoided the information by diverting or distracting their attention [39]. People may choose to pay attention to positive information and remain indifferent to adverse or threatening information, even though such information may be more useful [40]. [ 3] Delaying access. When people were unable to process information immediately due to cognitive or emotional factors but were aware that it had potential value, they tended to delay accessing it to gain enough time to adjust their cognition or emotional state [41]. Then, they tried to understand the information that had not been obtained after adjusting their state [42]. [ 4] Forgetting information. Even though people obtained the information, they still deliberately and selectively did not recall negative information [40]. [ 5] Denying information. When people tried to forget information and failed, they could have a biased understanding or interpretation of the information, thus rejecting and denying the original meaning of information transmission [37,40].
## 2.3. Research on Avoidance Results
Less attention has been paid to the effect of information avoidance on respondents, and the conclusions vary. Some pointed out that information avoidance brought on negative effects, while others believed that it brought on positive effects. [ 1] Negative effect. The most direct result of information avoidance makes people miss the opportunity to eliminate uncertainty and optimize decision making [11]. Individuals with health risks often avoided medical examinations, which made people miss opportunities for prevention, early detection of diseases, making better decisions, obtaining better treatment, and improving lifestyle habits [43]. [ 2] Positive effect. When people could not or believed they could not change their environment and status quo, information avoidance could help them increase cognitive uncertainty, alleviate cognition disorders and negative emotions such as fear and anxiety [35], or maintain their original state and firm up their existing decisions or plans [37]. Maintaining or increasing uncertainty could make patients optimistic and increase comfort, which is conducive to treatment and enables patients to temporarily live a “happy life” [6,40].
At present, the related researches mainly focus on the factors influencing the occurrence of health information avoidance behavior, devoting less attention to avoidance strategies and results, and there is a lack of research on “how avoidance behavior occurs”. Researchers pay less attention to diabetes information. Information encountering often occurs in the online environment. This paper tries to put avoidance behavior in the context of information encountering, to explore the users’ avoidance behavior of online diabetes information, and reveal the process and influencing factors of avoidance behavior, to comprehensively grasp how and why the users’ avoidance behavior occurs.
## 3.1. Research Method Selection
Because information avoidance was not easy to observe directly, the interview method was mainly used to collect qualitative data in previous studies, and the diary method was rarely used [11]. The diary method is a self-report method of obtaining and recording the subject’s immediate feelings. Compared with the interview, the diary method can help researchers collect dynamic and real-time data from respondents, effectively shorten the time interval of recall, reduce the risk of retrospective bias, and ensure the authenticity of research results [44,45]. The interview method is also advantageous in obtaining details of user behavior and mental activity, and it can be used alone or as a complement to the diary method. Therefore, the interview method, with the critical incident technique, and the diary method were adopted to collect qualitative data on users’ avoidance behavior when they encountered online diabetes information.
## 3.2. Respondents Selection and Recruitment
In the previous research on the avoidance behavior of disease information, researchers mainly focused on patients. Obtaining disease information facilitates not only timely diagnosis, treatment, and daily health care for patients, but also health management and disease prevention for non-patients. The patient’s family members understand the relevant knowledge, which can supervise the patient’s treatment and daily health care to help control the patient’s condition. Therefore, this study investigated diabetic patients, family members of diabetic patients, and general users to obtain a comprehensive understanding of users’ avoidance behavior. The authors recruited respondents on different platforms such as the Post bar of Wuhan University, WeChat moments, Diabetes forum, QQ group of diabetes, etc.
## 3.3. Data Collection
The data were collected from 14 January to 31 March 2022. First, the authors told the participants what “online diabetes information they encountered” was, what “the avoidance of online diabetes information they encountered” was, and several forms of avoidance of online diabetes information. After that, the authors asked them to keep a diary for two weeks, providing them with diary points and diary examples. The diary points included the time, place, scene, emotional state, activities, platform, whether there was a clear demand before information encountering, the way of information encountering, the topic and characteristics of the information encountered, the reaction to the information encountered, the reason for avoidance, the strategy, result, and intensity of avoidance behavior, behavior after avoidance, etc. Participants needed to record the avoidance behavior in a diary when it occurred. A minimum of 150 words were required to be recorded. Participants were informed that a minimum number of diary entries was not required and not related to the final reward. After they completed their diaries, the authors conducted supplementary interviews with them to address what was unclear in the diaries and interviewed them again based on the interview outline which was the same as the diary points to obtain their experience of avoidance behavior. Affected by the COVID-19 epidemic, the interviews were completed through WeChat voice. The authors told participants who only participated in the interview that we would record the interview content for the convenience of subsequent data collation, desensitize them in the subsequent processing, and record them after obtaining consent. The authors adjusted the content of the interview according to the actual situation to collect relevant data on the avoidance behavior of the respondents. The length of each interview was 15–30 minutes.
Seventeen respondents (encoded as P1–P17) participated in the diary and interview data collection methods, including eleven females and six males. Because there were diabetics around or in their families, the respondents were often concerned or willing to learn about diabetes-related information. Among them, there were two diabetic patients, eleven family members of diabetic patients, and four general users, aged between 19 and 32, with college, undergraduate, master, and doctorate education backgrounds. Their majors included library science, information science, information management and information system, management science and engineering, accounting, chemistry, communication engineering, law, clinical medicine, etc.
## 3.4. Data Pre-Processing
Seventeen respondents contributed forty-seven incidents (encoded as I1–I47), forty-two of which come from diaries and five come from interviews. Since most respondents were first exposed to the concepts of “information encountering” and “information avoiding”, the phenomena of “false information encountering” and “false information avoiding” was inevitably included. To ensure the accuracy and effectiveness of this study, the authors screened according to the following criteria: [1] whether the participants encountered online diabetes information under unexpected situations, [2] whether the online diabetes information they encountered was useful or interesting for the participants, [3] whether the participants avoided the information they encountered under unexpected situations, and [4] excluding the records of avoidance made by the participants due to advertising information. Unfortunately, seven of the incidents were detected to be false, as attributable to the following reasons: ① It does not belong to information encountering: I38 and I46. Users discovered online diabetes information during their active search and had expectations. The user (P13) actively searched for “diet and resting to prevent diabetes” on Weibo (I38), and the user (P16) searched for “will low blood glucose turn into high blood glucose” on Baidu (I46). The search content had a high correlation with diabetes, and users had expectations for the search results of the two incidents.
② It belongs to information encountering: I20, I41, I42, I43, and I44. Users (P7 and P15) encountered interesting or useful information in unexpected circumstances and checked the content. These instances belonged to information encountering, but they did not trigger information avoiding.
## 3.5. Data Analysis Method
The qualitative thematic analysis method included identifying, analyzing, and reporting patterns or topics in data [46]. Inductive thematic analysis was based on empirical data and data-driven methods. Grounded theory was employed to find new phenomena that had not been mentioned in existing research [46]. The grounded theory allowed researchers to theoretically explain the general characteristics of the topic through associative patterns, while the explanation was based on the empirical observation of the data through categorical coding.
Therefore, this study used inductive thematic analysis to analyze and extract the topics involved in the process of avoidance behavior. The authors followed the basic analysis steps of thematic analysis, that is, getting familiar with data, generating initial coding, formal coding, and summarizing topics [46]. The authors conducted the thematic analysis as follows: [1] the researchers read all the descriptions carefully and took notes for each meaningful unit; [2] initial codes were created based on these notes; [3] the relationships between the initial codes were analyzed, and similar ones were combined to generate formal codes; [4] formal codes were refined or incorporated to form sub-themes and main themes. The authors used grounded theory to analyze and refine the influencing factors of avoidance behavior and followed the three-level coding process of open coding, spindle coding, and selective coding. The goal of open coding is to extract initial concepts from the original material; the goal of spindle coding is to develop main categories based on open coding by refining and merging the initial categories; and the goal of selective coding is to further develop core categories based on the main categories.
## 4.1. Phase of the Avoidance Behavior Process
The authors analyzed the remaining 40 true incidents based on thematic analysis to identify the key phases of the avoidance behavior process. Table 1 provides three examples of the coding process. Simply speaking, a note was a keyword or phrase captured in original descriptions, an initial code was a higher-level abstraction of the phenomenon reflected in a note, and a formal code unified several similar initial codes. The authors annotated meaningful sentence fragments, marking 387 nodes in total, generating 136 initial codes, such as QQ Zone, Weibo, and WeChat official account. After comparing and combining the initial codes, 93 official codes such as QQ, Weibo, and WeChat were finally formed.
Then, the authors analyzed the relationship between formal codes, classified and merged them according to their similarity in meaning, and formed 43 sub-themes, including social media, search engines, video platforms, etc. Finally, according to the meaning expressed by the sub-themes and the correlation between them, the authors obtained 15 main themes, such as the online environment, pre-encountering emotional state, and foreground activities. The sub-themes were second-level themes. According to the sequence of occurrence, they could be divided into three stages: pre-encountering, encountering, and avoiding after encountering, as shown in Table 2.
The authors found two characteristics of avoidance behavior: dynamic variability of avoidance intensity and avoidance behavior. Dynamic variability of avoidance intensity included from general to strong avoidance, from strong to general avoidance, and avoidance behavior depending on the specific situation. Dynamic variability of avoidance behavior included from avoidance to non-avoidance, from non-avoidance to avoidance, unchanged, and avoidance intensity depending on the specific situation.
## 4.1.1. Pre-Encountering
The participants’ everyday life ($$n = 29$$), study ($$n = 7$$), and work ($$n = 1$$) provided the context for their online diabetes information encountering. Three incidents (e.g., I19, I29, I30) were missing activity scenes. Life-related scenes, such as shopping (e.g., I5, I7), socializing (e.g., I6), searching for health knowledge (e.g., I11, I33), or just killing time (e.g., I1, I3, I4), accounted for the absolute majority of incidents. In contrast, relaxing during doing homework (e.g., I26), reading literature (e.g., I31, I35), writing an opening report (e.g., I36), or solving problems users encountered during the study (e.g., I37) were typical study-related scenes. In work-related scenes, users mainly killed time during breaks (e.g., I15).
The foreground activities before the information encountering mainly included browsing ($$n = 33$$), searching ($$n = 5$$), and social interaction ($$n = 2$$). The term “browsing” was used here in a broad sense. It may be that users opened mobile devices to view the latest information, or used social media ($$n = 24$$), video platforms ($$n = 10$$), search engines ($$n = 3$$), etc. to consume various information. Browsing aimlessly, without specific goals, was especially helpful for information encountering (e.g., I1, I2, I3). In contrast, prior activities were identified in five of these incidents. To solve problems in everyday life and studying (e.g., I11, I33, I35, I36, I37), users searched and then encountered the information, even when the user’s explicit target was covered by an entirely different implicit target. Social interaction was found in everyday life-related scenes such as chatting (e.g., I6) and playing games (e.g., I10). Instant messaging services such as WeChat had promoted the information exchange of network users when establishing or maintaining online social relations.
The users’ emotional state of pre-encountering influenced their reaction and attitude to health information, which could be classified as positive or negative. Positive emotional states were mainly manifested in leisure, happiness, relaxation, etc., while negative emotional states were mainly manifested in sadness, grief, pain, etc. Users were mostly in positive emotional states ($$n = 32$$) and less in negative emotional states ($$n = 7$$) in pre-encountering. It was easier to avoid the online diabetes information encountered in a negative emotional state.
## 4.1.2. Encountering
Users’ avoidance behavior began when they noticed stimulus elements in the information that they encountered, which caused users to deviate from the original exploratory behavior and make cognitive and behavioral responses according to their cognition and needs [47].
The information content of pre-encountering and encountering mainly had two types: ① When users browsed or searched irrelevant content on health, such as WeChat Moments, news, foods, painting, etc., users encountered diabetes information (e.g., I1, I3, I7). ② Users encountered diabetes information when browsing or searching for general health information, such as fat reduction and renal failure (e.g., I11, I35).
Stimulus noticed. The topic and presentation of the online diabetes information encountered attracted users’ attention. The topics of the online diabetes information encountered included diagnosis and examination, treatment, daily health care, complications, social life, prevention, scientific research, etc. The topics of complications and scientific research were more likely to be avoided by users than other topics. Most users felt that the content related to complications was too uncomfortable. Users avoided scientific research due to their poor readability (e.g., I11, I15, I23). Users read or watched text, pictures, videos, and other forms of content.
Reaction to stimulus. After noticing the online diabetes information they encountered, users matched their cognition and needs with their knowledge and the needs of themselves or others and responded behaviorally. Users immediately avoided or further accessed the online diabetes information encountered. [ 1] Users immediately avoided online diabetes information ($$n = 13$$), including avoiding information sources and delaying access. When the online diabetes information encountered caused users discomfort, such as panic, irritability, rejection, etc., users would immediately avoid information sources (e.g., I4, I13, I34). When the user was inconveniently obtaining the online diabetes information encountered due to time or place constraints, he would delay access (e.g., I36, I39). [ 2] Users further accessed the online diabetes information encountered ($$n = 27$$). When the user thought that the online diabetes information he encountered was useful or interesting, he would access the online diabetes information further. Users would examine the specific content when they found the title of the online diabetes information attractive and useful to them or others, guiding patients in their medication and satisfying their knowledge needs (e.g., I8, I12). When users found the information interesting or novel, it would arouse their curiosity and drive them to click on the content to examine it (e.g., I15, I23).
Content examined. Even if users examined the online diabetes information they encountered, it did not mean they would accept and use it. The user’s surroundings, user information access preferences, and content affected the user’s reaction and emotional state after examining the online diabetes information he encountered, which in turn affected subsequent behavior. If the readability of the online diabetes information they encountered was poor, it would reduce users’ interest in reading, resulting in users’ distraction or withdrawal from the current read (e.g., I21). Practicality also had an impact on users’ judgment about the value of the information encountered (e.g., I10). When information caused users cognitive conflict, users would choose to avoid the current information (e.g., I31). After examining the online diabetes information encountered, it gave rise to users’ positive or negative emotional states. Positive emotional states motivated users to use the information further (e.g., I24, I27, I28), while negative emotion tended to lead to avoidance behaviors (e.g., I11, I35).
## 4.1.3. Avoiding after Encountering
After information encountering, users adopted some strategies to avoid the information encountered due to cognitive imbalance or emotional discomfort to reduce the impact of the information encountered on them [11].
Avoidance strategies and their manifestations. Confronted with the online diabetes information encountered, users adopted some strategies, such as avoiding information sources ($$n = 17$$), controlling attention ($$n = 13$$), delaying access ($$n = 5$$), forgetting information ($$n = 7$$), and denying information ($$n = 1$$). It should be noted that the user may adopt multiple avoidance strategies in an incident. For example, the user first avoided information sources and then forgot information (e.g., I45). Even if users adopted the same avoidance strategy, its manifestation could also be different. [ 1] The manifestations of avoiding information sources included directly swiping these away, staying away from information sources ($$n = 10$$), quitting reading information ($$n = 2$$), withdrawing applications ($$n = 3$$), turning off mobile phones ($$n = 1$$), etc. ( e.g., I1, I4, I9). [ 2] The manifestations of controlling attention included quickly browsing the information content by distracting one’s attention ($$n = 8$$) (e.g., I4, I6), examining some content that conformed to the current stage ($$n = 3$$) (e.g., I11), or only being distracted by other content ($$n = 2$$) (e.g., I35), even if other contents were also useful. [ 3] The manifestations of delaying access. Users delay access to information when they encountered it at a time where there was time pressure or inconvenient access to the information. Users found the information useful for themselves and (or) patients, but they had difficulty remembering or implementing it (e.g., I27, I28, I39). They would record, collect, save, share, etc., for subsequent access (e.g., I27, I28). [ 4] The manifestations of forgetting information. A: The information was useful, but it was not useful at the current stage. Users selectively forgot or directly ignored the information encountered (e.g., I10). B: The information was useful, but it caused users discomfort or disturbed users’ current life state. Users chose to forget the information encountered to maintain the current state (e.g., I35). C: The information was useful, but the information content or suggestions was not easy to practice. Users chose to ignore the information (e.g., I15). D: The information was useful, but users felt that the complications of diabetes were not easy to prevent. Users did not want to think of it (e.g., I29). E: The information was useful, but it was different from the user’s actual situation, so the user no longer remembers it (e.g., I40). [ 5] The manifestations of denying information. When the information content or suggestion obtained was inconsistent with the user’s inherent ideas or habits, the user would deny them to maintain his current behavior (e.g., I31).
Avoidance intensity. It included general avoidance and strong avoidance. In most cases, users generally avoided it based on the information and its content (e.g., I33). Compared with daily health care, prevention, and treatment of diabetes, complications and professional academic research were more likely to cause strong avoidance by users (e.g., I35). When users were in group activities, in public places, or depressed, they were more likely to avoid the health information encountered (P15).
The effect of avoidance behavior. Its positive effects were mainly manifested in reducing worry and discomfort, improving the efficiency of information acquisition, and reducing cognitive burden (P2). The negative effect was mainly manifested in reducing the acquisition of health knowledge, which was not conducive to disease prevention (P7). For family members of diabetic patients and general users, who thought that they could not implement the content or suggestions of online diabetes information by themselves, or they were in good health, with low information demand, avoiding the online diabetes information encountered had little or no effect on them (P9).
The emotional state and behavior after avoiding. Avoiding information might maintain or reverse users’ emotional state, strengthen or weaken their initial emotions, showing positive or negative emotional states, which further affects their subsequent behavior. They performed the following behaviors: ① Returning to the initial activity before information encountering ($$n = 12$$); ② Ending all activities ($$n = 7$$); ③ Using the information encountered ($$n = 3$$); ④ Further exploring ($$n = 3$$).
In addition, users’ avoidance behavior had two characteristics, including the dynamic variability of avoidance behavior and avoidance intensity. Vertically, user behavior was dynamic. It changed from avoidance to non-avoidance, and from non-avoidance to avoidance. Once the avoidance preference has been formed, it will not change in a short time. [ 1] From avoidance to non-avoidance, users (P4 and P10) pointed out that they had never learned about information related to diabetes (i.e., blood glucose) in the past and believed that only people with diabetes needed to be concerned about some information, so they had been avoiding it. After they inadvertently learned about their utility, they no longer avoided such information. Therefore, it is feasible and necessary to promote and disseminate diabetes knowledge among general users and family members of diabetic patients. In addition, users decide whether to avoid online diabetes information depending on the stage they are in. [ 2] From non-avoidance to avoidance, this occurred mainly for specific information sources and information content. When users (P12) knew that certain information sources were unreliable or had low information value, they would avoid information on that source. In addition, users’ avoidance behavior varied with their health status, cognitive level, knowledge needs, information content, and the environment when faced with the same topic or content from an information source, depending on the specific situation. The dynamic variability of users’ avoidance behaviors suggests that interventions can be made to improve users’ utilization of information resources and facilitate information flow. However, some users’ avoidance behaviors are unvarying. For topic-specific content or information from a specific information source, users always avoid it. Users’ willingness to avoid has a dynamic change from general avoidance to strong avoidance and from strong avoidance to general avoidance, depending on the context (P15).
## 4.2. Factors Influencing the Occurrence of Avoidance Behavior
Based on the idea of grounded theory, the authors extracted 246 original sentences and corresponding initial concepts from the initial material, generating 86 initial concepts, such as practical, academic, and useful. After comparing and combining the initial concepts, 37 categories were finally formed, such as practicability, readability, and usefulness. Table 3 provides three examples of the coding process. Analyzing and integrating those categories, 15 main categories were formed, such as information quality, information overload, and information dissemination. Finally, according to the meaning of the main categories and their interrelationships, they were summarized into five core categories: information-related factors, user-related factors, environment-related factors, emotion-related factors, and information avoidance behavior, as shown in Table 4.
## 4.2.1. Information-Related Factors
The authors extracted three information-related factors from the data, including information quality ($$n = 10$$), information dissemination ($$n = 9$$), and information overload ($$n = 2$$). When users perceived that the information quality was not high or not as good as expected, they would avoid the online diabetes information encountered. The information was of poor practicality, low usefulness, poor readability, and unreliable content, consistent with the previous research results [26,41].
Information dissemination, including information source reliability, information title description, information topic, and information presentation, was related to the realization of information value. *Users* generally did not directly avoid trusted information sources and information published by certified and authoritative publishers.
Users tended to read novel, professional, clear, and rigorous titles and avoided frightening and lengthy titles.
Whether the information topic and the title could attract users’ attention was directly related to whether the information could be further utilized. From the analysis results, users tended to avoid information about diabetes complications, severe or painful experiences caused by diabetes, and scientific research progress.
Information in graphic form was easier to be noticed for users.
Information overload caused by excessive information feeds and high similarity gave rise to users’ cognitive overload, triggering negative emotions, which led to avoidance. It was consistent with the previous research conclusions [13,25,34].
## 4.2.2. User-Related Factors
The authors extracted five user-related factors from the data, including information sufficiency ($$n = 5$$), health-behavior perception ($$n = 4$$), demographic characteristics ($$n = 3$$), perceived threat ($$n = 2$$), and perceived control ($$n = 1$$). Information sufficiency was determined by the gap between the information that an individual had (i.e., knowledge reserve) and the amount of information required (i.e., information demand). When the gap was small, the user was prone to avoid it.
Health-behavior perception was the user’s subjective judgment of the difficulty and utility of health behavior, which affected the user’s willingness to avoid it. If the content or suggestions of the online diabetes information they encountered were easy to implement and had good utility, users would use the information. If it was effective but difficult to implement, users would choose to forget the information.
Demographic characteristics affected the users’ perception of health information when they encountered online diabetes information. When the user was in poor health, the user’s needs would increase, which reduced the possibility of avoidance. In addition, personal or family history of disease influenced users’ judgment of online diabetes information.
Perceived threat, including perceived severity and perceived susceptibility, influenced users’ attitudes toward online diabetes information. When the user perceived diabetes susceptibility, the user was more willing to obtain daily health care and prevention information and reduced the possibility of direct avoidance (P6). When users perceived diabetes to be severe, being confronted with the online diabetes information encountered, especially diabetes complications or other serious consequences, increased users’ worry and fear, which promoted the occurrence of avoidance behavior (P2).
Perceived control refers to the user’s perceived control over the information and the consequences of his actions. When the patient perceived that his condition was stable, he was more confident, which would reduce the likelihood of avoiding information about diabetes (P5).
## 4.2.3. Environment-Related Factors
The authors extracted four environment-related factors from the data, including context type ($$n = 16$$), behavior place ($$n = 2$$), time pressure ($$n = 7$$), and social factors ($$n = 1$$).
Context type mainly refers to foreground activities, including browsing, searching, social interaction, studying, working, and everyday life. Compared with browsing, the user was more likely to avoid the online diabetes information encountered while searching and during a social interaction. Users tended to directly seek the target content in the search scene, which reduced the possibility of obtaining the online diabetes information encountered and increased the user’s willingness to avoid it. The online diabetes information encountered by the user interrupted his mental state in the social interaction scenario and thus led to avoidance.
However, most users browsed aimlessly or randomly. When the online diabetes information encountered was useful or interesting, users would further obtain it. With plenty of time in the everyday life scene, users did not directly avoid the online diabetes information encountered, but it was easy to occur in the study and work scene.
Behavior place. When users were in public places, their behavior was restricted by their surroundings, thus reducing the probability of obtaining information about online diabetes they encountered and increasing their willingness to avoid it.
Time pressure refers to the lack of free time when users encounter online diabetes information, which refers not only to the feeling of not having enough time but also to the emotional experience of being rushed and overwhelmed [47]. When users are busy or in situations of time constraints, they avoid the online diabetes information they encounter.
Social factors in this paper referred mainly to subjective norms, that is, the pressure from others or society that users felt while deciding whether or not to examine the online diabetes information they encountered. The impact of subjective norms on avoidance behavior was more pronounced in patients.
## 4.2.4. Emotion-Related Factors
The authors extracted two emotion-related factors from the data, including the emotional state of pre-encountering and post-encountering. Positive emotional states promoted user approach behavior, and negative emotional states led to users’ avoidance behavior.
Based on the results of the above analysis, a model of online diabetes information avoidance behavior in the context of information encountering was obtained, as shown in Figure 1. It should be noted that not all incidents contain every element in the process of avoidance behavior.
## 5.1. Implications of the Phase in the Process
This study puts the avoidance behavior in the context of information encountering, which was complementary to previous information avoidance-related researches and contributed to the understanding of the information avoidance process.
## 5.1.1. Effective Information Stimuli Help Reduce Information Avoidance
Avoidance behavior begins with the user’s attention to the information encountered. In terms of avoidance strategies, avoiding information sources was adopted most. This showed how attracting users’ attention during information dissemination, and thus facilitating their click behavior, was the first step in helping to realize the value of information. From the results of the analysis, the information that helped control and prevent diabetes could guide the user’s practice, could attract their attention, and trigger further examination. In the future, researchers can explore which topics, presentations, and information-organization methods are more conducive to attracting users’ attention and clicking, guiding better information flow and information value.
## 5.1.2. Avoidance Behavior Can Be Intervened
Users’ avoidance behavior from avoidance to non-avoidance suggested that appropriate publicity and guidance would help users reduce avoidance of useful online diabetes information, facilitate the flow of online diabetes information, achieve the value of the information, and help change users’ unhealthy behaviors and improve their health. Users’ avoidance behavior from non-avoidance to avoidance meant that after successfully attracting users at the beginning, how to maintain user stability, reduce user churn, and enhance user stickiness should be considered.
In terms of avoidance intensity, many users showed a strong avoidance intention of topics such as diabetes complications, patients’ painful experiences, and scientific research, while users showed a general avoidance intention of most other topics. Since diabetes can lead to various complications, diabetic patients and family members of diabetic patients need to learn about diabetes complications, such as preventive measures for complications. During the dissemination of diabetes complications, more attention should be paid to the prevention of various complications. To attract users’ attention, a small amount of information about the serious consequences of complications can also be added. The intensity of user avoidance was dynamic, especially the change from general avoidance to strong avoidance, which indicated that when propagating diabetes-related information to users, it is necessary to ensure the quality of information and the credibility of the information source to reduce the loss of users.
## 5.2. Implications of the Influencing Factors
This study identified 14 factors that influenced the occurrence of avoidance behavior. They were further recognized as user-related, information-related, environment-related, and emotion-related factors. Targeted countermeasures can be conducted from user-related, information-related, and environment-related factors to reduce the occurrence of avoidance behavior.
## 5.2.1. User-Related Factors
Demographic characteristics, including health status, personal/family disease history, and habits, were stable factors and difficult to change, and it was difficult to intervene in users’ avoidance behavior through them. On the other hand, health-behavior perception, perceived threat, perceived control, and information sufficiency was dynamic, and users’ avoidance behavior could be intervened through them.
[1] Health-behavior perception. When deciding whether to implement the content or suggestions of the online diabetes information encountered, general users, diabetic patients, and family members of diabetic patients would first consider barriers (i.e., perceived barriers) and benefits (i.e., perceived benefits). Online diabetes information will only be accepted and used by them if it is within an acceptable range of difficulty of implementation and utility.
[2] Perceived threat. Currently, the awareness rate of diabetes is still low. Many people thought that if there were no diabetic patients in their families, the possibility of suffering from diabetes was low, paying no attention to the prevention of diabetes in their daily life. It is necessary to increase the awareness of diabetes-related knowledge, enhance users’ awareness of the susceptibility and severity of diabetes, and help them form healthy living habits.
[3] Perceived control. Through interviews with patients and their families, we learned that elderly patients have a good mentality, pay attention to daily health care, and have good condition control. The newly diagnosed younger patients had large emotional fluctuations when facing diabetes (P15) and were prone to give rise to negative emotions when facing such information. Cases or stories can be used to explain to them that diabetes is manageable and to increase their confidence in coping with the disease.
[4] Information sufficiency. It was affected by information demand and knowledge reserve and was determined by the gap between the user’s knowledge reserve and information demand. When user information demand is greater than the current knowledge reserved, users tend to acquire knowledge. On the one hand, it is necessary to clarify which diabetes information users are interested in according to their usage habits. On the other hand, it is necessary to include new information in the recommendation process to increase their reading possibilities.
## 5.2.2. Information-Related Factors
It includes information dissemination, information quality, and information overload.
[1] Information dissemination, including information source credibility, title description, information topic, and information presentation. From the results of the analysis, in addition to complications, severe or painful experiences caused by diabetes, and scientific research, other topics of online diabetes information were of high concern to the general users, diabetic patients, and family members of diabetic patients. In terms of complications, the information on how to prevent complications is more acceptable to users than the consequences caused by complications. In terms of scientific research, some users pay attention to the research that can be implemented. Diabetes-related severe or painful experiences might alert individuals to the seriousness of the disease and draw their attention. Therefore, it is necessary to consider a more acceptable way to present this information to users.
Title description. Users were more interested in viewing rigorous, professional, and focused titles. How titles are expressed can attract users’ attention and stimulate reading interest needs further verification. Existing research found that message framing and evidence types influenced users’ health information adoption and behavior change. In the future, we can explore whether message framing and evidence types can play a role in attracting users’ attention and reading online diabetes information, and compare whether there are differences between them.
Information sources’ credibility includes trusted information release channels and trusted information publishers. Most users preferred to read the content posted by experts, such as doctors and professors, on official platforms, such as hospital online platforms, WeChat official accounts, authentication Weibo, TikTok, etc., while a few users were more concerned with patients’ personal experiences and daily health care. Information distribution platforms can increase information filtering, ensure the authority of information publishers and published content, and enhance users’ trust in information sources, thus reducing direct avoidance caused by information sources and promoting information flow.
[2] Information quality. For different users, it is necessary to explore which information presentation method can achieve better communication effects. High-quality information with high readability, usefulness, and practicality will stimulate users’ interest in reading and increase the possibility of information being used; Low-quality information with poor readability, uselessness, and low practicability will directly lead to user avoidance. High information quality is the key to ensuring continuous information flow and access to information. Therefore, it is necessary to ensure information quality.
[3] Information overload, including high pushing frequency, large pushing quantity, and high similarity, are important factors that cause users to avoid it. The appearance of a large number of similar information will arouse users’ visual fatigue. To ensure better information dissemination, the platform should appropriately control the amount of information dissemination to reduce the cognitive burden of users.
## 5.3. Environment-Related Factors
In the browsing context, users are more likely to encounter online diabetes information and view it when browsing aimlessly. In the process of intelligent recommendation, a focus on the information push in the browsing context is recommended.
## 6. Conclusions and Future Research
This study focused on users’ avoidance behavior of online diabetes information under the background of information encountering. Diary and interview methods were used to collect data on the avoidance behavior of diabetic patients, family members of diabetic patients, and general users. Based on the thematic analysis method and grounded theory, the authors analyzed the process of users’ avoidance behavior and its influencing factors. The results show that the process of users’ avoidance behavior includes three phases: pre-encountering, encountering, and avoiding after encountering. First, browsing, searching, or social interaction provides the context for encountering. Second, the encountering occurrence consists of three steps–noticing the stimuli, reacting to stimuli, and examining the content. And third, to avoid the online diabetes information users encountered, users will adopt avoidance strategies, such as avoiding information sources, controlling attention, delaying access, forgetting information, and denying information, which is manifested as general avoidance and strong avoidance. It has positive, negative, or no effect on users. After avoiding, users will take actions such as returning to the pre-encountering activities, ending the current activities and further exploring and using the information encountered. Avoidance behavior and avoidance intensity are dynamic. Avoidance behavior is affected by user-related factors, information-related factors, environment-related factors, and emotion-related factors.
The limitation of this study is that it only reveals the process and influencing factors of avoidance behavior of online diabetes information from a qualitative perspective and does not further verify the mechanism of the process and influencing factors of avoidance behavior. The data obtained from the interview comes from the user’s memory, which is less complete than the diary, leading to an incomplete process of avoidance behavior based on interview data. In the future, we need to conduct in-depth research on the avoidance behavior of health information from the perspective of research content and research methods and conduct an in-depth analysis of different phases of avoidance behavior from the aspect of the content. For example, in the pre-encountering phase, we can explore the contributing factors of health information encountering. In the encountering phase, we can analyze how users’ cognition evolves and what characteristics of health information will lead to users’ approach or avoidance. In the avoiding after encountering phase, we can explore how factors act on users’ avoidance behavior and the mechanism of emotional factors on users’ avoidance behavior, and weigh the influence of individual beliefs on the selection and interpretation of health information. In terms of research methods, qualitative data can be collected by combining observation methods, and objective data on users’ avoidance behavior can be obtained by eye-tracking experiments. In addition, data analysis can be combined with qualitative comparative analysis and simulation analysis to systematically reveal the complex relationship between the influencing factors of avoidance behavior and enhance the reliability of the conclusion.
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|
---
title: The Sympathetic Nervous System Regulates Sodium Glucose Co-Transporter 1 Expression
in the Kidney
authors:
- Jennifer Matthews
- Moira Hibbs
- Lakshini Herat
- Markus Schlaich
- Vance Matthews
journal: Biomedicines
year: 2023
pmcid: PMC10045340
doi: 10.3390/biomedicines11030819
license: CC BY 4.0
---
# The Sympathetic Nervous System Regulates Sodium Glucose Co-Transporter 1 Expression in the Kidney
## Abstract
Hyperactivation of the sympathetic nervous system (SNS) has been demonstrated in various conditions including obesity, hypertension and type 2 diabetes. Elevated levels of the major neurotransmitter of the SNS, norepinephrine (NE), is a cardinal feature of these conditions. Increased levels of the sodium glucose cotransporter 1 (SGLT1) protein have been shown to occur in the parotid and submandibular glands of hypertensive rodents compared to normotensive controls. However, there was a need to examine SGLT1 expression in other tissues, such as the kidneys. Whether NE may directly affect SGLT1 protein expression has not yet been investigated, although such a link has been shown for sodium glucose cotransporter 2 (SGLT2). Hence, we aimed to determine (i) whether our murine model of neurogenic hypertension displays elevated renal SGLT1 expression and (ii) whether NE may directly promote elevations of SGLT1 in human proximal tubule (HK2) cells. We did indeed demonstrate that in vivo, in our mouse model of neurogenic hypertension, hyperactivation of the SNS promotes SGLT1 expression in the kidneys. In subsequent in vitro experiments in HK2 cells, we found that NE increased SGLT1 protein expression and translocation as assessed by both specific immunohistochemistry and/or a specific SGLT1 ELISA. Additionally, NE promoted a significant elevation in interleukin-6 (IL-6) levels which resulted in the promotion of SGLT1 expression and proliferation in HK2 cells. Our findings suggest that the SNS upregulates SGLT1 protein expression levels with potential adverse consequences for cardiometabolic control. SGLT1 inhibition may therefore provide a useful therapeutic target in conditions characterized by increased SNS activity, such as chronic kidney disease.
## 1. Introduction
The sympathetic nervous system (SNS) is responsible for the ‘fight or flight’ response. Upon its activation, blood flow from the skin and the gastrointestinal tract is redirected to the brain, heart and lungs [1]. At rest, the SNS, composed of preganglionic neurons originating from the spinal cord, maintains homeostatic blood pressure, body temperature and blood glucose levels through a hormonal cascade. These preganglionic neurons secrete acetylcholine to activate the sympathetic postganglionic neurons or specialised cells in the adrenal gland. Once activated, the major neurotransmitters of the SNS, norepinephrine (NE) or epinephrine, are secreted to target specific organs or tissues, which express either alpha or beta-adrenergic receptors [2]. This enables the effective binding of the catecholamines to the specific organ or tissue sites. Overactivity of the SNS has been associated with adverse metabolic consequences in various common conditions such as obesity, hypertension and diabetes mellitus [3,4,5].
Recent studies have demonstrated the critical role of Sodium Glucose Co-transporters (SGLT’s) in metabolic, cardiac and renal disease [6]. The exact mechanisms underlying the benefits of Sodium Glucose Co-transporter 2 inhibitors (SGLT2i) in providing cardiovascular and renal protection remain to be fully elucidated [7]. We have previously shown a link between Sodium Glucose Co-transporter 2 (SGLT2) expression and its modulation by the SNS [3,4]. The potential interaction between Sodium Glucose Co-transporter 1 (SGLT1) and SNS has not yet been explored.
Although the function of SGLT1 is identical to that of SGLT2, it is more widely expressed throughout the body including the small intestine, eye, kidney, liver, pancreas and heart [6].
Currently, there is limited information on the regulation of SGLT1, particularly in the context of a potential interplay with the SNS. We, therefore, aimed to determine whether the SNS regulates SGLT1 expression. This was achieved by (i) measuring SGLT1 expression in the kidneys of our neurogenically hypertensive mice and (ii) treating human proximal tubule (HK2) cells with NE and subsequently assessing SGLT1 expression and associated mechanisms. We hypothesised that SNS activation may upregulate SGLT1 expression. This study may ultimately highlight that SGLT1 inhibition may be beneficial to treat diseases associated with SNS activation such as chronic kidney disease.
## 2.1. Animals
Renal tissue was collected from 15-week-old male and female blood pressure normal (BPN/3J) mice or blood pressure high (BPH/2J, also known as Schlager) mice [3,8]. Our BPH/2J Schlager mice with neurogenic hypertension [9,10] are a highly relevant mouse model since they mimic human disease with increased sympathetic activity [9], elevated heart rate and heightened blood pressure [8,11] driven by neurogenic mechanisms [12]. All dissections were carried out at the Royal Perth Hospital (RPH) animal holding facility in accordance with the guidelines of the RPH Animal Ethics Committee (R$\frac{537}{17}$-20, approval date 17 August 2017). Kidney tissue was fixed in paraformaldehyde and subsequently embedded in paraffin wax as reported by Herat et al. [ 3].
## 2.2. Immunohistochemistry of Tyrosine Hydroxylase (TH) in Renal Tissue
We performed immunohistochemistry in the kidneys of our normotensive BPN/3J mice and hypertensive BPH/2J mice. Kidney tissues from both our BPN/3J and BPH/2J mice were sectioned at 5 μm onto positively charged microscope slides and de-waxed in xylene and rehydrated in ethanol. Antigen retrieval was performed on the slides by heating in EDTA buffer (pH 8.5; Sigma-Aldrich, Sydney, NSW, Australia). Slides were treated with $3\%$ hydrogen peroxide and then blocked in $5\%$ FCS in PBS/$0.1\%$ Tween-20. Tyrosine hydroxylase was detected with rabbit anti-tyrosine hydroxylase antibody (AB152; Merck Millipore, Melbourne, VIC, Australia). Antibody binding was detected with anti-rabbit (1:100, Santa Cruz Biotechnology, Sydney, NSW, Australia) secondary antibodies conjugated to HRP, followed by treatment with diaminobenzidine (DAB, Ventana, AZ, USA). Tissues were counterstained with haematoxylin before being dehydrated in ethanol and cleared in xylene and mounted with DPX (Sigma-Aldrich, Sydney, NSW, Australia). Photomicrographs were taken of stained kidneys from mice using a Nikon Eclipse Ti Microscope (Nikon Instruments Inc, Tokyo, Japan). Tyrosine hydroxylase positive nerves were counted in random fields of view.
## 2.3. SGLT1 Immunohistochemistry of Renal Tissues
We performed immunohistochemistry in the kidneys of normotensive BPN/3J and hypertensive BPH/2J mice. Briefly, kidney tissue was fixed in $10\%$ buffered formalin for 24 h, followed by wax embedding. Paraffin sections (5 μm) were collected and mounted on slides. For antigen retrieval, slides were heated for 2.5 min in a pre-heated 1× EDTA buffer (pH 8.5; Sigma-Aldrich, Sydney, NSW, Australia). After washing twice in PBS/$0.1\%$ Tween for 5 min, tissue sections were outlined with a paraffin pen. Sections were blocked with $3\%$ H2O2 for 10 min, washed twice with PBS/$0.1\%$ Tween for 5 min and blocked with $5\%$ FCS in PBS/$0.1\%$ Tween for 1 h in a humidified chamber. Sections were then incubated overnight at 4 °C in a humidified chamber with both rabbit anti-SGLT1 antibody (1:180; Abcam, Sydney, NSW, Australia) and rabbit anti-SGLT1 antibody (1:100; Novus, Sydney, NSW, Australia) in $5\%$ FCS/PBS/$0.1\%$ Tween. Following overnight incubation, sections were washed three times with PBS/$0.1\%$ Tween for 5 min and incubated with anti-rabbit (1:100, Santa Cruz Biotechnology, Sydney, NSW, Australia) secondary antibodies conjugated with HRP in PBS/$0.1\%$ Tween for 1 h. This was followed by incubation with diaminobenzidine (DAB, Ventana, AZ, USA). Slides were counterstained with hematoxylin, dehydrated, and mounted with DPX (Sigma-Aldrich, Sydney, NSW, Australia). Photomicrographs were taken of stained kidneys from mice using a Nikon Eclipse Ti Microscope (Nikon Instruments Inc, Tokyo, Japan). The intensity of proximal tubule staining in each field of view was rated against a scale of 0–3 (0 = no staining; 1 = low staining; 2 = intermediate staining; 3 = high intensity of staining).
## 2.4. Human Kidney 2 Cell Culture
The human renal proximal tubule cell line, HK2, was generously provided by Dr Melinda Coughlan and Prof Karin Jandeleit-Dahm (Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia). Cells were cultured in high-glucose Dulbecco’s Modified Eagle Medium (HG-DMEM) supplemented with L-glutamine ($1\%$), streptomycin/penicillin ($2\%$) and fetal calf serum (FCS) ($10\%$) (Thermo Fisher, Melbourne, VIC, Australia).
Unless stated otherwise, cells were trypsinized, plated in Corning Cell Bind 6 well plates (Corning, Glendale, AZ, USA) and allowed to grow to $70\%$ confluency before being treated with NE (Sigma-Aldrich, Sydney, NSW, Australia). Norepinephrine was diluted in Baxter water and added to the wells in accordance with previous studies [4]. Control wells were treated with Baxter water. Norepinephrine was protected from light during its preparation and experiments.
## 2.5. Immunocytochemistry
SGLT1 was detected in HK2 cells using the immunocytochemistry technique. Using a 6 well plate, the cells were fixed in methanol/acetone (1:1) and then endogenous peroxidases were blocked with $3\%$ H2O2 followed by blocking with $10\%$ FCS/Tx/PBS. The primary antibody (1:500, Rabbit anti-SGLT1 antibody, Novus, Centennial, CO, USA.) diluted in Triton X/PBS was added to each well and incubated at 4 °C overnight. The following day a secondary conjugated antibody (1:100 goat anti-Rabbit IgG Peroxidase, Thermofisher, Melbourne, VIC, Australia) was added to each well and then stained with DAB prior to visualisation with a high-powered microscope.
## 2.6. Sodium Glucose Co-Transporter-1 Translocation in HK2 Cells Treated with NE or Hyper Interleukin 6 (H-IL-6)
HK2 cells were seeded into six-well Cell Bind plates and treated with NE (10 μΜ) for 48 h. Cells were permeablized and separated into cytoplasmic, cytoskeletal and membrane protein fractions using the Subcellular Protein Fractionation Kit for Cultured Cells (Cat#: 78840, Thermo Fisher Scientific, Carlsbad, CA, USA). Extracts were analysed using human SGLT1 ELISA (Cloud-Clone, Wuhan, China). Alternatively, HK2 cells were treated with Hyper IL-6 (10 ng/mL–1000 ng/mL; a kind gift from Prof. Stefan Rose-John, University of Kiel, Germany) acutely (15 min) or chronically (24 h).
## 2.7. Interleukin-6 (IL-6) and Tumor Necrosis Factor Alpha (TNF-α) Secretion in Human Kidney 2 Cells Treated with NE
Cells were seeded into six-well Cell Bind plates and treated with NE. The media from each well was sampled at 24 h. Samples were centrifuged at 2100 rpm for 10 min and the cell-free culture media supernatants were stored at −80 °C until analysis was conducted using a Quantikine human IL-6 ELISA kit (Cat#: D6050, R&D System, Minneapolis, MN, USA) or human TNF-α ELISA kit (Elisakit.com, Product 0005, Melbourne, VIC, Australia).
## 2.8. Western Blotting
Phosphorylated STAT-3 was detected using anti-phospho STAT-3 antibody (Tyr-705; Cat#: 9131, Cell Signaling Technology, Danvers, MA, USA) followed by goat anti-rabbit 800 antibody (Cat#: 926-32211, LiCor, Lincoln, NE, USA). Beta-actin was detected using mouse anti-beta-actin antibody (Cat#: ab6276, Abcam, Sydney, NSW, Australia) followed by anti-mouse 680 antibody (Cat#: 926-68020, LiCor, Lincoln, NE, USA). Cyclin Dependent Kinase 4 (CDK4) was detected using mouse anti-CDK4 antibody (Cat#: AHZ0202, Invitrogen, Sydney, NSW, Australia) followed by anti-mouse 680 antibody (Cat#: 926-68020, LiCor, Lincoln, NE, USA). Imaging was performed using the Odyssey detection apparatus (Licor, Lincoln, NE, USA).
## 2.9. Enzyme-Linked Immunosorbent Assays
Frozen Kidneys were homogenized and analysed for NE content using the mouse norepinephrine NE ELISA kit (CSB-E07870m; Cusabio, Wuhan, China) according to the manufacturer’s instructions.
## 2.10. Statistical Analysis
All quantitative data is presented as mean ± SEM. A significance level of p value less than 0.05 was considered significant. Significance was determined for all data using Students t-tests. Graphs were generated using GraphPad Prism 9 (GraphPad Software, San Diego, CA, USA).
## 3.1. Tyrosine Hydroxylase (TH) Is Increased in the Kidneys of BPH/2J Neurogenically Hypertensive Mice in Comparison to BPN/3J Normotensive Mice
In our current study, we used a neurogenic hypertensive mouse model, known as the Schlager (BPH/2J) mouse which has a heightened sympathetic tone. In order to elucidate that the hypertensive model has sympathetic hyperactivity compared to the normotensive BPN/3J model, we investigated the renal TH protein levels in both strains and found that there is a significant increase in TH positive punctate staining in the neurogenically hypertensive BPH/2J mice (Figure 1).
## 3.2. Norepinephrine Levels Are Significantly Elevated in the Kidneys of BPH/2J Neurogenically Hypertensive Mice in Comparison to BPN/3J Normotensive Mice
We have shown that the marker of sympathetic hyperactivity, norepinephrine, is significantly elevated in the BPH/2J mice when compared to our BPN/3J normotensive mice (Figure 2).
## 3.3. SGLT1 Protein Levels Are Increased in BPH/2J Neurogenically Hypertensive Mice in Comparison to BPN/3J Normotensive Mice
The protein SGLT1 is currently studied as a therapeutic target for the treatment of diabetes [13]. We observed that neurogenically hypertensive BPH/2J mice displayed significantly upregulated SGLT1 protein expression in the kidney compared to the normotensive BPN/3J mice (Figure 3).
## 3.4. Norepinephrine Promotes Increased Expression and Translocation of SGLT1
Norepinephrine (NE) is the major neurotransmitter of the SNS. Using our previously optimised concentration of NE in HK2 cells, we have previously demonstrated that NE increased SGLT2 expression [4]. In our current study, we demonstrated for the first time that NE reproducibly resulted in increased SGLT1 expression in HK2 cells (Figure 4A). We then wanted to determine whether NE induced SGLT1 protein translocates to the cell membrane where it may be functional. Using subcellular fractionation to isolate the membrane fraction, we indeed observed that NE promoted SGLT1 to translocate to the cell membrane (Figure 4B).
To further supplement the above findings in Figure 4, we also conducted SGLT1 immunocytochemistry. In support of the quantitative SGLT1 ELISA data, we demonstrated that NE consistently elevates SGLT1 protein which is evident in the cytoplasm of the HK2 cells (Figure 5).
## 3.5. Norepinephrine Treatment Increases IL-6 Secretion from HK2 Cells
As NE increased SGLT1, we then wanted to ascertain upstream mediators. It is known that TNF-α and IL-6 may regulate SGLT1 (either in concert with other cytokines or individually; [14,15]). Therefore, we determined the secreted levels of TNF-α and IL-6 in our in vitro experiments. Interestingly, TNF-α secretion was not different between vehicle and NE treated cells. However, NE profoundly upregulated IL-6 release (Figure 6). Therefore, we wanted to further understand whether IL-6 may directly promote upregulation of SGLT1.
## 3.6. Hyper IL-6 Is Bioactive in HK2 Cells and Promotes Increased SGLT1 Expression
As conditions involving hyperactivation of the SNS such as type 2 diabetes (T2D) and hypertension display increased levels of IL-6 and its soluble IL-6 receptor (sIL-6R) [14,16,17], we utilised the IL-6 and sIL-R fusion protein, hyper IL-6. All cells express GP130 which is necessary for IL-6/sIL-6R signalling. Concentrations of 100 ng/mL and above were bioactive in HK2 cells as evidenced by increased STAT-3 phosphorylation (Figure 7).
We were able to also demonstrate that Hyper IL-6 elevates SGLT1 expression in HK2 cells (Figure 8).
## 3.7. Hyper IL-6 Promotes Proliferation of HK2 Cells and Increases Cyclin Dependent Kinase 4 (CDK4) Levels
In addition to Hyper IL-6 upregulating SGLT1, we consistently observed that the IL-6/sIL-6R fusion protein promoted proliferation of HK2 cells (Figure 9). This is a highly novel finding.
As further evidence that hyper IL-6 promotes proliferation of HK-2 cells, we looked at expression of the 34 kD protein CDK4. We found that hyper IL-6 significantly upregulated CDK4 protein levels (Figure 10). This result, together with the proliferation data (Figure 9) provides strong evidence that hyper IL-6 may promote proliferation of proximal tubule cells during chronic kidney disease.
## 4. Discussion
Hypertension and DM are chronic conditions that cumulatively affect more than two billion people globally every year [18,19]. Blood glucose levels and blood pressure are regulated by the SNS via the regulation of liver, pancreas and kidney function and peripheral vasculature tone [20]. The high incidence, mortality rates and conditions associated with hypertension and diabetes have highlighted that further research regarding the management and treatment of these diseases is urgently required.
The interplay between obesity and hypertension is evident since obesity dysregulates the SNS via various pathways including an increase in renal SNS activity [19]. This in turn affects the renin-angiotensin-aldosterone system and overall increases sodium retention and promotes hypertension [21]. Furthermore, there is a correlation between diabetes and hypertension since it has been established that more than $50\%$ of people with diabetes are also hypertensive [22].
Various approaches are available to treat neurogenic hypertension. Moxonidine is a centrally acting selective imidazoline receptor agonist (SIRA) that reduces peripheral sympathetic activity and, therefore, decreases peripheral vascular resistance [23]. Surgically, renal denervation utilises radiofrequency ablation to ablate renal nerves [24], leading to a suppression of SNS activity and thereby decreasing blood pressure and renal glucose reabsorption [24]. The decrease in renal glucose reabsorption may be due to the fact that we and others have shown that (i) the major neurotransmitter of the SNS, NE, is critical for promoting expression of SGLT’s which is relevant for glucose reabsorption. Of the two main family members, Sodium Glucose Co-transporter 2 (SGLT2) has been widely studied for decades and has been found to be regulated by the SNS [6], whereas Sodium Glucose Co-transporter 1 (SGLT1) is less well investigated. Rafiq et al. [ 2015] demonstrated that NE, which is the major neurotransmitter of the SNS, may increase Sglt2 mRNA [25]. However, SGLT2 protein was not assessed. Our group [4] displayed for the first time that SGLT2 protein expression can be positively regulated by the SNS in human proximal tubule (HK2) cells [4]. In these experiments, HK2 cells were treated with various concentrations of NE to mimic the activation of the SNS. The findings demonstrated a dose-response regarding NE treatment and SGLT2 expression. With these findings in mind, our current study aimed to determine whether the activity of the SNS also influenced SGLT1 expression. This hypothesis is further supported by our current in vivo findings which suggest that a hyperactive SNS may also be associated with increased SGLT1 protein expression.
In our current study, we show for the first time in our BPN/3J and BPH/2J mice, that the neurogenically hypertensive BPH/2J mice have significantly increased TH and NE levels in the kidney, and this promoted renal SGLT1 expression. Together, the elevated NE and TH levels in the BPH/2J mice support the notion that this strain displays SNS hyperactivation compared to the BPN/3J strain. The increased TH and NE levels in the BPH/2J mice correlate with our previously published blood pressure results where we highlight that BPH/2J mice display neurogenic hypertension [3]. The increased renal SGLT1 expression in the BPH/2J mice highlights that SGLT1 may be a therapeutic target. Furthermore, previous studies utilising the spontaneous hypertensive rats (SHR) and the Wistar Kyoto rats (WKY) showed that the sympathetic nerve activity and SGLT1 levels are elevated in the salivary glands of the hypertensive rodents [26]. In our study, we performed immunohistochemistry in the kidneys of the normotensive BPN/3J mice and neurogenically hypertensive BPH/2J mice and found that SGLT1 was specifically elevated in the BPH/2J kidneys (Figure 3). We then followed this result up with novel in vitro studies which aimed to determine if increased SNS activity may directly affect SGLT1 protein levels.
Norepinephrine is one of the primary markers of SNS activation. We investigated whether NE increased SGLT1 expression in the HK2 cells which has already been shown to express SGLT1 [27]. In our current study, we highlight a statistically significant increase in SGLT1 protein expression after NE treatment when using both specific immunohistochemistry and a specific SGLT1 ELISA (Figure 4 and Figure 5). This provides strong evidence that the SNS positively regulates the SGLT1 protein which may be pathogenic if increased too greatly as it may promote hypertension and glucose reabsorption.
Two of the prominent pro-inflammatory cytokines, TNF-α and IL-6 are elevated in conditions resulting from heightened SNS activation, such as T2D [14,15,16] and hypertension [28,29]. While TNF-α has been shown to decrease the SGLT1 expression in the brush border membrane of the intestine [30,31,32], IL-6 has been shown to increase the SGLT1 expression [33]. With TNF-α and IL-6 already being known to be involved in the regulation of SGLT1, we wanted to ascertain the effect that NE had on these upstream mediators. Although TNF-α was not differentially regulated by NE, IL-6 was significantly upregulated (Figure 6), therefore prompting further experimentation involving IL-6. As both IL-6 [14,16,17] and soluble IL-6 receptor (sIL-6R) [17] are increased in T2D, we utilised the hyper IL-6 fusion protein (IL-6 and sIL-6R), which resembles the pathogenic IL-6 mediated effects in T2D. In our study, we uncover a highly novel finding that demonstrates that in the HK2 cell line, Hyper IL-6 not only promoted elevated expression of SGLT1 but also promoted proliferation of the cells (Figure 8, Figure 9 and Figure 10). Our findings are biologically relevant as the proximal tubule is particularly targeted during acute and chronic kidney injuries [34].
A marker of cell proliferation is cyclin D-dependent kinase 4 (CDK-4) which helps to drive the progression of cells into the DNA synthesis phase of the cell division cycle. We found that hyper IL-6 significantly upregulated CDK4 levels in HK2 cells (Figure 10). Interestingly, CDK4 mediated proliferation has been associated with pathogenicity. It is likely that blocking CDK4 will prevent damaged proximal tubule cells from proliferating during kidney injury. Injured proximal tubule cells promote tubulointerstitial fibrosis through production of proinflammatory and profibrotic cytokines [34]. In conclusion, blocking cell cycle progression by inhibiting CDK4 may protect against chronic kidney disease by preventing damaged proximal tubule cells from proliferating by reducing tubular injury, fibrosis and senescence [34].
## 5. Conclusions
In this novel study, we demonstrated that the SNS promotes SGLT1 expression in the kidneys in vivo. We also found that the major neurotransmitter of the SNS, NE, increased SGLT1 protein expression and translocation to the cell surface in vitro. Additionally, NE promoted a significant elevation in interleukin-6 (IL-6) levels which resulted in the promotion of SGLT1 expression and proliferation in HK2 cells. Our findings suggest that the SNS upregulates SGLT1 protein expression levels with potential adverse consequences for cardiometabolic control.
There is a current lack of studies examining the transcription and translation of SGLT1. Therefore, it would be highly interesting to examine the transcriptional and translational regulatory mechanisms underlying SNS induced increases in SGLT1. Future studies should look at utilization of Sodium Glucose Co-transporter 1 inhibitors (SGLT1i) such as KGA2727 in diseases where the SNS is dysregulated. SGLT1 inhibition may, therefore, provide a useful therapeutic target in conditions characterized by increased SNS activity, such as chronic kidney disease.
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|
---
title: The Transcription Factor NRF2 Has Epigenetic Regulatory Functions Modulating
HDACs, DNMTs, and miRNA Biogenesis
authors:
- Ignacio Silva-Llanes
- Chang Hoon Shin
- José Jiménez-Villegas
- Myriam Gorospe
- Isabel Lastres-Becker
journal: Antioxidants
year: 2023
pmcid: PMC10045347
doi: 10.3390/antiox12030641
license: CC BY 4.0
---
# The Transcription Factor NRF2 Has Epigenetic Regulatory Functions Modulating HDACs, DNMTs, and miRNA Biogenesis
## Abstract
The epigenetic regulation of gene expression is a complex and tightly regulated process that defines cellular identity and is associated with health and disease processes. Oxidative stress is capable of inducing epigenetic modifications. The transcription factor NRF2 (nuclear factor erythroid-derived 2-like 2) is a master regulator of cellular homeostasis, regulating genes bearing antioxidant response elements (AREs) in their promoters. Here, we report the identification of ARE sequences in the promoter regions of genes encoding several epigenetic regulatory factors, such as histone deacetylases (HDACs), DNA methyltransferases (DNMTs), and proteins involved in microRNA biogenesis. In this research, we study this possibility by integrating bioinformatic, genetic, pharmacological, and molecular approaches. We found ARE sequences in the promoter regions of genes encoding several HDACs, DNMTs, and proteins involved in miRNA biogenesis. We confirmed that NRF2 regulates the production of these genes by studying NRF2-deficient cells and cells treated with dimethyl fumarate (DMF), an inducer of the NRF2 signaling pathway. In addition, we found that NRF2 could be involved in the target RNA-dependent microRNA degradation (TDMD) of miR-155-5p through its interaction with Nfe2l2 mRNA. Our data indicate that NRF2 has an epigenetic regulatory function, complementing its traditional function and expanding the regulatory dimensions that should be considered when developing NRF2-centered therapeutic strategies.
## 1. Introduction
The cells of multicellular organisms have the same genetic content, yet their functions are diverse because they express different genes. These differences are due in large part to epigenetic mechanisms that lead to heritable and stable changes in gene expression programs that occur through alterations in chromatin structure. *Epigenetic* gene regulation provides an adaptive layer of control of gene expression to enable the organism to adjust to a varying environment by eliciting histone modifications, DNA methylation, and gene silencing via microRNAs (miRNAs) [1,2]. Epigenetic mechanisms are not only key in the processes of cell development and differentiation, but they also play important roles in many pathologies, including neurodegenerative diseases.
Oxidative stress arises from an imbalance between reactive oxygen species and the cell’s antioxidant capacity, leading to an accumulation of ROS and a disruption of the epigenetic state of the cell. In turn, oxidative damage triggers epigenetic changes in the chromatin structure, histone modifications, DNA methylation, and DNA-binding proteins [3]. One of the ways for the cell to combat oxidative stress is by activating the NRF2 (nuclear factor erythroid-derived 2-like 2) transcription factor signaling pathway. NRF2 is an essential factor that transcriptionally regulates over 250 genes involved in the antioxidant response, biotransformation reactions, mitochondrial bioenergetics, inflammation, and proteostasis, among others [4,5,6,7]. Because NRF2 is able to regulate so many genes and therefore has a considerable impact on a wide range of cellular functions, its expression tightly regulated. In basal conditions, there are low levels of NRF2 due to the action of an E3 ubiquitin ligase complex containing a substrate adaptor protein, Kelch-like ECH-associated protein 1 (KEAP1), which binds to and negatively regulates NRF2 [8,9]. However, in conditions in which there is a significant increase in oxidative stress, NRF2 signaling is induced through modifications of key cysteine residues in KEAP1, which induce conformational changes in the binding of NRF2–KEAP1 and prevent the degradation of NRF2. This allows for the accumulation of newly synthesized NRF2, which can then translocate to the nucleus, binds the antioxidant response element (ARE) sequence in the promoter regions of NRF2-dependent genes, and recruits the transcriptional machinery [9,10,11]. The rise in NRF2 expression can also be elicited at the epigenetic level; for example, hypermethylation of the first five CpG sites in the NRF2 promoter was associated with mouse prostate tumorigenesis [12] and the frequency of demethylation was significantly higher in colorectal cancer [13]. Further, recent evidence has identified several miRNAs that can be regulated by NRF2 in the context of several pathologies, such as cancer [14], cardiovascular diseases [15], and neurodegenerative diseases [16].
However, until now, whether NRF2 influences epigenetic processes by modulating the expression of DNA methyltransferases (DNMTs), histones deacetylases (HDACs), and miRNAs has not been investigated. Here, we identify for the first time several HDACs, DNMTs, and genes encoding proteins involved in the biogenesis of miRNAs. Additionally, we present evidence that NRF2 could modulate levels of specific miRNAs through target-directed miRNA degradation (TDMD), further expanding the functional toolkit of NRF2.
## 2.1. Bioinformatics Analysis
The script used in this study, with some modifications, was previously described [17]. Briefly, it uses, as input, a Browser Extensible Data (BED) file containing the chromatin immunoprecipitation sequencing (ChIP-seq) peaks for the transcription factors of analysis, a text file containing a list of RefSeq transcript accession numbers, and a position frequency matrix (PFM) file from the JASPAR database containing the consensus transcription factor-binding sites to be computed. Additionally, it makes use of the BED file at the UCSC Genome Browser, Table Browser resource (https://genome.ucsc.edu/cgi-bin/hgTables) (accessed on 3 February 2023) containing the locations of every transcript and its RefSeq accession number in the genome. To identify regulatory elements, a combined segmentation BED file was generated by concatenating Combined Segmentations [18] at the UCSC Genome Browser for the hg19 human genome, using BEDTools, or the ENCODE Candidate Cis-Regulatory Elements (cCREs) [19] combined from all cell type tracks was used for the mm10 mouse genome. The script retrieves the genomic coordinates for the desired transcripts, extends them 5000 bp upstream of the transcription start site, and intersects them with ChIP-seq peaks downloaded from all experiments in ChIP-Atlas [20] for the given transcription factors using the wrapper of BEDTools for Python, pybedtools [21,22]. In this analysis, all the available binding sites for NFE2L2, MAFF, MAFK, MAFG, and BACH1 or their mouse orthologs were downloaded and intersected with the extended transcripts of HDAC1, HDAC2, HDAC3, SIRT1, DNMT1, DNMT3A, DNMT3B, DROSHA, DGCR8, DICER1, and TARBP2 genes or their mouse orthologs. Then, the sequences of the ChIP-seq peaks were extracted using pybedtools from the FASTA file of the hg19 human genome (Supplementary Table S1) or the mm10 mouse genome (Supplementary Table S2). The profile for NFE2L2 was downloaded from the JASPAR database [23] in PFM format from the entry MA0150.1. Absolute frequencies were turned into a PSSM (position specific-scoring matrix), containing scores through the log2(odds-ratio) (odds ratio: observed frequency/expected frequency). One unit was added as a pseudo-count to each absolute frequency to avoid log[0]. The scoring of each site followed a similar procedure as we have previously described [5]. Briefly, a sliding window of a width dependent on the profile to be used was passed over the extracted sequences. Each nucleotide in the sliding window received a score according to the PSSM, and then, the score from each nucleotide was added up in order to provide an absolute score for the site. The relative score, the maximal and minimal scores, were obtained with a given PSSM and computed as (absolute score + |minScore|)/(|maxScore| + |minScore|). Sites with a relative score below 0.8 were discarded, and the remaining ones were provided as a BED file. In order to detect active regions, the script makes use of pybedtools to intersect the segmentation file with the regions described in the regulatory element bed file.
## 2.2. Cell Cultures and Treatments
Nfe2l2+/+ and Nfe2l2−/− littermate MEFs were derived from E11.5 mouse embryos and immortalized with SV40 large T antigen and provided by Dr. Antonio Cuadrado (Universidad Autónoma de Madrid, Spain) and are previously described [24,25,26]. Keap1−/− and Keap1+/+ MEFs were provided by Dr. Ken Itoh (Center for Advanced Medical Research, Hirosaki University Graduate School of Medicine, Hirosaki, Japan). Mouse embryonic fibroblasts (MEFs) and mouse hippocampus-derived HT22 cells were grown in Dulbecco’s modified Eagle’s medium (D5648, Sigma-Aldrich, St. Louis, MO, USA) supplemented with $10\%$ fetal bovine serum (CH 30160.03, HyClone, Logan, UT, USA) and 80 μg/mL gentamicin (763011.1, Laboratorios Normon, Madrid, Spain). All cell lines were mycoplasma-free, as ascertained through regular tests. Cells were changed to serum-free DMEM without antibiotics 16 h before the addition of dimethyl fumarate (DMF-20 μM) treatment (Merck, Darmstadt, Germany).
## 2.3. Analysis of mRNA Levels via Quantitative Real-Time PCR
Total RNA extraction, reverse transcription, and quantitative polymerase chain reaction (qPCR) were performed as detailed in previous articles [27]. Primer sequences are shown in Supplementary Table S3. Data were analyzed using the 2−ΔΔCT method, with normalization of the raw data based on the geometric mean of Actb and Gapdh (Applied Biosystems), encoding housekeeping proteins. All PCR amplifications were performed in triplicate.
## 2.4. Plasmids
The expression vector pcDNA3.1/V5HisB-mNRF2ΔETGE was described in McMahon et al. [ 11]. pEF-ΔNRF2(DN), was kindly provided by Dr. J. Alam (Dept. of Molecular Genetics, Ochsner Clinic Foundation, New Orleans, LA). For luciferase assays, transient transfections were performed with the expression vector pSGG-NRF2-3’UTR, kindly provided by Dr. Qun Zhou (University of Maryland School of Medicine, Baltimore, USA), which is a reporter plasmid containing the wild-type NRF2 3’UTR.
## 2.5. Luciferase Assays
Transient transfections of MEFs or HT22 cells and luciferase assays were performed as described in [26]. pTK-Renilla was used as an internal control vector (Promega).
## 2.6. Immunoblotting
Whole-cell lysates were prepared in RIPA-Buffer (25 mM Tris-HCl pH 7.6, 150 mM NaCl, 1 mM EGTA, $1\%$ Igepal, $1\%$ sodium deoxycholate, $0.1\%$ SDS, 1 mM PSMF, 1 mM Na3VO4, 1 mM NaF, 1 μg/mL aprotinin, 1 μg/mL leupeptin, and 1 μg/mL pepstatin). Whole-cell lysates were loaded for SDS-PAGE. Immunoblots were performed as described in [26]. The primary antibodies used are described in Supplementary Table S4.
## 2.7. Antisense Oligonucleotide (ASO) Pull-Down Assay
To identify Nfe2l2 mRNA-associated miRNAs, ASO pull-down was performed using non-overlapping biotinylated ASOs recognizing LacZ (four ASOs) and Nfe2l2 (eleven ASOs). Incubation of whole-cell lysates with biotinylated ASOs was followed by incubation with Streptavidin-coupled Dynabeads™ (Invitrogen by Thermo Fisher Scientific, Waltham, MA, USA). RNAs were isolated from the pull-down materials, and qPCR was performed. Briefly, whole-cell lysates were prepared using RIPA buffer with a cocktail of protease and phosphatase inhibitors (Thermo Fischer Scientific, Waltham, MA, USA). One milligram of whole-cell extract was incubated with 1 μg of either Nfe2l2 ASO or control LacZ ASO for 16 h at 4 °C, whereupon RNA complexes were isolated with M-280 Streptavidin Dynabeads (Invitrogen) for 2 h at 25 °C. Total RNA was isolated with Trizol-Choloroform and cDNAs were synthesized with the Maxima Reverse Transcription kit following the manufacturer’s protocols (Thermo Fisher Scientific, Waltham, MA, USA); real-time quantitative (q)PCR analysis was then performed using a PCR kit according to manufacturer’s instructions (KAPA Biosystems, Wilmington, MA, USA), and the mRNA abundance was calculated via the 2−ΔΔCT analysis method, using Gapdh mRNA levels as the control transcript for normalization. miRs were reverse-transcribed using the MiR-X kit (Takara Bio, Shiga, Japan) and quantified via qPCR analysis using U6 as the normalization control RNA.
## 2.8. Analysis of miRNA Levels via Quantitative Real-Time PCR
Total RNA extraction was performed using the miRNeasy Mini Kit (Qiagen, Maryland, Germany). For reverse transcription and qPCR, we used miRCURY LNA SYBR® Green PCR Kit (Qiagen, Maryland, Germany). We employed hsa-miR-128-3p miRCURY LNA (YP00205995), mmu-miR-155-5p miRCURY LNA (YP02119303), and miR-103a-3p miRCURY LNA (YP00204063) PCR Assays (Qiagen, Maryland, Germany). Data analyses were based on the ΔΔCT method, with normalization of the raw data based on UniSp6 (Applied Biosystems, Foster City, CA, USA). All PCR amplifications were performed from at least triplicate samples.
## 2.9. Statistical Analyses
Data are presented as the mean ± SEM. To determine the statistical test to be used, we employed GraphPad Instat 3, which includes the analysis of the data to a normal distribution via the Kolmogorov–Smirnov test. In addition, statistical assessments of differences between groups were analyzed (GraphPad Prism 8 by Dotmatics, San Diego, CA, USA) by performing an unpaired Student’s t-tests. A one-way ANOVA with post-hoc Newman–Keuls test was used.
## 3. Results
The epigenome is comprised of modifications to chromatin, including histone modifications and DNA methylation. One of the main histone modifications is acetylation, which is often a necessary precursor to other modifications, such as phosphorylation, methylation, and ubiquitylation. Acetylation is controlled by the opposing functions of two families of enzymes: histone acetyltransferases (HATs) and histone deacetylases (HDACs). HDACs are involved in key biological functions, such as transcription, cell cycle, autophagy, DNA damage repair, stress responses, and senescence [28,29]. HDACs are classified according to their sequence similarities with yeast HDACs into class I, class II (IIa and IIb), class III, and class IV. HDACs have been found to regulate NRF2 signaling by directly modulating NRF2 acetylation [30]. In this study, we focused on the impact of NRF2 on the expression of HDAC1, HDAC2, and HDAC3. We also tested SIRT1 (a type-IV HDAC) given that its crosstalk with NRF2 has been previously described [31]. DNA methylation, another major epigenetic change, results from the transfer of a methyl group onto the cytosine to form 5-methylcytosine. DNA methylation regulates gene expression by recruiting proteins involved in gene repression or by inhibiting the binding of transcription factor(s) to DNA [32]. DNMTs include DNMT1, with a maintenance function to copy DNA methylation patterns from the parental DNA strand onto the newly synthesized daughter strand during DNA replication, and DNMT3a and DNMT3b, with de novo functions to establish new methylation patterns on unmodified DNA. DNA methylation is crucial for regulating tissue-specific gene expression, genomic imprinting, and X chromosome inactivation. Given that oxidative stress modulates DNA methylation levels in cancer [33], cardiovascular diseases, and type 2 diabetes [34], we sought to study if the expression of HDACs and DNMTs is dependent on the transcription factor NRF2.
## 3.1. Identification of Putative ARE Sequences in HDCAs and DNMTs
First, to define comprehensively the role of NRF2 in the transcriptional regulation of HDACs and DNMTs, we searched for putative ARE sequences in the ChIP-Atlas database, an integrative database covering almost all public data archived in the Sequence Read Archive of NCBI, EBI, and DDBJ, using ChIP-seq data [20] of the human (Table 1) or mouse (Table 2) genomes for HDAC1, HDAC2, HDAC3, SIRT1, DNMT1, DNMT3a, and DNMT3b.
The ChIP-Atlas database includes experimental data from chromatin immunoprecipitation (ChIP) analysis of the ARE-binding transcription factors MAFG, MAFF, MAFK, BACH1, and NFE2L2. We used Python-based bioinformatic analysis to scan this binding region for the consensus ARE, as established in the JASPAR database [17,35]. Depending on the gene, we detected zero, one, or several putative ARE sequences with a relative score higher than $80\%$, a commonly used threshold for transcription factor binding-site analysis [36,37]. These putative ARE sequences in the promotor region have a high degree of similarity with the consensus ARE sequence (NTGACNNNGCN) described by [38]. As shown in Table 1 and Table 3, bioinformatic analyses suggested that there are ARE sequences in HDACs, especially in DNMTs. We then performed functional assays to test the putative function of these sequences.
## 3.2. HDCAs Are NRF2-Dependent Genes
To test the bioinformatic predictions, we analyzed the levels of HDAC mRNAs in mouse embryonic fibroblasts (MEFs) derived from Nfe2l2+/+ and Nfe2l2−/− mice (Supplementary Figure S1A-verification of MEF genotype). As shown, the ablation of NRF2 led to a significant decrease in mRNA levels (Figure 1A). These reductions were reflected at the protein level (Figure 1B), further supporting the view that the production of HDAC1, HDAC2, HDAC3, and SIRT1 was regulated by NRF2. We then studied whether inducing NRF2 levels might enhance HDAC expression in hippocampal HT22 neurons (Supplementary Figure S1B,C). We treated cells with dimethyl fumarate (DMF), an activator of the NRF2 pathway through both the KEAP1 and GSK-3 pathways, as previously described [39]. Treatment with DMF induced a time-dependent increase in the levels of all HDAC mRNAs (Figure 1C). These results were corroborated at the protein level, as we found that DMF treatment significantly induced protein levels of HDAC1, HDAC2, and SIRT1 (Figure 1D). Taken together, these data indicate that NRF2 is able to modulate the expression of HDAC1, HDAC2, HDAC3, and SIRT1 in different cell types, suggesting a novel function with an epigenetic impact on this transcription factor.
## 3.3. NRF2 Is a Modulator of DNMTs Expression
After bioinformatic analysis of ARE elements in the promoters of DNMTs, we followed the same strategy for the analysis of HDACs. First, we analyzed the levels of Dnmt1, Dnmt3a, and Dnmt3b mRNAs in NRF2-deficient MEFs. We observed that the levels of Dnmt1 and Dnmt3b mRNAs were significantly reduced, while the changes in Dnmt3a mRNA were more modest ($$p \leq 0.07$$) (Figure 2A). These changes were mirrored at the protein level for DNMT1; DNMT3a levels were moderately reduced, while DNMT3b was not detectable (see Figure 2B). We then analyzed the effects of inducing NRF2 by treating HT22 cells with DMF. As shown, DMF treatment induced DNMT1 and DNMT3b at both mRNA and protein levels, validating the effects observed in MEFs and further supporting the notion that they are regulated by NRF2. For DNTM3a, there was a slight induction of mRNA levels but not at the protein level (Figure 2C,D); further analysis is needed to determine whether the expression of DNMT3a is regulated by NRF2.
## 3.4. NRF2 Regulates the Expression of Proteins Implicated in miRNA Biogenesis
Besides histone acetylation and DNA methylation, miRNAs (small non-coding RNAs) reduce the stability and translation of target mRNAs and are also epigenetic regulators. ROS can modulate miRNA biogenesis at many levels, and several enzymes and components of the miRNA processing machinery can be affected by ROS [40]. Therefore, we examined the possibility that expression of the proteins involved in microRNA biogenesis (DGCR8, DROSHA, DICER, and TARBP2) might be regulated by NRF2.
Therefore, as before, we investigated bioinformatically whether there were ARE sequences in the promoter regions of the DGCR8, DROSHA, DICER1, and TARBP2 genes. We observed that, especially in the human genome (Table 3), there were several possible ARE sequences within all genes analyzed. In the mouse genome, we only found possible ARE sequences in the regulatory regions of the Dicer1 and *Drosha* genes (Table 4).
In MEFs from Nfe2l2+/+ and Nfe2l2−/− mice, we observed significant decreases in Dgcr8, Drosha, Dicer1, and Tarbp2 mRNAs (Figure 3A). Similarly, the expression levels of DGCR8, DROSHA, and DICER1 proteins decreased greatly in the absence of NRF2 (Figure 3B), while the levels of TARDBP2 protein did not change. On the other hand, treatment of HT22 cells with DMF significantly induced the levels of Dgcr8, Drosha, Dicer1, and Tarbp2 mRNAs (Figure 3C), as well as the proteins DGCR8 and DICER, while TARBP2 was less induced and DROSHA was unchanged (Figure 3D). These data suggest that many proteins involved in miRNA biogenesis are regulated by NRF2.
## 3.5. NRF2 Modulates miRNA Expression
The sequences of 3′-untranslated regions (3’UTRs) of messenger RNAs (mRNAs) govern their stability, localization, and expression [41]. miRNAs typically bind to the 3′ UTRs of target mRNAs with which they share partial complementarity and reduce their stability and translation. Therefore, we evaluated whether miRNAs interacting with the 3’UTR of NFE2L2 mRNA suppressed NRF2 expression and whether NRF2 was able to modulate this loop. To test this hypothesis, the ability of miRNAs to regulate the 3’UTR of Nfe2l2 mRNA was evaluated using luciferase reporters. MEFs from Nfe2l2+/+ and Nfe2l2−/− mice were transfected with the pSGG luciferase vectors bearing the NRF2 3’UTR, along with a control renilla vector. As shown in Figure 4A, the absence of NRF2 led to increased expression of miRNAs that negatively modulate the expression of the 3’UTR. Similarly, these data were confirmed in HT22 cells, where transfection of a dominant negative NRF2 (DN-NRF2) negatively regulated the expression of the 3’UTR of NRF2 (Figure 4C). In contrast, an increase in NRF2 levels, either in KEAP1-deficient MEFs (where there is an increase in NRF2 levels) (Figure 4B) or via transfection of the NRF2-ΔETGE-V5 (Figure 4C) that lacks four residues (ETGE) essential for recognition by the E3 ligase complex Cul3/KEAP1, led to a decrease in the levels of miRNAs that inhibit the 3’UTR of NRF2 and thus an increase in its expression. These data were verified using the NRF2 inducer DMF at different doses (Figure 4D). The results indicate a dose–response effect in which the higher the increase in NRF2 levels the greater the de-repression of the reporter 3’UTR. Although in these experiments we cannot rule out the impact of other factors, such as RNA-binding proteins, other non-coding RNAs, or RNA modifications on this 3’UTR, in addition to the action of miRNAs, the data are consistent with a model whereby NRF2 reduces the levels of specific microRNAs capable of binding the Nfe2l2 mRNA and reducing Nfe2l2 mRNA and NRF2 protein.
## 3.6. Implication of NRF2 Expression in Target-Dependent miRNA Degradation (TDMD) of miR-155-5p
The fact that NRF2 expression levels could modulate the levels of miRNAs led us to identify the specific miRNAs involved. We first analyzed which miRNAs might be binding to the Nfe2l2 mRNA, by using the Targetscan (119 miRNAs) and miR DB (55 miRNAs) databases (Figure 5A). In total, there were 53 merged miRNAs. Of these 53 miRNAs, there were miRNAs with two binding sites (miR-144-4p, miR-1950, miR-20a-3p, and miR-544-3p) and with conserved sites (miR-27b-3p, miR-27a-3p, miR-6539, miR-128-3p, miR-142a-5p, miR-340-5p, miR-153-3p, miR-155-5p, and miR-144-3p). To investigate these interactions directly, 11 antisense oligonucleotides (ASOs) directed at Nfe2l2 mRNA (NM_010902.4) were designed in order to pull down the endogenous Nfe2l2 mRNA. Whole-cell lysates from HT22 cells were then prepared and incubated with either Nfe2l2 ASOs or control LacZ ASO, whereupon RNA complexes were isolated with streptavidin Dynabeads (Invitrogen). As shown in Figure 5A, Nfe2l2 mRNA was highly enriched in Nfe2l2 ASO samples compared to that in LacZ ASO samples. We then measured the levels of all the predicted miRNAs (Figure 5A) in the pulldown complexes and found that miR-27a-3p, miR-27b-3p, miR-128-3p, and miR-155-5p were enriched in Nfe2l2 ASO-pulldown samples (Figure 5B), suggesting that these miRNAs are associated with Nfe2l2 mRNA.
As mentioned above, miRNAs control target gene expression by inhibiting translation and degrading target RNAs. In addition, there is evidence that mRNAs can affect microRNA activity in two manners [42]. First, some mRNAs can function as competing endogenous RNAs (ceRNAs), as seen when two endogenous targets compete with each other for binding to a shared miRNA [43]. In this case, if one of the endogenous mRNA targets changes its expression, the activity of miRNAs upon the other targets will change accordingly. This mechanism appears to have been ruled out, since NRF2 overexpression itself reduced the levels of the miRNAs that bind to it. The second mechanism is target-directed miRNA degradation (TDMD) [44]. In TDMD, the target mRNA promotes the degradation of the miRNA that binds to it [45]. To test whether this might be what was happening with NRF2, we treated HT22 cells with DMF (conditions similar to Figure 4D, 20 μM) and analyzed the expression levels of miR-27a-3p, miR-128-3p, and miR-155-5p. As observed in Figure 5C, NRF2 induction promoted a significant decrease in miR-155-5p levels, while other miRNAs were unchanged. Finally, we sought to determine in which biological processes miR-155-5p is involved, mainly at the neuronal level, in order to determine the role that its modulation through NRF2 may have. To do this, we determined its targets through the TargetScan database, and using the ShinyGo 0.76.2 platform and its pathway database, we performed a GO biological process analysis. Although miR-155-5p participates in many processes, it was found to be involved in the regulation of ~45 mRNAs encoding proteins that participate in the development of the central nervous system (CNS) and ~64 mRNAs encoding proteins implicated in neurogenesis (Figure 6), respectively. Thus, a more exhaustive analysis of the involvement of miR-155-5p and the possible regulation by NRF2 in the development of the central nervous system is required.
## 4. Discussion
Although the expression of the transcription factor NRF2 at the epigenetic level has been studied extensively, the reciprocal process, i.e., the impact of NRF2 on epigenetic gene regulation, has not been explored. In this study, we show for the first time that NRF2 is able to regulate the expression of type-I HDACs (HDAC1, HDAC2, HDAC3) and SIRT1, DNMTs, and proteins involved in miRNA biogenesis, DROSHA, DGCR8, DICER1, and TARBP2. Our data further suggest that NRF2 may be involved in the regulation of the levels of certain miRNAs through TDMD. These new data are of great potential relevance to the pharmacological regulation of NRF2 as a therapeutic strategy for various pathologies since epigenetic changes triggered by NRF2 will also have to be weighed.
NRF2 is a pleiotropic transcription factor capable of regulating the expression of genes involved in different processes, including xenobiotic, redox, and carbohydrate metabolism, inflammation, and proteostasis [5] (Figure 7). Therefore, its dysregulation has been described in a multitude of pathologies, in many cases along with epigenetic changes that cause aberrant gene expression programs and the loss of homeostasis. These data suggest that NRF2 affects many cellular functions underlying disease, although to-date, we only understand how epigenetic modifications affect the expression and function of the NRF2 pathway. The fact that NRF2 can promote the expression of type-I HDAcs (Figure 1), DNMTs (Figure 2), and proteins involved in miRNA biogenesis (Figure 3) opens new perspectives on the spectrum of actions of NRF2, its epigenetic influence, and its implications in disease. In this study, we have focused on the study of type-I and SIRT1 HDACs, but in further studies, it will be interesting to determine the involvement of NRF2 related to the other HDACs and to determine whether the results of the study presented here can be extrapolated to all types of HDACs or is specific to type-I HDACs and SIRT1.
Our studies suggest that when NRF2 levels are decreased in pathologies, this reduction may lead to decreased expression of Type-I HDACs and increased expression of genes that were repressed under physiologic conditions. Similarly, NRF2 deficiency would also lower DNMT levels, in turn inducing the expression of genes that were previously repressed. On the other hand, NRF2 inducers, such as sulforaphane, were found to induce NRF2 regulation at the epigenetic level, mainly associated with DNA methylation [47]. Epigenetic changes in the mechanism of action of DMF have also been described [48,49,50]. In contrast with the several agents that function as NRF2 inducers, very few molecular components have been recognized as NRF2 inhibitors. Brusatol, luteolin, trigonelline, and retinoic acid are several compounds that have been described as having inhibitory effects on NRF2 signaling [51], but their effects at the epigenetic modulation level have not yet been described. In future experiments, it will be interesting to analyze the effect of NRF2 inhibitors on the levels of HDACs, DNMTs, and miRNAs, to determine the possible impact of NRF2 inhibitor treatments at the epigenetic level. Our data support the fact that the pharmacological regulation of NRF2 involves different downstream effectors (Figure 7), including HDACs, DNMTs, and miRNAs, and thus broadening the spectrum of action of this transcription factor.
The results presented in this study can be potentially relevant to a wide range of pathologies where epigenetic mechanisms are of particular importance, such as cancer [52,53], allergies [54], and neurodegenerative diseases [55,56]. In cancer, specific methylation and other alterations of the NFE2L2 promoter have been documented [12,57,58], which can alter the expression levels of NRF2, linked to carcinogenesis through metabolic reprogramming, tumor promotion, inflammation, and resistance to therapy. NRF2 silencing or pharmacological inhibition by brusatol reduced the proliferation and migration of breast cancer (BC) cells, inhibited proliferation, activated apoptosis, sensitized BC cells to cisplatin in vitro, and slowed tumor cell growth in vivo [59]. Along these lines, esophageal adenocarcinoma (EAC) displayed increased NRF2, and both the knockdown of NRF2 and pharmacological inhibition with brusatol inhibited tumor growth by inducing ferroptosis and apoptosis [60]. In the case of metastatic *Ewing sarcoma* and osteosarcoma, it has been described that oxidative stress attenuates metastasis; here, treatment with the class-I HDAC inhibitor MS-275 inhibited the deacetylation of YB-1 (Y-box binding protein 1), reduced its binding to the 5’UTR of NFE2L2, reduced the translation of NRF2, and increased the levels of intracellular ROS [61]. However, other studies showed that HDAC inhibitors increased NRF2-signaling in tumor cells [62]. Therefore, further studies will be needed to look at the crosstalk between HDACs and NRF2, taking into consideration that NRF2 has pleiotropic roles in cancer cells [51].
Outside of cancer, type I and II HDAC inhibition mediated by Trichostatin A (TSA) activated transcription factor NRF2 and protected against cerebral ischemic damage. On the other hand, SIRT1 activation was also found to induce the NRF2 signaling pathway, with beneficial effects in focal cerebral ischemia [63], indicating that further studies are needed to unravel the crosstalk between HDAC and NRF2 in this pathology [64]. In neurodegenerative diseases, HDAC inhibitors were found to improve the redox balance and attenuate neuronal degeneration in Huntington’s disease [65] and amyotrophic lateral sclerosis [66] mouse models and in Alzheimer’s disease-like pathological changes in SH-SY5Y neuroblastoma cells [67]. One mechanism of action described in this regard is that HDACs remove acetyl groups in histones associated with the KEAP1 promoter region, inducing an increase in KEAP1 transcription, and therefore, the inhibition of HDAC might have opposite effects [65]. Additionally, NRF2 levels were found to be elevated in many neurodegenerative diseases [27,68,69], and thus, further studies are warranted to fully understand the interaction between NRF2 and HDACs and the therapeutic value of interventions directed at NRF2 and/or HDACs. Similar to HDACs, DNMTs are also potential therapeutic targets, since alterations in their activity have also been associated with various pathologies. Therefore, as with HDACs, more studies are needed to establish the value of therapeutic strategies that modulate NRF2 and DNMTs pharmacologically [70,71,72].
A multitude of miRNAs are predicted to repress NRF2 production [73], and many miRNAs are involved in oxidative stress processes associated with physiological and pathological conditions [74]. The fact that oxidative stress is capable of regulating the expression of proteins involved in the biogenesis of miRNAs [75,76,77] led us to evaluate the potential involvement of NRF2 in this mechanism. Our data indicate that NRF2 promotes the production of proteins DROSHA, DGCR8, DICER1, and TARBP2 involved in miRNA biosynthesis (Figure 3), expanding the function of this transcription factor into the post-transcriptional space. Although miRNAs typically modulate the stability and translation of their target mRNAs, we have shown that the absence of NRF2 leads to the increased expression of miRNAs that negatively modulate the expression of the 3’UTR-Nfe2l2 (Figure 4A,C) and vice versa, underscoring the fact that NRF2 levels can also repress the actions of some miRNAs. More detailed studies are necessary to elucidate the specific miRNAs involved in this mechanism. As mentioned above, we cannot rule out the impact of other factors, such as RNA-binding proteins, other non-coding RNAs, or RNA modifications on this 3’UTR, in addition to the action of miRNAs. Further studies of additional regulatory factors should also be considered.
Oxidative stress is one of the main inducers of the NRF2 pathway, and thus, its activation is linked to the induction of oxidative stress-associated miRNAs, the so-called “redoximiRs”, such as miR-27a-3p and miR-155-5p [75,78]. In HT22 hippocampal cells, our data indicate that of all miRNAs analyzed (Figure 5A), only miR-27a-3p, miR-27b-3p, miR-128-3p, and miR-155-5p associate with Nfe2l2 mRNA (Figure 5B). There is previous evidence that miR-27a-3p and miR-27b-3p are redox-sensitive miRNAs [79,80,81,82] and modulate NRF2 levels, in agreement with our results. For example, in maternal diabetes-induced oxidative stress, miR-27a-3p levels rise, in turn suppressing NRF2 production [81]. Furthermore, an analysis of miRNA signatures in transgenic mice expressing a constitutively active, cardiac-specific NRF2 (caNrf2-Tg) [15] revealed that increasing the levels of NRF2 leads to reduced miR-155-5p levels. These results support our data that the induction of NRF2 decreased miR-155-5p levels (Figure 5B). Here, we focused on “redoximiRs” and found that NFE2L2 mRNA might drive the degradation of specific miRNAs mediated by TDMD and thereby reduce the levels of specific miRNAs. Further experiments are necessary to determine the exact mechanism by which NRF2 causes the degradation of other microRNAs, such as miR-155-5p, given its implication in neuroinflammation and other pathologies, and is the main miRNA induced by LPS treatment in microglia [83,84]. Furthermore, miR-155 alters the expression of genes that regulate axon growth [85], supporting the bioinformatic prediction that miR-155 can regulate the expression of genes involved in CNS development and neurogenesis (Figure 6). Therefore, the modulation of this miR-155-5p could be of great relevance in relation to neurodegenerative diseases, such as Alzheimer’s disease. The precise regulation of miR-155 and other microRNAs by NRF2 awaits future study. It would also be interesting to determine, in future experiments, whether these miRNAs are specific to a specific neuronal type (e.g., hippocampal neurons) or have a more general functions, as well as whether there are differences between the various brain cell types.
## 5. Conclusions
This study demonstrates for the first time that the molecules involved in epigenetic gene regulation, namely HDACs, DNMTs, and miRNA biogenesis factors, are under the control by NRF2, expanding the field of action of this transcription factor.
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|
---
title: Prenylcysteine Oxidase 1 Is a Key Regulator of Adipogenesis
authors:
- Cristina Banfi
- Alice Mallia
- Stefania Ghilardi
- Maura Brioschi
- Erica Gianazza
- Sonia Eligini
- Pelin Sahlén
- Roberta Baetta
journal: Antioxidants
year: 2023
pmcid: PMC10045348
doi: 10.3390/antiox12030542
license: CC BY 4.0
---
# Prenylcysteine Oxidase 1 Is a Key Regulator of Adipogenesis
## Abstract
The process of adipogenesis involves the differentiation of preadipocytes into mature adipocytes. Excessive adipogenesis promotes obesity, a condition that increasingly threatens global health and contributes to the rapid rise of obesity-related diseases. We have recently shown that prenylcysteine oxidase 1 (PCYOX1) is a regulator of atherosclerosis-disease mechanisms, which acts through mechanisms not exclusively related to its pro-oxidant activity. To address the role of PCYOX1 in the adipogenic process, we extended our previous observations confirming that Pcyox1−/−/Apoe−/− mice fed a high-fat diet for 8 or 12 weeks showed significantly lower body weight, when compared to Pcyox1+/+/Apoe−/− mice, due to an evident reduction in visceral adipose content. We herein assessed the role of PCYOX1 in adipogenesis. Here, we found that PCYOX1 is expressed in adipose tissue, and, independently from its pro-oxidant enzymatic activity, is critical for adipogenesis. *Pcyox1* gene silencing completely prevented the differentiation of 3T3-L1 preadipocytes, by acting as an upstream regulator of several key players, such as FABP4, PPARγ, C/EBPα. Proteomic analysis, performed by quantitative label-free mass spectrometry, further strengthened the role of PCYOX1 in adipogenesis by expanding the list of its downstream targets. Finally, the absence of Pcyox1 reduces the inflammatory markers in adipose tissue. These findings render PCYOX1 a novel adipogenic factor with possible pathophysiological or therapeutic potential.
## 1. Introduction
Adipose tissue plays an important role in energy homeostasis through its capacity to store energy, mobilize stored lipids for fuel, and secrete hormones and cytokines [1]. Cardiovascular diseases, type 2 diabetes, and metabolic syndrome are all associated with excess fat accumulation in white adipose tissue (WAT) [2]. Understanding the molecular events that regulate adipocyte differentiation is an essential step towards preventing obesity and metabolic diseases because adipocyte differentiation determines adipose tissue mass.
Adipocyte differentiation involves hormonal stimulators and the induction of a network of transcription factors that induce changes in gene expression and cell morphology. At the top of this transcriptional hierarchy are the basic region/leucine zipper proteins CCAAT-enhancer binding protein (C/EBP)δ, C/EBPβ, C/EBPα, and the nuclear receptor peroxisome proliferator-activated receptor (PPAR)γ [3]. These transcription factors are induced in a sequential and tightly regulated manner, and all are essential for normal adipogenesis. However, several important unanswered questions remain, and a more complete understanding of the developmental origin as well as the cellular and molecular components of adipose tissue is necessary to further illuminate how excess adiposity contributes to the onset and/or progression of metabolic disorders.
We have recently shown that prenylcysteine oxidase 1 (PCYOX1) deficiency in apolipoprotein E deficient mice (Apoe−/−) is associated with reduced body weight and adipose tissue deposits [4], but the role of PCYOX1 in adipogenesis has never been addressed since its discovery in 1997 by Casey’s group in studies related to the metabolism of prenylated proteins [5,6].
To substantiate the contribution of PCYOX1 in the adipogenic process, we investigated its role in vitro and in vivo, taking advantage of a complementary approach based on gene silencing and label-free quantitative proteomics.
Here we describe for the first time the role of PCYOX1 as a novel regulator of adipogenesis. Employing proteomics and gene expression analysis in Pcyox1 silenced cells, we show that it acts upstream of the key factors that control the adipogenic process, while the in vivo absence of the *Pcyox1* gene in mice is associated with reduced adipose deposits, and related adipose tissue inflammation. Overall, these data identify PCYOX1 as a master regulator and potential therapeutic target in obesity-related diseases.
## 2.1. Cell Culture and Induction of Differentiation
3T3-L1 preadipocytes (American Type Culture Collection, Manassas, VA, USA) were maintained in Dulbecco’s Modified Eagle Medium (DMEM) (Gibco; Thermo Fisher Scientific, Milan, Italy) with 4500 mg/L glucose supplemented with $10\%$ fetal bovine serum (EuroClone, Milan, Italy). To induce differentiation, 2 days after reaching confluence (day 0), cells were exposed to a cocktail of 0.5 mmol/L 3-isobutyl-1-methyl-xanthine (Sigma-Aldrich, Milan, Italy), 0.25 µmol/L dexamethasone (Sigma-Aldrich, Milan, Italy) and 1 µg/mL insulin (Sigma-Aldrich, Milan, Italy) for 48 h, followed by exposure to insulin 1 µg/mL alone for additional 3 days. After this period, the medium was replaced every 2 days with DMEM containing $10\%$ fetal bovine serum until the ninth day.
## 2.2. PCYOX1 Overexpression in CHO Cells
CHO cells overexpressing PCYOX1 were generated as previously described [4]. Briefly, an empty pcDNA5/FRT vector and a custom pcDNA5/FRT:PCYOX1 (Invitrogen; Thermo Fisher Scientific, Milan, Italy) were transfected into Flp-In-CHO cells (R758-07, Invitrogen; Thermo Fisher Scientific, Milan, Italy) using a pOG44 expression vector (V6005-20, Invitrogen; Thermo Fisher Scientific, Milan, Italy). The selection of PCYOX1-expressing clones was performed according to the Flip-In System protocol (K6010-01, Invitrogen; Thermo Fisher Scientific, Milan, Italy).
## 2.3. Stable Transfection with Short Hairpin RNA (shRNA)
*Stable* gene silencing of Pcyox1 and Cebpb in 3T3-L1 cells was achieved using shRNA plasmids (Santa Cruz Biotechnology, Dallas, TX, USA), a pool of 3 target-specific lentiviral vector plasmids each encoding 19–25 nt (plus hairpin) shRNAs designed to knock down Pcyox1 and *Cebpb* gene expression. A shRNA plasmid encoding a scrambled shRNA sequence that does not induce the degradation of any cellular message was taken as negative control (control cells, shNEG). Cells at 50–$70\%$ confluency were transfected for 24 h with a multiplicity of infection (MOI) of 5 for Pcyox1 shRNA and 7.5 for Cebpb shRNA lentiviral particles, and 5 µg/mL of Polybrene (Santa Cruz Biotechnology, Dallas, TX, USA) for each well of a 12 well/plate and cultured in complete medium containing 2 µg/mL puromycin to allow selection.
## 2.4. Oil Red O Staining
Cells were washed with phosphate-buffered saline (PBS) and fixed with formalin ($4\%$) for 1 h. After washing with water, cells were treated with $60\%$ isopropanol for 5 min, and then stained with Oil Red O working solution prepared according to the manufacturer’s instructions (Sigma-Aldrich, Milan, Italy).
## 2.5. Real-Time Quantitative Reverse Transcriptase PCR (qRT-PCR)
Cells were harvested in the lysis buffer, and RNA was extracted with the Total RNA Purification Kit (Norgen Biotek Corp., Thorold, ON, Canada). Adipose tissues were homogenized by means of TissueLyser II (QIAGEN, Milan, Italy) before RNA extraction with the Fatty Tissue RNA Purification Kit (Norgen Biotek Corp., Thorold, Ontario, Canada) and reverse transcribed (1 μg) as described [7]. The quality of cellular and tissue RNA was checked by the Agilent 2100 Bioanalyzer system (Agilent Technologies, Santa Clara, CA, USA). Real-time qRT-PCR was performed in triplicate with 2.5 μL of cDNA incubated in 22.5 μL IQ Supermix containing primers and SYBRGreen fluorescence dye (Bio-Rad Laboratories, Milan, Italy) using the iCycler Optical System (Bio-Rad Laboratories, Milan, Italy) with an initial denaturation for 3.3 min at 95 °C, followed by 50 cycles of amplification (15 s at 95 °C and 60 °C for 1 min), and by melting curve. The sequences of the primers used are listed in Supplementary Table S1. The other specific primers were purchased from QIAGEN (Milan, Italy): Pcyox1, Pparg, Fabp4, Cebpa, Cebpb, Lipe, Car3, Plin1, Agpat2, Ces1f, Gpd1, Emr1, Itgam, Itgax, Lgals3, and Saa3, and summarized in Table S2. Expression levels were calculated by Ct values normalized to the housekeeping 18s rRNA or *Gapdh* genes using the 2−ΔΔCT data analysis method. Pcyox1 amplicons (120 bp) were analysed by electrophoresis in agarose gel $2\%$ w/v containing GelRed (Biotium, Fremont, CA, USA) and visualized with Gel doc (Bio-Rad Laboratories, Milan, Italy).
## 2.6. Oxidized Low Density Lipoprotein (oxLDL) Assay
The quantitation of oxLDL in the cell culture medium was performed by a quantitative immunoenzymatic assay according to the manufacturer’s instructions (MyBioSource, Inc., San Diego, CA, USA). Briefly, shNEG and shPcyox1 silenced cells were induced to differentiate for 9 days. After this period, medium was collected and oxLDL levels were measured.
## 2.7. PCOYX1 Activity Assay
PCYOX1 activity was assessed as previously described [4]. Briefly, H2O2 produced in cells by the PCYOX1 reaction was measured using the Amplex Red Kit (Life Technologies, Milan, Italy). In the presence of peroxidase, the Amplex Red reagent is converted by H2O2 into the red-fluorescent oxidation product resorufin. The resorufin produced was measured following the fluorescence emission in a microplate reader Infinite 200 (TECAN, Mannedorf, Switzerland), equipped for excitation at 530 nm and fluorescence emission detection at 590 nm. Results are expressed as picomoles of H2O2 /µg protein.
## 2.8. Label-Free Mass Spectrometry (LC-MSE) Analysis
Cell pellets were dissolved in 25 mmol/L NH4HCO3 containing $0.1\%$ RapiGest (Waters Corporation, Milford, MA, USA), sonicated, and centrifuged at 13,000× g for 10 min. After 15 min of incubation at 80 °C, proteins were reduced with 5 mmol/L dithiothreitol (DTT) at 60 °C for 15 min, and carbamidomethylated with 10 mmol/L iodoacetamide for 30 min at room temperature in darkness. Digestion was performed with sequencing grade trypsin (Promega, Milan, Italy) (1 µg every 20 µg of proteins) overnight at 37 °C. After digestion, $2\%$ trifluoroacetic acid (TFA) was added to hydrolyze RapiGest and inactivated trypsin. Tryptic peptides were used for label-free mass spectrometry analysis, LC-MSE, performed on a hybrid quadrupole-time of flight mass spectrometer (SYNAPT-XS, Waters Corporation, Milford, MA, USA) coupled with a UPLC Mclass system and equipped with a nano-source (Waters Corporation, Milford, MA, USA), as previously described [8,9]. Statistical analysis was performed by means of Progenesis QIP v 4.1 (Nonlinear Dynamics) using a Uniprot mouse protein sequence database (v2020). The mass spectrometry proteomics data have been deposited to the ProteomeXchange *Consortium via* the PRIDE [10] partner repository with the dataset identifier PXD039943 and 10.6019/PXD039943.
## 2.9. GO Analysis
The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING 10.5) database [11] was used to identify enriched Gene Ontology (GO) terms in the biological process, molecular function, or cellular component categories, as previously described [12]. The enrichment function of STRING, which calculates an enrichment p value based on a hypergeometric test using the method of Benjamini and Hochberg for correction of multiple testing (p value cut-off < 0.05), was used.
## 2.10. Mass Spectrometry-Based Quantification of PCYOX1
Tryptic peptides (0.5 μg/uL), obtained as described above, were added with the stable isotope labelled proteotipic PCYOX1 peptide (CPSIILHD(R) from Thermofisher Scientific (Milan, Italy), desalted with ZipTip C18 (Millipore, Burlington, MA, USA) according to the manufacturer’s instruction, and then dissolved in water with $0.1\%$ formic acid before mass spectrometry analysis. Two microliters of each sample, containing 10 fmol/μL of labelled heavy peptide, were injected into a Xevo TQ-S micro triple quadrupole mass spectrometer coupled to a Waters ACQUITY ultra-performance liquid chromatography (UPLC) M-Class system through an ionKey source (Waters Corporation, Milford, MA, USA), and analysed as previously described [13].
## 2.11. Mice and Diets
Pcyox1−/− mice were bred with Apoe−/− mice (B6.129P2-Apoetm1Unc/J, stock 002052, JAX™ Mice Strain) as previously described [4]. Intercrosses of resulting Apoe−/−/Pcyox1+/− mice generated offspring that entered the study. All procedures were approved by the Institutional Animal Care and Ethics Committee of the University of Milan and by the Ministry of Health DGSAF (N. 782-2020; approval 10 August 2020). Mice were housed in an air-conditioned room at 22 ± 0.5 °C with a 12-h lighting cycle and free access to food and water. For experiments, double knockout mice (Pcyox1−/−/Apoe−/−) and control mice (Pcyox1+/+/Apoe−/−) were fed ad libitum with a high fat diet (HFD) containing $0.2\%$ cholesterol, $21.2\%$ fat ($42\%$ kcal), and $17.5\%$ protein by weight (Teklad diet TD.88137; Envigo, Milan, Italy), starting at 11 weeks of age and continuing for 8 or 12 weeks. After the indicated period of HFD, mice were anesthetized by intraperitoneal injection of ketamine hydrochloride (75 mg/kg) and medetomidine (1 mg/kg) prior to visceral fat harvest. Abdominal visceral adipose tissue (VAT) was rapidly removed, weighed, and snap frozen for RNA and mass spectrometry analyses. Each experimental session included animals of both genotypes (Pcyox+/+/Apoe−/− $$n = 23$$; Pcyox−/−/Apoe−/− $$n = 19$$), with animals being assigned to the experimental groups according to genotype, and with the investigators blinded to group assignment during all experimental stages and when evaluating outcome measures.
## 2.12. Statistical Analysis
Data analysis was performed with GraphPad Prism 9.3 software (GraphPad Software Inc., San Diego, CA, USA). All data sets were tested for normality of distribution and analysed using the Student t test or analysis of variance (ANOVA) for multiple comparison followed by Dunnett’s or Tukey’s post hoc test as indicated. Statistical significance level was accepted at $p \leq 0.05.$
## 3.1. Pcyox1−/− Mice Have Decreased Adiposity
Pcyox1−/−/Apoe−/− mice fed an HFD for 8 or 12 weeks showed $16.3\%$ and $20.2\%$ lower body weight, respectively, when compared to Pcyox1+/+/Apoe−/− mice (Figure 1A), due to a $40\%$ and $52.5\%$ reduction in visceral adipose content (Figure 1B), thus confirming preliminary observations [4]. Pcyox1 mRNA and protein, measured by quantitative mass spectrometry, were both present in the VAT of Pcyox1+/+/Apoe−/− mice fed an HFD for 8 weeks (Figure 1C,D). As previously demonstrated, serum analysis in Pcyox1−/−/Apoe−/− mice showed significantly decreased triglycerides, free fatty acid, and cholesterol concentrations, without any effects attributable to differences in food intake [4]. Overall, these data suggest that PCYOX1 may play a role in promoting in vivo adipogenesis. To address this, we explored the role of PCYOX1 in adipogenesis in in vitro differentiating cells.
## 3.2. PCYOX1 Expression Is Induced during Adipocyte Differentiation In Vitro
Pcyox1 mRNA expression is significantly increased when 3T3-L1 are fully differentiated to adipocyte-like cells after 9 days from the beginning of the differentiation protocol (Figure 2A). This occurs concomitantly with a rising expression of Pparg, a nuclear receptor critically involved in adipocyte differentiation, and Fabp4, a downstream target of PPARγ, which is a terminal marker of adipocyte differentiation (Figure 2B,C).
To explore the determinants of PCYOX1 induction during adipogenesis, we analysed the effects of the three components of the cocktail used to induce differentiation: insulin, dexamethasone (DEX), and the phosphodiesterase inhibitor 3-isobutyl-1-methylxanthine (IBMX). Insulin minimally perturbed Pcyox1 expression (Figure 3A), whereas IBMX and dexamethasone strongly increased *Pcyox1* gene expression (Figure 3B,C). Because IBMX and DEX are each necessary for maximal and sustained expression of the pro-adipogenic transcription factor CCAAT/enhancer binding protein β (C/EBPβ) [14], we evaluate its mRNA modulation in the initial stages of differentiation (Figure 3D).
## 3.3. PCYOX1 Is Critical for Adipogenesis In Vitro
To examine the role of PCYOX1 in adipogenesis, short-hairpin shRNA retroviral constructs targeting three regions of the Pcyox1 mRNA were generated, and stably transfected into 3T3-L1 preadipocytes. The control and knockdown cell lines were then induced to differentiate for 9 days. Before the induction of differentiation, Pcyox1 mRNA levels were reduced in silenced cells (−92.8 ± $1.1\%$ with respect to control cells, $$n = 5$$, $p \leq 0.001$), and remained significantly reduced until day 9 (−86.4 ± $2.5\%$, $$n = 8$$, $p \leq 0.001$ versus control cells). Similarly, treatment of 3T3-L1 cells with the Pcyox1 shRNA reduced endogenous PCYOX1 protein levels by 79.1 ± $6\%$, as assessed by mass spectrometry ($$n = 3$$; $p \leq 0.0002$). The shPcyox1-treated 3T3-L1 were also examined for their ability to differentiate into adipocytes compared to control cells. In response to adipogenic inducers, control cells underwent efficient morphological differentiation into lipid droplet-containing adipocytes. By contrast, Pcyox1-depleted 3T3-L1 preadipocytes accumulated fewer lipid droplets when induced to undergo differentiation (Figure 4A).
The mRNA expression of Fabp4, a terminal marker of adipogenesis (Figure 4B), was found to be significantly reduced in Pcyox1-silenced cells compared to control cells at the end of differentiation.
To identify the developmental stage regulated by PCYOX1, we harvested control and Pcyox1-depleted 3T3-L1 cells at 0, 1, and 9 days after the addition of adipogenic inducers in order to evaluate the expression of known transcriptional factors involved in adipogenesis. Pparg (Figure 4C) and Cebpa (Figure 4D) were significantly lower in Pcyox1-silenced cells compared to controls at day 9. Importantly, the earlier induction of Cebpb was unaffected by the loss of PCYOX1 in 3T3-L1 cells, being induced to the same extent in control and Pcyox1-silenced cells 24 h after the addition of the adipogenic cocktail (Figure 4E), suggesting that PCYOX1 acts downstream of C/EBPβ to promote the adipogenic program.
To assess whether C/EBPβ can directly regulate PCYOX1, we silenced cells for Cebpb. Although there was a significantly lower expression of Cebpb (−54 ± $6\%$ in silenced cells with respect to control cells treated with a negative construct, $$n = 3$$, $p \leq 0.002$) and the known C/EBPβ downstream targets Pparg and Cebpa, Pcyox1 expression was unaffected (Figure 5).
## 3.4. The Effects of PCYOX1 in Adipogenesis Are Independent of Its Pro-Oxidant Activity
We previously demonstrated that PCYOX1 is able to generate H2O2, which in turn induces the formation of oxLDL [4], a known activator of PPARγ because a variety of oxLDL components act as PPARγ ligands [15]. Therefore, we assessed whether PCYOX1 could induce the formation of oxLDL during adipogenesis. First, we measured PCYOX1 activity in control and Pcyox1-silenced cells, in comparison with CHO cells overexpressing PCYOX1. The results obtained indicated that, in differentiated adipocytes, PCYOX1 is expressed but is not active (1.4 pmol H2O2/µg protein in CHO cells overexpressing PCYOX1, undetectable in differentiated adipocytes, $$n = 3$$). Furthermore, the levels of oxLDL, as assessed by immunoenzymatic assay, were not different between control cells and Pcyox1-silenced cells (1.1 ± 0.3 ng/mL and 1.0 ± 0.2 ng/mL, respectively, $$n = 6$$).
## 3.5. PCYOX1 Significantly Affects the Cell Proteome
The impact of PCYOX1 deletion on adipogenesis was further investigated by proteomics. Label-free quantitative mass spectrometry revealed that 43 proteins were significantly less abundant in the Pcyox1-deficient cells, and only two were more abundant in the Pcyox1-deficient cells compared to control cells (Table 1).
The GO analysis of proteins that were less abundant after Pcyox1 silencing (Figure 6 and Supplementary Table S3) revealed the enrichment of GO terms related to the lipid metabolic process ($$n = 18$$, $$p \leq 5.79$$e−10, i.e., hormone-sensitive lipase +(Lipe), fatty acid-binding protein (Fabp4), perilipin-1 (Plin1)), fatty acids β-oxidation ($$n = 7$$, $$p \leq 2.01$$e−8, i.e., enoyl-CoA hydratase), tricarboxylic acid cycle ($$n = 6$$, $$p \leq 4.21$$e−8, i.e., malate dehydrogenase 2, citrate synthase), gluconeogenesis ($$n = 3$$, $$p \leq 0.0069$$, i.e., glycerol-3-phosphate dehydrogenase), and oxidation reaction process ($$n = 26$$, $$p \leq 1.26$$e−20).
Furthermore, the results from the proteomic analysis were validated in independent experiments by assessing the mRNA levels of the less abundant proteins: hormone-sensitive lipase (Lipe), carbonic anhydrase 3 (Car3), perilipin-1 (Plin1), 1-acyl-sn-glycerol-3-phosphate acyltransferase (Agpat2), carboxylesterase (Ces1f), platelet glycoprotein 4 (Cd36), and glycerol-3-phosphate dehydrogenase (Gpd1) (Figure 7A–G).
We then evaluated gene expression in the VAT of mice fed an HFD for 8 weeks. As shown in Figure 8, Pcyox1 deficiency was associated with a significant reduction in the expression of the genes involved in adipogenesis, such as Cd36, Pparg, Lpl, and Ldlr (Figure 8).
To determine the effect of the ablation of Pcyox1 on adipose tissue inflammation, we examined the expression of inflammatory markers serum amiloyd A3 (SAA3), MAC2, CD11b, CD11c, and EMR1. All of them were decreased in the VAT of Pcyox1−/−/Apoe−/− mice versus Pcyox1+/+/Apoe−/− mice after 8 weeks on HFD (Figure 9).
## 4. Discussion
New treatments that directly target adipose tissue accumulation may be possible if we understand all the factors necessary for normal adipogenesis. To the list of these factors, we add PCYOX1 as a novel regulator of adipogenesis. Our results demonstrate that PCYOX1 is expressed in adipose tissue, and that its deficiency results in reduced fat deposits. In agreement with these findings, in vitro experiments revealed that PCYOX1 is necessary for adipogenesis. PCYOX1 first emerged at the end of the 1990s as a lysosomal enzyme involved in the catabolism of prenylated proteins acting as a flavin adenine dinucleotide (FAD)-dependent thioether oxidase able to generate a stoichiometric amount of H2O2 [5,16]. Afterwards, thanks to the advent of proteomics, the knowledge of PCYOX1 was extended to the finding that this protein belongs to the proteome of lipoproteins, in which it contributes to their oxidative modifications [17]. Furthermore, Pcyox1 silencing in vitro was found to affect the cellular proteome by influencing multiple functions related to inflammation, oxidative stress, and platelet adhesion [4,13]. We also showed that Pcyox1 deficiency in Apoe−/− mice on C57/BL6J background mice (B6.129P2-Apoetm1Unc/J) retards atheroprogression, is associated with decreased features of lesion vulnerability and lower levels of lipid peroxidation, and reduces plasma lipid levels and inflammation, thus highlighting for the first time the role of PCYOX1 in vivo. Indeed, the pioneering study of Beigneux et al. [ 18] showed the absence of any histologic abnormalities in a survey of >30 tissues from Pcyox1-deficient mice on a mixed C57BL/6-129/SvJae genetic background. The observation that Pcyox1 deficiency in Apoe−/− mice fed with HFD, a model of obesity-accelerated atherosclerosis accompanied by development of a metabolic syndrome phenotype [19], have less adipose tissue depots, led us to further investigate the role of PCYOX1 in adipogenesis.
The differentiation of preadipocytes into adipocytes is regulated by an elaborate network of transcription factors that coordinate the expression of hundreds of proteins responsible for establishing the mature fat-cell phenotype. At the center of this network are the two principal adipogenic factors, PPARγ and C/EBPα, which oversee the entire terminal differentiation process. PPARγ in particular is considered the master regulator of adipogenesis; without it, precursor cells are incapable of expressing any known aspect of the adipocyte phenotype [20].
We found that the knockdown of Pcyox1 in 3T3-L1 preadipocytes renders them defective in inducing markers of terminal differentiation such as C/EBPα, PPARγ, and FABP4 and in accumulating fat, suggesting that PCYOX1 plays a pivotal role during the early events of the process. In this process, we ruled out the reciprocal regulation between PCYOX1 and C/EBPβ, suggesting that PCYOX1 acts independently from this crucial transcription factor. In an attempt to define the sequence of events leading to terminal adipogenesis, it was proposed that C/EBPβ and C/EBPδ simultaneously control the expression of both PPARγ and C/EBPα. Alternatively, some investigators have suggested that C/EBPβ induces C/EBPα and that, together, these factors regulate PPARγ expression [21]. The precise role of C/EBPβ and C/EBPδ in regulating this cascade of factors has been questioned, however, in knockout mice. Specifically, Tanaka et al. [ 22] demonstrated that adipocyte differentiation in vitro proceeds according to the proposed transcriptional regulatory cascade in which adipogenic transcription factors such as C/EBP family members and PPARs are activated sequentially. However, in vivo, C/EBPα and PPARγ can be induced without expression of C/EBPβ and C/EBPδ. These data suggest that there is some redundancy in the early steps of adipogenesis in vivo where alternative pathways operate to ensure the expression of PPARγ and C/EBPα. Over the last few years, many studies suggested that many additional transcription factors are potential components of this complex network of factors responsible for inducing adipogenic gene expression [23,24,25]. It is likely that additional factors of parallel pathways are induced early and converge on PPARγ at a stage downstream of C/EBPβ and C/EBPδ [21,25].
The evidence that PCYOX1 generates H2O2, which in turn leads to the oxidative modifications of lipoproteins [4], suggested that it might be involved in the synthesis of PPARγ ligands. Indeed, it has been reported that oxLDL induces PPARγ activation, and that 9-hydroxyoctadecadienoic acid (9-HODE), 13-hydroxyoctadecadienoic acid (13-HODE), and oxidized phospholipids, which are components of oxLDL, are involved in oxLDL-induced PPARγ activation [15]. However, our findings excluded that PCYOX1 might contribute to the adipogenic process by providing a ligand for PPARγ, as far as oxLDL is concerned.
Furthermore, a peak of expression of PCYOX1 at later stages of 3T3-L1 differentiation highlights an additional role in terminal differentiation. Inactivation of Pcyox1 blocked the expression of several mediators involved in adipogenesis, including, among others, Perilipin-1 (Plin1), 1-acyl-sn-glycerol-3-phosphate acyltransferase beta (Agpat2), Carboxylesterase 1 (Ces1), Hormone-sensitive lipase (Lipe), and Carbonic anhydrase 3 (Car3).
Importantly, Perilipin-1 is abundantly expressed in mature adipocytes, phosphorylated in a cAMP-dependent manner, and localized to lipid droplet surfaces during differentiation of 3T3-L1 adipocytes into lipid-accumulating mature adipocytes. Plin1-knockout (KO) mice exhibited striking phenotypes [26,27], being lean, with microscopically reduced lipid droplet sizes in adipose tissues, increased glucose tolerance and resistance to diet-induced obesity [28]. In addition, the high lipolytic activities in the WAT of Plin1-KO mice prevent the accumulation of triglycerides, suggesting that Perilipin-1 exerts essential roles in lipid droplet formation and triglyceride metabolism in vivo.
Additionally, isoform 2 of the 1-acyl-sn-glycerol-3-phosphate acyltransferases (Agpat2) is a key enzyme involved in lipid synthesis, which is highly expressed in adipose tissue. It catalyses the acylation of lyso-phospatidic acid (LPA) to produce phosphatidic acid (PA), which will subsequently enter triglyceride or phospholipid synthesis. Cellular studies have supported that Agpat2 is necessary for adipocyte differentiation, suggesting that the absence of WAT in Agpat2 KO was the result of altered adipogenesis [29,30]. Furthermore, decreased levels of LPC in Agpat2 KO could lead to reduced synthesis of LPA, which has been previously shown to be a physiological PPARγ ligand [31].
Recent advances in research have shown the relevance of carboxylesterases to metabolic diseases such as obesity and fatty liver disease [32]. Expression of Ces1 was induced during 3T3-L1 adipocyte differentiation [33], and administration of Ces1 inhibitors to HFD fed mice or db/db mice protected from weight gain reduced plasma lipids, ameliorated liver steatosis, and improved glucose tolerance [34]. Furthermore, in the adipose tissue of obese and type 2 diabetic patients, the activity of Ces1 is elevated, which is consistent with other studies showing that Ces1 expression is higher in adipose tissue from obese patients compared to lean subjects [35,36].
Hormone-sensitive lipase (Lipe) is rate-limiting for diacylglycerol and cholesteryl ester hydrolysis in adipose tissue and essential for complete hormone-stimulated lipolysis [37]. Gene expression profiling in Lipe−/− mice suggests that it is important for modulating adipogenesis and adipose metabolism. In vitro studies showed that Lipe increases during differentiation [38], likely providing ligands for the activation of PPARγ.
PCYOX1 also modulates Car3, which belongs to the family of carbonic anhydrases, enzymes involved in the promotion of fatty acid synthesis in adipocytes and the liver [39]. Car3 is highly abundant in tissues that can store lipids [40,41], and increases in rodents fed Western-type high-fat diets [42], becoming one of the most abundant transcripts in both human [43] and rodent [44] adipose tissues, accounting for up to $2\%$ of the total mRNA. Moreover, Car3 constitutes the most abundant protein in mature adipocytes, comprising up to $24\%$ of the total soluble protein fraction [40].
Overall, the modulation of a plethora of genes involved in adipogenesis supports the hypothesis that PCYOX1 not only acts at early stages of adipogenesis, but also may account for the persistent expression of genes relevant for terminal adipogenic differentiation.
Importantly, PCYOX1 deficiency abrogated, in vitro and in vivo, the expression of CD36, a multifunctional immuno-metabolic receptor that is involved in many physiological and pathological processes [45]. Compared to wild-type mice, CD36 deficient mice with an HFD exhibited reduced adipose tissue inflammation, as evidenced by decreased pro-inflammatory cytokine levels in adipose tissue, and less macrophage and T-cell accumulation in adipose tissue [46,47].
Consistent with the role of PCYOX1 in the regulation of adipose tissue inflammation is the finding that SAA3, one of the members of the acute-phase proteins serum amyloid A family, is also downregulated in Pcyox1−/−/Apoe−/− mice. Furthermore, SAA3 has been recently utilized for monitoring the adipose inflammatory state, possibly serving as an index of the number of infiltrated macrophages in adipose tissue [48]. In support of this hypothesis, we also found that the macrophage markers Mac2, Cd11b, Cd11c, and Emr1 were all decreased in the adipose tissue of Pcyox1 deficient mice, thus substantiating the hypothesis of a crosstalk between adipocytes and infiltrated macrophages as an important pathological phenomenon leading to adipose tissue inflammation.
## 5. Conclusions
In summary, we report here that PCYOX1 is a novel regulator of adipogenesis, which acts upstream of known transcription factors and genes involved in lipogenesis, lipid droplet formation as well as lipid binding, and inflammation. These novel findings expand our knowledge on PCYOX1 biology and functions beyond its role in the metabolism of prenylated proteins [5,6,18,49]. Indeed, PCYOX1 is emerging as a multifunctional protein with a relevant role in atherogenesis by modulating lipid metabolism, inflammation and lipid peroxidation [4,17], in thrombosis by likely regulating circulating coagulant and inflammatory factors [13], and lastly, in adipogenesis. How PCYOX1 can modulate such different processes, which might not be restricted to its enzymatic pro-oxidant activity, is under investigation. Understanding the biology and mechanisms of all functions of this unique enzyme will help to provide additional therapeutic opportunities in addressing such conditions.
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|
---
title: Rosemary (Rosmarinus officinalis L.) Glycolic Extract Protects Liver Mitochondria
from Oxidative Damage and Prevents Acetaminophen-Induced Hepatotoxicity
authors:
- Natalia S. S. Guimarães
- Vyctória S. Ramos
- Laura F. L. Prado-Souza
- Rayssa M. Lopes
- Gabriel S. Arini
- Luís G. P. Feitosa
- Ricardo R. Silva
- Iseli L. Nantes
- Debora C. Damasceno
- Norberto P. Lopes
- Tiago Rodrigues
journal: Antioxidants
year: 2023
pmcid: PMC10045355
doi: 10.3390/antiox12030628
license: CC BY 4.0
---
# Rosemary (Rosmarinus officinalis L.) Glycolic Extract Protects Liver Mitochondria from Oxidative Damage and Prevents Acetaminophen-Induced Hepatotoxicity
## Abstract
Rosmarinus officinalis L. (rosemary) is an aromatic culinary herb. Native to the Mediterranean region, it is currently cultivated worldwide. In addition to its use as a condiment in food preparation and in teas, rosemary has been widely employed in folk medicine and cosmetics. Several beneficial effects have been described for rosemary, including antimicrobial and antioxidant activities. Here, we investigated the mechanisms accounting for the antioxidant activity of the glycolic extract of R. officinalis (Ro) in isolated rat liver mitochondria (RLM) under oxidative stress conditions. We also investigated its protective effect against acetaminophen-induced hepatotoxicity in vivo. A crude extract was obtained by fractionated percolation, using propylene glycol as a solvent due to its polarity and cosmeceutical compatibility. The quantification of substances with recognized antioxidant action revealed the presence of phenols and flavonoids. Dereplication studies carried out through LC-MS/MS and GC-MS, supported by The Global Natural Product Social Molecular Networking (GNPS) platform, annotated several phenolic compounds, confirming the previous observation. In accordance, Ro decreased the production of reactive oxygen species (ROS) elicited by Fe2+ or t-BOOH and inhibited the lipid peroxidation of mitochondrial membranes in a concentration-dependent manner in RLM. Such an effect was also observed in liposomes as membrane models. Ro also prevented the oxidation of mitochondrial protein thiol groups and reduced glutathione (GSH). In model systems, Ro exhibited a potent scavenger activity toward 2,2′-diphenyl-1-picrylhydrazyl (DPPH) radicals and superoxide anions. It also demonstrated an Fe2+ chelating activity. Moreover, Ro did not exhibit cytotoxicity or dissipate the mitochondrial membrane potential (∆Ψ) in rat liver fibroblasts (BRL3A cells). To evaluate whether such antioxidant protective activity observed in vitro could also be achieved in vivo, a well-established model of hepatotoxicity induced by acute exposure to acetaminophen (AAP) was used. This model depletes GSH and promotes oxidative-stress-mediated tissue damage. The treatment of rats with $0.05\%$ Ro, administered intraperitoneally for four days, resulted in inhibition of AAP-induced lipid peroxidation of the liver and the prevention of hepatotoxicity, maintaining alanine and aspartate aminotransferase (ALT/AST) levels equal to those of the normal, non-treated rats. Together, these findings highlight the potent antioxidant activity of rosemary, which is able to protect mitochondria from oxidative damage in vitro, and effects such as the antioxidant and hepatoprotective effects observed in vivo.
## 1. Introduction
The Lamiaceae family contains a set of plants, often cultivated as herbs, whose leaves can be used as seasonings and whose essential oils are used as flavors in cosmeceuticals [1]. Among these plants, *Rosmarinus officinalis* L. stands out. Popularly known as rosemary (or alecrim in Brazil), R. officinalis is native to the Mediterranean region and is currently found worldwide. It has been extensively studied for its use in food and as a spice and/or preservative, in which it operates by inhibiting microbial growth and oxidative reactions [2]. The study of medicinal plants and herbs has proved to be an efficient strategy for prospecting novel compounds with therapeutic potential [3,4]. In this regard, a large number of secondary metabolites have been isolated and identified from Rosmarinus spp., including essential oils, flavonoids, tannins, terpenes, and phenolic acids [5,6,7]. In addition, carnosol, carnosic acid, and rosmarinic acids, which are reported to be the main components of rosemary, account for many of its biological activities [8,9,10]. The production of these bioactive secondary metabolites by rosemary depends on several factors, such as the plant part, climatic conditions and soil nutrients, humidity, temperature, water availability, and others [11]. Due to the large number of chemical studies carried out on R. officinalis, we opted for a dereplication strategy to avoid re-isolations [12]. Hyphenated liquid chromatography with electrospray ionization mass spectrometry (LC-ESI-MS/MS) is currently the most suitable technique for metabolomics approaches [13]. However, when analyzing extracts with an antioxidative potential, it is important to follow the oxidation processes at the source of the ESI in detail since substances with a low oxidation potential can lose electrons, changing the expected mass balance and leading to erroneous interpretations of chemical structures [14,15].
Furthermore, R. officinalis has long been used as a medicinal plant. In this context, a plethora of biological effects and health benefits have been attributed to rosemary essential oil, leaf extracts, and isolated substances, including antibacterial [16,17,18], antifungal [19,20], anti-inflammatory [21,22], antiatherogenic [23,24], antiangiogenic [25,26], antihypertensive [27], antiulcer [28], anti-diabetic [29,30], anticancer [31], and other effects (reviewed elsewhere [32,33]). In addition to these effects, this plant is also well known for its powerful antioxidant activity (reviewed in [34]). This is expected, as phytochemical analyses of rosemary extracts and essential oils have revealed several substances with recognized antioxidant properties, such as flavonoids and phenolic compounds [35,36]. In fact, such antioxidant activities of R. officinalis might help to explain some of the biological effects described above. The pathophysiology of several human diseases is related to the overproduction of reactive oxygen species (ROS) or a decreased capacity of the antioxidant defense system, resulting in oxidative stress, cellular/tissue damage, and, ultimately, organ dysfunction [37]. In this regard, it has been shown that R. officinalis exhibits hepatoprotective effects in different models of xenobiotic-induced liver toxicity, including carbon tetrachloride (CCl4) [38,39,40,41], creosote [38], azathioprine [39], hexavalent chromium [40], streptozotocin [41], and cyclophosphamide [42]. However, its protective effect against acetaminophen-induced hepatotoxicity has not been clearly demonstrated yet. Acetaminophen (AAP) is an anti-inflammatory and anti-pyretic drug, and AAP overdose is associated with acute liver failure [43]. During cytochrome P450 liver metabolism, AAP is transformed in the highly reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI), which oxidizes GSH [44] and causes oxidative stress.
Although the antioxidant activity of R. officinalis has been extensively studied in several biological systems and toxicity models, its potential protective effect on mitochondria under oxidative stress conditions has not been investigated. Despite the central role they play in cellular metabolism and energy production, mitochondria are also often associated with oxidative status since superoxide radical anions (O2•−) are continuously generated during electron transport in the respiratory chain. This radical is counteracted by the antioxidant defense system, with the reducing power provided by reduced glutathione (GSH) and NAD(P)H [45]. However, excessive O2•− formation and, consequently, its conversion to hydrogen peroxide (H2O2), can produce the extremely reactive hydroxyl radical (•OH) by means of the Fenton reactions, which are catalyzed by Fe2+ and other transition metals [46]. Thus, the investigation of the effects of R. officinalis in such a complex mitochondrial scenario can further elucidate the molecular mechanisms of antioxidant protection in biological systems. Here, we investigated the antioxidant properties of R. officinalis leaf extracts in rat liver mitochondria and addressed its protective effect against AAP-induced hepatotoxicity in rats.
## 2.1. Chemicals, Plant Source, and Extract Preparation
All reagents used in this study were of the highest commercially available grade of purity. Aqueous solutions were prepared using type I water obtained using a Milli-Q system (Millipore, USA). Rosmarinus officinalis L. species were collected in Brazil (GPS localization: 760 m, 23°29840′ S) during the winter (August) of 2018. After botanical identification, voucher specimens were deposited at the Herbarium Mogiense (University of Mogi das Cruzes, Brazil). After drying at 40 °C in a ventilated drying oven, 100 g of selected leaves were submitted to fractionated percolation using a mixture of propylene glycol/water ($\frac{7}{3}$) as solvent, resulting in 100 mL of *Rosmarinus officinalis* glycolic extract (Ro). This extract was considered a $100\%$ crude extract for subsequent concentration calculations.
## 2.2. Isolation of Mitochondria, Animal Treatments, and Sample Preparation
Liver mitochondria were isolated from rats by differential centrifugation in isosmotic media, as previously described [47]. Adult male Wistar rats weighing approximately 180 g were randomly divided into four groups ($$n = 7$$), kept in a $\frac{12}{12}$ h light/dark cycle, and fed ad libitum. All experiments involving animals were conducted in accordance with the guide for the care and use of laboratory animals (NIH Guidelines) and were previously approved by the Animal Ethics Committee of University of Mogi das Cruzes (CEUA). In order to induce hepatotoxicity, the AAP group received a single dose of 900 mg/kg of acetaminophen (Sigma-Aldrich, St. Louis, MI, USA) intraperitoneally. Animals were sacrificed 4 h after drug administration. The control group (C) received the same volume of solvent used for AAP dissolution, i.e., dimethyl sulfoxide (DMSO; Sigma-Aldrich, USA). The other two groups received 0.1 mL of $0.5\%$ Ro intraperitoneally once per day in the morning for four consecutive days. One of these groups (Ro/AAP) also received AAP on the last day, as described above, 4 h before sacrifice. The animals were anesthetized with xylazine (5 mg/kg) and ketamine (60 mg/kg) for cardiac blood collection. The blood was immediately centrifuged at 700× g for 5 min to achieve serum separation. For homogenate preparation, the livers were removed and cut into small fragments in a buffer containing 250 mmol/L sucrose, 1 mmol/L EGTA, and HEPES- KOH 10 mmol/L at a pH of 7.4 at 4 °C. After washing the samples twice with the same medium, the tissues were homogenized using a Potter-Elvehjem. This was followed by centrifugation at 580× g for 5 min at 4 °C. The supernatant, called a homogenate, was immediately frozen at −70 °C for subsequent experiments.
## 2.3. Preparation of PCPECL Liposomes
The phospholipids phosphatidylcholine, phosphatidylethanolamine, and cardiolipin (PCPECL, 5:3:2 ratio) were dissolved in CHCl3, which was further evaporated under argon flux. The lipidic film was hydrated with 10 mM of cold sodium phosphate buffer at a pH of 7.4 and vortexed. To obtain the liposome solution (1 mM), lipids were submitted to sonication for 30 min at 4 °C using a Ney Ultrasonik (J. M. Ney Co., Bloomfield, CT, USA).
## 2.4. Total Phenols and Flavonoids
The soluble phenol derivatives were estimated using the Folin–Ciocalteu method [48] and expressed as μM of gallic acid equivalents based on a standard curve [49]. For flavonoid quantification, an aliquot was incubated in a medium containing 60 μL of glacial acetic acid, 1.0 mL of pyridine H2O:AlCl3 $12\%$ solution (17:80:3), and 1.24 mL of DMSO:H2O (1:1) for 5 min at 25 °C. The absorbance of the chromophore produced in this reaction was determined spectrophotometrically at 420 nm, and the flavonoid content was determined based on a standard curve and expressed as µM of quercetin equivalents.
## 2.5. DPPH Assay, Fe2+, and Superoxide Scavenger Activity
The reduction of the 1,1′-diphenyl-2-picrylhydrazyl radical (DPPH, Sigma-Aldrich, USA) by Ro was accompanied by photometric measurement in a UV1800 spectrophotometer (Shimadzu, Kyoto, Japan). An amount of 1.5 mL of 40 mM sodium acetate pH 5.5 was mixed into the reaction with 1.0 mL of absolute ethanol containing DPPH to achieve a final concentration of 0.1 mM. After incubation with different Ro concentrations for 5 min at 25 °C, the final absorbance was measured at 517 nm. Quercetin (Q, Sigma-Aldrich, USA) was used as reference. The amount of Fe2+ was quantified photometrically at 535 nm using 0.2 mM bathophenanthroline disulfonic acid (Sigma-Aldrich, USA) [50] in a competitive assay with Ro. At last, the xanthine/xanthine oxidase system was used to generate O2•−. The scavenger activity of Ro was estimated by the inhibition of the nitroblue tetrazolium (NBT, Sigma-Aldrich, USA) reduction. After adding 0.08 U/mL xanthine oxidase to a phosphate buffer at a pH of 7.5, which contained 0.05 mM EDTA, 0.2 mM hypoxanthine, and 0.1 mM NBT, the absorbance was measured at 540 nm after 20 min of incubation at 37 °C (Shimadzu UV1800 Spectrophotometer, Tokyo, Japan).
## 2.6. Reactive Oxygen Species (ROS)
The production of mitochondrial ROS was estimated kinetically using 2′,7′-dichlorodihydrofluorescein diacetate (H2DCFDA, Sigma-Aldrich, USA) [51], as previously described [52]. Briefly, mitochondria (1 mg/mL) were incubated in a buffer containing 125 mM sucrose, 65 mM KCl, and 10 mM HEPES-KOH at a pH of 7.4, plus 1 µM H2DCFDA at 30 °C, under continuous stirring in the presence of 5 mM potassium succinate (Sigma-Aldrich, USA) (plus 2 μM rotenone, Sigma-Aldrich, USA). The fluorescence emissions were recorded in a Hitachi F-2500 Spectrophotometer (Tokyo, Japan) at $\frac{503}{529}$ nm for excitation/emission wavelength pairs, respectively.
## 2.7. Lipid Oxidation
The liposomes (1 mM), mitochondria (1 mg/mL), or liver homogenates (1 mg/mL) were incubated with or without different Ro concentrations at 37 °C for 30 min, and with 50 μM Fe(NH4)2(SO)4 (plus 2.0 mM sodium citrate) or 0.6 mM t-BOOH as inducers of oxidative stress. Following incubation, for a thiobarbituric acid reactive substances (TBARS) assay, $1\%$ thiobarbituric acid (TBA, Sigma-Aldrich, USA) was prepared by adding 50 mM NaOH, 15 μL of 10 M NaOH, and 75 μL of $20\%$ H3PO4 to each sample, followed by further incubation for 20 min at 85 °C. The MDA-TBA complex was extracted with 2 mL of n-butanol, and the absorbance was measured at 535 nm. The TBARS were calculated from ε = 1.56 × 105 M−1.cm−1, as described in [53]. Lipid hydroperoxides (LOOH) were also quantified in isolated mitochondria using xylenol orange, as previously described in [54]. When applied, the percentages of inhibition by Ro were calculated in relation to positive controls (t-BOOH or Fe2+) which were considered to achieve $100\%$ inhibition.
## 2.8. GSH and Protein Thiol Groups
After 30 min of incubation at 37 °C in a medium containing 125 mM sucrose, 65 mM KCl, and 10 mM HEPES-KOH at a pH of 7.4, plus 5.0 mM potassium succinate and 2.0 μM rotenone, the mitochondrial suspensions or liver homogenates were treated with 0.5 mL of $13\%$ trichloroacetic acid and centrifuged at 400× g for 5 min. For the GSH assay, aliquots (100 µL) of the supernatant were mixed with 1.8 mL of a 0.1 M sodium phosphate buffer at a pH of 8.0 containing 5 mM EGTA plus 100 μL of 1 mg/mL o-phthalaldehyde (Sigma-Aldrich, USA). After 15 min of incubation, the fluorescence emissions were detected at $\frac{350}{420}$ nm (excitation/emission) in a Hitachi F-2500 (Japan) fluorescence spectrophotometer [55]. The reduced thiol groups of proteins were quantified using 5,5′-dithiobis(2-nitrobenzoic acid) (DTNB, Sigma-Aldrich, USA) [56]. The pellet obtained from the acid precipitation described above was suspended with 1 mL of a 0.5 M potassium phosphate buffer at a pH of 7.6 which contained $0.7\%$ SDS. After adding 100 μM DTNB, the absorbance was measured at 412 nm and the amount of the reduced thiol groups was calculated from ε = 13,600 M−1.cm−1 [57].
## 2.9. Cell Culture and Cellular Assays
BRL 3A cells (CRL-1442, ATCC) were cultivated in high-glucose Dulbecco’s modified Eagle’s medium (DMEM; Sigma-Aldrich, USA) supplemented with $10\%$ fetal bovine serum (FBS) (Gibco, Thermo Fischer Scientific, Waltham, MA, USA), 100 U/mL penicillin, and 100 μg/mL streptomycin at 37 °C in a $5\%$ CO2 atmosphere (Panasonic MCO-19AIC incubator, Osaka, Japan). Cells were used for the experiments during 4–8 passages after thawing. For the experiments, cells were washed twice with a calcium- and magnesium-free buffered saline solution (CMF-BSS), detached from the flasks using trypsin/EDTA (Gibco, Thermo Fischer Scientific, USA), and suspended in the supplemented medium. For the viability assay, cells (5 × 104 cells/cm2) were added to 96-well microplates (0.2 mL final volume) and incubated with different concentrations of Ro for 24 h. After adding 0.25 mg/mL MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide] (Sigma-Aldrich, USA), 4 h of incubation, and the solubilization of formazan crystals, the absorbance of each well was measured at 570 nm in a Biotek ELX 800 microplate reader (BioTek Instruments, Winooski, VT, USA). Cell viability was determined relative to the control (absence of Ro), which was considered to have a $100\%$ viability [58]. The mitochondrial transmembrane potential in the BRL 3A cells was estimated using fluorescence microscopy. Cells (5 × 104 cells/cm2) were seeded in 3.5 cm glass dishes (with a 0.17 mm thick cover glass on the bottom (Greiner Bio-One, Frickenhausen, Germany) and loaded with 40 nM DiOC6[3] (Thermo Fisher Scientific, USA) and 5 nM Hoechst 33258 (Thermo Fisher Scientific, USA) with incubation at 37 °C for 30 min. Images were acquired in a widefield Leica AF6000 microscope (Leica Microsystems, Wetzlar, Germany), using the HCX APO UVI 100×/1.3 oil plan apochromatic objective and the ultrafast Leica DFC365 FX monochromatic digital camera (Leica Microsystems, Germany). The set of cube filters used included A4 (ex $\frac{360}{40}$, DC 400 nm, em $\frac{470}{40}$) and L5 (ex $\frac{480}{40}$, DC 505, em $\frac{527}{30}$) (Leica Microsystems, Germany) filters.
## 2.10. Blood Biochemical Analyses
Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were determined in serum using commercial kits according to the manufacturer’s instructions (LABTEST, Lagoa Santa, MG, Brazil).
## 2.11. Untargeted Metabolomics Analysis by HPLC-ESI-MS/MS
An HPLC-MS analysis was performed in a Shimadzu UFLC system coupled to a quadrupole time-of-flight mass spectrometer (micrOTOF QII, Bruker Daltonics, Billerica, MA, USA) using a C18 column (5 µm, XB-C18 Kinetex, 100Å, 150 × 3 mm, Phenomenex). The mobile phase was composed of water (A) and MeOH (B), both with $0.1\%$ formic acid, at a flow rate of 0.75 mL.min−1. The following gradient was employed: 0–23 min, 10–$100\%$ B; 23–26 min, $100\%$ B; 26–27 min, 100–$10\%$ B; and 27–30 min, $10\%$ B. The column oven was set to 45 °C, and an injection volume of 10 µL was selected. Chromatograms were acquired in both positive and negative ionization modes, and the following parameters were employed for the mass spectrometer: end plate offset, 500 V; capillary voltage, 3200 V for negative mode and 3500 V for positive mode; nebulizer pressure, 4.5 bar; dry gas (N2) flow, 9 L.min−1; dry temperature, 200 °C; mass range, m/z 150 to 1200; MS/MS scan mode; number of precursors, 3; exclusion activation, 1 spectrum; and exclusion release, 36 s.
## 2.12. Gas Chromatography-Mass Spectrometry (GC-MS) Analysis
The glycolic extract was submitted to a head space analysis, and the GC-MS methodology was based on the previously reported methodology [59]. The analysis was carried out on the GCMS-QP2010 (Schimadzu, Japan) according to the following parameters: injector temperature, 250 °C; column temperature, 60 °C; heating ramp from 60 to 210 °C, at 3 °C/min, with a total time of 50 min; chromatographic column, DB-5, 30 m × 0.25 mm in diameter, 0.25 μm in thickness; and helium was used as the carrier gas under 79.7 kPa at 1.30 mL/min with a linear velocity of 41.6 cm/s, a 1 μL injection volume, and a 1:60 split.
## 2.13. Statistical Analyses
Quantitative data are presented as the mean ± SD of (at least) three independent experiments performed in triplicate. For multiple comparisons, a one-way ANOVA was used, followed by Tukey’s post hoc test. The Prism 8.0 software (GraphPad Software Inc., La Jolla, CA, USA) was used to perform the data analyses. Statistical significance was defined as * ($p \leq 0.05$), ** ($p \leq 0.01$), and *** ($p \leq 0.001$).
## 3.1. Rosmarinus officinalis Glycolic Extract (Ro) Protects Mitochondrial Lipids and Proteins from Oxidation
The production of mitochondrial ROS was evaluated through the kinetic measurement of dichlorofluorescein (DCF) fluorescence. When incubated with t-BOOH or Fe2+, isolated rat liver mitochondria energized by succinate immediately increased the production of ROS. Due to the nature of the oxidative stress inducer, it was possible to observe that the fluorescence increase rate was faster for the Fe2+ (Figure 1B, black line) than for the t-BOOH (Figure 1A, red line). The preincubation of the mitochondrial suspension with Ro abolished the ROS production triggered by both inducers in a concentration-dependent manner. These effects were translated into the protection of mitochondrial membranes from oxidation by Fe2+ (squares, orange) or t-BOOH (circles, red), estimated by TBARS (Figure 1C). Moreover, the formation of Fe2+-induced lipid hydroperoxides was inhibited by Ro at $0.025\%$ (orange) and $0.05\%$ (red) (Figure 1D). Such a lipid protective action exhibited by Ro was accompanied by the prevention of GSH oxidation by t-BOOH (Figure 1E) and the oxidation of reduced thiol groups of mitochondrial proteins by both t-BOOH (Figure 1F) and Fe2+ (Figure 1G) at the same concentrations.
Together, these results indicate the ability of Ro to protect mitochondria (and possibly cells) from oxidative damage, highlighting its potential to prevent pathological conditions and diseases associated with oxidative stress.
## 3.2. Iron (II) Chelating and Free Radical Scavenger Activity Account to the Antioxidant Protection Exhibited by Ro
The quantification of total phenols and flavonoids, substances with recognized antioxidant action, are presented in Table 1. In an attempt to provide further mechanistical insights regarding the antioxidant capacity of Ro, its ability to chelate Fe2+, which is used here as inducer of oxidative stress, was investigated. In a competitive spectrophotometric assay using bathophenanthroline, Ro chelated more than $75\%$ of the available Fe2+, even at a lower concentration (Figure 2A). This may help to explain, at least partially, the protective effects observed in the Figure 1. Additionally, the free radical scavenger activity of Ro was investigated. As observed in Figure 2B, Ro reduced (scavenged) DPPH radicals in a concentration-dependent manner. At $0.025\%$, the effect was similar to 10 μM quercetin, a well-studied flavonoid known for its free radical scavenger activity and antioxidant properties [60]. Since DPPH is not a biological free radical, we also investigated the ability of Ro to scavenge O2•− generated by the xanthine/xanthine oxidase system, using NBT as indicator [61]. Ro exhibited significant O2•− scavenger activity at 0.05 and $0.01\%$, evaluated by the inhibition of NBT reduction by this radical. Finally, using a lipidic model system to mimic mitochondrial membranes [62], i.e., unsaturated PCPECL liposomes, it was possible to demonstrate that Ro prevents Fe2+-induced lipid oxidation regardless of mitochondrial function or a dependence on mitochondrial constituents. Thus, the ability to scavenge free radicals and to block lipid peroxidation reactions contributed to Ro’s antioxidant activity and to the protective effects observed in mitochondria (Figure 1).
## 3.3. Ro Does Not Affect Viability or Mitochondrial Membrane Potential (∆Ψ) of Liver Fibroblasts
To strengthen the pharmacological potential of Ro, its cytotoxicity was evaluated in vitro. This is relevant since many antioxidant substances also have a cytotoxic effect [63] which can hinder their therapeutic potential. In this regard, the possible cytotoxicity of Ro was investigated in cultured BRL 3A cells, a fibroblast-like cell line isolated from rat livers. Cell viability, evaluated by the MTT assay, was not affected by Ro in the concentration range tested (0.005–$0.05\%$), i.e., the incubation of Ro with BRL3A cells for 24 h did not decrease cell viability compared to the control (Figure 3A). These results were confirmed by the Trypan blue exclusion assay (Figure 3B). Moreover, Ro did not alter the ∆Ψ of BRL 3A cells assessed by fluorescence microscopy using DiOC6[3] (Figure 3C(b),D, red bar). As a control, the total ∆Ψ dissipation was achieved by adding CCCP, an uncoupler of the OXPHOS (Figure 3C(c),D, white bar).
## 3.4. Ro Protection against Acetaminophen-Induced Hepatotoxicity in Rats
The antioxidant activity of Ro, its effect in protecting isolated rat liver mitochondria from oxidative stress conditions, and its absence of cytotoxicity in vitro led us to investigate whether such protective effects can be observed in vivo. To this end, a well-established and clinically relevant model of oxidative-stress-mediated hepatotoxicity was selected. The acute exposure to high doses of AAP generates radical intermediates during its hepatic metabolism, depleting antioxidant defenses and resulting in oxidative tissue damage [43]. To establish the experimental model, a single dose of AAP (900 mg/kg) was administrated to the rats, which were or were not treated with $0.5\%$ Ro, and the blood levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were analyzed. This high dose of AAP is well established in the literature to induce acute hepatotoxicity in mice and rats [64,65]. As expected, AAP administration increased serum levels of ALT (Figure 4A, black bar) and AST (Figure 4B, black bar), indicating the occurrence of liver injury. As a control, Ro alone did not exert any effect on ALT or AST levels (orange bars, Figure 4A,B, respectively) compared to the basal levels, i.e., control, non-treated rats (white bars, Figure 4A,B), indicating the absence of an intrinsic hepatotoxicity of the extract.
Such a hepatotoxic effect of AAP was accompanied by GSH consumption (Figure 4C, black bar) and increased lipid oxidation (Figure 4D, black bar) without affecting the reduced thiol levels of proteins (Figure 4E, black bar). Interestingly, the treatment of animals with $0.5\%$ Ro was able to reestablish the basal levels of ALT and AST in AAP-treated animals (red bars, Figure 4A,B, respectively), indicating a complete restoration of the liver integrity against the AAP-induced toxicity. We then further investigated whether this effect was accompanied by an improvement in oxidative stress indicators. In AAP-treated rats, Ro partially inhibited GSH oxidation (Figure 4C, red bar) and completely prevented lipid oxidation (Figure 4D, red bar) without an effect on the redox state of the protein thiol groups (Figure 4E, red bar). It is noteworthy that Ro diminished even the basal lipid oxidation (Figure 4D, orange bar).
## 3.5. Chemical Composition of Rosmarinus officinalis L. Glycolic Extract
In order to gain more information about the chemical composition of Ro, we conducted an untargeted metabolomics analysis of the glycolic extract at both positive and negative ionization modes. The annotated metabolites are shown in Figure 5/Table 2 and the ion intensity of each metabolite are presented in Figure 6. As expected, several phenolic compounds already described for this plant were detected [36], e.g., caffeic acid, rosmanol, and rosmarinic and carnosinic acids. All metabolites had their annotations confirmed through a detailed discussion of the decomposition reactions in the gaseous phase [66], following the correlation with the literature recently proposed by Pilon and collaborators [67] for the analysis of glycosylated flavonoids.
## 4. Discussion
The wide range of biological actions reported for R. officinalis has long drawn the attention of researchers worldwide. In this study, for the first time, we showed that the antioxidant activity exhibited by rosemary extract and its chemical constituents is able to protect mitochondria subject to oxidative stress conditions. During the electron transport by the respiratory chain, mitochondria generate superoxide anions that are converted to hydrogen peroxide (H2O2). In the presence of Fe2+, H2O2 is converted to hydroxyl radicals, and these species are able to oxidize mitochondrial lipids and proteins, compromising energy production and Ca2+ homeostasis and culminating in cell death [46,72]. Thus, we used this complex system to evaluate the antioxidant potential of the glycolic extract of R. officinalis (Ro). Two different methods of inducing oxidative stress were used: Fe2+ and t-butyl hydroperoxide (t-BOOH). The former is able to catalyze Fenton reactions, amplifying the production of reactive oxygen species (ROS). and the latter is an organic peroxide that per se consumes antioxidant defenses to be eliminated, exposing cells to oxidative damage [45,46]. In both situations, Ro was able to inhibit ROS production and the oxidation of mitochondrial lipids and proteins. Previous studies have reported the ability of R. officinalis to inhibit the lipid peroxidation of phospholipids and membrane model systems [73,74,75], erythrocytes [76,77], low density lipoproteins (LDL) [78], and tissue homogenates [28].
Among the mechanisms of action for antioxidant activity, we found that Ro exhibits a free radical scavenger activity and the ability to chelate Fe2+. Most studies have used a DPPH assay to infer the scavenger activity of rosemary extracts and essential oils; however, it is noteworthy that DPPH is not a radical produced in biological systems. Therefore, we further examined and demonstrated the capacity of the rosemary leaf glycolic extract to scavenge superoxide anions. Such an ability was previously shown for diterpenoids isolated from R. officinalis [79], and it is subject to seasonal variations [80]. The essential oil of R. officinalis was also able to scavenge hydroxyl radicals and chelate Fe2+ [81]. These properties of R. officinalis extracts are provided by their high content of powerful, well-known, synergistically acting antioxidant compounds including flavonoids, phenolic acids, and terpenes. For example, the antioxidant activity exhibited by carnosol was linked to an enhanced health and lifespan in C. elegans, accompanied by an increase in the activity of several antioxidant enzymes and a decrease in TBARS content [82]. As expected, the phytochemical analysis of the glycolic extract of R. officinalis identified the presence of several phenolic compounds already described for this plant. It should be noted that chlorogenic acid, a common compound with significant antioxidant activity, was not observed in these samples. A recent study demonstrated that the concentration of chlorogenic acid varies greatly depending on the drying process used for the leaves [83], which may explain, in part, the absence of the signal. The polyphenolic profile of rosemary has been widely described in the scientific literature [70,84,85,86], and the profile observed in the glycolic extract of the R. officinalis employed in this study was characterized by the presence of carnosic acid, carnosol, rosmarinic acid, and hesperidin. The mechanism of action was related to the free radicals’ chain terminators and scavengers of ROS. On the other hand, compounds such as hesperidin are known for their ability to chelate metals. This confers a resistance to pests, as described in citrus [87], but can also support antioxidant properties. The occurrence of astragalin reinforces all the biological effects described in our article. This kaempferol 3-glucoside has several biological activities described, including antioxidant effects [88]. Therefore, the global analysis of the main metabolites contained in the extract support the observed activities. Finally, as expected, GC-MS exhibited a trace signal. The major compound detected was camphor, showing no contribution of the previous essential oil constituents to the described biological activities.
The antioxidant power of R. officinalis has been shown to be responsible for the plant’s protective effects against oxidative stress. Rosemary prevented the renal toxicity elicited by diethylnitrosamine [89] and potassium dichromate [90] by inhibiting lipid peroxidation and improving the capacity of the antioxidant enzymatic system. Potassium dichromate was also employed to induce hepatotoxicity in rats. In this context, rosemary essential oil exhibited hepatoprotective action, characterized by the inhibition of the lipid peroxidation, GSH, and protein oxidation, and by the restoration of the levels of antioxidant enzymes [40]. Similar observations were made for hepatotoxicity induced by CCl4. Rosemary essential oil inhibited the lipid peroxidation and ‘reversed’ the activities of antioxidant enzymes catalase, peroxidase, glutathione peroxidase, and glutathione reductase in a liver homogenate [91]. A methanolic extract obtained from R. officinalis leaves [92,93] and a shoot tincture [94] also presented the same protective results on CCl4-induced hepatotoxicity in rats. When t-BOOH was used as the oxidizing agent used to induce liver damage, R. officinalis also exhibited protective effects [95]. Acetaminophen is one of the most widely used analgesic and antipyretic drugs in the world. Although it is a relatively safe drug at therapeutic doses, acute overdose, chronical exposition, or association with other xenobiotics can result in severe hepatotoxicity. After oral intake, a major part of it is conjugated with glucuronic acid in the liver and eliminated by the kidneys. However, a fraction of AAP undergoes metabolization by the cytochrome P450 system, generating the toxic metabolite N-acetyl-p-benzoquinone imine (NAPQI) which, under normal conditions, is conjugated with GSH and eliminated. Nonetheless, increased NAPQI production results in the depletion of GSH and, consequently, oxidative liver damage [96]. Thus, we investigated for the first time the possible protective effect of Ro on AAP-induced hepatotoxicity. To validate the model, our data showed that a single high dose of AAP caused a depletion of GSH and increased lipid peroxidation. Such oxidative alterations were accompanied with liver damage. This was attested by increased levels of ALT and AST, biochemical markers of hepatocyte damage. Both aminotransferases were quantified since tissues other than the liver have elevated AST levels, such as the erythrocytes, heart, and muscle, while ALT has more specificity to the liver. Our data showed an increased AST/ALT ratio (De Ritis ratio), higher than 1.0, when rats were treated with AAP. This is predictive of long-term complications such as fibrosis and cirrhosis [97]. As shown, Ro indisputably protected the rat livers from AAP toxicity since the AST and ALT levels returned to the basal levels when compared to control. The powerful antioxidant activity of Ro seems to be responsible for this hepatoprotection since the GSH depletion was abolished and the lipid oxidation was also diminished. This strategy of using antioxidants to protect the liver from AAP toxicity was successfully achieved with N-acetyl cysteine [98,99].
Finally, it is important to correlate the general chemistry data annotated in this paper with the Ro effects. More than half of the compounds have the catechol group. It is well known that catechol and its many functionalized derivatives are excellent metal chelators [100]. Considering only the phenol group, which is a good and well-known antioxidant [100], the number is even more expressive since all 18 major compounds noted have at least one hydroxyl linked to an aromatic ring. Therefore, we believe that the observed effect must surely be a synergistic combination of all the actives described in this work.
## 5. Conclusions
Together, our data reinforced the antioxidant activity of R. officinalis through a free radical scavenger activity and by diminishing the Fe2+-catalyzed Fenton reactions. We showed that these activities enabled Ro to protect isolated rat liver mitochondria from oxidative damage caused by different mechanisms (Fe2+ or t-BOOH). Moreover, Ro did not present cytotoxicity in cultured liver cells, and it exhibited a potent hepatoprotective effect against AAP toxicity in vivo. Further studies are necessary to the development of pharmaceutical formulations containing Ro, and clinical trials are required to evaluate the potential hepatoprotective effect in patients.
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|
---
title: Protective Potential of β-Hydroxybutyrate against Glucose-Deprivation-Induced
Neurotoxicity Involving the Modulation of Autophagic Flux and the Monomeric Aβ Level
in Neuro-2a Cells
authors:
- Yi-Fen Chiang
- Ngan Thi Kim Nguyen
- Shih-Min Hsia
- Hsin-Yuan Chen
- Shyh-Hsiang Lin
- Ching-I Lin
journal: Biomedicines
year: 2023
pmcid: PMC10045359
doi: 10.3390/biomedicines11030698
license: CC BY 4.0
---
# Protective Potential of β-Hydroxybutyrate against Glucose-Deprivation-Induced Neurotoxicity Involving the Modulation of Autophagic Flux and the Monomeric Aβ Level in Neuro-2a Cells
## Abstract
Hypoglycemia has been known as a potential contributory factor to neurodegenerative diseases, such as Alzheimer’s disease. There may be shared pathogenic mechanisms underlying both conditions, and the ketone body, β-hydroxybutyrate (BHB), as an alternative substrate for glucose may exert neuroprotection against hypoglycemia-induced injury. To investigate this, Neuro-2a cells were subjected to a 24 h period of glucose deprivation with or without the presence of BHB. Cell viability, reactive oxygen species (ROS) production, apoptosis, autophagy, and adenosine triphosphate (ATP) and beta-amyloid peptide (Aβ) levels were evaluated. The results show that Neuro-2a cells deprived of glucose displayed a significant loss of cell survival with a corresponding decrease in ATP levels, suggesting that glucose deprivation was neurotoxic. This effect was likely attributed to the diverse mechanisms including raised ROS, defective autophagic flux and reduced basal Aβ levels (particularly monomeric Aβ). The presence of BHB could partially protect against the loss of cell survival induced by glucose deprivation. The mechanisms underlying the neuroprotective actions of BHB might be mediated, at least in part, through restoring ATP, and modulating ROS production, autophagy flux efficacy and the monomeric Aβ level. Results imply that a possible link between the basal monomeric Aβ and glucose deprivation neurotoxicity, and treatments designed for the prevention of energy impairment, such as BHB, may be beneficial for rescuing surviving cells in relation to neurodegeneration.
## 1. Introduction
The neurons in the hippocampus and cerebral cortex are responsible for the function of learning and memory, and are the most vulnerable to damage from hypoglycemia [1]. Hypoglycemia is commonly associated with the treatments of diabetes, but contributes to increased risks of neurodegenerative diseases, i.e., dementia and cognitive impairment, in diabetic patients [2]. Intriguingly, a growing body of evidence suggests that reduced glucose metabolism is a pivotal pathogenic component for Alzheimer’s disease (AD) which is the most common cause of dementia [3]. Epidemiological evidence reveals that elderly diabetic patients who experience severe hypoglycemia are at greater risk of developing dementia and AD [4]. If hypoglycemia is not corrected with glucose immediately, brain glucose deprivation can occur, leading to severe brain injury. Animal studies have demonstrated that insulin-induced hypoglycemia causes significant neuronal cell death and cognitive impairment in rats, and in an in vitro study, the exposure of cortical neurons to glucose deprivation also manifests neuronal cell death [5]. Collectively, glucose deprivation could contribute to the pathogenesis of neurodegenerative diseases such as AD.
In response to nutrient starvation or energy deprivation, an adaptive mechanism at the cellular level, namely macroautophagy (hereafter referred to as autophagy), can be triggered to promote cell survival via the maintenance of cellular energy homeostasis [6]. Under normal conditions, autophagy is a self-degradative pathway for eliminating cytoplasmic constituents including abnormal protein aggregates, defective proteins and organelles, which is pivotal to maintaining cellular homeostasis [7,8]. Autophagy in neurons appears to play a critical role in protecting against aging and relevant neurodegenerative diseases [9,10]. For instance, a dysfunctional autophagy pathway has been reported to be involved in hypoglycemia-induced neuronal cell death [11] as well as neurodegenerative proteinopathies (e.g., Aβ accumulation) [10]. In the healthy brain, a balance between Aβ production and its removal is maintained by the competent autophagy machinery, indicating that Aβ accumulation is likely prevented [10]. The accumulation of pathogenic Aβ in AD may be the consequence of dysregulated autophagy [12,13,14]. As mentioned above, impaired glucose metabolism and Aβ accumulation may be involved in the pathogenesis of AD; however, whether both events shared a common mechanism in relation to autophagy remains unclear.
Ketone bodies, which include acetoacetate, β-hydroxybutyrate (BHB) and acetone, can act as alternative energy substrates in the brain during the conduction of a limited glucose supply, e.g., prolonged fasting, starvation and hypoglycemia, in order to prevent the loss of brain function. Several animal studies have reported the protective effects of BHB against hypoglycemia-induced neuronal cell death [15,16]. Likewise, in vitro studies associated with energy failure such as glucose deprivation and glycolysis inhibition have shown the potential of BHB to prevent neuronal cell death [16,17]. The mechanisms underlying the potential neuroprotective actions of BHB may be attributable to its antioxidant and autophagy stimulation properties [17,18,19]. Interestingly, a previous in vitro study has shown that BHB exerts putative neuroprotection against Aβ-induced neuronal cell death [20]. However, whether the mechanism by which BHB attenuates Aβ neurotoxicity is related to autophagy remains elusive. Although there are studies investigating the beneficial effects of BHB under the condition of glucose deprivation in vitro, none of them has explored the association between Aβ production and the neurotoxicity of glucose deprivation or the neuroprotective potential of BHB. Given the possible involvement of hypoglycemia in the pathogenesis of AD, we made an attempt to ascertain whether metabolic disturbances in glucose deprivation showed a possible link between neuronal cell death and subsequent changes in Aβ levels, and what role BHB played in this event.
Therefore, in the present study, we hypothesized that the ketone body, BHB, could prevent neuronal cell death under a condition of glucose deprivation through restoring ATP, stimulating autophagy, and modulating the levels of Aβ and ROS. To test this, the mouse Neuro-2a neuroblastoma cell line was exposed to a 24 h period of glucose deprivation condition with or without the presence of BHB, and cell survival, autophagy function, ROS production and Aβ and ATP levels were determined.
## 2.1. Cell Culture β-Hydroxybutyrate Treatment and Bafilomycin A1 Pre-Treatment
The mouse Neuro-2a neuroblastoma cell lines were obtained from the Bioresource Collection and Research Center (BCRC, No. 60026, Hsinchu, Taiwan). This cell line was chosen because it is of neuronal origin [21] and has been used in AD research regarding Aβ cytotoxicity [22,23]. Briefly, the Neuro-2a cells were then cultured in Dulbecco’s modified Eagle Medium (DMEM, Gibco, Grand Island, NY, USA) containing 25 mM glucose supplemented with $10\%$ fetal bovine serum (FBS, CORNING, Manassas, VA, USA) and 100X penicillin streptomycin solution (CORNING, Christiansburg, VA, USA) at 37 °C in a humidified $5\%$ CO2 incubator. The Neuro-2a cells cultured in this glucose-containing basal condition served as a control group, which is further referred to as the “C” condition. For the experimental condition of glucose deprivation, the Neuro-2a cells were cultured in non-glucose DMEM (Gibco, Grand Island, NY, USA) with the same environment, which is further referred to as the “N” condition. For β-hydroxybutyrate (BHB, Sigma-Aldrich, St. Louis, MO, USA) treatment, 10 mM BHB was added simultaneously with the non-glucose DMEM and was then used for the Neuro-2a cell cultures. Thus, the Neuro-2a cells were cultured in non-glucose DMEM with the presence of 10 mM BHB, which is further referred to as the “B” condition. To monitor the effects of glucose deprivation with or without the presence of BHB on autophagy, an autophagosome–lysosome fusion inhibitor, bafilomycin A1 (BAF, Cayman Chemical Company, Ann Arbor, MI, USA) was added to the glucose-containing medium with a concentration of 100 nM. The Neuro-2a cells were then cultured in this medium for 4 h at 37 °C in a humidified $5\%$ CO2 incubator. After pre-incubation with BAF, the medium was removed and a fresh glucose-containing medium or non-glucose medium with or without the presence of BHB was added, followed by incubation for another 24 h. With the BAF pre-treatment, therefore, the Neuro-2a cells cultured in glucose-containing DMEM, and non-glucose DMEM with or without the presence of BHB are further referred to as the “BAF”, “N + BAF” and “B + BAF” conditions, respectively.
## 2.2. Cell Viability Assessment
Cell viability was evaluated by the use of 3-(4,5-dimethyl thiazol)-2,5-diphenyltetrazolium bromide (MTT) assays. Briefly, 3 × 103 cells were seeded into a 96-well cell culture plate. The next day, cells were cultured in the C, N or B conditions for 8, 24 and 48 h. Cell survival was further monitored at respective time points by adding 100 μL of the 0.1 mg/mL MTT, and the cells were kept in a 37 °C CO2 incubator for 3 h. After dissolving formazan crystals in dimethyl sulfoxide (DMSO) solution, cell survival was judged based on the absorbance of this colored solution, which was measured using an ELISA reader at the wavelengths of 570 and 630 nm. In addition, MTT assays were also employed to evaluate the role of glucose deprivation in autophagy-induced cytotoxicity. For this purpose, Neuro-2a cells were pre-treated with BAF for 4 h and then the culture medium was replaced with either a glucose-containing basal medium or non-glucose medium with or without the presence of 10 mM β-hydroxybutyrate followed by incubation for another 24 h. After treatments, the Neuro-2a cells were subjected to MTT assays following the aforementioned protocol.
## 2.3. Cell Counting Trypan Blue Stain Assay
Further, trypan blue stain assay was conducted for the determination of a viable cell count in order to confirm the cytotoxic effects of experimental conditions. Neuro-2a cells were cultured in a 6-well plate (2 × 105 cells/well) under C, N or B conditions for 8, 24 or 48 h. After incubation, cells were detached by trypsinization. The cell pellet was collected and re-suspended in PBS solution followed by staining with trypan blue (CORNING, Christiansburg, VA, USA). The viable cells, which did not take up the stain, were counted with a hemocytometer under a microscope (Olympus, Tokyo, Japan).
## 2.4. Assessment of Intracellular ROS Generation
Quantification of oxidative stress in Neuro-2a cells exposed to the C, N or B conditions was carried out by measuring total ROS using 2′,7′-dichlorofluorescin diacetate (DCFDA, Cayman, Ann Arbor, MI, USA) staining. The non-fluorescent DCFDA can serve as an indicator for ROS, because it can be rapidly oxidized to form fluorescent 2′,7′-dichlorofluorescein (DCF) in the cells with the presence of ROS. In brief, after Neuro-2a cells were cultured in the C, N and B conditions for 24 h, cells were incubated with 25 μM DCFDA for 30 min to detect total ROS by quantifying the fluorescence intensity of DCF. Next, microscopy was used to produce the fluorescence image, and the intensity of fluorescent DCF in a single cell was quantified using ImageJ software (Version 1.52t, NIH, Bethesda, MD, USA).
## 2.5. Propidium Iodide Staining
After the Neuro-2a cells were cultured in the C, N and B conditions for 24 h, the cells were stained with PI (1 μg/mL, dissolved with sterile ddH2O, Sigma-Aldrich, St. Louis, MO, USA) solution for 1 h. Fluorescence was monitored at 200× magnification using microscopy (Olympus, Tokyo, Japan). To compare the fluorescence intensity in Neuro-2a cells among the groups, Image J software (Version 1.52t, NIH, Bethesda, MD, USA) was used to quantify the fluorescence intensity in a single cell. In brief, after 4–6 images (each image representing one biological replicate) of each group were taken at random locations, three different cells representing technical replicates in each image were randomly selected to determine the level of fluorescence with the ImageJ software.
## 2.6. Assessment of ATP Concentrations and ATP/ADP Ratios
After Neuro-2a cells were cultured in the C, N and B conditions for 24 h, cells were further subjected to the analysis of ATP concentration and ATP/ADP ratio by ADP/ATP Ratio Bioluminescent Assay Kit (BioVision, Cambridge, UK) with a luminometer. The assays were performed according to the manufacturer’s instructions. Briefly, the background luminescence value was defined as data A. After treating the Neuro-2a cells in the control or experimental conditions, the culture medium was removed and the cells were treated with a nucleotide-releasing buffer for 5 minutes at room temperature, and the luminescence values were measured and considered data B. Then, this value was read again as data C for determining the ADP levels. Finally, the luminescence values were determined again as data D followed by the addition of an ADP-converting enzyme to activate the reaction. ATP concentration and the ATP/ADP ratio were calculated according to the following formulas: ATP= data B − data A and ATP/ADP ratio= (data B − data A)/(data D − data C), respectively.
## 2.7. Western Blot Analysis
After the Neuro-2a cells were cultured in the C, N, B, BAF, N + BAF or B + BAF conditions for 24 h, the cell lysates were prepared in an ice-cold lysis buffer (50 mmol/L Tris (pH 8.0), 100 mmol/L sodium chloride (NaCl), $0.1\%$ sodium dodecyl sulfate (SDS), $1\%$ NP-40 and 0.5 mM ethylene diamine tetra acetic acid (EDTA) containing the protease (Roche, Basel, Switzerland). The proteins (30 μg) were boiled for 5 min, separated using $10\%$ or $15\%$ SDS-polyacrylamide gel electrophoresis, and then transferred onto Immobilon-P polyvinylidene fluoride membranes (0.22 µm) for 150–180 min at 280 mA and 250 V. Then, the membranes were washed three times in tris-buffered saline (TBS) plus Tween 20 (TBST) buffer for 10 min each, blocked with blocking buffer ($5\%$ BSA) for 1 h at room temperature and incubated overnight with primary antibodies, i.e., Aβ 1–42 (1:1000) (Millipore, Rehovot, Israel), PARP (1:000) (Cell signaling, Danvers, MA, USA), p62 (1:1000) (Cell signaling, Danvers, MA, USA), LC3B (1:1000) (Cell signaling, Danvers, MA, USA), cathepsin B (1:1000) (Cell signaling, Danvers, MA, USA) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (1:10,000) (Proteintech, Rehovot, Israel) at 4 °C. The next day, the membranes were washed three times in the TBST (tris-buffered saline with Tween 20) buffer for 10 min each, incubated for 1 h in the blocking buffer with anti-rabbit/mouse immunoglobulin G (IgG) coupled to alkaline phosphatase (1:10,000), and washed three times in the TBST buffer for 10 min each. Then, the bands were detected using enhanced chemiluminescence (ECL). The chemiluminescent signals were detected by the e-BLOT Touch Imager (e-BLOT, Shanghai, China). The values shown were quantified, normalized to the internal control GAPDH, and then densitometry estimation was performed using the ImageJ software (NIH, Bethesda, MD, USA). Original, uncropped images of Western blots are presented in Supplementary Figure S1.
## 2.8. Intracellular Aβ ELISA
After the Neuro-2a cells were cultured in the C, N or B conditions for 24 h, cells were collected with pre-cooling PBS and the cell lysates were prepared for intracellular Aβ determination. The levels of cellular Aβ were quantified by using the mouse Aβ ELISA kit (Novus Biologicals, Littleton, CO, USA) according to the manufacturer’s instructions with the determination of optical density at 450 nm by an ELISA plate reader.
## 2.9. Immunofluorescence Analysis
Co-localization of p62 and LC3B or cathepsin B was analyzed for monitoring the autophagic flux. After Neuro-2a cells were cultured in the C, N, or B conditions for 24 h, cells grown on coverslips were washed in PBS and fixed using $4\%$ paraformaldehyde for 10 min at room temperature followed by PBS wash. The coverslips were then incubated in the permeabilization solution containing 0.5 % Triton X-100 in PBS for 10 min at room temperature. After washing three times with PBS, the coverslips were blocked in a blocking solution containing $5\%$ bovine serum albumin (BSA) in TBST for 30 min at room temperature. The coverslips were incubated with the primary antibodies, anti-p62 (1:1000) anti-LC3B (1:1000) and anti-cathepsin B (1:200, cell signaling) at appropriate dilutions overnight at 4 °C. After washing with PBS, the coverslips were incubated with the respective secondary antibodies, which were either Alexa Fluor 546-goat anti-mouse or Alexa Fluor 488-anti-rabbit IgG antibodies (1:200) (Life Technologies, Gaithersburg, MD, USA) for 1 h at room temperature. The nuclear counterstaining was performed with 4′,6-diamidino-2-phenylindole (DAPI) (Thermo Fisher Scientific, Waltham, MA, USA). The results were visualized under a fluorescence microscope (Olympus, Tokyo, Japan).
## 2.10. Statistical Analysis
All quantitative results are expressed as mean ± standard error of the mean (SEM), and were analyzed using the Prism version 6.0 software (GraphPad, San Diego, CA, USA). The Shapiro–Wilk test was performed to test the normality of the data. Because all datasets passed the Shapiro–Wilk normality tests with p-values greater than 0.05, the differences between the mean values of the three groups were then determined using one-way analysis of variance (ANOVA) followed by multiple comparisons with Tukey’s HSD post hoc test. Significance was accepted at $p \leq 0.05.$
## 3.1. β-Hydroxybutyrate Confers Partial Neuroprotection against Glucose-Deprivation-Induced Neuro-2a Cell Death
Cell viability and trypan blue assays were used to evaluate cytotoxicity. In parallel, Western blot analysis was also performed for detecting poly ADP-ribose polymerase (PARP) cleavage. This cleavage has been recognized as an indication of cell death [5]. As shown in Figure 1a, glucose-deprived Neuro-2a cells, regardless of the presence of BHB, exhibited a marked decrease in cell viability in a time-dependent manner. Relative to control exposure (C group), cell viability in response to glucose deprivation decreased significantly at all times analyzed, with the 48 h exposure demonstrating the greatest decrease ($p \leq 0.001$, Figure 1a). When compared to the glucose-deprived Neuro-2a cells in the absence of BHB (N group), the presence of BHB appeared to significantly reverse the glucose-deprivation-induced decrease in Neuro-2a cell viability at all times analyzed (B group, $p \leq 0.05$, Figure 1a). Glucose deprivation with the presence of BHB for 24 h (B group) displayed maximal suppression of neuronal cell death ($p \leq 0.05$, Figure 1a). Similar results were observed when cell survival was monitored by the trypan blue assay. The number of viable cells was not altered by glucose deprivation exposure for 8 h, but was significantly decreased by glucose deprivation exposure for 24 h and 48 h, regardless of the presence of BHB ($p \leq 0.001$, Figure 1b). Co-incubation with BHB for 24 h and 48 h significantly attenuated the decreased number of glucose-deprived Neuro-2a cells ($p \leq 0.05$, Figure 1b). Likewise, as shown in Figure 1c, the cleaved PARP protein expression was not altered after glucose deprivation exposure for 8 h, but was significantly increased after glucose deprivation exposure for 24 h and 48 h, indicating that glucose deprivation could induce Neuro-2a cell death in a time-dependent manner. The glucose deprivation-mediated increase in the cleaved PARP protein expression of Neuro-2a cells was profoundly decreased by co-incubation with BHB for 24 h (Figure 1c). These results suggest that the glucose deprivation was likely cytotoxic for Neuro-2a cells leading to cell death in a time-dependent manner. Co-incubation with BHB during glucose deprivation appeared to partially alleviate these glucose-deprivation-induced cytotoxic effects in Neuro-2a cells. Moreover, according to Figure 1, due to the potent induction of half Neuro-2a cell loss by glucose deprivation exposure for 24 h, and the maximal suppression of glucose-deprivation-induced cytotoxicity by co-incubation with BHB for 24 h, a 24 h period of glucose deprivation exposure and resulting deleterious effects were chosen for further experiments.
## 3.2. β-Hydroxybutyrate Exerts Partial Neuroprotection against Glucose-Deprivation-Induced Neuronal Cell Death through the Normalization of Intracellular ROS
It has been reported that glucose-deprivation-induced neurotoxic response is the result of oxidative stress in PC12 cells [24]. We also confirmed this observation in glucose-deprived Neuro-2a cells without BHB treatment (N group), the green fluorescence (DCFDA) of which was significantly enhanced in comparison with that of the control cells (C group) as can be viewed in the representative images (Figure 2a) and quantitative data ($p \leq 0.05$, Figure 2b). A marked increase in ROS production was observed within glucose-deprived Neuro-2a cells without BHB treatment, but this effect was able to be completely abolished by the presence of BHB (B group, $p \leq 0.05$, Figure 2b). BHB treatment showed a significant reduction in ROS generation within glucose-deprived cells with low green fluorescent intensity, which was similar to that observed in the control cells (Figure 2b), suggesting the inhibitory effect of BHB on intracellular ROS production. When overproduction of ROS was induced in the glucose-deprived Neuro-2a cells, an increase in neuronal cell death determined by PI staining was simultaneously observed (Figure 2c,d). As shown in the representative images (Figure 2c) and quantitative data (Figure 2d), the PI signal was significantly stronger in the glucose-deprived Neuro-2a cells, regardless of the presence of BHB, than in the control cells, indicating that increased neuronal cell death could be attributed to the excessive generation of ROS induced by glucose deprivation. However, this effect was partially reversed by the presence of BHB (Figure 2c,d), suggesting that BHB could act through scavenging intracellular ROS, at least in part, to protect against Neuro-2a cell death induced by glucose deprivation.
## 3.3. The Neuroprotective Role of β-Hydroxybutyrate Correlates with Cellular Energy Status
To investigate whether the neuroprotective action of BHB correlated with changes in cellular energy status, adenosine triphosphate (ATP) concentrations and ATP/adenosine diphosphate (ADP) ratios were determined after glucose deprivation exposure with or without the presence of BHB for 24 h. As shown in Figure 3, ATP and ADP concentrations as well as the ratio of the two were significantly reduced in the glucose-deprived Neuro-2a cells without the presence of BHB (N group) compared to those of the control cells ($p \leq 0.05$, Figure 3). As expected, these results show a reduced cellular energy status due to glucose deprivation. During glucose deprivation, ATP concentration and the ratio of ATP to ADP were significantly higher in the BHB-treated Neuro-2a cells (B group) than in the untreated cells (N group) ($p \leq 0.05$, Figure 3a,c), indicating that glucose-deprivation-induced ATP reduction could be restored, at least in part, by BHB. These data suggest that a metabolic action in relation to the preservation of ATP could partially contribute to the neuroprotective effect of BHB against glucose-deprivation-induced neuronal cell death.
## 3.4. β-Hydroxybutyrate Partially Improves Glucose-Deprivation-Induced Impaired Autophagy Flux
To evaluate the autophagy efficacy, the expression of microtubule-associated protein 1 light chain-3B (LC3B-I/C3B-II), p62 and cathepsin B proteins were analyzed, all of which are recognized as autophagy markers at different steps of autophagy. During the induction of autophagy, autophagosome formation is a concomitant of the conversion of LC3B-I to LC3B-II, and therefore increased levels of LC3B-II may indicate accumulation of autophagosomes resulting from autophagy induction [10,25]. The p62 protein, also known as sequestosome1 (SQSTM1), acts as an autophagy adapter and substrate enabling the interaction with LC3B and thereby undergoing autolysosomal degradation [8,25], while cathepsin B is one of the abundant lysosomal proteases and is responsible for lysosomal degradation [26]. In this context, changes in the levels of both proteins may indicate the capacity of autophagic degradation or autophagic flux [25,27]. In the present study, autophagic flux was also determined by employing an autophagosome–lysosome fusion inhibitor, bafilomycin A1 (BAF) [28], which allowed us to confirm whether glucose-deprived cells displayed defective or component autophagy machinery. As shown in Figure 4a–c, in the absence of BAF and BHB treatments, significant increases in the LC3B-II/ LC3B-I ratio and expression of p62 protein accompanied by a significant reduction in expression of cathepsin B protein were observed in Neuro-2a cells under glucose deprivation (N group), compared to those of the control cells (C group, $p \leq 0.01$). These observations imply that either induction of autophagy or impaired autophagic flux might likely occur in Neuro-2a cells under glucose deprivation. Accumulation of autophagosomes accompanied by the suppression of autolysosomal degradation could be the result of impaired autophagic flux. It is worth noting that an induction of autophagy or upregulation of autophagic flux is generally characterized by an increased LC3B-I to LC3B-II conversion with a concomitant decrease in p62 expression [25]. To more accurately evaluate autophagy capacity, inhibition of autophagosome–lysosome fusion with BAF appeared to cause profound changes in all autophagy markers in glucose-deprived cells, regardless of the presence of BHB (Figure 4a–c). The LC3B-II/ LC3B-I ratio and p62 protein expression in the N + BAF group was statistically further increased from those in the N group (Figure 4a,b). Furthermore, the BAF inhibitor caused an even more marked reduction in cathepsin B expression for all groups ($p \leq 0.001$, Figure 4c). This finding further supports the assumption that the autophagosome accumulation was likely the consequence of a blockage of autophagosome–lysosome fusion by glucose deprivation. In other words, presumably, Neuro-2a cells exposed to a 24 h period of glucose deprivation could result in impaired autophagy flux. However, this adverse effect could be partially reversed by the presence of BHB as evidenced by the results showing that co-incubation with BHB during glucose deprivation significantly inhibited the increase in the LC3B-II/ LC3B-I ratio and p62 expression, and the reduction in cathepsin B expression ($p \leq 0.05$, Figure 4a–c). Additionally, the reduction in cell viability in the N group was notable, but was significantly decreased by the pre-treatment with BAF (N + BAF group, $p \leq 0.01$, Figure 4d). It seemed that BAF pre-treatment could augment the cytotoxic effect of glucose deprivation on Neuro-2a cells, suggesting a critical role of autophagosome–lysosome fusion in neuronal survival under glucose deprivation. These findings support a previous study showing that competent autophagy machinery is important for neuronal cell survival [29]. On the other hand, during a 24 h period of glucose deprivation with the presence of BHB, BAF pre-treatment had no additional effect on the loss of cell survival (B + BAF group, $p \leq 0.05$, Figure 4d) implying that energy is likely required for autophagy machinery to be completely fulfilled. The presence of BHB seemed to elicit a modulatory effect favoring improved autophagy flux, and such an effect could be potentially neuroprotective as BHB restored a loss of cell survival to a limited extent in parallel (Figure 4d). In agreement with these findings, the results of immunofluorescence showed that co-localization of p62 and LC3B (Figure 4e) or cathepsin B (Figure 4f) was also enhanced when Neuro-2a cells were cultured in the N condition. In addition, this effect was stronger after inhibition of autophagosome–lysosome fusion with BAF. The presence of BHB appeared to weaken this effect as shown in Figure 4e,f, where the signal of co-localization of p62 and LC3B or cathepsin B in the B group was weaker than in the N group. Taken together, these data suggest that glucose deprivation might lead to impaired autolysosomal degradation, thereby reducing autophagic flux efficacy, whereas the presence of BHB might partially suppress this effect.
## 3.5. The Neuroprotective Role of β-Hydroxybutyrate Correlates with Alteration in Intracellular Aβ Levels
As mentioned above, Aβ accumulation in AD pathology is associated with defects in glucose metabolism and autophagy. However, under non-pathological conditions, Aβ may have crucial physiological roles [30]. On the basis of this concept, we investigated whether intracellular Aβ levels of Neuro-2a cells were affected by glucose deprivation with or without the presence of BHB. It is worth noting that amyloid plaques, the key pathological characteristic of AD, are formed and aggregated from different Aβ species including monomeric Aβ, oligomeric Aβ, protofibrils and fibrils [31]. The oligomeric Aβ is formed from the self-aggregation of the monomeric Aβ due to its hydrolytic properties [31]. Utilization of the enzyme-linked immunosorbent assay (ELISA) approach has allowed the quantification of monomeric Aβ species (molecular weight ~4 KDa) [31,32]. Changes in intracellular Aβ levels are shown in Figure 5a. Glucose deprivation itself resulted in a significant decrease in monomeric Aβ levels in the N group, compared to that of the control cells in the C group ($p \leq 0.01$, Figure 5a), and this decrease was significantly attenuated by co-incubation with BHB ($p \leq 0.001$). During glucose deprivation, BHB-treated Neuro-2a cells (B group) exhibited significantly higher levels of monomeric Aβ than untreated cells (N group, $p \leq 0.001$, Figure 5a). Furthermore, in order to detect intracellular oligomeric Aβ, Western blot analysis was performed in parallel. According to a previous study [33], oligomeric Aβ species can be shown as bands at 56 (dodecamer), 50, 40 (nonamer), 25 (hexamer) and 12 (trimer) kDa in a Western blot by the use of the Aβ antibody. As shown in Figure 5b, by using the same source of the Aβ antibody as Sandoval et al. [ 33] in their study, specific bands corresponding to 56, 50, 40, 25 and 12 kDa were observed within the intracellular fractions in all groups representing oligomeric Aβ species. However, no significant changes were found in the expression of the $\frac{56}{50}$, 40 or 25 kDa bands among the groups ($p \leq 0.05$). The expression of the 12 kDa band was significantly higher in the B group than in the C and N groups ($p \leq 0.05$, Figure 5b). Nevertheless, the decreased levels of monomeric Aβ were likely associated with the loss of Neuro-2a cell survival after glucose deprivation exposure, and BHB might play a neuroprotective role, in part, in modulating the decreased monomeric Aβ level due to glucose deprivation.
## 4. Discussion
Previous evidence has shown that hypoglycemia could lead to neuronal cell death, which contributes to cognitive impairment and dementia including AD [2,3,5]. However, whether hypoglycemia plays a role in Aβ accumulation is unclear. Ketone bodies have been shown to elicit beneficial effects that pertain to autophagy regulation [17,19] and neuroprotection against neurodegenerative diseases [34], but whether it has the potential to modulate Aβ levels is unknown. In the present study, a 24 h period of glucose deprivation exposure was able to induce Neuro-2a cell death, which is in agreement with previous studies demonstrating that neurotoxicity is the consequence of glucose deprivation [35]. Furthermore, we assumed that its underlying mechanisms might involve inadequate ATP supply, excessive ROS production, autophagy dysregulation and aberrant Aβ levels in Neuro-2a cells under such a condition of stress. Our observation showing that glucose deprivation could cause an elevation in ROS production is in accordance with previous studies using different cells, such as primary neurons [24,36] and SH-SY5Y cell lines [35]. In addition, the reduced ATP levels and ATP/ADP ratios accompanied by increased neuronal cell death due to glucose deprivation in Neuro-2a cells suggests a possible association between insufficient ATP supply and neuronal cell death. It has been suggested that energy failure contributes to neuronal cell death, which has also been implicated in neurodegenerative diseases [37].
When cells are subjected to nutrient stress, cell survival is normally promoted by an activated autophagy, as described above; however, dysfunctional autophagy can cause autophagic cell death, in which the accumulation of autophagosomes is observed [35]. In the present study, the protein expression of LC3B-II relative to LC3B-I in Neuro-2a cells was upregulated during glucose deprivation, indicating the increased number of autophagosomes [25]. Although this speculation might be explained by the possibility of autophagy enhancement, an elevation in the number of autophagosomes is not necessarily caused by an enhancement of autophagy as it could also be caused by a blockage in lysosomal degradation occurring in the later stage of autophagy [25]. Therefore, distinguishing between autophagy enhancement and degradation inhibition by glucose deprivation was achieved by the assessment of autophagy flux. In the present study, a corresponding increase in p62 levels of Neuro-2a cells was observed, suggesting a likelihood of lysosomal degradation inhibition under glucose deprivation. This assumption was further confirmed by the addition of a BAF inhibitor, which pointed to a putative impairment of autophagic flux that might occur in the glucose-deprived Neuro-2a cells for 24 h. Our findings are in line with a previous study showing that glucose deprivation, albeit for 2 h, in cortical neurons resulted in autophagosome accumulation and an impaired autophagic flux accompanied by the increase in LC3B and p62 levels. The authors of this study attributed their results to glucose-deprivation-induced ATP depletion [38]. Furthermore, we assume that this defective autophagy resulting from glucose deprivation could also contribute to the Neuro-2a cell death. It has been reported that the autophagy machinery is intrinsically associated with neuronal cell survival in terms of cellular homeostasis [31].
In the present study, the detrimental effects of glucose deprivation on Neuro-2a cells were partially reversed by the co-incubation with BHB, suggesting the neuroprotective potential of BHB against glucose-deprivation-induced injury. Likewise, the neuroprotective effects of BHB have been demonstrated in various neuronal cell death models, which are associated with oxidative damage [16,18], glucose deprivation [16,17] and Aβ exposure [20]. Furthermore, we provide evidence that the putative neuroprotective mechanisms of BHB were likely attributed to the preservation of ATP, attenuation of ROS and partial restoration of autophagic flux and Aβ levels. The observed neuroprotective mechanisms of BHB in the present study are compatible with a previous study suggesting that BHB protecting against hypoglycemia-induced neuronal cell death is associated with the preservation of energy levels and the alleviation of ROS production [16]. Presumably, the metabolic and antioxidative actions are likely responsible for its neuroprotection. This inference is further supported by another study, in which BHB exerts its antioxidant effect by eliminating ROS production to protect against neuronal death in an in vitro model of hypoglycemia and by inhibiting lipid peroxidation to protect against hypoglycemia-induced oxidative damage in rats [18]. The authors in the aforementioned study indicated that BHB is a potential antioxidant due to its ability to directly scavenge hydroxyl radicals (•OH) [23].
In light of the fundamental importance of autophagy in promoting neuronal survivability associated with neurodegenerative diseases, it was our intention to elucidate the effect of BHB on autophagy and Aβ levels in Neuro-2a cells under glucose deprivation. In addition to the metabolic, antioxidant actions, BHB appeared to exert a putative autophagy-modulating effect in the present study. Consequently, a concomitant reduction in glucose-deprivation-induced Neuro-2a cell death was seen, which might be explained in part by the effect of BHB on modulating autophagy in favor of improved autophagic flux efficacy. This interpretation was supported by our observation that the presence of BHB during glucose deprivation resulted in significant attenuation of autophagosome accumulation and lysosomal degradation inhibition. Similarly, it has been revealed that BHB treatment is able to stimulate autophagic flux in cultured neurons deprived of glucose, thereby preventing neuronal cell death [17]. Furthermore, in a rodent model of severe hypoglycemia, it was demonstrated that neuronal cell survival is promoted by the treatment of BHB via improved autophagy flux efficacy resulting from the reduced accumulation of autophagosomes and enhanced degradation of p62 [19]. Collectively, this modulatory effect on autophagy flux could be the mechanism underlying the neuroprotective action of BHB on glucose-deprivation-injured Neuro-2a cells. Interestingly, it has been documented that autophagy itself is considered as an ATP-consuming process, in which ATP provides a driving force for reactions at different stages [39]. For instance, the late stage of autophagy is involved in the degradation of unwanted protein and damaged organelles within the lysosome, and this lysosome-mediated protein degradation has been proven to depend on the ATP supply [40]. Accordingly, the modulation of autophagic flux by BHB under glucose deprivation might be attributable to its metabolic role.
Autophagy is also important for metabolizing Aβ. The degradation of Aβ has been reported to occur in lysosomes as well as in other intracellular organelles [27,41]. Both in vitro and in vivo studies have shown that autophagy activation increases Aβ clearance [42,43]. Under physiological conditions, Aβ is a soluble component of cellular metabolism through the proteolytic cleavage of the neuron trans-membrane β-amyloid precursor protein by β- and γ-secretases, and there is equilibrium between Aβ production and its degradation [31,44]. It is possible that impaired autophagy could affect Aβ clearance. We then examined changes in the intracellular levels of Aβ. Intriguingly, we observed that the level of monomeric Aβ, but not oligomeric Aβ, was significantly reduced in Neuro-2a cells deprived of glucose, and this effect was partly reversed by the presence of BHB. Oligomeric Aβ has been considered to be neurotoxic [31,45], whilst monomeric Aβ has been reported to be neuroprotective [30]. In the present study, it is plausible that the loss of Neuro-2a cell survival after glucose deprivation exposure might be associated with the decreased levels of monomeric Aβ. Evidence from in vitro studies has revealed that monomeric Aβ can exert neuroprotective roles in inhibiting excitotoxic neuronal cell death [30] and apoptosis, and stimulating autophagy [14]. Importantly, a physiological role for monomeric Aβ in the glucose metabolism of the brain has been suggested, and this is crucial to the neuronal survival [46]. In the present study, the reversal of the decreased level of monomeric Aβ by the presence of BHB suggests a potential neuroprotective action of BHB for glucose-deprived Neuro-2a cells. Incidentally, there is evidence showing a link between hyperoxia-induced activation of autophagy and intra-lysosomal accumulation of Aβ in vitro [47]. However, owing to the fact that the total intracellular levels of Aβ were measured in the present study, whether intra-lysosomal Aβ degradation is also affected by glucose deprivation remains to be further investigated.
## 5. Conclusions
In conclusion, the results of the present study suggest that cell death induced by a 24 h period of glucose deprivation in Neuro-2a cells was apparent, and this neurotoxic effect was attributed to diverse mechanisms including insufficient ATP supply, raised ROS, defective autophagic flux and a reduced level of intracellular monomeric Aβ. Changes in monomeric Aβ levels underlining a possible role of monomeric Aβ in glucose-deprivation-induced neurotoxicity is noteworthy. These findings imply that elevating glucose availability may be beneficial, and that can be relevant to the prevention of neurodegenerative diseases [48]. On the other hand, the presence of BHB was able to partially suppress this neurotoxicity, suggesting that BHB is likely neuroprotective in Neuro-2a cells under glucose deprivation. We postulate that the energy metabolism in glucose-deprived Neuro-2a cells could be partly sustained by BHB treatment, which in turn, might render neuroprotection for Neuro-2a cells, at least in part, against glucose-deprivation-induced neurotoxicity. The putative neuroprotective effects of BHB on Neuro-2a cells deprived of glucose might be mediated through multiple mechanisms of action, i.e., mitigating ROS production and monomeric Aβ reduction, and improving autophagic flux efficacy. Not only metabolic, but also other neuroprotective-associated actions of BHB, may make it a promising candidate for the development of potential neuroprotective agents. Further studies are warranted to assess the potential of BHB as a neuroprotective agent in in vivo models of hypoglycemia in relation to neurodegeneration or neurodegenerative diseases.
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|
---
title: Zingiber officinale Roscoe Rhizome Extract Exerts Senomorphic and Anti-Inflammatory
Activities on Human Endothelial Cells
authors:
- Giulia Matacchione
- Vittoria Borgonetti
- Deborah Ramini
- Andrea Silvestrini
- Marta Ojetti
- Nicoletta Galeotti
- Fabiola Olivieri
journal: Biology
year: 2023
pmcid: PMC10045365
doi: 10.3390/biology12030438
license: CC BY 4.0
---
# Zingiber officinale Roscoe Rhizome Extract Exerts Senomorphic and Anti-Inflammatory Activities on Human Endothelial Cells
## Abstract
### Simple Summary
Aging is related to a low-grade and sterile inflammation called inflammaging, recognized as the main risk factor for age-related disease (such as diabetes, dementia, and cancer) development. At present, several natural compounds have gained attention to be tested in the framework of anti-aging therapies. Here, we investigated the anti-senescence and anti-inflammatory properties of an Asian-native Ginger extract, commonly consumed as a food spice and herbal medicine, on human endothelial cells and murine microglial cells. The anti-senescence and anti-neuroinflammatory effects that we observed on such cellular models suggest the potential relevance of Ginger extract in delaying/postponing the most common age-related diseases development and progression.
### Abstract
Aging is related to a low-grade and sterile inflammation called inflammaging, recognized as the main risk factor for age-related disease (ARD) development. Inflammaging is fostered by the repeated activation of immune cells, as well as by the accumulation of senescent cells. Recently, a number of natural compounds have gained attention to be tested as anti-aging therapies, based on their anti-inflammatory activity and/or ability to reduce the pro-inflammatory secretome of senescent cells (senomorphyc activity). Here, we investigated the anti-inflammatory and senomorphic properties of an Asian-native Zingiber officinale Roscoe extract (ZOE), commonly consumed as a food spice and herbal medicine. We employed two models of primary endothelial cells (HUVECs), such as the replicative-senescence and LPS-induced response, to investigate the anti-inflammatory/senomorphic effect of ZOE, and one cellular model of neuroinflammation, i.e., immortalized murine microglial cells (BV2). First, we found that the ZOE treatment induced the inhibition of NF-kB activation in BV2 cells. Among the constituents of ZOE, we showed that the terpenoid-enriched fraction (ZTE) was the component able to counteract the phosphorylation of NF-kB(p65), while 6-gingerol (GIN) and 6-shogaol (SHO) did not produce any significant effect. Further, we observed that the treatment with 10 µg/mL of ZOE exerted anti-inflammatory activity on LPS-stimulated young (y)HUVEC and senomorphyc activity on replicative senescent (s)HUVEC, significantly reducing the expression levels of IL-1β, TNF -α, IL-8, MCP-1, and ICAM-1. Moreover, the ZTE treatment was able to significantly reduce the IL-8 levels secreted in the medium of both LPS-stimulated yHUVEC and sHUVEC. Overall, our data suggest a potential protective role of ZOE on neuroinflammation and endothelial inflammation/activation, thus suggesting its potential relevance in delaying/postponing ARD development and progression, characterized by endothelial dysfunction.
## 1. Introduction
Chronic, low-grade, and sterile pro-inflammatory status is a pervasive phenomenon of aging. It has been defined as “inflammaging”, and it was identified as an important contributor to tissue dysfunction and a significant risk factor for the development of the most common age-related diseases (ARDs), such as diabetes, neurodegenerative diseases, and atherosclerosis [1,2]. Overall, inflammaging level is currently recognized as the main risk factor for morbidity and mortality in the elderly [3,4]. Inflammaging is fostered by the repeated activation of the immune cells, as well as by the accumulation of senescent cells during aging. Senescent cells are characterized by cell cycle arrest in association with alterations in the metabolic activities and morphology. The most relevant senescent-associated feature in the framework of inflammaging is the development of a pro-inflammatory secretory phenotype, named senescence-associated secretory phenotype (SASP) [5,6].
Eliminating senescent cells has been shown to improve age phenotypes in mouse models [7], and there is some initial evidence that it may contribute to postponing ARDs, thus extending the health span [2]. Senomorphic treatment provides an alternative pharmacological approach to targeting senescent cells, as it can suppress the detrimental effects of SASP, without affecting cell viability [8]. At the molecular level, senomorphics act by targeting the most relevant transcription factors, i.e., NF-kB, for inflammatory mediators, which are released as SASP factors (such as cytokines, chemokines, and metalloproteases).
In the research of senolytic/senomorphyc compounds, the attention of the scientific community was attracted by natural compounds, used in ancient medicine, known for their beneficial effects and high tolerability. The Asian-native Zingiber officinale Roscoe, commonly known as ginger, has long been widely consumed as a food spice and herbal medicine to treat various symptoms, including vomiting, nausea, and pain [9,10].
Biological compounds are contained in the dried rhizome, which is particularly abundant in essential oil and oleoresin. The non-volatile components, which represent the phenolic compounds, include gingerols, shogaols, paradols, and zingerone [11].
Among terpenes, zingiberene is the major component found in ginger root and has been known for its anti-bacterial activities, anti-carcinogenic properties, and help in preventing the high blood sugar levels that are often associated with its anti-oxidative and anti-inflammatory activities [12]. Moreover, ginger extracts were studied to treat neuropathic pain symptoms in animal models by inhibiting neuroinflammation [13].
In addition, recent evidence has highlighted the ability of ginger extracts to restrain inflammation, also by targeting senescent cells [14]. Among the components of ginger extract, gingerenone A and 6-shogaol showed promising senolytic properties, characterized by the selective elimination of senescent cells [14].
The central role played by the endothelium and innate immune cells in activating and sustaining acute and chronic inflammation justifies the efforts to identify new strategies to counteract endothelial cell degeneration and immune cell activation. In this framework, we aimed to analyze, in vitro, the anti-inflammatory effects of ginger extracts and some of its components on both microglia and endothelial cells. Considering the crucial role of endothelial dysfunction and neuroinflammation during aging and ARDs, we employed two models of primary endothelial cells (HUVECs), replicative-senescence and LPS-induced response, to investigate the possible anti-inflammatory/senomorphic effect of ginger extracts, in addition to one cellular model of neuroinflammation, i.e., immortalized murine microglial cells (BV2).
We tested a standardized Z. officinale rhizomes extract (ZOE), obtained by CO2 supercritical extraction on both cellular models of microglia and endothelial cells. In particular, 6-gingerol (GIN), 6-shogaol (SHO), and terpenoid-enriched fraction (ZTE), were tested on the microglia. As the volatile component of ZOE, ZTE, which contains Zingiberene, was the most effective in restraining inflammation in the immune cells, we also tested its effect on the endothelial cells.
## 2.1. Chemicals
The ZOE, obtained by supercritical CO2 extraction, and standardized to contain $24.73\%$ total gingerols and $3.03\%$ total shogaols, was kindly provided by INDENA S.p. A. (Milan, Italy), batch number 46349. The 6-gingerol (GIN) was purchased from Sigma-Aldrich (Milan, Italy) and the 6-shogaol (SHO) was purchased from Extrasynthese (Genay, France). The extraction of the terpenoid-enriched fraction (ZTE) was performed as previously described (Ferguson, 1956). The quantification of GIN and SHO in the ZOE was obtained by HPLC-DAD, while the volatile compounds were analyzed through gas chromatography coupled with a flame ionization detector (GC-FID) and with a mass spectrometer, as previously reported [13].
## 2.2. BV2 Cells
Immortalized murine microglial cells (BV2; C57BL/6 Tema Ricerca, Genova, Italy) were cultured in 75 cm2 flasks (Sarstedt, Verona, Italy) in a medium containing RPMI with $10\%$ heat-inactivated fetal bovine serum (56 °C, 30 min) (FBS, Gibco®, Milan, Italy), $1\%$ glutamine, and $1\%$ penicillin-streptomycin solution (Merck, Milan, Italy). The cells were cultured at 37 °C and $5\%$ CO2 with a daily change of the culture medium.
## 2.3. Neuroinflammatory Model
For the neuroinflammatory model, bacterial lipopolysaccharide from Gram- (LPS, Salmonella enteritidis, Merck, Darmstadt, Germany) was solubilized in RPMI to obtain a 500 µg/mL stock, which was then diluted in the medium to obtain a final concentration of 250 ng/mL. BV-2 cells (3 × 105 cells/well) were seeded into 6-well plates and cultured for 24 h. We previously performed a dose-response curve, obtained using a CCK-8 assay, to investigate the maximum non-cytotoxic concentration of ZOE on the BV2 cells [13]. Briefly, the cells were treated with increasing concentrations of ZOE (i.e., 0.01, 1, 5, 10, 50, and 100 μg/mL) for 24 h. The maximum non-cytotoxic concentration was found to be 10 μg/mL. The concentrations of GIN, SHO, and ZTE were calculated by considering the percentage of each compound within the extract. Thus, the cells were pre-treated for 4 h with ZOE (10 μg/mL), GIN (1 μg/mL), SHO (0.17 µg/mL), and ZOE terpenoid-enriched fraction (ZTE, 3 µg/mL), and then stimulated with LPS (250 ng/mL) for 24 h [15].
## 2.4. HUVEC Cells
Human umbilical vein endothelial cells (HUVEC) are a pool of endothelial primary cells derived from the human umbilical vein (Clonetics, Lonza, Switzerland). The HUVECs were cultured in an endothelial growth medium (EGM-2, Lonza, Switzerland), composed of endothelial basal medium (EBM-2, Lonza, Switzerland) and the SingleQuot Bullet Kit (Lonza, Switzerland). The HUVECs were seeded at a density of 5000/cm2 in T75 flasks (Corning Costar, Sigma Aldrich, St. Louis, MO, USA) and cultured at 37 °C and $5\%$ CO2 with a daily change of the culture medium.
## 2.5. Characterization of Young and Senescent HUVEC Cells
The senescent phenotype was acquired by replicative exhaustion and measured as through cumulative population doublings (cPD). The cPD is described as the sum of the PD, which is measured by the formula: (log10(F)–log10(I))/log10[2], where F is the number of cells at the end of the passage, and I is the number of seeded cells.
HUVECs were considered young or senescent based on three different markers of senescence: the cPD, the senescence-associated (SA)-β -Galactosidase (β-Gal) activity, and the expression of p16ink4a. The SA-β-Gal activity was detected using a Senescence Detection Kit (BioVision Inc., Milpitas, CA, USA), following the manufacturer’s instructions.
## 2.6. Cell Viability Assay
We tested the cell viability using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Young (y) and senescent (s) HUVECs were grown in 24-well plates at a density of 5 × 104 cells/cm2 and then treated for 24 h with different doses of ZOE.
Briefly, the MTT (1 mg/mL) solution was added, and the cells were incubated for 4 h; the obtained product, a formazan salt, was solubilized in dimethyl sulfoxide (DMSO) and measured by a microplate reader (MPT Reader, Invitrogen, Milano, Italy) at the optical density of 540 nm.
The cell viability was calculated according to the equation (T/C) $100\%$, where T and C represent the mean optical density of the treated group and the control group, respectively.
## 2.7. Zingiber Officinale Roscoe Extract Treatments
The yHUVEC were pretreated with ZOE (10 µg/mL) or ZTE (3 µg/mL) for 4 h, followed by 24 h treatment with LPS (from E. coli O55:B5, Sigma Aldrich, St. Louis, MO, USA) to induce inflammation, together with ZOE (10 µg/mL) or ZTE (3 µg/mL). The sHUVEC were treated with ZOE (10 µg/mL) or ZTE (3 µg/mL) for 24 h. The HUVECs were grown in EGM-2 medium as a control (yHUVEC or sHUVEC). Following these treatments, the cell pellets were prepared and used for the subsequent analysis.
## 2.8. RNA Isolation, mRNA and Mature miRNAs Expression by RT-qPCR
The Total RNA Norgen Biotek Kit (Thorold, ON, Canada) was used to isolate the RNA according to the manufacturer’s instructions, and these were stored at −80 °C until use. The mRNA and miRNA expression were determined through RT-qPCR analysis, as previously described [16]. Briefly, the PrimeScript™ RT reagent Kit with gDNA Eraser and the TB Green™ Premix Ex Taq™ (TAKARA, Shiga, Japan) were used to respectively reverse-transcribe and amplify the mRNA, whereas the TaqMan miRNA assay (ThermoFisher Scientific, Waltham, Massachusetts, United States) was employed for the miRNA quantification. The RT-qPCR analysis was standardized with GAPDH and β-actin for the mRNA expression and with RNU48 for the miRNA expression.
## 2.9. Western Blot Analysis
The HUVECs were lysed with the RIPA solution ($0.1\%$ SDS, 150 mM NaCl, $1.0\%$ Triton X-100, 10 mM Tris, 5 mM EDTA pH 8.0), to which we added a protease and phosphatase inhibitor cocktail (Roche Applied Science, Indianapolis, IN, USA). In each sample, the protein concentration was evaluated using a Bradford assay. Proteins (25 µg) were separated by 4–$15\%$ precast polyacrylamide gel (Bio-Rad, Hercules, CA, USA), and then transferred to a 0.2 mm nitrocellulose membrane (Bio-Rad, Hercules, CA, USA). A blocking buffer (Bio-Rad, Hercules, CA, USA) was used to block the membrane, which was then incubated overnight with primary antibodies. Mouse anti-phospho-p38 (Cell Signaling), rabbit anti-phospho-NF-kB (Cell Signaling), mouse anti-ICAM-1 (Cell Signaling), mouse anti-β-actin, mouse anti-α-tubulin, and rabbit-anti-GAPDH (Cell Signaling) were used as the primary antibodies. Anti-mouse or anti-rabbit horseradish peroxidase-conjugated antibodies were used as the secondary antibodies (The Jackson laboratory, Bar Harbor, ME, USA). A Uvitec Imager (UVItec, Cambridge, UK) was used to distinguish the protein bands, using a chemiluminescence substrate (Bio-Rad), that were then quantified using ImageJ software. Each measure was normalized versus β-actin, α-tubulin, or GAPDH.
## 2.10. ELISA Assay
A conditioned medium was collected from the BV-2 and HUVEC cultures at the end of each incubation, centrifuged at 14.000 RPM for 20 min, and then stored at −80 °C until use. An IL-8, TNF-α, and IL-1β ELISA Kit (Invitrogen, Waltham, MA, USA) was used to measure the concentration of these cytokines released in the medium, according to the manufacturer’s instructions.
## 2.11. Statistical Analysis
The reported data are indicated as the mean of three independent replicates ± SD or frequency (%). A paired sample T-test was used for the analysis of the real-time, densitometric data and the ELISA. Data analysis was performed using IBM SPSS Statistics for Windows, version 25 (IBM Corp, Armonk, NY, USA). Statistical significance was defined as a two-tailed p-value < 0.05.
## 3.1. ZTE Is the Main Responsible for ZOE Anti-Inflammatory Activity in the In Vitro Model of Neuroinflammation
The anti-neuroinflammatory activity of ZOE has recently been described [13]. To identify which constituent of ZOE was the most responsible for these effects, we tested the activity of GIN, SHO, and ZTE, at the concentration present in the active dose of ZOE, on the protein activation of NF-kB and cytokines expression. The phosphorylation of the NF-kB-p65 subunit represents one of the most important pathways involved in the inflammatory processes [17]. The kinase IKB-α is a main regulator of the NF-kB signaling pathways, as its degradation allowed the NF-kB-p65 subunit to enter into the nucleus and regulate the target gene transcription [18]. Therefore, we studied its role in the mechanism of action of ZOE. The treatment with ZOE 10 µg/mL up-regulated the levels of IKB-α and reduced the phosphorylation of NF-kB(p65) in the LPS-stimulated BV2 cells. Among the treatments, ZTE was the fraction able to counteract the downregulation of IKB-α and the phosphorylation of NF-kB(p65), while GIN and SHO did not produce any effect (Figure 1A,B). The activation of this transcription factor results in its nuclear translocation and in the increased expression of the genes involved in the inflammatory processes, including the pro-inflammatory cytokines, tumor necrosis factor α (TNF-α) (Figure 1C), and interleukin-1β (IL-1β) (Figure 1D) that were overexpressed in the culture medium of BV2 stimulated with LPS. The pretreatment with ZOE and ZTE strongly prevented these events. In contrast, GIN and SHO showed no significant effect. The inflammatory factors released by the pro-inflammatory microglia are known to induce neurotoxicity; in fact, the LPS-conditioned BV2 medium reduced the viability of SH-SY5Y cells compared to the untreated control. The LPS-conditioned BV2 medium from the cells treated with ZOE and ZTE completely prevented this cytotoxic effect, returning to the control values (Figure 1E). Thus, the anti-neuroinflammatory activity of ZOE appears to be prominently related to its content in ZTE.
## 3.2. Replicative Senescence in HUVECs
To assess the capacity of ZOE and ZTE to reduce inflammation and SASP, we first described yHUVEC and sHUVEC. The yHUVEC were characterized by cPD < 8 and SA-β-Gal positive cells < $15\%$, whereas the sHUVECs were characterized by cPD > 16 and SA-β-Gal positive cells > $80\%$ (Figure 2A,B). In addition, a significant increase in the p16ink4a mRNA (Figure 2C) levels in the sHUVEC compared to the yHUVEC confirm the acquisition of the senescent status.
## 3.3. Zingiber Officinale Extract Effect on HUVEC Viability
The different ZOE concentrations (100, 50, 10, 5, 1, 0.5, 0.1 µg/mL) were evaluated using the MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay the yHUVEC and sHUVEC after 24 h of treatment (Figure 3A,B). The experiments were then performed considering the concentration of the extract that gave at least $80\%$ viability of the treated HUVEC (10 µg/mL ZOE). Subsequently, the HUVEC were treated with 3 µg/mL ZTE, which corresponds to $30\%$ of the tested ZOE concentration.
## 3.4. ZOE Anti-Inflammatory Activity in LPS-Stimulated HUVECs
The potential anti-inflammatory capacity of ZOE was evaluated by assessing the expression of pro-inflammatory markers in the yHUVEC stimulated with 250 ng/mL LPS for 24 h. The yHUVEC were pretreated for 4 h with ZOE and then 24 h with ZOE and LPS. The ZOE significantly decreased the expression levels of the cytokines IL-1β and TNF -α, the chemokines IL-8 and MCP-1, and the adhesion molecule ICAM-1 compared to the LPS-stimulated HUVEC (Figure 4A). Furthermore, the release of IL-8 in the medium (Figure 4B) in the LPS-stimulated HUVEC was significantly reduced by the ZOE treatment. The ZOE treatment was also associated with a significant down-regulation of the ICAM-1 protein level (Figure 4C), a significant reduction in the phospho-p38 MAP kinase (MAPK) activation (Figure 4D), and a significative down-regulation in the NF-kB p65 subunit phosphorylation (Figure 4E), compared to the LPS-stimulated HUVECs. Finally, we analyzed the expression of the angio-miR, miR-126, one of the main regulators of angiogenesis and endothelial proliferation [19]; MiR-126 was significantly up-regulated in the LPS-stimulated cells treated with ZOE (Figure 4F).
## 3.5. Senomorphic Effect of ZOE in Senescent HUVECs
To evaluate the potential senomorphic activity of ZOE, we analyzed the expression levels of several molecules, considered as SASP components or modulators, such as proinflammatory cytokines and chemokines (IL-1β, TNF-α, IL-8, and MCP-1), adhesion molecules (ICAM-1), microRNAs (inflamma-miR-21 and angio-miR-126), and transcription factors (NF-kB). The sHUVEC were treated with 10 µg/mL of ZOE for 24 h. The expression of TNF-α, IL-8, MCP-1, IL-1β, and ICAM-1, as well as the expression of miR-21, were significantly increased in the sHUVEC compared to the yHUVEC. Interestingly, the ZOE treatment of sHUVEC was able to significantly decrease the TNF-α, IL-8, MCP-1, IL-1β, and ICAM-1 expression levels (Figure 5A). The ZOE treatment was able to induce an important reduction in the IL-8 chemokine release in the culture medium (Figure 5B). Regarding p38 MAPK and NF-kB activation, in the sHUVEC treated with ZOE, the expression of both phospho-p38 MAPK and phospho-NF-kBp65 were downregulated compared to the non-treated senescent cells (Figure 5D). Moreover, the ZOE treatment was associated with a strong down-regulation of miR-21 and with an up-regulation of the miR-126 expression levels (Figure 5E).
## 3.6. ZTE Biological Activity in yHUVEC and sHUVEC
ZTE is a volatile component of ZOE, composed of $28.2\%$ of zingiberene, which is the most abundant volatile compound. We observed that ZTE was the ZOE fraction responsible for its anti-neuroinflammatory activity (Figure 1). To assess whether ZTE is responsible for ZOE’s anti-inflammatory and senomorphic effects, we tested the activity of ZTE in the LPS-stimulated yHUVEC and in the sHUVEC at the concentration of 3 µg/mL ($30\%$ of the dose of ZOE) on the pro-inflammatory markers. The treatment with ZTE in the yHUVEC was associated with a significant reduction in the IL-1β and IL-8 mRNA expression (Figure 6A), IL-8 secretion (Figure 6B), and miR-126 level (Figure 6C) compared to the LPS-treated yHUVEC.
Similarly, the sHUVEC treated with ZTE showed a significant down-regulation of IL-1β and IL-8 mRNA expression (Figure 6D), as well as IL-8 secretion (Figure 6E) and the miR-126 and miR-21 levels (Figure 6F) compared to the sHUVEC.
## 4. Discussion
Aging is described as the progressive loss of physiological integrity associated with functional impairment and a high susceptibility to several pathologies, defined as age-related diseases (ARDs) [1,20]. The accumulation of the senescent cells that acquire SASP is now recognized as one of the main detrimental characteristics of the aging process, fostering inflammation, and thus promoting degeneration and tumorigenesis [14]. SASP factors consist of a plethora of pro-inflammatory cytokines, chemokines, growth factors, and matrix-remodeling enzymes that affect the microenvironment surrounding the senescent cells [21]. The central role played by the vasculature and innate immunity in activating and sustaining acute and chronic inflammation justifies the efforts to identify new strategies to counteract endothelial degeneration and immune cell activation.
Although the anti-inflammatory activity of Zingiber officinale roscoe (ZOE) has been already well recognized in both in vivo and in vitro models [14,22,23,24,25], studies on the senomorphic activity in human endothelial cells, as well as on neuroinflammation, are scarce.
First, we found an anti-neuroinflammatory activity of ZOE in the BV2 murine microglial cells, which was perpetuated at the molecular level by the inhibition of NF-kB activation. As NF-kB signaling is partly responsible for the onset of neuropathic symptoms, ZOE could be suggested as a nutraceutical compound to control neuropathy.
The primary human endothelial cells obtained from the umbilical vein (HUVEC) were extensively investigated as a human model of endothelial cells to assess the effects of senolytic and senomorphic compounds [26,27,28,29]. We observed that 10 µg/mL of ZOE exerts anti-inflammatory activity on LPS-stimulated yHUVEC by reducing the expression levels of IL-1β, IL-8, MCP-1, TNF-α, and ICAM-1. ICAM-1 reduction was also confirmed at the protein level, suggesting that ZOE could impair leucocyte adhesion to endothelial cells and transmigration through the vasculature. Moreover, we examined the activation of p38 MAP kinase (MAPK) and the p65 subunit of NF-kB.
Both the key MAPK p38 and the nuclear transcription factor NF-kB are involved in regulating inflammation and in the production of inflammatory mediators [17,30].
The ZOE treatment of the LPS-stimulated HUVEC was associated with a down-regulation of p38-MAPK activation, through the phosphorylation of threonine 180 and tyrosine 182, as well as the reduction in the NF-kB-p65 subunit phosphorylation (serine 536).
The senomorphic effect of ZOE in the replicative senescent HUVEC was demonstrated by the reduced expression of pro-inflammatory markers, such as IL-8, IL-1β, MCP-1, TNF-α, and ICAM-1.
Importantly, the ZOE treatment was found to decrease the level of the phosphorylated p65 subunit of the NF-kB in the sHUVEC. NF-kB is one of the master regulators of the inflammatory process and activates the target genes that could contribute to cellular senescence and SASP acquisition [31]. NF-kB aberrant activation was associated with ARD development and progression [32]. In this framework, the senotherapeutic properties of ZOE suggest a potential contribution to reducing the progression rate of the most common human ARDs, such as diabetes and neurodegenerative and cardiovascular diseases. Some evidence on this topic has already been provided. Ginger supplementation of type 2 diabetic patients [33], as well as of patients affected by osteoarthritis [34], was associated with reduced inflammatory cytokines.
We have also analyzed the expression levels of two miRNAs: miR-21, involved in the modulation of inflammatory pathways; and miR-126, previously associated with vascular development and homeostasis [35,36]. To the best of our knowledge, there is still no evidence regarding the role of ZOE in modulating miRNA expression in HUVECs. Here, we found that the levels of miR-126 were up-regulated by ZOE treatment in both the yHUVEC and sHUVEC. Moreover, in the sHUVEC, the expression level of miR-21 was reduced by the ZOE treatment. These results suggest that ZOE treatment can play an anti-inflammatory and a potential protective role on the vasculature.
To investigate the main constituents of ZOE involved in such anti-inflammatory and senomorphic activity, we also tested the effects of Zingiber officinale terpenoid-enriched extract (ZTE), as, in BV2 cells, the anti-neuroinflammatory effect appears distinctly related to this fraction. Terpenes represent one of the largest groups of plant-derived secondary metabolites, but their biological activity is poorly studied. Consistent with this, ginger oil has been scarcely investigated and only one study has reported its efficacy in reducing acute inflammation in mice [37]. Zingiberene is the most abundant component of ZTE, and it is a monocyclic sesquiterpene, mainly present in ginger with oil content (Zingiber officinale). ZTE has several pharmacological properties and, in particular, possesses the ability to modulate the inflammatory PI3K/AKT/mTOR pathway in human cells [38,39].
In our study, we demonstrated that ZTE treatment was able to significantly reduce the expression level of IL-1β and IL-8, the IL-8 secreted in the medium, and the expression of miR-21 and miR-126 in both the LPS-stimulated yHUVEC and sHUVEC, thus supporting both the anti-inflammatory and senomorphic activities of this extract. Although the anti-inflammatory activity of zingiberene has already been observed [40], the lack of data about purified zingiberene senomorphic activity is a limitation of this work and further experiments will be performed to assess the role of zingiberene in cellular senescence.
Overall, our data show the anti-inflammatory and senomorphic effects of ZOE and ZTE on young and senescent human endothelial cells, thus supporting the efforts devoted to identifying new natural compounds with the potential ability to contribute to delaying/postponing ARD development and progression.
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|
---
title: Smoothness of Gait in Overweight (But Not Obese) Children Aged 6–10
authors:
- Micaela Porta
- Demetra Cimmino
- Bruno Leban
- Federico Arippa
- Giulia Casu
- Maria Chiara Fastame
- Massimiliano Pau
journal: Bioengineering
year: 2023
pmcid: PMC10045369
doi: 10.3390/bioengineering10030286
license: CC BY 4.0
---
# Smoothness of Gait in Overweight (But Not Obese) Children Aged 6–10
## Abstract
Excessive body mass represents a serious threat to the optimal psychophysical development of children, and it is known to be able to significantly affect their locomotor capabilities, making them more prone to the development of musculoskeletal disorders. However, despite the relevant number of existing studies, a clear gait pattern of overweight children has not been defined yet, particularly in the case of a mass excess that is relatively small (i.e., in those not obese). In the present study, we employed a wearable inertial measurement unit placed on the low back to derive spatio-temporal parameters and quantify the smoothness of gait (by means of harmonic ratio) from trunk accelerations acquired during gait trials carried out by 108 children aged 6–10 ($46\%$ males), stratified into two groups according to their body mass index (normal weight, $$n = 69$$ and overweight, $$n = 39$$). The results show that while gait speed, stride length, cadence and double support duration were found to be almost identical in the two groups, significant differences were observed in terms of harmonic ratio. In particular, overweight children exhibited a reduced harmonic ratio in the antero-posterior direction and higher harmonic ratio in the medio-lateral direction. While the significantly lower harmonic ratio in the antero-posterior direction is likely to be indicative of a loss of smoothness in the walking direction, probably due to a combination of factors associated with the altered movement biomechanics, the higher harmonic ratio in the medio-lateral direction might be associated with specific strategies adopted to increase lateral stability. Although further studies are necessary to elucidate the specific mechanisms that influence the smoothness of gait, it is noteworthy that harmonic ratios appear sensitive even to subtle change in locomotor control in overweight children characterized by apparently regular spatio-temporal parameters of gait and might be employed to assess the effectiveness of interventions designed to improve mobility functions.
## 1. Introduction
Worldwide epidemiological data report that, over the last four decades, childhood obesity appears characterized by an increasing trend of growth, although with some differences depending on the geographical area. For instance, in most high-income industrialized countries, where such a phenomenon came forward earlier, in the last few years, the prevalence of overweight and obesity, although high, has reached a sort of plateau, while it continues to steadily increase in low-income and middle-income countries [1,2].
Among the wide spectrum of medical comorbidities (which involve both physical and psychological dimensions) associated with a mass excess, a commonly encountered issue is represented by the relevant changes in biomechanical functions that occur during the execution of both simple and complex motor tasks. Such alterations, in combination with the increased risk of musculoskeletal problems (i.e., malalignment, pain, osteoarthritis, etc.), ultimately lead to a reduction in mobility, physical activity and overall quality of life [3,4]. In particular, a significant part of the research on mobility issues in overweight children attempted to quantitatively characterize the possible alterations of gait patterns associated with mass excess by analyzing several kinematic and kinetic parameters. Despite the significant heterogeneity of the studies carried out in the last few decades in terms of age range, male-to-female ratio, percentage of overweight and obese participants and experimental setup, they suggest that there is strong evidence as regards the existence of significant kinematic alterations and differences in generated/absorbed power at the hip/pelvis and knee joints (see the review of Molina-Garcia et al. for details [5]). In contrast, the level of evidence is inconsistent for most spatio-temporal parameters and only moderate in the case of step width and stance phase duration (which have been found to be significantly increased due to mass excess). Such findings have two important consequences, namely [1] the most important differences in gait biomechanics (kinematics and kinetics) can be detected only using specialized laboratory equipment, including motion capture systems and force platforms, and [2] spatio-temporal parameters of gait appear substantially unsuitable to identify differences associated with mass excess (except for step width and stance phase duration, as previously mentioned), especially when of small magnitude.
In this context, particularly appealing is the possibility to employ wearable inertial sensors (i.e., inertial measurement units, IMUs) to obtain information about gait patterns based on trunk/limb acceleration data. Such devices gained popularity among the researchers involved in the quantitative assessment of human movement [6,7] due to their miniaturized size, easiness of use, affordable cost and, above all, because they allow the overcoming of several limitations typical of motion capture systems, such as the need to have available a dedicated space, to perform specific preparations for the tested subjects (i.e., undressing, anthropometric collection data, marker placement, etc.) and the overall conditions in which the test takes place, which make this type of analysis uneconomical. In particular, the configuration, which consists of a unique sensor (usually located on the low back, close to the body’s center of mass), is characterized by minimal encumbrance for the individual, fast setup and the possibility to perform tests in a variety of settings (including clinics, schools, gyms, outdoor settings), terrain conditions, overground or treadmill walking, straight or curved paths, etc. While such an approach is commonly employed to obtain the spatio-temporal parameters of gait (by processing the acceleration data with suitable algorithms [8]), an interesting feature associated with the use of IMUs when they are located on the low back is the possibility to characterize different aspects of gait using metrics directly derived from trunk acceleration data. In this regard, several different approaches in terms of acceleration processing and the calculation of associated metrics, which cover important characteristics of the motor control underlying the realization of gait patterns, such as smoothness, efficiency, automaticity, adaptability, variability, stability and symmetry, have been proposed [9]. For the purposes of the present study, we will focus our attention on the smoothness of gait, which is a feature able to summarize the consistent forward progression and the repeatability of step patterns (i.e., step-to-step symmetry).
The use of trunk accelerations to detect and characterize the existence of possible alterations of gait dates back to the 1970s, when Smidt et al. [ 10] proposed an approach based on the harmonic analysis of the three orthogonal accelerations recorded at the low-back level in the frequency domain. In particular, they suggested that the value of a parameter called the harmonic ratio (HR), obtained as the ratio of the sum of the coefficients of the even harmonics and the sum of the coefficients of the odd harmonics, could represent a measure of the smoothness of gait and demonstrated that several types of gait alterations (associated either with orthopedic and neurologic conditions or even with the use of walking aids) were able to affect smoothness by reducing the HR values. In the last two decades, even exploiting the remarkable advancements of the micro-electro-mechanical systems (MEMS) technology, such concepts have been refreshed, enriched and applied to a variety of studies on gait involving both general and clinical populations. It is now generally recognized that HRs represent a reliable marker of whole-body balance during gait [11,12] and are able to discriminate changes in the smoothness of gait associated with gait maturation [13,14,15,16] and aging [12,17]. Moreover, it has been demonstrated that HR values are altered in the presence of neurologic and orthopedic conditions [18,19,20], even when spatio-temporal parameters appear physiological [21] and in older adults with cognitive deficits [22]. Lastly, HRs can be used, in combination with other parameters, to assess either the effectiveness of rehabilitative treatments targeted at gait function [23,24] or the outcome of orthopedic surgery that involves the lower limbs [25,26].
It is noteworthy that a limited number of studies investigated the possible changes occurring in the smoothness of gait due to body mass abnormalities (i.e., thinness or overweight/obesity) and, to our knowledge, only one specifically tested children. Misu et al. [ 27] reported that, among community-dwelling older adults, malnutrition is associated with reduced values of HR in the medio-lateral direction, hypothesizing that nutritional status might play a relevant role in the lateral trunk control during walking. Cimolin et al. [ 28] analyzed the smoothness of gait in 75 children aged 7–14, stratified into three groups composed, respectively, of underweight, normal-weight and overweight/obese participants. They found that while the spatio-temporal parameters of gait did not differ significantly across groups, the HR in the medio-lateral direction significantly increased while passing from under- to overweight and the HR in the antero-posterior and superior-inferior directions was significantly lower in those underweight with respect to overweight. Moreover, HRs in all directions were found to be significantly correlated with body mass index (BMI). Lastly, significantly reduced values of HR in the antero-posterior and superior-inferior directions were found in young adults affected by Prader–Willi syndrome, a genetic developmental disability that represents the most commonly known genetic cause of obesity [29].
In summary, although the analysis of gait smoothness seems to represent a promising source of information to support the accurate and detailed quantitative characterization of gait patterns in individuals with body mass alterations, the available data are scarce and heterogenous. To partly overcome such limitations, in the present study, we aimed to assess the smoothness of gait in a sample of overweight (but not obese) primary schoolchildren, to test the hypothesis that, even they still have not reached the obesity condition and the spatio-temporal parameters of their gait are weakly (or not at all) changed in comparison with those of normal-weight peers, some signs of gait alteration are detectable in terms of HR values.
## 2.1. Participants
In the period March–May 2022, the Laboratory of Biomechanics and Industrial Ergonomics of the University of Cagliari (Italy), in collaboration with two primary schools of the province of Cagliari (Italy), launched a call for a screening of balance, gait and functional mobility in schoolchildren aged 6–10. Of the 284 children who regularly attended the schools, 224 ($79\%$) agreed to participate as they and their parents signed an informed consent form that included a detailed explanation of the purposes of the study and of the testing procedure. Although no inclusion or exclusion criteria were explicitly defined in the call, the parents of the schoolchildren were asked to report the existence of either musculoskeletal or neurologic conditions able to significantly impair balance and walking abilities. In this regard, although it was planned to test all children who agreed to participate (this was also the intention of the school, with the specific purpose to avoid the possibility that some children felt “different” or “excluded”), we took care not to consider for the study individuals with prosthetic or orthotic devices or any other birth defect able to influence gait and balance. The study, which was carried out according to the principles expressed in the Declaration of Helsinki and its later amendments, was approved by the Ethics Committee of the University of Cagliari (authorization number 2022-UNCACLE-0001470).
Experimental tests were performed directly at participating schools during regular days of lessons, in dedicated spaces made available by the School Board. Children were called in small groups and, preliminarily, their height and body mass were recorded using an ultrasonic digital height meter (Soehnle 5003, Soehnle, Backnang, Germany) and a digital scale (RE310, Wunder, Milan, MI, Italy). The subsequent calculation of BMI (obtained by the ratio body mass/height2) allowed us to classify them as normal-weight, overweight or obese according to the cut-off points defined by Cole et al. [ 30]. Although all the participants were tested, for the purposes of the present study, the attention was focused on the group composed of overweight children ($$n = 39$$, $17.4\%$ of the whole cohort) and on a control group of 69 normal-weight children matched for age, sex and height. Obese children ($$n = 10$$, $4.5\%$ of the whole cohort) were not included in the analysis. The demographic and anthropometric features of the children selected for the analysis are reported in Table 1.
## 2.2. Gait Data Acquisition
Instrumental gait analysis was performed using a commercially available, wearable inertial sensor (G-Sensor®, BTS Bioengineering, Milan, MI, Italy), which was previously employed in similar studies involving children and adolescents [16,31,32,33]. The device was inserted into the pocket of a semi-elastic belt attached to the participant’s waist in such a way as to have it positioned approximately at the L4-L5 vertebrae level. Children were then instructed to stand still for few seconds (to ensure the proper calibration of the sensor) and, following a verbal signal, to walk down a 35-m hallway along a straight trajectory at a self-selected speed and in the most natural way possible. Such distance approximately corresponded to a number of strides in the range of 20–40 depending on the child’s stature. The sensor acquired the trunk accelerations along three orthogonal axes, namely antero-posterior (AP, which corresponds to the walking direction), medio-lateral (ML) and supero-inferior (SI), at 100 Hz frequency and transmitted them in real time via Bluetooth to a PC. Such data were then post-processed by means of a custom Matlab® routine that discarded the first and last two strides (to exclude the effects of acceleration and deceleration transients) and we calculated the following variables of interest:Spatio-temporal parameters of gait (namely gait speed, stride length, cadence and duration of double support phase expressed as a percentage of the gait cycle). The parameters known to be influenced by an individual’s anthropometry (i.e., gait speed, stride length and cadence) were normalized by dividing them by each participant’s height [34,35,36].HRs for AP, ML and SI directions.
Spatio-temporal parameters of gait were calculated using the peak detection algorithm proposed by Zijlstra [37], which essentially consists of processing the acceleration components (signals) in order to identify the characteristic patterns of trunk movement during gait as predicted by the inverted pendulum model. Instead, the calculation of the HRs was carried out following the approach proposed by Pasciuto et al. [ 38]. In short, the accelerations acquired during the gait trials were preliminarily processed in the frequency domain using a finite Fourier series, and then the HRs were calculated by dividing the square of the amplitude of the first ten even harmonics (AP and SI directions) or odd harmonics (ML direction) by the sum of the squares of the amplitudes of the first twenty even and odd harmonics. Such a ratio was then multiplied by 100, thus providing an index of easy interpretation that may assume values from 0 (in case of total asymmetry) to 100 (perfect symmetry). Previous studies indicated that, in case of healthy children and adolescents, the values range from 89 to 95 (AP and SI direction) and from 81 to 86 (ML direction) [16].
## 2.3. Statistical Analysis
Preliminarily, parametric model assumptions were verified for all variables of interest (i.e., normality, homogeneity and presence of outliers). Thus, the existence of possible differences introduced in the spatio-temporal parameters of gait by mass excess was assessed using a one-way multivariate analysis of variance (MANOVA). The independent variable was the group (i.e., normal or overweight) and the dependent variables were the 4 spatio-temporal parameters previously listed. As regards the HRs, considering that previous studies reported a significant influence of gait speed on their values (i.e., HRs tend to increase with increasing speed [12]), a one-way multivariate analysis of covariance (MANCOVA) was performed, including gait speed as a covariate. In all cases, the level of significance was set at $$p \leq 0.05.$$ Univariate ANOVAs were carried out as a post-hoc test by reducing the level of significance to $$p \leq 0.0125$$ ($\frac{0.05}{4}$) for spatio-temporal parameters and $$p \leq 0.016$$ ($\frac{0.05}{3}$) for HRs after a Bonferroni correction for multiple comparisons. All analyses were carried out using the IBM SPSS Statistics v.23 software (IBM, Armonk, New York, NY, USA).
## 3. Results
Spatio-temporal parameters of gait and HRs for the two groups of children are reported in Table 2.
The statistical analysis did not detect a significant main effect of mass excess on the spatio-temporal parameters of gait, either when considering the absolute values [F[4,103] = 0.78, $$p \leq 0.533$$, Wilks λ = 0.97, η2 = 0.03] or the normalized values [F[4,103] = 0.88, $$p \leq 0.46$$, Wilks λ = 0.98, η2 = 0.017].
As regards the smoothness of gait parameters (see Figure 1), after controlling for gait speed, the MANCOVA detected a significant main effect of overweight on HR values [F[3,103] = 12.22, $p \leq 0.001$, Wilks λ = 0.74, η2 = 0.26]. In particular, the post-hoc analysis revealed that, compared with their normal-weight peers, overweight children were characterized by significantly lower HR values in the AP direction (93.18 vs. 95.13, $$p \leq 0.003$$) and higher HR values in the ML direction (84.36 vs. 80.35, $$p \leq 0.008$$). No significant differences were found between groups for HRs in the SI direction.
## 4. Discussion
The present work aimed to assess the existence of possible alterations in the main spatio-temporal parameters and in the smoothness of gait in a sample of primary schoolchildren aged 6–10 characterized by a mass excess that leads to classifying them as overweight but not obese. At first, our results demonstrated that, even though our sample of overweight participants was characterized by a BMI more than $30\%$ higher than that of their normal-weight peers, the spatio-temporal parameters of gait were substantially similar across the two groups. As previously mentioned, there is no clear agreement in the existing literature about the actual influence of mass excess on such parameters; however, it should be noted that the recent review by Molina-Garcia et al. [ 5] pointed out that only the step width and stance phase duration are consistently altered in overweight and obese children (level of evidence: moderate). Although obtained from a sample relatively limited in size, our findings seem to suggest that changes in the main spatio-temporal parameters (i.e., speed, stride/step length and cadence) are expectable only in the case of obese children.
In contrast, significant differences emerged from the analysis of the HR, a parameter that has been interpreted as indicative of smoothness, rhythmicity and dynamic stability and that has been demonstrated to be effective in detecting subtle alterations in locomotor mechanisms that are not expressed through significant variations in spatio-temporal parameters [11]. Indeed, our results show that overweight children are characterized by worse smoothness in AP (i.e., the walking direction), as indicated by the reduced HR, but, at the same time, they exhibit higher HR values in ML. What explanation can be provided for such apparently contradictory results? At first, it should be recalled that, as regards the AP direction, the data of previous studies indicate no significant differences between normal weight and overweight/obese [28] or, consistent with the results of the present study, significantly lower values were observed in those who were obese [29]. Even though the overall amount of data is limited, we can hypothesize that such a lack of agreement could be attributed to differences in the sample compositions in terms of age and sex. In order to avoid any confounding effect, in the present study, we tried to carefully match any overweight participant with a normal-weight peer having very similar anthropometric and demographic features. Previous studies reported reduced smoothness in the AP direction in healthy older adults due to aging [17] and in the presence of neurologic diseases, even at early stages [19,21]. Interestingly, such conditions share the existence of impairments in postural control due to reduced performance of the sensory input system (i.e., vestibular, visual and proprioceptive), as well as to issues associated with their integration at a central level. It is, thus, possible that in overweight children, the alteration of postural control [39,40,41], which is likely due to the impaired effectiveness of the proprioceptive input originating from stress concentrations at the plantar region [42], possibly in combination with other factors able to affect the development of the lower limb musculoskeletal system (reductions in femoral anteversion, relative strength reductions, etc. [ 43]), can influence the whole-body movement during gait and, thus, consequently, reduce smoothness.
On the other hand, it was somewhat surprising to find that overweight children exhibit higher values of HR in the ML direction. In fact, such a result (which was previously observed even in a sample of children and adolescents who were overweight and obese by [28]) according to the commonly accepted interpretation of HR would suggest that they are characterized by better smoothness with respect to normal-weight individuals. However, there are several aspects that should be considered in order to correctly interpret such a finding. At first, although direct evidence is not available as the single-IMU configuration is unable to provide such data, it is possible that the gait pattern of our overweight children was characterized by a larger step width, a phenomenon that was previously reported in several studies [39,44,45,46]. The possible influence of step width on HR in ML was hypothesized by Raw-Lazzarini et al. [ 47], who found improved ML smoothness in older adults when walking on a treadmill with respect to an overground test; they attributed such changes to the different foot positions that characterized the two conditions [48]. On the other hand, Lowry et al. [ 49], who tested older adults walking at different speeds while adopting a narrow and wide base of support, did not find any difference in HR-ML in the case of preferred or wide step width. However, such a lack of difference could have been due to the fact that, in this latter case, the foot position was artificially constrained and not unconsciously adopted. Another interesting insight that could partly explain the ML results refers to the possibility that changes in step-to-step (AP and SI) and stride-to-stride (ML) smoothness characterize different aspects of gait, namely impairment or adaptability. To better clarify this hypothesis, we suggest that readers refer to the interesting papers of Moe-Nilssen et al. [ 50,51] and Helbostad et al. [ 52], who reported a similar apparent contradiction when examining the trunk acceleration variability. In particular, in the experiments described in [51], trunk acceleration variability during gait was calculated for two groups of older adults (fit and frail). The results showed that, as expected, frail subjects exhibited significantly higher variability in trunk accelerations in the AP and SI directions but, surprisingly, reduced variability in the ML direction. Helbostad et al. [ 52] found that older adults who underwent a fatigue protocol exhibited trunk acceleration variability during gait in the AP and SI directions that was higher with respect to non-fatigued individuals, but variability decreased in the ML direction. Such results have been interpreted by suggesting that not all features of the trunk acceleration can be considered representative of a situation of impairment. In particular, Moe-Nilssen suggested that different measures of variability may represent different aspects of locomotor control, being, for instance, those in the AP and SI directions indicative of “impairment”, and those of the ML direction indicative of “adaptability” [50]. Thus, we can speculate that the different alterations of HR in children, which originated from a mass excess, express different aspects of locomotor control and, thus, while HR in the AP direction can be considered a suitable measure of gait impairment, HR in the ML direction should be rather treated as an indicator of adaptability to the biomechanical and neuromuscular conditions imposed by overweight, which possibly reflect in changes in gait strategy (for instance, the increased step width).
Of course, the study has some limitations that should be acknowledged. Firstly, due to the relatively limited sample size, it was not possible to stratify the participants in such a way as to consider the effects of age and sex that might exist because of different trajectories of psychophysical development. Secondly, since the experimental trials were performed only in the case of level walking along a straight path at a self-selected speed, it has not been possible to investigate how other environmental conditions (e.g., curved paths, even and uneven terrains) or walking speeds influence HR values [12,17,18]. Moreover, since we did not have available a detailed medical record for the participants, nor did we have the chance to directly perform an accurate screening for the presence of pathological lower-extremity abnormalities (for instance, pes planus, genu varum or valgum, etc.), we are not able to clarify how the possible presence of such conditions could have affected the results. Lastly, as previously mentioned, it is possible that specific features of the body composition of overweight children might be responsible for some of the observed alterations in trunk acceleration (and, thus, consequently in HR values). In particular, further studies should be carried out in the future to elucidate the mechanisms by which factors such as fat distribution across the body, lower-extremity or appendicular lean mass, muscle mass of the lower extremities, etc., are able to influence the smoothness of gait.
## 5. Conclusions
Overweight (but not obese) children exhibit substantially similar gait patterns in terms of spatio-temporal parameters. However, the analysis of the gait smoothness, quantified by means of HR values, detected significant differences, with respect to normal-weight children, which involve both the AP and ML directions. While few data are available for individuals characterized by mass excess, the existing literature suggests that a reduction in HR in the AP direction is indicative of worse smoothness of gait and, thus, in this context, the use of HR would allow the detection of subtle alterations of gait even in the presence of an apparently regular gait. However, the fact that HR in ML was found to be significantly higher in overweight children seems to contradict, to some extent, this straightforward interpretation. This raises the need to rethink such concepts, or, at the very least, a specification of the way in which they should be interpreted depending on the considered context and source of possible gait anomalies. Here, we suggest that HR in the ML direction may be affected by specific biomechanical changes adopted by overweight children to optimize their walking efficiency (i.e., an increase in step width). However, this hypothesis needs further verifications, even considering that lateral trunk accelerations show different behavior with respect to those of AP in terms of variability. In any case, the use of HR, which relies on a relatively simple experimental approach and data processing, has certainly several advantages (limited intrusiveness, possibility to perform the tests under very ecological conditions), which makes its use recommendable as a screening tool to detect gait alterations early on that are associated with overweight and to assess the effectiveness of interventions targeted at improving mobility.
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|
---
title: Rotational Distortion and Compensation in Optical Coherence Tomography with
Anisotropic Pixel Resolution
authors:
- Guangying Ma
- Taeyoon Son
- Tobiloba Adejumo
- Xincheng Yao
journal: Bioengineering
year: 2023
pmcid: PMC10045376
doi: 10.3390/bioengineering10030313
license: CC BY 4.0
---
# Rotational Distortion and Compensation in Optical Coherence Tomography with Anisotropic Pixel Resolution
## Abstract
Accurate image registration is essential for eye movement compensation in optical coherence tomography (OCT) and OCT angiography (OCTA). The spatial resolution of an OCT instrument is typically anisotropic, i.e., has different resolutions in the lateral and axial dimensions. When OCT images have anisotropic pixel resolution, residual distortion (RD) and false translation (FT) are always observed after image registration for rotational movement. In this study, RD and FT were quantitively analyzed over different degrees of rotational movement and various lateral and axial pixel resolution ratio (RL/RA) values. The RD and FT provide the evaluation criteria for image registration. The theoretical analysis confirmed that the RD and FT increase significantly with the rotation degree and RL/RA. An image resizing assisting registration (RAR) strategy was proposed for accurate image registration. The performance of direct registration (DR) and RAR for retinal OCT and OCTA images were quantitatively compared. Experimental results confirmed that unnormalized RL/RA causes RD and FT; RAR can effectively improve the performance of OCT and OCTA image registration and distortion compensation.
## 1. Introduction
Optical coherence tomography (OCT) is a non-invasive medical imaging technology that has been broadly used in ophthalmology clinics and research laboratories [1,2,3]. For clinical OCT systems, the acquisition of a 3D volume normally takes several seconds. Within the acquisition, a fixation target is usually used to minimize voluntary eye movements. However, there are still inevitable involuntary eye movements [4], which cause image drift and distortion that affect the image quality and clinical interpretation. Different approaches have been introduced to compensate for eye movements [5]. Image registration is a simple and low-cost strategy widely used in commercial systems [6,7,8]. Image registration benefits OCT data processing from two aspects. First, image registration can help to align repeated B-scans at the same location. OCT images inherently suffer from speckle noise. Averaging a few images taken from the same location is a common way to reduce noise [9,10,11,12,13]. However, averaging is always affected by the image displacement caused by eye movement. Therefore, image registration is frequently used to compensate for the movement to enhance image quality. Additionally, registered repeated B-scans are the prerequisites for OCT angiography (OCTA) data processing algorithms [14,15]. Established OCTA processing methods, such as speckle-variance [16], phase-variance [17], optical microangiography (OMAG) [18], and split-spectrum amplitude-decorrelation angiography (SSADA) [19], compute the signal variance of a certain number of repeated B-scans. With the assumption that the signal of blood flow is variable compared to that of static tissues, the blood vasculature can be extracted by computing the signal variance of each pixel [16,20,21]. As the computation assumes that the B-scans are recorded exactly at the same location, the repeated images have to be registered precisely to compensate for the movement and allow pixel-wise comparison. Second, registration between the consecutive B-scans is required to correct the vasculature distortion and discontinuity in en face OCTA images [4,22].
Image registration is also an imperative step for recently emerging optoretinography (ORG) [23]. ORG measures the stimulus-evoked intrinsic optical signal (IOS) changes, which reflect the functional status of retinal photoreceptors and inner neurons [23]. As ORG has a much higher spatial resolution than electroretinography (ERG), it has been actively studied in recent years [24,25,26,27,28,29,30,31]. OCT-based ORG maps the IOS amplitude [25,30] and phase [26,27,28,31] changes in the retina evoked by visible light stimulation. An ORG study typically records the retina in three phases including pre-stimulation, stimulation on, and post-stimulation. Therefore, a relatively long imaging time is needed, and inevitable eye movements may occur during the image acquisition. On the other hand, the photoreceptor outer segment shrinkage, a typical phenomenon observed in ORG, is only several hundred nanometers [26,29]. A small image movement will greatly affect the interpretation reliability of the experimental result.
OCT image registration has been studied since it started to be applied in ophthalmology [2,5]. The common strategy is to register the image displacement by applying a transformation matrix to A-lines or B-scans. The transformation matrix is optimized by maximizing the cross-correlation coefficient between the images to be registered. In previous studies, only x, y, and z direction shifts were considered [22,32,33,34]. However, the rotational movement always happens simultaneously with translational movement [4]. Therefore, for precise registration, compensation for the rotational movement should also be considered.
In OCT, it is known that the lateral resolution is diffraction-limited, while the axial resolution is defined by the spectral bandwidth of the light source [1]. The OCT instruments typically have anisotropic resolutions in the lateral and axial dimensions. Recently, we tried to compensate for eye movement by registering the B-scans for both rotational and translational degrees of freedom. We observed that residual distortion (RD) and false translation (FT) always existed in the OCT images with anisotropic pixel resolution even after the registration. The RD and FT provide the evaluation criteria for image registration.
In the following sections, we will first demonstrate a conceptual simulation of the effect of the lateral and axial resolution ratio (RL/RA) on rotational distortion, and then experimentally validate an image resizing assisting registration (RAR) approach for rotational distortion compensation in OCT and OCTA images. Both theoretical analysis and experimental results confirmed that RL/RA normalization can significantly improve registration performance.
## 2.1. Conceptual Illustration of Rotational Distortion
Figure 1 is a schematic illustration of the compensation performance of rotational movements in OCT images with isotropic (RL/RA = 1) and anisotropic (RL/RA ≠ 1) resolutions. Figure 1a shows the first (1st) scan with OCT illumination perpendicular to the bottom line of the triangular target, and Figure 1b corresponds to the second (2nd) scan of the same target with a rotational movement. As shown in Figure 1c–e, the rotational displacement in the OCT with isotropic resolution (RL/RA = 1) can be perfectly corrected. On the contrary, the image distortion remained in the registered scan with anisotropic resolution (RL/RA ≠ 1) after the rotational correction (Figure 1f–h).
## 2.2. Quantitative Simulation of Rotational Movement
Figure 2 illustrates the procedures for quantitative assessment of the rotational eye movement and image registration performance. Figure 2a is a simulated retinal B-scan, working as the reference frame, without rotational movement. Each pixel signal can be represented as Ps(xs,ys) in Cartesian coordinates and Ps(rs,θs) in polar coordinates, which follows the relationship between Cartesian and polar coordinate systems [1]. [ 1]x=rcos(θ), y=rsin(θ)r=x2+y2, θ=tan−1(yx) Figure 2b shows angular rotation caused by an eye movement. As our focus is the rotational movement, to simplify the simulation, the translation movement is assumed as 0, and the rotational movement is denoted as ϕ. As the retinal position is typically guided by the fixation target in OCT, the pivot is assumed at the center of the fovea, noted as Pr[0,0] in Figure 2b. To simplify the calculation, the origin of the coordinate system is set at the pivot. The corresponding image pixel with rotational movement is represented as Pr(xr,yr) in Cartesian coordinates and Pr(rr,θr) in polar coordinates.
Considering the rotational movement only, the relationship between the source frame Ps and rotated frame *Pr is* shown as follows. [ 2]Pr(rr,θr)=Ps(rs,(θs+ϕ)) Therefore, the transformation of a certain point in Ps to Pr can be derived as [3] in polar coordinates and [4] in Cartesian coordinates. [ 3]rr=rs=xs2+ys2θr=(θs+ϕ)=tan−1(ysxs)+ϕ [4]xr=xs2+ys2cos(tan−1(ysxs)+ϕ)yr=xs2+ys2sin(tan−1(ysxs)+ϕ) To evaluate the effect of the RL/RA, the source frame and rotated frame can be resized as follows: [5]xs′=xsn, ys′=ys [6]xr′=xrn, yr′=yr where n = RL/RA. Thus, the resized Ps(xs,ys) and Pr(xr,yr) can be represented as Ps′(xs′,ys′) (Figure 2c) and Pr′(xr′,yr′) (Figure 2d). Then, Equation [7] can be derived from [4]–[6]. [ 7]xr′=1n(nxs′)2+ys′2cos(tan−1(ys′nxs′)+ϕ)yr′=1n(nxs′)2+ys′2sin(tan−1(ys′nxs′)+ϕ) Equation [7] represents the relationship between Ps′(xs′,ys′) and Pr′(xr′,yr′), which was used for further registration computation.
## 2.3. Image Registration
Image Pr′ was registered to Ps′ by executing a rotation with an angle of ϕ′ followed by a translation with a vector of t(xt,yt). The registered image was denoted as Pr″. Therefore, the relationship between Pr″ and Pr′ can be expressed as follows. [ 8]Pr″step1(r,θ)=Pr′(r, (θ+ϕ′)) [9]Pr″=Pr″step2(x,y)=Pr″step1(x, y)+t(xt,yt) The registration performance can be validated by [10]Dsum(t(xt,yt),ϕ′)=∑∑(xs′ij−xr″ij)2+(ys′ij−yr″ij)2 where Ps′ij(xs′ij,ys′ij) and Pr″ij(xr″ij,yr″ij) represent the same locations of the source image Ps′ and the registered image Pr″. Therefore, Dsum represents the sum of the on-image distance between Ps′ij and Pr″ij with the unit of pixel. The optimized ϕ′ and t are achieved by minimizing Dsum.
## 2.4. Displacement Characterization
The images are considered as properly registered when ϕ′ and t(xt,yt) are optimized (Figure 2f). Then, the RD is characterized. RD is defined as the distance between the location of an individual pixel between the resized source frame (Ps′(xs′ij,ys′ij)) and the registered rotated frame (Pr″(xr″ij,yr″ij)), which is shown as [11], [11]RD(i,j)=(nxs′ij−nxr″ij)2+(ys′ij−yr″ij)2 where, RD(i,j) denotes the RD at lateral (i) and axial (j) location. The purpose of defining RD in the real dimension is to allow the comparison of RD over images of different RL/RA values.
We assessed the registration performance over various ϕ and RL/RA to investigate the relationship among ϕ, RL/RA, and RD. Corresponding to different RL/RA and ϕ, the RDs are represented in Figure 3. It was observed that there is always RD after the registration of rotational movement for OCT images with anisotropic pixel resolution; RD increases significantly as RL/RA and ϕ increase. The dark bands (relatively lower intensity) in the center of each image were because of the pivot (Figure 3). The bands were not symmetric when the ϕ was 2.5 or 1 degree, because the initial rotational movement we simulated was counterclockwise.
## 2.5. Characterization of the Transformation Occurred during Registration
When the optimal registration is achieved, the corresponding transformation information is recorded (Figure 4). The rotational compensation (ϕ′) is represented in Figure 4a. The result showed that all ϕ′ increases with RL/RA value increase; ϕ′ equals the initially introduced angle (ϕ) for RL/RA = 1, whereas ϕ′ is larger than ϕ for RL/RA ≠ 1. The translational compensation t(xt,yt) is represented in Figure 4b,c. Because only the rotational movement is introduced, the t(xt,yt) represents the translation artifact away from the original location. Thus, we can consider t(xt,yt) as FT. The result shows that FT increases as RL/RA and ϕ angle increase. The lateral FT is significantly larger than the axial FT. Figure 4b,c indicates that if RL/RA is not normalized, the registration for rotational movement will introduce FT to the images, especially in the lateral direction. We will describe the effects of FT on 3D OCTA registration in Section 4.2: Registration of 3D OCT image.
An explicit analysis can help us to understand how the ϕ′ and t(xt,yt) are affected by RL/RA. Figure 5a shows the reference frame Ps and the rotated frame Pr, both with RL/RA = 1. Pr(xr,yr) is matched with Ps(xs,ys) at the same location after image rotation by angle ϕ. Figure 5b shows Ps′(xs′,ys′) and Pr′(xr′,yr′) with RL/RA = n. The original rotational angle ϕ is changed to ψ and defined as [12]. [ 12]ψ=θs′−θr′ ψ reflects how the ϕ is changed when RL/RA is changed to n. We can obtain [13] by first converting the angle to triangular function and then substituting [5] and [6] for [12]. [ 13]ψ=tan−1(ys′xs′)−tan−1(yr′xr′)=tan−1(ysxsn)−tan−1(yrxrn)=tan−1(nysxs)−tan−1(nyrxr) As the retina is an elongated structure, for small RL/RA values, the majority of the points satisfy the small angle approximation. Thus, [13] can be derived as [14]. [ 14]ψ=(nysxs)−(nyrxr)=n(ysxs−yrxr)=n(θs−θr) Considering the definition of ϕ, the relationship between ψ and ϕ can be described as [15]. [ 15]ψ=nϕ
The ratio between ψ and ϕ (ψ/ϕ) equals n. Note that ψ corresponds to each pixel, and it is a function of location. [ 15] is correct only if the small angle approximation is satisfied. For large RL/RA values, the image will be more compressed along the lateral direction, which causes the small angle approximation unsatisfied, and ψ/ϕ becomes smaller than n.
As ψ reflects the ϕ after RL/RA is changed to n, it can be considered as an approximation of ϕ′. Figure 5d depicts the ratio between ϕ′ and ϕ; it is close to n for small RL/RA values and becoming smaller than n for the large RL/RA values. This result supports that ψ is an approximation of ϕ′.
Figure 5c showed that if the rotation of ψ is compensated, Pr′ is changed to Pr″step1, Pr″step1(θr″step1,rr″step1) is close to Ps′(θs′,rs′). However, they are not completely matched, because after the rotation of Pr″step1 by ψ, θr″step1=θs′, whereas rr″step1<rs′. It was already demonstrated in the illustration (Figure 5c) that after the rotation, there was still a residual between the two points. The lateral residual was proportional to sine(θs′), and the axial residual was proportional to cosine(θs′). For the second step, these residuals would be compensated; therefore, the compensated lateral residual is much larger than the axial residual.
Note that the real registration computes the two steps simultaneously, then assesses the final result. Thus, in the optimized registration, it is not necessary to rotate exact ψ followed by a t(xt,yt). It can be a rotation close to ψ with a corresponding t(xt,yt) together, which gives better Dsum. Therefore, the real computation result can be different from this explicit analysis. Nevertheless, this analysis helps to understand the relationship between ϕ, ϕ′, and t(xt,yt), especially for the scenario when RL/RA is not too large.
## 2.6. Summary
In summary, the theoretical simulation indicates that for OCT image registration, there is always RD and FT if the RL/RA ≠ 1. A preprocessing procedure to normalize the image to RL/RA = 1 is important for accurate registration to correct rotational movement.
## 3.1. Human Subjects
This study was approved by the Institutional Review Board of the University of Illinois at Chicago and followed the ethical standards stated in the Declaration of Helsinki. Each subject provided informed consent before participation in the research. The repeated OCT B-scans and the 3D OCT/OCTA images were acquired from a healthy 27-year-old female and a healthy 36-year-old male, respectively.
## 3.2. Imaging System and Data Acquisition
A custom-designed SD-OCT was developed for human retina imaging (Figure 6). Briefly, a broadband (M-T-850-HP-I, Superlum, Cork, Ireland, λcenter=850 nm, Δλ=165 nm) superluminescent diode (SLD) was used as the light source. A fiber coupler (TW850R2A1, Thorlabs, Newton, NJ, USA; 90:10) divided the OCT light to the sample ($10\%$) and reference ($90\%$) arms. A custom-designed spectrometer was constructed with a line CCD camera (AViiVA EM4, E2V Technologies, Chelmsford, UK; 2048 pixels) and a transmission grating (Wasatch Photonics, West Logan, UT, USA; 1200 line/mm). The axial and lateral pixel resolutions were 1 µm and 10 µm, respectively. A fixation target with red light was used to minimize voluntary eye movements. For OCT recording, the illumination power on the cornea was ∼600 μW. The repeated OCT B-scans were acquired from the macular region covering 5.4 mm retina, ~18 eccentricity degrees. The total B-scan number was 90 with a frame speed of 100 frames per second (fps). The 3D OCT volume was acquired at the macular region with a size of 3.5 mm × 3.5 mm for the OCTA image. The number of B-scan repetitions for OCTA construction was 4. The frame speed was 200 fps. The total recording time was 7 s.
## 3.3. Data Processing
OCT B-scans were reconstructed from raw data through k-sampling, numerical dispersion compensation, Hanning windowing, fixed pattern removal, and fast Fourier transformation (FFT). Then, RAR was performed following the workflow of resizing the image to RL/RA = 1, registration, and resizing the image to the original RL/RA (Figure 7). The image was resized using the Matlab (R2021a, Portola Valley, CA, USA) built-in function “imresize”, with interpolation mode “nearest”. The images were registered by the ImageJ plugin “MultiStackReg” (v1.4) with mode “rigid”. “ MultiStackReg” is based on the minimization of the mean square intensity difference between a reference and a moving image [5,35], which has been demonstrated to be effective for retinal OCT images [12,13,22,36]. Choosing the “rigid” mode was to compensate for both translational and rotational eye movement. The compensated rotational and translational movements (Figure 8a,b) were calculated from the transformation matrix file generated by “MultiStackReg”. The 2D correlation coefficient (CC) of repeated B-scan data (Figure 8b) was computed by Matlab built-in function “corr2”, and a single CC point was computed using each of the images and the mean image of the stack. The CC of the consecutive B-scans of the 3D OCT/OCTA data was computed in two steps: first, to obtain the mean B-scan by averaging the B-scans at the same location (every 4 frames), and second, to calculate the CC of the mean B-scans at the adjacent locations. The image line profile was computed by the ImageJ function “Plot profile” with the line width “5”.
The OCTA signal was computed via the speckle variance method; in other words, the hemodynamic signal was extracted by computing the intensity variance of the repeated B-scans. For post-processing, contrast enhancement and strip suppression were used to enhance the hemodynamic signal.
## 4.1. Registration of Repeated B-Scans
Without registration, the retinal repeated OCT B-scans were unstable (supplemental material S1, left video) because of eye movement. To compensate for the movement, direct registration (DR) and RAR were applied to the image stack. The result showed that both DR and RAR can stabilize the images. However, the image stack with DR was not perfectly registered, and the image distortion was observed over frames (Figure 8(c1) and S1, middle video); with RAR, the image stack was well overlapped, and no significant movement was observed (Figure 8(c2) and S1, right video).
The rotational and translational compensation were recorded and plotted in Figure 8a. The rotational compensation of RAR was smaller than DR. The lateral translational compensation of RAR and DR was different, whereas the axial translational compensation was very similar. These results were consistent with the theoretical simulation (Figure 4). The registration performance was validated by the 2D correlation coefficient (CC) (Figure 8b). The CC of RAR was higher than DR for every frame, which means that RAR was more effective than DR. The registration performance was further investigated by comparing the mean image of the entire stack. The mean image of DR (Figure 8(c1)) was more blurred than that of RAR (Figure 8(c2)). We evaluated the sharpness of the images by the gradient method [37]. The sharpness of the mean image of RAR was $15\%$ higher than that of DR. The detailed differences were validated by the zoom-in view and line profiles (Figure 8d). The mean image of RAR showed a clearer structure and better separation of individual retinal bands. For instance, Bruch’s membrane was more visible in the mean image of RAR.
## 4.2. Registration of 3D OCT Image
Figure 9a shows the resliced B-scan along the slow scan direction of OCT 3D data. Before the registration, severe eye movement was observed (Figure 9(a1)). After DR (Figure 9(a2)) and RAR (Figure 9(a3)), the distortion caused by the eye movement was significantly reduced. The registration information is recorded and plotted in Figure 9b. Similarly to Figure 8a, the rotational compensation of RAR was smaller than that of DR, the lateral translation of RAR was different from that of DR, and the axial translation of RAR was very similar to that of DR. These results are consistent with those of the theoretical simulation (Figure 4). The registration performance is validated in Figure 9c. It shows the CC of two frames at two consecutive locations. For each of the consecutive B-scan pairs, the CC of RAR is larger than DR.
Figure 10a shows representative en face OCTA processed with DR and RAR. The black regions at the top and bottom areas were caused by zero filling when part of the image moved out of the boundary during the image registration. The zoom-in view of the OCTA en face image with RAR showed better vessel connectivity (Figure 10(b1)), less vessel distortion (Figure 10(b2), and a smoother vessel boundary (Figure 10(b3)). Additionally, better capillary vessel visibility was observed in all of the zoom-in views of RAR. Figure 10c shows the representative OCTA B-scans processed by DR and RAR from the same location. It is observed that the OCTA B-scans of DR (Figure 10(c1)) have a higher background signal than that of RAR (Figure 10(c2)). Figure 10d shows the representative OCT B-scans of the same frame registered by DR and RAR. The black region was caused by zero filling during the registration. This black region was smaller in RAR because the rotational and axial translational compensation of RAR was smaller than that of DR.
## 5. Discussion
To the best of our knowledge, this is the first comprehensive study of the compensation for the rotational movement of retinal OCT images. Anisotropic pixel resolution and elongated retinal structure are the two special characteristics that make OCT retinal image registration distinguishable from other biomedical imaging modalities. Both the theoretical simulation and the experimental validation demonstrated that the normalization of RL/RA is important for the registration of retinal OCT images with rotational movement.
We theoretically demonstrated the registration effectiveness of OCT images with an isotropic resolution better than that of the images with anisotropic resolution. First, we showed that for images with various RL/RA values, except RL/RA = 1, unignorable RD was observed (Figure 3). This meant that only the OCT images have an isotropic resolution; otherwise, they cannot be perfectly registered. Second, we showed that for images with anisotropic resolution and rotational movement, registration would introduce FT, which is larger in the lateral direction than in the axial direction. This phenomenon can cause significant distortion in the registration of 3D OCT/OCTA data.
The experimental results were consistent with the theoretical simulation. The experimental validation of registration for anisotropic and isotropic resolution OCT images was performed via DR and RAR. RAR showed better performance for both the repeated OCT B-scans and the 3D OCT data. The registration performance was validated via CC (Figure 8b and Figure 9c). The compensational transformation information of the registration process was recorded, and all were consistent with the theoretical simulation.
RAR can be used to solve the registration problem caused by the anisotropic resolution of OCT images by normalizing RL/RA before registration. The advantages of RAR can be summarized as follows.
The compensation for the image displacement caused by movement is the primary characteristic of an OCT registration algorithm. Compared to DR, RAR is more effective in displacement correction. The direct evidence is the CC, which was higher in the images processed with RAR for all the frames in all the data. The other evidence is provided by the mean images and en face images, which were clearer and showed more detail in RAR than in DR.
The three OCT retinal images in Figure 7a were recorded from the same eye at the same location, with different eye directions. The RL/RA of the images was 10. The direction angular differences of the second and third images compared to the first image were 1.57 and −2.29 degrees, respectively. As Figure 7b shows, DR had poor registration results, consistent with the theoretical simulation (Figure 3), which showed that when the rotational movement is large, such as 1 or 2 degrees, the RD can be as large as several hundreds of micrometers. If we directly look at the patterns of the images, we can easily see that the patterns in these three images were very different. In other words, the second and third images were totally distorted because of retinal direction differences. That was why DR lost the capability of registering them together. However, RAR worked well for this case; the retinal direction was recovered, and the overall patterns were similar. This scenario may arise when comparing two retinal OCT images recorded at different periods, where the retinal direction changes dramatically between two acquisitions. Registration that digitally recovers the retinal direction and corrects the distortion can allow a better and more detailed comparison. This will be very helpful for longitudinal clinical monitoring and lab research.
In most quantitative OCTA studies, the blood vessel structure information is extracted from the OCTA en face image [14], such as blood vessel density [38,39,40], blood vessel tortuosity [41,42], and blood vessel caliber [39,42]. Figure 10 shows that RAR can truly represent blood vessel structures such as density, continuity, smoothness, and tortuosity, which can provide a robust precondition for OCTA quantitative feature extraction and future analysis.
Because of the transformation that occurred during the registration, part of the image was moved out of the image boundary, leaving a blank region in the opposite direction (Figure 10d) as a result. In the OCTA en face image, this blank region corresponded to the black regions at the top and bottom (Figure 10a). Because the blank parts contained no information, it was better to keep them as small as possible. Both lateral translation and rotation were responsible for these blank regions. The lateral translation directly moved the image out of the boundary; the rotational compensation rotated the image and moved part of the image out of the boundary. *In* general, the axial translational compensation can also leave a blank region. However, there is always free space at the top and bottom of OCT B-scans; thus, the useful area is not disturbed. Figure 10d shows that the en face image processed by RAR had a small black region compared to DR. The reason is that first, RAR did not introduce TF and thus had a small lateral translation; second, RAR had a much smaller rotational compensation than DR (Figure 9b), which barely generated a new blank region. Therefore, RAR can preserve a large useful area of the image.
In the simulation, the lateral FT was much larger than the axial FT (Figure 4). However, in the experiments, the compensated lateral translation was smaller than the compensated axial translation (Figure 8 and Figure 9). This is because, in the experiment, the compensated translations were composed of two parts; one was the image movement caused by the eye movement, and the other was FT. Because the eye movements along the axial direction were much larger than those in the lateral direction, the total compensated axial translation was larger than the axial translation.
One limitation of this study is that in the simulation, we only simulated cases where the foveal center was the pivot. In the real world, the pivot may not always be the foveal center; thus, the rotation change might be more complicated.
## 6. Conclusions
In this study, we proposed a new image registration strategy, RAR, for precise OCT/OCTA registration processing. We first theoretically demonstrated that without pixel resolution normalization, direct registration will introduce RD and FT, which distorts the images. To avoid RD and FT, we proposed RAR. Then, the effectiveness of RAR was demonstrated by OCT/OCTA data. This study demonstrated that RAR has better performance than DR. For OCT/OCTA image post-processing and future OCT/OCTA registration algorithm design, the normalization of pixel resolution should be seriously considered.
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|
---
title: Beneficial Effects of Viable and Heat-Inactivated Lactobacillus rhamnosus GG
Administration on Oxidative Stress and Inflammation in Diet-Induced NAFLD in Rats
authors:
- Laura Arellano-García
- Jenifer Trepiana
- J. Alfredo Martínez
- María P. Portillo
- Iñaki Milton-Laskibar
journal: Antioxidants
year: 2023
pmcid: PMC10045382
doi: 10.3390/antiox12030717
license: CC BY 4.0
---
# Beneficial Effects of Viable and Heat-Inactivated Lactobacillus rhamnosus GG Administration on Oxidative Stress and Inflammation in Diet-Induced NAFLD in Rats
## Abstract
Oxidative stress and inflammation are well-known triggers of NAFLD onset and progression. The aim of this study is to compare the potential benefits of a viable probiotic (*Lactobacillus rhamnosus* GG) and its parabiotic (heat-inactivated) on oxidative stress, inflammation, DNA damage and cell death pathways in the liver of rats featuring diet-induced NAFLD. The consumption of the steatotic diet led to increased final body and liver weights, higher hepatic triacylglycerol content, altered serum transaminase levels and enhanced oxidative and inflammatory status. Administration of the probiotic and the parabiotic partially prevented the body weight increase induced by the steatotic diet, whereas the probiotic caused more effective decreasing hepatic triglyceride content. Sharp but nonstatistically significant decreases in serum transaminase levels were also observed for both treatments. The reduction in antioxidant enzyme activities found in the nontreated animals fed the steatotic diet was partially prevented by both treatments (GPx activity). Similarly, the reductions in nonenzymatic antioxidant protection (GSH content) and total antioxidant capacity (ORAC) found in the nontreated rats were restored by the administration of both treatments. These results show that both viable and heat-inactivated *Lactobacillus rhamnosus* GG administration partially prevent steatotic diet-induced liver oxidative stress and inflammation induced in rats.
## 1. Introduction
Nonalcoholic fatty liver disease (NAFLD) prevails as the most common liver morbidity, representing the leading cause of liver-related morbidity and mortality [1] and becoming a major health menace worldwide. NAFLD encompasses a spectrum of hepatic conditions ranging from simple steatosis to more harmful stages including steatohepatitis (steatosis with inflammation and hepatocyte injury), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC) [2]. NAFLD is diagnosed when hepatic lipid accounts for more than $5\%$ of the liver weight without evidence of hepatocyte damage in the absence of excessive alcohol consumption [3,4]. Since the liver plays a key role on lipid and glucose metabolism, NAFLD is normally present in obese patients and represents a risk factor for the development of type 2 diabetes [5]. Indeed, the insulin resistance that is commonly present in obesity (the cornerstone for metabolic syndrome diagnosis) is considered the triggering event leading to excessive liver lipid accumulation (due to enhanced de novo lipogenesis and increased free fatty acid influx from white adipose tissue), resulting in hepatic steatosis [6]. As a result, the prevalence of NAFLD ranges from $60\%$ to $95\%$ among obese patients. Moreover, approximately $60\%$ of the individuals who suffer from diabetes have also been diagnosed with NAFLD [7]. Given the impact of this liver disease in further metabolic impairments, NAFLD is commonly known as the hepatic manifestation of metabolic syndrome [8].
One of the common characteristics among patients who suffer from NAFLD is the consumption of unbalanced diets. In this regard, the current trend is to replace traditional diets for a Westernized dietary pattern, which is characterized by high contents of saturated fats and sugar. An excessive consumption of high fat foods and added sugars represents a major risk not only for NAFLD development, but also for its progression [8]. Among added sugars, fructose has gained special attention due its lipogenic capacity, acting both as a substrate and as an inducer of lipogenic pathways in the liver [9]. Moreover, its metabolization results in a temporary depletion of intracellular phosphate and adenosine triphosphate (ATP) levels, provoking a decrease in protein synthesis, an elevation of oxidative stress, and mitochondrial dysfunction [10].
Even though the dietary pattern is clearly associated with NAFLD development and progression, there is also a complex network of factors (environmental and genetic factors) that act jointly in the onset of NAFLD [6]. In this regard, a “multiple-hit” theory has been proposed to understand the underlying mechanisms leading to NAFLD [6]. This theory describes the different “hits” that may compromise the adipose tissue (AT), the gastrointestinal tract and the liver functionality, by way of the triangular interplay among these elements and its relationship with NAFLD progress [5]. Factors such as an unhealthy dietary pattern or obesity may derive from adipocyte hypertrophy, which causes alterations in AT, such as insulin resistance. This leads to an increased lipolysis, and thus a higher secretion of free fatty acids (FFAs), and to an increased production of proinflammatory mediators (TNF-α, IL-1ß, and Il-6). The inflammatory state of AT contributes to liver inflammation and compromises its functionality, enhancing hepatic de novo lipogenesis and decreasing lipid ß-oxidation [5]. These alterations cause higher triglyceride (TG) synthesis, along with altered mitochondrial lipid oxidation and the production of lipotoxic intermediates in the liver. The production of these lipotoxic intermediates contributes to further hepatic inflammation and mitochondrial disfunction [6]. Indeed, impairments in this cell organelle lead to enhanced oxidative stress and to the production of ROS [6].
In addition, the state of the gastrointestinal tract is a key factor in NAFLD pathogenesis. In this regard, changes taking place in gut microbiota composition, namely dysbiosis (decreased bacterial diversity and richness, along with impaired gut barrier function and bacterial metabolite production), are crucial in this process. In this regard, microbiota-derived ethanol and its related metabolites (including acetaldehyde and acetate) contribute to changes in both enterocyte morphology and functionality (promoting endotoxin infiltration) and, therefore, to a rapid generation of ROS. Moreover, acetate represents a substrate for FA synthesis, which leads to increased circulating FFA levels [11]. This state of enhanced oxidative stress and inflammation in the liver contributes to hepatocyte death (apoptosis), which has been described as an additional “hit” influencing the progression of steatohepatitis towards more harmful stages [12].
Since the medical management of NAFLD is limited, the scientific community has been searching for alternative or complementary therapies that may be potentially beneficial for its amelioration or prevention. Given the aforementioned relationship between gut microbiota dysbiosis and inflammation, particular attention has been paid to treatments focused on reestablishing gut microbiota composition [13]. On this subject, probiotics have emerged as an interesting therapeutic tool for NAFLD management due to their capacity to down-regulate lipid synthesis, activate lipid oxidation, downregulate pro-inflammatory pathways, and modulate microbiota composition in animal models [14]. Although proven effective, probiotic-based therapies have some limitations. According to the Food and Agriculture Organization/World Health Organization (FAO/WHO), probiotics may predispose some individuals to certain side effects such as systemic infections, deleterious metabolic activities, excessive immune stimulation, and gene transfer [15]. This, coupled with the difficulty to maintain the viability and safety of microorganisms during their storage and industrial processing, has increased the interest in treatments based on inactivated bacteria. Consequently, parabiotics, which are nonviable microbial cells (intact or broken) or crude cell extracts that may confer benefits when consumed in enough quantities [16], have emerged as plausible alternative to overcome the limitations of probiotics.
In this context, the current research aimed to compare the effects of a probiotic (*Lactobacillus rhamnosus* GG), and its parabiotic, on oxidative stress, inflammation, DNA damage, and cell death pathways in the liver of rats featuring liver steatosis induced by a high-fat and high-fructose diet.
## 2.1. Animals, Diets, and Experimental Design
A total of thirty-four (8–9-week-old) male Wistar rats (Envigo, Barcelona, Spain) were used to perform the experiment, which took place in accordance with the institution’s guide for the care and use of laboratory animals (M$\frac{20}{2021}$/214). Rats were housed in polycarbonate conventional cages (two rats per cage) and placed in an air-conditioned room (22 ± 2 °C) with a 12 h light–dark cycle. After six days of adaptation, animals were distributed into four different experimental groups. The first group of rats was fed a standard laboratory diet (C group; $$n = 8$$) (D10012G; Research Diets, New Brunswick, NJ, USA). The remaining three groups of animals were fed a high-fat high-fructose diet (D21052401; Research Diets, New Brunswick, NJ, USA) (Table 1). The rats fed the obesogenic diet received either the diet alone (HFHF group; $$n = 8$$) or supplemented with a commercially acquired viable probiotic (*Lactobacillus rhamnosus* GG, Ferring Pharmaceuticals, Switzerland) (PRO group; $$n = 9$$) or the same probiotic as a parabiotic (*Lactobacillus rhamnosus* GG heat-inactivated) (PAR group; $$n = 9$$). The probiotic was diluted in phosphate-buffered saline (PBS) containing $5\%$ of sucrose, ensuring a dose of 109 CFU/day as described elsewhere [17,18]. In the case of the parabiotic, which was inactivated by heat treatment (80 °C for 20 min), as explained elsewhere [19,20], the same probiotic- and sucrose-containing PBS dilution was used (ensuring a dose of 109 CFU/day). The animals in the C and the HFHF groups received sucrose-enriched PBS as the vehicle. These experimental conditions were maintained for six weeks, an experimental period length that was selected according to the experimental conditions used by other authors to test the effects of probiotic administration in the management of NAFLD [14]. All the treatments were administered daily via oral gavage. Animals had free access to food and water, and body weight and food intake were measured on a daily basis.
At the end of the experimental period (6 weeks), the animals were anesthetized (chloral hydrate) and euthanized after fasting (8–12 h) via cardiac exsanguination using a sterile syringe and needles. Following sacrifice, the livers were dissected using tweezers and scissors, weighed, and immediately frozen in liquid nitrogen. Blood samples were centrifuged (1000× g for 10 min, at 4 °C) for serum extraction. All samples were stored in an ultrafreezer at −80 °C until analysis.
## 2.2. Liver Triacylglycerol Content and Serum Transaminases
Total hepatic lipids were extracted following the method described by Folch et al. [ 21]. The lipid extract was dissolved in isopropanol, and the triacylglycerol content was measured via spectrophotometry using a commercial kit (Spinreact, Barcelona, Spain). As for the assessment of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, commercially available kits were also used (Biosystems, Barcelona, Spain).
## 2.3.1. Lipid Peroxidation Measurement
Rat liver samples were homogenized and lipid peroxidation was determined by using a commercial TBARS assay kit (Cayman Chemical, Ann Arbor, MI, USA). According to the manufacturer’s instructions, thiobarbituric acid reactive substances (TBARS) were measured as a marker for lipid peroxidation. This method is based on the reaction of malondialdehyde (MDA) and thiobarbituric acid (TBA) in an acid medium. The amount of MDA-TBA adduct was quantified in an Infinite 200Pro plate reader (Tecan, Männedorf, Zürich, Switzerland). Results were expressed as µM MDA/mg of tissue.
## 2.3.2. Total Antioxidant Capacity Determination
Rat liver homogenates were used to analyze the total antioxidant capacity by using the commercial kit OxiSelect Oxygen Radical Antioxidant Capacity (ORAC) activity assay (Cell Biolabs, San Diego, CA, USA). Briefly, the ORAC assay was performed using fluorescein as a fluorescence probe. AAPH (2,2-azobis [2-amidinopropane] dihydrochloride) was utilized as a free radical initiator to produce peroxyl radicals. Thus, AAPH was added to the sample and the fluorescence was reordered in an Infinite 200Pro plate reader (Tecan, Männedorf, Zürich, Switzerland). Furthermore, a calibration curve was built with Trolox solution. Finally, results were calculated based upon differences in areas under the fluorescence decay curve among blank, samples and standards, and final ORAC values were expressed as µM Trolox equivalents/mg tissue.
## 2.3.3. Determination of Nonenzymatic Antioxidant Glutathione
The glutathione colorimetric assay kit (Biovision, Milpitas, CA, USA) was used to determine the glutathione (GSH) concentrations in rat liver homogenates. This assay is based on the glutathione recycling system in the presence of GSH and the DTNB fluorophore. When DTNB is reduced, it produces a stable fluorescent product which can be detected in an Infinite 200Pro plate reader (Tecan, Männedorf, Zürich, Switzerland). Results were expressed as µg GSH/mg of tissue.
### EC 1.15.1.1)
Total superoxide dismutase activity in rat liver homogenates was analyzed by the SOD activity assay kit (Sigma-Aldrich, San Louis, MO, USA) according to the manufacturer’s instructions. The method is based in the generation of superoxide anions by means of the xanthine–xanthine oxidase system. Thus, the superoxide anion reduced WST-1, which was converted into WST-1 formazan and its absorbance was recorded in an Infinite 200Pro plate reader (Tecan, Männedorf, Zürich, Switzerland). In the presence of SOD, O2− underwent a dismutation into O2 and H2O2, thus decreasing the WST-1 formazan formation. The SOD activity (U/mL) was calculated according to the manufacturer’s instruction using the inhibition curve.
### EC 1.11.1.6)
Rat liver samples were homogenized with the aim of determining catalase activity according to Aebi [22]. Briefly, the reaction took place in a final volume of 250 µL containing 90 mM potassium phosphate buffer (pH 6.8) and it started with the addition of H2O2 (37.5 mM final concentration). Next, the H2O2 disappearance was measured at 240 nm spectrophotometrically. The results were expressed as nmol/min/µg of protein.
### EC 1.11.1.9)
Glutathione peroxidase activity was analyzed by measuring the H2O2 scavenging capacity using the GPx assay kit (Biovision, Milpitas, CA, USA). GSSG was formed upon the reduction of H2O2 by GPx, and it was recycled in its reduced state (GSH) by both glutathione reductase (GR) and reduced nicotinamide adenine dinucleotide phosphate (NADPH). Next, NADPH absorbance decrease was measured in an Infinite 200Pro plate reader (Tecan, Männedorf, Zürich, Switzerland), and GPx activity was expressed as GPx U/mL.mg of protein.
## 2.3.7. Determination of Total Proteins
Total protein was spectrophotometrically quantified in lysates and homogenates at 595 nm by Bradford assay [23], using bovine serum albumin as standard.
## IL-1β and TNF-α Determination
Interleukin 1 beta (IL-1β) and tumor necrosis factor alpha (TNF-α) amounts were determined in rat liver lysates by using commercial kits (RyD Systems, Minneapolis, MO, USA and ThermoFisher, Waltham, MA, USA, respectively).
## 2.5. Parameters Related to DNA Damage and Cell Death by Immunoblotting
For Poly (ADP-ribose) polymerase (PARP), H2A histone family member X (γH2AX), ATM serine/threonine kinase (ATM), phosphorylated-ATM (Ser 1981) and beta actin (ß-actin) protein quantification, liver samples (100 mg) were homogenized in 1 mL of cellular PBS (pH 7.4), containing protease inhibitors (100 mM phenylmethylsulfonyl fluoride and 100 mM iodoacetamide). The homogenates were centrifuged at 800× g for 5 min at 4 °C.
Immunoblot analyses were performed by loading 60 or 80 μg of total protein from liver extracts separated by electrophoresis in either 4–$15\%$ (PARP, γH2AX and ß-actin) or $7.5\%$ (p-ATM and ATM) SDS-polyacrylamide gels and transferred to polyvinylidene difluoride (PVDF) membranes (Merck, Darmstadt, Germany). The membranes were then blocked with $4\%$ BSA for 1.5 h at room temperature. Afterwards, they were blotted with the appropriate antibodies, PARP (1:1000; Cell Signaling, Danvers, MA, USA), γH2AX (1:1000; Abcam, Cambridge, UK), p-ATM (1:500; Novus Biologicals, Centennial, CO, USA), ATM (1:500; Abcam, Cambridge, UK) and ß-actin (1:1000; Cell Signaling, Danvers, MA, USA) overnight at 4 °C. Subsequently, membranes were incubated with polyclonal anti-mouse (1:5000) (Santa Cruz Biotech, Dallas, TX, USA) for γH2AX, p-ATM and ß-actin, and anti-rabbit (1:5000) (Santa Cruz Biotech, Dallas, TX, USA) for PARP and ATM, for 2 h at room temperature. The bound antibodies were visualized by an ECL system (Thermo Fisher Scientific Inc., Rockford, IL, USA) and quantified by a ChemiDoc MP Imaging System (Bio-Rad, Hercules, CA, USA). The measurements were normalized either by ß-actin or the phosphorylated isoform.
## 2.6. Statistical Analysis
Results are presented as mean ± SEM. Statistical analysis was performed using SPSS 24.0 (SPSS, Chicago, IL, USA). The normal distribution of data was assessed by Shapiro–Wilks test. Normally distributed parameters were analyzed by one-way ANOVA followed by the Newman–Keuls post hoc test. Significance was assessed at the $p \leq 0.05$ level.
## 3.1. Body and Liver Weights, Hepatic Triglyceride Content and Serum Transaminase Levels
At the end of the experimental period, the high-fat high-fructose diet feeding resulted in a significant increase in final body weight, compared to the control group. Despite not finding significant changes regarding this parameter in the animals fed the same steatotic diet and supplemented with the probiotic or the parabiotic, a partial reduction in final body weight was observed. Indeed, trends towards reduced final body weights were found in both groups ($p \leq 0.1$ for PRO and $p \leq 0.09$ for PARA) compared to the HFHF group (Table 2). As for liver weight, a similar pattern was appreciated. In this regard, all groups fed the high-fat high-fructose diet had a significant increase in liver weight compared to the C group. As opposed to the HFHF group, nonsignificant trends towards lower values were found in the groups fed the steatotic diet and supplemented with the probiotic and the parabiotic ($p \leq 0.1$ for PRO and $p \leq 0.07$ for PARA) (Table 2).
Regarding hepatic TG content, the animals fed the high-fat high-fructose diet showed a significant increase in this parameter in comparison to the animals fed the control diet, showing that liver steatosis was achieved. The administration of the probiotic significantly reverted this effect in comparison to the nontreated animals fed the high-fat high-fructose diet ($p \leq 0.05$). However, the reduction in hepatic TG content found in the animals in the PRO group did not reach that observed in the C group. As for the group receiving the parabiotic, no change in this parameter was found compared to the HFHF group (Table 2). As far as serum transaminases were concerned, both ALT and AST levels were significantly increased in the HFHF group compared to the C group. In the case of ALT, none of the tested treatments resulted in significant changes in comparison with the nontreated animals fed the steatotic diet. Despite not being statistically significant, it is worth mentioning that the reductions in serum ALT levels found in the PRO and PARA groups were $23.4\%$ and $40.1\%$ lower than those found in the HFHF group (respectively). A similar pattern was further observed with regard to serum AST levels. Additionally, in this case, the reductions found in the PRO and PARA groups did not reach statistical significance when compared to the HFHF group. However, the administration of the probiotic and the parabiotic resulted in reductions of $44.2\%$ and $39.8\%$ (respectively) in this parameter compared to the HFHF group.
## 3.2. Parameters Related to Oxidative Stress in Liver
To evaluate the effects of the treatments on the hepatic oxidative stress of the animals exposed to the high-fat high-fructose diet, we measured the antioxidant capacity of the treatments and the activity of key enzymes that contribute to redox homeostasis maintenance, as well as the content of nonprotein antioxidants and lipid peroxidation products. When the activity of antioxidant enzymes was analyzed, a significant reduction in superoxide dismutase (SOD) activity, along with a sharp decrease in glutathione peroxidase (GPx) activity, was found in the nontreated animals fed the high-fat high-fructose diet, compared to the control rats ($p \leq 0.001$ and $$p \leq 0.057$$ vs. control group, respectively) as shown in Figure 1. A tendency to higher catalase (CAT) activity was also observed in the animals of the HFHF group compared to the control group ($$p \leq 0.090$$). Concerning nonenzymatic antioxidants, there were no differences in total glutathione (tGSH; Figure 1) levels in the HFHF group, when compared to the C group ($$p \leq 0.18$$). As for lipid peroxidation product assessment, no changes in MDA content were found in the nontreated animals fed the HFHF diet compared to the animals in the C group. Nonetheless, the total antioxidant capacity (ORAC), showed a decrease, compared to the C group ($p \leq 0.001$).
Concerning the antioxidant enzyme activities, the treatments were not able to restore the SOD activity decrease found in the HFHF group. Nevertheless, a nonsignificant trend towards a higher GPx activity and a significant increase were observed in the groups treated with the probiotic and the parabiotic, respectively ($$p \leq 0.082$$; $p \leq 0.01$). Lastly, the hepatic CAT activity was not significantly modified by the high-fat high-fructose feeding. The groups supplemented with the probiotic or the parabiotic did not show significant differences with the HFHF group but displayed significant increases with regard to the control group ($p \leq 0.05$ and $p \leq 0.01$, respectively). Concerning the nonenzymatic antioxidant protection, both the probiotic and the parabiotic administration significantly increased the GSH content compared to the HFHF group ($p \leq 0.001$). Indeed, the values were significantly higher than those in the C group ($p \leq 0.001$ and $p \leq 0.01$ for PRO and PARA vs. C, respectively). Regarding the effects of the treatments on lipid peroxidation, no changes in MDA content were found neither in the PRO nor in the PARA group, compared to the animals in the C and the HFHF groups. As for the antioxidant capacity, the group fed the high-fat high-fructose diet and supplemented with the probiotic showed a nonsignificant trend towards higher values compared to the HFHF group ($$p \leq 0.068$$). In the case of the animals supplemented with the parabiotic, the sharp decrease in the antioxidant capacity derived from the high-fat high-fructose diet feeding was totally reverted ($p \leq 0.05$ vs. HFHF).
## 3.3. Parameters Related to Inflammation in Liver
Due to the key role of inflammation in the pathogenesis and progression of NAFLD, the hepatic levels of IL-1β and TNF-α, two well-known inflammatory markers, were analyzed. In this regard, 1L-1β levels increased by $20\%$ in the animals fed the high-fat high-fructose diet, compared to the control group, although this change did not reach statistical significance. Nonetheless, a sharp increase in TNF-α levels was observed in the HFHF group compared to the control animals (Figure 2).
As for the effects of the treatments, in both cases, the IL-1ß levels were similar to those found in the C and HFHF groups. In the case of TNF-α levels, animals treated with the probiotic showed a sharp but nonsignificant decrease in the hepatic levels of this cytokine compared to the HFHF group ($$p \leq 0.075$$). Lastly, the parabiotic-treated animals displayed significantly lower hepatic TNF-α content compared to the HFHF group ($p \leq 0.05$), reaching values similar to those found in the C group.
## 3.4. Parameters Related to DNA Damage and Cell Death by Immunoblotting
Owing to the harmful effects that both oxidative stress and inflammation have on DNA nature and cell viability, some of the key molecular markers of these processes were also studied. In this scenario, a very early response of mammalian cells to DNA double-strand breaks is the phosphorylation of histone H2AX at serine 139 (γH2AX), at the sites of DNA damage by the protein kinase ataxia-telangiectasia mutated (ATM). Firstly, the high-fat high-fructose feeding induced a reduction in the activation rate of ATM (p-ATM/ATM ratio) compared to the C group ($$p \leq 0.044$$) (Figure 3). By contrast, regarding the expression of γH2AX, no significant changes were observed between these same experimental groups.
Concerning the effects of the treatments on the aforementioned parameters, no differences were observed in ATM activation with either the probiotic or the parabiotic compared to the HFHF group. Regarding γH2AX protein expression levels, a reduction was noted in both treated groups compared to the HFHF group (−$61.90\%$ PRO; −$63.20\%$ PARA). These differences showed a statistical trend ($$p \leq 0.070$$ PRO vs. HFHF; $$p \leq 0.066$$ PARA vs. HFHF) that reached statistical significance when compared to the C group ($p \leq 0.05$ PRO vs. C; $p \leq 0.05$ PARA vs. C).
Regarding cell-death-related markers, the high-fat high-fructose diet-induced a significant increase in the protein expression of the cleaved fraction of PARP in comparison to the C group ($$p \leq 0.001$$). This effect was not reverted by either the probiotic or the parabiotic treatment (Figure 4).
## 4. Discussion
Unbalanced dietary patterns have been identified as a major contributor to the development of obesity and related metabolic alterations. In this regard, the consumption of diets rich in saturated fats and sugars (such as fructose) is known to impair glucose homeostasis and lipid metabolism, leading to the development of insulin resistance and NAFLD [24].
In the present study, feeding a diet rich in saturated fat and fructose to rats led to increased body and liver weight, along with a greater hepatic TG content, proving to be a dietary pattern effective to generate a model of steatosis. According to the reported results, the administration of a viable probiotic, as well as its heat-inactivated parabiotic, resulted in a slight decrease in both parameters (nonsignificant trends towards lower values). These results are in line with the available literature, in which the effectiveness of probiotic administration has been described for the management of obesity in both murine models and humans [25,26,27]. The lack of statistical significance obtained in the present study regarding these parameters may well be due to the selected experimental length, model and/or the probiotic strain. As for the parabiotic, similar results have been reported in a recently published study, despite the used experimental model (male C57BL/6 J mice), probiotic strain (*Lactiplantibacillus plantarum* K8) and experimental period length (14 weeks) being different [28]. Regarding the hepatic TG content, the administration of the probiotic resulted in a significant decrease in this parameter, which is in good accordance with the data published to date and reviewed elsewhere [14]. By contrast, the administration of the parabiotic did not ameliorate the liver TG accumulation induced by the high-fat high-fructose diet. Notwithstanding the scarcity of the available studies addressing the effects of parabiotics on hepatic lipid accumulation, it has been reported that the administration of an inactivated mixture of lactoferrin-expressing probiotic strains resulted in a lowered hepatic lipid content in mice fed a high-fat diet [29]. In spite of this apparent discrepancy, it must be noted that the experimental design used in that study differs significantly from that used in the present research.
Serum transaminase levels are another indicator that is commonly assessed when studying liver damage, as well as the potential benefits induced by the administration of bioactives. In this regard, the high-fat high-fructose diet caused a significant increase in the serum levels of ALT and AST, which is in good accordance with the vast majority of studies using similar experimental models [30,31,32]. In this case, neither the administration of the probiotic nor the parabiotic resulted in significant changes in these parameters, despite finding sharp reductions in both transaminase levels. These results are in accordance with those reported by Zhao et al. [ 33]. Moreover, several studies researching the potential usefulness of probiotics for NAFLD management have not reported changes in serum transaminase levels despite other benefits (such as decreased liver triglyceride content) being described [14].
Besides excessive hepatic lipid accumulation, alterations in the electron flow of the respiratory chain, leading to the formation of reactive oxygen species (ROS), also occur during the steatotic process [34], which result in an imbalance between ROS and antioxidant defenses in favor of the former [35,36]. Thus, some parameters related to oxidative stress were analyzed in the present study to better elucidate the potential benefits of probiotic and parabiotic administration in diet-induced NAFLD management.
The results show that the ability of the antioxidant enzymes SOD and GPx to neutralize ROS diminished in rats under the high-fat high-fructose diet, which is in good accordance with the reduction observed in the antioxidant capacity, measured by ORAC. However, the CAT enzyme activity, which catalyzes the decomposition of hydrogen peroxide to water and oxygen, and the nonenzymatic antioxidant GSH levels were not significantly modified in rats fed the steatotic diet. Due to the alteration of both SOD and GPx enzymatic activities induced by the high-fat high-fructose diet, a rise in superoxide anion and hydrogen peroxide production could be expected in this experimental model, which may induce a detrimental oxidative status, even though the oxidative stress of lipids was still rather nonexistent. Although controversial results have been reported with regard to changes in the antioxidant enzyme system observed in NAFLD models [37,38], the results reported in this study are in good accordance with those shown in several studies of rats fed a high-fat high-fructose diet [39,40,41,42]. In fact, in a rat model of obesity, steatosis and insulin resistance induced by a high-fat high-fructose diet, a down-regulation of SOD, GPx and hepatic total GSH content prompted an imbalance in the oxidant/antioxidant system [43]. Moreover, Feillet-Coudray et al. [ 43] argued that lipid peroxidation also remained very low after 20 weeks of high-fat high-fructose diet feeding. Thus, the authors argued that hepatic lipid accumulation induces moderate oxidative stress which is not sufficient to cause a significant MDA accumulation in the livers of animals under a high-fat high-fructose diet despite a marked oxidative status appearing at the end of the steatotic stage.
It is well known that probiotics play a key role as free radical scavengers, being able to reduce the damage caused by oxidation [44,45,46]. In addition, parabiotics also exhibit antioxidant activity, but the available literature that supports this is still scarce [47]. In the present study, when rats under high-fat high-fructose feeding were supplemented with a commercially acquired viable probiotic (*Lactobacillus rhamnosus* GG), this bacterium effectively increased hepatic GSH levels compared to the HFHF group. Moreover, probiotic administration was able to partially prevent ($$p \leq 0.08$$) the HFHF diet-induced GPx depletion. These effects were also observed when the selected probiotic was administered after heat inactivation (parabiotic). In this line, it was observed that the parabiotic was able to completely restore the down-regulation induced in GPx activity and the depletion of antioxidant capacity prompted by the high-fat high-fructose diet. In addition, the nonviable bacteria significantly increased the nonenzymatic GSH antioxidant. Taken together, these results show that the parabiotic treatment was effective in defending the liver against the oxidative stress induced by the high-fat high-fructose diet feeding to a greater extent than the viable *Lactobacillus rhamnosus* GG. The results obtained with the probiotic are consistent with those reported by other authors using another strain of Lactobacillus. In this line, Park et al. [ 48] observed increased levels of either GPx or CAT activity in rats fed a high-fat high-fructose diet supplemented with two *Lactobacillus plantarum* strains for eight weeks, without restoring SOD inhibition induced by the HFHF diet. Thus, even longer experimental periods (eight instead of six weeks, as in the present study) did not prevent the antioxidant SOD reduction induced by a high-fat high-fructose diet. It should be noted that, although there are studies focused on the effects of parabiotics on high-fat-diet-induced obese rats [49], the data reported in the present study cannot be compared to other studies, since no data concerning the effects of these inactivated bacteria on oxidative status have been reported so far.
Hepatic inflammation is a key component in the progression of NAFLD to steatohepatitis [50,51]. In fact, the lipotoxicity induced by fatty hepatocytes contributes to the activation of Kupffer cells, which produce inflammatory cytokines such as IL-1β and TNF-α, two crucial inflammation markers and relevant mediators in the development of NAFLD [52]. In this cohort of rats, although IL-1ß levels in the HFHF group were higher than in the control group, statistical significance was not reached. Regarding TNF-α, the steatotic diet induced a two-fold increase that was partially prevented by the probiotic and completely restored to control values by the parabiotic. As in the case of oxidative stress, both the probiotic and the parabiotic were efficient in preventing inflammation, but the latter seemed to be more effective.
A relevant issue to consider regarding the NAFLD pathophysiology is that this metabolic disorder contributes to the DNA damage and, thus, can favor the development of hepatocellular carcinoma [53,54]. To address this issue, the protein kinase ATM protein, which is activated by double-strand DNA breaks (DSB), was measured. Once activated, ATM activates intermediary protein substrates, such as γH2AX, leading to cell cycle arrest triggering DNA repair. In the present study, it was observed that the high-fat high-fructose diet significantly decreased ATM phosphorylation, although no changes were observed in the DNA damage marker γH2AX. These results are in good accordance with those reported by Daugherity et al. [ 55], who observed a significantly increased oxidative stress in the liver of high-fat diet-fed mice (eight weeks), without substantial activation of H2AX protein. In addition, other authors have also reported decreased p-ATM levels in nonhepatic tissues (skeletal muscle) in mice fed a high-fat diet for eight weeks [56]. Nevertheless, it is important to consider that other kinases, such as Ataxia-telangiectasia and Rad3-related protein (ATR) and DNA-dependent protein kinase (DNA-PK), play a key role in the phosphorylation of H2AX protein in the response to DNA injury. Overall, these data suggest that, although high-fat high-fructose feeding promotes a significant oxidative status, it does not induce nucleic acid damage in a period feeding of 6–8 weeks.
In order to assess the relationship between inflammation and cell death, and taking into account that the TNF-α overexpression could activate proapoptotic pathways in the rats under the high-fat high-fructose diet, PARP cleavage was studied since this protein is a preferred substrate for caspases [57]. The obtained results show that, compared to the control group, the steatotic diet up-regulated PARP cleavage which is essential for cell death signaling. It is noteworthy that apoptotic hepatocytes stimulate hepatic stellate cells and immune cell activation, both being central to the progression of NAFLD and steatohepatitis [58]. However, none of the tested treatments (probiotic or parabiotic administration) significantly avoided this effect. This suggests that the dietary model used in the present study activated apoptosis, albeit treatments were not able to prevent this situation, and thus, they seem not to be effective preventing the progression of hepatic damage towards more harmful stages through this pathway. In fact, Karahan et al. [ 59] reported that the modulation of apoptosis in a nonalcoholic steatohepatitis model of rats supplemented with a probiotic was different depending on the experimental period or the probiotic administration. Therefore, one limitation of the present study is that the chosen experimental period (6-weeks) seems to be insufficient for prompting DNA breaks and modulating hepatocyte cell death. For this reason, further research with longer experimental periods is needed in order to determine whether the treated animals would gain more benefits from the probiotic and parabiotic, fighting against the hepatotoxicity induced by the steatotic diet.
To sum up, the current results show that the probiotic *Lactobacillus rhamnosus* GG administration is able to partially prevent the oxidative stress and the inflammation induced in the liver by high-fat high-fructose feeding. Moreover, it is demonstrated for the first time that the parabiotic (heat-inactivated *Lactobacillus rhamnosus* GG) maintains both antioxidative and anti-inflammatory activities, and it seems to be even more effective than the originating probiotic, avoiding the potential side effects of the viable bacteria such as systemic infections and excessive immune stimulation. Although bacterial viability and cell wall integrity have been thought to be indispensable requisites for probiotic action, some of the bacterial molecule’s key in host metabolism regulation are located within bacteria [60]. In this regard, several authors highlighted the potential role of lysozyme, which disrupts bacterial membranes and releases bacterial products with beneficial effects on the host, such as anti-inflammatory effects in mucosal sites [61]. This could partially explain why the effectiveness of the supplementation with already-inactivated microorganisms seems to be greater in comparison with its viable counterpart.
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|
---
title: An Examination of the Relationships between Eating-Disorder Symptoms, Difficulties
with Emotion Regulation, and Mental Health in People with Binge Eating Disorder
authors:
- Felipe Q. da Luz
- Mohammed Mohsin
- Tatiana A. Jana
- Leticia S. Marinho
- Edilaine dos Santos
- Isabella Lobo
- Luisa Pascoareli
- Tamiris Gaeta
- Silvia Ferrari
- Paula C. Teixeira
- Táki Cordás
- Phillipa Hay
journal: Behavioral Sciences
year: 2023
pmcid: PMC10045385
doi: 10.3390/bs13030234
license: CC BY 4.0
---
# An Examination of the Relationships between Eating-Disorder Symptoms, Difficulties with Emotion Regulation, and Mental Health in People with Binge Eating Disorder
## Abstract
Eating disorders, such as binge eating disorder, are commonly associated with difficulties with emotion regulation and mental-health complications. However, the relationship between eating-disorder symptoms, difficulties with emotion regulation, and mental health in people with binge eating disorder is unclear. Thus, we investigated associations between eating-disorder symptoms, difficulties with emotion regulation, and mental health in 119 adults with binge eating disorder. Participants were assessed with the Eating Disorder Examination Questionnaire, Loss of Control over Eating Scale, Difficulties in Emotion Regulation Scale, Depression Anxiety and Stress Scale, and the 12-Item Short Form Survey at the pre-treatment phase of a randomized controlled trial. Structural-equation-modelling path analysis was used to investigate relationships between variables. We found that [1] eating-disorder behaviors had a direct association with depression, anxiety, and stress; [2] depression, psychological stress, difficulties with emotion regulation, and eating-disorder psychopathology had a direct association with mental-health-related quality of life; and [3] eating-disorder psychopathology/behaviors and stress had a direct association with difficulties with emotion regulation. Our findings show that depression, stress, difficulties with emotion regulation, and eating-disorder psychopathology were related in important ways to mental-health complications in people with binge eating disorder.
## 1. Introduction
Binge eating disorder (BED) is an eating disorder characterized in the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) by recurrent binge-eating episodes that have occurred at least once a week for the past three months [1]. Binge-eating episodes are defined as the ingestion of an amount of food that is larger than most people would consume under similar circumstances, accompanied with a sense of loss of control over eating [1]. The DSM-5 criteria for BED also require that people experience at least three of the following five features: [1] eating much more quickly than normal; [2] eating until feeling excessively full; [3] overeating when not feeling physically hungry; [4] eating alone because of embarrassment related to the amount of food consumed; and [5] feeling disgusted, depressed or very guilty after binging, and reported marked distress with the binge eating [1].
People with BED commonly experience comorbid mental-health problems. For instance, a systematic review found that BED is significantly associated with depression [2], and another study reported that anxiety is an important factor in the development and maintenance of binge eating [3]. Moreover, a recent study in the United States found that BED was associated with lifetime mood disorders and anxiety disorders [4]. In addition to mood and anxiety disorders, psychological stress also has a relationship with the desire to binge eat in people with BED [5]. For instance, psychological stress can lead to a greater desire to binge eat in people with BED compared to those without BED [5]. Lastly, BED can also be associated with poor mental-health-related quality of life (HRQoL). For example, a study in Brazil found reduced mental HRQoL in people with BED compared to people without BED [6]. In line with this, another study found that people with obesity and comorbid BED experience poorer mental HRQoL in comparison to people with obesity but without BED, or people without obesity and without BED [7]. Moreover, mental HRQoL can be particularly poorer in women with BED compared to men with BED [7]. Taken together, the aforementioned studies showed significant relationships between BED and poor mental health (i.e., depression, anxiety, psychological stress, and reduced mental HRQoL).
In addition to poor mental health, people with eating disorders can experience difficulties with emotion regulation. Effective emotion regulation is the awareness, understanding, and acceptance of emotions, modulation of emotional arousal, and the ability to act in desired ways regardless of emotional state [8]. Emotional regulation is important for mental health, and ineffective emotion regulation can be an important factor in the maintenance of eating-disorder behaviors [9]. It is noteworthy that people with eating disorders report overall poorer emotion regulation in comparison to people without eating disorders [10], and that poor emotional awareness and clarity has been found in people with eating disorders [11]. Studies with samples of people with BED found similar results [12,13]. For instance, limited access to emotion-regulation strategies were associated with BED in people with obesity who were candidates for bariatric surgery [12]. Moreover, women with BED can experience greater emotion-regulation difficulties, namely nonacceptance of emotional responses, lack of emotional clarity, difficulties engaging in goal-directed behavior, impulse-control difficulties, and limited access to emotion-regulation strategies in comparison to women without BED [13]. Women with BED may also use more maladaptive emotion-regulation strategies (i.e., rumination, self-blame), and use less adaptive emotion-regulation strategies (i.e., positive refocusing, putting into perspective), in comparison to women without BED [13].
The existing literature indicates that there is an elevated occurrence of difficulties with emotion-regulation and mental-health problems in people with eating disorders such as BED. However, more research in this field is necessary, as difficulties with emotion regulation can be a risk factor for severe mental-health complications (e.g., suicidality) in people with eating disorders [14]. Thus, it is important to investigate the relationship between eating-disorder symptoms, difficulties with emotion regulation, and mental health, to potentially improve prevention and treatment programs for people with BED. To the best of our knowledge, no previous study thoroughly investigated the relationships between multiple measures of eating-disorder symptoms and mental health in people with BED using an advanced statistical analytic tool (e.g., structural-equation-modelling technique) to examine complex models. Thus, in this study we examined the relationships between eating-disorder psychopathology (i.e., dietary restraint, concerns about body shape, weight, and eating), eating-disorder behaviors (i.e., objective binge-eating episodes, subjective binge-eating episodes, loss of control over eating), difficulties with emotion regulation, poor mental health (i.e., symptoms of depression, anxiety, psychological stress), and mental HRQoL in a sample of adults with BED.
## 2.1. Study Design and Participants
We assessed data from pre-treatment measures of participants of a randomized controlled trial that investigated the efficacy of two different online treatment programs for people with BED and comorbid overweight or obesity [15]. Participants’ inclusion criteria were [1] age > 18 years; [2] BED, according to the DSM 5 criteria [1]; [3] body mass index (BMI) > 27 and <45 kg/m2; [4] being literate; [5] access to a computer with internet; [6] access to a private room to participate in the online therapy sessions; [7] time available to participate in the whole program; and [8] access to a scale and stadiometer to measure their body weight and height. Exclusion criteria were [1] having bariatric surgery in the previous 24 months; [2] simultaneous participation in another treatment for weight loss or binge eating; [3] clinical conditions that interfere with weight control (e.g., Prader–Willi syndrome, Cushing’s syndrome); [4] being pregnant; and [5] severe psychiatric disorder (i.e., schizophrenia, bipolar disorder) or a high suicide risk.
Recruitment of participants from the general community occurred via advertisements on the University of São Paulo’s social media from August 2020 to June 2022. The advertisement indicated that the research project offered online group therapy for people with BED and comorbid overweight or obesity, and included a link to a survey that could be completed by people that were interested in participating in the randomized controlled trial. This link led to an online screening survey with questions that assessed the inclusion/exclusion criteria, demographic characteristics, and contact information. Potentially eligible participants were invited for a semi-structured clinical interview via videoconference with a member of the research team. The interviewers assessed whether participants met the DSM-5 criteria for BED described in Table 1. Participants were also required to measure their body weight and height before the interview, and to provide this information to interviewers.
## 2.2. Ethics
The study was approved by the Research Ethics Committee of the University of São Paulo’s Faculty of Medicine Hospital (CAAE: 19551419.1.0000.0068) in Brazil.
## 2.3.1. Demographic Characteristics
A self-report questionnaire was used to collect information on age, sex, race, body weight, height, occupation, marital status, and income.
## 2.3.2. Eating Disorder Examination Questionnaire (EDE-Q)
The EDE-Q is a widely used 28-item self-report questionnaire derived from the “gold standard” interview for the assessments of eating disorders, namely the Eating Disorder Examination [16]. The EDE-Q was used to assess the quantity of objective and subjective binge-eating episodes, as well as the severity of eating-disorder psychopathology in the past 28 days. The EDE-Q generates a global score that is obtained by averaging the subscales (i.e., dietary-restraint, weight-concern, shape-concern, and eating-concern) scores, with higher scores indicating greater eating-disorder psychopathology. We used participants’ EDE-Q global scores to assess the severity of eating-disorder psychopathology in our study. Overall, the EDE-Q is a reliable and valid measure of eating-disorders symptoms [17]. We used an unpublished Brazilian-Portuguese version of the EDE-Q that was adapted from the European Portuguese EDE-Q and was previously used in research in Brazil [18,19]. In this study sample, Cronbach’s alpha (α) for the item pool of EDE-Q global score was 0.70.
## 2.3.3. Loss of Control over Eating Scale (LOCES)
The experience of loss of control over eating constitutes a clinically significant feature of eating disorders. However, this feature is assessed only in a dichotomous “yes or no” manner in the EDE-Q, and this may lead to imprecise assessments. Therefore, the LOCES was used in the current study to complement assessments from the EDE-Q. The LOCES is a 24-item self-report scale that is used to assess the severity of a core feature of eating disorders, namely the loss of control over eating [20]. Each item is rated on a 5-point Likert scale that ranges from 1 (“never”) to 5 (“always”), which is averaged to generate a total score. Higher score on the LOCES indicate more severe loss of control over eating in the past 28 days. The LOCES shows good internal consistency and test–retest reliability, as well as convergent and discriminant validity [20]. We used a Brazilian-Portuguese version of the LOCES to assess loss of control over eating [21]. Cronbach’s alpha for the item pool of LOCES in this study was 0.91.
## 2.3.4. Difficulties in Emotion Regulation Scale (DERS)
The DERS is a 36-item self-report scale that is widely used to assess clinically relevant difficulties in emotion regulation [8]. The DERS is used to assess the following 6 dimensions of difficulties with emotion regulation: lack of awareness of emotional responses, lack of clarity of emotional responses, non-acceptance of emotional responses, limited access to emotion-regulation strategies perceived as effective, difficulties controlling impulses when experiencing negative emotions, and difficulties engaging in goal-directed behaviors when experiencing negative emotions [8]. Each item is rated on a 5-point Likert scale of 1 (“almost never”) to 5 (“almost always”). For this study, we used only the total score of all 36 items, with higher scores indicating increased difficulties with emotion regulation. The DERS shows good construct validity, good internal consistency, and good discriminative ability [22]. The Brazilian-Portuguese version of the DERS was used in our study [23]. In this study sample, Cronbach’s alpha (α) for the total item pool of DERS was 0.86.
## 2.3.5. Depression, Anxiety and Stress Scale (DASS-21)
The DASS-21 is a self-report scale with 21 items that is used to assess the magnitude of symptoms of depression (7 items), anxiety (7 items), and psychological stress (7 items) in both clinical and non-clinical samples [24]. Each item is rated on a 4-point Likert scale from 0 (“did not apply to me at all”) to 3 (“applied to me very much or most of the time”) assessing the severity of symptoms over the past week. For this study, the subscale scores were used separately with higher scores indicating more severe symptoms of depression, anxiety, or psychological stress. The DASS-21 is a valid measure of dimensions of depression, anxiety, and psychological stress, and shows appropriate construct validity and high reliability [25]. We used the Brazilian-Portuguese-validated version of the DASS-21 in our study [26]. Cronbach’s α for our sample was 0.92 for the total DASS-21 item pool, 0.89 for the depression subscale, 0.77 for the anxiety subscale, and 0.81 for the psychological stress subscale.
## 2.3.6. 12-Item Short Form Survey (SF-12)
The SF-12 is a reliable measure used to assess mental and physical HRQoL in different population groups [27]. The SF-12 is also a valid and sensitive measure of impairment in HRQoL in people with eating disorders [28]. The survey scores are categorized into two domains, a physical-composite-scale (PCS) score and a mental-composite-scale (MCS) score, each including six items. In our study we analyzed only mental HRQoL using the MCS score. Elevated scores on the MCS indicate greater mental HRQoL. We used a Brazilian-Portuguese version of the SF-12 to assess participants’ mental HRQoL [29]. Cronbach’s alpha (α) for the MCS item pool was 0.70.
## 2.4. Statistical Analyses
Firstly, we documented the descriptive data for demographic characteristics (i.e., age, gender, race, occupation, marital status, income) and clinical features (i.e., eating-disorder psychopathology, objective binge-eating episodes, subjective binge-eating episodes, loss of control over eating, difficulties with emotion regulation, depression, anxiety, psychological stress, and mental HRQoL. Continuous variables were presented as means and standard deviation (SD); and categorical variables were presented as percentages. Next, we examined the associations of demographic characteristics with mean scores for all clinical features. We calculated a correlation matrix to explore potential correlations among clinical features. Theoretically relevant indices that showed a significant ($p \leq 0.05$) bivariate relationship with any of the clinical features were entered into the path model within a structural-equation-modelling (SEM) framework [30,31]. The SEM was designed to test the following associations: [1] inter-relationships among clinical features; [2] paths leading from objective or subjective binge-eating episodes, eating-disorder psychopathology, loss of control over eating, psychological stress, and anxiety, to difficulties with emotion dysregulation, depression, and mental HRQoL; [3] direct and indirect paths leading from binge eating, eating-disorder psychopathology, loss of control over eating, psychological stress, difficulties with emotion regulation, and depression, to mental HRQoL. Model fitness was assessed according to conventional criteria, including a non-significant chi-square test; comparative fit index (CFI) > 0.90; the Tucker–Lewis Index (TLI) > 0.90; the root-mean-square error of approximation (RMSEA) < 0.08; and the standardized root-mean-square residual (SRMR) < 0.08 [32,33,34]. The analyses were performed in SPSS v. 27 [35] and Mplus 7.1. [ 33].
## 3.1. Participants’ Demographic Characteristics
One hundred and nineteen participants were included in our study (see Appendix A). The demographic characteristics of all 119 participants are shown in Table 2. The participants’ mean age was 36 years (SD, 8.8); $21.8\%$ ($$n = 26$$) were 18 to 29 years of age, $45.4\%$ ($$n = 54$$) were 30–39 years of age, and $32.8\%$ ($$n = 39$$) were 40–59 years of age. Most participants were female ($$n = 108$$, $90.8\%$). Three quarters of the participants were from a white ethnicity group and the remainder ($25\%$) consisted of black or other ethnic backgrounds. Almost two-thirds ($66\%$) of the participants were full-time or part-time employed, and a similar proportion ($65\%$) reported to be either married or living with a partner (see Table 2).
The mean scores of the clinical features were: 14.2 (SD, 15.2) for objective binge-eating episodes; 10.5 (SD, 8.0) for subjective binge-eating episodes; 3.75 (SD, 0.9) for eating-disorder psychopathology, 81.9 (SD, 14.1) for loss of control over eating; 100.3 (SD, 24.8) for difficulties with emotion regulation; 15.6 (SD, 9.7) for depression; 10.3 (SD, 7.4) for anxiety; 20.8 (SD, 8.3) for psychological stress; and 32.7 (SD, 9.7) for mental HRQoL (see Table 2 and Appendix B).
## 3.2. Bivariate Analyses
Association of participant’s demographic characteristics and mean scores for all clinical features are shown in Table 1. There were no significant differences observed for any of the clinical features by participants’ demographic characteristics. Table 3 shows the correlation matrix of all clinical features.
## 3.3. Path Analysis
Figure 1 displays the path diagram with standardized estimates (β) indicating direct and indirect associations. The model achieved a good fit with a non-significant chi-square value, χ2[15] = 18.06, $$p \leq 0.92$$; CFI = 1.00, TLI = 1.00, RMSEA < 0.001, and SRMR = 0.04.
## 3.3.1. Correlates of Mental-Health-Related Quality of Life (HRQoL)
Depression (β = −0.50, $p \leq 0.01$), eating-disorder psychopathology (β = −0.20, $p \leq 0.05$), psychological stress (β = −0.19, $p \leq 0.05$), and difficulties with emotion regulation (β = −0.16, $p \leq 0.05$) showed significant direct associations with mental HRQoL (Figure 1). Indirect pathways to mental HRQoL included anxiety (indirect standardized coefficient = −0.34, $p \leq 0.01$) via psychological stress or depression; loss of control over eating (indirect standardized coefficient = −0.20; $p \leq 0.001$) via difficulties with emotion regulation or depression; objective binge-eating episodes (indirect standardized coefficient = −0.14; $p \leq 0.01$) via eating-disorder psychopathology; and subjective binge-eating episodes (indirect standardized coefficient = −0.10; $p \leq 0.01$) via eating-disorder psychopathology or psychological stress.
## 3.3.2. Correlates of Difficulties with Emotion Regulation
Psychological stress (β = 0.41, $p \leq 0.01$), eating-disorder psychopathology (β = 0.19, $p \leq 0.05$), and loss of control over eating (β = 0.18, $p \leq 0.05$) showed significant direct associations with difficulties with emotion regulation (Figure 1). Additionally, we found an indirect pathway from anxiety to difficulties with emotion regulation via psychological stress (indirect standardized coefficient = 0.25, $p \leq 0.01$).
## 3.3.3. Correlates of Depression
Loss of control over eating (β = 0.19, $p \leq 0.05$), anxiety (β = 0.30, $p \leq 0.01$), psychological stress (β = 0.22, $p \leq 0.01$), and difficulties with emotion regulation (β = 0.23, $p \leq 0.01$) showed significant direct associations with depression (Figure 1). Furthermore, eating-disorder psychopathology showed an indirect association with depression, via loss of control over eating and difficulties with emotion regulation (indirect standardized coefficient = −0.20, $p \leq 0.01$).
## 3.3.4. Correlates of Anxiety
Objective binge-eating episodes (β = 0.19, $p \leq 0.05$) and loss of control over eating (β = 0.23, $p \leq 0.01$) showed significant direct associations with anxiety.
## 3.3.5. Correlates of Psychological Stress
Subjective binge-eating episodes (β = 0.15, $p \leq 0.05$) and anxiety (β = 0.61, $p \leq 0.01$) showed significant direct associations with psychological stress.
## 3.3.6. Correlates of Eating-Disorder Psychopathology
Objective binge-eating episodes (β = 0.22, $p \leq 0.01$) and subjective binge-eating episodes (β = 0.18, $p \leq 0.05$) showed significant direct associations with eating-disorder psychopathology.
## 3.3.7. Correlates of Loss of Control over Eating
Objective binge-eating episodes (β = 0.20, $p \leq 0.05$) and eating-disorder psychopathology (β = 0.44, $p \leq 0.01$) showed significant direct associations with loss of control over eating.
## 4. Discussion
Our study investigated relationships between eating-disorder symptoms, difficulties with emotion regulation, general mental health, and mental HRQoL in adults with BED. Overall, we found that eating-disorder behaviors and psychopathology were associated with poorer mental health in participants included in our study. For instance, we found that: [1] objective binge eating had a direct association with anxiety; [2] subjective binge eating had a direct association with psychological stress; [3] loss of control over eating had a direct association with anxiety and depression; and [4] eating-disorder psychopathology had a direct association with mental HRQoL. Moreover, we found that eating-disorder psychopathology and loss of control over eating had a direct association with less effective emotion regulation. Lastly, we found that depression and psychological stress had a direct association with mental HRQoL, and psychological stress had a direct association with less effective emotion regulation.
Our study showed that several factors can be associated with poor mental HRQoL in people with BED. Our findings suggest that it is important to address a range of mental-health problems, i.e., depression, psychological stress, difficulties with emotion regulation, and eating-disorder psychopathology, to enhance mental HRQoL in this population. Thus, people with BED may require comprehensive assessment and treatment approaches—rather than treatments focused only on the cessation of binge-eating episodes—to improve their mental health. For instance, it is important that clinicians working with clients with BED assess their clients’ levels of depression, psychological stress, and difficulties with emotion regulation, and provide the required specialized therapies to address these complications when necessary. Clinicians can ask their clients with BED to complete self-report scales such as the DASS-21 and DERS to assess their mental-health status and difficulties with emotion regulation [8,24]. It may also be useful to comprehensively assess eating-disorder psychopathology in clients with BED, using measures such as the semi-structured interview for the investigation of eating-disorder symptoms, the Eating Disorder Examination [16]. This assessment can enable the identification of specific characteristics of the eating-disorder psychopathology that are prominent in each client, so that clinicians can address them and potentially prevent the deterioration of mental HRQoL. Moreover, it is noteworthy that some treatments for eating disorders can also induce improvements in general mental health. For instance, cognitive behavior therapy (CBT) for eating disorders can reduce depression, anxiety, mood intolerance, low self-esteem, clinical perfectionism, and interpersonal difficulties in people with BED [16,36,37].
Our findings also enable a better understanding of the occurrence of difficulties with emotion regulation in people with BED. We found that eating-disorder psychopathology, loss of control over eating, and psychological stress had a direct association with less effective emotion regulation in our sample of adults with BED. This finding suggests that a reduction in eating-disorder symptoms through CBT [38], and reduction in psychological stress via access to specialized treatments (e.g., mindfulness-based stress reduction) [39] may facilitate effective emotion regulation in people with BED. The attenuation of difficulties with emotion regulation is particularly important, as we found that such difficulties have a direct effect on depression and poor mental HRQoL in this population. Taking this into consideration, psychological therapies that focus on training in emotion-regulation skills (e.g., dialectical behavior therapy) are known to be useful to address mental-health complications and eating-disorder symptoms in people with BED and comorbid difficulties with emotion regulation [40], but are under researched [41,42]. Overall, it may be beneficial that clinicians working with treatment models that focus mostly on the reduction of eating-disorder symptoms consider adding skills training on emotion-regulation and stress-management interventions to their treatment plans for clients with BED.
In addition to direct relationships between eating-disorder symptoms, difficulties with emotion regulation, and mental health in people with BED, we also found significant indirect relationships. These indirect relationships were described in detail in the Results section; nonetheless, here we provide a summary: [1] objective and subjective binge eating, loss of control over eating, and anxiety showed an indirect association with mental-health-related quality of life; [2] eating-disorder psychopathology showed an indirect association with depression; and [3] anxiety showed an indirect association with difficulties with emotion regulation. We found multiple direct and indirect relationships between eating-disorder symptoms, difficulties with emotion regulation, and poor mental health in people with BED. Overall, the relationships that were found in our study provide a better understanding of the complexity of psychopathology associated with BED. However, our findings do not substitute individualized clinical assessments of symptoms of BED and associated mental-health complications. Clinicians working with clients with BED will need to conduct individual assessments of eating-disorder symptoms, difficulties with emotion regulation, and mental-health status, to understand how these factors influence each other in order to plan individualized treatments.
Our findings also have implications for research on treatment outcomes for people with BED. A significant number of treatment trials for BED focus on the reduction or abstinence of binge eating as an outcome, and neglect broader aspects of mental health and mental HRQoL [43]. This limits the understanding of the efficacy and effectiveness of treatments for BED. Thus, the inclusion of general measures of mental-health status (e.g., DASS-21 [24]) in treatment trials for people with BED is necessary to investigate potential effects of these treatments on overall mental health. Moreover, future research—including longitudinal studies—is necessary to elucidate causality, mediation, and bidirectional analyses between eating-disorder symptoms, difficulties with emotion regulation, and mental health in people with BED.
This study has several strengths and limitations. Notable strengths include the use of an advanced statistical analytical approach (i.e., the structural-equation-modelling technique)—to examine complex causal models. Additionally, we included several measures of eating-disorder symptoms (i.e., EDE-Q, LOCES) and aspects of mental health (i.e., DASS-21, DERS, SF-12 MCS score) in a sample of adults with BED. The combined use of these different statistical analyses and measures allowed us to examine relationships between eating-disorder symptoms, difficulties with emotion regulation, and mental health, in a comprehensive and reliable manner. The main limitation of our study is that we used a cross-sectional design, and causal inferences cannot be made. Another potential limitation is that $90.8\%$ of the study sample was female. There were no significant differences between males and females in difficulties-with-emotion-regulation scores in our sample; however, our findings may not be generalizable to males with BED or people with BED in regions with significant cultural differences. Additionally, a potential limitation is that all data used for statistical analyses in this study were obtained via self-report measures. It is possible that we could have obtained more accurate clinical data if instead of self-report measures we used semi-structured interviews, such as the Eating Disorder Examination [16]. A final limitation of our study is that while we thoroughly examined effects of eating-disorder symptoms on mental-health status, we did not examine relationships in the opposite direction (i.e., potential effects of mental-health status on eating-disorder symptoms).
In summary, our study found multiple direct and indirect relationships between eating-disorder symptoms, difficulties with emotion regulation, and mental-health status in adults with BED. We found that depression, psychological stress, difficulties with emotion regulation, and eating-disorder psychopathology had a direct association with mental HRQoL. Additionally, eating-disorder psychopathology, loss of control over eating, and psychological stress had a direct association with difficulties with emotion regulation. Thus, research involving the evaluation of clinical-trial outcomes as well as real-world treatment plans for people with BED should address comprehensively the symptoms of depression, psychological stress, difficulties with emotion regulation, eating-disorder psychopathology (i.e., dietary restraint, excessive concerns about body shape, weight, and eating) and loss of control over eating.
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|
---
title: 'Short Report: Lack of Diurnal Variation in Salivary Cortisol Is Linked to
Sleep Disturbances and Heightened Anxiety in Adolescents with Williams Syndrome'
authors:
- Jessica Hayton
- Atiqah Azhari
- Gianluca Esposito
- Ray Iles
- Michaella Chadiarakos
- Giulio Gabrieli
- Dagmara Dimitriou
- Stephen Mangar
journal: Behavioral Sciences
year: 2023
pmcid: PMC10045386
doi: 10.3390/bs13030220
license: CC BY 4.0
---
# Short Report: Lack of Diurnal Variation in Salivary Cortisol Is Linked to Sleep Disturbances and Heightened Anxiety in Adolescents with Williams Syndrome
## Abstract
Objective: The aim of the current study was to examine the potential relationship between sleep patterns, cortisol levels, and anxiety profiles in adolescents with Williams Syndrome (WS) compared to typically developing adolescents. Method: Thirteen adolescents with WS and thirteen TD adolescents (age range 12–18 years) were recruited. Participants were provided with a “testing kit”, containing instructions for collecting data through a sleep diary, MotionWare actigraphy, the Childhood Sleep Habits Questionnaire (CSHQ), and the Spence Children’s Anxiety Scale, and a salivary cortisol collection kit. Results: Adolescents in the WS group did not show diurnal variation in salivary cortisol. Significantly higher scores were reported for two CSHQ subsections, night wakings and parasomnias, in the WS group. Regarding the actigraphy, only significantly longer sleep latency was observed in the WS group. In comparison to the TD group, the WS group had significantly higher anxiety. As expected, the TD group showed typical diurnal variation in cortisol, whereas the WS group showed a flattened cortisol profile throughout the day. Conclusions: From the developmental perspective, this study provides new data supporting the conclusion that sleep problems are not transient but continue to persist into adolescence in WS. Future studies ought to consider examining the role of cortisol and its interplay with anxiety levels and sleep problems across the lifespan in individuals with WS.
## 1. Introduction
Sleep disturbances are commonly reported in children with developmental disorders. Poor sleep habits may trigger impairments in cognitive and behavioural functioning [1,2], including lower academic performance [3], reduced attentional capacities (e.g., [4]), and poor executive functioning [5]. A suboptimal quality of sleep has also been associated with adverse and challenging anti-social behaviours [6], such as aggression, tantrums, non-compliance, and impulsivity [2,7,8]. Sleep disturbances have been found to be predictors of a reduced quality of life, related to stress, depression, and overall family functioning [9,10]. In childhood, a reduced sleep duration has been associated with developmental delays in language acquisition and consolidation [11,12]. Sleep disturbances have also been reported in infants with neurodevelopmental disabilities such as Williams Syndrome [13], which raises the importance of early identification and intervention during development, as these could mitigate against the cognitive and behavioural consequences of poor sleep.
Williams Syndrome (WS) is a rare neurodevelopmental disorder affecting approximately 1 in 20,000 individuals in the United Kingdom. WS is equally prevalent in male and female populations, and is not specific to ethnicity [14]. The disorder is caused by a micro-deletion of approximately 26–28 genes from the long arm of chromosome 7 at the point q11.23 [14]. Sleep concerns have been reported in infants with WS [15]. In early childhood, children with WS have been found to display long sleep latencies, reduced sleep efficiency and increased night wakings [16,17,18,19], frequent bed wetting and sleep anxiety [16,17], and movements during sleep [20]. Moreover, a few studies have reported an atypical sleep architecture, comprised of reduced rapid eye movement (REM) and amplified slow-wave sleep (SWS) stages [21,22]. Additionally, associations between elevated bedtime cortisol, a sleep-related hormone, and sleep onset have been reported in children with WS [23].
Cortisol has an established 24-h circadian rhythm with peak levels in the morning, particularly up to around thirty minutes after waking, before its concentration decreases throughout the day, with the lowest level being observed before night-time [24,25]. It has been argued that there is a bi-directional relationship between sleep deprivation and the secretion of cortisol, where poorer sleep is often associated with higher cortisol levels [24,26,27]. However, several recent studies have shown a rather different pattern. For instance, [28] observed a flattened curve in individuals with sickle-cell disease, which was associated with deficits in neurocognitive profiles that were moderated by sleep quality [28]. In another study, mothers of autistic children who exhibited a lack of diurnal variation suffered from sleep disturbances and high depression scores [9].
The present study aimed to examine the relationships between sleep patterns, anxiety, and cortisol levels in adolescents with WS compared to TD healthy adolescents. We hypothesised that [1] adolescents with WS would show a different cortisol profile than the age-matched TD controls, and [2] the cortisol profiles would be related to sleep parameters and anxiety scores.
## 2.1. Participants
Thirteen adolescents with WS were recruited via the database of the Williams Syndrome Foundation, UK. The control group included typically developing (TD) adolescents who were matched by chronological age to the WS cohort (see Table 1). None of the TD participants were diagnosed with any learning disability, nor had they received treatment for sleeping problems at the time of testing. English was used as a first language for all recruited participants. Ethical approval was granted from the Institute of Education, UCL Ethics Committee (grant number: 72838) and the Williams Syndrome Foundation, UK. Written informed consent was obtained from all parent/guardians, and consent was also secured from each child participant.
## 2.2.1. Child Sleep Habits Questionnaire (CSHQ)
The CSHQ [29] is a standardised 45-item parent report measure for assessing sleep habits and potential sleep difficulties in children.
## 2.2.2. Spence Children’s Anxiety Scale (SCAS)
The Anxiety Scale [30] more broadly measures the severity of the anxiety symptoms that are outlined in DSM-IV, including panic and aggravation, separation anxiety, obsessive–compulsive disorder, and generalised anxiety. The medical history questionnaire gathered data on other conditions that may have an impact on sleep, e.g., asthma, health habits, and diet.
## 2.2.3. Actigraphy
The MotionWatch8, manufactured by CamNtech, is a CE-marked Class 1 medical device with FDA approval (K132764). The actiwatch was worn on the non-dominant wrist for 5 weekday nights within the same week. The actigraphy collected movement samples in 30-s epochs. The following measures were recorded: bedtime, get-up time, time in bed, assumed sleep, actual sleep (duration), actual sleep (%), sleep efficiency (%), sleep latency, and the fragmentation index. A sleep diary was used in conjunction with actigraphy to record the time children went to bed.
## 2.2.4. Salivary Cortisol
Mothers were asked to take three samples of their children’s saliva on one weekday of the week during which they wore the actigraphy watch. An oral fluid collector (OFC) consisting of a synthetic polymer swab designed to collect 0.5 mL of saliva mixed with 3 mL of OFC buffer was used to collect the samples (Soma Bioscience Ltd., Wallingford, UK). With this technique, samples are stable at room temperature for several weeks and are unaffected by recent food and drink ingestion. Salivary cortisol was determined using an enzyme immunoassay (EIA) test kit (Soma Bioscience Ltd., Wallingford, UK) and read by an automated analyser (Tecan Nanoquant, Männedorf, Switzerland). The assay range for cortisol was 0.25–32.0 ng/mL. In the case where maximum values were obtained, samples were titrated and re-analysed. Cortisol profiles were assessed using all 3 values to determine if each participant had a flat or normal cortisol profile compared to the individual group mean.
Each participant was required to provide salivary samples for 3 time points over a 24-h period. The timings were: (a) afternoon at approximately 4 p.m. (baseline); (b) 30 min before habitual bedtime; (c) 30 min after waking. Either parents or participants themselves (under adult supervision) were asked to place a cotton/polymer swab in their mouth for 30–45 s in order to collect each sample.
## 2.3. Analytical Plan
Data were analysed using Python (v. 3.11.1, Centrum voor Wiskunde en Informatica (CWI), Amsterdam, The Netherlands). Independent samples t-tests were conducted to examine the results of the CSHQ, SCAS, and cortisol secretion. Mann–Whitney U tests were employed to compare actigraphy measures by group. Finally, to examine the relationship between cortisol levels, sleep habits, and anxiety scores, a two-way multivariate analysis of variance (MANOVA) was conducted.
## 3.1. Child Sleep Habits Questionnaire
Table 2 shows the results from the indepedent t-test. Eighteen participants had a cut-off score that was greater than the clinical threshold of ≥41, of whom nine were from the TD group and nine were from the WS group. There was no outlier present in the CSHQ data.
## 3.2. Spence Children’s Anxiety Scale
Table 3 shows the results from the independent t-test analysis of differences in anxiety measures between the TD and WS groups. Statistically significant differences were found in four out of six SCAS subscales (panic and aggravation, separation, obsessive compulsive, and generalised anxiety) and the total SCAS score. No statistical difference was found between groups in the subscales of physical injury and social anxiety. There were no outliers observed for the SCAS measures.
## 3.3. Actigraphy
Table 4 depicts the results for the independent samples t-tests comparing actigraphy (supported by the sleep diary) and sleep variables between the WS and TD groups. The sleep diary data were used to support bed- and get-up-time data and showed that adolescents with WS had earlier bed- and get-up-times compared to TD adolescents.
It should be noted that the sleep data from objective actigraphy were not in line with the data reported from the CSHQ. The actigraphy data showed that the WS group had a greater sleep latency than the TD group, but this difference between groups was not reported on the CSHQ sleep onset delay subscale. However, it is important to note that the CSHQ provided additional information, namely, a higher number of night wakings and parasomnias in the WS group.
## 3.4. Salivary Cortisol
Table 5 shows the means and standard deviations for both groups. Salivary cortisol samples were collected from all 26 participants, though only 22 participants ($$n = 13$$ WS; $$n = 9$$ TD) provided sufficient samples for quantification. Only one morning sample for a participant with WS did not contain enough to be quantified. Three samples for one TD participant were also removed due to the participant’s incorrect storage of the buffer (returned upside down), which led to elevated and spurious findings.
No statistical significance between cortisol levels was found in the WS sample. Statistically significant differences were found in the TD samples between bedtime and morning samples and between baseline and morning samples Table 6. Figure 1 illustrates the cortisol concentrations of the TD and WS groups for three data points: the baseline, bedtime, and morning time points. In the TD group, the morning cortisol level was significantly higher than both the baseline and bedtime time points. In contrast, in the WS group, the cortisol levels remained relatively unchanged across all three time points.
## 3.5. Sleep, Anxiety, and Cortisol
To investigate the association between cortisol profiles, sleep quality, and anxiety scores, a multivariate analysis of variance (MANOVA) was conducted, with the cortisol levels at the three different time points as the dependent variables and the CSHQ and SCAS scores as the independent variables. The results, shown in Table 7, revealed no significant or interaction effects between sleep habits or anxiety and cortisol profiles.
## 4. Discussion
Adolescence is considered a sensitive period, during which some of the largest sleep disruptions occur (e.g., [31,32]). This “perfect storm” has been related to pubertal changes, alterations in the circadian rhythm (including later bed- and wake-times), and changes in social functioning [33]. The current study supported the notion that problematic sleep is a general characteristic of adolescence, as most participants ($82\%$, $$n = 11$$ TD; $$n = 10$$ WS) were categorised as having sleep disturbances. However, unlike TD adolescents, who restricted their sleep duration, the range of sleep problems was varied and persistent across developmental stages in individuals with WS. Actigraphy data showed that adolescents with WS spent a longer time in bed and experienced more sleep, albeit marginally, compared to their TD peers. The National Sleep Foundation recommendations suggest that adolescents should optimally receive 8–10 h of sleep per night [34]. However, the actual mean duration of sleep was 7:36 for the WS group and 7:05 for the TD group.
The sleep profiles obtained from the CSHQ and actigraphy suggested that both groups experienced disturbed sleep. Similar to previous studies, the actigraphy data and the parental report (CSHQ) indicated discordance (see [17,35]). The findings and effect sizes of the CSHQ and actigraphy data suggested that it is suitable for the two measures to be used in conjunction with each other in young populations. Used together, the instruments can provide more holistic information on different aspects of sleep health profiles, which could be informative for healthcare professionals in the sleep management of patients.
Previous work has indicated that sleep-related problems in adolescence are closely associated with elevated anxiety levels [36], and this relationship was explored in the context of cortisol in the current study. Compared to the TD group, the WS group showed a lack of diurnal cortisol variation, with similar concentrations observed across the three time points. This pattern was in line with recent studies (e.g., [28]), which similarly revealed that individuals with sickle-cell disease showed a flattened diurnal cortisol curve. It is important to note that the literature currently lacks a sufficient understanding of the optimal cortisol secretion within this developmental period. To date, researchers are still not cognizant of how the different medical conditions in individuals with WS might impact cortisol secretion and interact with the sleep/wake cycle.
Significant results were reported in the WS group relative to the total anxiety score, including the subscales of general anxiety, separation anxiety, and panic and aggravation. These findings suggested that adolescents with WS experienced higher total anxiety compared to their TD peers, which could explain the larger effect sizes in the sleep anxiety dimension of the CSHQ. This result concurred with the established literature, according to which elevated general anxiety is considered a persistent behavioural phenotype in WS [37,38,39,40], as is separation anxiety [41] and panic-related anxiety [42,43,44]. Non-significant findings were reported in the following anxiety subscales: physical injury, obsessive–compulsive disorder, and social anxiety. Arguably, this could be due to the pro-social behaviour exhibited by adolescents with WS. Further, the effect sizes indicated trends in terms of variance, which suggested that a larger sample size could have potentially yielded a statistically significant result. Though the prevalence of anxiety in individuals with WS exceeded that in TD individuals, its persistence over time is relatively stable compared to TD adolescents (who have been noted to experience remission within the first 12 months of diagnosis [40,45]). Chronic anxiety in individuals with WS might be associated with the lack of variation in cortisol secretion, though caution needs to be exercised here, as this finding ought to be examined further.
The findings presented here were based on a cross-sectional design with a small sample size of participants at the adolescent stage of life only. In the continued search for the possible mechanisms involved in the interaction between sleep, anxiety, and cortisol, future studies should employ either a longitudinal approach to examine individuals with WS across the lifespan, or adopt a larger collaborative international study that could buttress the sample size. Finally, future research could further examine the interplay and associations between cortisol, actigraphy, sleep disturbances, and anxiety in WS populations.
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|
---
title: Impact of Bariatric Surgery on the Stability of the Genetic Material, Oxidation,
and Repair of DNA and Telomere Lengths
authors:
- Franziska Ferk
- Miroslav Mišík
- Benjamin Ernst
- Gerhard Prager
- Christoph Bichler
- Doris Mejri
- Christopher Gerner
- Andrea Bileck
- Michael Kundi
- Sabine Langie
- Klaus Holzmann
- Siegfried Knasmueller
journal: Antioxidants
year: 2023
pmcid: PMC10045389
doi: 10.3390/antiox12030760
license: CC BY 4.0
---
# Impact of Bariatric Surgery on the Stability of the Genetic Material, Oxidation, and Repair of DNA and Telomere Lengths
## Abstract
Obesity causes genetic instability, which plays a key-role in the etiology of cancer and aging. We investigated the impact of bariatric surgery (BS) on DNA repair, oxidative DNA damage, telomere lengths, alterations of antioxidant enzymes and, selected proteins which reflect inflammation. The study was realized with BS patients ($$n = 35$$). DNA damage, base oxidation, BER, and NER were measured before and 1 month and 6 months after surgery with the single-cell gel electrophoresis technique. SOD and GPx were quantified spectrophotometrically, malondealdehyde (MDA) was quantified by HPLC. Telomere lengths were determined with qPCR, and plasma proteome profiling was performed with high-resolution mass spectrophotometry. Six months after the operations, reduction of body weight by $27.5\%$ was observed. DNA damage decreased after this period, this effect was paralleled by reduced formation of oxidized DNA bases, a decline in the MDA levels and of BER and NER, and an increase in the telomere lengths. The activities of antioxidant enzymes were not altered. Clear downregulation of certain proteins (CRP, SAA1) which reflect inflammation and cancer risks was observed. Our findings show that BS causes reduced oxidative damage of DNA bases, possibly as a consequence of reduction of inflammation and lipid peroxidation, and indicate that the surgery has beneficial long-term health effects.
## 1. Introduction
According to the WHO, 1.9 billion adults are overweight and 650 million are obese. Furthermore, the organization stated that excess body weight (BW) causes around 2.8 million deaths annually [1].
A most promising strategy to reduce adverse health effects in individuals with severe obesity is bariatric surgery (BS), which leads to weight loss and reduction of the incidence of weight-related disorders, including diabetes type II, cardiovascular diseases, and cancer [2,3,4]. The latest report of the International Federation for Surgery of Obesity and Metabolic Disorders contains data from 50 countries and states that 507,298 operations were performed in 2021; according to the American Society for Metabolic and Bariatric Surgery, the number of BS increased substantially in the last years (ASMBS 2021, accessed on 10 December 2021, www.asmbs.org).
Different BS techniques have been developed, and the most frequently used procedures are gastric sleeve (GS) and Roux-en-Y gastric bypass (RYGB), one-anastomosis gastric bypass (OAGB), and gastric band. It was postulated that OAGB reduces the operation time and early and late complications [5]. It is well documented in systematic reviews that BS improves the health status of overweight individuals, i.e., it normalizes glucose metabolism, reduces the risk for CVD and diabetes, and increases the lifespan [6,7,8].
Only a few studies have been published which indicate that overweight and obesity lead to DNA damage, which plays a key role in the etiology of several diseases, including cancer as a consequence of inflammation and release of radical oxygen species [9]. The aim of the present study was a comprehensive investigation of the consequences of weight loss of BS patients ($$n = 35$$) who underwent different types of surgery on genomic and telomeric stability, oxidative damage of DNA bases, DNA repair, and parameters which have an impact on the integrity of the genetic material (redox status, proteins, which reflect inflammation). The design which we used was identical to that of earlier dietary intervention trials, i.e., the extent of DNA damage and other parameters are monitored before the surgery and at two time points (1 and 6 months) after the operations.
DNA damage, oxidation of purines, and DNA repair (nucleotide excision repair, NER and base excision repair, BER) were measured with different protocols of the single-cell gel electrophoresis (SCGE) assay. This method is based on the quantification of DNA migration in an electric field [10] and is increasingly used in human biomonitoring [11]. The endpoints, which are measured in SCGE experiments are related to human health. It was found that the extent of comet formation predicts the risk of mortality [12]. Additionally, it is well documented that DNA migration is increased in patients with high-prevalence diseases, including specific forms of cancer [13]. Oxidation of DNA bases is a consequence of inflammation and redox stress, and it was stated by the European Food Safety Authority (EFSA) that prevention of oxidative damage has a positive impact on human health [14]. DNA repair systems (BER and NER) play a causal role in the etiology of cancer and other diseases [15,16]. Telomere shortening causes cellular senescence [17], and evidence is accumulating that it may accelerate aging processes in humans [18]. Superoxide dismutase (SOD) and glutathione peroxidase (GPx), which were monitored in the present study are antioxidant enzymes which reflect the redox status [19]; low activities are associated with different human pathologies [20,21]. Malondialdehyde (MDA) is a lipid peroxidation (LP) product which reflects the oxidation of fatty acids and causes damage to the genetic material [22,23].
Only a few studies have been realized in which the consequences of BS on DNA stability were investigated. All earlier trials were performed with patients who underwent GS and RYGB operations, while no data are currently available concerning OAGB surgery. Bankoglu and co-workers investigated the consequences of BS on DNA damage in SCGE experiments [24,25]. Furthermore, some studies have been published concerning the formation of oxidized guanine (8-oxoGuo and 8-OHdG) [26,27,28]. The impact of BS on BER and NER has not been studied according to our knowledge, but Habermann and co-workers investigated DNA repair in obese postmenopausal women after weight loss [29]. Results of studies concerning the reduction of telomere lengths after BS are controversial; some of them point in the direction of beneficial long-term effects [30], also the findings concerning alterations of the activities of antioxidant enzymes after weight loss are inconsistent [28,31,32].
## 2.1. Recruitment of the Participants
The study was approved (18.10.2016) by the Ethical Committee of Medical University of Vienna ($\frac{1479}{2016}$). All patients provided written consent, and 40 patients were recruited from the Department of Surgery, MUW; 35 individuals finished the study. Inclusion criteria were BMI values > 35 kg/m2 and an age range between 18 and 60 years. Exclusion criteria were chronic diseases (diabetes mellitus type II, cystic fibrosis, arthritis, asthma), intake of food supplements before surgery, and intake of anti-inflammatory drugs and pharmaceuticals with antioxidant properties.
The patients underwent different types of BS, namely RYGB ($$n = 11$$), OAGB ($$n = 19$$), GS ($$n = 2$$) and SADI-S ($$n = 3$$). The study had an intervention design, i.e., values that were obtained before the surgery were compared with the values that were obtained after the operation.
The same design was used in many other dietary studies [33,34] and in weight loss trials [9,25]. Blood samples (40 mL/patient) were collected at three time points, namely one day before the operation (T0) and 1 month (T1) and 6 months (T2) after the surgery (Figure 1).
BS leads to nutritional deficiencies [35]; therefore, all participants consumed a supplement containing vitamins and trace elements after the surgery (WLS Forte, Berlin, Germany). The composition is specified in Table S1.
## 2.2. Isolation of Plasma and Lymphocytes
Plasma was separated from blood by centrifugation (650 g, 20 min). Subsequently, aliquots were stored at −80 °C. Peripheral lymphocytes were isolated by gradient centrifugation (800 g, 15 min, 16 °C) with Histopaque (Sigma–Aldrich, Steinheim, Germany). The pellets were suspended in 100 μL RPMI and aliquoted in Biofreeze Medium (Biochrom AG, Berlin, Germany, frozen overnight at −80 °C and stored in liquid nitrogen.
## 2.3. SCGE Experiments with Lymphocytes
The experiments were carried out according to international guidelines for SCGE experiments [10,36]. The viability of the cells was determined by use of a CASY cell counter (Schärfe-System GmbH, Reutlingen, Germany); DNA damage was only analyzed in samples with a viability ≥ $70\%$ since reduced viability may cause misleading results [37].
For standard comet assays the cells were mixed with $0.5\%$ LMPA and transferred to agarose coated slides ($1.0\%$ NMPA). After lysis (pH 10.0), electrophoresis was carried out under alkaline conditions (30 min, 300 mA, 1.0 V/cm, at 4 °C, pH > 13). Subsequently, the slides were washed two times (8 min), air-dried, and stained with propidium iodide (10.0 μg/mL, Sigma-Aldrich, Steinheim, Germany).
Per experimental point, three slides were made and 50 cells were evaluated randomly. Cells were examined under a fluorescence microscope (Nikon EFD-3, Tokyo, Japan) using a 20-fold magnification. DNA migration was determined with a computer aided image analysis system (Comet Assay IV, Perceptive Instruments, Bury Saint Edmunds, UK). The percentage of DNA in tail (% DNA) was monitored as an endpoint, as suggested in international guidelines [37].
To determine the formation of oxidized purines, nuclei were exposed after lysis (1 h) to formamidopyrimidine glycosylase (FPG, Sigma-Aldrich, Steinheim, Germany). To establish the optimal enzyme concentration, a calibration experiment was carried out [38]. After lysis, the slides were washed twice with enzyme reaction buffer (pH 8.0, 8 min.). Subsequently, the nuclei were treated (30 min., 37 °C) with 50 μL of FPG solution (1:3000 dilutions) or with the enzyme reaction buffer. After the treatment, electrophoresis was carried out and the slides were evaluated as described above. To calculate the extent of DNA damage attributable to formation of oxidized purines the values, which were obtained with the enzyme buffer were subtracted from the values, which were obtained with the lesion specific enzyme [38]. Technical controls (from two individuals, who were not involved at the study) were included in all experiments [13].
## 2.4. Measurement of BER and NER
A modification of the SCGE assay was used to measure BER and NER [10]. This approach is based on the ability of repair proteins in cell extracts to recognize and to cut substrate DNA, which contains specific lesions [36].
Protein extracts were prepared from lymphocytes (1.5 × 106) by centrifugation (700 g, 10 min, 4 °C) after addition of 65 μL of extraction buffer (45 mM HEPES, 0.4 M KCl, 1 mM EDTA, 0.1 mM dithiothreitol, $10\%$ glycerol, pH 7.8) with $1\%$ of Triton X-100 (Buffer A). Samples were vortexed at top speed and snap-frozen in liquid nitrogen. Lysates were thawed and centrifuged at 15,000× g (5 min at 4 °C). Supernatants (55 μL) were collected and mixed with 220 μL cold buffer B (40 mM HEPES, 0.5 mM EDTA, 0.2 mg/mL BSA, 0.1 M KCl, pH 8.0). Protein concentrations of extracts were quantified with a DC Protein Assay Kit (BIO-RAD, Veenendaal, The Netherlands).
A549 cells (a human lung fibroblast carcinoma line, provided from the ATCC, Manassas, VA, USA) were used as substrate cells. They were cultivated in RPMI 1640 medium (low glucose, with L-glutamine), supplemented with $10\%$ FCS and U/mL penicillin/streptomycin (Invitrogen, Darmstadt, Germany) under humidified conditions ($5\%$ CO2, 37 °C). At 85–$90\%$ confluence, the cells were washed with Dulbecco’s PBS and harvested with $0.25\%$ trypsin-EDTA.
For the BER measurements, a photosensitizer, Ro 19-8023 (Chiron AS, Trondheim, Norway) at 1.0 μM was used, which causes oxidation of DNA bases. Substrate cells were treated in presence and absence of visible light (400 W, 60 cm distance, 4 min). Subsequently, they were centrifuged (700× g for 10 min). Subsequently, the pellets were re-suspended in freezing medium (Biofreeze Medium, Biochrom AG, Berlin, Germany) and cryopreserved at −80 °C. For the NER assay, UVC (2.0 Jm−2, 22 s. on ice) was used to produce cyclobutane pyrimidine dimers.
After the chemical treatments, the cells (2.5 × 104 per gel) were embedded in agarose and lysed. For NER measurements. The slides were washed twice for 10 min buffer N (45 mM HEPES, 0.25 mM EDTA, 0.3 mg/mL BSA, $2\%$ glycerol, pH 7.8) and for BER in buffer B (40 mM HEPES, 0.5 mM EDTA, 0.2 mg/mL BSA, 0.1 M KCl, pH 8.0). Subsequently, the nuclei were incubated either with 40 μL “extract mix” (lymphocyte extract, extract buffer with Triton X-100 and reaction buffers) or with control buffer. Alkaline unwinding (40 min) and electrophoresis (30 min) were performed as in standard comet experiments.
## 2.5. Measurement of GPx and SOD
The activities of GPx and SOD were measured spectrophotometrically (Tecan Infinite M200 Plate Reader, Switzerland) with commercially available kits (GPx, ab102530; SOD, ab65354, Abcam, Cambridge, UK) according to the instructions of the manufacturers at 350 nm for GPx and at 450 nm for SOD. All samples were measured in duplicates. SOD activity was measured as % inhibition of formation of a water-soluble tetrazolium salt.
## 2.6. Measurement of Malondiadehlyde in Plasma
MDA concentrations were determined in plasma according to the method of Ramel et al. [ 39], which we used in earlier studies [40,41,42]. The samples were neutralized after heating (60 min, 100 °C) with methanol/NaOH and centrifuged at 3000 rpm (for 3 min). Subsequently, MDA was measured with HPLC with excitation at 532 nm and emission at 563 nm (LaChrom Merck Hitachi Chromatography system, Tokyo, Japan). Each sample was analyzed in duplicate.
## 2.7. Measurement of the Telomere Lengths
Genomic DNA was isolated from pellets using Gentra PureGene Cell Kit (Qiagen, Venlo, Netherlands). Quantification of DNA was conducted with iQuant Broad Range dsDNA Quantification Kit (Genecopoeia, Rockville, MD, USA), according to the protocol of the manufacturer with a Qubit Fluorometer (Thermo Fischer Scientific Inc., Waltham, MA, USA) and stored at −80 °C for further measurements.
Telomere lengths were determined by monochrome multiplex qPCR as described by Cawthon [43]. Telomeric contents were measured in reference to one selected experimental DNA sample and to one of the single-copy genes 36B4 and ALB; for more details see [44]. The relative telomere-to-single-copy-gene (T/S) ratio was determined in each sample in triplicate.
## 2.8. Proteome Analyses of the Plasma Samples
The protein concentrations of the plasma samples were determined with a bicinchoninic acid (BCA) assay. Enzymatic digestion of samples was achieved applying a protocol using the S-trap technology [45]. Finally, peptides were eluted, dried and stored at −20 °C until LC-MS/MS analyses.
For LC-MS/MS analyses, dried peptide samples were reconstituted in 10 μL of $30\%$ formic acid (FA) containing 4 synthetic standard peptides (10 fmol/μL) and further diluted with 80 μL mobile phase A ($97.9\%$ H2O, $2\%$ ACN, $0.1\%$ FA). LC-MS/MS analyses were performed on a Dionex Ultimate 3000 nano LC-system coupled to a timsTOF Pro mass spectrometer (Bruker) equipped with a captive spray ion source. For mass spectrometric analyses, the timsTOF Pro Mass Spectrometer (Bruker Daltonics USA, Billerica, MA, USA) was operated in the parallel accumulation-serial fragmentation (PASEF) mode. Trapped ion mobility separation was achieved by applying a 1/k0 scan (0.60–1.60 V. s/cm2) resulting in a ramp time (166 ms). All experiments were performed with 10 PASEF MS/MS scans per cycle leading to a total cycle time (1.88 s). MS and MS/MS spectra were recorded using a scan range (m/z) from 100 to 1700.
Protein identification and label-free quantification (LFQ) were carried out using MaxQuant (version 1.6.17.0, Max-Planck-Institute of Biochemistry, Martinsried, Germany) running Andromeda as search engine and searching against the SwissProt Database (version 14122019 with 20,380 entries, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland); for details, see Cox und Mann [46]. Search criteria included an allowed peptide tolerance for the first and main search of 20 and 10 ppm and a maximum of 2 missed cleavage sites. All peptide and protein identifications met a false discovery rate (FDR) ≤0.01. After protein identification, proteins were filtered for common contaminants as well as reversed sequences, and data evaluation was performed using Perseus (version 1.6.1.3, Max-Planck-Institute of Biochemistry, Martinsried, Germany).
## 2.9. Statistical Analyses
SCGE data were arcsine transformed, and telomere lengths were log transformed to obtain homogenous variances and normality of residuals. The Box M test was carried out to assess symmetry of the variance-covariance matrices. Kolmogorov–Smirnov tests with Lilliefors’ corrected p-values were performed to assess normality of residuals. For the analysis of the different endpoints of DNA stability and repair, telomere lengths, and enzyme activities, a general linear model was applied with age, sex, smoking status, and BMI at baseline as covariates. Testing against baseline values was performed by linear contrasts with Bonferroni correction. In addition, trend tests with respect to time since surgery were performed. All analyses were performed by Stata 13.1 (StataCorp, College Station, TX, USA). Graphs were prepared by GraphPad Prism 5.0 (Graphpad Software, San Diego, CA, USA).
Statistical analysis of plasma proteomics data was performed using a software package (version 1.6.1.3, Max-Planck-Institute of Biochemistry, Martinsried, Germany). Prior to the analysis, LFQ intensity values were transformed (log2x). T-tests were performed between the study groups applying an FDR of 0.05 and a S0 of 0.1, whereby S0 controls the relative importance of t-test p-value and difference between the means. Results are shown as volcano plots.
## 3.1. Description of the Study Group
The demographic characteristics of the study group are summarized in Table 1. The average BMI values were in all group similar and the body weights were also in a narrow range. About one-third of the participants were females.
## 3.2. Impact of BS on Weights and BMIs
Figure 2A–D show the reduction of the body weights and BMIs in the overall BS group. The values decreased substantially ($p \leq 0.001$) 6 months after the surgery (BWs by $27.5\%$ and BMIs by $28\%$). The decline in both parameters was similar in the OAGB group (Figure 2C,D).
## 3.3. Impact of BS on DNA Stability and Oxidative DNA Damage and Repair
Figure 3A summarizes the results of the SCGE experiments. Significant reduction ($$p \leq 0.009$$, $54\%$) in DNA damage was observed under standard conditions after 6 months. No significant effects were found 1 month after the surgery (scatter plots showing the individual values are shown in Supplementary Figure S1A–D).
The middle section of the graphs shows alterations of the FPG-sensitive sites. The extent of comet formation attributable to formation of oxidized purines declined after the surgery. This effect did not reach significance, but a clear trend was observed ($p \leq 0.001$).
The activities of BER and NER decreased after 6 months (NER, $$p \leq 0.049$$ and BER, $$p \leq 0.001$$). A decline in both repair systems was observed already 1 month after the surgery (NER, $16.5\%$ and BER, $7\%$) but this effect did not reach significance.
We analyzed also the effects in the RYGB subgroup. The findings, which were obtained under standard conditions, were identical to those obtained in the overall group ($13\%$ decrease after 1 months and $47\%$ after 6 months). FPG sensitive sites declined by $12.5\%$ after 6 months. We observed an unexpected increase (by $29\%$) of oxidative purines after 1 month. The activity of BER was reduced by $8\%$ after 1 month and $14\%$ after 6 months. The NER activity declined by $18\%$ after 1 month and by $26\%$ after 6 months.
Figure 3B shows the results which were obtained with the OAGB patients. The effects were similar to those found in the overall group. Significant changes were detected under standard conditions, which reflect single- and double-strand breaks ($$p \leq 0.0002$$, $50\%$) after 6 months. The activity of BER was clearly reduced after this period ($$p \leq 0.008$$), while the decline in oxidized bases showed only a trend ($p \leq 0.001$).
## 3.4. Alterations of the Activities of Antioxidant Enzymes
Table 2 and Figure S2A,B show the results of GPx and SOD measurements before and after BS. The activities of both enzymes declined slightly after one (SOD: $6.4\%$ GPx: $7.3\%$) and 6 months (SOD: $1.9\%$ and GPx: $2.5\%$) but these effects did not reach significance in the overall group and in the subgroups.
## 3.5. Results of Malondialdehyde Measurements
We found in the overall group evidence of a significant decrease in this LP product in plasma of the patients half a year after the surgery (baseline before surgery 4.42 ± 0.72 μM/L, after 1 month 4.21 ± 1.1 μM/L, and after 6 months 2.60 ± 0.89 μM/L); also, in the subgroups RYGB and OAGB, a clear decline was detected (OAGB: before surgery: 4.49 ± 0.86 μML, after 1 month 4.32 ± 0.90 μM/L, after 6 months 2.67 ± 0.80 μM/L; RYGB: baseline before surgery 4.50 ± 0.57 μM/L, after 1 month 4.24 ± 0.61 μM/L an after 6 months 2.60 ± 0.48 μM/L).
## 3.6. Alterations of the Telomere Lengths
Table 3 summarizes the results of measurements of the telomere lengths. The T/S values varied over a broad range and increased in the period between one and 6 months in the ALB assay in the overall group and also in OAGB subgroup ($$p \leq 0.022$$ and $$p \leq 0.046$$). The 36B4 assay showed a similar trend without reaching significance.
## 3.7. Alterations of the Proteome Profile
We analyzed 410 proteins compiled from 3182 peptides. The individual proteins are listed in Supplementary Table S2. Figure 4A–C show the results of analyses with plasma samples. No alterations were observed after 1 month (Figure 4A), but significant effects were found 6 months after the surgery (Figure 4C). Four proteins were downregulated, namely serum amyloid A1 (SAA1), C-reactive protein (CRP), and two hemoglobin subunits (HBB and HBA1). The level of apolipoprotein A-IV (APOA4) was significantly higher 1 month after surgery compared to the level detected 6 months after BS (Figure 4B).
## 4. Discussion
As mentioned in the introduction, several earlier investigations indicated that BS has beneficial health effects. For example, it was found that it affects the artherogenic properties of plasma lipoprotein [47] and reduces cardiovascular risks [48]. Furthermore, several studies showed that it normalizes the metabolism of amino acids and proteins [49] as well as the levels of systemic hormones and signaling peptides [50,51,52,53,54] and improves glycemic control [51].
The present study focused on alterations of the stability of the genetic material and related parameters. These observations enable to draw conclusions concerning beneficial long term health effects of the operations. An earlier study focused on the consequences of RYGB and GS, which are the most frequently used techniques. The present study provides additional information about OAGB, which is the most widely used technique after GS and RYGB [55].
We observed a time-dependent weight loss in all participants. Furthermore, we studied for the first time the impact of BS techniques on DNA repair functions. The effects in the different subgroups were more or less identical and similar to findings of earlier studies [56,57,58].
Six months after the surgery, the extent of DNA damage decreased substantially ($54\%$) in the overall group and a similar reduction was found in the OAGB group ($50\%$) and in patients after RYGB ($47\%$). Only one study with BS patients who underwent RYGB and GS [25] has been published in which DNA damage was analyzed in SCGE experiments with lymphocytes and whole blood from the same patients [24,25]. The authors did not detect reduced comet formation 6 months later, but clear effects were found after 1 year [24,25]. One of the reasons for the lack of an effect after 6 months could be that the extent of weight reduction was less pronounced as in our study; i.e., the participants lost only $20\%$ after half a year in the German study, while the BWs decreased in the present investigation by $27.5\%$. We found in the literature only few studies concerning non-surgical weight loss, and the reduction in the BWs in all investigations was less pronounced. In two SCGE studies, a clear decrease in comet formation was detected after 6 months [59,60], while no evidence for a reduction in the micronucleus frequencies (reflecting structural and numerical chromosomal aberrations) was observed in lymphocytes of individuals after consumption of a low carbohydrate/low protein diet by Benassi-Evans and co-workers [61].
It is known that the formation of “comets” reflects adverse health effects in humans, i.e., a recent analysis showed that “large comets” in humans are indicative for increased mortality [12]. Furthermore, it is well documented that subjects with oxidative stress (due to diabetes and other diseases) have more DNA damage [62], and it is also well documented that exposures to chemicals and radiation, which lead to cancer, cause DNA migration [63]. On the other hand, reduction of comet formation may be indicative of positive effects. In this context it is notable that plant-derived foods, beverages, vitamins, and trace elements with cancer protective and antioxidant properties reduce comet formation in humans [34].
We did not detect significant reduction of FPG-sensitive sites which reflect formation of oxidized purines, but their formation decreased in a time-dependent manner in the overall BS group. We found this effect also in the OAGB group. It was stated recently by the EFSA that prevention of oxidative DNA damage has beneficial health consequences [14]. Several earlier articles concern the oxidation of guanosine after BS. For example, Monzo-Beltran and co-workers [28] reported a decline of 8-oxodG in serum and urine samples after GS at time points ≥ 6 months; the same observation was also made in a Turkish study [27]. Carlsson and co-workers [26] measured 8-oxodG and 8-oxoGuo in urine samples after RYGB surgery; both markers decreased 1–2 years after the surgery, while an increase in oxidative DNA damage was detected 3 months after the operations. This observation is interesting as we observed in RYGB patients a pronounced increase (by $29\%$) of FPG sensitive sites after 1 month, possibly as a consequence of post-surgical redox stress (data not shown); notably, no such effect was observed in the OAGB group.
BER and NER are prominent repair pathways in eukaryotic organisms [15] and dysfunctions lead to fatal diseases such as cancer and accelerate aging [15,64]. The impact of BS on the activities of these repair systems was not studied earlier. We found in the present study a clear time dependent decrease in the activities of BER and NER regardless of the type of surgery. These findings were unexpected as it was found in earlier human obesity studies that the activities of both repair systems are higher in lean individuals [9,65]. An explanation for the lower levels which we found after weight loss is the intake of a dietary supplement containing vitamins and trace elements. Supplements are given routinely to BS patients since the uptake of micronutrients is reduced after the operations [35,66,67]. It was found in earlier studies that DNA repair functions decrease after consumption of supplements and antioxidant rich foods. For example, reduction in BER was observed after intake of folate [68]. Additionally, after consumption of a vitamin supplement and an antioxidant rich diet a decrease in this repair system was observed [69]. A decrease in NER was reported in a study with kiwi fruit and also after consumption of antioxidant-rich plant products [70]. According to the authors, these effects may be due to adaptive responses, i.e., downregulation as a consequence of lower levels of DNA damage. It is interesting that we found alterations of the repair systems already 1 month after the surgery. These effects increased only moderately in the following months. On the contrary, DNA damage decreased only slightly after the first month and much stronger effects were seen at the last time point. These differences in the time kinetics indicate that weight loss is not the cause for the alterations of the repair systems.
It is difficult to elucidate which molecular mechanisms account for the reduction of oxidative DNA damage, which we observed. BS had in our study no impact on the activities of SOD and GPx, which are important health related antioxidant enzymes. The expression of genes which encode for these enzymes is regulated by the transcription factor Nrf2, and evidence for its activation was observed in a previous study with BS patients [25]. Results of earlier investigations on the activities of these enzymes after BS are controversial. Guan et al. [ 71] found no alterations of SOD in GS and RYGB patients after 6 months and an increase in the latter group after 12 months. Abad-Jimenez [32] reported an increase in both enzymes after RYGB surgery, while other investigations found reduced activities [31,72]. Many earlier studies indicated that reduction in body weight leads to normalization of the glucose and insulin levels [9,73], and it is well document that increased concentrations lead to release of ROS and cause damage of the genetic material under in vitro conditions (for details, see [9,74]), and also the levels of triglycerides, which are elevated in obese individuals, may play a causal role. It was found in an earlier study that their levels correlate with the extent of DNA damage in obese individuals [75]. A further possible explanation of the high levels of DNA damage as a consequence of excess overweight is the formation of lipid peroxidation (LP) products, which are formed as a consequence of oxidation of fatty acids. Many products of this reaction (aldehydes and ketones) cause DNA damage and cancer. As described in the results section, we found a pronounced decrease in the formation of MDA after BS in the present study. This observation was not unexpected as it is known that MDA levels and other LP products are increased in obese individuals as a consequence of oxidative stress [76,77,78]. In this context, it is notable that several aldehydes and ketones which are formed as a consequence of the oxidation of fatty acids cause DNA damage and cancer [23].
The impact of BS on telomere lengths is a controversial issue. We analyzed in the present study alterations of telomere lengths by two assays using two different single-copy genes ALB and 36B4. The ALB assay showed an increase in telomere lengths between one and 6 months in the overall group and in the OAGB subgroup. In support of this outcome, the 36B4 assay was increased at the end of the study, but this effect did not reach significance. Results of earlier investigations are described in a review of Pene and co-workers [30]. The authors concluded that only results of long-term studies suggest a clear effect on telomere lengths and stated that it is difficult to drawn firm conclusions. Additionally, reviews concerning the consequence of non-surgical weight loss on telomere lengths point in the direction of positive long-term effects [79,80].
Proteome profiling identified a number of proteins, which were altered after BS. Clear upregulation of APOA4, which is indicative for changes of the lipid metabolism, was also found in earlier studies [81]. In the present study, four proteins were downregulated after 6 months. The decrease in beta globulin and alpha globulin is probably a consequence of iron deficiency, which was observed in earlier BS studies [82]. SAA1 and CRP are biomarkers of acute inflammation and cancer development [83,84]; also, in earlier proteome analyses of BS patients, a decrease in the concentrations of both proteins was reported [81,85].
## 5. Conclusions
The results of the present study show that BS leads to stabilization of the genetic material and reduces oxidative DNA damage; these findings are possibly causally related to a decrease in inflammatory reactions. Our findings indicate that adverse health effects, which are caused by increased BW as a consequence of instability of the genetic material, can be reduced by BS.
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|
---
title: Low Levels of Vitamin C during Pregnancy; a Risk Marker of Progression of Diabetic
Retinopathy in Type 1 Diabetic Women?
authors:
- Bente Juhl
- Flemming Klein
- Toke Bek
- Line Petersen
journal: Antioxidants
year: 2023
pmcid: PMC10045393
doi: 10.3390/antiox12030576
license: CC BY 4.0
---
# Low Levels of Vitamin C during Pregnancy; a Risk Marker of Progression of Diabetic Retinopathy in Type 1 Diabetic Women?
## Abstract
Pregnancy is a risk factor for the development or aggravation of diabetic retinopathy. Here, we suggest a relationship between plasma vitamin C (vitC) status during pregnancy and into postpartum in type 1 diabetes and the possible progression of diabetic retinopathy based on data of 29 women. VitC was measured in first, second, and third trimesters and three months postpartum. The women had visual acuity testing and fundus photography performed at least twice during pregnancy and onto four months after birth. An overall retinopathy grade was assigned on a scale from 0 (no retinopathy) to four according to the International Clinical Diabetic Retinopathy scale. At baseline in 1st trimester, 12 women had no retinopathy; seventeen women had retinopathy in grade 1–3. The retinopathy grade increased in nine women; remained unchanged in 17 women, and improved in three women. No women had or developed proliferative retinopathy (grade 4). The level of vitC in 1st trimester predicted the possible progression of retinopathy—the lower the vitC, the more probable the progression ($$p \leq 0.03$$; OR 1.6 ($95\%$ CI:1.06–3.2); $$n = 29$$ (multiple logistic regression))—while the combined levels of 1st and 2nd trimesters and the mean vitC level of the whole pregnancy did not. The diabetes duration, retinopathy grade per se in 1st trimester, 24-h blood pressure measurements, kidney function, urinary protein, HbA1c, or lipid profile were not independent predictors of progression of retinopathy during pregnancy. Retrospectively, the women who experienced progression of their retinopathy during and into postpartum had significantly lower vitC levels in 1st trimester ($$p \leq 0.02$$; $$n = 9$$/20), combined level of vitC in 1st and 2nd trimester ($$p \leq 0.032$$; $$n = 7$$/18), and mean vitC level of the whole pregnancy ($$p \leq 0.036$$; $$n = 7$$/9), respectively. In conclusion, our results suggest that low vitC status in pregnancy could be associated with progression of diabetic retinopathy.
## 1. Introduction
Diabetic retinopathy is one of the most common vision-threatening diseases in the western world and progression in pregnancy has been related to high levels of HbA1c, high blood pressure, low kidney function, lipid profile, longer duration of diabetes mellitus, and preexisting high level of diabetic retinopathy in [1,2,3]. However, pregnancy is also a well-known risk factor by itself of development or progression of diabetic retinopathy in women with type 1 diabetes mellitus (T1DM) [1,4,5,6,7]. The odds of progression of retinopathy in pregnant women have been reported to be about double that compared to non-pregnant women [7,8], and additionally there is a risk of progression during the postpartum [1,6,9].
While the pathophysiology of diabetic retinopathy is not fully understood, research in recent years has disclosed interesting relations between diabetic eye disease and vitamin C (VitC) metabolism. Thus, vitC plays an essential role as an antioxidant and free radical scavenger to detoxify free radicals in the retina and brain [10,11], and impaired activities of this antioxidant defense appear to be one of the possible sources of oxidative stress in diabetic retinopathy [12], leading to other key pathological processes in the development of diabetic retinopathy [13]. Since vitC has been shown to be depleted 10-fold in the vitreous humor of the eyes of patients with proliferative diabetic retinopathy compared to non-diabetic controls [14], this indicates a role of vitC in the development of diabetic retinopathy. Furthermore, in patients with diabetes mellitus, the plasma vitC levels were found to be reduced compared to normal persons [15,16,17,18,19].
While decreases during pregnancy in healthy women were found [20,21,22,23], this decrease also seems to occur in pregnant women with T1DM [23,24], and thus it can be hypothesized that the preceding low level of vitC followed by a further decrease during pregnancy might be associated with the development or progression of diabetic retinopathy. However, the relationship between vitC and diabetic retinopathy during pregnancy has not previously been examined. Therefore, in the present study, measurements of vitC and eye examinations were performed in a cohort of 29 pregnant women with T1DM during pregnancy and postpartum.
## 2. Materials and Methods
Twenty-nine pregnant women with T1DM attending the Department of Obstetrics, Aarhus University Hospital, Denmark fulfilled the inclusion criteria for participation in the study: pregestational T1DM, age > 18 years, no other systemic disease than diabetes, singleton pregnancy, and retinal examinations performed at least twice during pregnancy and onto puerperium.
The insulin treatment of the women was based on multiple daily injection insulin therapy and the women were followed at the maternity ward every other week throughout the pregnancy. Blood samples for vitC and HbA1c were taken during these routine visits as well as routine blood tests, including for kidney function. Moreover, a 24-h urine was collected for measurement of albumin excretion rate. An ambulatory 24-h blood pressure was measured using a portable oscillometry monitor in each trimester and after delivery.
Furthermore, fifteen additional women with T1DM had vitC measurements performed only in the prepregnant condition. None of these women had visual acuity testing and fundus photography performed and they served as an indicator for vitC level in the nonpregnant condition in the study. The 15 women were comparable regarding age, onset, diabetes duration, BMI and HbA1c with the present cohort of 29 pregnant women followed regarding retinopathy. Twenthyfour-h urinary albumin excretion and 24-h blood pressure were not available in this group. Nine of 15 women were non-smokers. The study was approved by the local Ethics Committee (jr.nr$\frac{.1992}{2523}$, $\frac{1998}{4147}$ and 2026-99) and was performed in accordance with the Helsinki II declaration and all women had given their informed consent. The women were informed that the study intended to evaluate trace elements during pregnancy and not specifically the levels of vitC to avoid confounding of vitC complementary intake on the women’s own initiative on the results. The collection of samples for vitC was approved by the local Ethics Committee (jr.nr$\frac{.1992}{2328}$).
## 2.1. Ophthalmological Examination
A standard examination for diabetic retinopathy was performed at the Department of Ophthalmology, Aarhus University Hospital. Visual acuity test was performed using principles defined in the early treatment for diabetic retinopathy (ETDRS) [25] charts and mydriasis was induced by tropicamide $1\%$ eye drops followed by fundus photography with two 60° photographs centered on the fovea and on the optic disc respectively.
The presence of each type of pathological lesion, i.e., hemorrhages and/or microaneurysms, hard exudates, cotton wool spots or vascular abnormalities, such as intraretinal microvascular abnormalities (IRMA), venous beading, or neovascularization, was noted.
Based on this, the retinopathy grade was assessed using a standardized scale: 0: no retinopathy; 1: mild non-proliferative diabetic retinopathy; 2: moderate non-proliferative diabetic retinopathy; 3: severe non-proliferative diabetic retinopathy and 4: proliferative diabetic retinopathy [26].
In each patient, the retinopathy grade on the worst eye condition according to the first available eye examination in the pregnancy was used for comparison to the last available grading for the individual women during pregnancy and onto postpartum. This was supposed to evaluate the final retinal outcome: progression, unchanged or improvement of the retinal eye status.
## 2.2. Vitamin C Measurements
Blood samples for vitC were taken in a non-fasting state to avoid hypoglycemic episodes. Blood samples for plasma vitC measurements were stabilized in sodium EDTA-anticoagulated vacutainer tubes containing dithiothreitol. Tubes were centrifuged and plasma was removed and deproteinized by the addition of $6\%$ perchloric acid. The samples were kept at −80 °C until analysis and assayed by HPLC [27], an accepted gold standard for this measurement [28].
A plot of the ratio of vitC to internal standard vs. the concentration of 6 aqueous standards resulted in a linear curve to at least 86 μM ($y = 0.16$x − 0.028) R2 = 0.99). The within-day and day to day coefficient of variation was $2.6\%$ and $3.9\%$, respectively, of a mean concentration of 19 μmol/L. The analytical recoveries were $111\%$, $104\%$, $102\%$, and $101\%$ at vitC concentrations of 5.75, 28.75, 43.125, and 57.5 μmol/L, respectively.
## 2.3. Data Editing and Statistical Analysis
In the present study, we focused on the level of vitC as a marker of the possible progression of retinopathy. Thus, the predictive value of the mean of vitC samples taken in 1st trimester, the mean of the vitC in combined 1st and 2nd trimester, and of the vitC of the whole pregnancy, were evaluated regarding possible progression in retinal status during and onto postpartum (multiple logistic regression). If more than one sample of vitC per trimester was measured, the sample mean was used in the data analysis. Corresponding to this prospective analysis, a retrospective analysis of differences between two means of vitC arising from the final retinal outcome, progression or no progression, was performed in the similar group separation of vitC. This approach allowed a direct comparison of the prospective and retrospective analysis.
In other analysis, we applied the mean vitC of the single trimester and postpartum. Comparison of 2 means was performed by Student’s t-test if Gaussian distribution could be assured. Otherwise Mann–Whitney’s test.
We a priori calculated to have sufficient data to minimize a type 2 error (power > $80\%$), assuming a difference between the groups of 10 µmol/L and an expected SD of about 10 µmol/L, which was found earlier in vitC measurements of pregnancy [23].
We carried out a predefined vitC subgroup analysis using the threshold of the $50\%$ percentile of the mean vitC of the whole pregnancy (=31.1 μmol/L) in calculating the probability for development progression or not in retinopathy (Fisher’s Exact test). The $50\%$ percentile was an arbitrarily chosen threshold since we had no a priori research to lean on in this matter.
The time relationship between mean vitC level in each trimester and the progress of pregnancy and into postpartum were analyzed by linear regressions analysis.
The simple mean in case of more than one measurement of HbA1c, the creatinine clearance, and the measurements of urine albumin excretion rate taken in each trimester and three months postpartum were calculated and used in descriptive statistics of the cohort.
Multiple logistic regressions were used as predictive analysis of the diabetes duration, retinopathy grade per se, 24-h blood pressure measurements, urinary protein, HbA1c, and lipid profile as independently predictors of progression of retinopathy during pregnancy as the dependent variable.
Statistical analysis was performed with Sigma Plot12, Systat software.
Values are given as mean SD, unless otherwise stated. A two-sided $p \leq 0.05$ was chosen as level of significance.
## 3. Results
Clinical data and characteristics of the participants are shown in Table 1.
The mean HbA1c in 1st trimester and during the whole pregnancy was below $7.0\%$ (corresponding to 53 mmol/mol) in $44\%$ and $47\%$ of the women respectively. HbA1c median (5–$95\%$) of the whole pregnancy was $7.1\%$ (5.6–$9.3\%$). The levels of HbA1c in 1st trimester in the group that progressed in retinopathy compared to the group without progression and as a mean of the whole pregnancy, were NS: (7.5 (0.73) vs. 7.3 (0.92), $$p \leq 0.51$$) and (7.5 (0.97) vs. 7.2 (0.89), $$p \leq 0.32$$) respectively.
The levels of vitC in 1st trimester were similar whether the women had retinopathy ($$n = 17$$) or not ($$n = 12$$). The level of HbA1c, systolic and diastolic 24 h blood pressure in 1st trimester were similar whether the women had retinopathy ($$n = 17$$) or not ($$n = 12$$).
Altogether, twenty-three women had their first eye examination in the 1st trimester and, of these, one woman had her last examination in the 2nd trimester, three women had their last eye examination in third trimester, and 19 had the last examination postpartum. Six patients had the first examination in 3rd trimester and the last one postpartum.
Nineteen women were examined twice, nine women were examined three times, and one patient was examined four times in the study period from 1st trimester and onto four months postpartum.
The retinopathy progressed in nine women; remained unchanged in 17 women and improved in three women. Thus, from entry in the study to postpartum four out of 12 women with initially no retinopathy (grade 0) progressed to grade 1 retinopathy, while one progressed to grade 2; four out of 14 women with grade 1 retinopathy progressed to grade 2 while one patient returned to no retinopathy (grade 0). One out of two patients with moderate retinopathy (grade 2) improved to grade 1 while the other woman remained unchanged. One woman with severe retinopathy (grade 3) improved to grade 1. Prospectively, the level of vitC in 1st trimester predicted the possible progression of retinopathy—the lower the vitC, the more probable the progression ($$p \leq 0.03$$; OR 1.06–3.2; $$n = 29$$ (multiple logistic regression))—and the combined level of 1st and 2nd trimester tended to but did not reach significance ($$p \leq 0.06$$; OR 0.97–5.34; $$n = 25$$), while the mean vitC level of the whole pregnancy did not (p = NS; $$n = 16$$), respectively (Table 2).
We did not find diabetes duration, retinopathy grade per se, 24-h blood pressure measurements, urinary protein, HbA1c, or lipid profile to be independent predictors of progression of retinopathy, and thus these parameters were not included in the prospective multiple logistic regression analysis. We did not find smoking associated with progression of retinopathy; three out of nine smokers and six of 20 non-smokers progressed in their retinopathy respectively. The levels of vitC were similar in smokers and non-smokers (30.6 µmol/L (SD 15.0) vs. 35.7 µmol/L (SD 35.7) (pNS)) in 1st trimester.
Retrospectively, the women who experienced progression of their retinopathy during and into postpartum had significantly lower vitC levels in 1st trimester, in the combined level of vitC in 1st and 2nd trimester and in the mean vitC level of the whole pregnancy compared to the women without progression (mean (SD), p, n = +/−: 25.2 µmol/L (10.3) vs. 38.1 µmol/L (14.4), $$p \leq 0.02$$; $$n = 9$$/20) and (24.8 µmol/L (SD 5.86) vs. 38.7 µmol/L (SD 15.53), $$p \leq 0.032$$; $$n = 7$$/18) and (25.7 µmol/L (SD 7.8) vs. 40.6 µmol/L (SD 15.5), $$p \leq 0.036$$; $$n = 7$$/9), respectively, as shown in Table 3.
In the control group of 15 clinically comparable non-pregnant women with T1DM (Table 1), the vitC level was 40.0 µmol/L (17.8) compared to the 34.1 µmol/L (14.2) in 1st trimester indicating a lower vitC in the 1st trimester, but not statistically significant. However, a comparison between the vitC level in the non-pregnancy and in the group of women who had progression of retinopathy had a significant lower vitC in 1st trimester (25.2 µmol/L (10.3)) compared to the non-pregnant women ($$p \leq 0.03$$).
Linear regression analysis did not show a significant linear decrease of vitC levels in in relation to weeks of ongoing pregnancy, but the levels in the women with progression and no progression of their retinopathy seem to be constantly below or above throughout pregnancy and post partum respectively compared to the whole group (Figure 1).
Table 4 shows the result of Fishers exact test in the subgroups of women with a vitC level below or above the median level of the mean vitC (=31.1 μmol/L) in relation to the development or not of retinopathy.
The relative risk of development of progression was 3.75-fold higher in the group of women with a vitC level below that level than the one found in the group of women with a vitC status above this level. Relative risk was calculated as ($\frac{7}{14}$ = 0.5)/($\frac{2}{15}$ = 0.1333) = 3.75 (see also Table 4).
In approximately $52\%$ (15 out of 29), we observed a poor vitC status defined as a plasma vitC < 23 µmol/L at least one time during pregnancy and postpartum. In two women ($7\%$), we found a level of <11 µmol/L postpartum corresponding to the level of scurvy. Both women had retinopathy and progressed during pregnancy.
## 4. Discussion
In the present cohort, we expected to find the level of vitC to be lower owing to the diabetic pregnancy itself than generally reported in the nonpregnant T1DM state and thereby disclosing a possible relation between vitC and the diabetic pregnancy with its “flourishing” retinopathy; a relation that is difficult to reveal when evaluating a longstanding low, but not necessarily poor level of vitamin C throughout a long term ongoing T1DM.
Seen in this perspective, the presented results seem to support our hypothesis, as discussed in the following.
Firstly, in the present prospective study of the course of diabetic retinopathy during/into the puerperium of 29 pregnancies, we found progression in $31\%$ of the pregnant women; a level also reported by Phelps et al. in a similar sized study [8] and several others, as reviewed in [7], and an approximately twofold higher level of progression of no retinopathy to simplex retinopathy than in non-pregnant T1DM patient under conventional treatment [29]. The progression of retinopathy has been reported to occur at varying times during the pregnancy and our observation of worsened retinopathy also postpartum is not the most common outcome and since the women were evaluated ophthalmologically only four months postpartum, we do not know whether the progression persisted or anything about the subsequent vitC levels. However, while progression up to one year postpartum has been reported [1,9], long term studies have shown that the aggravation seems not to have long-term detrimental effects as regards the progression of retinopathy unless it has proceeded to pre-proliferative condition and phases to be followed by persistency [6].
Secondly, the obtained glycemic control in the present study of 7.3–$7.4\%$ was in the same range as also found in the DAPIT study of 762 women during pregnancy, and likewise the level of vitC found in our study was in accordance with the level found in the placebo group in this study; a randomized placebo-controlled trial for prevention of pre-eclampsia in women with T1DM [24]. The level of vitC in 248 women in the placebo decreased from 44 to about 35 µmol/L during pregnancy, representing a significant decrease ($p \leq 0.05$ calculated on the given information in the article).
We did not find a decrease of vitC in our cohort of women during pregnancy (linear regression) as found in the DAPIT study [24], but if there was any decrease of vitC, it might have occurred from the non-pregnant to the pregnant stage. The vitC level in the comparable 15 women (Table 1) with T1DM and nonpregnant was 40.0 µmol/L (17.8) compared to the 34.1 µmol/L (14.2) in 1st trimester, indicating a decrease, however not statistically significant.
In another cohort of 20 T1DM nonpregnant patient with retinopathy investigated by Juhl et al. by the same methods and the same technicians as the present study [30], the authors found a level of 50 µmol/L (36.1) compared to the level of 34.1 µmol/L (14.2) in the whole group of women in 1st trimester (Table 1). Harding et al. found a level of 43.7 µmol/L (18.4) in 735 men and women with diabetes [17].
Under all circumstances, whether the plasma vitC decreased from the non-pregnant to the pregnant condition or not, we observed a plasma vitC < 23 µmol/L in approximately $52\%$ of the women at least one time during pregnancy and postpartum; apparently a higher proportion of women compared to approximately $25\%$ of nonpregnant T1DM patients [30], approximately $12\%$ in the healthy control pregnancies in the study of Juhl et al. [ 23], and $5\%$ in the general population [15].
Thirdly, prospectively, the vitC level in 1st trimester in multiple regression analysis was an independent predictor for a progression of retinopathy; the lower the vitC, the more probable the progression of retinopathy. The combined level of 1st and 2nd trimester tended to but did not reach significance ($$p \leq 0.06$$), while the mean vitC level of the whole pregnancy did not. The significance also persisted when adjusted for common diabetic risk factors as the majority of the literature has associated it with progression of retinopathy during pregnancy [1,4,5,6,7] and this predictive ability of vitC was furthermore supported by the finding of an increased relative risk of 3.75 of progression of retinopathy if the vitC level was in the lower half as a mean of the whole pregnancy, although the latter analysis was found not significant ($$p \leq 0.05$$).
Retrospectively and in support of the level of vitC as an independent predictor for a progression of retinopathy—the lower the vitC, the more probable the progression of retinopathy—, we found that the nine women who experienced progression of their retinopathy during and into postpartum were all characterized by a significantly and constantly lower mean level of vitC (Table 3) throughout pregnancy and an even further significant decrease was observed postpartum. Thus, two (of seven) women had a level of vitC < 11µmol/L, corresponding to the level of scurvy that in the long term will lead to scurvy. Both women had progression of retinopathy during/into the puerperium four months later. Furthermore, we found that the nine women who progressed in their retinopathy had vitC levels in 1st trimester that were significantly lower than the level in the non-pregnant women ($p \leq 0.03$), in opposition to the levels of vitC found in the group of women that did not develop progression. This result indicates a decrease of vitC at least in the group of women with progression from the non to the pregnant stage followed with a more or less constant low vitC level just above the level of insufficiency (23 µmol/L) throughout pregnancy.
These retrospective findings indicate the importance of low vitamin C already from 1st trimester in relation to the progression of retinopathy.
The above clinical results lead to a further discussion about the relevance of the findings.
As the focus on the importance of oxidative stress in the development of diabetic retinopathy has increased, further research has disclosed interesting relations between angiogenesis in diabetic eye disease and VitC metabolism [5,6,7].
Thus, vitC has been found present in retinal and brain tissues at high concentration compared with other organs, and there is a greater than 10-fold gradient between the concentrations of vitC in the retina and brain tissues and blood [10,11].
Furthermore, the retina is reported to have the highest glucose oxidation and oxygen uptake of any tissue, thus being extremely susceptible to increased oxidative stress if activities of antioxidant defense (such as vitC and superoxide dismutase) are not present [12].
A description of the pathology associated with diabetic retinopathy is beyond the scope of this article, but recent papers have excellently reviewed the pathological features of diabetic retinopathy [13,31] based on key pathogenic processes that drive the abnormalities in the retina. In summary, the loss of vascular autoregulation leads to nutrient and oxygen deprivation of the retina, and retinal vascular BM thickening occurs and might impair cell–cell communication of the endothelium. This retinal vascular insufficiency leads to the development of diabetic retinopathy first heralded by the appearance of lesions, such as microaneurysms, maybe owing to pericyte death contributing to a weakening of the capillary. Retinal capillaries become progressively non-perfused in the diabetic retina as a direct result of vasodegeneration. The capillaries appear as naked BM tubes where the endothelial cells have disappeared secondary to pericyt death. This non-perfusion leads to ischemic pathology, with the upregulation of VEGF resulting in neovascularization and excessive vasopermeability as one the most important peptide secretions driving end stage pathology [13].
Nitrit oxide (NO) is produced in endothelial cells and exerts an important function in the autoregulation of the brain. Moreover, reduced availability of NO leads to impaired vasodilation; a well-known condition in diabetes implied in subsequent endothelial dysfunction [32,33,34,35]. VitC is directly involved in the bioavailability of NO [36,37].
An in vitro study found that ascorbic acid in cultured microvascular brain pericytes could prevent high glucose induced apotheosis [10]. In the paper, loss of pericytes is considered one of the earliest changes in the development of diabetic retinopathy associated with dysfunction of the endothelium and loss of very tight endothelial permeability barrier.
The importance of increased formation of advanced glycation end products (AGE) in diabetes was reviewed by Singh et al. The accumulation of AGEs increased the retinal endothelial cell permeability leading to vascular leakage [38]. In vitro high glucose-induced barrier leakage was mediated largely by endothelial activation of the receptor for advanced glycation end products (RAGE) since it was prevented by RAGE blockade and mimicked by RAGE ligands. VitC completely prevented RAGE ligand-induced increases in barrier permeability [39].
Another experimental study found oxidative stress to be involved in the upregulation of vascular endothelial growth factor protein in the retina in diabetic rats [40] and to increase VEGF-induced endothelial barrier permeability which was prevented by vitC [41]. As described, VEGF is considered a critical stimulus for diabetic macula edema (DME) and both retinal and choroidal neovascularization [42,43,44]. A recent in vitro study proposed vitC as a possible treatment modality in diabetic macula edema since the vitamin is severely depleted 10-fold in the vitreous humor of the eye of patients with proliferative retinopathy compared to controls [14] and on line with treatment with anti VEGF antibodies injections approved for the treatment of DME [41,45].
The key pathogenic processes discussed above offer a theoretical background for linking these events to the low vitC levels found in T1DM and even lower levels found during pregnancy as in the present study.
Limitations of the present study obviously include the small number of participants. Obtainment of vitC measurements and eye status before pregnancy in the present cohort could have contributed important predictive information on the effect of pregnancy itself on the subsequent retinopathy status and vitC levels during pregnancy in the studied cohort. Moreover, sufficient vitC measurements post-partum could have allowed for relevant evaluation in relation to the postpartum progression of the retinopathy. The samples for vitC were taken in a non-fasting state to avoid hypoglycemic episodes, which may have increased the SD of the vitC measurements and thus the risk of type 2 mistakes in the statistics.
## 5. Conclusions
In conclusion, the results from this small-sized observational study of a pregnant T1DM cohort, the first of its kind, indicate that low levels of vitC status could be associated with an increased risk of development and/or progression of retinopathy. The results are in accordance with the presented research, but further investigation is needed to verify the results. In the long term, it could have important clinical implications for T1DM pregnancy.
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|
---
title: Smooth Muscle Cells from a Rat Model of Obesity and Hyperleptinemia Are Partially
Resistant to Leptin-Induced Reactive Oxygen Species Generation
authors:
- Ocarol López-Acosta
- Magdalena Cristóbal-García
- Guillermo Cardoso-Saldaña
- Karla Carvajal-Aguilera
- Mohammed El-Hafidi
journal: Antioxidants
year: 2023
pmcid: PMC10045401
doi: 10.3390/antiox12030728
license: CC BY 4.0
---
# Smooth Muscle Cells from a Rat Model of Obesity and Hyperleptinemia Are Partially Resistant to Leptin-Induced Reactive Oxygen Species Generation
## Abstract
The aim of this study was to evaluate the effect of leptin on reactive oxygen species’ (ROS) generation of smooth muscle cells (SMCs) from a rat model of obesity and hyperleptinemia. Obesity and hyperleptinemia were induced in rats by a sucrose-based diet for 24 weeks. ROS generation was detected by using dichloro-dihydrofluorescein (DCF), a fluorescent ROS probe in primary SMCs culture. An increase in plasma leptin and oxidative stress markers was observed in sucrose-fed (SF) rats. At baseline SMCs from SF rats showed a more than twofold increase in fluorescence intensity (FI) compared to that obtained in control (C) cells. When the C cells were treated with 20 ng leptin, the FI increased by about $250\%$, whereas the leptin-induced FI in the SF cells increased only by $28\%$. In addition, sucrose feeding increased the levels of p22phox and gp91phox, subunits of Nox as an O2•− source in SMCs. Treatment of cells with leptin significantly increased p22phox and gp91phox levels in C cells and did not affect SF cells. Regarding STAT3 phosphorylation and the content of PTP1B and SOCS3 as protein markers of leptin resistance, they were found to be significantly increased in SF cells. These results suggest that SF aortic SMCs are partially resistant to leptin-induced ROS generation.
## 1. Introduction
Metabolic syndrome (MetS) and obesity are risk factors for the development of cardiovascular diseases (CVD) such as hypertension, atherosclerosis and heart failure, which are considered leading causes of death worldwide [1]. In obesity associated with hyperleptinemia, leptin-induced reactive oxygen species (ROS) generation in vascular tissues is suggested to be a mechanism involved in the physiopathological processes of hypertension and atherosclerosis [2,3,4,5]. Leptin, a 16-kDa polypeptide, was primarily reported to be only released from adipose tissue to regulate food intake energy expenditure in the brain [6,7]. However, cardiomyocytes and vascular smooth muscle cells (SMCs), were recently described as both producers and targets of leptin [8,9,10]. Leptin exerts its biological action by binding to its receptor, which is expressed in several peripheral tissues [11] but its physiological function remains to be established. Various peripheral tissues, including liver and lung, express the short-form leptin receptor (Lep-Ra) which is only involved in leptin transport [12]. In the vasculature, the long-form leptin receptor (Lep-Rb), with a molecular size of 170 kDa, is expressed in endothelial cells [13]. In vascular smooth muscle cells (SMC), the 130 kDa short form of the leptin receptor was reported to mediate the proliferative phenotype [14]. The effect of leptin on artery relaxation is controversial. In some reports, leptin was found to impair vascular relaxation via its receptor and induce superoxide anion generation which reduces nitric oxide availability [15,16]. However, other reports have shown that leptin protects against aorta contractile response to angiotensin II, either by inhibiting the increase in cytosolic Ca2+ or by a mechanism involving nitric oxide generation [17,18]. In endothelial cells and cardiomyocytes, leptin increases the level of oxidative stress markers [19], participates in vascular remodeling, since it induces rat aortic SMC proliferation [14], and promotes SMC neo-intimal growth after vascular injury in mice [20]. Leptin-induced SMC proliferation is mediated by ROS generation via NADPH oxidase (Nox) assembly and activation [21]. Nox activity is considered the most important source of superoxide anion (O2•−) in vascular tissues and plays an important role in vascular remodeling and dysfunction during the development of CVD [22,23].
In pathological conditions such as obesity and MetS, several circulating factors such as leptin can directly interact with vascular cells to induce a change in cell phenotype and damage by a mechanism that involves ROS generation. Therefore, most studies on leptin effect have been performed on normal cells or cells exposed to angiotensin to mimic impaired relaxation or cell proliferation [24]. Studies using cells from obese or hyperleptinimic models to understand the pathophysiological role of hyperleptinemia on ROS generation are rare. Our group experimented on a model of intra-abdominal fat accumulation induced by a high sucrose diet where aorta ring vasoconstriction was found to be enhanced in response to norepinephrine, and vasorelaxation reduced in response to acetyl-choline [25]. These responses are associated with increased ROS generation through Nox activity in the vascular tissue [25]. Recently, a significant structural change of the middle medium layer of the thoracic aorta of SF animals compared to C rats was reported [26]. A sucrose diet induces a change in vascular tissue thickness that may be associated with a change in the contractile to synthetic (proliferative) smooth muscle cell phenotype that might be associated with alterations in aortic ring vascular reactivity and hypertension. In addition, the model of sucrose-diet induced obesity is characterized by increased plasma free fatty acid (FFA) levels, hypertriglyceridemia (TG) and hyperleptinemia, and is expected to develop leptin resistance [27]. Indeed, lowering plasma leptin levels, either by inhibiting adipocyte leptin production or by increasing kidney leptin clearance, has been described to restore and improve leptin sensitivity in mice [21,28].
The interaction of leptin with its Lep-R involves the participation of protein tyrosine phosphatase-1B (PTP1B), the suppressor of cytokine signaling 3 (SOCS3), and of the signal transducer and activator of transcription 3 (STAT3), well-known molecules that attenuate leptin signaling [29]. For example, SOCS3 is a leptin-inducible inhibitor of leptin signaling. Therefore, the use of SMCs extracted from an obese model with hyperleptinemia, may be a relevant approach for studying the leptin action and the mechanism by which leptin contributes to ROS generation. Hence, the objective of this study was to evaluate the effect of leptin on ROS generation and on the antioxidant system, in a primary culture of SMC derived from the aorta of a model of sucrose-diet induced obesity.
## 2. Experimental Design
Animals. The experiments were conducted in compliance with the Mexican Federal Regulation for Animal Experimentation and Care (NOM-062-ZOO-2001). Weanling male Wistar rats aged 4 weeks and weighing approximately 65 ± 5 g were obtained from the animal facility of the National Institute of Cardiology Ignacio Chávez. The animals were divided into two groups of 12 rats each: the control group (C) received a solid food ad libitum (Lab diet formula 5001, Ralston Purina Corp., St Louis, MO, USA) and water; the sucrose-fed group (SF) received a $30\%$ sucrose solution in drinking water and the same solid food ad libitum as the C group. At the end of the treatment period, blood pressure measurements of the rats were performed by the tail-cuff method: the cuff was connected to a pneumatic pulse transducer (Narco Bio-Systems, a Healthdyne Co., Houston, TX, USA) and a programmed electro-sphygmomanometer from the same company. Recordings were obtained in duplicate by means of a Narco Bio-Systems polygraph [30]. After 24 weeks of treatment, the rats were fasted overnight and sacrificed the next day.
Plasma leptin, insulin, FFA, TG, and glucose analysis. Blood was collected from the abdominal aorta into tubes containing an anticoagulant ($0.1\%$ EDTA) and immediately centrifuged at 600× g for 20 min at 4 °C. To the plasma thus obtained, $0.005\%$ of butylated hydroxy toluene (BHT) was added as an antioxidant and the mixture was stored at −70 °C until FFA analysis, which was performed by gas chromatography as described previously [31] while lipids were extracted according to the method of Folch et al. [ 32]. Plasma glucose and TG concentrations were measured according to the method described by Nagele et al. [ 33]. Plasma insulin and leptin levels were measured using an insulin and a leptin kit (Linco Research, St. Charles, MO), respectively. The HOMA-IR was calculated from the insulin and glucose values using the following formula: {[insulin] (in mU/l) × [glucose] (in mmol/l))/22.5}. Intra-abdominal fat was dissected off retroperitoneal cavity and around both kidneys, and immediately weighed. Visceral and duodenal fat was not included in this procedure.
Oxidative stress markers. Plasma carbonyl proteins were quantified in plasma prepared as described above using a modified method as reported previously [34,35]. Thiobarbituric acid reactive substance (TBARS) was determined in the plasma as described previously [30].
Smooth muscle cell primary culture. The SMCs were extracted from the aorta in sterile conditions as described previously [36]. The tissue was immediately placed in a buffer containing 140 mM NaCl, 4.7 mM KCl, 1.2 mM Na2HPO4, 2.4 mM MgSO4, 2 mM CaCl2, 5.6 mM glucose, 0.02 mM EDTA, 25 mM HEPES, pH 7.4.
In a first step, the fat was removed and the aorta was incubated with 1 mg/mL type II collagenase (Gibco) for 20 min to discard the adventitial tissue from smooth muscle tissue along the aortic wall. In a second step, aorta without adventitia was incubated in the medium containing 1 mg/mL papain (Roche) for 40 min to disperse the smooth muscle cells. Subsequently, the SMCs were filtered through a 230 μm pore sieve (Tissue Grinder Kit, Sigma) and seeded in a 25 cm2 culture flask, in DMEM/F-12 as the culture medium (Gibco), supplemented with $10\%$ fetal bovine serum (FBS, Gibco) which was inactivated at 56 °C for 30 min. The SMCs were incubated at 37 °C, in an atmosphere of $5\%$ CO2 and $90\%$ humidity. When the cells reached confluence, they were dispersed with $0.25\%$ trypsin-EDTA (Gibco) and re-seeded in a 75 cm2 tissue flask in the same culture medium as described above (first passage).
Smooth muscle cell ROS generation. In the second passage, cells were seeded at 10,000 cells per cm2 for rapid growth in a 6-well cell culture plate (Corning Incorporated) containing a DMEM/F12 medium supplemented with $10\%$ FBS. After 48 h of culture, cells were incubated in the same medium without FBS but in the presence of 10 μM of 2′,7′ dichlorodihydrofluorescein diacetate (DCF-DA) for 15 min. After washing the cells from excess DCF, they were stimulated for a further 16 min with leptin at different concentrations (20, 40 and 80 ng/mL culture mediums) to induce ROS generation. At the end of the experiment, the cells were washed and fixed with $1\%$ paraformaldehyde for 30 min at 4 °C. To visualize the nucleus, the fixed cells were incubated with 5 μM DAPI (4′,6-diamidino-2-phenylindole).
The effect of leptin on ROS generation was also analyzed in the presence of apocynin and diphenylene-indol (DPI) as Nox inhibitors, or in the presence of N-acetyl-cysteine (NAC) as a reducing agent. The assay was performed on adhered cells grown on a 6-well culture flask that was pre-incubated for 15 min with apocynin, DPI or NAC, and then incubated with 10 μM DCF-DA for 15 min before the cells were stimulated with leptin at 40 ng for 15 more minutes to stimulate ROS generation. The cells were then washed with PBS to remove excess DCF-DA and were fixed with $1\%$ paraformaldehyde for 30 min at 4 °C. The cells were then washed again three times with PBS. The fluorescence of oxidized DCF and DAPI was detected by fluorescence microscopy.
Image analysis. Images were obtained by fluorescence microscopy using LSM-700 Zeiss equipment (Baden-Württemberg) equipped with a 20X objective. The fluorescence of oxidized DCF and DAPI were detected at Excitation326nm/Emission432nm and Ext358/Em461, respectively. The fluorescence image was analyzed using SEISS ZEN microscope software. The fluorescence intensity (FI) of DCF in a given area was divided by the FI of DAPI as a reference of the number of nuclei. The ratio of the FI (DCF)/FI (DAPI) value was reported in the results.
Effect of leptin on protein content. As described above, in the second passage, SMCs were seeded at 10,000 cells per cm2 for rapid growth in a DMEM/F12 medium, supplemented with $10\%$ FBS in Corning (100 × 20 mm) style dishes. When the cells reached confluence, they were stimulated with leptin for 24 h. At the end of the experiment, cells were harvested and lysed in a buffer containing 100 mM Tris-HCl, 5 mM sodium pyrophosphate, 10 mM EDTA (pH 7.2), 50 mM NaF and $1\%$ Triton X100, and supplemented with 1 mM sodium orthovanadate, 1 mM phenylmethylsulfonyl-fluoride (PMSF), 2 μg/mL aprotinin, 2 μg/mL pepstatin and 2 μg/mL leupeptin as anti-proteases. The sample was then centrifuged at 8000× g for 10 min at 4 °C to remove cell debris. Protein levels were quantified in the homogenate using the Bradford method [37]. Two hundred μg protein of each sample was collected, suspended in 25 μL of buffer load containing 125 mM Tris-HCl (pH6.8), $20\%$ glycerol, $4\%$ SDS, $10\%$ 2-mercaptoethanol and $0.004\%$ bromophenol blue, completed to 50 μL with Laemmli’s solution (40 mM Tris, $1\%$ SDS and $1\%$ β-mercaptoethanol).
Fifty to 80 μg protein of sample was loaded into an SDS-PAGE gel with the acrylamide percentage depending on the protein to be analyzed as indicated in the figure legend. The electrophoresis was run for 3 h at 120 V. The protein transfer was performed onto a PVDF (polyvinylidene fluoride) membrane with a pore size of 0.22 μm (Immobilon Millipore) at 350 mA for 60 min in a semi-dry transfer chamber (Bio-Rad, Trans Blot SD). The non-specific protein detection was reduced by blocking membranes in a TBS (25 mM Tris, 150 mM NaCl) solution containing $5\%$ skim milk and $0.1\%$ Tween 20. Then, the membranes were incubated with polyclonal antibodies against (Cu/Zn)SOD, (Mn)SOD, catalase, p22phox, gp91pox, Nox4, leptin receptor (Lep-R) and GAPDH as a control load from Santa Cruz (Biotechnology Corporation, Santa Cruz, CA, USA) except for the anti-catalase antibody, anti-SOCS3, anti-PTP1B, anti-STAT3 and phosphorylated anti-STAT3, which were purchased from Abcam. The secondary antibodies used were peroxidase conjugated. Proteins were revealed by chemiluminescent reagent clarity (Bio-Rad) and the membranes were exposed to image plates (BioMax, Kodak) for 5 min. The image plate was captured with an imaging system GelDoc-It (UVP Inc., Upland, CA, USA). Bands were analyzed by a UVP image analyzer and optical density (OD) was evaluated with VisionWorks LS software (UVP Inc., Upland, CA, USA).
The SOD and CAT activities. The activities of SOD and CAT in vascular SMC homogenate were assessed using the technique of native polyacrylamide gel staining, which allows the assay of the activity of CAT or single SOD isoform and excludes interference from non-CAT or non-SOD molecules in the crude tissue extract, which is not possible to avoid when using the spectrophotometric method [38]. Briefly, 10 μL of each sample containing 2 mg/mL total protein was loaded onto $5\%$ staking and $8\%$ native polyacrylamide gel (without SDS) and the proteins were separated at constant current (120 V) at 4 °C for 3 h. After electrophoresis, the gels were washed with a 50 mM phosphate buffer (pH: 7.8) for 10 min and then incubated in a solution containing 50 mM potassium phosphate (pH: 7.8), 275 μg/mL nitroblue tetrazolium (NBT), 65 μg/mL riboflavin and $0.25\%$ tetramethylenediamine (TEMED). After 15 min incubation in the dark, the blue NBT stained gel for O2•− was rinsed in phosphate buffer and illuminated for 15 min with a UV light source. The SOD activity appeared as clear bands on a purple background.
For CAT activity, the washed gel was incubated in a buffer containing 5 mM H2O2 for 10 min and excess H2O2 was eliminated by washing the gel three times with double distilled water. Then the gel was stained with a mixture of FeCl3/K3Fe(CN)6 (potassium ferricyanide) at $1\%$ each. The CAT activity appears as clear bands on a blue-green background. Then, the gels were immediately captured with a GelDoc-It imaging system and analyzed by a UVP image analyzer as described above. The results were reported as pixels.
## 3. Statistical Analysis
All statistical analyses were performed with Sigma plot version 11 (Systat Software Inc., San Jose, CA, USA). All values are expressed as means ± SD. Differences between groups were analyzed by one-way ANOVA for selected variables, followed by a Tukey ad hoc test. The number of animals used for each analysis is indicated in the figure and table legends. Statistical differences were considered significant when $p \leq 0.05.$
## 4.1. General Characteristics of Animals
The treatment of rats with $30\%$ sucrose in drinking water for 24 weeks induced a statistically significant increase ($p \leq 0.05$ to $p \leq 0.01$) in systolic blood pressure, plasma TG, FFA, insulin and leptin, and a greater accumulation of intra-abdominal adipose tissue (Table 1). No significant changes in body weight, glucose and total cholesterol were observed between the groups (Table 1). However, the significant difference in HOMA-IR between the control and SF rats indicates insulin resistance in the model, as previously demonstrated by the hyperinsulinemic/euglycemic clamp experiment [35]. Regarding cholesterol associated with HDL, a significant decrease was observed in the SF animals ($p \leq 0.05$).
## 4.2. Oxidative Stress Markers
Protein carbonyls, markers of oxidative stress in vivo, were significantly increased by approximately $50\%$ ($p \leq 0.05$) in the plasma of the SF animals (Table 1). In regard to TBARS, a marker of lipid peroxidation, it was found significantly enhanced in the plasma of SF rats by approximately $50\%$ ($p \leq 0.05$).
## 4.3. Smooth Muscle Cell ROS Generation
To evaluate ROS generation by SMCs, we used DCF-DA, which is permeable to the plasma membrane and, once in the cell, is hydrolyzed to free DCF through the action of a non-specific esterase and is oxidized by ROS. Microscopic images (Figure 1) show that in DCF-DA loaded SMCs, the fluorescence intensity at baseline (without leptin stimulation) was three and a half times more intense in SF cells compared to cells from control animals. Figure 1 shows the result obtained from the ratio of DCF FI to DAPI FI as a reference to cell number. The bottom panel also shows the effect of leptin on the ratio in a dose-dependent manner in control cells with an increase of approximately $250\%$, $425\%$ and $700\%$ at 20, 40 and 80 ng of leptin, respectively. Whereas leptin enhanced the ratio in SF cells only by $28\%$, $44\%$ and $52\%$ at 20, 40 and 80 ng, respectively (Figure 1).
The increase in FI induced by 20 ng leptin was modulated in cells from control and SF rat aortas by apocynin and DPI, Nox inhibitor, and by NAC as a reducing agent (Figure 2). The increased fluorescence of DCF induced by leptin was more sensitive to apocynin and DPI than to NAC (Figure 2).
Both apocynin and DPI inhibit the FI of oxidized DCF induced by leptin in a dose-response manner in C and SF cells. The ratio of FI (DCF)/FI (DAPI) was decreased by $60\%$ in both SF and control cells (Figure 2) by DPI at 10 μM.
The presence of apocynin, a more selective inhibitor of Nox, when pre-incubated with SMC, also inhibited the increase in the FI ratio in a dose-response manner (Figure 2) and decreased ROS generation in SF cells but with less efficacy than did DPI. In regard to NAC, a reduction of the ratio was observed but without reaching a statistically significant difference.
## 4.4. Western Blot of Nox and Their Subunit Proteins
The Western blot analysis showed a significant increase in the level of p22phox, by approximately $170\%$ in SMCs from SF aortas as compared with C (Figure 3a). When leptin was incubated with the cells for 24 h, the p22phox content was found to be enhanced in the control cells by approximately $64\%$ and was not significantly affected in SF cells. Concerning the gp91phox content (Figure 4b), a significant increase in the protein level was observed in SMCs from the SF aortas in comparison with the control SMCs.
When cells were incubated with leptin, a slight but a significant ($p \leq 0.05$) increase in gp91phox was observed in control cells. In SF cells however, leptin did not significantly affect the gp91phox level (Figure 3b). In regard to Nox4 content, no significant difference in the protein level was observed between SF and control cells (Figure 3c) and no significant change was observed under the effect of leptin in SF and control SMCs (Figure 3c).
## 4.5. Leptin Receptor (Lep-R)
The Western blot analysis demonstrated the presence of a band that matched the predicted molecular weight of the Lep-R form expressed in the brain (see supplemented data). Sucrose feeding induced a significant decrease in receptor levels compared with the control cells. When cells were incubated with 20 ng/mL leptin for 24 h in a primary culture, the band was significantly decreased in the control cells and slightly enhanced in SMCs from SF rats (Figure 4a).
## 4.6. Effect of Leptin on STAT3, PTP1B and SOCS3
The Western blot analysis showed a significant increase in the level of PTP1B by approximately $20\%$ in SF smooth muscle cells as compared with the control cells (Figure 4c). In regard to leptin treatment (20 ng), this did not affect the content of PTP1B in either the control cells or the SF cells. Concerning SOCS3 levels (Figure 4b), a significant difference between C and SF smooth muscle cells was observed. When cells were incubated with leptin, a moderate increase of SOCS3 was observed in both C cells but no effect was observed in the SF cells.
The Western blot analysis of STAT3 phosphorylation shows an increase in the content of phosphorylated STAT3 in cells from SF animals and did not depend on leptin treatment. With regard to total STAT3 content, no significant difference was observed between C and SF cells, nor with the leptin-treated cells (Figure 5).
## 4.7. Effect of Leptin on Catalase and SOD Contents and Activities
The effect of sucrose feeding and leptin treatment of SMCs on CAT and SOD content and activities involved in H2O2 degradation and O2•− to H2O2 dismutation, respectively, were also assessed by native polyacrylamide gel staining. Figure 6a and the corresponding native gel show a significant increase in CAT activity in SF cells compared with the control cells, and leptin did not significantly affect CAT activity in either the SF cells or control cells. Regarding CAT content, Western blot showed no difference between control and SF aortic SMCs or after leptin treatment (Figure 6b). Similarly, Cu/Zn-SOD activity was significantly increased by $50\%$ in SF smooth muscle cells compared with C cells and leptin treatment did not affect this activity (Figure 6c).
The Western blot analysis of Cu/Zn-SOD showed no difference in the protein content of this enzyme between the SF and control cells (Figure 6d), and leptin treatment did not affect its expression in the SMCs of both groups of animals. In the presence of leptin, the protein content showed no change in the cells compared to untreated cells (Figure 6d). For Mn-SOD, which is specific to mitochondria, a native polyacrylamide gel staining analysis showed no difference between the C and SF cells and leptin treatment decreased the activity of the enzyme in both C and SF cells (Figure 6e), whereas the amount of protein did not change either between C and SF cells or under leptin treatment (Figure 6f).
## 5. Discussion
This work was undertaken to investigate the ability of leptin to induce in vitro ROS generation in SMCs obtained from the aortic tissue of SF and C rats, and also to show that in vitro research using a primary culture of SMCs, may closely mimic the in vivo response of SMCs to hyperleptinemia-induced ROS generation. Sucrose feeding induces hyperleptinemia, oxidative stress markers and changes in several clinical parameters such as blood pressure, intra-abdominal obesity and hypertriglyceridemia which reflect several characteristics of the clinical diagnosis observed in patients with obesity and metabolic syndrome. Therefore, these findings make the animal model of sucrose feeding useful to investigate the smooth muscle cell ROS generation and oxidative stress as a mechanistic link between obesity and the development of cardiovascular diseases, even though there was no weight gain in the sucrose feeding model. In a previous work, we described how the lack of weight difference between the control and SF groups is attributable to the lack of difference in their energy intake. Indeed, SF rats ingested less solid food than the control animals [39]. Body composition was not examined in detail in this study, and we do not know whether sucrose administration caused an increase in adipose tissue content at the expense of other tissues. The SF rats consumed approximately half the amount of food consumed by animals that were not given sucrose; consequently, the availability of nutrients from the solid food was lower as described previously [39]. Thus, the lower energy intake of the SF rats was compensated by the additional calories from the sucrose solution.
The in vitro increase in ROS generation in a primary culture of SF rats’ SMCs can be attributed to enhanced Nox expression or activity induced by a sucrose-rich diet during the animal treatment period. Nox is a multiprotein complex composed of different subunits. Among them, the p22phox subunit, one of the most important subunits because of its catalytic site, generates O2•− and gp91phox, which are required for Nox complex assembly and activity in cell membrane: hence an increase of the subunit levels in SF smooth muscle cells is related to the increased O2•− generation. In the SF rat model, enhanced SMC ROS generation and oxidative stress markers may be considered as a consequence of obesity, and metabolic alterations induced Nox activity and expression as described previously [25]. However, it was reported that the overexpression of p22phox, a subunit of Nox, in vascular SMCs in mice, increased vascular ROS production, caused obesity and increased fat mass [40]. This observation allows us to speculate that increased ROS generation in SMCs may contribute to the development of obesity with hyperleptinemia and a possible leptin resistance in our SF experimental model. Indeed, chronic exposure of vascular tissue to high levels of circulating leptin can induce leptin resistance in SF rats, as described elsewhere [41,42]. In SMCs from SF animals, the low response to leptin-induced ROS generation of the Nox subunits p22phox and gp91phox levels as compared with control SMCs suggests leptin resistance in the cell. When 20 ng/mL leptin was added to control cells, FI increased by $225\%$ and only by $28\%$ in SF aorta cells. In addition, leptin-induced ROS generation through Nox activity was evidenced by treating SF and control SMCs with both DPI and apocynin, widely used in the literature to elucidate the involvement of Nox in different biological systems. The involvement of Nox in ROS generation in SMCs can be attributed to the interaction with leptin and its receptor Lep-R as described in endothelial cells 42 [40]. In phagocytic cells, Lep-R was described to be coupled to Nox activity involved in ROS generation [43]. Evidence for the direct involvement of the leptin receptor in ROS generation will be further investigated in our laboratory. However, the result of the Western blot analysis shows that the level of Lep-R in SF does not differ from that in the control SMCs, suggesting an equal involvement of the leptin receptor in both cell types. Lep-R signaling initiated by the interaction of leptin with its receptor, leads to phosphorylation of the tyrosine residue of the receptor by activation of Jak 2. This mediates different signals, such as phosphorylation of STAT3, which activates transcription of the SOCS3 gene. After long-term stimulation, the SOCS3-translated protein binds to the phosphorylated Tyr of Lep-R and thus inhibits Lep-R-mediated signals [44].
In this study, the increased SOCS3 and PTP1B level in SMCs from SF is related to an increase of STAT3 phosphorylation, suggesting an alteration in leptin signaling in SF smooth muscle cells in response to leptin-induced ROS generation. Indeed, the over expression of the constitutively active form of STAT3 (phospho-STAT3) translocates to the nucleus and activates the SOCS3 which results in leptin resistance and fat accumulation in mice [45]. Our findings suggest that sucrose feeding induces phosphorylated STAT3 and SOCS3 as a leptin-inducible inhibitor of leptin signaling and blocks leptin-induced signal transduction in SMCs.
Hence, hyperleptinemia and high FFA from increasing the STAT3 phosphorylation in SMCs impairs the leptin signaling pathways during the development of diet-induced obesity, which is associated with disorders of energy homeostasis due to diet-induced obesity [46,47]. Therefore, excessive SOCS3 activity is considered as a potential mechanism for the leptin resistance that characterizes human obesity. Other intracellular proteins such as PTP1B provide a negative feedback regulatory mechanism to prevent over-activation of Lep-R pathways. In db/db mice, a model of diabetes, the deletion of PTP1B was found to improve leptin resistance and reduce superoxide generation [48]. In addition, leptin receptor-deficient ob/ob and db/db mice develop cardiovascular and vascular dysfunction [49]. These leptin and leptin receptor-deficient rodent models have provided many useful insights into the underlying molecular and pathophysiological mechanisms of metabolic and cardiovascular diseases associated with obesity and type 2 diabetes. For example, it has been described that animals deficient in leptin receptors show elevated triglyceride levels and lipid accumulation in the myocardium, which may promote lipotoxicity and directly impacts cardiac contractility [50].
The balance between ROS generation and the antioxidant system to maintain ROS at physiological levels contributes to the normal endothelial function and smooth muscle cell contraction in the vascular system. A loss of this balance results in the uncontrolled production of ROS leading to the development of cardiovascular diseases [51]. Under conditions of oxidative stress induced by high ROS generation, the increased expression of antioxidant enzymes has been described in skeletal muscle [52]. The increased ROS generation in SF smooth muscle cells can also be due to the increased dismutation of superoxide anion to H2O2 by increased activities of Cu/Zn-SOD and Mn-SOD in both cytosol and mitochondria, respectively. This increase in the activities of Cu/Zn-SOD, Mn-SOD and catalase in SMCs from SF rats, can also be considered as a protection against excessive superoxide anion and H2O2 generation. However, the endogenous oxidant H2O2, depending on the concentration, can be considered of central importance in redox signaling to modulate cellular redox status including enzyme activities. At elevated concentrations, ROS can directly modulate the activity of SOD by a reaction with the catalytic site and some amino acid residues, inducing changes in protein conformation and antioxidant activity. In the control aortic SMCs, the leptin-reduced effect of Mn-SOD activity can be indirectly related to its ROS-inducing effect via activation of NADPH oxidase and mitochondria [53,54]. To our current knowledge, there is no data about the direct effect of leptin on the activity of antioxidant enzymes (catalase, Cu/Zn SOD and Mn-SOD). Therefore, further studies are needed to elucidate the mechanism by which leptin modulates the antioxidants’ enzyme activity in SMCs from both the control and SF animals.
What is known to date is that vascular hypertrophy was blunted in SOD1−/− mice compared to WT mice [55] and that Cu/Zn-SOD contributes to visceral fat accumulation by causing insulin secretion and insulin resistance by a mechanism that involves ATP production in mitochondria [56]. In regard to catalase, its overexpression was also described to inhibit SMC proliferation by reducing the content of endogenous and exogenous H2O2 [57]. Hydrogen peroxide has been described as acting as a second messenger by modulating the activity of kinases and phosphatases in several signaling pathways to induce cell proliferation, differentiation and migration involved in the progress of vascular disease [58,59]. In addition, apocynin reduces superoxide anion generation via Nox inhibition as described previously [36].
In summary, our results indicate that SF rats with hyperleptinemia and high fat accumulation, the coexistence of which is a marker of leptin resistance, and increased leptin protein signaling may partly explain the differential effect of leptin-induced ROS generation through Nox activities in SF and C smooth muscle cells.
Taken together, these models have been widely used for various purposes, and future research will address in detail the molecular basis and the pathophysiological manifestations of these models as well as how they compare with human T2DM disease states.
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|
---
title: Simple and Powerful PCG Classification Method Based on Selection and Transfer
Learning for Precision Medicine Application
authors:
- Ahmed Barnawi
- Mehrez Boulares
- Rim Somai
journal: Bioengineering
year: 2023
pmcid: PMC10045405
doi: 10.3390/bioengineering10030294
license: CC BY 4.0
---
# Simple and Powerful PCG Classification Method Based on Selection and Transfer Learning for Precision Medicine Application
## Abstract
The World Health Organization (WHO) highlights that cardiovascular diseases (CVDs) are one of the leading causes of death globally, with an estimated rise to over 23.6 million deaths by 2030. This alarming trend can be attributed to our unhealthy lifestyles and lack of attention towards early CVD diagnosis. Traditional cardiac auscultation, where a highly qualified cardiologist listens to the heart sounds, is a crucial diagnostic method, but not always feasible or affordable. Therefore, developing accessible and user-friendly CVD recognition solutions can encourage individuals to integrate regular heart screenings into their routine. Although many automatic CVD screening methods have been proposed, most of them rely on complex prepocessing steps and heart cycle segmentation processes. In this work, we introduce a simple and efficient approach for recognizing normal and abnormal PCG signals using Physionet data. We employ data selection techniques such as kernel density estimation (KDE) for signal duration extraction, signal-to-noise Ratio (SNR), and GMM clustering to improve the performance of 17 pretrained Keras CNN models. Our results indicate that using KDE to select the appropriate signal duration and fine-tuning the VGG19 model results in excellent classification performance with an overall accuracy of 0.97, sensitivity of 0.946, precision of 0.944, and specificity of 0.946.
## 1. Introduction
The World Health Organization (WHO) report [1] states that cardiovascular diseases (CVDs) are a leading cause of death, with 17.3 million deaths annually and an estimate of over 23.6 million deaths by 2030. Early and accurate CVD diagnosis can save lives by reducing the risk of heart failure [2]. One effective method for diagnosing CVDs is acoustic or PhonoCardioGram (PCG) pattern classification. This method recognizes abnormal blood flow sounds from heart valve dysfunction using acoustic signals. However, obtaining accurate results from classical CVD auscultation requires a highly skilled cardiologist. Screenings performed by primary care physicians or medical students have only $40\%$ accuracy [3,4] and even experienced cardiologists have a screening accuracy of only $80\%$ [3,5].
The neglect of regular heart screenings, due to unhealthy lifestyle habits, exacerbates the issue of CVDs. Making accessible and accurate CVD recognition solutions would encourage individuals to integrate regular heart screenings into their daily routine. Many studies have been conducted to diagnose CVDs using PCG signals, with a focus on improving classification results. However, these studies often rely on complex preprocessing steps, optimized heart cycle segmentation, and combined classifier techniques applied to private or modified public PCG datasets. There is no objective comparative benchmark reference for future PCG-based CVD classification.
This paper addresses these issues by presenting a new CVD classification benchmark dedicated to the PCG Physionet dataset and a simple classification architecture based on PCG signal selection with CNN fine-tuning and transfer learning techniques.
The prepocessing of the acoustic signal prior to feeding it into a convolutional neural network (CNN) for classification can significantly impact the accuracy of the results. However, it is important to note that filtering may also remove essential information required by the CNN for proper classification, leading to a reduction in the signal’s dynamic range and obscuring critical spectral features necessary for class differentiation. Our approach leverages strategies that avoid harmful filtering while still improving performance. By carefully selecting the training samples based on sample length and/or signal-to-noise ratio in the prepocessing phase, we have demonstrated the ability to significantly enhance the accuracy of the classification results.
The paper is organized as follows. In Section 2, we present some related work. In Section 3, we introduce the dataset setting and the different data selection methods. In Section 4, we present our classification model. In Section 5, experimental results are presented. In Section 6, we conclude the paper and indicate future and related research directions.
## Contributions
Our research focuses on the classification of normal and abnormal PhonoCardioGram (PCG) signals from the Physionet dataset using Convolutional Neural Network (CNN) technology. Our work presents two main contributions:Development of a common benchmark for Physionet PCG dataset based on CNN transfer learning and fine-tuning techniques. This includes the presentation of classification results such as accuracy, sensitivity, specificity, and precision based on raw Physionet data. Proposal of a simple and effective classification architecture without any prepocessing steps. Our approach is based on a simple PCG data selection technique to improve the normal and abnormal Physionet signal classification results using CNN technology.
## 2. Related Works
Automatic classification of Cardiovascular Diseases (CVDs) is considered a challenging task due to the difficulty in acquiring a large labeled PCG dataset that covers the majority of CVDs. Despite these difficulties, numerous studies have been conducted in recent years. One such study by Grzegorczyk et al. [ 6] used a hidden Markov model for automatic PCG segmentation and neural networks for PCG signal training. The authors tested their approach on the Physionet dataset [7] and applied pretreatment to eliminate abnormal PCG records. They achieved a classification result with a specificity of 0.76 and a sensitivity of 0.81.
The study by Nouraei et al. in [8] examined the effect of unsupervised clustering strategies, including hierarchical clustering, K-prototype, and partitioning around medoids (PAM), on identifying distinct clusters in patients with Heart failure with preserved ejection (HFpEF) using a mixed dataset of patients. Through the examination of subsets of patients with HFpEF with different long-term outcomes or mortality, they were able to obtain six distinct results.
In [9], the authors conducted a comprehensive review of the relationship between artificial intelligence and COVID-19, citing various COVID-19 detection methods, diagnostic technologies, and surveillance approaches such as fractional multichannel exponent moments (FrMEMs) to extract features from X-ray images [10] and potential neutralizing antibodies discovered for the COVID-19 virus [11]. They also discussed the use of multilayer perceptron, linear regression, and vector autoregression to understand the spread of the virus across the country [12].
Similarly, Chintalapudi et al. in [13] investigated the importance of utilizing machine learning techniques such as cascaded neural network models, recurrent neural networks (RNN), multilayer perception (MLP), and long short-term memory (LSTM) in the correct diagnosis of Parkinson’s disease (PD).
We can also cite the work of [14] who proposed a public challenge based on the Physionet PCG dataset to improve the recognition score, which was initially 0.71 (sensitivity = 0.65, specificity = 0.76). During the competition, 48 teams submitted 348 open source entries and the highest score achieved was 0.86 (sensitivity = 0.94, specificity = 0.78). In the work of [15], the authors proposed a CVD classification technique using the Physionet dataset, which consisted of only 400 heart sound recordings. They relied on the time and frequency domain transformation of the phonocardiogram signal and used a logistic regression hidden semi-Markov model for PCG segmentation. For the classification task, they used and compared three different classifiers: support vector machines, convolutional neural network, and random forest.
In the study of [16], the authors proposed a classification method for cardiovascular diseases (CVD) using deep convolutional neural networks (CNNs) and time/frequency representations of the signals. In the work of [17], the authors used AdaBoost and CNNs to classify normal and abnormal PCG signals from the Physionet dataset. They achieved a sensitivity, specificity, and overall score of 0.9424, 0.7781, and 0.8602 respectively. In [18], the authors proposed a CVD classification based on preprocessing, feature extraction, and training with the Physionet dataset. They used neural networks to classify normal and abnormal signals and obtained a sensitivity of 0.812 and a specificity of 0.860 with an overall accuracy of 0.836.
The study in [19] used the Physionet dataset to perform anomaly detection using signal-to-noise ratio (SNR) and 1D Convolutional Neural Networks. In [20], the researchers presented a heart sound classification technique using multidomain features instead of heartbeat segmentation. They achieved an accuracy of $92.47\%$ with improved sensitivity of $94.08\%$ and specificity of $91.95\%$. The researchers in [20] used a Butterworth bandpass filter and a pretrained CNN model for CVD classification. In [21], the authors used deep neural network architectures and one-dimensional convolutional neural networks (1D-CNN) with a feed-forward neural network (F-NN) to classify normal and abnormal PCG signals from the Physionet dataset.
In the work of [22], the authors used Logistic Regression-Hsmm for PCG segmentation and feature extraction for CVD classification of normal and abnormal PCG signals from the Physionet dataset. They obtained an accuracy of $79\%$. In the study of [23], the authors used a pretrained CNN model (AlexNet) and achieved $87\%$ recognition accuracy. The study in [24] aimed to use a nonlinear autoregressive network of exogenous inputs (NARX) for normal/abnormal classification of PCG signals from Physionet. In [25], the authors proposed a deep CNNs framework for heart acoustic classification using short segments of individual heartbeats. They used a 1D-CNN to learn features from raw heartbeats and a 2D-CNN to take inputs from two-dimensional time-frequency features.
## 3. Dataset
In this section, two different PCG datasets are presented. First, the raw Physionet dataset without any data selection process is described. Then, three different data selection methods applied on the original dataset are presented. The goal is to experiment with the impact of selection on the classification results.
## 3.1. Raw Dataset
The publicly available Physionet dataset [14] is a not balanced PCG dataset which contains 665 normal sample and 2575 abnormal sample in WAV format. As shown in Figure 1, the majority of PCG samples are concentrated in the duration range between 8 and 40 s for normal and abnormal class.
If we look at Figure 2, we can deduce that for abnormal class, the highest density of PCG samples is defined at duration 35 s. Concerning the normal class, we can also deduce that the largest concentration of PCG samples are in signal duration 20 s.
Concerning the signal-to-noise ratio (SNR) sample distribution in the function of density (as seen in Figure 3), we can deduce that the highest KDE value of SNR for normal and abnormal classes is zero. This means that the majority of Physionet PCG samples are approximately clean with an acceptable noise signal.
In the same manner, if we look at the Figure 4, it is visually clear that the highest concentration of PCG sample distribution related to normal and abnormal classes in function of SNR is approximately zero.
## 3.2. PCG Data Selection
Based on the different results issued in the previous subsection, in this subsection, we present three main data selection process: data selection based on KDE for optimal signal duration determination, data selection based on optimal SNR, and data selection based on clustering. Notice that we will experiment the impact of these three data selection process on the classification results in the experimentation section.
## 3.2.1. Data Selection Based on Kernel Density Estimation for Optimal Signal Duration Determination
Kernel density estimation (KDE) [26] is a non-parametric method for estimating the probability density function of a random variable. Given a set of points Xi with $i = 1...$n in a d dimension space Rd, the kernel multivariate density estimation is obtained with a kernel K(x) and with window width h as following:[1]f^(x)=1nhd∑$i = 1$nK|Xi−x|h With K(u): is a kernel function (using a Gaussian kernel (Formula [2]). The estimator f^(x) determines the percentage of observations closest to a given x. If there are several observations close to x then f^(x) widens. Conversely, if there are only a few Xi close to x then f^(x) remains weak. In other words, the h parameter of the Equation [1], determines the degree of smoothing of the KDE function. [ 2]k(u)=e−u22σ2 Based on the discovery issued from the KDE curve shown in Figure 2, the idea is to select all the PCG samples for normal classes with signal duration equal to 20 s and 35 s for abnormal class. As seen in Figure 5, after applying this simple selection process, we obtain 238 PCG samples from abnormal class and 1291 PCG samples from normal class. If we look at the Figure 6 and Figure 7, the obtained PCG samples after the KDE duration selection process for normal and abnormal classes have acceptable SNR values with a high SNR concentration, very close to zero.
## 3.2.2. Data Selection Based on Optimal SNR
Signal-to-noise ratio (SNR) is defined as the ratio of signal power to the background noise power [27]. Based on the analysis of Figure 3 and Figure 4, which show the highest concentration of SNR related to PCG samples for both normal and abnormal classes, we decided to select PCG samples with SNR greater than or equal to zero. As a result of this selection process, we obtained 221 PCG samples for the abnormal class and 822 PCG samples for the normal class, as shown in Figure 8. Additionally, Figure 9, Figure 10 and Figure 11 provide an overview of the PCG sample distribution in terms of duration after the data selection process with SNR greater than or equal to 0, the KDE curve of PCG samples related to normal and abnormal classes in terms of duration after the SNR greater than or equal to zero in the data selection process, and the PCG sample distribution of normal and abnormal classes in terms of SNR greater than or equal to zero.
## 3.2.3. Data Selection Based on Clustering
In this part, we chose to use biclustering as our data selection process. The main idea behind biclustering data selection is to suppose that the highest dense cluster constitutes our useful PCG data. In other words, we discard the remaining noise cluster and we preserve only the PCG samples belonging to the big cluster.
For this aim, we have chosen the mixture Gaussian model (GMM) [28] which is a parametric unsupervised clustering model. This model is used for data partitioning into several groups according to the probabilities of belonging and association to each Gaussian characteristics. GMM is based on a mixture of Gaussian models relying on learning the laws of probability that generated the observation data xn (see Equation [3]). [ 3]f(xn|θk)=∑$k = 1$MπkN(xn|μk,σk2) N(xn|μk,σk2)=1(2π)d/2σ$\frac{1}{2}$e(−12σk2(xn−μk)2), πk∈1..M is the probability of belonging to a Gaussian k; k∈1..M), μk∈1..M is the set of the M Gaussian averages, σk2∈1..M the set of covariances matrices, and θk=πk,μk,σk2. Similarly, the multidimensional version of the *Gaussian is* as follows: N(xn|μk,Σk)=1(2π)d/2Σ$\frac{1}{2}$e−12(xn−μk)T−Σk−1(xn−μk). The best-known method for estimating the GMM parameters (πk,μk and σk2), is the iterative method of maximum likelihood calculation (expectation-maximization algorithm or EM [29]). The EM algorithm could be defined through 3 steps:-Step 1: Parameter initialization θk:πk,μk,σk2-Step 2: Repeat until convergence The time complexity of EM algorithm for GMM parameters estimation [28,29,30,31] is as following: If X: is the dataset size, M: the Gaussian number, and D: the dataset dimension.
EM estimation step O(XMD+XM).
EM maximization step O(2XMD).
As seen in Figure 12, the result of the selection process based on the highest dense cluster issued from GMM biclustering gives us a 334 PCG sample for the abnormal class and a 1626 PCG sample for the abnormal class. The KDE curve in the function of duration and SNR related to normal and abnormal PCG samples is shown, respectively, in Figure 13 and Figure 14. Furthermore, Figure 15 gives us an overview of the KDE curve in function of SNR for normal and abnormal PCG classes after the GMM data selection process.
## 4. The Process of Our CNN Benchmark
In this paper, we present a CNN classification system based on transfer learning and fine-tuning. Our system starts with the Physionet dataset, which we use to train the model. Figure 16 shows the architecture of our system, which is built on pretrained CNN models from ImageNet dataset. The first step involves transforming the wav PCG signals into mel spectrogram images using an FFT window of 1024 and a sample rate of 44,100. The second step defines the CNN parameters, including a two-class recognition, an input image size of width = 640 and height = 480, a batch size of 5, 30 epochs, and stochastic gradient descent as the optimizer with a learning rate of 0.0001. In the third step, we fine-tune the layers by using convolutional layers from the pretrained CNN models as feature extraction layers. Additionally, we add six layers including a GlobalAveragePooling2D layer for averaging and better representation of our training vector, three dense layers for the full connected network, a BatchNormalization layer to limit covariate shift, and a dense layer with a sigmoid activation function to obtain a classification value between 0 and 1 (probability).
## 4.1. Mel Spectrogram Representation
The fast Fourier transform is a powerful method to decompose acoustic signal amplitude over time into a multifrequency non periodic signal. However, if we need to represent the spectrum of these frequencies in function of time, we need to perform FFT over several windowed partitioned segments of the input signal. In fact, inspired by measured responses from the human auditory system, studies [32,33,34,35] have shown that humans perception does not perceive the frequencies on a linear scale. For this reason, a dedicated unit to transform frequencies was proposed by Stevens, Volkmann, and Newmann in 1937. This is called the mel scale, which performs mathematical operation on frequencies to convert them to mel scale. In order to obtain the mel spectrogram, we perform the following steps (as seen in Figure 17:Specify the signal into short frames. Windowing in order to reduce spectral leakage. Work out the discrete Fourier transformation. Applying filter banks. Applying the log of the spectrogram values to obtain the log filter-bank energies. Applying discrete cosine transform to decorrelate the filter bank coefficients.
In this work, we have chosen MFCC signal by converting the output features into a png image, which will be applied to the CNN classifier. Figure 18 gives an overview of a normal and abnormal MFCC representation of the input PCG signal.
## 4.2. CNN Models
Recently, deep learning and more especially convolutional neural network (CNN) has trended as an image analysis and classification tool. In fact, many research has [36,37,38,39] have been conducted using CNN to propose neural network models that enable powerful image classification results. Moreover, it is known that CNNs can perform high-level feature extraction while tolerating image distortion conditions and illumination changes, and can provide invariance of image translation. For these reasons, we chose to adopt CNN as our PCG image trainer and classifier.
In fact, in 1998 LeCun [40] introduced the first CNN architecture, designed to recognize handwritten characters. Since the last decade, due to their satisfactory results in computer vision tasks such as face detection [41,42,43], handwritten recognition [44,45,46], and image classification [47,48,49], CNNs are the most-used technology for classifying images. However, in order to design new powerful CNN models, CNN requires large training datasets. Thanks to the knowledge-transfer technique also known as transfer learning appellation [50], it becomes possible to take the advantages of the already trained CNN models on ImageNet by applying some modifications called fine-tuning. Therefore, we can customize these pretrained CNN models in order to be trained on a small dataset without a huge drop in the classification results.
In our work, we used several pretrained CNN models to classify normal/abnormal PCG spectrogram images. Based on the small public dataset PhysioNet, we fine-tuned and trained the 17 pretrained Keras CNN models (see Table 1). We preserved the convolutional layers which will be used for feature extraction then the additional layers are added:GlobalAveragePooling2D layer for averaging and better representation of our training vector. Three dense layers to define our full connected network. BatchNormalization layer to limit covariate shift by normalizing the activations of each layer. Dense layer with sigmoid activation function in order to obtain classification values between 0 and 1 (probability).
Keras CNN models are trained on the following dataset using the Google Colab plateform to allow the use of dedicated GPU facilities: 1×Tesla K80, having 2496 CUDA cores, compute 3.7, 12 GB (11.439 GB Usable) GDDR5 VRAM:Raw PhysioNet dataset. PhysioNet dataset with data selection using KDE for duration extraction. PhysioNet dataset with data selection using optimal SNR.PhysioNet dataset with data selection using GMM biclustering.
## 5. Experiments and Results
The effect of selecting data on the accuracy of the classification is being studied. First, we concentrate on training and classifying CNN models using the raw dataset without any data selection. Next, we train our CNN models on the data that has been selected based on a 20 s duration for normal PCG signals and 35 s for abnormal PCG signals. Finally, we examine the impact of selecting data based on SNR greater than 0 in the third section. It is worth mentioning that all the classification results have been obtained by taking the average of the results from the three-fold cross validation.
## 5.1. Classification Using Raw Dataset
After performing CNN training on the raw Physionet dataset, we can notice that VGG19 gives the best classification results with accuracy = 0.854, sensitivity = 0.860, precision = 0.794, and specificity = 0.860 (as seen in Table 2).
In addition, we can see that the classification results related to InceptionResNetV2 are close VGG19 with accuracy = 0.825, sensitivity = 0.807, precision = 0.748, and specificity = 0.807. Similarly, Figure 19 gives an overview of the validation and training curves related to VGG19 and InceptionResNEtV2. If we look at Figure 20, we can see that, if we consider the training step duration, mobileNet is the fastest CNN model and ResNet101 is the lowest CNN model. On the other hand, we can see that despite the number of layer of VGG19 (best accuracy result) which is 26 (as seen in Table 1) compared to deeper architecture (such as DenseNet201 with 201 layers) VGG19 is slower than DenseNet201 and is ranked as the fourth-slowest CNN model in term of training time.
## Classification Using Kernel Density Estimation as Data Selection
Method for Signal Duration 20 s Normal and 35 s Abnormal
After performing data selection on Physionet through the use of signal duration extraction with 20 s for normal PCG signals and 35 s for abnormal PCG signals, we trained all the 17 pretrained CNN models (see Table 1 and we obtained the classification results presented in Table 3. We can notice that through the use of this simple data selection, we obtained an enhancement of all the classification results compared to those without any data selection. As seen in Table 3, we obtained an improvement of VGG19 accuracy from 0.854 (raw dataset) to 0.970, for sensitivity from 0.860 to 0.946, for precision from 0.794 to 0.944, and for specificity from 0.860 to 0.946. Similarly, Figure 21 gives an overview of the validation and training curves related to VGG19 and VGG16. In addition, as seen in Figure 22, the training phase related to VGG19 becomes faster (fourth position after mobilenet, inceptionV3 and resnet50) than the one without data selection. This means that this data selection method allows us to speed up the training phase related to VGG19. On the other hand, we performed an experimental test in order to argue the choice of 20 s and 35 s signal duration extraction, respectively, for normal and abnormal signals. In this test we chose a random signal duration extraction value equal to 50 s for normal and abnormal signals. The classification results related to this experiment is shown in Table 4. If we compare the classification results presented in Table 3 and Table 4, we can see that for VGG19 (best model), the accuracy decreases from 0.970 to 0.870, sensitivity decreases from 0.946 to 0.851, precision decreases from 0.944 to 0.801, and specificity decreases from 0.946 to 0.851. All these results support the idea behind our duration selection method (explained in data selection based on kernel density estimation for optimal signal duration determination subsection).
## 5.2. Classification Using Data Selection Based on Optimal SNR
The idea behind this data selection method is to select all the PCG signals with a signal-to-noise ratio greater than or equal to 0. In other words, we experiment the impact of selecting signals with SNR ≥ 0 on the classification result without performing any prepocessing steps or denoising methods. After applying this data selection method, we trained all the 17 pretrained CNN models (Figure 23 gives an overview of training and validation curves related to VGG19, VGG16, DenseNet169, and InceptionResNetV2). As seen in Table 5, we obtained very good classification results with VGG19, VGG16, DenseNet169, and InceptionResNetV2. The best result was obtained with VGG19 (accuracy = 0.96, sensitivity = 0.943, precision = 0.94 and specificity = 0.943). This result is very close to the classification result obtained after applying data selection based on signal duration.
In fact, if we look at Figure 24, we notice that the VGG19 training time is at the fifth position compared to the fourth position obtained with VGG19, trained on 20 s and 35 s normal and abnormal PCG signals. In other words, the best results in term of training time and classification results was obtained using VGG19 trained on 20 s and 35 s normal and abnormal PCG signals.
## 5.2.1. Classification Using Clustering as Data Selection Method
In this subsection, we investigate the impact of selecting training data using unsupervised biclustering. We used GMM biclustering with the hypothesis to consider the cluster with the maximum number of sample as our training data. As shown in Table 6 and in Figure 25, we obtained good classification results compared to results without using any data selection method. However, if we compare with the previous results, we can conclude that the best results are obtained using signal selection, based on duration 20 s for normal and 35 s for abnormal PCG data. In this configuration, VGG16 gives the best classification metrics compared to the remaining 16 CNN models with an acceptable training time (sixth position) as seen in Figure 26.
## 5.2.2. Synthesis
We have undergone a general comparative study against the state-of-the-art methods, as summarized in Table 7. As seen in this table, Dominguez et al. [ 60] achieved good classification results (accuracy of 0.97, sensitivity of 0.93, specificity of 0.95) using a complex recognition methodology based on heartbeat segmentation and a modified version of the CNN AlexNet model. Philip et al. [ 61] obtained the worst classification results in Table 7, and this is due to the elimination of the complex heart-cycle segmentation step. The majority of the research work presented in this table employed complex segmentation steps in their classification approach, and they obtained accuracy varying from 0.80 to 0.97, sensitivity from 0.76 to 0.96, and specificity from 0.72 to 0.95. In this work, our main contribution is to obtain very good classification results using a simple classification approach without any complex preprocessing steps, without any segmentation process, and without the use of any new CNN architecture. As seen in Table 7, compared to the work of Dominguez et al. [ 60], we have achieved similar results with an accuracy equal to 0.97, a slightly better sensitivity result of 0.946, and a slightly lower specificity result of 0.946.
## 6. Conclusions and Perspectives
In this work, we presented a simple classification architecture based on a data-selection process designed to recognize normal and abnormal Physionet PCG signals. We compared our work with the state-of-the-art approaches and concluded that using a data selection process based on a signal duration of 20 s for normal and 35 s for abnormal PCG signals obtained very good CNN classification results with an overall accuracy equal to 0.97, an overall sensitivity equal to 0.946, an overall precision equal to 0.944, an overall specificity equal to 0.946. This work was tested only on the most-used binary class dataset Physionet, which can be considered as a limiting factor. We plan to test it on other public or private multiclass datasets. In addition, the feature-selection process can be improved through the exploitation of a large set of ML feature extraction/selection methods. Furthermore, we plan to create our own multiclass PCG dataset which will be trained on a new CNN model created especially for PCG spectrogram images.
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|
---
title: Reference Standard for Digital Infrared Thermography of the Surface Temperature
of the Lower Limbs
authors:
- Ho Yeol Zhang
- Seong Son
- Byung Rhae Yoo
- Tae-Mi Youk
journal: Bioengineering
year: 2023
pmcid: PMC10045408
doi: 10.3390/bioengineering10030283
license: CC BY 4.0
---
# Reference Standard for Digital Infrared Thermography of the Surface Temperature of the Lower Limbs
## Abstract
Digital infrared thermographic imaging (DITI) is a supplementary diagnostic technique to visualize the surface temperature of the human body. However, there is currently no reference standard for the lower limbs for accurate diagnosis. In this study, we performed DITI on the lower limbs of 905 healthy Korean volunteers (411 males and 494 females aged between 20 and 69 years) to obtain reference standard data. Thermography was conducted on the front, back, lateral sides, and sole area, and 188 regions of interest (ROIs) were analyzed. Additionally, subgroup analysis was conducted according to the proximity of ROIs, sex, and age groups. The mean temperatures of ROIs ranged from 24.60 ± 5.06 to 28.75 ± 5.76 °C and the absolute value of the temperature difference between both sides reached up to 1.06 ± 2.75 °C. According to subgroup analysis, the sole area had a significantly lower temperature than any other areas, men had higher temperatures than women, and the elderly had higher temperatures than the young adults except for the 20s age group ($p \leq 0.001$, respectively). This result could be used as a foundation for the establishment of a reference standard for DITI. Practical patient DITI can be accurately interpreted using these data, and it can serve as a basis for further scientific research.
## 1. Introduction
Digital infrared thermographic imaging (DITI) is a technique used to display the body’s surface temperature using thermography [1,2]. DITI has been used as a complementary diagnostic tool in various clinical fields [3,4,5,6,7,8,9]. In several disorders involving the lower limbs, such as lumbar radicular pain, chronic regional pain syndrome, vascular disease, and peripheral nerve entrapment, DITI allows visualization of the affected area as hypo-radiant (hypothermia) or hyper-radiant (hyperthermia) compared to the unaffected area [10,11,12,13,14,15].
In terms of interpreting DITI, the normal range of skin temperature and criteria for hypo-radiant and hyper-radiant are ambiguous. Empirically, the temperature difference between both sides of the lower limbs is significant when it is more than 0.1–0.3 °C, depending on the location of the surface area [1,16,17]. However, a formally approved consensus on the definition of significant difference between both sides, as well as hypo-radiant or hyper-radiant, is still undetermined due to variations in equipment, environment (room temperature and humidity) of the test room, and the ability of the surveyor [5]. Furthermore, despite the consistent examination conditions, the range of normal surface temperature still varies according to baseline characteristics such as sex, age, body mass index, patient condition, and medical history [17].
To overcome these barriers to the definition of abnormality and to establish a correct standard for DITI, a standardized measurement protocol and a reference standard for DITI are necessary. However, there are no studies about reference standard data for DITI of the lower limbs. In this study, we performed DITI on a large group of healthy volunteers using a standardized protocol and provide detailed reference standard data for DITI of the lower extremities.
## 2.1. Trial Design and Ethics
This multi-center, single-arm, open-label trial was conducted for 2 years in accordance with the 1964 Helsinki Declaration and its later amendments. All processes of the study were approved by the Institutional Review Board of three different research centers. Additionally, this research was registered as a clinical trial in the Clinical Research Information Service of the Republic of Korea (number KCT0006880).
## 2.2. Sample Size
The number of samples was calculated as follows: The population proportion (θ) for the exam was set to 0.85 and the margin of error (d) was set to 0.025. Using the above formula with a significance level of $5\%$ and a confidence level of $95\%$, a sample size of 784 was calculated. Considering a dropout rate of $15\%$, a total of 922 participants were necessary.
## 2.3. Subjects
Healthy test subjects were voluntarily recruited through public announcements and tests were conducted at three institutions from March 2018 to December 2020.
To minimize bias related to subject selection and external effect, inclusion criteria were as follows: [1] adults between the ages of 20 and 69; [2] no specific medical history including diabetes mellitus, peripheral neuropathy, spinal stenosis, disc herniation, joint disease of the leg, previous surgery history of the spine and lower limbs, or recent trauma; [3] no definite present pain or skin lesion in the lower limbs; [4] no potential risk of test such as claustrophobia, pregnant, or lactating women; [5] who can maintain a stationary posture for the required amount of time during the test; [6] without any other reason for disqualification according to the judgment of the researchers. Participation was granted when the requirements were met based on the inclusion criteria questionnaire.
A total of 922 healthy Korean volunteers were registered with an even distribution based on sex and age group. DITI was conducted following a standardized protocol and informed consent was obtained in advance from all participants. Among them, 905 participants were evaluated after excluding 17 participants due to measurement failure and/or withdrawal of consent.
## 2.4. Equipment and Examination Protocol
All examinations were conducted in outpatient clinics in three different hospitals. DITI was performed using the Iris-XP Digital infrared imaging system (Medicore, Seoul, Republic of Korea). Volunteers scheduled for DITI were informed about general precautions such as avoiding exposure to cold or hot environments, not smoking, and not consuming caffeine for 1 h before the test [18].
The skin temperature of subjects can be affected by environmental temperature and humidity due to sweating evaporation and vasoconstriction/vasodilation response [19,20,21]. To maintain consistency, we controlled the air temperature and humidity in the test room. Specifically, the room temperature and humidity were maintained at 20.0–23.0 °C and 30–$75\%$, respectively. After undressing completely, the subjects remained in the room for approximately 20 min to acclimate prior to the examination. They were allowed to stand or sit on a chair with a back, depending on their preference.
The measurement reliability of temperature using the DITI equipment was found to be reasonable. The uncertainty of the thermography equipment ranged from 0.000 °C to 0.369 °C, as specified by the Korean Agency for Technology and Standards.
The test was conducted in the front area, back area including buttocks, both lateral-side areas, and the sole area of both feet. A total of 188 regions of interest (ROIs) were manually divided into 15 × 2 ROIs in the front area, 44 × 2 ROIs in both lateral-side areas, 20 × 2 ROIs in the back area, and 15 × 2 ROIs in the sole area (Figure 1). To ensure the accuracy of ROI division and measurement, objective testing and diagraming of pictures based on 188 ROIs of all subjects were performed by five certified surveyors.
## 2.5. Statistical Analysis
A quantitative analysis of data was conducted by a specialized doctor and a statistician who was blinded to participant information.
The analysis was performed using SPSS version 27.0 (IBM Corporation, Armonk, NY, USA). The normal distribution of the data was evaluated using the Kolmogorov–Smirnov test, and all data were reported as mean ± standard deviation or mean with $95\%$ confidence intervals (CI). One-way analysis of variance (ANOVA), linear regression analysis, and paired t-tests were performed according to the characteristics of the values. Statistical significance was accepted at $p \leq 0.05.$
## 3.1. Subjects
The mean age of all participants ($$n = 905$$) was 42.86 ± 12.87 years, and $45.4\%$ of the participants were male ($$n = 411$$). The demographic distribution of volunteers according to age group was as follows: 183 (97 males and 86 females) in their 20s; 213 (108 males and 105 females) in their 30s; 228 (109 males and 119 females) in their 40s; 177 (65 males and 112 females) in their 50s; 104 (32 males and 72 females) in their 60s.
## 3.2. Overall Data: The Mean Temperature and Difference between Both Sides (°C)
The mean temperature of the ROIs of each area and the temperature difference between both sides (ΔT, right—left) were as follows: in the front area, the overall mean temperature was 27.69 ± 5.34 (ranged from 26.73 ± 5.12 (extended uncertainty 10.27) to 28.75 ± 5.76 (extended uncertainty 11.54)) and the overall mean difference was 0.03 ± 0.41 (ranged from −0.09 ± 0.33 to 0.24 ± 0.47); in the back area, the overall mean temperature was 27.70 ± 5.38 (ranged from 25.74 ± 5.09 (extended uncertainty 10.21) to 28.48 ± 5.74 (extended uncertainty 11.50)) and the overall mean difference was −0.04 ± 0.42 (ranged from −0.23 ± 0.59 to 0.20 ± 0.42); in the lateral-side area, the overall mean temperature was 27.18 ± 5.49 (ranged from 25.56 ± 5.19 (extended uncertainty 10.41) to 28.53 ± 5.79 (extended uncertainty 11.60)) and the overall mean difference was −0.58 ± 2.72 (ranged from −1.06 ± 2.75 to −0.09 ± 2.37); in the sole area, the overall mean temperature was 25.74 ± 4.98 (ranged from 24.60 ± 5.06 (extended uncertainty 10.1) to 27.69 ± 5.31 (extended uncertainty 10.65)) and the overall mean difference was −0.09 ± 0.80 (ranged from −0.17 ± 0.74 to 0.06 ± 0.71) (Table 1, Table 2, Table 3 and Table 4).
According to the location of the ROIs, the mean temperature of the ROIs was significantly different between the four areas ($p \leq 0.001$, ANOVA). In particular, the temperature of the sole area was significantly lower than that of any other areas; the difference between the sole and other areas was 1.93 ($95\%$ CI, 1.53–2.33), 1.95 ($95\%$ CI, 1.57–2.32), and 1.41 ($95\%$ CI, 1.08–1.74), respectively ($p \leq 0.001$, ANOVA post hoc analysis) (Figure 2).
Moreover, the absolute value of the temperature difference between both sides (|ΔT|) was also significantly different between the four areas ($p \leq 0.001$, ANOVA). In particular, the |ΔT| of the lateral-side area was 0.58 ± 2.72 °C ($95\%$ CI, 0.40–0.76), which was significantly larger compared to any other area; the mean difference of |ΔT| between lateral-side and other areas was 0.50 ($95\%$ CI, 0.38–0.63), 0.48 ($95\%$ CI, 0.37–0.60), and 0.48 ($95\%$ CI, 0.36–0.60), respectively ($p \leq 0.001$, ANOVA post hoc analysis) (Figure 3).
## 3.3. Subgroup Analysis of the Temperature (°C) According to Proximity of ROIs
The temperature tended to drop from the proximal to the distal part in only the lateral-side area ($$p \leq 0.001$$, regression analysis), not in the front or back areas (Figure 4).
In terms of |ΔT| according to the proximity of ROIs, the |ΔT| tended to increase from the proximal to the distal part in only the front area ($$p \leq 0.047$$, regression analysis), not in the back or lateral-side areas (Figure 5).
## 3.4. Subgroup Analysis of the Temperature (°C) According to Sex
The mean temperature of each area depending on the sex was as follows: in the front area, the mean temperature was 28.83 ± 5.15 (ranged from 27.10 ± 5.16 to 32.02 ± 4.85) in males and 26.54 ± 5.53 (ranged from 24.03 ± 5.16 to 29.32 ± 5.66) in females; in the back area, the mean temperature was 28.90 ± 5.18 (ranged from 25.99 ± 5.05 to 31.84 ± 4.65) in males and 26.50 ± 5.61 (ranged from 22.86 ± 4.86 to 28.74 ± 5.59) in females; in the lateral-side area, the mean temperature was 27.99 ± 5.45 (ranged from 25.32 ± 5.25 to 32.15 ± 4.71 in males and 26.29 ± 5.55 (ranged from 22.89 ± 4.95 to 29.02 ± 5.58) in females; in the sole area, the mean temperature was 26.59 ± 4.87 (ranged from 25.32 ± 5.08 to 30.36 ± 5.03) in males and 24.85 ± 5.03 (ranged from 22.19 ± 4.69 to 28.21 ± 5.40) in females; and in all areas, the mean temperature was 28.08 ± 5.16 in males and 26.05 ± 5.43 in females (Table 1).
In terms of trends according to sex, the mean surface temperature in the same ROIs was higher in males than in females in all areas of all age groups ($p \leq 0.001$, paired t-test), although the mean differences varied depending on the areas and age groups. The males’ surface temperatures were at least 0.52 ($95\%$ CI, 0.09–0.94) and at most 3.42 ($95\%$ CI, 3.19–3.65) higher than that of females (Table 5 and Figure 6).
## 3.5. Subgroup Analysis of the Temperature (°C) According to Age Group
The mean temperature of each area depending on the age group was as follows: in the 20s age group, the mean temperature was 27.34 ± 5.17 (ranged from 24.14 ± 4.69 to 29.33 ± 5.21); in the 30s age group, the mean temperature was 25.82 ± 5.37 (ranged from 22.19 ± 4.69 to 28.95 ± 5.74); in the 40s age group, the mean temperature was 26.21 ± 5.71 (ranged from 23.74 ± 5.30 to 30.00 ± 5.43); in the 50s age group, the mean temperature was 27.65 ± 5.11 (ranged from 24.67 ± 5.16 to 30.84 ± 4.95); in the 60s age group, the mean temperature was 28.20 ± 5.29 (ranged from 25.06 ± 5.34 to 32.15 ± 4.85) (Table 5).
In terms of trends according to age group, the surface temperature increased as age increased, except for the 20s age group, in all areas ($p \leq 0.001$, ANOVA). Among all age groups, the 30s age group of both sexes showed the lowest temperature in all areas ($p \leq 0.001$, ANOVA post hoc analysis) (Table 5 and Figure 7).
## 4.1. The Mean Temperature and Difference between Both Sides
The surface temperature of the lower limb was difficult to define as a single numerical average because the mean temperature of ROIs was significantly different between the areas and location of ROIs (ranging from 24.60 ± 5.06 °C to 28.75 ± 5.76 °C). Notably, the temperature of the sole area was significantly lower than that of other areas. This finding supports the previous suggestion that distal skin regions, including feet and hands, are hypo-radiant areas because they are further away from the body’s main thermal cores, such as the great vessels and viscera [22,23].
In previous clinical studies, the normal range of |ΔT| was limited to 0.2 °C, although it varied depending on the region [10,15,17]. According to the present study, |ΔT| was within 0.2 °C, as suggested previously in almost all ROIs except in the lateral-side area. In the lateral-side area, |ΔT| was higher than 0.2 °C at 0.58 ± 2.72 °C ($95\%$ CI, 0.40–0.76). The reason for this variability requires further study, and careful interpretation should be taken when evaluating |ΔT| in the lateral-side area.
The results of this study, which include mean temperature and mean ΔT of each ROI from a large sample, can serve as a reference standard in DITI. Based on this reference standard, objective hypo-radiant/hyper-radiant and clinical significance of ΔT can be determined by comparing the practical DITI results with this reference data. However, it may be difficult to subdivide the ROIs in practical clinics as was done in this study. In such cases, abbreviations for representative RIOs can be used and analyzed. It is important to compare values in each ROI of each area, rather than relying on simple overall averages. Additionally, because various individual characteristics, such as sex, age, medical condition, body composition, and circadian rhythm, can affect the skin temperature [24,25,26,27], normal values for an individual may fall outside the range of reference standards from this study. Therefore, further research is needed to assess the sensitivity and specificity of this reference standard by applying it to actual patients in the future.
## 4.2. Subgroup Analysis
We investigated subgroup analysis, including the trend of surface temperature according to the proximity of ROIs, sex, and age groups, to verify existing claims and controversies related to surface temperature. A previous suggestion that the surface temperature decreases and |ΔT| increases from the proximal to the distal part was limited to only certain areas. Additionally, it was confirmed that men have significantly higher surface temperatures than women in all areas and in all age groups. In terms of the trend of surface temperature related to age, a complex phenomenon that the temperature increased with age except for the 20s age group concluded several existing controversies.
This study’s findings that the surface temperature in the lateral-side area decreases from the proximal to the distal part and that the temperature of the sole is the lowest among the four areas are consistent with existing hypotheses. Previous studies suggested that the body temperature would drop from the proximal part to the distal part of the body [6]. We speculate that the reason for this phenomenon is that the bloodstream temperature of the proximal part is warmer than that of the distal part. However, in the front and back areas, this hypothesis does not apply and is, therefore, still controversial.
Based on the results of this study, |ΔT| increased toward the distal part in the front area only, but not in other areas. Furthermore, |ΔT| was within 0.2 °C in the sole area and it was measured as higher than 0.2 in the lateral-side area. In contrast, some authors have suggested that |ΔT| increases toward the distal part of the body and that the normal range of |ΔT| can be larger than 0.2 °C in the periphery [10,17]. As a result, previous findings are controversial, and it is necessary to be careful about the interpretation of the significance of |ΔT| depending on the area.
According to this study, there was a significant trend that the surface temperature of females was lower than that of males in all areas of lower limbs. The influence of sex on surface temperature has been a subject of controversy. Some studies have reported that sex differences were significant for only certain ROIs, while others have suggested that women have lower skin temperatures [24]. This study concludes the previous controversy in this regard. A possible explanation is that the higher level of subcutaneous adipose tissue in women is associated with decreased surface temperature [28]. Greater subcutaneous fat in females may provide a significant insulating layer that blunts heat transfer from the core of the body or major blood vessels [29].
In terms of the relationship between surface temperature and aging, there has been controversy. Several studies have identified lower surface temperatures in the elderly and suggested that elderly individuals may have a lower skin temperature due to the association of aging with the loss of muscle mass, which reduces metabolism and limits heat generation [30,31,32]. In contrast, other studies have found that the elderly tend to have similar or higher skin temperature than young people and insisted that the blood flow of the human skin is controlled by the sympathetic nervous system innervation, which is mainly affected by the aging process [33,34,35].
According to the present study, the trend of surface temperature across age groups revealed a complicated pattern. Specifically, although the surface temperature tended to increase with age, the surface temperature in the 20s age group was paradoxically higher than that in the 30s age group. Consequently, individuals in their 30s showed the lowest temperature compared to all other age groups in both sexes. This trend may suggest that body surface temperature can vary according to age, even within the same individual.
Aging is related to the alteration of the cutaneous vasodilation and vasoconstriction reflexes that modify peripheral circulation [3]. In other words, older adults have a higher skin temperature due to increased blood flow in the skin caused by a deficit in the venous return [36,37]. On the other hand, the higher metabolic rate of the muscle tissue and active reproductive organs with higher blood supply could have a positive influence on the higher surface temperature of young adults, especially the 20s age group [30,31]. We presume that the 30s age group has a paradoxical heat loss (heat redistribution) in the subcutaneous or skin layer, although they also have a high core temperature. Abundant subcutaneous fat in the 30s age group compared to the 20s age group could lower skin temperature by blocking heat transfer from the core of the body or major blood vessels [29]. In summary, we assume that the trend of body surface temperature according to age reveals a complicated pattern due to complex physiological phenomena related to heat generation and heat redistribution according to the aging process.
## 4.3. Limitations
This study has some limitations regarding various intrinsic or extrinsic factors that can influence surface temperature [38,39]. Firstly, the environment of the subjects was not entirely controlled during the DITI exam. All physiological and psychological factors, such as time of the test, circadian rhythm, menstrual cycle, menopause, emotional stress, and season, that can affect autonomic function, were neither controlled nor collected. Secondly, the control range of the test room temperature and humidity was too wide. We were unable to strictly control these factors due to practical limitations in the test room environment and seasonal variations. Thirdly, other demographic factors, such as ethnic variability, body mass index, and body fat percentage, were not considered.
However, we tried to minimize errors by limiting the inclusion criteria to healthy subjects with no specific medical history or symptoms, although healthy volunteers did not rule out the possibility of varicose veins, knee osteoarthritis, scars on the lower limbs, limb shortening, postural deviations, or extra hair on the legs. Additionally, a large number of participants who underwent consistent measurement techniques could strengthen the reliability of our examination and analysis. To the best of our knowledge, this study is the first report to investigate the reference standard data of DITI.
## 5. Conclusions
This large-scale study of DITI of the lower limb could serve as a basis for establishing a reference standard for DITI. Additionally, we were able to analyze the trend of the surface temperature of lower limbs in terms of the proximity of ROIs, sex, and age. Using these reference standards and trends, DITI results in various diseases can be assessed through comparative analysis. Furthermore, the results of the present study can be used in the development of diagnosis using deep learning-based artificial intelligence in the future.
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|
---
title: HIF-1α-Overexpressing Mesenchymal Stem Cells Attenuate Colitis by Regulating
M1-like Macrophages Polarization toward M2-like Macrophages
authors:
- Wenya Zhu
- Qianqian Chen
- Yi Li
- Jun Wan
- Jia Li
- Shuai Tang
journal: Biomedicines
year: 2023
pmcid: PMC10045413
doi: 10.3390/biomedicines11030825
license: CC BY 4.0
---
# HIF-1α-Overexpressing Mesenchymal Stem Cells Attenuate Colitis by Regulating M1-like Macrophages Polarization toward M2-like Macrophages
## Abstract
A modified mesenchymal stem cell (MSC) transplantation is a highly effective and precise treatment for inflammatory bowel disease (IBD), with a significant curative effect. Thus, we aim to examine the efficacy of hypoxia-inducible factor (HIF)–1α-overexpressing MSC (HIF-MSC) transplantation in experimental colitis and investigate the immunity regulation mechanisms of HIF-MSC through macrophages. A chronic experimental colitis mouse model was established using 2,4,6-trinitrobenzene sulfonic acid. HIF-MSC transplantation significantly attenuated colitis in weight loss rate, disease activity index (DAI), colon length, and pathology score and effectively rebuilt the local and systemic immune balance. Macrophage depletion significantly impaired the benefits of HIF-MSCs on mice with colitis. Immunofluorescence analysis revealed that HIF-MSCs significantly decreased the number of M1-like macrophages and increased the number of M2-like macrophages in colon tissues. In vitro, co-culturing with HIF-MSCs significantly decreased the expression of pro-inflammatory factors, C-C chemokine receptor 7 (CCR-7), and inducible nitric oxide synthase (INOS) and increased the expression of anti-inflammatory factors and arginase I (Arg-1) in induced M1-like macrophages. Flow cytometry revealed that co-culturing with HIF-MSCs led to a decrease in the proportions of M1-like macrophages and an increase in that of M2-like macrophages. HIF-MSCs treatment notably upregulated the expression of downstream molecular targets of phosphatidylinositol 3-kinase-γ (PI3K-γ), including HIF-1α and p-AKT/AKT in the colon tissue. A selected PI3K-γ inhibitor, IPI549, attenuated these effects, as well as the effect on M2-like macrophage polarization and inflammatory cytokines in colitis mice. In vitro, HIF-MSCs notably upregulated the expression of C/EBPβ and AKT1/AKT2, and PI3K-γ inhibition blocked this effect. Modified MSCs stably overexpressed HIF-1α, which effectively regulated macrophage polarization through PI3K-γ. HIF-MSC transplantation may be a potentially effective precision therapy for IBD.
## 1. Introduction
Inflammatory bowel disease (IBD), including Crohn’s disease and ulcerative colitis, is a progressive, immune-mediated, chronic, and recurrent inflammatory disease with an undetermined etiology and a rapidly increasing global prevalence [1,2]. New research reveals that immunomodulatory therapy targeting inflammatory factors and immune cells shows promising better results in IBD therapy [3]. Mesenchymal stem cells (MSCs) are multipotent cells characterized by self-replication ability, multilineage differentiation, and specific surface markers [4], having properties in tissue regeneration and immunomodulation [5]. MSCs have been shown to effectively suppress inflammation and have immunoregulatory effects in IBD, albeit challenged by cost and the incomplete characterization of the effect [6]. Genetic modification is one strategy for optimizing MSC function, including homing and immunoregulation [7]. Transplantation with optimized stem cells should be considered as a method for the precise treatment of IBD. For example, pretreatment with IFN-γ and pre-exposure to muramyl dipeptide potentiate the effect of MSCs [8,9]. Since MSCs are considered to originate in hypoxic niches such as bone marrow [10], they may stably express HIF-1α in normoxic environments [11], thereby adapting to hypoxic environments by inducing glycolysis and contributing to the maintenance of an undifferentiated state [12]. Hypoxia preconditioning effectively optimizes the immunoregulatory effect of MSCs [13]. Hypoxia-inducible factor (HIF) plays the most important role in regulating the hypoxia response [14]. HIF-1α is a mediator of cellular adaptation to hypoxia and generally regulates the metabolism and multipotency of MSC. Moreover, intestinal tracts have a steep oxygen gradient under physiological conditions, while the inflamed intestinal mucosa presents as severely hypoxic. Oxygen-sensitive prolyl hydroxylases (PHDs), critical regulators of HIF-1α, have been identified as promising therapeutic targets in IBD [15]. Therefore, we hypothesized that the stable overexpression of HIF-1α in MSCs will improve cellular adaptation to the hypoxic intestinal environment of IBD, thereby enhancing the function of MSCs in inflammatory intestinal tracts, including immunoregulation.
Immuno-therapeutic mechanisms of MSCs include regulating inflammatory factors, controlling key molecules of inflammatory pathways, rebuilding the lymphocyte subtype balance (Th1/Th2 and Th17/Treg), inducing T-cell apoptosis, and polarizing macrophages [16,17]. The mechanisms of MSCs regulating the metabolic state and polarizing macrophages include cell–cell contact, extracellular vesicles, and immunosuppressive factors [18]. Macrophages play a key role in the initiation and resolution of inflammation, with dynamic polarization processes between M1 and M2 subtypes [19]. The largest population of macrophages resides in the gastrointestinal tract, and Lissner et al. [ 20] showed that M1 macrophages induce intestinal barrier disruptions by downregulating tight junction proteins and inducing epithelial cell apoptosis. The plasticity of macrophages during the gut inflammatory response and the cascade regulation effect of inflammatory factors, such as IL-23 and IL-10, on other immune cells indicate that macrophages are potential targets of therapeutic intervention in IBD [21,22]. Moreover, alternatively activated macrophage (M2 macrophage) differentiation is a successful IBD therapy [23]. Based on these findings, we attempted to determine whether optimized MSCs maintain the intestinal immune balance and alleviate colitis by regulating macrophage polarization.
This study aims to elucidate the potential effects and mechanisms of HIF-1α-overexpressing MSCs (HIF-MSCs) in modulating the immune balance and disease relief in IBD by targeting macrophage polarization and the potential key role of PI3K-γ in the mechanism, which has not been reported yet. HIF-1α overexpression was achieved via lentiviral transfection of MSCs isolated from the human umbilical cord. We transplanted 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced experimental colitis mice, which we had previously established as a successful chronic colitis mouse model, with HIF-MSCs.
## 2.1. MSC Culture
Human umbilical cord MSCs (hUCMSCs) were isolated from the umbilical cord tissue of volunteers, who provided informed consent. All samples were collected after a normal delivery at the Obstetrics Department of the Sixth Medical Center, Chinese PLA General Hospital. Primary cells were obtained with Wharton’s jelly using the explant method [24]. Wharton’s jelly was separated from the endothelial tissue and cut into pieces of 1–2 mm. The pieces were then mixed with minimum essential medium (Gibco, St. Emeryville, CA, USA) containing $10\%$ fetal bovine serum (FBS; Gibco, St. Emeryville, CA, USA) and cultured at 37 °C in the presence of $5\%$ CO2 for 7–14 days; the medium was replenished every 3 days. The non-adherent tissues and suspended blood cells were removed by medium replacement. Single adherent cells crawled out of the edge of Wharton’s jelly tissue at days 4–5, and cell clusters were gradually formed. The density of the adherent cells reached up to 70–$80\%$ at days 10–12. The adherent cells were recorded as P0 generation and passaged in the ratio of 1:2. Primary cells were passaged to the P3 generation for subsequent experiments. All the above operations were performed under aseptic conditions.
## 2.2. Recombinant Lentivirus Design and Transfection
The backbone vector, Ubi-MCS-3FLAG-CBh-gcGFP-IRES-puromycin (Hanbio, Inc., Shanghai, China), was used to reconstruct a lentiviral vector expressing HIF-1α, fragments of which were amplified with the primers listed in Supplementary Table S1. The plasmid was extracted from the correctly sequenced bacterial solution with a Plasmid Mini Kit (TIANGEN BIOTECH, Beijing, China). In the logarithmic growth stage, 293T cells were transfected with the plasmid, and the supernatant was collected to obtain a purified and concentrated vector.
At passage three, MSCs at a density of 2 × 105 cells/mL were inoculated and cultured for 16–24 h until the cell confluence was 30–$40\%$. Green fluorescent protein (GFP)-labeled HIF-1α-expressing lentivirus with puromycin resistance was diluted with complete medium to a titer of 1 × 108 transduction units (TU)/mL and then added to the medium at a multiplicity of infection of 20. Then, it was allowed to cultivate for 18 h after infection, followed by refreshment of the complete medium. The cell morphology was normal during the entire process. Exactly 1 µg/mL of puromycin (Sigma, St. Louis, MO, USA) was added to the culture after 48 h to eliminate the uninfected MSCs. The GFP fluorescent signal of successfully infected cells (HIF-MSCs) was observed using a fluorescence microscope (OLYMPUS, Tokyo, Japan). The cells were sub-cultured for further experiments when they reached 80–$90\%$ confluency.
## 2.3. Pro-Inflammatory M1-like Macrophage Induction and Co-Culture
THP-1 cells were purchased from BeNa Culture Collection (Xinyang, China) and cultured in RPMI 1640 medium (Gibco) containing $10\%$ FBS at 37 °C in the presence of $5\%$ CO2. Subsequently, 50 ng/mL PMA (Sigma) was used to induce THP-1 cells for 48 h. Then, 0.25 µg/mL lipopolysaccharide (LPS) and 20 ng/mL IFN-γ (Sigma) were added to the cells for another 48 h, thereby inducing differentiation into pro-inflammatory M1-like macrophages.
M1-like macrophages were co-cultured with HIF-MSCs (P3 generation) or MSCs (P5 generation) in Transwell permeable supports with a 0.4-μm polyester membrane (Corning International, Tokyo, Japan) for 48 h. Then, HIF-MSCs or MSCs were plated on the upper chamber in DMEM, and macrophages were plated on the lower chambers in RPMI 1640 medium.
## 2.4. Cell Phenotype and Viability
The expression levels of cell surface antigens (CD90, CD73, CD45, and CD34) on MSCs and HIF-MSCs and cell surface antigens (CD80, CD86, CD163, and CD206) on macrophages were detected using flow cytometry. Harvested cells were digested with trypsin-EDTA and stained with FITC anti-human CD34, APC anti-human CD73, PE anti-human CD90, PE anti-human CD45, PE anti-mouse CD86, PE anti-human CD163, FITC anti-human CD80 and FITC anti-human CD206 (Biolegend, San Diego, CA, USA), all human-specific antibodies. Immunofluorescence was performed to detect the expression of macrophage surface molecules F$\frac{4}{80}$, CD86, and CD163 in tissue sections. The expression levels were then analyzed using a BD FACS Calibur cytometer (Beckman, Pasadena, CA, USA). The viability of MSCs was evaluated using trypan blue exclusion and cell counting kit-8 (CCK-8) (Beyotime, Shanghai, China).
## 2.5. Colitis Mouse Model
Female BALB/c mice (6–8 weeks old) were obtained from Sipeifu Animal Technology Co. (Beijing, China). The mice were fed in a specific pathogen-free environment at 25 °C, exposed to a $\frac{12}{12}$ h light/dark cycle, and were blindly sampled following a randomized design (six mice in each group). Colitis was induced using a $35\%$ TNBS (Sigma) solution containing $20\%$ anhydrous alcohol (Sigma). After stimulated defecation, mice were administered 0.1 mL of TNBS solution via rectal perfusion once every 7 days (four times in total) to imitate chronic colitis. Day 21 was the end point of modeling.
## 2.6. MSCs and HIF-MSC Transplantation
On D22, 0.1 mL of MSC (P5 generation) suspension (107 cells/1 mL PBS), 0.1 mL of HIF-MSC (P3 generation) suspension (107 cells/1 mL PBS), or 0.1 mL of PBS was injected via the tail vein to the MSC, HIF-MSC, and TNBS groups 24 h after the last induction. The selected phosphatidylinositol 3-kinase-γ (PI3K-γ) inhibitor IPI549 (MCE, NJ, USA) was administered intraperitoneally and simultaneously with cell injection at a dose of 0.3 mg per animal.
D25 was the end point of observation. MSCs and HIF-MSCs colonized in intestinal tissue (Supplementary Figure S2). Clinical assessment included weight, fur, stool, and activity status; the disease activity index (DAI) was scored based on weight loss, stool characteristics, and blood in the stool. The weight loss rate was determined as the loss in weight/primary weight over time. The pathological score was evaluated based on hematoxylin and eosin staining.
## 2.7. Macrophage Depletion
Clodronate liposomes (CL2MDP; Yeasen, Shanghai, China) were injected via the tail vein at 200 μL (5 mg/mL) per mouse every 2 days before and after HIF-MSC transplantation. Three days after injection, mice were sacrificed to collect serum and colon specimens. The CLP group treated the TNBS mice with CL2MDP, and the HIF-CLP group treated the TNBS mice with CL2MDP and HIF-MSC injection.
## 2.8. Inflammatory Cytokine and Target Gene Detection
ELISA kits (BIOFINE, Beijing, China) were used to detect inflammatory cytokines, including TGF-β, IL-10, IL-12β, and IL-17A, in the mouse serum. Colonic tissue fragments were lysed with RIPA lysis buffer (Beyotime, China), and the proteins were separated and transferred to PVDF membranes (Millipore, St, Louis, MO, USA).
Western blotting was performed to detect inflammatory cytokines and the proteins of target genes in colon tissue. Protein was extracted with an operation at 4 °C, as quickly as possible, to reduce the degradation of HIF-1α in normoxia, appropriately extending the splitting time. After being incubated with primary and secondary antibodies, the membranes were assessed using enhanced chemiluminescence (ECL). Densitometric analysis was performed using Image Pro-Plus (Media Cybernetics, Rockville, MD, USA).
Quantitative PCR (qPCR) was performed to analyze the expression levels of inflammatory cytokines and the target genes of cells. The primers used are listed in Supplementary Table S2.
## 2.9. Statistical Analysis
Quantitative data are expressed as the mean ± standard deviation. Statistical comparisons were performed using ANOVAs and t-tests in SPSS v25.0 (SPSS, Inc., Chicago, IL, USA). $p \leq 0.05$ was considered statistically significant.
## 3.1. Cellular Morphology, Phenotype, and Viability of HIF-1α-Overexpressing MSCs
Isolated primary MSCs were long spindle-shaped cells distributed in a bundle or vortex with a closely arranged adherent growth, and the cell morphology did not change after passage or lentiviral transfection. Screened using puromycin, transfected GFP-expressing cells are defined as P1 HIF-MSCs. As depicted in Figure 1A, the intensity and density of the fluorescent signal in transfected cells did not decline with cell passage. As shown in Figure 1B, flow cytometry revealed that HIF-MSCs had a similar phenotype as MSCs; $92.6\%$ and $98.7\%$ of MSCs, as well as 92.3 and $98.7\%$ of HIF-MSCs, were CD73+CD45- and CD90+CD34-, respectively. Cellular morphology and phenotype were not affected by lentiviral transfection.
The expression of HIF-1α was detected using qPCR and Western blotting. HIF-1α expression at mRNA and protein levels were remarkably elevated upon transfection and did not decline following cell passage (Figure 1C), indicating that HIF-1α overexpression via lentivirus transfection could effectively and stably upregulate HIF-1α expression in MSCs.
Growth of HIF-MSCs and MSCs transfected with the negative control lentivirus was both observed during the incubation, showing logarithmic growth and then a plateau, forming a typical S-type growth curve similar to untreated MSCs, demonstrating that neither lentivirus nor HIF-1α affected MSCs growth (Figure 1C). Trypan blue staining revealed that the viability of MSCs and HIF-MSCs was over $90\%$. CCK-8 showed that the optical density of HIF-MSCs increased significantly compared with MSCs at 1d, 2d, 3d, 4d, and 5d, indicating that cell viability was significantly enhanced (Figure 1E).
Qualitative PCR detection revealed that compared with initial MSCs, HIF-1α overexpression upregulated the expression of vascular endothelial growth factor (VEGF) as well as glycolysis-related indicators, including glyceraldehyde-3-phosphate dehydrogenase (GAPHD) and lactate dehydrogenase (LDHA). Likewise, the expression of the homing-related indicator CXCR-4 was upregulated ($p \leq 0.05$), suggesting a potential effect of HIF-1α overexpression on the function, energy metabolism, and homing of MSCs (Figure 1F).
## 3.2. HIF-MSCs Attenuate TNBS-Induced Experimental Colitis
Using a $35\%$ TNBS enema solution, mice in the experimental model gradually experienced a decrease in vitality and body weight and exhibited anorexia, diarrhea, and bloody stools. The DAI was used to evaluate the general clinical status of the mice and was calculated according to weight loss, stool characteristics, and blood in the stool.
On day 21, at the end of molding, the weight loss rates of the model mouse group (TNBS group) were significantly higher than those of the normal control group. Following stem cell transplantation, the weight loss of the MSC and HIF-MSC group mice stopped after 3 days, while the weight of the TNBS group mice continued to decline (Figure 2A). On day 25, the weight loss rates of the HIF-MSC group were significantly lower than those of the TNBS and MSC groups ($p \leq 0.05$) (Figure 2B).
After stem cell transplantation, the DAI of the MSC and HIF-MSC groups decreased significantly compared with that of the TNBS group on day 25. Moreover, the mean value of the DAI of the HIF-MSC group mice was significantly lower than that of the MSC group mice (Figure 2C).
Compared with the control mice, the colonic mucosa of the model mice presented severe congestion, edema, bleeding, erosion, and ulceration; multiple segments of the bowel with alternating stenosis and expansion were observed. On day 25, 3 days after MSC and HIF-MSC transplantation, the degree of congestion, edema, bleeding, erosion, and ulceration was reduced. Compared with the TNBS and MSC groups, the shortened colon length recovered significantly in the HIF-MSC group ($p \leq 0.05$) (Figure 2D).
Histological examination was used to evaluate colitis further. High concentrations of neutrophils and lymphocytes were found in the submucosa, and abscesses (formed by the aggregation of inflammatory cells) were observed around the recess. On day 25, the histopathological damage of mice in the MSC and HIF-MSC groups was relieved, manifesting as the notable relief of congestion and edema, reduction of inflammatory cell infiltration, and partial repair of mucosal erosion. The pathological score was based on the depth of the lesion, the extent of recess destruction, the extent of the lesion, and the degree of inflammatory infiltration. The pathological score of the HIF-MSC group was significantly lower than those of the TNBS and MSC groups ($p \leq 0.05$) (Figure 2E,F).
In addition to local inflammation, the change in intestinal epithelial appearance suggested that HIF-MSC and MSC transplantation affected the epithelial integrity directly. There was a significant difference in the expression of intestinal tissue repair markers after transplantation in experimental colitis mice. The expression of Ki67, endothelial nitric oxide synthase (eNOS), and occludin was used to evaluate cell proliferation, colonic mucosal angiogenesis, and the integrity of the intestinal epithelium, respectively. Transplantation with MSCs and HIF-MSCs effectively elevated the expression of the three indicators. There was notably greater variation in expression levels of the three indicators in the HIF-MSC group than that in the MSC group ($p \leq 0.05$) (Figure 2G).
These results indicated that HIF-MSCs more effectively ameliorated intestinal inflammation symptoms than MSCs and prompted intestinal epithelium recovery.
## 3.3. HIF-MSCs Affect the Immune Balance of Mice and Colon Tissue via Macrophages
The levels of serum inflammatory factors in mice were detected using ELISA. The levels of anti-inflammatory factors, transforming growth factor-β (TGF-β) and interleukin 10 (IL-10), in the sera of the HIF-MSC and MSC groups mice increased, while those of pro-inflammatory factors, interleukin12β (IL-12β) and interleukin17A (IL-17A), decreased and were significantly different from those in the TNBS group mice. The increase in anti-inflammatory factors and the decrease in pro-inflammatory factors were more evident in the HIF-MSC group than in the MSC group. TGF-β and IL-17A levels were significantly different between the HIF-MSC and MSC groups ($p \leq 0.05$) (Figure 3A).
Western blotting was performed to detect tissue inflammatory factors. The change in inflammatory factor expression in the tissues was similar to that in the serum. Furthermore, the expression of colonic anti-inflammatory factors was higher and that of pro-inflammatory factors was lower in the HIF-MSC group than in the MSC group ($p \leq 0.05$) (Figure 3B).
To determine the role of macrophages in the immunoregulation of HIF-MSCs, clodronate liposomes (CL2MDP) were injected for the depletion of macrophages, including intestinal macrophages (CLP group). Immunofluorescence analysis revealed F$\frac{4}{80}$ expression clearly decreased more in the CLP group than in the TNBS group (Figure 3C). Compared with the TNBS group, HIF-MSCs did not alleviate the DAI and pathological score upon macrophage depletion ($p \leq 0.05$) (Figure 3D). Western blotting revealed that macrophage depletion notably reduced the influence of HIF-MSCs on inflammatory cytokines in the HIF-CLP-treated group, and there was no significant difference between the HIF-CLP-treated and TNBS groups ($p \leq 0.05$) (Figure 3E). Moreover, the differences between the CLP group and the TNBS group in DAI, pathological score, TGF-β, IL-10, and IL-17A were not significant ($p \leq 0.05$) (Figure 3D,E). The results demonstrated that the depletion of macrophages significantly impaired the benefits of HIF-MSC-treated colitis mice, thereby indicating the role of macrophages in the immunoregulation of HIF-MSCs.
## 3.4. HIF-MSCs Promote M1-like Macrophages Polarization toward M2-like Macrophages in Colitis Tissue
In vivo, immunofluorescence revealed that more GFP-labeled HIF-MSCs could colonize the intestine than GFP-labeled MSCs (Supplementary Figure S1). To further investigate whether HIF-MSCs affect the polarization of macrophages by playing a role in immunoregulation, we analyzed the polarization of intestinal macrophages in colitis mice. Immunofluorescence analysis was used to detect F$\frac{4}{80}$, CD86, and CD163 in the colonic tissue. To minimize the impact of the difference in F$\frac{4}{80}$ expression, we calculated the relative ratio of merge expression and single F$\frac{4}{80}$ expression. The results demonstrated that HIF-MSC injection promoted a decrease in the relative expression ratio of F$\frac{4}{80}$+CD86+ and an increase in that relative expression ratio of F$\frac{4}{80}$+CD163+ in the colonic tissues of experimental colitis mice ($p \leq 0.05$) (Figure 4A). Moreover, Western blotting revealed that HIF-MSCs effectively upregulated M2-like macrophage-characteristic Arg-1 expression and downregulated M1-like macrophage-characteristic INOS expression in the colon tissue, thereby having a more significant effect than MSCs (Figure 4B).
## 3.5. HIF-MSCs Promote M1-like Macrophages Polarization toward M2-like Macrophages In Vitro
To investigate the effects of HIF-MSCs on inflammatory cells in vitro, we induced M1-like macrophages in THP-1 cells as a cellular immunological model (Group LPS) with LPS and IFN-γ. The expressions of inflammatory cytokines and macrophage-characteristic products were analyzed using qPCR. Co-culturing with MSCs and HIF-MSCs (Group M and H) decreased pro-inflammatory (TNF-α, IL-6, IL-12b, IL-23) cytokine expression and increased anti-inflammatory (TGF-β and IL-10) cytokine expression compared with induced M1 macrophages (Group LPS) and normal controls ($p \leq 0.05$) (Figure 5A). We also detected other characteristic products to explore the effects of MSCs and HIF-MSCs on macrophage subtype transformation. The expression of CCR-7 and INOS decreased significantly following co-culture with MSCs and HIF-MSCs, whereas the expression of Arg-1 increased significantly ($p \leq 0.05$). HIF-MSCs had a more significant effect on the regulation of inflammatory cytokines, Arg-1, CCR-7, and INOS expression than MSCs ($p \leq 0.05$) (Figure 5B).
Flow cytometry was used to detect the effect of HIF-MSCs and MSCs on induced M1-like macrophages, with CD80+ CD86+ cells representing M1-like macrophages and CD163+ CD206+ cells representing M2-like macrophages. The results demonstrated that co-culturing HIF-MSCs promoted a decrease in the proportions of M1-like macrophages and an increase in those of M2-like macrophages, being notably more effective than MSCs ($p \leq 0.05$) (Figure 5C).
## 3.6. HIF-MSCs Affect Macrophage Polarization through the PI3K-γ Pathway
In our previous study, we demonstrated that MSCs aggravate intestinal inflammation in PI3K-γ-knockout mice, suggesting the possible role of PI3K-γ in HIF-MSC therapy [25]. VEGF is an important factor secreted by MSCs and is widely recognized as an agonist of the PI3K signaling pathway. Consistent with mRNA expression, Western blotting revealed a significantly higher expression of VEGF in HIF-MSCs than in MSCs (Figure 6A). Subsequently, we detected the effect of HIF-MSCs on the downstream molecular targets of PI3K-γ, including HIF-1α and p-AKT/AKT, in the colon tissue. HIF-MSC treatment upregulated the expression of HIF-1α and p-AKT/AKT compared with that in the MSC treatment ($p \leq 0.05$) (Figure 6B,C).
To further elucidate the role of PI3K-γ in the effect of HIF-MSCs, a selected PI3K-γ inhibitor, IPI549, was used to block the PI3K-γ pathway, combined with HIF-MSC transplantation (Group HIF-PI3K-). Western blotting revealed that PI3K-γ inhibition blocked the upregulation effect of HIF-MSCs on HIF-1α and p-AKT/AKT in the HIF-PI3K[-] group ($p \leq 0.05$) (Figure 6B,C).
To verify how PI3K-γ influenced the immunoregulation of HIF-MSCs, we detected the inflammatory factors in the colon tissue of Group HIF-PI3Kγ- and found that the expression of IL-12β significantly increased, whereas that of the anti-inflammatory factors (TGF-β and IL-10) significantly decreased ($p \leq 0.05$) (Figure 6D).
Since PI3K-γ inhibition attenuated the effect of HIF-MSCs in increasing TGF-β and IL- 10 expression, we speculated that PI3K-γ inhibition might affect the influence of HIF- MSCs on macrophage polarization. We next focused on the effect of the PI3K-γ pathway in the regulation of macrophage polarization. Western blotting revealed that the expression of Arg-1 was notably decreased in Group HIF-PI3K[-], and the expression of INOS was increased ($p \leq 0.05$) (Figure 6E). Immunofluorescence analysis was used to detect F$\frac{4}{80}$, CD86, and CD163 expression in the colonic tissue of Group HIF-PI3K[-] (Figure 6F). Compared to the HIF-MSC group, PI3K-γ inhibition notably decreased the relative expression ratio of F$\frac{4}{80}$+CD163+ and increased the relative expression ratio of F$\frac{4}{80}$+CD86+ ($p \leq 0.05$), while there was no significant difference between the HIF-PI3K[-] and TNBS groups ($p \leq 0.05$) (Figure 6G). HIF-MSC injection promoted a decrease in the proportion of M1-type macrophages and an increase in that of M2 macrophages in the colonic tissues of experimental colitis mice, while PI3K-γ inhibition attenuated this effect.
To further elucidate the mechanism by which HIF-MSCs regulate macrophage polarization through the PI3K-γ pathway, we detected AKT subtype expression. Western blotting revealed that HIF-MSCs significantly upregulated AKT1 expression in the colonic tissues ($p \leq 0.05$) (Figure 6E). In vitro, IPI549, with a concentration of 20 nM, was used to inhibit the PI3K-γ effect in induced M1 macrophages. qPCR revealed that HIF-MSCs upregulated the expression of C/EBPβ and AKT1/AKT2 ($p \leq 0.05$), which promoted M1 macrophage polarization to M2 macrophages, as well as the expression of anti-inflammatory factors and M2 macrophage biomarkers. PI3K-γ inhibition blocked the effect of HIF-MSCs, leading to a significant decrease in the relative mRNA expression of Akt1/Akt2 and C/EBPβ ($p \leq 0.05$) (Figure 6H).
These results demonstrated the PI3K-γ pathway as a critical mechanism underlying the HIF-MSC-mediated promotion of macrophage polarization.
## 4. Discussion
MSCs are multipotent adult cells that have unique immunoregulatory properties that are currently being investigated as a treatment option for inflammatory disorders such as IBD. In our previous study, experimental colitis in mice was significantly improved after MSC transplantation. Thus, optimized therapeutic strategies targeting MSCs in IBD therapy are of great interest.
This study revealed three key findings: [1] through lentiviral transfection, HIF-1α-overexpressing MSCs were obtained in normoxic environments, with a significant increase in viability; [2] compared with MSCs, the expression of inflammatory cytokines was significantly affected by HIF-1α-overexpressing MSCs both in vitro and in vivo, thereby accelerating colonic mucosal repair in IBD experimental colitis mice; and [3] HIF-MSCs regulated immune balance by regulating the polarization of M1-like macrophages to M2-like macrophages, with relative anti-inflammatory effects, through a mechanism targeting the PI3k-γ pathway.
Hypoxia-sensitive pathways have an important impact on MSCs, and HIF-1α is critical for hypoxic adaptation. The advantages of MSCs cultured under hypoxic conditions include maintaining MSC proliferation, differentiation, metabolic balance, and other physiological processes [26]. As the hypoxic environment could not be maintained in vivo, we expected to increase the effectiveness of MSCs by intervening in the hypoxia-sensitive pathway. The modified MSCs we constructed maintained a high expression of HIF-1α at mRNA and protein levels without a decrease after passaging so that the characteristics obtained through genetic modification remained stable. In our study, HIF-1α overexpression in MSCs led to significantly enhanced viability and a rise in the mRNA expression of key glycolytic enzymes GAPHD and LDHA, which suggests an enhanced therapeutic effect of modified MSCs.
Herein, we have determined whether targeting related molecules in the hypoxic pathway of MSCs can be optimized as a treatment strategy, especially in a relatively hypoxic inflammatory intestinal environment. We established mouse models of chronic colitis, having inflammatory characteristics similar to those of repeated and progressive IBD, by repeated administration of low-concentration TNBS. We have demonstrated that both HIF-MSCs and MSCs could alleviate the severity of IBD, including clinical features and colon tissue pathology. The degree of remission exerted by HIF-MSCs was higher than that of MSCs, reflected in the improvement in DAI, body weight, colon length, and colon histology. The changes in the expression of Ki67, eNOS, and occludin led to the regeneration and repair of damaged tissues, which were all significantly higher in the HIF-MSC group. We, therefore, suggest that HIF-MSCs are more efficient in tissue repair and disease remission and suggest that HIF-MSCs can be regarded as an amplifier of the function of primary MSCs.
HIF-1α overexpression in MCSs influences cell-autonomous effects, including autonomous angiogenic and osteogenic effects [27]. The significantly enhanced cellular vitality and hypoxia adaptability help HIF-1α-overexpressing MSCs to have strong exocrine properties, immune regulation, and other functions. However, most studies involving HIF-affected MSCs in IBD have focused on the effects on tissue repair and angiogenesis, while our research was centered on immunological regulation through the intervention of HIF-1α overexpression in MSCs. We evaluated the immunoregulation upon MSC and HIF-MSC transplantation on the third day. We observed that HIF-MSCs more significantly affected the immune balance than MSCs, which was manifested in the colon rather than the whole body. It was reported that repair promoted by HIF-MSCs in intestinal mucosal inflamed tissues is closely associated with the immune response [28], which is consistent with our result that local immune balance reconstruction is closely associated with mucous rehabilitation.
The interaction with local immune cells is part of the complicated immune regulation effect of stem cells on immune-mediated disorders [29]. Several studies have proved that the HIF signaling pathway plays a role in the immunomodulatory effect of MSCs, including inducing higher expressions of IL6 in MSCs [30] and regulating Th17 and Treg differentiation, mediated by MSCs through the mTOR pathway [31]. It has been reported that HIF-1α overexpression modification enhances immunomodulation in dental MSCs [32] and improves the healing properties of extracellular vesicles by suppressing activated T-cells in Crohn’s disease [33]. Intestinal resident macrophages are at the front line of host defense at the mucosal barrier and are a potential therapeutic target in IBD [23]. Therefore, the intervention of macrophage polarization is an important requirement for immune regulation in the treatment of IBD.
The anti-inflammatory factors that we detected in the serum and tissue of colitis mice included TGF-β and IL-10, the two major cytokines secreted by alternatively activated macrophages (M2 macrophages) [34]. The changes in characteristic inflammatory factors caused by HIF-MSC transplantation led us to speculate that macrophages may be an important target of HIF-MSCs. Subsequently, we verified the role of macrophages in HIF-MSC therapy through macrophage depletion, and we confirmed that the immunoregulation effect of HIF-MSCs is highly dependent on macrophages. Immunofluorescence analysis results showed that MSC transplantation could regulate the M1/M2 ratio in inflammatory intestinal tissue, which confirmed our hypothesis. In vitro, HIF-MSCs similarly had an enhanced effect on macrophage polarization. Therefore, we concluded that HIF-MSCs promoting the polarization of M1-like macrophages into M2-like macrophages are one of the immunoregulating mechanisms in colitis mice.
The balance of pro-inflammatory M1 and anti-inflammatory M2 phenotypes is dynamic and strongly influences inflammation, which is critical for intestinal immune homeostasis [35]. Adoptive polarized M2 macrophages have protective effects on colitis mice [36]. Macrophage subtype predomination is temporally dynamic at different stages of inflammation, with a large spectrum of macrophage activation [37]. In addition, in the process of macrophage transformation, cell surface markers are changed. In our study, flow cytometry detected the cell expression of single CD80+ or single CD86+ and single CD163+ or single CD206+, suggesting the possibility of transitional morphology occurring in the co-culturing process. Moreover, the M2-like macrophages may be derived from the transformation of monocytes recruited from blood rather than only the intestinal M1-like macrophages [21]. Therefore, we only use the classical naming method, M1-like, or M2-like, to characterize whether macrophages have pro-inflammatory or anti-inflammatory effects and the detection of characteristic chemokines and enzymes of classic M1/M2 macrophages such as CCR7 [38], INOS, and ARG-1 to indicate the intestinal macrophages with different phenotypes. However, this change cannot represent any single intestinal macrophage, and further research is needed on primary intestinal macrophage extraction.
The PI3K-AKT pathway and its downstream targets have emerged as central regulators of the active phenotype in macrophages [39], and AKT1 and AKT2 protein kinases differentially contribute to macrophage polarization [40]. The effects of different isoforms of PI3K on macrophage activation are still controversial. It was reported that macrophages in PI3Kγ-deficient mice and humans had higher secretions of pro-inflammatory cytokines after pattern recognition receptor stimulation [41]. We showed that PI3K-γ attenuates the therapeutic effect of MSCs in IBD through PI3K-γ-knockout colitis mice. Kaneda et al. [ 42] reported the PI3Kγ-regulated immune suppression signature on M1 macrophages. Here, we observed the phenotype changes of M1-like macrophages induced by the PI3K-γ inhibitor in colitis tissue, suggesting that PI3K-γ inhibition significantly weakened the effects of HIF-MSCs in encouraging M2 macrophage polarization. The increased expression of TGF-β, IL-10, and IL-12b in the tissue through HIF-MSC transplantation was also attenuated upon PI3K-γ inhibition. In vitro, we demonstrated that HIF-MSCs promoted M1 polarization toward the M2 subtype through upregulated AKT1/AKT2 ratios, and C/BBPβ and PI3K-γ inhibition by IPI549 notably blocked this effect. The complexities of these results demonstrate that HIF-MSCs regulate macrophages through PI3K-γ, and upregulated VEGF in HIF-MSCs is a possible activator of the PI3K-γ pathway.
The PI3K/AKT/mTOR pathway has been demonstrated to primarily mediate non-hypoxic HIF regulation [43]. In our research, we also demonstrated that the selected PI3K-γ inhibitor attenuated HIF-MSC transplantation-induced HIF-1α overexpression in colonic tissues. HIF-1α overexpression in local inflammatory tissue promotes adaptive immunity by promoting lymph angiogenesis, and the TH1/TH17 response has a major impact on the development of inflammation [44]. We also found that the trend in HIF-1α expression in the colonic tissues was similar to that of inflammatory cytokines. Consequently, it may also be regulated by local inflammation rather than the merocrine secretions of homing HIF-MSCs.
HIF-1α was reported to be induced by Th1 cytokines in M1 macrophage polarization [45]; nevertheless, we observed that HIF-1α upregulation in colon tissue did not correspond with M1 polarization. This divergence may be because HIF-1α expression in colonic tissues could not represent it in specific macrophages as well as the influence of the HIF pathway on the other immune cells in IBD. In our study, we focused on immune regulation and the related mechanism exerted by MSCs with HIF-1α overexpression. The change in the HIF pathway caused by HIF-MSC transplantation and its influence on macrophages is another interesting research direction.
HIF-1α-overexpressing MSCs showed a superior immune regulation effect on colitis mice, but there is still insufficient research comparing this effect with that of primary MSCs. This may require further studies, such as RNA sequencing, to explore the specific mechanisms of HIF1α-overexpressing optimized MSCs in other aspects of therapy for colitis.
## 5. Conclusions
Herein, we have generated HIF-1α-overexpressing MSCs that show a stable overexpression in normoxic conditions using lentiviral vector transfection. HIF-1α-overexpressing MSCs effectively modulate the expression of inflammatory cytokines and M2-like macrophage polarization through PI3K-γ. Transplantation of HIF-1α-overexpressing MSCs in mice with experimental colitis resulted in good immune balance and mucosal rehabilitation, thereby proving a potentially effective treatment for IBD or other inflammatory diseases that can be applied in the future.
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|
---
title: 'Effects of Different Fasting Interventions on Cardiac Autonomic Modulation
in Healthy Individuals: A Secondary Outcome Analysis of the EDIF Trial'
authors:
- Paul Zimmermann
- Daniel Herz
- Sebastian Karl
- Johannes W. Weiß
- Helmut K. Lackner
- Maximilian P. Erlmann
- Harald Sourij
- Janis Schierbauer
- Sandra Haupt
- Felix Aberer
- Nadine B. Wachsmuth
- Othmar Moser
journal: Biology
year: 2023
pmcid: PMC10045415
doi: 10.3390/biology12030372
license: CC BY 4.0
---
# Effects of Different Fasting Interventions on Cardiac Autonomic Modulation in Healthy Individuals: A Secondary Outcome Analysis of the EDIF Trial
## Abstract
### Simple Summary
The impact of a fasting intervention on cardiometabolic health is a noteworthy topic in the scientific community, whereby the coherences of a fasting intervention and autonomic cardiac responses is a topic that is scarcely analyzed. Therefore, the aim of this study is to scientifically investigate the influence of different fasting interventions on cardiometabolic health, i.e., autonomic cardiac response. Twenty-seven individuals (male 16, female 11, aged 26.3 ± 3.8 years) participated and completed this study with a controlled run-in period and were included for analyses. Following the controlled run-in period, participants were randomized into three different fasting groups: (I) alternate day fasting ($\frac{24}{24}$ h of fasting/feasting; $$n = 8$$); (II) the $\frac{16}{8}$ fasting cohort ($\frac{16}{8}$ h of fasting/feasting, $$n = 11$$) and (III) the $\frac{20}{4}$ fasting method, including $\frac{20}{4}$ h of fasting/feasting ($$n = 8$$). An analysis of baseline electrocardiogram parameters and heart rate variability parameters following different fasting interventions demonstrated the safety of these interventions without impacting on heart rate variability parameters during Schellong-1 testing, and demonstrated comparable preserved autonomic responses independently of the fasting intervention. In conclusion, different fasting protocols showed comparable cardiac autonomic responses, determined by electrocardiogram and heart rate variability measurements.
### Abstract
The impact of a fasting intervention on electrocardiographic (ECG) time intervals and heart rate variability (HRV) is a focus that is scarcely analyzed. The main focus of these secondary outcome data was to describe the impact of a different fasting intervention on ECG and HRV analyses. Twenty-seven healthy individuals participated in this study (11 females, aged 26.3 ± 3.8 years, BMI 24.7 ± 3.4 kg/m2), including a pre-intervention controlled run-in period. Participants were randomized to one of the three fasting cohorts: (I) alternate day fasting (ADF, $$n = 8$$), (II) $\frac{16}{8}$ fasting ($\frac{16}{8}$ h of fasting/feasting, $$n = 11$$) and (III) $\frac{20}{4}$ fasting ($\frac{20}{4}$ h of fasting/feasting, $$n = 8$$). An analysis of baseline ECG parameters and HRV parameters following different fasting interventions demonstrated the safety of these interventions without impacting on heart rate variability parameters during Schellong-1 testing, and revealed comparable preserved autonomic cardiac modulation (ACM) independently of the fasting intervention. In conclusion, different short-term fasting interventions demonstrated no safety ECG-based concerns and showed comparable ACM based on ECG and HRV assessments. Finally, our research topic might strengthen the scientific knowledge of intermittent fasting strategies and indicate potential clinically preventive approaches with respect to occurring metabolic disease and obesity in healthy young subjects.
## 1. Introduction
Two-thirds of men and half of women suffer from being overweight and a quarter of German adults are obese. Therefore, the research for effective weight loss methods has been ongoing for several years [1,2]. Fasting, an integral of many religious and ethnic cultures, has emerged as a potential remedy to treat this ‘overweight and obesity crisis’ [3]. Fasting may be conducted via several different approaches, originally initiated to cleanse the body and mind as a spiritual and religious cause for Christians around Easter and Muslims during Ramadan.
The scientific community has picked up the term ‘intermittent fasting’ (IF) that mainly means to refrain from eating for a certain period of time. Typical forms of fasting include fasting for 24 h every other day, with ad labitum (ad lib) caloric intake on the food/caloric drink intake days; this is called alternate day fasting (ADF). Nevertheless, most applied forms of IF represent time-restricted feeding periods (TRF), such as fasting for 16 h and caloric intake for the remaining 8 h ($\frac{16}{8}$). An enhanced version of IF $\frac{16}{8}$ is the $\frac{20}{4}$ method, during which individuals fast for 20 h with only a daily 4 h window for caloric intake. These different methods of IF and TRF depend on the type of protocol. ADF can include a “fasting day”, whereby < $25\%$ of baseline energy needs are allowed to be consumed; alternatively, some protocols may allow for no caloric intake on fasting days at all [4].
IF has gained much attention due to several studies evaluating and discussing the impact of IF. Therefore, IF strategies encompass a broad spectrum of effects in the management of non-obese as well as in obese subjects.
In non-obese subjects, ADF has been shown to be feasible and has improved the average daily fat oxidation accompanied by mild fat mass loss [5]. Additionally, positive effects of the ADF strategy on cholesterol metabolism and cardioprotective effects, such as an improvement in cardiovascular parameters and lowering the risk of cardiovascular disease, were reported in normal weight adults in previous studies [6,7].
Focusing on adult men with obesity, Byrne et al. revealed positive effects of intermittent energy restrictions on weight loss and fat mass reduction [8]. In this context, a recent review from Templeman et al. compared different energy-restriction fasting methods due to the management of metabolic health, in which they found that ADF without energy restrictions was less effective in reducing body mass than daily energy restrictions [9]. In accompaniment, the impact of IF on cholesterol metabolism in obesity is differential, whereby some previous studies reported a cardioprotective reduction in low density lipoprotein (LDL) cholesterol between $7\%$ and $32\%$ and for total cholesterol concentration from $6\%$ to $21\%$, as well as unchanged high-density lipoprotein (HDL) cholesterol concentrations [6,10,11,12]. ADF and IF have shown decreased serum glucose and insulin levels in rodents, whereby the feasibility and translation in daily routines for clinical populations is limited. Nevertheless, positive effects on reductions in fasting insulin levels ranged from $11\%$ to $57\%$ and improvements in insulin resistance have been revealed in overweight subjects, contributing to cardiovascular risk reduction, whereby overnight fasting blood glucose levels remained largely unchanged [13,14].
The latest research evaluating IF in people with type 2 diabetes on insulin therapy revealed significantly reduced HbA1c, body weight and insulin dose in comparison to the standard of care [15]. Additionally, fasting in general is associated with increasing levels of free fatty acids and ketone bodies, which may have opposing effects on inflammation [16].
Next to the presented positive effects of IF strategies and calorie restrictions on cardiovascular health by delaying the progress of cardiovascular ageing and arteriosclerosis [17,18], previous clinical research revealed, in detail, the coherences between HRV and ACM parameters’ improvement and weight lost or IF strategies, both in adults with central obesity as well as in moderately overweight postmenopausal women [17,19].
Due to the variety of studies scientifically processing the positive consequences of fasting, we initiated our study protocol, of which investigated “The effects of Different Fasting Interventions on Anthropometry, Metabolic Health and Functional Performance in non-obese Individuals: a randomized trial with a controlled run-in period–the EDIF trial”, and presented in this manuscript the secondary outcome analysis, focusing on autonomic cardiac modulation (ACM) based on electrocardiogram (ECG) and heart rate variability (HRV) assessments. The novelty of our secondary outcome EDIF analysis was to investigate how ADF (0/$100\%$ daily caloric intake), $\frac{16}{8}$ IF (0/$100\%$ daily caloric intake) and $\frac{20}{4}$ IF (0/$100\%$ daily caloric intake) might modify ECG baseline parameters and HRV parameters during an interventional period follow up (8 weeks) after an initial controlled run-in period of 4 weeks. We hypothesized that there would be significant differences in-between the participating individuals for the ECG baseline parameters and HRV measurements, i.e., autonomic sympathicovagal balance, due to the transiently acquired metabolic alterations during the different fasting schedules [4].
## 2. Materials and Methods
This was a secondary outcome analysis of a single-center randomized trial with a controlled run-in period. In the participating healthy, physically active individuals, we assessed the effects of ADF (0/$100\%$ daily caloric intake), $\frac{16}{8}$ IF (0/$100\%$ daily caloric intake) and $\frac{20}{4}$ IF (0/$100\%$ daily caloric intake) on ECG baseline parameters and HRV parameters. The study protocol was registered at the local ethics committee of the University of Bayreuth (Bayreuth, Germany) (Az. O $\frac{1305}{1}$–GB 20 May 2022).
The trial was planned and carried out in accordance with the principles of Good Clinical Practice and the Declaration of Helsinki [20]. Potential participants were informed about the study protocol in the accompanying study center, and the participating subjects had to sign a written consent form to take part in the study before any trail related examinations were performed. This trial was conceived as a proof-of-concept study and was subscribed at the German Clinical Trials Register (DRKS00029003).
## 2.1. Inclusion and Exclusion Criteria
The participating subjects had to meet the following inclusion criteria: male or female gender, body mass index (BMI) between 20.0 and 29.9 kg/m2 and aged between 18 and 65 years. After informed consent was obtained, a body mass specific oxygen uptake > 20 mL/min/kg−1 and normal fasting glucose tolerance were further preconditions to be enrolled in the trial. Individuals were excluded if they fulfilled one of the subsequent requirements: enrollment in another trial, receiving investigational medicinal devices, significant bradycardia tendency < 35 beats per minute (bpm) at screening or significant abnormal ECG alterations at screening—as judged by the investigator—and supine blood pressure outside of the range of 90–150 mmHg for systolic and 50–95 mmHg for diastolic after resting for five minutes in a supine position. Furthermore, participating individuals had to be withdrawn if they were suffering from multiple and/or severe allergies to drugs or foods or a history of severe anaphylactic reactions. A further exclusion criterion was the anamnesis of a life-threatening disease or clinically severe disease that could directly affect the trial results, as judged by the investigator. The common and uncommon usage of any pharmaceutical drugs, which might influence the analyzed ECG parameters, represented the exclusion criteria (i.e., antihypertensive drugs, antiarrhythmic medication, antidepressant medication with potential impact on ECG time intervals, as QT lengthening). Before being enrolled in the study, inclusion and exclusion criteria were evaluated and our participating subjects were examined by a medical investigator at the screening appointment.
## 2.2. Trial Schedule
Our participating subjects ($$n = 27$$) were randomized to the order of fasting interventions by a research associate that was not further involved in the study (performed by Research Randomizer 4.0 (Social Psychology Network, Lancaster, PA, USA)® (1:1:1) [21]. This randomized study was designed with a controlled initial run-in period of 4 weeks, starting with the screening visit and being followed by two study-specific visits, as described below (Figure 1). The controlled run-in period of 4 weeks was evaluated at visit 2. Afterwards, the ECG baseline parameters and HRV were finally assessed during visit 3 after the 8-week interventional phase follow-up. During each study-related visit, participants were asked to arrive at the research facility fasted. Due to the COVID-19 pandemic situation, the participants were screened for clinically relevant symptoms before entering the scientific laboratory area. If the participants were thought to be sick or feeling weak, the appointment was rescheduled.
## 2.3. Fasting Interventions
The participants were enrolled in one of the three fasting interventions.
## 2.3.1. 16/8. Intermittent Fasting
During the $\frac{16}{8}$ fasting intervention, participants ($$n = 11$$, male 9, female 2) were asked to fast for 16 consecutive hours. During that time, only the consumption of water was allowed. In this context, the consumption of diet drinks, non-sweetened tea or coffee was not allowed. During the other following 8 h, participants were allowed to consume any kind of drink or food of their choice. It was recommended that the participants conducted at least $50\%$ of their fasting period over night-time.
## 2.3.2. 20/4. Intermittent Fasting
During the $\frac{20}{4}$ fasting intervention, the participants ($$n = 8$$, male 3, female 5) were asked to fast for 20 consecutive hours. During that time, only the consumption of water was allowed. In comparison to the $\frac{16}{8}$ fasting intervention, no diet drinks, non-sweetened tea or coffee were allowed. During the other 4 h, the participants were allowed to consume any kind of drink or food of their choice. Even in this fasting protocol, it was recommended that the participants conducted at least $50\%$ of their fasting period over night-time.
## 2.3.3. Alternate Day Fasting
During the alternate day fasting period, the participants ($$n = 8$$, male 4, female 4) were asked to fast for 24 consecutive hours. During that time, only the consumption of water was allowed, with no consumption of alternative drinks, as stated above. On the alternate day, participants were allowed to consume any kind of drink or food of their choice.
## 2.4.1. Screening Appointment (Visit 1)
During the screening appointment (visit 1), the course of the trial was introduced to our participating subjects and they were evaluated for their medical anamnesis. The participants’ body compositions were evaluated via bioelectrical impedance assessment (Inbody 720, Inbody Co., Seoul, Republic of Korea) and their body heights were registered manually (Seca 217, Seca, Hamburg, Germany). Additionally, Schellong-1 testing was registered at the laboratory. The testing was performed as follows: initially, the participants had to rest in a supine position for 10 min, followed by standing up as quickly as possible, and finally, a standing period for two additive minutes. The testing was accompanied by Holter-electrocardiograph recording (Holter ECG) (Faros 180; Bittium, Oulu, Finland) to evaluate the sympathicovagal balance and HRV assessment during Schellong-1 testing. Schellong-1 testing is established as a commonly used clinical orthostatic function testing to prove preserved cardiovascular response and to detect orthostatic abnormalities. Baseline ECG parameters (CardioPart 12, Amedtec, Aue-Bad Schlema, Germany) were recorded subsequently during the laboratory visit.
## 2.4.2. Trial Visits (Visits 2 and 3)
After the 4-week initial run-in period, the cardiac measurements from the screening visit (visit 1) were repeated during visit 2, including a 12-lead ECG and Holter-ECG during Schellong-1 testing. Participants were instructed during the course of the study, especially the IF periods. Afterwards, the participants’ general health statuses were determined via physical examination.
Following randomization to the three different IF cohorts, the cardiac measurements were repeated during visit 3. The final visit 3 was conducted in a similar fashion after the 8-week interventional period according to visit 2. Additionally, participants were asked about their general health status via a final physical examination. Participants were supervised by the study team to verify their adherence to each fasting intervention.
## 2.5. ECG Assessment
The recorded 12-lead ECGs of the participating subjects were analyzed with regard to baseline electrocardiographic parameters, including heart beats at rest (HR) registered in bpm, and ECG time interval measurements, including PQ interval duration (assessed in ms), QRS interval pattern (recorded in ms) and QTc time interval dynamics (measured in ms) [22]. The computerized measurements of baseline ECG parameters were performed digitally using the Amedtec–ECG assessment software (CardioPart 12, Amedtec, Aue-Bad Schlema, Germany) [22]. All study participants were critically evaluated for the following suspected ECG abnormalities: potential clinical relevant sinus bradycardia (predefined as HR < 60 bpm); physiological atrioventricular blocks (AVB), defined as the first and second (Mobitz I) degree AVBs; abnormal right and left axis aberration (defined as more positive than 110 or more negative than 0); pathological QRS interval prolongation (estimated as QRS lengthening > 120 ms) or criteria of preexcitation syndromes, as well as early repolarization (ER) patterns [22]. In the end, no participant had to be eliminated due to abnormal baseline ECG parameters.
## 2.6. HRV Assessment
The long-term Holter-ECG recording—administrated in our trial—utilized one channel with a 250-Hz sampling frequency [22]. In this context, during the laboratory Schellong-1 testing, the following ECG data measurements were evaluated to assess the sympathicovagal balance based on HRV analyses: firstly, the standard deviation of R-R intervals (SDNN); secondly, the square root of the mean standard difference of successive R-R intervals (RMSSD); and finally, logarithmic analysis referring to the ratio low frequency/high frequency, ln (LF/HF) [22]. As reported in our previous research, a power spectral analysis regarding the frequency domain assessment was performed using Fast-Fourier Transformation in Cardiscope (developed by Hasiba Medical GmbH, Graz, Austria) [22]. The balance of the autonomic nervous system was displayed by the HRV data evaluation of RMSSD and the ratio of low frequency/high frequency (ln (LF/HF)) [22]. Our HRV assessment and data acquisition were conducted based on the following current Task Force guidelines: firstly, the European Society of Cardiology (ESC) guidelines, and secondly, the recommendations of the North American Society of Pacing and Electrophysiology (NASPE) [23,24].
## 2.7. Statistics
All acquired data were processed in SPSS software (IBM SPSS Statistics 28, IBM, New York, NY, USA). Our data were assessed for normal distribution by analyzing the data via the Shapiro–Wilk normality test. Afterwards, we evaluated our data via the analysis of variance testing (ANOVA) referring repeated measurements for interaction differences across our participating subjects. The interaction differences due to variable factors, such as time, phase and group were taken into consideration by two-way ANOVA testing. Adjusted post hoc tests were performed in order to explore the differences between the different group data means. Statistical significance was accepted at $p \leq 0.05$, whereby the statistical significance of our results was judged by performing an appropriate F statistic in combination with the corresponding p-value.
## 3. Results
A total of 27 healthy people (male 16, female 11) were included in the study. A total of 5 participants of the initially enrolled 32 subjects terminated the study prematurely due to incompliance or gastrointestinal disorders. Hence, the data assessment was based on 27 data sets; the anthropometric characteristics of the equally distributed participating subjects are displayed in Table 1.
The baseline ECG parameters are presented in Table 2. Baseline ECG parameters, such as HR (measured in bpm), PQ duration (displayed in ms), QRS duration (assessed in ms), and QTc interval analysis (assessed in ms) were analyzed across our three different fasting cohorts in the run-in period (visit 1 to visit 2) as well as after randomization in the intervention period (visit 2 to visit 3). All participants showed comparable findings due to the analyzed 12-lead ECG baseline measurements without any relevant clinical pathology and no significant severe abnormal ECG findings at rest, such as atrioventricular blockings, QRS widening or complete branch blocking, any hints for preexcitation syndrome patterns or ER abnormalities.
By focusing on the data analyses of HR measurements (in bpm), significant time × group effects for the HR interval assessment could be revealed across the three participating IF cohorts ($$p \leq 0.040$$, results displayed in Table 2 and Figure 2 as interaction Δ heart rate differences). Upon detailed consideration, a pronounced Δ heart rate reduction for the $\frac{20}{4}$ fasting participants and a mild Δ heart rate reduction in the ADF cohort could be obtained during the intervention period, whereby no relevant Δ heart rate reduction for the $\frac{16}{8}$ cohort could be elucidated. These individually pronounced differences between the three different fasting cohorts are displayed in Figure 2.
Additionally, in the data assessment of the QRS interval duration, significant time × group effects could be proven across the three participating IF cohorts ($$p \leq 0.032$$, results displayed in Table 2). By detailed statistical consideration, no relevant differences within the intervention phase could be proven in the $\frac{16}{8}$ IF cohort, whereby slight—clinically safe—QRS interval widening could be elucidated in the $\frac{20}{4}$ IF cohort as well as in the ADF cohort. In this context, it must be stated that the highest—clinically safe—starting level of QRS interval duration was generally observed in the $\frac{16}{8}$ IF cohort at the beginning of the intervention phase.
The statistical characteristics displayed in Table 2 provide the progression from visit 1 to visit 2 (run-in period) and from visit 2 to visit 3 (interventional period).
None of the initial analyzed baseline ECG parameters showed significant inter-cohort differences (HR: $$p \leq 0.336$$; PQ: $$p \leq 0.353$$; QRS: $$p \leq 0.168$$; QTc: $$p \leq 0.160$$).
The influence of different short-term IF and TRF schedules on the HRV displaying ACM are presented in Table 3. Our data display comparable preserved ACM of the participating subjects in the intervention phase independently of the performed fasting schedule. In this context, significant changes could be elucidated for SDNN (ms) in the $\frac{20}{4}$ IF cohort as well as in the ADF cohort in the interventional period ($$p \leq 0.031$$, results displayed in Table 3).
The statistical characteristics displayed in Table 3 provide the progression from visit 1 to visit 2 (run-in period) and from visit 2 to visit 3 (interventional period).
None of the initially analyzed baseline ECG parameters showed significant inter-cohort differences (SDNN: $$p \leq 0.516$$; RMSSD: $$p \leq 0.871$$; ln(LF/HF), $$p \leq 0.752$$).
The participants’ HRV data were collected over three periods by Holter ECG recording: 10 min in a sitting position, followed by the fast standing up and the final standing duration, as described in our previous research [22].
By discriminating the detailed ECG and ACM variations—in reference to the different time periods during the Schellong-1 testing across our three different IF and TRF schedules—we recorded the differences in participants’ cardiac data in response to the standing-up compared to the sitting period in the controlled run-in period and observational period follow-up. These differences are displayed as Δ measurements in Table 4 and Table 5.
Therefore, no significant interaction differences could be elucidated in the baseline ECG data assessment during the controlled run-in period and interventional period (the results are displayed in Table 4).
The statistical characteristics displayed in Table 4 provide the progression from visit 1 to visit 2 (run-in period) and from visit 2 to visit 3 (interventional period).
None of the initial analyzed baseline ECG parameters showed significant inter-cohort differences (ΔHR: $$p \leq 0.456$$; ΔPQ: $$p \leq 0.832$$; ΔQRS: $$p \leq 0.302$$), except ΔQTc: $$p \leq 0.038.$$
According to the presented ACM of HRV assessment in Table 3, no significant differences between the different time periods during Schellong-1 testing could be revealed for the presented Δ values of the HRV assessment, thus displaying similar preserved ACM independently of the participants’ fasting schedule (results represented in Table 5).
The statistical characteristics displayed in Table 5 provide the progression from visit 1 to visit 2 (run-in period) and from visit 2 to visit 3 (interventional period).
None of the initial analyzed baseline ECG parameters showed significant inter-cohort differences (ΔSDNN: $$p \leq 0.943$$; ΔRMSSD: $$p \leq 0.842$$; Δ ln(LF/HF), $$p \leq 0.386$$).
## 4. Discussion
This secondary outcome analysis of a randomized trial with an initial run-in period revealed that different intermitted short-term fasting interventions and TRF protocols in healthy individuals are associated with no significant ECG changes of concern.
Alterations in baseline ECG parameters, i.e., QT interval alterations and HRV values, are known, relevant, clinical indicators, and small alterations in these parameters might be associated with life-threatening arrhythmogenic events and sudden cardiac death [22,25,26]. Acute increases in blood glucose concentration—within physiological range—have especially been demonstrated to be associated with higher parasympathetic and lower sympathetic cardiac autonomic modulation and subsequent HRV alterations [27].
Previous research on the impact of IF and cardiac effects revealed contrary findings. Some studies in healthy individuals demonstrated no increased cardiac risk during body mass reduction by the modified fasting intervention of moderate duration [28] and unaltered ECG following the fastening condition [29]. Contrary findings were revealed previously which analyzed the influence of brief and transient fasting on ECG parameters as well as HRV data, whereas decreased measurements for QRS duration, baseline HR and changes in QTc duration as well as HRV alterations could be revealed [27,30,31]. Additionally, the presence of transient ER pattern, QRS shortening as well as decreased HR have been reported in subjects with food deprivation [32,33]. The substantial impact of fasting on ECG parameters with a certain intersubjective variability of physiological response by food intake, demonstrated in previous research [30], can be confirmed by our data on ECG parameter changes. In this context, our obtained findings in healthy subjects demonstrated the safety of various fasting interventions with no clinically relevant ECG parameter changes. The reduction in baseline HR observed during the run-in period in the $\frac{16}{8}$ and ADF group can be explained by the study participants becoming more used to the study environment and potentially regarded as regression to the mean. Our observations did not demonstrate any negative impact of QRS widening nor Δ QTc alterations and adverse cardiac events, such as heart rhythm abnormalities, syncope or proarrhythmogenic risk, but a preserved sympathicovagal balance. Therefore, our findings might provide important information for the feasibility and safety of IF and ACM in healthy young subjects.
Additionally, the obtained data of our study emphasize maintaining autonomic cardiac modulation due to variable metabolic fasting conditions in our healthy young participants and could not reveal an increased risk for arrhythmogenic substrates and adverse cardiac events determined by the baseline 12-lead ECG assessment. Therefore, the administrated variable IF and TRF schedules in our healthy young participants seem to be safely transferable in daily routines based on our short-term follow-up assessment. Nevertheless, our observations have to be handled with care due to the following reasons: firstly, cardiac repolarization changes in general are known to be individually associated with fasting and feeding; secondly, the obtained QTc levels might be influenced by variable sympathetic activity due to circadian rhythmic; therefore, finally, the ACM might play a role in fasting-related QTc changes [30,34]. In order to obtain comparable and unbiased results, we scheduled the visits (mainly) in the morning hours to exclude any interferential effects of the variable sympathetic activity due to the circadian rhythm and to exclude the previously described QTc shortening after lunch and QTc lengthening after dinner [35].
Our observations, comparing—to the best of our knowledge—primarily ECG and ACM in healthy individuals during three different short-term IF and TRF interventions, could not elucidate clinically relevant QRS widening nor QTc lengthening and sequential proarrhythmogenic risk nor increased risk of sudden cardiac death. Previous case reports displayed a certain risk of QT interval lengthening after fasting or following with very low-calorie diets and its proarrhythmogenic impact by sudden attacks of ventricular torsades de pointes tachycardias [36,37]. Furthermore, changes in metabolic parameters, such as diet habits, are associated in previous case reports with the occurrence of premature ventricular complexes (PVC) and ventricular arrhythmias in subjects without any cardiac and organic diseases. These PVC are usually estimated to be benign in healthy subjects, whereby the homeostasis of myocardial cellular metabolisms and ion channels are essential to maintain electrophysiological stability and to prevent cardiac arrhythmias due to metabolic changes during IF [38].
Globally, cardiovascular disease and associated metabolic disorders have been progressing in recent decades due to the exposure of individuals to suboptimal metabolic and hormonal factors as well as increasing stress levels [18]. In this context, the obtained findings of our pilot trial on different daily practicable IF strategies might contribute to the future prevention of cardiovascular diseases and promote the cardiometabolic health of individuals. Next to regular physical activity, stress-level reducing strategies and conscious daily micro- and macronutrient intake, IF and TRF strategies seem to have great future importance for combating metabolic diseases and the global problem of obesity-related illness [19]. In this context, our pilot study provides important information for safe application in healthy individuals without any enhanced risk of cardiac arrhythmogenic disorders or cardiac stress levels.
However, our preliminary reporting has diverse limitations. First of all, the number of included subjects is relatively small ($$n = 27$$), for which reason, the obtained data of our pilot study should be considered as hypothesis-generating and further research should focus on a larger sample size of participating subjects to verify the scientific evidence base. By assessing our pilot study results, the following circumstances and their potential impact on ACM and ECG parameters throughout the study period have to be taken into consideration: individual variable differences with regard to physical activity, which have not been determined initially for the participating subjects, as well as lifestyle habits in general during the intervention, such as interindividual sleeping habits, as reported in our previous research [22].
## 5. Conclusions
This secondary outcome analysis of the EDIF trial provided, for the first time, new evidence of the persevered sympathicovagal balance—determined by baseline ECG parameters and HRV assessment—across the three different participating short-term IF and TRF cohorts without any negative clinical impact on the enhanced severe clinical proarrhythmogenic events.
In conclusion, IF and TRF seem to be efficiently transferable into daily routines in healthy young individuals displaying preserved sympathicovagal balance and did not reveal any enhanced cardiac arrhythmogenic potential and cardiac stress levels during our intervention phase.
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|
---
title: Polymorphisms within the Tumor Necrosis Factor-Alpha Gene Is Associated with
Preeclampsia in Taiwanese Han Populations
authors:
- Chih-Wei Lin
- Chung-Hwan Chen
- Meng-Hsing Wu
- Fong-Ming Chang
- Lin Kang
journal: Biomedicines
year: 2023
pmcid: PMC10045416
doi: 10.3390/biomedicines11030862
license: CC BY 4.0
---
# Polymorphisms within the Tumor Necrosis Factor-Alpha Gene Is Associated with Preeclampsia in Taiwanese Han Populations
## Abstract
Preeclampsia (PE) occurs in women pregnant for more than 20 weeks with de novo hypertension and proteinuria, and is a devastating disease in maternal–fetal medicine. Cytokine tumor necrosis factor (TNF)-α may play a key role in the pathogenesis of PE. We conducted this study to investigate the regulatory regions of the TNF genes, by investigating two promoter polymorphisms, TNFA-308G/A (rs1800629) and -238G/A (rs361525), known to influence TNF expression, and their relationship to PE. An observational, monocentric, case–control study was conducted. We retrospectively collected 74 cases of severe PE and 119 pregnant women without PE as control. Polymerase chain reaction (PCR) was carried out for allele analysis. Higher A allele in women with PE was found in rs1800629 but not rs361525. In this study, we first found that polymorphism at the position -308, but not -238, in the promoter region of the TNF-α gene can contribute to severe PE in Taiwanese Han populations. The results of our study are totally different to previous Iranian studies, but have some similarity to a previous UK study. Further studies are required to confirm the roles of rs1800629 and rs361525 in PE with circulating TNF-α in PE.
## 1. Introduction
Preeclampsia (PE) occurs in women pregnant for more than 20 weeks with de novo hypertension and proteinuria, and is a devastating disease in maternal–fetal medicine [1,2]. Maternal complications include the notorious eclampsia, various end-organ damage such as liver and renal injury, and even increased risks of future permanent organ damage or cardiovascular diseases. Common fetal consequences include intrauterine growth restriction, premature birth, and even stillbirth. For pregnant women affected with severe PE, the only cure for this condition is to deliver the placenta, often ending with an indicated preterm birth. Intensive care of the preterm newborn may be needed, with potential long-term sequelae.
Although there have been extensive studies on the pathogenesis of preeclampsia, the real etiology is still unclear. Immune maladaptation, placental and endothelial dysfunction, abnormal trophoblast differentiation, and exaggerated systemic inflammatory response may be the etiology of PE [3]. Cytokine tumor necrosis factor (TNF)-α may play a key role in the pathogenesis of PE [4,5]. The impaired placental perfusion as a result of defective maternal spiral artery remodeling leads to endothelial activation [4]. In addition, genes that have been found to display altered placental expression in patients with PE include TNF-α, intercellular adhesion molecule 1, Integrin, interferon-γ, and so on [4]. The relationship between cytokines and the development of PE has been extensively studied, and evidence suggests that pro-inflammatory cytokines, including TNF-α, IL-1, and IL-6, play a significant role in the pathogenesis of severe PE [5]. Additionally, blocking these inflammatory factors has been proposed as a potential treatment strategy due to their involvement in development of PE. TNF-α is a particularly promising target for further study and designing treatment [5]. No anti-TNF-α agents have been used clinically, but they hold potential as a future treatment option. Several studies have shown that TNF-α inhibitors can reduce certain physiological changes mediated by TNF-α in PE [5].
At least three gene–disease association studies have presented controversial results. Chen et al. [ 6] showed that TNF-alpha mRNA expression is significantly elevated in preeclamptic patients compared with two other control groups. In addition, the high expression of TNF-α may be associated with the TNF1 allele, whose frequency is increased in PE [6]. They concluded that their observations are consistent with a major role for TNF-α in mediating endothelial disturbances, and suggest a key role for TNF-α in the development of preeclampsia. They proposed that TNF-α may alter the balance between prostacycline and thromboxane, increasing the vascular resistance in PE.
In contrast, Dizon-Townson et al. reported that the frequency of the TNF gene is not increased in patients with preeclampsia or HELLP syndrome (hemolysis, elevated liver enzymes, and low platelet count) [7]. Despite not finding significant differences in the allele frequency of the TNF-α gene, researchers still believe that TNF-α plays a crucial role in the development of PE. The lack of significant differences in the allele frequency does not negate the potential significance of TNF-α in the pathogenesis of PE [7]. However, Haggerty et al. reported preeclamptic white women were more likely than normotensive white women to carry the up-regulating TNF-α-308 A/A (odds ratio, 4.1; $95\%$ CI, 1.1–15.3) genotype, and concluded that cytokine genotypes were associated with preeclampsia and may identify women who are at high risk for preeclampsia [8]. The researchers concluded that genetic polymorphisms may contribute to excessive immune system stimulation during pregnancy, thus increasing the risk of developing PE, underlying the genetic susceptibility to the disease [8]. In addition, Saarela et al. observed that the polymorphisms of the TNF-α gene showed a significant haplotype association with susceptibility to preeclampsia in the Finnish population [9]. Specifically, the C-A haplotype of the two polymorphisms, C-850T and G-308A, was found to be associated with a higher risk of PE, while the T-G haplotype was less common in women with PE [9]. To date, no one has studied the haplotype association with preeclampsia in a Taiwanese Han population.
Given these contradictory results, the TNF-α gene is a good candidate gene for PE research. To date, at least two polymorphisms of the TNF-α gene have been reported [7,9,10,11]. We conducted this study to investigate the regulatory regions of the TNF genes, by investigating two promoter polymorphisms, TNFA-308G/A (rs1800629) and -238G/A (rs361525), known to influence TNF expression, and their relationship to PE. We use these two polymorphisms as a basis to find nearby new markers and undertake a haplotype study between the TNF-α gene and PE.
## 2.1. Ethics Statement
This is an observational, monocentric, case–control study. The Institutional Review Board (IRB) of National Cheng Kung University Hospital (NCKUH) approved this study (IRB No.: HR-95-43 and HR-100-066). All participants have written informed consent.
## 2.2. Patients
All subjects in this study were from an ethnically Taiwanese Han population. We retrospectively collected 74 cases of severe PE meeting the criteria of the American College of Obstetricians and Gynecologists at the Department of Obstetrics and Gynecology of NCKUH from 1 August 2006 to 31 July 2011 [12,13]. From January 2006 to December 2010, 119 pregnant women who delivered at the Department of Obstetrics and Gynecology of NCKUH and did not have PE served as normal controls. Patients with severe PE were called back for blood tests with informed consent. The above diagnoses were made according to the medical records of NCKUH, which were reviewed carefully to confirm the fulfillment of the diagnostic criteria described below based on medical history, clinical manifestations, and laboratory data. During the period, pregnant women who had given birth after uncomplicated pregnancies and who had at least two normal pregnancies cared for at NCKUH provided blood samples as normal controls. All participants in this study were matched for fetal sex, parity, gestational age, and maternal age to within 5 years. None of the normal controls had clinical signs of PE or other medical or pregnancy complications. At the time of blood sampling, none were in labor. PE was defined as de novo hypertension in a previously normotensive pregnant woman after 20 weeks of gestation with new-onset proteinuria [3,12,13,14,15]. Hypertension was defined as a systolic blood pressure ≥140 mmHg or a diastolic blood pressure ≥90 mmHg on at least two occasions and 4–6 h apart after the 20th week of gestation in previously normotensive women [3,12,13]. Proteinuria was defined as 300 mg or more protein excretion in 24 h urine collection, or protein concentration of 300 mg/L or higher in urine (≥1+ on dipstick) [3,12,13]. Severe PE was defined as more than one of the following: blood pressure of $\frac{160}{110}$ mmHg or higher, excretion of 5 g or more of protein in a 24 h urine sample, the presence of multiorgan involvement such as oliguria, pulmonary edema, visual or cerebral disturbance and pain in the epigastric area or right upper quadrant, abnormal liver enzymes, and thrombocytopenia (platelet count < 100,000 per μL) [3,12,13]. Gestational age was based on the precise date of the last menstrual period or/and ultrasound measurement of crown–rump length in the first trimester. Women who fulfilled PE criteria but did not have severe PE were not included in this study. Other exclusion criteria were as follows: fetal abnormalities, autoimmune disorders, diabetes mellitus, chronic hypertension, chorioamnionitis, premature rupture of membranes, or multiple pregnancies.
## 2.3. Gene Analysis
Blood samples from a peripheral vein were obtained for gene study. We followed the methods described by Saarela et al. to examine the polymorphisms of the TNF-α gene promoter [9]. DNA was extracted from blood using the Puregene System (Gentra Systems, Research Triangle Park, NC, USA) and stored at 4 °C until analyzed.
The TNF-alpha polymerase chain reaction (PCR) was constructed to identify a polymorphism at G-308A in the promoter region. A total of 500 ng of patient DNA was added to a 50-µL volume containing 10 mM Tris HCl (pH, 8.3), 1.5 mM MgCl2, 50 mM KCl, 1.0 mM of each deoxynucleotide triphosphate, 20 pmol of each primer, and 1 U of Taq polymerase. Conditions for PCR were denaturation at 94 °C for 3 min followed by 35 cycles at 94 °C for 15 s, 58 °C for 45 s, and 72 °C for 45 s, followed by a final extension at 72 °C for 6 min. Primer sequences were 5′AGGCAATAGGTTTTGAGGGCCAT and 5′TCCTCCCTGCTCCGATTCCG. The 107-base pair (bp) PCR products were cleaved with NcoI (Boehringer Mannheim; Mannheim, Germany), resulting in cleavage of the TNF-alpha allele into two fragments of 78 and 20 bp, whereas the TNF alpha-2 allele (-308G-A) was not cleaved. The PCR products were separated on a Meta Phor $4\%$ agarose gel (FMC; Rockland, ME, USA) stained with ethidium bromide and visualized under ultraviolet light [7,9,10].
For the amplification of the G-238A polymorphism in the promoter region, we used primers of the downstream and upstream primers as follows: upstream primer: 5′-TCC TGC ATC CTG TCT GGA AGT TAG-3′; downstream primer: 5′-TCA CAC TCC CCA TCC TCC CGG CT-3′, which generate a PCR product of 182 base pairs. The PCR was performed in a final volume of 20 µL that contained 200 ng genomic DNA, 20 picomoles of each primer, each of four dNTP at 250 mmol/L, and 2 U Taq polymerase (PROTECH). PCR conditions for both polymorphisms were as follows: 94°C for 4 min, 35 cycles at 94°C for 30 s, 60°C for 30 s, and 72 °C for 1 min, followed by a final extension step of 5 min at 72°C. After amplification, 8 µL of the product are digested with 5 U of NlaIV (New England Biolabs) at 37°C for 6 hrs [7,9,10].
## 2.4. Statistical Analysis
Genotype and allele frequencies were compared using χ2 testing, using the statistical package SPSS (SPSS Inc., Chicago, IL, USA). Yates correction of continuity was used when an observed number was ≤5.
## 3. Results
The baseline characteristics and pregnancy outcomes of 74 cases of severe PE and 119 cases of normal controls are shown in Table 1. There was no difference in women with severe preeclampsia and the normal controls in age, parity, and the gender of newborn babies. The newborns from the women with severe PE showed earlier gestational age, lower Apgar scores, and lower birth weight. Our results indicate that preeclampsia contributes to perinatal morbidity and mortality [3,16,17]. Specifically, women affected with severe PE may experience an indicated preterm birth, resulting in earlier delivery at a gestational age, and, subsequently, lower birth weights.
Genotype distributions and allele frequencies of the NcoI polymorphism at the position -238 in the promoter region of the TNF-α gene among normal controls and women with severe preeclampsia are shown in Table 2. Genotype was determined in the 74 women with severe preeclampsia and 119 normal controls. Overall, three genotypes (A/A, A/G, G/G) and two alleles (A, G) were seen. The frequency of homozygotes (A/A) was $94.6\%$ (70 of 74 women) in women with severe PE, and $96.6\%$ (115 of 119 women) in normal controls. The frequency of homozygotes (G/G) was $0\%$ both in women with severe PE and normal controls. The allele frequency of A alleles was $97.3\%$ (144 of 148 alleles) in women with severe preeclampsia and $98.3\%$ (234 of 238 alleles) in normal controls. The allele frequency of G alleles was $2.7\%$ (4 of 148 alleles) in women with severe preeclampsia and $1.7\%$ (4 of 238 alleles) in normal controls. For the NlaIV polymorphism at the position -238 in the promoter region of the TNF-α gene, neither genotype distributions nor allele frequencies showed statistically significant differences between normal controls and the women with severe PE.
Genotype distributions and allele frequencies of the NlaIV polymorphism at the position -308 in the promoter region of the TNF-α gene among normal controls and women with severe PE are shown in Table 3. Genotype was determined in the 74 women with severe PE and 119 normal controls. Overall, three genotypes (G/G, A/G, A/A) and two alleles (A, G) were seen. The frequency of homozygotes (G/G) was $81.1\%$ (60 of 74 women) in women with severe PE and $57.1\%$ (68 of 119 women) in normal controls. The frequency of homozygotes (A/A) was $5.4\%$ (4 of 74 women) in women with severe PE and $0.9\%$ (1 of 119 women) in normal controls ($p \leq 0.001$). The allele frequency of G alleles was $87.8\%$ (130 of 148 alleles) in women with severe PE and $78.2\%$ (186 of 238 alleles) in normal controls. The allele frequency of A alleles was $12.2\%$ (18 of 148 alleles) in women with severe PE and $21.8\%$ (52 of 238 alleles) in normal controls ($$p \leq 0.016$$). For the NlaIV polymorphism at the position -308 in the promoter region of the TNF-α gene, both genotype distributions and allele frequencies showed statistically significant differences among normal controls and the women with severe PE.
The results of haplotype frequencies for the Nla IV and Nco I polymorphisms at the promoter region of the TNF-α gene in severe preeclampsia and controls are shown in Table 4. The proportions of A/G, A/A, G/G, and G/A in the women with severe preeclampsia were $85.49\%$, $11.81\%$, $2.35\%$ and $0.35\%$, respectively. The proportions of A/G, A/A, G/G, and A/G in the normal controls were $76.47\%$, $21.82\%$, $1.68\%$ and $0\%$, respectively. There was a significant difference between normal controls and the women with severe PE (Table 4).
## 4. Discussion
In this study, we first found that polymorphism at position -308, but not -238, in the promoter region of the TNF-α gene can contribute to severe PE in Taiwanese Han populations. Similar results have previously been reported in Caucasian, Turkish, Tunisian, and Iranian populations [9,18,19,20,21,22,23]. A study by Pfab et al. of 1480 Caucasians who were genotyped for TNF-α-308G/A found that the A allele was associated with proteinuria using dipstick tests at the third trimester [18]. Nevertheless, no association between the genotypes and blood pressure throughout all trimesters among pregnant women was found [18]. Another study by Pazarbaşi et al. involving 40 women with eclampsia and 113 women with PE demonstrated that the A/A genotype frequency at the -308 position was significantly higher both among eclamptic women and those with PE compared to normotensive women [20]. In addition, the T/T genotype at the -805 position was less frequent in these two groups of patients compared to the control group [20]. Nonetheless, they proposed that the functional association between the gene polymorphisms, cytokine levels and development of PE still needed to be investigated [20]. Mirahmadian et al. found that the frequency of A alleles at the G-308A position was significantly higher in the 160 preeclamptic Iranian women compared to the control group ($10.62\%$ vs. $0\%$) [21]. On the other hand, at the -238 position, the allele G was more frequent in women with PE compared to the control group ($60.62\%$ versus $50\%$) [21]. They suggested that the inconsistent results found in studies examining TNF-α gene polymorphisms and their relationship to the development of PE may be due to ethnic heterogeneity. Despite this, they believe that the role of gene polymorphism remains important in the development of PE. [ 21]. Similarly, work by Mohajertehran et al. has shown that allele A frequency was $24.1\%$ among the 54 women with PE and $8.0\%$ among normal pregnant women [22]. As for the genotype study, the frequency of homozygote G/G was $51.9\%$ in the PE group and $84.0\%$ in the normal control group. No homozygote A/A was detected [22]. Tavakkol Afshari et al. investigated the -238 and the -308 position, and demonstrated that the A allele frequencies were significantly higher at both positions among the 153 preeclamptic women compared to 150 healthy pregnant women [23]. At the former position, $14.3\%$ of the preeclamptic women had the homozygous genotype (G/G), compared to $62\%$ of the control group. For the -308 location, $52.2\%$ of the affected women had the homozygous genotype (G/G), while $84\%$ of the control group had this genotype [23]. Studies on other cytokine genotypes have been less consistent, highlighting the important role of TNF-α in mediating PE. A meta-analysis study revealed that TNF-α-308G/A polymorphism is susceptible to PE. The A allele of TNF-α-308G/A polymorphism enhances the chance of PE, especially in Caucasian and *Iranian primiparae* [24]. The results indicate that TNF-α-308G/A gene polymorphism may play important roles in the pathogenesis of severe preeclampsia.
TNF-α polymorphisms, such as -308G/A, -850C/T, -238G/A, are possibly associated with PE [20,23,25]. TNF-α rs1800629, a G to A transition in the promoter at position −308, is associated with the level of TNF-α expression and is the most studied polymorphism [26,27,28]. The polymorphism at the TNFA 308 locus lies within the promoter region for the gene for TNF-α and may alter the binding of transcription factors, thus leading to increased TNF-α messenger ribonucleic acid synthesis [29,30,31,32]. For example, the TNF2 allele was found more frequently in patients with septic shock who did not survive ($52\%$) compared to those who did survive ($24\%$), but no correlation was established with TNF-α [29]. Nevertheless, TNF-α production stimulated with lipopolysaccharide has been shown to be correlated with polymorphism at the -308 position of the promotor region [30]. With transition to A, transcriptional activity of TNF-α increases with more p29 production [32]. Some of the results of previous studies on the promoter polymorphisms of the TNF-α gene have been inconsistent and may have shown only a weak association with various diseases of interest. The heterogeneity of the diseases may contribute to the difficulties in establishing correlations between different studies, and multiple genes may be interacting [32]. Despite the critical role of TNF-α in inflammation regulation, the evidence on the impact of TNF-α genotype on diseases and their outcomes has been conflicting. However, the genetic regulation of TNF-α still holds significance and its study is valuable [31]. The association between polymorphisms in the TNF-α gene and various inflammatory conditions, including infections, autoimmune diseases, transplantation, and even cancers, has been described [31].
Even though many studies have demonstrated the association between the risk of PE and TNF-α-308G/A polymorphism in various countries, the link between the risk of PE and TNF-α-308G/A polymorphism is still controversial due to different ethnicity. A meta-analysis encompassing 22 studies included 2459 cases of PE suggested the association between the TNF-α-308G/A polymorphism, and subgroup analysis revealed that the association was evident in certain Caucasian and Iranian populations. [ 24]. Our study suggested that polymorphism at the -308 position in the TNF-α gene promoter in Taiwanese Han populations may also play a crucial role. Single SNP analysis of 1598 women demonstrated that rs1800629 was associated with increased risks of PE (RR = 1.8) [33]. Though several previous studies have found that the A allele of rs1800629 contributed to PE [8,9,21,22,23,33], there are some studies which have found that more G alleles at rs1800629 contributes to PE [6]. For example, a study in the UK involving 14 women with PE showed that the frequency of homozygotes (G/G) was $64.3\%$ (9 of 14 women) compared to that of $16.7\%$ (2 of 12 women) among normal pregnant women [6]. In addition, they found that individuals who were homozygous for TNF1 had higher TNF-α mRNA expression [6]. In this study, we found more G alleles of rs1800629 in PE, which is same as the study from the UK [6]. Further studies are needed to confirm the roles of alleles of rs1800629 in PE.
The TNF −238A allele (rs361525) has also been implicated in a number of autoimmune diseases including rheumatoid arthritis [34], ankylosing spondylitis [35], systemic lupus erythematosus [36], juvenile idiopathic arthritis [37], Graves’ disease [38], and type I diabetes mellitus [39]. It also plays roles in many infectious diseases including influenza A (H1N1) [40], pulmonary tuberculosis [41,42], hepatitis B [43], infective endocarditis [44], sepsis and septic shock [45], and dengue fever [46]. However, the studies about the role of rs361525 in PE are few. Only four studies in Iranian populations have demonstrated regulatory roles of A alleles of rs361525 in PE [21,23,25,47]. Three studies showed higher A allele frequency of rs361525 in PE [21,23,25]. For instance, a case–control study conducted in Iran involving 153 preeclamptic pregnant women and 140 healthy pregnant women analyzed the polymorphism of rs361525 and found that homozygotes (A/A) were more prevalent in the preeclamptic group compared to the control group ($90\%$ versus $10\%$). Furthermore, the frequency of the A allele was also higher in the case group ($51.6\%$) compared to the control group ($18\%$), with a significant difference of $p \leq 0.001.$ Additionally, the study also revealed significant differences in diastolic blood pressure among patients with different genotypes [25]. On the contrary, one recent study, also from Iran, revealed a protective role of A allele of rs361525 in PE [47]. It revealed that the A allele of rs361525 was less frequent among women with PE than among normal pregnant women ($1.8\%$ versus $6.1\%$, $$p \leq 0.03$$) [47]. In addition, the same study also showed that the homozygote (G/G) was more frequent at rs1800629 in women with PE than the control group ($91.9\%$ versus $83.5\%$), and the frequency of the A allele was lower in the effected women than the control group ($4.5\%$ versus $8.3\%$) [47]. Combined together, the GA/GG (-308/ -238) genotypes corresponded to a lower risk of PE [47]. They further evaluated the biological effects of the polymorphism at the -308 position and showed that that the G to A allele substitution results in the loss of a transcription factor DNA-binding site [47]. In our study, we did not find the regulatory role of rs361525 in PE. Due to the above conflicting results and our study, further studies to evaluate the roles of rs361525 in PE are required.
There are some limitations to our study. First, we did not study the serum concentration of TNF-α. Circulating TNF-α can prove a functional relationship between polymorphisms, elevated TNF-α, and PE. Because serum samples were obtained at least one month after delivery, we did not measure circulating TNF-α, because it would be unrepresentative of PE levels. Additional studies of TNF-α polymorphisms and circulating TNF-α with early pregnancy serum samples would confirm the relationship between genetic polymorphisms, excessive inflammation, and PE. Second, the number of subjects is limited, which may contribute to the insignificant difference in rs361525. Third, Hardy–*Weinberg equilibrium* (HWE) for the -308 variant, and the p value of the chi square test was 0.007 for the PE and 0.04 for the controls. There is possibility of undefine allele which may not be found in our study. Further study is required. Fourth, further study is required to transfect the two variants of -308 in cell models and test the effects on a reporter gene. This would link genetic observations to physiology.
## 5. Conclusions
In conclusion, we found that the G alleles of rs1800629 contributed to PE and no allele roles of rs361525 were found in PE in a Taiwanese Han population. The results of our study are totally different to several previous Iranian studies [21,23,25,47] with some similarity to an UK study [6]. Further studies are required to confirm the roles of rs1800629 and rs361525 in PE with circulating TNF-α in PE.
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|
---
title: miR-4432 Targets FGFBP1 in Human Endothelial Cells
authors:
- Roberta Avvisato
- Pasquale Mone
- Stanislovas S. Jankauskas
- Fahimeh Varzideh
- Urna Kansakar
- Jessica Gambardella
- Antonio De Luca
- Alessandro Matarese
- Gaetano Santulli
journal: Biology
year: 2023
pmcid: PMC10045418
doi: 10.3390/biology12030459
license: CC BY 4.0
---
# miR-4432 Targets FGFBP1 in Human Endothelial Cells
## Abstract
### Simple Summary
The inner layer of blood vessels is formed by endothelial cells. When these cells do not work properly, several issues ensue in the human body. One of these issues is elevated blood pressure, also known as hypertension, which is an established risk factor for ischemic heart disease, stroke, chronic kidney disease, and dementia. However, the exact mechanisms linking dysfunctional endothelium and hypertension are not fully defined. In this work, we discovered that a small nucleic acid (miR-4432) is able to target and inhibit a specific gene (fibroblast growth factor binding protein 1, FGFBP1) in human brain microvascular endothelial cells, and we demonstrate for the first time that this miR-4432 significantly reduces endothelial oxidative stress, a well-established feature of hypertension. Taken together, our findings provide unprecedented mechanistic insights and open the field to new studies aimed at ameliorating endothelial dysfunction by harnessing miR-4432-based strategies.
### Abstract
MicroRNAs (miRs) are small non-coding RNAs that modulate the expression of several target genes. Fibroblast growth factor binding protein 1 (FGFBP1) has been associated with endothelial dysfunction at the level of the blood–brain barrier (BBB). However, the underlying mechanisms are mostly unknown and there are no studies investigating the relationship between miRs and FGFBP1. Thus, the overarching aim of the present study was to identify and validate which miR can specifically target FGFBP1 in human brain microvascular endothelial cells, which represent the best in vitro model of the BBB. We were able to identify and validate miR-4432 as a fundamental modulator of FGFBP1 and we demonstrated that miR-4432 significantly reduces mitochondrial oxidative stress, a well-established pathophysiological hallmark of hypertension.
## 1. Introduction
Hypertension is a leading risk factor for ischemic heart disease, stroke, chronic kidney disease, and dementia [1]. It is a multifactorial disease involving interactions among genetic, environmental, demographic, vascular, and neuroendocrine factors [2,3]. Endothelial dysfunction is an established hallmark of hypertension [4,5,6]; however, the exact molecular mechanisms linking dysfunctional endothelial cells (ECs) and high blood pressure are not fully understood. Several genome-wide association studies (GWAS) have identified a number of genes associated with hypertension [7,8], but only a few of these genes have been functionally validated. In 2019, the International Consortium of Antihypertensive Pharmacogenomics Studies (ICAPS) recognized fibroblast growth factor binding protein 1 (FGFBP1) as one of the genes involved in the regulation of blood pressure [9]. FGFBP1 is a key promoter of the development of the blood–brain barrier (BBB) [10], an aspect that is especially relevant considering that ECs are a major component of the BBB [11], which is crucial for maintaining neuronal and glial function [12]. Specifically, FGFBP1 has been implied in refining and maintaining barrier characteristics in the mature BBB endothelium [13].
MicroRNAs (miRs) are a relatively well conserved group of small (~21 nucleotides) non-coding RNAs that modulate the expression of their target genes: miRNAs can bind the 3′ untranslated region (UTR) of specific genes, thereby inhibiting their expression. Thus, miRNAs have been involved in numerous pathological and physiological processes [14,15]. Others and ourselves have, in the last decades, identified a variety of miRs involved in the regulation of endothelial function [16,17].
Since FGFBP1 has been previously linked to the modulation of the BBB, and precisely to endothelial function, the central scope of the present study is to detect which miR can target FGFBP1 in hBMECs (human brain microvascular endothelial cells).
## 2.1. miR-4432 Targets FGFBP1 in a Conservative Manner
We applied bioinformatic analyses and functional experiments which led, for the first time to our knowledge, to the identification of hsa-miR-4432-3p (miR-4432) as a crucial modulator of FGFBP1 transcription, in a manner that is highly conserved across different species, including primates such as chimpanzee (Pan troglodytes), orangutan (Pongo abelii), macaque (Macaca mulatta), and gorilla (Gorilla gorilla), although it is not detected in mouse (Mus musculus) and rat (Rattus norvegicus), as shown in Figure 1.
Furthermore, we designed a mutant construct of FGFBP1 3′-UTR (“FGFBP1 MUT”) that harbors nucleotide substitutions at the level of the miR-4432 binding sites of FGFBP1 3′-UTR, as illustrated in Figure 2.
## 2.2. miR-4432 Regulates FGFBP1 Transcription in Endothelial Cells
We first verified that miR-4432 is actually expressed in two different types of endothelial cells, namely hBMECs, which remain the best in vitro model of the BBB [18], and human umbilical vascular endothelial cells (HUVECs), and that its expression is regulated by miR-4432 mimic and miR-4432 inhibitor, as shown in Figure 3.
Then, we performed a series of experiments in hBMECs to test whether miR-4432 is a regulator of FGFBP1 transcription. Through luciferase assays, we determined that FGFBP1 is a target of miR-4432 (Figure 4); these findings were also endorsed in HUVECs (Supplementary Figure S1).
## 2.3. FGFBP1 Expression Is Controlled by miR-4432
As depicted in Figure 5, we experimentally proved that miR-4432 significantly diminishes the mRNA expression of FGFBP1 in hBMECs.
These findings were then confirmed by immunoblot at the protein level (Figure 6), as well.
## 2.4. miR-4432 Regulates Mitochondrial Oxidative Stress in Human ECs
The next logical step was to gain more insights into the physiological and disease-related consequences of the interaction between miR-4432 and FGFBP1. *The* generation of mitochondrial reactive oxygen species (ROS) induced by the known vasoconstrictor angiotensin II (Ang II) in ECs [19] has been mechanistically implied in the pathogenesis of hypertension [20,21,22] and previous investigations have evidenced that the upregulation of FGFBP1 can increase oxidative stress signaling, leading to pro-hypertensive effects [23].
On these grounds, we quantified, by MitoSOX, the ROS production induced by Ang II in hBMECs transfected with miR-4432 mimic, miR-4432 inhibitor, or, as control, miR-scramble. Strikingly, we observed that mitochondrial oxidative stress was significantly reduced by miR-4432 mimic and increased by miR-4432 inhibitor (Figure 7).
To mechanistically prove the functional role of FGFBP1, we repeated the ROS quantification after the knock-down of FGFBP1, showing that in the absence of FGFBP1 there is no significant effect of miR-4432 (Figure 8).
## 3. Discussion
The experimental observation herein reported indicates that miR-4432 targets FGFBP1 in human ECs, representing a novel potential strategy against numerous diseases characterized by endothelial dysfunction, including hypertension [24,25,26,27,28,29].
Consistent with our results, hypertensive patients have been shown to have approximately 1.5- and 1.4-fold higher expression of FGFBP1 mRNA and protein compared to normotensive subjects [30], further corroborating the crucial role of FGFBP1 in the pathophysiology of hypertension.
A genetic polymorphism in the human FGFBP1 gene has been associated with a higher gene expression and an increased risk of familial hypertension [30]. Preclinical studies in spontaneously hypertensive rats substantiated a contribution of the FGFBP1 genomic locus to hypertension and to glomerular damage [31]. In addition, the induction of FGFBP1 in a transgenic mouse model resulted in sustained hypertension and increased vascular sensitivity to the vasoconstrictor angiotensin II (Ang II) via ROS and MAP kinase pathway signaling [23,32]. Taken together, these pieces of evidence indicate that FGFBP1 can finely control steady-state blood pressure, most likely by regulating vascular sensitivity to endogenous Ang II.
Another study explored the indirect relationship between FGFBP1 and miRs in human umbilical vein ECs, showing that miR-146a promotes angiogenesis by increasing FGFBP1 expression via targeting CREB3L1 (Cyclic AMP Responsive-Element-Binding Protein-3-Like 1) [33]. In agreement with these data, FGFBP1 has been shown to be significantly upregulated in the hemolytic uremic syndrome associated with human immunodeficiency virus (HIV-HUS), which is characterized by endothelial damage and microcystic tubular dilation [34,35]; furthermore, the inhibition of FGFBP1 was shown to be beneficial in preventing brain vessel damage triggered by acute kidney injury [32].
Intriguingly, FGFBP1 is also expressed in keratinocytes, infiltrating mononuclear cells, and Kaposi’s Sarcoma spindle cells [36,37]; its activation during the process of wound healing in the skin can induce angiogenic lesions that closely resemble Kaposi’s Sarcoma [36]. Equally importantly, FGFBP1 can promote hepatocellular carcinoma metastasis [38], and patients with pancreatic cancer who express higher FGFBP1 levels have been shown to have a worse prognosis [39].
So, FGFBP1 is generally considered an indicator of early stages of pancreatic and colorectal adenocarcinoma [40], and as a biomarker it is very useful in predicting bacillus Calmette–Guérin response in bladder cancer [41]. It has been shown to be significantly upregulated in early dysplastic lesions of the human colon as well as in primary and metastatic colorectal cancers, whereas its knock-down led to anti-proliferative effects [42,43,44]. Therefore, its targeting using miR-based approaches could also lead to novel strategies in oncology.
Last but not least, the FGF signaling pathway has been shown to be intimately involved in the regulation of the vascular tone, with important roles in a number of homeostatic processes including blood pressure regulation, inflammation, shock, and ischemia-reperfusion, as well as injury/repair situations involving the vasculature, nervous system and dermal wound healing [45,46], and it also affects vascular morphogenesis of pre-endothelial cells of the embryo [47]. One of the main limitations of our study is having performed just in vitro assays; however, the FGFBP1 targeting by miR-4432 was confirmed in two different cell types (i.e., hBMECs and HUVECs). Additional studies are necessary to confirm the effects of miR-4432 in the pathobiology of hypertension and other cardiovascular and cerebrovascular disorders.
In summary, we established that FGFBP1 is expressed in ECs and that miR-4432 finely controls its expression levels both at the mRNA and protein level.
## 4.1. Cells and Other Reagents
hBMECs were purchased from Neuromics (Catalog code number: HEC02; Minneapolis, MN, USA). HUVECs were purchased from ThermoFisher Scientific (Catalog code number: C0035C; Waltham, MA, USA). Cells were cultured at early passages (3–7) under standard conditions (37 °C, $5\%$ CO2), as previously described [48]. In some assays, the cells were transfected with pcDNA3.1-FGFBP1 plasmids obtained from GenScript (Piscataway, NJ, USA). All other reagents were obtained from Merck (Darmstadt, Germany).
## 4.2. Identification of miR-4432 as a Modulator of FGFBP1
To ascertain which miRs could specifically target the 3′-UTR of FGFBP1, we harnessed Target Scan Human 8.0, as reported previously [48]. The effects of miR-4432 on FGFBP1 gene transcription were assessed in hBMECs cells through a luciferase-reporter that contained the 3′-UTR of the predicted miR interaction site, in both the WT and mutated forms. The mutant of FGFBP1 3′-UTR (FGFBP1-MUT, see Figure 1 and Figure 2), which contained substituted nucleotides in the region of the predicted miR-4432 binding-site of FGFBP1 3′-UTR, was designed via the NEBase Changer and Q5-site-directed mutagenesis kit (New England-Biolabs, Ipswich, MA, USA) as previously reported [48].
Using Lipofectamine-RNAiMAX (Thermo Fisher Scientific), hBMECs were transfected ($66\%$ transfection efficiency) with 0.05 μg of the 3′-UTR plasmid as well as miR-4432 mimic (a chemically synthesized double-stranded RNA that mimics endogenous miR-4432, MedChemExpress, Monmouth Junction, NJ, USA) or miR-4432 inhibitor (a steric blocking oligonucleotide that hybridizes with mature miR-4432 and inhibits its function, IDT, Coralville, IA, USA), or a negative control (non-targeting scramble, IDT), reaching a final concentration of 50 nMol/L [48]. Utilizing the Luciferase-Reporter Assay System (Promega, Madison, WI, USA), we quantified Firefly-and-Renilla luciferase activities forty-eight hours after the transfection, as previously described [48]. In some experiments, endothelial cells were transfected with shRNA-FGFBP1 or shRNA-scramble (Origene, Rockville, MD, USA), following the manufacturer’s instructions. TaqMan microRNA Assays (Thermo Fisher Scientific) were used to quantify mature miR-4432 using U18 as endogenous control, as described in the literature [16]. FGFBP1 expression was assessed via RT-qPCR as previously reported [48], normalizing to glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The sequences of oligonucleotide primers (Merck, Darmstadt, Germany) are shown in Table 1.
## 4.3. Immunoblotting
Immunoblotting assays were performed as previously described and validated by our group [16,49]; the intensity of the bands was quantified using FIJI (“Fiji Is Just Image J”) software. The antibody for FGFBP1 was purchased from ThermoFisher Scientific (Catalog code number: PA5-77220); the antibody for β-Actin was purchased from abcam (Cambridge, MA, USA; Catalog code number: ab8229).
## 4.4. Mitochondrial ROS
Mitochondrial ROS generation was assessed using MitoSOX Red (catalog code number: #M36008; Thermo Fisher Scientific) in hBMECs cells treated with Ang II (400 nMol for 4 h), as previously described [50].
## 4.5. Statistical Analysis
All data were expressed as means ± standard error of the means (SEMs). The statistical analyses were carried out using GraphPad 9 (Dotmatics, San Diego, CA, USA). Statistical significance, set at $p \leq 0.05$, was tested using the non-parametric Mann–Whitney U test or a two-way ANOVA followed by Bonferroni multiple comparison test, as appropriate.
## 5. Conclusions
Taken together, our results indicate for the first time, to the best of our knowledge, that miR-4432 specifically targets the 3′UTR of FGFBP1, thereby representing a novel potential strategy against hypertension, cerebrovascular disease, and other disorders characterized by endothelial dysfunction.
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|
---
title: Hangover-Relieving Effect of Ginseng Berry Kombucha Fermented by Saccharomyces
cerevisiae and Gluconobacter oxydans in Ethanol-Treated Cells and Mice Model
authors:
- Eun Jung Choi
- Hyeongyeong Kim
- Ki-Bae Hong
- Hyung Joo Suh
- Yejin Ahn
journal: Antioxidants
year: 2023
pmcid: PMC10045427
doi: 10.3390/antiox12030774
license: CC BY 4.0
---
# Hangover-Relieving Effect of Ginseng Berry Kombucha Fermented by Saccharomyces cerevisiae and Gluconobacter oxydans in Ethanol-Treated Cells and Mice Model
## Abstract
This study aimed to evaluate the hangover relieving effect of ginseng berry kombucha (GBK) fermented with *Saccharomyces cerevisiae* and Gluconobacter oxydans in in vitro and in vivo models. The antioxidant activity and oxidative stress inhibitory effect of GBK were evaluated in ethanol-treated human liver HepG2 cells. In addition, biochemical and behavioral analyses of ethanol treated male ICR mice were performed to confirm the anti-hangover effect of GBK. The radical scavenging activity of GBK was increased by fermentation, and the total ginsenoside content of GBK was 70.24 μg/mL. In HepG2 cells, in which oxidative stress was induced using ethanol, GBK significantly increased the expression of antioxidant enzymes by upregulating the Nrf2/Keap1 pathway. Moreover, GBK (15 and 30 mg/kg) significantly reduced blood ethanol and acetaldehyde concentrations in ethanol-treated mice. GBK significantly increased the levels of alcohol-metabolizing enzymes, including alcohol dehydrogenase and acetaldehyde dehydrogenase. The balance beam test and elevated plus maze test revealed that high-dose GBK significantly ameliorated ethanol-induced behavioral changes. Collectively, GBK exerted a protective effect against ethanol-induced liver damage by regulating the Nrf2/Keap1 pathway.
## 1. Introduction
Alcohol absorbed into the body is metabolized to acetaldehyde and nicotinamide adenine dinucleotide (NADH) by alcohol hydrolase and alcohol dehydrogenase (ADH). Accumulation of acetaldehyde causes hangovers, which include symptoms such as headache, nausea, vomiting and diarrhea, accelerated liver toxicity, liver damage, and fat accumulation. NADH is oxidized to produce the reactive oxygen species (ROS) hydroxyl radical (•OH) and superoxide radical anion (O2•−), which induce oxidative damage and disrupt the antioxidant system [1]. Excessive production of ROS causes protein and DNA damage, cell death, tissue and organ damage, aging, and various diseases [2]. In addition, ethanol-induced oxidative stress in hepatocytes plays a key role in the development of alcoholic liver disease [3]. Therefore, the Nrf2 signaling pathway, which inhibits ROS generation and prevents lipid accumulation, is attracting attention for the development of drugs for alcoholic liver disease [4]. Acute alcohol intoxication reduces endogenous antioxidants in the liver, and Nrf2 signaling regulates the expression of these antioxidants and reduces oxidative stress [5]. Recently, many people have shown interest in natural plants and drinks that treat hangovers owing to an increase in income and quality of life [6]. Moreover, research is being conducted to identify liver-protective substances derived from natural products that are safe and have excellent antioxidant activity [7,8].
Ginseng fruit that is more than three years old exhibits antioxidant, cardiovascular disease-improving, and antidiabetic effects [9,10,11]. Ginsenosides, polyacetylenes, polysaccharides, proteins, and phenolic compounds are reportedly the main active substances in ginseng and ginseng berries. In particular, ginseng berries are known to have a higher content of ginsenosides, especially Re, than ginseng roots [9,12]. Many glycoside compounds that exist in nature exert a stronger effect when sugar is decomposed and converted into aglycon [13]. Ginsenosides and polyphenols, which are active compounds in ginseng berries, are mainly present as glycosides, and their activity increases when sugar is converted to aglycon, which is when sugar is decomposed or metabolites have fewer sugars [14,15]. It has been reported that the minor ginsenosides Rg2 and Rh1 protect against liver damage by inhibiting inflammation and apoptosis through the activation of the Nrf2 signaling pathway in LPS-stimulated Hepg2 cells [16]. Therefore, we attempted to increase the bioavailability of the active ingredients in ginseng berries by preparing ginseng berry kombucha (GBK) through fermentation by microorganisms. Kombucha is a beverage fermented with a symbiotic culture of bacteria and yeast (SCOBY) by adding sugar to green or black tea extracts [17]. Kombucha is known to promote detoxification and metabolism, and has recently begun to be widely consumed in the United States and Europe [18]. The fermentation metabolites and physiological activity of kombucha depend on the fermentation substrate, microorganisms in the SCOBY, additives, and fermentation method [19]. GBK was fermented by *Saccharomyces cerevisiae* M-5 isolated from candied ginseng and Gluconobacter oxydans isolated from commercial kombucha. It has been reported that S. cerevisiae M-5, a β-glucosidase-producing strain, is involved in the conversion of ginsenosides and polyphenols, which are the active compounds in ginseng berries. Therefore, GBK fermented with a strain with β-glucosidase activity is expected to have higher antioxidant and hepatoprotective effects than commercially available kombucha.
Previous studies have reported the activity and isolation of a symbiotic community of acetic acid bacteria and osmophilic yeast involved in kombucha production [20]. In addition, a large number of studies have been conducted on physical processing and bioconversion to convert major ginsenosides present in ginseng to minor ginsenosides [21]. This study aimed to develop a functional beverage and analyze its functionality by producing kombucha and converting ginsenosides using two separate strains. The purpose of this study was to investigate the effects of GBK against ethanol-induced liver damage in HepG2 cells and animal models of hangover. In particular, the hepatoprotective and antioxidant effects of GBK in ethanol-treated HepG2 cells were investigated. In addition, behavioral changes, blood ethanol concentration, levels of toxic intermediate metabolites, and activity of alcohol-metabolizing enzymes in a hangover-induced mouse model were analyzed. The study clarifies the biochemical hangover-relieving activity of GBK and may aid in the development of functional hangover-relieving drinks.
## 2.1. GBK Preparation
Ginseng berries were purchased from a ginseng farm in Goesan-gun (Republic of Korea). GBK fermentation was performed according to previous studies [22]. Ginseng berry medium (GBM) containing raw ginseng berries (20 g), sucrose (2 g), ascorbic acid (0.02 g), and $0.54\%$ black tea infusion (20 mL) was sterilized. Sterilized GBM was inoculated with S. cerevisiae M-5 and G. oxydans at $5\%$ concentration and incubated at 30 °C for 18 d. S. cerevisiae M-5 was isolated from sugar-preserved ginseng with high β-glucosidase activity; G. oxydans is an acetic acid-producing strain isolated from commercial Kombucha. Both isolated strains are stored in the Nutraceuticals laboratory at Korea University (Seoul, Republic of Korea). The resulting fermented GBK was filtered through a Whatman No. 5 filter and freeze-dried for use in the experiment.
## 2.2. Analysis of Radical Scavenging Activity of Fermented GBK
To measure the antioxidant activity of GBK, 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activities were measured as previously described [23]. The scavenging activity of GBK is expressed as the IC50 value, which is the concentration at which radical generation is reduced by $50\%$.
## 2.3. Analysis of the Content of Ginsenosides in GBK
The ginsenoside content was measured using high-performance liquid chromatography (HPLC, Agilent Technologies, Santa Clara, CA, USA). The conditions used for HPLC analysis were as follows: column, Cadenza CD-C18 (75 × 4.6 mm, 3 μm particle size); UV wavelength, 203 nm; flow rate, 1.2 mL/min; injection volume, 5 μL; and column temperature, 40 °C. For the separation of ginsenosides, $10\%$ and $90\%$ acetonitrile were used as mobile phases with the following gradient conditions: 90–$76\%$:10–$24\%$ (0–44 min), 76–$60\%$:24–$40\%$ (44–56 min), 60–$50\%$:40–$50\%$ (56–79 min), 50–$90\%$:50–$10\%$ (79–82 min), and $90\%$:$10\%$ (82–85 min).
## 2.4. Cell Culture
The human liver cell line HepG2 was purchased from the Korea Cell Line Bank (Seoul, Republic of Korea). HepG2 cells were cultured in a CO2 incubator ($5\%$ CO2, 37 °C; Thermo Fisher Scientific, Cleveland, OH, USA) in Dulbecco’s modified Eagle’s medium (Welgene, Seoul, Republic of Korea) supplemented with $10\%$ fetal bovine serum and $1\%$ penicillin/streptomycin.
## 2.5. Cell Viability Assay
To examine the effect of ethanol treatment on cell viability, HepG2 cells were seeded in a 96-well plate at a density of 1 × 105 cells/mL and cultured for 24 h. The cells were treated with ethanol at different concentrations (25, 50, 100, 200, 500, and 750 mM) for 24 h, then the cell viability was measured using a Quanti-Max™ WST-8 Cell Viability Assay kit (BIOMAX, Seoul, Republic of Korea). In addition, to evaluate the protective effect of GBK against ethanol-induced cell damage, the cells were treated with different concentrations of GBK (40, 60, and 80 μg/mL) added with 600 mM ethanol and then subjected to the WST-8 assay.
## 2.6. mRNA Expression Analysis of Genes Related to Oxidative Stress and Alcohol Metabolism
HepG2 cells were seeded into 6-well plates at a density of 1 × 105 cells/mL, cultured for 24 h, then treated with different concentrations of GBK (40, 60, and 80 μg/mL). After treating the cells with GBK added with 600 mM ethanol for 24 h, total RNA was extracted using TRIzol reagent and a quantitative real-time polymerase chain reaction (qRT-PCR) was performed according to a previously described method [24]. The expression of the following genes was analyzed: catalase (CAT, NM_001752.4), superoxide dismutase 1 (SOD-1, NM_000454.4), glutathione peroxidase 1 (Gpx, NM_000581.4), nuclear factor erythroid 2–related factor 2 (Nrf2, NM_001145412.3), kelch-like ECH-associated protein 1 (Keap1, NM_012289.4), alcohol dehydrogenase (ADH, NM_000668.6), aldehyde dehydrogenase (ALDH, NM_000689.5), cytochrome P450 2E1 (CYP2E1, NM_000773.4), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH, NM_001256799.3). GAPDH was used as an endogenous control.
To analyze the expression of proteins related to Nrf2/keap1 signaling, HepG2 cells were lysed using RIPA buffer (Abcam, Cambridge, MA, USA) and the supernatant was collected using centrifugation (10,000× g, 10 min, 4 °C). Protein concentration in the supernatant was measured using the BCA Protein Quantification kit (BIOMAX), and western blotting was performed as described previously [25] after adjusting the amount of protein to 40 μg. All antibodies used in the experiment were purchased from Cell Signaling Technology (Beverly, MA, USA) and diluted 1:1000 in $5\%$ skim milk. Antibodies against the following proteins were used: GAPDH (#5174), Nrf2 (#12721), Keap1 (#4678), heme oxygenase-1 (HO-1, #5853), and anti-rabbit IgG, HRP-linked antibody (#7074).
## 2.7. Malondialdehyde (MDA) Assay
HepG2 cells were seeded into 6-well plates at a density of 1 × 105 cells/mL, cultured for 24 h, then treated with different concentrations of GBK (40, 60, and 80 μg/mL). After treating the cells with GBK added with 600 mM ethanol for 24 h, cell supernatant was collected and MDA content was measured using the OxiTec™ TBARS (Lipid Peroxidation) Assay kit (BIOMAX) according to the manufacturer’s instructions.
## 2.8. Animals
Six-week-old (25–30 g) male ICR mice were purchased from Orient Bio (Seongnam, Republic of Korea) and acclimatized for one week in a room with a 12 h light/dark cycle, a temperature of 22 ± 3 °C, and relative humidity of 40–$60\%$. During the adaptation period, a normal diet (Altromin 1310, Altromin, Lage, Germany) was provided along with ad libitum access to sterilized water. Thirty mice were randomly assigned to five groups ($$n = 6$$/group): normal group (oral physiological saline administration), control group (ethanol and physiological saline administration), KL group (ethanol and a low concentration (15 mg/kg) of GBK administration), and KH group (ethanol and a high concentration (30 mg/kg) of GBK administration). Mice in all groups, except the normal group, were treated with ethanol. After 30 min of GBK or physiological saline administration, 2 mL/kg of $25\%$ ethanol was orally administered [26]. Blood was collected from the hepatic portal vein 0.5, 1, and 2 h after oral administration of ethanol. Serum was obtained using centrifugation at 2800× g and 5 °C. Mice were anesthetized with CO2 and dissected to remove liver tissues, which were rapidly frozen, stored at −70 °C, and used for analysis. Animal experiments were approved by the Korea University Institutional Animal Care and Use Committee (KUIACUC-2022-0037).
## 2.9. Analysis of Blood Ethanol and Acetaldehyde Concentrations
After ethanol administration, blood was collected at different times (0.5, 1, and 2 h after administration) and centrifuged at 1800× g for 10 min to obtain serum. Then, ethanol and acetaldehyde concentrations were measured using an Ethanol Assay kit (BIOMAX) and Aldehyde Assay kit (Biovision, Mipitas, CA, USA), respectively.
## 2.10. Analysis of ADH and ALDH Activities in the Liver Tissue
ADH and ALDH activities in the liver tissue were determined. Briefly, the liver tissue was washed three times with phosphate-buffered saline, mixed with a volume of 0.1 M Tris-HCl buffer (pH 7.4) 10 times the tissue weight (g) and homogenized with a glass-Teflon grinder under ice cooling. The homogenate was centrifuged at 2600× g for 10 min to obtain the supernatant. The ADH and ALDH activities of the supernatant were measured using an Alcohol Dehydrogenase Assay kit (Abcam, Cambridge, UK) and ALDH Activity Assay kit (Abcam), respectively, and the calculation formulas provided in each kit.
## 2.11. Analysis of Serum AST, ALT, Glucose, and LDH Levels
Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), glucose (Glu), and lactate dehydrogenase (LDH) levels were analyzed using an automatic biochemical analyzer (DRI-CHEM 3500i, Fujifilm, Co., Tokyo, Japan).
## 2.12. Behavioral Analysis Following Ethanol Administration
In the balance beam test (BBT, Figure S1), the beam apparatus consisted of a 1 m wooden beam with a flat surface of 12 mm width and placed on a table at a height of 50 cm using two pillars [27]. A black box was placed at the end of the beam as the finish point, and a 60-watt bulb was installed to illuminate the start point. To adapt the mice to the balance beam, the test was conducted 3 times a day for 5 days. On the day of the experiment, GBK and ethanol were orally administered and the time required for the mice to reach the 80 cm mark was measured. Behavioral analysis was conducted using a timer and video camera.
The elevated plus maze (EPM; Figure S1) test was performed to assess anxiety. The apparatus was made of black acrylic and consisted of two open branches facing each other in the form of a cross and two branches blocked on all sides [28]. This cross maze was installed at a height of approximately 50 cm from the floor, a video camera was placed on the central ceiling to record the animals’ behavior, and the light intensity was adjusted to 20 lx. At the beginning of the experiment, the mice were placed on the open arm of the maze with their heads facing out and allowed to freely explore the maze. Behavior was observed for 5 min, and then the time the mice stayed on the open and closed arms, number of entries and exits from each arm, and total moving distance were measured using the EthoVision program (Noldus Information Technology, Wageningen, The Netherlands).
## 2.13. Statistical Analysis
Experimental data of the in vitro tests are represented as mean and standard deviation, and data of the in vivo tests are represented as mean and standard error of the mean (SEM). Statistical significance between the groups and the average were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple test using SPSS (version 10.0; SPSS Inc., Chicago, IL, USA). The level of significance was set at $p \leq 0.05.$
## 3.1. Fermentation-Mediated Changes in Radical Scavenging Activity and Ginsenoside Content
During GBK fermentation, IC50 values for ABTS and DPPH radical scavenging tended to decrease as fermentation progressed (Figure 1). On day 12 of fermentation, the IC50 values for ABTS (8.12 mg/mL) and DPPH (3.89 mg/mL) radical scavenging were the lowest ($p \leq 0.05$) than before fermentation.
As shown in Table 1, the total ginsenoside content of GBK was 70.24 μg/mL. The ginsenosides found in GBK were Rh1, Rg2 (Rg2s and Rg2r), Rg3 (Rg3s and Rg3r), and Re at concentrations 16.81, 12.63, 9.10, and 8.03 μg/mL, respectively. It seems that ginsenosides contained in GBK are the primary substances that remove radicals.
## 3.2. Effect of GBK on the Viability of Ethanol-Treated HepG2 Cells
Figure 2a shows the survival rate of HepG2 cells after ethanol treatment. Ethanol treatment decreased HepG2 cell viability in a concentration-dependent manner. In particular, when the ethanol treatment concentration was 600 mM or more, the cell viability was less than $80\%$ compared to the NOR group ($p \leq 0.001$). Therefore, cells were treated with 600 mM ethanol to induce oxidative stress.
As a result of measuring the effect of GBK on ethanol-induced hepatocellular damage (Figure 2b), the survival rate was found to be significantly increased by GBK in a concentration-dependent manner when compared to that of control cells treated only with ethanol ($p \leq 0.001$). Treatment with 80 μg/mL GBK showed cell viability of approximately $88\%$. Taken together, GBK exhibited hepatoprotective effects against ethanol-induced cell damage.3.3. Effects of GBK on Oxidative Stress Elimination and Alcohol Metabolism-Related Gene Expression in Ethanol-Treated HepG2 Cells.
Treatment with 600 mM of ethanol significantly increased the production of MDA, an intracellular lipid oxidation product, in HepG2 cells ($p \leq 0.001$). On the contrary, treatment with GBK significantly decreased the production of MDA in a concentration-dependent manner ($p \leq 0.001$; Figure 3a). The expression of antioxidant enzymes related to the removal of oxidation products and ROS was significantly increased by ethanol treatment when compared to normal cells ($p \leq 0.05$ and $p \leq 0.001$, respectively; Figure 3b–d). GBK treatment significantly increased the expression of Cat ($p \leq 0.01$ and $p \leq 0.001$, respectively), Sod-1 ($p \leq 0.001$), and Gpx ($p \leq 0.05$ and $p \leq 0.001$, respectively) when compared to control cells in a dose-dependent manner. The ethanol-induced increase in MDA production seemed to be suppressed by GBK-induced increase in CAT, SOD-1, and GPx expression. In addition, we analyzed the expression of genes related to the Nrf2/Keap1 signaling pathway, which is the main signaling pathway that regulates the intracellular oxidation reaction (Figure 3e,f). The expression of the Nrf2 and keap1 genes in the GBK (60, and 80 μg/mL)-treated group was significantly different from that in the control cells ($p \leq 0.05$ and $p \leq 0.001$, respectively).
As a result of examining the mRNA expression level of factors related to alcohol metabolism, the expression of ADH and ALDH increased significantly when compared to normal cells due to ethanol treatment ($p \leq 0.001$; Figure 3g,h). On the other hand, GBK significantly increased the expression of ADH and ALDH in a dose-dependent manner when compared to control cells ($p \leq 0.01$ and $p \leq 0.001$, respectively). In addition, ethanol treatment significantly increased the expression of CYP2E1 when compared to normal cells ($p \leq 0.001$; Figure 3i). GBK (60, and 80 μg/mL) treatment group significantly decreased CYP2E1 expression when compared to control cells ($p \leq 0.05$ and $p \leq 0.001$, respectively).
## 3.3. Effects of GBK on Oxidative Stress Elimination-Related Protein Expression in Ethanol-Treated HepG2 Cells
GBK treatment increased the expression of Nrf2 ($p \leq 0.001$) and decreased the expression of Keap1 ($p \leq 0.001$) in a concentration-dependent manner when compared to the control group (Figure 4). Moreover, the protein expression of Nrf2 and HO-1, which was decreased in the ethanol-treated group, was significantly increased in HepG2 cells by GBK treatment ($p \leq 0.01$, $p \leq 0.05$, and $p \leq 0.001$, respectively). However, GBK (80 μg/mL) treatment significantly reduced Keap1 protein expression, which was increased by ethanol treatment ($p \leq 0.05$). Collectively, GBK exhibited a protective effect against liver damage caused by ethanol-induced oxidative stress by increasing the expression of antioxidant enzymes through the activation of the Nrf2/Keap1 signaling pathway.
## 3.4. Effects of GBK on Ethanol and Acetaldehyde Concentrations in the Blood of Ethanol-Treated Mice
GBK was administered at low (KL, 15 mg/kg) and high (KH, 30 mg/kg) doses, and after 30 min, $25\%$ ethanol was orally administered. After 0.5, 1, and 2 h, blood ethanol and acetaldehyde concentrations were measured (Figure 5). Compared to the normal group, blood ethanol concentration (%) rapidly increased until 30 min after ethanol administration and then slowly decreased, whereas the concentration of acetaldehyde (%), an alcohol oxidation product, increased until 30 min after ethanol administration and remained high.
Oral administration of GBK suppressed ethanol-induced increase in blood ethanol and acetaldehyde concentrations. High-dose GBK administration (KH) significantly lowered blood ethanol concentration when compared to the control group ($p \leq 0.001$). After 1 h, the concentration of acetaldehyde was significantly lower in the KH group than in the control group ($p \leq 0.001$). The administration of GBK not only suppressed the increase in blood ethanol concentration, but also suppressed the increase in the concentration of acetaldehyde, the causative agent of hangover.
## 3.5. Effects of GBK on ADH and ALDH Activities in the Liver of Ethanol-Treated Mice
Figure 6 shows changes in ADH and ALDH enzyme activities in mouse livers after GBK administration. ADH is an enzyme that is primarily involved in alcohol metabolism and converts alcohol into acetaldehyde. The activity of ADH in the liver tissue increased until 30 min after ethanol administration but decreased thereafter (Figure 6a). Similarly, the activity of ALDH, which is involved in the decomposition of acetaldehyde, the hangover causative metabolite, rapidly increased until 30 min after ethanol administration and showed little change until 2 h (Figure 6b).
The KH group showed significantly higher ADH ($p \leq 0.01$ and $p \leq 0.001$, respectively) and ALDH ($p \leq 0.05$ and $p \leq 0.01$, respectively) enzymatic activities than the control group. On the other hand, ADH activity was significantly higher in the KL group than in the control group until 30 min after ethanol administration ($p \leq 0.01$) but decreased thereafter to the enzyme activity similar to that in the control group. Similarly, ALDH activity was significantly higher in the KL group than in the control group until 30 min and 1 h after ethanol administration ($p \leq 0.01$ and $p \leq 0.001$, respectively). GBK (30 mg/kg) increased the activity of the enzymes involved in the degradation of alcohol and acetaldehyde.
## 3.6. Effects of GBK on AST, ALT, and LDH Levels in the Blood of Ethanol-Treated Mice
Table S1 shows GBK-induced changes in AST, ALT, glucose, and LDH levels in the blood of ethanol-treated mice. Serum levels of AST and ALT, which are used as indicators of liver damage, rapidly increased until 30 min after ethanol administration, but decreased thereafter. Contrarily, AST level after 30 min of ethanol administration was significantly lower in both the KL and KH groups than in the control group ($p \leq 0.001$). Serum ALT levels were significantly decreased ($p \leq 0.01$) only in the KH group. However, no significant differences were observed in AST, ALT, glucose, and LDH levels 1 and 2 h after ethanol administration (Table S1). The reduction in ALT and AST levels by oral GBK administration demonstrates an inhibitory effect of GBK on ethanol-induced liver damage.
## 3.7. Effects of GBK on Ethanol-Induced Behavior
The behavior of mice after ethanol administration was analyzed using BBT and EPM tests. Using BBT, the difference in the time taken to reach the 80 cm mark on the beam before and after ethanol administration was measured (Figure 7a). The difference in time to reach the 80 cm mark 30 min after ethanol administration increased by 1.2 s in the control group but increased by 0.32 s and 0.01 s when administered with KL and KH, respectively. Additionally, the number of times the foot slipped before reaching the destination was counted 30 min after ethanol administration (Figure 7b). Ethanol administration significantly increased the number of foot slips ($p \leq 0.001$), but it was significantly decreased compared to the control group due to GBK (15 and 30 mg/kg) administration ($p \leq 0.001$).
The EPM test was used to measure the time spent in open and confined spaces to analyze the behavior of mice in terms of exploring new environments and avoiding bright light and open spaces. After 30 min of ethanol administration, control group mice spent significantly more time at the open arms ($p \leq 0.01$) compared to normal group mice (Figure 7c). When GBK was administered, the time spent at open arms was reduced in a concentration-dependent manner compared to the control group. In particular, KH group mice spent more than twice as much time in the open arms as control group mice ($p \leq 0.05$). Administration of GBK (30 mg/kg) minimized the behavioral changes caused by ethanol consumption.
## 4. Discussion
In the body, alcohol metabolism is regulated by enzymes, such as ADH, and a microsomal ethanol oxidation system, and generates free radicals that affect the antioxidant system [29]. In the liver tissue, alcohol-induced reduction in antioxidants leads to liver damage by an increase in lipid peroxidation and protein oxidative damage. Additionally, alcohol consumption induces the production of ROS during CYP2E1 pathway oxidation [30]. Cells reduce the production of ROS and suppress the accumulation of lipid peroxides in the body through enzymatic oxidative defense mechanisms, which include SOD, CAT, and Gpx. The expression of these antioxidant enzymes is regulated by the Nrf2/Keap1 signaling pathway; through the activation of Nrf2, the expression of antioxidant enzymes is increased to suppress oxidative stress [31,32]. It has been reported that ginsenoside Rg1 prevents CCl4-induced acute liver damage by inhibiting oxidative stress and inflammatory responses through activation of the Nrf2 signaling pathway [33]. In this study, we found that GBK treatment effectively inhibited ethanol-induced oxidative stress by increasing the expression of antioxidant enzymes via the upregulation of the Nrf2/keap1 pathway.
Alcohol is converted to acetaldehyde by ADH in the body and then oxidized to acetic acid by ALDH, which is excreted as CO2 and in urine [34]. It is known that toxicity is caused not only by alcohol but also by acetaldehyde produced during alcohol metabolism [35]. Acetaldehyde is a highly toxic and reactive substance that causes alcohol-induced liver damage and is a major cause of hangovers [36]. AST and ALT activities are increased in damaged hepatocytes, and they are released from the liver into the blood. During alcohol-induced toxicity, AST and ALT are released and result in severe damage to liver tissue membranes [37]. Lee at al. [ 38] reported that ingestion of black red ginseng mixture in ethanol-administered SD-rats increased the activities of ADH and ALDH in the liver, thereby lowering the concentration of ethanol and acetaldehyde in the blood. In addition, in clinical studies, consumption of red ginseng drink lowered blood alcohol concentration 30 min after drinking and improved hangover symptoms [39]. Here, GBK was involved in relieving hangover by promoting ADH and ALDH activities in the liver and effectively reducing blood alcohol and acetaldehyde concentrations. During this process of ethanol metabolism, CYP2E1, a cytochrome enzyme, is activated and an oxidation reaction through CYP2E1 promotes excessive ROS production, resulting in liver damage [40]. Previous studies have reported an increase in oxidative stress by overexpression of CYP2E1 by ethanol treatment in Hepg2 cells [41]. Lee et al. [ 42] reported that administration of lactic acid bacteria in Hepg2 cells suppressed oxidative damage in the liver by inhibiting lipid peroxidation by CYP2E1 overexpressed with ethanol. Similarly, GBK reduced alcohol-induced oxidative stress by suppressing the expression of CYP2E1 and increasing the expression of antioxidant enzymes in Hepg2 cells (Figure 3).
Alcohol consumption affects the central nervous system and causes physiological and behavioral changes. Alcohol suppresses the functions of the central nervous system, including the suppression of excitatory neurons and inhibitory neurons [43]. Depending on the person, particularly differences in sensitivity to alcohol, excitatory behaviors are induced by the suppression of inhibitory neurons and sedative behaviors are induced by the suppression of excitatory neurons [44]. During the hangover state, decreased activity, temperature fluctuations, anxiety-like behaviors, and pain perception disorders appear [34]. Zhao et al. [ 45] reported that administration of Korean red ginseng extract improved ethanol-induced anxiety-related behaviors in SD-rats and inhibited the secretion of stress hormones such as corticosterone. In the present study, GBK administration minimized behavioral changes, as analyzed using BBT and EPM test 30 min after ethanol administration. GBK effectively decreased ethanol-induced behavioral changes by reducing hangover-causing metabolites through its antioxidant action.
The hangover-relieving effect of GBK appeared to be due to an increase in the content of polyphenols and ginsenosides during fermentation. Previous studies reported that polyphenol content in natural products, such as black tea, green tea, and ginseng berries, used in kombucha production is increased by the fermentation process, resulting in increased antioxidant activity [46,47]. Similarly, we found that fermentation increased the radical scavenging activity of GBK during fermentation (Figure 1). As the content of phenolic substances in the extract increases, the radical scavenging activity of ABTS and DPPH increases, and the radical scavenging activity is affected by the content of hydrophilic or hydrophobic substances contained in the sample [48]. In this study, GBK showed a higher DPPH radical scavenging activity than ABTS radical, but the trend according to fermentation time was similar. This difference in radical scavenging activity seems to be due to the various contents of ginsenoside contained in GBK. Our previous study confirmed that fermentation of ginseng berries by S. cerevisiae M-5 increased total polyphenol content, especially gallic acid, 3,4-dihydroxybenzoic acid, and chlorogenic acid. Chlorogenic acid and 3,4-dihydroxybenzoic acid, whose contents were increased during GBK fermentation, have been previously reported as antioxidants [49], and ginsenosides are also reportedly involved in the increased antioxidant activity [50]. In this study, the content of minor ginsenosides in GBK was also increased by the β-glucosidase activity of S. cerevisiae M-5 strain. β-Glucosidase cleaves the site at which the sugar chain is linked to the glycoside ginsenoside of red ginseng and converts it to the non-glycoside ginsenoside, thereby improving the absorption rate of ginsenoside [51]. GBK contains large amounts of Rh1 and Rg2 (Table 1). Rh1 and Rg2 are minor ginsenosides that can be converted from the major ginsenosides Re and Rg1, and biological conversion of ginsenosides appears to have occurred during GBK fermentation. Park et al. [ 52] demonstrated that Rg3 and Rh2 ginsenosides protected against alcohol-induced oxidative damage through the regulation of the MAPK pathway in mouse TIB-73 hepatocytes. In addition, it was reported that the ginsenoside Rg1 inhibits alcohol-induced liver fibrosis through the expression of antioxidant enzymes via the activation of the Nrf2 pathway [53]. The ginsenoside contained in GBK helps to remove radicals generated by alcohol, and it seems to have an effect on hangovers.
## 5. Conclusions
GBK effectively inhibited ethanol-induced oxidative stress and protected against hepatocyte damage through the upregulation of the Nrf2/keap1 signaling pathway. In addition, GBK administration suppressed ethanol-induced behavioral changes and regulated the activity of enzymes involved in alcohol metabolism to relieve hangover. Thus, GBK can be used as a hangover relieving drink. Moreover, it is necessary to verify the efficacy of GBK through clinical trials as well as additional studies to identify the interaction between the activity of enzymes involved in alcohol metabolism and the expected active ingredient of GBK using single ginsenoside compounds.
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|
---
title: 'Edible Seaweeds Extracts: Characterization and Functional Properties for Health
Conditions'
authors:
- Mariana Coelho
- Ana Patrícia Duarte
- Sofia Pinto
- Hugo M. Botelho
- Catarina Pinto Reis
- Maria Luísa Serralheiro
- Rita Pacheco
journal: Antioxidants
year: 2023
pmcid: PMC10045430
doi: 10.3390/antiox12030684
license: CC BY 4.0
---
# Edible Seaweeds Extracts: Characterization and Functional Properties for Health Conditions
## Abstract
Seaweeds are popular foods due to claimed beneficial health effects, but for many there is a lack of scientific evidence. In this study, extracts of the edible seaweeds Aramé, Nori, and Fucus are compared. Our approach intends to clarify similarities and differences in the health properties of these seaweeds, thus contributing to target potential applications for each. Additionally, although Aramé and Fucus seaweeds are highly explored, information on Nori composition and bioactivities is scarce. The aqueous extracts of the seaweeds were obtained by decoction, then fractionated and characterized according to their composition and biological activity. It was recognized that fractioning the extracts led to bioactivity reduction, suggesting a loss of bioactive compounds synergies. The Aramé extract showed the highest antioxidant activity and Nori exhibited the highest potential for acetylcholinesterase inhibition. The identification of the bioactive compounds in the extracts allowed to see that these contained a mixture of phloroglucinol polymers, and it was suggested that Nori’s effect on acetylcholinesterase inhibition may be associated with a smaller sized phlorotannins capable of entering the enzyme active site. Overall, these results suggest a promising potential for the use of these seaweed extracts, mainly Aramé and Nori, in health improvement and management of diseases, namely those associated to oxidative stress and neurodegeneration.
## 1. Introduction
Seaweeds have been an important dietary constituent in Asian countries such as China, Japan, and Korea [1]. In some regions of the world, the population is growing to reach a level where food production may not be sufficient to feed the population [2], therefore the demand for alternatives, whether for human consumption or industrial processing, has increased in recent decades [3]. Seaweeds are considered an abundant, rich and sustainable marine source of macro and micronutrients, and an alternative to animal or even synthetic products [3]. Furthermore, several seaweed compounds have been reported to be bioactive, thus providing beneficial health effects [2], with their bioactive compounds showing the potential to be used as ingredients, both in functional foods and in health and food supplements.
Regarding macronutrients, seaweeds are a good source of sulfated polysaccharides (15–$76\%$ dry mass), proteins (5–$47\%$ dry mass), including all the essential amino acids, and lipids (1–$5\%$ dry mass), such as polyunsaturated fatty acids [3,4]. Concerning micronutrients, seaweeds are a good source of lipid and water-soluble vitamins, namely A, B1, B12, C, D and E and minerals (7–$36\%$ dry mass), such as calcium, iron, magnesium, copper, and iodine [3,4,5]. Seaweeds are also a source of secondary metabolites such as polyphenols [1,3,4]. Although some of these compounds, especially the latter, have reported beneficial health effects, like antioxidant, antimicrobial, anti-inflammatory, anti-cancer, anti-diabetic, anti-hypertensive, anti-hyperlipidemic, and anti-obesity effects [6], there is an immense variety of seaweeds. Numerous reports concern individual species, and there are several reviews about these organisms. The widespread belief that seaweed products have the potential to treat or prevent most human conditions has been rising. However, often there is lack of the proof of concept for the claimed effects and no association of a particular species to the bioactivities, which are then assigned to the whole group.
Seaweeds are taxonomically classified into three main groups, brown seaweeds (phylum Ochrophyta), red seaweeds (phylum Rhodophyta), and green seaweeds (phylum Chlorophyta) [7].
Seaweed colors are associated with its pigment, such as chlorophyll for green, phycobilin for red, and fucoxanthin for brown seaweeds [3]. The compound content of each seaweed depends on the species, but also on other geographical and environmental factors, such as substrate firmness, exposure to ice and waves, salinity, wave force, light and competition between seaweeds [8,9]. For this work, three seaweeds commonly used in foods or supplements were chosen to be studied, and their composition and biological activities were compared to report on their given potential for health improvement and management of diseases, especially those associated with oxidative stress.
Eisenia bicyclis, traditionally known as Aramé, is a perennial brown seaweed [10] distributed along the mid-pacific coastlines of Korea and Japan [10]. This seaweed is used industrially to extract sodium alginate, and for consumption by the population of East Asia in soups and salads [11,12]. The main bioactive compounds reported for Aramé are phenolic compounds, and polysaccharides [13,14]. The most abundant phenolic compounds are phlorotannins (eckol and other phloroglucinol derivatives), which were reported to have various biological activities, namely anti-diabetic and antioxidant activities [15]. The most abundant polysaccharides seen to be present in Aramé were fucoidan and laminarin [14]. On *Ecklonia cava* [16] and Sargassum vulgare [17], other brown seaweeds, these polysaccharides were reported to have antioxidant activity and anti-inflammatory activity [16,17]. Nevertheless, to the best of our knowledge, there is no research about these type of activities for Aramé fucoidan.
Fucus vesiculosus, known as bladderwrack [18], is an edible brown seaweed of the rocky bottoms of the northern temperate coastal areas [19], used to make beverage infusions, in cooked dishes and soups, or sprinkled in salads [20]. In traditional medicine *Fucus is* used due to its high iodine content to treat gout and aid weight loss [21]. This seaweed has bioactive compounds such as phenolic compounds [22], and sulfated polysaccharides [23]. It also contains proteins, minerals, vitamins, fatty acids, sterols, dietary fiber, and iodine [20,24]. The phenolic compounds mostly present in this seaweed are phlorotannins [25], which have reported activities such as antioxidant [18], anti-diabetic, anti-inflammatory, anti-cancer, anti-obesity, anti-lipidemic, and anti-hypertensive [20,26,27,28]. Also, Fucus polysaccharides are fucoidan and laminarin [20]. The latter was reported to have anti-inflammatory, anticoagulant, antioxidant, anti-cancer, and hypolipidemic activity [29,30,31], but again for fucoidan from Fucus there are no reports.
Porphyra tenera, known as Nori, is a red seaweed considered the most valuable maricultured seaweed in the world, as it is one of the most popular edible seaweeds used in sushi and soups [32,33]. It is known to have major bioactive compounds phenolic compounds, sulfated polysaccharides, and peptides [34,35]. It is also a source of dietary fiber, essential fatty acids, vitamins, and minerals [36]. In Nori, phlorotannins were identified and described to exhibit antioxidant activity and protection against UV light [37,38]. Other bioactive compounds present in this seaweed are sulfated polysaccharides, called porphyrans, which are reported to have hypolipidemic, anti-cancer, and anti-inflammatory activities [39]. Other polysaccharides reported in red seaweeds, such as cellulose, xylans, and manans, are not water-soluble [40].
In this work, a novel approach was used. Three of the most consumed edible seaweeds, Aramé, Fucus, and Nori, were matched for the composition and biological activities associated to the aqueous extracts of the seaweeds. Though there are various reports about Aramé [13,14], Fucus [22,23,24], and Nori [34,35], individually there are no studies comparing their composition and beneficial health effects.
With this in mind, we herein report the characterization of aqueous extracts from the three seaweeds, obtained under the same conditions, and fractions of these extracts, enriched in different bioactive compounds classes from the three seaweeds. Their biological activities, namely the antioxidant activity and enzyme acetylcholinesterase (AChE) inhibition were investigated and compared in order to evaluate their potential against oxidative stress. In this work, reported for the first time is the capacity of Nori extracts to inhibit acetylcholinesterase, an enzyme associated to gastrointestinal motility and neurodegenerative diseases, as Alzheimer’s disease (AD). The comparison of the seaweeds extracts guided the association between the exhibited activities and their composition in bioactive compounds, supporting future exploration of targets for application. Additionally, the results herein reported may encourage the development of novel and natural products with the incorporation of these seaweeds into the diet, supplements, or functional foods, particularly to prevent oxidative stress. Oxidative stress is often associated to several diseases, such as cardiovascular diseases, metabolic conditions, and neurodegenerative disorders.
## 2.1. Seaweeds
Porphyra tenera was purchased from Flavers-International Flavours Shop® (Blue Dragon line, B#JS2039J01). While *Fucus vesiculosus* was collected from Tagus River (38.7822 N, 9.0913 W). The dry *Eisenia bicyclis* seaweed was purchased in a commercial surface from the Seara brand (B# T20220405, expiration date April 2022), as previously described in [13].
## 2.2. Chemical
All reagents and solvents were of analytical grade unless otherwise specified and used without further purification. Roswell Park Memorial Institute (RPMI-1640), Dulbecco’s Modified Eagle Medium (DMEM), trypsin and glutamine from Biowhittaker® Lonza. Fetal Bovine Serum (FBS) from Biowest, phosphate-buffered saline (PBS) were obtained from Corning (Corning, NY, USA). Antibiotic Antimycotic Solution 100 × (10,000 U/mL penicillin, 10 mg/mL streptomycin, and 25 μg amphotericin B/mL), reagent Folin & Ciocalteu, sodium acetate, 2,2-diphenyl-1-picyl-hydroxyl (DPPH), acetylcholinesterase (AChE) (149 U/mg solid, 241 U/mg protein), and acetycholine iodide (AChI) were obtained from Sigma®Aldrich (St. Louis, MO, USA). Calcium Carbonate, Concentrated Sulfuric Acid from Merck. Phloroglucinol from Aldrich® chemistry. Polygalacturonic acid and 5-5′-Dithiobis (2-nitrobenzoic acid) (DTNB) were purchased to Alfa Aesar (Ward Hill, MA, USA). Phenol and (4,5-dimetylthiazol-1-yl)-2,5-diphenyltetrazolium (MTT) were obtained from VWR (Radnor, PA, USA). Citric acid and Magnesium Chloride-6-hydrate were obtained from Riedel-de Haën (Seelze, Germany). Sodium Chloride was obtained from Panreac (Glenview, IL, USA).
## 2.3. Preparation of Seaweed Extracts
The dried and milled biomass of the seaweeds was used to prepare aqueous extracts. As the biomass of *Fucus vesiculosus* was collected in nature, it was subjected to an extensive washing procedure and further dried in an Heto® PowerDry LL3000 freeze dryer.
For the preparation of a dry mass of *Nori aqueous* extract, the biomass of *Porphyra tenera* was mixed with distilled water (20 g/L) and the suspension was autoclaved at 121 °C for 15 min. The suspension was filtered, frozen at −20 °C and freeze dried, to obtain the dry extract ($50\%$ g/g yield). The same procedure was performed to obtain a dry mass of *Fucus aqueous* extract, using 10 g/L biomass of *Fucus vesiculosus* ($38\%$ g/g yield). The procedure for obtaining a dry mass of Aramé aqueous extract using 33 g/L biomass of *Eisenia bicylis* ($66\%$ g/g yield) was already reported in a previous publication from our group [13].
## 2.4. Extract Fractioning by Solid Phase Extraction (SPE)
Solutions of the Aramé, Nori, and Fucus extracts were prepared by resuspending the extract dried mass in water to a concentration of 30 mg/mL, 15 mg/mL and 11.8 mg/mL, respectively, loaded into Sep-Pak C18 Plus Short Cartridge (360 mg sorbent per cartridge, 55–105 µm particle size, 50/pk), which had been pre-conditioned with methanol followed by water. One mL of the extract solution was loaded to the cartridge and then water 83 mL) and methanol (5 mL) were added, the procedure was repeated at least 3 times per cartridge, a total volume of 10 mL was used per extract solution. The fractions collected in water were frozen at −20 °C, freeze dried and named Aramé H2O, Nori H2O, and Fucus H2O. The fractions collected in methanol were evaporated and named Aramé MeOH, Nori MeOH, and Fucus MeOH.
## 2.5. Extracts and Fractions Characterization
The extract and fraction dried mass, obtained in Section 2.3 and Section 2.4, was dissolved in water to prepare solutions that were used for further quantifications and the biological activities assays, except for the cytotoxicity assays where the dried mass was dissolved in cells growth medium.
## 2.5.1. Quantification of the Total Phenolic Content (TPC)
The total phenolic content was determined according to the Folin-Ciocalteu method [41], and the results were expressed as mg of phloroglucinol equivalents (PGE) per mg of dry mass (phloroglucinol 0–0.06 mg·mL−1; R2 = 0.95), as the mean of triplicates. Briefly, 1350 μL water, 30 μL Folin-Ciocalteau reagent, 30 μL sample (extract, fraction, or standard phloroglucinol) solution, and 90 μL Na2CO3 ($2\%$ w/v) were kept in an orbital shaker for 1 h at 4 °C and, afterwards, the absorbance was measured at 760 nm in an UV-Vis Shimadzu spectrophotometer against a blank containing water instead of sample.
## 2.5.2. Quantification of the Total Proteins
For the quantification of total proteins, the 2-D Quant Kit from GE Healthcare® was used and the procedure was followed according to manufacturer instruction [42]. Bovine serum albumin (BSA) was used as standard to obtain a calibration curve (BSA 0–40 µg; R2 = 0.98) and the results were expressed in mg total proteins/mg dry mass, as the mean of triplicates.
## 2.5.3. Quantification of the Total Polysaccharides
The concentration of polysaccharides in the extracts and fractions was determined according to the phenol-sulfuric acid method, as described in [43]. The results were expressed as mg of polygalacturonic acid equivalents (PE) per mg of dry mass (polygalacturonic acid 0–0.2 mg·mL−1; R2 = 0.99), as the mean of triplicates. Briefly, 50 μL sample (extract, fraction, or standard polygalacturonic acid) solution, 150 μL concentrated sulfuric acid water, and 30 μL phenol solution ($5\%$ w/v) were incubated for 5 min at 90 °C. After cooling the absorbance was measured at 490 nm in a microplate reader TECAN Sunrise.
## 2.6.1. In Vitro Safety in Caco-2 and Hep-G2 Cells
Hepatocellular carcinoma cell line Hep-G2 (ECACC#85011430) and colorectal adenocarcinoma cell line Caco-2 (ECACC#86010202) were cultured in DMEM and RPMI-1640 medium, respectively, and supplemented with inactivated FBS $10\%$ (DMEM) or $20\%$ (RPMI-1640), antibiotic-antimycotic (100 U/mL penicillin-streptomycin and 0.25 μg amphotericin B), and 2 mM L-glutamine at 37 °C in an atmosphere with $5\%$ CO2. The medium was changed every 48–72 h, and cells were harvested before reaching confluence using PBS and 1x trypsin, and grown in the supplemented medium in 96-well microplates in an incubator with $5\%$ CO2 at 37 °C, until reaching $100\%$ confluence.
These cells lines were used because the seaweed extracts are a food product or food supplement. This type of food goes to intestine and liver, so the aim was to evaluate the cytotoxicity of the methanol fractions.
For the in vitro evaluation of the cytotoxicity of the extracts and fractions, the 3-(4.5-dimethylthiazol-2-yl)-2.5-diphenyltetrazolium bromide (MTT) method, described in [44] was used. The cell viability was evaluated after 24 h incubation, with 100 µL solutions of the extracts and fractions at the concentration of 0.5 and 1 mg dry mass/mL in growth media. After incubation, the solutions were replaced by 100 µL of 0.5 mg/mL MTT solution in culture medium and incubated at 37 °C, $5\%$ CO2 for 2 to 4 h. The formed formazan crystals were dissolved in 200 µL of methanol and the absorbance at 595 nm was registered against 630 nm (reference wavelength). For each solution, the percentage of growth inhibition/cytotoxicity was evaluated considering $100\%$ of viability for the absorbance of the control (cells incubated in the same conditions solely in growth media).
## 2.6.2. Antioxidant Activity
The antioxidant activity of the solutions of extract and fraction dry mass was measured using an adaptation of the DPPH method described in [44]. To 1 mL of $0.002\%$ w/v DPPH solution in methanol, 25 μL of sample solution was added and incubated for 30 min at room temperature. Afterwards, the absorbance of the mixture was measured at 517 nm and the percentage of antioxidant activity (%) was determined using Equation [1], where Abs 517 nm control is the absorbance at 517 nm of the blank DPPH solution with water instead of sample solution and Abs 517 nm *Sample is* the absorbance at 517 nm of the sample solution. The assays were carried out in triplicate. [ 1]%=100×Abs517 nm control−Abs517 nm sampleAbs517 nm control For the Aramé extract, which showed the highest antioxidant activity, the EC50 value was also calculated. EC50 is the concentration of the extract showing $50\%$ of DPPH-free radical scavenging activity, calculated by plotting the antioxidant activity for different concentration of the Aramé extract solutions.
## 2.6.3. AChE Inhibitory Activity
The inhibition of acetylcholinesterase (AChE) enzymatic activity was measured using the Ellman’s colorimetric method with some alterations [44]. Briefly, 325 μL of 50 mM Tris–HCl buffer (pH 8), 100 μL of the extract solution, and 25 μL of AChE (0.1 U/mL) in 50 mM Tris–HCl buffer pH 8 were incubated for 15 min. Subsequently, 75 μL of acetylthiocholine iodide (AChI) (0.023 mg/mL) and 475 μL of 3 mM 5,5′-dithiobis(2-nitrobenzoic acid) (DTNB) in Tris–HCl buffer (pH 8) containing 0.05 M NaCl and 0.021 M MgCl2 were added to initiate the reaction. The initial rate of the enzymatic reaction was quantified by measuring the absorbance at 405 nm for 5 min (V[compound]). A control reaction was carried out using water instead of the extract solution, and this initial rate was considered $100\%$ of the enzymatic activity, Vcontrol. The percentage of AChE inhibition (I) for the extracts was determined as the ratio of V[compound] and Vcontrol. All the assays were carried out in triplicate. The concentration of the extracts used was 1 mg/mL.
## 2.7. LC-HRMS/MS Extract Analysis
For the LC/HRMS analysis, a LiChrospher® 100 RP-18 (5 μm) LiChroCART® 250-4 mm column and a mobile phase constituted by a binary system of formic acid $0.1\%$ MeOH at a rate of 1 mL/min. The method used was as follows: 0 min $80\%$ formic acid $20\%$ MeOH; 20 min $20\%$ formic acid $80\%$ MeOH; 25 min $20\%$ formic acid $80\%$ MeOH; 30 min $80\%$ formic acid $20\%$ MeOH. High resolution mass spectra were acquired using negative ESI mode because the goal was to identify phenolic compounds that are majority found in this mode. The results were analyzed by the mass higher than 100 (m/z) and intensities around $100\%$. All the extracts were injected with a concentration of 1 mg/mL. Mass spectra were acquired, in the range of 120–1000 m/z and the mass spectrometer parameters were adjusted to optimize the signal-to-noise (S/N) ratio for the ions of interest. Briefly, the flow rates of nebulization and auxiliary gas (nitrogen) were 40 and 20 arbitrary units, the capillary temperature was set at 250 °C and the collision energies at 40 and 45 eV. For the analysis of the mass spectrometry results, DataAnalysis software developed by Bruker® (Darmstadt, Germany) was used.
## 2.8. Data Analysis
The software used for treatment was Microsoft® Excel (Microsoft Office 365) and the results were expressed as average ± standard deviation. Additional analysis of variance was carried out using one-way ANOVA for values comparison, difference between mean values were considered significant when $p \leq 0.05.$
## 3.1. Extracts and Fractions Characterization
Extracts were prepared by first performing a water extraction from Arame, Nori, and Fucus biomass. The extracts were fractionated using SPE in water and methanol to obtain MeOH and H2O fractions for each extract. Methanol, according to ICH Q3, is limited to 3000 ppm per day (Class 2) due to its inherent toxicity, and therefore it was completely evaporated to obtain a dried mass of the fractions [45]. For comparison, the same procedure was performed both for the extract and water fraction.
## 3.1.1. Quantification of the TPC
The results of the phenolic quantification of the Arame, Nori, and Fucus extracts, as well as its MeOH and H2O fractions, are shown in Figure 1. The extract showing higher TPC was Aramé, with 0.062 ± 0.005 mg PGE/mg dry mass [13]. However, the methanol fraction of Aramé showed the highest TPC per mg dry mass amongst all the analyzed samples. In the case of the water fraction of Nori, it was seen to have a low TPC below the detection limit. This behavior suggests a different composition of phenolic compounds for each seaweed extract, appearing to be mostly hydrophobic in the Nori extracts, and with the Aramé and Fucus extracts also having water-soluble phenolic compounds.
## 3.1.2. Quantification of Total Proteins
Proteins were found at low concentration in the Fucus extract (0.0074 ± 0.0004 mg/mg dry mass), being below the detection limit in all other samples.
Although seaweeds are considered a rich source of proteins, their aqueous extracts are not, as already reported for the Aramé extract [13]. This may be caused by the complex cell walls hampering protein extraction from the crude biomass [46] but also by the temperature used for biomass extraction, which causes protein denaturation.
## 3.1.3. Quantification of Total Polysaccharides
The results for polysaccharides quantification are shown in Figure 2, reported as mg of polygalacturonic acid equivalents (PE)/dry mass. In the case of the extracts, Nori showed the highest quantity and Aramé the lowest. Regarding Nori and Aramé extract fractions, these showed highest content of polysaccharides per mg dry mass. In the case of Nori, the fractions of methanol were enriched with these compounds, as were both fractions of Aramé, containing higher content in polysaccharides than the extract per mg dry mass. This was not the case with Fucus samples.
As mentioned, sulfated polysaccharides such as fucoidan have already been found in brown seaweeds and others, such as laminarin [47]. In the case of red seaweeds, porphyran is present in the cell walls of the red macroalgae Porphyra [48].
## 3.2.1. In Vitro Safety of Seaweed Extracts in Caco-2 and Hep-G2 Cells
As the seaweed extracts and their fractions may contain some compounds at very high concentration, the safety of these was addressed to eliminate concerns regarding hepatic toxicity or intestinal damage associated either to the dose or to the type of compounds present. Liver (Hep-G2) [49] and intestinal epithelial cells (Caco-2) [50] were used to evaluate the safety of the extracts and fractions for consumption. Hep-G2 cell line is widely accepted by regulatory agencies for medicines and food supplements to assess liver toxicity. The same applies for the Caco-2 cell system, a well characterized intestinal in vitro model with morphologic resemblance to intestinal epithelia.
According to the literature and ISO 10993, extracts or mixtures of compounds are considered not to be toxic to humans if its IC50, the concentration of extract to reduce $50\%$ cell viability, is above a concentration of 0.1 mg/mL [51].
As can be seen in Figure 3 and Figure 4, both liver (Hep-G2) and intestine (Caco-2) cell viability against extract and fraction concentrations of 0.5 and 1 mg/mL, during 24 h, was always above this threshold. Thus, it can be concluded that the seaweed extracts and fractions obtained are not cytotoxic, which was relevant to evaluate before proceeding to other stages of the work. For Fucus only the extract was tested due to the consistent low compounds content in the previous trials.
## 3.2.2. Antioxidant Activity
The antioxidant activity of the seaweed extracts and fractions are shown in Table 1. For the Aramé extract, the antioxidant activity for 0.25 mg/mL was 65 ± $3\%$ [13], and an EC50, the concentration of the extract for achieving $50\%$ antioxidant activity, of 0.174 mg/mL was obtained. Nori samples showed the lowest antioxidant activities.
For Aramé and Fucus, the antioxidant activity of the seaweed extracts was significantly higher than for the corresponding fractions, although, as seen previously, some of these fractions had higher TPC or polysaccharides per mg of dried mass relative to the extract. Evidently, the synergy of compounds in the extract mixture is an important feature of the exhibited antioxidant activity, as already seen in other cases [52]. As a result, only the extracts were analyzed for their capacity to inhibit acetylcholinesterase (AChE) enzyme.
## 3.2.3. AChE Inhibitory Activity
AChE enzyme inhibition by the extracts was evaluated and the results are shown in Figure 5 for 1 mg dry mass/mL solutions of the extract. Though all the extracts showed a mild capacity to inhibit this enzyme, the highest value of inhibition was obtained for the Nori extract (28 ± $2\%$). Therefore, this suggests that the compounds in the Nori extract may be seen as a promising natural option for increasing gastrointestinal motility, when included in diet, or to ameliorate neurodegenerative disorders, as AD, as AChE inhibition is the target for pharmacological treatment of this disease.
## 3.3. LC-HRMS/MS Extracts Characterization
The characterization of the compounds present in the extracts was performed using liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS/MS).
The chromatographic profiles of the samples were compared, and between the extracts at the same concentration some of the m/z peaks differed in intensity, and other peaks were only present in some of the extracts. The chromatograms were obtained in positive and negative modes, but only the negative mode is presented here (Supporting Information-Figure S1). The compounds were tentatively identified based on the MS fragmentation patterns, literature sources [8,53,54], molecular masses, and predicted molecular formula (Table 2). Assuming that in phlorotannins with ether bonds, such as phloroethols or eckols, fragmentation can occur on either side of the ether bond of the attached phloroglucinol units, the expected MS/MS spectra of these compounds often present [M-H]− at m/z 125, 141, and 110, corresponding to phloroglucinol, tetrahydroxy benzene, or resorcinol, as well as their combination with additional phloroglucinol, for example m/z 233, corresponding to two phloroglucinol units [53,54]. In the case of eckols, due to the presence of dibenzodioxin structures, the MS/MS spectra of compounds may present an [M-H]− at m/z 261 corresponding to fragmentation of the ether bonds linking these structures to phloroglucinol units. All these [M-H]− 125, 139, 111, 233, and 261 were seen in the MS fragmentation pattern for compounds m/z 575 and 596, and therefore these two compounds were tentatively assigned as eckol derivatives.
The m/z 265 was tentatively identified as a fuhalol derivative, corresponding to a tetrahydroxy benzene and its combination with phloroglucinol [53,54].
Finally, considering the MS fragmentation patterns of m/z 325, 311, and 339, and that in fucols, having only C-C bonds between its phloroglucinol units, is more likely to occur cross-ring cleavages [53,54], as well as their combinations with additional phloroglucinol, (e.g., [M-H]− at m/z 165), and/or with water moieties (e.g., [M-H]− at m/z 183), it is suggested that these phloroglucinol derivatives could be fucol type phlorotannins.
A heatmap representing the variation of the intensity of the tentatively assigned compounds between the extracts was also obtained to better understand the differences between the extracts (Table 2). In the extracts, several phlorotannins derivatives, such as eckol, fuhalol, and other phloroglucinol derivatives, were tentatively identified. Additionally, in the Fucus extracts, citric acid and glycidil compound were identified by comparing with those previously identified in our previous work [8,55].
Regarding phlorotannins, amongst the extracts, the Aramé extracts showed the highest intensity peak of m/z 575, and this was tentatively identified as an eckol derivative. This and other eckol derivatives were not detected in the other extracts. The Nori extract showed the highest intensity peaks for lower molecular weight phlorotannins, tentatively assigned as fucol type phloroglucinol derivatives, m/z 325, 311, and 339. These had lower intensity in the Aramé extract and were not detected in the Fucus extract. In the case of the Fucus compounds, the highest intensity was detected with m/z 265, proposed as a fuhalol derivative. This compound was also seen to be present in other Fucus extracts [8,53].
As previously seen, the highest activities were dependent on the extract; antioxidant activity was better for the Aramé extract and the Nori extract showed the highest capacity to inhibit AChE. This seems to indicate that higher molecular weight compounds, suggested as eckol derivatives in the Aramé rich extract, may be important for antioxidant activity. These, synergistically with lower molecular weight fucol type phloroglucinol derivatives, may explain the highest antioxidant activity achieved in this extract. On the other hand, these lower weight phlorotannins may well be also associated to the AChE inhibitory activity of the Nori extract. These smaller structures will be more prone to fit inside the enzyme’s active site. It is well known that AChE is inhibited by compounds having phenolic moieties in their structure due to the establishment of π–π interactions at the active site [56] and this may be the case for phlorotannins. However, the unit of phlorotannins, phloroglucinol, was used as standard and assayed for AChE inhibition and it was seen that 0.1 mg/mL solution showed 15 ± $2\%$ inhibition, which is considered very small.
## 4. Discussion
As mentioned, seaweeds have been an important part of folk medicine and a source for dietary intake in Asian countries, which have been rapidly expanding globally in previous years. The demand for seaweeds has increased in proportion to the renewed interest in sustainable and alternative ways to provide sufficient healthy food for the growing global population. Seaweeds thus appear to contribute to the possibility of reaching the goal set by the United Nations for sustainable development, as several cultivation plants are addressing the sustainable cultivation of seaweed biomass across Europe [7,57,58]. Seaweed growth is not very demanding. They do not require fertilizers and their biomass captures carbon dioxide, having a negative carbon footprint. Their growth rate is higher than plants and they are less likely to be infected with pests and other diseases [59].
The increased interest in seaweeds was also significantly influenced by their claimed health benefits, which are often associated with the presence of several bioactive compounds. However, due to differences amongst several species and the variety of compounds present in these organisms, most of their bioactive compounds are yet to be identified and associated to their potential effects, hindering the proof–of-concept necessary for their application, either in therapeutic areas or as functional foods.
This work aims to increase knowledge about the future trends and perspectives for the application of three of the most common edible seaweeds: Aramé, Nori, and Fucus. A novel approach to address this issue was used. The seaweed extracts and their compounds, separated in enriched fractions, were characterized and compared in terms of composition and exhibited biological activities.
The total phenolic content, proteins, and polysaccharides content of the extracts and corresponding fractions were evaluated, and it was seen that fractionating the compounds present in the extracts had a major impact on the extract’s composition and in the exhibited biological properties.
Regarding the DPPH antioxidant activity, both the Aramé and Fucus extracts exhibited good antioxidant activity. The Aramé extract demonstrated the strongest antioxidant activity, and the opposite was seen for the Nori extract. Additionally, a clear reduction was seen in the antioxidant activity of the fractions, although some of the fractions, relative to the extract, were richer in compounds, such as phenolic compounds, often associated to high antioxidant activity [60], and polysaccharides [31]. This type of behavior indicates that bioactivity depends on the combinations of compounds present in the extract, and the synergistic effect of the mixture of compounds is evidently missing in the fractions causing poorest performance for the latter.
Mass spectrometry tentative identification of compounds present in the extracts showed that the Aramé extract, exhibiting the highest antioxidant activity, contained a combination of eckols, fuhalol, and other phloroglucionol derivatives of lower molecular weight. As shown by Brand-Williams and colleagues [61], there is a correlation between the interaction with DPPH radical antioxidant capacity and the structural conformation of the compounds tested. The capacity for DPPH scavenging, associated to phlorotannins, may be correlated to the extent of electron donating groups, such as the hydroxyl group, especially at the ortho or para position, occurring in the phloroglucinol unit. Additionally, phlorotannins with a lower polymerization degree, such as eckol and phloroeckol, show an increased antioxidant activity relative to higher molecular weight, such dieckol and 8,8’-bieckol, as higher polymerization condenses electron donating groups [62]. As for the analysed extracts, but mainly for the Aramé extract, a combination of lower molecular weight phlorotannins was identified, and therefore in accordance with the previous observations. The Nori extract was seen to contain lower TPC and a less significant array of phlorotannins, and both of these circumstances affected the antioxidant capacity.
Regarding the AChE activity, overall, the extracts showed milder inhibitory capacity, with this being the first report for a Nori extract. The Nori extract showed the best results for AChE inhibition, therefore its major bioactive compounds, tentatively identified as smaller sized fucol type phloroglucinol derivatives, could be suggested to be further explored for its potential to improve gastrointestinal motility and in the treatment/prevention of Alzheimer’s disease (AD). AChE is an enzyme located in the neuromuscular junctions and in the neurosynaptic gaps [63]. AChE inhibition may improve digestion [64], and there is also clinical evidence that the inhibition of AChE activity is an effective therapeutic target for the management of AD [65,66]. The inhibition of AChE increases the levels of ACh in synaptic cleft, which attenuates the cholinergic deficit associated to AD and improves cognition and memory function [67]. Also, it is reported that dementia is associated with poor nutrition, so it is suggested that the use of small size phlorotannins from seaweed extracts, as Nori extract phloroglucinol derivatives, could be effective both to inhibit the enzyme, improving symptoms in AD management, and a safe diet complement [68]. Oxidative stress has also been implicated in AD, because brain cells are predisposed to free radical attack due to their content and inability to synthesize antioxidant enzymes [69,70], which can lead to free radical attack at cell biomolecules [71]. Oxidative stress is associated to other chronic and degenerative diseases, such as cancer [72], cardiovascular associated diseases [73], multiple sclerosis [74], and rheumatoid arthritis [75]; as a debilitated antioxidant system within the organism may affect the elimination of reactive species formed during cell metabolism.
Thus, considering the results presented in this work, as the bioactive compounds from seaweed extracts demonstrated strong antioxidant activity, especially the mixture of eckols, fuhalol, and other phloroglucinol derivatives from brown seaweed Aramé, it is projected that the inclusion of these extracts or bioactive compounds in either a healthy diet, supplements, or functional foods is prone to improve health conditions.
The extracts did not show cytotoxicity in intestinal Caco-2 and liver Hep-G2 cell lines, which was expected as these seaweeds have been used this way in the diet for many years. The bioactive compounds incorporation into upcoming supplements or functional foods requires supplementary validation steps according to international standards. Among these, safety tests should be performed in normal cell lines, as the cell lines, Caco-2 [76] and Hep-G2 [49] used in this work have the metabolic profile characteristic of immortalized cells.
## 5. Conclusions
Seaweeds are a promising source of bioactive compounds, but their composition and associated biological activities may vary depending on the species and other attributes. Considering that most of these issues continue to be underexplored, the present study aimed to elaborate a scientific comparison between extracts of the three of the most consumed seaweeds Aramé, Nori, and Fucus, regarding the commonly claimed qualities and biological activities associated to seaweeds.
It was seen that these seaweed extracts might have therapeutic potential against oxidative stress and neurological disorders, such as Alzheimer’s disease. It was additionally seen that, for all seaweeds, the mixture of bioactive compounds, obtained by extraction in hot water—as often used for consumption—had the most promising antioxidant activity, relative to extract fractions containing the separated compounds. The Aramé extract, seen to be a mixture of phlorotannins, tentatively assigned as eckols, fulahol, and other phloroglucinol derivatives, showed the highest antioxidant potential, therefore promising against oxidative stress associated conditions. Results also showed that the red seaweed Nori extract, containing smaller sized phlorotannins, showed the lowest antioxidant activity. On the other hand, the Nori extract demonstrated the highest AChE inhibitory capacity when compared with the other seaweeds; therefore, Nori bioactive compounds emerge as promising to improve digestion and complement AD management.
In conclusion, given the interesting outcomes with the extract’s bioactive compounds association to health improvement and management of diseases, mainly those associated with oxidative stress and neurodegeneration, future trends and perspectives are to persist towards the validation of the extract’s capacity to be used as dietary supplements or functional food, pursuing the development of seaweed-based food or novel and natural products with the incorporation of these seaweeds.
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|
---
title: 'The association between psychosocial factors and mental health symptoms in
cervical spine pain with or without radiculopathy on health outcomes: a systematic
review'
authors:
- Michael Mansfield
- Mick Thacker
- Joseph L. Taylor
- Kirsty Bannister
- Nicolas Spahr
- Stephanie T. Jong
- Toby Smith
journal: BMC Musculoskeletal Disorders
year: 2023
pmcid: PMC10045438
doi: 10.1186/s12891-023-06343-8
license: CC BY 4.0
---
# The association between psychosocial factors and mental health symptoms in cervical spine pain with or without radiculopathy on health outcomes: a systematic review
## Abstract
### Background
Neck pain, with or without radiculopathy, can have significant negative effects on physical and mental wellbeing. Mental health symptoms are known to worsen prognosis across a range of musculoskeletal conditions. Understanding the association between mental health symptoms and health outcomes in this population has not been established. Our aim was to systematically review the association between psychosocial factors and/or mental health symptoms on health outcomes in adults with neck pain, with or without radiculopathy.
### Methods
A systematic review of published and unpublished literature databases was completed. Studies reporting mental health symptoms and health outcomes in adults with neck pain with or without radiculopathy were included. Due to significant clinical heterogeneity, a narrative synthesis was completed. Each outcome was assessed using GRADE.
### Results
Twenty-three studies were included ($$n = 21$$,968 participants). Sixteen studies assessed neck pain only ($$n = 17$$,604 participants); seven studies assessed neck pain with radiculopathy ($$n = 4$$,364 participants). Depressive symptoms were associated with poorer health outcomes in people with neck pain and neck pain with radiculopathy. These findings were from seven low-quality studies, and an additional six studies reported no association. Low-quality evidence reported that distress and anxiety symptoms were associated with poorer health outcomes in people with neck pain and radiculopathy and very low-quality evidence showed this in people with neck pain only. Stress and higher job strain were negatively associated with poorer health outcomes measured by the presence of pain in two studies of very low quality.
### Conclusions
Across a small number of highly heterogenous, low quality studies mental health symptoms are negatively associated with health outcomes in people with neck pain with radiculopathy and neck pain without radiculopathy. Clinicians should continue to utilise robust clinical reasoning when assessing the complex factors impacting a person’s presentation with neck pain with or without radiculopathy.
### PROSPERO registration number
CRD42020169497.
### Supplementary Information
The online version contains supplementary material available at 10.1186/s12891-023-06343-8.
## Background
Cervical spine pain with or without radiculopathy (CSp ± R) has a significant negative impact on people’s physical and mental health. It is an enormous burden for individuals, families and societies [1, 2]. The reported incidence of cervical spine radiculopathy (CSR) is between 0.83 and 1.79 per 1000 person-years, and prevalence ranges from 1.2 to 5.8 per 1000 [3]. The one-year incidence of cervical spine pain ranges between $10\%$ and $21\%$ [4, 5]. The global prevalence of cervical spine pain and years lived with disability has each increased by $19\%$ over the last 10 years [6].
The association between psychological and/or mental health symptoms and LBP is well-established with low back pain [7, 8]. It is recognised that these symptoms are negatively associated with health outcomes and quality of life [7, 8]. Psychosocial factors encompass a wide range of cognitions, emotions, behaviours and family and workplace influences [9]. Mental health symptoms or conditions are an extension of such factors. Stress, anxiety, depression and negative coping behaviours negatively impact prognosis with musculoskeletal conditions such as low back pain [10], work related neck pain [11], knee osteoarthritis [12], carpal tunnel syndrome [13] and shoulder pain [14]. Psychosocial factors and/or mental health symptoms should be considered as part of a clinical reasoning framework to positively affect health outcomes and support prognosis [15]. The extent to which these factors may impact acute or persistent CSp ± R across global locations has not yet been synthesised in a systematic review study design.
Establishing the associative factors between psychosocial factors and/or mental health symptoms and health outcomes will enhance our understanding of these complex interactions. Furthermore, it should enhance clinicians’ assessment and management plans [16, 17]. To the authors’ knowledge, no systematic review has examined this association. Consequently, we report a systematic review assessing the association between psychosocial factors and/or mental health symptoms to health outcomes in adults with CSp ± R.
## Methods
This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO) database (Reference: CRD42020169497). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [18] was followed. The review protocol has been previously published [19].
## Search strategy
A systematic search of the electronic databases EMBASE, CINAHL and MEDLINE (PubMed) from inception to 31st April 2021 was completed by one reviewer (NS) under the supervision of a second (MM). The search was updated by the lead reviewer (MM) from 31st April 2021 to 1st September 2022. The PubMed search strategy is presented in Appendix 1. Unpublished (grey) literature search and trial registry was searched (e.g., WHO.It, ZETOC, British library higher education thesis deposits). All included studies underwent reference checking.
## Eligibility criteria
Studies were included if they met the following criteria: A sample that included adults aged 18 years and over with CSp ± R. Following the International Association of the Study of Pain [20] and The Bone and Joint Decade 2000–2010 Task Force on Neck Pain [21] cervical spine pain definitions. We defined neck pain as cervical spine pain perceived anywhere in the posterior neck region to the first thoracic spinous process. Furthermore, a pragmatic approach was undertaken, and studies with probable or definite cervical spine radiculopathy diagnoses were adapted from IASP and North American Spine Society were eligible for inclusion [20, 22, 23] (Supplementary file 1).Assessed psychosocial factors or mental health symptoms as an exposure. Studies must have investigated one or more psychosocial or mental health symptoms (or conditions). Psychosocial factors may have included: cognitive (e.g., neuropsychological functioning), affective (e.g., distress, mood), behavioural (e.g., coping strategies), vocational (e.g., job satisfaction, self-perceived work ability) or interpersonal processes (e.g., social support) [24]. Mental health symptoms and conditions such as depressive symptoms, clinical depression, anxiety, perceived stress, personality, psychotic, traumatic and eating disorders were also considered. Self-reported, objective, standardised questionnaires (e.g., Beck Depression Index, Karasek’s Job Control Questionnaire, GHQ-12) and psychosocial factors or mental health symptoms assessed using dichotomous data (“yes/no”) were also considered. Studies were also eligible if the study population compared different severities of mental health symptoms, conditions or psychosocial factors related to an outcome. Published in English language and were either case-control, cross-sectional or cohort study design.
No restriction on publication date was applied. Studies were excluded if they were animal or cadaveric studies, commentaries, editorials, single case studies, reports or laboratory data, books or book chapters, letters, conference posters or proceedings or study protocols. Furthermore, we excluded studies whose participants’ CSp ± R resulted from an upper motor neuron lesion, fracture, radiculitis, myelopathy, post-surgery, whiplash-associated disorder, systemic pathology or metabolic diseases such as diabetes.
## Study identification
We uploaded the search strategy results into the Rayann systematic review online platform (https://www.rayyan.ai). Two reviewers (MM, TS) independently reviewed, checked titles and abstracts and documented decisions on study eligibility. All potentially eligible full-text papers were independently reviewed by the same two reviewers to determine final inclusion. A third reviewer (MT) was available to review any disagreements; this was not required.
## Data extraction
Data extraction forms were designed by the lead reviewer (MM). This form was reviewed and agreed upon by all reviewers. Two reviewers (MM, JT) independently extracted data from included studies. The same two reviewers discussed the data extracted and reached a consensus through discussion. Data extracted included lead author and date of publication; study design; study demographics (country, sample size, age range or mean gender ratio); definition of exposure; report of the comparator; outcome measure description; risk estimates (risk ratios, hazard ratios, odds ratio and mean differences including $95\%$ confidence intervals (CI)) where available.
## Methodological quality
Two reviewers (MM, TS) independently assessed the quality of each included study using a Newcastle-Ottawa Quality Scale (NOS) assessment quality appraisal tool [25]. The NOS checklist assesses the quality of studies across three domains: selection of the studies groups, comparability of the groups and control for confounding factors and exposure. The two reviewers discussed NOS quality appraisal scores and, through discussion, reached a consensus. The certainty of the evidence was assessed as very low, low, moderate or high certainty using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) [26].
## Synthesis
Two reviewers (MM, TS) assessed all included analyses from a clinical (e.g., diagnosis, variability in population characteristics) and study methodology perspective to determine the suitability of meta-analysis. Both reviewers agreed on the existence of significant clinical heterogeneity, questioning the appropriateness of meta-analysis. Data were, therefore, narratively analysed by patient populations and clinical diagnoses.
## Results
The results of the search strategy are presented in Fig. 1. A total of 6732 studies were identified and screened. Of these 6450 were excluded from the title and abstract. Of the remaining 282 full-text studies reviewed, 259 were excluded. Twenty-three studies met the inclusion criteria and were included in the review [2, 27–48].
Fig. 1PRISMA 2020 flow diagram for new systematic reviews, which included searches of databases, registers and other sources. From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71
## Study characteristics—population and location
A total of 21,968 participants were recruited across the 23 included studies. There were 17,604 participants with non-specific neck pain and 4364 participants with CSR. Sixteen studies included neck pain populations, five were cohort study designs [27, 29, 34, 43, 46] and 11 were cross-sectional in study design [2, 28, 32, 35–37, 39, 41, 42, 45, 47]. Of the seven studies that included CSR populations, five were observational [30, 31, 38, 44, 48] and two were secondary analyses of healthcare records [33, 40]. The characteristics of the included studies are presented in Table 1 (summary study characteristics). A full table of study characteristics can be accessed in Supplementary File 2.
Table 1Summary study characteristicsAuthor and yearSpinal diagnosisMental health diagnosis or symptomsHealth outcomeAlipour [2009]Non-specific neck painAnxiety symptoms regarding changedSick Leave from employmentBeltran-Alacreu[2018]Non-specific neck painKinesiophobiaPresence of pain (NPRS)Bohman [2019]Neck pain for 3 months or longerDepressive symptomsNeck Disability IndexCarroll [2004]Non-specific neck painDepressive symptomsDevelopment of pain (NPRS)Diebo [2018]Cervical spine radiculopathyPsychological outcomes with SF-36Neck Disability Index (NDI)Divi[2020]Cervical spine radiculopathyPsychological outcomes with SF-12Neck Disability Index (NDI)Elbinoune [2016]Neck pain for 3 months or longerAnxiety and depressive symptomsPresence of Pain (NPRS)Engquist [2015]Cervical radiculopathyDepressive symptomsNeck Disability IndexGrimby-Ekman [2012]Non-specific neck painStressPresence of pain (NPRS)Hill[2007]Non-specific neck painPsychological distressPresence of pain (NPRS)Hoe [2012]Non-specific neck painJob strain & SF-12 MCSPresence of pain (NPRS)Hurwitz [2006]Non-specific neck painSF-36 Mental healthNeck Disability IndexKim[2018]Cervical spine radiculopathyDepressive symptomsNeck Disability Index and Numeric Pain Rating ScoreLee [2007]Non-specific neck painPsychological distressPresence of pain (NPRS)MacDowell [2018]Cervical radiculopathyAnxiety and depressive symptomsNeck Disability IndexMcLean [2011]Neck pain for 3 months or longerAnxiety and depressive symptomsDisability of arm and shoulder (DASH)Meisingset [2018]Non-specific neck painCatastrophisingPain (NPRS)Myhre [2013]Non-specific neck painEmotional distressFABQ-WPeolsson [2006]Cervical spine radiculopathyDistressNeck Disability IndexPico-Espinosa [2019]Non-specific neck painDepressive symptomsPain levels (NPRS)Rodriguez-Romero [2016]Non-specific neck painPsychological outcomes with SF-36Presence of pain (NPRS)van den Heuvel [2005]Non-specific neck painJob strainPresence of neck and upper limb pain shoulder pain (NPRS)Wibault[2014]Cervical spine radiculopathyDepression and AnxietyNeck Disability Index Seven studies included participants with CSR recruited from elective spinal surgery waiting lists. The CSR diagnosis was made using imaging associated with a neurological deficit on clinical examination [30, 31, 33, 38, 40, 44, 48]. Despite contacting the corresponding authors for further information, no further details were obtained.
Nine studies measured depressive symptoms [2, 29, 32, 33, 38, 40, 43, 45, 48]. Five studies measured anxiety symptoms [27, 32, 40, 43, 48] and three studies measured job-strain and stress [34, 35, 46]. Three studies used the psychological components of SF-36 [30, 39, 47]. Two studies used the psychological components of SF-12 [31, 35]. One study measured kinesiophobia [28] and one study measured catastrophising [41]. Three studies used more than one mental health symptom measurement [32, 35, 43]. A summary of the mental health symptoms and tools to measure the severity of mental health conditions across the 23 included studies are presented in Table 1.
## Neck pain associative outcomes: depressive symptoms
Of the 16 studies with people with non-specific neck pain, there were positive and negative associations between mental health symptoms and health outcomes. Four studies reported a positive association [2, 32, 43], and one study reported a negative association [29] with depression. Using GRADE classifications, the overall strength of evidence was ‘low’, which is attributed to a high risk of bias.
Depressive symptoms measured through Hospital Anxiety and Depression Scale (HADS) was positively associated with the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire (r:0.245, $$p \leq 0.004$$) [43], Odds Ratio (OR): 3.46 ($95\%$ CI: 2.01–5.95) [45] and OR: 1.02 ($95\%$ CI: 0.98–1.06) [32]. When measured through the Center for Epidemiologic Studies Depression Scale (CES-D), depressive symptoms were positively associated with pain (Hazard Ratio (HR): 3.97, $95\%$ CI: 1.81–8.72) [2]. Depressive symptoms measured by the Montgomery Asberg Depression Rating Scale were negatively associated with Neck Disability Index (NDI) (OR: 0.94, $95\%$ CI: 0.86–1.03) [29].
## Neck pain associative outcomes: anxiety symptoms
Anxiety symptoms were positively associated with poorer health outcomes in two studies [27, 32] and had no significance in one study [43]. The overall strength of evidence was ‘very low’ in the GRADE assessment which is attributed to a high risk of bias and imprecision.
Anxiety symptoms measured through the Nordic musculoskeletal questionnaire were more likely to be associated with sick leave (OR: 1.4, $95\%$ CI: 0.9–2.1) [27]. Anxiety symptoms measured through HADS were more likely to be associated with the presence of pain (OR: 1.02, $95\%$ CI: 0.98–1.05) [32]. Whereas in one study, anxiety symptoms measured through HADS had no statistical significance with DASH (r: 0.104, $$p \leq 0.220$$) [43].
## Neck pain associative outcomes: Kinesiophobia
Kinesiophobia was associated with poorer health and the presence of pain (r: 0.566, P = < 0.05) in one study [28].
## Neck pain associative outcomes: Catastrophising
Catastrophising, measured by the catastrophising pain scale, was positively associated with pain (OR: 1.03, $95\%$ CI 0.97–1.09) in one study [41].
## Neck pain associative outcomes: stress
Stress was positively associated with the presence of pain (OR: 0.32, $95\%$ CI: 0.25–0.39) in one study [34].
## Neck pain associative outcomes: job strain
A higher job strain was negatively associated with the presence of pain in the neck and shoulder in two studies (Relative Risk (RR): 1.79, $95\%$ CI: 1.19–2.69) [46] and OR: 1.51 ($95\%$ CI: 0.88–2.59) [35]. This was rated as ‘low’ in the GRADE assessment, attributed to imprecision across the studies.
## Neck pain associative outcomes: distress
Distress was positively associated with health outcomes in three studies [37, 39, 42] and negatively associated with health outcomes in two studies [36, 47]. The overall strength of evidence using the GRADE approach is ‘very low’, which is attributed to a high risk of bias and imprecision.
Psychological distress measures were positively associated with the presence of pain when measured by SF-36 (r2: 0.12, $p \leq 0.01$) [39] and Hopkins Check List-10 (OR: 2.32, $95\%$ CI: 1.20–3.43) [42]. Similarly, this was positively associated with NDI (OR: 1.75, $95\%$ CI 0.83–3.70) [37]. Two studies reported a negative association between distress and the presence of pain (OR: 0.88, $95\%$ CI: 0.62–1.24) [36] and OR: -0.3, $95\%$ CI -0.4-0.1 [47].
## Cervical spine radiculopathy associative outcomes: depressive symptoms
Of the seven studies with CSR populations, there were both positive and negative associations between depressive symptoms and health outcomes. Three studies reported a negative association [33, 40, 44], whereas one study reported a positive association [38]. The overall strength of evidence using the GRADE approach was ‘very low’, this is attributed to a high risk of bias and imprecision.
Depressive symptoms were positively associated with NDI when measured through the Zung Self-Reporting Scale (NDI with depression 42.8 (High) (SD: 19.9) vs. 20.9 (SD: 15.9), $p \leq 0.0001$) [38]. Three studies reported negative associations (OR: 0.71, $p \leq 0.001$) [44], regression coefficient 0.25 ($95\%$ CI: -0.01-0.50) [40] and risk of depression not being significant ($$p \leq 0.3$$) [33].
## Cervical spine radiculopathy associative outcomes: distress
There were two studies that reported a positive association between SF-36 ($p \leq 0.05$) [30] and SF-12 ($$p \leq 0.04$$) [31] and NDI. Whereas one study reported distress being negatively associated with NDI (r2 = 0.80, $$p \leq 0.0005$$) [44]. The overall strength of evidence using the GRADE approach was ‘very low’. This is attributed to a high risk of bias and imprecision.
## Cervical spine radiculopathy associative outcomes. Anxiety symptoms
In one study, anxiety symptoms were positively associated with NDI in CSR populations (OR: 0.63, $$p \leq 0.006$$) [48]. All associative outcomes data are populated in Table 2.
Table 2Associative data between health outcome and mental healthAuthor and yearAssociative data between health outcome and mental healthAlipour [2009]OR: 1.4($95\%$ CI: 0.9–2.1)Beltran-Alacreu[2018]*Association kinesiophobia* and presence of pain ($r = 0.566$)Bohman [2019]OR: 0.94($95\%$ CI: 0.86–1.03)Carroll [2004]Hazard Rate Ratio 3.97($95\%$ CI 1.81–8.72)Diebo [2018]When NDI is lowMHC = 25.81(SD: 8.85)When NDI is highMCS = 25.60(SD: 8.87)Divi[2020]MHC low score23.9($95\%$ CI: 21.0-26.7)vs. MHC high score31.8($95\%$ CI: 24.7–38.9) ($$p \leq 0.04$$)Elbinoune [2016]HADS-AnxietyOR: 1.02($95\%$ CI: 0.98–1.05)HADS-Depression OR: 1.02($95\%$ CI: 0.98 to 1.06)Engquist [2015]No risk of depression4 ($95\%$ I: -4 to 15)At risk of depression10 ($95\%$ CI: 1–19)($$p \leq 0.3$$)Grimby-Ekman [2012]OR 0.32($95\%$ CI: 0.25–0.39)Hill[2007]OR 0.88($95\%$ CI: 0.62–1.24)Hoe [2012]High Job StrainOR: 1.51($95\%$ CI: 0.88–2.59)SF-12 Mental Health Component OR: 0.98($95\%$ CI: 0.96–0.99)Hurwitz [2006]OR 1.75 ($95\%$ CI 0.83–3.70)Kim[2018]NDIDepression 42.8 (SD: 19.9)vs. Low-depression 20.9 (SD: 15.9) ($p \leq 0.0001$)NPRSDepression 5.5 (SD: 2.2)vs. Low depression 3.0 (SD: 2.4)($p \leq 0.0001$)Lee [2007]SF-36 MCS and Physical activity (r2: 0.12 $p \leq 0.01$)MacDowell [2018]Regression Coefficient0.25($95\%$ CI: -0.01-0.50)McLean [2011]Depressionr: 0.245($$p \leq 0.004$$)Anxietyr:0.104($$p \leq 0.220$$)Meisingset [2018]OR: 1.03($95\%$ CI 0.97–1.09)Myhre [2013]OR: 2.32($95\%$ CI: 1.20–3.43)Peolsson [2006]NDI r2 = 0.80to DRAM($$p \leq 0.0005$$)Pico-Espinosa [2019]OR: 3.46($95\%$ CI 2.01–5.95)Rodriguez-Romero [2016]OR: -0.3($95\%$ CI: -0.4-0.1)van den Heuvel [2005]Low job strainRR: 1.00 ($95\%$ CI 0.76–1.92)High job strainRR: 1.79($95\%$ CI 1.19–2.69)Wibault[2014]DepressionOR: 0.71(p = < 0.001)AnxietyOR: 0.63 ($$p \leq 0.006$$)
## Quality assessment. Neck pain populations
Five cohort studies included patients with non-specific neck pain as their exposure [27, 29, 34, 43, 46]. These studies scored between five and seven out of nine on the NOS. All studies met the ‘representativeness of exposed cohort’ and ‘adequate follow-up’. All five studies did not complete the ‘assessment of outcome’ item.
Eleven studies were cross-sectional in study design. Scores ranged from five to seven out of nine on the NOS. All studies met the ‘representativeness of exposed cohort’ and ‘adequate follow-up’. All studies did not meet the ‘assessment of outcome’ item. Three studies completed a secondary analysis of data [36, 37, 45]. These studies scored six to seven out of a possible nine. All studies did not meet the ‘demonstration that outcome of interest was not present at the start of study’ item and ‘assessment of outcome’. The overall strength of evidence measured through GRADE is populated in Table 3. The quality assessment tables are populated in Table 4.
Table 3Certainty of evidence. GRADE approach for health outcomesStudy DesignStudy lead authorNumber of studies/patientsRisk of biasImprecisionInconsistencyIndirectnessOverall strength of evidence Observational Neck pain without CSR DepressionBohmanCarollElbinouneMcCleanPico-Espinosa$\frac{5}{1}$,718HighSeriousModerateNo seriousnessLowAnxietyAlipourElbinouneMcClean$\frac{1}{12}$,415HighSeriousHighNo seriousnessVery lowCatastrophisingMeisingset$\frac{1}{70}$HighSeriousHighNo seriousnessVery lowStressGrimby-Ekman$\frac{1}{1200}$HighSeriousHighNo seriousnessVery lowJob strainVan den HeuvelHoe$\frac{2}{1898}$HighSeriousModerateNo seriousnessLowDistressLeeHillHurwitz$\frac{3}{802}$HighSeriousModerateNo seriousnessVery LowKinesiophobiaBeltran-Alacreu$\frac{1}{128}$HighSeriousModerateNo seriousnessLow Observation CSR DistressDieboDiviPeoplsson$\frac{3}{639}$HighSeriousModerateNo seriousnessVery LowDepressionKim;PeolssonEnquistMacDowell$\frac{4}{471}$HighSeriousModerateNo seriousnessVery LowAnxietyWilbault;$\frac{1}{254}$HighSeriousModerateNo seriousnessVery LowThrough this, the certainty of the evidence was either increased (upgraded) or decreased (downgraded) against the following five criteria:[1] Methodological limitations using the Cochrane Risk of Bias tool (downgraded where there was a high risk of bias for three or more items; upgraded where all items demonstrated a low risk of bias);[2] Indirectness relating to similarity to clinical practice (downgraded where reviewers felt the study design was not generalisable to UK practice; upgraded where study design was generalisable to UK practice);[3] Imprecision relating to the number of participants and events (downgraded where outcomes reported less than 300 participants or five events; upgraded where effects reported in excess of 450 participants or 20 events);[4] Inconsistency in effect estimates across trials for a given analysis (downgraded where the CIs were four-times the magnitude of the effect estimate; upgraded where CIs were two-times the magnitude of the effect estimate)[5] Likelihood of publication bias (downgraded when reviewers observed asymmetry in funnel plot shape; upgraded when reviewers observed symmetry in funnel plot shape) Table 4Quality assessment scoring for all included studiesAuthor and yearRepresentativeness of the exposed cohortSelection of the non-exposed cohortAscertainment of exposureDemonstration that outcome of interest was not present at start of studyComparability of cohorts based on the design or analysisAssessment of outcomeWas follow-up long enough for outcomes to occurAdequacy of follow up of cohortsTOTAL STARSAlipour [2009]110120107Beltran-Alacreu[2018]110000115Bohman [2019]110000115Diebo [2018]111020117Divi[2020]111020117Carroll [2004]110020117Elbinoune [2016]110020116Engquist [2015]111000115Grimby-Ekman [2012]110020117Hill[2007]110020106Hoe [2012]110020117Hurwitz [2006]110020106Kim[2018]110020116Lee [2007]110000115MacDowell [2018]111020117McLean [2011]110010116Meisingset [2018]110020005Myhre [2013]110020117Peolsson [2006]111020106Pico-Espinosa [2019]110020117Rodriguez-Romero [2016]110020106van den Heuvel [2005]110120107Wibault[2014]110020116
## Quality assessment. Cervical spine radiculopathy populations
Five cohort studies included patients with CSR as their exposure population [30, 31, 38, 44, 48]. These studies scored between six and seven out of a possible nine on NOS. All studies met the ‘representativeness of exposed cohort’ and ‘adequate follow-up’. All five studies did not complete the ‘assessment of outcome’ item. Two studies with a CSR study population were retrospective secondary data analyses where each study scored five [33] and seven [40], respectively. The overall strength of evidence measured through GRADE is populated in Table 3. The quality assessment tables are populated in Table 4.
## Discussion
This is the first systematic review investigating the association of mental health symptoms and conditions with health outcomes in adults with CSp ± R. Our results indicate that depressive symptoms were associated with poorer health outcomes in seven studies classified as with ‘low quality’, four studies with CSR populations and three studies with non-specific neck pain populations. There was no association with depressive symptoms health outcomes in six studies (four studies with CSR populations and two studies with non-specific neck pain populations) with very low quality. Distress and anxiety symptoms were associated with poorer health outcomes in CSR populations and non-specific neck pain in two studies with ‘very low-level’ quality. Stress and higher job strain was negatively associated with poorer health outcomes measured by the presence of pain in two studies with very low quality sampling non-specific neck pain populations. Stress and higher job strain symptoms were not reported in our included studies that sampled CSR populations.
At the time of conducting this research, there was no universal agreement on CSR diagnosis [3, 49]. Therefore, a pragmatic approach was undertaken, and studies with probable or definite CSR diagnoses were adapted from IASP and North American Spine Society [20, 22, 23] (Supplementary file 1). The diagnostic criteria for CSR varied between each included study. Included studies used a combination of subjectively reported symptoms, clinical assessment testing associated with imaging findings assessed by a physician, and/or sensory and motor electrophysiological testing. In line with our protocol [19], the included patients with CSR would have a ‘definite’ CSR diagnosis. All participants with CSR were on an orthopaedic surgery waiting list, which may question the external validity to alternative healthcare settings such as primary care.
It is acknowledged that a recent international e-Delphi study has been published [50] with an agreement on CSR classification criteria. The 12 physiotherapists who participated in the e-Delphi reached a consensus of radicular pain with arm pain worse than neck pain and paraesthesia or numbness and/or weakness and/or altered reflex and MRI confirmed nerve root compression compatible with clinical findings [50]. Future research should now be conducted to test the reliability and determine which tools can be used to assess these criteria [50]. Strengthening these CSR diagnostic criteria should facilitate standardisation of assessment criteria across multiple health care professionals globally and enhance pooling of results and conclusions regarding this disabling condition.
Our results indicate that depressive symptoms were associated with poorer health outcomes in seven studies classified as ‘low quality’. Of these, four studies were with CSR populations and three studies with non-specific neck pain populations. There was no association with depressive symptoms health outcomes in six studies of very-low quality (four studies with CSR populations and two studies with non-specific neck pain populations). The mixed association between depressive symptoms and health outcomes across CSR and non-specific neck pain populations may be attributed to a difference in the assessment tools used to measure depressive symptoms.
Although each assessment tool has appropriate psychometric properties to measure mental health symptoms, the mode of delivery to collect these data may influence responses [64, 65]. For example, previous literature suggests people may rate their health and well-being, more favourable in telephone interviews compared to self-reported paper-based questionnaire [64, 65]. Furthermore, it is not clear whether the included studies assessing CSR and non-specific neck pain populations compared participant’s scores to the general population’s normative values or by using cut-off scores to indicate different levels of clinically relevant distress, anxiety and/or depressive symptoms [66]. These two points may provide some reasoning for the mixed association findings reported between nonspecific neck pain and CSR populations.
Comparing this review’s results to other spinal pain populations may enhance our understanding of health outcomes and inform assessment and management strategies. Depressive symptoms or clinical depression are reported to have worse recovery and greater healthcare utilisation, but not pain or work-related outcomes in people with LBP [51]. However, healthcare utilisation was based on one study and depressive symptoms were based on six highly heterogeneous studies [51]. The differences between our reported findings may be attributed to the inclusion of acute episodes of low back pain (pain lasting less than one month), whereas the CSp ± R populations in this review were all persistent in presentation (lasting more than three months).
The symptoms related to CSR are likely to be underpinnings of neuropathic pain mechanisms compared to non-neuropathic mechanisms associated with nonspecific neck pain [67]. It is known that neuropathic pain is associated with more severe pain, higher workplace absenteeism, distress and higher medical costs [67, 68] compared to non-neuropathic pain which is comparable to our review’s findings. However, it is reported that the expectation of recovery for patients with CSR pending operative management, may reduce the psychological impact on health outcomes [63]. The mixed observations across CSR and non-specific neck pain populations may therefore explained by the complex contributing biopsychosocial factors impacting a health outcomes.
The interactions and mechanisms underpinning mental health symptoms, conditions and health outcomes in musculoskeletal pain populations are highly complex [52–54]. Clinical conditions such as spinal pain with or without radiculopathy will have complex interactions and influences that will be unique to each individual [17]. These factors include genetic [55], pathoanatomical [56] and psychological and lifestyle health factors [17, 57]. The complex interactions will influence pain perceptions, levels of distress and, subsequently, health outcomes [58, 59]. Enhancing our knowledge and understanding of mental health symptoms on health outcomes such as disability, function and pain can guide expectations and management strategies for clinicians and patients with CSp ± R. Healthcare providers should continue to assess mental health symptoms in a holistic assessment framework as part of a robust clinical reasoning process. The identification of patients potentially at risk of long-term disability and worse recovery can enhance patient-centred care pathways and may improve health outcomes [60].
We acknowledge limitations in our review. Included studies were written in the English language or those that could be translated. This may have resulted in a publication bias of our included studies by language. Health outcomes in our target populations can often have multidimensional and complex interactions [61, 62], which may be reflected in the variability of single measurement tools in the included studies. Future research should consider the multidimensional factors and develop core outcome measurements when evaluating health outcomes for this patient population.
## Conclusions
This systematic review has reported variable associations between mental health symptoms and diagnosis with health outcomes in people with CSp ± R. Stress, depressive and anxiety symptoms are associated with poorer health outcomes in patients with CSp ± R. However, this is based on a small number of low-quality studies. The low quality can be attributed to wide-ranging diagnostic criteria and population sampling methods. Further research is indicated to standard diagnosis classification criteria for radiculopathy and developing core outcomes to further our understanding of this debilitating condition.
## Electronic supplementary material
Below is the link to the electronic supplementary material.
Supplementary Material 1 Supplementary Material 2
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|
---
title: Transcriptome Analysis of the Immortal Human Keratinocyte HaCaT Cell Line Damaged
by Tritiated Water
authors:
- Yan Zhang
- Yuanyuan Zhou
- Hui Wu
- Zhuna Yan
- Jinwu Chen
- Wencheng Song
journal: Biology
year: 2023
pmcid: PMC10045445
doi: 10.3390/biology12030405
license: CC BY 4.0
---
# Transcriptome Analysis of the Immortal Human Keratinocyte HaCaT Cell Line Damaged by Tritiated Water
## Abstract
### Simple Summary
Tritium is one of the most abundant radioactive elements in nuclear waste and is difficult to remove. In addition, tritiated water can enter an organism through the skin, respiratory and digestive systems. Tritiated water damages a large portion of organs or even causes cancer due to internal radiation. In our study, the changes in the cell viability of the immortal human keratinocyte HaCaT cell line after exposure to tritiated water were investigated, and the related molecular mechanisms were analyzed using sequencing technology and bioinformatics methods. Meanwhile, a Western blot assay was conducted to verify some of the sequencing results. The results provide a theoretical basis for researching the mechanisms of tritiated water hazards.
### Abstract
Radioactive elements, such as tritium, have been released into the ocean in large quantities as a result of the reactor leakage accident. In this study, an MTT assay demonstrated that the viability of HacaT cells decreased after tritiated water treatment. Bioinformatics analysis was used to analyze gene changes in the HacaT cells. The sequencing results showed 267 significantly differentially expressed genes (DEGs), and GO enrichment analysis showed that the DEGs were mainly divided into three parts. The KEGG pathway analysis showed that the up-regulated DEGs were involved in Wnt and other pathways, while the down-regulated DEGs were involved in Jak–STAT and others. A Western blot assay was used to verify the parts of the sequencing results. This study was the first to explore the mechanism of tritiated water on HacaT cells using Transcriptome analysis. The results will provide a theoretical basis for the study of tritiated water hazard mechanisms.
## 1. Introduction
With the development of industry, the development and utilization of nuclear energy increased correspondingly, and a large number of nuclear power stations were built. Earthquakes, tsunamis and improper operation due to worker behavior all may lead to nuclear reactor leakage accidents, resulting in the release of large amounts of nuclear wastewater into the environment [1]. Generally, nuclear wastewater contains a large number of radioactive substances, among which tritium is the most common substance and the most difficult to remove [2]. Tritium is a radioactive isotope of Hydrogen, which mainly exists in three main forms: tritiated water, tritiated gas and organically bound tritium. Among them, the average energy of tritium β-rays is 5.7 keV, and the maximum is 18.6 keV. It has a range of about 0.56 μm in water, which is much smaller than the average diameter of the cell (10–20 μm) [3]; therefore, tritiated water can produce a biological effect on an organism through irradiation [4]. In addition, tritiated water is similar to H2O, which is volatile, forming tritiated water vapor. Tritiated water enters the body through the respiratory system, skin infiltration or the food chain, and it can be distributed in the human body through the blood circulation system in about 2–3 h [5].
Low doses of tritiated water may not cause damage to organisms or may even have protective effects on organisms. Stuart et al. found that frogs in Duke Swamp exposed to tritiated water radiation (5000–35,000 Bq/L) for a long time were able to reduce their susceptibility to radiation damage [6], which suggested an adaptive response in frogs exposed to radiation from tritiated water. Arcanjo et al. found that 0.4 and 4 mGy/h tritiated water exposure enhanced the expression of some genes related to DNA repair (h2afx and ddb2) [7]. Stuarta et al. found that when B-lymphoblast cells (3B11 and FHMT-W1) were exposed to 10–100 Bq/L tritiated water, intracellular ATP content increased, and cell vitality did not decline [8].
However, high doses of tritiated water radiation can damage organisms. An analysis of the chromosomes of nuclear workers exposed to tritium (average dose 9.33 mGy) in the UK found that the workers had an increased rate of chromosomal aberrations [9]. In addition, tritiated water leads to liver, ovarian, leukemia, lung, breast damage, skin cancer and osteosarcoma in rats [10,11,12]. For example, Yin et al. proved that tritiated water above 8 × 1010 Bq could induce liver cancer in male rats, but only above 3.7 × 1012 Bq, could it induce the occurrence of ovarian cancer in female rats [10]. Seyama et al. injected 7.4 × 108 Bq of tritiated water into mice, which induced leukemia and lymphoma in more than $80\%$ of the mice, as well as increasing the risk of lung cancer [11]. Balonov et al. found that exposure to tritiated water in rats for 6 months at 3.7 × 104 Bq·g−1/Kg induced skin cancer and osteosarcoma [12]. In addition, tritium radiation damaged the cardiovascular [13,14,15], immune [16,17] and reproductive [18] systems. Li et al. found that when human B lymphocytes (AHH-1-1) were treated with 3.7 × 109 Bq/L tritiated water for 48 h, cell apoptosis could be observed [17]. Lee et al. proved that micronucleus appeared in the blood samples of rats exposed to tritiated water after 14 d in rats with a total oral dose of 3.7 × 104 Bq, and the appearance of micronucleus, which represents chromosome aberration. Nowosielska et al. treated mice with tritiated water of 0.888, 8.88 or 88.8 × 1012 Bq, and found that after 8 d, NK lymphocytes were damaged and that tritiated water promoted increased NO by macrophages [16]. Kamiguchi et al. found that after treating human sperm with 5.66–59.91 × 105 Bq/mL tritiated water for 80 min, the incidence of chromosome aberration in the sperm structure increased linearly in a dose-dependent manner [18]. Along with some behavioral experiments that showed that the learning and memory ability of mice decreased significantly when they were treated with tritiated water above 24.09 × 104 Bq/g tritiated water after 10 d [19]. Among them, studies have shown that high doses of tritium radiation also had a negative impact on the survival of algae, bacteria, shellfish and fish [20,21,22,23]. For example, Selivanova et al. proved that when the concentration reached 1 × 1014 Bq/L, tritiated water would damage bacterial cells [20]. Réty found that the cell density of the algal decreased significantly under 5.9 × 1016 Bq/L tritiated water [22].
Recently, some studies have focused on the mechanisms related to the decrease in cell viability caused by tritiated water. Quan et al. found that after incubation with 2 × 1010 Bq/L tritiated water for 3 h, the proportion of S-phase cells in human mesenchymal stem cells increased, while that of G1- and G2-phase cells decreased [24]. Vorob’eva et al. proved that Tritium could cause DNA damage by increasing the expression of γH2AX and dsDNA [25]. In addition, Yan et al. used 3.7 × 106 Bq/L tritiated water to induce the cell senescence of vascular endothelial cells [14], and Cui et al. demonstrated that this might be due to tritiated water down-regulating the expression of c-myc via miR-34a [13]. Qiu et al. found that treating rat nerve cells with 3.7 × 1010 Bq/L tritiated water for 8 h reduced the expression of neural cell adhesion molecule (NCAM), which could decrease the migration ability of nerve cells [26]. Zhou et al. treated mouse brain cells with tritium β-rays at doses of 0.19 Gy and above, which resulted in the increased gene expression of P53 in the brain cells [27].
In addition, since the skin is the largest tissue in the human body, tritiated water can easily reach the skin. Therefore, some studies have shown that tritiated water produced toxic effects on human skin cells. For example, Little et al. used a total dose of 100 Gy tritiated water to culture human skin fibroblasts for 100 h, which caused cell death [28]. However, the molecular mechanism of damage to epidermal cells caused by tritiated water has not been elucidated. Therefore, this study focused on the decreased cell vitality caused by tritiated water to the immortal human keratinocyte HaCaT cell line and related mechanisms.
Next-generation RNA sequencing (RNA–SEQ) is an emerging, rapid and efficient method for gene expression analysis [29]. In this study, HacaT cells were used as experimental subjects, and transcriptome sequencing technology, as well as bioinformatics analysis, were used to explore the effects and mechanisms of tritiated water exposure on the HacaT cells, and Western blot was used to verify parts of the sequencing results, This study will provide a theoretical basis for the studying the mechanisms of high-dose tritiated water hazards.
## 2.1. Cell Line Culture
The immortal human keratinocyte HaCaT cell line (HaCaT) cells were purchased from keyGEN BioTECH (Cas: 20210513) and cultured in a complete medium composed of a DMEM cell medium (GIBCO, Carlsbad, CA, USA) supplemented with a $10\%$ fetal calf serum (LONSERA, Shanghai, China) and $1\%$ penicillin/streptomycin (NCM Biotech, Suzhou, China). The cells were grown in 35 mm dishes under standard cell culture conditions (37 °C and $5\%$ CO2 in an incubator).
## 2.2. Cell Viability Assay
HacaT cells were grown to $70\%$ of the culture surface area after the cells were attached to the wall and fully stretched and exposed to different concentrations of tritiated water, and then the HaCaT cells were cultured for 48 h in a cell incubator. The cell viability was conducted using MTT (Sigma–Aldrich, St. Louis, MO, USA), and the absorbance (OD value) was measured at 492 nm. Then, the cell viability value was calculated on the basis of the following formula, as previously used [30]. [ 1]cell viability=absorbancetreatmentabsorbanceBK×$100\%$ *In this* formula, absorbancetraeatment represents the OD value of the DZ and GJL group, and absorbance BK represents that of the BK group.
## 2.3. Radiation Treatment
The initial specific radioactivity of the tritiated water used in the experiment was 3.7 × 1010 Bq/L, which was obtained from the Institute of Nuclear Energy Safety (Hefei Institutes of Physical Science, CAS, Hefei, China). Tritiated water was filtered and sterilized before experimental use, and DMEM medium was used to dilute different concentrations of tritiated water. HacaT cells were treated with 0 Bq/L and 3.7 × 109 Bq/L radiation as a blank group (KB), a control group (DZ) and a treatment group (GJL), respectively. Specifically, the cells in the KB group were cultured in 5 mL DMEM; the DZ group was cultured in 4500 μL DMEM and 500 μL sterile water, which was replaced with the same volume of tritiated water in the GJL group. Additionally, a follow-up experiment was conducted after 48 h of continuous exposure to tritiated water.
## 2.4. RNA Extraction
The DZ and GJL group cells (three replicates for each group) were selected for the subsequent experiments. The HacaT cells were treated with 0 Bq/L and 3.7 × 109 Bq/L radiation. After being cultured for 48 h, the cells were digested by trypsin, collected into frozen storage tubes, and stored at −80 °C. After that, the total RNA from the HacaT cells was extracted according to the manufacturer’s instructions by using the TRIZOL kit (Invitrogen, Carlsbad, CA, USA). The quality of the RNA was evaluated by bioanalyzer Agilent 2100 (Santa Clara, CA, USA). The qualified RNA was used for subsequent experiments.
## 2.5. cDNA Library Preparation and Sequencing
The traditional mRNA enrichment method was used to extract the mRNA from the total RNA [31], which enriched the mRNA with polyA tail using magnetic beads with Oligo (dT). The RNA was fragmented with a Frag/Prime Buffer of about 200 bases and reverse transcribed with random N6 primers. Later, dsDNA was synthesized with the end flattened and phosphorylated at the 5′ end, with a bubblelike joint protruding a ‘T’ at the 3′ end. Then, they were amplified using PCR. After that, single-stranded DNA was formed and cycled to a single-stranded cDNA library. The constructed library was inspected, and the DNBSEQ platform was used for sequencing.
## 2.6. Sequencing Data Filtering and Reference Genome Comparisons
This experiment was commissioned by The Beijing Genomics Institute (BGI), and the specific steps were as follows: SOAPnuke software (V1.5.2) [32] was used for filtering to obtain high-quality sequencing data, i.e., clean reads. The readings containing adapters in sequencing fragments and an unknown base N content greater than $5\%$ and the low–quality reads were removed from the sequencing fragment to obtain clean reads. HISAT2 2.0.4 was used to align the clean reads to the reference genome sequence [33], and Bowtie2 software was used for the Quality Control of the alignment.
## 2.7. Bioinformatics Analysis
To quantitatively analyze the DEGs of the two samples, the DEGSeq R package was used to analyze the differential expression based on the gene expression levels (principal components, correlations, differential gene screening, etc.). Furthermore, we set |log2FC| ≥ 0.6, Qvalue ≤ 0.05 screening DEGs between two samples, and then, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to conduct an analysis of the sequencing results.
## 2.8. Western Blot Verification
The HacaT cells were treated with 0 Bq/L and 3.7 × 109 Bq/L radiation. After 48 h culture, the DZ and GJL group cells were lysed by an RIPA cell lysis buffer (Beyotime, Shanghai, China), and the proteins of the cells were extracted following the manufacturer’s instructions. Protein supernatants were separated by $10\%$ SDS–PAGE gels and then transferred to the NC membrane (Beyotime, Shanghai, China), sealed with non-fat milk, and probed with primary antibodies at 4 °C overnight and incubated with HRP-conjugated secondary antibody for 40 min. Several antibodies were used as follows: anti–Wnt7b, anti–Jak, anti–STAT3 and anti–β–Actin (ABclonal, Wuhan, China). Later, ECL Plus Reagent (Thermo Fisher Scientific, Waltham, MA, USA) was used to develop, and Chemiluminescence Gel Imaging System (Tanon, Shanghai, China) was used to visualize the protein bands.
## 2.9. Statistical Analysis
The data of the assays were presented as means ± S.D. The data were determined using Student’s t-test. A p-value < 0.05 (*) was defined as statistically significant.
## 3.1. Tritiated Water Impaired the Viability of HacaT Cell
The results of the MTT experiment found that tritiated water could lead to the viability of HacaT cells significantly decreasing, as shown in Figure 1. After 48 h of radiation, the average OD value of the DZ group in the MTT experiment was about 0.94, while that of the treatment group was about 0.82, which was $13.0\%$ lower than that of the DZ group. Thus, tritiated water could impair the viability of HacaT cells significantly.
## 3.2. Overview on Transcriptome Sequencing Data Quality and Difference Analysis of HacaT Cells Exposed to Tritiated Water
In this experiment, the BGISEQ platform was used to measure a total of six samples, and the samples from each group produced 6.66 G data on average. The average rate of genome alignment was $92.64\%$, and that of the gene set was $80.46\%$. A total of 15,807 genes were detected. The bases with sequencing Q20 accounted for more than $97.54\%$ of all bases, while the bases with sequencing Q30, which accounted for more than $93.55\%$ of all bases. In this case, the average sequencing efficiency was about $93.84\%$. Therefore, the sequencing data were of good quality and met the requirements for subsequent analysis (Table 1). In addition, Pearson’s correlation coefficient between every two samples was calculated in order to reflect the correlation of gene expression between the samples, which was presented in the form of a heat map. The higher the correlation coefficient, the more similar the level of gene expression, as shown in Figure 2. In this study, the square of Pearson’s correlation coefficient was all greater than 0.95. These outcomes indicated that the sequencing results were valid.
In addition, from the DEGseq analysis, a total of 267 DEGs, 191 significantly up-regulated DEGs, and 76 down-regulated DEGs, are shown in Figure 3 (|log2FC| ≥ 0.6, Qvalue ≤ 0.05). Additionally, there are several outstanding DEGs on both sides and top. There are several outstanding DEGs on both sides and top, we included detailed information about these genes in the Supplementary material Table S1.
## 3.3. GO Enrichment Analysis of DEGs
GO enrichment analysis was divided into three parts: molecular function, biological process and cellular component. Figure 4 shows the GO enrichment analysis of the total DEGs between the GJL and DZ groups in terms of the biological process module; DEGs were enriched in cellular processes, biological regulation, metabolic processes, the regulation of biological processes and so on. In terms of the cellular component, DEGs were enriched in the cell, cell part, organelle, membrane and so on. While in terms of the binding, catalytic activity, molecular function regulator, molecular transducer activity and so on. Specifically, we list 10 of the most highly enriched signaling pathways according to their p-values in Table 2. In addition, all of the specific genetic information of the DEGSs analyzed by GO is listed in detail. ( Supplementary material Table S2.)
## 3.4. KEGG Pathway Enrichment Analysis
KEGG pathway enrichment analysis also performed on the DEGs in the DZ and GJL groups is shown in Figure 5. The up-regulated DEGs were mainly enriched in the neuroactive ligand-receptor interaction, amoebiasis, axon guidance, proteoglycans in cancer, Wnt and MAPK signaling pathway; while the down-regulated DEGs were mainly enriched in chemical carcinogenesis, fatty acid elongation, fatty acid metabolism, Jak-STAT signaling pathway and so on.
## 3.5. Tritiated Water Induced Protein Expression Differences in HacaT Cell
The results of the KEGG enrichment analysis showed that the expression of the Wnt signaling pathway was up-regulated, while Jak-STAT was down-regulated. Therefore, some genes (Wnt7b, Jak, STAT3) concluded that those two pathways were selected to verify the accuracy of the sequencing results of the Western blot assay. Figure 6 and Supplementary material Figure S1 show the protein expression of the DZ and GJL groups; the expression of Wnt7b was significantly increased, while Jak and STAT3 decreased in HacaT cells exposed to tritiated water. The results were consistent with the transcriptome results, which proved the accuracy of the sequencing results.
## 4. Discussion
In this study, HaCaT cells were used as the experimental objects to explore the damage effects of tritiated water. We found a significant decrease in cell viability after 48 h of treatment with 3.7 × 109 Bq/L tritiated water. Some previous reports in the literature proved that tritiated water could also inhibit the vitality of Human Umbilical Vein Endothelial Cells and cause cell senescence after long–term exposure [13,14,15]. In addition, tritiated water could also affect the vitality of rat lymphocytes and NK cells in terms of the immune system [16,17]. As a radioactive element, the damage to cells of tritiated water mainly included the following two aspects: first, tritium β–decay released energy, resulting in DNA single-strand break (SSB) or double-strand break (DSB), leading to cell apoptosis or cell senescence [34,35]. Some characteristics related to apoptosis and senescence ensued, such as cell cycle arrest, increased γH2AX and IL-8 contents, as well as an increase in the proportion of positive cells stained with β-galactosidase (SA-β-gal) [14,24]. Second, as ionizing radiation, Tritium caused the radiolysis of water, which promoted the formation of ROS [36] to attack intracellular biological macromolecules such as DNA, protein and lipids, causing cell damage [37]. In addition, Li et al. treated AHH-1-1 with 3.7 × 106 Bq/mL tritiated water, and only $72.1\%$ of the cells survived [17]. We have similar experimental conditions; the HacaT cell survival rate was about $87\%$ after treatment. This may be due to different cell types, resulting in different sensitivity to radiation. In addition, we calculated the total radiation dose (R) of tritiated water received by HaCaT cells according to this formula [38]: R = KEC0t. Where t is the radiation exposure time (s), which is 1.73 × 105 s (24 h) in our experiment, and C0 is the activity of tritiated water in the medium, which is 3.7 × 109 Bq/L in our experiment. E is the average energy of beta rays, 5.7 keV; K is the conversion coefficient, 1. 6 × 10−13 L·Gy/MeV. Thus, the total radiation dose of tritiated water received by HacaT cells in our study was 0.584 Gy.
In addition, the results of KEGG enrichment analysis and Western blot assay demonstrated that HaCaT cells treated with 3.7 × 109 Bq/L tritiated water for 48 h had significant changes in up-regulating the expression of Wnt and down-regulating Jak-STAT. Some researchers have shown that the Wnt pathway is involved in embryonic development, cardiovascular, wound healing, bone regeneration and other important life activities [39,40,41,42], but its abnormal activation or mutation was usually associated with Epithelial–mesenchymal transition (EMT) processes, which is a feature of cancer development and metastasis [43]. EMT was marked by the loss of E–cadherin (CDH1) and cell–cell adhesion junctions, which Wnt could down-regulate the expression of E–cadherin [44]. Shi et al. found that ROS could induce the expression of SOX2 under hypoxia and then activated the activation of Wnt/β-catenin, thus promoting the EMT of HacaT cells [45]. Quan et al. proved that tritium β-rays could lead to increased ROS and the occurrence of an inflammatory reaction in breast epithelial cell line McF–10a cells [46]. Therefore, we hypothesized that the up-regulation of the Wnt pathway induced by tritiated water was related to ROS production. In addition, the Jak–STAT pathway is involved in the regulation of cell proliferation, differentiation, apoptosis, angiogenesis, inflammation and immune response [47]. Some drugs, such as Acitretin and Rhododendron Album Blume Extract, could inhibit the growth and invasion of HacaT cells by down-regulating the Jak/STAT pathway [48,49].
## 5. Conclusions
In this study, we found that the viability of HacaT cells decreased under tritiated water exposure, and we further analyzed the sequencing results using bioinformatics. The results demonstrated that a total of 267 DEGs, of which 191 were significantly up-regulated DEGs and 76 were down-regulated(|log2FC| ≥ 0.6, Qvalue ≤ 0.05). GO enrichment analysis showed that up-regulated and down-regulated DEGs were mainly enriched in three parts. KEGG pathway enrichment analysis showed that up-regulated DEGs were involved in Wnt and other signaling pathways, while the down-regulated DEGs were enriched in Jak-STAT and others. Finally, Wnt7b, Jak and STAT3 were selected for Western blot experiments, and the results showed that the expression of Wnt7b increased and Jak, as well as STAT3, was decreased. Thus, the sequencing results were verified by Western blot assay. The results will provide a theoretical basis for the study of tritiated water hazard mechanisms.
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|
---
title: Molecular Investigation of DKK3 in Cerebral Ischemic/Reperfusion Injury
authors:
- Maria Caffo
- Roberta Fusco
- Rosalba Siracusa
- Gerardo Caruso
- Valeria Barresi
- Rosanna Di Paola
- Salvatore Cuzzocrea
- Antonino Francesco Germanò
- Salvatore Massimo Cardali
journal: Biomedicines
year: 2023
pmcid: PMC10045463
doi: 10.3390/biomedicines11030815
license: CC BY 4.0
---
# Molecular Investigation of DKK3 in Cerebral Ischemic/Reperfusion Injury
## Abstract
Dickkopf-3 (Dkk3) is an atypical member of the Dkk family of Wnt inhibitors, which has been implicated in the pathophysiology of neurodegenerative disorders. Its role in the mechanisms of cellular degeneration and protection is still unknown. The aim of our work is to investigate the endogenous activation of the DKK3 pathway in a model of transient occlusion of the middle cerebral artery in rats. In particular, the animals were subjected to 1 h of ischemia followed by different reperfusion times (1 h, 6 h, 12 h and 24 h) to evaluate the downstream pathway and the time course of its activation. Western blot analysis showed increased Dkk3 expression in animals with the highest time of reperfusion. The increased levels of Dkk3 were accompanied by reduced Wnt3a, Frz1 and PIWI1a expression in the cytosol while FOXM1 and β-catenin decreased in the nucleus. These molecular changes led to an increase in the apoptotic pathway, as showed by the increased expression of Caspase 3 and Bax and the reduced levels of Bcl-2, and to a decrease in neurogenesis, as shown by the decreased expression of Tbr2, Ngn2 and Pax6. In the second part of the study, we decided to employ curcumin, an activator of the Wnt/β-catenin signaling, to investigate its effect on Dkk3. In particular, curcumin was administered 1 and 6 h after ischemia, and animals were sacrificed 24 h later when the expression of Dkk3 was higher. Our data displayed that curcumin administration decreased Dkk3 expression, and increased Wnt3a, Frz1 and PIWI1a levels. Well in line with these data, curcumin administration increased nuclear β-catenin and FOXM1 expression. The down-regulation of Dkk3 by curcumin led to reduced apoptosis and increased neurogenesis. Summarizing, our results showed that Dkk3 acts as an inhibitor of Wnt/β-catenin signaling during cerebral ischemia. Additionally, its inhibition and the contextual activation of the Wnt/β-catenin pathway are protective against ischemic stroke.
## 1. Introduction
Stroke is a rapid alteration of cerebral blood supply that induces disturbance of cerebral function. It should be divided into two types: ischemic and hemorrhagic with, respectively, 15 and $85\%$ incidence [1,2]. Ischemic stroke is the third cause of mortality worldwide and the first cause of disability. Nevertheless, ischemic stroke still needs a treatment that has beneficial outcomes. In the acute phase of the event, there is glucose and oxygen depletion in the brain, a reduction in blood flow that alters ionic homeostasis, and an increase in reactive oxygen species (ROS) generation and intracellular calcium stress responses [3]. Additionally, inflammatory and apoptotic pathways lead to neuronal cell death and loss of biological functions [4]. Thus, one of the main goals of stroke treatment is the protection of neurons [5,6]. Of particular interest, researchers have underlined the activation of intrinsic and extrinsic pathways of cell death [7]. In the activation of the intrinsic pathway, the permeabilization and depolarization of the mitochondrial membrane and the release of proapoptotic mediators from the mitochondrial space are involved [8]. In particular, due to mitochondrial injury, cytochrome c is released leading to the proteolytic activation of caspases [9]. Among them, it has been described that the activation of caspase 3 is strongly increased in experimental models of ischemic stroke [7]. Wnt/β-catenin signaling has shown protective effects in the brain after traumatic brain injury [10]. It displayed neuroprotective effects preserving neurogenesis and having anti-apoptotic and anti-inflammatory properties [11]. In particular, in absence of Wnt ligands, β-catenin expression is reduced due to proteasome degradation, while in the presence of Wnt ligands, β-catenin levels increase. In this case, β-catenin translocates into the nucleus and initiates the transcription of Wnt target genes, including FOXM1, which blocks Bax and caspase 3 activation and increases Bcl-2 expression [12,13]. In addition, β-catenin can combine with transcription factors of the T-cell factor/lymphoid enhancer factor (Tcf/Lef) family and manage the expression of proteins such as Pax 6, neurogenin 2 and Tbr 2 [14,15,16]. The Wnt pathway is regulated by the Dickkopf (Dkk) family, which includes four members (Dkk1 to 4) of which Dkk3 differs from the others [17]. Different from the proteins of the same family, the modulatory effects of Dkk3 on the Wnt pathway are contest-dependent [18]. Several studies have displayed that Dkk3 has a key role in the regulation of fundamental cellular processes, such as cellular proliferation and differentiation death. Dkk3 acts in a variety of cancers as an oncosuppressor protein by inducing apoptotic death [19,20,21,22]; although, it might promote cancer cell spreading by inducing angiogenesis [23,24]. Dkk3 promotes kidney cell death [25] and, in contrast, promotes survival in retina cells [26]. The aim of this study was to assess how Dkk3 is involved in regulating the Wnt/β-catenin pathway during instances of cerebral ischemia and reperfusion injury.
## 2.1. Animals
Male Wistar rats (200–250 g) were purchased from Envigo (Milan, Italy) and employed for this study. All animal experiments agree with the new regulations in Italy (D.Lgs $\frac{2014}{26}$), EU regulations (EU Directive $\frac{2010}{63}$).
## 2.2. Surgical Procedure
Animals were anesthetized and middle cerebral artery (MCA) occlusion was performed by introducing a 4.0 nylon monofilament, precoated with silicone via the external carotid artery into the internal carotid artery to occlude the MCA [27,28]. Control animals were subjected to the same procedure, but no filament was introduced. At the end of the surgery, anesthesia was discontinued, and the animals were returned to a prone position [29].
The experimental procedures were performed according to the following protocol: [1]*After ischemia* animals were sacrificed at different timepoints (1 h, 6 h, 12 h and 24 h) and brain tissues were harvested for further analysis (Figure 1).Experimental groups:-Control animals sacrificed after 1 h from the surgery.-MCAO animals sacrificed 1 h after the end of occlusion.-Control animals sacrificed after 6 h from the surgery.-MCAO animals sacrificed 6 h after the end of occlusion.-Control animals sacrificed after 12 h from the surgery.-MCAO animals sacrificed 12 h after the end of occlusion.-Control animals sacrificed after 24 h from the surgery.-MCAO animals sacrificed 24 h after the end of occlusion.[2]One and six h after ischemia, animals were administered with curcumin (100 mg/Kg) [30], and sacrificed 24 h after the end of the occlusion (Figure 2). Brain tissues were harvested for further analysis. Experimental groups:-Control animals sacrificed after 24 h from the surgery,-MCAO animals sacrificed 24 h after the end of occlusion,-MCAO animals administered with curcumin 1 and 6 h after the end of the occlusion and sacrificed 24 h after the end of occlusion.
## 2.3. Quantification of Infarct Volume
Tissues were incubated in a $2\%$ solution of 2,3,5-triphenyltetrazolium chloride (TTC) for 30 min at 37 °C, processed, and quantified as previously described [31]. All analyses were carried out by two observers blinded to the treatment.
## 2.4. Western Blot Analysis
Western blots were performed as already described [32]. Brain samples were suspended in buffer A (0.2 mM phenylmethylsulfonyl fluoride, 0.15 μM pepstatin A, 20 μM leupeptin, and 1 mM sodium orthovanadate) homogenized for 2 min, and centrifuged at 10,000× g for 10 min at 4 °C. Supernatants represented the cytosolic fraction. The pellets, containing nuclei, were re-suspended in buffer B (150 mM NaCl, $1\%$ Triton X-100, 1 mM EGTA, 1 mM EDTA, 10 mM Tris–HCl pH 7.4, 0.2 mM phenylmethylsulfonyl fluoride, 20 μM leupeptin, and 0.2 mM sodium orthovanadate). After centrifugation for 30 min at 15,000× g at 4 °C, the supernatants contained nuclear proteins. Samples were stored at −80 °C for further analysis. Filters were probed with the primary antibodies: anti-Dkk3 (ab2459), or anti-wnt3a (ab28472), or anti-Frz1 (ab126262), or anti-PIWI1a (ab12337), or anti-β-catenin (ab32572), or anti-FOXM1 (sc-376471), or anti-Caspase 3 (ab13847), or anti-Bax (Santa Cruz Biotechnology, Dallas, TX, USA, sc526), or anti-Bcl-2 (Santa Cruz Biotechnology, sc492), or anti-Ngn2 (Santa Cruz Biotechnology, sc-293430), or anti-Tbr2 (Santa Cruz Biotechnology, sc-376776), or anti-Pax6 (ab109233) at 4 °C overnight. Membranes were incubated with peroxidase-conjugated bovine anti-mouse IgG secondary antibody or peroxidase-conjugated goat antirabbit IgG (Jackson ImmunoResearch, West Grove, PA, USA) for 1 h at room temperature. Blots were also incubated with primary antibodies against β-actin protein (Sigma-Aldrich, St. Louis, MI, USA) or laminin (Sigma-Aldrich Corp.), which were used as internal standards.
## 2.5. Statistical Analysis
All values are shown as the mean ± standard error of the mean (SEM) of N observations. Data were analyzed by one-way ANOVA followed by a Bonferroni post hoc test for multiple comparisons. A p-value of less than 0.05 was considered significant: * $p \leq 0.05$ versus sham; ** $p \leq 0.01$ versus sham; *** $p \leq 0.001$ versus sham; # $p \leq 0.05$ versus MCAO; ## $p \leq 0.01$ versus MCAO; ### $p \leq 0.001$ versus MCAO.
## 3.1. Analysis of Ischemic Brain Area
MCAO was performed in rats, sacrificing animals at different timepoints. TCC staining showed increased infarct volume with increased time of reperfusion (Figure S1). In order to evaluate the expression of Dkk3 in the brain at different time points and how it modulates the WNT/β-catenin pathway, Western blot analysis was performed. Dkk3 expression strongly increased with the time of reperfusion reaching the highest level at 24 h (Figure 3A). Levels of Wnt3a (Figure 3B), Frz1 (Figure 3C) and PIWI1a (Figure 3D) decreased with the time of reperfusion as compared to the control. Nuclear expression of FOXM1 (Figure 3E) and β-catenin (Figure 3F) decreased in MCAO animals with the time of reperfusion as compared to the control. All investigated proteins reached the lowest level at 24 h of reperfusion.
## 3.2. Analysis of Apoptosis and Neurogenesis in Ischemic Brain
Western blot analysis showed increased Caspase 3 (Figure 4A) and Bax (Figure 4B) expression in MCAO animals with the increased time of reperfusion, as compared to control, while Bcl-2 (Figure 4C) expression decreased in animals subjected to MCAO with the time of reperfusion. Western blot analysis also showed decreased Tbr2 (Figure 4D), Ngn2 (Figure 4E) and Pax6 (Figure 4F) expression in animals subjected to MCAO at the different times of reperfusion. The lowest expression was reached at 24 h after the occlusion.
## 3.3. Analysis of Dkk3 Expression after Curcumin Administration in Ischemic Brain
TCC analysis showed decreased infarct volume in animals administered with curcumin, as compared to the MCAO group (Figure 5A). Western blot analysis showed decreased Dkk3 expression (Figure 5B) and increased Wnt3a (Figure 5C), Frz1 (Figure 5D) and PIWI1a (Figure 5E) in animals administered with curcumin, as compared to MCAO rats. Nuclear FOXM1 (Figure 5F) and β-catenin (Figure 5G) expression increased in curcumin-administered rats, as compared to the MCAO group.
## 3.4. Analysis of Apoptosis and Neurogenesis after Curcumin Administration in Ischemic Brain
Western blot analysis showed increased Caspase 3 (Figure 6A) and Bax (Figure 6B) expression in MCAO animals, as compared to control, while Bcl-2 (Figure 6C) expression increased in animals subjected to MCAO. Curcumin administration decreased Caspase 3 (Figure 6A) and Bax (Figure 6B) levels and increased Bcl-2 (Figure 6C) expression. Western blot analysis also showed decreased Tbr2 (Figure 6D), Ngn2 (Figure 6E) and Pax6 (Figure 6F) expression in animals subjected to MCAO, as compared to control. Curcumin administration increased Tbr2 (Figure 6D), Ngn2 (Figure 6E) and Pax6 (Figure 6F) levels.
## 4. Discussion
Dkk3’s role and function in the management of the Wnt pathway are still unclear even though it shares about $40\%$ of protein identity with other well-characterized members of the Dkk family. Dkk3 diverges from all other family members because its modulatory action on this signaling is context-dependent and complex. The activation of the Wnt pathway has been described as neuroprotective in previous studies on cerebral ischemia and reperfusion [33]. This study focuses on the role of Dkk3 in Wnt signaling during neuronal injury. In the first part of our investigation, we investigated the expression of Dkk3 in the cerebral cortex surrounding the ischemic focus at different timepoints after ischemia. Dkk3 levels strongly increased with the time of reperfusion, reaching the highest expression at 24 h after ischemia. The upregulation of Dkk3 was accompanied by the down-regulation of Wnt3a, Frz-1 and PIWI1a expression at the same timepoints. Moreover, FOXM1 and β-catenin levels in nuclei were decreased. GSK3β is one of the main effectors of the Wnt/β-catenin pathway [34]. GSK3β induces the phosphorylation of β-catenin inducing its degradation into the cytoplasm [35,36]. GSK3β activity may be blocked by the phosphorylation of its Ser-9. This enzymatic inhibition leads to the stabilization of β-catenin. Once accumulated in the cytosol, β-catenin translocates into the nucleus and binds to the TCF/LEF factor, inducing the transcription of several genes [37]. In particular, the down-regulation of the Wnt/β-catenin induced by MCAO increased apoptosis, increasing Bax and Caspase 3 expression and reducing Bcl-2 levels. Additionally, the down-regulation of the Wnt pathway by Dkk3 also induced the decreased expression of the neurogenesis-promoting elements Tbr2, Ngn2 and Pax6. Ngn2 supported the differentiation of hippocampal neuroblasts [38]. Tbr2 supported the conversion from radial glia to progenitor cells [39], and Pax6 promotes the differentiation of neurons in the olfactory bulb [40]. All these data indicated that the cerebral ischemia and reperfusion injury increased the expression of Dkk3 in the borders of the ischemic focus leading to down-regulation of Wnt/β-catenin signaling. To examine how the expression of Dkk3 changes in time during ischemic stroke and how it manages the Wnt/β-catenin pathway, we decided to employ curcumin, a well-known activator of Wnt/β-catenin signaling, to investigate its effect on Dkk3. In particular, curcumin was administered 1 and 6 h after ischemia, and animals were sacrificed 24 h later when the expression of Dkk3 was higher. Our results showed that curcumin administration decreased Dkk3 expression, which, in turn, increased Wnt3a, Frz1 and PIWI1a levels. Well in line with these data, curcumin administration increased nuclear β-catenin and FOXM1 expression. The down-regulation of Dkk3 by curcumin led to reduced apoptosis by decreasing Caspase 3 and Bax expression and increasing Bcl-2 levels. Indeed, curcumin promotes neurogenesis as shown by Tbr2, Ngn2 and Pax6 increased levels.
However, this research has some limitations. Limitations of the model include its end-arterial occlusive nature that makes the lesion resistant to flow enhancement strategies. Additionally, deep investigations are required to describe how Dkk3 would influence other molecular pathways involved in the disease.
Overall, our results showed that Dkk3 acts as an inhibitor of Wnt/β-catenin signaling during cerebral ischemia. Additionally, its inhibition and the contextual activation of the Wnt/β-catenin pathway would be protective against ischemic stroke.
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|
---
title: 'Antioxidant Properties of Thymoquinone, Thymohydroquinone and Black Cumin
(Nigella sativa L.) Seed Oil: Scavenging of Superoxide Radical Studied Using Cyclic
Voltammetry, DFT and Single Crystal X-ray Diffraction'
authors:
- Raiyan Sakib
- Francesco Caruso
- Sandjida Aktar
- Stuart Belli
- Sarjit Kaur
- Melissa Hernandez
- Miriam Rossi
journal: Antioxidants
year: 2023
pmcid: PMC10045468
doi: 10.3390/antiox12030607
license: CC BY 4.0
---
# Antioxidant Properties of Thymoquinone, Thymohydroquinone and Black Cumin (Nigella sativa L.) Seed Oil: Scavenging of Superoxide Radical Studied Using Cyclic Voltammetry, DFT and Single Crystal X-ray Diffraction
## Abstract
Black cumin seeds and seed oil have long been used in traditional foods and medicine in South Asian, Middle Eastern and Mediterranean countries and are valuable flavor ingredients. An important ingredient of black cumin is the small molecule thymoquinone (TQ), which manifests low toxicity and potential therapeutic activity against a wide number of diseases including diabetes, cancer and neurodegenerative disorders. In this study, the antioxidant activities of black seed oil, TQ and a related molecule found in black cumin, thymohydroquinone (THQ), were measured using a direct electrochemical method to experimentally evaluate their superoxide scavenging action. TQ and the black seed oil showed good superoxide scavenging ability, while THQ did not. Density Functional Theory (DFT) computational methods were applied to arrive at a chemical mechanism describing these results, and confirmed the experimental Rotating Ring Disk Electrode (RRDE) findings that superoxide oxidation to O2 by TQ is feasible, in contrast with THQ, which does not scavenge superoxide. Additionally, a thorough inquiry into the unusual cyclic voltammetry pattern exhibited by TQ was studied and was associated with formation of a 1:1 TQ-superoxide radical species, [TQ-O2]−•. DFT calculations reveal this radical species to be involved in the π-π mechanism describing TQ reactivity with superoxide. The crystal structures of TQ and THQ were analyzed, and the experimental data reveal the presence of stacking intermolecular interactions that can be associated with formation of the radical species, [TQ-O2]−•. All three of these methods were essential for us to arrive at a chemical mechanism that explains TQ antioxidant activity, that incorporates intermolecular features found in the crystal structure and which correlates with the measured superoxide scavenging activity.
## 1. Introduction
The annual herb *Nigella sativa* L. is native to the Mediterranean region, northern Africa and south Asia. Historical evidence of its use by ancient civilizations in those areas exists and seeds of the plant (black cumin) were even found in King Tutankhamen’s tomb [1]. Today, populations in those geographical locations still use the black seeds and the related oil, containing the phytochemicals thymoquinone (TQ) and thymohydroquinone (THQ), in traditional foods as valuable flavor ingredients and for medicinal purposes, ingested with food or honey [1,2]. The main active phytochemicals in the seeds and oil include several monoterpenes, TQ (by far, the highest concentration), THQ, p-cymene, carvacrol and thymol [3]. Additionally, black cumin seed oil is rich in nutritionally beneficial fatty acids such as linoleic acid ($57.71\%$) and oleic acid ($24.46\%$) [2]. As with many agricultural materials, black seeds and the related cold-pressed oil show compositional variation depending on the area of cultivation [4].
Importantly, black seeds and their oil have demonstrated widespread action against numerous diseases. Because the low toxicity and potential therapeutic activity of TQ is notable, including diseases such as diabetes, cancer and neurodegenerative disorders, it has been the subject of many review articles [5,6,7]. Recently, TQ therapeutic activity has extended to include its use as a viable treatment against Covid-19 [8]. The presence of TQ and THQ in other plant species besides N. Sativa, including the *Thymus vulgaris* L. and Origanum species, is confirmed [5,9]. Studies on the biosynthesis of TQ and THQ in Lamiaceae established that the monoterpenes, thymol and carvacrol, are used to produce THQ by cytochrome P-450 enzymes, CYP76S40 or CYP736A300, which then is converted to TQ [10].
An objective of this study was to obtain chemical data to help clarify the relationship between the antioxidant and free radical scavenging properties of these substances and to gain insight into the chemical mechanisms underlying the therapeutic benefits of these phytochemical ingredients. We investigated the crystal and molecular structures of the small molecules TQ and THQ, as this method also reveals information regarding intermolecular interactions among neighboring molecules. We measured the antioxidant activity of black seed oil, TQ and THQ using the RRDE and one-electrode cyclic voltammetry electrochemical methods to obtain information about scavenging properties. Last, we used DFT methods to describe electronic properties since these are related to a molecule’s ability to donate and/or receive electron density and its antioxidant capability. These computational methods were essential for us to arrive at a superoxide scavenging chemical mechanism that incorporates intermolecular features found in the crystal structure and which correlates with the measured superoxide scavenging activity.
## 2.1. Reagents
Thymoquinone (Toronto Research Chemicals, Toronto, ON, CA), thymohydroquinone (Cayman Chemical, Ann Arbor, MI, USA) and Cold Pressed Black Seed Oil (Maju Superfoods, San Diego, CA, USA). For electrochemical studies, tetrabutylammonium bromide (TBAB; TCI Chemicals, Portland, OR, USA) and $99.9\%$ anhydrous Dimethyl Sulfoxide (DMSO; Sigma-Aldrich, Inc., St. Louis, MO, USA).
## 2.2.1. Electrochemistry
A Pine Research WaveDriver 20 bipotentiostat with the Modulated Speed Electrode Rotator was used to perform the hydrodynamic voltammetry at a rotating ring-disk electrode (RRDE) as well as cyclic voltammetry (CV). The working electrode is the AFE6R2 gold disk and gold ring rotator tip (Pine Research, Durham, NC, USA) combined with a coiled platinum wire counter electrode and a reference electrode consisting of an AgCl coated silver wire immersed in 0.1 M tetrabutylammonium bromide (TBAB) in dry DMSO in a fritted glass tube. The electrodes were placed in a five-neck electrochemical cell together with means for either bubbling or blanketing the solution with gas. Voltammograms were collected using Aftermath software provided by Pine Research. Careful cleaning of the electrodes was performed by polishing with 0.05 µm alumina-particle suspension (Allied High Tech Products, Inc., Rancho Dominguez, CA, USA) on a moistened polishing microcloth to eliminate potential film formation [11]. Cyclic voltammetry was performed using the same electrodes and cell.
## 2.2.2. X-ray Diffraction
An APEX2 DUO platform X-ray diffractometer from Bruker Advanced X-ray Solutions (Madison, WI, USA) was used to obtain X-ray data measurements on suitable crystals at 125 K. Temperature was maintained using a cold liquid nitrogen stream from Oxford Cryosystems (UK).
## 2.3.1. Hydrodynamic Voltammetry (RRDE)
Stock clear light-yellow 0.03 M solution of TQ (0.0492 g in 10 mL) and clear colorless 0.03 M solution THQ (0.0498 g in 10 mL), in anhydrous DMSO ($99.9\%$ purity), were used in trials, whereas black seed oil was directly introduced in the electrochemical cell.
For the experiment, a solution of 0.1 M TBAB electrolyte in anhydrous DMSO was bubbled for 5 min with a dry O2/N2 ($35\%$/$65\%$) gas mixture to establish the dissolved oxygen level in the electrochemical cell of 50 mL. The Au/Au disc electrode was then rotated at 1000 rpm and potential sweep applied to the disk from 0.2 V to −1.2 V and then back to 0.2 V while the ring was held constant at 0.0 V; the disk voltage sweep rate was set to 25 mV/s. The molecular oxygen reduction peak (reaction 1) is observed around −0.6 V, at the disk electrode; the oxidation current (reaction 2) occurs at the ring electrode. An initial blank, in the absence of an antioxidant, was run on this solution and the ratio of the ring/disk current was calculated as the “efficiency”. This blank efficiency was found to be about $20\%$. Next, an antioxidant aliquot was added, the solution bubbled with the gas mixture for 5 min, the voltammogram was rerecorded, and efficiency obtained. In this way, the rate at which increasing concentrations of antioxidant scavenge the generated superoxide radicals during the electrochemical reaction is determined as each additional antioxidant aliquot is added. Results from each run were collected on Aftermath software and represented as voltammograms showing current vs. potential graphs that were later analyzed using Microsoft Excel. The aliquots used are indicated in related RRDE graphs. Ultimately, the slope of the overall decrease in efficiency with addition of antioxidant serves as a quantitative measure of the antioxidant activity of each compound. Any decrease in the collection efficiency is expected to be due to the amount of superoxide removed by the antioxidant.
In an RRDE voltammetry experiment, the generation of the superoxide radicals occurs at the disk electrode while the oxidation of the residual superoxide radicals (that have not been scavenged by the antioxidant) occurs at the ring electrode.
Reaction 1: Reduction of molecular oxygen at the disk electrode Disk Reaction O2 + e− → O2•− [1] Reverse Reaction 2: Oxidation of superoxide radicals at the ring electrode Ring Reaction O2•− → O2 + e− [2]
## 2.3.2. Cyclic Voltammetry
On completion of the RRDE study of TQ, CV was performed both in the presence and absence of oxygen dissolved in the DMSO solvent in order to further study the reactions occurring at the electrode surfaces.
## 2.4. Computational Study
Calculations were performed using software programs from Biovia (San Diego, CA, USA). Density Functional Theory (DFT) included in DMol3 was applied to calculate energy, geometry, and frequencies implemented in Materials Studio 7.0 (PC platform) [12]. We employed the double numerical polarized (DNP) basis set that included all the occupied atomic orbitals plus a second set of valence atomic orbitals, and polarized d-valence orbitals [13]; the correlation generalized gradient approximation (GGA) was applied including Becke exchange [14] plus BLYP-D correlation including Grimme’s correction when van der Waals interactions were involved [15]. All electrons were treated explicitly and the real space cutoff of 5 Å was imposed for numerical integration of the Hamiltonian matrix elements. The self-consistent field convergence criterion was set to the root mean square change in the electronic density to be less than 10−6 electron/Å3. The convergence criteria applied during geometry optimization were 2.72 × 10−4 eV for energy and 0.054 eV/Å for force. Calculations included the effect of DMSO solvent using the continuous model of Dmol3 [16], to allow correlation with the experimental features from cyclovoltammetry results.
## 2.5. Diffraction Study
Suitable large yellow single crystals of TQ were grown from a 2:1 (v/v) methanol:water solution. Colorless crystals of THQ were recrystallized from 1:1 (v/v) ethanol:water solution. The crystal structures were solved and refined using full-matrix least-squares on F2 with the Bruker incorporated ShelX programs [17]. We input the X-ray data into the MERCURY program from Cambridge Structural Database (CSD) to produce images of the molecules and crystal packing [18]. Crystal data of THQ and TQ have been deposited at the CSD and are available at https://www.ccdc.cam.ac.uk/structures/? ( accessed on 1 January 2023) using Identifier CCDC number 2239493-2239494 and are available upon request [19].
## 3.1. Diffraction Study
Crystal data for THQ and TQ are given in Table 1. Both THQ and TQ crystallized with two molecules in the asymmetric unit, displayed in Figure 1. Atomic distances and angles in both structures agree with expected values.
## 3.1.1. Thymoquinone
The two molecules in the asymmetric unit differ mainly in the rotation of the isopropyl group, as seen in Figure S1.
Alternating inversion center related molecules of TQ are stacked in a displaced manner primarily along the a axis, allowing the hydrophobic isopropyl and methyl groups to be close to each other. The displaced stacking among these planes is close to 3.4 Å. Similarly, TQ molecules in the same plane are arranged with CH…O close contacts of about 3.4 Å. These are displayed in Figure 2 and illustrate that only van der Waals forces are seen in the crystal structure.
A lower-resolution powder diffraction structure of thymoquinone had been earlier reported with CSD refcode NIDKER [20]. This structure determination was not able to detect the hydrogen atoms in the molecule.
## 3.1.2. Thymohydroquinone
The space group for THQ was ultimately chosen to be the non-centric space group Pc. The centrosymmetric P21/c was attempted, but refinement in that space group gave an unacceptable solution with much higher R-value and abnormally high anisotropic displacement parameters. As expected, THQ manifests extensive and strong hydrogen-bonding intermolecular interactions, which are shown in Figure 3, and whose geometric details are reported in Table 2. Each hydroxyl group (O1H, O2H in Molecule 1 and O3H and O4H of Molecule 2 in the asymmetric unit) has two strong intermolecular hydrogen bonds creating an infinite hydrogen bond network throughout the crystal structure. No stacking interactions are evident.
## 3.2.1. Thymoquinone
After X-ray atomic coordinates of TQ were input in Materials Studio (Dmol3) quantum mechanical program, geometry optimization was applied and the resulting minimum energy structure is shown in Figure 4A. Single bonds in the quinone ring are in the range 1.47–21.501 Å, obviously longer than the two double bonds, 1.356 Å (compared with X-ray values of 1.473–1.493 Å (single) and 1.337–1.342 Å (double)).
Next, we studied the TQ structural modifications after a superoxide radical was π-π placed at van der Waals separation (3.50 Å) between quinone and superoxide centroids. DFT geometry minimization, Figure 4B, shows the superoxide being more distant, 3.579 Å apart, and with the initial superoxide O-O bond length distance of 1.373 Å shortening to 1.283 Å, which rather corresponds to the O2 double bond distance. Meanwhile, the TQ ring bond lengths become modified, for instance, C=C double bonds become longer, 1.372 Å (from initial values shown in Figure 4A 1.356 Å), while the quinone single C-C bonds become 0.02–0.03 Å shorter. Shorter single bonds and longer double bonds can be associated with ring aromatization, suggesting the unpaired electron of superoxide is donated to the quinone ring. This result has already been observed by us in related polyphenols scavenging superoxide [21]. The electron captured by the ring also has an effect on the C=O bond lengths as they become elongated by 0.03 Å. We call this process (a). From Figure 4 we conclude that superoxide oxidation (and O2 formation) by TQ is feasible.
However, since TQ has no hydroxyls available, an alternative process (b) can be envisioned involving interaction between the quinone and available protons. This route can induce reduction of a C=O carbonyl to a C-OH moiety and has been described for the quinone natural product embelin [22]. The initial state of this process is shown in Figure 4C, where a proton is placed at van der Waals separation from the O(carbonyl), 2.60 Å (1.20 Å + 1.40 Å, for H and O van der Waals radii, respectively), Figure 4A. After DFT minimization, Figure 4D shows the proton captured by the TQ, O-H bond length = 0.986 Å, and lengthening of the corresponding C-O bond, 1.311 Å, compared to initial 1.241 Å in Figure 4A, thus confirming C-OH formation. Indeed, Figure 4D shows the input for the next DFT calculation, i.e., the approach of an additional proton to the second O(carbonyl) in TQ, located initially at 2.60 Å, and which results in the energy minimum moiety shown in Figure 4E, a 2+ charged polyphenol (from 2 captured protons), and having 2 hydroxyls, [THQ]2+. As observed in Figure 4B, superoxide is able to transfer its unpaired electron to the TQ ring, and we can expect that the dicationic polyphenol in Figure 4E will permit an even easier electron transfer to the ring. Indeed, this happens and the DFT outcome after energy minimization of the initial structure, a superoxide π-π posed at 3.50 Å (Figure 4E), is shown in Figure 4F, having shorter separation between stacked centroids, 2.697 Å. Upon an additional π-π attack by a second superoxide on the opposite side of the polyphenol ring, this radical also binds to the ring with a longer separation, 2.987 Å, Figure 5. This resulting thymohydroquinone-η-2O2 complex is a neutral species with aromatic character, as shown by the ring C-C bonds in the range 1.394–1.418 Å; this is process (b). Attempts to extract one H(hydroxyl) from the thymohydroquinone-η-2O2 structure shown in Figure 5, by an additional superoxide via σ attack, were not successful, as the possible expected radical product {[thymohydrosemiquinone-η-2O2]• HO2−} is +4.3 Kcal/mol higher than the reagent, thus indicating no further reactivity of the thymohydroquinone-η-2O2 complex.
As recently described, molecular oxygen is an important product when polyphenols act as mimics of superoxide dismutase enzymes, following reaction [3] [23]. 2 O2•− + 2H+ → O2 + H2O2 [3] The reacting proton component of reaction [3] is associated with a polyphenol hydroxyl H atom transfer (HAT, σ attack, [23]) and is more often described in polyphenol antioxidant studies than the π-π attack. According to our DFT results, in TQ scavenging of superoxide, the reaction [3] reactants are involved, since two protons (Figure 4C,D) are captured as well as two superoxide radicals (Figure 4F and Figure 5), but the products of reaction [3], O2 and H2O2, are not produced by process (b). However, the independent process (a), shown in Figure 4B, suggests O2 formation. In any case, H2O2 is not produced, and so TQ does not mimic SOD action, unlike behavior recently described for some polyphenols [23]. We conclude that TQ scavenging of superoxide can be described only in terms of stoichiometric reactions.
## 3.2.2. Thymohydroquinone
THQ X-ray atomic coordinates were treated in a similar way with Dmol3. The DFT energy minimum structure Figure 6A shows aromatic ring distances (1.40–1.41 Å), which can be compared to the corresponding X-ray values (1.37–1.41 Å). A superoxide σ-oriented towards one H(hydroxyl), initially at van der Waals separation 2.60 Å, results in a structure having shorter separation, 1.583 Å, Figure 6B. This structure was compared with the one obtained after posing a HO2− anion near the corresponding thymohydrosemiquinone radical (a calculation describing the potential expected product), which resulted in a slightly shorter H–O separation, 1.564 Å, Figure 6C. A comparison between the results of both minimizations showed ΔG of 0.3 kcal/mol, indicating no product feasibility. The π-π attack was also analyzed after placing superoxide on top of Figure 6A, and DFT minimization showed both reagents rejected, Figure 4D. We conclude that THQ does not scavenge superoxide.
## 3.3.1. Thymoquinone
The antioxidant activity of TQ was studied using an electrochemical technique developed by Belli et al. [ 24]. Figure 7 shows RRDE graphs of TQ for all aliquots. Figure 8 shows the corresponding collection efficiency, while Figure 9 shows the collection efficiency of the initial five TQ additions. In addition, CV was performed on a O2 saturated solution (bubbled 5 min) containing a single TQ aliquot (Figure 10), and then after purging with dry N2 gas, Figure 11. Both CVs show two complete scans.
The collection efficiency for the TQ RRDE experiment (Figure 8) is anomalous, showing an initial decrease in efficiency through the first four TQ additions (as normally observed), but then the efficiency increased with each further addition of TQ aliquot, which has never been observed in previous studies [22,24,25,26,27]. To clarify this behavior of TQ, cyclic voltammetry of an RRDE solution yielded the voltammogram in Figure 10. Under these conditions, the reduction of oxygen to generate superoxide, reaction [1], −0.60 V, as well as the reverse reaction [2] (oxidation of superoxide), −0.30 V, was previously examined by analyzing a blank solution (without antioxidant), Figure 12 [24]. We analyzed the peaks seen in Figure 10, starting with the first reduction peak (non-reversible) at about −0.30 to −0.35 V and assigned it to incorporation of an electron into TQ (TQ + e- → [TQ]●). A reverse reaction was not observed, as after reversing the potential (more positive) than 0.20 V, no related oxidation peak was seen (not shown).
To assign the first oxidation peak, labelled in Figure 10 at about −0.45 V, we used DFT to analyze the reactivity of [TQ]−• (seen at peak −0.30 to −0.35 V), and saw that this species is able to react with bubbled oxygen to form the radical [TQ-O2]−•, Figure 13, a reaction not influenced by the further negative electrochemical potential. This capture of O2 by a radical species is uncommon, and the resulting species, [TQ-O2]−•, is therefore associated with its oxidation peak in Figure 10. By purging the electrochemical cell with bubbled nitrogen, in Figure 11, the peak was strongly decreased, consistent with decreasing O2, although not completely eliminated because of the presence of some residual non-purged oxygen. Thus, the anomalous increase in efficiency, Figure 8, is not associated with antioxidant features of TQ, and contrary to results seen for previously studied scavengers [22,24,25,26,27]. Rather, this increase in efficiency is due to increasing [TQ-O2]−• concentration, formed as TQ aliquots are added and react with bubbled O2.
However, it is interesting to compare the peaks associated with reactions [1] and [2] in Figure 10, as reaction [2] peak height (indicated by short vertical arrow) is shorter than that of reaction [1] (represented by longer horizontal arrow). For comparison, Figure 12 shows a typical blank, also using one working electrode, where both peak heights are seen to be equal. Thus, in Figure 10, the difference in peak height between the amount of superoxide present at the oxidation peak and the amount of superoxide at the reduction peak is due to TQ scavenging of superoxide. These features have been characterized in a previous study using both electrochemical methods, RRDE and CV [24]. The interference of radical [TQ-O2]−• seems not to be important at low concentrations of TQ, as seen in the first five data points in Figure 8. These initial values are plotted in Figure 9 to obtain the efficiency at low concentrations; the related slope (slope = −2.11 × 104) for the linear expression y = −21104x + 20.9 (R2 = 0.9965), is a good indicator of superoxide scavenging ability of TQ. We conclude that RRDE experiments on TQ show a mixed effect: on one hand, at low concentrations, TQ is able to scavenge superoxide, and shows the expected decreasing efficiency while at higher TQ concentrations, an unexpected increase in efficiency can be associated with formation of the [TQ-O2]−• radical. This radical species is oxidized after reversing the potential at about −0.45 V in the electrochemistry experiment using one working electrode, or alternatively, is detected at the ring electrode, whose setting is 0.0 V in the RRDE experiment.
Table 3 shows electrochemical RRDE data of other polyphenols analyzed previously. The slope of TQ, −2.11 × 104 falls between chrysin and eriodyctiol, but is closer in value to the latter.
Our results support earlier investigations that describe TQ superoxide scavenging ability [28] as well as a thorough inquiry on the unusual cyclic voltammetry pattern shown by TQ [29].
## 3.3.2. Thymohydroquinone
THQ was also explored with the RRDE method, and results are shown in Figure 14. There was no variation in disk and ring current, and so THQ does not scavenge superoxide, in agreement with the results of the DFT study described earlier, and so the data show no change from the blank run, both below and above the potential axis, indicating unmodified reaction [1] and [2], respectively. In other words, THQ has no effect on the RRDE outcome.
## 3.3.3. Black Seed Oil
Black seed oil was also analyzed, and its RRDE cyclovoltammetry data are shown in Figure 15. Figure 16 shows decreasing collection efficiency overall, with the greatest decrease at low concentrations. Figure 17 shows the collection efficiency of the first four aliquots, having good linear behavior (y = −0.0781x + 20.08, R2 = 0.9763), demonstrating a good scavenging ability by the black seed oil.
Earlier RRDE studies by our group on another cold-pressed vegetable oil, extra virgin olive oil [30], allow us to compare the slope of the RRDE efficiency of black seed oil (−0.078) and that of extra virgin olive oil (−0.0838). The latter is characterized by a linear trend (y = −0.0838x +19.73, R2 = 0.99348) for all 11 runs, (aliquot range 0–100 µL), and shows a slightly better scavenging of superoxide by olive oil.
## 4. Conclusions
The molecular mechanisms that underlie the therapeutic effects of TQ are not completely understood, and literature reports show that TQ likely interacts with a number of receptors. Its low toxicity and the fact that TQ as well as the oil and seeds from which it is isolated have been used for thousands of years, make studying its therapeutic capacity appealing [6].
In this work, we have measured the superoxide scavenging ability of cold-pressed black cumin oil and two of its ingredients, TQ and THQ. Our results show that the oil and TQ are strong scavengers of the superoxide radical, whereas THQ has no effect on the scavenging, despite the presence of two para-hydroxyl groups. Structural X-ray diffraction data support subsequent DFT calculations that show a path of energetically feasible molecular transformations which corroborate cyclovoltammetry experimental features, i.e., the scavenging of superoxide by TQ, and no scavenging by THQ. The suggested stoichiometric reactivity of TQ when reacting with superoxide involves 1) direct π-π attack, involving superoxide oxidation to produce O2 as a product, and 2) superoxide σ proton attack on a TQ O(carbonyl), which gets reduced to C-OH, and is not sensitive to further attack by superoxide.
This theoretical assessment is confirmed using two cyclovoltammetry techniques, cyclic voltammetry and hydrodynamic voltammetry at an RRDE. Lastly, our work shows the efficacy of combining multidisciplinary approaches, including experimental X-ray crystallography and voltammetry as well as computational DFT methods, to provide understanding of the mechanism of action of small molecule antioxidants. This research supports further exploration of other natural products having important biomedical activities.
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|
---
title: 'Monosodium Glutamate Perturbs Human Trophoblast Invasion and Differentiation
through a Reactive Oxygen Species-Mediated Pathway: An In-Vitro Assessment'
authors:
- Indrani Mukherjee
- Subhrajit Biswas
- Sunil Singh
- Joyeeta Talukdar
- Mohammed S. Alqahtani
- Mohamed Abbas
- Tapas Chandra Nag
- Asit Ranjan Mridha
- Surabhi Gupta
- Jai Bhagwan Sharma
- Supriya Kumari
- Ruby Dhar
- Subhradip Karmakar
journal: Antioxidants
year: 2023
pmcid: PMC10045473
doi: 10.3390/antiox12030634
license: CC BY 4.0
---
# Monosodium Glutamate Perturbs Human Trophoblast Invasion and Differentiation through a Reactive Oxygen Species-Mediated Pathway: An In-Vitro Assessment
## Abstract
The overproduction of reactive oxygen species (ROS) has been associated with various human diseases. ROS exert a multitude of biological effects with both physiological and pathological consequences. Monosodium glutamate (MSG), a sodium salt of the natural amino acid glutamate, is a flavor-enhancing food additive, which is widely used in Asian cuisine and is an ingredient that brings out the “umami” meat flavor. MSG consumption in rats is associated with ROS generation. Owing to its consumption as part of the fast-food culture and concerns about its possible effects on pregnancy, we aimed to study the impact of MSG on placental trophoblast cells. MSG exposure influenced trophoblast invasion and differentiation, two of the most critical functions during placentation through enhanced production of ROS. Similar findings were also observed on MSG-treated placental explants, as confirmed by elevated Nrf2 levels. Ultrastructural studies revealed signs of subcellular injury by MSG exposure. Mechanistically, MSG-induced oxidative stress with endoplasmic reticulum stress pathways involving Xbp1s and IRE1α was observed. The effect of MSG through an increased ROS production indicates that its long-term exposure might have adverse health effect by compromising key trophoblast functions.
## 1. Introduction
Reactive oxygen species (ROS) refer to oxygen-containing molecules having an unpaired electron or to unstable compounds such as hydrogen peroxide (H2O2), superoxide (O2−), hydroxyl (OH−), and peroxyl radicals [1]. ROS are naturally produced, the majority being a by-product of mitochondrial oxidative phosphorylation [2]. At physiological levels, ROS are produced at the preimplantation milieu and are found to be critical for early embryogenesis. However, the redox balance in the early window of embryo development needs to be precisely controlled owing to the detrimental effects by the overproduction of ROS [3]. Any deviation from redox homeostasis can have serious consequences affecting the embryo implantation and its subsequent development.
In pregnancy-related disorders, such as preeclampsia (PE) and pregnancy-induced hypertension, an increase in oxidative stress is considered to be a major inducing factor [4]. Oxidative stress (OS) is reported to cause tissue damage and other related pathologies [5,6,7,8]. In PE patients, ROS increases the level of lipid peroxidation, mainly malondialdehyde (MDA), which is majorly owing to the decline in activity of the antioxidant defense machinery [9]. Monosodium glutamate (MSG) is a known food additive and is used as a major ingredient in most commercially prepared foods [10]. The global size of the glutamic acid market has been estimated to be over 2.9 million tons in 2014 and more than 4 million tons by 2023 [11]. The MSG-related revenue is expected to be worth more than USD 15.5 billion by 2023, growing with an estimated compound annual growth rate above $7.5\%$ up to 2023 [11]. With such an enormous appetite for this additive in the food industry, the health concerns are also substantial given that MSG administration increases the number of pachytene stage cells in primary spermatocytes [12,13] and induces OS [14,15] and free radical generation [16,17]. In addition, obesity [18,19,20,21], disorders of the central nervous system [10,22,23], hepatic damage [24,25,26], reproductive malfunctions [12,27,28,29], cardiovascular diseases [30,31], and hypertension [32,33,34] are considered to be some of the major side effects of MSG.
However, the detailed molecular pathogenesis regarding MSG consumption is poorly understood. The placenta is important in sustaining a pregnancy and supporting fetal growth and development. Trophoblast cells constitute the functional and structural components of the placenta to support pregnancy by orchestrating delicate feto-maternal crosstalk and its endocrine function. This involves the exchange of nutrients and waste materials across the feto-placental unit. Trophoblast cells are transiently invasive [35,36] and participate in the remodeling of the maternal uterine matrix and its vasculature to gain access to its nutrient-rich milieu. Successful pregnancy depends on the efficiency of this process, which depends on an efficient trophoblast differentiation program.
Therefore, in the present study, we investigated the effect of MSG on placental trophoblast cells and extrapolated its possible consequences on placental function. Whether maternal consumption of MSG will result in its trans-placental transport to the developing embryo is still debatable. However prolonged consumption and exposure could affect the function of placental trophoblast cells either directly or indirectly through dysregulating the redox homeostasis at the feto-placental interface.
## 2.1. Cell Culture
HTR-8/SVneo cells and BeWo choriocarcinoma cells were obtained from American Type Culture Collection (ATCC, Rockville, MD, USA). Cells from relatively early passages ($R = 3$) were cultured using RPMI-1640 (HyClone) containing $1\%$ penicillin-streptomycin (Invitrogen) and $10\%$ fetal bovine serum (FBS) (Invitrogen) [37].
Cells (1 × 106) were plated in a 90-mm petri dish and cultured at 37 °C within a humidified chamber with $5\%$ CO2. The experiments were broadly divided into acute and chronic stimulation. Acute stimulation groups were divided into three sub-groups: (i) control, (ii) cells treated with 25 mM MSG for 24 h, and (iii) cells treated with 50 mM MSG for 24 h (Figure S1A,B). Chronic stimulation groups were divided into two sub-groups: (i) control and (ii) cells treated with 25 mM MSG every alternate day for 16 days (Figure S1C,D).
To confirm the induction of OS in acute conditions, cells were (iv) treated with 10 mM N-acetyl cysteine (NAC), a potent antioxidant, for 24 h and (v) pretreated with NAC for 2 h followed by MSG treatment for 24 h. To perform rescue experiments in chronic conditions, cells were (a) treated with 10 mM NAC on every alternate day and (b) pretreated with NAC for 2 h followed by 25 mM MSG treatment on every alternate day, for 16 days. At 50–$60\%$ confluence, cells were kept in a phenol red-free medium containing $5\%$ FBS and treated with NAC and MSG.
## 2.2. Explant Culture
First-trimester human placental samples of different gestational ages between 8–10 weeks were obtained from medically terminated pregnancies ($$n = 10$$) after delivery, and their tissue explants were cultured.
Small tissue sections (10 mg) were cut and plated in a collagen-I-coated single well of 12-well plates (Corning). Tissue sections were washed thoroughly using 1× phosphate-buffered saline (PBS), and RPMI-1640 with $10\%$ FBS and $1\%$ penicillin–streptomycin was added. Tissues were cultured at 37 °C within a humidified chamber under $5\%$ CO2 [37]. For experimental purposes, early villi sections were divided into two groups: (i) control and (ii) sections treated with 50 mM MSG for 24 h (Supplementary Figure S1E). Tissues were treated with TriZol (Thermo Fisher Scientific, Washington, DC, USA) for RNA isolation. The explants were divided into two more sub-groups: (i) explants treated with 10 mM NAC for 24 h and (ii) explants pretreated with NAC for 2 h followed by 50 mM MSG treatment for 24 h to assess ROS generation. The explants were stimulated for 72 h also to study their ultrastructural changes after chronic stimulation by MSG.
## 2.3. RNA Isolation and Reverse Transcription–Quantitative Polymerase Chain Reaction (RT-qPCR)
Total RNA was extracted from cells using an RNA Simple Total RNA isolation kit (Promega RNA Tissue/Cell Miniprep System) according to the manufacturer’s instructions. In-column DNase digestion was performed to obtain DNase-free RNA. RNA was quantified using Nanodrop (Thermo Fisher Scientific, Inc., Washington, DC, USA), and agarose gel electrophoresis was performed to assess RNA integrity. RNA samples were then reverse transcribed into cDNA using a Verso cDNA synthesis kit (AB1453A, Thermo Fisher Scientific, Inc., Washington, DC, USA). RT-qPCR was performed using a DyNAmo Flash SYBR Green qPCR kit (F415S, Thermo Fisher Scientific, Inc., Washington, DC, USA). The reaction cycles were as follows: incubation at 95 °C for 7 min, 40 cycles at 95 °C for 15 s and 60 °C for 20 s. The PCR products were subjected to a melting curve analysis to confirm amplification specificity. mRNA levels were then normalized with respect to mRNA levels of GAPDH using the 2−ΔΔCq method [37]. PCR primer sequences are provided in Table S1.
## 2.4. Cell Viability and Proliferation Assay
Cells were plated in 96-well plates and treated with different doses of MSG (5, 25, 50, 100, 150, and 200 mM) for 24 h. Water-soluble tetrazolium-1 (WST-1) assay was performed to assess the proliferation and viability of cells following the manufacturer’s protocol. Results were analyzed by comparison with the standard curve [37].
## 2.5. Cell Cycle and Apoptosis
For cell cycle analysis, MSG-treated trophoblast cells (HTR-8/SVneo and BeWo) were collected from the log phase, washed with 1× PBS, and fixed with $70\%$ ethanol overnight at 4 °C. After washing twice with 1× PBS, cells were resuspended and incubated in 500 µL PBS containing 100 µg/mL RNase and 50 µg/mL propidium iodide (PI) for 30 min at room temperature. Cells were analyzed by flow cytometry (ThermoFisher Scientific, Cat No. V13242, Washington, DC, USA), and the percentage of cell proliferation was analyzed using GraphPad Prism v.6.01.
The extent of apoptosis was analyzed by flow cytometry using Annexin V-FITC/propidium iodide (PI) double-label assay, according to the manufacturer’s protocol (BMS500FI/100CE, Invitrogen). Cells (1 × 106) were trypsinized and incubated in 100 μL binding buffer containing 5 μL AnnexinV/FITC and 10 μL 20 μg/mL PI for 15 min in the dark at room temperature. A total of 10,000 events/runs were acquired, and the results were analyzed using FlowJo software (Ashland, OR, USA) [37].
## 2.6. ROS Production
Cells were plated in 12-well plates and treated with 25 and 50 mM MSG for 24 h (acute group) and 25 mM MSG every alternate day for 16 days (chronic group). Then, 5 μM CellRox (Cellular ROS Assay Kit, ab186029S) was added to each well and was incubated for 30 min at 37 °C. For the acute group, cells were pretreated with 10 mM NAC for 2 h followed by MSG treatment for another 24 h. Cells were then washed thrice with 1× PBS and analyzed by flow cytometry (BD FACSCanto) [37].
For assaying thiobarbituric acid reactive substances (TBARS), cells were harvested after acute or chronic treatment as previously described. This assay was also performed with the following early placental explants groups: control, 50 mM MSG treatment, 10 mM NAC, and pre-treatment with NAC for 2 h followed by 50 mM MSG treatment. Thiobarbituric Acid Reaction Species Assay (Cayman Chemicals) was performed to estimate the levels of MDA, the final product of lipid peroxidation. TBARS concentrations were measured at 532 nm.
## 2.7. Western Blotting
Cells were lysed using a radioimmunoprecipitation assay buffer, containing protease and phosphatase inhibitors. Proteins (60 μg) were separated using $10\%$ discontinuous sodium dodecyl sulfate–polyacrylamide gel electrophoresis and transferred to a polyvinylidene difluoride membrane. The membrane was blocked with $5\%$ non-fat milk for 1 h and then incubated with primary antibodies at 1:1000 dilution overnight at 4 °C. The membrane was washed in Tris-buffered saline containing $0.1\%$ Tween 20 and then incubated with horseradish peroxidase (HRP)-conjugated secondary antibodies at room temperature for 1 h. Protein bands were visualized by a densitometer using an enhanced chemiluminescence (ECL) detection kit (NCI4106; Thermo Fisher Scientific, Inc.) [37]. The same membrane was used for re-probing with an anti-GAPDH antibody (Cell Signaling Technology, Inc., Beverly, MA, USA) at 1:1500 dilution. Band intensities were estimated using Image J, and the expression of proteins was normalized with respect to that of GAPDH.
Antibodies used have been listed in Table 1.
## 2.8. Gelatin Zymography
Bioactivities of secreted matrix metalloproteinases (MMPs)–$\frac{2}{9}$ in the conditioned media of HTR-8/SVneo cells were measured using substrate gel gelatin zymography. Proteins were separated using an $8\%$ polyacrylamide gel containing $0.1\%$ gelatin. The gel was then washed with $2.5\%$ Triton X-100 solution for 1 h to renature proteins, washed further with distilled water, and incubated in activation buffer (150 mM NaCl, 10 mM CaCl2, 50 mM Tris, and $0.025\%$ sodium azide) at 37 °C with gentle shaking overnight. An amount of $0.1\%$ Coomassie brilliant blue ($0.1\%$) was used to stain the gel for 30 min. The gel was destained using $10\%$ acetic acid solution and visualized [37].
## 2.9. Wound Healing Assay/Cell Migration Assay
Cells were seeded in 6-well plates at a density of 2 × 105 cells per well and incubated to attain 80–$90\%$ confluence. A small pipette tip was used to generate a scratch through the cell monolayers, and the debris was removed using 1× PBS. After treating the cells for 24 h, as previously mentioned, images were acquired at regular intervals until complete wound healing (filling up of the scratch with cells), using a phase-contrast microscope [37].
## 2.10. Matrigel Invasion Assay
The invasion assay was performed using a 24-well insert system (8 μm pores; Transwell chamber, Merck Millipore, Darmstadt, Germany). The surface of the insert plate was coated with 50 μL diluted Matrigel (400 µg/mL) (356234; Becton Dickinson and Company, Franklin Lakes, NJ, USA, 1:9 in RPMI-1640). An aliquot of 200 uL of HTR-8/SVneo cell suspension (1 × 105 cells) was seeded into the insert, and FBS-supplemented RPMI was added to the reservoir well. Cells were treated and cultured for 24 h. After incubation, a swab was used to remove the remaining cells from the upper insert. Trophoblast cells that infiltrated and reached the other side of the insert were fixed using ice-cold methanol and stained with 4′,6-diamidine-2′-phenylindole dihydrochloride (D9564, Sigma-Aldrich) for nuclear staining and Alexa Fluor 488 Phalloidin (green) (Cell Signalling Technology, Beverly, MA, USA) for cytoplasmic staining. Images obtained were captured using an upright microscope (TI-E, 601869, Nikon Laser Scanning Confocal Microscope) at 200× magnification [37].
## 2.11. Transmission Electron Microscopy (TEM)
Early placental explant tissues (1 mm3/piece) and cells pellets (1 × 106) treated with 50 mM MSG for 72 h were fixed with Karnovsky’s fixative at 4 °C, rinsed with 0.1 M phosphate buffer (pH 7.4) twice, and post-fixed with $1\%$ osmium tetroxide for 1 h. Samples were then dehydrated in acetone, embedded in Araldite CY212, and polymerized. Sections (60–70 nm thick) were cut and stained with uranyl acetate and lead citrate and then examined using a Talos 200S transmission electron microscope (Thermo Scientific, Inc., Washington, DC, USA) [37].
## 2.12. Immunohistochemistry
Early placental explant tissues treated with 50 mM MSG for 72 h were washed in PBS and fixed overnight in $4\%$ buffered formalin at 4 °C. Samples were then washed to remove the fixative, and paraffin-embedded 5 µm-thick sections were cut using a microtome (36,000; ThermoFisher Scientific, Washington, DC, USA). The sections were deparaffinized, rehydrated, and microwaved for 20 min in Tris-EDTA buffer (pH 9.0) for antigen retrieval. Endogenous peroxidase was quenched by treating the sections with $3\%$ H2O2 for 15 min. Nonspecific binding was blocked using a BlockAid Blocking Solution (Invitrogen). The sections were incubated with rabbit anti-Nrf2 antibody (dilution: 1:200; sc-365949, Santa Cruz Biotechnology, Inc., Dallas, TX, USA) and rabbit anti-Xbp1s antibody (dilution: 1:200; 40435, Cell Signal Technology, Beverly, MA, USA) at 4 °C in a humid chamber for 12–14 h. Subsequently, the sections were incubated with fluorophore-conjugated anti-rabbit secondary antibody (Dako, Santa Clara, CA, USA) at room temperature for i h, washed thrice with 0.1 M TBS, and mounted with DPX mounting medium (Merck, Millipore, Germany). The sections were observed using a compound microscope [37]. Scoring was done on the basis of intensity (i) and percentage of immunopositivity of the cells (Pi). The i-values were assigned on a scale of 0–3, where 0, 1, 2, and 3 indicated no, weak, moderate, and strong staining. The P value varied from 0–$100\%$, and the final score was derived from the sum of (i × P) value as shown in the equation below. This score ranges from 0–300 [38]. H-score = (0 × P0) + (1 × P1) + (2 × P2) + (3 × P3)[1] For nuclear factor erythroid 2-related factor 2 (Nrf2):H score of the control explant = (0 × 5) + (1 × 5) + (2 × 10) + (3 × 80) = 265 H score of the MSG treated explant = (0 × 5) + (1 × 75) + (2 × 15) + (3 × 5) = 120 For X-box binding protein 1 (Xbp1s):H score of the Control explant = (0 × 7) + (1 × 80) + (2 × 10) + (3 × 3) = 109 H score of the MSG treated explant = (0 × 5) + (1 × 8) + (2 × 85) + (3 × 2) = 184 H-score was calculated using mean ± standard deviation (SD).
## 2.13. Haematoxylin and Eosin Staining
Slides containing tissue sections were placed in a staining jar and deparaffinized by submerging into three series of absolute xylene for 4 min, followed by treatment with $100\%$, $100\%$, $95\%$, $90\%$, and $70\%$ ethanol for 4 min each. The slides were then washed with running tap water for 2 min, submerged into Harris hematoxylin (Sigma-Aldrich, Darmstadt, Germany) for 2 min, washed with running tap water for 2 min, and finally mounted with a coverslip using DPX mounting agent after dehydration in graded ethanol. Explant tissue sections were stained with hematoxylin and eosin to study placental villi, syncytial knot formation, and stromal pathology.
## 2.14. Collagen Special Staining (a Modified Masson’s Trichrome Staining)
Slides containing early explant tissues were placed in a staining jar, deparaffinized by submerging into three series of absolute xylene, and rehydrated through a graded series of ethanol. The slides were then submerged in warm Bouin’s solution (Sigma-Aldrich, Darmstadt, Germany) at 60 °C for 45 min and then thoroughly washed with running tap water until the yellow color in the samples disappeared. To differentiate nuclei, the slides were then immersed in modified Weigert’s hematoxylin for 8 min and then washed with running water for 2 min. To stain cytoplasm and erythrocytes, the slides were submerged in anionic dyes and acid fuchsin (Sigma-Aldrich, Darmstadt, Germany) for 5 min and washed with running tap water for 2 min. Next, the slides were treated with phosphomolybdic acid solution (a mordant) for 10 min and immediately submerged into methyl blue (C.I. 42780, Merck, Germany) solution for 5 min to stain collagen and fibroblasts. Then, the slides were thoroughly washed with running tap water for 2 min and treated with $1\%$ acetic acid solution for 1 min. The slides were then dehydrated through a graded series of ethanol, dipped into absolute xylene for 1 min, mounted with a coverslip using DPX mounting reagent, and observed using a microscope (TI-E, 601869, Nikon Laser Scanning Confocal Microscope) at 200× magnification.
## 2.15. Enzyme-Linked Immunosorbent Assay (ELISA)
ELISA was performed to assess the levels of β subunit of human chorionic gonadotropin (β-hCG) in conditioned media of BeWo cells and placental explant cultures using a human hCG-beta ELISA Kit (EH235RB, Thermo Fisher Scientific, Inc., Washington, DC, USA). Conditioned media (100 µL) was added to each well of a 96-well plate and incubated for 2.5 h at room temperature with gentle shaking. Then the media was removed, and the plate was washed four times. Then, 100 µL biotin conjugate was added to each well and incubated for 1 h at room temperature with gentle shaking, and the plate was washed again. Then, 100 µL streptavidin-HRP solution was added to each well and incubated for 45 min at room temperature with gentle shaking. The plate was washed again, and 100 µL of 3,3′,5,5′-tetramethylbenzidine substrate was added to each well and incubated for 30 min at room temperature in the dark with gentle shaking. Stop solution (50 μL) was added to each well and gently mixed until the color changed from blue to yellow [37]. The absorbance was read at 450 nm within 30 min.
## 2.16. Statistical Analysis
All experiments were repeated at least thrice. Data are presented as mean ± standard deviation (SD). The statistical significance was assessed by Student’s t-test using GraphPad Prism v5.0 (San Diego, CA, USA), with a p value < 0.05 considered statistically significant.
## 3.1. Effect of MSG Stimulation on Viability and Proliferation of Trophoblast Cells
The sub-lethal dose of MSG and its toxic effects on trophoblast cell lines were evaluated using WST-1 assay. A dose-dependent reduction in viability was observed in HTR-8/SVneo (Figure 1a) and BeWo (Figure 1b) cells. Trypan blue staining (Figure 1c,d) showed similar results. Annexin-V/PI staining showed that more than $75\%$ cells were viable when treated with 25 and 50 mM MSG for acute stimulation and 25 mM MSG for chronic stimulation in HTR-8/SVneo and BeWo cells. ( Figure S2a–d) Cell cycle analysis following acute stimulation (24 h) with 25 and 50 mM MSG showed a nonsignificant change in the G1 and S phases in BeWo cells, as compared to those of the control group. A significant increase in proliferation in the G2 phase was noticed in BeWo cell stimulated with 50 mM MSG (Figure S2e); however, no significant change was observed in the percentage of HTR-8/SVneo cells in the S phase compared to that of untreated cells. ( Figure S2f). Moreover, no significant difference in cell proliferation was observed between the control and the treated groups in BeWo (Figure S2g–j) and HTR-8/SVneo (Figure S2k–n) cells. Therefore, both 25 and 50 mM MSG doses were used for studying the acute effects of MSG, and a 25 mM dose was used for chronic stimulation studies.
## 3.2. Acute Stimulation with MSG Increases Differentiation and Invasion in Trophoblast Cells and Early Placental Explants
To assess the effect of MSG on trophoblast differentiation, BeWo cells were used to analyze the expression of trophoblast differentiation markers including syncytin-1 (SYN-1), syncytin-2 (SYN-2), and glial cells missing-1 (GCM1), dysferlin (DYSF), β subunit of human chorionic gonadotropin (β-hCG), solute carrier family 1 Member 5 (SLC1A5), and major facilitator superfamily domain containing 2A (MFSD2A). MSG (25 and 50 mM) significantly increased the mRNA levels of SYN-1, SYN-2, DYSF, GCM-1, β-hCG, SLC1A5, and MFSD2A (Figure 2a–g). β-hCG concentration was also evaluated in the conditioned media of cells, and significant upregulation of β-hCG level was observed after acute stimulation with MSG (Figure 2h). We next evaluated the effect of MSG in the early placental explants derived from first trimester chorionic villi obtained from medically terminated pregnancy cases (8–12 weeks of pregnancy). The expression of SYN-1, SYN-2, DYSF, GCM1, and β-hCG was significantly upregulated ($p \leq 0.01$). mRNA levels of SLC1A5 and MFSD2A, the receptors of SYN-1 and SYN-2, respectively, showed similar trends (Figure 2i). β-hCG protein levels were significantly upregulated in early explants treated with 50 mM MSG (Figure 2j). Therefore, MSG significantly upregulated trophoblast differentiation markers in trophoblast cells and tissue explants.
We next analyzed the effects of MSG on trophoblast invasion. Using the extravillous trophoblast cells HTR-8/SVneo, we assessed the mRNA expression of invasion-associated genes MMP-2, MMP-9, and uPA, and their inhibitors TIMP-1, TIMP-2, and PAI-1, respectively. Significant upregulation of mRNA expression of MMP-2, MMP-9, and uPA was observed with MSG treatment compared to those of the untreated controls ($p \leq 0.05$). ( Figure 3a,b,e). MSG treatment (50 mM) showed an insignificant decrease in the mRNA expression of TIMP-2 and PAI without altering the mRNA expression of TIMP-1 (Figure 3c,d,f). Interestingly, we observed an elevated mRNA expression of ONZIN/placenta associated 8 (PLAC8) with both doses of MSG ($p \leq 0.01$) (Figure 3g). ONZIN has been earlier reported [39] to be positively associated with the invasiveness and migratory behavior of trophoblast cells. The Western blot analysis showed similar trends, with MSG stimulation increasing the expression of MMPs and decreasing the expression of TIMPs. However, TIMP-1 expression was reduced by 50 mM MSG (Figure 3h–l).
To further confirm that the effect of MSG on the pro-invasiveness of HTR-8/SVneo cells, as seen in the invasion assay, is owing to the secretion of MMPs, a functional assay was performed using gelatin zymography. Results showed a significant upregulation of MMP-2 and MMP-9 activities in MSG-stimulated HTR-8/SVneo cells (Figure 4a–c). Matrigel invasion assay showed a similar trend with a significant upregulation of the average number of invading HTR-8/SVneo cells per field after the acute stimulation of MSG (Figure 4d,e). In the wound-healing assay, HTR-8/SVneo cells showed a significantly higher migration rate than did the control cells, following MSG treatment ($p \leq 0.01$) (Figure 4f,g). To further elucidate the effect of short-term MSG exposure on early placental explants, we assessed the gene expression of the invasion markers. mRNA expression of MMP-2, MMP-9, and uPA was significantly upregulated in the placental explants; however, those of TIMP-1 and TIMP-2 were significantly downregulated (Figure 3m). mRNA expression of PLAC8 was significantly higher in the MSG-treated group. Therefore, acute stimulation of MSG is responsible for elevated differentiation and invasion potentials in trophoblast cells and early placental explants.
## 3.3. Long-Term Chronic Stimulation of MSG Decreases Differentiation and Invasion of Trophoblasts
Next, we assessed mRNA expression of differentiation markers in BeWo cells on Day 4, Day 8, Day 12, and Day 16 after chronic stimulation (16 days) by 25 mM MSG by treating cells every alternate day for the entire span of 16 days. Surprisingly, we observed an opposite trend with a significant decrease in the expression of SYN-1, SYN-2, SLC1A5, MFSD2A, DYSF, GCM1, and β-hCG ($p \leq 0.01$) (Figure 5a–g). We assessed the expression from conditioned media on days 4, 8, 12, and 16, which showed a significant reduction (Figure 5h).
To determine the effect of chronic stimulation of MSG on the invasion of trophoblast cells, we analyzed the expression of genes previously studied during acute stimulation. Interestingly, we observed that the expression of MMP-2, MMP-9, and uPA were significantly downregulated on days 4, 12, and 16. MMP-9 expression was downregulated by approximately three-fold, and MMP-2 and uPA showed similar trend (though not statistically significant on Day 8 for MMP-2 and uPA, and a nonsignificant increase in MMP-9 on Day 4) (Figure 6a,b,e). mRNA expression of TIMP-1 and TIMP-2 were upregulated on all four days. The fold changes for TIMP-1 on days 8, 12, and 16 and TIMP-2 on days 4 and 8 were not significant (Figure 6c,d). In contrast, PAI-1 level was slightly upregulated on days 4 and 8 and was eventually downregulated on Day 16 of stimulation (Figure 6f). PLAC8 level was significantly downregulated on days 4, 12, and 16 (Figure 6g).
The Western blot analysis showed that MMP-2 expression was significantly downregulated on all four days, while TIMP-2 expression was upregulated on days 4, 8, and 16 (Figure 6h,j,l). MMP-9 and TIMP-1 expression were significantly upregulated on days 4 and 16 and were downregulated on Day 8. On Day 12 we observed an opposite trend for both MMP-2 and TIMP-1 expression. Moreover, MMP-9 was downregulated, and TIMP-1 was significantly upregulated on Day 12 (Figure 6i,k). Consistent with these findings, gelatin zymography revealed that the activities of MMP-2 and MMP-9 were significantly reduced in HTR-8/SVneo cells after chronic stimulation of MSG on all four days ($p \leq 0.05$) (Figure 7a–c). Matrigel invasion and wound healing assays performed after 16 days of chronic MSG stimulation showed a very small number of invading cells and reduced migration, respectively (Figure 7d–g). Therefore, chronic stimulation of MSG significantly downregulated the invasive and migratory properties of trophoblasts.
## 3.4. MSG Stimulation Induces OS in Cells and Tissues
MSG elicits OS [15,40]. Therefore, we indirectly measured the concentration of TBARS generated by ROS following acute and chronic exposure of MSG in HTR-8/SVneo and BeWo cells. A significant upregulation in TBARS level was noticed in cells treated with 25 and 50 mM MSG for 24 h. To assess the role of ROS in producing TBARS, we performed rescue experiments using antioxidant NAC. Interestingly, NAC significantly downregulated TBARS production in trophoblast cells after MSG treatment ($p \leq 0.01$) (Figure 8a,b).
A similar study performed on chronic MSG treatment group revealed a significant upregulation of TBARS on all four days. In HTR-8/SVneo cells, NAC failed to quench TBARS on Day 16. In BeWo cells, a significant decrease in TBARS level was noticed on days 4, 8, 12, and 16 in the group pretreated with NAC after stimulating the cells with 25 mM MSG on every alternate day (Figure 8c,d). An increase in TBARS level was noticed in early placental explants treated with MSG, compared to that in the control group. ( Figure 8e). Therefore, we stained the cells with CellRox that showed a right peak shift (increase) in cells treated with MSG in both acute and chronic conditions, as compared to that in the untreated control group. Cells pretreated with 10 mM NAC showed low levels of ROS, similar with those of the control group. The mean fluorescence intensity was measured, and cells pretreated with 10 mM NAC followed by MSG treatment showed no significant change in peak shift as compared to the group treated with MSG only, thereby suggesting that NAC could quench ROS generated in these cells (Figure 9a–d). Similarly, we confirmed the induction of OS by chronic stimulation of MSG in the early placental explants by performing an immunohistochemical analysis. In early placental explants treated with 50 mM MSG for 72 h, Nrf2 expression was significantly downregulated, and H-scores of the control and treated groups were 265 ± 16 and 120 ± 22, respectively (Figure 9e). The Western blot analysis showed significant downregulation of Nrf2 expression in both the cell lines treated with 25 mM MSG for 24 h (Figure S3a–f). Taken together, MSG treatment induced OS in trophoblast cells and early placental explants.
## 3.5. Alteration of Ultrastructural Features in Early Placental Explants and BeWo Cells by Chronic Stimulation of MSG
We speculated that ROS-mediated intracellular injury by MSG stimulation is responsible for altered trophoblast function in placental tissue explants. Using TEM, we explored the ultrastructural details of early placental tissue explants after a chronic stimulation of 50 mM MSG for 72 h. Significant ultrastructural changes were observed in placental tissue explants ($$n = 10$$). Disintegrated syncytiotrophoblast, short and distorted microvilli, disintegrated mitochondria with high glycogen content, disintegrated nuclei, and swollen endoplasmic reticulum (ER) were observed in the MSG treated group while the control group presented with completely healthy cells and intracellular organelles (Figure 10). These observations indicate that MSG caused ultrastructural changes in placental explant tissues. Moreover, we observed significant ultrastructural changes in the BeWo cells treated with 50 mM MSG for 72 h ($$n = 3$$). Disintegrated mitochondria, distorted microvilli, swollen ER, and high glycogen content were observed in MSG-treated cells (Figure S8). These results further supported our findings in treated placental explants.
## 3.6. OS Induced by MSG May Cause ER Stress in Trophoblast Cells
TEM results showed that MSG treatment (50 mM) altered the ultrastructure of mitochondria and ER in the early placental explants. To investigate the role of unfolded protein response (UPR) pathway here, cells were treated with MSG for 24 h. The immunoblot analysis showed a significant upregulation of BiP in BeWo cells after 50 mM MSG treatment (Figure 11a,b). In HTR-8/SVneo cells, a significant upregulation of BiP was noticed by 25 mM MSG treatment (Figure 11f,g). In BeWo cells, phosphorylated IRE1α (pIRE1α) was significantly upregulated by 25 and 50 mM MSG treatment (Figure 11a,c); whereas, in HTR-8/SVneo cells, pIRE1α was significantly upregulated with 50 mM MSG treatment (Figure 11f,h). IRE1α expression was also significantly upregulated in BeWo cells treated with 50 mM MSG (Figure 11a,d); however, a significant downregulation was noticed in HTR-8/SVneo cells. MSG (25 mM) did not induce any significant change in IRE1α levels (Figure 11f,i). Xbp1 was significantly upregulated in BeWo cells treated with 25 mM MSG (Figure 11a,e) and in HTR-8/SVneo cells treated with 50 mM MSG (Figure 11f,j). We also checked Xbp1s expression in early placental explant tissues. Immunohistochemical analysis showed significant upregulation of Xbp1s in the MSG-treated group (H-score: 184 ± 22) compared to that in the untreated early villi explant group (H-score: 109 ± 18) (Figure 9e,g,h). These results suggest that OS caused by MSG treatment may induce ER stress in trophoblast cells.
## 4. Discussion
MSG is a majorly used food additive [41,42,43]. Although MSG is naturally present in several foods, including tomatoes, cheese, meat, and vegetables, it is mostly used as an external additive and a flavor enhancer. MSG consumption in experimental animals causes obesity, insulin resistance, reduced glucose tolerance, metabolic disorders, and disrupted energy balance [21,26,44,45,46].
This study investigated the short- and long-term effects of MSG on placental trophoblast invasion and differentiation. Using invasive extravillous trophoblasts, HTR-8/SVneo, and non-invasive villous but fusogenic BeWo cells, we explored the effects of MSG and underlying molecular mechanisms. Our study is influenced by earlier observations pointing towards a detrimental effect of MSG on the physiological system [13,33,47,48]. Although these studies reported serious health consequences of MSG, they did not explore detailed mechanistic insights. Further, the effect of MSG on the placenta and feto-maternal health has not been addressed before. The present study is an attempt in that direction.
Roman-Ramos et al. [ 49] reported that MSG elevates the interleukin 6 level and tumor necrosis factor-alpha-mediated inflammatory response through a microRNA-dependent pathway. Apart from its metabolic effects, MSG has a detrimental effect on the reproductive system, involving an increased number of pachytene-stage cells among the primary spermatocytes in rodents and humans [13,50]. MSG exposure in mice disrupts the basement membrane of the theca follicle in the ovary, thereby leading to atrophy and degeneration [12,13,51]. This is probably owing to enhanced OS leading to the damage of DNA and chromatin, and adduct formation in the stromal cells [17].
Despite these harmful effects of MSG on human physiology [52], no conclusive study has been undertaken to investigate the short- and long-term effects of MSG on placental function. A quick literature search in PubMed with the keywords “MSG and human placenta/trophoblast” has yielded no significant studies, thereby suggesting that not much has been investigated in this direction.
The global market for MSG is estimated at US$3.8 billion in 2020 and is projected to attain a revised size of US$4.7 billion by 2027 [53]. The MSG market in the U.S. alone is estimated at $1 billion in the year 2020. Presently, the world’s largest MSG consumer and producer is mainland China [54]. With such an enormous consumption worldwide [55] and with the possibility of its harmful effect on humans, we therefore undertook this study. Our study identified critical pathways related to trophoblast invasion and differentiation, which are perturbed upon MSG exposure in cell line-based models and placental explants. Further, MSG elicited ER stress response mediated through the BiP and IRE1α pathways in vitro. Moreover, MSG induced OS, as evidenced by elevated ROS production. This resonates with previous reports of MSG-inducing OS [31,56,57,58]. Our study also found that MSG exposure (24 h) increased the invasiveness of trophoblasts by elevating the levels of MMPs that degrade the extracellular matrix. Surprisingly, an extended MSG exposure (14 days) reduced invasion by trophoblasts. Therefore, we observed a dual effect of MSG in this aspect. This brings to us an interesting question that why MSG shows this dual response. Based on previous reports [58], we hypothesize that low levels of ROS (upon short-term MSG treatment) could enhance trophoblast invasion by multiple mechanisms including the formation of invadopodia [59] and engaging SRC family of kinases, c-Jun N-terminal kinase, and p38 kinase [60]. Moreover, ROS may activate protein kinase C by releasing intracellular calcium [61] and enhancing cell proliferation. An initial event of shallow trophoblast invasion within the decidual layer is followed by a more extended interstitial and endovascular invasion [61,62] that results in rapid maternal blood flow in the intervillous space establishing hemochorial placenta [63]. The intervillous space is oxygen-deficient before week 12 of gestation in humans. This creates transient hypoxia, which is imperative for initiating trophoblast invasion and placental angiogenesis by hypoxia-inducible factor-mediated activation of vascular endothelial growth factor [64,65]. Therefore, we expect a well-regulated step-by-step increment in oxygen level in the feto-maternal space [63,64], which should parallel with a step-by-step increase in the invasiveness of trophoblasts to maintain an adequate oxygen gradient. The importance lies in the synchrony of this entire process. A premature trophoblast invasion is as detrimental as an inadequate trophoblast invasion, with both resulting in serious consequences [66]. One way to safeguard against this premature trophoblast invasion is trophoblast-mediated sealing of uterine arteries forming plugs that prevent rapid blood flow and oxygenation at the feto-maternal interface [67].
In this study, short-term MSG treatment enhanced the migration and invasion of HTR-8/SVneo cells. We therefore speculate that MSG could potentially offset the fine balance necessary to establish physiological oxygen gradient by perturbing invasion through ROS. Long-term MSG treatment downregulated both invasion and differentiation probably owing to excessive ROS production by exhausting cellular antioxidant defense systems, as was evident by the downregulation of Nrf2, a master regulator of an antioxidant response, leading to loss of invasive potential [68] and apoptosis of these cells [69].
It is conceivable that OS could be a secondary finding in PE, but may still be a significant contributor to PE pathology (if not the only one). This statement is supported by our own lab findings as well from other studies [37,70,71,72]. That a ROS-mediated pathogenesis may contribute to PE is further justified by several clinical trials using antioxidants like melatonin [72,73] or some beneficial effect upon antioxidant administration [74]. However, we would like to state that the evidence so far linking OS to placental pathology is not yet established to be a causation and appears more of an association that is driven by other modifiers and regulators in addition to ROS.
Trophoblast invasion is a highly coordinated process involving remodeling of the maternal vasculature. The success of this process largely depends upon an orchestrated tempo-spatial effort of pro- and anti-invasive proteins [75,76]. MSG tilts this delicate balance, thereby perturbing the trophoblast invasion and differentiation program. MSG under acute exposure upregulated trophoblast differentiation markers, associated with cell–cell fusion for syncytium. In villous trophoblasts, cell–cell fusion to form syncytiotrophoblast is an important step, which is regulated by multiple drivers such as hormones, cytokines, protein kinases, and transcription factors. Short-term MSG exposure upregulated SYN-1, SYN-2, GCM-1, DYSF, MFSD2A, and β-hCG, thereby indicating abnormal syncytialization. Trophoblast differentiation is impaired in preeclamptic pregnancies as demonstrated by Fantone et al. [ 77].
MSG-induced ROS caused cellular damage as evident from biochemical and ultrastructural studies, and depleted Nrf2 level, as found in the placental histology. Nrf2 regulates the antioxidant defense system through multiple mechanisms [78,79,80]. Loss of Nrf2 upon MSG treatment, therefore, induces OS. We have previously observed ROS-mediated activation of UPR pathways, leading to altered trophoblast function [37]. The present study indicates that MSG probably acts through a similar mechanism. Long-term consequences of MSG consumption on placenta trophoblast cells might have an adverse effect on the conceptus though we do not have experimental evidence at this point to support our statement. Our study is preliminary in this direction. Further efforts are undertaken using rodent models to delineate in vivo effects of long-term MSG exposure on pregnancy outcomes. To confirm that the above effects are because of MSG only and not because of any osmotic changes in the cellular environment upon MSG exposure, we performed qPCR using $0.5\%$ glycerol (Figure S9). No significant effect was observed on cell invasion and differentiation, implying an MSG-specific effect on the cells.
## 5. Conclusions
MSG affected trophoblast function through ROS-mediated cellular stress. We presented evidence to show that trophoblast invasion and differentiation pathways are perturbed. Therefore, we speculate that a long-term exposure to MSG might have a detrimental effect on placentation, as represented in the graphical abstract (Figure 12). Further in vivo investigation of the effect of MSG on embryogenesis using animal models is necessary. Our study is the first report as proof of principle establishing the harmful effect of MSG on the placenta and trophoblast cells. Rodent studies are currently ongoing to explore the long-term effect of MSG through the oral route on pregnancy outcome, placental function, and possibly post-natal life. Though pregnancy in rodents does not exactly map with those of humans, the information gathered from animal studies will still be valuable in studying the effect of exposure on placentation. Our findings are novel as the effect of MSG exposure on placental trophoblasts has not yet been addressed. Identifying the possible harmful effects of MSG on trophoblasts may caution against its excessive consumption.
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|
---
title: Role of Cystathionine β-Synthase and 3-Mercaptopyruvate Sulfurtransferase in
the Regulation of Proliferation, Migration, and Bioenergetics of Murine Breast Cancer
Cells
authors:
- Sidneia Sousa Santos
- Larissa de Oliveira Cavalcanti Peres Rodrigues
- Vanessa Martins
- Maria Petrosino
- Karim Zuhra
- Kelly Ascenção
- Abhishek Anand
- Reham Mahmoud Abdel-Kader
- Mohamed Z. Gad
- Carole Bourquin
- Csaba Szabo
journal: Antioxidants
year: 2023
pmcid: PMC10045476
doi: 10.3390/antiox12030647
license: CC BY 4.0
---
# Role of Cystathionine β-Synthase and 3-Mercaptopyruvate Sulfurtransferase in the Regulation of Proliferation, Migration, and Bioenergetics of Murine Breast Cancer Cells
## Abstract
Cystathionine β-synthase (CBS), CSE (cystathionine γ-lyase) and 3-mercaptopyruvate sulfurtransferase (3-MST) have emerged as three significant sources of hydrogen sulfide (H2S) in various forms of mammalian cancer. Here, we investigated the functional role of CBS’ and 3-MST’s catalytic activity in the murine breast cancer cell line EO771. The CBS/CSE inhibitor aminooxyacetic acid (AOAA) and the 3-MST inhibitor 2-[(4-hydroxy-6-methylpyrimidin-2-yl)sulfanyl]-1-(naphthalen-1-yl)ethan-1-one (HMPSNE) were used to assess the role of endogenous H2S in the modulation of breast cancer cell proliferation, migration, bioenergetics and viability in vitro. Methods included measurements of cell viability (MTT and LDH assays), cell proliferation and in vitro wound healing (IncuCyte) and cellular bioenergetics (Seahorse extracellular flux analysis). CBS and 3-MST, as well as expression were detected by Western blotting; H2S production was measured by the fluorescent dye AzMC. The results show that EO771 cells express CBS, CSE and 3-MST protein, as well as several enzymes involved in H2S degradation (SQR, TST, and ETHE1). Pharmacological inhibition of CBS or 3-MST inhibited H2S production, suppressed cellular bioenergetics and attenuated cell proliferation. Cell migration was only inhibited by the 3-MST inhibitor, but not the CBS/CSE inhibitor. Inhibition of CBS/CSE of 3-MST did not significantly affect basal cell viability; inhibition of 3-MST (but not of CBS/CSE) slightly enhanced the cytotoxic effects of oxidative stress (hydrogen peroxide challenge). From these findings, we conclude that endogenous H2S, generated by 3-MST and to a lower degree by CBS/CSE, significantly contributes to the maintenance of bioenergetics, proliferation and migration in murine breast cancer cells and may also exert a minor role as a cytoprotectant.
## 1. Introduction
Hydrogen sulfide (H2S) is an endogenous gaseous transmitter which has been implicated in multiple regulatory processes in mammals [1,2]. There are three principal enzymatic sources of H2S in various cancer cells: cystathionine β-synthase (CBS), cystathionine γ-lyase (CSE) and 3-mercaptopyruvate sulfurtransferase (3-MST) [1,2].
Over 10 years, a novel concept emerged in cancer biology, demonstrating that various cancer cells upregulate endogenous H2S-producing enzymes and utilize H2S to support various cancer cell functions, such as cell proliferation, cytoprotective signaling, cellular bioenergetics, and angiogenesis [3,4].
In the current study, we have characterized the expression of H2S-producing and H2S-metabolizing enzymes in the murine breast cancer cell line EO771. In addition, using pharmacological approaches, we have assessed the role of CBS and 3-MST catalytic activity in the maintenance of various fundamental cellular functions in vitro including cellular bioenergetics, cell proliferation, migration and cell viability. To this aim, we have utilized the standard CBS/CSE inhibitor aminooxyacetic acid (AOAA) [5] and the recently discovered, selective 3-MST inhibitor, 2-[(4-hydroxy-6-methylpyrimidin-2-yl)sulfanyl]-1-(naphthalen-1-yl)ethan-1-one (HMPSNE) [6].
The data presented indicate that in EO771 cells, the 3-MST/H2S system, and—to a lower extent—the CBS/H2S system contribute to the maintenance of cellular bioenergetics, cell proliferation and cell migration, and that the 3-MST system may also serve a minor cytoprotective role against oxidative stress.
## 2.1. Cell Culture
The EO771 murine epithelial-like carcinoma cell line (ATCC #CRL-3461; American Type Culture Collection, Manassas, VA, USA) was grown in DMEM culture medium containing 4.5 g/L D-glucose, supplemented with $10\%$ fetal bovine serum (FBS, Hyclone, Pittsburgh, PA, USA), 100 units/mL of penicillin and 100 µg/mL of streptomycin and $2\%$ of HEPES (GE Healthcare, Pittsburgh, PA, USA). For experiments and sub-culturing, cells were rinsed with PBS and detached from T75 flasks by incubating with $0.25\%$ (w/v) trypsin 0.53 mM EDTA for 2 min at 37 °C followed by resuspension in culture medium.
## 2.2. Western Blotting
The EO771 cell suspension was centrifuged for 5 min at 400× g and the pellet was resuspended in RIPA Lysis and Extraction Buffer (Thermo Scientific, Waltham, MA, USA) complemented with Halt™ Protease and Phosphatase Inhibitor Cocktail (Thermo Scientific) just prior use. The protein concentration was determined with Bradford assay (employing Pierce™ Coomassie Plus Assay Reagent—Thermo Scientific) and an Infinite 200 Pro reader (Tecan, Männedof, Switzerland). Samples were prepared for gel electrophoresis in Bolt™ LDS Sample Buffer (4X) (Invitrogen) and Bolt™ Reducing Agent (10X) (Invitrogen, Thermo Scientific) according to manufacturer’s instructions, loaded in Bolt™ 4–$12\%$ Bis-Tris Plus Gels (Invitrogen, Thermo Scientific) and ran at 120 V.
Proteins were transferred onto a PVDF (polyvinylidene difluoride) membrane by dry transfer using the iBlot™ 2 Device and Transfer Stacks (Invitrogen). The membrane was blocked with $5\%$ Milk in TBS/$0.1\%$ Tween (TBST/$5\%$ Milk). Protein expression was evaluated by Western blotting using anti-CBS (14782S) 1:250 from Cell Signaling (Beverly, MA, USA), anti-3-MST 1:500 (ab154514), anti-CSE 1:1000 (ab151769), anti-TST 1:1000 (ab231248) from Abcam (Cambridge, UK), anti-ETHE-1 1:1000 (GTX109095) from GeneTex, anti-SQR antibody 1:1000 (HPA017079) and anti-beta-actin antibody (1:3000) was obtained from Sigma-Aldrich Chemie Gmbh (Munich, Germany). Incubations were conducted overnight at 4 °C under agitation. The membranes were subsequently washed with TBST, and incubated for 1 h at room temperature (RT) with the secondary antibodies anti-rabbit IgG or anti-mouse IgG, HRP-linked antibody (Cell Signaling, Beverly, MA, USA) diluted 1:5000 in TBST/$5\%$ Milk. Amersham ECL™ Prime Western Blotting Detection Reagent (GE Healthcare, Pittsburgh, PA, USA) was used for detection; chemiluminescence was measured and quantified with the Azure Imaging System 300 (Azure Biosystems, Dublin, CA, USA).
## 2.3. Viability and Metabolic Assay
EO771 cells were seeded in sterile 96-well plates (20,000 cells/well) and incubated at 37 °C and $5\%$ CO2. Cells were treated with aminooxyacetate hemihydrochloride (AOAA, Sigma-Aldrich, St. Louis, MO, USA) (300 µM) or HMPSNE (MolPort, Riga, Latvia) (200 µM) for 2 h or 24 h followed by 2 h with increasing concentrations of H2O2. Then, 50 µL of the supernatant from each well was then transferred to another plate. The activity of lactate dehydrogenase (LDH) in the supernatant was used to estimate the degree of cell necrosis [7].
Cells were then subjected to the MTT assay, a method to assess cell viability/mitochondrial activity based on the activity of the cell’s NADH-dependent cellular oxidoreductase enzyme activity [7]. Cells were placed in 50 µL/well of serum-free medium supplemented with MTT reagent (Abcam, Cambridge, UK) and were incubated for 3 h at 37 °C and $5\%$ CO2. Formazan produced by cells with active metabolism was solubilized in 150 µL/well of MTT solvent by mixing well and shaking in an orbital way for 60 s at RT protected from light. Absorbance was measured at 590 nm using a Tecan Infinite 200 Pro reader. The LDH assay was performed as described using the Pierce LDH Cytotoxicity Detection Kit Plus (Roche, Mannheim, Germany). Briefly, the LDH reaction mixture was prepared according to the manufacturer’s instructions, and 50 µL/well was added to the supernatants. The plate was incubated for 30 min at room temperature. The reaction was stopped with 50 µL/well of Stop Solution. The plate was shaken in an orbital way for 60 s by Infinite 200 Pro reader (Tecan). Finally, absorbance was measured at 490 nm, with absorbance at 680 nm used as background.
## 2.4. Detection of H2S Production in Live Cells
EO771 cells were seeded in sterile black 96-well plate with optical bottom at 15,000 cells/well in 100 µL of complete culture medium and incubated overnight at 37 °C and $5\%$ CO2. The day after cells were treated with different concentrations of AOAA or HMPSNE as described above. After 24 h treatment, H2S generation in live cells was measured using the 7-azido-4-methylcoumarin (AzMC) assay as described [8]. Briefly, culture medium was replaced with HBSS buffer supplemented with 100 μM AzMC fluorescent dye and further incubated for 1 h. The specific fluorescence of the dye was visualized using a Leica DFC360 FX microscope. Images were captured with Leica Application Suite X software (Leica Biosystems Nussloch GmbH, Germany) and subsequently analyzed with ImageJ software (v. 1.8.0; NIH, Bethesda, MD, USA) and data and graphed with GraphPad Prism 8 (GraphPad Software Inc.; San Diego, CA, USA).
## 2.5. Determination of Cellular Bioenergetics
The Seahorse XFe24 flux analyzer (Agilent Technologies, Santa Clara, CA, USA) was used to estimate cellular bioenergetics of EO771 cells as described [7]. Cells (20,000/well) were seeded on cell culture microplates, incubated for 24 h, followed by treatment with AOAA (300 µM), HMPSNE (200 µM) or its vehicle for 2 h. For analysis of mitochondrial respiration, cells were washed twice with DMEM (pH 7.4) supplemented with L-glutamine (2 mM, Gibco, Thermo Scientific, Waltham, MA, USA), sodium pyruvate (1 mM, Sigma-Aldrich) and glucose (10 mM, Sigma-Aldrich). After 1 h incubation at 37 °C in CO2-free incubator, the O2 consumption rate (OCR) after oligomycin (1 µM) was used to estimate the ATP production rate. Moreover, carbonyl cyanide-4-trifluoromethoxy phenylhydrazone (FCCP, 0.5 µM) was employed to estimate the maximal mitochondrial respiratory capacity. Electron flux through complex III and I was blocked, respectively, with antimycin A (0.5 µM) and rotenone (0.5 µM). Residual activity in the presence of these inhibitors was considered non-mitochondrial OCR.
For the analysis of glycolytic parameters, cells were treated with AOAA or HMPSNE as above, washed twice with phenol red-free DMEM (pH 7.4) containing L-glutamine (2 mM), sodium pyruvate (1 mM), glucose (10 mM) and HEPES (5 mM). After a 1 h incubation at 37 °C in CO2-free incubator, proton efflux rate (PER) from basal and compensatory glycolysis was measured. Rotenone (0.5 µM) and antimycin A (0.5 µM) were used to estimate mitochondrial acidification. At the end of the experimental run, 2-deoxy-D-glucose (50 mM) was used to stop glycolytic acidification.
For the analysis of the glutamine oxidation pathway, after treatment with AOAA and HMPSNE cells were washed twice with DMEM (pH 7.4) supplemented with L-glutamine (2 mM, Gibco), sodium pyruvate (1 mM, Sigma-Aldrich) and glucose (10 mM, Sigma-Aldrich). After 1 h incubation at 37 °C in CO2-free incubator, OCR after injection of 0.3 µM bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide (BPTES), an inhibitor of glutaminase, was used to estimate the dependency of cells to use the glutamine oxidation pathway to fuel bioenergetics. Addition of oligomycin (1 µM) and FCCP 0.5 µM, as above, was used to estimate the rate of ATP production and the maximal mitochondrial respiratory capacity, respectively. Eventually, antimycin A (0.5 µM) and rotenone (0.5 µM) were employed to estimate the non-mitochondrial OCR. All data were normalized with total protein content, using the BCA protein assay (Thermo Scientific).
## 2.6. Growth Monitoring, Viability and Metabolic Assay
EO771 cells were seeded in sterile 96-well plate (5000 cells/well) in 100 µL of complete culture medium and incubated over-night at 37 °C and $5\%$ CO2. The day after, different concentrations of AOAA or HMPSNE were added as indicated and cell proliferation was monitored for 72 h using the IncuCyte Live Cell Analysis device (20× objective) (Essen Bioscience, Hertfordshire, UK) as described [7]. Cell confluence was recorded every hour by phase-contrast scanning for 72 h at 37 °C and $5\%$ CO2 and calculated from the microscopy images.
## 2.7. Migration Assay
EO771 cells were seeded in sterile transparent 96-well plate at 50,000 cells/well in 100 µL of complete culture medium and incubated over-night at 37 °C and $5\%$ CO2. The day after, a scratch wound was made in the confluent cell monolayer of each well using the WoundMaker from Essen Bioscience as described [7]. The culture medium was then carefully replaced with indicated AOAA or HMPSNE serial dilutions and the plates were readily placed in IncuCyte device (20× objective) and incubated at 37 °C and $5\%$ CO2. Images were acquired every 2 h for up to 48 h to monitor the closure of the wound. Images were analyzed using the IncuCyte ZOOM software to calculate cell confluence over the time.
## 2.8. Statistical Analysis
Data are presented as representative blots or the mean values ± standard error of the 181 mean (SEM) of experiments performed on at least $$n = 3$$ experimental days. ANOVA followed by Bonferroni’s multiple comparisons test and One-way ANOVA and Dunnett’s multiple comparisons test were used to analyze the numerical data. A $p \leq 0.05$ was considered statistically significant. Significance is designated by asterisks signs: * or # for $p \leq 0.05$, ** for $p \leq 0.01$ and *** for $p \leq 0.001.$
## 3.1. Expression Analysis of H2S-Generating and -Metabolizing Enzymes in EO771 Cells
We have used EO771 cells, which is a murine luminal B mammary cancer cell line (estrogen receptor α negative, estrogen receptor β positive, progesterone receptor positive and ErbB2 positive), originally isolated from a spontaneous tumor in a C57BL/6 mouse [9]. The results demonstrate that the EO771 cells express all three principal H2S-generating enzymes, CBS, CSE and 3-MST. For CBS, in these cells, the cleaved form of the enzyme—which does not have the regulatory domain and is constitutively active [10,11]—is the predominant form present in these cells, with full-length CBS not detectable by Western blotting (Figure 1).
We also assessed whether AOAA or HMPSNE affect the expression of these enzymes after incubation for 24 or 48 h. No statistically significant effects were detected (Figure 1 and Figure 2).
Using live cell imaging (with the utilization of AzMC, a fluorescent H2S dye) significant H2S generation was detectable in EO771 cells (Figure 3).
When treated with the CBS/CSE inhibitor AOAA (Figure 3A,C), or the 3-MST inhibitor HMPSNE (Figure 3B,D), H2S generation was markedly decreased. These data indicate that cellular H2S generation is dependent on both the CBS/CSE and the 3-MST pathways.
Expression of the known H2S-metabolizing enzymes, SQR, TST (rhodanese) and ETHE-1 was also detected in these cells (Figure 4).
Treatment of the cells with AOAA tended to slightly reduce the expression levels of all 3 enzymes (Figure 4A–D), while treatment of the cells with HMPSNE (200 µM) significantly reduced TST expression (Figure 4A,C). It is likely that the protein levels of H2S degrading enzymes are regulated by the ambient H2S levels: when the H2S levels are pharmacologically suppressed, the H2S degrading enzymes may, in turn, may become downregulated as a response.
## 3.2. Role of CBS and 3-MST in the Regulation of Cellular Bioenergetics in EO771 Cells
Using Extracellular Flux Analysis, we have next tested the role of endogenous H2S generation on the maintenance of cellular bioenergetics in EO771 cells, an effect that has previously been demonstrated in various other cancer cell types [12]. The results show that both the inhibition of CBS/CSE and of 3-MST suppresses basal oxidative phosphorylation/mitochondrial ATP generation as well as—in the case of 3-MST but not CBS/CSE—anaerobic ATP generation (glycolysis), when the cells are using glucose as their primary bioenergetic source (Figure 5).
When we use glutamine as a bioenergetic source (instead of glucose), once again, both the 3-MST inhibitor and the CBS/CSE inhibitor suppress mitochondrial oxygen consumption and ATP generation (Figure 5). Based on these data, endogenously generated H2S, largely independently of its source (CBS/CSE vs. 3-MST) and largely independent of the substrate used by the cell (e.g., glucose vs. glutamine) plays a role in the maintenance of basal aerobic (i.e., mitochondria-dependent) bioenergetic function. With respect to basal cellular glycolysis, 3-MST, but not CBS/CSE appears to play a significant role.
## 3.3. Role of CBS and 3-MST in the Regulation of Proliferation and Migration in EO771 Cells
We have next assessed whether pharmacological inhibition of CBS or 3-MST affects proliferation and migration of EO771 cells. Inhibition of the CBS/CSE axis reduced cell proliferation, but only at its highest concentration (1000 µM) tested; the observed effect was transient, and at later time points (>24 h) cells appeared to regain a faster rate of proliferation; by 72 h, cell confluence was comparable in all groups with or without AOAA (Figure 6A,C,E).
In contrast, HMPSNE produced a concentration-dependent and sustained inhibition of cell proliferation throughout the 72 h observation period (Figure 6B,D,E). The effect of the 3-MST inhibitor remained pronounced and statistically significant at the conclusion of the experiments at 72 h (Figure 6B,D,E).
Cell migration was not significantly affected by treatment with AOAA (Figure 7A,B). In contrast, HMPSNE exerted a concentration-dependent inhibitory effect (Figure 7C,D).
## 3.4. Role of CBS and 3-MST in the Regulation of Oxidative Stress Response in EO771 Cells
Next, we determined if pharmacological inhibition of H2S biosynthesis affects the response to oxidative stress in EO771 cells. Using the LDH and MTT assays, the effect of the rapid acting cytotoxic oxidant hydrogen peroxide (H2O2) was tested. This oxidant, as expected, decreased cell viability in a concentration-dependent fashion. When cells were pretreated with AOAA, the response to the oxidant was unaffected (Figure 8).
In contrast to the lack of effect of AOAA, the 3-MST inhibitor HMPSNE tended to have a slight potentiating effect on the response to oxidative stress, but this effect was only statistically significant at 2 h and not 24 h, and only statistically significant at certain concentrations of the oxidant (Figure 9). For instance, in the presence of the 3-MST inhibitor, the ability of H2O2 (1000 and 2000 µM) to increase LDH release was more significant than in the absence of the inhibitor (Figure 9A). Moreover, the ability of 60 or 1000 µM H2O2 to suppress cellular MTT conversion to formazan was statistically more pronounced (Figure 9C).
These data indicate that H2S may play a slight role as a cytoprotective agent in breast cancer cells, but this effect is fairly minor, and is only detectable for 3-MST-derived H2S or polysulfides, but not for CBS/CSE-derived H2S. AOAA or HMPSNE, on its own, at the concentrations used, did not have any marked effects of cell viability in non-oxidatively stressed cells (Figure 8 and Figure 9).
## 4. Discussion
In 2013, it was demonstrated that colon cancer cells show increased expression of CBS, and use its product, H2S, to support their cellular bioenergetics, proliferation, growth, and angiogenesis [13]. Follow-up studies in colon cancer, as well as in a variety of other cancers including ovarian cancer, glioblastoma, and lung cancer, have confirmed and extended these observations [14,15,16,17,18,19,20]. The enzymatic source of H2S was found to be CBS in many cancer types; but in some models, CSE and/or 3-MST were found to contribute as well [3,7,15,19,21,22,23,24,25,26].
With respect to breast cancer, the first report was published by Sen and colleagues in 2015, demonstrating that CBS is upregulated in human breast cancer cell lines, H2S is produced in excess, and it serves as a tumor cell-supporting mediator [27]. Among others, this report demonstrated that H2S serves as a factor that protects breast cancer cells from macrophage-mediated cytotoxicity and elimination [27,28]. Importantly, in murine xenograft models, breast cancer cell growth was markedly slower in CBS-silenced cells than the growth of wild-type cells [27]. Subsequent studies, specifically focusing on triple-negative human breast cancer cells in vitro, demonstrated that exogenously administered H2S exerts a bell-shaped effect, with lower concentrations of the mediator promoting proliferation, migration and colony formation, while higher concentrations induce the opposite effects [29]. This bell-shaped concentration-response is characteristic of various gaseous mediators including H2S and also supports the development of multiple therapeutic concepts either based on inhibition of endogenous H2S generation or delivery of exogenous H2S to produce anticancer cell toxicity [1,2].
Subsequent studies on H2S in breast cancer cells focused on the identification of the endogenous enzymatic sources of this gasotransmitter, as well as on the effects it exerts. Wang and colleagues, using MDA-MB-231 human breast cancer cells (a triple-negative line) identified CSE as a key source of H2S and demonstrated that the metastatic ability of these cells is, at least in part, dependent on the CSE/H2S axis and also involves VEGF signaling and PI3K activation [30]. Later on, the work of Nagy and colleagues demonstrated that both CBS and CSE expression are important to support breast cancer cell proliferation and survival. This work primarily focused on basal-like breast cancer, an aggressive cancer subtype. These studies demonstrated that CBS silencing (shCBS) makes these cells less invasive, reduce their proliferation rate, renders them more vulnerable to oxidative stress and cystine deprivation, sensitizes them to ferroptosis, and renders them less responsive to HIF1-α activation under hypoxia [31].
The current work, utilizing a murine breast cancer cell line, focused on the expression of all major H2S-generating and H2S-metabolizing enzymes and tested the effect of pharmacological inhibition of CBS/CSE vs. 3-MST on a variety of functional parameters. While EO771 cells expressed all three major H2S-generating enzymes CBS, CSE, and 3-MST, and produced significant levels of H2S due to a combination of these enzymes, the pharmacological experiments (using the combined CBS/CSE inhibitor AOAA or the 3-MST inhibitor HMPSNE) revealed a more pronounced role of 3-MST in these cells than CBS or CSE. Regarding the bioenergetic aspects, both AOAA and HMPSNE tended to suppress various bioenergetic parameters related to oxygen-dependent ATP generation (i.e., mitochondrial function), while only the 3-MST inhibitor was found to suppress the glycolytic activity of these cells. When comparing the functional responses to these pharmacological agents, the CBS/CSE inhibitor only exerted a transient and relatively slight inhibitory effect on cell proliferation (and this effect was only noted at a high concentration of this agent, at which concentration effects on additional enzymatic targets may also possible [10]), and had no inhibitory effect on cell migration, nor did it affect the cell’s responsiveness to exogenously administered hydrogen peroxide. In contrast, the 3-MST inhibitor exerted a concentration-dependent, marked inhibitory effect both on cell migration and cell proliferation, and it also tended to exacerbate the response to the oxidant, although this effect was only noted at certain concentrations of H2O2 and only in the short-term, but not the longer-term experiment. Taken together, it appears that in EO771 cells, H2S generation from 3-MST plays a more prominent cancer-cell-supporting role, and the functional role of CBS and/or CSE is relatively minor. In this respect, EO771 cells appear to resemble the CT26 murine colon cancer cell line, in which also 3-MST (rather than CBS or CSE) appears to play the primary tumor-cell-supporting role [7]. Whether the more prominent role of 3-MST in murine cells (as opposed to CBS and/or CSE in human cells) represents a more general trend remains to be investigated in the future.
The current study, thus, confirms and extends the growing body of information regarding the functional importance of endogenously generated H2S in breast cancer cells. Clearly, it has several limitations. First of all, it is a strictly in vitro study and does not incorporate tumor-bearing mouse models. ( Notably, however, these cells are on a Bl6 background and will be amenable for such experiments in the future. Such experiments may be used in the future to compare the relative importance of tumor-cell-derived vs. host-derived H2S in the modulation of breast cancer cell growth.) Second, it primarily focuses on basal fundamental functional parameters (e.g., bioenergetics and cell proliferation and migration) and does not utilize more complex models (e.g., cancer cell death induced by anticancer agents or immune cell co-cultures). Third, it only utilizes one selected cell line (it is possible that the H2S-producing enzyme expression profile of other murine breast cancer cell lines is different from those characterized here). Fourth, it does not investigate the functional role of the H2S-degradation pathways, only focuses on the H2S production aspect. These enzymes SQR, TST and ETHE-1, indeed, play an important role in the modulation of intracellular H2S levels, by significantly affecting the rate of H2S degradation [1,2]. The reason for less focus on these enzymes in the current project is that we believe that inhibition of these enzymes is more translationally relevant than modulation of the degradation pathways; another reason is that the availability of cell-permeable small molecules to modulate the degradation pathways is rather limited. Fifth, the pharmacological agents used in the current study, AOAA and HMPSNE, have their own limitations. Regarding AOAA, the mechanism of its action has recently been overviewed, as well as its selectivity profile [10]. This compound, although commonly referred in the literature as a ‘CBS inhibitor’, also inhibits CSE [5] as well as many PLP-dependent enzymes [10]. Moreover, it is commonly referred as an ‘irreversible inhibitor’, although recent data reveal that its inhibitory effect on CBS can be also reversible under certain conditions [32]. With respect to its effect on H2S generation, we provide in the current report direct evidence that the compound, indeed, reduces cellular H2S levels (as shown by its effect on AzMC-aided H2S detection in live cells), and we also demonstrate that it does not affect the expression of the principal H2S-generating or H2S-metabolizing enzymes (as quantified by Western blotting). While it may have additional enzymatic targets beyond the H2S pathway, overall, its functional effects in the current system were minor. Thus, we feel that we can conclude with confidence that CBS and CSE in the current cell line only play a minor functional role. With respect to the 3-MST inhibitor used (HMPSNE), the availability of pharmacological 3-MST inhibitors is rather limited, and from the limited choices (which, in previous years, utilized non-specific compounds such as L-aspartic acid) this compound is vastly superior and is used in the literature fairly commonly, and without evidence of significant off-target or non-specific effects [7,11,33,34,35,36,37,38,39,40,41,42]. Using this compound (at the concentration range that is comparable to those used in prior studies), a significant functional role of the 3-MST/H2S pathway could be demonstrated in the current cellular model.
Nevertheless, the utilization of pharmacological agents (in general, and also in particular in the current set of experiment) may be complicated by non-specific (“off-target”) effects. Therefore, further studies remain to be conducted in the future to further validate the findings. Such studies may include silencing/knockout approaches (e.g., siRNA, shRNA or CRISPR) for CBS or 3-MST, with the caveat that these approaches may induce significant cytotoxicity due to the long-term absence of enzymes that may be crucial for cancer cell survival. Indeed, long-term treatment with 3-MST inhibitors have been shown to promote cancer cell apoptosis [42].
The current findings are solely in vitro. Future, in vivo studies remain to be conducted to test the effect of CBS or 3-MST inhibition in mouse models bearing breast cancer cell lines. Based on prior in vivo studies using other forms of cancer (e.g., colon cancer, ovarian cancer, or other forms of breast cancer) [4,31,38] we anticipate that inhibition of CBS or 3-MST will suppress cancer cell proliferation.
## 5. Conclusions
In summary, endogenous H2S, primarily produced by 3-MST (and to a minor degree by CBS/CSE), significantly contributes to the maintenance of bioenergetics, proliferation and migration in the murine breast cancer cell line EO771 and may also exert a minor role as an endogenous cytoprotectant. Given the physiological role of the same enzyme in maintaining and supporting various fundamental metabolic functions also in normal healthy tissues [40], further studies are required to determine if inhibition of 3-MST, on its own, or in combination with various anticancer therapeutics, may be useful to limit the growth and proliferation of breast cancer cells in vivo.
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|
---
title: Nitric oxide-releasing gel accelerates healing in a diabetic murine splinted
excisional wound model
authors:
- Dharshan Sivaraj
- Chikage Noishiki
- Nina Kosaric
- Harriet Kiwanuka
- Hudson C. Kussie
- Dominic Henn
- Katharina S. Fischer
- Artem A. Trotsyuk
- Autumn H. Greco
- Britta A. Kuehlmann
- Filiberto Quintero
- Melissa C. Leeolou
- Maia B. Granoski
- Andrew C. Hostler
- William W. Hahn
- Michael Januszyk
- Ferid Murad
- Kellen Chen
- Geoffrey C. Gurtner
journal: Frontiers in Medicine
year: 2023
pmcid: PMC10045479
doi: 10.3389/fmed.2023.1060758
license: CC BY 4.0
---
# Nitric oxide-releasing gel accelerates healing in a diabetic murine splinted excisional wound model
## Abstract
### Introduction
According to the American Diabetes Association (ADA), 9–12 million patients suffer from chronic ulceration each year, costing the healthcare system over USD $25 billion annually. There is a significant unmet need for new and efficacious therapies to accelerate closure of non-healing wounds. Nitric Oxide (NO) levels typically increase rapidly after skin injury in the inflammatory phase and gradually diminish as wound healing progresses. The effect of increased NO concentration on promoting re-epithelization and wound closure has yet to be described in the context of diabetic wound healing.
### Methods
In this study, we investigated the effects of local administration of an NO-releasing gel on excisional wound healing in diabetic mice. The excisional wounds of each mouse received either NO-releasing gel or a control phosphate-buffered saline (PBS)-releasing gel treatment twice daily until complete wound closure.
### Results
Topical administration of NO-gel significantly accelerated the rate of wound healing as compared with PBS-gel-treated mice during the later stages of healing. The treatment also promoted a more regenerative ECM architecture resulting in shorter, less dense, and more randomly aligned collagen fibers within the healed scars, similar to that of unwounded skin. Wound healing promoting factors fibronectin, TGF-β1, CD31, and VEGF were significantly elevated in NO vs. PBS-gel-treated wounds.
### Discussion
The results of this work may have important clinical implications for the management of patients with non-healing wounds.
## Introduction
Despite medical advances and various prevention efforts, diabetes mellitus has become a major global health crisis [1]. More than 26 million individuals in the United States were diagnosed with diabetes in 2020, and it is estimated that an additional 90 million individuals have evidence of pre-diabetes [2]. In 2017, the estimated medical cost of diagnosed diabetes was 237 billion US dollars. In addition to treatment of the disease itself, annual nonmedical costs associated with diabetes exceeded 15 billion dollars, with projections that more than 41 million individuals will be diagnosed with diabetes by 2030 [3]. These figures highlight the growing financial burden this disease places on society. In addition, diabetic complications significantly reduce quality of life and diminish social productivity. Diabetic neuropathy and microangiopathy inhibit cutaneous wound closure and can result in chronic lesions, ulcers, epithelial erosion, and amputation of the extremities despite treatment efforts. Therefore, efforts to effectively promote wound healing and tissue repair of chronic wounds are increasingly relevant and vital to combat this evolving public health issue.
The mechanisms underlying wound repair involve complex biologic processes and coordinated interactions between cells, growth factors, and extracellular matrix (ECM) proteins [4]. These mechanisms progress through a series of interdependent and overlapping phases including hemostasis, inflammation proliferation, and remodeling [5]. Chronic wounds are wounds that have failed to progress through these ordered phases and have instead entered a state of pathologic inflammation and unresolved healing [6]. The challenges associated with treating chronic wounds are potentiated by the systemic complications of diabetes, which include tissue hypoxia and decreased collagen production [7].
Nitric Oxide (NO) is an endogenous messenger molecule that plays a central role in wound healing [8]. NO levels typically increase rapidly after skin injury in the inflammatory phase and gradually diminish as wound healing progresses [6]. The NO molecule is produced from an oxidation process catalyzed by a group of three isozymes including endothelial nitric oxide synthetase (eNOS), inducible nitric oxide synthetase (iNOS), and neuronal nitric oxide synthetase (nNOS) [9]. NO plays an important role in wound healing by mediating vascular hemostasis, inflammation, and antimicrobial action. Decreased production of NO is characteristic of diabetes and has been associated with impaired healing in chronic wounds. Studies have shown that the topical application of NO-releasing agents on wounds can stimulate cell proliferation, increase the production of collagen and growth factors, and accelerate angiogenesis (10–12). However, the effect of increased NO concentration in the context of diabetic wound healing has yet to be described. In this study, we investigated the effect of local administration of an NO-releasing gel on excisional wound healing in diabetic mice.
## Animals
Genetically diabetic db/db mice (BKS.Cg-m $\frac{1}{1}$ Leprdb/J) were obtained from Jackson Laboratories (Bar Harbor, ME) (strain #: 697). These homozygous db/db mice possess a genetic mutation of the leptin receptor and represent a model of type 2 diabetes characterized by impaired wound healing, obesity, hyperglycemia, and hyperinsulinemia (Supplementary Table 1). Animal care was provided in accordance with the Stanford University School of Medicine guidelines and policies for the use of laboratory animals.
## In vivo stented excision wound model
Female db/db mice were randomized into two treatment groups: NO-gel or PBS-gel control ($$n = 5$$ mice per group). Splinted full-thickness excisional wounds were created as previously described by Galiano et al. [ 13] A full-thickness wound was excised using a sterile 6-mm punch biopsy tool on each side of the dorsal midline. Each wound was splinted with donut-shaped silicone splints cut from a 0.5 mm silicone sheet (Grace Bio-Laboratories, Bend, OR). The splint was centered around the wound, affixed to the skin using a bonding adhesive (surgical glue), and then sutured in place to prevent wound contracture and promote granulation tissue formation to mimic human wound healing. Two excisional wounds of each mouse received either NO-gel or control PBS-gel treatment twice daily until complete wound closure. All wounds were covered with a sterile occlusive dressing (Tegaderm, 3 M, St. Paul, MN, United States). Wound dressings were changed once per day for the duration of the experiment. Digital photographs were taken on day 0 and 1 and every other day thereafter until complete wound closure. The wound areas were quantified using ImageJ and expressed as a percentage of the original wound area.
## NO-gel preparation and application
Based on Zhu’s method, a warm solution of sodium nitrite (14.6 mM) in distilled water was introduced into a gel by adding hydroxyethyl cellulose (molecular weight 50,000–1,250,000) [9, 14].
This dosage was chosen as it releases a comparatively constant maximal output of NO over time. In the current study, 2 g sodium nitrite was dissolved in 100 mL 3.2 g/100 mL cellulose solution to prepare nitrite gel, and 0.85 g maleic acid and 1.3 g vitamin C were dissolved in 25 ml 3.2 g/100 mL cellulose solution to prepare low pH acid gel. After mixing equal amounts of the two gels immediately before use, the mixture was placed on the excisional wound. This dosage for application was established based on an approved protocol by the National Institute of Health-Small Business Technology Transfer (NIH-STTR) grant. The release kinetics of this nitric oxide gel has previously been monitored by an amperometric electrode technique (amiNO-2000 NO Sensor, Innovative Instruments, In. Tampa, FL). This NO-release study showed that the concentration of NO can be maintained at 10 nM within the wound bed over 1 h after application [9]. The PBS gel was prepared by exchanging sodium nitrite for sodium phosphate. The sodium nitrite and low pH gel prepared with the addition of maleic acid and ascorbic acid were mixed prior to application, and subsequently applied to the wound area, covering the area entirely. Immediately after wounding, either NO-releasing gel (1 × 10 in 100 μL of PBS) or the same volume of PBS-gel was applied onto wound twice daily until wound closure, and the rate of wound healing was evaluated every other day.
## Histological analysis of collagen content and architecture
Wounds were harvested on day 2 and 7 after wounding, and healed scar tissue was harvested at the end of the study on day 21. Tissues were fixed in $4\%$ paraformaldehyde overnight, dehydrated with sequential ethanol concentrations ($30\%$, $50\%$, $70\%$, and $95\%$), xylene, and paraffin washes, and embedded in paraffin for sectioning. Hematoxylin and Eosin (H&E) and Masson’s Trichrome staining were performed according to the manufacturer’s recommendations, and images were captured with a Leica Aperio AT2 digital whole slide scanner. We implemented an algorithm in MATLAB to automatically deconvolute the color information of each Trichrome image [15]. This algorithm allows for a robust and flexible method for objective immunohistochemical analysis of samples stained with up to three different colors. Picrosirius Red (Sigma Aldrich) staining was also performed, and we utilized a Leica DM5000 B upright microscope for linear polarized light microscopy to capture images of the Picrosirius Red-stained images. Polarized light was oriented to maximally display fibers parallel to the skin surface. Collagen fiber quantification was performed using CT-FIRE and CurveAlign, an open-source software package for automatic segmentation and quantification of individual collagen fibers1 [15]. Briefly, CurveAlign quantifies all fiber angles and the strength of alignment within an image, while CT-FIRE analyzes individual fiber metrics such as length, width, angle, and curvature. The average fiber parameters for each mouse were used for statistical analysis. Finally, complexity and heterogeneity were measured using the ImageJ plug-in FracLac [16]. The software analyzes tissue morphology using fractional dimensions to determine the lacunarity (L) values using the subsample box counting scan (50 grid default sampling size, minimal pixel density threshold = 0, and rectangle subscan). L measures the amount of randomness or heterogeneity in a sample. A low L implies less heterogeneous collagen fiber orientation.
## Immunofluorescent staining
Immunofluorescent staining was performed using primary antibodies Fibronectin (1:100 dilution, Abcam, Ab2413), TGFβ1 (1:100 dilution, Abcam, Ab215715), VEGF (1:100 dilution, Thermo Fisher Scientific, PA1-21796), and CD31 (Abcam, ab28364). The percentage of fluorescent area was quantified using a custom MATLAB image processing code written by the authors and previously published [17]. All immunofluorescent images shown are representative images.
## Statistical analysis
Statistical analysis was performed in Prism8 (GraphPad, San Diego, California). Continuous variables were assessed using an unpaired Student’s t-test or two-way analysis of variance (ANOVA). Data were presented as means ± standard error of the mean. Sample sizes (n) and p values are indicated in the figure legends. Values of *$p \leq 0.05$ were considered statistically significant.
## Nitric oxide-releasing gel accelerates excisional wound healing in db/db mice
The efficacy of topical administrated NO-releasing gel on wound healing was evaluated in a mouse excisional wound healing model as described previously (Figure 1A). To measure the effect of each hydrogel treatment on wound healing, we assessed wound area change over time by analyzing digital photographs that were taken during each dressing change (Figures 1B,C). The wound size is represented as an average size of 10 wounds per treatment group (5 mice per group, 2 wounds per mouse). At postoperative days 13 and 15, wounds treated with the NO gel were significantly smaller than wounds treated with PBS (Figure 1C). The absolute wound percentage sizes are also shown as individual bar graphs (Figure 1D) to further demonstrate this significant difference at both postoperative day (POD) 13 (*$p \leq 0.05$) and POD 15 (*$p \leq 0.05$). We then assessed the digital photographs of each mouse wound to determine the average number of days before complete wound closure for each treatment group. The mean time for complete wound healing was 14.0 ± 0.75 days in the NO-gel-treated group, significantly faster than 16.0 ± 0.75 days in the PBS-gel-treated group (*$p \leq 0.05$, Figure 1E).
**Figure 1:** *(A) Experimental overview of excisional wounding and treatment. (B) Representative images of the wound over time by treatment group, where NO = Nitric Oxide gel; PBS: Phosphate-Buffered Saline-gel control. Healed = healed wound that has closed. (C) Quantification of wound area over time by treatment group. (D) Wound area size at postoperative (POD) 13 and 15. (E) Days until complete wound closure by treatment group. Data are presented as mean value ± SEM, *p < 0.05.*
## Nitric oxide-releasing gel improves collagen architecture in healed diabetic wounds
Collagen tissue quality of healed wounds in the NO- and PBS-gel-treated groups at day 21 was evaluated using picrosirius red staining, which highlights collagen networks by making use of the birefringent properties of collagen molecules, to evaluate the collagen density and orientation of the scars in each group. Analysis of unwounded (UW) skin was included for comparison. The red pixel intensity among PBS and NO-gel-treated healed scars and UW skin were similar, indicating a comparable amount of mature collagen within the healed scars in both groups (Figure 2A). A quantitative assessment of the collagen architecture of the wounds was then performed using the software algorithms CT-Fire, CurveAlign, and FracLac, which have been previously developed for analysis of collagen fiber properties on histology images (18–20). We utilized this array of metrics to analyze the fiber length, angle skewness, red pixel intensity, and fiber lacunarity of the tissues. Using CurveAlign, we found that NO-gel-treated wounds showed significantly more random alignment compared to PBS-gel-treated wounds and displayed a similar phenotype to that of UW skin (*$p \leq 0.05$; Figure 2B). Using CT-FIRE, we found that NO-gel-treated wounds and UW skin also demonstrated a trend toward shorter fiber lengths compared to PBS-gel-treated wounds ($$p \leq 0.0807$$; Figure 2C). Finally, using FracLac analysis to assess the complexity and heterogeneity of the healed scars in all groups, we found that NO-gel-treated wounds and UW skin displayed significantly greater lacunarity compared to PBS-gel-treated wounds (*$p \leq 0.05$), indicating a more heterogeneous collagen fiber network orientation (Figure 2D). Lacunarity measures the number of gaps in the tissue and thus is a surrogate marker of tissue density. We found that NO-gel-treated wounds had a porous architecture akin to that of UW skin. Taken together, our results suggest that NO-gel promoted shorter and more randomly aligned collagen in the wound bed, more like the collagen fiber networks present in UW skin (Figures 2A–D) [4, 18, 21, 22]. In contrast, PBS-gel-treated wounds promoted a densely aligned collagen network with long fibers typically associated with fibrotic tissue.
**Figure 2:** *Picrosirius red staining and comparison of NO and PBS-gel-treated wounds, using collagen algorithms CurveAlign, CT-Fire, and FracLac. Scale bars: 200 μm. Quantification of (A) collagen fiber pixel intensity, (B) fiber angle skewness, (C) fiber length, and (D) tissue lacunarity. ns = nonsignificant. Data are presented as mean value ± SEM, *p < 0.05.*
## Nitric oxide-releasing gel improves dermal structure in healed diabetic wounds
The tissue composition of murine scar tissue was qualitatively assessed using Hematoxylin and Eosin (H&E) staining, which showed, on average, increased cellularity in the NO-gel-treated scars compared to the PBS-gel-treated scars (Figure 3A). Dermal structure of murine scar tissue was assessed using Masson’s Trichrome staining (Figure 3B). Trichrome staining confirmed the picrosirius red staining analysis results, showing a more randomly aligned collagen fiber network in the NO-gel-treated healed scars on day 21. In contrast, PBS-gel-treated healed scars on day 21 were characterized by longer and more avascular bundles of collagen. The collagen area was similar and nonsignificant between the NO and PBS-gel-treated groups. On day 2 of treatment, there were minimal differences in collagen deposition and area between the two groups. Interestingly, on day 7 of treatment, there was significantly higher collagen deposition in the NO-gel-treated wounds (Figure 3B).
**Figure 3:** *(A) Representative H&E images of tissue sections on days 2, 7, and 21 (healed) showing cells (nuclei in purple) and extracellular matrix (pink) in all groups. Arrows indicate blood vessels. Scale bars: 150 μm. (B) Masson’s trichrome staining of representative tissue sections showing dermal structure of NO and PBS-gel-treated wounds on days 2, 7, and 21 (healed). Analysis for total area positive for collagen (area blue). Scale Bar: 200 μm.*
## Nitric oxide-releasing gel increases expression of wound healing promoting factors
To assess the effect of NO on wound healing promoting factors, we performed immunostaining of fibronectin and TGF-β1, which have been shown to be reduced in abnormal wound repair and in chronic wounds (23–28). First, we observed that expression of fibronectin was significantly higher at days 2, 7, and 21 (post healing) in the NO-gel-treated group compared to the PBS-gel-treated group (Figure 4A). Further, fibronectin levels appeared to be consistently maintained over time in the NO-gel-treated group, while levels appeared to decrease over time in the PBS-gel-treated group. We observed that expression of TGF-β1 progressively decreased over the course of PBS-gel treatment and was significantly lower than in the NO-gel treatment group on day 21 (*$p \leq 0.05$) (Figure 4B). Staining for markers of angiogenesis, CD31 and VEGF, in explanted scar tissue revealed significantly higher expression of both markers in the NO-gel-treated group compared to the PBS-gel -treated group (*$p \leq 0.05$) (Supplementary Figure S1). Taken together, these results suggest that NO-gel treatment is associated with a cascade of downstream effects, including upregulation and sustained maintenance of wound healing and angiogenic promoting factors. Thus, administration of exogenous NO promotes a healing phenotype that reverses the impaired wound healing observed in diabetic mice.
**Figure 4:** *(A) Immunostaining for Fibronectin and (B) TGF-β1 in tissue sections on days 2, 7, and 21 (healed). Scale bars: 50 μm. Quantification of percent area positive for marker in each section. Data are presented as mean value ± SEM, *p < 0.05.*
## Discussion
Previous studies have shown that topical NO-releasing agents enhance excisional wound healing in diabetic models via a variety of mechanisms including increased cell infiltration, cytokine release, and growth factor production (6, 8, 10–12, 14). However, the tissue architectural changes in collagen structure and alignment resulting from the application of exogenous NO in diabetic wound healing have not been described. Here, we found that the application of NO-gel treatment accelerates wound healing and promotes tissue with shorter, less dense, and more randomly aligned collagen fibers, more similar to the natural architecture of unwounded skin. Further, we show that application of NO-gel treatment elevates expression of fibronectin and TGF-β1 throughout the healing process, as well as elevates expression of angiogenic factors CD31 and VEGF within the healed tissue.
We found that the NO-gel-treated and PBS-gel-treated diabetic wounds had similar rates of wound closure until approximately day 9, when the NO-gel-treated wounds began to close more rapidly. This divergence indicates that our treatment produces the most significant effects toward the later stages of diabetic wound healing. Interestingly, although the total collagen area in both groups was similar in the healed scars by day 21, the resultant tissue architecture was markedly different between the two groups. Our unbiased collagen analysis showed that healed tissue from NO-gel-treated wounds exhibited a “basket weave”-like collagen fiber network, resembling the physiologic dermal collagen architecture of unwounded murine skin. This contrasted with PBS-gel-treated wounds, which were predominantly composed of large, long bundles of avascular collagen and a less robust tissue architecture. A “basket weave”-like tissue architecture has been associated with significantly higher resistance to mechanical tensile forces compared to scars that display more highly aligned collagen networks (29–31). Our immunohistochemical analyses showed that levels of fibronectin and TGF-β1 progressively decreased in the PBS-gel-treated group but remained persistently elevated in the NO-gel-treated group over the course of healing.
Fibronectin is a large glycoprotein that provides critical linkage between the ECM and integrins [24]. During healing, fibronectin acts as a building block that helps to facilitate the formation of more mature ECM (e.g., collagens), granulation tissue, and new epithelial tissue in concert with fibroblasts and other cell types [23]. Reduced fibronectin matrix deposition is associated with chronic wound healing and an inability to form a new ECM in the wound bed (32–34). NO-synthase has been shown to be directly involved in enhancing fibronectin production by endothelial cells [35]. Upregulated fibronectin expression was observed as early as day 2 and then persistently throughout all time points, which likely helped to promote accelerated wound closure, ECM reconstruction, and overall beneficial tissue healing.
Chronic wounds, including diabetic foot ulcers, have been found to exhibit a lack of expression of all transforming growth factor (TGF-β) isoforms [27]. Specifically, fibroblasts from diabetic wounds, which are recruited to the wounds from immune cells, appear to exhibit impaired TGF-β signaling and decreased ECM synthesis [26, 36]. In the context of wound healing, TGF-β is involved in angiogenesis, fibrosis, as well as the production and maintenance of ECM components including fibronectin and collagen [26]. TGF-β downregulates the expression and activity of matrix-degrading enzymes such as MMPs, which are highly upregulated in diabetic wounds. Some studies have suggested a mutual feedback mechanism between nitric oxide synthase (NOS) and TGF-β1 where NOS may be exerting its action within the wound bed via signaling of TGF-β1, leading to fibroblast activation and collagen production (25, 28, 37–40). In normal wound healing, TGF-β1 secreted from macrophages stimulates granulation tissue formation, collagen formation, and ECM remodeling [5]. Our data indicate that NO-gel treatment is associated with steadily increasing TGF-β1 levels within the wound bed, which is likely linked in part to the improved tissue quality we observed.
Overall, our findings suggest that NO-gel treatment in chronic diabetic wounds accelerates wound healing and promotes a scar phenotype more similar to the natural basket-weave architecture of unwounded skin. The direct and indirect effects of NO pharmacologically accelerate wound healing, likely in part, by increasing angiogenesis and production of fibronectin and TGF-β1 within the wound bed. These factors lay the appropriate foundation for normal ECM reconstruction, angiogenesis, and tissue reconstruction in chronically impaired wounds. We show that by restoring the physiological environment present in normal wound healing, we can promote tissue reconstruction and accelerate healing in diabetic wounds. Future studies will need to be performed to interrogate the molecular mechanisms driving healing from exogenous NO therapy, as well as the relationship between NO, fibronectin, TGF-β1, and angiogenesis in chronic wound healing.
## Data availability statement
The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors.
## Ethics statement
The animal study was reviewed and approved by Stanford University School of Medicine.
## Author contributions
NK, HaK, CN, DS, KC, FM, and GG designed the study. HaK, NK, HuK, KF, DH, AT, BK, ML, MG, AH, and WH performed animal experiments and data analysis. DS, CN, and NK wrote the manuscript. GG and KC helped to revise and edit the manuscript. All authors contributed to the article and approved the submitted version.
## Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
## Supplementary material
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmed.2023.1060758/full#supplementary-material
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|
---
title: Bone Marrow Mesenchymal Stem-Cell-Derived Exosomes Ameliorate Deoxynivalenol-Induced
Mice Liver Damage
authors:
- Zitong Meng
- Yuxiao Liao
- Zhao Peng
- Xiaolei Zhou
- Huanhuan Zhou
- Andreas K. Nüssler
- Liegang Liu
- Wei Yang
journal: Antioxidants
year: 2023
pmcid: PMC10045494
doi: 10.3390/antiox12030588
license: CC BY 4.0
---
# Bone Marrow Mesenchymal Stem-Cell-Derived Exosomes Ameliorate Deoxynivalenol-Induced Mice Liver Damage
## Abstract
Deoxynivalenol (DON) is a kind of Fusarium toxin that can cause a variety of toxic effects. DON is mainly metabolized and detoxified by the liver. When the concentration of DON exceeds the metabolic capacity of the liver, it will trigger acute or chronic damage to the liver tissue. Previous studies demonstrated that bone marrow mesenchymal stem-cell-secreted exosomes (BMSC-exos) reduce liver injury. Therefore, we issue a hypothesis that in vitro-cultured rat BMSC-secreted exos could ameliorate liver damage after 2 mg/kg bw/day of DON exposure. In total, 144 lipids were identified in BMEC-exos, including high polyunsaturated fatty acid (PUFA) levels. BMSC-exos treatment alleviated liver pathological changes and decreased levels of alanine aminotransferase, aspartate aminotransferase, inflammatory factors interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and lipid peroxidation. Otherwise, low or high BMSC-exos treatment obviously changes DON-induced hepatic oxylipin patterns. According to the results from our correlation network analysis, Pearson correlation coefficient analysis, and hierarchical clustering analysis, the top $10\%$ oxidized lipids can be classified into two categories: one that was positively correlated with copper–zinc superoxide dismutase (Cu/Zn SOD) and another that was positively correlated with liver injury indicators. Altogether, BMSC-exos administration maintained normal liver function and reduced oxidative damage in liver tissue. Moreover, it could also significantly change the oxylipin profiles under DON conditions.
## 1. Introduction
DON is one of the most important trichothecenes in grain contamination, frequently contaminating food and feed around the world [1,2]. The presence of DON in human or animal food can cause serious health problems. For example, 50 μg/kg bw (ip or oral) can elicit emesis in Yorkshire barrows pigs, causing LD50 values for the ip and oral exposure of mice to range from 49 to 70 and 46 to 78 mg/kg bw, respectively. Norwegian Landrace pigs consuming 2 and 4 ppm of DON caused decreased feed intake, weight gain, and feed utilization efficiency throughout the experiment, and short-term exposure to DON at 2.5 and 5 mg/kg bw could impair reproduction and development in rodents [3,4,5]. Therefore, long-term low-dose DON exposure may become a global threat to human health [6].
Several studies have illustrated that DON-induced reactive oxygen species (ROS) production occurs in a dose-dependent manner in in vitro experiments, with a peak of ROS production within 1 h, clearly indicating that oxidative stress is an early event in the process of DON-induced toxic effects [7,8,9]. ROS can initiate lipid peroxidation in lipid membranes, leading to damage to membrane phospholipids and lipoproteins that further trigger membrane dysfunction and indirectly induce DNA and protein denaturation through free radical propagation chain reactions [10,11]. Many studies have also shown that DON exposure could increase lipid peroxide levels and promote the formation of aldehyde products in DON-induced cytotoxicity and apoptosis [7,9,12]. This also suggests that the oxidative damage from DON may be related to its polar chemical structure containing three free hydroxyl groups (•OH) [13]. In addition, according to the 2011 WHO report, humans’ average daily intake of DON is 0.2–14.5 μg/kg bw/day [14]. In some countries, DON intake in children exceeds 1.0 μg/kg bw/day, which is the provisional maximum tolerated daily intake (PMTDI, PDI) [15]. However, the potential harm of this low-dose exposure in target organs remains poorly controlled, especially in the liver, which is mainly responsible for detoxifying DON in animals and humans. Therefore, we hope to find a potential strategy to combat DON-induced liver damage.
Emerging studies have also focused on the therapeutic effects of bone marrow mesenchymal stem-cell-secreted exosomes (BMSC-exos) on liver injury [16,17,18,19]. BMSC-exos are nano-scale vesicles with a lipid bilayer membrane structure of 40–160 nm, which can be separated by the affinity membrane technique, and their membrane lipid composition is closely related to BMSC cells [20]. BMSC-exos have the advantages of low cost, less invasiveness, convenient isolation, easy storage, low immunogenicity among heterogeneous species, and differentiated pluripotency [21,22]. In direct or indirect studies, vesicles from BMSC could conflict with hepatic failure induced by D-galactosamine/tumor necrosis factor-α (TNF-α) [16]. Additionally, human BMSC-exos attenuated rat liver fibrosis by reducing alpha-smooth muscle actin (α-SMA) expressions to restore liver function [23]. Mouse BMSC-exos obviously alleviated autoimmune hepatitis-related liver necrosis and inflammatory markers [24]. Therefore, BMSC-exos may be an ideal strategy for ameliorating liver injury after DON exposure. However, the underlying mechanism of its therapeutic effect is unclear.
Otherwise, many studies of exosomes mainly focused on their contents, such as mRNA, microRNA, and proteins [25,26]. Lipids are an essential part of exosome membranes. Most studies on exosome lipids focused on lipid membrane structure, lipid species, and lipid abundance distribution [27]. Various studies have shown that oxidative stress is often closely associated with the occurrence and progression of liver disease [28,29,30], and antioxidant therapy has been used to treat liver disease [31,32]. Biofilms contain many PUFAs and the unsaturated double bonds in PUFAs are the primary attack targets from free radicals. The particle size of exosomes generally ranges between 40 and 160 nm [20]. The petite particle size makes them more preferentially react with free radicals and induces lipid peroxidation within in vitro experiments [33]. Therefore, according to the above context, we issue a hypothesis that the BMSC-exos lipid membrane might be “another helpful defensive line” against the liver’s oxidative damage with DON treatment.
In this study, we first aimed to evaluate the protective effect of different doses of BMSC-exos on DON-induced liver damage. Next, we explored whether the lipids of BMSC-exos play a critical role in conflicting oxidative damage triggered by DON. We hope that this research can provide a new strategy for future research.
## 2.1. Reagents
DON (12, 13-epoxy-3, 4, 15-trihydroxytrichotec-9-en-8-one, C15H20O6, molecular weight: 296.32, purity ≥ $99\%$, CAS number: 51481-10-8) was purchased from Sigma-Aldrich (St. Louis, MI, USA). The enhanced BCA protein assay kit (P0010), the total glutathione peroxidase (GPx) kit (S0058), the catalase (CAT) kit (S0051), the total superoxide dismutase (SOD) kit (S0101M), the Cu/Zn-SOD and Mn-SOD kit with WST-8 (S0103), and the lipid peroxidation (MDA) kit (S0131M) were purchased from Beyotime Biotechnology (Shanghai, China). The phosphatase inhibitor cocktail (B15001) and protease inhibitor cocktail (B1400) were purchased from Bimake (Houston, TX, USA). The alanine aminotransferase (ALT) kit (E-BC-K235-M), the aspartate aminotransferase (AST) kit (E-BC-K236-M), and the mouse tumor necrosis factor-alpha (TNF-α) (E-EL-0128c) ELISA kit were purchased from Elabscience Biotechnology Co., Ltd. (Wuhan, China). The mouse interleukin-6 (IL-6) (EK206HS) ELISA kit was purchased from Multisciences (Hangzhou, China). Fetal bovine serum (FBS) and DMEM/F12 media were purchased from Gibco (Thermo Fisher Scientific Inc. Waltham, MA, USA). Exosome-depleted FBS was purchased from SBI (System Biosciences, California, CA, USA). The mesenchymal stem cell surface marker detection kit (RAXMX-09011) was purchased from OriCell Biotechnology Co., Ltd. (Guangzhou, China). DiR iodide [1,1-dioctadecyl-3,3,3,3-tetramethylindotricarbocyanine iodide] cell membrane labeling solution was purchased from AAT Bioquest, Inc. (Sunnyvale, CA, USA). The primary antibodies of CD9 (ab223052), CD63 (ab217345), and CD81 (ab109201) were purchased from Abcam (Cambridge, UK). The secondary antibodies of horseradish peroxidase (HRP)-linked anti-rabbit IgG [7074] and horseradish peroxidase (HRP)-linked anti-mouse IgG [7076] were purchased from CST (Cell Signaling Technology, Inc., Danvers, MA, USA).
## 2.2. Animals’ Housing and Treatment
The Animal Care and Use Institutional Committee of Huazhong University of Science and Technology has approved all animal experiments procedures (IACUC Number: S2851). Eight-week-old SPF C57BL/6J male mice weighing 16–22 g were obtained from Beijing Charles River Experimental Animal Technology Co., Ltd., Beijing, China, and were bought and raised in the SPF Animal Laboratory of Huazhong University of Science and Technology. The temperature of the controlled environment was 22 ± 2 °C, the humidity was $60\%$, the circadian rhythm was 12 h (day and night from 8:00 a.m. to 8:00 p.m.), and food and drink were free.
After 1 week of adaptive feeding, the mice were randomly divided into 4 groups: the control group ($$n = 12$$), the DON group ($$n = 12$$), the DON + L-exo group ($$n = 12$$), and the DON + H-exo group ($$n = 12$$). The mice in the DON + L-exo group and the DON + H-exo group received 4 mg/kg/bw/day and 16 mg/kg/bw/day of BMSC-exo via an oral gavage, respectively [32]. Then, 2 mg/kg bw/day DON doses were also administered to mice in the DON group, the DON + L-exo group, and the DON + H-exo group via an oral gavage for 30 days [3,34] (Figure 1). The control group mice received the same standard ultrapure water with the gavage, and the mice were sacrificed and dissected immediately after the experiments were conducted. The liver samples were fixed in $4\%$ phosphate-buffered paraformaldehyde for 48 h for hematoxylin–eosin (H&E) staining. The remaining liver samples were rapidly frozen in liquid nitrogen and stored at −80 °C for subsequent experiments.
## 2.3.1. Bone Marrow Stem Cell Culture and Identification
The cell culture conditions and animal surgery strategies were based on previous studies with minor modifications [35,36]. The 3-week-old SPF SD male rats, weighing 60–90 g, were obtained from Beijing Charles River Experimental Animal Technology Co., Ltd. Bone marrow stem cells (BMSCs) were extracted from the femoral bone marrow of the rat. After the cells were washed with the DMEM/F12 medium (supplemented with $10\%$ FBS and $1\%$ (v/v) penicillin–streptomycin), the suspension of bone marrow was transferred into a 75 cm2 cell culture flask and incubated at 37 °C in a humidified atmosphere of $5\%$ CO2. The medium was renewed every two days until the cells reached $90\%$ confluency. The BMSC identification experiment was performed according to the instructions of the mesenchymal stem cell surface marker detection kit (RAXMX-09011). Briefly, BMSCs were harvested and suspended in 1 × PBS buffer containing $0.1\%$ BSA. The cell suspension was mixed with trypan blue at a volume of 1:1 and counted by an automatic cell counter (Shanghai Ruiyu IC1000). The cell concentration was then adjusted to 3 × 106 cells/mL. BMSCs were incubated with anti-rat CD29 (1:50; Cyagen Biosciences, California, CA, USA), anti-rat CD44 (1:50; Cyagen Biosciences, Santa Clara, CA, USA), anti-rat CD90 (1:50; Cyagen Biosciences, Santa Clara, CA, USA), and anti-rat CD45 (1:50; Cyagen Biosciences) for 30 min at 4 °C. After the cells were washed twice by the buffer, the fluorescent secondary antibody FITC (1:50; Cyagen Biosciences) was added and incubated at 4 °C for 30 min. After the cells were washed twice with buffer, the percentage of positively stained cells was analyzed by a NovoCyte flow cytometer (ACEA Biosciences, Santiago, California, CA, USA) and NovoExpress™ software (NovoCyte, Santiago, CA, USA).
## 2.3.2. Exosome Isolation, Purification, and Identification
In this study, BMSC-exos were produced from 3–5 passage BMSCs. After reaching $90\%$ confluency, BMSCs were washed with PBS. After 48 h incubation with the DMEM/F12 medium containing $5\%$ extracellular-vesicle-depleted FBS, the supernatant was collected and centrifuged at 2000× g for 20 min to remove the cell debris. According to the manufacturer’s instructions, BMSC-exos were isolated and purified from cell supernatants using the exoEasy Maxi kit (Qiagen, Valencia, CA, USA). Briefly, cell supernatants were filtered using 0.45 μm filters (EMD Millipore, Burlington, MA, USA). An ultrafiltration membrane (MWCO) (Millipore, USA) with a molecular weight cutoff of 100 KDa was concentrated at 1000 × g for 15 min. The supernatant was mixed with Buffer XBP and bound to exoEasy membrane affinity spin columns. Bound BMSC-exos were washed with buffer XWP, eluted with 400 μL of buffer XE (aqueous buffer mainly containing inorganic salts), and the BMSC-exos suspension was filtered through a 0.22 μm filter (Millipore). The protein content was determined with the BCA protein assay kit and stored at −80 °C for further studies, and the final concentration was adjusted to 16 mg/mL. All procedures for stem cell culture and exosome extraction are illustrated in Figure 1.
The morphology of BMSC-exos was observed using a transmission electron microscopy (FEI Tecnai 12, Philips, Holland). Then, 10 μL of uranyl acetate was added dropwise with a pipette onto the copper mesh for 1 min and the suspension was removed with filter paper. After drying for several minutes at room temperature, electron microscopy was performed at 100 kV to obtain the TEM imaging results.
Meanwhile, after diluting the exosome suspension 100-fold, the scattered light signal of BMSC-exos particles was collected through nanoparticle tracking analysis (NTA; NanoSight NS300, Malvern, UK). Three 60 s images were then repeatedly shot, sampling 30 frames per second. The NTA 3.3 Dev Build 3.3.104 software tracks and each particle’s Brownian motion were used to calculate the nanoparticle’s hydrodynamic radius and concentration.
## 2.4. Western Blotting
The protein markers (CD9, CD63, and CD81) of BMSC-exos were detected by Western blot. Protein samples of 20 μg were loaded and separated through $12\%$ SDS-PAGE gel. Proteins were then transferred to 0.45 μm nitrocellulose (NC) membrane (Millipore, HATF00010, USA), followed by blocking for 1 h using $5\%$ nonfat milk in TBST. The membrane was incubated into the primary antibody with a 1:1000 dilution overnight at 4 °C. For detection purposes, the membranes were incubated with the secondary antibody of peroxidase-conjugated horseradish for 1 h. The NC membrane was sprayed with ECL staining solution into a gel imaging analyzer (Syngene, Cambridge, UK), the images were collected by GeneSnap (Syngene, Cambridge, UK), and images were analyzed by GeneTools (Syngene, GeneTools 4.0, Cambridge, UK).
## 2.5. Liver Function Detection
The serum ALT and AST levels in four groups of mice ($$n = 9$$–12) were quantified in triplicate using commercial kits (Elabscience, Wuhan, China). Test results are expressed as IU/L. A Syngene multimode reader (BioTek Instruments, Winooski, VT, USA) was used to measure the optical density (OD) values.
## 2.6. Systemic Inflammatory Cytokine Detection
According to the manufacturer’s instructions, four groups of mice serum IL-6 and TNF-α levels ($$n = 9$$–12) were duplicated using commercially available ELISA kits. The test results were expressed in pg/mL. A Syngene multimode reader measured the optical density (OD) values (BioTek Instruments, USA).
## 2.7. Determination of Lipid Peroxidation Levels and Antioxidant Enzyme Activities in the Liver
Then, $10\%$ mouse liver homogenate was prepared with a high-throughput tissue grinder (Xinzhi Biotechnology Co., Ltd. Ningbo, China). The homogenate of liver tissue was centrifuged for 10 min at 2500 rpm/min to remove the precipitate. The D liver MDA levels and antioxidant enzyme activities (including total SOD, Cu/ZnSOD, MnSOD, CAT, and GPX) across four groups were measured in triplicate according to the manufacturer’s protocol (Beyotime, Hangzhou, China). The liver 4-HNE content of four groups of mice was determined in duplicate using a commercially available ELISA kit (Elabscience, Wuhan, China). Through a multi-plate reader (Bio-Tek, USA), optical density (OD) values were measured. Indicator levels were finally normalized to every milligram of protein.
## 2.8. Exosome Labeling and Tracking Distribution in Mice
Then, a 5 µM final concentration of DiR was co-incubated with BMSC-exos at 37 °C for 30 min in the dark. Then, DiR-labeled BMSC-exos were washed with PBS and passed through the exosome extraction procedure again to remove the excess dye. Mice were scanned at 745 nm (λex) using an exposure time of 300 ms per image frame after the gavage of DiR-labeled BMSC-exos. The DiR-labeled BMSC-exos were tracked in mice using the SPECTRAL Lago X in a vivo imaging system [37].
## 2.9.1. Lipid Profiling
Untargeted lipidomics analysis was performed based on previous research [38]. The lipid profiling of BMSC-exos samples was performed using the LC-MS/MS method with a Vanquish UHPLC system (Thermo Fisher, Germany) and an Orbitrap Q ExactiveTM HF mass spectrometer (Thermo Fisher, Germany) was obtained. The methanol (0.75 mL) was added to the exosome sample (100 µL). MTBE (2.5 mL) was then added and the mixture was incubated on a shaker for 1 h at room temperature. The addition of water (0.625 mL, MS-grade) induced the phase separation. After incubation at room temperature for 10 min, the sample was centrifuged at 1000× g for 10 min. The upper (organic) phase was harvested, and the lower phase was back-extracted with 1 mL of solvent mixture (MTBE/methanol/water, 10:3:2.5, v/v/v) and the upper phase was managed. After drying, the composite organic phase was dissolved in isopropyl alcohol (100 μL) and stored as well as analyzed by LC-MS/MS [39]. Compound Discoverer 3.01 (CD3.1, Thermo Fisher) was used to process the original data files generated by UHPLC-MS/MS. The peak comparisons and peak selections of each metabolite were performed, and they were then quantified. The main parameter settings were as follows: a retention tolerance of 0.2 min, an actual quality tolerance of 5 ppm, a signal strength tolerance of $30\%$, a signal-to-noise ratio of 3, and a minimum strength of 100,000. After that, the peak intensity was normalized to the total spectral intensity. Using normalized data, molecular formulas were predicted based on additive ions, molecular ion peaks, and fragment ions. Then, the LipidMaps [40] and LipidBlast [41] were used for peak matching to obtain accurate qualitative and relative quantitative results.
The chromatographic conditions were as follows: Thermo Accucore C30 (150 × 2.1 mm, 2.6 μm) column, an injection gradient of 20 min, and a flow rate of 0.35 mL/min. The column temperature was set at 40 °C. Mobile phase buffer A consisted of acetonitrile–water ($\frac{6}{4}$) + 10 mm of ammonium acetate + $0.1\%$ formic acid and mobile phase buffer B consisted of acetonitrile–isopropyl alcohol ($\frac{1}{9}$) + 10 mm of ammonium acetate + $0.1\%$ formic acid. The solvent gradients were initially set as $30\%$ B 2 min, $43\%$ B 5 min, $55\%$ B 5.1 min, $70\%$ B 11 min, $99\%$ B 16 min, and $30\%$ B 18.1 min.
Q ExactiveTM HF mass spectrometry operated in the positive (negative) polarity mode with the following conditions: jacket gas—20 psi, scavenging gas—1 L/min, auxiliary gas rate—5 L/min (7 L/min), spray voltage—3 kV, capillary temperature—350 °C, heater temperature—400 °C, S-Lens RF level—50, scanning range—140–1700 m/z, automatic gain control target—1 × 106, positive collision energy—25 eV and 30 eV (20 eV, 24 eV, and 28 eV), injection time—100 ms, isolation window—1 m/z, automatic gain control objective (MS2)—1 × 105, and dynamic exclusion—15 s.
## 2.9.2. Oxylipin Profiling
Oxylipidomics analysis was performed based on previous research [42]. The lipids from liver samples were analyzed by LC-MS/MS using the ExionLC™AD system (SCIEX) and the QTRAP®6500+ mass spectrometer (SCIEX). Then, 2 mg doses of liquid nitrogen ground tissue samples were taken, diluted to 1 mL with 50 mM phosphate buffer, and then equilibrated using a Strata-X reversed-phase SPE column, eluted with methanol (3 mL) and equilibrated with 3 mL of MS water. After loading, the samples were eluted with $10\%$ methanol (3 mL) to remove any impurities. Eluted metabolites were added with methanol (1 mL), dried with a nitrogen blower, and a resolvent (water–acetonitrile–acetic acid in a volume ratio of 60:40:0.02) was added to dissolve for 5 min and then placed in a centrifuge tube of 15,000× g. After centrifugation at 4 °C for 10 min, the supernatant was collected and injected into LC-MS for analysis [43]. An equal amount of each sample was taken from each experimental sample and mixed as the QC sample. SCIEX OS V1.4 software was used for the peak integration and calibration of original data. The peak area of each chromatographic peak represents the relative quantitative value of the relevant material. The integrated peak area averages were compared to each of the lipid conditions.
Chromatographic conditions: C18 column (10 cm × 2.1 mm) was injected with a linear gradient of 14 min at a flow rate of 0.3 mL/min. The eluents were eluent A ($0.1\%$ formic acid) and eluent B (acetonitrile). The solvent gradients were set as $35\%$ B 0.5 min, 35–$95\%$ B 9.5 min, $95\%$ B 10.5 min, 95–$35\%$ B 11 min, and $35\%$ B 14 min [44].
The QTRAP®6500+ mass spectrometer operated in a positive polarity mode with a screen gas of 40 psi, a collision gas as the medium, an ion spray voltage of −4500 V, a temperature of 500 °C, an ion source gas of 1:55, and an ion source gas of 2:55.
## 2.10. Statistical Analysis
The preprocessed oxylipidomics dataset was imported into MetaboAnalyst for orthogonal projections to latent structure–discriminate analysis (OPLS-DA), volcano plot analysis, and principal component analysis (PCA). The variable importance in projection (VIP) score was > 1 ($p \leq 0.05$) and the fold change (FC) was >2 (upregulated) or <0.5 (downregulated) to screen for metabolite species that significantly differed between groups. Pathway enrichment analysis and metabolite annotation were performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways database. Prism software (GraphPad 8.0) was used for data processing and statistical analysis. All experimental results are expressed as mean ± standard error (x ± SE). All data were derived from more than three separate experiments. One-way analysis of variance (ANOVA) was used to compare the multiple groups. Significance was defined as $p \leq 0.05.$ For detailed lipid detection methods, please refer to the “Materials and Methods S1”.
## 3.1. Characterization of BMSCs and BMSC-exos
The morphology and surface marker expression characteristics of BMSCs in this study conformed to the mesenchymal stem cell criteria defined by the International Society for Cell Therapy (ISCT), which could satisfy subsequent experiments [45]. After three passages, the BMSC cells were fibroblast-like, and most cells had clear borders and formed uniform colonies (Figure 2a). BMSC-specific biomarkers were identified by flow cytometry, and the data showed expressions of positive markers of CD29, CD44, and CD90, but a negative expression of CD45 could also be observed (Figure 2b).
Moreover, with the use of TEM, the BMSC-exos were observed to have a typical cup-like morphology (Figure 2c). NTA showed that the size of BMSC-exos was predominantly distributed between 30 and 200 nm in size (Figure 2d). The bands of exosome-specific markers CD63, CD9, and CD81 in BMSC-exos were also observed. In contrast, the above proteins were not detected in the cell culture media, indicating the successful isolation of high-purity BMSC-exos (Figure 2e).
## 3.2. Comprehensive Analysis of Lipid Profiles for BMSC-exos Using UHPLC-MS/MS
Untargeted lipidomic analysis for BMSC-exos using UHPLC-MS/MS enables the unbiased analysis of almost all classes of lipids in samples. The UHPLC system in ESI+ and ESI− modes was able to separate and elute various polar lipids in BMSC-exos within 20 min (Figure 3a). We identified lipid species with stringent criteria. Firstly, the parameters such as retention time and mass-to-charge ratio were screened. For different samples, peak alignment was performed according to the retention time and mass deviation to make the identification more accurate. Peak extraction and peak area quantification were performed according to the set ppm, signal-to-noise ratio, adduct ions, and other information. The qualitative and relative quantitative results of lipids were obtained by searching and comparing Lipidmaps and Lipiblast spectral databases. Finally, a total of 144 lipids were identified in BMSC-exos samples, including 13 free fatty acids (FFAs), 1 triacylglycerol (TAG), 61 phosphatidylcholines (PCs), 19 phosphatidylethanolamines (PEs), 2 phosphatidylinositols (PIs), 46 sphingomyelins (SMs), and 2 ceramides (Cers) (Figure 3c).
To ensure the reproducibility and stability of the BMSC-exos lipidomics method, we calculated the Pearson correlation coefficient among quality control (QC) samples. The higher the correlation of QC samples (R2 is closer to 1), the better the stability and data quality of the whole detection process (Figure 3b). The total ion chromatogram (TIC) plots of six BMSC-exos samples and multiple QCs were overlaid (Figure 3a). Meanwhile, unsupervised principal component analysis (PCA) was performed on all samples, including QCs, which showed that all QC samples were tightly clustered (Figure 3b). We also evaluated the relative standard deviation (RSD) distribution of 144 lipids in all QC samples (Figure 3d). Moreover, data demonstrated that approximately $79\%$ of the lipids [113] had an RSD of less than $15\%$. The above pieces of evidence showed that the UHPLC-MS/MS method was reproducible throughout the experimental period. Furthermore, we evaluated the RSD distribution of 144 lipids in BMSC-exos samples by extracting from different batches (Figure 3e), and approximately $79\%$ of lipids [114] had less than $20\%$ RSDs. At the same time, the abundances of different lipids were uniformly distributed in different BMSC-exos samples (Figure 3f). The above results showed that the BMSC-exos samples used in this experiment had good stability and consistency.
To assess the degree of lipid unsaturation in BMSC-exos, we also quantified the unsaturation index (UI). The degree of unsaturation was calculated as an index of the sum of each lipid’s relative contents, multiplied by their respective number of double bonds [46,47]. BMSC-exos contained a large amount of polyunsaturated fatty acids (PUFAs), of which phosphatidylcholine (PC) had the highest degree of unsaturation, with a UI of $65\%$ (Figure 3g).
## 3.3. BMSC-exos Alleviated DON-Induced Liver Damage
After the oral gavage of DiR-labeled BMSC-exos for 3 h, DiR signals could be detected in the upper abdomen of mice. Meantime, no background fluorescence was detected in PBS control mice, confirming that the signal in treated animals was from DiR-labeled BMSC-exos (Figure 4a). Otherwise, we sacrificed the animals, excised major organs for ex vivo imaging, and observed DiR signals in the liver to confirm that BMSC-exos reached the liver (Figure S1). Histological examination showed the prominent infiltration of inflammatory cells around the central vein of liver lobules in DON group mice, accompanied by deformation, the swelling of liver cells, and the irregular arrangement of hepatic cords. However, BMSC-exos administration alleviated the hepatocyte injury mentioned above (Figure 4b). Compared with the control group, the serum ALT, AST, IL-6, and TNF-α levels of mice in the DON group were significantly increased. The BMSC-exos treatment at 16 mg/kg bw/day could significantly inhibit the serum ALT, IL-6, and TNF-α levels. Meanwhile, the levels of MDA and 4-HNE in the liver of mice were significantly increased after DON exposure, but BMSC-exos could significantly decrease the levels of lipid peroxidation in the liver (Figure 4c–h). In addition, SOD and Cu/Zn SOD activities were increased after BMSC-exos administration (16 mg/kg bw/day). However, CAT and GPX activities were not significantly changed (Figure 4i–m).
## 3.4. Effects of BMSC-exos Administration on Oxylipin Profile or Pattern after DON Exposure
The results of oxidized lipid profiles demonstrated 62 oxylipins in the liver with HPLC-MS/MS analysis. This method can simultaneously explore many oxygenated PUFA species with high sensitivity and specificity. The HPLC system could separate and elute various oxylipins in the liver within 10 min (Figure 5a). We qualitatively analyzed the compounds in terms of Q1 (precursor ion), Q3 (product ion), RT (retention time), DP (declustering potential), and CE (collision energy). Compounds were quantified based on the peak area of Q3 (product ion). Mass detection analysis TIC plots of different samples and multiple QCs were overlaid (Figure 5a), the Pearson correlation coefficient R2 was close to 1 between QC samples (Figure 5b), and the QC samples in PCA analysis (shown as pink dots) was centrally aggregated (Figure 5c), which meant that the extraction and detection process of oxylipins in this study had excellent system reproducibility and stability. The orthogonal partial least squares discriminant analysis (OPLS-DA) model is a supervised discriminant analysis method used to investigate the differentially oxidized lipidome further. The abscissa directions of the DON group and the DON+H-exo group were utterly separated from each other in the OPLS-DA score graph, which meant that there were significantly different oxylipin profiles between the two groups. However, the OPLS-DA score maps of the other pairwise combinations were not completely separated in the abscissa direction (Figure 5d). This indicates that the administration of 16 mg/kg bw/day of BMSC-exos could significantly change the DON-induced hepatic oxylipin profile. A radar chart displayed the distribution pattern of oxylipins in the liver, and the data were expressed as log[2] FC over control (Figure 5e). Compared with the control group, most of the oxylipins in the DON group increased, and only a tiny part decreased. Compared with the DON group, most oxylipins were further elevated after BMSC-exos administration.
PUFAs are direct metabolic precursors for lipoxin biosynthesis, and they belong to two prominent families: omega-3 PUFAs (ALA, DHA, EDA, and EPA) and omega-6 PUFAs (AA, DGLA, and LA). Enzymatic and/or non-enzymatic reactions oxidize polyunsaturated fatty acids, and the three main enzymatic pathways involved in lipoxin production are cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 (CYP) isomer catalysis. Hierarchical clustering analysis of the heat map of relative abundance distribution of oxylipins showed that the distribution characteristics of oxylipin abundance in different groups were more related to the source of precursor lipids but less related to the formation pathway through enzymatic or non-enzymatic processes (Figure 5f). The enrichment analysis showed that the oxylipins detected in the liver were mainly enriched in the arachidonic acid metabolic pathway and the linoleic acid metabolic pathway (Figure 5e). KEGG pathway annotation was performed on the detected oxylipins using Pathview (Figure S2) to better observe changes in the detected oxylipins in the above two pathways. In order to more intuitively view the changing trend of each oxylipin in the four groups, we made a boxplot analysis of the relative content of all detected oxylipins in the four groups (Figure 6).
## 3.5. Screening for Different Key Oxylipins
Volcano plot analysis was used to screen for the metabolites that differed significantly between groups, with $p \leq 0.05$ and a fold change (FC) > 2 (up-regulation) or < 0.5 (down-regulation) selected as important features (Figure 7). The differential metabolites of “VIP > 1” between different groups (Table S1) were analyzed using a Venn diagram to obtain the intersection. The differential metabolites of “Control and DON” and “DON and DON + L-exo and DON and DON + H-exo” did not intersect, indicating that BMSC-exos could defend against free radicals through their PUFAs, rather than altering the contents of mouse liver to alter the DON pattern oxylipin profile (Figure 7). The 18-HETE, 9-HODE, 9,10-EpOME, and 12,13-diHOME in the intersection represent the DON-mode oxylipins that BMSC-exos could alter substantially in a dose-dependent manner (Figure 7).
## 3.6. Association of Key Oxylipins with Lipid Peroxidation, Antioxidants, and Liver Function/Phenotype
The correlation network between the seven oxylipins (screened in Section 3.5) and liver biochemical indexes was constructed by calculating the Pearson correlation coefficient (Figure 8a). Among them, Cu/Zn SOD had the strongest and positive correlation with the targeted oxylipins, indicating that Cu/Zn SOD played a synergistic role in the process of BMSC-exos changing the DON-mode oxylipin profile. The 4-HNE was negatively correlated with oxylipins, and was specifically altered by BMSC-exos, suggesting that BMSC-exos defense against free radicals may reduce 4-HNE production (Figure 8a). To comprehensively observe the correlation between liver oxylipin profiles and biochemical indicators, we screened the indicators with the top $10\%$ correlation coefficients to construct a heat map. Among them, red represents a positive correlation, blue represents a negative correlation, and asterisks represent a significant correlation. Hierarchical clustering found that these oxylipins were divided into two categories: one that was mainly positively correlated with Cu/Zn SOD and others that were mostly positively correlated with liver function indexes (ALT, AST), inflammatory factors (IL-6, TNF-α), and oxidative stress products (MDA, 4-HNE) (Figure 8b).
## 4. Discussion
Accumulating evidence suggests that oxidative damage is one of the primary mechanisms by which DON induces cytotoxicity or pathological tissue damage [9,48]. Meanwhile, many studies have also shown that the production of ROS in hepatocytes is related to the dose and duration of DON administration. For example, DON (0.1 μg/mL) can induce oxidative stress in rat liver clone-9 cells and its ROS level is further correlated with hepatotoxicity [12]. However, when HepG2 cells were incubated with DON (15–60 μM) for 1 h, intracellular ROS levels were not significantly increased at lower concentrations but increased significantly (1.4-fold) at 60 μM [9,49]. In addition, it has been reported that DON can dose-dependently induce ROS generation, with ROS generation peaking within 1 h [7,8,9]. This indicates that oxidative stress is an early event in the process of DON-induced toxicity.
Other studies have shown that MSC-exos can reverse liver oxidative damage [32]. However, the roles and underlying mechanisms of BMSC-exos in the progression of hepatic oxidative damage are not fully understood. Therefore, we considered oxidative stress as a key point to explore the protective effects of BMEC-exos on hepatotoxicity induced by DON exposure. Otherwise, exosomes can maintain their structure with high tolerance to gastric acid and then enter the liver after oral administration [32,50]. Therefore, this study adopted this non-invasive method for exosome administration purposes. This study basically validates our hypothesis that BMSC-exos can attenuate pathological liver changes by decreasing the levels of lipid peroxidation (MDA and 4-HNE) and inflammatory factors (IL-6 and TNF-α) to further maintain liver function indicators (ALT and AST).
PUFAs in organisms mainly exist in the lipids of biological membranes. The non-polar matrix region in the middle of phospholipid bilayers is ideal for free radicals to initiate and propagate amplification chain reactions [51,52,53]. Therefore, biofilms are the primary target of free radicals’ attack. Studies have shown that liposomes with smaller sizes are more vulnerable to free radicals’ attack because of the greater curvature of their bilayer leaflets and wider lipid–lipid spacing [33]. The lipid composition of the membrane also affects the lipid oxidation of liposomes [54]. Exosomes are nano-scale vesicles with a lipid bilayer membrane structure of 40–160 nm, and their membrane lipid composition is closely related to the type of cell from which they are derived [20]. Therefore, we comprehensively analyzed lipid species in BMSC-exos using UHPLC-MS/MS. A total of 144 lipids were identified, containing a large amount of PUFAs, of which PC had the highest degree of unsaturation, with a UI of $65\%$. This suggests that BMSC-exos have the potential to defend against free radicals preferentially. Since the oxidation of PUFAs by free radicals can generate a series of lipid metabolites, these generated mediators of oxygenated PUFAs play essential roles in the physiological and pathological regulation of many critical biological processes. However, because such mediators may have opposite and redundant properties, it is difficult to fully explain the molecular mechanism of biological processes by only studying a limited number of eicosanoids, and the overall balance between various oxygenated PUFAs regulates many biological processes [55,56]. Therefore, we performed a comprehensive analysis on the oxylipin profile in the liver using HPLC-MS/MS, which enables many oxygenated PUFA metabolites to be simultaneously measured in order to further explore their roles in health and disease conditions. We detected a total of 62 oxylipins in mouse liver. The increasing dose of BMSC-exos could significantly change the DON-induced hepatic oxylipin profile pattern. Compared with the DON group, most oxylipins were further elevated after BMSC-exos administration. Moreover, the distribution characteristics of oxylipin abundance in different groups were closely related to the source of precursor lipids, mainly derived from the metabolism of arachidonic acid and linoleic acid. We screened the oxylipins, with significant differences noted between groups. After taking the intersection of Venn diagram analysis, we found that BMSC-exos resisted free radicals through their PUFAs, rather than changing the contents of the liver to alter the oxylipin profile pattern of DON. These results confirmed our hypothesis: [1] based on the small particle size and higher membrane lipid unsaturation of exosomes, BMSC-exos are preferentially attacked by free radicals than hepatocytes; [2] the “main battlefield” or “first helpful battle line” of DON-induced lipid peroxidation may occur on exosome membranes, thereby further alleviating lipid peroxidation damage to liver cell membranes and other cellular components (Figure 9).
Lipid peroxidation is a continuous chain reaction that produces lipid hydroperoxide (LOOH). Peroxidation can only be stopped when there is a severely damaging effect, a reaction with antioxidant enzymes, or a reaction with antioxidants with a free radical chain blocking effect [57]. Generally, there are three main aspects of cell damage caused by lipid peroxidation: [1] lipid membrane changes lead to membrane dysfunction and membrane enzyme damage; [2] new free radicals generated during the chain reaction can further damage enzymes and other cellular components damage; [3] the effects of LOOH’s decomposition products on cells and their components (especially aldehyde products, such as MDA and 4-HNE) are toxic [58,59,60]. Since the lifespan of ROS is extremely short, as the lifespan of hydroxyl radicals is only 10−9 s, free radicals are mainly damaged through lipid peroxidation to cell membrane damage [60,61]. On the other hand, LOOH has a longer lifespan and can exist for several hours to several days before homolysis. *The* generated aldehyde products can cause damage to spread to other cellular components or even escape to other cells to cause damage [60,62]. It is not enough to replace tissue cells to resist the attack of free radicals and it is necessary to block the chain reaction of lipid peroxidation in time. Therefore, we measured the activity of antioxidant enzymes and found that the activity of Cu/Zn SOD in the liver of mice after BMSC-exos treatment was significantly higher than that of the control group. In addition, Cu/Zn SOD had a strong positive correlation with the screened BMSC-exos function-related targeted oxylipins. At the same time, we screened the top $10\%$ oxylipins with biochemical index correlations for hierarchical clustering and found that these oxylipins were divided into two categories: one was mainly positively correlated with Cu/Zn SOD and the other one was mainly positively correlated with liver injury indexes. This result indicates that Cu/Zn SOD played a synergistic role with BMSC-exos in resisting DON-induced lipid peroxidation and might play a role in terminating the chain reaction. Based on this study, we believe that the preferential reaction of BMSC-exos with free radicals through its lipid membrane is an essential mechanism for inhibiting DON’s toxic effects. The type and antioxidant content of exosomes further determine their effectiveness in resisting oxidative stress damage. Therefore, in future studies, BMSC-exos can also be engineered by encapsulating antioxidant content to further optimize the effect of ameliorating DON-induced oxidative damage.
## 5. Conclusions
In conclusion, this study demonstrated that BMSC-exos exerted a hepatoprotective effect in a dose-dependent manner. The exosomal lipidome and liver oxidized lipidome showed that BMSC-exos defended themselves against free radicals through their PUFAs and could significantly alter the DON-patterned oxylipin profile.
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---
title: 'COVID-19 in Older Patients: Assessment of Post-COVID-19 Sarcopenia'
authors:
- Almudena López-Sampalo
- Lidia Cobos-Palacios
- Alberto Vilches-Pérez
- Jaime Sanz-Cánovas
- Antonio Vargas-Candela
- Juan José Mancebo-Sevilla
- Halbert Hernández-Negrín
- Ricardo Gómez-Huelgas
- María Rosa Bernal-López
journal: Biomedicines
year: 2023
pmcid: PMC10045496
doi: 10.3390/biomedicines11030733
license: CC BY 4.0
---
# COVID-19 in Older Patients: Assessment of Post-COVID-19 Sarcopenia
## Abstract
[1] Background: Acute COVID-19 infections produce alterations in the skeletal muscle, leading to acute sarcopenia, but the medium- and long-term consequences are still unknown. The aim of this study was to evaluate: [1] body composition; [2] muscle strength and the prevalence of sarcopenia; and [3] the relationship between muscle strength with symptomatic and functional evolution in older patients affected by/recovered from COVID-19; [2] Methods: A prospective, longitudinal study of patients aged ≥65 years who had suffered from COVID-19 infection between 1 March and 31 May 2020, as confirmed by PCR or subsequent seroconversion. Persistent symptoms, as well as anthropometric, clinical, and analytical characteristics, were analyzed at 3 and 12 months after infection. The degree of sarcopenia was determined by dynamometry and with SARC-F; [3] Results: 106 participants, aged 76.8 ± 7 years, were included. At 3 months postinfection, a high percentage of sarcopenic patients was found, especially among women and in those with hospitalization. At 12 months postinfection, this percentage had decreased, coinciding with a functional and symptomatic recovery, and the normalization of inflammatory parameters, especially interleukin-6 (4.7 ± 11.6 pg/mL vs. 1.5 ± 2.4 pg/mL, $p \leq 0.05$). The improvement in muscle strength was accompanied by significant weight gain (71.9 ± 12.1 kg vs. 74.7 ± 12.7 kg, $p \leq 0.001$), but not by an increase in lean mass (49.6 ± 10 vs. 49.9 ± 10, p 0.29); [4] Conclusions: Older COVID-19 survivors presented a functional, clinical, and muscular recovery 12 months postinfection. Even so, it is necessary to carry out comprehensive follow-ups and assessments that include aspects of nutrition and physical activity.
## 1. Introduction
The outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly around the world, and it has had a huge impact on healthcare systems. The disease is associated with a wide spectrum of presentations, from mild, asymptomatic disease, to severe acute respiratory failure, resulting in damage to organs, such as myocardial dysfunction, hepatic injury, and renal injury.
Sarcopenia is a condition characterized by a progressive loss of muscle mass and strength. It arises as a consequence of aging; thus, it was originally confined to the elderly population. However, emerging evidence suggests that sarcopenia can develop at any age. Other than aging, possible causes, including nutrition, inflammation, or levels of vitamin D, have been recognized as potential mechanisms for the development of this disease.
Older people comprise the category most affected by COVID-19 infection, with almost 3 million cases in people aged ≥60 having been confirmed in Spain [1]. Infection produces a broad clinical spectrum of symptoms that are associated with lower nutrient intake, increased energy expenditure, or decreased nutrient absorption. As a consequence, nutritional requirements are often not met, resulting in weight and muscle loss. During the acute infection, patients are at risk of losing between 5 and $10\%$ of their body weight [2,3]. In addition, systemic inflammation and reduced physical activity also contribute to this muscle wasting.
Sarcopenia is associated with limitations in physical function and quality of life [4,5], an increased risk of falls [6], vulnerability [7], and mortality [8]. Sarcopenia can occur acutely, over the course of days [9], or insidiously, over the course of months or years [8]. The European Working Group on Sarcopenia in Older People (EWGSOP) defines acute sarcopenia as incidental sarcopenia occurring within 6 months after stressful events, and it occurs most often in hospitalized patients [4]. The prevalence of sarcopenia is up to $15\%$ in healthy older adults, and it can reach a rate of $69\%$ in hospitalized patients. The prevalence of sarcopenia in individuals aged 60–70 years olds is reported as $15\%$, while the prevalence ranges from 11 to $50\%$ in people >80 years old. [ 10]. Sarcopenia is likely when low muscle strength is detected, and diagnosis is confirmed by the presence of low muscle quantity or quality. A wide variety of tests and tools are available for the characterization of sarcopenia: the SARC-F questionnaire, grip strength, impedance, muscle ultrasound, gait speed, etc. Refs. [ 11,12] The selection of tools may depend on the patient, access to technical resources in the healthcare testing setting, or the purpose of the test.
The relationship between sarcopenia and COVID-19 has received substantial interest in the current literature. Sarcopenia can greatly affect the hospital prognosis of patients, as well as vulnerability to functional and physical deterioration after infection [13]. Published studies show that COVID-19 survivors are at an increased risk of sarcopenia during the weeks following infection [14,15], but few studies have evaluated long-term muscle strength. A study of patients who had recovered from COVID-19 showed a decrease in muscle strength and functionality, obtaining strength values below normal at the biceps brachii and the quadriceps femoris levels [16].
In this study with older patients affected by/recovered from COVID-19, the objectives were to evaluate: [1] body composition; [2] muscle strength and the prevalence of probable sarcopenia; and [3] the relationship between muscle force, disease severity, and symptomatic and functional evolution.
## 2.1. Study Design and Recruited Population
We conducted a prospective, longitudinal study of patients aged ≥65 years who were infected by SARS-CoV-2 between 1 March and 31 May 2020, as confirmed by RT-PCR or subsequent seroconversion using an antibody serological test. The participants were admitted to the Regional University Hospital of Malaga. The study did not include patients who died after admission or during follow-up, or those who had difficulty participating. Once potential participants were selected, the researchers contacted them to inform them about the study and invited them to participate. This study was approved by the Provincial Research Ethics Committee of Malaga (Spain), with the approval code “COVID-19/ANC”, dated 4 June 2021.
## 2.2. Written Informed Consent
Patients were invited to join the COVID-19 follow-up consultation group at the Internal Medicine Service of the Regional University Hospital Malaga, where they were informed about the study, and where they were required to sign the written informed consent. In the case that they were unable to sign the form, a legal guardian was asked to do so.
## 2.3. Clinical Data Collection
All participants gave their consent to collect their personal clinical data. Information regarding age, sex, comorbidities (hypertension, diabetes mellitus, obesity with a body mass index (BMI) ≥ 30, coronary heart disease, nonemboligenic ischemic stroke, peripheral arterial disease, liver disease, kidney disease, neoplastic disease, chronic obstructive pulmonary disease (COPD) or asthma), the need for hospital admission during acute illness, the length of hospital stay, and the need for admission to the ICU was collected. The Barthel *Index is* a widely validated item used to establish an individual’s functional condition [17]. This index refers to the ability to perform the basic activities of daily living. The Barthel *Index is* scored from 0 to 100, and it establishes the following categories: score <20: total dependence; 21–60: severe dependence; 61–90: moderate dependence; 91–99: mild dependence, and 100: independent. The comorbidity burden of patients was established with the age-adjusted Charlson comorbidity index [18], which is a system widely used for assessing life expectancy at 10 years, depending on the age at which it is assessed, and the subject’s comorbidities. *In* general, scores of 0–1 points indicate no comorbidity; scores of 2 points indicate low comorbidity; and scores of >3 indicate high comorbidity. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE) [19]. The MMSE is the most-used test for assessing a wide range of domains, including attention, language, memory, orientation, and visuospatial competence. The maximum score that can be obtained is 30 points, with the following interpretation: no cognitive impairment (27–30 points); possible or borderline cognitive impairment (25–26 points); mild-to-moderate cognitive impairment (10–24 points); moderate-to-severe cognitive impairment (6–9 points); and severe cognitive impairment (<6 points). Finally, the FRAIL scale was used to detect frailty [20]; it evaluates five items: fatigue, resistance, aerobic capacity, illnesses, and weight loss. A score ≥3 indicates frailty.
## 2.4. Visits
Medical and nursing visits were made at 3 and 12 months after acute infection.
The clinicians carried out a general assessment of patients with an adequate history and physical examination, and they questioned patients about possible symptoms after acute infection.
Patients underwent a first visit and a follow-up visit with a nurse, during which weight, height, BMI, waist circumference (WC), hip circumference, heart rate, and blood pressure measurements were obtained. Weight, lean mass quantification, and fat mass were assessed using bioelectrical impedance (BIA) via an electronic scale (Tanita Body Composition Analyzer (TBF-300 MA) Tanita Corporation, 1–14–2 Maeno-cho, Itabashi-ku, Tokyo, Japan). The Tanita system is an easy and effective tool for measuring body composition. It has a high level of test-pretest validity although it presents a somewhat higher margin of error as compared to the gold-standard body composition tests (hydrodensitometry and dual-energy X-ray absorptiometry (DEXA) tests). The measurement of height was performed with participants shoeless and a wall stadiometer (Stadiometer Barys Electra Model 511-300-A0A, ASIMED, Tokyo, Japan). BMI was measured by the division of weight (kg) by height squared (m2). The measurement of WC was carried out halfway between the last rib and the iliac crest, by means of an anthropometric tape. Blood pressure was obtained via an automated electronic sphygmomanometer (OMRON M7 (HEM-780-E), OMRON Healthcare Co., Ltd., Kyoto, Japan).
Blood samples were drawn after a 12-h fast, and biochemical measurements (hemoglobin, lymphocytes, D-dimer, gamma-glutamyl transferase (GGT), oxaloacetic glutamic transaminase (GOT), lactate dehydrogenase (LDH), C-reactive protein (CRP), ferritin, and interleukin-6) were determined using routine methods at the Clinical Analysis Laboratory of the Regional University Hospital of Málaga.
## 2.5. Sarcopenia Assessment
The diagnostic criteria for sarcopenia were based on those of the 2018 European Working Group on Sarcopenia in Older People (EWGSOP-2). The strength of the hand was assessed by dynamometry (Jamar Plus) using the Southampton protocol [21]. This protocol consists in measuring grip strength with the subject seated in a chair with the forearms resting on the arms of the chair. The wrist is placed in a neutral position with the thumb on the top of the chair and three measurements are taken on each side, alternating sides, and starting with the right hand. The best result from each side is selected. Probable sarcopenia was defined as values of <16 kg in women and <27 kg in men [4].
In addition, all participants completed the SARC-F questionnaire, which is a self-screening questionnaire for sarcopenia risk, and it allows for the identification of potential cases [22]. It evaluates five components: strength, help walking, getting up from a chair, climbing stairs, and falls. Scores range from 0 to 10 points. A value ≥ 4 points is an indication of sarcopenia.
Sarcopenia grades were evaluated in the total population, by sex, and with the consideration as to whether a patient needed to be hospitalized, or not, during the acute phase of infection.
## 2.6. Dietary Assessment
All participants completed a validated food frequency questionnaire of 14 items [23] to assess their adherence to the Mediterranean diet. The questionnaire categorizes responses as high (12–14 points); moderate (8–11 points); low (5–7 points); or very low adherence (<5 points).
## 2.7. Statistical Analysis
Data analysis was performed with the IBM SPSS v22.0 program. Quantitative variables with a normal distribution were expressed as means ± standard deviation (SD), and qualitative variables were expressed as percentages. Student’s t-test was used to compare quantitative variables, and the chi-squared test was used to compare qualitative variables. Pearson’s correlation coefficient was used to determine the correlations between quantitative variables.
## 3. Results
A total of 150 individuals were identified as possible participants. Out of those, 39 refused to participate, and 111 attended the first visit. Five patients were excluded from the study. Finally, 106 participants of both sexes ($51.9\%$ men and $48.1\%$ women) were included. From them, 80 participants required hospital admission during the acute phase, and 26 patients did not (see Figure 1).
The clinical and epidemiological variables of the study population at diagnosis of SARS-CoV-2 infection are shown in Table 1. The mean age of all participants was 76.8 ± 7 years. The age of females was slightly higher than that of males (76.5 ± 6.5 years for males and 77.3 ± 7.2 years for females). At the functional level, prior to infection, most participants were independent or had a mild level of dependence for the performance of the basic activities of daily living, with males having a higher degree of independence than females. In this sense, a worsening was observed after 3 months in the total population, as compared to baseline conditions (87.9 ± 21.3 points vs. 93.7 ± 15.7 points), and in both sexes (88.1 ± 19.2 vs. 95.5 ± 12.6 points in men and 87.8 ± 23.2 vs. 91.7 ± 18.4 points in women). However, 12 months after infection, an improvement was observed, achieving almost baseline conditions (total population: 93.6 ± 15.2 points; men: 94.6 ± 15.2; and women: 92.1 ± 16). No significant differences were found between the sexes in the MMSE scores or the FRAIL Index scores.
Our population displayed a high comorbidity grade (4.6 ± 1.8 points), with it being higher in males than in females (4.9 ± 1.9 vs. 4.2 ± 1.6, respectively). The main comorbidities were arterial hypertension, dyslipidemia, heart disease, and diabetes mellitus. Significant differences in the presence of cardiopathy, smoking, COPD, neoplasms, SAHS, and alcoholism, depending on sex, were found, with those being most prevalent among the men. However, females showed a higher rate in the incidence of psychological disorders such as depression and anxiety.
The symptomatic evolution of all participants, as assessed at the follow-ups, is shown in Table 2. Significant differences were found in the most frequent symptoms, including asthenia ($p \leq 0.001$), dyspnea ($$p \leq 0.003$$), and weight loss ($p \leq 0.001$), between the two follow-ups. At 3 months postinfection, $61.7\%$ of the patients reported two or more persisting symptoms, while at 12 months, this percentage had dropped to $8.1\%$ ($p \leq 0.001$). At 12 months, all analyzed symptoms presented as improving although the rate of recovery was lower in the female sex.
The anthropometric, body composition, and analytical parameters throughout the follow-up are shown in Table 3. After 12 months, there was a significant increase in weight, globally (+2.8 kg) and in both sexes (+2.9 kg in males and +1.4 kg in women). Body fat percentage and fat mass increased significantly globally (+$1.8\%$ and +1.2 kg, respectively) and in males (+$2.2\%$ and +$1.7\%$, respectively) although it did not reach a level of significance (+$0.2\%$ and +0.5 kg, respectively) in women. However, no significant differences in lean mass were found. After 12 months, significant decreases in neutrophil count (−1590 U/μL), D-dimer (−242.5 ng/mL), and interleukin-6 (−3.2 pg/mL) were observed, as well as an increment in the lymphocyte count (+410 U/μL).
Table 4 shows the values determined via dynamometry and the SARC-F, as well as the percentage of patients diagnosed with sarcopenia according to the results, stratified by sex. An improvement in dynamometry values was observed globally (+1.2 kg), and by sex (males +2.5 kg and women +0.5 kg) although the improvement was only significant in males. The SARC-F scores were also better at 12 months, but only significant differences were present in males. The percentage of patients diagnosed with probable sarcopenia was lower at 12 months, both globally and in both sexes, although these differences were significant only in men. Hospitalized patients had lower dynamometry values (−1.7 kg and −1.5 kg at 3 and 12 months, respectively) and higher SARC-F scores (+1.1 points and +1.0 point, at 3 and 12 months, respectively) than those of nonhospitalized patients. These differences were only significant at 3 months postinfection.
Correlations between muscle strength and epidemiological, anthropometric, clinical, and analytical factors were found globally. Positive correlations between muscle strength and lean mass (r: 0.68; $p \leq 0.001$), weight (r: 0.5; $p \leq 0.001$), independence (r: 0.35; $p \leq 0.001$), and cognitive level (r: 0.25; $p \leq 0.001$) were found. In contrast, negative correlations between muscle strength and SARC-F (r: −0.55; $p \leq 0.001$), frailty (r: −0.47; $p \leq 0.001$), age (r: −0.37; $p \leq 0.001$), comorbidities (r: −0.35; $p \leq 0.001$), an increase in symptoms post-infection (r: −0.22; $$p \leq 0.03$$), and lymphopenia (r: −0.22; $$p \leq 0.04$$) were found. No significant correlations with days of hospital admission or elevated IL-6 levels were found.
Finally, adherence to the Mediterranean diet was evaluated in all patients. No significant differences were found in any times of follow-up, with a moderate rate of adherence.
## 4. Discussion
With this study, we demonstrated that, in older patients (whether hospitalized, or not) functional, clinical, and muscular recovery was achieved 12 months after COVID-19 infection. This recovery at the muscular level translates to an increase in muscle strength and a lower degree of sarcopenia in both sexes although this improvement was only significant in males. These results were associated with greater values for weight, functional independence, and the absence of cognitive impairment. Muscle mass also increased slightly, but not significantly.
The identification of sarcopenia in our study was performed via the detection of muscle strength, as measured by dynamometry, using grip strength. Data recorded by dynamometry in our study reflect that, 3 months after infection, nearly $80\%$ of the patients presented with low muscle strength and probable sarcopenia. This percentage is higher than that described in previous studies [24]. We identified a higher percentage of sarcopenia, or patients at risk of sarcopenia, among women, unlike most studies, where no association between sarcopenia and sex was found [8,25] or a predominance in males was found [26]. The greater incidence in males appears to be related to the higher degree of smoking [27], alcoholism [28], and diabetes [29]. These three factors also predominated in the males in our sample; therefore, the higher incidence of sarcopenia found in females could be due to a greater persistence in symptoms and a slower recovery after infection.
In addition, all participants completed the SARC-F self-assessment questionnaire for identifying at-risk patients. The SARC-F questionnaire is a simple and inexpensive method that allows us to detect individuals at risk of adverse sarcopenia outcomes [4], and it has been used in multiple studies, including ones conducted with elderly patients during the COVID-19 pandemic [30,31]. It is recommended as a screening method, and it is capable of detecting severe cases of sarcopenia, but it has a low-to-moderate level of sensitivity for predicting low muscle strength. [ 4] Ageing produces changes in body composition [32], and sarcopenia increases with age [33], which could be another reason for the high rate of sarcopenia in our study, as previously demonstrated by other authors [34]. However, the degree of sarcopenia may be influenced by various risk factors, such as age, a prolonged hospital stay > 7 days, the need for invasive mechanical ventilation, and obesity [24]. Nonetheless, the specific risk factors for post-COVID sarcopenia are not yet well-known.
Hospitalization is associated with acute alterations in the sarcopenia status of patients [30], but, in addition, the presence of sarcopenia conditions is associated with complications during a hospital admission and with a higher rate of readmission [35]. In our study, at 3 months, subjects who had required hospitalization had a higher percentage of sarcopenia, which was not significant compared to nonhospitalized patients. However, both percentages are higher than those reported in the literature [24]. At 12 months, an improvement in both groups was found, but there were no significant differences between them.
A lack of exercise is another major risk factor for sarcopenia [36]. Immobilization results in significant changes in muscle cross-sectional area, volume, and mass, which promotes metabolic dysfunction and leads to impaired functionality [37]. Levels of physical inactivity were higher during the COVID-19 lockdowns, which forced the elderly population to stay at home, depriving them of regular physical activity, which accelerates the loss of strength and muscle function [38]. This immobilization probably explains the high degree of sarcopenia found in nonhospitalized patients. This increased social isolation has prevented the elderly from participating in their group activity programs, greatly affecting their physical condition [38], as has occurred due to previous pandemics.
There is increasing evidence that hyperinflammation is closely related to the development of sarcopenia. Elevated C-reactive protein (CRP), IL-6, and TNF-alpha have shown the strongest correlation with sarcopenia and frailty, resulting in extreme muscle wasting due to the promotion of catabolic signals mediated through these proinflammatory cytokines [39]. A direct relationship between increased IL-6 [40] and TNF- alpha concentrations [41] is associated with decreases in muscle mass and strength muscle. In our study, IL-6 levels after 12 months displayed a significant decrement although this decline was not correlated with increases in muscle strength.
As previously mentioned, our data reflect an improvement in muscle strength at 12 months after infection, but they do not correlate significantly with gains in lean mass. Sarcopenia was once synonymous with a loss of muscle mass, but nowadays, other parameters such as loss of muscle strength and physical performance are considered to be more important. The relationship between low muscle mass and disability is not well-defined, but there is a clear association with low muscle strength [42]. The decline in muscle strength is known to occur much more quickly than the concomitant loss of muscle mass [43], and in this sense, some authors prefer the term “dynapenia” to refer to this loss of muscle strength with age [44].
The measurement of body composition in our study was performed via bioelectrical impedance analysis (BIA) using the Tanita system. BIA is based on the principle that the conductivity of water in the body varies in the different compartments, thus allowing differentiation between fat mass and lean mass, and it is a simple and widely used method. Its main disadvantage compared to the gold-standard tests for body composition (computerized axial tomography (CT), magnetic resonance imaging (MRI), and dual-ray X-ray absorptiometry (DEXA), is its greater margin of error and its limitations in patients with hydrological decompensation.
In addition, a low-protein diet is considered to be another factor that accelerates the onset of sarcopenia in older adults [45]. A high prevalence of malnutrition has been found among older COVID-19 survivors [46]. Therefore, it is essential to routinely perform nutritional studies with these patients [46]. Patients with sarcopenia detected after infection may benefit from oral nutritional supplementation (ONS) providing at least 400 kilocalories (kcal) per day, with 30 g of protein or more. Such a strategy should be continued for at least 30 days [47] although we propose that, in older patients with post-COVID sarcopenia, this oral supplementation could be maintained for at least 3 months post-acute infection.
Not only protein deficiency is responsible for sarcopenia. An inadequate intake of other micronutrients can contribute to it. High adherence to the Mediterranean diet is associated with a lower incidence of chronic diseases and less physical deterioration in old age [48], which may reduce the risk of experiencing sarcopenia among the elderly [49]. In this sense, our population exhibited a moderate level of adherence to the Mediterranean diet. Another important component for improving muscle strength and reducing the risk of sarcopenia is physical activity. There are multiple, validated guidelines for improving physical activity that could help in the recovery of patients who have suffered COVID-19 infection. [ 50]. It is recommended that older people admitted to the hospital or in home-based quarantine for COVID-19 should undergo regular physical training [51]. The practice of low-intensity aerobic with resistance training produces an improvement in hand grip strength in older adults with post-COVID sarcopenia [52]. Home exercise programs have been shown to improve different components of health and fitness, such as muscular strength, muscular endurance, and balance, in older people [53]. Thus, in times of restricted physical activity due to pandemic situations, home-based resistance exercises are an alternative for preserving the physical fitness of older adults. A minimal form of exercise supervision is recommended, e.g., through weekly visits and/or telephone calls.
Sarcopenia and frailty are related, and sometimes they overlap, especially if we focus on the physical aspect of Fried’s definition of frailty, which includes a low walking speed, a low grip strength, and weight loss [54]. This relationship is present in our study; greater frailty means less muscle strength and more sarcopenia. In addition, our data relate such a relationship between sarcopenia, functional dependence, and comorbidities, as noted in previous studies [55,56] In the older population, sarcopenia has become an important focus of research and public policy debate. The loss of muscle strength contributes directly to exercise intolerance and the impairment of daily activities, making it a strong determinant of quality of life, mortality, and healthcare spending [57]. Despite its clinical importance, sarcopenia remains poorly understood and poorly managed in routine clinical practice. Our study emphasizes the importance of knowing how to recognize those older patients who are at risk, especially after overcoming a severe infectious process such as COVID-19, as well as the need to establish guidelines for follow-up and action through a specific and controlled assessment that allows for the identification and treatment of the effects of muscle damage caused by the infection.
## 5. Conclusions
COVID-19 infection has been associated with a wide spectrum of symptoms and an increased risk of sarcopenia during the weeks following infection, especially in elderly patients. Along with infection, the increase in physical inactivity during the pandemic has contributed to further physical deterioration and the loss of muscle strength. Our results show a progressive functional, clinical, and muscular recovery occurring 12 months after acute infection in older patients who survived the disease, with this recovery being greater in men. Even so, we found a high percentage of sarcopenia and a persistence of symptoms. Therefore, to ensure this recovery, it is necessary to perform structured and coordinated follow-ups, promoting healthy lifestyle habits, as well as to know the main sequelae caused by the infection.
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|
---
title: Income and rural–urban status moderate the association between income inequality
and life expectancy in US census tracts
authors:
- Steven A. Cohen
- Caitlin C. Nash
- Erin N. Byrne
- Mary L. Greaney
journal: Journal of Health, Population, and Nutrition
year: 2023
pmcid: PMC10045499
doi: 10.1186/s41043-023-00366-6
license: CC BY 4.0
---
# Income and rural–urban status moderate the association between income inequality and life expectancy in US census tracts
## Abstract
### Background
A preponderance of evidence suggests that higher income inequality is associated with poorer population health, yet recent research suggests that this association may vary based on other social determinants, such as socioeconomic status (SES) and other geographic factors, such as rural–urban status. The objective of this empirical study was to assess the potential for SES and rural–urban status to moderate the association between income inequality and life expectancy (LE) at the census-tract level.
### Methods
Census-tract LE values for 2010–2015 were abstracted from the US Small-area Life Expectancy Estimates Project and linked by census tract to Gini index, a summary measure of income inequality, median household income, and population density for all US census tracts with non-zero populations ($$n = 66$$,857). Partial correlation and multivariable linear regression modeling was used to examine the association between Gini index and LE using stratification by median household income and interaction terms to assess statistical significance.
### Results
In the four lowest quintiles of income in the four most rural quintiles of census tracts, the associations between LE and Gini index were significant and negative (p between < 0.001 and 0.021). In contrast, the associations between LE and Gini index were significant and positive for the census tracts in the highest income quintiles, regardless of rural–urban status.
### Conclusion
The magnitude and direction of the association between income inequality and population health depend upon area-level income and, to a lesser extent, on rural–urban status. The rationale behind these unexpected findings remains unclear. Further research is needed to understand the mechanisms driving these patterns.
## Introduction
Compared to more equitable societies, those with wider income gaps between rich and poor have worse population health outcomes [1, 2], including obesity [3], cancer [4], cardiovascular disease [5], and mortality [4, 6]. A 2018 longitudinal study found a strong association between state-level income inequality and life expectancy (LE) [7], a commonly used summary measure of population health representing the average number of years a person in an area can expect to live, based on current age-specific mortality rates [8]. The consensus in public health is the more equitable society is, the better the population health [2].
However, empirical evidence suggests that the association between income inequality and population health is more nuanced. For example, research has determined that the strength of these associations between LE and income inequality in the USA was significantly stronger in areas of higher overall income [4] and in rural areas compared to urban areas [6]. Results of a Canadian study further suggest that rural populations may be more vulnerable to the influence of income inequality on health due to certain population and geographic characteristics, such as reduced access to basic health care services and greater socioeconomic and demographic homogeneity compared to urban areas [9]. Nonetheless, the reasons for these observed nuances are not fully understood.
Although rural–urban status is often viewed and conceptualized for analysis as a dichotomy, it is more accurately understood as a continuum [10], with important implications for population health [10, 11]. Dichotomous measures of rural–urban status may be easier to interpret; however, important nuances between less urban and rural areas may be missed, especially in those areas of intermediate rural–urban status. There are a number of rural–urban status measures available on the national scale that attempt to capture a more detailed gradation of what it means for a geographic area (e.g., neighborhood, county, state, etc.) to be rural or urban [12].
Furthermore, the magnitude and direction of associations between income inequality and health depend on the geographic unit of analysis [13]. The association between higher income inequality and poor health outcomes is well established [1–4, 7, 9]. However, the majority of evidence demonstrating an association between income inequality and worse population health was conducted on large geographic scales, such as the national, state, or regional levels [14]. On a finer geographic scale, such as the neighborhood or municipal level, the processes related to inequality may operate differently [15]. It has been posited that income inequality at smaller scales may be less likely to reflect the degree of social stratification and endogenous inequality in the wider society, and as a result, be related to population health outcomes [14]. A 2015 study conducted in Switzerland found that mortality was actually lower in neighborhoods with high-income inequality than those with lower income inequality. This finding has been deemed the “Swiss paradox” [16].
Studies examining income inequalities and health on a fine geographic scale are lacking in the USA, however. Despite this, there is growing evidence that neighborhood and community-level factors play a unique and critical role in population health outcomes. According to an analysis by Woolf and colleagues, a “web of conditions” on the neighborhood or community level that may be difficult to disentangle contributes to individual behaviors and, therefore, population health and health inequalities [17]. These include, but are not limited to, race/ethnicity, education, socioeconomic status, the built environment, access to critical resources of everyday living (e.g., healthy foods, recreation, etc.), and social support and cohesion. Recent evidence supports the importance of examining population health inequalities on a fine geographic scale. A 2020 analysis found several key associations between population health outcomes and measures of healthcare access and social determinants of health that would have been masked had the analysis been conducted on a higher level of geospatial aggregation, such as the county or state level [18]. Another study identified small-scale associations between neighborhood-level socioeconomic status and premature mortality [19] and HIV status [20], associations which may have been masked had a higher level of spatial aggregation been used. Therefore, there is a support for and a need to investigate more nuanced relationships between socioeconomic status, inequality, community type, and health outcomes on a fine geographic scale.
To facilitate such investigations, improvements to the quality of methods and availability of national data on LE on a fine geographic scale, such as the census tract, allow researchers and policymakers to better understand the subtle but important differences of the impact of potential small-scale geographic and place-based characteristics on population health. However, to date, few studies have directly examined the potential for other socioeconomic and demographic factors to moderate or attenuate the established association between income inequality and LE. Therefore, the objective of this empirical study was to determine how income and rural–urban status potentially moderate the associations between LE and income inequality on a fine geographic scale (i.e., census tract).
## Measures
LE at birth (2010–2015) for each US census tract was the main outcome variable and was obtained from the CDC Wonder database [21]. Census tracts are small subdivisions of a county or statistically equivalent entity, such as a city [22] and can be considered as a geographic cluster of neighborhoods or small communities. Each census tract generally contains between 1200 and 8000 people, with an optimum size of 4000 [22].
LE was then linked by census tract to socioeconomic and demographic data from the 2010 US Census [23] and the 2010 American Community Survey (ACS) [24]. The main explanatory variable was Gini index, which measures the extent to which the income distribution among units within an area deviates from a perfectly equal distribution and ranges from 0 for perfectly equitable distributions to 1 where all income is concentrated in one individual [25].
Key moderator variables from the 2010 ACS included median household income and population density in each census tract. Population density is a continuous measure and one of the most commonly used proxy measures for rural–urban status in the population health literature. All three variables—Gini index, median household income, and population density—were converted into quintiles (Q1–Q5) to capture the continuous nature of each element and to aid in interpretation [16, 26–28]. Covariates used in the analysis were percent of the population that identified as Black or African American (% Black), percent identifying as Hispanic or Latino/a/x (% Latino/a/x), percent with a bachelor’s degree or higher, and median age of the population in each Census tract.
Descriptive statistics (means, standard deviations, medians, and interquartile ranges [IQR]) were obtained for all study variables. Checks of normality on all study variables were conducted using Kolmogorov–Smirnov statistics and visually using Q–Q plots. Bivariate associations were estimated for all pairs of study variables (e.g., LE and Gini index) using Spearman’s rank correlation tests for non-normally distributed measures. Partial correlations were used to estimate the adjusted bivariate associations between LE and Gini index, adjusting for covariates. These partial correlations were conducted for all census tracts combined and stratified by quintile of income and rural–urban status to assess differences and linear trends in the magnitude of the associations between LE and Gini index by these factors. Average LE was also calculated for groups of census tracts cross-classified by quintile of income, rural–urban status, and Gini index. Lastly, multivariable models were used within each quintile of income inequality to examine the adjusted associations between median household income, population density, and their interaction with census-tract LE. All data were aggregated, and no individual-level data were used for this analysis. SAS version 9.4 (Cary, NC) and IBM SPSS version 27 (Armonk, NY) were used for analyses.
## Results
There were 66,857 census tracts in the analytic sample. The mean tract-level LE was 78.3 years with a standard deviation (SD) of 4.0 years, a minimum LE of 56.3 (tract # 40001376900 in Adair County, Oklahoma) and a maximum of 97.5 (tract # 37037020104 in Chatham County, North Carolina) (Table 1). The mean tract-level values for median household income were $66,792 (SD $32,688) and 0.426 (0.064) for Gini index. The mean tract-level population density was 5231 people/square mile, with a standard deviation of 11,729.Table 1Descriptive statistics for US Census tracts ($$n = 66$$,857)MeasureMean (SD)Min–MaxSkewnessKurtosisLife expectancy (LE) at birth78.3 (4.0)56.3–97.5− 0.260.36Population density (per square mile)5231 [11,729]0.01–508,6977.27100.8Median household income ($)66,792 [32,688]2744–250,0001.412.86Gini index0.426 (0.064)0–10.541.32Percent Black or African American13.9 (21.8)0–1002.244.43Percent Hispanic/Latino/a/x16.0 (22.8)0–1002.073.71Median age (years)38.1 (7.5)12.1–94.00.461.71Percent with bachelor’s degree or higher30.7 (19.3)0–1000.880.09Population size4445 [2349]22–72,0412.6729.3 Spearman correlation coefficients between LE and Gini index, median household income, percent Black population, and percent with a bachelor’s degree or higher were − 0.132, 0.672, − 0.364, and 0.608, respectively (Table 2). All were statistically significant ($p \leq 0.001$). Furthermore, LE was significantly correlated with population density (Spearman’s ρ = 0.035, $p \leq 0.001$). Gini index was significantly correlated with median household income (Spearman’s ρ = -0.329, $p \leq 0.001$), % Black population (Spearman’s ρ = 0.108, $p \leq 0.001$), and population density (Spearman’s ρ = 0.054, $$p \leq 0.001$$).Table 2Spearman’s rank correlations (and p values) among major study variables by census tractPDMHHIGINIPBLPHLAGEBACHLE0.035 (< 0.001)0.672 (< 0.001)− 0.132 (< 0.001)− 0.364 (< 0.001)0.065 (< 0.001)0.236 (< 0.001)0.608 (< 0.001)PD0.002 (0.669)0.054 (< 0.001)0.330 (< 0.001)0.442 (< 0.001)− 0.384 (< 0.001)0.160 (< 0.001)MHHI− 0.329 (< 0.001)− 0.309 (< 0.001)− 0.030 (< 0.001)0.264 (< 0.001)0.728 (< 0.001)GINI0.108 (< 0.001)− 0.050 (< 0.001)0.057 (< 0.001)0.004 (0.296)PBL0.129 (< 0.001)− 0.350 (< 0.001)− 0.155 (< 0.001)PHL− 0.415 (< 0.001)− 0.091 (< 0.001)AGE0.215 (< 0.001)LE life expectancy at birth, PD population density, MHHI median household income ($), GINI Gini index, PBL Percent Black or African American, PHL Percent Hispanic or Latino/a/x, AGE Median age, BACH Percent of population aged 25 + with at least a bachelor’s degree Substantial differences in the associations between LE and Gini index by quintile of median household income were evident (Fig. 1). Among the tracts in the lowest income quintile (Q1), LE was negatively associated with Gini index and LE decreased monotonically from 74.9 years in the tracts with the lowest Gini index to 73.3 years in the tracts with the highest Gini index ($$p \leq 0.003$$). However, among the tracts in the highest income quintile (Q5), the association between LE and Gini index was reversed and positive: higher LE was observed in areas with higher Gini indices (LE 81.4 in Q1 of Gini and 82.2 in Q2 of Gini, $$p \leq 0.011$$).Fig. 1Mean census-tract life expectancy overall and cross-classified by quintile of median household income, Gini index, and rural–urban status Additional variability was observed when stratifying the tracts further by rural–urban status. The lowest average LE (72.3 years) was observed in the tracts with the lowest income, highest Gini index, and with intermediate (Q3) rural–urban status. The highest average LE (82.3 years) was observed in the tracts with the highest income (Q5), second-highest Gini index (Q4) and second most urban (Q4). The monotonic trends with increasing LE with decreasing Gini index in the tracts with the lowest income generally held for all levels of rural–urban status, but the reverse trends (increasing LE with increasing Gini index) in the highest income tracts varied by rural–urban status.
The complex associations between Gini index and LE are further illustrated in Fig. 2. This figure shows the partial correlation coefficients between LE and Gini index in each group of census tracts, cross-classified by rural–urban status quintile and median household income quintile, as well as average LE in each class of census tracts. For the four lowest quintiles of income (Q1–Q4) in the four most rural quintiles of census tracts, the associations between LE and Gini index were significant and negative (Spearman’s ρ between − 0.198 and − 0.041, p between < 0.001 and 0.021). In contrast, the associations between LE and Gini index were significant and positive for the census tracts in the highest income quintiles, regardless of rural–urban status. For the most urban census tracts, those in the lowest quintiles of income (Q1–Q4) there were no significant associations between LE and Gini index. Fig. 2Partial correlation coefficient between Gini index and life expectancy and mean life expectancy by quintile of median household income and rural–urban status Lastly, multivariable models were used to assess the associations between LE and rural–urban status and median household income, overall and by quintile of Gini index (Table 3). Overall, each one-quintile increase in population density was associated with an average decrease in life expectancy of 0.13 years ($95\%$ CI 0.11, 0.15). The association between population density and LE remained significant across all quintiles of Gini index, yet the magnitude of the association was significantly stronger in areas of low inequality than in high inequality (p value for trend 0.022). For median household income quintile, each one-quintile increase in income was associated with an average 1. 11-years increase in life expectancy and did not vary significantly by Gini index. The interaction terms for quintiles of rural–urban status and median household income were significant overall and for the areas with the lowest Gini index (Q1-Q3), but not significant in the census tracts with higher levels of the Gini index (Q4 and Q5).Table 3Adjusted* model estimates of main effects and interactions on census tract-level life expectancy in years (with $95\%$ confidence intervals) overall for all census tracts and by Gini quintile (Boldface = $p \leq 0.05$)Population density quintile**Median household income quintile***Population density X Median household incomeOverallMain effects− 0.13 (− 0.15, − 0.11)1.11 (1.08, 1.13)With interaction term− 0.17 (− 0.21, − 0.13)1.06 (1.02, 1.10)0.015 (0.004, 0.027)Q1 (lowest Gini)Main effects− 0.13 (− 0.17, − 0.09)1.00 (0.95, 1.05)With interaction term− 0.33 (− 0.44, − 0.23)0.80 (0.70, 0.90)0.061 (0.032, 0.090)Q2Main effects− 0.18 (− 0.22, − 0.14)1.08 (1.03, 1.13)With interaction term− 0.32 (− 0.41, − 0.23)0.95 (0.85, 1.04)0.045 (0.019, 0.072)Q3Main effects− 0.18 (− 0.22, − 0.14)1.10 (1.05, 1.16)With interaction term− 0.27 (− 0.35, − 0.18)1.02 (0.93, 1.11)0.029 (0.004, 0.055)Q4Main effects− 0.12 (− 0.16, − 0.07)1.12 (1.07, 1.18)With interaction term− 0.13 (− 0.21, − 0.05)1.11 (1.02, 1.20)0.005 (− 0.020, 0.030)Q5 (highest Gini)Main effects− 0.07 (− 0.12, − 0.03)1.00 (0.94, 1.06)With interaction term− 0.01 (− 0.09, 0.08)1.07 (0.97, 1.17)− 0.023 (− 0.049, 0.002)*Adjusted for tract-level percent Black or African American, percent Hispanic or Latino/a/x, median age, and percent with bachelor’s degree or higher**p value for trend (in main effects models) < 0.05***p value for trend (in main effects models) < 0.05
## Discussion
In this study, the association between LE and Gini index in most US census tracts was negative, supporting the vast literature concluding that lower income inequality is associated with better population health [1–7]. However, those associations were not present in more urban areas. Furthermore, in the census tracts with the highest income, the association was reversed: higher LE was associated with higher Gini indices. These findings are partially antithetical to the “income inequality thesis”, which states that increasing wealth is associated with improved population health, but only to a certain level of wealth [14]. Once this threshold of wealth is reached, reducing income inequality is the most important driver of improving population health [15]. Study findings support the tenet of the income inequality thesis proposing that increasing wealth is associated with better population health, as measured through LE. Increasing median household income was associated with increased tract-level LE. However, the findings contradict the part of the income inequality thesis that for sufficiently high levels of wealth, reducing income inequality is associated with increased LE. For the wealthiest census tracts, increasing LE was associated with increased income inequality, consistent with the Swiss study described earlier [16]. However, more research is needed to determine if these unexpected associations are observed for other population health outcomes [29, 30].
The findings for rural–urban status and LE were more complex. The association between income inequality and LE was strongest in areas outside the most rural (Q1) and most urban (Q5) census tracts. The reasons for this are not well understood. One explanation for this finding is that areas with greater poverty could be more vulnerable to the deleterious effects of income inequality on health, especially when those areas lie in the intermediate areas of rural–urban status. Broadly speaking, while not specific to urban areas, over the past century, urban areas are more likely to have adequate housing, access to primary health care, sanitation, and resources [31], which may temper the associations between LE and inequality, even in lower income areas. Likewise, there are potential health benefits to living in highly rural and remote areas, such as the lower cost of living, access to green space, pace of life, improved environmental factors (e.g., pollution) [32–34]. However, like the benefits of urban living, these attributes are not unique to the most rural and remote areas. Therefore, the reasons for these highly nuanced differences in the strength and direction of association between LE and income inequality jointly by wealth and rural–urban status remain unclear and merit further research.
The empirical findings of the current study should be interpreted in the context of several limitations. First, estimating LE on a small geographic scale such as census tract is subject to systematic errors [35]. Second, the partial correlations only adjusted for two factors, percent Black population and percent with a bachelor’s degree or higher, and therefore the observed associations are subject to residual confounding. This analysis only considered moderation of the association between income inequality and LE by two factors, income and rural–urban status. Factors, such as race/ethnicity, education, and built environment, likely moderate these associations. The analysis also did not consider potential regional differences in the association between income inequality and LE [36]. Only one measure of each main predictor variable was used, largely due to limited variables available at the census tract level. Patterns of association and moderation may vary based on which measure of health was used [37]. This study used Gini index as the main measure of income inequality [38]. As with all measures of income inequality, the Gini index is only somewhat sensitive to income inequality occurring in the middle of the income distribution [39]. Future studies could determine if the observed associations are sensitive to the type of income inequality measure used, such as the Atkinson Index, which is less sensitive to differences in the middle of the distribution. Also, the analysis considered only one measure of rural–urban status—population density. As there is no universally accepted and utilized measure of rural–urban status, it is possible that the observed associations would also change if a different measure of rural–urban status, such as distance to the nearest metropolitan area or percent urban population, were used [40]. Lastly, for analysis and interpretation, continuous measures—area-level income, income inequality, and population density—were categorized into quintiles. Choosing other cut-points (i.e., quartiles) may result in different patterns of associations.
Despite these limitations, this study provides empirical evidence that the widely established principle that areas with lower income inequality generally experience better population health may not extend to all areas and, in fact, may be reversed among high-income populations. The rationale for these findings is unclear and requires further research. While this analysis found that for most census tracts, the established associations held, the variation by income suggests that any efforts to improve population health through reducing income inequality must be tailored to the needs of distinct populations to maximize effectiveness. Future research should focus on identifying and addressing these nuanced associations that lead to critical health inequalities that may be masked when examining such associations on a higher geographic level of aggregation [41].
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|
---
title: 'Positive Correlation between Relative Concentration of Spermine to Spermidine
in Whole Blood and Skeletal Muscle Mass Index: A Possible Indicator of Sarcopenia
and Prognosis of Hemodialysis Patients'
authors:
- Hidenori Sanayama
- Kiyonori Ito
- Susumu Ookawara
- Takeshi Uemura
- Sojiro Imai
- Satoshi Kiryu
- Miho Iguchi
- Yoshio Sakiyama
- Hitoshi Sugawara
- Yoshiyuki Morishita
- Kaoru Tabei
- Kazuei Igarashi
- Kuniyasu Soda
journal: Biomedicines
year: 2023
pmcid: PMC10045508
doi: 10.3390/biomedicines11030746
license: CC BY 4.0
---
# Positive Correlation between Relative Concentration of Spermine to Spermidine in Whole Blood and Skeletal Muscle Mass Index: A Possible Indicator of Sarcopenia and Prognosis of Hemodialysis Patients
## Abstract
Several mechanisms strictly regulate polyamine concentration, and blood polyamines are excreted in urine. This indicates polyamine accumulation in renal dysfunction, and studies have shown increased blood polyamine concentrations in patients with renal failure. Hemodialysis (HD) may compensate for polyamine excretion; however, little is known about polyamine excretion. We measured whole-blood polyamine levels in patients on HD and examined the relationship between polyamine concentrations and indicators associated with health status. Study participants were 59 hemodialysis patients (median age: 70.0 years) at Minami-Uonuma City Hospital and 26 healthy volunteers (median age: 44.5 years). Whole-blood spermidine levels were higher and spermine/spermidine ratio (SPM/SPD) was lower in hemodialysis patients. Hemodialysis showed SPD efflux into the dialysate; however, blood polyamine levels were not altered by hemodialysis and appeared to be minimally excreted. The skeletal muscle mass index (SMI), which was positively correlated with hand grip strength and serum albumin level, was positively correlated with SPM/SPD. Given that sarcopenia and low serum albumin levels are reported risk factors for poor prognosis in HD patients, whole blood SPM/SPD in hemodialysis patients may be a new indicator of the prognosis and health status of HD patients.
## 1. Introduction
The polyamines spermine (SPM), spermidine (SPD), and their precursor putrescine (PUT) are aliphatic amines essential for all living cells (Supplemental Figure S1). A graph with the chemical formulae of polyamines is presented in Supplemental Figure S1. Polyamines are synthesized intracellularly from arginine and undergo catabolism by several enzymes. In addition, cells can take up polyamines from their surroundings, and intracellular polyamines are excreted from cells [1]. The involvement of several enzymes in polyamine synthesis and catabolism and the presence of transport systems across the cell membrane suggest that intracellular polyamine concentrations are tightly regulated, which in turn indicates that polyamines are important for cellular homeostasis.
Polyamines have diverse functional profiles and are involved in a variety of biological processes, including chromatin structure remodeling, gene transcription and translation, cell proliferation, and circadian clock regulation. Polyamines act on nucleic acids by interacting with the negatively charged phosphodiester backbone, resulting in conformational changes in DNA and stabilization of tRNA. Polyamines also act as chemical chaperones and may be associated with protein conformational changes and function [2].
Intracellular de novo synthesis is considered the major source of polyamines during the fetal and developmental stages. With growth, the enzymatic activity of polyamine synthase gradually decreases, and the capacity for intracellular polyamine synthesis is reduced. Based on these findings, it can be inferred that polyamine levels decrease with age. Indeed, the titles and abstracts of certain studies describe age-dependent decreases in polyamine concentrations. For example, when the relationship between age and polyamine concentrations is examined at all ages, including in children, blood polyamine levels decline with age [3]. However, this age-dependent decline occurs only in the very early stages of growth; that is, particularly during fetal life. Many studies have clearly shown that polyamine concentrations in adult tissues, blood, and urine do not decline with age [1]. In addition to intracellular de novo polyamine synthesis, cells can take up polyamines from the surrounding environment. The most important source of polyamines in adults is the gastrointestinal tract; that is, polyamines in ingested food are synthesized in the gastrointestinal tract through the action of intestinal bacteria. In recent years, changes in blood SPM concentrations have been observed with the continued consumption of a high-polyamine diet in healthy volunteers [4].
However, polyamines in the body are excreted in urine via the kidneys. Polyamine synthesis is enhanced by the autonomous activation of polyamine synthase enzymes in cancer cells, and polyamines synthesized by cancer cells are transferred to blood cells [1]. It is well known that increased polyamine excretion is observed in cancer patients [5]. This also means that polyamines in the body are not eliminated via the kidneys in patients with renal failure, and high blood polyamine levels have been observed in patients with renal failure [6]. Hemodialysis (HD) is used to treat uremia in patients with renal failure. However, little is known about polyamine efflux into the dialysate or the changes in blood concentrations caused by HD. One purpose of this study was to compare blood polyamine levels between patients with chronic renal failure (CKD) undergoing HD and healthy volunteers. The effects of HD on blood polyamine levels were examined before and after HD.
Several researchers have been reported to correlate with degree of aging and may be predictive of prognosis in HD patients as well as in otherwise healthy individuals [7,8]. Recent studies have shown that blood polyamine levels and the SPM-to-SPD ratio are associated with health status and various age-related chronic diseases [4,9]. We examined the relationship between polyamine concentration and indicators reported to be associated with healthy life expectancy. Additionally, this study examined whether blood polyamine levels are an indicator of both health status and degree of senescence in dialysis patients.
## 2.1. Study Design and Participants
The study was conducted in accordance with the Declaration of Helsinki (revised in Tokyo in 2004) and was approved by the Institutional Review Board of Minami-Uonuma City Hospital (ID: R1-13). Both adult patients undergoing hemodialysis for renal failure and healthy adult volunteer participants were fully informed about the study and provided informed consent before participating. All patients received intermittent hemodialysis (HD) or hemodiafiltration (HDF) three times per week for 3–5 h. Participants on HD or HDF with pacemaker implants were excluded from the study because their skeletal muscle mass could not be measured using bioelectrical impedance analysis (BIA). Healthy volunteers were adults over 20 years of age with no specific illnesses who were recruited through notices such as posters. Healthy volunteers underwent annual medical checks (laboratory tests: blood count, blood glucose, HbA1c, creatinine, and blood urea nitrogen levels) and had no history of regular hospital visits or oral medications. Because the presence of neoplasms has a significant impact on polyamine levels, patients with cancer and those with a history of cancer treatment within 3 months were excluded from the study.
## 2.2. Data and Sample Collection
Medical backgrounds and other relevant data of the HD and HDF patients were collected from their medical records, such as information on the causative diseases of renal failure and dialysis, including dry weight (DW). The health status of the healthy adult volunteers was determined through interviews and physical examinations.
Body mass index (BMI) was calculated as body weight in kilograms divided by height in meters squared. Multifrequency bioelectrical impedance analysis (MF-BIA) was performed using InBody S10 (InBody Japan, Tokyo, Japan) to measure body composition and muscle mass. Skeletal muscle mass index (SMI) was calculated by dividing the limb skeletal muscle mass in kilograms by height in meters squared. Hand grip strength (HGS) was measured using a hand grip strength meter (Smedley’s Hand Dynamo Meter, Matsumiya Ika Seiki, Tokyo, Japan) in a sitting position; the highest numerical value measured in the left and right hand grip strength tests was used.
Blood samples were obtained at ambient temperature from the patients before and after HD or HDF. For the measurement of polyamine concentrations in the dialysate from dialysis patients, the dialysate was collected from six dialysis patients before dialysis began, 30 min after dialysis began, and just before the end of dialysis. For both HD patients and volunteers, whole blood samples for the measurement of polyamine concentrations (as well as dialysate collected from dialysis patients for the polyamine assay) were stored at −20 °C until the assay.
## 2.3. Blood and Biochemical Tests
All blood sample measurements, except those for polyamines, were performed in the clinical laboratory of Minami-Uonuma City Hospital. Hemoglobin (Hb) concentration was measured using the sodium lauryl sulfate hemoglobin detection method with an automated blood cell counter (XN-2000; Sysmex Corporation, Kobe, Japan). Biochemical blood tests were performed using an automated biochemical analyzer (BM6070, JEOL Ltd., Akishima, Japan). Serum albumin (Alb) concentration was measured using the modified bromocresol purple (BCP) method. Blood urea nitrogen (BUN) and creatinine (Cre) levels were measured using enzymatic methods. C-reactive protein (CRP) levels were measured using the latex immunoturbidimetric method. Serum calcium (Ca) and phosphorus (P) levels were measured using Arsenazo III colorimetric and enzymatic calorimetric methods, respectively.
## 2.4. Determination of Polyamine Concentrations in Whole Blood
Since most polyamines in the body are associated with cells, and the majority of blood polyamines are also attached to blood cells [10], we measured polyamine concentrations in whole blood. Whole blood samples were obtained from the arteriovenous fistula before and after HD., and then heparinized, collected, and stored at −20 °C. For polyamine measurement, whole blood was thawed and degraded by sonication and freeze-thaw cycles. Polyamine concentrations were determined using high-performance liquid chromatography (HPLC) at the Cardiovascular Institute for Medical Research at Saitama Medical Center of Jichi Medical University [11]. To extract polyamines, whole blood was diluted five times with $5\%$ trichloroacetic acid (TCA). Subsequently, adjusted samples were incubated at 95 °C for 45 min. After centrifugation at 13,000× g for 20 min at 4 °C, the supernatant was collected and deproteinated by increasing the TCA concentration to $10\%$. Next, incubation was carried out at 95 °C for 45 min, followed by centrifugation at 13,000× g for 20 min at 4 °C. The polyamines in 20 µL of TCA supernatant were separated with an HPLC system (Shimadzu Corporation, Kyoto, Japan) with a TSKgel Polyaminepak column (column size 4.6 mm ID × 50 mm length, particle size 7 µm, TOSOH Bioscience, Tokyo, Japan) at 50 °C. The flow rate of the separation buffer (0.09 M citric acid (Nacalai Tesque, Inc., Kyoto, Japan), 2 M NaCl (Nacalai Tesque, Inc.), 0.64 mM n-capric acid (Nacalai Tesque, Inc.), $0.1\%$ Brij-35 (Sigma-Aldrich Japan, Tokyo, Japan), $20\%$ methanol (FUJIFILM Corporation, Osaka, Japan), adjusted to pH 5.10) was 0.42 mL/min. Polyamines were detected by fluorescence intensity after the reaction of the column effluent at 50 °C with a solution containing 0.4 M boric buffer (pH 10.4) (Nacalai Tesque, Inc.), $0.1\%$ Brij-35, 2.0 mL/L 2-mercaptoethanol (Nacalai Tesque, Inc.), and $0.06\%$ o-phthalaldehyde (Nacalai Tesque, Inc.). The flow rate of the o-phthalaldehyde solution was 0.42 mL/min, and fluorescence was measured at an excitation wavelength of 340 nm and an emission wavelength of 455 nm. The retention times for SPD and SPM were 12 min and 23 min, respectively. The concentrations in the original whole blood samples were expressed as micromolar concentrations (µM).
## 2.5. Determination of Polyamine Concentrations in Dialysate
Dialysates were collected from the waste stream before dialysis started, 30 min after dialysis started, and immediately before the end of dialysis. Immediately after collection, the dialysate was frozen at −20 °C and thawed before measurement. For the extraction of polyamines, dialysate containing $5\%$ TCA was incubated at 95 °C for 45 min. The HPLC assay was performed under the same conditions as those used for the blood samples. In a preliminary study, the detection limits of SPD and SPM concentrations in the dialysate were 0.5 nM and 5 nM, respectively. The flow rate of the dialysate was 500 mL/min. The total volume of the dialysate was determined by the time required for dialysis, and the amount of polyamine excreted in the dialysate was calculated using the polyamine concentration measured by HPLC.
## 2.6. Statistical Analysis
The Shapiro–Wilk normality test was used to determine the normal distribution of the dataset. Continuous variables with normal distributions were expressed as mean ± standard deviation, and non-normal variables were expressed as median and interquartile ranges. A paired Student’s t-test was used to compare normally distributed values. For non-normally distributed values, the Wilcoxon signed-rank test was used to compare the matched polyamine concentration data before and after dialysis. Additionally, the Mann–Whitney U test was used to compare non-matched data between dialysis patients and healthy controls.
Correlations between the two groups were evaluated using Pearson’s correlation for normally distributed data and Spearman’s rank correlation for non-normally distributed data. All analyses were performed using IBM SPSS Statistics for Windows, version 28.0 (IBM Corp., Armonk, NY, USA). A p value < 0.05 was considered statistically significant.
## 3.1. Characteristics of the Participants
A flowchart of the patient registration process is shown in Supplementary Figure S2. Overall, 11 patients refused to participate in the study, two patients died before the end of the study, one patient did not meet the requirements for participation because he was wearing a pacemaker, and six patients who had a past or current history of cancer were excluded. A total of 59 patients (35 men and 24 women) were enrolled in the study (Supplemental Figure S2).
The backgrounds and characteristics of the participants are presented in Table 1. Many previous research results have shown that polyamine concentrations do not change with age in healthy adults [1]. Therefore, we did not focus on matching the age range of the control group with that of the target group, but respected the volunteers’ willingness to participate; as a result, the control and dialysis groups were not matched for age. Their median age was 70.0 years (range, 62–75 years), and their median duration from the introduction of hemodialysis was 62 months (range, 29–142 months). The causative diseases requiring dialysis were glomerulonephritis ($$n = 20$$), diabetes mellitus ($$n = 18$$), nephrosclerosis ($$n = 6$$), and other diseases ($$n = 15$$). Forty-four patients received HD, and 15 patients received HDF. Twenty-six healthy volunteers (11 men and 15 women) participated in the study as controls, and none were excluded from the study. Their median age was 44.5 years (range: 37–52 years). There was no difference in sex ($$p \leq 0.149$$) between the dialysis and control groups, whereas dialysis patients were significantly older in ($p \leq 0.001$). HD patients had significantly lower SMI (6.3 ± 1.1 vs. 8.0 ± 1.2, $p \leq 0.001$) and HGS (23.5 ± 9.0 vs. 35.3 ± 9.6, $p \leq 0.001$) values than healthy individuals (Table 1).
## 3.2. Comparison of Blood Polyamine Levels
The blood SPD concentrations in HD patients were higher than those in healthy participants (10.1 (6.9–12.7) µM vs. 6.0 (4.8–7.1) µM, $p \leq 0.001$). The numerical values of blood SPM concentrations in HD patients were higher than those in healthy volunteers; however, there was no significant difference between them (4.4 (2.6–5.8) µM vs. 3.6 (2.7–4.9) µM, $$p \leq 0.401$$). The blood SPM/SPD ratio in HD patients was significantly lower than that in healthy participants (0.43 (0.34–0.59) vs. 0.64 (0.48–0.79) µM; $p \leq 0.001$) (Figure 1).
SPD and SPM concentrations and SPM/SPD ratios were evaluated before and after HD (Figure 2). HD did not significantly affect the SPD or SPM levels in whole blood; however, the SPM/SPD ratios decreased after HD (0.43 (0.34–0.59) vs. 0.42 (0.32–0.54), $p \leq 0.001$).
## 3.3. Polyamine Concentrations in Dialysate
HPLC did not detect (0.5 and 5 nM below the detection limit for SPD and SPM, respectively) either SPD or SPM in the dialysate before dialysis. SPD concentrations were detected in the dialysate 30 min after the start of dialysis for all six patients; the mean SPD concentration in the dialysate was 0.21 ± 0.13 μM. However, only four of the six patients had detectable SPD concentrations in the dialysate immediately before the end of dialysis. The mean concentration of the four samples was 0.14 ± 0.13 μM. SPM was not detected in any of the samples.
## 3.4. Analyses of Various Measurements in HD Patients
Various correlations between clinical parameters (excluding polyamines) were examined (Table 2). Patient age was negatively associated with SMI (ρ = −0.493, $p \leq 0.001$), HGS (ρ = −0.422, $$p \leq 0.001$$), Alb (ρ = −0.276, $$p \leq 0.034$$), and Cre (ρ = −0.427, $$p \leq 0.001$$). HD duration was negatively correlated with BMI (ρ = −0.420, $$p \leq 0.001$$) and HGS (ρ = −0.293, $$p \leq 0.024$$), but positively correlated with Cre (ρ = 0.325, $$p \leq 0.012$$). BMI and SMI were positively correlated ($r = 0.377$, $$p \leq 0.003$$). SMI was positively correlated with HGS ($r = 0.629$, $p \leq 0.001$), Alb (ρ = 0.281, $$p \leq 0.031$$), and Cre (ρ = 0.350, $$p \leq 0.007$$). HGS was positively correlated with Alb (ρ = 0.372, $$p \leq 0.004$$) and Cre (ρ = 0.405, $$p \leq 0.001$$). The Hb and CRP levels were negatively correlated (ρ = −0.284, $$p \leq 0.029$$). Alb was negatively correlated with CRP (ρ = −0.480, $p \leq 0.001$) and positively correlated with Ca (ρ = 0.463, $p \leq 0.001$). BUN was positively correlated with Cre (ρ = 0.354, $$p \leq 0.006$$) and p levels (ρ = 0.390, $$p \leq 0.002$$).
## 3.5. The Relationship between Polyamines and Various Measurements
The SPD and SPM concentrations and SPM/SPD ratios in relation to other clinical parameters are shown in Table 3. Notably, age and BMI did not correlate with either SPD and SPM concentrations or the SPM/SPD ratio. No significant correlation was found between HD duration and SPD, SPM, or the SPM/SPD ratio. The SPM/SPD ratio was significantly and positively correlated with SMI (ρ = 0.309, $$p \leq 0.017$$) and HGS (ρ = 0.260, $$p \leq 0.046$$) in a simple linear regression analysis (Figure 3). SMI did not correlate with SPM or SPD, and HGS showed no significant association with SPM or SPD.
## 4. Discussion
In this study, we determined that whole-blood SPD levels were higher in HD patients than in healthy participants; however, SPM levels did not differ between groups. The results of the present study are similar to those reported previously. Several reports have shown that erythrocyte SPD concentrations are significantly higher in patients with chronic renal failure than in healthy participants; however, their SPM levels are comparable to those in healthy participants [6]. Moulinoux et al. reported a significant increase in erythrocyte SPD levels in patients undergoing hemodialysis, whereas SPM levels were abnormally high in only a small proportion of patients [12]. Decreased urinary polyamine excretion in both patients with chronic renal failure and those on HD is considered one of the major causes of polyamine accumulation in blood cells.
Polyamine excretion from the dialysate was confirmed. Previous reports have shown that serum polyamine levels decrease after dialysis [13], indicating that HD can lead to the excretion of polyamines. However, in the present study an increase in polyamine excretion in the dialysate was mainly observed immediately after the start of dialysis, without affecting polyamine concentrations in whole blood. This suggests that polyamine excretion into the dialysate was insufficient to reduce whole-blood polyamine levels, as previously reported [6]. Given that most blood polyamines are present in association with blood cells, this may be due to the loss of intracellular polyamine delivery from blood cells to renal cells through intercellular contact.
Because of the noticeably higher SPD, the SPM/SPD ratio in HD patients was significantly lower than that in healthy volunteers. A lower SPM/SPD ratio in HD patients has also been previously reported [6,14]. In this study, HD patients were significantly older on average than healthy volunteers. Several reports have shown that the SPM/SPD ratio tends to decrease in healthy individuals because of the absence of an age-related decrease in SPD concentration and the presence of an age-related decreasing trend in SPM concentration [4,9,15]. However, these changes were minor and not statistically significant. Therefore, although the age difference between the two groups in this study may have had some effect on both polyamine SPM concentrations and SPM/SPD ratios, this is not expected to have a significant effect on the SPM/SPD ratio, especially the SPD concentration.
The findings of this study are consistent with those of previous studies. The difference in age between dialysis patients and controls resulted in a significant difference in muscle mass, as indicated by SMI, and muscle power, as indicated by HGS. This age-related change was also observed in a study involving patients on dialysis alone. In other words, SMI and HGS were negatively correlated with age. Furthermore, Alb and Hb levels decreased with age. The finding that CRP levels are negatively correlated with Alb and Hb levels is consistent with the finding that inflammation inhibits Alb and Hb synthesis. SMI and HGS, which were strongly correlated, were also positively correlated with Alb, a representative indicator of nutritional status, and Cre, the values of which are affected by muscle mass. Previous reports have indicated that several factors correlate with the prognosis of dialysis patients [16,17,18]. Among these, sarcopenia (for which the major diagnostic criteria are gait speed, HGS, and muscle mass [19,20]) is a major factor associated with a poor prognosis [21,22].
The intracellular concentrations of polyamines are tightly regulated by their import, export, synthesis, and catabolism. As part of this process, SPD and SPM are mutually converted [1], and because of this the SPM/SPD ratio has the potential to change. Chronic inflammation is known to be closely related to the development of various age- and lifestyle-related diseases [23,24]. It has also been recognized as the main component of the uremic phenotype linked to cardiovascular diseases and protein-energy wasting, which leads to sarcopenia [25,26] and is a strong predictor of poor outcomes in dialysis patients [27]. Inflammation activates spermidine/spermine-N1-acetyltransferase (SSAT), which acetylates the primary N1 amines of SPD and SPM. Both acetylated SPM and acetylated SPD are subsequently oxidized by N1-acetylpolyamine oxidase to produce SPD or putrescine, depending on the starting substrate, with H2O2 and aldehyde 3-acetoaminopropanal as byproducts [28,29,30]. Inflammation also activates the alternative enzyme spermine oxidase (SMO), which directly converts SPM to SPD while producing H2O2 and aldehyde 3-aminopropanal [31]. *The* generated 3-aminopropanal is spontaneously deaminated to produce acrolein, a highly toxic aldehyde [32]. Increased plasma polyamine oxidase activity and elevated acrolein levels have been reported in patients with chronic renal failure [12,33]. Briefly, two molecules of SPM become two molecules of SPD through two enzymes: SSAT and SMO. Simultaneously, one molecule of SPD becomes one molecule of putrescine via SSAT because it does not act on SPD. The inflammation-induced catabolism of SPM was accelerated more than that of SPD, resulting in a decrease in the SPM/SPD ratio (Supplemental Figure S3). The mechanism of both the increase in SPD and decrease in SPM/SPD in hemodialysis patients needs further investigation; however, similar findings have been reported in neurodegenerative diseases in which chronic inflammation is present as a pathological background. Decreased SPM/SPD ratios have been reported in patients with neurodegenerative diseases and cerebral ischemia associated with elevated SPD [9,34,35].
Recently, the relationship between muscles and polyamines has been examined in various ways. SPD and SPM were significantly decreased in the skeletal muscle of aged mice compared with that of young mice [36]. In contrast, a study of changes in skeletal muscle polyamine concentrations during exercise in male rats showed exercise-induced endogenous testosterone, followed by polyamine synthesis [37]. Polyamines are thought to be involved in skeletal muscle atrophy and hypertrophy and are of great interest in the prevention and treatment of muscle diseases [38,39]. Interventions for polyamine metabolism have the potential to be therapeutic interventions for muscle atrophy; however, further studies are needed.
Novel findings of this study include the positive correlations between both the SPM/SPD ratio and SMI and between the SPM/SPD ratio and HGS in HD patients. As SMI and HGS (which are also indicators of sarcopenia) are used to predict the prognosis of patients with HD, the SPM/SPD ratio may be a new predictor of prognosis and health status in patients with HD.
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|
---
title: 'Beyond Antioxidant Activity: Redox Properties of Catechins May Affect Changes
in the DNA Methylation Profile—The Example of SRXN1 Gene'
authors:
- Patrycja Jakubek
- Jovana Rajić
- Monika Kuczyńska
- Klaudia Suliborska
- Mateusz Heldt
- Karol Dziedziul
- Melita Vidaković
- Jacek Namieśnik
- Agnieszka Bartoszek
journal: Antioxidants
year: 2023
pmcid: PMC10045509
doi: 10.3390/antiox12030754
license: CC BY 4.0
---
# Beyond Antioxidant Activity: Redox Properties of Catechins May Affect Changes in the DNA Methylation Profile—The Example of SRXN1 Gene
## Abstract
The role of catechins in the epigenetic regulation of gene expression has been widely studied; however, if and how this phenomenon relates to the redox properties of these polyphenols remains unknown. Our earlier study demonstrated that exposure of the human colon adenocarcinoma HT29 cell line to these antioxidants affects the expression of redox-related genes. In particular, treatment with (−)-epigallocatechin (EGC) downregulated transcription of gene encoding sulfiredoxin-1 (SRXN1), the peroxidase involved in the protection of cells against hydrogen peroxide-induced oxidative stress. The aim of this study was to investigate whether the observed SRXN1 downregulation was accompanied by changes in the DNA methylation level of its promoter and, if so, whether it was correlated with the redox properties of catechins. The impact on DNA methylation profile in HT29 cells treated with different concentrations of five catechins, varying in chemical structures and standard reduction potentials as well as susceptibility to oxidation, was monitored by a methylation-sensitive high-resolution melting technique employing the SRXN1 promoter region as a model target. We demonstrated that catechins, indeed, are able to modulate DNA methylation of the SRXN1 gene in a redox-related manner. The nonlinear method in the statistical analysis made it possible to fish out two parameters (charge transfer in oxidation process Qox and time of electron transfer t), whose strong interactions correlated with observed modulation of DNA methylation by catechins. Based on these findings, we present a proof-of-concept that DNA methylation, which limits SRXN1 expression and thus restricts the multidirectional antioxidant action of SRXN1, may represent a mechanism protecting cells against reductive stress caused by particularly fast-reacting reductants such as EGC and (−)-epicatechin gallate (ECG) in our study.
## 1. Introduction
Plant-borne foods and beverages constitute a rich source of antioxidant phytochemicals such as polyphenols, whose consumption has been documented to bring beneficial effects for human health [1]. Dietary phenolic compounds belong to several classes, among which the most common are flavonoids. Electrochemical properties, hence the antioxidant activity of these compounds, are strictly related to their chemical structure. Flavonoids exhibiting particularly strong reducing potential are flavan-3-ols, commonly named—catechins. They constitute the major components of green tea, mainly represented by (−)-epigallocatechin gallate (EGCG), (−)-epigallocatechin (EGC), (−)-epicatechin gallate (ECG), (−)-epicatechin (EC), and (+)-catechin (C). Catechins are also abundant in fruits such as berries, apples, grapes, and grape seeds, as well as in cocoa and cocoa-based foodstuffs [2].
Catechins, especially those derived from green tea, have been frequently reported to exhibit a variety of chemopreventive activities both in vitro and in vivo [3]. These protective effects are believed to play a role in the prophylaxis of such chronic conditions as cancer, cardiovascular and infectious diseases, liver anomalies, as well as in diabetes [4,5,6,7]. The benefits seem associated mainly with the chemical neutralization of prooxidants, thus with the antioxidant potential of catechins, but may occasionally result from more specific activities, such as the ability to affect metabolic and signaling pathways [8]. The redox-related activities of these flavonoids embrace scavenging of reactive oxygen species (ROS), chelation of transition metal ions, inhibition of transcription factors induced under oxidative stress (e.g., activator protein 1—AP-1, and nuclear factor kappa-light-chain-enhancer of activated B cells—NF-κB), and other. The impact on the expression of redox-related genes has been recently shown as well [9].
Catechins have also been demonstrated to influence epigenetic mechanisms by the modulation of DNA methylation and histone acetylation levels [10,11,12,13]. However, how these impacts relate to the redox properties of catechins has not been studied to date, though the dependence of methyl transfer reactions on the redox status of cells is known [14]. DNA methylation is a reversible epigenetic modification often impaired in diseased states, e.g., in cancer tumor suppressor genes are frequently silenced by hypermethylation. Therefore, the inhibition of DNA methylation of such protective genes has become a promising target of anticarcinogenic prophylaxis [15]. By definition, the preventive strategy is mainly addressed to healthy people with increased risk of illness; thus, food ingredients are suggested to be the most accessible and safe protective factors. Among catechins, EGCG has been shown to be the strongest inhibitor of maintenance DNA methylation since its gallic acid moiety accommodates in the active site of DNA methyltransferase 1 (DNMT1), where it blocks DNMT1 catalytic activity and thereby decreases DNA methylation levels [13]. The inhibition of DNA methylation by catechins has been reported to also be driven indirectly as a consequence of methylation of catechins by catechol-O-methyl transferase (COMT), particularly in the case of EC and C. COMT competes with DNA methyltransferases (DNMTs) for the donor of a methyl group, S-adenosylmethionine (SAM), thereby diminishing their enzymatic activity [16]. Moreover, the demethylation of SAM leads to the formation of S-adenosylhomocysteine (SAH), which is an efficient and selective inhibitor of DNMTs [17].
DNA methylation affects both genome stability and gene expression; thus, any abnormalities concerning methylomes, such as hypo- or hypermethylation, may modulate mRNA levels and further influence disease development [18]. The impact of nutrition on gene expression has also been well established [19]. As shown for catechins in our previous study [9], exposure of the HT29 cell line to their different concentrations induced changes in the expression of redox-related genes. The physiological concentration (1 μM) of catechins upregulated several of them, while the higher 10 μM concentration seemed to sufficiently preserve cellular redox homeostasis, so the expression of redox-related genes remained not affected. The puzzling exception was the downregulation of the sulfiredoxin 1 (SRXN1) gene, encoding one of the members of the cellular thiolstat [20]. The main function of SRXN1 is to protect cells against hydrogen peroxide-induced oxidative stress by peroxiredoxin (I–IV) reactivation [21]. The activity state of peroxiredoxins is dependent on the oxidation state of sulfur in the peroxidatic cysteine (Cp), located in the catalytic center of the enzyme. Hyperoxidation of Cp to sulfinic acid results in the inactivation of peroxiredoxin, which can be reversed in an ATP-dependent manner solely by SRXN1 with the aid of its single conserved cysteine residue present in the catalytic center [22]. Our observations suggested that the treatment with strong antioxidants by diminishing the expression of SRNX1 sort of excluded this enzyme from the endogenous cellular antioxidant barrier. One may presume that this could represent a mechanism preventing organisms from being pushed into reductive stress when exposed to an excess of compounds whose electrochemical properties make them particularly effective reducing agents. The role of DNA methylation in the control of redox homeostasis in cells exposed to exogenous strong antioxidants was a tempting explanation in view of our earlier findings [9].
The objective of this study was to examine whether the previously observed [9] downregulation of the SRXN1 gene resulted from changes in the profile of the DNA methylation of CpG islands within its promoter. The cellular model was the same as in the previous study, i.e., undifferentiated human colon adenocarcinoma HT29 cell line exposed to redox-active dietary phytochemicals. Compounds selected for these investigations included catechin derivatives with different chemical structures and values of standard reduction potentials. Additionally, important but relatively weak compared to polyphenols [9,23], thiol antioxidant—glutathione—produced endogenously but also found in foods (exogenous source) [24] was chosen as a reference reducing agent, which, according to our previous studies, has no impact on SRXN1 expression. We also wanted to determine whether changes in DNA methylation levels in the SRXN1 promoter region are dependent on catechin structure or corresponding electrochemical properties. Our investigations provide new data related to the impact of catechins on DNA methylation in the context of their chemical structures, electrochemical properties, and concentration applied to cells. Based on the study results, we suggest the indirect role of DNA methylation in fine-tuning cellular redox homeostasis.
## 2.1. Selected Redox-Active Compounds
The study included the following redox-active compounds: (+)-catechin (C), (−)-epicatechin (EC), (−)-epigallocatechin (EGC), (−)-epicatechin gallate (ECG), (−)-epigallocatechin gallate (EGCG) from Extrasynthese (Genay Cedex, France) and glutathione (GSH) from Sigma-Aldrich (St. Louis, MO, USA). The DNA demethylating agent 5-aza-2′-cytidine (5-Aza) was purchased from Sigma-Aldrich (St. Louis, MO, USA).
## 2.2. Cell Culture
The human colon adenocarcinoma cell line (HT29) from the ATCC was cultured in McCoy’s medium supplemented with L-glutamine (2 mol/L), sodium bicarbonate (200 g/L), fetal bovine serum (100 mL/L) and antibiotics (100 U/mL penicillin and 100 g/L streptomycin) in a humidified atmosphere with $5\%$ CO2 at 37 °C in a SMARTcell incubator (Heal Force). All reagents for cell culture were obtained from Sigma Aldrich (St. Louis, MO, USA).
## 2.3. Treatment of Cells with Selected Redox-Active Compounds
*For* gene expression analysis, HT29 cells were seeded in 24-well tissue culture plates (6 × 104 cells per well in 1.8 mL of medium). Stock solutions of catechins and glutathione were prepared in analytical-grade ethanol (POCH, Gliwice, Poland) and ultrapure water purified with QPLUS185 system from Millipore (Burlington, MA, USA), then sterilized using Millex sterile R33 mm (0.22 µm) syringe-driven filters from Millipore (Burlington, MA, USA). After 24 h of settling down, the cells were treated with 0.2 mL of antioxidant solution and left for a further 24 h at 37 °C or for 72 h in the case of 5-Aza treatment (5-Aza treatment was repeated every day). The cells treated with catechins were exposed to $3\%$ (v/v) of ethanol as a solvent, so the same concentration of ethanol was applied to control cells. In the case of glutathione, control cells were treated with water. A stock solution of 10 mM 5-Aza was prepared in dimethyl sulfoxide (DMSO, SERVA Electrophoresis GmbH, Heidelberg, Germany), and subsequent dilutions were prepared in culture medium. The final DMSO concentration to which cells were exposed did not exceed $0.1\%$.
For methylation analysis, HT29 cells were seeded in 6-well tissue culture plates (5 × 105 cells per well in 3.6 mL of McCoy’s medium). After 24 h, cells were treated with 0.4 mL solutions of the investigated compounds in the 0.1–100 µM concentration range and incubated for 24 h at 37 °C. The subsequent steps were carried out in the same way as described earlier. All experiments were performed in three independent biological replicates.
## 2.4. Total RNA Isolation
Total RNA isolations from treated and control cells were carried out using RNeasy Mini Kit (Qiagen, Hilden, Germany). For homogenization, QIAshredder (Qiagen, Hilden, Germany) was used. To assure complete elimination of genomic DNA contamination, RNase-free DNase kit (Qiagen, Hilden, Germany) was applied. All steps were performed as stated in the manufacturer’s protocols. RNA quality and quantity was checked with Nanodrop 2000c (Thermo Scientific, Waltham, MA, USA) at absorbance ratios of $\frac{260}{280}$ nm and $\frac{260}{230}$ nm. Isolated RNAs were stored at −80 °C.
## 2.5. Microarray Analysis
Isolated mRNA (500 ng) was reverse transcribed to cDNA using an RT2 First Strand kit (Qiagen, Hilden, Germany). The obtained cDNA was subsequently mixed with an RT2 SYBR Green kit (Qiagen, Hilden, Germany) and pipetted into 96-well RT2 ProfilerTM PCR microarray human oxidative stress plates provided by Qiagen (Hilden, Germany). qPCR was performed with the aid of LightCycler® 96 Instrument (Roche, Basel, Switzerland). All steps were carried out according to instructions provided by the manufacturer. The whole procedure was previously described in detail by Baranowska et al. [ 9].
## 2.6. Genomic DNA Isolation
Genomic DNA was isolated from treated and control cells using QuickDNA Miniprep Plus Kit from Zymo Research (Irvine, CA, USA) according to the manufacturer’s protocol. DNA quality and quantity were checked using Nanodrop 2000c (Thermo Scientific, Waltham, MA, USA) by measuring the ratio of absorbances at $\frac{260}{280}$ nm and $\frac{260}{230}$ nm. The DNA isolates were stored at −20 °C.
## 2.7. Bisulfite Conversion
Bisulfite conversion of isolated genomic DNA was performed with the EZ DNA Methylation kit (Zymo Research, Irvine, CA, USA) according to the protocol provided by the manufacturer. The reaction conditions were adjusted so as to obtain full cytosine (C) to thymine (T) conversion, as stated in the appendix of the instruction manual.
## 2.8. Prediction of CpG Islands and Primer Design for Methylation Analysis
Prediction of the CpG island of the human SRXN1 gene was performed with EMBOSS CpGplot as described before [25]. Primers for the SRXN1 gene were designed using MethPrimer. Two separate sets of primers were prepared: first corresponding to methylated (M) and second to unmethylated (U) promoter region. Their sequences are listed in Table S1 (Supplementary Materials). All the primers used for DNA methylation analysis were provided by Invitrogen (Waltham, MA, USA).
## 2.9. Methylation-Specific PCR (MSP)
MSP was performed using Maxima SYBR Green/ROX qPCR Master Mix (2x) from Thermo Scientific (Waltham, MA, USA). The reaction mix included Maxima SYBR Green/ROX qPCR Master Mix (2x), 10 µM of each primer, and 100 ng (M1/U1) or 200 ng (M3/U3) of bisulfited DNA. Thermal cycling conditions were set as described before [25]. A no-template control was used to detect any reagent contamination or formation of primer dimers. QuantStudio 3 Real-Time PCR System from Applied Biosystems (Waltham, MA, USA) was used to run MSP. The percentage of DNA methylation was calculated according to the formula: %$M = 1$/(2dCt + 1), where dCt = CtM − CtU. CtM, cycle threshold value for MSP performed with methylated primers; CtU, cycle threshold value for MSP performed with unmethylated primers.
## 2.10. Methylation-Sensitive High-Resolution Melting (MS-HRM)
Conditions and experiment design for MS-HRM have been described in detail previously [22]. Shortly, standard curves for MS-HRM analysis were prepared using human methylated and non-methylated DNA standards (Zymo Research, Irvine, CA, USA). Bisulfite-converted standards were mixed to obtain $0\%$, $50\%$, and $100\%$ of DNA methylation. The reaction mixture consisted of 2x MeltDoctorTM HRM Master Mix from Applied Biosystems (Waltham, MA, USA), 0.15 µM of each of the forward and reverse primers from the methylated and unmethylated set, and 10 ng (M1/U1) or 20 ng (M3/U3) of bisulfited DNA. PCR amplification and subsequent MS-HRM analysis were performed as described earlier [25]. Data normalization and quantitative calculation of DNA methylation percentage were carried out as described by Rajić et al. [ 26].
## 2.11. Quantitative Reverse Transcription PCR (RT-qPCR)
Reverse transcription was conducted using QuantiNova Reverse Transcription Kit (Qiagen, Hilden, Germany). The amount of mRNA used for cDNA synthesis was 500 ng. Synthesized cDNA was diluted 1:9 in DNase-free water prior to RT-qPCR according to the manufacturer’s recommendation. RT-qPCR was performed using FastStart Essential DNA Green Master (Roche, Basel, Switzerland) in LightCycler® 96 Instrument (Roche, Basel, Switzerland). The thermal cycling conditions included initial denaturation at 95 °C for 15 min and subsequent 40 cycles of a three-step protocol: 95 °C for 10 s, 60 °C for 10 s, and 72 °C for 100 s. The three-step protocol was followed by melting: 95 °C for 10 s, 65 °C for 1 min, and 97 °C for 1 s. Primers for SRXN1 gene expression analysis were designed with the aid of Primer-BLAST based on the sequence available in GeneBank with the accession number NM_080725.3. Primers were provided by Genomed (Warsaw, Poland), and their sequences are listed in Table S2 (Supplementary Materials). Gene expression was calculated with the delta-delta Ct method after normalization to glyceraldehyde 3-phosphate dehydrogenase (GAPDH) used as a reference gene. The choice of reference gene was suited for the HT29 cell line based on the literature [27].
## 2.12. Statistical Analysis
The results are presented as the mean value ± SD of 3 independent biological replicates unless stated otherwise. The determination of the statistical significance between DNA methylation levels in control and in treated samples was evaluated by one-way ANOVA with Dunnett’s test using the Prism 6.0 software package (GraphPad Software, Inc., Boston, MA, USA). Differences were statistically significant at the level of $p \leq 0.05.$ The search for strong interactions indicating differences between DNA methylation determinations and electrochemical as well as biological parameters established for the tested compounds in other studies was performed by t-test, Welsch, and Cochran tests with the aid of SAS Viya for Learners 3.5 analytics and data management platform
## 3.1. The Impact of Catechins on SRXN1 Expression
Catechins are known to affect the expression of genes implicated in the maintenance of cellular redox homeostasis, such as these encoding phase II enzymes [28]. However, relatively less information is on SRXN1. Our former microarray analysis of the expression of redox-related genes showed that EGC at a relatively high concentration (10 µM) caused a statistically significant ($p \leq 0.05$, fold change > 2) drop in SRXN1 gene transcription in HT29 cells [9]. The trends in the modulation of SRXN1 gene transcription observed for treatment with other catechins seemed to be influenced by their chemical structures. These structure–activity relationships are illustrated in Figure 1A. The parent form, i.e., (+)-catechin (C), was able to increase SRXN1 expression. Epimers of C, (−)-epicatechin (EC) and (−)-epigallocatechin (EGC), caused a decrease in SRXN1 transcription, whereas esters of catechin and gallic acid, (−)-epicatechin gallate (ECG) and (−)-epigallocatechin gallate (EGCG), increased SRXN1 expression at lower concentration (1 µM), but decreased it when applied at higher concentration (10 µM). In contrast, GSH, a major intracellular antioxidant, exhibited no significant stimulatory impact on SRXN1 transcriptional activity when applied exogenously to HT29 cells (Figure 1B). Here, we examined if DNA methylation could be one of the potential mechanisms responsible for the downregulation of SRXN1 expression and how this phenomenon relates to the physicochemical properties of investigated compounds.
## 3.2. Methylation of SRXN1 Promoter
To examine whether mRNA expression of SRXN1 could be regulated by DNA methylation, HT29 cells were treated for 72 h with DNA demethylating agent 5-azacytidine (5-Aza) in concentrations of 7.5 µM and 10 µM, which for the treatment of HT29 cells with this compound corresponded to EC30 and EC45, respectively (Supplementary Materials Figure S1). After treatment with a lower 5-Aza concentration, RT-qPCR revealed the same level of SRXN1 mRNA as in control cells. In contrast, a statistically significant, almost 2-fold increase in SRXN1 mRNA level was determined after treatment with 10 µM 5-Aza (Figure 2). These results confirmed that, indeed, DNA methylation may be an important regulator of SRXN1 gene transcription.
*The* gene for SRXN1 is located on the minus strand of chromosome 20, extending from position 646,615 to 653,200 (NCBI RefSeq NC_000020.11). According to the EMBOSS CpGplot, the human SRXN1 contains a 706 bp long CpG island that covers the region from 652,858 to 653,032, i.e., −537 to +169, with regard to the position of the transcription start site (TSS) marked as +1 (NCBI RefSeq NM_080725.3) (Figure 3). In order to evaluate the effect of catechins on the DNA methylation profile of CpG island within the promoter of the SRXN1 gene, MSP analysis of one (M1/U1) and HRM analysis of two selected regions (M1/U1 and M3/U3) were performed. Positions of the primers used for DNA methylation analysis are shown in Figure 3.
## 3.2.1. DNA Methylation within M1/U1 Region of SRXN1 Promoter Analyzed by MSP
MSP analysis with M1/U1 primer pairs showed some trends but no statistically significant differences in DNA methylation level between any of the treatments compared to the control (Figure 4). In the case of HT29 cells treated with C, DNA methylation remained at the same level as in control cells, while treatment with EC tended to decrease DNA methylation level, especially at the concentration of 1 µM, where a decline of $31.3\%$ was observed. In other groups of treated cells, a slight increase in DNA methylation was detected with all applied concentrations, except in the cells treated with 1 µM and 10 µM EGCG. The highest increase was observed in cells treated with the highest concentrations of ECG (up to $24.1\%$) and EGC (up to $25.9\%$), and indeed, the latter compound downregulated SRXN1 significantly (Figure 1. GSH at concentrations ranging from 0.1 µM to 100 µM tended to increase DNA methylation level from $14\%$ to $20.7\%$, respectively, compared to control, with the exception of 1 µM GSH-treated cells, where $19.8\%$ decrease in DNA methylation was observed (Figure 4). The percentage of DNA methylation, fold-changes, and p-values obtained by MSP analysis are presented in Supplementary Materials (Supplementary Materials Table S3). The obtained MSP results suggest that CpGs at positions 463, −402, and −392 (present in the DNA sequence complementary to the primer sequences) were not differentially methylated in cells treated with different catechins compared to the control.
## 3.2.2. DNA Methylation in Both M1/U1 and M3/U3 Regions of SRXN1 Promoter Analyzed by MS-HRM
To include an additional four CpGs in DNA methylation analysis, positioned in the region between forward and reverse primer pairs, HRM analysis of the same region as for MSP was conducted with a mix of four primers (M1fw/M1rev and U1fw/U1rev). This region covered the sequence from −482 to −378 with regard to the position of TSS. In that way, detailed information regarding the DNA methylation status of the targeted SRXN1 region (7 CpGs in total) was obtained. Analysis showed a statistically significant decrease in DNA methylation level in C- and EC-treated cells compared to control cells at all applied concentrations (decrease up to $86.7\%$, Figure 5A). Additionally, the diminishment of DNA methylation level was statistically significant also for HT29 cells treated with 1 µM ECG ($52.2\%$) and 10 µM EGCG ($73.1\%$). The increase of DNA methylation level was observed only in cells treated with 10 µM EGC as well as 10 µM and 100 µM ECG. DNA methylation levels were $76.8\%$, $88.9\%$, and $59.6\%$ higher than under control conditions, respectively, and the differences were statistically significant. Other applied concentrations of catechins and treatments with GSH did not influence the SRXN1 DNA methylation status compared to adequate control (Figure 5A). The percentage of DNA methylation, fold-changes, and p-values obtained as a result of HRM analysis are presented in Supplementary Materials (Table S4). For treatments that caused a statistically significant increase in DNA methylation, representative aligned melt curves, difference plots showing positions of control and catechin curves with respect to $0\%$, $50\%$, and $100\%$ methylated standards, standard curves, and bar graphs representing DNA methylation levels obtained from standard curves are separately presented in Supplementary Materials Figure S2.
Another region of SRXN1 promoter was analyzed by MS-HRM with a mix of four primers (M3fw/M3rev and U3fw/U3rev) to estimate changes of DNA methylation of 23 CpGs located within the sequence from −345 to −190 directly upstream of the TSS. The changes in the methylation levels are shown in Figure 5B. As in the first analyzed region, there was a decline in DNA methylation level in HT29 cells treated with all concentrations of C and EC, compared to control, still with statistical significance achieved only in the case of cells treated with 100 µM EC ($39.8\%$). Additionally, a significant decrease in DNA methylation was also observed in 0.1 µM ECG-treated cells ($40.4\%$). HRM analysis showed more than a $20\%$ increase in DNA methylation level in cells treated with 10 µM EGC and 10 µM and 100 µM ECG among which the treatment with 10 µM ECG showed a statistically significant increase ($41\%$) compared to the control. In other applied concentrations and treatments, including GSH, DNA methylation levels were comparable to adequate controls (Figure 5B). The percentage of DNA methylation, fold-changes, and p-values obtained as a result of HRM analysis are presented in Supplementary Materials (Table S4). Representative aligned melt curves, difference plots, standard curves, and bar graphs are separately presented for treatments that caused a statistically significant increase in DNA methylation in Supplementary Materials Figure S3.
## 3.3. RT-qPCR Analysis of SRXN1 Expression
To confirm that the observed changes in DNA methylation levels are associated with altered levels of SRXN1 mRNA expression, RT-qPCR was performed for the treatments that showed a statistically significant increase in DNA methylation level in the case of HRM analysis (Figure 5). In HT29 cells treated with 10 µM ECG, SRXN1 mRNA expression was $14.5\%$ lower than in control, while in cells treated with 100 µM ECG, this decline reached $53.3\%$ compared to control. The lowest and statistically significant decrease in SRXN1 mRNA expression was observed in HT29 cells treated with 10 µM EGC (Figure 6). Downregulation of $76.2\%$ compared to the control SRXN1 mRNA level was in accordance with the results obtained from profiler analysis (Supplementary Materials Table S5).
## 3.4. The Search for Correlations between Investigated Parameters
The correlation between levels of DNA methylation and available parameters defining redox properties for both catechins and GSH, as well as their bioactivity (gathered in Table 1), was investigated by linear methods: t-test, Welch’s test, and Cochran test. In this case, we compared the results of DNA methylation levels performed by the MS-HRM method for the M1/U1 pair of primers and each individual electrochemical parameter, as presented in Table 1. No significant correlation was found for any of these parameters. However, all tests applied suggested some hypothetical influence of Qox, AOE, and t because, in these cases, p-values in the t-test were p ≤ 0.15. In other cases, the t-test showed $p \leq 0.18$ or much higher. Therefore, these three electrochemical parameters were analyzed for possible strong interactions. For this purpose, again, the three abovementioned statistical tests were applied to investigate nonlinear effects. This approach revealed the impact on DNA methylation of strong interactions between Qox. and t (t-test $p \leq 0.0380$, Welch’s test $p \leq 0.0271$, Cochrane test $p \leq 0.0999$). The interactions between AOE and t did not reach statistical significance (t-test $p \leq 0.0831$, Welch’s test $p \leq 0.1009$, Cochrane test $p \leq 0.1969$) and thus seemed to have a smaller impact.
## 4. Discussion
Epigenetic mechanisms affect various biological processes involved in the preservation of health as well as implicated in the initiation and progression of diseases. Epigenetic modifications, e.g., DNA methylation, are known to be reversible in response to various environmental factors, including diet. Therefore, it is not surprising that the investigations on epigenetic factors behind the beneficial activities of dietary compounds have gained much attention. The impact of food components on DNA methylation can occur at four levels: (i) availability of methyl donors, (ii) modulation of DNMTs activity, (iii) impact on the activity of enzymes involved in one-carbon metabolism, and (iv) involvement in mechanisms related to active DNA demethylation [31]. Methylation of CpGs in DNA is maintained by DNMT-dependent transfer of methyl groups from SAM, a methyl donor generated in the methionine cycle [32]. The methionine cycle is closely related to the folate cycle, and together, these pathways shape the “one-carbon metabolism”. Numerous nutrients and some non-nutritive compounds (e.g., catechins) have been reported to affect one-carbon metabolism and subsequent SAM generation, which further leads to the modulation of histone and DNA methylation levels [33]. To date, catechins have been demonstrated to affect DNA methylation by interfering with folic acid metabolism as well as by inhibiting of DNMTs activity and expression [10,34]. Even though it is generally agreed that catechins mainly act as direct DNMT1 inhibitors, in mice whose diet was supplemented with EGCG, the decrease in this enzyme activity was accompanied by the lowered expression of the DNMT1 gene caused by the increased level of DNA methylation in its promoter [35]. These latter results suggest that catechins may exhibit the ability to influence DNA methylation also by mechanisms other than inhibition of DNMT1 enzymatic activity.
Previously, we had reported a rather surprising observation that one catechin, namely EGC, downregulates the expression of the SRXN1 gene in human colon HT29 cells [9]. Therefore, in the current study, we investigated using the same cell line whether the observed EGC-induced decrease in SRXN1 transcription is associated with changes in its promoter methylation pattern, similarly as it was shown for EGCG and DNMT1 expression [35]. The initial assumption implied that the changes in expression of the SRXN1 gene might be a consequence of epigenetic modulation triggered by an altered redox environment. This assumption stemmed from former results suggesting that in HT29 cells, catechins at 10 µM concentration brought the cellular redox status to the borderline of maintained homeostasis [9]. Recently it has been shown that a sustained overexpression of nuclear factor, erythroid 2-like 2 (Nrf2)-driven antioxidant transcriptome (involving SRXN1) leads to reductive stress in cardiac tissue in vivo [36], whereas catechins are known modulators of Nrf2 expression [37]. We hypothesized that in cells exposed to strong antioxidants, the production of antioxidant enzymes is not needed, and as a result, the silencing of expression of some genes, e.g., of SRXN1, via DNA methylation takes place to maintain proper redox homeostasis, in particular, to prevent pushing cells into reductive stress. To verify this hypothesis, the impact of catechins on the DNA methylation profile of the SRXN1 gene in HT29 cells was investigated in a wide concentration range, from 0.1 µM physiologically to 100 µM intestinally achievable, to pinpoint the possible dose–response relationships for a series of catechin derivatives differing in chemical structures and electrochemical properties.
The results of the MS-HRM study confirmed our hypothesis that the observed EGC-induced downregulation of SRXN1 expression (Figure 1 and Figure 6) may be related to changes in the DNA methylation of this gene promoter. However, the clear cause–effect relationship for antioxidants studied turned out to be difficult to pinpoint at first sight, which is not surprising, taking into account the variety of mechanisms influencing DNA methylation triggered by these polyphenols. The level of DNA methylation within the first analyzed region of the SRXN1 promoter significantly increased in the case of treatment of HT29 cells with high concentrations of EGC and ECG. As mentioned before, high concentrations of catechins are relevant only to colonic cells, which are in direct contact with ingested food [38]. The ileal fluid reaching the colon may contain up to $70\%$ of ingested catechins [39]; thus, their effective concentrations exceed those found in human plasma that reache around 1 µM if these polyphenols are consumed in typical amounts [40]. In our hands, EGC and ECG applied to HT29 cells at physiological concentrations either did not affect or slightly decreased DNA methylation in the SRXN1 promoter. For C and EC, a decrease in DNA methylation level was observed, regardless of the applied concentration (Figure 5). Although GSH was reported to be involved in the regulation of several epigenetic mechanisms, it hardly influenced the DNA methylation level of any of the analyzed regions, which is in line with earlier studies reviewed by García-Giménez et al. [ 41]. Moreover, recently endogenous reducing thiols, including GSH, have even been shown to support SRXN1-driven reactivation of PRDXs [42], which may explain why this thiol antioxidant should not be expected to downregulate SRXN1 expression.
The chemical structures of EGC and ECG that increased DNA methylation of SRXN1 gene promoter do not possess any specific structural features that are not seen in other catechin derivatives. The cis configuration of substituents on carbons C2 and C3, which shapes the 3-dimensional structure of the whole molecule, and hence could impact interaction with target proteins, is also present in other derivatives (except for C being the trans epimer). The hydrophobicity of ECG is higher than that of EC but lower than that of EGCG [43]. Both latter compounds, in contrast to ECG, decrease rather than increase DNA methylation. The presence of pyrogallol moiety also does not seem to have a decisive role, as EGCG, which did not increase DNA methylation level, contains two such substituents. Moreover, all studied pyrogallol derivatives display similar chelating properties [30], i.e., the feature that could alter their availability for interactions. In addition, the ability to form internal hydrogen bonds is similar in the case of both ECG and EGCG [30]. All mentioned facts make it impossible to propose any straightforward structure–activity relationship and to indicate any sole physicochemical property of catechins as that influencing cellular DNA methylation machinery.
Moreover, the treatment of HT29 cells with different concentrations of catechins did not reveal any clearcut concentration dependence for SRXN1 gene promoter DNA methylation. However, a similar lack of concentration dependence was observed for the same set of catechins and their ability to influence the expression of redox-related genes in HT29 cells in our earlier nutrigenomic experiments [9]. Such observations may suggest that there are additional intracellular factors/mechanisms that somehow counterbalance the biological actions of catechins. One such mechanism may be related to their metabolism, in particular, the pathway of biotransformation of catechins upon which these compounds become methylated [44]. As already mentioned, catechins are methylated by COMT, which competes with DNMTs for methyl groups provided by SAM [16]. Thus, COMT-catalyzed reactions decrease the pool of available SAM and increase its demethylated form, SAH, which may further inhibit DNMT1 [17]. Such a mechanism could explain the decrease in DNA methylation observed in the case of treatment of HT29 cells with catechol moiety containing C and EC, but not the impact of pyrogallol derivatives of epicatechin on methylation of SRXN1 promoter (Figure 5A).
Other analyzed features of compounds studied, which via influencing cellular redox status, could affect DNA methylation level, included their redox properties. The way of reasoning here was the following: (i) active demethylation occurs as a result of oxidation of methyl group in 5-methylcytosine [45], (ii) strong antioxidants scavenge ROS creating a more reductive cellular environment, (iii) under such conditions, active DNA demethylation becomes less probable, (iv) as a result DNA methylation levels may increase. Reduction potentials represent the electrochemical property that may thus determine the impact of antioxidants on cellular redox homeostasis. Initially, we assumed that this property of catechins was behind the increased DNA methylation and, therefore, lower expression of the SRXN1 gene incurred by some catechins [9]. We speculated that the ease of donating electrons by these antioxidant compounds drives the cellular environment toward a more reductive state, thereby preventing active DNA demethylation. *In* general, thermodynamically, the lower the standard reduction potential E0, the higher the antioxidant activity, which in the case of the studied redox-active compounds increases at 37 °C in the following order: GSH < EGC < C < EC < EGCG < ECG [9]. The presented results seemed to clearly disprove this initial working hypothesis. The increase in DNA methylation was induced by EGC and ECG, which, among other catechins, displayed the lowest and the highest standard reduction potentials, respectively. GSH, used as a reference antioxidant, did not affect DNA methylation within the examined promoter area of SRXN1 regardless of its concentration, even though its standard reduction potential is similar to that of EGC. Thus, the observed changes in the DNA methylation level of this gene did not seem to depend on the reduction potentials of investigated compounds. However, the total antioxidant activity (TAA) of a compound is determined not only by thermodynamics, reflected by a standard reduction potential. In addition, the kinetics of oxidation of an antioxidant, expressed as the charge transferred in the oxidation reaction within a time unit, influences the TAA. The implementation of a kinetic factor in antioxidant activity determination, which previously was reported for catechins as the stoichiometry value n10, showed that the total reducing capacity of EGC was stronger than it appeared based solely on E0 (Figure 7) [9]. Indeed, our preliminary results of voltammetric measurements performed for catechins revealed that during the oxidation process, EGC transferred about twice the amount of charge compared to that transferred by ECG within a similar time period (Table 1). Due to the lack of complete electrochemical characterization of catechins, this aspect simply could not be satisfactorily clarified. Nonetheless, the importance of kinetic aspects was confirmed by the applied statistical tests investigating nonlinear effects, which revealed the impact of strong interactions between Qox. and t on the DNA methylation of SRXN1 promoter (Section 3.4), and maybe also other redox-related albeit not yet identified genes, in cells exposed to strong antioxidants.
Altogether, our results that compare redox properties of studied catechins with their impact on DNA methylation summarized graphically in the heatmap included in Figure 7, point to the fact that the effectiveness of reducing (exogenous) compounds in shaping cellular redox status may depend on both thermodynamics and kinetics of redox processes, in which they are involved. It can be noticed that both EGC and ECG differ from other catechins in two features: (i) medium ability to transfer charge, but (ii) in the shortest times. This makes them very efficient antioxidants. To maintain proper homeostasis, cells must neutralize oxidants by mobilization of an antioxidant defense system but also must respond to particularly effective reducing agents that could block cellular ROS-dependent processes [22]. In the latter case, lowering expression of SRXN1 by DNA methylation of its promoter seems a particularly powerful mechanism as this enzyme is necessary for the restoration of activity of one of the most important classes of antioxidant enzymes—peroxiredoxins as well as the reduction of other numerous S-sulfinylated proteins [46]. Our study provides the unique proof-of-concept that changes in the DNA methylation profile of a redox-related gene promoter, thus biological effects, may be affected by the electrochemical properties of antioxidants shaping cellular redox homeostasis. In view of the fact that our reasoning focused mainly on the chemical explanation of the observed biological effects and concentrated on one specific group of polyphenols, more research is needed to confirm that the proposed mechanism of modulation of redox homeostasis can also be observed in the case of other reducing agents or antioxidant-related genes or other cellular models.
## 5. Conclusions
In conclusion, our study demonstrated that the downregulation of SRXN1 gene transcription by some catechins might be a result of increased DNA methylation level within its promoter. This effect seems to depend neither on the standard reduction potentials of these antioxidants nor on their chemical structures as decisive features but rather on the kinetics of redox reaction. A comprehensive electrochemical characterization of catechins and more advanced dedicated experiments are needed to fully understand whether the changes in DNA methylation level in the SRXN1 promoter might have been driven by the postulated redox-sensitive cellular response. The demonstrated increased DNA methylation of SRXN1 promoter region by EGC and ECG sheds new light on the epigenetic potential of catechins, which so far has been mainly associated with the impaired maintenance of global DNA methylation patterns as a result of DNMT1 activity inhibition. Our results revealed unexpected interrelations between otherwise seemingly independent phenomena (electrochemistry and epigenetics), indicating that novel, interdisciplinary research approaches are needed to define the cause-and-effect relationship for bioactive food components before their usefulness in epigenetic-based cancer chemoprevention becomes predictable.
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|
---
title: The Water Extract of Ampelopsis grossedentata Alleviates Oxidative Stress and
Intestinal Inflammation
authors:
- Zhaojie Wang
- Qian Jiang
- Pingping Li
- Panpan Shi
- Chao Liu
- Wenmao Wang
- Ke Huang
- Yulong Yin
- Peng Huang
journal: Antioxidants
year: 2023
pmcid: PMC10045513
doi: 10.3390/antiox12030547
license: CC BY 4.0
---
# The Water Extract of Ampelopsis grossedentata Alleviates Oxidative Stress and Intestinal Inflammation
## Abstract
Oxidative stress is recognized as a significant contributor to the development and progression of inflammation and disruptions in the balance of gut microflora, commonly referred to as intestinal dysbiosis. It is crucial that safe and effective antioxidant and anti-inflammatory agents are identified to address these conditions. Ampelopsis grossedentata, a natural plant abundant in flavonoids and primarily found in southern China, has demonstrated potent antioxidant properties. However, the extent to which flavonoids in A. grossedentata impact intestinal inflammation and alter the composition of the gut microbiome remains to be fully understood. The purpose of this study was to explore the potential benefits of using A. grossedentata as an antioxidant and anti-inflammatory agent in the context of intestinal inflammation, both in vitro and in vivo. We first conducted an initial comparison of the effects of dihydromyricetin (DMY), an alcohol extract of A. grossedentata (AEA, $82\%$ total flavonoids), and a water extract of A. grossedentata (WEA, $57\%$ total flavonoids) on the cell viability and intestinal barrier integrity of porcine epithelial cells IPEC-J2. Although the total flavonoid content is much lower in WEA than in AEA, the results show that they have similar effects. Subsequently, the antioxidant properties of WEA were compared with those of commonly utilized antioxidants in vitro. Lastly, the antioxidant and anti-inflammatory properties of WEA, as well as its impacts on gut microbiota, were evaluated in animal models, including mice and Drosophila. In summary, the results of our study indicate that WEA, due to its antioxidant properties, exhibits a protective effect on the intestinal barrier function in porcine epithelial cell line IPEC-J2. Additionally, WEA demonstrates a positive correlation with DPPH, ABTS radical scavenging rate, FRAP, and reducing power under in vitro settings. Furthermore, WEA was shown to effectively alleviate oxidative stress in animal models by reducing the levels of pro-inflammatory cytokines and increasing the antioxidant enzyme activity in the liver, as well as by activating the Nrf2 signaling pathway in the duodenum. Additionally, WEA was able to regulate gut microbiota, promoting the growth of beneficial bacteria and inhibiting harmful microbes, as well as extending the lifespan of Drosophila. Overall, these findings suggest that WEA may serve as a valuable dietary supplement for addressing oxidative stress and inflammation through its anti-inflammatory and prebiotic effects, which are conferred via the Nrf2/Keap1 pathway.
## 1. Introduction
Oxidative stress is caused by the overproduction of free radicals and reactive oxygen species (ROS), which leads to a decline in the body’s antioxidant defense ability [1]. Increased oxidative stress can cause cellular and tissue damage, resulting in the inability to resolve the inflammatory response, thereby leading to a chronic inflammatory state [2]. The status of oxidative balance plays an important role in maintaining the integrity of the intestinal mucosa through regulating its regeneration and repair [3]. Therefore, maintaining the structural integrity of the gut and reducing intestinal inflammation and oxidative stress play a key role in preserving the body’s health.
Plant secondary metabolites play an important role in human medicine and healthcare [4]. Therefore, many natural products have been widely used as antioxidant, antibacterial, and anti-inflammation agents [5]. Among the many available natural products, flavonoids are well-known antioxidant and anti-inflammatory substances that are now being used in the treatment and prevention of chronic diseases [6,7]. Ampelopsis grossedentata (Chinese name “Mei-Cha”), also called vine tea, is widely distributed in the southwest of China, and its young leaves have been used in beverages for centuries [8]. Previous studies have shown that A. grossedentata has a high content of total flavonoids and DMY, which are particularly enriched in dried leaves; as such, it is known as the “King of flavonoid-rich plants” [9]. Recently, it has been reported that A. grossedentata has a variety of pharmacological properties, and DMY has been identified as its principal medicinal substance, with antioxidant, anti-inflammatory, antibacterial, and hypoglycemic properties [10,11,12]. Previous studies have established that the activation of the nuclear factor-κB (NF-κB) signaling pathway is inseparable from the inflammatory response, and that the activation of the nuclear factor-E2-related factor 2 (Nrf2) signaling pathway can play an antioxidant role by promoting the expression of antioxidant enzymes in the body [13,14]. For example, studies have demonstrated that vine tea polyphenol activates the Nrf2-mediated expression of HO-1 and NQO1 [15]. However, details of the ability of the supplementation with A. grossedentata water extract to alleviate oxidative stress in vivo are not clear, and its target remains to be further confirmed [16]. Despite the fact that previous studies have demonstrated the ability of DMY to modulate the composition and interactions of gut microbiota, and the fact that the rat intestinal microbiota is responsible for the transformation of DMY into three specific metabolites [17], the underlying mechanisms and active ingredients responsible for the effects of berry tea on intestinal health and overall well-being remain unclear.
In the present study, we sought to clarify whether WEA alleviates oxidative stress and intestinal inflammation. First, the effects of DMY, AEA, and WEA on intestinal barrier function were investigated using an LPS-induced IPEC-J2 barrier damage model. Subsequently, the antioxidant performance of WEA was assessed via comparison with that of commonly used antioxidants in an in vitro environment. In addition, we also used an LPS-induced oxidative stress model in mice explore the molecular basis of the oxidative stress mitigation effect of WEA in depth, aiming to elucidate the mechanism by which it exerts this effect. Finally, we further explored the effects of WEA on the survival rate of Drosophila melanogaster using a paraquat-induced aging model.
## 2.1. Materials and Reagents
Dihydromyricetin (DMY, purity > $90\%$), an alcohol extract of A. grossedentata (AEA, total flavonoid content > $82\%$), and a water extract of A. grossedentata (WEA, total flavonoid content > $57\%$) were purchased from Hunan Qiankun Biological Technology Co. LTD., Zhangjiajie, China. Lipopolysaccharide (LPS), ferric-reducing antioxidant power (FRAP), tea polyphenols (TP), vitamin C (VC), N-acetylcysteine (NAC, anti-oxidant), and DEPC water were obtained from Beyotime Biotechnology. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) kits were purchased from Beijing Solarbio Science & Technology Co. Ltd. Methanol, potassium ferricyanide, trichloroacetic acid, ferric chloride, chloroform, isopropyl alcohol, and ethanol were provided by Sinopharm Chemical Reagent Co. Ltd., Shanghai, China. Paraquat was obtained from Chengdu Huaxia Chemical Reagent Co. Ltd. Interleukin 6 (IL-6), interleukin 1β (IL-1β), and tumor necrosis factor-alpha (TNF-α) ELISA kits were purchased from CHSABIO. Catalase (CAT) and the total antioxidant capability (T-AOC) kits were obtained from Beijing Boxbio Science & Technology Co. Ltd. IL-6, IL-1β, TNF-α, nuclear factor E2-related factor 2 (Nrf2), Kelch-like ECH-associated protein 1 (Keap1), and quinone oxidoreductase (NQO1) genes were purchased from Hunan Qingke Biotechnology Co. Ltd., Changsha, China. The TRIzol and RT Mix Kit with gDNA Clean for qPCR kits were provided by Accurate Biology. SYBR Green was obtained from Roche. Wild-type Drosophila w1118 was kindly provided by the Laboratory of Hunan Normal University. ICR mice and SPF chow were obtained from Changsha Tianqin Biotechnology Co. Ltd., Changsha, China. All chemicals were of analytically pure grade.
## 2.2. Cell Culture and Treatment
This study utilized porcine intestinal epithelial cells (IPEC-J2) obtained from the cell repository of Hunan Agricultural University. These cells were grown in Dulbecco’s modified Eagle’s medium containing $10\%$ fetal bovine serum at 37 °C in a $5\%$ CO2 atmosphere. The effects of WEA on the viability of IPEC-J2 cells were assessed through CCK-8 assays. The cells were treated with WEA and subsequently incubated for two hours at 37 °C, with the number of viable cells being determined by measuring absorbance at 450 nm using a microplate reader (TECAN, Infinite MPLEX, Mannedorf, Switzerland). The integrity of the IPEC-J2 cell monolayers was evaluated by assessing the transepithelial electrical resistance (TEER) and the permeation of fluorescein isothiocyanate-dextran 4 kDa (FITC-D4). The TEER was measured using an Epithelial Voltohmmeter (EVOM), while the FITC-D4 concentrations were determined by fluorimetry using a SpectraMax M2 microplate reader (TECAN, Infinite MPLEX, Mannedorf, Switzerland) at excitation and emission wavelengths of 485 and 530 nm, respectively.
## 2.3. In Vitro Antioxidant Activity
The measurement of the active ingredient content in WEA was undertaken using spectrophotometry. The total flavonoids, calculated as dihydromyricetin, were determined through a colorimetric assay utilizing aluminum trichloride and potassium acetate, with absorbance values measured at 294 nm. The polysaccharides, calculated as glucose, were determined through a colorimetric assay employing phenol and concentrated sulfuric acid, with absorbance values measured at 490 nm. The polyphenols, calculated as gallic acid, were determined through a colorimetric assay using forinol and sodium carbonate, with absorbance values recorded at 765 nm. Subsequently, standard curve equations were established, and the total flavonoids, polysaccharides, and polyphenols in WEA were calculated. Then, the antioxidant activity was evaluated using DPPH, ABTS, and FRAP free radical scavenging activity according to the manufacturer’s instructions. The absorbance was measured at 515, 405, and 505 nm with a microplate reader (TECAN, Infinite MPLEX, Mannedorf, Switzerland). The DPPH and ABTS radical scavenging ability was calculated as follows:DPPH scavenging rate = (A0 − As)/A0 × $100\%$ ABTS scavenging rate = (A0 − As)/A0 × $100\%$ A0 is the absorbance of the control sample, and As represents the absorption of WEA or other standards.
The reducing power of WEA was determined via a method previously established by Oyaizu [18] with minor modifications. The samples WEA and TP were separately prepared at concentrations of 0.125, 0.25, 0.5, 1, 2, and 4 mg/mL and mixed with 300 μL potassium ferricyanide (0.01 g/mL). After 30 min of incubation at 50 °C in the dark, 300 μL trichloroacetic acid (0.1 g/mL) was added to stop the reaction; the tubes were then centrifuged at 3000 r/min for 15 min. Then, 300 μL of supernatant was mixed with 300 μL of distilled water and 100 μL aqueous ferric chloride (0.1 g/100 μL) solution. The absorbance was measured at 700 nm with a microplate reader (TECAN, Infinite MPLEX).
## 2.4. Animals and Drug Administration
The study was approved by the Animal Ethical Committee of Hunan Agricultural University. Forty-eight adult male ICR mice were maintained on a standard diet and water ad libitum. The mice were housed in a controlled environment with a consistent temperature, humidity, and light–dark cycle. After acclimatizing for one week, the mice were randomly divided into six groups ($$n = 8$$) (Figure 1), including the positive control (NAC) group, which was administered N-acetylcysteine (NAC) at a dose of 300 mg/kg/day [19]; the blank (control) and model (LPS) group, which was administered saline by oral gavage; and the low-, medium-, and high-dose WEA (WEA-L, WEA-M, WEA-H) groups were administered WEA at concentrations of 50, 100, and 200 mg/kg/day, respectively. To evaluate the safety and efficacy of WEA, fresh fecal samples were collected at the end of the experimental period and stored at −80 °C for subsequent analysis. On the 22nd day, the control group was intraperitoneally administered PBS, while the other groups, which had received LPS, NAC, and WEA, were administered lipopolysaccharide (LPS) at a dose of 10 mg/kg [20]. Subsequently, fresh fecal samples were collected from the model group. At the end of the treatment period, after a 6 h fast, the mice were weighed, and blood was collected from their eyes. The mice were then sacrificed, and the serum, liver, duodenum, jejunum, ileum, and intestinal contents were rapidly collected and stored at −80 °C for further biochemical analysis.
Subsequently, the concentrations of IL-6, IL-1β, and TNF-α in serum and T-AOC and CAT in the liver were analyzed utilizing appropriate diagnostic kits as per the manufacturer’s protocols. Total RNA was extracted from liver and duodenum tissue samples using TRIzol reagent and quantified using a Ultramicro ultraviolet spectrophotometer (Thermo Fisher, NanoDrop One, Shanghai, China). The extracted RNA was then converted to cDNA via reverse transcription utilizing the RT Mix Kit with gDNA Clean for qPCR kits. RT-qPCR was performed using SYBR Green, and the relative mRNA expression of the target genes was calculated with GAPDH as the internal control. The primer sequences are provided in Table S1.
## 2.5. Histological Analysis
The liver, duodenum, jejunum, and ileum fixed in $4\%$ formaldehyde were used to determine morphology using hematoxylin–eosin staining. After dehydration, embedding, sectioning, and staining, the liver, duodenum, jejunum, and ileum were observed with a microscope. The villus height and crypt depth were measured using Case Viewer software 2.4.0.
## 2.6. Gut Microbiota Analysis
The microbial DNA present in the feces was extracted using an E.Z.N.A. Stool DNA Kit, and its purity was confirmed through $2\%$ agarose gel electrophoresis. The pair-end library was constructed as per Illumina’s genomic DNA library preparation guidelines, using the NEXTFLEX Rapid DNASeq Kit. The compositions of the microbial communities present in the intestinal contents and feces samples were determined through 16S rDNA sequencing, carried out by Meiji Biological Co. Ltd. The amplicons were then sequenced on the Illumina MiSeq PE300 platform, utilizing the MiSeq Reagent Kit v3.
## 2.7. The Drosophila Lifespan Test
The Drosophila Lifespan Test of WEA adhered to a previous method with minor modifications [21,22,23]. For this test, Drosophila wild-type w1118 strain was utilized to evaluate the lifespan. The experiments were conducted under controlled conditions at 25 °C and a 12 h light–dark cycle. A sample of 180 healthy Drosophila individuals was selected and divided into four groups: the control group, the 0.1 mg/mL VC group, and groups treated with WEA at doses of 0.05 and 0.2 mg/kg. The experimental design was replicated in triplicate, with each group consisting of 15 Drosophila individuals per food vial. The food vials were replaced every other day. After a period of three days, the Drosophila were treated with 6 mM paraquat. The survival of the Drosophila was subsequently monitored and recorded at 0, 12, 15, 18, 21, 24, and 36 h. The lifespan curves were plotted for each group, and statistical analyses were performed to determine the mean lifespan, $50\%$ survival rate, and maximum lifespan of the Drosophila. The maximum lifespan was calculated as the mean lifespan of the longest surviving $10\%$ of Drosophila individuals.
## 2.8. Statistical Analysis
All experimental data were expressed as the mean ± standard error of the mean (SEM). The data were analyzed using IBM SPSS Statistics 23 and GraphPad Prism 9.0 software. Differences in the experimental groups were determined using the one-way analysis of variance (ANOVA). $p \leq 0.05$ was deemed a significant difference.
## 4. Discussion
In China, vine tea is a plant resource with both medicinal and edible properties, and it is known to possess a high flavonoid content [26]. One of its key flavonoid components is dihydromyricetin, which carries a range of biological functions. Previous research has shown a positive correlation between the flavonoid content and antioxidant effect [15,27]. However, the poor water solubility of DMY results in its low membrane permeability and bioavailability, limiting the widespread use of vine tea. As a result, in this study, the use of WEA was investigated as a means to enhance its antioxidant function and improve its bioavailability.
In this study, first, the cell assay results indicate that AEA and WEA, but not DMY, could reverse LPS-induced intestinal IPEC-J2 cell barrier dysfunction, with WEA demonstrating a more pronounced effect than AEA, which is in line with the findings of previous studies [28]. Additionally, the antioxidant activity of WEA was evaluated using four different in vitro assays, including DPPH, ABTS, FRAP, and reducing power. These assays are commonly used to measure the antioxidant activity. The results of this study are consistent with those of previous research [27]. Despite the positive results obtained through in vitro studies, it is important to note that the DPPH, ABTS, FRAP, and reducing power assays are limited models that do not take into account all of the antioxidant activities present in WEA. Furthermore, driven by these encouraging results, and given the diverse range of biological activities (such as antioxidant, anti-inflammatory, antitumor, antidiabetic, neuroprotective, and others) assigned to certain components of WEA, the further testing of WEA was conducted in vivo using mouse models [29].
Previous research has demonstrated that the flavonoid component DMY in WEA has the potential to ameliorate LPS-induced sickness and depressive-like behaviors in mice by inhibiting the TLR4/Akt/HIF1a/NLRP3 pathway [30]. Additionally, other studies have shown that the DMY has the ability to inhibit osteoclastogenesis and bone loss through scavenging LPS-induced oxidative stress and activating the NF-KB and MAPK pathways [31]. Furthermore, it has been discovered that vine tea, which contains WEA, can suppress the NF-kB signal pathway, thereby alleviating DSS-induced colitis [32]. Moreover, research has indicated that DMY can inhibit the expression of pro-inflammatory cytokines via activating the Nrf2 pathway in the RA model [33]. In the present study, we further investigated the molecular mechanism of WEA in relation to oxidative stress by establishing an inflammation model via LPS injection into the intraperitoneal area and then studying the effects of WEA. The results indicate that WEA administration significantly reduces the levels of IL-6, IL-1β, TNF-α, and T-AOC and increases the contents of CAT, which are markers of oxidative stress and inflammation used to indicate the presence of cellular damage.
The Nrf2/Keap1 signaling pathway plays a crucial role in the defense against oxidative and electrophilic stress, which can arise from both endogenous and exogenous sources [34]. The Keap1 protein mediates the ubiquitination and degradation of Nrf2 in both the cytoplasm and nucleus. Under normal physiological conditions, Keap1 binds to Nrf2 and targets it for proteasomal degradation [35], however, under conditions of oxidative stress, Nrf2 is released from Keap1 and translocates to the nucleus, where it binds to antioxidant response elements (AREs) or electrophile response elements (EpREs) to activate the transcription of downstream genes [36]. There is a growing body of evidence that suggests that various drugs can inhibit oxidative stress and inflammation by activating the Nrf2/Keap1 pathway. For instance, cardamonin, a natural flavone, has been shown to alleviate inflammatory bowel disease by inhibiting NLRP3 inflammasome activation through the Nrf2/NQO1 pathway [37]; chlorogenic acid, a polyphenolic, ameliorates oxidative stress and improves endothelial function in diabetic mice via Nrf2 activation [38]; pterostilbene suppresses oxidative stress and allergic airway inflammation through AMPK/Sirt1 and Nrf2/HO-1 pathways [39]. In the current study, we found that WEA administration significantly elevates the expression of Nrf2 and downstream antioxidants, such as NQO1, and decreases the expression of pro-inflammatory cytokines IL-1β and TNF-α resulting from LPS-induced oxidative stress in mice. Additionally, WEA effectively alleviates pathological damage to the liver and intestinal epithelium as well as increases the villus height and V/C in the duodenum, jejunum, and ileum. These effects may be due to the presence of flavonoids and DMY in WEA.
Increasing evidence suggests that oxidative stress and the gut microbiota are frequently linked [40,41,42]. Therefore, we explored the gut contents and fecal microbiota composition using 16S rRNA sequencing and evaluated oxidative stress-related intestinal bacterial indicators. In our study, in the gut contents, microbial growth differed between the different groups. In terms of alpha diversity, the LPS group presented significantly higher values of Shannon and ACE indices. According to the results, it appears that the presence of LPS has a discernible effect on the diversity and composition of the microbial population within the intestinal tract. This observation is consistent with a significant body of previous research that has also demonstrated this phenomenon [43,44,45,46,47]. LPS, which are commonly found in the cell wall of Gram-negative bacteria, have been shown to elicit significant alterations in the composition and structure of the gut microbiota. The dysregulation of gut microbial homeostasis due to LPS exposure can have significant impacts on the host’s physiology and health. This disruption in the microbial community’s balance can lead to the proliferation of pathogenic bacteria and the production of harmful metabolites. The resulting changes in the microbial composition and diversity can increase the permeability of the intestinal barrier, allowing the translocation of these noxious agents across the epithelial lining. This can trigger an inflammatory response and further damage the gastrointestinal system, exacerbating the impact on the host’s well-being. Therefore, maintaining a healthy gut microbial ecosystem is crucial for preserving the host health and preventing the onset of disease. In contrast, the WEA-H group showed converse results, indicating that oxidative stress and WEA significantly influence the diversity of the gut microbiota. Meanwhile, our results are in agreement with those of previous studies [17]. The PLS-DA analysis also indicated that, in all groups, the compositions of the gut microbiota were distinct, which further indicates that the gut microbiota reacts differently to different oxidative stresses.
In contrast, the WEA-H group showed converse results, indicating that oxidative stress and WEA significantly influence the diversity of gut microbiota. Meanwhile, our results are in agreement with those of previous studies [17]. The PLS-DA analysis also indicated that in all groups, the compositions of the gut microbiota were distinct, which further indicates that the gut microbiota reacts differently to different oxidative stresses.
In order to clarify how WEA reshapes the gut microbiota composition, comparisons of the relative abundances in differently treated groups were conducted. At the phylum level, the LPS group showed a lower abundance of Firmicutes and Bacteroidetes. In contrast, the WEA treatment was able to reshape the composition of the disordered gut microbiota. Traditionally, the F/B ratio, as the most important ratio in microbiome studies, may reflect the eubiosis or dysbiosis of the GI tract and is regarded as a representative parameter of health status [48]. However, in the present study, there was no significant difference in the F/B ratio between the groups. In addition, the abundance of Lactobacillus was higher and the abundance of norank_f__Muribaculaceae was lower in intestinal digesta following the WEA treatment. Lactobacillus has been recognized as a beneficial factor that can reduce intestinal toxins, control the growth of pathogens, and alleviate inflammation responses [49]. Norank_f__Muribaculaceae is thought to be associated with ecological imbalance [50]. Moreover, current research shows that Lactobacillus in the intestinal digesta is positively associated with the expression of the *Keap1* gene in the duodenum, and negatively correlated with the expression of IL-1β and IL-6 in the liver, as well as the expression of IL-1β and TNF-α in the duodenum, and norank_f_Muribaculaceae in the intestinal digesta was positively correlated with the expression of TNF-α in the duodenum. However, in the correlation analysis, WEA was not found to have a significant impact on the fecal microbiota of the studied mice. This may be because the fecal samples of other groups, except for the LPS group, were collected before LPS injection. Therefore, we conclude that WEA has no negative effect on intestinal flora, and WEA is safe and reliable. The above results indicate that WEA may boost the growth of beneficial bacteria and inhibit the propagation of harmful bacteria, thus alleviating oxidative stress, which may have an inhibitory effect on the proliferation of inflammatory factors and the recovery of liver function.
According to the LEfSe analysis, different biomarkers in mice treated with WEA also confirmed that WEA can change the composition of gut microbiota, which showed varying oxidative stress responses. In this research, the gut microbiota in the WEA group presented higher abundances of beneficial bacteria and lower abundances of pathogenic bacteria. Additionally, in another study, LBLF therapy significantly restored the gut dysfunction brought on by a high-fat diet, altering the composition of the gut bacterial community by increasing the presence of beneficial microbiota and reducing harmful bacteria [51]. The results indicate that LPS disrupts the homeostasis of gut microbiota and WEA tends to limit the reproduction of pathogenic bacteria. Emerging evidence indicates that the flavonoid-rich A. tenuissimum flower could remedy glycolipid metabolic disorders and inflammation in diabetic mice by modulating protein expression and gut microbiota [52]. In another study, DMY was shown to reduce the hepatic lipid synthesis and inflammation through the modulations of gut microbiota [53].
Drosophila melanogaster (fruit fly) is an excellent model because of its short lifespan and the ease with which it can be grown. As a result, we finally investigated the antioxidant activity of WEA in Drosophila. The results are similar to those of the above experiments, indicating that WEA can increase the lifespan of Drosophila, thus further demonstrating its antioxidant properties.
Regrettably, our study also has some limitations. For example, the sample size is relatively small, and research on mechanisms (relevant experiments, Western blot analysis) was not carried out due to the lack of tissue samples. Although we analyzed WEA’s ability to alleviate oxidative stress and intestinal inflammation, the exact monomer that plays this role needs to be further identified. In addition, although we determined that gut microbiota may also be involved in the alleviation of oxidative stress, further in-depth studies with fecal transplantation are needed to confirm the regulatory role of microbiota. In future studies, all these factors will be considered and addressed.
## 5. Conclusions
In summary, our in vitro results indicate that WEA can reverse LPS-induced IPEC-J2 cell intestinal barrier dysfunction, and within a certain range, the mass concentration of WEA is directly proportional to the DPPH and ABTS radical scavenging rate as well as the FRAP and reducing power. We sought to further investigate the molecular mechanism of WEA’s action on oxidative stress using LPS-induced mice as a model. According to this study, WEA alleviates oxidative stress by regulating the Nrf2/Keap1 pathway, thereby suppressing the inflammatory response. In addition, WEA not only significantly impacts the diversity of gut microbiota but may also boost the growth of beneficial bacteria and inhibit the propagation of harmful bacteria. We assume that the beneficial effects of WEA on oxidative stress might be mediated by changes in the gut microbiota. On the other hand, WEA also exhibited strong antioxidant capacity in the Drosophila assays. The above results suggest that WEA is a promising option for remedying oxidative stress. However, the efficacy and safety of WEA are worth investigating in clinics in the future. Therefore, based on our results, a more in-depth study should be carried out to explore the consequences of altered gut microbiota, such as whether it results in alterations in the production of endogenous metabolites such as SCFA, enhanced gastrointestinal immunity, improved gut barrier function, inhibited development of inflammation, or whether it can prevent the occurrence of disease.
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|
---
title: 'The characteristics of elevated blood pressure in abdominal obesity correspond
to primary hypertension: a cross-sectional study'
authors:
- Jyrki Taurio
- Elina J. Hautaniemi
- Jenni K. Koskela
- Arttu Eräranta
- Mari Hämäläinen
- Antti Tikkakoski
- Jarkko A. Kettunen
- Mika Kähönen
- Onni Niemelä
- Eeva Moilanen
- Jukka Mustonen
- Ilkka Pörsti
journal: BMC Cardiovascular Disorders
year: 2023
pmcid: PMC10045516
doi: 10.1186/s12872-023-03150-w
license: CC BY 4.0
---
# The characteristics of elevated blood pressure in abdominal obesity correspond to primary hypertension: a cross-sectional study
## Abstract
### Background
Obesity-related hypertension and the associated metabolic abnormalities are considered as a distinct hypertensive phenotype. Here we examined how abdominal fat content, as judged by waist:height ratio, influenced blood pressure and hemodynamic profile in normotensive subjects and never-treated hypertensive patients.
### Methods
The 541 participants (20–72 years) underwent physical examination and laboratory analyses and were divided into age and sex-adjusted quartiles of waist:height ratio. Supine hemodynamics were recorded using whole-body impedance cardiography, combined with analyses of radial tonometric pulse wave form and heart rate variability.
### Results
Mean waist:height ratios in the quartiles were 0.46, 0.51, 0.55 and 0.62. Radial and aortic blood pressure, systemic vascular resistance, pulse wave velocity, markers of glucose and lipid metabolism, leptin levels and C-reactive protein were higher in quartile 4 when compared with quartiles 1 and 2 ($p \leq 0.05$ for all). Cardiac index was lower in quartile 4 versus quartile 1, while no differences were seen in heart rate variability, augmentation index, plasma renin activity, and aldosterone concentration between the quartiles. Linear regression analyses showed independent associations of abdominal obesity with higher aortic systolic and diastolic blood pressure, systemic vascular resistance, and pulse wave velocity ($p \leq 0.05$ for waist:height ratio in all regression models).
### Conclusion
Higher waist:height ratio was associated with elevated blood pressure, systemic vascular resistance, and arterial stiffness, but not with alterations in cardiac sympathovagal modulation or activation of the circulating renin-angiotensin-aldosterone system. Although obesity-related elevation of blood pressure has distinct phenotypic features, these results suggest that its main characteristics correspond those of primary hypertension.
### Trial registration
ClinicalTrails.gov NCT01742702 (date of registration 5th December 2012).
## Background
Obesity is a major global health risk, and the prevalence of obesity has doubled since 1980 [1]. In 2015, high body mass index (BMI) was estimated to account for 4 million deaths predominantly from cardiovascular diseases [1]. BMI has been the gold standard in the estimation of excess body fat, but it does not discriminate between fat and fat-free mass, which may lead to flawed results on body composition [2]. In 1996, Ashwell et al. reported that the correlation between tomography-measured intra-abdominal fat with BMI was 0.69, but for waist:height ratio (WHtR) the correlation was 0.83 ($p \leq 0.001$ for the difference). WHtR was concluded to be the better anthropometric predictor of intra-abdominal fat in both sexes [2]. High waist circumference that indicates excess abdominal fat content is also a predictor of future hypertension [3].
Excess visceral fat is associated with changes in glucose and lipid homeostasis that predispose to the development of hypertension [4]. Increased perivascular fat content and the associated changes in synthesis and release of adipokines may influence the recruitment of inflammatory cells in the vasculature, vascular smooth muscle proliferation, and the control of arterial tone [5]. Obesity related adipokines like leptin have been linked with several cardiovascular risk factors, but previous results about the association of leptin with arterial stiffness are inconsistent [6, 7]. Impaired endothelial function and increased arterial stiffness have been associated with obesity [8]. Elevated sympathovagal balance [9] and upregulation of the renin-angiotensin-aldosterone system (RAAS) [10] may also contribute to the cardiovascular changes in obesity. Obese subjects may have increased cardiac output, while systemic vascular resistance may be low in obese normotensives and normal or elevated in obese hypertensives [11].
Although the underlying mechanisms are not completely understood, elevated blood pressure (BP) in obese subjects is considered to have distinct phenotypic features [9, 12]. Obesity predisposes to impaired nocturnal BP dipping, increased prevalence of masked hypertension, higher exercise related increase in systolic BP, and treatment resistant hypertension [13]. However, when compared with essential hypertension, no definite instructions for the treatment of obesity-related hypertension in addition to weight reduction are included in the guidelines regarding e.g. the choices of antihypertensive medications [13].
To evaluate the hemodynamic features associated with abdominal obesity, we examined the influence of visceral fat content, defined as WHtR, on BP and hemodynamic profiles in normotensive and previously undiagnosed hypertensive subjects without antihypertensive medications. Cardiac autonomic modulation was evaluated utilizing analyses of heart rate variability (HRV).
## Study subjects
The participants were recruited as previously described [14, 15]. All underwent physical examination and laboratory analyses for elevated BP [16]. Medical history and lifestyle habits including alcohol consumption and smoking were documented. Subjects with a history of coronary artery disease, stroke, cardiac failure or valve disease, heart rhythm other than sinus, chronic kidney disease, diabetes, secondary hypertension, alcohol or substance abuse, and psychiatric illnesses other than mild depression or anxiety were excluded.
Altogether 541 participants, aged 20–72 years, without antihypertensive medications were included. They were divided into age-adjusted quartiles of WHtR separately for sexes. The following medications were regularly used by the participants with no significant differences between the quartiles of WHtR: female hormones (contraception, hormone replacement therapy, $$n = 67$$), intrauterine hormonal device for contraception ($$n = 29$$), antidepressants ($$n = 25$$), vitamin-D supplements ($$n = 31$$), thyroxin ($$n = 16$$), inhaled glucocorticoids ($$n = 14$$), antihistamines ($$n = 12$$), statins ($$n = 11$$), proton pump inhibitors ($$n = 9$$), nonsteroidal anti-inflammatory agents ($$n = 4$$), anxiolytic agents ($$n = 4$$), allopurinol ($$n = 2$$), antiepileptics ($$n = 2$$), coxibs ($$n = 2$$), varenicline ($$n = 2$$), gabapentin or pregabalin ($$n = 2$$), warfarin ($$n = 1$$).
Signed informed consent was obtained from all participants. The study complies with the Declaration of Helsinki and was approved by the Ethics Committee of the Tampere University Hospital (study code R06086M) and the Finnish Medicines Agency (Eudra-CT registration number 2006-002065-39) and was registered in a database (ClinicalTrails.gov NCT01742702).
## Laboratory analyses
Blood and urine samples were drawn after ~ 12 h of fasting. Concentrations of leptin and adiponectin in plasma samples were determined using enzyme-linked immunosorbent assay (DuoSet ELISA; R&D Systems Europe Ltd, Abingdon, United Kingdom). Interassay coefficient of variation was $4.0\%$ for leptin and $3.9\%$ for adiponectin. The other laboratory analyses were performed as described previously in detail [15, 17].
## Experimental protocol
Hemodynamics were recorded as described previously [14, 15]. Electrodes for impedance cardiography placed on body surface, tonometric sensor on left radial pulsation, and oscillometric cuff to the right upper arm. The left arm was fixed to 90 degrees in a support. Hemodynamic data was captured continuously for 5 min, and mean values of each 1-minute period were calculated. The good repeatability and reproducibility of the measurements has been demonstrated [14, 15].
## Pulse wave analysis
As in our previous reports, radial pulse wave form was continuously captured using a tonometric sensor (Colin BP-508T, Colin Medical Instruments Corp., USA) [14, 16]. Aortic BP was derived with the SphygmoCor system (SpygmoCor PWMx, Atcor Medical, Australia) [18]. Aortic pulse pressure, augmentation index (AIx, augmented pressure/pulse pressure*100), AIx adjusted to heart rate 75/min (AIx@75), and central forward wave amplitude were determined [19]. Large arterial compliance was evaluated as the ratio of stroke volume to aortic pulse pressure [20].
## Whole-body impedance cardiography
Whole-body impedance cardiography (CircMonR, JR Medical Ltd., Tallinn, Estonia) was used to determine heart rate, stroke volume, cardiac output, pulse wave velocity (PWV), and extracellular water balance, as previously described [21–23]. Systemic vascular resistance was calculated from the tonometric BP and cardiac output by CircMonR. Stroke volume, cardiac output and systemic vascular resistance were related to body surface area and presented as indexes – SI, CI, and SVRI, respectively. The measured stroke volume and cardiac output values are in good agreement with 3-dimensional echocardiography [15] and the thermodilution and direct oxygen Fick methods [21], and the recorded PWV values show good correlation with ultrasound and tonometric values [22, 24].
## Frequency domain analysis of heart rate variability
Recorded electrocardiograms (sampling rate 200 Hz) were analyzed using Matlab (MathWorks Inc., Natick, Massachusetts, USA). Normal R-R intervals were recognized, and a beat was considered ectopic if the interval differed > $20\%$ from previous values. Artefacts were processed using cubic spline interpolation method, and the frequency domain variables were calculated using Fast Fourier Transformation: (i) power in low frequency (LF) range (0.04–0.15 Hz), (ii) power in high frequency (HF) range (0.15–0.40 Hz), and (iii) LF/HF ratio [25].
## Statistics
Analysis of variance was applied for normally distributed variables and the Kruskal-Wallis and Mann-Whitney U-tests for non-normally distributed variables. The Bonferroni correction was applied in all post-hoc analyses. IBM SPSS Statistics Version 26 (IBM Corporation, Armonk, NY, USA) was used. The mean hemodynamic values from the minutes 3–5 were used when the signal was most stable. The LF power, HF power, and LF/HF ratio were transformed to natural logarithm for statistics due to skewed distributions, and the analyses were adjusted for heart rate [26]. The participants were divided to age-adjusted quartiles (Q) of WHtR separately for sexes.
Stepwise linear regression analyses were used to investigate factors associated with aortic systolic and diastolic BP, SVRI, and PWV. Smoking was categorized (current smokers, previous smokers, never smokers) using two discrete variables, alcohol consumption using three discrete variables (category either 0 or 1); cut-points for women 0, 1–7 (low), 8–14 (moderate), and ≥ 15 doses per week (high); for men 0, 1–14, 15–24, and ≥ 25 doses per week, respectively, according to the Finnish Guidelines [27]. The regression analyses included age, sex, WHtR, smoking status, categorized alcohol intake; plasma leptin, adiponectin, C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, sodium, calcium, parathyroid hormone (PTH), uric acid, renin activity, aldosterone; quantitative insulin sensitivity check index (QUICKI) [28] and estimated glomerular filtration rate (eGFR) as independent factors. In the analyses of aortic systolic and diastolic BP the model also included PWV, and in analyses of PWV the model also included mean aortic blood pressure. $P \leq 0.05$ was considered significant.
## Study population and laboratory values
Mean weight, waist circumference, and BMI were different in all quartiles of WHtR (Table 1). The difference in adiposity was substantial, as BMI was 9.0 (0.3) kg/m2 [mean (standard error)] higher in Q4 than in Q1. Mean BMI in the study participants was 26.8 (0.2) kg/m2. The Spearman correlation between WHtR and BMI was 0.895. Average height was slightly lower in Q4 of WHtR than in Q1 (Table 1).
Table 1Study participants shown in age adjusted quartiles (Q) of waist:height ratioVariableQ1 ($$n = 132$$)Q2 ($$n = 137$$)Q3 ($$n = 138$$)Q4 ($$n = 134$$)Range (all quartiles)Male / Female68 / 6471 / 6671 / 6768 / 66Age (years)44.7 (12.4)45.4 (11.6)45.8 (11.0)45.4 (11.4)20–72Waist:height ratio0.46 (0.04)0.51 (0.04)*0.55 (0.04)*†0.62 (0.05)*†‡0.38–0.76Weight (kg)70.6 (12.7)76.5 (13.6)*82.1 (12.2)*†94.1 (15.0)*†‡45–135Waist circumference (cm)80.2 (9.6)88.4 (10.1)*95.6 (8.4)*†106.5 (10.1)*†‡63.0-132.0Body mass index (kg/m2)22.8 (2.5)25.1 (2.5)*27.4 (2.6)*†31.9 (3.7)*†‡17.9–42.1Height (cm)175.0 (10.0)173.8 (9.6)172.8 (8.2)171.5 (9.0)*150–203Current smokers (%)1210151310–15Alcohol (standard drinks/week)2 [1–4]2 [1–5]2 [1–7]3 [1–7]0–42Office systolic BP (mmHg)134 [20]137 [20]142 [22]*149 [20]*†100–216Office diastolic BP (mmHg)85 [11]86 [11]90 [13]*†95 [13]*†‡54–135Extracellular water balance1.00 (0.09)0.98 (0.10)0.96 (0.09)*0.97 (0.09)*0.63–1.55Results shown as mean (standard deviation) or median [25th -75th percentile]; *$P \leq 0.05$ vs. Q1; †$P \leq 0.05$ vs. Q2; ‡$P \leq 0.05$ vs. Q3 No differences were observed in the prevalence of smoking and average alcohol intake between the quartiles of WHtR. Office systolic BP was higher in Q3 than in Q1, and in Q4 than in Q2 and Q1 (Table 2). The difference in office systolic BP between Q4 vs. Q1 was 15 [3] mmHg. Office diastolic BP was highest in Q4, and higher in Q3 than in Q2 and Q1. The difference in office diastolic BP between Q4 vs. Q1 was 10 [1] mmHg. Extracellular water balance was lower in Q3 and Q4 than in Q1 (Table 1).
Table 2Clinical characteristics and laboratory results in age adjusted quartiles (Q) of waist:height ratioVariableQ1Q2Q3Q4Range (all quartiles)Hemoglobin (g/l)142 [12]144 [12]146 [11]145 [12]113–177Sodium (mmol/l)140.7 (2.0)140.2 (2.1)140.3 (1.9)140.3 (1.9)134–146Potassium (mmol/l)3.82 (0.27)3.75 (0.26)3.83 (0.26)3.85 (0.30)†3.2–4.9Calcium (mmol/l)2.30 (0.11)2.29 (0.10)2.32 (0.12)2.30 (0.10)2.07–2.74Parathyroid hormone (pmol/l)4.4 (1.7)4.3 (1.4)4.5 (1.6)5.0 (2.1)*†‡1.4–9.9 C-reactive protein (mg/l)0.6 [0.5-1.0]0.6 [0.5–1.3]1.0 [0.5–1.7]*1.9 [0.8–3.1]*†‡0.1–17.9Uric acid (µmol/l)277 [73]287 [72]313 [76]*†328 [77]*†103–600Creatinine (µmol/l)76 [14]75 [14]74 [13]71 [14]*42–116Cystatin C (mg/l)0.82 (0.14)0.82 (0.16)0.86 (0.14)*0.87 (0.13)*†0.47–1.31Estimated GFR (ml/min/1.73m2)102 [17]102 [19]97 [18]96 [17]*53–152Leptin (ng/ml)8.6 (8.5)12.1 (9.2)15.9 (12.8)*28.0 (20.1)*†‡0.2–92.3Adiponectin (µg/ml)4.3 (2.4)3.9 (1.6)3.4 (1.7)*3.5 (1.7)*0.5–18.2Renin activity (ng Ang I/ml/h)0.8 [0.5–1.3]0.8 [0.4–1.3]0.7 [0.4–1.3]0.6 [0.4–1.1]0.1–10.0Aldosterone (pmol/l)436 [306–636]434 [329–581]459 [338–595]416 [304–539]68-1704Aldosterone:renin ratio597 [398–791]634 [383–884]640 [430–948]632 [389–979]45-2701Fasting plasma Total cholesterol (mmol/l)4.9 (1.0)4.9 (1.0)5.3 (1.1)*†5.4 (1.0)*†2.5-9.0 Triglycerides (mmol/l)0.9 [0.6–1.2]1.0 [0.7–1.3]1.1 [0.8–1.5]*1.2 [1.0–2.0]*†0.3–5.5 HDL cholesterol (mmol/l)1.8 (0.5)1.6 (0.4)*1.5 (0.4)*1.4 (0.4)*†0.7–3.1 LDL cholesterol (mmol/l)2.8 (0.9)2.8 (0.9)3.2 (0.9)*†3.3 (0.9)*†0.8–5.8 Insulin (mU/l)6.0 (3.6)6.9 (4.7)8.2 (5.3)*11.5 (7.9) *†‡1.0-51.8 Glucose (mmol/l)5.3 (0.5)5.4 (0.5)5.5 (0.5)*5.7 (0.8)*†‡4.1–7.5QUICKI0.380 (0.056)0.366 (0.036)*0.354 (0.032)*0.338 (0.033)*†‡0.268–0.740Results shown as mean (standard deviation) or median [25th -75th percentile]; BP, blood pressure; estimated GFR, estimated glomerular filtration rate based on cystatin C (CKD-EPI) [45]; QUICKI, quantitative insulin sensitivity check index [28]; *$P \leq 0.05$ vs. Q1; †$P \leq 0.05$ vs. Q2; ‡$P \leq 0.05$ vs. Q3 Average blood hemoglobin and plasma concentrations of sodium, potassium, and calcium were within the normal range in all quartiles (Table 2). Plasma PTH and CRP were highest in Q4, while uric acid was higher in Q3 and Q4 than in Q1 and Q2. Creatinine and cystatin C concentrations presented with minor differences between the quartiles, while eGFR derived from cystatin C was slightly lower in Q4 than in Q1. Less than $4\%$ of the subjects presented with values of the above variables that were outside the normal range (Table 2).
Plasma leptin concentration was clearly highest in Q4, and higher in Q3 than in Q1, while adiponectin was lower in Q3 and Q4 than in Q1. Plasma renin activity, aldosterone concentration, and aldosterone:renin ratio did not differ between the quartiles (Table 2).
Q3 and Q4 of WHtR had less favorable lipid profiles than Q1 and Q2. Plasma total cholesterol, LDL cholesterol, and triglycerides were above the normal range in $53\%$, $47\%$, and $15\%$ of the subjects, respectively. Plasma HDL cholesterol was below the normal range in $9\%$ of the subjects. Fasting plasma insulin and glucose were higher in Q3 than in Q1, while both insulin and glucose were highest in Q4. Insulin was above the normal range in $2\%$ and glucose in $13\%$ of the participants. Based on QUICKI, insulin sensitivity was highest in Q1 and lowest in Q4 (Table 2).
## Blood pressure, arterial stiffness, cardiac variables, and heart rate variability
Radial systolic and diastolic BP were elevated in Q4 when compared with Q1 and Q2 (Fig. 1A and B). Aortic systolic BP was higher in Q3 when compared with Q1, and aortic systolic and diastolic BP were higher in Q4 than in Q1 and Q2 (Fig. 1 C and 1D). The difference in aortic systolic / diastolic BP between Q4 vs. Q1 was 11 [2] / 7 [2] mmHg.
Fig. 1Radial systolic (A) and diastolic (B) blood pressure, and aortic systolic (C) and diastolic (D) blood pressure during laboratory measurements in 541 subjects divided separately for sexes into age-adjusted quartiles of waist/height ratio; mean ± confidence interval of the mean; significant differences shown between groups ($P \leq 0.05$) Aortic pulse pressure and forward wave amplitude were higher in Q4 than in Q1 and Q2 (Fig. 2A and B). Evaluated aortic compliance (stroke volume to central pulse pressure ratio) was lower in Q4 than in Q1 and Q2 (Fig. 2C), while aortic to popliteal PWV was higher in Q4 than in Q1 and Q2, and in Q3 than in Q1 (Fig. 2D). The difference in PWV between Q4 vs. Q1 was 1.0 (0.2) m/s. No differences were observed in AIx or AIx@75 (Fig. 2E F).
Fig. 2Aortic pulse pressure (A), forward wave amplitude (B), stroke volume to aortic pulse pressure ratio (C), pulse wave velocity (D), augmentation index (E), and augmentation index adjusted to heart rate of 75 beats per minute (bpm) (F); statistics as in Fig. 1 Heart rate was higher in Q4 than in Q1 and Q2 (Fig. 3A), while SI was different in all other quartiles but not between Q2 and Q3 (Fig. 3B). CI was lower in Q4 than Q1 (Fig. 3C), while SVRI was higher in Q4 than in Q1 and Q2, and in Q3 than in Q1. The difference in SVRI between Q4 vs. Q1 was 391 [71] dyn*s/cm5*m2 (Fig. 3D).
Fig. 3Heart rate (A), stroke index (B), cardiac index (C), systemic vascular resistance index (D) in 541 subjects; statistics as in Fig. 1 The HRV measurements consisted of LF and HF power and LF/HF ratio determinations (Fig. 4). No differences were observed between the quartiles in these analyses.
Fig. 4Box plots show heart rate variability in age-adjusted quartiles of waist/height ratio divided separately for sexes. Low frequency (LF) power (A), high frequency (HF) power (B), and LF/HF ratio (C); median (thick line inside box), 25th -75th percentile (box), range (whiskers); outliers were omitted from the figures but were included in the statistics with logarithmically transformed values
## Regression analyses of hemodynamic variables
The linear regression analyses showed statistically significant independent associations of [1] WHtR, PWV, eGFR, QUICKI, LDL cholesterol and triglycerides with aortic systolic and diastolic BP; [2] plasma sodium concentration and age with aortic systolic BP; and [3] male sex and high alcohol consumption category with aortic diastolic BP (Table 3).
Table 3Linear regression analyses with stepwise elimination of explanatory factors for aortic blood pressure, systemic vascular resistance index, and pulse wave velocity Aortic systolic BP (mmHg) R 2 = 0.398 Unstandardized coefficient B Standardized coefficient Beta P value (constant)-4.1470.935Pulse wave velocity2.2180.225< 0.001eGFR-0.219-0.198< 0.001LDL cholesterol3.4690.165< 0.001Waist:height ratio32.4860.1190.006Age0.2010.1170.016Plasma sodium0.7850.0780.024QUICKI-42.355-0.0920.016Triglycerides-1.934-0.0920.019 Aortic diastolic BP (mmHg) R 2 = 0.346 Unstandardized coefficient B Standardized coefficient Beta P value (constant)92.850< 0.001eGFR-0.200-0.266< 0.001Pulse wave velocity1.2760.190< 0.001LDL cholesterol2.3340.163< 0.001QUICKI-36.109-0.1150.003Male sex3.0710.1130.002Triglycerides-1.828-0.1270.003High alcohol consumption category8.7570.0910.014Waist:height ratio17.8610.0960.031 SVRI (dyn*s/cm 5 *m 2) R 2 = 0.219 Unstandardized coefficient B Standardized coefficient Beta P value (constant)1659< 0.001Waist:height ratio19110.235< 0.001eGFR-4.981-0.1510.002LDL cholesterol77.9920.1250.006Present smoking-178.938-0.0990.011Age5.2970.1030.037 Pulse wave velocity (m/s) R 2 = 0.553 Unstandardized coefficient B Standardized coefficient Beta P value (constant)-0.7360.127Age0.0740.475< 0.001Uric acid0.0050.196< 0.001Mean aortic pressure0.0180.152< 0.001Waist:height ratio4.8950.199< 0.001Leptin-0.013-0.1130.001Aldosterone3.86 × 10− 40.0810.008Present smoking-0.479-0.0870.003Triglycerides0.1350.0710.031See Methods for included variables; BP, blood pressure; eGFR, estimated glomerular filtration rate using the CKD-EPI creatinine-cystatin C equation; HDL, high density lipoprotein; LDL, low density lipoprotein; QUICKI, quantitative insulin sensitivity check index; SVRI, systemic vascular resistance index; CRP, C-reactive protein WHtR, eGFR, LDL cholesterol, present smoking, and age were independently associated with SVRI. Age, uric acid, mean aortic pressure, WHtR, leptin, aldosterone, present smoking, and triglycerides were independently related with PWV (Table 3).
## Discussion
Obesity-related hypertension is considered as a distinct phenotype [9, 12], but the underlying mechanisms remain elusive. The pathophysiology of obesity-induced hypertension involves various potential pathways [4, 5, 8–12]. Excess visceral adiposity is associated with altered secretion of bioactive peptides like adiponectin, leptin, interleukin-6, and tumor necrosis factor-α, predisposing to inappropriate inflammatory responses, insulin resistance, increased sympathetic activity and RAAS activation. These changes impair endothelial function and increase tubular reabsorption of sodium and water, leading to elevated BP [4, 9]. In the present study, aortic systolic BP, systemic vascular resistance, and large arterial stiffness were elevated with higher intra-abdominal fat content in the absence of changes in volume balance, modulation of cardiac sympathovagal balance, or circulating RAAS. The differences between the study quartiles emphasized the influences of SVRI and arterial stiffness as BP-elevating factors related with higher WHtR, and the regression analyses confirmed that WHtR was independently associated with aortic BP, SVRI, and large arterial stiffness.
WHtR better correlates with intra-abdominal fat content than waist circumference, BMI, or waist to hip ratio [2]. WHtR also presents with stronger inverse correlation with cardiovascular health than waist circumference [29]. A cutoff value of 0.5 for WHtR has been suggested for the risk assessment of cardiovascular disease [30], and this value was exceeded in three of the present quartiles that exhibited mean BMI values ranging from 25.1 to 31.9 kg/m2. According to a recent survey, mean BMI in *Finland is* 27.7 kg/m2 in men and 27.5 kg/m2 in women, while $27\%$ of men and $26\%$ of women aged 30–64 years are obese [31]. The present study cohort with a mean BMI of 26.8 kg/m2 well corresponds to the concurrent Finnish population.
Previously, a direct correlation between BMI and plasma aldosterone concentration was reported in overweight patients independent of age, sex and sodium intake [32]. In addition, weight loss was found to reduce plasma renin activity and aldosterone concentration in overweight subjects [33]. In the present study, no differences were detected in plasma renin activity, aldosterone concentration, or aldosterone:renin ratio between the quartiles, and measurements of extracellular volume balance did not indicate volume retention with higher WHtR. Thus, there were no findings indicating changes in circulating RAAS activity between the WHtR quartiles. However, increased WHtR was associated with an unfavorable lipid profile, and in linear regression analyses LDL cholesterol was associated with systolic and diastolic BP and SVRI, as previously reported [34].
As expected, systolic and diastolic BP were increased with higher WHtR. Heart rate was also increased, but stroke volume and cardiac output adjusted to body surface area were decreased with higher WHtR, suggesting that hyperdynamic circulation was not the cause for elevated BP. In contrast, SVRI was clearly increased with higher WHtR. Like in essential hypertension [35], the mechanisms leading to elevated SVRI are probably multifactorial. The hemodynamic pattern of reduced CI and increased SVRI has been shown in subjects with essential hypertension [36]. Also, Krzesiński et al. reported that hypertensive patients with or without abdominal obesity presented with similar SVRI, whereas left ventricular contractility and thoracic fluid content were lower in hypertensive subjects with abdominal obesity [37].
PWV is an acknowledged measure of large arterial stiffness [38]. We found that PWV, and also forward wave amplitude that has been associated with aortic stiffness [19], were increased with higher fat content in the central body. However, the indices of wave reflection AIx and AIx@75 [24, 38], did not differ between the quartiles. AIx is influenced by arterial stiffness, but also by height, sex, ventricular ejection duration, heart rate, and systemic vascular resistance [24, 38]. We also evaluated arterial compliance by calculating the ratio of stroke volume to aortic pulse pressure [20], and found that this variable was lower with higher WHtR. Our findings strongly support the view that obesity is associated with increased arterial stiffness [39].
Obesity related increase in plasma leptin concentration is assumed to induce unfavorable cardiovascular changes via the activation of the sympathetic nervous system [40] and RAAS [41], leading to hypertension and increased large arterial stiffness. Studies investigating the association of leptin and arterial stiffness have provided variable results [6, 7]. In the present study, subjects with high WHtR presented with elevated plasma leptin levels, and a 3.3-fold difference in leptin was detected between the highest and lowest quartiles of WHtR. Leptin was moderately related with PWV in the regression analysis, but RAAS activity or sympathetic modulation of HRV were not increased. Thus, the association of WHtR with BP and arterial stiffness may be more related to abdominal obesity itself than high level of circulating leptin.
Excess body fat has been associated with increased sympathetic activity, but the matter remains controversial [42–44]. We evaluated modulation of cardiac autonomic tone using HRV analyses, and found no differences in LF power or HF power, reflecting predominantly sympathetic and parasympathetic influences, respectively [25], or LF/HF ratio between the quartiles of WHtR. Previously, Skrapari et al. reported lower LF and HF power in obese (BMI ~ 40 kg/m2) versus lean (BMI ~ 22 kg/m2) subjects [43], while Hillebrand et al. found that BMI was associated with LF power but not with HF power [44]. Emdin et al. reported decreased LF power throughout the 24-hour recording period in obese (BMI ~ 35 kg/m2) versus lean (BMI ~ 24 kg/m2) subjects, while HF power was lower, and the LF/HF ratio was higher, during the postprandial phases [42]. Higher daytime LF/HF ratios have been related with higher plasma insulin concentrations independent of BMI, sex, age, and heart rate [42]. In the present study, subjects in the upper quartiles of WHtR were more insulin resistant based on their QUICKI values, but no parallel changes in cardiac sympathovagal modulation were observed.
## Study Limitations
Non-invasive recordings of hemodynamics were utilized in this study, which can be considered a limitation. Stroke volume and cardiac output were evaluated from the bioimpedance signal based on a mathematical algorithm and simplification of physiology [21]. However, these methods have been validated against invasive measurements, 3-dimensional echocardiography recordings, and carotid-femoral measurements of PWV [15, 18, 21, 24]. Although this study presented associations between BP, systemic vascular resistance, HRV, and arterial stiffness, the cross-sectional design does not allow conclusions about causality. Importantly, the participants included in this study were without antihypertensive medications that can cause significant confounding during hemodynamic measurements.
## Conclusion
The present results showed that elevated BP related to abdominal obesity was characterized by increased systemic vascular resistance and arterial stiffness, but not by increased cardiac sympathovagal modulation, volume retention, or activation of the circulating RAAS. Although high BP in obese subjects has been characterized by distinct phenotypic features including increased sympathetic tone, impaired endothelium-mediated vasodilatation and RAAS upregulation [9, 12], the present results suggest that the most characteristic features related with elevated BP during higher WHtR are corresponding to those in primary hypertension. Prospective future studies are required to evaluate the clinical significance of the principal phenotypic features related with abdominal obesity.
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|
---
title: Development of a Molecular-Subtype-Associated Immune Prognostic Signature That
Can Be Recognized by MRI Radiomics Features in Bladder Cancer
authors:
- Shenghua Liu
- Haotian Chen
- Zongtai Zheng
- Yanyan He
- Xudong Yao
journal: Bioengineering
year: 2023
pmcid: PMC10045524
doi: 10.3390/bioengineering10030318
license: CC BY 4.0
---
# Development of a Molecular-Subtype-Associated Immune Prognostic Signature That Can Be Recognized by MRI Radiomics Features in Bladder Cancer
## Abstract
Background: Bladder cancer (BLCA) is highly heterogeneous with distinct molecular subtypes. This research aimed to investigate the heterogeneity of different molecular subtypes from a tumor microenvironment perspective and develop a molecular-subtype-associated immune prognostic signature that can be recognized by MRI radiomics features. Methods: Individuals with BLCA in The Cancer Genome Atlas (TCGA) and IMvigor210 were classified into luminal and basal subtypes according to the UNC classification. The proportions of tumor-infiltrating immune cells (TIICs) were examined using The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm. Immune-linked genes that were expressed differentially between luminal and basal subtypes and associated with prognosis were selected to develop the immune prognostic signature (IPS) and utilized for the classification of the selected individuals into low- and high-risk groups. Functional enrichment analysis (GSEA) was performed on the IPS. The data from RNA-sequencing and MRI images of 111 BLCA samples in our center were utilized to construct a least absolute shrinkage and selection operator (LASSO) model for the prediction of patients’ IPSs. Results: Half of the TIICs showed differential distributions between the luminal and basal subtypes. IPS was highly associated with molecular subtypes, critical immune checkpoint gene expression, prognoses, and immunotherapy response. The prognostic value of the IPS was further verified through several validation data sets (GSE32894, GSE31684, GSE13507, and GSE48277) and meta-analysis. GSEA revealed that some oncogenic pathways were co-enriched in the group at high risk. A novel performance of a LASSO model developed as per ten radiomics features was achieved in terms of IPS prediction in both the validation (area under the curve (AUC): 0.810) and the training (AUC: 0.839) sets. Conclusions: Dysregulation of TIICs contributed to the heterogeneity between the luminal and basal subtypes. The IPS can facilitate molecular subtyping, prognostic evaluation, and personalized immunotherapy. A LASSO model developed as per the MRI radiomics features can predict the IPSs of affected individuals.
## 1. Introduction
Globally, one of the most prevalent cancers related to urological cancer is bladder cancer [1]. Of newly diagnosed cases, $75\%$ are cases of non-muscle-invasive bladder cancer (NMIBC), while $25\%$ are cases of muscle-invasive bladder cancer (MIBC), the latter carrying a higher risk of disease progression and metastasis. Despite radical surgery and cisplatin-based chemotherapy, an immune checkpoint inhibitor has been introduced as a novel and safe method to treat BLCA [2]. Unfortunately, only nearly a quarter of patients benefit from immune checkpoint inhibitors, which highlights the importance of patient selection [2,3,4]. In recent years, molecular subtyping based on a comprehensive transcriptomic profile has been introduced to reflect the heterogeneity of bladder cancer, including UNC classification, Lund classification, MDA classification, and TCGA classification. Generally, these classifications overlap, and MIBC can be classified into luminal and basal subtypes [5,6,7,8]. Distinct intrinsic mechanisms and treatment responses among molecular subtypes have been identified [9,10], but the heterogeneity of different molecular subtypes has not been elucidated from an immunological perspective.
The tumor microenvironment (TME), a complicated system, includes diverse components that have important roles in immunotherapy response and prognosis [11,12]. As a crucial component of TME, tumor-infiltrating immune cells (TIICs) reflect the status of TME and perform vital functions in inhibiting and promoting tumor growth and progression [13]. In addition, some TIICs, such as regulatory T cells and macrophages, have a strong association with immune escape, thereby leading to the failure of immunotherapy [14].
Magnetic resonance imaging (MRI) is preferred and recommended for preoperative diagnosis of BLCA in clinical practice. MRI images can be examined through computational medical imaging, also called radiomics, by extracting high-throughput quantitative features that cannot be deciphered by the human eye, thus allowing preoperative prediction of the biological behavior at tumor onset through a non-invasive approach [15,16]. In addition, prior research has linked features extracted from CT images to gene expression patterns in bladder cancer [17,18]. Therefore, it could be assumed that radiomics could be used to construct a non-invasive, convenient, and efficient model for genetic status prediction.
This research aimed to elucidate the different mechanisms underlying the link between luminal and basal subtypes from an immunological perspective in BLCA. MIBC was classified into luminal and basal subtypes according to the UNC classification system. The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was applied to present a TIIC landscape and explore the differences in TIICs between the subtypes. As per the expression of five immune-related genes (IRGs), an immune prognostic signature (IPS) was developed which was shown to have a high association with molecular subtypes and critical immune checkpoint gene expression. The IPS exhibited good performance in predicting prognosis and immunotherapy response. An IPS-based nomogram was constructed for prognostic prediction. Furthermore, RNA-sequencing and preoperative MRI data of 111 individuals with BLCA in our center were utilized to construct a least absolute shrinkage and selection operator (LASSO) model for IPS prediction.
## 2.1. Data Collection
Figure 1 shows the workflow of the present study.
Individuals with BLCA in Shanghai Tenth People’s Hospital were subject to the following inclusion criteria: [1] histologically diagnosed as BLCA; [2] samples were accessible for RNA-sequencing after surgery; [3] MRI was performed within 20 days before surgery. The criteria for exclusion were as follows: [1] any treatments were performed before MRI examination; [2] poor-quality MRI images; [3] tumors with poorly defined boundaries; [4] the subjects lacked baseline clinical factors. RNA sequencing, paired-end library generation, total RNA extraction, and MRI examination were performed as per the prior description [19,20]. Random classification of BLCA subjects into the training and validation sets at a 7:3 ratio was performed.
The standardized expression data set of mRNA (RNA-sequence) Fragments Per Kilobase of transcript per Million Fragments along with clinical data were retrieved from The Cancer Genome Atlas (TCGA)-BLCA cohort (https://portal.gdc.cancer.gov, accessed on 25 September 2022). The IMvigor210 trial provided data on atezolizumab (PD-L1 inhibitor)-treated subjects (metastatic urothelial cancer subjects), such as clinical and RNA expression data (http://research-pub.gene.com/IMvigor210CoreBiologies, accessed on 25 September 2022). The Gene Expression Omnibus (GEO) provided the RNA expression data for GSE32894, GSE31684, GSE13507, and GSE48277, along with their corresponding prognostic data (https://www.ncbi.nlm.nih.gov/geo/, accessed on 25 September 2022). The average value of RNA expression was calculated for gene symbols with multiple probes.
## 2.2. Evaluation of TIICs
As per the marker gene’s RNA expression data, the CIBERSORT algorithm was run to assess 22 TIICs in terms of their relative proportions (https://cibersort.stanford.edu, accessed on 25 September 2022). Monte Carlo sampling was applied for the deconvolution and CIBERSORT p-value calculation for every sample. The CIBERSORT p-value < 0.05 was set as the sample selection threshold for examining the proportions of TIICs. The TCGA data set, which had the highest number of MIBC subjects, was utilized for assessing various TIICs.
## 2.3. RNA Expression Data-Based Molecular Subtyping
The molecular subtypes of subjects with MIBC were obtained using the ‘BLCA subtyping’ R package (https://github.com/cit-bioinfo/BLCAsubtyping, accessed on 25 September 2022) based on the RNA expression data. Six classification approaches, including UNC, CIT, Lund [2017], MDA, Baylor, and TCGA classifications [2017], were applied for molecular subtyping.
## 2.4. Molecular-Subtype-Associated IRGs
The IRG list was accessed from the Immunology Database and Analysis Portal database (https://immport.niaid.nih.gov, accessed on 25 September 2022). The TCGA and IMvigor210 patients were divided into luminal and basal subtypes as per the UNC classification. The differentially expressed IRGs (adjusted p-value < 0.05 and |Fold change| > 0.5) between luminal subtypes and basal subtypes were obtained using the ‘limma’ R package v3.46 in TCGA and IMvigor210, respectively. The resulting IRGs were analyzed through univariate Cox regression to further identify the overall survival (OS)-associated IRGs in TCGA and IMvigor210, respectively. The OS-associated IRGs were then imported into an online Venn diagram tool (http://bioinformatics.psb.ugent.be/webtools/Venn/, accessed on 25 September 2022) to find the overlapping genes between TCGA and IMvigor210.
## 2.5. IPS Construction and Validation
The IPS was developed per the expression of the overlapping genes between TCGA and IMvigor210. The formula for the IPS is presented below:Metabolic score=scale (∑X−∑Y) where X and Y represent the selected gene with HR > 1 and HR < 1, respectively. The formula above was utilized for quantifying the patient’s risk score. The R package ‘survminer’ v0.4.8 calculated the optimal threshold values, according to which high- and low-risk groups of the subjects were established. The prognosis predictive performance of the IPS was investigated using the Kaplan–Meier and log-rank tests in TCGA and IMvigor210. Four GEO data sets (GSE32894, GSE31684, GSE13507, and GSE48277) were used to further validate the prognosis predictive potential of the IPS.
Additionally, a meta-analysis was performed utilizing the results of the univariate Cox regression analyses (confidence interval (CI) of $95\%$ and HR) for each data set. The heterogeneity of the meta-analysis was evaluated using the I2 statistic and the χ2-based Q test and was assessed by the I2 value. The fixed-effect inverse-variance model was utilized when the I2 value was < $25\%$ and the p-value was > 0.05 and the heterogeneity was considered to be low. Any possible publication bias was assessed by means of Egger’s test and Begg’s plotting, where bias was considered to be absent at a p-value > 0.05.
## 2.6. Gene Set Enrichment Analysis (GSEA)
The biological processes between high- and low-risk values were compared using GSEA software (http://www.broad.mit.edu/GSEA/, accessed on 25 September 2022) in terms of their different biological pathways (http://www.broadinstitute.org/gsea/index.jsp, accessed on 25 September 2022). GSEA is able to uncover biological processes based on sets of differentially expressed genes instead of individual genes. Significant results were defined as a false discovery rate < 0.25 and a nominal p-value < 0.05.
## 2.7. Nomogram Construction
Univariate and multivariate Cox regression analyses were utilized to investigate the prognostic significance of clinicopathological features and IPS in TCGA. The significant variables in multivariate Cox regression analysis were selected for nomogram construction. The nomogram’s performance was examined through calibration plots that utilized the ‘Rms’ R package v5.1. The potential of the nomogram in clinical settings was investigated through decision curve analysis (DCA).
## 2.8. MRI Protocal
Patients were instructed to drink water 1 h before the MRI study and to present with a full bladder. Imaging was performed with a 3-T MRI system (Magnetom Trio; Siemens Healthcare, Munich, Germany) using an eight-channel phased-array pelvic coil. Conventional T1-weighted spin-echo images (499 ms repetition time (TR), 12 ms echo time (TE); 204 × 256 matrix; 40 cm field of view; 5 mm section thickness; 1.3 mm intersection gap; two signals acquired) and T2-weighted turbo spin-echo images (4000 ms TR, 100 ms TE; 256 × 256 matrix; 20 cm field of view; 5 mm section thickness; 1 mm intersection gap; two signals acquired) were obtained in the axial plane. High-resolution T2 weighted turbo spin-echo images (4700 ms TR, 107 ms TE; 256_256 matrix; 16 cm field of view; 5 mm section thickness; 1 mm intersection gap; one signal acquired) were obtained in three orthogonal planes. DW images were obtained using a single-shot spinecho echoplanar sequence (b, 0 and 1500 sec/mm2 (DW gradients applied in three orthogonal directions); TR/TE,$\frac{5200}{74.9}$ ms; matrix, 96 × 130; section thickness, 3 mm; gap, 1 mm; field of view, 28 × 28 cm; number of sections, 27; NEX, 6).
Contrast-enhanced MRI was performed in the axial plane using 2D turbo FLASH sequences with an IV bolus administration by hand injection of 0.1 mmol/kg of body weight of a gadolinium chelate contrast agent. In the following contrast sequences, 10 turbo FLASH series, each lasting 30 s, were performed sequentially in 5 min using parameters identical to those of the unenhanced sequence. The onset of the contrast injection and the data acquisition were triggered synchronously.
## 2.9. Region of Interest (ROI) Segmentation and Feature Extraction
An open-source, free software package (ITK-SNAP, v3.6.0; http://itk-snap.org) was utilized by a radiologist (F Xu, experienced in bladder MRI reading with more than 5 years of practice) to manually delineate the ROIs along the edges of the tumors, slice by slice, on T2WI images and the delay phase of dynamic contrast-enhanced (DCE) images. In the case of numerous lesions in an individual with BLCA, only the biggest lesion was analyzed further. In order to examine the reliability of the observer, another radiologist was selected to perform the same experiment. The same radiologist performed his experiment after a month utilizing randomly selected individuals that were 40 in number alongside another new radiologist (T Xu). The reliability of their observations was examined by assessing the interobserver reliability.
Four types of radiomics features, including image intensity (first-order features), shape- and size-based, wavelet, and textural features, were obtained from the PyRadiomics platform (http://www.radiomics.io/pyradiomics.html, accessed on 25 September 2022) [21]. The ROIs of each subject were utilized for this extraction. Ultimately, the extraction of 3562 radiomics features from T2WI and DCE images (1781 radiomics features from T2WI and DCE images, respectively) was carried out with subsequent normalization of each feature with a Z-score prior to feature selection.
## 2.10. Feature Selection and Radiomics Signature Development
To examine the interobserver reliability, inter- and intraclass correlation coefficients (ICCs) were derived. Features with ICCs > 0.75 were selected for the minimum redundancy maximum relevance (mRMR). mRMR is a supervised feature-selection algorithm which calculates the mutual information (MI) between a target variable and features. It ranks features by maximizing MI with respect to the target variable and then minimizes the average MI for features with higher rankings [22]. The importance of features was ranked through the mRMR algorithm, and the 10 leading features were selected for radiomics signature development. In this study, the LASSO algorithm was used via the R package “glmnet” for radiomics signature development. The LASSO algorithm can select features with non-zero coefficients and remove features with negligible effect on the target variable, which is able to prevent overfitting and enhance model interpretation [23]. The penalty regularization parameter lambda (λ) was chosen via 10-fold cross-validation to obtain radiomics features with non-zero coefficients and minimize the mean square error. Meanwhile, the minimal λ was identified to obtain the radiomics features. Each subject’s radiomics score was calculated as follows:Radiomics score=∑$i = 1$nCoefi×xi where xi is the standardized value of each selected radiomics feature and *Coefi is* the coefficient corresponding to each radiomics feature.
The optimal parameter configuration obtained from the training set was utilized for the construction of the radiomics signature, which was subsequently evaluated in the validation set. The performance of the above-mentioned signature was evaluated through the quantification of the specificity, sensitivity, accuracy, negative and positive predictive values (NPV and PPV, respectively), and the area under the receiver operating characteristic (ROC) curve (AUC).
## 2.11. Statistical Analysis
One-way ANOVA, Wilcoxon testing, or t-testing was utilized for the variable evaluation of the subjects categorized by molecular subtypes and risk groups. The ‘Pheatmap’ R package v1.0.12 and the ‘ggalluvial’ R package v0.12.3 were utilized to generate heatmap and alluvial diagrams, respectively. R v3.6.1 (https://www.r-project.org/, accessed on 25 September 2022) and SPSS 23.0 (SPSS, Armonk, NY, USA) were employed to analyze the data statistically. The meta-analyses were performed using the R package ‘meta’ v4.16 (Aaron Lun, San Francisco, CA, USA) and the R package ‘metafor’ v2.4 (Aaron Lun, San Francisco, CA, USA). The link of IPS to the expression of critical immune checkpoint genes was explored using the ‘corplot’ R package v4.0.3 (Alexander Ploner, Stockholm, Sweden). Significant results were defined as a two-sided p-value < 0.05.
## 3.1. Comparison of TIICs between Luminal and Basal Subtypes
The percentages of 22 TIICs in 343 MIBC subjects (including 185 luminal and 158 basal subtypes) in TCGA with CIBERSORT $p \leq 0.05$ were examined (Figure 2A). There were 11 out of 22 TIICs that showed a difference in distribution between luminal and basal subtypes. Specifically, the basal subtypes had relatively higher percentages of Macrophages M0, Macrophages M1, NK cells activated, resting memory, and memory-activated CD4 T-cells, as well as neutrophils. Conversely, the luminal subtypes had higher percentages of dendritic cells activated, regulatory T cells (Tregs), plasma cells, memory B cells, and naïve B cells (Figure 2B).
## 3.2. Selection of IRGs
According to the UNC classification system, individuals in TCGA and IMvigor210 were classified into luminal (249 and 165, respectively) and basal subtypes (162 and 183, respectively). There were 739 and 75 differentially expressed IRGs in TCGA and IMvigor210, respectively (Figure 3A,B). After the univariate Cox regression analysis, the OS-associated IRGs in TCGA and IMvigor210 were 168 and 11, respectively. The Venn diagram showed that there were five overlapping genes (CD3G, CD8A, CTLA4, FAM3B, and GNLY) between TCGA and IMvigor210 (Figure 3C). The survival analyses of five genes were investigated (Figure 3D,E).
## 3.3. Construction and Performance of the IPS
Each subject’s risk score was derived based on the expression of the five genes and the aforementioned formula. In TCGA, the high-risk group was positively associated with clinicopathological features, including pathological stage, morphology, histological grade, as well as the T, M, and N stages (Figure 4A), and subjects in this group had considerably poorer OS than those at lower risk (Figure 4B). GSEA showed that several oncogenic KEGG signaling pathways, including ‘BLADDER_CANCER’, ‘JAK_STAT’, ‘NOTCH, ‘KEGG_PATHWAYS_IN_CANCER’, ‘TGF_BETA’, and ‘WNT’, were coenriched in the more at-risk group (Figure 4C).
The risk group was considerably linked to six classification approaches (Figure 5A), and the basal subtype had a significantly higher risk score than the luminal subtype (Figure 5B–G).
In IMvigor210, subjects in the low-risk group had poorer OS than those in the high-risk group (Figure 6A). In addition, subjects in the low-risk group had an increased percentage of partial response (PR)/complete response (CR) compared to those in the high-risk group ($38.0\%$ and $22.8\%$, respectively; Figure 6B). PR/CR subjects had considerably decreased risk scores compared to progressive disease (PD)/stable disease (SD) subjects (Figure 6C). In addition, IPS was negatively related to the expression profiles of critical immune checkpoint genes (Figure 6D).
## 3.4. Validation of the IPS
Except for GSE13507, IPS showed potential for prognosis prediction in GSE32894, GSE31684, and GSE48277 through Kaplan–Meier and log-rank tests (Figure 7A–D). Meta-analysis was further utilized for a comprehensive investigation of the prognostic value of IPS. As the heterogeneity test revealed negligible heterogeneity among data sets (I2 = $0.00\%$, p-value = 0.53), the fixed-effect inverse-variance model was used for the meta-analysis. The results suggested that for individuals suffering from BLCA, IPS could act as a risk factor (Figure 7E,G; $p \leq 0.001$, HR = 1.31, $95\%$ CI: 1.18–1.43). The funnel plot was also basically symmetrical (Figure 7F). The Egger’s test ($$p \leq 0.935$$), Begg’s test ($$p \leq 0.719$$), and Egger’s publication bias plot revealed no publication bias (Figure 7H).
## 3.5. Construction of Nomogram
In a univariate Cox regression analysis, IPS, age, monograph, stage, histological grade, T stage, and N stage were linked to OS and introduced into multivariate Cox regression analysis (Table 1). IPS, age, and T and N stages were indicated to be significant and were selected to develop the nomogram for predicting 1-, 3- and 5-year OS (Figure 8A). Calibration plots presented a considerable consistency with actual 1- and 3-year OS (Figure 8B,C). DCA further indicated the clinical usefulness of the nomogram (Figure 8D,E).
## 3.6. Radiomics Signature Development and Performance Determination
This research examined the data of 111 BLCA subjects. The training and validation sets comprised 77 and 34 subjects, respectively. Data regarding the clinical features of the subjects were assessed (Table 2). The two sets did not exhibit any differences that were statistically significant.
In addition, 0.762 to 0.908 was determined as the range of the inter-reader ICC between the two radiologists, indicating favorable inter- and intraobserver reproducibility. The features in the top 10 positions as ranked by mRMR were retained and utilized for the development of radiomics signatures. Therefore, we constructed a LASSO model based on these ten features (Figure 9A,B). These aforementioned features did not show a strong correlation with one another (Figure S1; mean absolute Spearman ρ = 0.158), revealing that the valuable radiomics features were obtained and that overfitting was avoided. The feature’s coefficients were also examined (Figure S1). The performance of the LASSO model was investigated (Figure 9C), with AUC values for the training and validation sets of 0.839 and 0.810, respectively (Figure 9D). In addition, individuals in the high-risk group showed considerably elevated radiomics scores as compared to those in the low-risk group in the two sets (Figure 9E,F; both $p \leq 0.001$).
## 4. Discussion
TIICs are vital constituents of non-tumor cells in TME, and the interaction between TIICs and tumor cells plays a vital role in tumorigenesis and malignant progression [24]. This research focused on investigating the different immune infiltrations and immune activities between molecular subtypes. The results showed that 11 out of 22 TIICs were significantly different between luminal and basal subtypes. This indicated that the dysregulation of TIICs could partly explain the distinct treatment responses and prognoses between luminal and basal subtypes. Previous research has reported the vital functions of macrophages in tumor angiogenesis, progression, metastasis, therapeutic resistance, and immune escape [25,26,27]. Neutrophils play an important role in the TME and tumor progression through secreting certain factors [28]. Thus, high infiltration of neutrophils may contribute to the malignant tumor behavior related to metastasis and poor prognosis in basal subtypes. Macrophages M1 promote antitumor immunity by secreting reactive oxygen species and proinflammatory cytokines, and activated NK cells play crucial roles in protective immunity against tumors [29]. Our results demonstrated that those in the basal subtype had significantly higher percentages of Macrophages M1 and activated NK cells than those in the luminal subtype, which revealed the high immune activity in basal subtypes. Conversely, the luminal subtypes had a higher percentage of regulatory T cells, which can inhibit tumor immune response. Thus, the results of our study showed an enrichment for immune infiltration and immune activity in basal subtypes, which was consistent with previous reports [30,31]. The molecular subtypes are associated with different TIICs and likely with different responses to immunotherapy, suggesting that the molecular subtypes should be considered for further clinical studies involving immunotherapy.
The molecular differences between molecular subtypes and immunotherapy response in BLCA comprise a complex multigenic process instead of a single gene functioning in isolation [8,13]. Currently, several immune-related models have been built for predicting prognoses or immunotherapeutic responses in BLCA [11,32,33,34]. However, most of these models have a single function, and the relationship between models and molecular subtypes has not been investigated. Thus, this research focused on developing a model based on multiple IRGs for molecular subtyping, prognostic prediction, and immunotherapy response prediction. A five-gene-based IPS was constructed that had a high association with molecular subtypes and critical immune checkpoint gene expression. The above-mentioned IPS demonstrated good performance in predicting the prognoses and immunotherapy responses of BLCA subjects. Specifically, IPS was negatively related to the expression profiles of critical immune checkpoint genes, so BLCA subjects in the low-risk group have high expression of critical immune checkpoint genes, thereby contributing to immunotherapy response and favorable prognosis. In addition, the capability of IPS to predict patient prognosis was further validated with several GEO data sets and comprehensively evaluated by means of a meta-analysis. Thus, the IPS is a multifunctional model and may be a beneficial tool for the evaluation of molecular subtyping, prognostic prediction, and treatment decision making. An IPS-based nomogram was constructed to be used by clinicians. The C-index and the calibration plots indicated that the 1- and 3-year OS prediction of the nomogram was in line with the actual 1- and 3-year OS. The clinical predictive superiority of this nomogram was established by DCA. Overall, the IPS and the IPS-based nomogram may be useful reference tools to assist in clinical decision making.
To further investigate the oncogenic mechanism and biological function of the IPS, GSEA was carried out for the IPS. Notably, the results revealed high enrichment levels of several oncogenic pathways in the high-IPS subgroup, which could explain the positive relationship between IPS and malignant clinicopathological features and poor prognoses.
Among the five genes in the IPS, CTLA4 is an important negative regulator of T cells [35] and can inhibit T cell function via various mechanisms [36,37], which contributed to the clinical development and application of anti-CTLA4 for tumor immunotherapy [38]. CD8A acts as a coreceptor with the T-cell receptors on T cells to recognize antigens displayed by antigen-presenting cells in the context of class I MHC molecules. Our previous study reported that CD8A is a novel indicator for predicting prognosis and immunotherapeutic response in BCa [39]. GNLY and FAM3B have been selected as hub genes in previous models for predicting prognosis and immunotherapy response in BCa [32,40], revealing the good performance of the two genes in prognostic and immunotherapy response prediction. CD3G is involved in T-cell development and signal transduction and has been reported to be associated with TME and prognosis in tumor patients [41,42]. However, no studies have investigated the role of CD3G in prognosis and TME in BCa.
In this study, we also tried to predict IPS scores through MRI-based radiomics in our clinical patient cohort. Notably, radiomics has already been identified as a feasible and effective method to predict tumor immune phenotypes, such as CD8+ T cell infiltration or neutrophil-to-lymphocyte ratios, even PD-1 treatment outcomes [43,44,45,46]. Using paired MRI and RNA sequencing, radiomics phenotypes were also found to be involved in immune regulation [47]. Therefore, it is possible to establish a radiomics model to preoperatively acquire tumor immune features. In bladder cancer, radiomics has been used to predict clinical pathological factors, such as prognosis, muscle-invasive status, and tumor grade, which could reduce the variability created by human error and provide more non-invasive information to guide treatment decisions [48,49]; however, few studies have used radiomics to predict tumor immune features in BLCA so far. This research utilized ten of the extracted radiomics features from DCE and T2WI images to construct a risk-predictive radiomics signature for BLCA subjects. The risk prediction for BLCA subjects was efficient in the validation and training sets, indicating the potential of some features of MRI-based radiomics to characterize the biological behavior at tumor onset. Notably, for this signature, the number of radiomics features from DCE and T2WI were both five, implying that the features of both have equal significance in the assessment of IPS.
This research has a few limitations. One is the absence of mechanistic analyses of the hub genes in BLCA, which need further functional studies in the future. Another limitation is the small number of BLCA subjects in our center. An increased number of BLCA subjects with RNA-sequence, preoperative MRI, and prognostic information are needed to further validate the prognostic value of the IPS and evaluate the performance of the radiomics signature in IPS prediction.
## 5. Conclusions
This research indicated that half of the TIICs between luminal and basal subtypes were different. The five-gene IPS had the possibility of serving as a clinically promising model for molecular subtyping, prognostic prediction, and immunotherapy response prediction. GSEA analysis clarified the biological function of the IPS in the tumor progression of BLCA. An MRI-based radiomics signature can preoperatively assist in predicting patients’ IPSs, thereby contributing to the preoperative prediction of prognosis and immunotherapeutic susceptibility in BLCA.
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|
---
title: 'Phytochemical Composition and Antioxidant, Anti-Acetylcholinesterase, and
Anti-α-Glucosidase Activity of Thymus carnosus Extracts: A Three-Year Study on the
Impact of Annual Variation and Geographic Location'
authors:
- Carlos Martins-Gomes
- Jan Steck
- Judith Keller
- Mirko Bunzel
- João A. Santos
- Fernando M. Nunes
- Amélia M. Silva
journal: Antioxidants
year: 2023
pmcid: PMC10045533
doi: 10.3390/antiox12030668
license: CC BY 4.0
---
# Phytochemical Composition and Antioxidant, Anti-Acetylcholinesterase, and Anti-α-Glucosidase Activity of Thymus carnosus Extracts: A Three-Year Study on the Impact of Annual Variation and Geographic Location
## Abstract
Thymus carnosus Boiss. is a near-threatened species, and, as for many species, its potential for medicinal purposes may be lost if measures towards plant protection are not taken. A way of preserving these species is to increase knowledge about their medicinal properties and economic potential. Thus, with the objective of studying the potentiality of introducing T. carnosus as a crop, the stability of the phytochemical profile of T. carnosus was studied during a period of three years by comparing the phytochemical profile of extracts obtained from plants harvested in two different edaphoclimatic locations, as well as by comparing the respective bioactivities, namely, antioxidant, antidiabetic, antiaging, and neuroprotective activities. It was reported, for the first time, the effect of annual variation and geographic location in the phytochemical composition of aqueous decoction and hydroethanolic extracts of T. carnosus. In addition, the presence of two salvianolic acid B/E isomers in T. carnosus extracts is here described for the first time. Despite the variations in phytochemical composition, according to harvesting location or year, T. carnosus extracts maintain high antioxidant activity, assessed by their capacity to scavenge ABTS•+, •OH, NO•, O2•− radicals, as well as to prevent β-carotene bleaching. All extracts presented significant potential to inhibit acetylcholinesterase (AChE), tyrosinase, and α-glucosidase, denoting neuroprotective, anti-aging, and anti-diabetic potential. In conclusion, the vegetative stage and location of harvest are key factors to obtain the maximum potential of this species, namely, a phytochemical profile with health benefit bioactivities.
## 1. Introduction
Nowadays, the food, pharmaceutical, and cosmetic industries have a growing and constant demand for new products and ingredients with health promoting effects, with an emphasis on natural products. In addition to the general low cost and safe use, the consumption of natural products attracts consumers [1]. Medicinal and aromatic plants are within the natural products with higher potential applications in these industries, where plants from Thymus L., Mentha L., Salvia L., and other genera belonging to the Lamiaceae family are already used as condiments and preservatives in the food sector [2,3,4,5,6], as well ingredients in functional beverages [7] and other products.
Nevertheless, not all species have yet been approached for these purposes, and due to anthropogenic action and loss of natural habitats, a large number of plant species, which currently do not present industrial or commercial use, have been listed in the IUCN’s (International Union for Conservation of Nature) Red List of Threatened Species [8], some of them belonging to the Thymus genus. This is the case for *Thymus carnosus* Boiss., a near-threatened species commonly known as beach thyme, and it is endemic to the Iberian Peninsula, growing mainly on Portugal’s south and southwest shores [9,10].
In the same way as reported for other Thymus species listed in IUCN’s Red List, such as Thymus albicans (Hoffmanns. and Link), which is listed as vulnerable [11,12], a large number of these species are only now beginning to be characterized regarding their phytochemical composition, bioactivities, and potential use for human health benefit. Through the study of its health-promoting effects, it is expected to raise awareness towards a sustainable crop aiming at later industrial applications, as well as the maintenance of biodiversity. According to the IUCN’s latest Red List report (9 December 2022), among the 60,470 flowering plant species assessed since 1996, 24,000 were listed as threatened (sum of critically endangered, endangered, or vulnerable species) [13]. Bernardini, et al. 2018 [14] reported, in 2017, that only approximately 60,000 plant species were screened for pharmaceutical uses, from which 135 pharmaceutical products originated [14]. Given that the total number of flowering plant species described by IUCN ascends to 369,000 species, it is clear that the knowledge regarding the health-promoting activities of flowering plans is still far from its maximum potential. Even more, considering species such as T. carnosus, listed in IUCN’s Red List of Threatened Species, there is a risk of losing the knowledge and potential applications.
By increasing the potential applications of T. carnosus, and its value to the industry, it is expected that actions towards a sustainable crop occur, thus benefiting the maintenance of biodiversity, as well as also the diversity of pharmaceutical options. As limitations to increase the interest in poorly studied species, it can be pointed out that: [1] the absence of a complete phytochemical composition, as well as the correlation of phenolic compounds with various potential bioactivities; [2] knowledge regarding its safety profile, to be further included in human diet, as well as health-promoting effects; and [3] its suitability to be adapted to agricultural production in order to be proposed as a sustainable source of medicinal effects and bioactive compounds.
Aiming at the preservation of T. carnosus, regarding the points described above, our group has recently described, for the first time, the phytochemical composition of aqueous decoction and hydroethanolic extracts of this species. HPLC-DAD-ESI-MSn analysis of these extracts revealed a unique phytochemical composition, mainly rich in phenolic acids, such as rosmarinic acid (RA), salvianolic acids A (SAA), and K (SAK), as well as a novel salvianolic acid A isomer (SAA iso), which are present in high quantities, as well as glycosidic derivatives of luteolin [9]. In addition, high quantities of oleanolic (OA) and ursolic (UA) acids were found in hydroethanolic extracts [9]. These results highlighted these extracts as a source of phytochemicals of high pharmaceutical value, which required posterior validation. Thus, using human cell culture models of colorectal carcinoma (Caco-2), hepatocarcinoma (HepG2), breast adenocarcinoma (MCF-7), and mammary gland ductal carcinoma (BT-474), both aqueous and hydroethanolic extracts were shown to induce anti-proliferative effect against these tumoral cell lines, the hydroethanolic extract being the one with higher effect [9,15]. In Caco-2 cells, the anti-proliferative/cytotoxic effect was correlated with apoptosis induction, cell cycle arrest, and morphological changes [15]. In addition, both extracts revealed anti-inflammatory potential, higher for the aqueous extracts, observed during the reduction of nitric oxide production in a lipopolysaccharide-stimulated macrophage cell model [9]. However, the sustainable crop requires the knowledge of the stability of T. carnosus phytochemical profile and the ability to expand its habitat, which are dependent on other factors, such as the geographic location and edaphoclimatic conditions, which may induce changes in the phytochemical composition.
In the Thymus genus, most studies analysing the effects of edaphoclimatic conditions, inter-year climate changes, and vegetative stage are mainly towards the composition of essential oils, being reported that these factors modulate the essential oils’ phytochemical composition, and therefore their bioactivities, as described for *Thymus vulgaris* L. [16], Thymus pulegioides L. [17], Thymus pallescens Noë. [ 18], or *Thymus hyemalis* Lange [19]. For *Thymus vulgaris* [16], in addition to the phytochemical composition, a change in antioxidant and antibacterial activities was also observed. Regarding thyme extracts, using *Thymus longicaulis* C. Presl collected in different seasons, it was observed that its hydro-methanolic (1:1; % v/v) extract’s polyphenolic composition presented significant variances [20]. The main compound, RA, varied from 12.97 to 3029.56 µg/mL (in quercetin equivalents) in plants harvested from July to October of the same year. However, other phenolic acids also showed variations with the time of harvest and, for example, salvianolic acid K showed a concentration variation inverse to that of RA, and this was also observed for other phenolic acids. The seasonal variance effect was also clearly observed in the tested bioactivities, with significant differences for anti-inflammatory, anti-proliferative, and antioxidant activities [20]. The variation of pentacyclic triterpenoids concentration, such as OA and UA (compounds present in high amounts in T. carnosus HE extract [9]), induced by the vegetative stage, has been described in various thyme species. Analysed in methanolic extracts, small variations in OA and UA content through the various vegetative phases was reported in Thymus praecox ssp. arcticus Opiz. extracts, while, in other species, such as Thymus pulegioides at the end of vegetative stage OA and UA content, was 2.2 and 2.98 times higher than the value at fruit maturation stage [21]. Interestingly, the stage with higher content in each pentacyclic triterpenoids is dependent on the species under study [21], highlighting the need to understand the best conditions for each species.
Therefore, considering T. carnosus as a potential crop, the aim of this work was to study the stability of T. carnosus phytochemical profile over a period of three years to compare the phytochemical profile of extracts obtained from plants harvested in two different edaphoclimatic conditions, as well as to compare the respective bioactivities, namely, antioxidant, anti-diabetic, anti-aging, and neuroprotective activities. For this reason, in the present study, aerial parts of T. carnosus were collected in November, a post-flowering stage, in which the phytochemical profile of the plant may reflect the environmental stresses experienced in the previous months. Aerial parts were collected both at its natural habitat, where it grows as an endemic wild plant, as well as at UTAD’s botanical garden, where the plant has adapted to a different climatic condition. The first location generally presents higher average temperatures in the last trimester of the year when compared to UTAD’s botanical garden. In addition, precipitation is usually higher in northern Portugal, which may also induce variations in the phytochemical profile. The composition of aqueous and hydroethanolic extracts in phenolic and terpenoid compounds was assessed by chromatographic methodologies and correlated to its potential as an antioxidant, anti-diabetic, anti-aging, and/or neuroprotective agent.
## 2.1. Standards and Reagents
Commercial standards used for HPLC identification and quantification were purchased from Sigma-Aldrich/Merck (Algés, Portugal), Extrasynthese® (Genay, France), and Santa Cruz Biotechnology Inc. (Frilabo, Porto, Portugal). All solvents used were HPLC or PA grade and were obtained from Sigma-Aldrich/Merck (Algés, Portugal). Folin-Ciocalteu’s reagent, sodium carbonate, sodium molybdate, aluminium chloride (III), sodium nitrite, (±)-6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid (Trolox), 2,2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS), potassium persulfate, sodium nitroprusside, sulfanilamide, N-(1-naphthyl)ethylenediamine dihydrochloride, β-carotene, linoleic acid, xanthine oxidase, hypoxanthine, nitro blue tetrazolium, ascorbic acid, ethylenediaminetetraacetic acid (EDTA), hydrogen peroxide ($30\%$ solution), trichloroacetic acid (TCA), thiobarbituric acid (TBA), and 2-deoxy-D-ribose were used. Enzymes and reagents for enzymatic assays were purchased from Sigma-Aldrich/Merck (Algés, Portugal). Other salts and reagents not mentioned above were obtained from Sigma-Aldrich/Merck (Algés, Portugal).
## 2.2. Plant Material
Aerial parts (constituted by leaves and stems) of T. carnosus Boiss. were collected in Arrábida National Park (coordinates: latitude 38.492637°/longitude −9.181475°; Sesimbra, Setúbal, Portugal), further identified as location one (L1) and in the Botanical Garden of the University of Trás-os-Montes e Alto Douro (coordinates: latitude 41.287538°/longitude −7.740203°; UTAD), and further identified as location two (L2), in November of 2018, 2019, and 2020. L1 harvest was dependent on authorization granted by the Portuguese Institute for Nature Conservation and Forests (ICNF) (License no. $\frac{867}{2018}$/RECOLHA; $\frac{868}{2018}$/RECOLHA; $\frac{723}{2019}$/RECOLHA; $\frac{723}{2019}$/RECOLHA; $\frac{198}{2020}$/RECOLHA; $\frac{199}{2020}$/RECOLHA). A portion of the plant material (containing leaves and stems) harvested in L1-2018 was used for authentication by the Botanical Garden office at the University of Trás-os-Montes and Alto Douro (UTAD, Vila Real, Portugal), originating the voucher specimen nº HVR22496, and the following harvests were performed in the same exact location. The existing specimen in UTAD’s botanical garden had been previously identified with the voucher nº HVR21093. L1 and L2 localization, climate parameters (average temperature (°C), and accumulated precipitation (mm)) in the 2018–2020 period, as well as relevant geographical parameters, are schematized in Figure 1. L1′s data were obtained through a dataset of Portugal’s weather conditions developed and described by Fonseca and Santos 2018 [22]. For L2, the data were retrieved from a weather station located at UTAD. After each harvest, the plant material was rinsed with distilled water, weighted, frozen, and lyophilized (Dura Dry TM μP freeze-drier; −45 °C and 250 mTorr). After this step, the plant material was ground and stored in a cool and dry place, protected from light, until further extraction and analysis.
## 2.3. Preparation of Extracts
Aqueous and hydroethanolic extracts were obtained as described by Martins-Gomes et al. [ 2018] [9], using aqueous decoction extraction (AD) and exhaustive hydroethanolic (HE) extraction procedures, respectively. Briefly, 0.5 g of lyophilized, ground plant material were used for both methods. To obtained AD extracts, 150 mL of distilled water were added to the plant material, followed by heating to 100 °C, where it was maintained for 20 min, under agitation. After this period, the mixture was allowed to cool down, to room temperature, and then was filtered. HE exhaustive extraction comprised a three-step sequential extraction method of the plant material with 50 mL of an ethanol:water solution (80:20, % v/v), each of the steps being under agitation (orbital shaker; 150 rpm) for one hour and then centrifuged (7000 rpm, Sigma Centrifuges 3–30 K, St. Louis, MO, USA). The three supernatants were collected, combined, and filtered. Both extracts were filtered twice (Whatman nº 4 filter and fiberglass filter (1.2 µm; acquired from VWR International Ltd., Alfragide, Portugal)) and concentrated to 100 mL in a rotary evaporator (35 °C), the step in which the ethanol was removed from the HE extract [9]. These methodologies were repeated three times, and all extracts were frozen and lyophilized, followed by weighing for yield calculation and proper storing until further analysis.
## 2.4. Total Phenolic Compounds, Total Flavonoids and Ortho-Diphenols Content
Total phenolic compounds content (TPC), total flavonoid content (TFC), and ortho-diphenol content (ODC) were quantified using colorimetric reactions based on Folin-Ciocalteau reagent, molybdenum complexation, and aluminium complexation, respectively. All methodologies were performed as described by Taghouti, et al. 2020 [23]. TPC and ODC were expressed as caffeic acid equivalents (mg CA eq./g lyophilized plant or mg CA eq./g extract), and TFC was expressed as catechin equivalents (mg C eq/g lyophilized plant or mg C eq/g extract).
## 2.5. Phytochemical Composition Profiling and Quantification by HPLC-DAD and HPLC-ESI-MSn
Individual phenolic compounds, oleanolic acid, and ursolic acid identification and quantification were performed by RP-HPLC-DAD analysis using a Vanquish Core HPLC system (Thermo Fisher Scientific, Waltham, MA, USA) equipped with auto-sampler, pump, column compartment, and diode array detector. Chromatographic separation was performed using a C18 column (Merck Purospher® STAR, Hibar® C18; 250 mm × 4.6 mm; particle size 5 μm), with an injection volume of 100 μL, and the temperature kept at 40 °C, and the flow rate was 0.5 mL/min.
The elution system used for phenolic compounds consisted of solvent A ($0.1\%$ formic acid prepared in ultra-pure distilled water, v/v) and solvent B (methanol) with the elution profile as follows: 0–15 min, 10–$30\%$ B (v/v); 15–60 min, 30–$56\%$ B; 60–65 min, 56–$100\%$ B; 65–66 min, 100–$10\%$ B; and 66–75 min, $10\%$ B (equilibration). The total acquisition time was 65 min, and the total run time was 75 min.
Chromatographic separation of terpenoids was achieved using the same column, solvents, injection volume, flow rate, and temperature described above, using the following elution system: 0–45 min, 80–$90\%$ B; 45–54 min, $90\%$ B; 54–55 min, 90–$80\%$ B; and 55–65 min, $80\%$ B (equilibration). The total acquisition time was 55 min, and the total run time was 65 min.
UV/Vis detection was performed at 200–600 nm, being 280 nm and 325 nm, which were used for phenolic compound quantification, and 210 nm was used for terpenoid quantification. Chromeleon software (Version 7.3; Dionex, USA) was used for data acquisition, peak integration, and analysis.
RP-HPLC-ESI-MSn analysis was performed for accurate phenolic compounds identification using a Thermo Scientific system equipped with a Finnigan Surveyor Plus auto-sampler, pump, LXQ Linear ion trap detector, and a photodiode array detector. The elution system, column, solvents, temperature, flow rate, injection volume, and detection parameters were performed as described by Martins-Gomes et al. [ 2018] [9].
The identification of individual phenolic compounds present in T. carnosus extracts was based on the data acquired from UV-VIS and mass spectrometry analysis, as well as retention time comparison with commercial standards and/or literature data. Oleanolic and ursolic components were identified only by HPLC-DAD by comparison to their respective commercial standards. Phytochemicals’ quantification was performed based on calibration curves of commercial standards, if available, or using the aglycones or standard compounds with structural similarity to commercial standards. Caffeic acid (CA; PubChem CID: 689043) was quantified as its respective standard. Luteolin and apigenin derivatives were quantified as luteolin-7-O-glucoside (L-7-G; PubChem CID: 5280637); quercetin derivatives were quantified as quercetin-3-O-glucoside (Pubchem CID 25203368); eriodyctiol derivatives were quantified as eriodyctiol-7-O-glucoside (Pubchem CID 13254473); RA, SAA iso, SAK, and salvianolic acid K isomer (SAK iso) were quantified as RA (PubChem CID: 5281792).
## 2.6. In Vitro Antioxidant Activity Assessment
In vitro radical scavenging capacity of T. carnosus aqueous and hydroethanolic extracts was evaluated using ABTS (ABTS•+) and superoxide (O2•−) radicals scavenging and β-carotene bleaching assays. ABTS•+ scavenging assay was performed, as described by Taghouti et al. [ 2018] [24] and expressed as mmol Trolox equivalent/g dry plant. Trolox was also used as a positive control (IC50 = 0.24±0.01 mg/mL) Regarding O2•− scavenging by T. carnosus extracts, 6.7 µL of extracts were added to 193.3 µL of the reaction mixture (174 µL of phosphate buffer (50 mM; pH 8), 12.86 µL of nitro blue tetrazolium solution (NBT; 4 mM) and 6.43 µL of hypoxanthine solution (4 mM)), and the mixture was incubated 2 min at 37 °C. The reaction was initiated with the addition of xanthine oxidase solution (20 µL at 0.04 U/mL; in 50 mM phosphate buffer (pH 8) supplemented with 500 µM EDTA). The absorbance was first measured immediately after enzyme addition (blank) at 570 nm (Multiskan EX microplate reader (MTX Labsystems; Bradenton, Florida, USA)). After a 20 min incubation at 37 °C, 20 µL of HCl (0.6 M) were added to stop the reaction, followed by a second absorbance measurement at 570 nm. Rosmarinic acid was used as a positive control (95.71 ± $8.55\%$ inhibition at 120 µg/mL).
For β-carotene bleaching assay, the emulsion was prepared by adding 500 mg of between 20 to 250 µL of β-carotene solution (2 mg/mL solution; in chloroform) and was followed by mixing in a round-bottom evaporation flask [25]. After evaporating the solvent in a rotary evaporator (35 °C), 25 mg of linoleic acid and 50 mL of distilled water were added, in this order. To produce the emulsion, the mixture was then gently homogenized using the rotary evaporator (rotary motion with no vacuum) at room temperature. The assay was carried out in a 96-well microplate, in which 50 µL of the extracts were added to 250 µL of the emulsion, followed by blank measurement at 450 nm. After 2 h incubation at 50 °C, the microplates were placed over ice to stop the reaction, in the dark, for two minutes, followed by a second absorbance measurement. Hydroethanolic extracts were dissolved in $10\%$ (v/v) DMSO solution, and then they were tested to assure no interference with the assay. Rosmarinic acid was used as a positive control (IC50 = 22.05 ± 1.02 µg/mL).
Hydroxyl (•OH) and nitric oxide (NO•) radicals scavenging assays were only performed for aqueous extract, due to ethanol interference, as the HE extracts are not fully water-soluble. Both assays were performed as described by Taghouti et al. [ 2020] [23]. With the exception of ABTS•+ scavenging assay (tested at 1 mg/mL), a range of concentrations of the extracts (0.1–1 mg/mL) was analyzed, and results are expressed as inhibition percentage and IC50, calculated according to equation 1. Distilled water was used as the negative control, and rosmarinic acid was used as a positive control for •OH scavenging assay without EDTA (43.27 ± $3.50\%$ inhibition at 45 µg/mL) and for the NO• scavenging assay (44.43 ± $2.62\%$ inhibition at 15 µg/mL). [ 1]Inhibition (%)=Blank abs−Sample abs Blank abs ×100
## 2.7. Enzymatic Inhibition Assays
T. carnosus aqueous decoction and hydroethanolic extracts were studied for their potential neuroprotective, anti-aging, and anti-diabetic activities. These bioactivities were evaluated based on the capacity to inhibit key enzymes of target metabolic pathways. Acetylcholinesterase (AChE) and tyrosinase inhibition were evaluated for neuroprotection, tyrosinase and elastase for anti-aging activity, and α-amylase and α-glucosidase for anti-diabetic activity.
All methodologies were performed using colorimetric assays, as described by Taghouti et al. [ 2018] [24]. All extracts were tested in a range of concentrations from 0.1 to 1 mg/mL. Hydroethanolic extract dilutions were prepared from a DMSO stock solution, and they never exceed $2.5\%$ DMSO final concentration. A control was performed in all assays to exclude DMSO interference, and distilled water was used as control (blank). As positive controls, quercetin was used for AChE (48.61 ± $3.50\%$ inhibition at 120 µg/mL) and elastase (51.20 ± $7.20\%$ inhibition at 120 µg/mL), kojic acid for tyrosinase (97.04 ± $1.09\%$ inhibition at 1 mg/mL), and acarbose for α-amylase (79.48 ± $3.62\%$ inhibition at 1 mg/mL) and α-glucosidase (76.67 ± $1.33\%$ inhibition at 1 mg/mL).
## 2.8. Statistical Analysis
The experimental assays were performed for all the extracts obtained in each extraction method, with three experimental repetitions for each extract. Analysis of variance (ANOVA), followed by Tukey’s multiple tests, were performed to analyze statistically significant differences. Correlations were evaluated using Pearson’s coefficient (significant if $p \leq 0.05$). The IC50 values were obtained from the dose–response assays described above and calculated, as described by Silva, et al. 2019 [26]. Principal component analysis (PCA) was used to evaluate inter-year variance of the individual phenolic components and performed as described by Ferreira, et al. 2020 [27]. The correlation between individual phytochemicals and antioxidant or enzymatic inhibition activities was performed through orthogonal partial least squares-discriminant analysis (OPLS-DA), as described by Martins, et al. 2022 [28]. Statistical analyses and graphic design were performed using Statistica (Version 14; TIBCO Software Inc., California, USA), SIMCA software (Version 14.1. Umetrics, Umea, Sweden), GraphPad Prism (Version 8; GraphPad Software Inc, California, USA), and Microsoft Office Excel (Microsoft Corporation, Washington, DC, USA).
## 3. Results and Discussion
Medicinal and aromatic plants’ phytochemical composition is known to present high heterogeneity, even in species belonging to same genus. An example is the Thymus genus, since several species, such as T. pulegioides [24], *Thymus zygis* Loefl. ex L. [29], *Thymus fragrantissimus* [30], *Thymus mastichina* L. [23], Thymus × citriodorus (Pers.) Schreb. [ 31], and T. vulgaris [31], were harvested in the same location, grown in the same conditions, and whose phytochemicals were extracted using the same methodologies, and the extracts presented different yields, phytochemical profiles, and bioactivities. In addition to inter-species genetic variations, factors, such the vegetative phase and edaphoclimatic conditions, play a critical role in phytochemical composition variation [27,32,33,34]. The latter is being widely discussed in light of climate changes induced by global warming. The effect of edaphoclimatic factors, such as temperature, precipitation or soil chemistry, and moisture, is well established as a determinant of secondary metabolite production [27,32,33,34].
Within the Thymus genus, several studies have been performed to evaluate these variations, T. vulgaris and its essential oils being the most frequently addressed, given its significant economic impact. Lemos et al. [ 2017] studied the seasonal variance of T. vulgaris’ essential oil from plants harvested in Brazil between July 2012 and July 2013, and it was observed that the October harvest presented higher antioxidant and antimicrobial activity, as well as an increase of 1.36 times in thymol and 1.85 times in p-cymene content, the major phytochemicals [16]. Additionally, using essential oils in T. vulgaris’ and T. hyemalis, Jordán et al. [ 2006] have addressed the effect of the vegetative cycle on the phytochemical profile [35], while Pirbalouti et al. [ 2013] evaluated wild and cultivated samples of T. daenensis essential oil to ascertain the adaptability to crops, where this species produced higher contents of carvacrol or thymol under wild or cultivated growth, respectively [36]. As stated above, the effect of edaphoclimatic parameters on thyme extracts’ phytochemical composition is poorly described. In the present research, we provided new data on the composition variation of aqueous and hydroethanolic extracts of *Thymus carnosus* over a three-year period, comparing both wild plants (harvested at location 1: L1) and plants cultivated in a botanical garden (harvested at location 2: L2), being the geographical locations shown in Figure 1A. L1 corresponds to plants grown in natural conditions, in sand dunes near to the coastline (229 m), and with low elevation (19 m), while L2 corresponds to plants originating in Arrábida National Park (L1) that were cultivated at the botanical garden of the University of Trás-os-Montes and Alto Douro, at an altitude of 451 m and 79 km from the coastline, which adapted to the northern inland climate and soil over a 12-year period. Regarding climate parameters, L2 presents the highest temperature variation, registering lower average temperatures in the winter months and higher average temperatures in summer months when compared to L1, but it overall presents a lower annual average temperature for the 2018–2020 period, as seen in Figure 1B,C. When considering the accumulated precipitation, L2 registered a significantly higher value than L1 (Figure 1B,C).
## 3.1. Extraction Yield, Total Phenolic, Total Flavonoid, and Ortho-Diphenols Content
The extraction yields and results concerning total phenolic (TPC), total flavonoid (TFC), and ortho-diphenols (ODC) content, assessed for all extracts of T. carnosus harvested in L1 and L2, in the 2018–2020 period, are presented in Table 1. The extraction yield values ranged from $17.82\%$ to $25.43\%$, being both the lowest and highest yields obtained for hydroethanolic extracts. With the exception of 2020’s harvest at L1, all HE extracts present higher yield compared to the respective AD extracts, as reported for other thyme extracts using the same extraction methods [23,31]. The geographical location also affected the variation of extraction yields, with extracts from L2 presenting higher mean yield values than L1, this difference being more notorious in 2018’s harvest. Concerning inter-year variance, the major differences were observed in 2020, where both HE extracts and AD extracts from L2 presented a decrease in the extraction yield.
T. carnosus AD extracts present higher TPC than the respective HE extract (Table 1), unlike the described for other Thymus extracts obtained using the same extraction methodologies (e.g., T. pulegioides [24] or T. mastichina [23]), in which TPC, assessed by the Folin-Ciocalteau method, was higher in HE extracts. The exception is L2 harvest of 2018, in which no significant differences were found between AD and HE extracts, identical to that reported for T. fragrantissimus [30]. However, Folin-Ciocalteau method limitations for TPC quantification are well described, since the reagent can be reduced by other chemical components in the extracts, such as, for example, proteins, thiols, carbohydrates, and amino-acids, where it is likely that AD extracts contain other reducing compounds, which might contribute to TPC overestimation [37]. This observation is supported by ODC and TFC quantification (Table 1), where most HE extracts have significantly higher ODC and TFC contents compared to the respective AD extract, L1 2019′s harvest being an exception. In fact, AD-L1–2019 presented higher TPC, ODC, and TFC than the remaining AD extracts, the ODP and TFC contents being in line with the respective HE extracts, and this extract was highlighted, even having the second lowest extraction yield within AD extracts (Table 1). Regarding the harvest location, overall L1′s extracts present the highest TPC, ODC, and TFC when compared to L2. Inter-year effect proved to induce variations in the extracts’ phytochemical composition. As an example, ODC and TFC inter-year variation can be considered for L1-AD extract, as it is seen that from the first [2018] to the second [2019] year, where the content increased (in mg/g dry plant) 1.40 and 1.34 times, and then it reduced 0.94 and 0.86 times from 2019 to 2020, for ODC and TFC, respectively. In an opposing trend, L2′s HE extract presented the highest ODC and TFC in 2018, being followed by a reduction in the following years, which then present similar values.
Thus, considering these results, geographical location induces a clearer pattern in the presented data, while climate variations present less predictable results. Regarding HE extracts, a previous report presented TPC values of 41.89 and 45.47 mg/g dry plant for flowering (July) and post-flowering (October) phases, respectively, both higher than the values here presented for T. carnosus HE extracts (Table 1).
## 3.2. Profiling and Quantification of Individual Compounds by HPLC-DAD and HPLC-ESI-MSn
To better understand the variations in the phytochemical composition, HPLC-DAD-MSn analysis was performed to analyze the variation of the main components of extracts, and that will be relevant to correlate with bioactivities. In Figure 2, HPLC-DAD quantification of total phenolic acids, total flavonoids, total phenols, and total terpenoids, for HE (Figure 2B) and AD (Figure 2C) extracts, was obtained from chromatograms, such as those presented in Figure 2A. The identification of individual compounds was performed with HPLC-ESI-MSn and by comparison of the literature. When considering the sum of all identified and quantified compounds by HPLC-DAD, L1-2020-HE arises as the harvest with the higher content in both phenolics and terpenoids (Figure 2B), while, in AD extracts (Figure 2C), L1-2019-AD is the harvest, presenting higher content in phenolic compounds, as it was also observed in Table 1 for TPC, ODP, and TFC contents in AD extracts. Martins-Gomes, et al. 2018 [9] reported the total phenolics contents assessed by HPLC-DAD, as well as for extracts of T. carnosus harvested in July and October 2015, at flowering and post-flowering stages, respectively, with values ranging from 42.92–60.18 mg/g dry AD extract and 146.09–166.45 mg/g dry HE extract. In Table 2, values range from 37.96–99.86 mg/g dry AD extracts, thus most extracts are within the range of those previously reported. However, L1-2019-AD harvest presents a phenolic content above the average, as observed through HPLC-DAD quantification (Figure 2C and Supplementary Table S2). Regarding HE extracts, in the present research, we report phenolic contents within 87.17–122.36 mg/g dry HE extract (Figure 2B and Supplementary Table S1), and all values are lower than the ones previously reported by Martins-Gomes, et al. 2018 [9] for the 2015 harvest. Given the extractability limit of aqueous extraction method, we observe that the contents here presented for AD extracts are in-line with the previous reported [9], while the increased extractability of exhaustive hydroethanolic extraction allows the extraction of all phenolic compounds, revealing that, when compared to July and October 2015 harvests, a harvest in November presents a decrease in total extractable phenolic compounds, most likely arising from changes in the plants’ vegetative phases.
In Figure 3 (phenolic acids), Figure 4 (flavonoids), Figure 5 (terpenoids), and in Supplementary Tables S1 and S2, we present the quantification of individual compounds identified in T. carnosus extracts from L1 and L2 harvests. Overall, T. carnosus extracts present a similar profile to extracts reported previously [9] regarding phenolic acids with the presence of RA and salvianolic acids as major components, the identification of two salvianolic acid B/E isomers being identified, and T. mastichina [23] and T. zygis [29] extracts were also identified, but they were not previously described in T. carnosus extracts.
Regarding the effect of the location, edaphoclimatic factors may play a significant role. As described above, L1 is the natural habitat of T. carnosus. In fact, extracts obtained from harvests in L1 generally present higher content in phytochemicals. In L2, the average temperature in October and *November is* lower when compared to L1, which could induce an earlier end of the vegetative phase, thus reducing phytochemicals’ production. A second hypothesis is the effect of drought stress, which is linked to increased secondary metabolite production [38]. Within Portugal’s various edaphoclimatic zones, L1 is within an upper thermomediterranean and dry sub-humid zone, with higher aridity and less precipitation, while L2 is within lower supramediterranean and humid/upper mesomediterranean and humid zones [39]. Thus, the higher availability of water in plants adapted to L2′s climate may justify, in part, the decrease in phytochemicals’ production.
In a previous report, T. carnosus extracts’ phytochemical composition, during flowering and post-flowering stages (July and October 2015, respectively), presented salvianolic acids’ A isomer (SAA isomer) and K (SAK), determined as the major phenolic compounds of both AD and HE extract, ranging from 14.87–27.50 mg/g and 61.92–67.34 mg/g of SAA isomer, as well as 12.53–19.66 mg/g and 38.51–65.33 mg/g of SAK, in AD and HE extracts, respectively [9]. The values for inter-year variance of phenolic acids (Figure 3), for harvests in November, report SAA isomer contents ranging from 6.57–12.24 mg/g in AD extract and 12.83–17.90 mg/g in HE extracts, both lower than the ones from October 2015 harvest [9].
Regarding RA content, T. carnosus AD extracts content in RA ranges between 4.48 and 20.12 mg/g extract, while HE extracts range between 19.99 and 29.94 mg/g, being the major phenolic acid in these extracts (Figure 3). Considering T. carnosus extracts from flowering and post-flowering stage, RA was less predominant when compared to salvianolic acids, with a content of 0.16–4.40 mg/g AD extract and 27.84–29.07 mg/g HE extract [9]. We hypothesize that the much higher amount of salvianolic acids in the plants harvested in July and October 2015 limited RA extraction in AD extracts, whilst, in the present research, a lower content in other phenolic acids allowed a higher RA content in AD extracts, since the overall maximum extractable content (evaluated through HE extracts) is lower or similar to the previous report [9]. Regarding inter-year variance, RA content in HE extracts is overall stable in the three-year period in both locations. On the other hand, AD extracts present an increasing pattern for L2, where RA content increases 1.8 times between 2018 and 2020, whilst, in L1, there were no significant differences between these two years, but L1-2019 presented an increase of 1.83 times in RA content, being much richer in this phenolic acid, as was also observed for salvianolic acids. Raudone, et al. 2017 [21] studied the variation of rosmarinic acid through the various vegetative stages of 8 thyme species ($70\%$ hydroethanolic extracts). In all species, the content in RA was decreased in the end of vegetative phase, being, for example, Thymus praecox ssp. arcticus RA’s content 6.95 times higher in May/June, when compared to August/September [21]. Thus, T. carnosus RA content at L2 (19.99–23.24 mg/g extract) increased in plants harvested in November, although it decreased when compared to July (29.07 mg/g extract [9]; between 1.25 and 1.45 times higher), and it was is less expressive when compared to the species described by Raudone, et al. 2017 [21], harvested in September, revealing the stability of RA content in T. carnosus extracts even at later harvests.
Nevertheless, the major difference between the data here presented and the previous report is concerning the flavonoids content, presented in Figure 4 and Supplementary Tables S1 and S2. The extracts from L1 and L2 (2018–2020 harvests) exhibited a flavonoid content ranging from 17.24 to 45.69 mg/g for AD extracts and 34.94 to 60.63 mg/g for HE extracts, higher values than the ones reported by Martins-Gomes, et al. 2018 [9] for plants harvested in July and October 2015 (0.92–5.76 mg/g AD extracts and 8.57–9.02 mg/g HE extracts). Contributing to this higher content in flavonoids, the presence of two apigenin derivatives, two eriodictyol derivatives, two quercetin derivatives, and six luteolin derivatives, from which quercetin-O-hexoside and luteolin-O-hexoside are highlighted as major compounds within the extracts (Figure 4), can be highlighted. Concerning HE extracts, quercetin-O-hexoside presented a larger variation in its content in L1. While 2018 harvest had a similar content to L2 harvests in the three years, for the 2020 harvest at L1, we report the highest value for T. carnosus extracts with 25.92 mg/g extract.
In accordance with the compounds described above, AD extracts obtained from 2019 harvest at L1 presented not only the highest concentration of quercetin-O-hexoside, but also of luteolin-O-hexoside, this being last the major phenolic compound of the 2020 harvest at both L1 and L2. As expected, the highest concentrations were obtained for HE extracts, L1-2020-HE once again being highlighted as the extract with higher content in luteolin-O-hexoside (19.63 mg/g), and overall, luteolin-O-hexoside content in HE extracts ranged between 13.04 and 19.63 mg/g. The concentration of this compound in other Thymus species HE extracts was reported for T. carnosus [9] (4.61 mg/g extract), T. pulegioides [24] (6.31 mg/g extract), and T. zygis [29] (3.64 mg/g extract), which were lower than the concentration presented in this research, while being in line with that reported for T. mastichina [23] (20.85 mg/g extract), which also presented similar values for quercetin-O-hexoside (20.34 mg/g extract) to those here reported for T. carnosus HE extracts.
Results presented in Figure 3 and Figure 4 and Supplementary Tables S1 and S2 were used to perform a statistical analysis of inter-year variance based on the quantification of its phenolic individual components through principal component analysis (PCA), which is presented in Figure 5. In Figure 5A,B we present the scatter plots for each extract (and its replicates) as a function of two PCs, explaining $42.45\%$ (PC1) and $19.23\%$ (PC2) of the variation for HE extracts, as well as $64.31\%$ (PC1) and $20.60\%$ (PC2) for AD extracts. PC2 correlates positively with quercetin derivatives in both HE and AD extracts. Figure 5A represents the variance of HE extracts, in which it is possible to observe a major cluster, with clear separation of L1-2019 and L1-2020-HE. This arises from the fact that both extracts present higher content in quercetin-O-hexoside, but L1-2019-HE does not present the same pattern for the RA and SAA isomers, which have less correlation with PC1. The remaining HE extracts are mainly grouped within a major cluster, where L2-2018 presents the major correlation to PC1 and lowest correlation to PC2, thus representing a strong correlation with apigenin-[6,8]-C-diglucoside and with one eriodictyol derivative and caffeic acid.
Regarding AD extracts (Figure 5B,D), a larger dispersion is observed between harvests, with a cluster being formed by L2 harvests in the 2018–2020 period, and then a strong dispersion is observed within L1 in the three-year harvest. L1-2019-AD clearly stands out as varying according to PC2, and it is correlated negatively with PC1 as a result of its higher RA, salvianolic acids, caffeic acid, and quercetin derivatives content. L1-2020-AD correlates poorly with PC2, being that these extracts are differentiated by a higher content in luteolin derivatives. L1-2018-AD, presents higher content of apigenin-[6,8]-C-diglucoside, the second highest caffeic acid concentration, but lower contents of quercetin derivatives, which assume a distinct position from the other L1 harvests. Of all the analyzed extracts, the AD extracts from L2 present the least variation among them.
Concerning the pentacyclic diterpenoids, (Figure 6 and Supplementary Table S1), we observed that L1 overall presented a higher content of both OA and UA when compared to L2 (with exception of UA content in 2019), and within the 2018–2020 period, 2020′s harvest presented the highest content of terpenoids (OA: 55.80 mg/g and UA: 51.84 mg/g). Oleanolic (OA) and ursolic (UA) acid have been described in T. carnosus HE extracts for the first time by Martins-Gomes, et al. 2018 [9], who reported a high content of both pentacyclic triterpenoids for both flowering stage (OA: 39.43 mg/g and UA: 75.17 mg/g) and post-flowering stage (OA: 41.74 mg/g and UA: 75.76 mg/g). A second conclusion can be retrieved when comparing vegetative phases, where, while OA content is similar to those presented by Martins-Gomes, et al. 2018 [9], the harvests of July and October favour a higher content in UA, whose highest content was 1.45 times higher than the observed for L1-2020-HE. Therefore, changes in the vegetative phase may induce differences in the production of such phytochemicals, that, similar to the ones observed for the phenolic acids described above, have a reduced concentration in November. Nevertheless, this comparison arises from an initial study from Martins-Gomes, et al. 2018 [9] with a single year analyzed. Additional studies for inter-year variation are essential to ascertain T. carnosus extracts’ phytochemical variation in response to vegetative phase changes and climate adaptation. It is possible to observe that November also benefits the production of flavonoids derivatives, and L1 (the location from where the species is native) presents overall higher content in the phytochemicals here analyzed, most likely a result of a better adaptation to the edaphoclimatic conditions.
The variation of oleanolic and ursolic acid was previously evaluated in the Thymus genus, in a single year harvest of plants grown in the same location, to study the variation induced by the vegetative stage in various species. In the various Thymus species analyzed by Raudone, et al. 2017 [21], *Thymus sibtorpii* Benth., *Thymus austriacus* Bernh. ex Rchb., Thymus × oblongifolius Opiz, and Thymus × citriodorus presented the highest content of OA and UA during the flowering stage, while *Thymus serpyllum* L., Thymus pulegioides, and *Thymus longicaulis* presented the highest content at the end of vegetative phase. Thus, we observe that pentacyclic terpenoids variation is also dependent on inter-species variation motivated by genetic variations, in addition to the edaphoclimatic parameters.
## 3.3. In Vitro Antioxidant Activity Assessment
The variation of herbal extracts’ antioxidant capacity induced by biotic and abiotic factors has been previously addressed for several species, as the antioxidant activity is one of the main sought-after bioactivities for these products. We report here, for the first time, the study of T. carnosus extracts antioxidant activity variation as a result of different edaphoclimatic parameters and inter-year variance. The results for ABTS•+, •OH, NO•, O2•−, and β-carotene bleaching assays are presented in Table 2.
ABTS•+ scavenging was used as a reference antioxidant assay to compare both the extracts here reported, but also to allow the comparison with other species. In Table 2, it is possible to observe that ABTS•+ scavenging results ranged between 0.15 and 0.25 mmol Trolox equivalent/DP. The highest scavenging value was obtained for L1-AD-2019, which also presented the highest TPC content (Table 1), and thus it correlated with the ABTS•+ scavenging for a higher content in reducing compounds, including phenolics and polysaccharides, for example. The lowest value was obtained for L2-HE-2020. Martins-Gomes, et al. 2018 [9], for T. carnosus, harvested in July October 2015, reported inhibitions of 0.14 and 0.21 mmol Trolox eq./DP, for AD and HE extracts, respectively, thus being comparable to the results here obtained. When compared to other Thymus species, our results align with the values reported for HE extracts T. vulgaris (0.22 mmol Trolox eq./DP) [31] and T. mastichina (0.20 mmol Trolox eq./DP) [23], whilst T. zygis (0.25 mmol Trolox eq./DP) presented higher inhibition for HE extracts. Concerning AD extracts, the T. carnosus extracts here presented performed better than T. x citriodorus (0.11 mmol Trolox eq./DP) [31] and T. mastichina (0.081 mmol Trolox eq./DP) [23], species commonly used for human consumption in herbal teas and as condiments. Concerning the inter-year variation, in AD extracts, L1-2018 presented an ABTS•+ scavenging activity significantly lower than the respective harvests in 2019 and 2020, whilst no significant variations were observed for L2. For the HE extracts, L1′s harvests did not present significant variations between years, however, in L2′s harvests, the 2018-HE-L2 extract presented significantly higher ABTS•+ scavenging. When comparing the variation induced by the different locations, AD extracts scavenging was only statistically different in 2020, where L1-2020-AD presented higher antioxidant activity. In the HE extracts, significant differences were observed in 2018, as L2-2018-HE presented higher scavenging.
Aiming to study the correlation between the various individual phytochemicals and each bioactivity, score-plots similar to those presented in Figure 5 for PCA were obtained using the OPLS-DA (orthogonal partial least squares discriminant analysis) model. This analysis allows an easier interpretation and presents advantages to data sets comprising a higher number of observations than the number of variables, being proposed as a promising tool to highlight statistically significant components in comparable data sets [28,40]. The OPLS-DA model uses an orthogonal signal correction filter to identify the variations related to the prediction of a quantitative response from the variations not related to the prediction [40]. We present the correlations obtained by the OPLS-DA model when significant correlations were observed, and the models present an adequate degree of validation (models’ validation is presented in the Supplementary material). Using data obtained in ABTS•+ scavenging assays, score-plots were obtained using the OPLS-DA model, which are presented in Figure 7. Most of phytochemicals identified and quantified in T. carnosus extracts positively correlate with the ABTS•+ scavenging (Figure 7A). Quercetin-O-hexoside-hexuronide, luteolin-O-hexoside-pentoside, and caffeic acid present the lowest correlation with this antioxidant activity in HE extracts. CA content does not present a large variation influenced by either year or location. Quercetin-O-hexoside-hexuronide is present at the highest concentration in L1-2019-HE, L1-2020-HE, and L2-2020-HE, which are within the extracts that present lowest ABTS•+ scavenging, thus being the components that least explain the increase in scavenging as provided by OPLS-DA model. Eriodictyol-O-hexoside isomer 2 and luteolin-O-hexoside-hexoside isomer 1 are the components which better explain the variation observed. Regarding AD extracts (Figure 7B), acetyl-luteolin-O-hexoside-pentoside, SAK, and SAA iso were the phytochemicals with highest contribution to ABTS•+ scavenging variance. L1-2019-AD and L1-2020-AD present the highest content of these three phytochemicals among the AD extracts studied, thus supporting the correlation.
In addition to ABTS•+, the scavenging of biologically relevant radicals was also performed, namely, for radicals such as •OH, NO•, and O2•−, as well as β-carotene bleaching as a model for lipid peroxidation. The capacity of extracts in •OH scavenging in the absence of EDTA was dependent on their geographical origin, as L1 presented higher activity, obtaining inhibitions greater than $50\%$, and L1-AD-2019 produced the lowest IC50 (0.8 mg/mL; Table 2), once again correlating to the higher content in phenolic compounds. When analyzing inter-year variance, L1-2020-AD presented a significantly lower inhibition when compared to 2018 and 2019, whilst, in L2, 2019′s harvest presented a higher inhibition, although not significantly higher than L2-2018-AD and L2-2020-AD. In the presence of EDTA, all extracts performed in a similar manner, with approximately $30\%$ of inhibition as the maximum value obtained in these conditions. In similar manner to that described for ABTS, the OPLS-DA model was applied to data obtained from •OH scavenging assay in the absence of EDTA and is presented in Figure 7C. All phytochemicals correlate positively with •OH scavenging, with phenolic acids (by this order: CA, RA, SAA iso and SAK) being the components with the highest influence in •OH scavenging, in line with the phytochemical composition obtained by HPLC-DAD, where overall extracts from L1 present higher content in these phenolic acids.
The capacity of extracts in NO• scavenging followed a pattern identical to •OH scavenging, as presented in Table 2. L1-AD-2019 produced both the highest inhibition ($73.31\%$) and the lowest IC50 (0.57 mg/mL) values. Similarly, L1 extracts presented higher ability to scavenge this radical, most likely due to higher content of phenolic compounds. When compared to a previous report of NO• scavenging by T. carnosus extracts [9] ($41.79\%$; 1 mg/mL), our extracts presented higher potential, all achieving IC50 values bellow 1 mg/mL. Considering the different harvests in the same location, extracts from plants harvested in 2019 presented higher inhibition, at 1 mg/mL, as well as lower IC50 values (Table 2). OPLS-DA analysis for NO• scavenging (Figure 7D) also revealed a similar pattern to ABTS•+ scavenging, with all compounds correlating with the activity, supported by the higher content in phytochemicals observed in L1-AD-2019, producing the highest inhibition and lowest IC50. The compound with higher correlation is also identical to ABTS assay, acetyl-luteolin-O-hexoside-pentoside, whose highest content is observed in L1-2019-AD.
In this research, we report, for the first time, T. carnosus extracts’ ability to scavenge O2•−, as well as the potential to reduce lipid peroxidation (Table 2). All extracts displayed significant capacity to scavenge O2•− using the xanthine oxidase/NBT assay. Overall, AD extracts present higher inhibition mean values, but these are only significant in the L1-2019 harvest. The inhibition values ranged between $31.41\%$ (L1-HE-2018) and $49.72\%$ (L1-AD-2019) for the most efficient extract (Table 2). Unlike for •OH or NO• radicals’ scavenging, there is no pattern for the location effect concerning the extracts’ scavenging of O2•−, since, when comparing locations, L1-2018 performed more poorly than L2-2018, and, when comparing inter-year effect, it presented less activity than L1-2019 and L1-2020. L2-2018 presented less O2•− scavenging than the respective harvest at L1 and the other L2 harvests. T. fragrantissimus extracts capacity to scavenge this radical indicated an inhibition of $48.81\%$ for AD extracts, as well as $49.63\%$ for HE extracts [30], values similar to those obtained in the 2019 harvest (Table 2), which are also in line with results obtained for T. zygis methanolic extracts ($40.3\%$) [41] and for T. vulgaris aqueous extracts (~$45\%$) [42].
Concerning lipid peroxidation, as seen in Table 2, all extracts were able to greatly inhibit β-carotene bleaching, with the most effective extract being L1-HE-2020, as well as being the extract with higher phenolic and terpenoid compounds quantified by HPLC-DAD, with the maximum inhibition of $96.25\%$ at 1 mg/mL. Overall, HE extracts presented higher maximum inhibitions, with the exception of L2-2018, but the IC50 revealed a different pattern. Only in L1-2019 and L1-2020 were significant differences observed concerning the IC50 values, which were found between extraction methods, with AD extracts presenting lower IC50 values. Thus, HE extracts, most likely due to a higher phenolic content, generally achieve higher inhibition, whilst AD extracts achieve about $50\%$ of inhibition with equal or slightly lower concentrations (Table 2). Concerning inter-year variation, in both AD and HE extracts, an increase in β-carotene bleaching inhibition is observed with the year of harvest, as 2018 < 2019 < 2020, whilst, in L2, the harvests of 2019 present higher inhibition. OPLS-DA model analysis (Figure 7E) revealed that, in HE extracts, compounds with increased hydrophobicity among the components of the extracts, namely, oleanolic acid, ursolic acid, SAK, and acetyl-luteolin-O-hexoside-pentoside, positively influence the extracts’ ability to inhibit the bleaching. In AD extracts, with a lesser content in these phytochemicals, luteolin-O-hexoside-pentoside and SAA isomer present the highest contributions to explain the variance observed.
Concerning the β-carotene bleaching assay, T. mastichina extracts have been reported to produce an IC50 of 0.9 mg/mL [43], a much higher value than the ones reported in the present study (Table 2). Nevertheless, extracts of T. pulegioides [44], T. caespititus [25], and T. pseudolanuginosus [25] presents IC50 values of 30 µg/mL, 6.1 µg/mL, and 2.4 µg/mL, respectively, thus showing higher potential to reduce lipid peroxidation when compared to T. carnosus extracts.
In sum, both extraction methods, year of harvest and location, induce significant variations in the overall antioxidant capacity of T. carnosus extracts. In addition, this activity, although reported for the various tested radicals, reveals that the differences in each extract’s composition (within each extraction method) induce variations in the scavenging ability, highlighting a capacity that is dependent of the radical selected. Considering its health-promoting effects, it is here demonstrated that T. carnosus bioactive components might be effective tolls to counter the oxidative stress activity in biological systems, which still requires further studies.
Various extracts of *Gingko biloba* obtained from material harvested in various locations in India over three different seasons showed that, in addition to a direct correlation between the phenolic content and antioxidant activity, the highest values of both parameters were reported in the autumn, where the antioxidant activity was expressed as ABTS and DPPH radicals scavenging [45]. In Thymus spp., variation of antioxidant activity induced by seasonal changes and developmental stages was also reported. Using essential oils from T. vulgaris harvested in Brazil over a twelve months period, Lemos, et al. 2017 [16] observed that ABTS and DPPH radicals scavenging was higher in Spring, correlating with a high content of thymol and carvacrol. Regarding the developmental stages, aqueous extracts from *Thymus hirtus* Boiss. and Reut., harvested in Tunisia, in a single year, in various vegetative phases and rich in catechin and epicatechin, were reported to present the highest antioxidant activity at flowering stage [46]. In T. longicaulis methanolic extracts, rich in RA, salvianolic acid K and luteolin derivatives, having a more similar phytochemical profile to the extracts of T. carnosus here reported, it was observed that, in a nine months period, the scavenging activity of ABTS and DPPH radical varied greatly, with IC50 values ranging 8.91–72.01 µg/mL and 9.50–64.61 µg/mL for ABTS and DPPH radicals, respectively, which provide a new insight into a significant variation of the antioxidant activity dependent of the date of harvest [20]. Nevertheless, even extracts from commonly consumed species, such as T. vulgaris, present reduced information regarding the variation of bioactivities induced by changes in the harvests’ location and date.
## 3.4. Enzymatic Inhibition Assays
In Table 3 are presented the results for T. carnosus extracts’ inhibition of key enzymes often described as druggable targets aiming neuroprotection (AChE and tyrosinase), anti-aging (tyrosinase and elastase), and diabetes management through lowering the intestinal absorption of glucose (α-amylase and α-glucosidase). With the exception of reports on T. carnosus essential oil activity in AChE inhibition [47], we present here, for the first time, the evaluation of T. carnosus AD and HE extracts’ anti-enzymatic activity described above.
Concerning potential neuroprotection effect, all extracts were effective in inhibiting AChE and tyrosinase activity, the most efficient extracts being L1-2019-AD for AChE and L2-HE-2020 for tyrosinase. All AD extracts presented significantly higher capacity to inhibit AChE when compared to the respective HE extract, despite the lower content in phenolic compounds (quantified by HPLC-DAD; Figure 2, Figure 3 and Figure 4). This may be explained by the presence of other water-soluble non-phenolic components that are extracted by the AD method that present the capacity to inhibit this enzyme. T. carnosus essential oil has been reported to inhibit AChE activity, with an IC50 of 0.72 mg/mL [47], and thus it is in-line with the extracts here present, whose best inhibition value at 1 mg/mL (L1-2019-AD) was $61.47\%$ inhibition. Rich in RA, T. pulegioides extracts presented a higher efficiency in inhibiting AChE, being able to reduce the enzyme activity in almost $90\%$ at 0.5 mg/mL [24]. T. vulgaris ethanolic extracts produced an inhibition above $75\%$ at 1 mg/mL [48], which is also higher than the values here reported (Table 3). A similar comparison can be performed for T. serpyllum ethanolic and aqueous extracts, which inhibited $50\%$ of AChE activity at 0.25 and 0.35 mg/mL, respectively [49]. On the other hand, T. fragrantissimus extracts produced lower inhibitions, being able to inhibit only $27.30\%$ at 0.5 mg/mL [30].
The OPLS-DA model was used to evaluate the influence of individual phytochemicals present in T. carnosus extract in AChE inhibition variation, as is presented in Figure 8A for HE extracts and Figure 8B for AD extracts. For HE extracts, eriodictyol-O-hexoside isomer 2, luteolin-O-hexoside-hexoside isomer 1, acetyl-luteolin-O-hexoside-pentoside, and the two quercetin derivatives are the individual components which most contribute to explain the increase in AChE inhibition. Quercetin was used as the positive control for this assay, as it inhibits AChE activity significantly, and thus quercetin’s glycoside derivatives identified in T. carnosus HE extracts likely also present inhibitory activity. In AD extracts, luteolin-O-hexoside-hexoside isomer 1 is also a major contributor to the variance observed in AChE inhibition, namely, in its increase.
Considering the location effect, L1, AD, and HE extracts, from the 2018 and 2019 harvests, produce greater AChE inhibitions. For the 2020 harvest, identical AChE inhibition was obtained with L1 and L2 HE extracts ($p \leq 0.05$). However, L2-AD-2020 has a greater capacity to inhibit AChE than L1-AD-2020. Regarding the inter-year variation, L1-HE extracts produced no variation in AChE inhibition, while L1-AD extracts harvested in 2020 produced a significant decrease in AChE inhibition. For L2′s extracts, AD extracts’ anti-AChE inhibition increases in 2019 and 2020, when compared to 2018, and HE extracts also present significantly higher inhibition in 2020.
The inhibition of tyrosinase activity by T. carnosus extracts is dependent on their phytochemical content, since the HE extracts always present higher inhibition than the AD extracts. However, L1-2020-HE, the extract with higher phenolic acids, flavonoids, and terpenoids quantified by HPLC-DAD did not produce the highest inhibitory effect. Overall, the extracts present potential for neuroprotection, with efficacy varying based on location and year of harvest, but without a defined pattern (Table 3). T. fragrantissimus AD extracts were also able to inhibit tyrosinase ($56.30\%$ at 0.5 mg/mL) [30], while T. pulegioides presented a much higher inhibition capacity ($93.72\%$ at 0.5 mg/mL) [24]. Both species showed higher potential than T. carnosus, whose extracts were able to inhibit a maximum of $42.54\%$ for L2-2020-HE (Table 3).
T. carnosus extracts presented a poor efficacy regarding elastase inhibition, thus not being the primary potential choice for anti-aging applications, unlike T. fragrantissimus HE extracts that inhibited $48.69\%$ of elastase activity [30]. T. carnosus extracts here presented (Table 3) showed a pattern similar to T. pulegioides [24], where no elastase inhibition capacity was observed for HE extracts, but AD extracts were able to reduce elastase activity. The highest inhibition obtained in the present research was $7.31\%$ using L1-2019-AD (Table 3), which is also the best extract for AChE inhibition.
As with the results of tyrosinase inhibition, the inhibition of α-amylase activity is dependent on the phenolic and terpenoids content, since the inhibition induced by HE extracts is significantly greater than the respective AD extracts. Nevertheless, once again L1-2020-HE was not the best performing extract, suggesting that the overall composition and ratio between all components may play a role, which are opposed to the simple higher content in each individual component. The extracts were not able to induce a reduction in α-amylase activity greater than $6\%$, which are results in line with those obtained by Taghouti et al. [ 2018] using T. pulegioides extracts [24]. On the other hand, T. carnosus’ potential for anti-diabetic applications may be achievable through α-glucosidase inhibition, where a maximum inhibition of $27.37\%$ was achieved for L1-2019-AD.
Regarding the location, AD extracts from L1 (in all harvests) produced, on average, higher inhibition of tyrosinase activity than AD extracts from L2. While, for HE extracts, significantly higher inhibition was produced by extracts from L2 harvests in 2018 and 2019, but not in 2020. Regarding the harvest year variation, it was observed that AD-2019-L1 extract produced higher tyrosinase inhibition than the other AD extracts, while the best HE extract was from L2 during the harvest of 2020 when compared to the other harvest years.
The extraction method influenced anti-glucosidase activity, as well as L2-HE extracts from 2018 and 2020 harvests, which show higher content in phytochemicals and also show higher inhibition capacity. In an opposed pattern, L1-2019-AD produced significantly higher α-glucosidade inhibition when compared to the respective HE extract (Table 3).
The contribute of individual phytochemicals to α-glucosidase inhibition variation was also evaluated by OPLS-DA model, and it presented in Figure 8C for HE extracts and Figure 8D for AD extracts.
As determined by OPLS-DA model (Figure 8), the higher contribute to α-glucosidase inhibition variation produced by HE extracts is due to the presence of luteolin-O-hexoside-pentoside, eriodictyol-O-hexoside isomer 1, and quercetin-O-hexoside-hexuronide, which may be connect to the presence of sugar residues in these glycoside derivatives. Future analysis of the role of individual compounds in this bioactivity should address the effect of the presence of sugar residues in comparison to the aglycone to ascertain if these moieties have higher affinity to the enzyme’s active site. In fact, L2-2018-HE, the HE extract with higher α-glucosidase inhibition, is also the extract with higher content of luteolin-O-hexoside-pentoside and of the first eriodictyol-O-hexoside isomer identified, which correlates with the OPLS-DA model. For AD extracts, the compounds whose variation better explain the inhibition pattern are acetyl-luteolin-O-hexoside-pentoside and the salvianolic acids, factors correlated with the increase in phytochemicals observed in L1-2019-AD, which produced a significantly higher α-glucosidase inhibition.
At 1 mg/mL, T. carnosus extracts presented an α-glucosidase inhibition ~2.16 times and 2.71 times higher than T. fragrantissimus [30] and T. pulegioides [24] extracts at 0.5 mg/mL (the only concentration tested). Aqueous extracts of T. vulgaris (concentration not mentioned) were reported to inhibit $4\%$ and $20\%$ of α-amylase and α-glucosidase, respectively [50], which are also in-line with the results were reported. Therefore, T. carnosus extracts present a moderate potential for the reduction of post-prandial blood sugar uptake by inhibiting α-glucosidase. Moreover, despite the variations induced by the unique phytochemical composition of each extract, influenced by harvest year, location, and extraction method, all extracts present neuroprotective and anti-diabetic activity, and thus T. carnosus can be a reliable functional food for these applications. Although there are few reports for salvianolic acids’ ability to inhibit these key enzymes, salvianolic acid B presents potential to inhibit AChE, and salvianolic acid C has been shown to inhibit α-glucosidase [51,52]. RA and pentacyclic triterpenoids have been shown to inhibit AChE, α-glucosidase, and α-amylase activity, and thus the harvest at earlier vegetative stages may increase this potential effect [48,53,54,55]. Thus, it is also relevant for future studies to further unveil the potential effects of T. carnosus extracts bioactivities, especially at the gastrointestinal tract, since AD extracts present a wide array of potential bioactivities, and this is reported in the present research.
## 4. Conclusions
Considering the high number of species used for its health-promoting bioactivities and the large number of pharmaceutical products obtained from plants, it is essential to increase the screening for new medicinal plants and phytochemicals with pharmaceutical potential. In addition, due to the increasing number of species threatened by climate and anthropogenic factors, there is a risk of losing the potential applications of a high number of species that were never considered for screening. Aiming to increase the interest in T. carnosus and encourage a sustainable crop, in the present research we complement the previous work related to T. carnosus extracts phytochemical composition and anti-proliferative activity by further analyzing its neuroprotective, anti-aging, and antidiabetic activity, complementing the antioxidant activity and evaluating the effect of edaphoclimatic parameters in the phytochemical composition and bioactivities. In addition to a unique phytochemical composition, T. carnosus extracts are a promising source of rosmarinic and salvianolic acids, as well as glycoside derivatives of various flavonoids, where the vegetative stage plays a significant role in the concentration of each phenolics subclass.
Despite the variations in the phytochemical profile, the extracts maintained significant antioxidant and neuroprotective activities and moderate anti-diabetic activity in the three-year period, thus revealing the potential to induce health-promoting activities when included in the diet, as demonstrated by the AD extracts, but also as a source of phytochemicals. Further studies on T. carnosus extracts should be performed to complement the information available, such as studies on its antioxidant and anti-diabetic potential in in vitro and in vivo experimental models.
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|
---
title: Preparation and Evaluation of 6-Gingerol Derivatives as Novel Antioxidants
and Antiplatelet Agents
authors:
- Sara H. H. Ahmed
- Tímea Gonda
- Orinamhe G. Agbadua
- Gábor Girst
- Róbert Berkecz
- Norbert Kúsz
- Meng-Chun Tsai
- Chin-Chung Wu
- György T. Balogh
- Attila Hunyadi
journal: Antioxidants
year: 2023
pmcid: PMC10045534
doi: 10.3390/antiox12030744
license: CC BY 4.0
---
# Preparation and Evaluation of 6-Gingerol Derivatives as Novel Antioxidants and Antiplatelet Agents
## Abstract
Ginger (Zingiber officinale) is widely used as a spice and a traditional medicine. Many bioactivities have been reported for its extracts and the isolated compounds, including cardiovascular protective effects. Different pathways were suggested to contribute to these effects, like the inhibition of platelet aggregation. In this study, we synthesised fourteen 6-gingerol derivatives, including eight new compounds, and studied their antiplatelet, COX-1 inhibitor, and antioxidant activities. In silico docking of selected compounds to h-COX-1 enzyme revealed favourable interactions. The investigated 6-gingerol derivatives were also characterised by in silico and experimental physicochemical and blood–brain barrier-related parameters for lead and preclinical candidate selection. 6-Shogaol [2] was identified as the best overall antiplatelet lead, along with compounds 3 and 11 and the new compound 17, which require formulation to optimize their water solubility. Compound 5 was identified as the most potent antioxidant that is also promising for use in the central nervous system (CNS).
## 1. Introduction
Ginger, Zingiber officinale Rosc. ( Zingiberaceae), is a well-known culinary plant and herbal remedy for many diseases. Ginger root extracts have been reported efficient against nausea and vomiting, diarrhoea, inflammatory conditions, metabolic syndrome, hepatotoxicity, and cardiovascular diseases [1,2,3]. The plant is rich in bioactive secondary metabolites including terpenes and phenolic compounds. The latter group consists mainly of gingerols, shogaols, paradols, and zingerone [4,5], among which 6-gingerol has been reported to be the most abundant in fresh ginger roots [6].
A plethora of preclinical studies demonstrated antioxidant [7,8], antimicrobial [9,10], anti-inflammatory [11], neuroprotective [12], antiplatelet [13], anti-obesity [14], antihepatotoxic [15], and anticancer effects for 6-gingerol [16]. Great efforts have been devoted to synthesizing and studying semisynthetic derivatives inspired by the structure of 6-gingerol. In our recent review, we have discussed such studies covering more than 150 semi-synthetic compounds, based on which the antiplatelet activity of gingerol derivatives seems to be the most promising [17].
Cardiovascular diseases (CVDs) represent a leading cause of death worldwide, with approximately 17.9 million deaths every year, according to the World Health Organisation (WHO) reports [18]. Many factors are implicated in CVDs’ development and progression, including an imbalance between haemostasis and thrombosis [19]. Platelets represent a key element in this due to their crucial role in the coagulation cascade, and antiplatelet therapies are of fundamental importance in the treatment of cardiovascular and in cerebrovascular pathologies [20]. Cyclooxygenase 1 (COX-1), constitutively expressed in all tissues, is a key regulator of platelet activation [21]. It has also been reported that high reactive oxygen species (ROS) levels contribute to platelet activation and play a causal role in CVDs [22]. While currently marketed antiplatelet drugs are undoubtedly efficient, all of them have some clinical limitations [23,24]. Aspirin is a good example of this: it significantly reduces morbidity in CVDs [25], but its gastrointestinal (GI) side effects limit its use, especially in those patients who are susceptible to, or already experience, gastrointestinal ulcers [26]. Therefore, there is still a need for additional safe and efficient alternatives.
Phytotherapy may offer complementary supportive treatment options for CVDs [27], and ginger has been suggested for this purpose [3] due to its effectiveness in reducing platelet aggregation [2,28,29,30,31]. Related clinical studies have also been conducted. Young et al. reported an increase in the antiplatelet activity upon ginger consumption by nifedipine-treated patients [32]. A similar effect was observed upon ginger administration in patients with coronary artery disease [33]. On the other hand, no effect was observed on platelet aggregation and coagulation when ginger was administered to healthy humans [34,35]. Furthermore, promising results have also been reported for the antiplatelet activity of semi-synthetic gingerol derivatives [36,37].
Ginger and many of its constituents, particularly gingerols and shogaols, are considered potent antioxidants through scavenging various biologically relevant free radicals [38] and modulating a range of redox signalling pathways [17]. It is worth mentioning that the modulation of antioxidant pathways by 6-gingerol protects H9c2 cardiomyocytes from hypoxia-induced damage [39], and that ginger constituents also inhibit the NLRP3 inflammasome [40] that has a key importance concerning cardiovascular health [41,42].
In the present work, we aimed to introduce different changes to the skeleton of 6-gingerol, and test the antiplatelet, COX-1 inhibitory, and antioxidant activity to evaluate their pharmacodynamic potential as cardio- and cerebrovascular protective agents. Furthermore, it was also our aim to characterize key physicochemical parameters and central nervous system (CNS)-related basic pharmacokinetic behaviour of the gingerol derivatives, including their in vitro blood–brain barrier permeability, to evaluate their additional potential as CNS antioxidants.
## 2.1. General Information
Reagents were purchased from Sigma (Merck KGaA, Darmstadt, Germany) unless otherwise stated. Solvents (analytical grade for synthetic work and flash chromatography purifications and high-performance liquid chromatography (HPLC)-grade for analytical and preparative HPLC work) were obtained from Macron Fine Chemicals (Avantor Performance Materials, Center Valley, PA, USA), Chem-Lab NV (Zedelgem, Belgium), VWR International S.A.S., and Fontenay-sous-Bois, France. A commercial ginger extract was purchased from Xi’an Pincredit Bio-Tech Co., Ltd., China. COX-1 kit was obtained from VWR International Kft. Debrecen, Hungary (original source: Biovision Inc., Milpitas, CA, USA).
For purification of the compounds, flash chromatography was used on a CombiFlashfi Rf+ *Lumen apparatus* (TELEDYNE Isco, Lincoln, NE, USA) equipped with evaporative light scattering (ELS) and diode array detectors, and the stationary phases were RediSep prefilled silica columns and RediSep cartridges (Teledyne Isco Inc., Lincoln, NE, USA). Hereinafter, solvent system compositions are always given in volumetric ratios.
Preparative purifications over RP-HPLC were performed on a Kinetex XB C18 (5 μm, 250 × 21.2 mm) column on an Armen Spot Prep II integrated HPLC purification system (Gilson, Middleton, WI, USA) with dual-wavelength detection, with an adequately chosen combination of acetonitrile–water, and a flow rate of 15 mL/min. The purity of the compounds obtained was determined by RP-HPLC analyses on a system of two Jasco PU 2080 pumps, a Jasco AS-2055 Plus intelligent sampler connected to a JASCO LC-Net II/ADC equipped with a Jasco MD-2010 Plus PDA detector (Jasco International Co. Ltd., Hachioji, Tokyo, Japan) utilizing a Kinetex C-18 (5 μm, 250 × 4.6 mm) column (Phenomenex Inc., Torrance, CA, USA) and applying a gradient of $30\%$–$100\%$ aqueous AcN in 30 min followed by $100\%$ ACN for 10 min with a flow rate of 1 mL/min. Analysis of samples from the PAMPA and kinetic solubility assays was performed the same way, by using 3-point calibrations and integrating each compound at its UV absorption maximum.
1H- and 13C NMR spectra were recorded in CDCl3 or CD3OD using 5 mm tubes at room temperature on a Bruker DRX-500 spectrometer at 500 (1H) and 125 (13C) MHz with the deuterated solvents’ signal taken as reference. The heteronuclear single quantum coherence (HSQC), heteronuclear multiple bond correlation (HMBC), 1H-1H correlation spectroscopy (COSY), and nuclear Overhauser effect spectroscopy (NOESY) spectra were obtained using the standard Bruker pulse programs. 1H- and 13C NMR spectra for compounds 4, 12, 14–18 and 22 are available in the Supplementary Materials, Figures S9–S24. High resolution mass spectroscopy (HRMS) spectra were recorded on a Q-Exactive Plus hybrid quadrupole-orbitrap mass spectrometer (Thermo Scientific, Waltham, MA, USA) equipped with heated electrospray ionisation (HESI-II) probe that was used in positive or negative mode per needed. HRMS spectra for compounds 4, 12, 14–18 and 22 are available as Supplementary Materials, Figures S1–S8.
All bioactivity data processing, including the calculation of inhibition percentage, mean and corresponding standard error of the mean (SEM), and IC50 values, was performed by GraphPad Prism 8.0 (La Jolla, CA, USA). IC50 values were calculated from the sigmoidal dose–response curves obtained by the log(inhibitor) vs. response and variable slope (DPPH assay) or the log(inhibitor) vs. normalised response and variable slope nonlinear regression model. On the results obtained, no statistical evaluation was performed; instead, differences greater than two-fold were considered relevant. Plotting of the antiplatelet and COX-1 inhibitory IC50 values and the linear regression of the data was performed by Microsoft Excel.
## 2.2.1. Purification of 6-gingerol ((S)-5-hydroxy-1-(4-hydroxy-3-methoxyphenyl)decan-3-one) (1)
Ginger extract was purchased from Xi’an Pincredit Bio-Tech Co., Ltd., Xi’an, China. 6-Gingerol [1] was purified from the crude extract at up to a 4 g scale using flash chromatography (Silica, gradient elution of 0–$10\%$ of acetone in n-hexane) and obtained as a dark yellow oil ($36.8\%$ yield). 6-Gingerol [1] was then utilised to synthesize 6-shogaol [2], and subsequently 4,5-dihydro-6-shogaol [3], as published previously [43]. Compound 11 was derived from vanillin [7] and 2,4-nonanedione [10], and compound 13 from compound 11, as published previously [44].
## 2.2.2. Synthesis of 1-(4-hydroxy-3-methoxyphenyl)decan-3-one oxime (4)
Hydroxylamine hydrochloride (228 mg, 3.3 mmol) was added to a solution of compound 3 (304 mg, 1.1 mmol) in MeOH (5 mL) at room temperature. The reaction was monitored by thin-layer chromatography (TLC), the reaction mixture was purified by flash chromatography (Silica, gradient elution of 0–$30\%$ of EtOAc in n-hexane) to afford compound 4, a pale-yellow solid (255 mg, $74.8\%$) [37].
Compound 4. HRESIMS: C17H27NO3, [M+H]+ m/$z = 294.20694$ (calcd 294.20692), 1H NMR (500 MHz, in CDCl3): δH 6.83 (m, 1H), 6.70 (dd, 2H, $J = 13.8$, 7.6 Hz), 3.88 (d, 3H, $J = 3.5$ Hz), 3.48 (s, 1H), 2.77 (q, 2H, $J = 8.0$ Hz), 2.60 (m, 1H), 2.46 (m, 1H), 2.36 (m, 1H), 2.10 (t, 1H, $J = 7.6$ Hz), 1.50 (m, 2H), 1.31 (m, 2H), 1.28 (m, 7H), 0.88 (td, 3H, $J = 7.0$, 2.9 Hz) ppm. 13C NMR (125 MHz, in CDCl3): δC 161.8, 161.7, 146.6, 144.1, 144.0, 133.6, 133.4, 121.0, 114.5, 111.1, 56.1, 36.4, 34.6, 32.5, 31. 9, 31.9, 31.5, 30.0, 30.0, 29.4, 29.2, 27.9, 26.4, 25.8, 22.8, 14.2.
## 2.2.3. Synthesis of (3R,5S)-1-(4-hydroxy-3-methoxyphenyl)decane-3,5-diol (5) and (3S,5S)-1-(4-hydroxy-3-methoxy phenyl)decane-3,5-diol (6)
Compound 1 (100 mg, 0.34 mmol) was dissolved in EtOH (10 mL) and NaBH4 was added (38 mg, 1 mmol). The reaction was monitored by means of TLC and after completion (1 h) the solvent was evaporated in vacuo and water (20 mL) was added to the residue. The aqueous phase was extracted with EtOAc (3 × 20 mL), and the combined organic phase was dried over Na2SO4, filtered, and evaporated in vacuo resulting in a yellow oil (85 mg, $84\%$), which contained the gingerdiols in high purity (>$95\%$), which were separated via preparative HPLC ($50\%$ aqueous AcN) to yield compound 5 as a faint yellow oil, and compound 6 as a white powder. The compounds’ MS and NMR spectra were in good agreement with the literature data [38].
## 2.2.4. Synthesis of (E)-1-(4-hydroxyphenyl)dec-1-ene-3,5-dione (12)
p-Hydroxybenzaldehyde 8 (1000 mg, 8.2 mmol), boron trioxide (2280 mg, 32.8 mmol), and 2,4-nonanedione (2800 mg, 24.6 mmol) were mixed with 2 mL of DMF and heated to 90 °C. A solution of isobutylamine (150 mg = 202 µL, 4 mmol) in 2 mL of DMF was added dropwise over 2 h. The reaction mixture was stirred at 90 °C for 1 h then 50 mL of water was added. The resulting mixture was stirred at 60 °C for 1 h at room temperature overnight. The reaction mixture was extracted with EtOAc and the solvent was evaporated. Purification by flash chromatography (Silica, gradient elution, 5–$10\%$ EtOAc in n-hexane) afforded compound 12, a yellow solid (179 mg, $8.5\%$) [39].
Compound 12. HRESIMS: C16H20O3, [M−H]− m/$z = 259.1332$, (calcd 260.13342), 1H NMR (500 MHz, in CD3OD): δH 7.57 (d, 1H, $J = 15.9$ Hz), 7.50 (d, 2H, $J = 8.6$ Hz), 6.84 (m, 2H), 6.51 (d, 1H, $J = 15.9$ Hz), 2.42 (m, 2H), 1.67 (p, 2H, $J = 7.7$, 7.3 Hz), 1.39 (m, 4H), 0.97 (t, 3H, $J = 7.0$ Hz) ppm. 13C NMR (125 MHz, in CD3OD): δC 201.6, 179.6, 160.9, 141.3, 2 × 131.0, 128.1, 120.6, 2 ×116.9, 44.3, 40.9, 32.6, 26.5, 23.5, 14.3.
## 2.2.5. Synthesis of 2-methoxy-4-(2-(3-pentyl-1H-pyrazol-5-yl)ethyl)phenol (14), 4-(2-(3-pentyl-1H-pyrazol-5-yl)ethyl)phenol (15), and (E)-4-(2-(3-pentyl-1H-pyrazol-5-yl)vinyl)phenol (16)
To a stirred solution of compounds 11 or 12 (164 mg, 0.57 mmol/100 mg, 0. 38 mmol) in ethanol (2 mL), hydrazine monohydrate (71 mg = 71 µL, 1.4 mmol/134 mg = 48 µL, 2.67 mmol) and a catalytic amount of concentrated HCl were added. The reaction mixture was refluxed for 6 h, cooled to ambient temperature, evaporated in vacuo, and purified using preparative HPLC (MeCN: H2O 40:60 for compound 14 and 42:58 for 15 and 16) to afford compounds 14 (270 mg, $17.8\%$), 15, (22 mg, $22.3\%$) or 16, (23 mg, $23.6\%$) as pale-yellow solids [40].
Compound 14. HRESIMS: C17H24N2O2, [M+H]+ m/$z = 289.19111$ (calcd 289.19160). 1H NMR (CDCl3, 500 MHz): δH 6.83 (d, 1H, $J = 8.0$ Hz), 6.70 (dd, 1H, $J = 8.0$, 2.0 Hz), 6.67 (d, 1H, $J = 2.0$ Hz), 5.84 (s, 1H), 3.84 (s, 3H), 3.48 (s, 1H), 2.89 (m, 4H), 2.59 (t, 2H, $J = 7.7$ Hz), 1.64 (m, 2H), 1.35 (m, 2H), 1.33 (m, 2H), 0.90 (t, 3H, $J = 7.1$ Hz) ppm. 13C NMR (125 MHz, in CDCl3): δC 146.6, 144.2, 133.6, 121.2, 114.5, 111.3, 102.6, 56.1, 35.6, 31.7, 29.6, 29.2, 27.0, 22.6, 14.1.
Compound 15. HRESIMS: C16H22N2O, [M+H]+ m/$z = 259.18057$ (calcd 259.18104), 1H NMR (500 MHz, in CDCl3): δH 6.99 (d, 2H, $J = 8.4$ Hz), 6.71 (d, 2H, $J = 8.5$ Hz), 5.86 (s, 1H), 3.48 (s, 1H), 2.88 (t, 2H, $J = 3.9$ Hz), 2.87 (t, 2H, $J = 4.2$ Hz), 2.59 (t, 2H, $J = 7.7$ Hz), 1.63 (m, 2H), 1.34 (m, 2H), 1.31 (t, 2H, $J = 3.9$ Hz), 0.90 (t, 3H, $J = 7.1$ Hz) ppm. 13C NMR (125 MHz, in CDCl3): δC 154.7, 149.4, 148.9, 133.1, 2 × 129.6, 2 × 115.6, 102.6, 34.9, 31.6, 29.3, 29.1, 27.1, 22.6, 14.1.
Compound 16. HRESIMS: C16H20N2O, [M+H]+ m/$z = 257.16489$ (calcd 257.16539), 1H NMR (500 MHz, in CD3OD): δH 7.34 (d, 2H, $J = 8.6$ Hz), 7.01 (d, 1H, $J = 16.5$ Hz), 6.85 (d, 1H, $J = 16.5$ Hz), 6.77 (d, 2H, $J = 8.6$Hz), 6.24 (s, 1H), 2.62 (t, 2H, $J = 7.6$ Hz), 1.67 (m, 2H), 1.38 (m, 2H), 1.36 (m, 2H), 0.92 (t, 3H, $J = 6.8$ Hz) ppm. 13C NMR (125 MHz, in CD3OD): δC 158.6, 131.1, 130.2, 2 × 128.8, 2 × 116.6, 103.8, 32.6, 30.3, 23.4, 14.3.
## 2.2.6. Synthesis of (E)-2-methoxy-4-(2-(3-pentylisoxazol-5-yl)vinyl)phenol (17) and (E)-4-(2-(3-pentylisoxazol-5-yl)vinyl)phenol (18)
Hydroxylamine hydrochloride (144 mg, 2.1 mmol/134 mg, 1.9 mmol) and pyridine (165 mg = 169 µL, 2.1 mmol/152 mg = 155 µL, 1.9 mmol) were added to a stirred solution of compounds 11 and 12 separately (122 mg, 0.42 mmol/100 mg, 0.38 mmol) in ethanol (4 mL) and refluxed for 6 hrs. The reaction was monitored by TLC. Subsequently, the mixture was cooled to ambient temperature, evaporated in vacuo, and purified by flash chromatography (Silica, gradient elution, 0–$20\%$ acetone in n-hexane) to afford compound 17, a pale-yellow solid (96 mg, $79.3\%$), while product 18 was obtained as a pure compound from the reaction mixture as a pale-yellow solid (98 mg, $99\%$) [40].
Compound 17. HRESIMS: C17H21NO3, [M+H]+ m/$z = 288.15999$ (calcd 288.15996), 1H NMR (500 MHz, in CDCl3): δH 7.22 (d, 1H, $J = 16.4$ Hz), 7.04 (dd, 1H, $J = 8.1$, 2.0 Hz), 7.01 (d, 1H, $J = 2.0$ Hz), 6.92 (d, 1H, $J = 8.1$ Hz), 6.77 (d, 1H, $J = 16.4$ Hz), 6.06 (s, 1H), 5.77 (s, 1H), 3.95 (s, 3H), 2.66 (t, 2H, $J = 7.5$ Hz), 1.68 (m, 2H), 1.37 (m, 2H), 1.36 (m, 2H), 0.91 (t, 3H, $J = 7.2$ Hz) ppm. 13C NMR (125 MHz, in CDCl3): δC 168.5, 164.6, 147.0, 134.6, 128.5, 121.5, 114.9, 111.3, 108.9, 100.6, 56.1, 31.5, 28.2, 26.2, 22.5, 14.1.
Compound 18. HRESIMS: C16H19NO2, [M−H]− m/$z = 256.13644$ (calcd 256.13375). 1H NMR (500 MHz, in CDCl3): δH 7.39 (dd, 2H, $J = 8.6$, 1.8 Hz), 7.23 (d, 1H, $J = 16.4$ Hz), 6.85 (dt, 2H, $J = 8.6$, 2.9, 2.1 Hz), 6.77 (d, 1H, $J = 16.4$ Hz), 6.06 (s, 1H), 3.49 (s, 1H), 2.66 (t, 2H, $J = 7.5$ Hz), 1.68 (m, 2H), 1.36 (m, 2H), 1.35 (m, 2H), 0.90 (t, 3H, $J = 7.2$ Hz) ppm. 13C NMR (125 MHz, in CDCl3): δC 168.7, 164.6, 157.1, 134.4, 2 × 128.8, 128.6, 2 × 116.0, 111.2, 100.6, 31.5, 28.2, 26.2, 22.5, 14.0.
## 2.2.7. Synthesis of N-heptyl-3-(4-hydroxyphenyl) propenamide (22)
A solution of compound 21 (300 mg, 1.5 mmol) in dry CH2Cl2 (10 mL) was cooled to 0 °C, DCC (316 mg) and DMAP (18 mg, 0.2 mmol) were added, and the mixture was stirred for 1 h at 0° C, then heptylamine (153 mg = 0.197 mL) was added and the reaction was monitored over TLC. Subsequently, the solvent was evaporated, redissolved in dichloromethane, washed with NaHCO3 solution, and the organic phase was evaporated to dryness. The product was purified by flash chromatography (Silica, gradient elution of 20-$30\%$ acetone in n-hexane) to yield compound 22 as a white solid (431 mg, $92.7\%$) [41].
Compound 22. HRESIMS: C17H27NO3, [M+H]+ m/$z = 294.20680$, (calcd 294.20692), 1H NMR (500 MHz, in CDCl3): δH 6.83 (d, 1H, $J = 8.1$ Hz), 6.72 (d, 1H, $J = 2.0$ Hz), 6.68 (dd, 1H, $J = 8.0$, 2.0 Hz), 5.47 (s, 1H), 3.87 (s, 3H), 3.20 (td, 2H, $J = 7.2$, 5.7 Hz), 2.89 (t, 2H, $J = 7.5$ Hz), 2.42 (t, 2H, $J = 7.5$ Hz), 1.43 (m, 2H), 1.26 (m, 8H), 0.88 (t, 3H, $J = 6.9$ Hz) ppm. 13C NMR (125 MHz, in CDCl3): δC 172.2, 146.6, 144.2, 133.0, 121.0, 114.5, 111.2, 56.3, 39.7, 39.2, 31.9, 31.7, 29.8, 29.1, 27.0., 22.7, 14.2.
## 2.3.1. Antiplatelet Activity
Human platelet suspension (3 × 108/mL in Tyrode’s buffer) was prepared as previously described [42]. The protocol for this study was approved by the institutional review board of Kaohsiung Medical University Hospital (Kaohsiung City, Taiwan). Platelets pre-treated with DMSO (vehicle control) or test compounds were stimulated with arachidonic acid (AA), and platelet aggregation was measured using turbidimetric aggregometer (Chrono-Log Co., Havertown, PA, USA) at 37 °C under stirring conditions (1200 rpm).
## 2.3.2. Diphenyl-2-picrylhydrazyl (DPPH) Scavenging Activity
DPPH (1,10-diphenyl-2-picrylhydrazyl) was purchased from Thermo Fisher Scientific. DPPH free radical scavenging assay was performed with some modifications based on the method by previous study [43]. Briefly, in a 96-well microplate, microdilutions of samples (100 µL, starting from 200 µM in HPLC grade MeOH) were made and 100 µL of DPPH reagent (100 µM in MeOH) was added. After 30 min at room temperature in the dark, the absorbance was measured at 550 nm using a FluoStar Optima plate reader (software version 2.20R2, BMG Labtech Ortenberg, Germany). For the blank control, MeOH was used. The scavenging activity was calculated as Inhibition (%) = (A0 − As)/A0 × 100, and IC50 values were calculated by GraphPad Prism 8.0 (La Jolla, CA, USA).
## 2.3.3. Oxygen Radical Absorbance Capacity (ORAC)
AAPH ((2,20-Azobis(2-methyl-propionamidine) dihydrochloride) free radical and Trolox standard were purchased from Sigma-Aldrich Hungary. Fluorescein was purchased from Fluka Analytical, Tokyo, Japan. ORAC assay was carried out *In a* 96-well microplate based on the method from previous study [44]. Briefly, 20 µL of the samples (1 µM final concentration, dissolved in phosphate buffer, pH = 7.4, containing $1\%$ MeOH) were mixed with 60 µL of AAPH (12 mM final concentration, dissolved in phosphate buffer, pH = 7.4) and 120 µL of fluorescein solution (70 nM final concentration, dissolved in phosphate buffer), then the fluorescence was measured (excitation at λ = 485 nm, and emission at λ = 520 nm) through 3 h with 1.5-min cycle intervals with a BMG Labtech FluoStar Optima plate-reader. All experiments were carried out in triplicate, and Trolox was used as standard. The antioxidant capacity is expressed as Trolox Equivalent (TE), as calculated using GraphPad Prism 8.0 (La Jolla, CA, USA).
## 2.3.4. Xanthine Oxidase Inhibitory Activity
The xanthine oxidase (XO) inhibitory activity of the compounds was determined using continuous spectrophotometric rate based on a modified protocol of Sigma. The samples were prepared in. In a 96-well plate, the final reaction mixture consisted of 10 µL of sample (dissolved in DMSO, 30 mM stock solution, 100 µM final), 100 µL of xanthine solution (0.15 mM, pH = 7.4), 140 µL of buffer (potassium phosphate, pH = 7.5) and 50 µL of XO (0.2 units/mL). When measuring the enzyme activity, control buffer was used in place of the sample. Allopurinol was applied as a control. The reaction was initiated by the automatic addition of 50 µL of XO solution. The absorbance of XO-induced uric acid production from xanthine was measured at 290 nm for 3 min in a 96-well plate on a BMG Labtech FluoStar Optima plate reader. The inhibitory percentage values were calculated by using Graph Pad Prism 8.0 (La Jolla, CA, USA).
## 2.3.5. Peroxynitrite Scavenging Activity
Peroxynitrite was synthesised by a continuous flow system using syringe pumps as published previously [45]. Briefly, an acidic solution of hydrogen peroxide (0.6 M H2O2, 0.7 M HCl) was pumped to a junction alongside of sodium nitrite solution (0.6 M) at a flow rate of 1.5 mL/min. After passing 10 cm of tubing, it was mixed with a sodium hydroxide solution (1.5 M), also pumped at 1.5 mL/min. The resulting peroxynitrite solution was a bright yellow colour. The tubing around the reaction was submerged in ice. The concentration of the solution was determined by spectrophotometry and was adjusted to 30 mM with 0.1 M NaOH solution.
In a 96-well microplate 245 µL of pyrogallol red (100 µM final concentration, dissolved in 0.1 M glycine buffer) was mixed with 50 µL of sample (0.5 mM final concentration, dissolved in DMSO) and 5 µL ONOO– solution (500 µM final concentration, freshly prepared). After mixing and keeping it at room temperature for 30 min the absorbance was measured at 550 nm using a FluoStar Optima plate reader (software version 2.20R2, BMG Labtech, Ortenberg, Germany).
## 2.3.6. COX-1 Inhibitory Activity
COX-1 inhibitory activity was tested based on the fluorometric method as described in BioVision’s COX-1 inhibitor screening kit leafkit (K548-100, BioVision, CA, USA). Sample solutions were prepared by dissolving in DMSO and subsequently buffer, to get desired concentrations. In a 96-well white plate (655101, F-bottom, Grenier bio-one, Germany), 80 µL reaction mix (containing 76 µL assay buffer, 1 µL COX Probe, 2 µL COX cofactor, and 1 µL COX-1 enzyme) was added to 10 µL sample solution, DMSO and assay buffer to get test wells assigned for sample screen (S), negative control (N) and blank, respectively. An aliquot of 10 µL of arachidonic/NaOH solution was added to each well using a multi-channel pipette to initiate the reaction at the same time, and the fluorescence of each well was measured kinetically at Ex/Em $\frac{550}{610}$ nm, at 25OC for 10 min using a FluoStar Optima plate reader (BMG Labtech, Ortenberg, Germany). The COX inhibitory activity of SC560, a standard inhibitor, was also determined.
The change in fluorescence between two points, T1 and T2 were determined, and relative inhibition was calculated according to the following equation:% Inhibition = (ΔN − ΔS)/ΔN × 100 [1] where N is the absorbance of the negative control, and S is that of the sample.
Dose-effect studies on the compounds were used to determine the concentration that inhibits $50\%$ of the enzyme activity. The sigmoidal dose–response model was obtained by using the software GraphPad Prism 8.0 (La Jolla, CA, USA), and these were used to determine the IC50 values of the compounds.
## 2.3.7. Physicochemical Character and Blood–brain Barrier Specific Permeability
Basic physicochemical parameters for drug design and candidate selection were calculated by Percepta Software Package (ACD/Labs, Toronto, Ontario, Canada) [46]. Tautomers and it is distributions for compounds 11, 12 and 13 were generated by Marvin Sketch and Tautomer Generator (Chemaxon Ltd., Budapest, Hungary) [47], which is freely accessible with academic license.
For kinetic aqueous solubility studies each sample was dissolved in DMSO to make 10 mM stock solutions. In a 96-well polypropylene plate (Greiner Bio-One, Kremsmünster, Austria), 15 μL stock solutions were added to 285 μL PBS (pH 7.4) to make starting donor solution with 500 μM as target concentration. For each sample, 3 replicates were measured. The samples were covered and shaken at 37 °C, 300 rpm for 2 h (Heidolph Titramax 1000, Heidolph Instruments GmbH & Co. KG, Schwabach, Germany). After that, each sample was transferred into a filter plate (MSSBLPC, Multiscreen Filter plate, Merck kGaA) and filtered (Vaccum Manifold, Merck kGaA, Darmstadt, Germany). The filtrates were transferred into HPLC vials, and acetonitrile (AcN) was added to aliquot to avoid precipitation. The final solvent ratio was AcN:PBS (70:30). Filtrate concentration was determined by HPLC-UV (see Section 2.1) using 3-points calibration.
Blood–brain barrier-specific (BBB) permeability measurements were carried out us- ing the PAMPA-BBB model. First, solutions with 500 μM target concentration were prepared as described for the kinetic solubility study. The solutions were sonicated for 10 min at room temperature. To prepare the artificial BBB-specific membrane, 16 mg BPLE were dissolved in 600 μL of n-dodecane:n-hexane (25:75). Each well of the donor plate (MultiscreenTM-IP, MAIPNTR10, pore size 0.45 mm, Merck kGaA) was coated with 5 μL lipid solution and fitted into the acceptor plate containing 300 μL PBS (pH 7.4) with $5\%$ DMSO, and 150–150 μL of the PBS solutions (made from the DMSO stock solutions) were placed on the donor plate’s artificial membrane. The sandwich plate system was covered with a tissue of wet paper and a plastic lid to avoid evaporation of the solvent, and it was incubated at 37 °C for 4 h. In the end, the initial 500 μM solutions (cD0), the donor (cDt) and acceptor solution (cAt) were analysed by HPLC-UV (see Section 2.1). BBB permeability was calculated using the effective permeability equation used for iso-pH conditions described by A. Avdeef [48] as follows. [ 2]Pe=−2.303A·t−τss·11+rv·lg−rv+1+rv1−MR·cDtcD0 [3]MR=1−cDtcD0−VAcAtVDcD0 where A is the filter area (0.3 cm2), VD and VA are the volumes in the donor (0.15 cm3) and acceptor phase (0.3 cm3), t is the incubation time (s), τss is the time to reach steady state (s), cDt is the concentration of the compound in the donor phase at time point t (mol/cm3), cD0 is the concentration of the compound in the donor phase at time point zero (mol/cm3), cAt is the concentration of the compound in the acceptor phase at time point t (mol/cm3), rv is the aqueous compartment volume ratio (VD/VA).
## 2.3.8. Molecular Docking
Compounds’ structures were drawn and saved in PDB format using ChemDraw 12.0.2 software (ACD/LABS, Advanced Chemistry Development, Inc.) [45]. The h-COX-1 enzyme structure was retrieved from the PDB database. PDB files for the enzyme and compounds were converted to the PDBQT format using the graphical user interface of AutoDock4 (The Scripps Research Institute). A grid box (X: −33.050, Y: −47.920, and Z: 0.234; the number of grid points in the three dimensions [npts]: X: 40, Y: 60, and Z: 60; spacing: 0.375) was set to include the amino acids mentioned by L. Tóth to characterize the binding site [46]. Docking parameters were set to the default values and ligands were docked via the Lamarckian algorithm. The binding energies were obtained from the resulting DLG files, and interactions visualisation was achieved via Biovia (Discovery Studio visualizer version 21.1.0.20298; Dassault Systèmes, Vélizy-Villacoublay, France) after conversion of the docked PDBQT files into PDB files using OpenBabel GUI software version 2.4.1 [47].
## 3.1. Chemistry
In this work, a commercially available ginger extract was utilised to obtain significant amounts of our selected starting material, 6-gingerol [1], which could be obtained in a single-step purification using flash chromatography. Using compound 1 as a starting material, 6-Shogaol [2] was synthesised according to a literature method [43], and subsequent hydrogenation resulted in 6-paradol [3] [43] in an excellent yield. The reaction of 3 with hydroxylamine hydrochloride resulted in an oxime derivative as a mixture of (E/Z) isomers [4].
Reduction of the keto function of 6-gingerol resulted in 6-gingerdiol epimers 5 and 6 in a ratio of 3 to 2, respectively. The compounds were separated by preparative HPLC, and their structures were confirmed by HRMS and one- and two-dimensional NMR techniques, and by comparing their relevant spectral data to literature values [49,50,51]. Heating and cooling did not affect the stereoselectivity of the reaction. Compounds prepared directly from 6-gingerol are presented in Scheme 1.
We also aimed to expand our study towards the chemical space around 6-dehydrogingerdione. To achieve this, a total synthetic approach was adopted (Scheme 2). First, 6-dehydrogingerdione [11] and its analogue lacking the aromatic methoxy function were synthesised starting from vanillin [7] or 4-hydroxybenzaldehyde [8] and 9-nonanedione according to a published method [44]. Catalytic hydrogenation of the double bond yielded compound 13 (6-gingerdione) [44]. The structure of compound 12 was confirmed using HRMS and NMR, and although the proton resonance of the enol methylene was not observed, the presence of carbon atoms at δC 201.6 and 179.6 clearly showed that 12 undergoes keto-enol tautomerisation in solution.
To facilitate exploring structure–activity relationships, oxygen and nitrogen-containing heterocyclic analogues were also prepared. Interestingly, the reaction of dehydrogingerdiol [11] and [12] with hydrazine monohydrate yielded two detectable products in both cases. Regarding the derivatives of 12, both products (15 and 16) were successfully isolated. On the other hand, in the case of compound 11, only compound 14 was isolated in a reasonable amount. Reactions of 11 and 12 with hydroxylamine hydrochloride resulted in oxazines 17 and 18, respectively. Unfortunately, some of the non-protonated aromatic carbons were not detected in the 13C NMR spectrum due to their long relaxation time after the irradiation, but the characteristic 1H proton resonances, HRMS spectra and spectral behaviour of the compounds allowed the establishment of their chemical structures.
To investigate bioactivity changes upon replacing the keto group of compound 3 with an amide, we also prepared a capsaicin-like derivative [22]. This was synthesised via a two-step procedure, starting with the catalytic hydrogenation of ferulic acid [19] to compound 20, followed by its DCC/DMAP-mediated coupling with heptylamine (Scheme 3).
## 3.2. Predicted and Experimental Physicochemical and BBB Penetration-Related Characterisation
The characterisation of the 6-gingerol derivatives was started with the determination of their physicochemical and blood–brain barrier (BBB)-specific permeability properties, which are commonly used in early-stage drug discovery. The study was carried out on two levels: (a) an in silico approach, using lead optimisation parameters and the Central Nervous System Multiparameter Optimisation (CNS MPO) compliance introduced by Wager et al. [ 52]; and (b) experimentally, through determination of kinetic solubility and in vitro BBB permeability of the test compounds. Predicted and experimental data are shown in Table 1.
Combining Lipinski’s rule of five (Ro5) [53] and CNS MPO [52] criteria systems, the proton dissociation and lipophilicity properties of 6-gingerol derivatives were compared in a first approach. Regarding their acid–base character, the compounds can be classified into three groups: (i) monoprotic phenols (1–6, 17, 18 and 22), (ii) diprotic amphoterics (imidazole derivatives; 14–16), and (iii) diprotic acids (gingerdione derivatives; 11–13). The proton-dissociation behaviour of gingerdione derivatives is particularly interesting due to their tautomeric states shown in Scheme 3. The distribution % of the A-C tautomeric states of derivatives 11–13 was generated using Chemaxon Ltd.’s freely available Tautomer Generator plugin. This suggests compounds 11–13 to be mostly present in their enol forms (A:B, ~30:$60\%$), while the dione forms with C-H acid function are much less expressed (C, ~$10\%$). It is also important to note that, while in the case of the other gingerols (1–6, 14–22) the strongest pKa,acid values refer to the aromatic OH function, the pKa,acid parameters indicate the proton-dissociation behaviour of the enol and dione C-H acid functions for 11–13. Thus, based on these pKa,acid values, two conclusions can be made. First, in the case of 11–13, the stronger acid function can be assigned to the enol and C-H acid moiety, and second, the acidic character of the A, B tautomeric forms is stronger than that of the C forms. In terms of lipophilicity, all 6-gingerol derivatives meet the drug-likeness criterion of Ro5 (logP < 5). At the same time, based on the two-level risk classification created by the lead-like [54] and CNS MPO criteria (logDpH7.4), 2–4 and 14–18 exceed (see Table 1, magenta: high violation), and 22 approach (yellow: moderate violation) the logDpH7.4 violation limit. The lipophilicity values of the tautomers of 11–13 also show a marked difference. For all three compounds, the enol forms A/B (11A, 12A, 13B) are more lipophilic than the dione forms (C), which also manifests in the corresponding CNS MPO values. Regarding the next medchem parameter, the polar surface area (TPSA), all the tested gingerols satisfy both the Veber’s rule (30Å2 < TPSA < 140Å2) for bioavailability [55] and the CNS MPO range (40Å2 < TPSA < 90Å2) [52]. CNS MPO values (physchem-based CNS compliance) of gingerols were evaluated by a three-level classification system (green–yellow–magenta) for easier overview. Compounds 1–3, 5–6, 11–13, 17 and 22 (green–yellow) can be considered as suitable candidates for further CNS-targeted preclinical studies. In the case of 11–13, due to the lipophilicity and HBD differences of the tautomers, the C tautomeric forms carry the optimal CNS MPO character. In addition to the predicted parameters, experimental kinetic solubility (PBS, pH 7.4) and in vitro BBB-specific permeability (PAMPA-BBB) of the compounds were also determined. Also applying a three-level classification for the kinetic solubility values, the compounds 1, 2, 5, 6, 13–15 and 22 were in the acceptable range (greater than 100 μM). In parallel, due to limitations resulting from poor solubility, we could only determine the permeability of these gingerols using PAMPA-BBB study. In Table 1, compounds 1, 2, 5, 6 and 22 are highlighted in green (Pe,BBB ≥ 25·10−7 cm/s), for which we identified increased BBB permeability. In addition to these compounds, 14–15 are also adequate for BBB penetration. In the case of 13, the increased hydrophilic character may impair the BBB permeability.
## 3.3. Antiplatelet Aggregation and COX-1 Inhibition Activity of the Compounds
The arachidonic acid (AA)-cyclooxygenase-1 (COX-1) pathway plays an important role in platelet activation [56]. Aspirin, the standard antiplatelet drug, can prevent AA metabolism to thromboxane A2 by inhibiting COX-1, and thus exert antiplatelet effects [57]. To evaluate similar bioactivities of 6-gingerol [1] and its derivatives, the compounds were tested for their inhibitory effects on AA-induced platelet aggregation. Compounds 3, 2, 17, 16, and 13 showed the most promising results, with IC50 values of around 2–4 µM, respectively, while the effects of 6-gingerol [1] and aspirin were up to 22 and 50 times weaker, respectively (Table 2).
The antiplatelet mechanism of action of 6-gingerol and its derivatives has previously been suggested to be COX-1 inhibition [37,58,59]. The results obtained for the newly synthesised compounds are in accordance with this notion. The IC50 datasets of Table 2 give a linear correlation coefficient (R2) value of 0.887 (Supplementary Materials, Figure S26), strongly suggesting that COX-1 inhibition is indeed the mechanism behind the observed antiplatelet action.
Concerning structure–activity relationships, our results suggest the importance of an aromatic methoxy group, as seen by comparing the IC50 values of 11 vs. 12, 14 vs. 15, and 17 vs. 18. Interestingly, this rule did not apply for compound 16. This may underline a possible role of the Δ1,2 olefin in some cases, e.g., when it is conjugated with a pyrazole ring. Presence of the 5-OH group is highly unfavourable; its elimination (as in compounds 2, 3, and 4) increased antiplatelet activity by ca. an order of magnitude, as well as its oxidation (compound 13 vs. 1) or replacement by a heterocycle (e.g., compound 14 vs. 1).
Compound 22, in which the β-keto alcohol function of compound 1 was replaced by an amide group, showed only moderate activity. Notably, however, replacing the 3-oxo group by an oxime group led to only a slight, ca. 2-fold decrease in the antiplatelet activity (IC50 = 5.2 µM), while this chemical change opened the way to diverse further functionalisation possibilities.
Our results come in accordance with previous reports on compound 3, i.e., 6-paradol that is naturally present in ginger roots.
Since the mid-2000s, the entropic or lipophilicity-driven lead optimisation constraint has mainly been observed in CNS-targeted drug discovery, significantly increasing the number of clinical candidates that were promiscuous or otherwise carrying off-target effects and toxicity risks [60]. To reduce this issue, several ligand efficiency metrics have been introduced [61], which can be used to filter out this effect. In this context, in our study, the IC50 data obtained on the two biological targets were evaluated using the ligand-lipophilic efficiency (LLE = pIC50−logP) metric [60]. After, a two-conditions-based lead selection was performed using the IC50 and LLE values, where the LLE values of 6-gingerol derivatives with an IC50 ≤ 10 µM and an LLE value higher than 1.0 were highlighted (Table 2, compounds coloured green for LLEAntipatelet: 2, 3, 11, 13 and 17 and LLECOX-1: 3). Summarizing the data in Table 1 and Table 2, due to the strict selection, only compound 2 can be assigned as a primary candidate for further preclinical studies, while compounds 3, 11 and 17 are potential leads that require an appropriate formulation to improve their aqueous solubility. From the point of view of lead optimisation, compound 3 is particularly interesting, satisfying the LLE/IC50 screening criteria for both biological targets. Compound 13 can also be identified as a secondary lead, for which the further goal may be fine-tuning the BBB permeability property.
## 3.4. Molecular Docking
Compounds were docked using AutoDock4 into the human COX-1 enzyme crystal structure retrieved from the Protein Data Bank (PDB ID: 6Y3C). Grid parameters were set to centre at residue Ser530 and to include residues Tyr385, Arg120, and Tyr348 that are in the COX-1 binding pocket [62]. In the cases of compounds 11, 12, and 13, the tautomeric forms A–C were subjected to in silico docking. Detailed results of the docking study are provided as Supplementary Materials, Table S1.
The highest binding affinity (−9.5 Kcal/mol) was found for the new isoxazole-containing compound 17, which was also among the most potent antiplatelet derivatives. L-Toth et al. discussed the importance of Tyr385 and Ser530 in the irreversible binding of aspirin to COX-1 active site; notably, the docking results showed hydrogen bonding interactions with Ser530 in the case of compound 1, 4, and 6, while compounds 11B, 12A, and 22 appeared to interact via hydrogen bonds with Tyr385 (Table S1). Interestingly, compound 17 did not show any of the above-mentioned interaction with either of these amino acids (Figure 1).
## 3.5. Antioxidant Assay
Antioxidant activity was assessed using multiple models, including DDPH, ORAC, ONOO− scavenging, and XO inhibition assays; results are shown in Table 3. Compounds 5, 17, 4, 1, and 11 showed the best activity in the diphenyl-2-picrylhydrazyl (DPPH) scavenging capacity assay. Among these, compound 5 is clearly the most promising antioxidant lead, considering its DPPH-scavenging IC50 value, its ORAC value, which is more than twice as potent as that of Trolox, and its predicted and experimental pharmacokinetic parameters. Interestingly, compound 6, the three-epimer variant of 5, showed only ca. half of the activity of 5 in the DPPH assay and was also weaker in terms of ORAC. Similar to the results obtained for the antiplatelet and COX-1 inhibition assay, the importance of an aromatic methoxy group for potent DPPH scavenging activity was highlighted; except for compound 16, all compounds without this moiety (12, 15, and 18) were inactive in this regard. Concerning their ORAC values, however, compounds 12 and 16 were the most potent among all compounds, which highlights the complementary value of these two bioassays to evaluate free radical scavenging activity of small molecule antioxidants.
## 4. Conclusions
In this study, a combination semi and total synthetic strategy was adopted to prepare fourteen 6-gingerol derivatives including eight new compounds, which were subsequently characterised as antiplatelet and COX-1 inhibitor agents, and free radical scavenger or XO inhibitor antioxidants. The compounds’ pharmacodynamic and pharmacokinetic characterisation revealed 6-shogaol [2] to be the best lead as a cardiovascular protective agent, and compounds 3, 11, and 17 as new starting points for hit-to-lead optimisation. The 3,5-diol compound 5 was identified as a more potent and less promiscuous antioxidant than its parent compound 6-gingerol [1] or its three-epimer compound 6. Due to its favourable pharmacokinetic parameters, compound 5 is also suggested as a potential CNS-specific antioxidant. Further studies to evaluate this notion are to be conducted soon.
## Figure, Schemes and Tables
**Scheme 1:** *Semi-synthesis of compounds 2–6 from 6-gingerol (1). Reaction conditions: a. pTsOH/toluene/110 °C; b. H2/Pd/C/EtOAc/r.t.; c. NH2OH.HCl/EtOH/rt; d. NaBH4/MeOH.* **Scheme 2:** *Preparation of gingerdione derivatives 11–13 and their heterocyclic analogues 14–18. Reaction conditions: a. 1. NaH/Et2O/Acetone/0 °C, 2. EtOH/HCl; b. B2O3/iBuNH2/DMF/90 °C; c. H6N2O/HCl/EtOH/80 °C; d. NH2OH.HCl/pyridine/ethanol/80 °C; e. H2/Pd/C/EtOAc/rt. Major tautomers of compounds 11–13 are indicated with A, B, and C.* **Scheme 3:** *Preparation of the amide analogue of 6-paradol (22). Reaction conditions: a. H2/Pd/C/EtOAc/rt; b. DCC/DMAP/CH2Cl2/rt.* **Figure 1:** *The binding mode of compounds 2 (A) and 17 (B) on h-COX-1 enzyme (PDB ID: 6Y3C) visualised with Discovery studio visualizer (21.1.0.20298); 3D orientation with the enzyme’s hydrophobicity surface to the left and 2D representation of the observed interactions to the right. Colour codes for A and B are identical.* TABLE_PLACEHOLDER:Table 1 TABLE_PLACEHOLDER:Table 2 TABLE_PLACEHOLDER:Table 3
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|
---
title: 'The Effects of Topiroxostat, a Selective Xanthine Oxidoreductase Inhibitor,
on Arterial Stiffness in Hyperuricemic Patients with Liver Dysfunction: A Sub-Analysis
of the BEYOND-UA Study'
authors:
- Yuya Fujishima
- Hitoshi Nishizawa
- Yusuke Kawachi
- Takashi Nakamura
- Seigo Akari
- Yoshiyuki Ono
- Shiro Fukuda
- Shunbun Kita
- Norikazu Maeda
- Satoshi Hoshide
- Iichiro Shimomura
- Kazuomi Kario
journal: Biomedicines
year: 2023
pmcid: PMC10045538
doi: 10.3390/biomedicines11030674
license: CC BY 4.0
---
# The Effects of Topiroxostat, a Selective Xanthine Oxidoreductase Inhibitor, on Arterial Stiffness in Hyperuricemic Patients with Liver Dysfunction: A Sub-Analysis of the BEYOND-UA Study
## Abstract
Background: The effects of uric acid (UA)-lowering therapy with xanthine oxidoreductase (XOR) inhibitors on the development of cardiovascular diseases remain controversial. Based on recent findings that plasma XOR activity increased in liver disease conditions, we conducted a sub-analysis of the BEYOND-UA study to examine the differential effects of topiroxostat on arterial stiffness based on liver function in hyperuricemic individuals with hypertension. Methods: Sixty-three subjects treated with topiroxostat were grouped according to baseline alanine aminotransferase (ALT) levels (above or below cut-off values of 22, 30, or 40 U/L). The primary endpoint was changes in the cardio-ankle vascular index (CAVI) from baseline to 24 weeks. Results: Significant reductions in CAVI during topiroxostat therapy occurred in subjects with baseline ALT ≥30 U/L or ≥40 U/L, and significant between-group differences were detected. Brachial-ankle pulse wave velocity significantly decreased in the ALT-high groups at all cut-off values. Reductions in morning home blood pressure and serum UA were similar regardless of the baseline ALT level. For eleven subjects with available data, ALT-high groups showed high plasma XOR activity, which was significantly suppressed by topiroxostat. Conclusions: Topiroxostat improved arterial stiffness parameters in hyperuricemic patients with liver dysfunction, which might be related to its inhibitory effect on plasma XOR.
## 1. Introduction
Hyperuricemia, defined as a serum uric acid (UA) level of more than 7.0 mg/dL, is a potential risk factor for life-threatening complications, such as chronic kidney disease (CKD) and cardiovascular disease (CVD) [1,2,3,4]. Individuals with hyperuricemia are a heterogeneous population, including reduced renal/extrarenal excretion type, over-production type, and mixed type [5]. In particular, the overproduction type in liver is associated with visceral fat-based metabolic syndrome, including type 2 diabetes mellitus, hypertension, dyslipidemia, and nonalcoholic fatty liver disease/steatohepatitis (NAFLD/NASH) [6], all of which are major independent risk factors for CVD.
Xanthine oxidoreductase (XOR) is a rate-limiting enzyme that catalyzes the production of UA from hypoxanthine and xanthine, and is the pharmacological target of anti-hyperuricemic agents such as allopurinol, febuxostat, and topiroxostat. XOR generates reactive oxygen species (ROS) through its catabolic processes and can bind to the apical surface of vascular endothelial cells [7,8], suggesting a possible role of this enzyme in endothelial dysfunction [9,10]. Human XOR expression is detected mainly in liver, lungs, and gut [11]. Recently, we reported that circulating XOR in humans and mice markedly increased with elevations in liver enzymes such as serum alanine aminotransferase (ALT) or aspartate aminotransferase (AST), reflecting excessive leakage of hepatic XOR, and that topiroxostat, a selective XOR inhibitor, suppressed plasma XOR activity and attenuated the development of vascular neointima formation in a diet-induced mouse model of NAFLD/NASH [12,13]. Therefore, we hypothesize that XOR inhibitors may have the potential to prevent or delay cardiovascular complications, especially in patients with liver dysfunction, possibly beyond their UA-lowering effect.
Arterial stiffness is generally recognized as a predictor of cardiovascular morbidity and mortality, and increased arterial stiffness reflects structural and functional changes in the diffuse medial layer of the vessel wall [14,15]. The Beneficial Effect by Xanthine Oxidase Inhibitor on Endothelial Function Beyond Uric Acid (BEYOND-UA) study was the first randomized, controlled trial comparing the effects of the XOR inhibitors, topiroxostat and febuxostat, on arterial stiffness parameters in Japanese hypertensive patients with hyperuricemia [16]. In the overall analysis, there were no significant changes in the cardio-ankle vascular index (CAVI) or brachial-ankle pulse wave velocity (baPWV) during the 24-week follow-up period in either treatment group. However, based on our previous work [12], subjects with liver dysfunction (who are expected to have increased circulating XOR activity) may benefit most from treatment with XOR inhibitors. Of the currently available XOR inhibitors, topiroxostat was reported to have the strongest inhibitory effect against human plasma XOR activity, with a $50\%$ inhibitory concentration (IC50) that was 194-fold and 16-fold lower than that of oxypurinol and febuxostat, respectively [17]. In the BEYOND-UA study, XOR activity significantly decreased during the treatment with topiroxostat, but not with febuxostat [16]. This post hoc subgroup analysis of the BEYOND-UA study determined the differential effects of topiroxostat on arterial stiffness in subgroups of hyperuricemic patients with hypertension based on baseline liver function.
## 2.1. Study Design
The BEYOND-UA study was a multicenter ($$n = 31$$), randomized, comparative, open-label, parallel trial conducted in Japan between March 2018 and December 2019 [16]. As previously described [15], the study enrolled patients aged 30–80 years who had hyperuricemia (serum UA ≥7 mg/dL; untreated or treated with allopurinol), hypertension that had been treated with stable antihypertensive therapy for ≥3 months, and a CAVI of ≥8 and ≤12. Exclusion criteria were as follows: History of hypersensitivity to trial drugs or allopurinol; treatment with anti-hyperuricemic drugs during the study or within 4 weeks prior to enrollment; existing cancer diagnosis; gouty arthritis within 2 weeks before enrollment;AST or ALT >2 times the upper limit of normal; serious liver dysfunction (Child-Pugh class B or C); renal dysfunction (estimated glomerular filtration rate <30 mL/min/1.73 m2); severe heart failure (New York Heart Association class 3 or 4); history of acute coronary syndrome or stroke within the previous 3 months; and participation in another clinical trial within the previous 6 months.
## 2.2. Randomization and Intervention
Patients were randomly assigned to receive treatment with topiroxostat or febuxostat for 24 weeks. Aiming to maintain serum UA at <6 mg/dL, topiroxostat was started at 40 mg/day then titrated to 80 mg/day at week 4, to 120 mg/day at week 8, and up to a maximum of 160 mg/day during weeks 8–24, and febuxostat was started at 10 mg/day titrated to 20 mg/day at week 4, 40 mg/day week 8 and up to a maximum of 60 mg/day during weeks 8–24.
As previously reported [16], 67 patients in the topiroxostat group and 68 in the febuxostat group were eligible for final safety and efficacy analysis. In the current sub-analysis, patients treated with topiroxostat were divided into two groups according to their baseline ALT level: above or below 22 U/L (the median value) (Table 1), above or below 30 U/L (Table 2), or above or below 40 U/L (the upper limit of normal) (Table 3) (Figure S1).
## 2.3. Outcomes
The primary endpoint was the change in CAVI from baseline to 24 weeks. Secondary outcomes were as follows: change in CAVI from baseline to 12 weeks; change in baPWV from baseline to 12 and 24 weeks; change in serum UA from baseline to 4, 8, 12, and 24 weeks; change in home blood pressure (BP) from baseline to 4, 8, 12, and 24 weeks; change in the urinary albumin-creatinine ratio (UACR) from baseline to 12 and 24 weeks. Change in plasma XOR activity from baseline to 12 and 24 weeks was investigated as an exploratory endpoint ($$n = 11$$ for the topiroxostat group).
## 2.4. Assessments
CAVI was measured at baseline, and after 12 and 24 weeks of treatment using a CAVI device (Vasera VS3000). Examinations were performed after a 5-min rest period. The pressure of all cuffs was kept at 50 mmHg to minimize the effect of cuff pressure on hemodynamics. BP was then measured. CAVI was determined using the following formula: CAVI = a [(2ρ/ΔP) × ln (Ps/Pd) PWV2] + b, where a and b are constants, ρ is blood density, ΔP is Ps − Pd, *Ps is* systolic BP, *Pd is* diastolic BP, and PWV is pulse wave velocity.
PWV was determined by dividing the vascular length by the time (T) taken for the pulse wave to travel from the aortic valve to the ankle. However, in practice, T was difficult to obtain because the time the blood left the aortic valve was difficult to identify from the sound of the valve opening. Therefore, because the time between the sound of the aortic valve closing and the notch of the brachial pulse wave is theoretically equal to the time between the sound of the aortic valve opening and the rise of the brachial pulse wave, T was determined by adding the time between the sound of the aortic valve closing and the notch of the brachial pulse wave, and the time between the rise of the brachial pulse wave and the rise of the ankle pulse wave.
Home BP was measured at baseline and after 4, 8, 12, and 24 weeks of treatment using a cuff oscillometric device (HEM-7080-IC; Omron Healthcare Co., Ltd., Kyoto, Japan). All measurements were performed according to the latest guidelines available at the time the trial was conducted [18]. Patients were instructed to measure their morning home BP (two readings within 1 h after waking, taken after urination, before taking morning medications and after 1–2 min of seated rest) on five successive days immediately prior to their scheduled clinic visit.
Plasma XOR activity measurement was performed by Sanwa Kagaku Kenkyusho Co., Ltd. (Inabe, Japan), using liquid chromatography/triple quadrupole mass spectrometry (LC/TQMS; Nexera HLC (SHIMADZU, Kyoto, Japan)/QTRAP 4500 (SCIEX, MA, USA)) to detect [13C2,15N2]-uric acid using [13C2,15N2]-xanthine as a substrate, as previously described [19].
## 2.5. Statistical Analysis
Mixed-effects model repeated measures (MMRM) analysis was used to compare the changes in CAVI and other outcomes from baseline to week 4, week 8, week 12, and week 24. MMRM included the subgroup based on each ALT cut-off value, time points (0, 4, 8, 12, and 24 weeks), the interaction between the group and time points as fixed effects, and age and sex as covariates. A two-sided test was used, and p-values of <0.05 were considered statistically significant. Intergroup comparisons were tested with a t-test for continuous variables, and Pearson’s Chi-squared test or Fisher’s exact test was used for dichotomous data. Data were analyzed using SAS version 9.4 (SAS Institute) at the Jet Academy, Tokyo, Japan.
## 3.1. Baseline Characteristics of Study Subjects Treated with Topiroxostat
Of the 67 subjects treated with topiroxostat, baseline CAVI data were not obtained in 4 patients; the remaining 63 were included in this post hoc analysis (Figure S1). Two patients were switched from previous allopurinol therapy. Table 1, Table 2 and Table 3 show baseline clinical characteristics in patient subgroups based on each ALT cut-off. Both ALT and AST levels were significantly higher in each ALT-high subgroup, and there was a tendency for body mass index (BMI) to be higher ($$p \leq 0.074$$) and the use of calcium channel blockers (CCBs) more frequent ($$p \leq 0.066$$) in the ALT ≥40 versus <40 U/L group. No significant differences between the ALT-high and -low groups at each cut-off value were seen for other clinical parameters, including serum UA, systolic and diastolic BP, CAVI, and baPWV (Table 1, Table 2 and Table 3).
## 3.2. Arterial Stiffness
Figure 1 shows the time course changes in arterial stiffness during the study period, assessed by CAVI or baPWV. As shown in Figure 1B,C, significant reductions in CAVI were observed at week 24 in patients with baseline ALT >30 U/L or >40 U/L. On the other hand, in the ALT-low groups, CAVI increased slightly but significantly in patients with baseline ALT <22 U/L (Figure 1A) and remained unchanged in the ALT <30 U/L or ALT <40 U/L groups (Figure 1B,C). At week 24, baPWV was significantly decreased in the ALT-high groups at all three cut-offs, whereas there was no significant change in each of the ALT-low groups (Figure 1D–F). There were also significant between-group differences in changes from baseline to week 24 in both CAVI (Figure 1A–C) and baPWV (Figure 1D–F).
## 3.3. Morning Home Blood Pressure
Overall, morning home systolic (Figure 2A–C) and diastolic (Figure 2D–F) BP decreased significantly from baseline, irrespective of baseline ALT level. There were no between-group differences in BP changes, except for at week 24 when patients with ALT ≥40 U/L had greater reductions in systolic and diastolic BP compared to those with ALT <40 U/L (Figure 2C,F).
## 3.4. Uric Acid Levels and Plasma XOR Activity
Serum UA levels decreased significantly from baseline to week 24 in all ALT subgroups ($p \leq 0.001$) (Figure 3A–C). However, there was a trend toward smaller reductions in serum UA in patients with ALT ≥30 U/L versus <30 U/L (Figure 3B). For the 11 subjects with available data, baseline plasma XOR activity increased gradually in the subgroups with higher baseline ALT as the cut-off value increased from 22 to 40 U/L (Figure 4A–C). Elevated XOR activity in the ALT-high groups decreased to levels that were similar to those in the ALT-low groups at week 12 and week 24 of treatment with topiroxostat (Figure 4A–C).
## 3.5. Urinary Albumin-Creatinine Ratio
In the overall population, UACR decreased significantly from baseline during topiroxostat treatment [16], but there were no significant changes in UACR in all the subgroups nor between-group differences (Figure 5A–C).
## 3.6. Alanine Aminotransferase
The time course changes in serum ALT levels are shown in Figure 6A–C. There were no significant changes in ALT nor between-group differences at cut-offs of ALT 22 U/L and 30 U/L, whereas patients with baseline ALT levels higher than 40 U/L showed a significant decrease in ALT at week 4 ($p \leq 0.05$) and week 24 ($p \leq 0.0001$) (Figure 6C).
## 4. Discussion
To the best of our knowledge, this sub-analysis of the BEYOND-UA trial is the first study to show that the selective XOR inhibitor topiroxostat improved arterial stiffness parameters (CAVI and baPWV) in hyperuricemic patients with hypertension and liver dysfunction.
Evidence from epidemiological studies suggests that elevated serum UA levels are a risk factor for CKD and CVD (1–4). Generation of XOR-dependent vascular ROS has been considered one of the underlying mechanisms responsible for endothelial dysfunction and atherosclerosis associated with hyperuricemia [9,10]. However, it remains controversial whether UA-lowering therapy with XOR inhibitors is effective for preventing CVD development in individuals with hyperuricemia. In two randomized trials, treatment with allopurinol attenuated the progression of carotid intima-media thickness (IMT) in patients with asymptomatic hyperuricemia and type 2 diabetes [20] or recent ischemic stroke [21]. In the Febuxostat for cerebral and caRdiovascular Events prevention study (FREED), in which 1070 patients with hyperuricemia at high CVD risk were randomly allocated to treatment with febuxostat or conventional therapy, the primary composite event rate (cerebral, cardiovascular, and renal events, and all deaths) was significantly lower in the febuxostat versus control group, but this result was mainly driven by differences in renal impairment [22]. Furthermore, a recent prospective, randomized, open-label, blinded trial, enrolling 5721 subjects with ischemic heart disease showed no difference in the rate of the primary outcomes of non-fatal myocardial infarction, non-fatal stroke, or cardiovascular death between patients receiving allopurinol and those receiving usual care [23]. These mixed results highlight the importance of identifying potential factors that might affect the cardiovascular protective effect of XOR inhibitors.
Accumulating clinical data indicate that NAFLD, the most common liver disease worldwide, increases the risk of CVD, independent of established cardiovascular risk factors [24,25,26]. Moreover, certain studies have suggested that liver function tests themselves, including ALT, AST, gamma-glutamyltransferase (GGT), and alkaline phosphatase (ALP), can be potential CVD risk markers, independent of their relationship to NAFLD [27,28,29]. Our previous studies in both humans and mice demonstrated that increased plasma XOR activity was directly induced by liver damage, together with increases in liver enzymes such as serum ALT and AST. Moreover, high XOR in liver disease conditions accelerated purine catabolism in the plasma per se using hypoxanthine secreted from vascular endothelial cells or adipocytes as substrate, which was accompanied by the development of vascular endothelial injury and neointimal proliferation [11,12,13]. Additionally, a cross-sectional study by another group reported a significant positive correlation between plasma XOR activity and CAVI in patients with type 2 diabetes and liver dysfunction [30]. These results suggest pathological crosstalk from the damaged liver to vascular diseases via hepatic XOR.
In that context, the aim of this post hoc analysis was to assess the efficacy of XOR inhibitors on arterial stiffness in subjects with liver dysfunction. In addition to the ALT cut off values of 22 U/L (the median value) and 40 U/L (the upper limit of normal), we also analyzed our subjects by dividing them above or below 30 U/L because such a slight increase of ALT ≥30 U/L in Japanese subjects has been reported to be associated with lifestyle-related chronic liver diseases such as NAFLD [31]. Baseline levels of CAVI and baPWV in the ALT-high groups tended to be higher as the ALT cut-off value increased (Figure 1). After 24 weeks’ treatment with topiroxostat, we found that CAVI significantly decreased from baseline in subjects with baseline ALT ≥30 U/L (mean ALT 47.8 U/L) and ≥40 U/L (mean ALT 61.1 U/L), and baPWV decreased significantly from baseline in subjects with ALT ≥22 U/L (mean ALT 35.8 U/L), ≥30 U/L, and ≥40 U/L. Albeit in a limited number of subjects, patients with a high baseline ALT level also showed increased plasma XOR activity, which was markedly suppressed during treatment with topiroxostat (Figure 4). Given that serum UA significantly decreased to approximately 6 mg/dL or less, irrespective of baseline ALT level (Figure 3), such improvement in arterial stiffness markers during topiroxostat therapy in the ALT-high groups was assumed to have resulted not only from a reduction in serum UA but also from a reduction in plasma XOR activity per se. In our subjects treated with febuxostat ($$n = 65$$), in whom no significant change was observed in plasma XOR activity [16], post hoc analysis using the same method did not detect any changes in either CAVI or baPWV (data not shown). On the other hand, in a recently published sub-analysis of the PRIZE (program of vascular evaluation under uric acid control by xanthine oxidase inhibitor, febuxostat: multicenter, randomized controlled) study, long-term (24 months’) treatment with febuxostat significantly improved arterial stiffness (assessed by CAVI or baPWV) compared with non-pharmacological management, without any change in carotid IMT progression [32]. Thus, further large-scale studies are needed to conclude whether differences in plasma XOR inhibitory activity between different XOR inhibitors influence their effects on arterial stiffness, especially in patients with liver dysfunction.
In the overall analysis of the BEYOND-UA study, there was a significant reduction in UACR over 24 weeks’ treatment with topiroxostat, especially in subjects with microalbuminuria at baseline [16]. However, unlike the CAVI and baPWV results, there were no differences in serial changes in UACR based on baseline ALT level (Figure 5). The underlying mechanisms for this discrepancy are uncertain, but similar reductions in systolic and diastolic BP in the ALT-high and ALT-low groups (Figure 2) might have a relatively strong beneficial effect on UACR. High UA is assumed to be involved in the development of hypertension and renal vasoconstriction via activation of the renin-angiotensin system (RAS) and reducing endothelial nitric oxide bioavailability [4,33]. As such, it is possible that improved hypertensive status associated with the reduction in UA had a greater impact on the change in UACR during treatment than the decrease in XOR activity. On the other hand, arterial stiffness is related not only to BP but also to remodeling of arterial structures caused by the proliferation of vascular smooth muscle cells (VSMCs) and connective tissues [14,15]. We previously showed that liver-derived XOR stimulated the proliferation and dedifferentiation of in vitro human VSMCs and in vivo neointima formation composed of proliferative SMCs in diet-induced NAFLD/NASH model mice, both of which were attenuated by the treatment with topiroxostat [13]. Because subjects in the ALT-high groups had markedly elevated baseline plasma XOR activity, the beneficial effects of topiroxostat on VSMCs via XOR suppression might result in a differential arterial stiffness response based on liver function.
Although not a predefined outcome in the BEYOND-UA study, changes in serum ALT were retrospectively examined to confirm the effect of topiroxostat on liver function itself. There were no significant changes in ALT in the ALT ≥22 U/L (Figure 6A) and ALT ≥30 U/L (Figure 6B) groups during the study period, suggesting that reductions in CAVI or baPWV and suppression of plasma XOR activity were not mediated by improved liver function, at least in these two subgroups. On the other hand, we found a significant decrease in ALT levels in subjects with baseline ALT ≥40 U/L (Figure 6C). Because of the small number of subjects ($$n = 8$$), the possibility that this is a chance finding cannot be ruled out. However, previous experimental and clinical studies provide evidence that XOR inhibitors have the potential to prevent the development of NAFLD, through attenuation of hepatic lipid accumulation, insulin resistance, and activation of macrophage and NLRP3 inflammasome [34,35,36]. Thus, these beneficial effects of topiroxostat on liver function might contribute, in part, to the improvement in arterial stiffness parameters in the ALT ≥40 U/L group.
There are several limitations in the present study. First, it is post hoc and exploratory by nature, and statistical comparisons were not adjusted for multiplicity. Although the data used in this study were generated in a randomized controlled clinical trial, the post hoc analysis was not pre-specified. Thus, potential sources of bias cannot be ruled out due to the post hoc nature of this analysis. Second, the results must be interpreted with caution due to the small sample size in each patient subgroup and due to the lack of a placebo control group. Third, the BEYOND-UA study was not originally designed to focus on liver function; therefore, the underlying causes of liver injury in each subject were not examined in detail, and subjects with different types of liver disease, not only NAFLD, could be enrolled in this study. In fact, we have confirmed that there was one subject with chronic hepatitis C whose ALT level was 15 U/L and two subjects with alcoholic hepatitis whose ALT levels were 22 and 28 U/L in the topiroxostat group. Moreover, we could not evaluate the outcomes in patients with severe liver dysfunction because an ALT or AST >2 times the upper limit of normal was an exclusion criterion for the main BEYOND-UA study. However, if inhibition of plasma XOR does mediate reductions in CAVI and baPWV, there is also a possibility that such patients might experience even more pronounced improvements in these arterial stiffness parameters during treatment with topiroxostat, but this remains to be determined.
## 5. Conclusions
Topiroxostat decreased CAVI and baPWV in hyperuricemic subjects who had higher ALT values at baseline, and this was accompanied by significant suppression of increased plasma XOR activity. Taken together, our results raise the possibility that topiroxostat has therapeutic potential for improving arterial stiffness and preventing atherosclerotic diseases in patients with liver dysfunction. Future large-scale prospective placebo-controlled studies enrolling NAFLD patients are warranted to confirm this hypothesis.
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|
---
title: 'Computational and Preclinical Analysis of 2-(4-Methyl)benzylidene-4,7-dimethyl
Indan-1-one (IPX-18): A Novel Arylidene Indanone Small Molecule with Anti-Inflammatory
Activity via NF-κB and Nrf2 Signaling'
authors:
- Reem M. Gahtani
- Ahmad Shaikh
- Hossam Kamli
journal: Biomedicines
year: 2023
pmcid: PMC10045539
doi: 10.3390/biomedicines11030716
license: CC BY 4.0
---
# Computational and Preclinical Analysis of 2-(4-Methyl)benzylidene-4,7-dimethyl Indan-1-one (IPX-18): A Novel Arylidene Indanone Small Molecule with Anti-Inflammatory Activity via NF-κB and Nrf2 Signaling
## Abstract
### Simple Summary
Inflammatory responses are recorded in many dreadful diseases. As the presently used mainline anti-inflammatory treatments are proven to have adverse short- and/or long-term side effects, the search for alternative anti-inflammatory agents that may possess lesser side effects is on constant demand. This study evaluates IPX-18, a novel arylidene indanone small molecule, due to its anti-inflammatory activity mediated by NF-κB and Nrf2 signaling. These findings provide new insights for future research on this molecule for its development as a novel anti-inflammatory agent to treat several diseases.
### Abstract
Background: The adverse effects of anti-inflammatory drugs urges the search for new anti-inflammatory agents. This study aims at the preclinical analysis of the in-house synthesized small molecule IPX-18. Human whole blood (HWB), peripheral blood mononuclear cells (PBMCs), and neutrophils were used. Rat basophil cells (RBL-2H3) were used to assess degranulation. Binding stability to NF-κB-p50 was predicted using computational docking and molecular dynamic simulations. Essential signaling proteins were evaluated through flow cytometry. Results: IPX-18 inhibited the release of TNF-α with an IC50 value of 298.8 nM and 96.29 nM in the HWB and PBMCs, respectively. The compound depicted an IC50 value of 217.6 nM in the HWB and of 103.7 nM in the PBMCs for IFN-γ inhibition. IL-2 release and IL-8 release were inhibited by IPX-18 in the HWB and PBMCs. The compound controlled the migration of and the elastase in the activated neutrophils. The IC50 value for basophil activation through the FcεRI receptor assay was found to be 91.63 nM. IPX-18 inhibited RBL-2H3-degranulation with an IC50 value of 98.52 nM. The computational docking analysis predicted that IPX-18 would effectively bind NF-κB-p50. NF-κB-phosphorylation in the activated RBL-2H3 cells was decreased, and the levels of nuclear factor erythroid 2-related factor 2 (Nrf2) were increased with IPX-18 treatment. Conclusions: IPX-18 demonstrated efficacy in mediating the effector cells’ inflammatory responses through NF-κB/Nrf2 signaling.
## 1. Introduction
Inflammation is regarded as a cellular or biochemical response to any endogenous/exogenous agonists to maintain the body’s homeostasis [1,2]. Inflammatory responses are recorded in many diseases, including asthma, cancer, chronic inflammatory diseases, atherosclerosis, diabetes, autoimmune and degenerative diseases, etc., [ 3]. The adverse short- and/or long-term side effects of treatment regimens include cardiovascular and gastrointestinal complications, growth restrictions, insulin resistance, and neurodevelopmental disability [4]. Therefore, the search for alternative anti-inflammatory agents that may possess lesser side effects is on constant demand.
The nuclear factor kappa light-chain enhancer of activated B cells, or NF-κB, is a transcription regulator that is activated by various stimuli, including cytokines. Its stimulation with either IL-1β or TNFα activates the IκB kinase (IKK) complex, which then mediates the phosphorylation, ubiquitination, and degradation of the IκB molecule, which, in turn, releases NF-κB. NF-κB, when translocated to the nucleus, binds to the κB motifs in the promoter region to induce the transcription of target genes [5]. On the other hand, accumulating evidence favors the idea that Nrf2 (nuclear factor erythroid 2-related factor 2) plays a central role in anti-inflammatory functions. [ 6]. Studies indicate that Nrf2 negatively controls the NF-κB signaling pathway through more than one mechanism. Firstly, Nrf2 inhibits oxidative-stress-mediated NF-κB activation by decreasing the intracellular ROS levels [7]. Secondly, Nrf2 inhibits the proteasomal degradation of IκB-α to prevent the nuclear translocation of NF-κB [8]. An increase in the Nrf2 levels induces the cellular HO-1 levels and, thereby, phase II enzyme expression, which, in turn, blocks the degradation of IκB-α [9]. Alongside this, NF-κB decreases free CBP, which is a transcriptional coactivator of Nrf2, by competing with the CH1-KIX domain of CBP while also promoting the phosphorylation of p65 at Ser276, which, in turn, prevents CBP from binding to Nrf2 [10]. Accumulating evidence also suggests that Nrf2 counteracts the NF-κB-driven inflammatory response by competing with the transcription coactivator cAMP response element (CREB) binding protein (CBP) [11,12]. Another interesting study described that the Akt (PKB)-dependent inactivation of GSK3β (Glycogen synthase kinase 3 β) leads to an anti-inflammatory response by inactivating NF-κB and activating CREB and Nrf2 [13]. While it is presumed that the Nrf2 and NF-κB signaling pathways conjoin, therefore maintaining the physiological homeostasis of inflammatory regulation, targeting these signals have been proven worthy for controlling inflammation.
Recent advances in medicinal chemistry have contributed an array of small bioactive molecules to treat various diseases. Arylidene indanone is one such class of small molecules that is identified to have potent bioactivity against several diseases, including tuberculosis [14], degenerative diseases [15], hypoglycemia [16], lipidemia [17], and cancer [18]. 2-benzylidene-1-indanone derivatives were reported to be anti-inflammatory agents for the treatment of acute lung injury [19]. On the other hand, it is established that small-molecule anti-inflammatory drugs have lesser adverse effects with uncompromised efficacy [20]. Therefore, screening such small molecules for anti-inflammatory properties stands to be essential in searching for effective and economical novel anti-inflammatory compounds. The current study evaluates IPX-18 (Figure 1), one potentially active arylidene small molecule, due to its anti-inflammatory properties.
## 2.1. Materials
Reagents and chemicals were procured from Sigma–Aldrich (Burlington, MA, USA). RBL-2H3 cell line was obtained from ATCC (Manassas, VA, USA). ELISA kits were from eBioscience (San Diego, CA, USA). The Flow CAST® kit was purchased form Buhlmann Diagnostics Corp (BDC) (Amherst, NH, USA). Migration inserts and 96-well plates were obtained from Nunc corp., Thermo Fischer Scientific (San Diego, CA, USA). Phospho-NF-κB p65 (S529) PE antibodies were from Thermo Scientific (San Diego, CA, USA). Recombinant PE anti-Nrf2 antibody was from Abcam (Fremont, CA, USA). Annexin V assay reagent was from Merck Millipore (Temecula, CA, USA).
## 2.2.1. Synthesis of 2-(4-Methyl)benzylidene-4,7-dimethyl Indan-1-one
Schematic of synthesis of the small molecule is provided in Supplementary Figure S1. Synthesis was initiated through the preparation of Baylis–Hillman adduct of p-tolualdehyde and t-butyl acrylate. This reaction was carried out on a solid-phase silica gel in presence of DABCO as catalyst. The reaction mixture was washed with ethyl acetate and was dried. After removing the solvent, crude product was chromatographed. Following this, the obtained hydroxy ester was dissolved in p-xylene and was treated with a catalytic amount of sulphuric acid under reflux. The solvent was removed under reduced pressure, and the residue was treated with TFAA in ethylene dichloride under reflux. Purification was carried out through column chromatography.
## 2.2.2. Ethical Approval
This study was approved by the Research Ethics Committee, Deanship of Scientific Research, King Khalid University, Abha, Saudi Arabia (Reference No. ECM#2020-0913 (22 June 2020).
## 2.2.3. Cell Culture
Eagle’s Minimum Essential Medium (supplemented with $10\%$ FBS, 100 U/mL of penicillin, and 100 U/mL of streptomycin) was used for the growth of RBL-2H3 cells, and cell culture was maintained following the standard protocols.
## 2.2.4. Annexin V Assay for Apoptosis/Cell Death
The assay was carried out by using Annexin V detection kit as per the manufacturer’s instructions. RBL-2H3 cells and PBMCs were treated with 100 nM or 250 nM IPX-18 along with suitable DMSO controls and incubation for 24 h. Cells were then treated with 0.25 μg/mL of Annexin V reagent for 15 min in the dark. After two washes in sterile PBS, cells were resuspended in kit buffer containing 0.5 μg/mL of propidium iodide. Ten thousand events were acquired on a Guava easyCyte™ flow cytometer. Data analysis was carried out with InCyte software (Version 6.0) to differentiate healthy and apoptotic cells (early and late apoptosis).
## 2.2.5. Cytokine Assays
Cytokine production was performed using whole blood and PBMCs. Density gradient centrifugation was used to isolate PBMCs from whole blood as described elsewhere [21]. 0.5 × 106 PMBCs/mL and HWB were resuspended in RPMI-8226 full growth media (1:3.5 dilution) and were seeded in 96-well tissue culture plates following incubation for 1 h at 37 °C with CO2. IPX-18, at the desired concentration, was applied to the wells in triplicate ($$n = 8$$) and was incubated for 30 min. Following this, PBMCs and HWB were induced with 50 ng/mL of phorbol-12-myristate-13-acetate (PMA) and 5 μg/mL of phytohaemagglutinin (PHA). All plates were incubated for 24 h for cytokine production, they were centrifuged at 4000 rpm for 10 min, and the supernatant was stored at −80 °C until further analysis. ELISA was performed per manufacturer’s instructions, and IC50 was calculated using Graphpad Prism (version 6.0).
## 2.2.6. Isolation of Neutrophils from HWB
Neutrophil isolation from HWB was performed as described by previously established protocol [22]. Briefly, HWB, added to dextran sulphate, was kept at room temperature for 60 min. At 4 °C, the supernatant was centrifuged at 1150 rpm for 12 min. After adding 0.6 M KCl, it was again centrifuged at 1300 rpm with HiSep density gradient. Cells were collected in ice-cooled HBSS. A 2 × 105 cells/mL density was adjusted for further neutrophil-based assays.
## 2.2.7. Neutrophil Migration Inhibition Assay
To a 24-well plate, 249 μL of HBSS was added followed by 1 μL of 10 nM of N-formylmethionyl-leucyl-phenylalanine (fMLP). The neutrophil cell suspension was added to inserts and was placed in these wells. A total of 249 μL to 1 μL of DMSO, or several concentrations of IPX-18, was applied and was allowed to migrate for 1.5 h at 37 °C in a CO2 incubator. Inserts were stained with crystal violet solution and were eluted, and elution absorption was quantified spectrometrically at 410 nM.
## 2.2.8. Neutrophil Elastase Assay
This assay was conducted as described elsewhere [23]. A total of 49 μL of neutrophils (2 × 105 cells/mL) was added to 96-well plate and was treated with 1 μL of IPX-18 at different concentrations. A total of 200 μL of master mix that contained 10 μM fMLP, 200 μg/mL of CytochalasinB, 1 mM Sodium azide, and 1 mg/mL of L-Methionine was used to activate neutrophils for 1.5 h at 37 °C. After centrifugation at 1000 rpm for 5 min, 90 μL of supernatant was transferred to each well of a new 96-well plate. Following this, all wells were filled with 10 μL of 10 mM substrate and were incubated for 1 hour at 37 °C. The plate was read for absorbance at 410 nM.
## 2.2.9. Basophil Activation Assay (BAT assay) in HWB
Flow CAST® assay kit was used as per the manufacturer instructions. Human blood was incubated with IPX-18 for fifteen minutes and was treated with antihuman-FcεRI. After this, stimulation buffer and staining reagent were added and incubated in the dark for another fifteen minutes. Post centrifugation, the cells were suspended with 1 mL of PBS and were acquired using flow cytometer. The percentage of CD63 cells was analyzed.
## 2.2.10. Cell Viability Assay
The cell viability was measured using MTT assay [24]. After preincubation for one hour with IPX-18, RBL-2H3 cells were activated for four hours with DNP-BSA. Furthermore, 100 μL of MTT (1 mg/mL) was added and incubated for 4.5 h. Formazan products were dissolved in DMSO and were read for absorbance at 560 nm.
## 2.2.11. TNF-α and Degranulation in RBL-2H3 Cells
In RBL-2H3 cells, IgE-degranulation was analyzed by following the protocol stated previously by Naal et al. [ 25]. RBL-2H3 cells were seeded at a concentration of 2 × 105 cells/mL in 24-well plates. These cells were sensitized with 1 μg/mL of IgE and were incubated overnight at 37 °C. Next day, the medium was aspirated and replaced with PIPES buffer and was further incubated at 37 °C for 15 min. After treating different concentrations of IPX-18 for one hour, anti-DNP-BSA was added for four hours. Supernatants from one set of experiments were stored at −80 °C and were used for TNF-α estimation through ELISA as per manufacturer protocol. Fresh supernatants from other set were removed from wells and were incubated with fluorescence substrate at 37 °C for 1 h. Fluorescence intensity was read at 450 nm (emission) and 360 nm (excitation).
## 2.2.12. Structure Retrieval and Protein–Ligand Docking
The three-dimensional structure of p50 was retrieved from PDB databank (PDBID: 1SVC). Docking protein was prepared by adding polar hydrogens using Discovery Studio Visualizer. IPX structure was also prepared using Discovery Studio Visualizer. Docking was performed using SiBDOCK web server at www.sibiolead.com (accessed on 3 September 2020), which uses autodock vina docking protocol [26,27]. Docking grid box was set to focus on p50’s DNA-binding region, and box dimension was set to 20. Docked complex was analyzed using Discovery Studio Visualizer. Version. 19.1.0.18287.
## 2.2.13. Molecular Dynamic Simulation
Simulation was performed using an automated protein–multiligand protocol developed at SiBioLead www.sibiolead.com (accessed on 3 September 2020) that uses GROMACS simulation package. Protein–ligand complex was immersed in a triclinic box containing SPC water molecules and NaCl as counterions. Furthermore, 0.15 M NaCl was added to the simulation system to maintain physiological conditions. OPLS/AA forcefield was applied to the simulation system. Before simulation, system was equilibrated for 300 ps using NVT/NPT protocol. Simulation was carried out using leapfrog integrator in a GPU-based Linux environment. Simulation trajectories were analyzed using GROMACS in-built results analyses package.
## 2.2.14. Flow Cytometry
Essential cellular protein singling was detected through flow cytometry. Initially, RBL-2H3 cells were sensitized with DNP-IgE, and then they were treated with doses of IPX-18 for 30 min and were induced with DNP-BSA for 4 h. Furthermore, cells were stained for 15 min with NF-κB p65 (S529) PE antibody or anti Nrf2 PE antibody in buffer reagent (Thermo scientific, San Diego, CA, USA). The cells were washed twice to remove excess stain and were resuspended in HBSS buffer. 5000 events were acquired with Guava EasyCyte™ flow cytometer, Merk Millipore (Temecula, CA, USA). Positively gated cells were further read for NF-κB/p65s529 or Nrf2 using InCyte software from Merk Millipore (Temecula, CA, USA).
## 2.2.15. Statistical Analysis
The experiments were performed in triplicate, and all data were represented as mean ± S.D. Graphpad Prism 6.0 (La Jolla, CA, USA) was used for statistical examinations. To compare the differences between the two groups, Student’s t-test was used for this analysis. ANOVA was used for determining the difference between three or more variants. Statistical significance was considered to be $p \leq 0.05$ (*).
## 3.1. Chemistry of Synthesized Small Molecule
A 1H NMR of the synthesized compound is attached in Supplementary Figure S2. The product showed IR absorptions at 1642, 1712, and 3414 cm−1, indicating this to be an α,β-unsaturated hydroxy ester. The compound was t-butyl-3-hydroxy-2-methylene-3-(4-methyl-phenyl) propanoate. This was confirmed with a PMR spectrum. A multiplet around 7.15–7.35 δ for four protons indicated the phenyl group. A singlet for one proton at 6.23 δ indicated the lone benzylidene proton, which was allylic, as well as the hydroxy methyl proton. Each of the two vinylic protons appeared as a singlet at 5.71 and 5.47 δ. A singlet at 2.4 δ indicated the three Ar–CH3 protons, and a singlet for nine protons indicated the t-butyl group, which appeared at 1.6 δ. The IR spectrum showed absorptions at 1689.5 cm−1 and 1624 cm−1, indicating this to be an aromatic α,β-unsaturated ketone. The PMR spectrum showed a multiplet around 7.7–7.53 δ for seven protons. These were the six aromatic protons and the one vinylic proton. A two-proton singlet at 3.75 δ indicated the benzylic and allylic methylene protons. The Ar–CH3 appeared as a three-proton singlet at 2.67 δ. Two singlets appeared at 2.37 and 2.32 δ for six Ar–CH3 protons. A signal at 195.74 δ in the 13C NMR spectrum indicated the α,β-unsaturated carbonyl carbon. The presence of the Ar–CH3 carbons appeared at 17.7, 18.31, and 21.59 δ. The aromatic carbon atoms appeared around 129 to 149.16 δ. The m/e value of the compound corresponded to the molecular weight of 262.5, and the elemental analysis agreed with the molecular formula of the compound. The following values were calculated: C, $86.92\%$; H, $6.91\%$. The following values were found: C, $86.98\%$; H, $6.94\%$. Based on the above data, the compound was identified to be 2-(4-methyl) benzylidene-4,7-methyl indan-1-one.
## 3.2. Nontoxicity of IPX-18
Prior to testing IPX-18’s anti-inflammatory effects, the nontoxicity of the compound was assessed through the annexin V assay. For this, IPX-18, at different concentrations, was incubated with the RBL-2H3 cells and the human primary leucocytic cells (PBMCs) with untreated controls for 24 h. The compound did not induce any early- or late-phase apoptosis in these cells when compared to the untreated controls (Supplementary Figure S3).
## 3.3. IPX-18 Attenuated Proinflammatory Cytokine Responses in Human Whole Blood and Peripheral Nucleocytes
The HWB and PBMCs were used in the initial screening of IPX-18 for proinflammatory cytokine inhibitions. The compound inhibited the release of TNF-α with an IC50 value of 298.8 nM and 96.29 nM in the HWB and PBMCs, respectively (Figure 2a). IPX-18 inhibited IFN-γ with an IC50 value of 217.6 nM in the HWB and of 103.7 nM in the PBMCs (Figure 2b). Inhibition of IL-2 and IL-8 in the HWB by IPX-18 was evident with IC50 values of 416.0 nM and 336.6 nM, respectively (Figure 2c,d). The IC50 values for these cytokines in the PBMCs were 122.9 nM for IL-2 and 105.2 nM for IL-8 (Figure 2c,d).
## 3.4. Effect of IPX-18 Treatment on Activated Neutrophils
The results of elastase activity and neutrophil migration confirmed the dose-responsive efficacy of the compound in inhibiting neutrophil migration (Figure 3a). Similarly, IPX-18 inhibited the elastase exocytosis of the stimulated neutrophils in a dose-responsive way (Figure 3b).
## 3.5. IPX-18 Effectively Inhibited the Activation of Basophils
The basophils in the HWB were stimulated by crosslinking the IgE binding receptors and anti-FcεRI monoclonal antibodies. When provoked, the CD63 surface receptors that were expressed in these cells were analyzed through flow cytometry. CCR3 positive cells were gated to determine CD63 + ve populations. The results demonstrated a loss in the CD63 cell population (Figure 4) with IPX-18 treatment. When assessed for dose dependency, the IC50 value for IPX-18 was found to be 91.63 nM (Figure 4).
## 3.6. Dose Tolerance of IPX-18 on Normal and Stimulated RBL-2H3 Cells
Prior to analyzing the effects of IPX-18 in the RBL-2H3 cells, an MTT assay was used to evaluate the viability of the RBL-2H3 cells. The viability of the RBL-2H3 cells was unaltered with up to 250 nM of IPX-18 (Figure 5a) for 24 h. To check out if the stimulation could bring out any toxic effect in these cells, different doses of IPX-18 were assessed for cytotoxicity with 0.025 μg/mL of DNP-BSA (dinitrophenyl human and bovine serum albumin) for 4 h in 1 μg/mL of the anti-DNP IgE antibody (antidinitrophenyl anti-IgE antibody) pretreated RBL-2H3 cells. Results indicated no loss of cell viability with up to 250 nM of IPX-18 in the presence of the stimulator (Figure 5b).
## 3.7. IPX-18 Inhibited TNF-α Release and Degranulation in Anti-DNP/IgE of Sensitized RBL-2H3 Cells
A reduction in TNF-α release (Figure 5c) in the cell supernatant was evident with IPX-18 treatment. In order to check the effect of the compound in the degranulation process, we assessed the release of β-glucuronidase, an essential degranulation enzyme, in the RBL-2H3 cells after stimulation with DNP-BSA. IPX-18, with an IC50 value of 98.52 nM, could dose-dependently control RBL-2H3 degranulation (Figure 5d).
## 3.8. Protein–Ligand Docking of IPX-18 to p50 Subunit of NFkB
In order to understand the mode of action, we performed the computational modeling and docking of IPX-18 to the NFkB p50 subunit. For this purpose, we used an experimental structure of p50 bound to DNA from the PDB databank (PDBID: 1SVC). An analysis of the retrieved p50-DNA complex suggested that targeting the amino acid residues that participate in DNA interactions would repress p50 DNA binding. We previously showed that targeting the DNA-binding region of p50 significantly induced apoptosis [1]; therefore, in this work, we targeted the same region for our docking studies (Figure 6a). An analysis of the DNA-binding interface of p50 identified crucial residues and a pocket that could be targeted with a small molecule (Figure 6b). We performed the protein–ligand docking of the IPX-18 molecule to the target site in the p50 protein. The results indicated that IPX-18 fits well in the DNA-binding interface of the p50 protein (Figure 6c). The docking score (binding energy) of IPX-18 to p50 was predicted to be −6.2 kcal/mol, which was comparable and better than the standard compound used in our previous work [1]. A protein–ligand interaction analysis of the p50 bound IPX-18 complex indicated that IPX-18 interacts with the crucial residues involved in DNA binding (Figure 6d).
## 3.9. Molecular Dynamic Simulation Predicted IPX-18 Binding Stability
In order to assess the binding stability of the IPX-18 complex with the p50 subunit of NFkB, we performed a 100 ns atomistic molecular dynamic simulation of the IPX-18 NFkB-p50 complex using the GROMACS simulation package. A simulation trajectory analysis at different timepoints predicted that IPX-18 would bind stably to the predicted binding site of the p50 subunit. Comparing the 50 ns and 100 ns frames with 0 ns, (i.e., the complex before the simulation), the IPX-18 molecule rotated from its initial docked position; however, the residue interactions of IPX-18 remained the same, indicating that IPX-18 attained a favorable conformation during the simulation (Figure 7a–c). The simulation trajectory video shows the binding stability of IPX frame by frame (Supplementary Video S1).
## 3.10. Efficacy of IPX-18 on Key Signaling Proteins of the Inflammatory Pathway
The phosphorylation of NF-κB in the stimulated RBL-2H3 cells was estimated through flow cytometry. DNP-BSA stimulated the RBL-2H3 cells and induced the phosphorylation of NF-κB at 4 h postinduction (Figure 8a). Preincubation with IPX-18 for 30 min before the stimulation reduced the phosphorylation of NF-κB (Figure 8a). Similarly, the expression levels of the nuclear Nrf2 proteins were upregulated by IPX-18 (Figure 8b) with the DNP-BSA stimulation of the RBL-2H3 cells sensitized previously with IgE.
## 4. Discussion
Chronic inflammation leads to severe conditions that may end up with complex manifestations [28]. Though there are several anti-inflammatory drugs available in the market, their long-term administration may cause several unfavorable side effects, including organ toxicities, ulcerations, and bleeding [28]. Therefore, the search for novel anti-inflammatory compounds is on demand. This research focuses on the preclinical evaluation of a novel arylidene indanone moiety as a potential agent against inflammatory responses. Cytokines constitute the prime physiological defense against any stimuli during the innate and adaptive inflammatory responses [29]. It is reported that inflammation is a complex phenomenon that involves the interplay between neutrophils, basophils, mast cells, etc., which is commonly orchestrated via cytokines [30]. Therefore, any agent that can bring down the levels of the cytokines in the activated whole blood or PBMCs can be regarded as having control over the inflammatory process. TNF-α is responsible for increasing the number of effector cells at the inflammation site [31], while IFN-γ and IL-2 are proven to drive monocytes, macrophages, and lymphocytes during autoimmune-related inflammation [32]. On the other hand, IL-8 invades the neutrophils and macrophages at the inflammatory site and further drives the process [33]. The efficacy of IPX-18 in deteriorating these cytokine levels could thereby be related to the molecule’s anti-inflammatory potency.
During acute inflammation, polymorphonuclear neutrophils constitute the first line of defense [34]. As observed in the neutrophil migration assay, the influx of the activated neutrophils was attenuated by IPX-18. Research indicates that TNF-α is a chief proinflammatory cytokine which plays a role in leukocyte rolling and adhesion [35]. Furthermore, studies have shown that the inhibition of NF-κB by impeding p50 nuclear translocation via interleukin-10 exerts anti-inflammatory effects [36]. The present study observed neutrophil attenuation and the migration inhibition of TNF-α by IPX-18. Neutrophil elastase is an essential factor for the progression of many types of inflammation and is well liked with respect to neutrophil migration and activation [2]. The dose-dependent elastase inhibition of IPX-18 observed in this study could be attributed to the attenuation of both the compound and the neutrophil infiltration functions. Similarly, basophil activation is yet another important mechanism in inflammatory responses [37]. The lysosomal membrane protein CD63 was well expressed on the activated basophil surface [38], which accounted a direct measure of the activated basophils using flow cytometry [39]. In order to discriminate the CD63 positive basophils from the other cell types, such as eosinophils, T cells, and neutrophils, CCR3 was used as a gate marker in the flow cytometry assay [40]. Consequently, the CCR3 + CD63 positive population accounted a direct measure for the activated basophils expressing the high-affinity IgE receptor FcεRI [40,41]. Therefore, several IgE mediated inflammatory responses were diagnosed using the FcεRI-BAT assay [42]. The observations in the present study stand well with reports indicating the efficacy of IPX-18 in inhibiting basophils’ activation.
Mainstream allergy diseases are mediated by immunoglobulin E (IgE)-dependent reactions [43]. These allergic inflammations are provoked in dual phases, the initial induction phase followed by the effector phase [44]. During the initial phase, IgE couples with the surface FcεRI-IgE receptors of mast cells and basophils [44]. During the second phase, the adjacent IgEs of different presensitized basophils/mast cells are crosslinked by the allergen to release proinflammatory cytokines [44]. At the end of the effector phase, secondary cells such as the neutrophils are recruited and are activated by the effector substances released by the activated mast cells and basophils [45]. Together, basophil stimulation and mast cell stimulation in addition to the downstream activation of neutrophils are centrally driven by IgE orchestrated mechanisms. Hence, this study evaluated the efficacy of IPX-18 in activated rat basophils (RBL-2H3 cells) on IgE mediated stimuli. The observations indicated the nontoxicity of IPX-18 in the normal RBL-2H3 cells and activated RBL-2H3 cells, thereby indicating its therapeutic safety. Additionally, the compound also dose-dependently inhibited TNF-α release and degranulation in the activated RBL-2H3 cells, proving the anti-inflammatory efficacy of IPX-18 in IgE driven inflammatory manifestations.
NF-κB is a multifunctional protein located downstream of Akt and is considered an ideal proinflammatory marker [46]. Studies show that NF-κB is activated by heterodimer formation between p50 and p65 [47]. Therefore, the p50 subunit of NF-κB could be targeted to impede complex formation, thereby deactivating NF-κB activation. Our computational analysis predicted that IPX-18 would effectively bind NF-κB-p50. The in vitro results of this study agreed with the computational prediction, where the inhibition of NF-κB phosphorylation was evident with IPX-18 treatment. It has been previously shown that NF-kB/p65 antagonizes Nrf2-ARE signaling [47]. Nrf2 activity is critical for the body’s defense against oxidants, carcinogens, and inflammatory insults, and the overexpression of p65 suppresses Nrf2 levels/activity. Furthermore, it is reported that Nrf2 signaling reversely affects the regulation of the inflammatory responses arbitrated by NF-κB [47]. Thus, inhibiting p65 activity upregulates the Nrf2 levels. The observations of the present study stand well with the literature, where IPX-18 induced the elevation of the Nrf2 levels by translocating it into the activated RBL-2H3 cells’ nuclei. Therefore, it can be postulated that the efficacy of IPX-18 could be driven by the NF-κB pathway, causing the upregulation of Nrf2 proteins.
## 5. Conclusions
In summary, IPX-18 demonstrated excellent efficacy in controlling various mediators of the inflammatory responses through the dephosphorylation of NF-κB and the upregulation of Nrf2 proteins. These findings provide new insights for future research on the molecule for its development into a novel anti-inflammatory agent to treat several diseases.
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|
---
title: Melatonin Supplementation during the Late Gestational Stage Enhances Reproductive
Performance of Sows by Regulating Fluid Shear Stress and Improving Placental Antioxidant
Capacity
authors:
- Likai Wang
- Laiqing Yan
- Qi Han
- Guangdong Li
- Hao Wu
- Xiao Ma
- Mengmeng Zhao
- Wenkui Ma
- Pengyun Ji
- Ran Zhang
- Guoshi Liu
journal: Antioxidants
year: 2023
pmcid: PMC10045541
doi: 10.3390/antiox12030688
license: CC BY 4.0
---
# Melatonin Supplementation during the Late Gestational Stage Enhances Reproductive Performance of Sows by Regulating Fluid Shear Stress and Improving Placental Antioxidant Capacity
## Abstract
In this study, the effects of daily melatonin supplementation (2 mg/kg) at the late gestational stage on the reproductive performance of the sows have been investigated. This treatment potentially increased the litter size and birth survival rate and significantly increased the birth weight as well as the weaning weight and survival rate of piglets compared to the controls. The mechanistic studies have found that these beneficial effects of melatonin are not mediated by the alterations of reproductive hormones of estrogen and progesterone, nor did the glucose and lipid metabolisms, but they were the results of the reduced oxidative stress in placenta associated with melatonin supplementation. Indeed, the melatonergic system, including mRNAs and proteins of AANAT, MTNR1A and MTNR1B, has been identified in the placenta of the sows. The RNA sequencing of placental tissue and KEGG analysis showed that melatonin activated the placental tissue fluid shear stress pathway to stimulate the Nrf2 signaling pathway, which upregulated its several downstream antioxidant genes, including MGST1, GSTM3 and GSTA4, therefore, suppressing the placental oxidative stress. All these actions may be mediated by the melatonin receptor of MTNR1B.
## 1. Introduction
During the process of pregnancy, the placenta (a temporary organ) is formed between the mother and the fetus. The placenta provides an interface between the mother and the fetal circulation for dual directional transportations of nutrients, oxygen and metabolic wastes, which is essential for proper fetal growth [1]. Therefore, the abnormal placental function will lead to a variety of pregnancy disorders, including intrauterine growth restriction, pre-eclampsia, and abortion. For example, the placental malfunction associated abnormal intrauterine environment during the embryonic period not only inhibits the fetus’ development and growth but also increases the risk of diabetes, hypertension and cardiovascular diseases after birth [2]. Even though multiple risk factors are attributed to placental dysfunctions, one of them is oxidative stress [3,4]. It has been reported that maternal exposure to high levels of reactive oxygen species (ROS) during pregnancy impairs placental function and leads to poor outcomes in pregnancy [5].
Oxidative stress can cause cell damage and, if not treated properly, ultimately will result in cell death [6]. Heat or cold stress, obesity, viral infection and other insults during pregnancy will increase the level of placental oxidative stress and jeopardize placental function with abnormal fetal development [7,8,9,10]. Specific to sows, the late gestation period is a critical stage for the development and growth of piglets. At this stage, the placenta needs to support the rapid growth of the fetus; therefore, it consumes a lot of energy, which will increase the maternal metabolic burden and oxidative stress [11]. To retard this placental oxidative stress, antioxidants have been used as effective strategies to prevent the adverse outcomes of pregnancy in animals [5].
Melatonin (N-acetyl-5-methoxytryptamine) is an antioxidant mentioned above. Melatonin is an indolamine molecule present in bacteria found in mammals [12]. It exhibits a spectrum of biological functions, including regulation of biological rhythm, sleep, immune function and reproductive physiology [13]. Importantly, melatonin and its metabolites have potent anti-oxidative activity, which not only directly scavenges free radicals but also upregulates the expression of antioxidant enzymes [14,15]. Evidence has shown that melatonin can be synthesized in the human placenta locally. This is indicated by the melatonin production positively relates to the function of the placenta. For example, the level of melatonin in peripheral blood gradually increases with the progress of human pregnancy, reaches a peak in the prenatal period, and returns to a normal level after delivery [16]. In addition, melatonin receptors 1A (MTNR1A) and 1B (MTNR1B) have also been expressed in human placental tissues [17]. Treatment of cytotrophoblast cells with melatonin improves cellular syncytization and promotes the synthesis and secretion of human chorionic gonadotophin (hCG) [17]. Under placental dysfunction with fetal growth restriction, the expressions of MTNR1A and MTNR1B are downregulated, and the level of melatonin in peripheral blood is significantly decreased, suggesting an important role of melatonin in the maintenance of human placental function [18,19]. Melatonin supplementation in rats between days 15 and 20 of gestation improves their placental function and puppy’s birth weight via upregulating the expression level of antioxidant enzymes in placental tissue under the condition of malnutrition [20]. Renshall et al., have reported that in mice with normal pregnancy, melatonin supplementation between days 12.5 and 18.5 of the gestation stage also increases fetal birth weight [21]. Recently, Peng et al., supplemented melatonin to sows from the period of fertilization to parturition [22]. They observed that the proportion of piglets with birth weight <900 g was reduced, but the average birth weight of piglets exhibited no significant difference compared to the control. They attributed these to the antioxidant properties of melatonin. The early intervention of pregnant animals with antioxidants is debatable since an appropriate ROS level is essential for placental angiogenesis at the initial stage of gestation. For example, Yang et al., found that the antioxidant treatment can significantly reduce the blood vessel density of the placenta in the mouse placenta formation stage and also significantly reduce fetal birth weight and aggravate the intrauterine growth restriction phenotype [23,24]. Specific to sows, the late gestation stage is the most important period of fetal growth and development, which will produce a large number of ROS and easily lead to intrauterine growth restriction [25].
Therefore, in the current study, melatonin was given to the sows at their gestation days between 90–114 to investigate whether melatonin supplementation at the late gestation stage could improve placental function and thus improve fetal growth. If it does, what are the underlying molecular mechanisms and signal transduction pathways? The results will provide valuable information for the application of melatonin to improve reproductive efficiency in swine or even in other animals.
## 2.1. Chemicals and Agents
Melatonin was purchased from Sigma Company (St. Louis, MO, USA). The glucose detection kit (F006-1-1), triglyceride detection kit (A110-1-1) and malondialdehyde detection kit (A003-1-2) were purchased from Nanjing Jiancheng Biological Engineering Research Institute Co., Ltd. (Nanjing, China) The prolactin detection kit (P07PZB), progesterone detection kit (P08PZB), estradiol detection kit (B05PZB), and cortisol detection kit (D10PZB) were purchased from Beijing North Biotechnology Research Institute Co., Ltd. Antibodies against AANAT (ab3505), MTNR1A (ab203038) and MTNR1B (ab203346) were purchased from Abcam (Cambridge, MA). The secondary antibody conjugated with CoraLite594 (SA00013-4) was purchased from Proteintech (Wuhan, China). The secondary antibody conjugated with Peroxidase (ZB-2301) was purchased from Beijing Zhongshan Jinqiao Biotechnology Co., Ltd. (Beijing, China).
## 2.2. Animals
The design of animal experiments in this study complies with the regulations of the Animal Welfare Committee of China Agricultural University (permission number: AW60103202-3-1). The sows (Large White × Landrace) are from Yantai Fuzu Food Co., Ltd. in Shandong province. All sows were first farrowing sows (approximately one year old) with similar backfat thickness.
## 2.3. Animal Study Design
Twelve sows with similar body weight (around 200 kg) at 90 days of gestation were divided into a control group and a melatonin group, with 6 sows in each group. The environmental light/dark cycle was $\frac{12}{12}$ h, and the temperature was controlled at 20–25 °C. These sows were given the same basal diet twice a day, at 7:00 am and 5:00 pm, but the experimental group was given additional melatonin. Melatonin was given daily at 7:00 am at a dose of 2 mg/kg added directly to the feed to ensure complete consumption. At 107 days of gestation, the sows were transferred to the farrowing room. The treatment was continued from 90 days of gestation to parturition.
## 2.4. Blood Sample Collection
In order to avoid premature labor caused by the stress of frequent blood collection, we decided to reduce the blood collection as less as possible. Therefore, we selected to collect blood every 10 days after melatonin treatment (corresponding to the middle and late stages of the melatonin feeding cycle), i.e., on days 100 and 112 of gestation, respectively. Blood was collected from the antecubital vein with 8 mL volume each time, and blood samples were placed in 10 mL sterile heparinized vacuum tubes and immediately centrifuged at 3500 g for 15 min. The plasma was separated and stored at −80 °C for further analysis of melatonin, hormone and biochemical indexes.
## 2.5. Measurement of Piglet Weight after Birth and Placental Tissue Collection
After birth, the total number of piglets was recorded, including the survived and dead (One sow in the control group had premature birth and was not included in the statistics). The weight of the piglets was measured after the piglet coat was dried. The expelled placental tissue was collected, rinsed in PBS and immediately placed in liquid nitrogen for rapid freezing (about 5 g per placenta, 3 to 4 cm from the point of umbilical cord insertion). A 2 mL of colostrum sample was collected from each sow and stored at −80 °C for future analysis.
## 2.6. Melatonin Detection
The serum or colostrum was mixed with methanol at a ratio of 1:4, vortex-oscillated, and centrifugated (4 °C, 12,000 rpm) to collect supernatant, filtered with 0.22 µm of filter, and the effluent was used for melatonin detection. Melatonin detection was carried out in the central laboratory of the Beijing Institute of Animal Science, Chinese Academy of Agricultural Sciences, by the high-performance liquid mass spectrometer (Agilent1290-G6470, Santa Clara, CA, USA).
## 2.7. Detection of Hormone and Biochemical Indicators
Serum reproductive hormones, including progesterone, estrogen, cortisol and prolactin, were determined by radioimmunoassay (Xi’an Nuclear Instrument Factory, XH6080). For progesterone and cortisol detection, 50 μL serum samples, 100 μL 125I-progesterone or 100 μL 125I-cortisol, then 100 μL rabbit anti-progesterone antibody or 100 μL rabbit anti-cortisol antibody, were pooled together, respectively. The samples were incubated at 37 °C for 1 h, then 500 μL of immunoseparation agent was added and placed at room temperature for 15 min. After that, the samples were centrifuged at 3500 rpm/15 min to remove the supernatant, and the radioactive count of the pallets was detected. For prolactin detection, 100 μL serum, 100 μL of 125I-prolactin and 100 μL of rabbit anti-prolactin antibody were mixed and incubated at 4 °C for 24 h, then 500 μL of immunoseparation agent were added and placed the samples at room temperature for 15 min, after that, the samples were centrifuged at 3500 rpm/15 min to remove the supernatant, and the radioactive count of the pallets was detected. For estradiol detection, 100 μL serum, add 100 μL of 125I-estradiol and 100 μL of rabbit anti-estradiol antibody were pooled together and incubated at 37 °C for 1 h, then 500 μL of immunoseparation agent were added, and the samples were placed at room temperature for 15 min, after that, the samples were centrifuged at 3500 rpm/15 min to remove the supernatant, and the radioactive count of the pallets was detected. The serum glucose was measured by use of the glucose oxidase method following the manufacturer’s instructions, and the absorption at the wavelength of 505 nm was detected to calculate the glucose content (Glucose concentration = sample absorption value/calibrator absorption value × calibrator concentration) [7]. The serum triglyceride was measured by use of the enzyme method following the manufacturer’s instructions, and the absorption at the wavelength of 546 nm was detected to calculate the triglyceride (Triglyceride concentration = sample absorption value/calibrator absorption value × calibrator concentration) [7]. The serum malondialdehyde was measured by use of the thiobarbituric acid method following the manufacturer’s instructions, and the absorption at the wavelength of 532 nm value was detected to calculate the malondialdehyde content ((Sample absorbance value − blank absorbance value)/(standard absorbance value − blank absorbance value) × Standard concentration) [7].
## 2.8. Real-Time Quantitative PCR
Total RNA was extracted from fresh placental tissue using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). 1 μg total RNA was synthesized using PrimeScript™ RT Master Mix (TaKaRa, Kusatsu, Japan). Primers selected for PCR analyses were designed using Primer5 and are listed in Supplementary Table S1. The total reaction volume (20 μL) comprised 2 μL of cDNA template solution, 10 μL of SYBR Green PCR Master Mix (Roche, Basel, Switzerland), 6.4 μL of water, and 0.8 μL of each primer. The RT PCR program included a 10 min incubation at 95 °C, followed by 40 cycles of denaturation for 15 s at 95 °C and annealing and extension for 30 s at 60 °C. The mRNA expression levels of the target genes were normalized to the expression of GAPDH. *Relative* gene expression was expressed as a ratio of the target gene to the control gene using the formula 2−(ΔΔCT).
## 2.9. Western Blotting
Total cell lysates were prepared from fresh placental tissue using a cell lysis buffer RIPA (Beyotime, Shanghai, China) containing $1\%$ PMSF. The placental tissue was homogenatized by a *Vortex* generator (Roche, Basel, Switzerland, USA), and the supernatant was collected after centrifugation. The protein concentrations were determined using an Enhanced BCA Protein Assay Kit (Beyotime, Shanghai, China). The same volume of 5 × loading buffer was mixed with the samples, which were subject to boiling for 10 min. After separation on $10\%$ SDS-PAGE, the samples were transferred to a 0.45 mm PVDF membrane followed by a 2-h blocking with $5\%$ non-fat dry milk at room temperature. Then the membranes were then incubated overnight at 4 °C with respective primary antibodies (dilution rate 1:1000). After incubation with a secondary antibody (dilution rate 1:10,000) for another 1 h, then the protein expression was detected by a Super Signal™ West Pico PLUS Chemiluminescent Substrate (Thermo, Waltham, MA, USA).
## 2.10. Immunofluorescence Detection of AANAT, MTNR1A and MTNR1B
Placental tissues fixed in $4\%$ paraformaldehyde were paraffin-embedded and sectioned at 5 μm thickness for AANAT, MTNR1A and MTNR1B immunofluorescence. The placental tissue sections were dewaxed and rehydrated; sodium citrate was used for thermal repair and then incubated with a catalase blocker for 10 min. After rinsed with PBS, a monoclonal antibody of AANAT, MTNR1A and MTNR1B were added for overnight incubation (dilution rate 1:100). A secondary antibody coupled with CoraLite594 (dilution rate 1:100) was incubated and nucleated with 4′,6-diaminyl-2-phenylindole (DAPI) for observation. Finally, the slides were visualized under a fluorescent microscope (Nikon Eclipse C1, Tokyo, Japan).
## 2.11. RNA-Seq for Placenta Tissue
Total RNA was extracted from placenta tissue by TRIzol (Ambion, 15596026), and genomic DNA was removed by DNase I (TaKara). The quality of RNA samples was detected by 2100 Bioanalyser (Agilent, Palo Alto, CA, USA) and ND-2000 (NanoDrop Technologies, Wilmington, DE, USA). After the samples were qualified (OD$\frac{260}{280}$ = 1.8–2.2, OD$\frac{260}{230}$ ≥ 2.0, RIN ≥ 6.5), 28S:18S ≥ 1.0, >2 mg) were sequenced.
TruSeqTM RNA Sample Preparation Kit (Illumina, San Diego, CA, USA) was used for the construction of the RNA library. SuperScript double-stranded cDNA synthesis Kit (Invitrogen, Carlsbad, CA, USA) was used to inversely synthesize cDNA and form a stable double-stranded structure. After cDNA enrichment by PCR (sample Preparation Kit (Illumina, San Diego, CA, USA) Kit), DNA clean Beads (DNA Clean Beads) are screened for 200–300 bp bands. After quantified by TBS380 (Picogreen), Illumina HiSeq XTEN/NovaSeq 6000 sequencing platform was used for high-throughput sequencing with a read length of PE150.
## 2.12. Statistical Analysis
Data are expressed as the means ± SEM. A two-tailed Student’s t-test was used for statistical analysis using GraphPad Prism Software 7.00. p-values < 0.05 were considered to be statistically significant.
## 3.1. Effects of Melatonin Supplementation on Levels of Melatonin in Blood and Colostrum
The blood melatonin levels at 100 and 112 days of gestation are shown in Figure 1A. Compared to the control group, melatonin supplementation significantly increased the blood melatonin levels in sows at day 100 and 112 of gestation, respectively ($p \leq 0.05$). The results also showed that blood melatonin concentrations in control sows at 112 days of gestation (188.1 ± 13.02 ng/mL) were significantly higher than those at 100 days of gestation (103.8 ± 26.49 ng/mL) ($p \leq 0.05$, Figure 1A). In addition, the melatonin level in the colostrum of sows was also significantly increased after melatonin feeding (61.0 ± 6.68 ng/mL versus 135.5 ± 12.20 ng/mL, $p \leq 0.01$, Figure 1B).
## 3.2. Effects of Melatonin Supplementation on Reproductive Performance of Sows
The results showed that the birth time of sows in the control group was mainly at night, while the birth time of sows in the melatonin supplementation group was mainly during the day (Figure 2A). As shown in Figure 2B,C, melatonin feeding exhibited the tendency to increase the average total litter size (12.0 ± 1.30 versus 13.0 ± 1.13) and average total live births of the piglets (11.0 ± 1.05 versus 12.4 ± 1.36) compared to the control group, but the difference did not reach to the statistical significance ($p \leq 0.05$). It is interesting to note that melatonin significantly increased piglet weight at birth compared to the control group (1.4 ± 0.04 kg versus 1.2 ± 0.05 kg, $p \leq 0.01$, Figure 2D) while no sows were found to have difficulty in farrowing due to the increased body weight of the litters in the melatonin group. The weaning survival rate (91.27 ± 0.81 versus 87.46 ± 1.34, $p \leq 0.05$, Figure 2E) and weight (8.2 ± 0.18 kg versus 7.2 ± 0.18 kg, $p \leq 0.01$, Figure 2F) of the piglets were also significantly higher in the melatonin-added group than in the control group at 21 days after birth.
## 3.3. Effects of Melatonin Supplementation on Blood Reproductive Hormone and Other Biochemical Parameters
The results showed that melatonin supplementation did not change blood prolactin levels at 100 days of gestation but significantly increased prolactin levels at 112 days of gestation (GD 100: 213.2 ± 15.42 µIU/mL versus 206.2 ± 13.98 µIU/mL, GD 112: 30.3 ± 1.38 µIU/mL versus 71.78 ± 0.03 µIU/mL) ($p \leq 0.05$, Figure 3A). Melatonin supplementation in late pregnancy did not change the concentrations of progesterone, estradiol and cortisol in the blood ($p \leq 0.05$, Figure 3B–D). In addition, melatonin supplementation in late gestation did not affect glucose and triglyceride levels in the peripheral blood of sows ($p \leq 0.05$, Figure 3E,F).
## 3.4. Effects of Melatonin Supplementation on Melatonin Synthetic Enzyme AANAT and Melatonin Receptor Expression in Placental Tissue
In this study, the expression of melatonin synthesizing rate-limiting enzyme AANAT and melatonin receptors MTNR1A and MTNR1B was detected by immunofluorescence in the placenta. The results showed that AANAT, MTNR1A and MTNR1B were expressed in the pig placenta and were mainly located in the outermost placental trophoblast cells (Figure 4A). Melatonin supplementation significantly increased the mRNA level of MTNR1B in placental tissue but did not affect the expression of MTNR1A compared with the control group (Figure 4B,C). In addition, Q-PCR and Western blot were used to detect the AANAT expression, as shown in Figure 4D,E; melatonin supplementation did not change the mRNA and protein level of AANAT in the placenta ($p \leq 0.05$).
## 3.5. Effects of Melatonin Supplementation on the Transcriptome of Placental Tissue of Sows
Transcriptome sequencing was performed on the placental tissues. As shown in Figure 5A, there were significant differences in gene expression in the placenta between the melatonin supplementation group and the control group. A total of 758 differentially expressed genes (DEGs) were screened, including 484 upregulated and 274 down-regulated genes (Figure 5B). The biological features of DEGs were analyzed using Gene ontology (GO) analysis. The differentially expressed genes obtained from GO enrichment analysis were classified according to biological process (BP), cellular component (CC) and molecular function (MF). The most remarkably enriched BP terms were cell adhesion (GO:0007155), GC terms were plasma membrane region (GO:0098590), and MF terms were G protein-coupled receptor binding (GO:0001664) (Figure 5C–E). Kyoto Encyclopedia of Genes and Genomes (KEGG) is a comprehensive data library that combines information on genomic, chemical and system functions. The most significantly enriched pathways for DEGs were fluid shear stress and atherosclerosis, rap1 signaling pathway and proteoglycans in cancer (Figure 5F). Based on the results of further analysis, we suggest that Fluid shear stress and atherosclerosis signaling pathways may mediate the effects of melatonin on placental function.
## 3.6. Placental Tissue Antioxidant Capacity Test
Fluid shear stress and atherosclerosis are antioxidant-related pathways that can activate the Nrf2 signaling pathway to regulate the expression of many antioxidant genes. The results of RNA sequencing analysis showed that many antioxidant genes were enriched in Fluid shear stress and atherosclerosis pathway, including MGST1, GSTM3, GSTA1, SOD2 and GSTA4. Therefore, Q-PCR was performed to verify these differential genes. The results showed that melatonin supplementation significantly increased the expression levels of antioxidant genes MGST1, GSTM3 and GSTA4 in placental tissue compared to control ($p \leq 0.05$, Figure 6A–C), while no significant differences were observed as to the expression of GSTA1 and SOD2 between the groups ($p \leq 0.05$, Figure 6E). In addition, the level of malondialdehyde (MDA) in the peripheral blood of melatonin-treated sows was significantly lower than that in the control group ($p \leq 0.05$, Figure 6F). These results indicate that melatonin can improve the anti-oxidative stress ability of placental tissue by regulating fluid shear stress.
## 4. Discussion
As a “transport station”, the placenta plays an important role in transporting nutrients, oxygen/carbon dioxide and metabolic waste between mother and fetus, and thus, the placenta’s health is the premise of the normal growth and development of the fetus. Evidence shows that placental tissue is highly susceptible to oxidative stress caused by its extensive metabolic activity and other environmental insults. The excessive oxidative stress in the placenta, if not balanced by the antioxidant system, will damage placental function, leading to pre-eclampsia, intrauterine growth retardation of the fetus, and abortion [26]. Therefore, antioxidants have been widely used to prevent and treat placental dysfunction in animal models and also in human subjects [20,27]. Melatonin is a naturally occurring antioxidant. Different from other antioxidants, melatonin is an amphiphilic molecule being soluble in both water and fat [27,28]. This feature of melatonin makes it permeable to the placental barrier as well as to the embryo, with ease to act on both of them. This is an important reason that melatonin was selected in the current study to test whether melatonin supplementation to sows at their late stage of gestation would provide beneficial effects on the placenta via its antioxidant activity. Melatonin has been used to improve reproductive activity in different animals. For example, in sheep, the subcutaneous embedding of melatonin promoted the growth and development of lambs [29]. As mentioned above, Peng et al., gave melatonin to early gestated sows and also tested their oxidative stress responsibility [22]. Their study seems to have some similarities to ours. However, the targeted problems, the methods used and the findings were considerably different. We believe that early antioxidant intervention for pregnant animals like Peng et al., may do more harm than good by impairing angiogenesis and reducing the vascular density of the placenta. This is the reason that we gave melatonin to the pregnant sows at their late stage of gestation. We observed that this treatment potentially increased litter size and survival rate and significantly increased the birth weight as well as the weaning survival rate and weaning weight of piglets compared to the control. These beneficial effects of melatonin were not observed by Peng et al. Therefore, melatonin therapy should be used with caution in the early stages of normal pregnancy in pigs.
To explore the potential mechanisms, the effects of melatonin on the reproductive hormones, including progesterone and estrogen, are analyzed. Progesterone and estrogen are important hormones that regulate reproductive activities and establish and maintain pregnancy [30]. In this study, it is found that melatonin supplementation does not modify levels of blood progesterone and estrogen. The results are similar to that reported by Peng et al., and Lv et al. [ 22,31]. In addition, energy metabolism and cortisol level are also important factors for the reproductive performance of animals [32,33]. However, melatonin supplementation at the late gestational stage of sows also does not influence glucose and lipid metabolism, as well as the blood cortisol content, compared to the control. In this study, melatonin supplementation can significantly promote prolactin levels in peripheral blood during the prenatal period (112 days of gestation), which may improve the lactation performance of sows after delivery, but does not affect prolactin levels at 100 days of gestation. Similar to the properties of melatonin, prolactin synthesis also has an obvious circadian rhythm, suggesting that there may be a regulatory relationship between melatonin and prolactin. Misztal et al., showed that melatonin injection for 30 min resulted in increased prolactin levels in the peripheral blood of sheep [34]. Melatonin may be involved in the synthesis of prolactin, but the specific molecular mechanism remains to be further explored. Based on the above observations, the focus, then, is given to the effects of melatonin on the placenta.
As mentioned previously, the placenta is the key structure to maintaining the fetus’s health, and it is also an important organ for melatonin synthesis during pregnancy [35]. The expressions of both melatonin synthetic rate-limiting enzymes AANAT and ASMT have been identified in human placental tissue. Meanwhile, melatonin receptors MTNR1A and MTNR1B are found in cytotrophoblast cells, syncytiotrophoblast cells and endothelial cells in the placental villi of humans [36]. Whether the melatonergic system is also expressed in the porcine placenta remains unknown. Here, we first report that the melatonergic system, including the mRNAs of AANAT, MTNR1A and MTNR1B, has been identified in the porcine placenta, and they are mainly expressed in trophoblast cells. In the current study, it was observed that melatonin supplementation at the late gestation stage mainly upregulated the expression of MTNR1B but not MTNB1A. The results suggest that the effects of melatonin on the placenta may be likely mediated by MTNR1B.
To further explore the molecular mechanisms, placental tissues are sequenced by RNA. KEGG analysis of differential genes showed that the fluid shear stress and atherosclerosis signaling pathways were significantly enriched in the melatonin-treated placenta. The fluid shear stress pathway in the placenta can regulate the expression of the placental growth factor, which is an important regulator of placental angiogenesis [37]. Meanwhile, fluid shear stress can activate TRPV6 to promote placental microvilli formation [38]. Most importantly, fluid shear stress plays an important role in regulating the body’s antioxidant capacity [39]. It stabilizes Nrf2 and upregulates the expression of a spectrum of downstream antioxidant genes [40]. This observation has not been reported previously. The expressions of several downstream antioxidant genes of Nrf2, including MGST1, GSTM3 and GSTA4 in placental tissue, were significantly upregulated with melatonin supplementation compared to the control group. This observation is in line with the report of Peng et al. They also found that maternal melatonin supplementation increased the expression of antioxidant-related genes SOD, GPx1 and NQO1 in the placenta. The regulation of the Nrf2 signaling pathway by melatonin has been well documented. Under heat stress, melatonin activates the Nrf2 signaling pathway to improve the antioxidant capacity of Sertoli cells and alleviates heat-induced damage [41]. During cryopreservation of ovarian tissue, melatonin stimulates Nrf2/HO1 signaling pathway and inhibits ovarian oxidative stress and apoptosis [42]. Melatonin also reduces cadmium-induced damage in supporting cells by activating the Nrf2 signaling pathway [43]. Although many studies have documented the regulation effect of melatonin on the Nrf2 signaling pathway, the specific molecular mechanism has not been clarified. In this study, we have found that the activation of the Nrf2 signaling pathway by melatonin is probably mediated by the fluid shear stress pathway, particularly in sow placental tissue, thus improving the antioxidant capacity of placental tissue. This conclusion is further supported by the significantly decreased levels of lipid peroxidation product MDA in the serum of melatonin-supplemented sows compared to the controls.
## 5. Conclusions
In conclusion, melatonin supplementation during a late gestational stage in sows significantly improves the reproductive performance of the sows, including the potential increase in litter size, birth survival rate and significant increases in the birth weight as well as the weaning weight of piglets. These beneficial effects are mainly associated with the improved placental function of the sows with melatonin supplementation. Actually, the melatonergic system, including the mRNAs of AANAT, MTNR1A and MTNR1B, has been identified in the placenta of the sows. The potential molecular mechanisms involved in melatonin activate the placental tissue fluid shear stress pathway, which stimulates the Nrf2 signaling pathway and upregulates the downstream antioxidant genes to suppress the placental oxidative stress. Judging from the expression patterns of MTNR1B and MTNB1A with melatonin supplementation at the late gestation stage, that is that this treatment mainly upregulated the expression of MTNR1B but not MTNB1A. Therefore, we suggest that these effects may be mediated by the melatonin receptor of MTNR1B. This pathway is illustrated in (Figure 7).
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|
---
title: 'Assessment of magnitude and spectrum of cardiovascular disease admissions
and outcomes in Saint Paul Hospital Millennium Medical College, Addis Ababa: A retrospective
study'
authors:
- Mekoya D. Mengistu
- Henok Benti
journal: PLOS ONE
year: 2022
pmcid: PMC10045542
doi: 10.1371/journal.pone.0267527
license: CC BY 4.0
---
# Assessment of magnitude and spectrum of cardiovascular disease admissions and outcomes in Saint Paul Hospital Millennium Medical College, Addis Ababa: A retrospective study
## Abstract
### Background
Cardiovascular diseases(CVD) remain the leading cause of death in the world and over $80\%$ of all cardiovascular-related deaths occur in low and middle income countries. Ethiopia is in epidemiologic transition from predominantly infectious diseases to non-communicable diseases and the CVD is a major public health challenge.
### Methods
The aim of this study was to assess the magnitude and spectrum of cardiovascular admission and its outcomes among medical patients admitted to both Medical Ward and ICU of St. Paul Teaching Hospital from 1st of Jan 2020 to 1st of Jan 2021.
### Results
Out of 1,165 annual medical admissions, the prevalence of cardiovascular diseases(CVD) was $30.3\%$. About $60\%$[212] of patients had advanced congestive heart failure of diverse causes. Hypertensive heart disease (HHD) was the next predominant diagnosis ($41\%$[146]), and also the leading cause of cardiac diseases followed by rheumatic valvular heart disease(RVHD) ($18\%$[64]) and Ischemic heart disease (IHD) ($12.2\%$[43]), respectively. Yong age, rural residence and female sex were associated with RVHD($$p \leq 0.001$$). Stroke also accounted for $20\%$[70] of CVD admission (hemorrhagic stroke-$17\%$ Vs Ischemic stroke-$83\%$). Hypertension was the predominate risk factor for CVD and present in $46.7\%$[168] of patients. The mean hospital stay was 12days and in-hospital mortality rate was $24.3\%$ with septic shock being the commonest immediate cause of death followed by fatal arrhythmia, brain herniation, and massive PTE.
### Conclusion
Cardiovascular diseases were common in the study area causing significant morbidity and mortality. Therefore, comprehensive approach is imperative to timely screen for cardiovascular risk reduction, disease control and complication prevention. Strategies should also be designed to increase public awareness regarding the cardiovascular risk reduction, drug adherence, and possible complications.
## Introduction
The impacts of non-communicable diseases (NCDs) are particularly devastating in poor and vulnerable populations [1]. NCDs currently cause more deaths than all other causes combined and is projected to increase from 38 million in 2012 to 52 million by 2030 [2]. Nearly three quarters of all NCD deaths occur in low- and middle-income countries. NCD deaths will increase by $17\%$ over the next ten years and the greatest increase will be seen in the African region [2]. In Ethiopia, the recent NCD deaths are estimated at around $42\%$ with cardiovascular diseases are the predominant cause of morbidity and mortality [3–5].
Cardiovascular disease remains the leading NCDs related cause of death in the world. Approximately $80\%$ of all cardiovascular-related deaths occur in low and middle income countries and at a younger age in comparison to high-income countries [6]. Africa is home to for over 1 billion people, and is a major contributor to the global burden of CVD [7,8]. In 2013, an estimated 1 million deaths were attributable to CVD in sub-Saharan Africa alone [7,9]. CVD-related deaths contributed to $38\%$ of all non-communicable disease-related deaths in Africa, reflecting the growing threat of both non-communicable disease and CVD [9]. The understanding of adults about CVD and its risk factors including hypertension and diabetes is low in developing countries. More than half of adults in sub-Saharan Africa have poor knowledge of CVD [10,11]. Similarly, in Ethiopia the knowledge of cardiovascular risk factors among CVD patients was unsatisfactory, and about half of the patients have suboptimal knowledge [12]. In another study, $52\%$ of Ethiopian hypertensive patients on follow up have poor basic knowledge of hypertension, and about $60\%$ of them have poor practice towards control of hypertension [13]. Patient noncompliance is also one of the most difficult challenges in the healthcare sector and therefore, it is vital to enhance patients’ awareness and knowledge about the complications and benefits of cardiovascular medications [14].
A cardiovascular spectrum study in Addis Ababa has revealed the five most common cardiovascular diseases such as valvular heart disease ($62\%$), hypertension ($14.7\%$), cerebrovascular disease ($11.5\%$), congenital heart disease ($8.5\%$), and ischemic heart disease (IHD) ($6.8\%$) [15]. Another outpatient CVD spectrum study also demonstrated that RHD was the common cause of cardiovascular disease followed by HHD and cardiomyopathy [16]. Similar study in the cardiac follow up clinic of Jimma Specialized Hospital showed that rheumatic heart disease was the leading cause of cardiac illness ($32.8\%$), followed by hypertensive heart disease ($24.2\%$), cardiomyopathy($20.2\%$), arrhythmia($13.5\%$) and cor-pulmonale($3.8\%$) [17]. However, there is an increasing trend of hypertensive heart disease in the subsequent periods replacing the place of valvular heart diseases.
A recent outpatient study conducted in Northern Ethiopia revealed that Hypertensive heart disease was the predominant etiologic diagnosis of cardiovascular disease followed by rheumatic heart disease [18]. In this study, hypertensive heart disease has markedly surpassed rheumatic heart disease as the leading heart disease which might be due to the high proportion of hypertension ($62.3\%$) among the CVD patients in the area [18]. In another African studies hypertension was also the main causes of heart failure ($21.3\%$), followed by rheumatic heart diseases ($20.1\%$), cardiomyopathy($16.8\%$), coronary artery disease($10\%$), and congenital heart disease ($9.8\%$) [19]. Different studies have demonstrated that much of the population risk of CVD is attributable to modifiable traditional risk factors, including hypertension, diabetes mellitus, dyslipidemia, smoking, lack of physical activity, and psychosocial factors [6,20]. These risk factors account for $61\%$ of CVD deaths globally and alleviating exposure to these risk factors would improve global life expectancy by almost 5 years [21]. In Ethiopia, there is a paucity of data regarding CVDs and their risk factors, making accurate estimation of burden in terms of the morbidity and mortality of CVDs extremely difficult. This study will therefore provide relevant data regarding the recent magnitude as well as spectrum of cardiovascular admission and its outcome among medical patients in St. Paul specialized hospital, Addis Ababa.
## Study setting
The study was conducted in the department of internal Medicine at St Paul Hospital Millennium Medical College (SPHMMC), which is one of the biggest tertiary governmental Teaching Hospitals in Addis Ababa, the Capital of Ethiopia and the seat of African Union. The hospital receives follow-up patients, emergency patients and referrals from other Hospitals and health facilities all over the country.
## Study design
An institutional based, retrospective, cross-sectional study was conducted at St Paul Teaching Hospital involving all the cardiovascular admissions in the medical ward and ICU from 1st of January 2020 to 1st of January 2021. Admission and discharge diagnosis was captured from the registry to further retrieve the chart of the patient for detailed review of demographic data, major investigations, co-morbidities, underlying background risk factors and control, admission/discharge diagnosis of cardiovascular diseases, duration of hospital stay and outcomes.
## Study population
The study included all eligible cardiovascular admissions among all the medical patients admitted to the study hospital during the stated period. A total of 353 patients with cardiovascular diagnosis among all the annual medical admissions of 1165 patients were evaluated during the specified study period. The exclusion criteria were patients whose medical records were incomplete or patients who were died before adequate diagnosis was made. A total of 40 patients with CVD diagnosis on the HMIS registry were excluded due to incomplete medical records.
## Data variables for the study
Relevant patient information was retrieved from the HMIS registry as well as medical records. Cardiovascular diseases included diseases that affect the heart and blood vessels. The main blocks of WHO International Classification of Diseases(ICD)-10th version for Mortality and Morbidity Statistics (MMS) (Version: 04 / 2019) was utilized to sort out the final diagnoses [22]. The unit of analysis was the hospital discharge and/or admission, not the patient and therefore, a patients admitted more than once in a year were counted each time as a separate “admission” to the hospital. In situations with more than one cardiovascular diagnosis in the same case, the different disease conditions were counted separately.
## Operational definition
Cardiovascular diseases comprise various diseases affecting the heart and blood vessels.
Hypertensive heart disease (HHD) was diagnosed in patients with hypertension presenting with symptoms and signs of heart failure, with or without left ventricular (LV) hypertrophy and left atrial enlargement on two-dimensional echocardiography or Doppler evidence of LV diastolic dysfunction in the absence of significant valvular heart disease or regional wall motion abnormality [16]. For those who have no documented 2-dimentional echocardiogrpahy, ECG evidence of left ventricular hypertrophy (LVH) was used.
Dilated cardiomyopathy (DCMP) was diagnosed in patients with marked LV dilatation and dysfunction in the absence of significant valvular, structural, or congenital heart disease or arterial hypertension [16].
Ischaemic heart disease (IHD) included any of the three entities: 1. Angina pectoris which is short lived, relieved with termination of the provoking factor or rest and had no typical ECG features of infarction, 2. Acute myocardial infarction which was defined by the presence of elevated cardiac biomarker together with acute onset chest pain, and/or typical ECG changes, 3. Prior myocardial infarction including patients who present with or without heart failure in whom echocardiography detected regional wall motion abnormality in the absence of a history of acute coronary syndrome [16]. Pathologic Q waves on ECG were used to predict the possibility of ischaemia as a cause of the regional wall motion abnormality in a dilated left ventricle with reduced ejection fraction.
Pulmonary heart disease (PHD): Right heart failure, also known as cor pulmonale due to altered structure and/or function of the right ventricle evidenced by 2-dimensional echocardiography.
Blood pressure control: Controlled BP when the mean BP < $\frac{140}{90}$ mmHg in hypertensive patients of all ages [23]. Uncontrolled BP when the mean BP ≥ $\frac{140}{90}$ mmHg in hypertensive diabetic patients of all ages [23].
Blood Sugar control: Good glycemic control when the mean Fasting blood sugar ≤ 130 mg/dL and /or HbA1C <$7\%$ and Poor glycemic control when mean Fasting blood sugar >130 mg/dL and/or HbA1C>$7\%$ [24].
## Data collection and instrument
In order to ensure the accuracy, completeness, and comparability of data, four senior medical residents were trained to complete data collection format. Data collection was made by the pretested structured check lists to document all the pertinent profiles of the study subjects.
## Data processing and statistical analysis
After checking for completeness, data was coded, entered, and analyzed using SPSS version 20 software. Descriptive statistics was used to calculate rates. Chi-square was used to estimate the associations between selected predictor variables. A p-value < 0.05 was taken as statistically significant.
## Ethical consideration
Ethical clearance was obtained from institutional review board (IRB) of St. Paul Teaching Hospital. Since it was a retrospective study, written consent was waived by the research and ethics committee. Anonymity of the patient profile was upheld.
## Socio-demographic characteristics of the study population
From the annual medical admissions of 1,165 patients to st. Paul Hospital Millennium Medical College from 1st of January 2010 up to 1st of January 2021, the total cardiovascular admissions constituted $30.3\%$[353]. Majority of the study subjects were females ($60\%$[213]). Addis Ababa together with Oromia regional state constituted $90\%$ of total cardiovascular admissions to St. Paul Hospital Millennium Medical College during the study period (Table 1). The minimum age among the cardiovascular admissions was 15years and the maximum age was 86years with the mean and median ages were 48.9 and 50years, respectively. The overall cardiovascular illness increased almost steeply with increasing age($$p \leq 0.001$$). However, further disease stratification showed that Rheumatic valvular heart diseases(CRVHD) and vascular diseases including deep vein thrombosis (DVT), pulmonary thromboembolism (PTE) and cerebral venous thrombosis (CVT) were more common in the younger age and proportionally decreased as age advances($$p \leq 0.001$$) (Fig 1).
**Fig 1:** *The associations of major cardiovascular diseases with increasing age.$p \leq 0.001.$* TABLE_PLACEHOLDER:Table 1
## Spectrum of cardiovascular diseases and associated risk factors
The spectrum of major cardiovascular diseases was scrutinized according to the ICD-10 classification of diseases [22] and most of the patients had two or more cardiovascular diagnoses. From all cardiovascular admissions, about $60\%$[212] of patients had advanced congestive heart failure (NYHA class III and class IV) (Table 2). The advanced congestive heart failure (CHF) had multiple underlying etiologies, and also multiple precipitating factors including hypertension($35\%$[74]), lung infection(pneumonia) ($34\%$[72]), drug discontinuation ($25.5\%$[54]), and arrhythmia ($23.6\%$[50]) predominantly atrial fibrillation with fast ventricular response(Afib with FVR).
**Table 2**
| CVD spectrum | Frequency(n) | Percentage(%) |
| --- | --- | --- |
| CHF(NYHA class III and IV) | 212 | 60.0 |
| HHD | 146 | 41.36 |
| CRVHD | 64 | 18.1 |
| IHD | 43 | 12.2 |
| PHD | 40 | 11.3 |
| DCMP | 34 | 9.6 |
| DVHD | 9 | 2.5 |
| Vascular DiseasesΔ | 85 | 24.0 |
| CVA or Stroke | 70 | 20.0 |
| Arrhythmia | 68 | 19.2 |
| Sub-acute bacterial endocarditis(SBE) | 10 | 2.8 |
| Others* | 31 | 8.8 |
Hypertensive heart disease (HHD) constituted for $41.4\%$[146] of the total CVD diagnosis as well as the leading etiologic cause of advanced heart failure. Its prevalence increased with increasing age ($p \leq 0.001$). HHD was more predominant among urban residents than rural ones (($63\%$[92] Vs $37\%$[54], $$p \leq 0.001$$)). Valvular heart diseases (both rheumatic and degenerative valvular heart diseases combined) accounted for about $34.5\%$ of all advanced cardiac failure cases and $20.5\%$ [73] of all the cardiovascular admissions as shown in the Table 2.
Chronic rheumatic valvular heart diseases(CRVHD) was more predominant in patients coming from outside of Addis Ababa compared to residents of Addis Ababa($82.8\%$[53] Vs $17.1\%$[11]($$p \leq 0.001$$). Echocardiography proven isolated MS and MS with MR constituted $26\%$[19] and $27.5\%$[20] of all valvular heart diseases, respectively. The proportion of degenerative valvular heart diseases increased with advancing ages ($$p \leq 0.01$$) whereas rheumatic heart diseases decreased as age increased ($$p \leq 0.01$$). Ischemic heart disease (IHD) accounted for $12.2\%$[43] of all CVD admissions. Its prevalence has significantly increased with age and males had higher proportion than females($$p \leq 0.001$$). IHD was more common in residents of Addis Ababa than those who came from out of Addis Ababa but the difference was not significant ($$p \leq 0.2$$). IHD was significantly associated with hypertension and diabetes ($$p \leq 0.001$$, each). From all IHD patients, $90.24\%$ had hypertension with $13.5\%$ had good hypertension control, $59.5\%$ had poor hypertension control, and $27\%$ were newly diagnosed hypertension. Similarly, $41.5\%$ of IHD patients had diabetes mellitus with $41.5\%$ had good glycemic control, $35.3\%$ had poor glycemic control and $17.6\%$ were newly diagnosed T2DM. About $11\%$[40] of CVD admissions had pulmonary heart disease(PHD) with over $42\%$ of them were attributed to COPD and the remaining were due to chronic PTE and post-TB fibrosis. PHD was more common in patients who came from Addis Ababa than those coming outside of Addis Ababa but the difference was not significant ($$p \leq 0.053$$). Females constituted over two-third of patients diagnosed with dilated cardiomyopathy and peripartal cardiomyopathy accounted for $26.5\%$($$p \leq 0.01$$).
Vascular diseases (VasD) were the most common cause of cardiovascular diseases next to CHF and HHD. It accounted for about a quarter of cardiovascular diagnosis and females constituted about two-third of the cases. DVT was the leading vascular cause accounting for $44\%$[37] followed by PTE of about $30\%$[25]. Peripheral arterial disease (PAD) and cerebral venous thrombosis(CVT) accounted for $15.5\%$[13] and $9.5\%$[8] of vascular disease admissions, respectively. Pregnancy and related conditions such as caesarian section and puerperium ($30.6\%$[26]); major surgery and prolonged immobilization for medical illnesses($28.2\%$[24]); and active cancers($11.7\%$[10]) were the major risk factors of venous thrombo-embolism(VTE). Hypertension and diabetes were significantly associated with PAD($$p \leq 0.001$$, each). Hypertension was documented as a risk factor in about $85\%$ of patients with PAD followed by diabetes mellitus and chronic kidney disease, each of which were implicated as a risk factor in $25\%$ of cases of PAD. The cumulative rate of vascular diseases have significantly decreased as the age of the patients increased($$p \leq 0.01$$) (Fig 1).
Cerebrovascular accident (stroke) accounted for about $20\%$[71] of total annual cardiovascular admission with hemorrhagic stroke constituted about $17\%$ and ischemic stroke for the remaining $83\%$ of the total stroke patients. Of all ischemic stroke, cardioembolic stroke accounted for $32.2\%$. From all the atherothrombotic ischemic stroke groups, $7.5\%$ had hemorrhagic transformation during the course of hospital stay. Stroke was predominant in residents of Addis Ababa than those who came outside of Addis Ababa although the difference was not statistically significant ($$p \leq 0.07$$) but it increased with increasing age($$p \leq 0.001$$) (Fig 1). There was no variation of stroke distribution between males and females (male = $45\%$ and female = $55\%$, $$p \leq 0.09$$). Hypertension was the leading risk factor for stroke, followed by atrial fibrillation (Fig 2). All patients with hemorrhagic stroke had hypertension and $75\%$ of them had long standing uncontrolled hypertension whereas the remaining $25\%$ had newly diagnosed hypertension. Similarly, $97.5\%$ of atherothrombotic ischemic stroke(non-cardio-embolic) patients had hypertension with $61.5\%$ of them had uncontrolled hypertension whereas about $38\%$ had newly diagnosed hypertension after the current presentation. About one-third of atherothrombotic ischemic stroke patients had diabetes. Atrial fibrillation accounted for $73.7\%$ of cardioembolic stroke admissions with $71.5\%$ of CRVHD patients and $60\%$ of DCMP patients had atrial fibrillation.
**Fig 2:** *Major risk factors of stroke among admitted patients in St Paul Hospital Millennium Medical College.*
## Hypertension and diabetes control among the cardiovascular admissions
Of all the 353 annual cardiovascular admissions, $47.6\%$[168] patients had history of hypertension. Hypertension was prevalent in patients from Addis Ababa than patients who came outside of Addis Ababa (($63.7\%$[107] Vs $36.3\%$[61], $$p \leq 0.001$$)). The minimum duration of hypertension ranged from newly diagnosed hypertension up to the maximum of 30 years. Only $20\%$ of patients had good hypertension control (BP<$\frac{140}{90}$mmHg) with adherence to the medications and have frequent follow up whereas $46.6\%$ of patients had poor hypertension control (BP≥$\frac{140}{90}$mmHg) who were either not adherent to or discontinued their pharmacologic therapy by themselves. About $35\%$ of hypertensive patients were newly diagnosed during their current admission. The control of hypertension in patients from Addis Ababa was significantly better than patients coming outside of Addis Ababa ($$p \leq 0.001$$). The proportion of diabetes mellitus(DM) among the cardiovascular admissions was $17.6\%$[62] and significantly prevalent in patients from Addis Ababa than those out of Addis Abbaba (($74.1\%$[46] Vs $25.8\%$[16], $$p \leq 0.001$$)). The duration of DM history ranged from newly diagnosed DM up to 25 years. About $40\%$ of DM patients had ’’good’’ DM control with mean FBS≤130mg/dl and/or A1C<$7\%$ whereas $46.8\%$ had ’’poor’’ DM control (mean FBS>130mg/dl and/or A1C>$7\%$). The control of diabetes in patients from Addis Ababa was significantly better than those coming outside of Addis Ababa ($$p \leq 0.001$$).
## Outcomes of cardiovascular disease admissions
Among patients with CVD admissions, the minimum hospital stay was one day and the maximum was 80 days with the average hospital stay was 12days. About $57\%$[201] of cardiovascular admissions were discharged from the hospital with improvement, $10\%$[36] were discharged with the same condition(most were stroke patients with dense hemiplegia and also stage-D CHF patients), and $4.5\%$ [16] were left against medical advice. The in-hospital mortality rate among the cardiovascular admission was $24.3\%$[86] with the predominated immediate cause of death being sepsis with septic shock($25.6\%$) followed by fatal arrhythmia ($19.8\%$), brain herniation ($15\%$), massive PTE ($14\%$), and cardiogenic shock ($11.6\%$) (Table 3).
**Table 3**
| Causes of death | frequency | percentage |
| --- | --- | --- |
| Septic shock | 22 | 25.6% |
| Fatal arrhythmia | 17 | 19.8% |
| Brain herniation | 13 | 15% |
| Massive PTE | 12 | 14% |
| Cardiogenic shock | 10 | 11.6% |
| Unexplained Sudden cardiac arrest | 6 | 7% |
| Cause of death no documented | 3 | 3.5% |
| Massive aspiration | 1 | 1.56% |
## Discussion
The epidemic of cardiovascular disease (CVD) is a global phenomenon, and the magnitude of its burden is alarmingly increasing in the developing world including Ethiopia [6]. In the current study which involved all the annual medical admissions of 1,165 patients at St. Paul Hospital Millennium Medical College, the total cardiovascular admission constituted $30.3\%$. The present burden of cardiovascular causes of medical admission was in agreement with the previous studies [25]. However, the previous studies considered hypertension as a separate exclusive CVD diagnosis but in this study hypertension was considered as a CVD risk factor and hypertensive heart disease was an exclusive diagnosis as per the International Disease Classification(ICD-10) [22]. The present finding is also in tandem with the cardiovascular admission of $31\%$ among all medical admission in the Nigerian Teaching hospital [26]. However, the current rate of CVD admission is much greater than $17.5\%$ of CVD admission in Asella Referal Hospital [27]. This difference might be due to large proportion of urban residence in our study dominated by cardiovascular risk factors including hypertension and diabetes unlike the former area where infectious causes of admission accounted for close to $50\%$ [27].
Most of the CVD patients ($60\%$) were admitted with the clinical diagnosis of advanced congestive heart failure (CHF) (NYHA class III and IV). This high rate of CHF in the current study is in agreement with other Ethiopian studies [25,28]. Surprisingly, apart from hypertension and pneumonia, over a quarter of CHF patients had associated history of drug discontinuation as a precipitating factor eventually worsening their heart failure condition. Therefore, healthcare providers should also equally focus on health education including adherence to the medical therapy in addition to prescribing the pharmacologic agents based on the appropriate diagnosis.
Hypertensive heart disease (HHD) was the second predominant diagnosis constituting for $41\%$ of overall cardiovascular admission and also the leading cause of heart failure followed by rheumatic valvular heart disease(RVHD) which constituted for about $18\%$ of all CVD. In most of the previous studies involving both inpatient and outpatient follow up clinics, VHD was considered to be the leading cause of CVD in general and cardiac diseases in particular [17,18,25,27–29]. This increased burden of HHD shown in the current study, however, is consistent with other recent studies in Ethiopia [18]. The high proportion of hypertension (about $48\%$) among our CVD patients also supports the high rate of HHD. Compared to rural dwellers, HHD in the current study was predominant in urban residents($$p \leq 0.01$$). It may be partly due to an increasing urbanization and westernization of diet in the present metropolitan area coupled with better health care availability allaying the risk factors for rheumatic valvular heart disease (RVHD). RVHD in the current study is dominant in patients coming from rural area than the residents of Addis Ababa($$p \leq 0.001$$). Rural predominance of RVHD is consistent with previous studies [16–18]. This could partly be justified by the early treatment of upper respiratory tract infection and better access to health care in urban residents. RVHD in the present study was also predominant in females ($$p \leq 0.001$$) and it is in agreement with previous studies [16,17]. Ischemic heart disease (IHD) and dilated cardiomyopathy(DCMP) were other causes of cardiac diseases constituting for $12.2\%$, and $9.6\%$ of annual CVD admissions, respectively and their burden increased with increasing age($$p \leq 0.01$$). These findings are in agreement with other national studies [16,18,28]. The tall of ischemic heart disease is significant when the current rate of 12,200 per 100,000 is compared with the data of 7,400 per 100,000 in 2014 [15]. The risk of IHD was associated with Hypertension and *Diabetes mellitus* ($$p \leq 0.001$$, each) and is in agreement with similar studies [15].
Cerebrovascular accident (CVA) or stroke accounted for $20\%$ of annual CVD admissions with ischemic stroke being the predominant sub-type($83\%$), and hemorrhagic stroke constituted the remaining $17\%$. This finding is consistent with the well-established global data and some of Ethiopian studies where Ischemic stroke is the dominant sub-type [15,30–32]. However, the current finding is not in agreement with some of the *Ethiopian data* in which hemorrhagic stroke was reported to be the dominant subtype [33–35]. The exaggerated hemorrhagic stroke compared to ischemic stroke which was reported in a number of studies in Ethiopia mandates further scrutiny. In this study, hypertension was present in $74\%$ of patients with stroke. All hemorrhagic stroke patients had hypertension and $75\%$ of them had long standing uncontrolled hypertension whereas the remaining $25\%$ had newly diagnosed hypertension. This finding is in agreement with other similar studies [30,33,36]. Since one-third of our ischemic stroke patients had pre-existing atrial fibrillation (AFib) and AFib significantly raises the likelihood of stroke, effective preventive therapy is critical and should be one of the key management priorities [14]. Furthermore, $97.5\%$ of atherothrombotic(non-cardioembolic) ischemic stroke patients had hypertension as a major risk factor where $61\%$ of them had uncontrolled hypertension and $38\%$ of them had newly diagnosed or untreated hypertension. This finding is also in conformity with other studies [30,33,36]. Therefore, poor screening, poor follow up and adherence against CVD risk factors including hypertension, makes it imperative to re-evaluate our management practices, so as to establish a consolidated approach involving the relevant stakeholders. For countries of poor economy including ours, prevention is much cheaper and profitable than the complex and costly managements of the subsequent CVD diseases and their complications. Therefore, timely screening for the cardiovascular risk factors as well as early identification of complications utilizing various approaches including technology of telemedicine could be an efficient, and cost effective method [37].
Hypertension, in the current study, was found to be the dominant risk factor for cardiovascular diseases where about $48\%$ of CVD patients had hypertension. However, this finding is higher than some of the previous reports of hypertension burden among the CVD patients in Ethiopia [15,16,17,25,38] but much lower than the $62\%$ as shown in the study conducted in Gondar Referral Hospital [18]. Our finding is also consistent with the overall increasing trends of atherosclerotic CVD burden in the recent decades with hypertension being a significant risk factor [18,39]. The worrisome finding was that only $20\%$ of our patients with longstanding hypertension had good hypertension control whereas about $47\%$ of patients had poor hypertension control who were either not adherent to or discontinued their antihypertensive therapies by themselves. Furthermore, $35.2\%$ of hypertensive patients were newly diagnosed or told to have raised blood pressure in the past but not on therapy or follow up. This poor hypertension control is consistent with other studies [40,41] and warrants timely intervention. Similarly, from all CVD patients with long standing diabetes mellitus, only $40.3\%$ had good glycemic control whereas $46.8\%$ had poor glycemic control and poor follow up. About $13\%$ of diabetes was newly diagnosed type-2 diabetes after they were admitted for the current cardiovascular illness. These findings are consistent with other studies in Ethiopia [42,43] but much better than the $20\%$ of good glycemic control at Tikur Anbessa Specialized Hospital [24]. Despite the rising cost of newer cardiovascular drugs are challenging the drug adherence in the settings with poor economies, some of the older, cheaper and effective agents can still be easily available to serve as a backbone and drug of first choice [44] so as to improve the drug adherence.
Vascular diseases including deep venous thrombosis (DVT), pulmonary thromboembolism (PTE), peripheral arterial disease (PAD), and cerebral venous thrombosis (CVT) were common in the present study area and all together constituted about $24\%$ of all the annual CVD admissions. DVT was the leading cause of vascular admission ($44\%$), followed by PTE($30\%$), PAD($15.5\%$) and CVT ($9.5\%$), respectively. The current vascular disease burden is much higher than the previous cardiovascular spectrum studies [15,16,18] which involved the outpatients, unlike the admitted patients who have higher risk factors [45,46]. Major risk contributors of venous thromboembolism (VTE) were pregnancy and its related conditions such as puerperium and cesarean section ($30.6\%$), major surgery and prolonged immobilization for medical illnesses ($28.2\%$), and active cancers ($11.7\%$). The higher burden of DVT, younger age and female predominance, major risks (pregnancy and puerperium, prolonged immobility and malignancy) documented in the current study are consistent with previous studies in Addis Ababa Hospitals [45,46]. The high rate of VTE, including massive PTE as one of the major immediate cause of death (Table 3), may be partly due to lack of comprehensive guideline based venous thromboembolism (VTE) prophylaxis consistent with the degree of risk factors. The Ethiopian custom of prolonged bed rest (immobility) during puerperium might have also exacerbated the existing procoagulant risks. Hypertension was a risk factor in about $85\%$ of patients with PAD followed by diabetes mellitus ($25\%$). This is consistent with the association of uncontrolled hypertension and diabetes with atherosclerotic CVD diseases including PAD [38]. Therefore, such findings mandate comprehensive approach to develop proper CVD risk assessment and disease control.
The mean duration of hospital stay in the current study was 12days with the minimum hospital stay was one day and the maximum was 80 days. This result is comparable with the average of 12.33days of hospital stay for medical admission [25] and 11.14days for stroke admissions at St. Paul hospital [34] but less than the 14.4days of total hospital stay at Asella referral hospital [27]. There were $57\%$ of CVD patients discharged with improvement and in-hospital mortality rate was $24.3\%$. These findings are comparable to the previous St. Paul hospital reports of in-hospital death rate of $24.2\%$ and discharge rate with improvement of $66\%$ among the medical admissions [25]. Despite the current mortality rate is lower than the $25\%$ documented among the cardiovascular admissions in Addis Ababa [28] and the $30\%$ mortality rate among stroke admissions in St. Paul Teaching hospital [34], it is higher than the $12.2\%$ among cardiovascular admissions in Nigeria [26]. Sepsis with septic shock was the leading immediate cause of death in about a quarter of deaths among CVD admissions, followed by fatal arrhythmia, brain herniation, massive PTE and cardiogenic shock in $20\%$, $15\%$ and $14\%$, respectively. Consistent with our study, infectious disease was also the leading cause of mortality among medical admissions studied previously [25,27]. Therefore, comprehensive work is needed to improve impatient medical care in addition to CVD risk assessment, and disease control.
## Limitations
Due to the retrospective nature of the study, it has a limitation of including additional cardiovascular risk factors including smoking history, obesity, and physical inactivity. Since it was also a hospital based study with limited sample size, it lacks the accurate representation of the actual burden of cardiovascular diseases in the wider community. Furthermore, incomplete documentation is common in the retrospective studies. To avoid the sampling bias, we have incorporated the entire annual medical admissions in the study.
## Conclusion
In conclusion, cardiovascular diseases are common in the study area causing significant morbidity and mortality. Most cardiovascular diseases have preceding unaddressed but easily modifiable risk factors, controlling which could have prevented or delayed the progression of the disease. Therefore, concerted effort is required from all stake-holders in terms of risk reduction as well as follow-up optimization to delay or if possible to prevent cardiovascular disease development, disease progression and subsequent complications. Strategies should also be designed to increase public awareness regarding cardiovascular risk reduction, drug adherence, and possible complications.
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|
---
title: Lipoprotein-Associated Phospholipase A2 Activity as Potential Biomarker of
Vascular Dementia
authors:
- Giovanni Zuliani
- Judit Marsillach
- Alessandro Trentini
- Valentina Rosta
- Carlo Cervellati
journal: Antioxidants
year: 2023
pmcid: PMC10045550
doi: 10.3390/antiox12030597
license: CC BY 4.0
---
# Lipoprotein-Associated Phospholipase A2 Activity as Potential Biomarker of Vascular Dementia
## Abstract
A wealth of evidence suggests that Lipoprotein-associated phospholipase A2 (Lp-PLA2) plays a relevant role in atherogenesis and inflammation, which in turn are associated with the risk of developing dementia. The aim of this study was to evaluate whether serum Lp-PLA2 activity might be an early and/or late biomarker for different forms of dementia. Serum Lp-PLA2 activity was assessed in older patients with mild cognitive impairment (MCI, $$n = 166$$; median clinical follow-up = 29 months), Late-Onset Alzheimer’s disease (LOAD, $$n = 176$$), vascular dementia (VAD, $$n = 43$$), dementia characterized by an overlap between LOAD and VAD (AD-VAD MIXED dementia) ($$n = 136$$), other dementia subtypes ($$n = 45$$), and cognitively normal controls ($$n = 151$$). We found a significant trend towards higher levels of Lp-PLA2 activity in VAD compared with the other groups (ANOVA, $$p \leq 0.028$$). Similarly, Lp-PLA2 activity was greater in MCI converting to VAD compared with those that did not or did convert to the other types of dementia (ANOVA, $$p \leq 0.011$$). After adjusting for potential confounders, high levels of Lp-PLA2 activity were associated with the diagnosis of VAD (O.R. = 2.38, $95\%$ C.I. = 1.06–5.10), but not with other types of dementia. Our data suggest that increased serum Lp-PLA2 activity may represent a potential biomarker for the diagnosis of VAD.
## 1. Introduction
Lipoprotein-associated phospholipase A2 (Lp-PLA2) has been widely suggested to be an independent predictor of cardiovascular disease (CVD) [1,2,3]. This enzyme is a calcium-independent PLA2 belonging to group VII, mainly secreted by macrophages and platelets, and circulates in the blood in association with low-density lipoprotein (LDL), and, to a lesser extent, high-density lipoprotein (HDL) [4]. It has been suggested that the net effect of Lp-PLA2 action depends on the carrier, antioxidant, or pro-inflammatory if it is associated with HDL or LDL particles, respectively [1,4,5].
Lp-PLA2 hydrolyzes the acetyl group at the sn-2 position of platelet-activating factor (PAF, indeed, it is also named PAF acetylhydrolase) thereby inactivating this pro-inflammatory phospholipid (PL). It is also capable to degrade oxidized PL (antioxidant activity) with a chemical structure similar to that of its natural endogen substrate to generate lysophosphatidylcholine and oxidized fatty acids, which have pro-inflammatory properties [4,6]. In turn, these by-products are believed to mediate the onset and progression of the inflammatory response in atherogenesis [4,6].
There is a wealth of evidence showing that Lp-PLA2 mass and activity are predictors of CVD and stroke [3,7]. It is well-known that inflammation, atherogenesis, and more in general, cardiometabolic risk factors and cerebrovascular disease are also associated with dementia incidence [8,9,10]. This was the rationale of a few observational studies exploring the potential link between Lp-PLA2 and cognitive impairment. The reported findings were inconclusive, with some showing increased serum/plasma levels of these enzymes in patients with dementia [11,12,13,14], and others failing to disclose significant alterations [15,16,17]. In particular, it remains unclear whether Lp-PLA2 could be an early biomarker of dementia and whether it could discriminate between different forms of this syndrome. To shed light on this uncertain scenario, we assessed Lp-PLA2 activity in a large sample including patients with mild cognitive impairment (MCI), Late-Onset Alzheimer’s disease (LOAD), *Vascular dementia* (VAD), dementia characterized by an overlap between LOAD and VAD (AD-VAD MIXED), other less frequent types of dementia and cognitively healthy controls.
## 2.1. Subjects
Seven hundred and seventy subjects referring to the Center for Cognitive Decline and Dementia (CDCD) (University of Ferrara, Ferrara, Italy) were enrolled in the study as detailed elsewhere [18,19]. The samples included:One hundred sixty-six amnestic MCI patients, defined as those with a presence of either short or long-term memory impairment, with or without impairment in other single or multiple cognitive domains. Most of these individuals were affected by amnestic multi-domain MCI. The classification of these subjects is based on the absence of dementia, according to the standardized criteria for this syndrome [20]. Subjects with MCI caused by documented conditions or diseases (for example, major depression, and severe vitamin B-12 deficiency) were excluded from the study. These patients were consecutively enrolled after the first visit and MCI diagnosis at the CDCD; they underwent a regular clinical follow-up as outpatients (mean = 29 months; range = 11–156) (see major detail in [21]). The Mini-Mental State Examination (MMSE) ranged from 18 to 28 (median = $\frac{24.6}{30}$). Seventy-eight enrolled ($55\%$) progressed to dementia within the follow-up period. One hundred seventy-six patients with Late-Onset Alzheimer’s disease (LOAD), with a disease onset after the age of 65. The diagnosis was drawn according to the National Institute on Aging–Alzheimer’s Association (NIA-AA) workgroups criteria [22]. Following these well-established clinical criteria, we included only patients with “probable” LOAD, while patients with “possible” LOAD or with LOAD and cerebrovascular disease were not excluded. Mini-Mental State Examination (MMSE) ranged between 18–23 and the Clinical Dementia Rating (CDR) ranged between 1–4.Forty-three patients with the diagnosis of VAD according to the National Institute of Neurological Disorders and Stroke and Association Internationale pour la Recherché et l’Enseignement en Neurosciences (NINDS-AIREN) criteria for a diagnosis of probable VaD [23]. The initial diagnosis of VAD was confirmed by magnetic resonance in all cases. The subjects had an MMSE ranging between 19–23.One hundred thirty-six with MIXED AD-VAD; in these patients, a definite diagnosis of LOAD or VAD was not possible since they presented both the characteristics of VAD (e.g., significant vascular disease, focal neurological signs) and LOAD (e.g., memory impairment, type of progression). MMSE ranged between 16–23; CDR ranged between 1–2.Forty-five patients with other forms of dementia (Dementia subtypes: Lewy Body disease/Parkinson’s dementia, frontotemporal dementia, condition related to psychiatric conditions, neoplasm/metastasis, hydrocephalus, Fahr’s syndrome, alcohol-related, not defined). MMSE ranged between 18–25; CDR ranged between 1–2.One hundred fifty-one cognitively healthy subjects (Controls). Subjects enrolled in this group complained of no memory problems and did not present symptoms of cognitive impairment or any related functional disabilities. MMSE ranged between 26–30.
All subjects included were informed about the research project and gave their written consent before being included in the study. For people with dementia, relatives or caregivers were asked to sign the informed consent form. The study was carried out according to the Declaration of Helsinki (World Medical Association, http://www.wma.net accessed on 25 July 2017), and the guidelines for Good Clinical Practice (European Medicines Agency, http://www.ema.europa.eu accessed on 25 July 2017). The institutional review board of the University of Ferrara approved the study (study n. 170579).
The diagnosis of dementia was drawn by trained geriatricians. Personal data and medical history were collected through a structured interview with patients and caregivers. All patients underwent a general and neurological examination. All enrolled patients underwent neuropsychological evaluation by a standardized battery of tests including MMSE, Rey’s 15 words, Raven progressive test, clock drawing test, and routine clinical tests for the evaluation of agnosia, apraxia, and aphasia. Assessment of functional disabilities was made by Instrumental Activities of Daily Living (IADL) and Basic Activity of Daily Living (BADL). Routine clinical chemistry tests in blood were performed to exclude other causes of cognitive impairment. Subjects affected by severe congestive heart failure, severe liver or kidney disease, severe chronic obstructive pulmonary disease, and cancer were excluded. The use of non-steroidal anti-inflammatory drugs, antibiotics, or steroids led to the exclusion from the study.
## 2.2. Biochemical Parameters
Ten mL of venous blood was sampled from the antecubital vein using a 21-gauge and collected into regular serum-separating tube vacutainers with a clot activator. Blood sampling was performed in the morning with patients in a sitting position. Every patient was required to be in a fasting state. After 30 min at room temperature, the samples were centrifuged at 4650× g for 20 min at 4 °C and serum was separated and stored in single-use aliquots at −80 °C until analysis. The levels of plasma lipids (total cholesterol, HDL-cholesterol, and triglycerides), albumin, and high-sensitivity c-reactive protein (hs-CRP) were assessed by the centralized laboratory of Sant’Anna Hospital (Ferrara) by standard enzymatic techniques. Levels of LDL-cholesterol (LDL-C) were obtained according to Friedewald’s formula.
## 2.3. Lp-PLA2 Activity Assay
Serum activity levels of Lp-PLA2 were assessed by using 2-thio PAF as substrate by a spectrophotometric assay (by using Tecan infinite M200 Tecan Group Ltd., Männedorf, Switzerland). The substrate of Lp-PLA2, thio PAF (Cayman Chemical, Ann Arbor, MI, USA), was first resuspended in ethanol and then subdivided into aliquots which were finally placed at −80 °C. On the day of the assay, the solvent in the substrate aliquot was evaporated under a stream of nitrogen, for approximately 2 min. Subsequently, thio-PAF was resuspended in assay buffer (containing: 100 mM Tris, 0.1 mmol/L Ethylene glycol-bis(2-aminoethylether)-N,N,N′, N′-tetraacetic acid (EGTA), pH = 7.2) to a final concentration of 400 nM. Ten microliters of serum were mixed with 5 μL of assay buffer and 10 μL of Ellman’s reagent (containing, 5,5′-dithiobis-(2-nitrobenzoic acid, DTNB). This mixture was incubated at room temperature in dark conditions for 30 min. The reaction was initiated by adding 200 μL of substrate solution and followed for 10 min. The formation of free thiols, due to the catalyzed hydrolysis of thio PAF, was detected according to Ellman’s procedure, as described in Ref. [ 24]. A molar extinction coefficient of 13,600 M−1 cm−1 (wavelength = 410 nm) was used for the calculation of enzyme activity, as expressed in units per liter (U/L).
## 2.4. Statistical Analyses
The normal distribution of all continuous variables was first checked by the Shapiro-Wilk test. According to the outcome of this statistical test, the levels of normally distributed variables were expressed as mean ± standard deviation (SD), or median (interquartile range) when they were non-normally distributed. Parametric and non-parametric analyses were employed according to the variable distribution. T-test and one-way analysis of variance (ANOVA), with Bonferroni correction for multiple comparisons, were used to compare two and more than two groups of subjects, respectively. Analysis of covariance (ANCOVA) was made to check the effect of potential confounding factors on the outcome variable. Non-parametric Mann–Whitney U test and Kruskal-Wallis were employed to compare medians. The comparison of the prevalence of categoric variables were assessed by the χ2 test. Correlations between continuous variables were analyzed by Pearson’s and Spearman’s tests. Multivariable logistic regression analysis (using the levels of Lp-PLA2 activity below the median calculated in controls as cut-off) was performed to evaluate the effect of selected covariates on the relationship between Lp-PLA2 and different forms of dementia. All statistical analyses were carried out using SPSS for Windows statistical package, version 13.0.
## 3.1. Demographic and Main Clinical Characteristics of the Population Sample
Table 1 displays the general characteristics of the sample subjects. Healthy controls were the youngest group. The difference was statistically significant ($p \leq 0.001$ for all -Bonferroni post hoc tests) with all groups with the exception of dementia subtypes. Female gender was less prevalent in Controls and MCI patients (around $50\%$) compared with the other study groups (range 64–$70\%$) ($p \leq 0.001$, for all posthoc comparisons). Regarding comorbidities, the prevalence of CVD and diabetes did not significantly vary among the groups. Hypertension was more prevalent in VAD patients ($p \leq 0.01$ compared with Controls). No significant changes in lipid profile, albumin, and Hs-CRP were detected across the subject groups. As expected, years of formal education, and scores of neuropsychiatric and functional tests (MMSE, IADLs, and BADLs) were significantly higher in Controls compared with all the other groups ($p \leq 0.001$ for all).
## 3.2. Serum Lp-PLA2 Activity in Controls, MCI, and Patients with Dementia: Cross-Sectional Analysis
Serum Lp-PLA2 activity was different across the study groups as highlighted by ANOVA $$p \leq 0.021$$). In particular, the most evident differences were the increase of enzyme activity in VAD compared with Controls (+$12\%$) and of the latter compared with MIXED AD-VAD (+$18\%$). On the contrary, MCI, LOAD, and other dementia subtypes showed median values similar to Controls (Figure 1).
As a second step, we evaluated the possible influence that covariates might have on the association between Lp-PLA2 and the diagnosis of LOAD, MCI, VAD, or MIXED AD-VAD. We found that LDL-C and HDL-C were positively and inversely correlated with enzyme activity ($r = 0.351$ and $p \leq 0.0001$ and r = −0.259, $p \leq 0.001$, respectively; Supplementary Figure S1A,B). Notably, Lp-PLA2 did not correlate with age ($r = 0.011$, $$p \leq 0.779$$, Supplementary Figure S2). Moreover, a further comparison after the exclusion of younger Controls confirmed the lack of influence of this variable on Lp-PLA2 (ANOVA, $$p \leq 0.036$$, Supplementary Table S1).
The activity of Lp-PLA2 was significantly higher in men compared with women ($p \leq 0.001$, Supplementary Figure S3) and in individuals affected by CVD and diabetes mellitus ($p \leq 0.05$ for both, Supplementary Figures S4 and S5, respectively). Of note, the difference in Lp-PLA2 between men and women retained its significance after adjusting for potential confounders such as age, LDL-C, and HDL-C ($p \leq 0.001$). On the contrary, the change observed in subjects with CVD and diabetes disappeared after adjusting for these confounding factors.
## 3.3. Serum Lp-PLA2 Activity in Converter and Non-Converter MCI: Longitudinal Data
We also checked whether Lp-PLA2 activity might be associated with the progression from MCI to overt dementia (Figure 2). There was no significant difference in enzyme activity between the converter and non-converter (15.0 ± 4.2 U/L and 15.5 ± 4.0 U/L, respectively). However, we found a significant trend towards higher levels of Lp-PLA2 in MCI converted to VAD or LOAD compared with stable MCI (ANOVA, $$p \leq 0.029$$, Figure 2).
## 3.4. Odds of Having MCI, AD, VAD, and AD-VAD MIXED
Since a trend toward higher levels of Lp-PLA2 activity was observed in VAD compared with the other groups included in the study, we evaluated whether an Lp-PLA2 activity higher than the median value (15.2 U/L) might be associated with the risk of being affected by dementia or MCI compared with Controls, after controlling for possible confounders. As disclosed in Figure 3, higher Lp-PLA2 activity levels were associated only with a higher likelihood of receiving a VAD diagnosis compared with Controls (O.R. = 3.115, $95\%$ C.I. = 1.13–7.98), after adjustment for LDL-C, HDL-C, age, sex, diabetes, and CVD.
Finally, we checked whether increased Lp-PLA2 activity could discriminate among the different types of dementia. We found that higher levels of these enzymes were associated with greater odds of being affected by VAD compared with LOAD (O.R. = 2.76, $95\%$C.I. = 1.20–6.30), AD-VAD MIXED (O.R. = 3.50, $95\%$C.I. = 1.51–8.01), other dementia subtypes (O.R. = 2.38, $95\%$C.I. = 1.03–5), but not to MCI (O.R. = 2.38, $95\%$ C.I. = 0.67–4.839).
## 4. Discussion
The present is the first study dealing with the cross-sectional and longitudinal evaluation of serum Lp-PLA2 activity, a marker of atherogenesis, in individuals with different types of dementia or MCI. The main finding is that higher levels of Lp-PLA2 are significantly associated with VAD diagnosis, and the association is independent of potential confounders including LDL-C, HDL-C, sex, age, diabetes, and CVD. This is important since these are both some of the main risk factors for VAD and LOAD and strong predictors of Lp-PLA2 levels [7,8,25]. Remarkably, from the clinical point of view, higher levels of this enzyme activity appear to be able to discriminate VAD from other forms of dementia.
On the contrary, Lp-PLA2 activity was not significantly increased in MCI patients and failed to predict the conversion to dementia. However, we observed a significant trend towards higher levels of phospholipase activity in MCI converted to VAD compared with MCI stable or converted to other types of dementia.
The relationship between Lp-PLA2 and dementia has been already investigated in a few studies and the findings were inconclusive. The first and largest observational study ($$n = 6713$$ people), was published in 2006 and showed that healthy subjects in the highest quartile of Lp-PLA2 levels activity were at higher risk of all-cause dementia. However, the relationship was weak and the lack of measurement of LDL-C might have affected the accuracy of the findings. Indeed, as we demonstrated, this lipid parameter is strongly correlated with Lp-PLA2, and thus, it should be taken into account as a covariate in multivariate analysis [13].
In line with these findings, the Cardiovascular Health Study, including 5888 community-dwelling older adults, found an increased risk of developing AD in patients with low levels of Lp-PLA2 mass [14]. This large prospective study also found a strong association between increased Lp-PLA2 activity and the diagnosis of MIXED AD-VAD. Notably, these results were independent of confounding factors such as APOE ε4 allele, vascular comorbidities, inflammation markers, and lipid profile (although HDL-C was not assessed and thus not included in the multivariate analysis). An increase in Lp-PLA2 in AD was also reported in two studies with cross-sectional design [26,27]. In contrast, Davidson et al. [ 16], detected no significant differences in Lp-PLA2 activity between AD, aMCI, and control subjects. Additionally, the authors reported no significant correlation of Lp-PLA2 with cerebrospinal fluid (CSF) biomarkers of AD (Aβ42, t-TAU, and p-TAU), nor with white matter changes. Similar results were obtained by the Framingham Study, which explored the relationship between some conventional and unconventional CVD risk factors, AD, and all-cause dementia, demonstrating an overlap with those for cardiovascular disease. From this longitudinal study, it emerged that plasma concentration of Lp-PLA2 was not significantly associated with the risk of developing dementia or AD [17].
In the above-cited investigation, Lp-PLA2 is described as a biomarker of inflammation, which plays a critical role in the onset and progress of atherosclerosis. The involvement of this lipoprotein-associated enzyme as a proactive agent in atherogenic and inflammatory processes is the major rationale for our and other studies on its association with dementia.
Indeed, there is a wide consensus that atherosclerosis and low-grade inflammation are, although often subclinical, conditions associated with cognitive decline in the elderly [28,29,30,31,32]. High Lp-PLA2 reflects in enhanced phospholipid hydrolysis, high contents of oxidized non-esterified fatty acids and PLs are produced, which promote expression of adhesion molecules, stimulate cytokine production (TNF-α, IL-6), and attract macrophages to the arterial intima [33,34,35]. This exacerbates endothelial dysfunction and accelerates the growth of the plaque and, eventually, the formation of a necrotic core [14]. Owing to the direct role in atherosclerosis and the widely documented association between circulatory levels and CVD prevalence, the trend towards greater levels of Lp-PLA2 in VAD compared with the other dementias, was not surprising, but even not obvious. Indeed, it is well-established that VAD, the second most common form of dementia after AD, has a preponderant vascular component, being characterized by the presence of matter lesions or hyperintensities, and macro- and micro-cerebral infarcts [36,37,38]. It is also true that “neuro-vasculopathy” is also a common feature of AD and this, along with the overlap of symptoms and risk factors, makes the differential diagnosis challenging [9,39]. Our multivariate data suggest that Lp-PLA2 may help as a potential biomarker for discriminating between the two diseases, with this ability apparently not influenced by classical cardiometabolic risk factors such as dyslipidemia, diabetes, and history of previous CVD [40,41,42].
A similar trend shown in the cross-sectional analysis also emerged from longitudinal-like evaluations of the association between Lp-PLA2 activity levels and the progression to dementia in MCI patients. This category of patient is of paramount importance in clinical investigations of dementia. Individuals with MCI are more likely to progress to dementia ($15\%$ per year), as compared with non-amnestic forms [43]. For this reason, MCI still represents the main target population for pharmacological trials on AD. Our results are novel and intriguing; indeed, they suggest that an alteration in Lp-PLA2 may precede the development of VAD. However, we are aware that our findings should be corroborated by studies on a larger sample, with sequential measurements of Lp-PLA2 at different time points.
A further interesting result of the present investigation was the sexual dimorphism of Lp-PLA2. A similar increase in men compared with women was reported by a number of other large population-based studies [25,44,45]. Of note, to the best of our knowledge, only one of these studies (Dallas Heart Study, $$n = 3332$$), Ref. [ 25], adjusted the analysis for both LDL-C and HDL-C levels. This is important since these two parameters (which we included as covariates) have a strong association with Lp-PLA2 levels. The possible explanation of this observed phenomenon is the down-regulatory effect of estrogens on Lp-PLA2 expression [46].
Finally, we would wish to underline other important limitations of this study. The main caveat of the study is the lack of CSF biomarkers assessment; thus, the misclassification of some patients cannot be ruled out. The unavailability of CSF inevitably affects the clinical relevance of our findings. However, these biomarkers are employed for the diagnostic confirmation of AD, not VAD (i.e., the only form of dementia that we found to be associated with a change in Lp-PLA2). It should be noted that the NINDS-AIREN criteria (which state that evidence of vascular disease on magnetic resonance imaging for the brain is mandatory) for probable VAD have a low sensitivity (about 20–$60\%$) but a high specificity (about 90–$99\%$) as reported by clinical and neuropathological studies [23,47,48]. Thus, while we might have a non-negligible number of false negatives (i.e., individuals with VAD included in other dementia groups), the number of false positives would be very low. In this regard, it appears unlikely that the finding of an elevated serum Lp-PLA2 in VAD is unreliable due to the lack of CSF biomarker confirmation. Second, we cannot exclude that biases or unmeasured confounding factors (primarily obesity) might also influence the development of the forms of dementia considered in the study. However, we took into account a number of potential confounders, and the observed increase in Lp-PLA2 activity was independent of those factors. Finally, due to the reported association between pro-inflammatory cytokines and VAD [49], their assessment could add valuable data, other than potential covariates to include in the multivariate analysis.
## 5. Conclusions
We found that serum Lp-PLA2 activity increases in VAD. We also showed that this biomarker is able to discriminate this form of dementia from LOAD. This is an important novel finding because there are still no available fluid biomarkers to use for a differential diagnosis between VAD and LOAD. Further larger studies employing validated CSF biomarkers are warranted to confirm these findings.
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|
---
title: 'Newborns from Mothers Who Intensely Consumed Sucralose during Pregnancy Are
Heavier and Exhibit Markers of Metabolic Alteration and Low-Grade Systemic Inflammation:
A Cross-Sectional, Prospective Study'
authors:
- José Alfredo Aguayo-Guerrero
- Lucía Angélica Méndez-García
- Aarón Noe Manjarrez-Reyna
- Marcela Esquivel-Velázquez
- Sonia León-Cabrera
- Guillermo Meléndez
- Elena Zambrano
- Espiridión Ramos-Martínez
- José Manuel Fragoso
- Juan Carlos Briones-Garduño
- Galileo Escobedo
journal: Biomedicines
year: 2023
pmcid: PMC10045555
doi: 10.3390/biomedicines11030650
license: CC BY 4.0
---
# Newborns from Mothers Who Intensely Consumed Sucralose during Pregnancy Are Heavier and Exhibit Markers of Metabolic Alteration and Low-Grade Systemic Inflammation: A Cross-Sectional, Prospective Study
## Abstract
Robust data in animals show that sucralose intake during gestation can predispose the offspring to weight gain, metabolic disturbances, and low-grade systemic inflammation; however, concluding information remains elusive in humans. In this cross-sectional, prospective study, we examined the birth weight, glucose and insulin cord blood levels, monocyte subsets, and inflammatory cytokine profile in 292 neonates at term from mothers with light sucralose ingestion (LSI) of less than 60 mg sucralose/week or heavy sucralose intake (HSI) of more than 36 mg sucralose/day during pregnancy. Mothers in the LSI ($$n = 205$$) or HSI ($$n = 87$$) groups showed no differences in age, pregestational body mass index, blood pressure, and glucose tolerance. Although there were no differences in glucose, infants from HSI mothers displayed significant increases in birth weight and insulin compared to newborns from LSI mothers. Newborns from HSI mothers showed a substantial increase in the percentage of inflammatory nonclassical monocytes compared to neonates from LSI mothers. Umbilical cord tissue of infants from HSI mothers exhibited higher IL-1 beta and TNF-alpha with lower IL-10 expression than that found in newborns from LSI mothers. Present results demonstrate that heavy sucralose ingestion during pregnancy affects neonates’ anthropometric, metabolic, and inflammatory features.
## 1. Introduction
The global burden of obesity and type 2 diabetes (T2D) has dramatically increased worldwide in the last 30 years [1,2]. In the US, the prevalence of overweight and obesity grades 1, 2, and 3 substantially increased from 2000 to 2010, where $65.5\%$ of women and $71.1\%$ of men showed an abnormally high body mass index (BMI) [3]. In the same period, the consumption of non-nutritive sweeteners (NNS) raised $54\%$ in adults and $200\%$ in children from the US, especially sucralose [4]. Sucralose is the bestselling NNS among millions of global purchasers who demand sweet-tasting food and beverages with reduced calories and sugar [5,6,7]. Sucralose is also one of the most ingested NNS, especially by women of reproductive age who aim to avoid excessive weight gain during pregnancy [8,9]. Although the Food and Drug Administration (FDA) considers sucralose safe for pregnant women to consume, recent evidence indicates that sucralose ingestion during pregnancy may increase the offspring’s susceptibility to weight gain [10,11].
Cai et al. conducted a meta-analysis finding that women who consumed sucralose and other NNS during pregnancy delivered babies with an increased birth weight and a decreased gestational age compared to women reporting not to utilize NNS [12]. Moreover, the ingestion of aspartame or sucralose during gestation increased body mass index (BMI) and fat mass of children at three years, while also producing elevated body weight and adiposity in C57BL/6 mice [13]. This information supports the role of sucralose intake during pregnancy in increasing the progeny’s risk of developing obesity early in life. However, excessive weight gain does not come alone because it is often accompanied by metabolic disturbances and low-grade systemic inflammation, which actively contribute to the onset of chronic non-communicable diseases such as T2D.
Azad et al. found that exposing female mice to sucralose during pregnancy and lactation increases body weight, adipocyte hypertrophy, glucose intolerance, and insulin resistance in the offspring at 11 weeks of age [13]. In parallel, feeding pregnant mice with sucralose magnifies high-fat diet (HFD)-induced liver steatosis while amplifying tumor necrosis factor-alpha (TNF-alpha) expression in the progeny’s hepatic tissue at 12 weeks of age [14]. Furthermore, our research team recently demonstrated that sucralose consumption increases serum insulin levels and alters the monocyte subset balance in young women, with particular emphasis on classical and nonclassical monocytes [15]. Together with high interleukin (IL)-1 beta expression and low IL-10 mRNA levels, TNF-alpha expression and monocyte subset alteration are well-known molecular markers of low-grade systemic inflammation observed in patients with obesity and metabolic syndrome [16,17].
Even though robust data in animal models show that sucralose intake during gestation can predispose the offspring to weight gain, metabolic disturbances, and low-grade systemic inflammation, concluding information remains elusive in humans. Herein, we examined the effects of sucralose ingestion during pregnancy on markers of metabolic dysfunction and systemic inflammation, including birth weight, glucose and insulin levels, monocyte subsets; and IL-1 beta, TNF-alpha, and IL-10 expression in a large cohort of neonates born at term.
## 2.1. Participants
We conducted a cross-sectional, prospective, observational study, enrolling 292 neonates born at term from mothers aged 18–30 with low-risk pregnancies who gave birth by spontaneous vaginal delivery between 37 and 41 weeks. Pregnant women enrolled in the study voluntarily attended the Department of Gynecology of the General Hospital of Mexico to start prenatal care at the beginning of the second trimester of pregnancy. The enrollment of participants took place from April 2018 to March 2020 and August 2021 to September 2022. All the pregnant women enrolled in the study provided written informed consent, and fathers provided written informed assent, agreeing for their infants to participate in the research that the Institutional Ethical Committee of the General Hospital of Mexico had previously approved. We excluded pregnant women from the study with any pregnancy complications, including gestational diabetes, preeclampsia, eclampsia, placental complications, ectopic pregnancy, bleeding, or amniotic fluid complications. Moreover, we excluded pregnant women with a previous diagnosis of T2D, hypertension, endocrine disorders, infectious diseases, chronic inflammatory illnesses, autoimmune disease, human immunodeficiency virus (HIV) seropositivity, hepatitis C virus (HCV) seropositivity, or hepatitis B virus (HVB) seropositivity; and women under any anti-inflammatory or immunomodulatory drug therapy in the last six months. We also excluded pregnant women if they had more than 14 weeks of pregnancy at the time of the study’s beginning to avoid missing information regarding consuming sucralose or any other NNS during the last two weeks of pregnancy. We eliminated from the study participants previously enrolled who refused to keep participating or from whom we could not obtain all the demographic, anthropometric, clinical, and biochemical data. We conducted all the minimally invasive procedures in mothers and neonates in strict adherence to the principles of the 1964 Declaration of Helsinki and its posterior amendment in 2013, under the supervision of the Institutional Ethical Committee of the General Hospital of Mexico with the registration of the project number DI/17/UME/$\frac{03}{090.}$
## 2.2. Demographic, Anthropometric, and Clinical Measurements
We registered relevant demographic, anthropometric, and clinical data in all the pregnant women enrolled in the study using the digital version of the electronic records of the General Hospital of Mexico (ERGHM). The demographic, anthropometric, and clinical data obtained by ERGHM included age, pre-gestational BMI, number of previous pregnancies, pregnancy age, and blood pressure. We performed oral glucose tolerance tests (OGTT) in all the pregnant women at the beginning of the third trimester of pregnancy, starting with a 75 g glucose load at 0 min, measuring blood glucose levels at 0, 30, 60, 90, and 120 min, and serum insulin values at 0 min. In neonates, we registered sex, birth weight, height, Capurro index, and Apgar score at delivery. According to sex and gestational age, we calculated the birth weight percentile in all the neonates enrolled in the study using the Centers for Disease Control and Prevention (CDC) growth charts [18].
## 2.3. Design of Light or Heavy Sucralose-Consuming Groups
We invited pregnant women to participate in the study after estimating sucralose in-take frequency using the Food Frequency Questionnaire with Intense Sweeteners (FFQIS) previously validated in the Hispanic population [19]. We confirmed sucralose concentration in mothers’ serum and umbilical cord blood by high-performance liquid chromatography (HPLC). Based on previous studies [13,20], we grouped mothers into two groups according to the intensity of sucralose ingestion during pregnancy. Light sucralose-consuming mothers ate or drank less than 60 mg sucralose per week, equivalent to ingesting less than five commercial Splenda® packets per week during pregnancy, representing less than $20\%$ of the Acceptable Daily Intake (ADI) set by the Food and Drug Administration (FDA). Heavy sucralose-consuming mothers ate or drank more than 36 mg of sucralose per day, equivalent to ingesting more than three commercial Splenda® packets daily during gestation. We estimated the sample size based on the results from Azad et al., expecting an effect size of 0.39 with an alpha error of 0.05 and a power of $95\%$ for a difference between two independent means that resulted in a sample size of 286 participants [13].
## 2.4. Umbilical Cord Blood Samples
We collected umbilical cord blood samples of around 5–8 mL in all the neonates enrolled in the study by puncturing the umbilical vein 5 min after birth. Then, we equally divided the blood into a purple cap tube and a golden cap tube (Vacutainer, BD Diagnostics, NJ, USA) for the posterior isolation of white blood cells (WBC) and serum by centrifugation at 1800 g for 15 min at room temperature. After measuring glucose and insulin levels by the glucose oxidase assay (Megazyme International, Wicklow, Ireland) and the enzyme-linked immunosorbent assay (ELISA) (Abnova Corporation, Taipei, Taiwan), respectively, we properly stored WBC or serum samples until use.
## 2.5. Immunostaining and Flow Cytometry for Monocyte Subsets
Immediately after collecting WBC, we rinsed the cell pellet with 300 μL PBS 1X (Sigma Aldrich, St. Louis, MO, USA) and centrifuged at 1800× g for 15 min at room temperature. After adding 5 mL ammonium-chloride-potassium (ACK) lysing buffer (Thermo Fisher Scientific, Vienna, Austria), we resuspended the cell pellet gently and incubated it for 5 min at room temperature. Then, we centrifuged at 1800× g for 10 min and discarded the supernatant, rinsing and resuspending the cell pellet twice with 300 μL PBS 1X. Next, we resuspended 4 × 106 WBC in 50 μL cell staining buffer (BioLegend, Inc., San Diego, CA, USA), adding 5 μL True-Stain Monocyte BlockerTM (BioLegend, Inc., San Diego, CA, USA) for 10 min on ice. Immediately after, we added anti-CD14 PE/Cy7, anti-CD16 PE/Cy5, Zombie UVTM dye (BioLegend, Inc., San Diego, CA, USA), and anti-HLA-DR BUV661 (BD Biosciences, San Jose, CA, USA) for 20 min in darkness at 4 °C. After centrifuging and rinsing with cell-staining buffer, we added 150 μL PBS 1X, acquiring 10,000 cell events per test in triplicate corresponding to the HLA-DR+ cell population on a BD Influx flow cytometer (BD Biosciences, San Jose, CA, USA), using the BD softwareTM version 1.2. ( BD Biosciences, San Jose, CA, USA).
## 2.6. Gating Strategy for Monocyte Subsets
First, we gated WBC on a time/side scatter density plot, selecting the Zombie UV negative cell population as living cells. Then, we gated living cells for singlets on a forward scatter (FS)/Trigger Pulse Width density plot, selecting the HLA-DR+ cell population as monocytes. After using the rectangular gating method on the cell population expressing CD14 and CD16, we recognized classical monocytes (CM) as CD14++CD16- cells, intermediate monocytes (IM) as CD14++CD16+ cells, and nonclassical monocytes (NCM) as CD14+CD16+. We analyzed data with the FlowJo 10.0.7 software (TreeStar, Inc., Ashland, OR, USA).
## 2.7. Umbilical Cord Specimens for IL-1 Beta, TNF-Alpha, and IL-10 mRNA Expression
We collected 0.5 g umbilical cord tissue from all the neonates enrolled in the study 5 min after birth. Immediately after, we placed umbilical cord samples in TRIzol reagent (Thermo Fisher Scientific, Vienna, Austria) for the posterior isolation of total ribonucleic acid (RNA) using the phenol/chloroform/guanidine isothiocyanate method. After quantifying RNA by UV spectrophotometry, we generated complementary desoxyribonucleic acid (cDNA) using the M-MLV Retrotranscriptase system with dT primer (Thermo Fisher Scientific, Vienna, Austria) at 37 °C for 60 min. Then, we used cDNA for amplifying IL-1 beta, TNF-alpha, and IL-10 by the real-time quantitative polymerase chain reaction (qPCR) using SYBR Green Master Mix and AmpliTaq® Fast DNA Polymerase (Thermo Fisher Scientific, Vienna, Austria) in the presence of specific primers. We utilized the 18S-ribosomal RNA sequence as house-keeping gene control, normalizing the expression of IL-1 beta, TNF-alpha, and IL-10 with the house-keeping gene expression to report it as fold change.
## 2.8. Statistics
We divided numerical and categorical data from mothers and neonates into light sucralose-consuming mothers and heavy sucralose-consuming mothers during pregnancy. After estimating the normality of data by the Shapiro-Wilk test, we compared numerical variables by the unpaired Student’s t-test, expressing the values as mean ± standard deviation. We compared categorical variables by the Chi-squared test, presenting the values as absolute numbers. Differences in birth weight between neonates lightly or heavily exposed to sucralose during gestation were adjusted by confounding variables by multiple regression analysis using the terminal R 3.5.1. We considered differences significant when $p \leq 0.05$, using the GraphPad Prism 7 software.
## 3. Results
There were no significant differences between light and heavy sucralose-consuming groups for age, blood pressure, pregestational BMI, number of previous pregnancies, gestation age, and CTOG’s glucose values (Table 1). The serum insulin concentration tended to increase in the heavy sucralose-consuming group compared to light sucralose-consuming mothers. However, no significant differences were reached (13.2 ± 4.5 vs. 10.2 ± 4.2, $$p \leq 0.0618$$).
As expected, mothers who referred to consuming sucralose occasionally exhibited 3.1 ± 1.4 ng/mL of serum sucralose compared to mothers reporting to ingest sucralose heavily, who showed a significant 8-fold increase of around 25.4 ± 4.2 ng/mL ($p \leq 0.0001$) (Table 1). On the contrary, sucralose concentration in umbilical cord blood samples was undetectable by the same HPLC methodology. Moreover, although there were no apparent differences between light or heavy sucralose-consuming groups for the SCP type more frequently consumed, we observed a significant increase in the number of SCP ingested weekly ($p \leq 0.0001$) (Table 1). In infants, there were no apparent differences between neonates born from mothers who lightly consumed sucralose and newborns from mothers who heavily ingested sucralose for sex proportion, birth height, Capurro index, and Apgar score (Table 1). Conversely, infants born from mothers who heavily consumed sucralose displayed a significant increase in birth weight compared to that found in newborns from mothers who lightly ingested sucralose (3.2 ± 0.6 vs. 2.8 ± 0.1, $$p \leq 0.0005$$) (Table 1). As a matter of fact, we more often observed neonates with a birth weight above the 95th percentile in the heavy sucralose-consuming group compared to that in the light sucralose-consuming group ($14.9\%$ ($$n = 13$$) vs. $7.3\%$ ($$n = 15$$), $$p \leq 0.0470$$) (Table 1). The difference in birth weight between newborns lightly or heavily exposed to sucralose during gestation was maintained after adjusting by confounding variables, such as the mother’s pregestational BMI and the number of previous pregnancies (Table 2).
Weight gain is often associated with metabolic disturbances involving the circulating levels of glucose and insulin. In this sense, there were no differences between neonates born from mothers who lightly consumed sucralose during gestation and newborns from mothers who heavily ingested sucralose during pregnancy for glucose blood levels in the umbilical cord ($$p \leq 0.1719$$) (Figure 1A). Conversely, infants born from mothers who heavily consumed sucralose during pregnancy showed a significant increase in insulin levels compared to that found in neonates from mothers who lightly ingested sucralose (15.4 ± 5.7 vs. 12.2 ± 3.8, $$p \leq 0.0425$$) (Figure 1B).
Weight gain and metabolic alterations are linked to low-grade systemic inflammation, where monocyte subpopulations play a pivotal role. Figure 2 illustrates the gating strategy for detecting the three subsets of human monocytes, which vary apparently between neonates differently exposed to sucralose during gestation (Figure 2).
There were no differences between newborns from mothers in the light sucralose-consuming group and infants born from mothers in the heavy sucralose-consuming group for classical and intermediate monocyte subsets ($$p \leq 0.3410$$ and $$p \leq 0.2103$$, respectively) (Figure 3A,B). In contrast, the nonclassical monocyte percentage significantly increased in newborns from mothers in the heavy sucralose-consuming group compared to infants born from mothers in the light sucralose-consuming group (8.1 ± 0.7 vs. 4.9 ± 1.0, $p \leq 0.001$) (Figure 3C).
Besides alterations in the monocyte subset balance, the expression of IL-1 beta, TNF-alpha, and IL-10 are differential markers of low-grade systemic inflammation. Notably, the umbilical cord tissue of neonates born from mothers who heavily ingested sucralose during pregnancy exhibited a significant 3-fold increase in IL-1 beta expression compared to that found in newborns from mothers who lightly consumed sucralose (2.7 ± 0.5 vs. 1.0 ± 0.0, $$p \leq 0.003$$) (Figure 4A). TNF-alpha expression followed a similar behavior, significantly increasing in the umbilical cord specimens of infants from mothers who heavily ingested sucralose compared to that found in neonates from mothers who lightly consumed sucralose during gestation (1.2 ± 0.1 vs. 1.0 ± 0.0, $$p \leq 0.0488$$) (Figure 4B). Conversely, umbilical cord samples of newborns from mothers who heavily ingested sucralose during pregnancy showed a significant 5-fold decrease in IL-10 expression compared to that found in infants from mothers who lightly consumed sucralose (0.2 ± 0.06 vs. 1.0 ± 0.0, $p \leq 0.001$) (Figure 4C).
## 4. Discussion
A growing body of evidence strongly suggests that sucralose intake during pregnancy may be a risk factor for the offspring to develop obesity-related disorders, including weight gain, metabolic dysfunction, and systemic inflammation early in life [10,14,21,22]. Our results indicate that mothers who heavily ingested sucralose during gestation delivered heavier babies more often found above the 95th percentile of birth weight than mothers occasionally consuming this NNS. Similarly, Azad et al. observed that children born from mothers who frequently drank beverages containing sucralose and other NNS during pregnancy exhibited a higher BMI at one year than kids whose mothers sporadically consumed NNS [23]. Furthermore, our data show no differences between light or heavy sucralose-consuming groups for the kind of SCP more often ingested, where yogurt, diet sodas, candy bars, baked goods, jams, and gelatin are usually consumed by Mexican pregnant women. In contrast, we found that the main difference between light or heavy sucralose-consuming pregnant women is given by the amount of SCP eaten or drunk per week, which aligns with previous works reporting the type of food or beverages more often consumed by school-age children in Mexico [24]. These findings indicate we should be aware of the kind and amount of foods and beverages offered to pregnant women and children to avoid the onset of metabolic and immune abnormalities later in life.
The fact that sucralose appears to exert the ability to upregulate genes involved in lipogenesis in vitro and in vivo may explain the effect of maternal exposure to sucralose on the progeny’s weight gain [13]. In this sense, sucralose increases the expression of fatty acid synthase (FAS) and fatty acid-binding protein 4 (FABP4) on the in vitro cultured 3T3L1 adipocytes and adipose tissue of mouse offspring born to sucralose-fed dams [13]. Likewise, recent evidence shows that sucralose feeding enhances FAS expression in the liver of mice with HFD-induced steatosis via the taste receptor type 1 member 3 (T1R3), a member of the sucralose’s receptor family mediating sweet taste perception [25,26]. Taking this information together, it is feasible that sucralose of maternal origin may directly promote lipogenesis and fat mass expansion in the offspring via T1R3; thus, partially explaining the weight gain observed in neonates exposed to this NNS during gestation. We believe these results should encourage other research teams to explore the probable mechanisms through which sucralose may program the onset of obesity early in life, which could help recommend new public policies regarding using NNS during pregnancy.
In addition to increasing birth weight, sucralose intake during gestation boosted insulin levels in newborns. A consistent phenomenon described in several studies is that exposure to sucralose stimulates insulin production and release [27,28,29]. In vitro stimulation of the MIN6 pancreatic beta-cell line and mouse islet cells with sucralose results in increased insulin secretion via T1R2/T1R3 heterodimerization-dependent cyclic adenosine monophosphate (cAMP) release [30]. This information allows us to suppose sucralose can directly interact with beta cells to induce insulin release by activating T1R2 and T1R3-dependent signaling pathways. In mice, sucralose supplementation for nine weeks induces a 2-fold increase in serum insulin compared to control animals drinking water [31]. Moreover, our working group and other research teams have consistently shown that short- or long-term ingestion of sucralose elevates serum insulin, indicating this NNS can also increase insulin production or release in human adults [28,32,33,34]. In line with this body of information, our data show that neonates born from mothers who heavily consumed sucralose during pregnancy exhibit increased insulin levels compared to newborns from mothers who occasionally ingested this NNS.
To the best of our knowledge, this is the first report providing new evidence that sucralose may go from the mother’s bloodstream through the placenta to the newborn’s bloodstream via vertical passing, reaching the fetal pancreas to induce either insulin synthesis or secretion. Halasa et al. previously found sucralose in amniotic fluid, but not the umbilical cord blood, suggesting transplacental passing of this NNS with potential effects on the progeny’s metabolic health [35]. To some extent, Halasa’s report resembles our inability to detect sucralose in cord blood. On the contrary, we informed considerable amounts of sucralose in the mother’s serum, which is in line with previous reports showing up to $15\%$ of sucralose can be absorbed intestinally and pass into the bloodstream [36,37,38]. Once in the mother’s bloodstream, we speculate that sucralose may reach the amniotic fluid via transplacental passing and then, the neonate’s bloodstream to exert its actions on the fetal pancreas in charge of producing insulin. The possible transplacental passing of sucralose may have several implications for reproductive health and pregnancy, where metabolic abnormalities can be programmed and affect the offspring later in life. It is, thus, urgent to demonstrate scientifically the transplacental passing of sucralose, which would allow us to recommend women not to use NNS during pregnancy; above all, female patients with a T2D familial history involving a pancreatic compromise in insulin production.
Finally, both cellular and humoral markers of low-grade systemic inflammation accompanied the increase in birth weight and insulin observed in neonates exposed to sucralose in utero. In humans, circulating monocytes are divided into classical, intermediate, and nonclassical monocytes according to the CD14 and CD16 cell-surface expression [39]. While classical and intermediate monocyte subsets preferably adhere to endothelial tissue promoting immune cell migration, the nonclassical monocytes exert inflammatory functions by expressing cytokines such as IL-1 beta and TNF-alpha [40,41]. The molecular mechanisms contributing to polarizing the activities of monocyte subsets from cell adhesion and migration to inflammation largely depend on CD14 expression, which decreases in the nonclassical monocyte subpopulation [42]. CD14 synthesis is regulated by specificity protein 1 (SP1), a transcription factor mostly expressed during human embryogenesis with the ability to orchestrate cell differentiation and growth, organogenesis, and myeloid cell maturation such as monocytes [43,44]. Interestingly, the sucralose receptor T1R3 can regulate downstream the protein kinase B (AKT), which, in turn, promotes SP1 activation [45]. In this scenario, it is feasible that sucralose ingestion during pregnancy may favor SP1 activation in myeloid cells; thus, regulating CD14 production in monocytes and conversion of these cells into the nonclassical subtype that exerts inflammatory actions belonging to the low-grade systemic inflammation.
In line with the apparent inflammatory polarization of monocytes toward the nonclassical subgroup, we also observed abnormally high TNF-alpha and IL-1 beta circulating levels in newborns from mothers who heavily consumed sucralose during gestation. As mentioned, nonclassical monocytes mainly produce IL-1 beta, a cytokine with central roles in chronic and acute inflammatory responses, apoptosis, and obesity-related cardiovascular diseases such as atherosclerosis [46,47]. Nonclassical monocytes also primarily secrete TNF-alpha, a potent inflammatory inducer that can increase insulin resistance and insulinemia by dephosphorylating the insulin receptor substrate (IRS) and AKT via protein-tyrosine phosphatase 1B (PTP1B) activation [48,49,50]. Conversely, we also found that neonates regularly exposed to sucralose in utero displayed low systemic levels of IL-10, a cytokine with potent anti-inflammatory actions leading to immunosuppression and tissue repair [51,52]. IL-10 seems to counteract the low-grade systemic inflammation instigated by IL-1 beta and TNF-alpha in non-obese subjects, promoting weight loss and insulin sensitivity in both mice and humans [53,54]. Present results expand on the body of evidence indicating that sucralose consumption during pregnancy can predispose the offspring to low-grade systemic inflammation, a condition concurring with weight gain and altered insulin secretion in patients with obesity and metabolic dysfunction. However, we should take this evidence with caution until establishing the generalizability of the current findings in other scenarios, as with the fact that pregnant women can be exposed to other NNS and not only sucralose or how long a woman has ingested sucralose before getting pregnant.
## 5. Conclusions
To the best of our knowledge, this is the first study providing evidence in humans that sucralose intake during pregnancy may predispose the neonate to weight gain, altered insulin secretion, and low-grade systemic inflammation early in life. Together with numerous studies in animal models, present results expand on the notion that sucralose and other NNS may act as obesogenic factors during fetal development, influencing the onset of obesity and metabolic disease in childhood. We encourage other research teams to conduct prospective cohort studies to follow up on newborns intrauterinally exposed to sucralose across the years to draw significant conclusions regarding the possible role of NNS in programming obesity and metabolic disease later in life. The urgent need for additional investigation in this field is justified when considering that up to $50\%$ of obese children become obese in adulthood with a 4-fold increased risk of developing chronic non-communicable diseases such as T2D [55,56].
The study’s limitations include that we conducted a cross-sectional study that restricts us from finding cause-and-effect relationships among the studied variables. Moreover, we used HPLC to measure sucralose instead of ultra-high performance liquid chromatography coupled to mass spectroscopy, which probably would have improved our ability to detect sucralose in cord blood, even in tiny quantities. Conversely, the sample size is big enough to conclude that maternal sucralose intake during pregnancy is associated with increased birth weight, circulating insulin, and low-grade systemic inflammation in neonates born at term, a finding that demands further research. However, we think increasing the sample size would allow us to analyze data by quartiles, where we can compare the effect of never, occasionally, moderately, or heavily consuming sucralose on crucial neonatal parameters such as birth weight. Present results provide scientific evidence of the impact of maternal sucralose ingestion during gestation on the progeny that may help dictate new policies aimed at regulating NNS intake in pregnant women, above all, those with a familial history of obesity and T2D.
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|
---
title: The Proteomes of Oral Cells Change during Co-Cultivation with Aggregatibacter
actinomycetemcomitans and Eikenella corrodens
authors:
- Boris Schminke
- Philipp Kauffmann
- Phillipp Brockmeyer
- Nicolai Miosge
- Christof Lenz
- Andrea Schubert
journal: Biomedicines
year: 2023
pmcid: PMC10045561
doi: 10.3390/biomedicines11030700
license: CC BY 4.0
---
# The Proteomes of Oral Cells Change during Co-Cultivation with Aggregatibacter actinomycetemcomitans and Eikenella corrodens
## Abstract
Background: Changes in the proteome of oral cells during periodontitis have rarely been investigated. This lack of information is partially attributed to the lack of human cell lines derived from the oral cavity for in vitro research. The objective of the present study was to create cell lines from relevant oral tissues and compare protein expression in cells cultured alone and in cells co-cultivated with periodontitis-associated bacterial strains. Methods: We established human cell lines of gingival keratinocytes, osteoblastic lineage cells from the alveolar bone, periodontal ligament fibroblasts, and cementum cells. Using state-of-the-art label-free mass spectrometry, we investigated changes in the proteomes of these cells after co-cultivation with Aggregatibacter actinomycetemcomitans and Eikenella corrodens for 48 h. Results: Gingival keratinocytes, representing ectodermal cells, exhibited decreased expression of specific keratins, basement membrane components, and cell-cell contact proteins after cultivation with the bacterial strains. Mesodermal lineage cells generally exhibited similar proteomes after co-cultivation with bacteria; in particular, collagens and integrins were expressed at higher levels. Conclusions: The results of the present study will help us elucidate the cellular mechanisms of periodontitis. Although co-cultivation with two periodontitis-associated bacterial strains significantly altered the proteomes of oral cells, future research is needed to examine the effects of complex biofilms mimicking in vivo conditions.
## 1. Introduction
The periodontium is formed by the gingiva, cementum, periodontal ligament (PDL), and alveolar bone [1]. These soft and hard tissues are essential for tooth attachment and proprioception during mastication [2]. Moreover, periodontal tissues constitute a barrier against the oral microbiome, the penetration of which can lead to inflammation and periodontal disease [3]. Alveolar bone is composed of a few cell types, namely, osteocytes, which exhibit direct cell–cell contact, osteoblasts, and osteoclasts [4]. These cells are embedded in a vascularized, calcified extracellular matrix (ECM). Typical proteins of the alveolar bone ECM are collagen types I, III, V, and VI [5]. The composition of the cementum is similar to alveolar bone. Cementum surrounds the tooth root and is connected to the PDL. Cementoblasts and cementocytes also produce ECM proteins, mainly collagen types I and III [6]. The PDL mediates masticatory forces between alveolar bone and tooth; its ECM is produced by fibroblasts and is mainly composed of collagen types I [7], III, V, VI, and XII [2], oxytalan fibers [8], fibulins, and matrilins [9]. The gingiva is an epithelial tissue composed of gingival keratinocytes with a typical keratin pattern [10] and a small amount of ECM that mainly consists of glycosaminoglycans [11]. Although the structural composition of periodontal tissues is well described in the literature, little is known about the proteome and the molecular mechanisms of periodontal cells in health and disease. Periodontitis is defined as the chronic inflammatory disease of periodontal tissues [12] and is currently the most common disease in patients over 30 years of age [13]. The etiology of periodontitis is multifactorial; it includes a genetic predisposition, smoking, diabetes, an impaired host response, stress, and insufficient oral hygiene [14,15]. Periodontitis is the primary reason for tooth loss and is characterized by the irreversible destruction of the periodontium [3]. Periodontal destruction is initiated by microorganisms in the biofilm and the corresponding immune response, particularly infiltrating neutrophils [16]. This cascade leads to the synthesis of inflammatory mediators that collectively contribute to tissue destruction and bone resorption, including cytokines, chemokines, arachidonic acid metabolites, and proteolytic enzymes [17]. Two major pathogenic microorganisms associated with periodontitis are Aggregatibacter actinomycetemcomitans and Eikenella corrodens [14,18,19]. Both produce virulence factors that promote the rapid dismantling of the ECM of the periodontium [20,21].
Although periodontitis is a widespread disease, its molecular mechanisms in human oral cells are not completely understood. However, it is known that periodontitis as a host-mediated disease can be influenced by autologous proteins such as melatonin, which is able to reduce pocket depth and clinical attachment loss [22]. The importance of host-mediated disease is further emphasized when peri-implant marginal bone loss is evaluated. Here, in a similar bacterial setting, increased levels of MMP8 as a bone matrix degrading enzyme are observed compared to healthy implants [23]. Therefore, we established cell lines from the human oral cavity, including gingival keratinocytes (GK), osteoblastic lineage cells from the alveolar bone (OLAB), PDL fibroblasts (PDLF), and cementum cells (CC). Using label-free quantitative mass spectrometry, we investigated changes in the proteomes of healthy human oral cells after co-cultivation with Aggregatibacter actinomycetemcomitans and Eikenella corrodens for 48 h for the first time. Our findings reveal the specific protein profiles for each of the human oral cell lines. This information will improve our understanding of the pathological mechanisms of periodontitis and related diseases, such as rheumatoid arthritis [24], diabetes mellitus [25], and atherosclerotic vascular diseases [26].
## 2. Materials and Methods
Tissue sources: PDL, cementum, alveolar bone, and gingival epithelium were obtained from patients undergoing extraction of premolars or third molars for orthodontic reasons. We only included samples without clinical and radiological signs of periodontitis to ensure that the cultured samples were not contaminated with bacteria before commencing our experimental procedures. Samples from 12 patients were obtained: 6 females and 6 males. Their average age at the time of tooth extraction was 18 years. All patients were healthy nonsmokers and provided written informed consent, consistent with the ethical regulations of our institution (file number: $\frac{22}{1}$/05).
Cell isolation and culture: Standard explant cultures of alveolar bone, PDL, cementum, and gingival epithelium samples were performed. We ensured that only the respective tissues were included, without granulomas. All specimens were washed carefully with Braunol (864219, Braun, Melsungen, Germany) three times for 1 min each and then with phosphate-buffered saline (PBS) three times for 1 min each. Afterwards, tissue samples from the PDL or cementum were placed in cell culture dishes with Dulbecco’s Modified Eagle’s Medium (DMEM) + GlutaMAXTM (21885-025, Thermo Fisher, Waltham, WA, USA) supplemented with $10\%$ fetal bovine serum (10270106, Thermo Fisher) and 50 μg/mL gentamycin. After 10 d, outgrown PDLFs and CCs were harvested, and 5 × 104 cells were transferred to 75 cm2 flasks (83.1811.002, Sarstedt, Nümbrecht, Germany). Samples of alveolar bone were digested with 0.5 mg of dispase II (17105041, Thermo Fisher) and 1 mg of collagenase (17018029, Thermo Fisher) in 1 mL of DMEM for 12 h. After digestion, the OLABs were released from their matrix using a 40 μm cell strainer (352340, Thermo Fisher). Then, 5 × 104 cells were transferred to a 75 cm2 flask. The epithelium of the attached gingiva was separated from the underlying connective tissue by digestion with 2.5 mg of dispase II (17105041, Thermo Fisher) in 1 mL of DMEM for 12 h. Next, epithelial cells were dissociated by incubating the samples with $0.25\%$ trypsin in PBS for 30 min. Afterwards, GKs were seeded on feeder cells that had been inactivated with 50 μg/mL mytomycin C (M0503, Sigma-Aldrich, St. Louis, MO, USA) for 1 h. We used gingival fibroblasts (Han and Amar 2002) obtained from the gingival epithelium samples after the separation of the GKs from the connective tissue as feeder cells. GKs and feeder cells were cultured with Keratinocyte Growth Medium 2 (C-20011, PromoCell, Heidelberg, Germany) supplemented with 0.125 ng/mL EGF, 5 μg/mL insulin, 0.33 μg/mL hydrocortisone, 0.39 μg/mL epinephrine, 10 μg/mL transferrin, 0.004 μL/mL Bovine Pituitary Extract (C-39016, PromoCell), and 0.06 mM CaCl2 (C-34006, PromoCell).
Immortalization of oral cell lines, virus production: We seeded 5 × 105 293T-cells (ACC635, DSMZ, Braunschweig, Germany) into a dish (∅ = 10 cm) and grew them to $80\%$ confluence. On the next day, 10 μg of the hTERT lentiviral plasmid (Bodnar et al. 1998) (customer order, Amsbio, Abingdon, UK) and 10 μg of the packaging plasmid mixture (LV053, ABM, New York, NY, USA) were mixed with 1 mL of DMEM. Furthermore, 80 μL of lentifectin (G074, ABM) were mixed with 1 mL of DMEM. Both solutions were incubated at RT for 5 min, and then they were mixed to allow the transfection complex to form. After 20 min, 4.5 mL of DMEM were added to the transfection complex. The transfection complex was pipetted onto the cells, and 0.65 mL of heat-inactivated FCS was added after 6 h. On the next day, the medium was carefully removed from the cells, and 10 mL of DMEM or Keratinocyte Growth Medium 2 + $10\%$ heat-inactivated FCS + $1\%$ BSA fraction V (BL63-0500, Equitech-Bio, Kerrville, TX, USA) were added. After 24 h, the cells had produced a sufficient amount of the virus, and the supernatant was harvested, centrifuged, and filtered (SLHA033SB, Merck Millipore, Burlington, MA, USA).
Transfection: 1.8 × 105 freshly trypsinized cells were resuspended in 3 mL of virus supernatant and 30 μL of protamine sulfate (P3369, Sigma-Aldrich). Three wells of a 24-well plate were each filled with 1 mL of that solution. After 6 h, 1 mL of medium was added to each well. On the next day, medium and dead cells were removed, and adherent cells received another treatment with 1 mL of the virus supernatant and 10 μL of protamine sulfate per well overnight.
Selection: Infected cells were transferred to a 75 cm2 flask and selected by culture with up to 10 μg/mL blasticidin [27].
Culture of bacterial strains: The bacterial strains Aggregatibacter actinomycetemcomitans (11122, DSMZ) and Eikenella corrodens (8340, DSMZ) were kindly provided by the Department of Microbiology at the Georg August University Goettingen. Bacterial colonies were transferred from an agar plate to an Erlenmeyer flask containing 10 mL of Brain Heart Infusion (BHI) Broth (CM1135, Oxoid, Cheshire, UK) and incubated for 4 days at RT to allow the bacteria to proliferate. Cells were centrifuged and stored in aliquots containing $30\%$ glycerin in BHI to create a stock at −80 °C. For the experiments, one aliquot of each strain was resuspended in BHI at RT.
Cell culture with bacterial strains: We seeded 5 × 104 cells of each human oral cell line at the fourth passage in 75 cm2 flasks and grew them to $80\%$ confluence without antibiotics in the respective medium. According to the literature and pilot experiments in our lab, we decided to infect the oral cell lines with 2 × 106 bacterial cells from each strain for 48 h [15,28]. The number of bacteria was determined according to the McFarland standards [29]. After 24 h, human oral cell lines were carefully washed with PBS three times for 1 min each and centrifuged to collect cell pellets.
Cell lysis: Cell pellets were resuspended in a basic lysis buffer consisting of 25 mM Tris, pH 7.4, $0.9\%$ NP-40, 150 mM NaCl, and protease inhibitors (11873580001, Roche, Basel, Switzerland). Afterwards, cells were frozen with liquid nitrogen and thawed five times. The protein concentration was determined with a Pierce BCA Protein Assay Kit (23225, Thermo Fisher, Waltham, WA, USA) and Nanodrop 1000 spectrophotometer (0H517, Thermo Fisher). Protein samples were precipitated with acetone at −20 °C for 12 h.
Immunoblotting: 1.5 × 105 cells were dissolved in 30 μL of 3 × SDS buffer containing $10\%$ β-mercaptoethanol and heated to 95 °C for 5 min. SDS-PAGE was performed with $6\%$ acrylamide in the stacking gel and $8\%$ acrylamide in the resolving gel. After SDS-PAGE, the separated proteins were blotted onto Immobilon-P membranes (PVH07850, Merck Millipore). Total proteins were detected using Coomassie blue staining.
Mass spectrometry sample preparation: Fifty micrograms of protein from each sample were loaded onto a 4–$12\%$ NuPAGE Novex Bis-Tris Minigel (NP0329BOX, Thermo Fisher Scientific) and run 1.5 cm into the gel. Following Coomassie staining, the protein bands were excised, diced, and subjected to reduction with dithiothreitol, alkylation with iodoacetamide, and finally overnight digestion with trypsin. Tryptic peptides were extracted from the gel, and the solution was dried in a Speedvac and stored at −20 °C for further analysis [30]. Equal amounts of proteins in aliquots from each sample were pooled to a total of 80 μg and separated into eight fractions using a reverse-phase spin column (84868, Thermo Fisher Scientific) to generate a peptide library. All samples were spiked with a synthetic peptide standard for retention time alignment (Ki-3002-1, Biognosys, Schlieren, Switzerland).
LC/MS/MS analysis: Protein digests were analyzed on a nanoflow chromatography system (Eksigent nanoLC425) connected to a hybrid triple quadrupole-TOF mass spectrometer (TripleTOF 5600+) equipped with a Nanospray III ion source (ion spray voltage 2400 V, interface heater temperature 150 °C, and sheath gas setting 12) and controlled by Analyst TF 1.7.1 software build 1163 (all AB Sciex). Briefly, peptides were dissolved in loading buffer ($2\%$ acetonitrile and $0.1\%$ formic acid in water) to a concentration of 0.3 μg/μL. For each analysis, 1.5 μg of digested protein were enriched on a precolumn (0.18 mm ID × 20 mm, Symmetry C18.5 µm; 186000197, Waters, Milford, MA, USA) and separated on an analytical RP-C18 column (0.075 mm ID × 250 mm, HSS T3, 1.8 µm; 186003539, Waters) using a 90 min linear gradient of 5–$35\%$ acetonitrile/$0.1\%$ formic acid (v:v) at a rate of 300 nL/min. The qualitative LC/MS/MS analysis was performed using the Top25 data-dependent acquisition method with an MS survey scan of m/z 350–1250 that accumulated for 350 ms at a resolution of 30,000 full width at half maximum (FWHM). MS/MS scans of m/z 180–1600 were accumulated for 100 ms at a resolution of 17,500 FWHM and a precursor isolation width of 0.7 FWHM, resulting in a total cycle time of 2.9 s. Precursors exceeding a threshold MS intensity of 125 cps with charge states 2+, 3+, and 4+ were selected for MS/MS, and the dynamic exclusion time was set to 30 s. MS/MS activation was achieved by CID using nitrogen as a collision gas and the manufacturer’s default rolling collision energy settings. Four technical replicates per reverse-phase fraction and a single replicate of each cell co-culture were analyzed to construct a spectral library. For the quantitative SWATH analysis, MS/MS data were acquired using 65 variable size windows across the 400–1050 m/z range [31]. Fragments were produced using rolling collision energy settings for charge state 2+, and fragments acquired over an m/z range of 350–1400 for 40 ms per segment. The inclusion of a 100 ms survey scan resulted in an overall cycle time of 2.8 s. Data were acquired from three replicate injections of each biological sample.
Data processing and statistical analysis: Proteins were identified using ProteinPilot Software version 5.0 build 4769 (AB Sciex, Framingham, MA, USA) with “thorough” settings. A total of 689,558 MS/MS spectra from the combined qualitative analyses were searched against the combined UniProtKB Homo sapiens, Aggregatibacter actinomycetemcomitans, and Eikenella corrodens reference proteomes (revision 12-2018, 105,242 entries) augmented with a set of 52 known common laboratory contaminants to identify 2408 proteins with a false discovery rate (FDR) of $1\%$. Spectral library generation and SWATH peak extraction were performed with PeakView Software version 2.1 build 11041 (AB Sciex) using the SWATH quantitation microApp version 2.0 build 2003. Following retention time correction using the iRT standard, peak areas were extracted using information from the MS/MS library at an FDR of $1\%$ [32], resulting in the quantitation of 2000 proteins across all samples. Protein peak areas were normalized to total area sums (TAS), imported into Perseus v1.5.6.0 software [32,33], and transformed to the log2 scale. A nondirected principal component analysis was performed to examine the reproducibility of biological and technical replicates. Protein peak areas of all ‘Tox’ conditions were compared pairwise to standard conditions using Student’s t-tests ($p \leq 0.05$) and the Benjamini-Hochberg correction for multiple tests. MS raw data, protein identification, and protein quantitation results were deposited in the ProteomeXchange Consortium PRIDE [34] partner repository under the dataset identifier PXD013919. Protein groups that were significantly enriched or depleted were subjected to functional annotation and enrichment analyses using DAVID Bioinformatics Resources 6.8 [35].
## 3. Results
In the present study, we examined the protein expression patterns of GK, OLAB, PDLF, and CC. Each cell-specific proteome was determined in pure culture and after co-cultivation with Aggregatibacter actinomycetemcomitans and Eikenella corrodens for 48 h. The following cells are marked with a “+” for culture with bacteria or a “−” for culture without bacteria.
## 3.1. Characteristic Phenotypes of Oral Cells
GK, an ectodermal cell lineage, showed typical epithelial characteristics, such as a cobblestone morphology, high cell density, and direct cell-cell contacts (Figure 1A, first column). The cells of the mesodermal lineage, including OLAB (Figure 1A, second column), PDLF (Figure 1A, third column), and CC (Figure 1A, fourth column), exhibited a distinctive fibroblast-like shape. OLAB were slightly rounder in shape than PDLF and CC. Compared to OLAB and PDLF, CC showed elongated cell bodies.
Cells that were co-cultivated with Aggregatibacter actinomycetemcomitans or Eikenella corrodens nor their respective controls showed any signs of apoptosis after 48 h. Morphological differences were not observed between the control specimens (Figure 1A, left panel) and the specimens cultured with bacterial strains (Figure 1A, right panel). The cells cultivated with bacterial strains underwent apoptosis after 72 h (Figure 1B). A principal component analysis (PCA) was performed as a multivariate assessment and revealed distinctive protein patterns for each cell type and for each culture condition (cultivated without or with bacterial strains) (Figure 1C). OLAB, PDLF, and CC represent cells of the mesodermal lineage; generally, they exhibited similar protein expression patterns (Figure 1C, yellow, green, and red dots, respectively, in the lower right area of the graph). Interestingly, their proteomes differed distinctively from the proteome of GK (Figure 1C, blue dots in the upper right area of the graph), which are cells of the ectodermal lineage. Strikingly, all examined cells showed major differences in their proteome patterns after co-cultivation with Aggregatibacter actinomycetemcomitans and Eikenella corrodens (Figure 1C, yellow, green, red, and blue triangles, respectively, in the left area of the graph). Again, the different lineages of the oral cells were reflected in the different protein patterns (green, red, and blue triangles in the lower left area, blue triangles in the upper left area of the graph, respectively).
## 3.2. Tissue-Specific Characteristics
Below, we will focus on the tissue-specific characteristics of each cell type. The most significant alterations in proteome composition result for the core topics of immune response, cell interactions, and ECM.
## 3.2.1. GK
GK+ exhibit lower protein levels for interleukin-1 receptor antagonist protein, macrophage migration inhibitory factor, programmed cell death protein 4, and increased protein levels for neutrophil gelatinase-associated lipocalin and prostaglandin G/H synthase 1. The adjustments of these proteins, shown on the left in Figure 2, during bacterial culture result in an overall increased immune response.
On the right side of Figure 2, the changes in cell interactions and the ECM are shown. GK+ exhibits reductions in tight junction proteins ZO-2, ladinin-1, and plakophilin-3 compared with GK−, resulting in impaired direct cell interactions. As a component and connection to the basement membrane, laminin subunit gamma-2 are formed more in GK+ and integrin beta-1 is formed les sin GK−.
The specific expression profile for the keratins in GK is shown separately in Figure 3. GK synthesize keratins 1, 2, 5, 6A, 6B, 8, 9, 10, 13, 14, 16, and 18. During culture with the periodontitis-associated pathogens Aggregatibacter actinomycetemcomitans and Eikenella corrodens, all previously described keratins are synthesized at significantly reduced levels by GK+ compared with GK−. An exception is keratin 18, which was the only keratin synthesized in increased amounts by GK+ during culture with bacteria.
## 3.2.2. OBLAs
When cultured with bacteria, OLAB+ shows a reduction in leukocyte elastase inhibitor, macrophage migration inhibitory factor, and prostaglandin reductase 1, as well as increased synthesis of nectin-2 and prostaglandin G/H synthase 1, compared with OLAB−. These results in Figure 4, as previously described for GK in Figure 2, result in an increased immune response.
The changes in cell interaction and the ECM, shown on the right in Figure 4, indicate an increase of collagen alpha-1(I) chain, fibronectin, and integrin alpha-2, and a decreased production of palladin and zyxin for OLAB+ compared with OLAB−.
## 3.2.3. PDLF
As previously described for GK and OLAB, there are increased and decreased levels of immune-modulating proteins for PDLF, shown in Figure 5. There is increased synthesis of CD166 antigen, complement component C9, and leukocyte elastase inhibitor in PDLF+. Decreased levels of proteins are measured for macrophage migration inhibitory factor and for prostaglandin reductase 1 in PDLF+. Again, an enhancing modulation of the immune response occurs for PDLF+.
At the level of cell interaction and the ECM, there are increased protein levels of basigin, collagen alpha-1(V) chain, matrix metalloproteinase-14, and SPARC in PDLF+, as well as a decreased level of vinculin when compared to PDLF−. Here, bacterial culture causes a restructuring of cell interaction and ECM in PDLF+.
## 3.2.4. CC
Even for CC, there is a partial overlap with the previously described cells, shown in Figure 6. The synthesis of CD166 antigen, CD276 antigen, and Leukocyte elastase inhibitor is increased in CC+ compared with CC−. In contrast, a decrease in protein levels is seen for macrophage migration inhibitory factor and prostaglandin G/H synthase 1 in CC+. As with GK, OLAB, and PDLF, this modulation of protein levels results in an enhancement of the immune response.
Alterations of the proteome in the area of cell interaction and ECM are mainly shown by an increased synthesis of basigin, collagen alpha-1(V) chain, and SPARC, as well as a decreased synthesis of tight junction protein 1 and Viculin in CC+. The bacterial pathogens also cause remodeling with a tendency towards degeneration in CC+.
## 3.3. Similar Changes in the Proteome of the Cell Lines during Culture with the Bacteria
Previously, mainly differences in the individual cell series during culture with Aggregatibacter actinomycetemcomitans and Eikenella corrodens were considered. In order to generate possible therapeutic approaches, the similarities between the different cells should also be considered so that a potential therapeutic candidate can be identified and further investigated. Figure 7 and Figure 8, divided for a better overview, demonstrate the 12 most differentially expressed proteins.
In the upper left of Figure 7, an increase of the collagen alpha-1 (XII) chain in GK+, OLAB+, PDLF+, and CC+ can be seen compared to the corresponding cell series in culture without bacteria. A similar increase in protein level is observed for cytoskeleton-associated protein 4 (top right of Figure 7) and for Peptidylprolyl isomerase (bottom left of Figure 7) in the cells cultured with bacteria. A reduction of protein levels in GK+, OLAB+, PDLF+, and CC+ compared with GK−, OLAB−, PDLF−, and CC− could be measured for elongation factor 2 (center left in Figure 7), filamin-A (center right in Figure 7), and glutathione S-transferase P (bottom left in Figure 7).
During culture with the PA-associated bacteria Aggregatibacter actinomycetemcomitans and Eikenella corrodens, there is an increase in relative protein levels in GK+, OLAB+, PDLF+, and CC+ for phosphate carrier protein mitochondrial (top left of Figure 8), synaptophysin-like protein 1 (center left of Figure 8), transmembrane protein 165 (center right of Figure 8), and transmembrane 9 superfamily member 2 (bottom left of Figure 8). In contrast, for pyruvate kinase (PKM; top right of Figure 8) and vimentin (bottom right of Figure 8), decreased relative protein levels are measured in GK+, OLAB+, PDLF+, and CC+ compared with GK−, OLAB−, PDLF−, and CC−.
## 4. Discussion
In the present study, we investigated the protein expression patterns of GK, OLAB, PDLF, and CC using state-of-the-art label-free mass spectrometry. For the first time, we describe cell-specific protein expression patterns and specific changes in these patterns upon co-cultivation with Aggregatibacter actinomycetemcomitans and Eikenella corrodens.
## 4.1. The Proteome of Mesodermal Lineage Cells Vary Distinctly from Those of Ectodermal Lineage
OLAB, PDLF, and CC show specific but similar protein patterns in PCA. Comparable results were shown in mesodermal cells and their derivatives [36]. Remarkably, analogous protein patterns of the investigated cells from the mesodermal lineage were shown after bacterial irritation [37]. These results suggest that bacterial irritation of different mesodermal cells leads to similar metabolic responses.
As expected, large differences were observed in the protein pattern of GK from the ectodermal lineage compared with the group consisting of OLAB, PDLF, and CC of mesodermal origin. The protein pattern of GK is significantly altered after bacterial irritation, but with remaining differences from cells of the mesodermal lineage. In a multi-omics profiling experiment, similar findings regarding the differences between ectodermal and mesodermal cells could be described [38].
## 4.2. Changes in Keratin Pattern
The performed proteome analysis showed that GK are completely different from OLAB, PDLF, and CC. Although oral keratinocyte lines are scarce, it is known that they express keratins 5, 6, 7, 8, 13, 14, 16, 17, 18, and 19 in cell culture [10]. In addition to those, keratins 1, 2, and 10 were expressed by GK in the present study. Interestingly, we observed a decrease in keratin levels in GK after cultivation with the two bacterial strains, while an increase of keratins 1, 10, and 14 after cultivation with *Porphyromonas gingivalis* has been described [39]. Proteomic analyses of gingival crevicular fluid are consistent with our findings. A pattern of keratins, including keratins 1, 2, 3, 9, and 10 [40], was found. A decrease in keratin levels during bacterial irritation is clearly seen in the present investigation, consistent with an impaired mechanical barrier. Keratin 18 was the only keratin to increase during culture with bacteria. Such an increase of keratin 18 has been shown previously in colorectal carcinomas [41].
## 4.3. Modulation of an Enhanced Immune Response in All Investigated Cells
Signs of increased immune activation in GK were found in upregulated protein levels of neutrophil gelatinase-associated lipocalin [42], programmed cell death protein 4 [43], and downregulated levels of interleukin-1 receptor antagonist protein [44]. Macrophage migration inhibitory factor was downregulated in all cells examined, indicating increased macrophage activity. Increased levels of macrophage migration inhibitory factor were described in chronic periodontitis [45]. Prostaglandin G/H synthase 1, which is known to produce the inflammatory prostaglandin E2 [46], was increased in GK, CC, and OLAB. Decreases in prostaglandin reductase 1 in OLAB and PDLF after bacterial irritation lead to higher leukotriene B4 levels and thus increase the inflammatory response [47]. Down-regulation of leukocyte elastase inhibitor in mesodermal cells is also consistent with an activated immune response, in which more elastase is released from leukocytes [48]. Binding of CD166 antigen to CD6 promotes activation of the acquired immune system by T cells [49]. CD166 antigen expression was increased in PDLF and CC after bacterial irritation. Similarly, nectin-2, a modulator of T cell signaling [50], was increased in OLAB. In CC, the CD276 antigen, also associated with T-cell activation and IFN amplification [51], was increased. Complement component C9 was elevated in PDLF, indicating an enhanced innate immune response [52].
## 4.4. Proteins of Cell Interaction and ECM Are Affected by Culture with Bacteria
The reductions of tight junction protein ZO-2 [53], ladinin-1 [54], and plakophilin-3 [55] in GK, of paladin [56] and zyxin [57] in OALB, of tight junction protein 1 [53] in CC, and of vinculin [57] in PDLF and CC suggest impaired cell interaction and reduced ECM integrity. Similarly, increased protein levels of matrix metalloproteinase-14 and its activator basigin, typical of inflammation, in PDLF reflect the degradation of ECM [58]. In this light, the increases of laminin subunit gamma-2 [59] and integrin beta-1 [60] in GK, of collagen alpha-1(I) chain [1], fibronectin [61], and integrin alpha-2 [60] in OLAB, and of collagen alpha-1(V) chain [1] in PDLF and CC appear contradictory. Presumably, degradation and regeneration processes occur simultaneously during simulated inflammation in vitro [62].
## 4.5. Similar Changes in the Proteome across Cell Lines
Common changes in the proteomes of GK, OLAB, PDLF, and CC are of therapeutic importance to identify potential candidates, which would then need to be intensified for further investigation [63].
Collagen alpha-1 (XII) is responsible for the structure of the ECM. It is produced in high levels by all cells during bacterial culture. The PDL of a mouse with mutations in collagen alpha-1 (XII) demonstrated a loss of the ordered architecture of the PDL, without evidence of periodontitis [64]. Therefore, modulation of collagen alpha-1 (XII) does not seem to be targetable in terms of a new therapeutic approach for periodontitis. Cytoskeleton-associated protein 4 regulates the exocytosis of proteases, lipases, and inflammatory mediators from neutrophil granulocytes [65]. It is increasingly synthesized during bacterial culture and has been implicated in the immune response. Increased expression, as in the experiment, seems to be useful as part of the immune system, but on the other hand, it contributes to periodontal degradation. Elongation factor 2 catalyzes the coordinated movement of tRNA molecules. In conclusion, as in the experiment shown, protein biosynthesis is reduced by the lack of elongation factor 2 [66]. This seems to represent a possible intervention for a local therapy for periodontitis. Filamin-A is decreased during bacterial culture by GK, OLAB, PDLF, and CC. The roles of filamin-A are diverse and involve various interaction proteins. Most importantly, the role in neoplasia development, which is not precisely elucidated [67], leaves a therapeutic benefit for periodontitis therapy in the background. Glutathione S-transferase P serves to regenerate the cell [68]. A study with 60 subjects describes mutations of glutathione S-transferase P as a risk factor for chronic periodontitis [69]. FKBP11 is elevated in cells subjected to bacterial irritation. As an isomerase, it probably has little relevance to periodontitis therapy, although elevated levels have already been detected in patients with chronic periodontitis [70]. The phosphate carrier protein mitochondrial is ubiquitous, conserved through evolution, and overall, a non-influencing factor in this experiment or during periodontitis. Deficiencies in the phosphate carrier protein mitochondria are lethal within the first year of life [71]. Pyruvate kinase PKM is produced at a reduced level during bacterial culture in the experiment described. Potential therapeutic approaches for periodontitis need to be carefully evaluated, as there is an unclear association with oral squamous cell carcinoma [72]. Increased synptophysin-like protein 1 is involved in the release of neurotransmitters from the synapse [73]. Therapeutic relevance does not exist in the current low data situation. Increased levels of Transmembrane 9 superfamily member 2 were detected in all cells with bacterial cultures. An association with periodontitis exists at the genetic level [74]. It is presented as a potential oncogene and is expected to become a potential drug target for newer drugs [75]. It is quite conceivable that results from research on Transmembrane 9 superfamily member 2 as a new oncogene can also be applied to the therapy of periodontitis. Vimentin, as an intermediate filament within the cell, is reduced in production due to bacterial irritation. During periodontitis, most collagenous structures are degraded. Vimentin appears to have a protective effect on the stability of collagen mRNAs [15,76]. Thus, it could also represent a potential target site for therapies to maintain the biosynthesis of collagen. However, vimetin should be investigated more deeply as it plays a role in the epithelial–mesenchymal transition [77].
## 5. Conclusions
Periodontitis-like conditions were simulated by the co-cultivation of cells with two microorganisms, while periodontitis is triggered by a complex biofilm involving several bacteria and an immune response of the respective infected host organism in vivo. Therefore, our experimental procedures do not claim to be an accurate simulation of in vivo periodontitis conditions. Nevertheless, Aggregatibacter actinomycetemcomitans and Eikenella corrodens drastically alter the protein expression patterns of infected cells, even outside of an organized biofilm. Further investigations with multispecies biofilms will be required to translate our findings to in vivo conditions. The present study will help improve our understanding of the pathological mechanisms of periodontitis and may aid in the elucidation of new treatment options that focus on influencing cellular mechanisms. Remarkably, we established a pool of human oral cell lines from attached gingiva, alveolar bone, PDL, and cementum that will be available for future in vitro periodontitis research.
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|
---
title: Co-expression analysis of lncRNA and mRNA identifies potential adipogenesis
regulatory non-coding RNAs involved in the transgenerational effects of tributyltin
authors:
- Maria Fernanda da Silva Lopes
- Juliana de Souza Felix
- Natália Francisco Scaramele
- Mariana Cordeiro Almeida
- Amanda de Oliveira Furlan
- Jéssica Antonini Troiano
- Flávia Regina Florêncio de Athayde
- Flávia Lombardi Lopes
journal: PLOS ONE
year: 2023
pmcid: PMC10045570
doi: 10.1371/journal.pone.0281240
license: CC BY 4.0
---
# Co-expression analysis of lncRNA and mRNA identifies potential adipogenesis regulatory non-coding RNAs involved in the transgenerational effects of tributyltin
## Abstract
The obesity epidemic is considered a global public health crisis, with an increase in caloric intake, sedentary lifestyles and/or genetic predispositions as contributing factors. Although the positive energy balance is one of the most significant causes of obesity, recent research has linked early exposure to Endocrine-Disrupting Chemicals (EDCs) such as the obesogen tributyltin (TBT) to the disease epidemic. In addition to their actions on the hormonal profile, EDCs can induce long-term changes in gene expression, possibly due to changes in epigenetic patterns. Long non-coding RNAs (lncRNAs) are epigenetic mediators that play important regulatory roles in several biological processes, through regulation of gene transcription and/or translation. In this study, we explored the differential expression of lncRNAs in gonadal white adipose tissue samples from adult male C57BL/6J F4 generation, female C57BL/6J offspring exposed (F0 generation) to 50 nM TBT or $0.1\%$ DMSO (control of vehicle) via drinking water provided during pregnancy and lactation, analyzing RNA-seq data from a publicly available dataset (GSE105051). A total of 74 lncRNAs were differentially expressed (DE), 22 were up-regulated and 52 were down-regulated in the group whose F4 ancestor was exposed in utero to 50nM TBT when compared to those exposed to $0.1\%$ DMSO (control). Regulation of DE lncRNAs and their potential partner genes in gonadal white adipose tissue of mice ancestrally exposed to EDC TBT may be related to the control of adipogenesis, as pathway enrichment analyses showed that these gene partners are mainly involved in the metabolism of lipids and glucose and in insulin-related pathways, which are essential for obesity onset and control.
## Introduction
Exposure to environmental factors during embryonic development has been linked to increased risk of diseases such as obesity and type 2 diabetes mellitus later in life. The obesity epidemic is considered a global public health crisis, having as contributing factors increased caloric intake, sedentary lifestyles and/or genetic predispositions. Although the positive energy balance is one of the most significant causes of obesity, recent research has linked early exposure to endocrine disrupting chemicals (EDCs) to the disease [1].
EDCs are chemical compounds that interfere with production, release, transport, metabolism, action or elimination of endogenous hormones responsible for maintaining homeostasis and regulating developmental processes [2]. Obesogenic substances comprise a subset of EDCs, which can lead to accumulation of lipids through inadequate adipogenesis, hypertrophy or hyperplasia of adipocytes, or by affecting hormonal regulation of metabolism, appetite and satiety [3]. There is growing evidence suggesting that exposure to these chemicals during intrauterine development or lactation can strongly influence the offspring’s predisposition to obesity in adulthood [4].
The germline transmission of epigenetic information between generations in the absence of direct exposures to environmental factors is defined as transgenerational epigenetic inheritance. Exposure of the pregnant mother (F0), linked with the developing fetus (F1), to environmental insults (e.g. endocrine disruptors, toxics, malnutrition), causes epimutations that are transmitted to the F2 and F3 generation. The transgenerational epigenetic inheritance caused by the environment has significant consequences in the etiology of diseases, inheritance of phenotypic variation and in evolutionary biology [5]. Studies show that transgenerational effects obtained through exposure to environmental factors is associated with epimutations in DNA methylation patterns and in histone retention patterns, which are promoted specifically through the germline [6–8].
Transgenerational effects have been observed with some types of EDCs, such as bisphenol A (BPA), dichlorodiphenyltrichloroethane (DDT), dibutyl phthalate (DBP), triphenyltin (TPT) and tributyltin (TBT). Egusquiza and Blumberg [9] reported that TBT induces obesity by promoting the differentiation of adipocytes in the body while stimulating the activity of the RXR-PPARγ complex, and that the obesogenic effects of TBT exposure are propagated transgenerationally to unexposed offspring through epigenetic changes. Shoucri et al. [ 10] have demonstrated that exposure to TBT in mesenchymal stem cell culture is related to greater accumulation of lipids during subsequent adipose differentiation. In addition to their actions on the hormonal profile, EDCs can induce long-term changes in gene expression, possibly due to changes in epigenetic patterns [11]. Epigenetic mechanisms play essential roles in the processes that determine adult phenotypes through epigenetic programming. Numerous studies over the last two decades have shown that maternal nutrition can cause changes in the fetal epigenome, i.e., DNA methylation profile, post-translational histone modifications, and regulation of and by non-coding RNAs (ncRNAs), which can lead to permanent phenotypic changes in the offspring, as reviewed by Greco et al. [ 12].
LncRNAs are non-coding transcripts composed of more than 200 nucleotides, and play an important role in the transcriptional, post-transcriptional and epigenetic regulation of gene expression, thus being able to silence or activate specific genes or loci [13]. The mechanisms by which lncRNAs regulate their targets genes depend on specific features of primary sequence, secondary structure and genomic positioning of lncRNA transcripts. LncRNAs can act by recruiting different protein components of the chromatin remodeling complex to change chromatin organizational patterns; they can function as ’sponges’ by base pairing with complementary miRNAs, thus reducing their effects; they can play scaffolding roles by providing docking sites for proteins that function together in the same biological pathway; lncRNAs can activate transcription of certain genes by guiding transcription factors to their promoters, or suppress transcription by sequestering transcription factors; and they can also modulate mRNA by base pairing with them to inhibit translation, alter splicing patterns or affect degradation [14].
Considering the importance of maternal nutrition for epigenetic patterning on the offspring (and transgenerationally on their descendants), the diverse roles that lncRNAs play on gene expression control, and the previously demonstrated effects of TBT on the expression of genes relevant to fat metabolism [1], we aimed to evaluate the effects of ancestral exposure to obesogenic substances on the expression of lncRNAs, and to correlate their expression to those of their possible biological targets in the white adipose tissue (WAT) of mice.
In this study, we identified lncRNA expression profiles in the WAT of F4 mice transgenerationally exposed to 50nM TBT or $0.1\%$ DMSO (control). Differentially expressed lncRNAs were then used to predict putative cis- and trans-target genes which were then integrated with differentially expressed mRNA data to improve the accuracy of the target prediction. Putative target mRNAs of lncRNAs in cis and trans were then used to build lncRNA-mRNA correlation networks affected transgenerationally in F4, following exposure of F0 generation to the obesogen TBT.
## RNA-seq datasets
RNA-seq data were previously generated by Chamorro-Garcia et al. [ 1], and obtained from the Gene Expression Omnibus (GEO) public database (www.ncbi.nlm.nih.gov/geo/) under the bioproject PRJNA414476, with accession number GSE105051. Briefly, 7 week-old female C57BL/6 J mice (generation F0) were exposed to 50 nM TBT or $0.1\%$ DMSO (vehicle control) via drinking water provided during pregnancy and lactation. To form subsequent generations (F2-F4), non-sibling mice were randomly assigned from litters within the same experimental groups. Only animals from the F0 generation were directly exposed to 50 nM TBT (exposed to the TBT) or $0.1\%$ DMSO (control).
Mice were kept on low-fat chow (standard diet, SD—$13.2\%$ KCal of fat) throughout the experimentation period (F0-F4). To assess interaction between TBT exposure and dietary fat levels, F4 descendants ($$n = 4$$ for each experimental group) of TBT or DMSO F0 females were switched to a high-fat diet (HFD—$21.2\%$ KCal of fat) at week 19. These F4 animals were kept in the HFD for 6 weeks, then returned to SD for 8 weeks until 33 weeks of age. To assess the effect of ancestral exposure to TBT on fat mobilization, one week before euthanasia (week 32), animals were submitted to overnight fasting (16h). In total, 8 samples of gonadal WAT (gWAT) were used for RNA-Seq, consisting of 4 samples from the 50 nM TBT exposed group (exposed to TBT in the F0 generation) and 4 samples from the $0.1\%$ DMSO group (not exposed to TBT in the F0 generation).
## Bioinformatic identification of lncRNAs in RNA-seq datasets
Quality of the extracted RNA-seq readings was evaluated with FastQC available at the public server www.usegalaxy.org [15]. Data were aligned to the latest mouse genome reference sequence (GRCm38.p6, as provided by GENCODE) (https://www.gencodegenes.org/) using HISAT2 version 2.1.0+galaxy5 [16] with the Burrows-Wheeler Transformation (BWT) and the Ferragina-Manzini (FM) indexing algorithms. The resulting BAM file was then processed with FeatureCounts version 1.6.4+galaxy1 [17] to perform read counts using the GENCODE M25 (mouse) annotation as reference (https://www.gencodegenes.org/). Quality control of all steps was carried out using MultiQC. Next, DESeq2 (version 2.11.40.6 + galaxy1) was used to perform statistical analyses of differential expression of lncRNAs and mRNAs between samples from the TBT and control (DMSO) groups. This tool estimates the average variance in read counts and tests the differential expression using a binomial distribution model as basis and Wald test [18].
The Biomart tool was used to classify the transcripts according to their biotype. Biotypes are classified according to HAVANA gene biotype (http://www.ensembl.org/info/genome/genebuild/biotypes.html) and grouped into 3 classes: protein-coding genes, long non-coding RNA (lncRNAs) genes and small non-coding RNA genes. In the lncRNAs class, the following descriptions were considered: "processed_transcript", "pseudogene", "To be Experimentally Confirmed (TEC)", "lincRNA", "3prime_overlapping_ncrna", "antisense", "sense_intronic" and sense_overlapping".
Differently expressed (DE) LncRNAs ($p \leq 0.05$) and coding proteins ($p \leq 0.05$ and log2(FC) ≥ ± 0.5) were clustered with the heatmap3 package in R using the “complete linkage” method and the Euclidean distance as parameters (https://www.rdocumentation.org/packages/heatmap3/versions/1.1.7/topics/heatmap3).
## Prediction analysis of putative lncRNAs with cis-and trans action
Differentially expressed lncRNAs were used for the prediction of the putative cis- and trans-target genes. First, using normalized counts of differentially expressed lncRNAs and mRNAs, we performed correlation analysis by means of Pearson’s correlation coefficient. A lncRNA-mRNA interaction was considered significant when Pearson`s correlation |r| ≥ 0.80 and $p \leq 0.05.$ From the total correlation matrix, we performed two analyses to identify and classify the interactions and possible actions of lncRNAs (cis and/or trans) in relation to their target gene. To check potential lncRNA-mRNA interactions, LncTar (http://www.cuilab.cn/lnctar) [19] was used to predict lncRNA targets (normalized dG (ndG) was set to -0.10) and those with significant correlation, as identified by Pearson’s correlation (as described above), were maintained. Classification of DE lncRNAs was performed using the program FEELnc (Flexible Extraction of Long non-coding RNAs) (v.0.1.1) (https://github.com/tderrien/FEELnc) [20]. Based on locus analysis, lncRNA-mRNA interactions that had the target mRNA within a window of 100 kbps upstream or downstream of the lncRNA location were classified as cis-acting, and interactions outside the established window of 100 kbps and that also had a binding potential (ndG≤ -0.10) were classified as trans-acting.
Only DE lncRNAs with correlation and binding potential within the parameters and their corresponding cis- and trans-target genes were used to construct lncRNA-gene interaction networks using the Cytoscape 3.9.0 program (https://cytoscape.org/). Also, Cytoscape was used to identify nodes from the co-expression modules. The top five nodes were ranked according to interaction number of the lncRNAs and their targets.
To gather as much information as possible on all lncRNAs, we performed orthology analysis of all DE lncRNAs with humans using the Orthology Predictions Search tool, available at https://www.genenames.org/tools/hcop/#!/. Subsequently, the NcPath tool (http://ncpath.pianlab.cn/#/Home) was employed to compare the predict targets of the orthologous lncRNA to experimentally-verified lncRNA targets in humans.
## Gene ontology and pathway enrichment analysis
We used the g:GOSt (Function Profiling) tool within gProfiler (https://biit.cs.ut.ee/gprofiler/gost) for analysis of the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG Pathways) of all significant lncRNAs and partner mRNA pairs (https://biit.cs.ut.ee/gprofiler/gost). All p-values were adjusted using the Benjamini-Hochberg (FDR) method (adjusted p-value <0.05).
A schematic overview of the lncRNA analysis and identification pipeline can be seen in Fig 1.
**Fig 1:** *Workflow of lncRNA analysis and functional predictions.The workflow describes the step-by-step bioinformatics analyzes performed in our study. (A) Raw reads were extracted from the GEO database. (B) The bioinformatics analyzes (quality, alignment, counting and differential expression) of these readings were performed on the Galaxy platform. (C) Classification of transcripts was performed on the Ensembl Biomart platform. (D) Correlation between differentially expressed lncRNAs-mRNAs. (E) Classification of the action of lncRNAs and their target mRNAs. (F) Functional enrichment analysis.*
## MBD-seq data analysis
To evaluate the methylation profile of the regions of interest (DE lncRNAs), MBD-seq data, generated with the same model described for RNA-Seq (Chamorro-Garcia et al. [ 1]) and previously analyzed by the authors, was employed (GSE105051).
## Identification differential expression of lncRNA
Out of 818 differentially expressed transcripts, 708 ($86.5\%$) matched to protein coding and 74 (~$9\%$) were considered to have a lncRNA biotype, according to the HAVANA gene biotype classification, available on the Ensembl Biomart tool. Long intergenic non-coding RNAs (lincRNAs) accounted for $39.2\%$ of all DE lncRNAs, followed by antisense transcripts ($27\%$). The remaining non-coding transcript types were TEC ($18.9\%$), processed_transcripts ($8.1\%$), bidirectional promoter lncRNA ($5.4\%$), and sense_intronic transcripts ($1.4\%$).
Of these 74 DE lncRNAs in the contrast of the groups exposed to 50 nM TBT or exposed to $0.1\%$ DMSO (S1A and S1B Table), 22 showed increased expression in the group in which F0 was exposed to 50 nM TBT when compared to that exposed to $0.1\%$DMSO. The other 52 lncRNAs were downregulated in the group ancestrally (F4) exposed to 50 nM TBT (Fig 2).
**Fig 2:** *Heatmap of 74 differentially expressed lncRNAs between samples of gWAT ancestrally exposed to EDC TBT and samples of the control group (DMSO).Expression of lncRNA is represented according to the color scale shown at the top, corresponding to the z-score. Red represents higher expression, and green represents lower expression.*
## Correlation of expression and classification of trans and cis acting lncRNAs
To assess the influence of lncRNAs on the expression of mRNAs and their biological functions, we obtained a correlation matrix of 6595 significant interactions between DE lncRNA and mRNA (Pearson correlation r ≥ |0.80|; p-value <0.05) (S2 Table). Of these, we observed that a total of 1191 lncRNA-mRNA interactions presented significant binding potential, suggesting trans-action potential (normalized deltaG analysis in LncTar tool (ndG < -0.10)) (S3 Table).
In the prediction analysis of cis lncRNAs-mRNAs pairs (performed in the FEELnc tool), we obtained 11 DE lncRNAs linked to 11 genes close to DE, and of these 2 lncRNA-mRNA interactions showed significant correlation (Pearson correlation r ≥ |0.80 |; p-value <0.05) (S4 Table). As a cis-acting transcript, lncRNA Gm26704 could affect Fzd6 pre-transcriptionally, in addition to presenting binding potential (LncTar) with the Fzd6 mRNA. The lncRNA Gm10603 is a cis-partner of the *Ucp* gene.
Following orthology analysis of our 74 differentially expressed lncRNAs, only 2 lncRNAs had human orthologous, namely Rian (MEG8—human) and Ftx (FTX—human). Of these, Rian was the only one with predicted targets in mice that were also experimentally-verified targets in humans (Shank2 and Inhba).
## Biological function analysis
*For* gene ontology and KEGG pathway analyses, DE mRNAs and lncRNAs that showed significant correlation (Pearson correlation r ≥ |0.80 |; p-value <0.05) and binding potential (ndG < -0.10) were used. Therefore, 479 target genes identified from the 61 lncRNAs were used to obtain information about biological functions. KEGG analysis revealed 27 pathways (Fig 3) with 100 of our identified partner mRNAs, which in turn were potentially regulated by 50 DE lncRNAs. The enriched pathways were mainly related to lipid and glucose metabolism.
**Fig 3:** *KEGG pathways enriched for co-expressed mRNAs in Cytoscape network.KEGG pathway enrichment analysis was performed in gProfiler. The y-axis represents the KEGG pathways and the x-axis represents the number of genes participating in each pathway. The numbers in front of the bars represent the adjusted p-value of the respective route.*
Next, we constructed co-expression networks to better visualize the five major interactions between lncRNAs and their targets (Fig 4). Using the analyze network tool in Cytoscape, the top five lncRNAs were identified based on the number of interactions with mRNA partners (Table 1 and S5 Table).
**Fig 4:** **Network analysis* of the top 5 network analysis of the top 5 lncRNAs based on the number of interactions with mRNAs.Hexagons represent mRNAs, and triangles represent lncRNAs. Light blue nodes represent KEGG pathways. Expression of lncRNA and mRNA are represented according to the colors red and green, corresponding to up and down-regulated transcripts, respectively.* TABLE_PLACEHOLDER:Table 1
## Identification of DE lncRNAs in DMRs
Next, we used the MBD-*Seq data* obtained by Chamorro-Garcia et al. [ 1] in order to verify the location of Differentially Methylated Regions (DMR) in relation to our identified DE lncRNAs. In the study, the authors classified the regions according to the distance of the DMRs from the transcription start site (TSS), as well the number of DMRs present. Region I was comprised of genes with at least one DMR in close proximity (between -1500 bp and +500 bp) to the transcription start site (TSS). Region II indicates genes that overlap or flank at least one DMR, regardless of their distance from the TSS. Finally, region III represents genes located in iso-differentially methylated blocks (isoDMBs). Our results show that 35 of our DE lncRNAs were located within regions II and III, as classified by Chamorro-Garcia et al. [ 1], 9 of which were down-regulated in hypermethylated regions and 10 were up-regulated in hypomethylated regions (Table 2) suggesting that global changes in DNA methylation, resulting from ancestral exposure to the endocrine disruptor TBT, can alter the expression of lncRNAs and mRNAs involved in the adipogenesis process.
**Table 2**
| Gene symbol | Up/Down | Direction of change | DMR subset | DMR structure |
| --- | --- | --- | --- | --- |
| 1700018A04Rik | down | Hypermethylated | II | mDMR |
| 2810013P06Rik | down | Hypermethylated | III | isoDMB |
| 3300002A11Rik | down | Hypermethylated | III | isoDMB |
| Arhgap27os1 | down | Hypermethylated | III | isoDMB |
| B130024G19Rik | down | Hypermethylated | II | mDMR |
| BE692007 | down | Hypermethylated | III | isoDMB |
| E430024I08Rik | down | Hypermethylated | III | isoDMB |
| Gm10804 | down | Hypermethylated | II | mDMR |
| Gm37464 | down | Hypermethylated | II | mDMR |
| 1700047G03Rik | up | Hypomethylated | III | isoDMB |
| B430119L08Rik | up | Hypomethylated | II | mDMR |
| Gm10370 | up | Hypomethylated | II | mDMR |
| Gm10603 | up | Hypomethylated | III | isoDMB |
| Gm13067 | up | Hypomethylated | II | mDMR |
| Gm13375 | up | Hypomethylated | II | mDMR |
| Gm42917 | up | Hypomethylated | III | isoDMB |
| Gm43050 | up | Hypomethylated | III | isoDMB |
| Gm5144 | up | Hypomethylated | III | isoDMB |
| Gm5627 | up | Hypomethylated | III | isoDMB |
## Discussion
Exposure to endocrine-disrupting chemicals has been linked to transgenerational effects, including a predisposition to unfavorable phenotypic traits and the development of diseases, including obesity and other associated comorbidities [21]. In the present study, we analyzed the expression profiles of lncRNAs in the gWAT of F4 mice ancestrally exposed in F0 to obesogenic substances. Previous evidence indicates that epigenetic mechanisms, e.g. DNA methylation, histone methylation, histone retention and the expression of non-coding RNAs may be involved in transgenerational inheritance under the effects of endocrine disruptors [1, 22]. With a particular interest in ncRNA regulation of phenotypes, we used the RNA-*Seq data* elegantly generated by Chamorro-Garcia et al. [ 1], and identified a total of 74 differentially expressed lncRNAs in F4 mice ancestrally exposed in F0 to the EDC TBT, and analyzed the expression correlation with their presumptive partner genes, as lncRNAs are known to regulate protein-coding genes [23]. Among the many regulatory roles of lncRNAs [24], the use of transcriptome data affords the investigation of direct effects of lncRNAs on coding transcripts, through the use of target sequence-based prediction and coexpression analyses. In order to investigate the biological functions of these lncRNAs and their gene partners, we performed GO term analysis and pathway enrichment analysis. Pathway analysis showed that some of our DE lncRNAs and their partner genes are primarily involved in glucose and lipid metabolism and in insulin-related pathways, essential in regulating adipogenesis and obesity [25].
LncRNA Gm6277, upregulated in the TBT group, is correlated with the coding transcript for Slc2a4 (Solute Carrier Family 2 Member 4), also upregulated in the TBT group. Slc2a4 is a member of the solute transporter 2 (facilitated glucose transporter) family and encodes the main glucose transporter present in skeletal and cardiac muscles and adipose tissue, GLUT4. Expression of Slc2a4/GLUT4 is majorly involved in glucose removal from tissues and, consequently, in glycemic homeostasis, playing an important role in the pathophysiology of diseases such as Type 1 and 2 Diabetes Mellitus and Obesity [26]. Downregulation of GLUT4 in obesity is an important factor contributing to impaired insulin-stimulated glucose transport in adipocytes [27]. As reviewed by Yohannes Tsegyie Wondmkun [28], defective insulin receptor signaling is a major component of obesity-associated insulin resistance in humans. Bazhan et al. [ 29] reported that levels of the gene responsible for glucose uptake in white adipose tissue in mice, Slc2a4, were subject to age-related changes, with Slc2a4 expression increasing from young age to early adulthood and decreasing with age from adulthood onwards. Progression from early to late adulthood is commonly accompanied by an impaired glucose metabolism, including increased plasma insulin levels and impaired glucose tolerance. In agreement, Carvalho et al. [ 30] showed, also in mice, that reduced expression of Slc2a4 in white adipose tissue is associated with the development of impaired glucose tolerance and insulin resistance, while its overexpression is linked to insulin sensitivity. Insulin stimulates the transport of glucose and the synthesis of triglycerides (lipogenesis), in addition to inhibiting lipolysis, which may be responsible for excessive accumulation of adipose tissue. Thus, insulin resistance in obesity is exhibited by reduced insulin-stimulated glucose transport and metabolism in adipocytes, and by impaired suppression of hepatic glucose production [31]. Kamstra et al. [ 32] showed in 3T3-L1 cells, that exposure to endocrine disruptors (e.g. EDC BDE-47) increases the expression of specific adipogenesis markers such as Slc2a4, through activation of peroxisome proliferator-activated receptor (PPARγ). We observed that the expression of Slc2a4, a differentiated adipocyte marker gene [33], is potentially regulated by lncRNA Gm6277, and its high expression can be explained by exposure to endocrine disruptors, as described above. Endocrine disrupting chemicals promote adipogenesis by altering fat cell development and/or increasing energy storage in adipose tissue [34], which, in turn, can be inherited by subsequent non-exposed generations, as demonstrated by Chamorro-Garcia et al. [ 35]. We suggest that regulation of lncRNAs and their gene-partners in the white gonadal adipose tissue of mice ancestrally exposed to the EDC TBT may be related to the control of adipogenesis, suggesting that this regulation may be epigenetically inherited.
The second lncRNA with the highest number of mRNA targets, the TBT-downregulated Gm10804. Recently, Li and colleagues [36] reported that low expression of Gm10804 improves glucose and lipid metabolism disorders in hepatocytes from mice exposed to high glucose, which is of importance as the liver plays a key role in adjusting glucose levels, in turn affecting energy homeostasis in other tissues [37]. One of the correlated target mRNAs of this lncRNA is the TBT-downregulated Slc27a2 mRNA, also known as FATP2. Slc27a2 plays a key role in lipid metabolism through fatty acid transport and/or activation of very long-chain fatty acids and is linked with activation and/or inhibition of the transcription factors PPARγ (in adipocytes), PPARα (liver) and PPARβ (adipocytes), regulating the expression of several genes involved in lipid metabolism [38]. Further, Choi and colleagues [39] reported in C57BL/6 J mice, that reduced expression of genes involved in lipolysis and uptake and transport of fatty acids (such as Slc27a2) in response to a high-fat diet (HFD) can reduce β-oxidation, resulting in excessive fat accumulation. Chamorro-Garcia et al. [ 35] have previously demonstrated that exposure of pregnant F0 mice to TBT led to transgenerational effects on the accumulation of lipids in white adipose tissue and liver, and to the increase in expression of hepatic genes involved in the storage/transport of lipids, in all future generations evaluated. Early exposure to endocrine-disrupting chemicals may alter metabolic homeostasis points, predisposing exposed individuals and their offspring to store more fat [40]. Here in our study, we used the RNA-*Seq data* produced by Chamorro-Garcia et al. [ 1], from gonadal adipose tissue samples from F4 mice transgenerationally exposed to EDC TBT in F0, which were subjected to a high fat diet challenge (HDF– $21.2\%$ Kcal from fat) for 6 weeks, to assess the interaction between EDC TBT and fat accumulation. Our results suggest that low expression and the positive correlation of the mRNA Slc27a2 with the lncRNA Gm10804 in the gonadal white adipose tissue of mice ancestrally exposed to the obesogenic substance TBT, may alter lipogenic and lipolytic pathways, reflecting in increased fat storage as well as decreased fat mobilization, as observed in these mice. This corroborates previous reports of association of lncRNAs with several metabolic conditions such as obesity, type 1 diabetes mellitus, type 2 diabetes mellitus and non-alcoholic fatty liver disease [41].
LncRNA Rian, which is orthologous with the lncRNA MEG8 in humans, was down-regulated in our study. One of the correlated target mRNAs of this lncRNA is the TBT-downregulated Inhba, also known as activin A. Activin A is a secreted adipokine composed of two subunits of inhibin βA (INHBA) and is highly expressed in the adipose tissue of obese patients when compared to lean individuals. INHBA is a member of the transforming growth factor-β superfamily and regulates a number of cellular events, including regulation of cancer cell growth and metastasis, apoptosis and, primarily, proliferation and differentiation of human embryonic stem cells. Zaragosi and colleagues [42] analyzed the transcriptome of human adipose tissue-derived stem cells (hMADS) and identified that activin A is expressed in adipose progenitors of various human fat depots and is dramatically downregulated as these progenitor cells undergo adipogenesis. Thus, we suggest that downregulation of mRNA Inhba, positively correlated with the lncRNA Rian, may be associated to excessive accumulation of adipose tissue resulting from exposure to the endocrine disruptor tributyltin and adipogenic pathways.
Evidence shows that in many complex diseases (e.g. cancer, obesity, diabetes), expression levels of lncRNAs and mRNAs can be significantly altered through DNA methylation, which plays a vital role as an epigenetic regulator [43]. Hernando-Herraez et al. [ 44] reported that methylation of lncRNA promoters is involved in a variety of biological processes and can lead to silencing or activating their expression. Dysregulation of lncRNA expression, by means of promoter methylation, can directly affect expression of their target mRNAs, or indirectly affect mRNAs controlled by miRNAs that are targets of competing endogenous lncRNAs [45]. Methylation in the promoter region of genes and lncRNAs is a major component of epigenetic regulation, however much less is known about DNA methylation outside of proximal promoters [46]. Albeit less investigated, methylation of regulatory regions outside of promoters are also able to regulate gene expression, as reviewed by Ordoñez and contributors [47]. Chamorro-Garcia et al. [ 1] analyzed differentially methylated regions (DMRs) and isoDMB regions (genomic regions containing differentially methylated DNA blocks with similar methylation profile) and associated to differentially expressed genes related to metabolism. Using their methylation data, we found DE lncRNAs and mRNAs in regions classified by the authors as regions II and III (Chamorro-Garcia et al., [ 1]), with 11 lncRNAs and 183 mRNAs that were downregulated by TBT located in hypermethylated regions, and 9 lncRNAs and 58 mRNAs that were TBT-upregulated located in hypomethylated regions. Similar to the findings of Chamorro-Garcia et al. [ 1], these target mRNAs encode proteins that participate in pathways involved in fatty acid metabolism, such as β-oxidation, citric acid cycle and glycolysis, such as the Slc27a4 mRNA. Our results support and extend the findings of Chamorro-Garcia et al. [ 1] and suggest that some of the altered expression profiles of mRNAs and lncRNAs, observed transgenerationally following exposure to TBT, could be directly related and partly explained by alterations in methylation profile.
## Conclusions
Our analyses showed that ancestral exposure to obesogenic substances seems to play an important role in the low and/or high expression of mRNAs, potentially regulated by lncRNAs, which act in the glucose and lipid metabolism pathways, which are directly related to the adipogenesis process. Therefore, further studies are needed on the molecular and biological roles of lncRNAs as potential regulators of white adipose tissue functions.
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|
---
title: Unexpected Classes of Aquaporin Channels Detected by Transcriptomic Analysis
in Human Brain Are Associated with Both Patient Age and Alzheimer’s Disease Status
authors:
- Zein Amro
- Matthew Ryan
- Lyndsey E. Collins-Praino
- Andrea J. Yool
journal: Biomedicines
year: 2023
pmcid: PMC10045580
doi: 10.3390/biomedicines11030770
license: CC BY 4.0
---
# Unexpected Classes of Aquaporin Channels Detected by Transcriptomic Analysis in Human Brain Are Associated with Both Patient Age and Alzheimer’s Disease Status
## Abstract
The altered expression of known brain Aquaporin (AQP) channels 1, 4 and 9 has been correlated with neuropathological AD progression, but possible roles of other AQP classes in neurological disease remain understudied. The levels of transcripts of all thirteen human AQP subtypes were compared in healthy and Alzheimer’s disease (AD) brains by statistical analyses of microarray RNAseq expression data from the Allen Brain Atlas database. Previously unreported, AQPs 0, 6 and 10, are present in human brains at the transcript level. Three AD-affected brain regions, hippocampus (HIP), parietal cortex (PCx) and temporal cortex (TCx), were assessed in three subgroups: young controls ($$n = 6$$, aged 24–57); aged controls ($$n = 26$$, aged 78–99); and an AD cohort ($$n = 12$$, aged 79–99). A significant positive correlation ($p \leq 10$−10) was seen for AQP transcript levels as a function of the subject’s age in years. Differential expressions correlated with brain region, age, and AD diagnosis, particularly between the HIP and cortical regions. Interestingly, three classes of AQPs (0, 6 and 8) upregulated in AD compared to young controls are permeable to H2O2. Of these, AQPs 0 and 8 were increased in TCx and AQP6 in HIP, suggesting a role of AQPs in AD-related oxidative stress. The outcomes here are the first to demonstrate that the expression profile of AQP channels in the human brain is more diverse than previously thought, and transcript levels are influenced by both age and AD status. Associations between reactive oxygen stress and neurodegenerative disease risk highlight AQPs 0, 6, 8 and 10 as potential therapeutic targets.
## 1. Introduction
Healthy aging is associated with widespread cognitive, morphological, and functional changes in the brain. Such processes are exacerbated in age-related neurodegenerative disorders, including Alzheimer’s disease (AD) [1]. AD, characterized by the formation of amyloid plaques and neurofibrillary tangles (NFTs) consisting of hyperphosphorylated tau in vulnerable brain regions, is the leading cause of dementia in the aging population [2]. Amyloid plaques are thought to impair synaptic function, induce hyperexcitability, and enhance the generation of reactive oxygen species [3,4,5,6]. Similarly, insoluble NFTs of hyperphosphorylated tau have been correlated with neuronal toxicity [7], and found to serve as predictive markers for cognitive performance and overall dementia status [8]. Importantly, amyloid beta (Aβ) and tau-based evaluations indicate that the disease spreads through neighbouring anatomical areas beginning at the hippocampal formation and areas of the temporal (e.g., entorhinal cortex) and parietal (e.g., retrosplenial cortex; posterior parietal cortex; precuneus) lobes in preclinical stages of the disease before spreading to additional regions (e.g., prefrontal cortex; amygdala) as individuals become symptomatic [9,10,11] in a process proposed to involve networks of astrocytes and microglia [12]. In particular, the astrocytic internalization of Aβ plaques for clearance in AD has been suggested to involve aquaporin channels [13,14,15].
Aquaporin channels (AQPs) are transmembrane proteins that facilitate the bidirectional movement of water and small solutes, and are expressed in all forms of life [16,17]. The 13 classes of AQPs in humans (AQPs 0–12) show tissue-specific expressions in brain, kidney, eye, skin, heart, lungs and other organs [18]. The classical AQP subtypes, initially defined as strictly water-selective, include AQPs 0, 1, 2, 4 and 5, though additional permeabilities to ions, signalling molecules and metabolites continue to be added to the repertoire [19,20]. For example, AQP0 and 5 have both been shown to be permeable to hydrogen peroxide (H2O2) in addition to water [21,22], prompting an additional descriptor as ‘peroxiporins’. Similarly, AQPs 6, 8 and 11 are all classified as peroxiporins [23,24,25]. AQP subtypes initially characterized by their permeability to both glycerol and water are classified as aquaglyceroporins, including AQPs 3, 7, 9 and 10 [26], although AQP9 has also been shown to permeate H2O2 in mice [27]. Finally, the non-orthodox AQP12, which, similar to the peroxiporin AQP11, lacks one of the two conserved asparagine-proline-alanine (NPA) motifs important for the molecular structure of the pore passageway [28], has been suggested to play a role in digestive enzyme secretion [29].
In the mammalian brain, three AQPs—AQP1, 4 and 9—have been identified as proteins expressed under physiological and pathological conditions [30,31,32,33]. AQP1 is predominantly expressed in the choroid plexus, facilitating regulated cerebrospinal fluid (CSF) production under normal physiological conditions [30]. In the face of pathology (such as AD, contusion and subarachnoid haemorrhage, for example), reactive astrocytes initiate the abnormal expression of AQP1 [31,34]. In line with this, AQP1 levels are increased in early AD (as defined by Braak criteria) within astrocytes, and co-localized with Aβ plaques for reasons yet to be determined [35,36,37]. Unlike AQP1, which only is expressed in astrocytes under pathological conditions, AQP4 is dubbed the ‘brain AQP’ based on its high levels of physiological expression in astrocytes throughout the central nervous system, primarily in perivascular and peri-synaptic end-feet domains [32,38]. AQP4 channels are essential for the clearance of interstitial solutes, metabolic products and protein aggregates (such as Aβ and hyperphosphorylated tau) from the brain microenvironment via the glymphatic system [15,39,40,41,42,43]. Similarly, AQP9 is also thought to play a key role in astrocytes under normal physiological conditions and has been suggested to be involved in facilitating the diffusion of lactate from astrocytes to neurons for metabolic support [33,44,45].
Other AQPs also have been implicated in brain function under both normal physiological and pathological conditions, although, to date, these have been less well investigated. For example, AQP6 has been suggested to participate in the gated reabsorption of water to reduce neuronal synaptic swelling, since its expression and activity are reliant on low pH [46]. Transcript and protein levels of AQPs 3, 5, 8 have all been reported to increase in rat astrocytes and neurons in vivo after hypoxia, suggesting that they may play a possible role in post-injury edema [40]. Interestingly, AQP11 has been detected in cerebellum and hippocampus, but no functional role of this non-orthodox AQP has yet been proposed [47,48].
Given the diverse expression of AQPs within the mammalian brain, and their multi-faceted roles in numerous physiological processes, we propose that alterations in AQP channel expression may play a role in both healthy aging and AD pathogenesis. Significantly, given their role in response to stress and injury, we hypothesized that establishing AQP expression profiles in AD might reveal their potential as novel therapeutic targets. To identify the full set of candidate AQPs of interest, transcript levels were assessed from Allen Brain *Atlas data* for all 13 AQP subtypes, in brain regions selected for relevance in AD pathology. Transcript levels in AD brains were compared with age-matched healthy brains and young healthy controls. Notably, the Allen Brain Atlas serves as a substantial archive of collated RNAseq data that remain to be analysed; this public domain database is invaluable for enabling novel discoveries, as demonstrated in previous work [49].
## 2.1. Data Source
Data were acquired from the Allen Brain Atlas (ABA), a publicly available dataset. Microarray data were downloaded directly from the webpage (https://human.brain-map.org accessed on 21 September 2021). In brief, brains were processed serially with multiple sample batches submitted per brain analysed. Data were then normalised to an internal control, in accord with detailed method documents (https://help.brain-map.org/display/humanbrain/Documentation accessed on 21 September 2021).
## 2.2. Human Brain Atlas Database
This dataset contains RNAseq transcriptome data from six individuals aged 24–57 with no known pathology, designated as the young control group (C). Data from this database, in addition to the Institute of Aging, Dementia and TBI database, were collected from four brain regions for all age groups (Supplementary Table S1), given the anatomical areas of interest affected in AD highlighted in the introduction and as outlined by the Braak staging for disease spread [9]. Given the cortical areas known to be affected early on in the disease process in AD, the current analysis focused specifically on data from the temporal and parietal lobes [11]. A detailed description of tissue acquisition is available in the ABA white paper documentation (https://help.brain-map.org/display/humanbrain/Documentation accessed on 21 September 2021). Briefly, brain tissue was collected after obtaining informed consent from the patients’ next-of-kin, followed by a review and approval from the Institutional Review Board (IEB).
## 2.3. Institute Aging, Dementia and TBI Database
This dataset contains RNAseq transcriptome data from 107 individuals aged 77 and older with/without traumatic brain injury (TBI) and dementia obtained from the Adult Change in Thought cohort [50]. To investigate the effect of aging on the AQP gene expression profile in the brain, an aged control group (AC), comprised of 29 individuals aged 78–99 with no known pathology, was used for comparison with both the C and AD groups. For the AD group, 12 individuals aged 79–99 with a pathological diagnosis of probable AD and no prior history of TBI were selected for analysis. Individuals with a diagnosis of possible AD were excluded, as their underlying disease progression may be secondary to other comorbidities [51]. Additionally, due to the known influence of TBI on tau pathology and its relationship with an increased risk of AD [52,53], patients with any documented history of TBI were excluded from bioinformatics analysis.
## 2.4. Gene Probes
For each AQP channel gene, two probes for the young control group (selective for different exons) and one probe for the aged control and AD group were used for RNAseq analysis. For details on probe IDs, refer to Supplementary Table S2. For a comparison between groups, the two probes used for each gene in the C group were averaged.
## 2.5.1. Regression Model Analyses
To investigate the relation between age and AQP0-12 RNAseq levels, we used a random intercept model generated using the formula:RNAseq levelgene,region=β0,gene,region+β1age+ε.
Additionally, linear regression models were fit for all subjects for each gene/anatomical region separately, controlling p-values using the Bonferonni correction.
## 2.5.2. Supervised Clustering Analyses
Using our genes and anatomical regions of interest, supervised clustering methods were used to investigate which of the probes were primarily responsible for differences between clusters determined in the healthy young and aged groups (https://human.brain-map.org accessed on 21 September 2021). This method produces Principal Components, defined as a function of the probes loaded into the analyses. The ‘loadings’ (coefficients) for the probes show how strongly each of the probes affect the clustering. Each principal component describes a linear combination of probes that best distinguishes between the three anatomical regions (HIP, PCx, TCx). Probes for AQP11 and AQP9 defined Principle Component 1. A total of 22 probes for various AQP genes defined Principle Component 2. Supervised clustering analysis was performed using Sparse Partial Least Squares Discriminant Analysis, as implemented in the mixOmics package [54] on RStudio.
## 2.5.3. Differential Expression Analysis
To determine whether there was a differential expression between each of the three anatomical groups of interest in the young control (C) and AC group pooled, a differential expression analysis was conducted using the limma package [55] to fit linear models on RStudio. The models included individual ID as a covariate in order to account for the nested structure of the data, which included multiple samples from each of the six individuals. Furthermore, to investigate whether AQP gene expression changes with healthy aging, a differential expression analysis was conducted on these individuals, dividing them into their original groups (C and AC). Heatmaps were generated by graphing the log fold change (logFC) of genes on GraphPad Prism 9.0 for probes that both showed a significant result in the differential expression analysis.
## 2.5.4. Expression Analysis–Group Comparison
To investigate the potential change in individual gene expression profile in the control, aged control and AD groups, a one-way ANOVA followed by multiple comparison post hoc Tukey test of the RNAseq expression level for each AQP channel was conducted on GraphPad Prism V9.0. The significance level for all analyses was set at $p \leq 0.05.$
## 3.1. Subject Population Characteristics
The demographic information for each group is presented in Table 1. No statistically significant difference between the Aged Control (AC) and Alzheimer’s disease (AD) groups was observed for education level ($$p \leq 0.655$$) but was observed for age when comparing AC and AD groups to the C group ($p \leq 0.0001$). However, as expected, AD patients showed a significantly advanced degree of pathology, as measured by the Braak stage ($p \leq 0.05$). Detailed patient information is summarized in Supplementary Table S3.
## 3.2. Baseline AQP Expression Profiles Differ with Age in the Healthy Brain
Patterns of AQP4 channel expression in the brain have previously been shown to change during healthy aging [56]. Work here investigated the association of age with the expression profile of all AQPs in selected brain areas known to be impacted by AD, namely, the hippocampus (HIP), parietal cortex (PCx) and temporal cortex (TCx). In the C and AC groups, a supervised cluster analysis was conducted to probe the relationships between age and AQP baseline expression profiles (Figure 1). Using a mixed-effect linear plot to test for an overall relationship, a significant positive correlation ($p \leq 10$−10) was observed for AQP RNAseq transcript levels as a function of the subject’s age in years (Figure 1a). When segregated by AQP channel subtype, interesting region-specific differences in the age-dependence of expression were evident in the linear regression plots (Figure 1b). AQP1 and 4, previously identified in the human brain, show a significant upward trend of expression in the HIP only as a function of age ($p \leq 0.0001$). AQP5 and 10 gene expression profiles also increased with age in the HIP and PCx, respectively ($p \leq 0.05$), the novel AQP channels not previously identified in the human brain. AQP9 shows an upward trend in expression within the HIP with age but with no significance, rather, a significant downward expression is evident in both cortical regions investigated, PCx and TCx, with age ($p \leq 0.05$).
## 3.3. AQP Expression Profiles in the Hippocampus Differ from Those in Cortex in Healthy Brain
A clear distinction in expression profiles was observed between the HIP cluster and the PCx and TCx clusters, with no difference between cortical regions observed when comparing probes of AQP channel genes within each anatomical region (Figure 2). Two principal components (Figure 2a, component 1 and component 2) were evaluated as a function of all probes used (Supplementary Table S2). The distinction between the observed clusters was defined almost entirely by probes 1059114 (AQP9) and 1032651 (AQP11), suggesting an important role of these two AQPs in driving the differences between anatomical regions (Supplementary Table S4). Subsequently, a differential expression analysis was used to determine the log fold change (logFC) of gene expression within the PCx and TCx regions as compared to the HIP region (Figure 2b). Interestingly, for all AQP probes tested, the PCx and TCx regions showed no difference in expression profiles when compared to each other (Figure 2b,c); in contrast, differences were observed when either cortical region was compared to the HIP (Figure 2b,c). AQP11 probes showed significantly higher logFC values ($p \leq 0.001$; Table 2) in both PCx and TCx when compared to HIP (Figure 2d). Conversely, probes for AQP1, 3, 4, 9 and 10 showed low logFC values in the cortical regions, and higher expression in the HIP (Figure 2d, Table 2). Results here suggest that the diversity of AQP channels present in the human brain is broader than previously reported, and that their levels differ based on the anatomical location, as illustrated here for the HIP and cortical regions.
## 3.4. Age-Dependent Changes in AQP Expression Profiles Differ between the HIP and Cortical Regions in the Healthy Brain
Differences in expression profiles of AQPs detected in the HIP as compared to the PCx and TCx (Figure 2) were investigated for effects of the subject’s age in healthy brains from all ages (C and AC) (Figure 3). A comparison of transcript levels looking at the direction of gene expression change (Figure 3a) between each cortical region and the HIP showed that the logFC values of AQPs 1, 4 and 5 were lower in cortex in AC but not in C groups (Figure 3b,c). Conversely, logFC for AQP10 was lower in both cortical regions as compared to the HIP in the C but not the AC group. Interestingly, the expression profile of AQP9 in the PCx decreased with age, shifting from levels higher than the HIP in the C group to lower than HIP in the AC group (Figure 3b). In the TCx, a similar shift in the pattern of expression of AQP9 was observed, ranging from no difference as compared to the HIP in C to lower levels of expression in AC (Figure 3c). Regardless of age, both cortical regions showed lower levels of AQP3 ($p \leq 0.001$) and higher levels of AQP11 ($p \leq 0.001$) compared to the HIP (Figure 3b,c).
Analyses of the differential expression for AQPs in the parietal cortex versus hippocampus (Table 3) and in the temporal cortex versus hippocampus (Table 4) for both the C (i) and AC (ii) groups showed that most AQP classes (AQPs 0, 2, 6, 7, 8, 12) maintained comparable expression levels across both cortical regions as compared with hippocampus in healthy controls, and did not appear to be affected by age. Regional differences that appeared insensitive to age were observed for AQPs 11 and 3; AQP11 was consistently higher in both PCx and TCx than HIP in both young and aged cohorts, and AQP3 was consistently lower in the cortex than hippocampus across both age groups (Table 3 and Table 4). Regional differences that were sensitive to age were observed for AQPs 1, 4, 5, 9 and 10. In this set, lower levels of transcripts in both cortical regions were observed in the aged but not the young cohorts for AQPs 1, 4, 5, 9. Conversely, AQP10 was lower in the cortical regions than the hippocampus in young cohorts, but there was no difference between regions in the aged cohorts. These data suggest that aging has a notable effect on the expression profiles of several AQPs, but not AQPs 3 and 11 (as highlighted in Figure 3 above). Differences in levels of transcripts between anatomical regions suggest specialized roles or distributions for AQP classes among neuronal and glial cell types, supporting the idea that the levels and patterns of AQP expression also might be sensitive to age-related disease states, such as AD.
## 3.5. Regional Differences in Levels of AQP Transcripts Associated with Probable Alzheimer’s Disease
In the probable Alzheimer’s disease cohort, region-specific subsets of the classes of AQPs showed higher levels that were significantly greater or showed trends towards elevations in the disease group that exceeded the levels observed in aged controls (Figure 4). The AD-associated trends toward augmented levels of transcripts were observed in the temporal cortex for AQP0, in the parietal cortex for AQPs 5 and 10, and in the hippocampus for AQPs 1, 4, 5, 6 and 9 (Figure 4a). The reverse trend in which transcript levels decreased in AD as compared with AC was seen uniquely for AQP7 in the hippocampus.
Another intriguing pattern that emerged from this analysis was for AQP9, with levels high in young controls, substantially reduced in both AC and AD cohorts for both cortical regions, and conversely elevated with age in the hippocampus (Figure 4a). There were no changes in AQP3 or AQP11 levels in AD as compared to AC and C groups within regions, although differences between regions were observed. AQP3 was predominantly in the HIP with little cortical expression. Conversely, AQP11 levels were high in both cortical regions but minimal in the HIP. Consistent baseline levels of expression of AQPs 3 and 11 suggest that aquaglyceroporin function in the hippocampus and peroxiporin activity in the cortex are ongoing mechanisms of metabolism and homeostasis. With the notable exception of reduced cortical AQP9, the expression profiles for AQP channels increased during natural aging, a process that in a subset of AQP classes appeared to be amplified by AD pathology.
A limitation of this study was the low n values available for human samples; the transcript levels for AQPs 0, 6, 8 and 10 showed increases that only reached statistical significance in the AD group when compared to the C group (Figure 4a). For example, in HIP, the AQP6 transcript was increased in the AD as compared to the C group ($p \leq 0.05$); AQPs 0 and 8 expression levels were higher in the TCx of AD patients than C patients ($p \leq 0.05$); and AQP10 expression was increased in AD patients in the PCx ($p \leq 0.001$; Figure 4a) as compared to the young control group. However, it is important to note that when directly comparing AD to age-matched AC groups, there were no significant differences in transcript levels for any classes of AQPs.
Nonetheless, potentially informative patterns of increased AQP levels in AD were apparent for specific classes, as observed from data compiled as plots of average logFC values for the AD cohort versus the AC group (Figure 4b) in each of the three brain regions. In this analysis, identical levels of expression produce a theoretical line with a slope of 1.0. AQPs with levels higher in AD than AC are reflected by points above the line. For example, in the HIP, the average trend points of AQPs 5, 6, 9 and 11 fell above the line. In the PCx, AQPs 0, 3, 7, 9 and 11 were higher in the AD cohort. In the TCx, AQPs 0, 1, 7 and 11 were higher in the AD versus the AC cohorts (Figure 4b). While not definitive, these results offer testable predictions for ongoing work aimed at gaging the potential importance of the variety of CNS-expressed AQP channels (such as AQPs 0, 7 and 11 in cortex) as targets of interest for understanding healthy functioning, as well as processes of neuropathology.
## 4. Discussion
We have discovered a surprising diversity of AQP channels in the CNS, confirming seven known classes of AQPs, and showing that three additional classes—AQPs 0, 6, and 10—are present in the human brain at the transcript level. Prior work defined three classes of AQP channels, establishing AQPs 1, 4 and 9 as the primary subtypes expressed in the mammalian brain in both physiological and pathological conditions [30,33,42]. Less well investigated RNA signals for other AQPs such as AQPs 3, 5, 8 and 11 also have been detected in the brain in vivo [47,48], though possible functions remain to be defined. Work here using data harvested from the Allen Brain Atlas explored the expression profiles of all classes of AQPs (AQPs 0–12) in the human brain, and investigated whether their expression patterns were affected in healthy aging and AD. We identified novel RNAseq signals for AQPs 0, 3, 5, 6, 7, 8, 10 and 11 in the human brain in hippocampal and cortical regions known to be impacted by Alzheimer’s disease. Of these channels, peroxiporins AQPs 0, 6 and 8 [21,23,24] (which are permeable to H2O2) and the aquaglyceroporin AQP10 (permeable to glycerol) were expressed at higher levels in AD as compared to young controls.
The major advance reported in this study is the demonstration that AQP channels shown previously to be permeable to H2O2 (termed ‘peroxiporins’) show subtype-specific patterns of expression in the human brain that vary as a function of age, neuroanatomical region, and Alzheimer’s disease status. Oxidative stress levels are known to increase during aging [57], resulting in increases in reactive oxygen species by-products, such as H2O2. H2O2 levels are further elevated in AD as compared to healthy aging brains and are thought to potentiate mitochondrial dysfunction and disease pathology by promoting Aβ-induced neurotoxicity and pathological tau modifications [58,59,60]. The second outcome of interest here is the finding that multiple classes of aquaglyceroporins are differentially regulated with respect to brain age and disease status.
In the hippocampus in particular, a subset of the AQP classes (AQPs 1, 4, 5 and 9) showed strong increases with age, with or without AD. Additionally, in the hippocampus, AQP6 was increased in AD, and AQP7 showed higher levels with age. AQPs 7, 9 and 10 are aquaglyceroporins (discussed in more detail below). AQP1 has been shown to function as a perioxiporin in cardiac ventricular muscle cells [61]. Healthy aging previously was reported to correlate with the increased expression and localization of AQP4 in astrocytes [62]. AQP4, as do most members of the broad family, functions as a water channel but was not found to mediate H2O2 permeability when tested in the yeast expression system [63]; however, it is worth noting that AQP1 tested in the same assay similarly but did not enable detectable H2O2 fluxes, though this functionality was subsequently confirmed in mammalian heart cells [61]. AQP5 shows peroxiporin activity in the eye [21]. Three classes of AQPs that showed increased levels in brain regions only in the presence of Alzheimer’s disease (AQPs 0, 6, 8) also are known to function as peroxiporins [21,23,24]. AQP0 has been characterized as an intrinsic membrane protein uniquely expressed in the eye lens and has been shown to facilitate transmembrane fluxes of H2O2 [21,64]. AQP0 expression in the brain is a novel finding. In the hippocampus, AQP6, which has been characterised as a peroxiporin in malignant pleural mesothelioma [23], also was higher in the AD cohort. AQP8, a pancreatic β-cell peroxiporin, similarly was detected at high levels in the TCx of AD patients. AQP11 showed a unique pattern in being expressed at higher levels in the cortex than in the hippocampus. AQP11 has been characterized as a peroxiporin in endoplasmic reticulum that mitigates H2O2-induced stress in the kidney proximal tubule cells [25]. The demonstration here of the AQP11 expression in the cortex and hippocampus, coupled with prior work confirming the AQP11 RNA expression in the cerebellum of mice [48], suggests that AQP11 might also be involved throughout the brain as one of the mechanisms involved in decreasing oxidative stress.
Aquaglyceroporins that increased with age included AQPs 7 and 9 in the hippocampus, prompting the idea that an increased expression could be an adaptive response to altered metabolic demands [65]. In the parietal and temporal cortices, the changes in AQP expression with age were more subtle, ranging from no appreciable change to increased levels with age, with the exception of AQP9 which conversely showed strong decreases in the Ptx and Ctx regions of aged brains. Neuronal ATP production is thought to decline with aging [66], leading to a hypometabolic state [67] which might be offset in part by enhancing the glycerol uptake to boost pyruvate production and ATP synthesis [68]. AQP9 in astrocytes is known to facilitate glycerol shuttling from astrocytes to neurons for energy support [45,69]. Data here suggest that AQP9, while increased in HIP, might be less likely to be a candidate for compensatory mechanisms in the cortex given the striking decrease in transcript levels observed in the cortical regions for both the AC and AD cohorts. In contrast, the aquaglyceroporin AQP10 [70] was increased in the PCx of AD patients. AQP10 has been demonstrated previously to mediate the pH-sensitive transport of glycerol in adipose cells and enterocytes [70], and could serve a comparable role in the brain. Differences in the gating mechanisms between aquaglyceroporin classes might influence which subtypes are selectively upregulated to meet different brain region demands. The disease-specific increases in expression in certain AQP subtypes, which are statistically significant as compared to young controls, support a proposed association with neuropathological disease.
An intriguing concept which we propose merits further study is that specific classes of peroxiporins might be upregulated as a protective mechanism to shuttle excess H2O2 and alleviate stress. The regional influences governing AQP expression patterns remain to be determined, but could reflect heterogeneity in neuronal and glial subtypes, differences in neuronal activity and metabolic demands or other factors. A single-cell RNAseq study in C57BL/6J mice by Batiuk and colleagues [2020] showed that astrocyte populations from the hippocampus of mice, unlike cortical regions, contained large numbers of progenitor astrocytic stem cells (AST4) as well as mature astrocytes (AST1) [71]. The AQP expression in specific astrocyte subpopulations such as those in the hippocampus [32,38] could explain in part the observed regional specialization of AQP expression patterns. Reactive astrocytes accumulate in regions of damage, including those affected in age-related cognitive decline, resulting in hypertrophy and cellular volume increases [72] which might be linked to AQP expression [73]. AQP1 and 4 expression levels are increased in astrocytes during the early pathology stage of AD [36,37]. With the continued expansion of the Allen Brain Atlas database, future work will benefit from comparing the transcript levels of AQPs between Alzheimer’s disease and age-matched controls.
The limitations of this work are the modest n values available for human brain RNAseq data, which likely contributed to the lack of significant differences in expression profiles between the AD and the AC cohorts (though trends towards increased RNAseq levels were apparent in the disease group), and that age-dependent effects on the AQP expression are likely to overlap with the disease pathology. Another important limitation that might have influenced the absence of statistically significant differences between the AD and AC groups was the low representation of female donors in the AD group ($$n = 3$$) as compared to AC ($$n = 11$$). The risk for the development and progression of AD in females on average is higher than males but depends on estrogen levels [74]; a re-analysis of the AD and AC groups segregated by gender and hormone therapy status might reveal important correlations with AQP expression profiles that merit exploration when expanded database information becomes available. An additional limitation is the need to confirm AQP expression at the protein level, to determine whether the expression profile changes determined by transcript analyses are reflected by changes at the protein level. Probing the functionality of the proteins then will be an essential next step towards identifying possible novel targets for therapeutic interventions in AD.
It will be of interest to determine whether the trends towards similar responses observed here for AC and AD (which did not reach statistical significance) reflect processes of natural aging effects on AQP expression levels that are similar or amplified in the disease state. Histological analyses of human AD sections from the hippocampus have shown that the AQP1 expression appears to be localized in multipolar fibrillary astrocytes surrounding neurons, whereas AQP4 expression appears to be more diffusely distributed in astrocytes [34], suggesting that some of the spatiotemporal changes in AQP expression noted here might reflect changes in the regional status of astrocyte populations. It is important to consider that AQP up- or downregulation responses might be relevant to nervous system protection rather than being involved in driving the pathology, and levels of transcripts do not necessarily correspond directly to levels of functional protein in cell membranes. However, our data suggest that changes in AQP levels could be a response to natural processes of aging and mechanisms of either protection or pathology in neurodegenerative disease.
The patterns of AQP regulation in AD are novel and subtype-specific. The three established classes of brain AQPs described previously in normal physiological conditions, AQPs 1, 4 and 9, are associated with age, but data here suggest that these subtypes alone might not be sufficient to mediate responses to augmented pathological stressors. Our findings suggest that a diverse array of peroxiporin and aquaglyceroporin subtypes could be relevant to the processes of brain aging and disease. The results here are the first to show that AQPs 0, 6, 8 and 10 are expressed in the brain and increased with AD or age. Corresponding changes in protein levels and patterns of localization in neurons and glia remain to be defined and are a focus of work in progress. The exciting discovery of previously undetected classes of peroxiporins and additional aquaglyceroporins in the human brain compels further research on their potential roles in aging and AD-related diseases. Understanding the roles of an expanding array of identified brain peroxiporins and aquaglyceroporins in the brain is needed for uncovering homeostatic mechanisms that enable healthy aging and protection from damage, or compromise brain function in Alzheimer’s and other neuropathological diseases.
## 5. Conclusions
The major outcome of this study was the discovery that the pattern of AQP expression in the brain is more diverse than previously reported, with possible relevance to processes of healthy aging and AD. The further exploration of the expression and function of aquaglyceroporins, and in particular, peroxiporins, in neurological diseases is an area of ongoing research interest. Identifying the sub-cellular localization of AQP channels could provide critical insights into their potential roles in AD pathophysiology. AQPs are of interest as novel therapeutic targets for the treatment of not just AD, but potentially other neurodegenerative diseases that might similarly rely on changes in the expression profiles of peroxiporins as components of homeostatic responses to age and disease-related stressors.
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|
---
title: Designing Effective Multi-Target Drugs and Identifying Biomarkers in Recurrent
Pregnancy Loss (RPL) Using In Vivo, In Vitro, and In Silico Approaches
authors:
- Andrés Alexis Ramírez-Coronel
- Amirabbas Rostami
- Laith A. Younus
- José Luis Arias Gonzáles
- Methaq Hadi Lafta
- Ali H. Amin
- Mohammed Abdulkadhim Saadoon
- Hayder Mahmood Salman
- Abolfazl Bahrami
- Rossa Feilei
- Reza Akhavan-Sigari
journal: Biomedicines
year: 2023
pmcid: PMC10045586
doi: 10.3390/biomedicines11030879
license: CC BY 4.0
---
# Designing Effective Multi-Target Drugs and Identifying Biomarkers in Recurrent Pregnancy Loss (RPL) Using In Vivo, In Vitro, and In Silico Approaches
## Abstract
Recurrent pregnancy loss (RPL) occurs in approximately $5\%$ of women. Despite an abundance of evidence, the molecular mechanism of RPL’s pathology remains unclear. Here, we report the protective role of polo-like kinase 1 (PLK1) during RPL. We aimed to construct an RPL network utilizing GEO datasets and identified hub high-traffic genes. We also investigated whether the expressions of PLK1 were altered in the chorionic villi collected from women with RPL compared to those from healthy early pregnant women. Gene expression differences were evaluated using both pathway and gene ontology (GO) analyses. The identified genes were validated using in vivo and in vitro models. Mice with PLK1-overexpression and PLK1-knockdown in vitro models were produced by transfecting certain plasmids and si-RNA, respectively. The apoptosis in the chorionic villi, mitochondrial function, and NF-κB signaling activity was evaluated. To suppress the activation of PLK1, the PLK1 inhibitor BI2536 was administered. The HTR-8/SVneo and JEG-3 cell lines were chosen to establish an RPL model in vitro. The NF-κB signaling, Foxo signaling, PI3K/AKT, and endometrial cancer signaling pathways were identified via the RPL regulatory network. The following genes were identified: PLK1 as hub high-traffic gene and MMP2, MMP9, BAX, MFN1, MFN2, FOXO1, OPA1, COX15, BCL2, DRP1, FIS1, TRAF2, and TOP2A. Clinical samples were examined, and the results demonstrated that RPL patients had tissues with decreased PLK1 expression in comparison to women with normal pregnancies ($p \leq 0.01$). In vitro, PLK1 knockdown induced the NF-κB signaling pathway and apoptosis activation while decreasing cell invasion, migration, and proliferation ($p \leq 0.05$). Furthermore, the in vivo model proved that cell mitochondrial function and chorionic villi development are both hampered by PLK1 suppression. Our findings revealed that the PLK1/TRAF2/NF-κB axis plays a crucial role in RPL-induced chorionic villi dysfunction by regulating mitochondrial dynamics and apoptosis and might be a potential therapeutic target in the clinic.
## 1. Introduction
Recurrent pregnancy loss (RPL) is the term used to describe spontaneous abortions that occur three times or more in a row before 20 weeks of pregnancy and includes embryonic or fetal loss; it is a frequently occurring human infertility-related disease that affects 1–$5\%$ of parturients [1]. Various factors have been proven to cause the occurrence and development of RPL, including chromosomal abnormalities, genital tract anomalies, immunological diseases, endocrine diseases, antiphospholipid syndrome, thrombophilic disorders, and pathogen infections [2]. Approximately 40–$50\%$ of cases remain unexplained, and the molecular mechanisms have not been fully explored. These cases are defined as unexplained recurrent pregnancy loss [3]. Although the diagnosis of RPL is relatively clear, the lack of standardized definitions, the uncertainties of its pathogenesis, and the variable clinical manifestations still hamper progress in the treatment and prevention of RPL [4]. The different occurrences that construct the complex gestation process include parturition, placentation, decidualization, and implantation [5]. As well, molecular and physiological processes must support a relationship between a receptive uterus and the implantation of the embryo. The hierarchical process of embryo implantation necessitates fundamental techniques including apposition, adhesion, attachment, and penetration, in which villous trophoblasts and high-quality embryos play a crucial role. During embryo implantation, extravillous trophoblasts (EVTs) of the decidua basalis originating from trophoblastic cell columns of anchoring villi invade the maternal uterine decidua, up to the inner third of the myometrium. This process, i.e., invasion of EVTs, facilitates the attachment of the placenta to the uterus (interstitial invasion) to provide nutrients to the embryo from the placenta [6]. Consequently, trophoblasts are essential for a healthy pregnancy because they are the placenta’s precursor cells. Recent research has shown that aberrant spiral artery remodeling and shallow placentation may both contribute to dysfunctional trophoblast functions that are ultimately linked to poor pregnancy outcomes such as stillbirth and abortion.
Moreover, recurrent pregnancy loss involves a cascade of physiological reactions as well as the activation of numerous signaling pathways, and the NF-κB (nuclear factor-κB) pathway is a crucial pathway. Although, the NF-κB pathway’s function in different biological processes is debatable; on the one hand, it can promote host defense and other protective cellular responses, while on the other, its activation contributes to inflammatory harm in tissues [7]. It is not unexpected that the NF-κB pathway impacts mitochondrial function and architecture as the NF-κB pathway serves as a transcription factor of the oxidative stress reaction [8]. However, additional research should be carried out on the NF-κB precise function in the fusion and fission of mitochondria in the epithelium during pregnancy.
The well-known mitotic regulator polo-like kinase 1 (PLK1) participates in G2/M transition, DNA integrity maintenance, and the overexpression maturation of various organelles [9,10,11]. It has been shown that PLK1 inhibits NF-κB nuclear activation, but the related mechanism is unexplored. One of the upstream regulators of NF-κB signaling is the TRAF (*Tumor necrosis* factor receptor-associated factor) family proteins such as TRAF2. A previous investigation showed that PLK1 and TRAF2 interact in HEK293 cells [12]. However, the biological role of PLK1 in trophoblasts and consequently in the occurrence and progression of RPL remains unclear.
Furthermore, omics studies generate a large amount of information concerning the biomarkers, molecular mechanisms, and biological pathways involved in complex diseases [13]. More recently, due to advances in the development and optimization of high-throughput techniques, numerous studies have applied omics approaches to the study of RPL [14,15,16,17]. Therefore, in the present study, we aimed to construct an RPL regulatory network and investigate whether PLK1 as a hub high-traffic gene or protein induces a change in trophoblast functions in terms of proliferation, migration, invasion, and apoptosis and further contributes to RPL via the TRAF2/NF-κB axis. Additionally, we investigated whether PLK1 has an impact on early embryo growth and quality, affecting implantation and ultimately leading to RPL, using mouse pre-implantation embryos.
## 2.1. Data Mining and Identification of Genes Expression
RPL-related mRNA data of patient tissues and normal tissues were integrated from RNA from RNA-seq data expression datasets. In addition, the RNA-seq data were separately collected from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/ (accessed on 14 Jul 2022)), and the three gene expression profiles (GSE180485 [13], GSE161969 [18], and GSE65102 [19]) were selected with the GPL11154 platform.
Then, the raw sequences quality was assessed utilizing FastQC (v. 0.11.11); then, these reads were trimmed employing Trimmomatic (v.0.39.2) to exclude the polymerase chain reaction (PCR) primers, low-quality reads, and adapters [20]; HISAT2 (v. 2.2.2) was utilized to map the trimmed reads to the reference genome of Homo sapiens [21]. Utilizing the DESeq2 program (v. 2.11.41) [22], variations in transcript expression were then discovered. The threshold of statistical difference for mRNA/gene expression was set using the parameters of logFC (|log2(FC)| > 1.5) and false discovery rate (FDR) < 0.05. A total of 143 samples from RPL groups and healthy controls were included in these datasets.
## 2.2. Recurrent Pregnancy Loss Regulatory Network Construction and Module Finding
Construction of the recurrent pregnancy loss regulatory network was performed utilizing different databases. This network was combined with BIND, PPI, and BioGRID databases [23]. Interaction data were also detected by seeking in interaction databases including the STRING (https://string-db.org/ (accessed on 25 July 2022)) and GeneMANIA (https://genemania.org/ (accessed on 25 July 2022)) databases. The PPI network was shown using the Cytoscape program (v. 3.7.2), and the hub genes were screened using Cytoscape’s “degree” value in the “cytohubba” plugin [24]. A module-screening technique that was contrasted was molecular complex detection (MCODE) [25]. The network entropies were determined to counteract the selective speculation [26].
## 2.3. Functional Enrichment Analyses
Applying the “ClueGO” package in R with a cut-off condition of the adjusted p-value less than 0.05, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and GO (gene ontology) analyses were conducted [27]. Additionally, the Enrichr database was operated to conduct Wiki pathways of common host variables. The The Database for Annotation, Visualization and Integrated Discovery (DAVID) [28], g: Profiler (https://biit.cs.ut.ee/gprofiler/ (accessed on 10 August 2022)) [29], and GeneCards (www.genecards.org/ (accessed on 10 August 2022)) databases were utilized to investigate the pathways.
## 2.4. Samples Collection
Samples were collected from consenting participants from the Gynecology and Obstetrics Department of the King Faisal Hospital. The present study was reviewed and preapproved by the Ethics Committee of King Faisal Medical University (Approval number: PU-2021–11513, 29 June 2021) and all participants provided written informed consent. The control group included villi of the placenta taken from 26 healthy women between the ages of 19 and 40 who had already had one or more children but who choose to end their pregnancies on non-pathological bases. None of these ladies had ever previously experienced an abortion, a pre-term birth, or a stillbirth. The RPL group, on the other hand, consisted of fifteen patients between the ages of 19 and 40 who had gone through at least two consecutive first-trimester losses with an unknown cause between 2021 and 2022. This study excluded participants who had recognized risk factors for RPL, such as uterine deformity, hormone issues, significant chromosomal abnormalities, and infections. Supplementary Table S1 provides a complete list of the study participants’ characteristics. In the current investigation, samples of villous were acquired using a suction technique that was carried out following routine strategies. Following dilatation and curettage, fresh villi tissues that were free of bleeding and calcification zones were collected within 10 min, stored on ice, and brought right away to the lab. Each sample was divided into smaller pieces, each of which was then dehydrated operating an ethanol solutions gradient before being ingrained in paraffin. The samples were immediately transferred to a nitrogen tank and kept at −196 °C.
## 2.5. RNA-Seq Validation
To obtain total RNA, a GenElute RNA Extraction Kit (Sigma, St. Louis, MO, USA) was used. Evo M-MLV Mix Kits were used to create single-stranded complementary DNA from whole RNA (Qiagen; Hilden; Germany). Utilizing SYBR green premix pro-Taq qPCR Kits, real-time PCR was carried out (Qiagen; Hilden; Germany). The following step involved doing quantitative reverse transcription PCR for five genes, including TRAF2, PLK1, OPA1, FIS1, MFN1, and DRP1. The PCR cycling conditions employed were as follows: 30 s at 95 degrees, as well as 40 cycles of 5 s each at 95 and 60 degrees. Finally, the relative expression of gene levels was normalized to the expression of GAPDH. The forward and backward sequence of primers and related genes ID are presented in Supplementary Table S2.
## 2.6. Immunohistochemistry
Villi tissue was embedded in paraffin, fixed in paraformaldehyde $4\%$, and then cut into 6 m pieces. Next, for antigen retrieval, rehydration, and deparaffinization, goat serum was used to prevent nonspecific sections. Antigen retrieval was then conducted following a pre-treatment in 12 mM sodium salts of citric that was microwaved for 15 min. Following that, $2\%$ H2O2 was utilized to inhibit endogenous peroxidase. The slides were then exposed to an anti-PLK1 (1:500, Cambridge, UK) antibody for overnight incubation at 4 °C, followed by an appropriate biotin-conjugated secondary antibody. An Olympus optical microscope was used to image the slides’ complete field of view (Olympus, Tokyo, Japan).
## 2.7. Western Blotting
The villi tissue samples were isolated and a protein extraction kit (Beyotime Biotechnology, Shanghai, China) was used to extract whole proteins. Extracted proteins were rinsed with phosphate-buffered saline (PBS) and lysed with phosphatase/protease inhibitor cocktails. The protein concentrations were quantified by a BCA protein assay kit (Beyotime Biotechnology, Shanghai, China). The whole proteins were boiled and isolated in $12\%$ SDS-PAGE and disseminated to polyvinylidene difluoride membranes and incubated at 4 °C utilizing antibodies PLK1 (1:1000; Cambridge, UK), OPA1 (1:500; Cambridge, UK), DRP1 (1:500; Cambridge, UK), MFN1 (1:500; Cambridge, UK), FIS1 (1:500; Cambridge, UK), TRAF2 (1:500; Cambridge, UK), NF-κB (1:500; Cambridge, UK), Foxo1 (1:500, Cambridge, UK), CDK6 (1:1000, Cambridge, UK), CycilneD1 (1:500, Cambridge, UK), and actin (1:2000; Cambridge, UK). Finally, the signals were detected by a digital imaging set, and ImageJ v. 2.1.0 was used to quantify the protein bands.
## 2.8. Cell Culture
The immortalized human EVT cell line HTR-8/SVneo and the human choriocarcinoma cell line JEG-3 were provided by Zhou Chen from State Key Laboratory. DMEM/F-12 and RPMI (Gibco, Waltham, MA, USA) were used to culture HTR-8/SVneo and JEG-3, respectively, supplemented with $12\%$ fetal bovine serum (FBS). Furthermore, the human umbilical vein endothelial cell line Huvec was obtained from Shanghai Cell Bank (Beyotime Biotechnology, Shanghai, China) and cultured in a DMEM medium. All cells were cultured in a humidified atmosphere with $5\%$ CO2 at 37 °C.
## 2.9. 5-Ethynyl-2′-deoxyuridine (EdU) and Terminal Deoxynucleotidyl Transferase dUTP Nick end Labeling (TUNEL) Assay
To assess the replication of DNA and cell proliferation, the EdU assay kits (RiboBio, Guangzhou, China) were utilized. The cell under logarithmic growth was seeded into 48-well plates (0.4 × 104) and cultivated with F-12/DMEM medium including $12\%$ FBS for 36 h. Then, $4\%$ formaldehyde-disposed cells gained fixation with further penetrations in $0.4\%$ TritonX-200 for 15 min at 27 °C. Consequently, treated cells were dyed with the Hoechst and EdU based on instructions from the manufacturer. A TUNEL assay kit was utilized for assessing cell apoptosis. Referring to the instructions, the differentially processed cells were implanted in a 6-well plate with the same density. After 24 h, the plates experienced washing, fixation, permeation, and incubation. Ultimately, images were captured by a fluorescence microscope.
## 2.10. Flow Cytometry
About the samples applied to detect apoptosis, we dealt with the following processes. First, a 15 mL centrifugal tube containing the entire medium was collected and digested with $0.25\%$ trypsin. The cells were treated with the subsequent well combination and centrifuged at 2000 revolutions per minute for five minutes. The supernatant was discarded and replaced using brand-new precooled PBS. These actions were carried out twice. The cell pellet was consequently broken in 1000 mL of PBS. The sole difference in terms of studying the cell cycle was that 500 mL of iced $75\%$ ethanol was used to resuspend the cell pellet. A flow cytometer (CytoFLEX, eBioscience, San Diego, CA, USA) was employed following the manufacturer’s recommendations to evaluate the indications of cell apoptosis and cycles.
## 2.11. Wound-Healing Assay
To evaluate the migratory capabilities of human trophoblast cells, wound healing experiments were used. In a nutshell, JEG-3 cells that had been transfected were plated in 6-well dishes and grown till $95\%$ confluent. Then, a 12 mL pipette tip was utilized to design a wound on the monolayer of the cell. A fresh medium including $2\%$ fetal bovine serum was added to the wells after gently washing each well twice with PBS. A camera mounted on a light microscope was used to record the wound widths at 0 h, 12 h, 24 h, 36 h, and 48 h. To analyze the data, Image J was used (Version 1.46r).
## 2.12. Transwell Assay
A 1.5 mg/mL Matrigel was applied to the upper partition of the transwell with 10 m pores, and it was incubated for 5 h at 37 °C (BD Biosciences, Franklin Lakes, NJ, USA). After seeding transfected JEG-3 cells in 200 L of serum-free DMEM/F12 media, the lower section was loaded with 650 L of DMEM/F12 medium including $12\%$ fresh FBS. After 36 h of incubation in $5\%$ CO2 conditions at 37 °C, invasive cells were confirmed to have entered the matrix, whereas cells with the ability to migrate crossed over to the side of the membrane that was facing the lower chamber. Paraformaldehyde $4\%$ was utilized to fix invading cells and $0.1\%$ crystal violet (Beyotime Biotechnology, Shanghai, China) was utilized to stain them. The invasive cells were seen under a microscope (ZEISS, Aalen, Germany).
## 2.13. Plasmid Transfection
Either the control vector or the PLK1 overexpression plasmid was transfected into the cells of HTR-8/SVeo. HTR-8/SVeo cells were planted in 12-well plates one day prior to transfection. One hour prior to obtaining 60–$70\%$ cell confluency, the preceding medium was changed to 900 mL of new media containing $12\%$ FBS. Before being put into the 12-well plate, the previously described PolyJet and plasmids were blended with serum-free media (SignaGen, Frederick, MD, USA). The medium was switched out for a new medium after 10 h. For use in subsequent investigations, proteins or genes were extracted after two days.
## 2.14. Lentivirus Infection
Genechem provided lentiviruses containing human PLK1 short hairpin RNA coding sequences (Shanghai, China). The short small interfering RNA (siRNA) targeting PLK1 had the sequence 5′-GAACUAUGAGCAGAGAAUATT-3′. The infection index of the lentivirus was found to be 60 in early trials. According to the manufacturer’s recommendations, lentivirus transfection was performed on JEG-3 cells when they were 30–$40\%$ confluent. To find stable clones of transfected cells after two days, the transfected cells were cultured in 3 g/mL puromycin for a week. After that, cells were collected for Western blotting and other experiments.
## 2.15. Animal Preparation and RPL Model
The Ethics Committee and Animal Care Institution of King Faisal Specialist Medical University authorized all of the experimental protocols. All of the mice were maintained in a specified pathogen-free (SPF) room with a 12 h dark/light cycle, regular rodent food, and water access. A total of 27 7–9-week-old mice were superovulated by a pregnant mare of 12 IU gonadotropin intraperitoneally and then 12 IU hCG 40–50 h subsequently. After that, sex-ready male mice and female mice were kept in a cage at a balance of 1:2. Mice wearing vaginal pins were regarded as having given birth 0.5 days earlier. These mice were slaughtered and related tissues were removed at 8:00 each time 1.5 days after pregnancy. The samples were delivered right away to the lab. Using a stereo microscope to divide the fallopian tubes, two-cell phase embryos were harvested. In addition, these embryos were grown in a proportional M16 medium at 37 °C with $5\%$ CO2 after being washed in phosphate-buffered saline with $1\%$ bovine serum albumin (Sigma, St. Louis, MO, USA). At the two-cell phase, the embryos were processed using the PLK1 inhibitor BI2536 (Beyotime Biotechnology, Shanghai, China). The pre-implantation developmental rate was calculated at the four-cell stage.
## 2.16. Immunofluorescence Staining of Embryos
After being fixed in $5\%$ paraformaldehyde for 30 min, the processed embryos were permeabilized in phosphate-buffered saline including $0.6\%$ Triton X-200 for 15 min at 25 °C. To prevent nonspecific binding, the embryos were put into microdroplets including $10\%$ bovine serum albumin for two hours at 25 °C. After treatment with the primary antibody the next day, the embryos were flushed in $2\%$ bovine serum albumin before being treated for two hours with the complementary secondary antibody. Then, the nuclei were dyed with Hoechst for 45 min. After that, confocal microscopy was used to take several pictures. The intensity of the fluorescence was measured with Image J.
## 2.17. Mitochondrial Superoxide Measuring
Utilizing MitoSox Red (Carlsbad, CA, USA), which was liquefied in a 1:1 combination of M16 and dimethylsulfoxide to a definitive concentration of 5 M, four-cell stage embryos were examined to identify the superoxide production in the mitochondria of the embryo. Embryos completed receiving the MitoSox intrathecal injection about 40 min later. Hoechst was then used to stain for 30 min in complete darkness. A confocal laser scan microscope was used to survey the red fluorescence at $\frac{510}{580}$ nm. reactive oxygen species (ROS) levels were assessed by the intensity of fluorescence.
## 2.18. Potential of Mitochondrial Membrane Determination
A lipophilic cationic dye called JC-1 was able to enter the mitochondrial matrix while the membrane of the mitochondria became polarized. The dye may traverse the membrane and aggregate into J-aggregates, which may emerge red when exposed to Ultraviolet light if the mitochondrion has membrane potentials (m). When low m is present, the dye maintains its monomeric state, and the fluorescence shows green. Fluorescence microscopy makes it simple to examine the various distributions of red and green, and ratio labeling of red-to-green is utilized to evaluate the mitochondrial membrane potential in mouse embryos. The embryos were then incubated for 25 min with Hoechst (Beyotime Biotechnology, Shanghai, China), flushed with $1\%$ BSA, and seen using a confocal microscope. To assess statistically sound data, the fluorescence intensities were documented, and three separate tests were carried out.
## 2.19. Statistical Analysis
Prism v.8.0 (GraphPad Software Inc, San Diego, CA, USA) and SPSS 23.0 were used for creating the graphs and for the analysis of data. Quantitative data are presented as the mean ± SEM, and the data were statistically evaluated using Student’s t-tests. A value of $p \leq 0.05$ was considered statistically significant.
## 3.1. RPL Regulatory Network Construction and Hub High Traffic Genes Detection
A regulatory network containing 8829 edges and 1557 genes was created. Regulatory interactions between several genes are listed in Supplementary Table S3. With the help of MCODE’s comprehensive clustering, we detected a core module with 409 edges and 61 genes (Supplementary Table S4).
We identified 14 genes (PLK1 as a hub high-traffic gene and MMP2, MMP9, BAX, MFN1, MFN2, OPA1, COX15, FOXO1, BCL2, DRP1, FIS1, TRAF2, and TOP2A) in RPL regulatory network.
## 3.2. Pathway Enrichment Analysis
Forty-three pathways were identified in the RPL regulatory network, according to the findings (Figure 1). The NF-κB signaling, FOXO signaling, PI3K/AKT pathway, and endometrial cancer pathway were shown to be the most significant pathways in the RPL regulatory network.
## 3.3. Biological Processes and Protein Expression
Western blot examination was operated to assess the protein expression of PLK1, OPA1, MFN1, and DRP1 from healthy individuals and patients (Figure 2A). Similar results were also seen in the qRT-PCR analysis’ output (Figure 2B). Immunohistochemistry examination showed that PLK1 was localized in the villi nucleoplasm and that PLK1 expression was significantly increased in the healthy group ($p \leq 0.01$) (Figure 2C).
## 3.4. PLK1 as Hub High Traffic Gene Exerts Positive Effect on the Cell Differentiation
Following the findings of qRT-PCR analysis ($p \leq 0.01$), WB analysis indicated that the PLK1 expression in the villi tissue of RPL patients dropped by $76\%$ when compared to the normal group (Figure 2A,B). Collectively, these results indicated that PLK1 is expressed in the villi and that PLK1 expression is decreased in patients with RPL in comparison with that in the healthy group.
## 3.5. In Trophoblasts, PLK1 Knockdown Decreases Proliferation and Increases Apoptosis
We examined the expression of PLK1 in four trophoblast cell lines including BeWo, JAR, HTR8/SVneo, and JEG-3. PLK1 expression was high in JEG-3 cells and low in HTR8/Svneo cells. Hence, we selected these two cell lines as in vitro models to further explore the role of PLK1 in trophoblast functions. si-RNA targeting PLK1 and a PLK1-overexpression plasmid were transfected into to JEG-3 and Htr8 cells, respectively, to generate PLK1 knockdown (si-PLK1) and PLK1-overexpression (OE-PLK1) cells. The efficiency of knockdown and overexpression was verified by qRT-PCR and Western blot (WB) ($p \leq 0.05$) (Figure 3A). WB analysis indicated that PLK1 expression in the si-PLK1 group decreased by $93\%$ compared with that in the si-NC group ($p \leq 0.01$), which was consistent with the qRT-PCR analysis (FC = 0.631) ($p \leq 0.05$). Additionally, PLK1 protein levels in Htr8 cells in the OE-PLK1 group were 1.3 times higher than that in the vector group, which was consistent with the results of the qRT-PCR (FC = 1.31) ($p \leq 0.05$). In terms of proliferation, EdU, a thymidine analog that is incorporated into DNA during its synthesis, was used to assess cell proliferation. PLK1 knockdown considerably reduced the proportion of EdU-labelled cells, suggesting downregulation of cell proliferation. The expression of TRAF2 increased in si-PLK1 JEG-3 cells ($p \leq 0.05$), while it decreased in OE-PLK1 HTR8/Svneo cells ($p \leq 0.01$) (Figure 3B). Furthermore, the apoptosis ratio was also assessed with flow cytometry; overexpression of PLK1 reduced the apoptosis ratio compared to that in vector-transfected cells ($p \leq 0.01$), whereas the opposite was observed in the si-PLK1 group ($p \leq 0.01$) (Figure 3C,D). Fluorescence intensities in the TUNEL assay also supported these findings (Figure 3E).
## 3.6. PLK1 Promotes Trophoblasts’ G1-S Transition
We performed flow cytometry to analyze the effect of dysregulated PLK1 expression in the cell cycle (Figure 4A,B). Overexpression of PLK1 in Htr8 cells resulted in a significant increase in the percentage of cells in the S phase ($p \leq 0.05$), hereas downregulation of PLK1 in JEG-3 cells resulted in the G1 phase ($p \leq 0.001$). As for the G2 phase, no difference was observed in the PLK1 knockdown or plasmid-transfected groups.
## 3.7. Plk1 Stimulates Trophoblast Migration and Invasion
Further research was conducted to specify whether PLK1 can affect the invasion and migration of JEG-3 cells using wound healing and transwell assays. As seen in Figure 5A, there were significantly fewer invaded and migrating cells in the si-PLK1 group relative to the si-NC group ($p \leq 0.01$). Real-time PCR and Western blots were used to analyze PLK1’s impact on invasion potential. When compared to the si-NC group, the MMP-9 and MMP-2 expression, which stimulates invasion, was decreased in the si-PLK1 group ($p \leq 0.001$) (Figure 5B). PLK1 was found to have a favorable impact on invasion and migration as a result. Collectively, these findings suggest that a lack of PLK1 might cause early placental implantation, which would contribute to RPL to a certain extent.
## 3.8. PLK1 Stimulates the Trophoblast Cell Cycle and Proliferation
To further investigate whether PLK1 mediates its functions via the NF-κB pathway, the expression of NF-κB-pathway-related proteins and genes were measured. In comparison to the si-NC group, the si-PLK1 group had higher levels of NF-κB and TRAF2 after PLK1 knockdown ($p \leq 0.05$) (Figure 6A). Our findings demonstrated that PLK1 controls NF-κB signaling pathway activity to control proliferation and apoptosis. We utilized the Htr8 cells to check the downstream signaling species expression in order to further support these findings. PLK1-overexpression (OE-PLK1) significantly reduced the expression of TRAF2 (Figure 6B). In addition, the expression of cell-cycle-associated proteins including Foxo1, cyclinD3, and CDK6 was assessed using WB. The expression of FoxO1, CDK6, and cyclinD3 was significantly upregulated in the OE-PLK1 group compared to that in the si-PLK1 group ($p \leq 0.05$) (Figure 6C). Collectively, these results imply that the NF-κB pathway plays a regulatory function in PLK1’s regulation of cell apoptosis, proliferation, and cycle in JEG-3 and Htr8 cells.
## 3.9. Mice Blastocyst Development and Trophectoderm Differentiation Are Both Negatively Regulated by the PLK1 Inhibitor
Figure 7A shows the procedure followed to acquire and discard pre-implantation embryos. We cultivated two-cell embryos in a medium including BI2536, a specific inhibitor of PLK1, to better understand the function of PLK1 in the mice trophectoderm (TE) differentiation and blastocysts maturation. We verified that the BI2536-treated group’s blastocyst-developing and four-cell rates were significantly lower (Figure 7B). Based on detectable and exclusive staining of NANOG and GATA4, total cell counts from DAPI staining were categorizedas those corresponding to cells of the c inner cell mass or the trophectoderm (TE); TE, which are the outer cells that are not considered as part of the inner cell mass of the blastocyst, did not exhibit NANOG and GATA4 staining. The result showed that trophectoderm differentiation of the control group was higher than the BI2536-treated group ($p \leq 0.01$) (Figure 7C).
## 3.10. Expression of PLK1-Induced ROS and Dysfunction of the Mitochondria
We investigated whether PLK1 suppression led to ROS accumulation, which therefore slowed down the development of the embryo. Utilizing a confocal microscope, mitochondrial superoxide—a measure of the amount of ROS—was explored in embryos to investigate the inhibition mechanism of BI2536-treated PLK1. As seen in Figure 7D, four-cell embryos treated with BI2536 had significantly higher amounts of mitochondrial superoxide than the control embryos ($p \leq 0.05$). We stained JC-1 to analogize the fluorescence intensity in the BI2536-mediated and unmediated groups since ROS buildup can impair mitochondrial membrane permeability. When compared to the control group, embryos treated with BI2536 displayed a significantly higher level of green fluorescence, which indicated a reduction in the potential of the mitochondrial membrane ($p \leq 0.05$) (Figure 7E). The proteins expression of mitochondrial fission including FIS1 and DRP1 was decreased (Figure 2B). These findings imply that PLK1 reduced NF-κB activity and reduced apoptosis, high permeability, and mitochondrial dysfunction in embryo cells.
## 4. Discussion
Regarding the critical role of nodes with a high degree (hubs) in preserving the integrity of the network construction in anticipation of attacks and failures [30,31] in disseminating events [32], it is realistic to anticipate that hub nodes/genes control is crucial to prevent disease networks. Some hub genes cause lethality or infertility, making them unsuitable drug targets. Placental trophoblast cells can promote embryo implantation, uterine spiral artery remodeling, and placentation via their proliferation, invasion, and migration. Furthermore, these cells secrete numerous active substances to regulate maternal–fetal interactions to ensure the normal growth and development of the embryo and fetus [33]. It is important to understand the changes in trophoblast cell function in RPL to explain its pathogenesis. Whole-exome sequencing of villi indicated that different pathogenic genes played a vital role in RPL. For example, one patient was found to have compound heterozygous mutations in or jointly involved in the occurrence of RPL by affecting inflammation, oxidative stress response, and angiogenesis [34,35] at the maternal–fetal interface. Transcriptomics is widely used in the study of villi tissue of RPL. The RNA sequencing results showed that different genes’, for example, EGR1, PDLIM1, and MAPK3, mRNA expression levels were reduced in the trophoblasts of RPL [36]. Another study found that the most differentially expressed genes (DEGs) in trophoblastic cells of RPL could bind the transcription factor E2F [37]. Some studies have focused on the role of ncRNAs in RPL, and the differentially expressed ncRNAs participate in biological pathways, including immunity, apoptosis, and hormonal regulation [38,39]. Transcriptome studies have revealed that the altered expression of genes or regulatory factors was associated with trophoblast proliferation, invasion, migration, and apoptosis, resulting in placental dysfunction and embryo failure to survive. In addition, the function of trophoblasts during pregnancy is affected by the immune response at the maternal–fetal interface. DEGs involved in the balance between pro- and anti-inflammatory responses also contribute to the development of RPL.
Omics of the villi of RPL patients can indicate new biomarkers for the diagnosis and treatment of RPL; therefore, in this study, we constructed an RPL gene network using omics levels. In this regard, 14 genes in the RPL regulatory network were predicted to be involved in RPL-related biomarkers and risk prognosis. We studied whether PLK1 is engaged in RPL pathogenesis by controlling the embryo’s development and trophoblast cell functions and PLK1’s effect on the alteration of the chorionic villi transcriptome. We identified PLK1 as a hub high-traffic gene involved in RPL. We revealed that expression of PLK1 is decreased in the villi of RPL patients. PLK1 was previously found to be significantly expressed in hepatocellular carcinoma and to have a favorable impact on both cancer cell invasion and proliferation, according to Ando et al. [ 40]. Additionally, exome sequencing in unrelated samples or single cases has also identified candidate maternal-effect genes, including PIF1, CCDC68, PLK1, MMP10, FLT1, PADI6, and FKBP4 [41,42,43,44,45]. Forkhead box transcription factors are well known to have a function in the regulation of a wide range of biological procedures, such as oxidative stress, DNA damage and repair, cell proliferation, apoptosis, and cell differentiation, all of which are extremely important for cell biology [46].
In this study, we also demonstrated that PLK1 guards against RPL by balancing mitochondrial fission and fusion, lowering the apoptosis of chorionic villi. Additionally, our results showed that PLK1’s protective impact depends on its negative control of NF-κB signaling. The investigation also found that PLK1 limits the TRAF2 expression to control NF-κB signaling by interacting with TRAF2, an upstream NF-κB regulator. The PLK1/ TRAF2/ NF-κB axis was therefore demonstrated to be essential in RPL and may represent a possible therapeutic target in the clinic. Mitochondria are crucial organelles in chorionic villi because their dysfunction can lead to loss of function in different organs, such as the heart, kidneys, and lungs [47,48]. The present study revealed that RPL-induced mitochondrial damage was characterized by increased ROS, decreased MMP, and disruption of mitochondrial dynamic balance in the chorionic villi. Mitochondrial dynamic balance depends on fission and fusion, which are mediated by conserved dynamin-related GTPase proteins including the fusion proteins optic atrophy 1 (OPA1), mitofusin1 (Mfn1), and mitofusin2 (Mfn2), as well as the fission protein dynamin-related protein 1 (Drp1) and its receptor mitochondrial fission protein 1 (Fis1) [49,50]. Our results showed that the expression of Fis1 and Drp1 was increased in the villi tissue during RPL, while Mfn2, Mfn1, and OPA1 expression was decreased, indicating increased mitochondrial fission and insufficient mitochondrial fusion. Furthermore, impaired mitochondria release cytochrome c, an essential component of the respiratory chain, into the cytosol to trigger apoptosis [51,52]. The B-cell lymphoma 2 (Bcl2) family mediates cytochrome c release, and cytochrome c in the cytosol can bind to apoptotic protease factor 1 (Apaf1), forming the apoptosome complex, which activates caspase 9 and caspase 3, and resulting in apoptotic features such as DNA fragmentation and chromatin condensation [53]. This study also verified excessive apoptosis in the chorionic villi, which was characterized by elevated expression of Bax and cleaved caspase 3, decreased Bcl2 expression, and an increase in TUNEL-positive cells, which was accompanied by mitochondrial dysfunction during RPL. NF-κB signaling is known to play a pivotal role in inflammation by mediating the expression of inflammatory cytokines and chemokines [54]. The NF-κB family is composed of five members known as RelA/p65, RelB, c-Rel, NF-κB1 (p105/p50), and NF-κB2 (p100/p52), among which p50/p65 is the most representative dimer [55]. Incremental mitochondrial fragmentation can in turn increase NF-κB activity by phosphorylating IKK and IκBα through ROS accumulation [56]. Similarly, the present results demonstrated that pharmacological inhibition of the NF-κB pathway not only ameliorated the changes in fission proteins (Drp1 and Fis1) and fusion proteins (OPA1, Mfn1, and Mfn2) but also improved mitochondrial function by rescuing MMP in the chorionic villi during RPL.
Moreover, a TRAF-binding protein called TANK was discovered to have opposing regulatory features in innate immune activation. Because TANK can increase the NF-κB signaling function that expresses TRAF2, the impact of the inhibition of NF-κB and TRAF2 on the NF-κB pathway is also debatable. We showed at the TRAF2 level in the RPL and confirmed that the expression of TRAF2 was noticeably enhanced both in vivo and in vitro during RPL since the expression of TRAF2 varied with various stimuli [57].
We utilized BI2536 (S1109), a PLK1 inhibitor, in this investigation to further confirm the impact of PLK1 on the quality and growth of the pre-implantation embryo and trophoblast functions. Two cell embryos were cultured in an M16 medium containing BI2536 to observe the effect of PLK1 inhibition on four-cell embryos and blastocysts. We observed that embryos treated with BI2536 showed a reduced developmental rate compared to the control group, indicating that PLK1 inhibition negatively affects embryo quality. Furthermore, pooled embryos showed decreased differentiation of TE in comparison to the healthy group, suggesting that PLK1 may hinder the growth and functions of TE, thereby contributing to RPL. In oocytes and early embryos, mitochondria play a pivotal role in ATP generation as mitochondrial-based oxidative metabolism is required for development, rather than glycolysis [58]. The main function of mitochondria is ATP generation, which is directly associated with the potential of embryo development [59]. Apart from increased rates of aneuploidy, mitochondrial dysfunctions, including oxidative damage, changes in mitochondrial membrane potential, and decreased ATP generation, are observed in oocytes and embryos of older mothers, compared with those of their younger counterparts in both animal and human models [60,61,62,63], indicating that reduced rates of blastocyst development can be partly attributed to metabolic dysfunction. Following further investigation, it was discovered that PLK1 and TRAF2 physically interact in RPL, providing structural proof that PLK1 regulates the activity of NF-κB signaling by TRAF2. We observed that inhibition of PLK1 can suppress trophoblast proliferation, invasion, and migration through the NF-κB signaling pathway and impair the development potential of pre-implantation embryos by dysregulating mitochondrial functions. Therefore, we proposed that PLK1 binds to TRAF2 during RPL and inhibits it, negatively regulating NF-B signaling.
The study limitations should be mentioned. The experimental period was relatively short, and the collected samples were limited by region.
## 5. Conclusions
We proposed the construction of a recurrent pregnancy loss regulatory network and identified four related pathways of RPL. As well, 14 genes and proteins were detected, which can act as therapeutic targets for recurrent pregnancy loss treatment and further investigations. These results also revealed a detailed mechanism of PLK1 as a hub high-traffic gene in regulating the proliferation, migration, and invasion of cells in RPL. Our research verified that PLK1 prevents RPL by regulating mitochondrial malfunction and preventing apoptosis via the TRAF2/NF-κB signaling pathway. Therefore, the PLK1/TRAF2/NF-κB axis can be used as a potential clinical target for the prevention and treatment of RPL.
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|
---
title: Cryo-electron microscopy of adipose tissue extracellular vesicles in obesity
and type 2 diabetes mellitus
authors:
- Valentina V. Miroshnikova
- Kseniya V. Dracheva
- Roman A. Kamyshinsky
- Evgeny V. Yastremsky
- Luiza A. Garaeva
- Irina A. Pobozheva
- Sergey B. Landa
- Kristina A. Anisimova
- Stanislav G. Balandov
- Zarina M. Hamid
- Dmitriy I. Vasilevsky
- Sofya N. Pchelina
- Andrey L. Konevega
- Tatiana A. Shtam
journal: PLOS ONE
year: 2023
pmcid: PMC10045588
doi: 10.1371/journal.pone.0279652
license: CC BY 4.0
---
# Cryo-electron microscopy of adipose tissue extracellular vesicles in obesity and type 2 diabetes mellitus
## Abstract
Extracellular vesicles (EVs) are cell-derived membrane vesicles which play an important role in cell-to-cell communication and physiology. EVs deliver biological information from producing to recipient cells by transport of different cargo such as proteins, mRNAs, microRNAs, non-coding RNAs and lipids. Adipose tissue EVs could regulate metabolic and inflammatory interactions inside adipose tissue depots as well as distal tissues. Thus, adipose tissue EVs are assumed to be implicated in obesity-associated pathologies, notably in insulin resistance and type 2 diabetes mellitus (T2DM). In this study we for the first time characterize EVs secreted by visceral (VAT) and subcutaneous adipose tissue (SAT) of patients with obesity and T2DM with standard methods as well as analyze their morphology with cryo-electron microscopy. Cryo-electron microscopy allowed us to visualize heterogeneous population of EVs of various size and morphology including single EVs and EVs with internal membrane structures in samples from obese patients as well from the control group. Single vesicles prevailed (up to $85\%$ for SAT, up to $75\%$ for VAT) and higher proportion of EVs with internal membrane structures compared to SAT was typical for VAT. Decreased size of single and double SAT EVs compared to VAT EVs, large proportion of multilayered EVs and all EVs with internal membrane structures secreted by VAT distinguished obese patients with/without T2DM from the control group. These findings could support the idea of modified biogenesis of EVs during obesity and T2DM.
## Introduction
Obesity is a major risk factor for the development of metabolic syndrome, hypertension, cardiovascular disease, dyslipidemia, insulin resistance, and diabetes mellitus [1]. The role of adipose tissue (AT) released extracellular vesicles (EVs) in obesity-associated pathologies, notably in insulin resistance, has been actively discussed in recent years [2,3].
EVs are produced by cells of all known organisms and are important for cell-to-cell communication and physiology. EVs, which are vesicles surrounded by a phospholipid bilayer, form heterogeneous population classified as exosomes, microvesicles (MVs), and apoptotic bodies based on their size and mechanism of formation [1,4]. Exosomes are considered to be of endocytic origin and released upon fusion of multivesicular bodies (MVB) and the plasma membrane, MVs are directly derived from the plasma membrane and apoptotic bodies are formed exclusively during programmed cell death [4]. EVs can transmit a broad range of molecular signals through transfer of different cargo such as lipids, proteins and nucleic acids, including microRNAs, to recipient cells and the extracellular environment [3]. Such ubiquity establishes EV release as a fundamental process required for cellular communication in both normal and pathological conditions [4]. Thus, EVs have received much interest for clinical application as diagnostic biomarkers and therapeutic carriers of bioactive molecules [5].
Secretion as well as composition of EVs might be altered in obesity and diabetes mellitus [1]. Obesity is associated with an increase in the level of plasma EVs [6–8]. Adipose tissue EVs could regulate metabolic and inflammatory interactions inside adipose tissue depots as well as distal tissues [9,10]. For example, adipocytes were found to secrete lipid-laden EVs expressing the lipid droplet-associated protein perilipin 1, phospholipids, neutral lipids, and free cholesterol that are taken up by AT macrophages and can promote macrophage polarization into M1 phenotype [11]. In diabetes mellitus, EVs may stimulate endothelial cells to transform from normal phenotype into a diabetic phenotype [1]. It could be expected that AT EVs are likely involved in obesity-associated comorbidities. Still there is only limited information on the morphology and composition of EVs secreted directly by human AT [12,13].
Great morphological diversity has been described regarding EVs found in body fluids such as blood plasma, breast milk, ejaculate, cerebrospinal fluid [14–19]. All these studies established cryo-EM as the most suitable technique to study the morphology of EVs because it provides high spatial resolution and the ability to image EVs preserved in a near-native state using vitrification, without any staining or chemical fixation procedures [20–23]. Still today cryo-EM structure of AT EVs was not studied. Analysis of morphology of AT EVs in obesity and type 2 diabetes mellitus (T2DM) by cryo-EM could widen our understanding of the pathophysiological role of AT EVs in these diseases. Here we characterize EVs secreted by visceral and subcutaneous AT of patients with obesity and T2DM with standard methods as well as analyze their morphology with cryo-EM.
## Study participants
Patient groups were filled with obese subjects with or without T2DM who underwent a bariatric surgery and had body mass index (BMI)>35. Type 2 diabetes mellitus diagnosis was based on clinical and laboratory characteristics as per the 1999 WHO criteria for diabetes classification and diagnosis [24]. Patients with the following characteristics were included: fasting plasma glucose levels ≥7.0 mmol/L or 2 h post-challenge glucose levels in an oral glucose tolerance test ≥11.1 mmol/L. Control group was formed by normoglycemic subjects without obesity and T2DM who was selected from a convenience sample of patients undergoing unrelated abdominal procedures. Patient data is represented in Table 1.
**Table 1**
| Studied groups | Obesity with type 2 diabetes mellitusN = 7 | Obesity without type 2 diabetes mellitusN = 6 | Control group without obesity or type 2 diabetes mellitusN = 9 |
| --- | --- | --- | --- |
| Age | 47±9 | 39±11 | 41±8 |
| Male/Female | 4/3 | 1/5 | 3/6 |
| Body mass index | 47.5±7,2* | 40.9±5,5* | 24.0±3,0 |
| Weight | 108–173 | 100–145 | 60–95 |
| Glucose, mmol/L | 7.3 (5.7–9,6)¥§ | 5.6 (5.4–5.9)¥ | 5.0 (4.3–5.5) |
| Cholesterol, mmol/L | 5.5±0.6 | 4.7±0.9 | nd |
| HDL, mmol/L | 1.3±0.1 | 1.3±0.2 | nd |
| LDL, mmol/L | 3.0±0.8 | 2.5±0.8 | nd |
| Triglycerides, mmol/L | 2.6±1.1 | 2.1±1.2 | nd |
The study protocol is in accordance with the Declaration of Helsinki and was approved by the local ethics committee of Pavlov First Saint-Petersburg State Medical University, Saint-Petersburg, Russian Federation (protocol 259 by 2022 February 28). Written informed consent was given by each participant.
## Adipose tissue cultivation and extraction of extracellular vesicles
Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were excised during surgery from the omentum and the anterior abdominal wall incision site, respectively, immediately placed into Hank’s solution and transported to the laboratory.
VAT and SAT samples (1–2 g) were washed with phosphate buffered saline (PBS), cut into 1–4 mm pieces, transferred to petri dish containing DMEM/F12 medium with $10\%$ EV-free serum (Fetal Bovine Serum, exosome-depleted, Thermo Fisher Scientific, A2720803) supplemented with $1\%$ gentamicin and incubated for 12 h. The culture supernatant was prepared via serial centrifugations and filtration, specifically it was centrifuged at +4°C at 300g for 10 minutes, 3,500 g for 30 min, 10,000 g for 30 min; afrerwards it was filtered through 0,22 syringe PES filter to remove lipids, cells and cellular debris before ultracentrifugation. Culture medium prepared in this way was frozen in liquid nitrogen and stored at -80°C. 100 ml of pooled culture medium (thawed on ice) was subjected to ultracentrifugation at 110,000 g and +4°C to pellet EVs (Optima L-90K centrifuge, Ti45 rotor (Beckman Coulter)). EVs were washed by PBS and centrifuged again at 110,000 g and +4°C (Optima L-90K centrifuge, SW 55Ti rotor, (Beckman Coulter)) before the final EVs pellet was resuspended in 100 μL of PBS, and aliquots were frozen in liquid nitrogen and stored with subsequent storage at −80°C for further analysis.
## Nanoparticle Tracking Analysis (NTA)
The size and concentration of EVs were determined by NTA using the NTA NanoSight LM10 analyzer, equipped with a 405 nm laser (Nano-Sight, Malvern Instruments) and a C11440-5B camera (Hamamatsu Photonics K.K.). Before NTA measuring, an aliquot of the isolated EVs was thawed at room temperature and diluted with deionized water 1,000, 10,000, 100,000 times and injected in the sample chamber with sterile syringe. Recording and data analysis were performed using the NTA software 2.3. Particles were captured by recording 30s video at room temperature and following parameters: camera level—16, low threshold—0, high threshold—2015. Received videos (750 frames captured with 10–40 particles/per frame) were analyzed at detection threshold value of 8 and minimal expected size. The measurements were carried out three times. Software used identifies and tracks individual nanoparticles moving under Brownian motion and relates the movement to a particle size according to the Stokes-Einstein formula. So, the average hydrodynamic diameter, the mode of distribution, the standard deviation, and the concentration of vesicles in the suspension were determined.
## Dynamic Light Scattering (DLS)
Unprocessed EV preparations as well as after preliminary depletion of unnecessary particles by immunoprecipitation with anti-CD63 antibodies were subjected for DLS as described earlier [25,26]. This approach allows to distinguish particles by size (using hydrodynamic radius). The measurements were carried out using a laser correlation spectrometer DLS (INTOX MED LLC, St. Petersburg, Russia) with a heterogeneous measurement scheme. Mathematical processing of the obtained data was carried out using the algorithm [27] using the QELSspec (version 3.4) software package, Gatchina, Russia.
## Western blotting
EVs were lysed 1:1 in ice-cold RIPA buffer containing 50 mM Tris-HCl (pH 8.0), 150 mM NaCl, $1\%$ Triton X-100, $0.5\%$ sodium deoxycholate, $0.1\%$ SDS and protease inhibitor cocktail (Roche). The lysate was centrifuged at 14,000 g for 15 min at 4°C, then supernatant was carefully aspirated into a new tube. Protein concentrations were determined using the Micro BCA protein assay (Pierce). A mass of 5 μg (EVs) and 10 μg (AT lysate as a control) protein per lane was separated using $8\%$ SDS-PAGE gels. Proteins were transferred to PVDF membranes (Millipore) and pre-incubated with $5\%$ skim milk in PBS. The blots were incubated with rabbit polyclonal anti-СD63 (1:1000; ab216130, Abcam) and anti-FABP4 (1:1,000; PA5-30591, Thermo Fisher Scientific) primary antibodies diluted in $1\%$ skim milk in PBST ($0.05\%$ Tween 20 PBS) to prevent non-specific binding and followed by anti-rabbit HRP-conjugated secondary antibodies (1:3,000; ab6721, Abcam). Proteins were visualized using an ECL Western Blotting Detection Reagent (Amersham) using ChemiDoc Imaging system (BioRad).
## Cryo-EM
Cryo-EM was used for direct visualization of vesicles and their morphological examination. To prepare samples for cryo-EM study lacey carbon EM grids were glow-discharged (30 s, 25 mA) in Pelco EasiGlow system. 3 μL of the sample aqueous solution were applied onto the carbon side of EM grid, which was then blotted for 2.0 s using filter paper and plunged into the precooled liquid ethane with Vitrobot Mark IV (FEI, USA). This procedure results in embedding the samples in a thin layer of electron transparent amorphous ice preserving them in native state and protecting from electron beam damages. Plunge-frozen samples were imaged in a cryogenic transmission electron microscope Titan Krios 60–300 (FEI, USA), equipped with highly sensitive direct electron detector (DED) Falcon II (FEI, USA) and Cs image corrector (CEOS, Germany) at accelerating voltage of 300 kV. Acquisition of cryo-EM images was performed using EPU software (FEI, USA) in low-dose mode to minimize radiation damage, most of the images collected for analysis was taken with 7.45 Å per pixel, small number of images were taken at double the magnification. EVs feature measurement was performed in Fiji [28].
## Statistical analysis
Conformity of findings to normal distribution was tested using the Shapiro-Wilk test. To assess differences between groups, the Mann–Whitney test was used. Differences in the proportion of EV types (multilayered, total with internal membrane structures) were assessed by contingency tables accomplished using Fisher’s exact test. The level of significance was set at $p \leq 0.05.$ *Statistical analysis* was performed using SPSS 17.0 software. Clinical and experimental data are presented as the mean ± the standard deviation (SD) or the median (min-max) depending on the distribution.
## Characterization of adipose tissue EVs by NTA, western blotting and DLS
NTA was conducted for AT EVs of obese patients with/without T2DM and individuals without obesity and T2DM. On the whole EVs yielded concentration from 6.8*10^12 to 2.9*10^13 particles/mL with an average modal size of 89±17 nm for SAT EVs and 84±10 nm for VAT EVs. Parameter D90 (the diameter at which $90\%$ of the samples’ mass is comprised of particles with a diameter less than this value) was estimated as 186±17 nm and 176±16 nm for SAT and VAT EVs, respectively. The characteristic sizes of all EV preparations are shown in the Table 2. NTA size distribution diagrams for all groups studied are presented in Fig 1. Purity of EV preparations was assessed as the ratio of NTA measured particle number per μg of protein which introduces contaminating protein [29]. These data are represented in the Table 2 and demonstrate receivable purity level for ultracentrifugation.
**Fig 1:** *Size distribution of subcutaneous and visceral adipose tissue extracellular vesicles assessed by NTA and cryo-EM.* TABLE_PLACEHOLDER:Table 2 DLS analysis was proceeded for unprocessed EV samples and after CD63-positive particles depletion (S1 Fig). DLS analysis of unprocessed samples resulted in two distinct peaks corresponding to vesicle hydrodynamic radius in the range of 20–30 nm (red peak, contribution to scattering of 30–$40\%$) and 120 nm (blue peak, contribution to scattering of 50–$65\%$), respectively, without differences of size distribution between different EV preparations. DLS analysis of CD63+ particles depleted samples demonstrated contamination of samples by small CD63- particles about $1\%$ (S1 Fig).
All EV preparations were analyzed by Western-blot. The isolated particles contained canonical exosomal marker CD63 as well as adipocyte-specific fatty acid binding protein 4 (FABP4) (Fig 2). Unprocessed western blot images can be found in S1 File.
**Fig 2:** *Western blot analysis of the CD63 as common exosomal marker and FABP4 as adipose tissue specific marker.The origin bands are presented in supplementary files. Abbreviations in the figure: AT–adipose tissue, SAT–subcutaneous AT, VAT–visceral AT, EVs–extracellular vesicles, T2DM–type 2 diabetes mellitus.*
## Morphological characterization of adipose tissue EVs by сryo-EM
Sufficient number of EVs were counted and analyzed in series of microphotographs: from 334 to 1014 EVs depending on the study group. EVs of various sizes and morphology including EVs with internal membrane structures were observed by cryo-EM. More than $90\%$ of EVs were identified as exosome-like vesicles due to the clear presence of a lipid bilayer. As expected, most of the vesicles were round, but elongated vesicles were also detected.
The composition of EVs was heterogeneous including single layered vesicles, double membrane vesicles, double EVs (one inside the other), multilayered vesicles (two or more vesicles were contained inside a larger one), as well as exosomes (~100nm) and large vesicles (>100 nm) can be seen. Among EVs, single vesicles prevailed (up to $85\%$ for SAT, up to $75\%$ for VAT). Representative microphotographs of SAT and VAT EVs of obese patients with/without T2DM and individuals from the control group are presented in Figs 3 and 4, respectively. Additionally, microphotographs of EVs isolated from SAT and VAT culture mediums of patients with obesity and obese patients with concomitant T2DM are provided separately as supplementary material (S2–S5 Figs).
**Fig 3:** *Cryo-EM images of EVs isolated from SAT and VAT culture mediums of obese patients with and without T2DM.Various morphological types of extracellular vesicles have been identified: Single vesicles (S), double vesicles (D), vesicles with double membrane (DM), multilayered vesicles (M), vesicle with broken membrane (B), granulated vesicle (GR). Scale bars are 100 nm.* **Fig 4:** *Cryo-EM images of EVs isolated from SAT and VAT culture mediums of individuals from the control group: Single (S), double (D), multilayered (M) vesicles.Scale bars are 100 nm.*
Some vesicles were more electron dense than others and among them vesicles were different from single to multilayered (more dark vesicles on Figs 3 and 4). One granulated EV with cargo was found in the sample of SAT EVs of patients with T2DM (Fig 3, tagged as GR: it had highly dense discrete inclusions inside).
The total proportion of EVs with internal membrane structures was higher in the samples of VAT EVs compared with the SAT EVs ($$p \leq 0.000$$ for the patient groups, $$p \leq 0.002$$ for the control group) (Fig 5). Obese patients with/without T2DM had larger proportion of multilayered EVs and EVs with internal structures for VAT when compared to the control group; there were no such differences between obese and control subjects in the case of SAT (Fig 5).
**Fig 5:** *Proportional distribution diagram for main types of observed extracellular vesicles.Abbreviations in the figure: EVs–extracellular vesicles, SAT–subcutaneous adipose tissue, VAT–visceral adipose tissue, T2DM–type 2 diabetes mellitus.*
According to analyzed cryo-EM images mean size of single and double vesicles secreted by SAT were lower than VAT EVs for obese patients with and without T2DM (Table 3). Interestingly sizes of SAT and VAT EVs did not differ in the control group. Mean sizes of main types of observed vesicles are represented in Table 3.
**Table 3**
| Group | Obesity with type 2 diabetes mellitus | Obesity with type 2 diabetes mellitus.1 | Obesity without type 2 diabetes mellitus | Obesity without type 2 diabetes mellitus.1 | Control group | Control group.1 |
| --- | --- | --- | --- | --- | --- | --- |
| Adipose tissue type | SAT | VAT | SAT | VAT | SAT | VAT |
| Total number of analyzed EVs | 334 | 532 | 434 | 494 | 1014 | 581 |
| Types of extracellular vesicles§: | Types of extracellular vesicles§: | Types of extracellular vesicles§: | Types of extracellular vesicles§: | Types of extracellular vesicles§: | Types of extracellular vesicles§: | Types of extracellular vesicles§: |
| Single | Single | Single | Single | Single | Single | Single |
| Number, N(%) | 283 (84,7%) | 348 (65,4%) | 326 (75,1%) | 328 (66,4%) | 828 (81,7%) | 436 (75,0%) |
| Size, nm | 52 (16–210)* | 93 (25–275) | 64 (19–261)* | 89 (25–449) | 82 (18–339) | 76 (18–322) |
| Double membrane | Double membrane | Double membrane | Double membrane | Double membrane | Double membrane | Double membrane |
| Number, N(%) | 10 (3,0%) | 19 (3,6%) | 37 (8,5%) | 18 (3,7%) | 22 (2,2%) | 41 (7,1%) |
| Size, nm | 65 (49–116) | 82 (43–277) | 71 (38–130)¥ | 90 (58–142) | 85 (51–154) | 77 (32–184) |
| Double (one inside the other) | Double (one inside the other) | Double (one inside the other) | Double (one inside the other) | Double (one inside the other) | Double (one inside the other) | Double (one inside the other) |
| Number, N(%) | 27 (8,1%) | 119 (22,4%) | 48 (11,1%) | 95 (19,2%) | 115 (11,3%) | 87 (15,0%) |
| Size, nm | 97 (34–482)* | 123 (35–298) | 95 (40–211)** | 148 (58–406) | 121 (51–332) | 109 (49–342) |
| Multilayered | Multilayered | Multilayered | Multilayered | Multilayered | Multilayered | Multilayered |
| Number, N(%) | 14 (4,2%) | 46 (8,6%) | 23 (5,3%) | 53 (10,7%) | 49 (4,8%) | 17 (2,9%) |
| Size, nm | 146 (92–381) | 173 (122–446) | 153 (64–431)¥ | 203 (119–347) | 150 (72–311) | 141 (76–225) |
| Vesicles with defected or broken membrane: | Vesicles with defected or broken membrane: | Vesicles with defected or broken membrane: | Vesicles with defected or broken membrane: | Vesicles with defected or broken membrane: | Vesicles with defected or broken membrane: | Vesicles with defected or broken membrane: |
| Number | 27 | 70 | 40 | 41 | 32 | 45 |
| Size, nm | 68 (29–177) | 106 (40–374) | 95 (34–308) | 145 (63–378) | 116 (45–274) | 117 (35–327) |
## Discussion
In this study EVs secreted by VAT and SAT of patients with obesity and T2DM for the first time were characterized by cryo-electron microscopy evaluating the morphology, size and phenotype.
Single, double, double with two membrane bilayers and multilayered vesicles were revealed in SAT and VAT EV preparations for all studied groups in the present study. All these types of EVs were demonstrated for other human biological fluids and cell culture conditioned medium using cryo-EM earlier as well as increased particle size of multilayered vesicles compared to single vesicles was shown [14–19]. We visualized double and multilayered vesicles containing electron dense material with varying degrees of intensity, while most vesicles were electron lucent as was described earlier [18,30]. In addition, elongated EVs and EVs with compromised membrane integrity were identified. That could be explained by possible deformation and breakage occurred during sample preparation. Indeed, some studies have demonstrated the effect of ultracentrifugation on the integrity and morphology of vesicles isolated by this method [30,31]. However, the variants of vesicle morphology observed in our study (double, multilayer, etc.) were also detected in a number of other studies during the isolation of EVs by alternative methods from various biological fluids [32–34].
Unexpectedly according to processed cryo-electron microphotographs single and double EVs from SAT tended to be smaller than from VAT in obesity and T2DM. The size of multilayered vesicles did not significantly differ between SAT and VAT as well as between groups. At the same time there were no differences in sizes of any EVs from SAT and VAT of control subjects. These features were not observed by NTA analysis for several reasons. First of all, NTA does not distinguish different types of EVs (monolayer/multilayer), additionally it does not reliably differentiate between vesicles and non-vesicular particulate material such as debris or protein aggregates, which leads to diameter of any particle that moves within the solution to be recorded [35]. NTA measures hydrodynamic rather than true particle diameter [19,36]. Determined size depends on refractive index of the particles and the smallest (under 50 nm) particles are worse detected by NTA, so they can be underestimated [19,37]. These technical points as well as lack of discrimination between populations could explain the difference in relative estimation of vesicles’ sizes in the NTA and cryo-EM data [35]. For example, the smallest observed multilayered vesicle was 64 nm which is comparable to the size of single vesicles.
Obesity affects the biogenesis of EVs: their production is increased during obesity and is correlated with the onset of obesity-related pathologies such as insulin resistance [38,39]. It could be speculated that reduced mean size of single and double SAT EVs may be a consequence of increased or accelerated secretion of smaller vesicles by SAT in obesity and associated metabolic complications. Recent studies showed that small vesicles (20–50 nm) of unclear vesicular nature and subcellular origin are present within EV preparations [25,37,40,41]. However, these smallest particles were shown to contain CD63, a representative MVB marker, on their membrane structure [40]. Another interesting point from our study is an increased proportion of multilayered vesicles from VAT compared to SAT that we observed for patients with obesity with and without T2DM. This may also indicate that the EV biogenesis pathway may be disrupted during obesity and visceral fat accumulation. Still the regulatory mechanisms controlling secretion of different classes of EVs are largely unknown [40]. MVBs are formed by invagination of vesicles into the endosome lumen to form intraluminal vesicles (ILVs), the process is mediated by the endosomal sorting complexes required for transport (ESCRT) machinery and by alternative way via tetraspanin webs and lipids rafts [42]. An additional mechanism for EV biogenesis involves the bioactive lipid ceramide which accumulates in the endosomal membrane and form lipid patches (similar to lipid rafts) that interact with proteins [42]. Adipocyte hypertrophy is associated with cellular stress and chronic low-grade inflammation which could regulate the secretion of EVs [39]. Additionally several important lipid molecules including ceramide are shown to be elevated in the adipose tissue of obese subjects which could influence the budding of MVBs from the adipocytes [43,44]. It has been proposed that ceramide promotes spontaneous membrane curvature by microdomain formation and coalescence into larger ceramide-rich domains, which onwards induce vesicle budding [39,45]. It was shown that EV secretion is markedly reduced by GW4869, a neutral inhibitor of sphingomyelinase, enzyme which generates the bioactive ceramide [46]. This is consistent with the data of demonstrated increased size of blood plasma EVs in patients with Gaucher disease which is caused by mutations in the gene encoding lysosomal enzyme glucocerebrosidase and characterized by accumulation of glucosylceramide [47]. Any adipocyte-derived EV is predicted to contain a lipid droplet and its associated proteins, including adipocyte triglyceride lipase and perilipin 1 [11]. It was shown that adipose tissue from lean mice released ~ $1\%$ of its lipid content per day via EVs ex vivo, and this rate more than doubles with obesity [11]. So, it could be assumed that lipid accumulation in obesity influences size and morphology of EVs. Thus, lipids not only serve as structural components of exosomal membranes but also play a role in EV formation and release.
Recent studies proposed a link between the AMP-activated protein kinase (AMPK) pathway and EV secretion [45]. AMPK is a cellular sensor of energy homeostasis being a central player in glucose and lipid metabolism. Reduction of AMPK activity is associated with obesity and insulin resistance and subsequent enhanced EV release [45,48]. AMPK activation reduced adipocyte-mediated exosome release [48]. Inactivation of AMPK by its inhibitor compound C as well as silencing of AMPKα1 subunit encoding gene in 3T3L1 adipocytes both results in increased EV secretion and simultaneous enhanced TSG101 protein levels [48]. TSG101 is a core component of ESCRT pathway and plays a role in recruiting the whole ESCRT machinery, formation of ILVs and grouping them within MVBs [49,50].
Multilayered exosome-like vesicles were not exclusive for obese AT and were observed among SAT and VAT EVs of the control group; these structures are a natural occurence as they were found earlier in plasma and semen of healthy individuals [14,18,32]. The role of these vesicles is unclear and it can be only speculated that they could have special function such as transportation of internal vesicles. At the same time increased formation of such membrane structures may be the result of a pathological disturbance in the process of EV biogenesis. Still, it is currently unknown how multilayered vesicles are formed. Similar morphology of the vesicles was described for unprocessed EVs from ejaculate that suggests these structures are unlikely to be artifacts of ultracentrifugation [32]. Additionally, multilayered vesicles were observed among cerebrospinal fluid EVs isolated by size-exclusion chromatography [19]. It is known that MVBs are eventually degraded by lysosomes or fused with plasma membrane and secreted as EVs [42]. Increased proportion of multilayered EVs could be explained by accelerated release of MVBs that designed but failed to degrade in lysosomes. An increased number of double and multilayer vesicles among plasma EVs from patients with Gaucher disease was shown by us earlier and could be linked to lysosome dysfunction [47]. In present study larger proportion of vesicles with internal membrane structures was shown for VAT compared to SAT and this is more likely linked to the differences between fat depots. SAT functions as a benign storage depot of fatty acids as triglycerides, while VAT expansion is associated with abdominal obesity and it’s adverse metabolic and inflammatory profile [51]. Proteome analysis of adipose tissue EVs in obesity showed that VAT EVs are enriched in proteins related to energy pathway and metabolism, while SAT EVs contain more proteins linked to signal transduction and communication [52].
Durcin et al demonstrated differences in proteomic content of small and large (>100 nm, vesicles released from mature 3T3-L1 adipocytes [38]. Restricted number of proteins included in small EVs may be linked to the specific sorting of exosomes from MVBs, which is known to be controlled by Rab GTPases and other proteins of ESCRTI [38]. At the same time the fraction of large EVs which expected to contain multilayered EVs shows larger diversity of proteins [38]. This in turn may be related to the ability of large vesicles to encompass more material, especially cytosolic proteins and membranous lipid-raft proteins caveolin 1 and flotillin 2 [38]. Large EVs are specifically enriched in metabolic enzymes (mainly of mitochondrial origin) and thus may influence metabolic pathways in recipient cells [38]. It could be assumed that functions of large as well as multilayered EVs can be very diverse and additional studies are needed.
## Conclusion
In conclusion, this study for the first time described the characteristics and high degree of morphological variability of AT EVs. Larger proportion of vesicles with internal membrane structures including multilayered EVs compared with SAT is a feature of VAT. Decreased size of single and double SAT EVs compared to VAT EVs, large proportion of multilayered EVs and all EVs with internal membrane structures secreted by VAT distinguished obese patients with/without T2DM from the control group.
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|
---
title: Natriuretic Peptide Levels and Stages of Left Ventricular Dysfunction in Heart
Failure with Preserved Ejection Fraction
authors:
- Elisa Dal Canto
- Marielle Scheffer
- Kirsten Kortekaas
- Annet Driessen-Waaijer
- Walter J. Paulus
- Loek van Heerebeek
journal: Biomedicines
year: 2023
pmcid: PMC10045594
doi: 10.3390/biomedicines11030867
license: CC BY 4.0
---
# Natriuretic Peptide Levels and Stages of Left Ventricular Dysfunction in Heart Failure with Preserved Ejection Fraction
## Abstract
In heart failure with preserved ejection fraction (HFpEF), natriuretic peptide (NP) levels are frequently lower. In several trials, the outcome differed between patients with low and high NP levels. This suggests that NP could be used to identify distinct stages of left ventricular (LV) remodeling and myocardial tissue composition. This study investigated cardiac remodeling/dysfunction and myocardial tissue characteristics assessed by echocardiography and cardiac magnetic resonance (CMR) in HFpEF patients in relation to NP levels. Clinical and echocardiographic data of 152 HFpEF patients were derived from outpatient visits. A total of 71 HFpEF patients underwent CMR-derived T1-mapping. Multivariable regression analyses were performed to examine the association of NT-proBNP categories (</> median) and NT-proBNP as continuous variable with echocardiography and CMR-derived T1-mapping. Mean age was 71 ± 9, $93\%$ of patients were women and median NT-proBNP was 195 pg/mL, with $35\%$ of patients below the diagnostic cut-off value (<125 pg/mL). Patients with high NT-proBNP had comparable LV systolic function and LV relaxation but significantly worse LV stiffness and left atrial function compared with patients with low NT-proBNP. Higher NT-proBNP was significantly associated with higher LV stiffness and extracellular volume fraction (ECV) (β = 1.82, $95\%$ CI: 0.19;3.44, $$p \leq 0.029$$). Higher NT-proBNP levels identify HFpEF patients with worse LV stiffness because of more severe myocardial extracellular matrix remodeling, representing an advanced stage of HFpEF.
## 1. Introduction
Heart failure (HF) with preserved ejection fraction (EF; HFpEF) is characterized by a rising prevalence and similarly dismal outcome as HF with reduced EF (HFrEF) [1,2]. HFpEF represents a complex and heterogeneous clinical syndrome [3], and current recommendations advocate improved phenotyping of HFpEF patients to allow targeted therapies [4]. Recently, a distinct metabolic/inflammatory “obesity” HFpEF phenotype, especially prevalent in women, was identified [5,6], which corroborates the paradigm proposing comorbidities (such as obesity, diabetes mellitus, hypertension, chronic kidney disease, older age and postmenopausal state) to induce myocardial extracellular matrix (ECM) remodeling and augmented cardiomyocyte stiffness through coronary microvascular endothelial inflammation [7]. Cardiomyocyte stiffness in HFpEF is increased by the downregulation of cyclic guanosine monophosphate (cGMP)–protein kinase G (PKG) signaling due to the impaired upstream bioavailability of nitric oxide (NO) and natriuretic peptides (NPs) [8]. NP levels are frequently low in HFpEF patients, with a substantial proportion (20–$30\%$) of patients with invasively confirmed HFpEF presenting with low to even normal values [9,10], complicating the diagnosis of HFpEF. Low plasma levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) in HFpEF were attributed to metabolic comorbidities inducing a relative state of NP deficiency and decreased tissue responsiveness [5,6,11], low left ventricular (LV) diastolic wall stress due to concentric LV remodeling [12], a cushioning effect of epicardial fat, dampening LV diastolic distension [5] and postmenopausal estrogen deficiency [13]. Despite suboptimal diagnostic accuracy, NP levels carry important prognostic value and predicted adverse outcome and prognosis in HFpEF clinical trials [14,15,16]. In addition, NP levels were also associated with cardiac remodeling in HFpEF and community-based populations [17,18,19] and with therapeutic efficacy in several [14,15,20], but not all [16,21,22], HFpEF trials. In particular, NT-proBNP plasma levels correlated with the collagen volume fraction in endomyocardial biopsies from HFpEF patients [17] and with the myocardial extracellular volume (ECV) assessed by cardiac magnetic resonance (CMR) in individuals from the Multiethnic Atherosclerosis Study [18] and HFpEF patients [19]. Overall, these findings suggest that NP levels could correspond to distinct HFpEF stages, characterized by different myocardial structural and functional changes as well as clinical characteristics and prognosis. However, how measures of cardiac remodeling and dysfunction and of myocardial tissue composition relate to NP plasma levels in HFpEF patients remains incompletely understood. Accordingly, this study aims to investigate the association between clinical and echocardiographic characteristics and CMR measurements of myocardial ECV with NT-proBNP levels in HFpEF patients.
## 2.1. Clinical and Echocardiographic Characteristics
The mean age of HFpEF patients was 71.2 ± 8.8 years, and $92.7\%$ were women. There was a high prevalence of arterial hypertension ($71.7\%$), type 2diabetes mellitus (T2DM, $34.2\%$) and obesity ($53.9\%$) and frequent use of cardiovascular drugs. Thirty-four HFpEF patients had atrial fibrillation (AF, chronic ($$n = 12$$) or paroxysmal ($$n = 22$$), together $22.4\%$. Median plasma NT-proBNP value was 194.9 pg/mL (interquartile range 84.7–436.4) (Table 1). The mean H2FPEF score was 4.9 ± 1.8, and the mean HFA-PEFF score was 4.6 ± 1.1.
All HFpEF patients had evidence of LV diastolic dysfunction consisting of a prolonged DT (206.5 ± 41.5 ms), reduced E′ velocity (mean E′ = 6.5 ± 1.4 cm/s), elevated E/E′ (mean E/E′ = 13.9 ± 4.7), reduced mean A’ velocity (8.7 ± 2.1 cm/s), dilated left atrial (LA) volumes (max LA volum index (LAVI) = 43.6 ± 11.8, pre-A LAVI = 32.4 ± 9.8 and min LAVI = 25.0 ± 9.4 mL/m2), depressed LA reservoir function (LA global emptying fraction (ef) = 44.6 ± $9.0\%$) as well as LA conduit (LA passive ef = 25.2 ± $7.7\%$) and pump (LA active ef = 26.5 ± $9.4\%$) functions (Table 2).
## 2.2. Clinical Characteristics, Cardiac Structure and Function in HFpEF Patients with Low and High NT-proBNP Levels
The distribution of HFpEF patients in accordance with plasma NT-proBNP is shown in Figure 1. According to the median NT-proBNP value of 194.9 pg/mL, $34.9\%$ of HFpEF patients fell below the diagnostic cut-off value proposed in the 2021 ESC-HFA guidelines (≤125.0 pg/mL) [23] and $70.4\%$ of HFpEF patients fell below the NT-proBNP cut-off value recommended for risk enrichment in HFpEF trials (<360.0 pg/mL) [24], whereas $61.2\%$ of HFpEF patients fell below the cut-off values frequently used in clinical trials (300 pg/mL).
To detect differences in clinical and cardiac characteristics in relation to plasma NT-proBNP levels, HFpEF patients were categorized into low or high NT-proBNP groups based on their NT-proBNP being lower or higher than the median value of 194.9 pg/mL (Table 1 and Table 2). HFpEF patients with high NT-proBNP were older and had worse renal function, whereas the comorbidities burden (arterial hypertension and T2DM) was similar compared with HFpEF patients with low NT-proBNP. Additionally, HFpEF patients with high NT-proBNP had a more frequent use of diuretics and beta blockers compared to those with low NT-proBNP (Table 1).
In terms of cardiac phenotype, HFpEF patients with high NT-proBNP had a similar LV geometry, LV systolic function and LV relaxation (lateral, septal and mean E′) compared with HFpEF patients with low NT-proBNP (Table 2).
However, patients with high NT-proBNP showed a significantly deteriorated LV diastolic stiffness, as evident from higher E/E′ ratios (septal and mean) at comparable LV end diastolic volume (LVEDV), additional LA enlargement (max, pre-A and and min LAVI) and additional worsening of LA function (reduced A’, LA active ef and LA compliance) (Table 2). These differences remained significant in the fully adjusted model, except for LA active ef (Table 2). When NT-proBNP was analyzed as a continuous variable, increasing values of log-transformed NT-proBNP were not significantly associated with any indices of LV remodeling, systolic function and LV relaxation in the fully adjusted analysis (Table 3).
Conversely, with increasing values of log-transformed NT-proBNP, all indices of LV diastolic stiffness deteriorated (E/E′ ratios, A’ mean, LA global and active ef and LA compliance). Additionally, increasing NT-proBNP levels were significantly associated with larger right atrial volume (RAV) (Table 3). Sensitivity analysis, which compared echocardiographic measures of patients with NT-proBNP below and above the cut-off value suggested for risk enrichment in HFpEF trials, showed differences between the groups in terms of further impaired LV stiffness, LA remodeling and dysfunction. In fact, patients with NT-proBNP > 360.0 pg/mL showed a significantly decreased A’, increased lateral E/E′, larger LA volumes and decreased LA active ef and LA compliance compared with those with NT-proBNP < 360.0 pg/mL (Supplementary Table S1). Finally, patients with NT-proBNP > 360.0 pg/mL had significantly larger RAV and showed signs of depressed right ventricular (RV) function, with reduced RV strain, and additionally reduced LV global longitudinal strain (GLS), although these differences were no longer significant in the fully adjusted analysis (Supplementary Table S1).
## 2.3. Association between Myocardial Tissue Characteristics and NT-proBNP Levels
The association between NT-proBNP as a continuous variable and CMR indices of myocardial fibrosis was investigated in 71 HFpEF patients. The clinical and echocardiographic characteristics of this subgroup reflected those of the whole study population (Supplementary Table S2). Log-transformed NT-proBNP was significantly associated with log-transformed CMR-derived extracellular volume (Table 4). The linear relationship between log-transformed NT-proBNP and ECV is represented in Figure 2. Higher NT-proBNP plasma levels were significantly and independently associated with higher proportion of ECV, β = 1.74 ($95\%$ CI:0.10–3.48).
## 3. Discussion
The present study investigated the association between cardiac remodeling and dysfunction measures and NT-proBNP plasma levels in a chronic, stable HFpEF population that consisted predominantly of postmenopausal women with a high prevalence of metabolic comorbidities and hypertension. Compared with patients with lower NT-proBNP levels, those with higher NT-proBNP levels had comparable evidence of LV concentric remodeling, systolic function and slow LV relaxation, but substantially higher LV stiffness (Table 2). The analysis of NT-proBNP as a continuous variable confirmed these results as only the associations between NT-proBNP and LV stiffness related parameters, and not those with measures of LV remodeling, systolic function and relaxation, were significant. Furthermore, we demonstrated that increased LA volumes and LA dysfunction are strongly associated with rising NT-proBNP levels, which is in agreement with LA dilatation and dysfunction being reflective of the progression of diastolic LV dysfunction [25,26] and increased filling pressures [27] in HFpEF patients.
In a subgroup of HFpEF patients undergoing CMR, increased levels of NT-proBNP were associated with more advanced myocardial ECM remodeling, evident from higher ECV. Previously, in HFpEF patients, NP levels were shown to correlate with higher LV filling pressure [28], collagen volume fraction in endomyocardial biopsies [17] and myocardial ECM remodeling quantified by CMR [19]. Furthermore, ECV as measured by CMR was independently associated with invasively measured LV stiffness moduli in HFpEF patients [29]. According to the amount of ECV, different HFpEF pathomechanisms can be assumed, with predominant myocardial stiffness in patients with increased ECV and predominant impairment of LV relaxation kinetics for those with normal ECV [29]. Taken together, our results are in line with previous findings, with different levels of NP indicating distinct stages of LV remodeling and dysfunction and myocardial tissue composition in HFpEF.
## 3.1. Relatively Low NT-proBNP Plasma Levels in “Comorbidity-Driven” HFpEF Patients
In the present study, median NT-proBNP was relatively low (194.9 pg/mL) and $34.9\%$ of the population fell below the diagnostic cut-off value proposed by current guidelines (≤125.0 pg/mL), whereas $70.4\%$ of the patients had a NT-proBNP level below 360 pg/mL, the cut-off level suggested for risk enrichment in HFpEF trials [24]. Conditions highly prevalent in patients with HFpEF, such as concentric LV remodeling, cardiometabolic comorbidities and postmenopausal estrogen deficiency, are associated with lower NT-proBNP levels [5,6,11,12,13]. The relatively low NT-proBNP levels in our study population consisting primarily of comorbidity-driven HFpEF patients, may thus be explained by: [1] study design criteria with recruitment of a chronic, stable outpatient HFpEF population and exclusion of cardiomyopathies; [2] recruitment of a subgroup of HFpEF patients who may be in an earlier stage of myocardial disease progression because elevated NT-proBNP was not compulsory for HFpEF diagnosis; and [3] the predominance of elderly, postmenopausal women with high prevalence of cardiometabolic risk factors.
## 3.2. NP Levels Mirror Stage of Myocardial Disease Progression in HFpEF
Despite relatively low to even normal plasma NT-proBNP levels in a subset of our HFpEF patient population, HFpEF patients with NT-proBNP levels in the lower range showed concentric LV remodeling, diastolic LV dysfunction and LA dilatation and dysfunction (Table 2). Our results are supported by a recent study, which showed that patients with invasively proven HFpEF and normal NP levels had more LV hypertrophy, worse diastolic LV function, worse LA function and a 2.7-fold higher risk for mortality or HF readmissions compared with controls [30,31]. In terms of cardiac structural and functional remodeling as well as prognosis, HFpEF patients with normal NP levels were situated between controls and HFpEF patients with high NP levels, and it was suggested that HFpEF with normal NP levels reflects an earlier stage of myocardial disease progression [30,31]. In HFpEF, myocardial stiffness is mainly determined by both the ECM and the cardiomyocytes [32,33,34]. Increased cardiomyocyte stiffness results from post-translational modifications of the giant elastic sarcomeric protein titin due to impaired upstream NP- and NO-mediated activation of cGMP-PKG signaling [8,35,36], which is proposedly inflicted by comorbidity-induced systemic inflammation and coronary microvascular endothelial dysfunction. In addition, estrogen hormone is crucially involved in cardiomyocyte lusitropic signaling as it enhances cardiomyocyte relaxation [37] and stimulates endothelial NO synthase activity to improve NO-mediated titin-based cardiomyocyte compliance [38]. On the other hand, estrogen deficiency, present in postmenopausal women, reduces NP and NO bioavailability, which compromises cardiomyocyte relaxation and distensibility [13]. Hence, high diastolic LV stiffness in HFpEF patients with lower range NP levels is more likely to result from increased cardiomyocyte stiffness rather than prominent myocardial interstitial fibrosis, and improving cardiomyocyte stiffness could therefore represent a therapeutic target. Interestingly, sodium glucose cotransporter 2 inhibitors (SGLT2i) were recently shown to improve clinical outcomes in HFpEF patients [21,22] and to ameliorate cardiac remodeling and dysfunction [39,40,41]. In human HFpEF cardiac biopsies and animal HFpEF models, SGLT2i were shown to inhibit myocardial fibrosis, hypertrophy, inflammation and oxidative stress and to improve mitochondrial function, coronary microvascular endothelial function and NO bioavailability and enhance cGMP-PKG mediated cardiomyocyte distensibility [39,40,41]. These mechanisms of action help to explain the beneficial effects of SGLT2i for HFpEF patients in general, but also suggest that SGLT2i might be especially beneficial in patients with the metabolic/inflammatory HFpEF phenotype regardless of NP levels, because of the close matching of therapeutic myocardial targets to prevailing underlying pathophysiological mechanisms.
## 3.3. NP Levels as Selection Criteria for HFpEF Trials
Markedly elevated NT-proBNP levels are used as an inclusion criterion in phase III HFpEF trials [24]. A relatively high NP cut-off level improves the diagnostic specificity and increases cardiovascular event rates in the studied population. However, setting high NP entry criteria will skew the recruited HFpEF study population towards a phenotype with more advanced ECM remodeling, in whom NP levels are significantly elevated, and will exclude a significant proportion of HFpEF patients with less advanced ECM remodeling, in whom NP levels may be lower to normal, but who still have genuine diastolic LV dysfunction, probably due to increased titin-based cardiomyocyte stiffness. The cut-off criteria for NT-proBNP levels were ≥300 pg/mL in both the EMPEROR-preserved and DELIVER trials, whereas actual median NT-proBNP levels were close to 1000 pg/mL in both trials [21,22]. According to our results, such NT-proBNP selection cut-off criteria would lead to the exclusion of $70\%$ of HFpEF patients, who may have also been responsive to SGLT2i therapy, despite lower NT-proBNP levels. This hypothesis is currently being tested in the phase II randomized Stratified Treatment to Ameliorate DIAstolic left ventricular stiffness in early Heart Failure with preserved Ejection Fraction (STADIA-HFpEF) trial (ClinicalTrials.gov identifier NCT04475042) [42]. The STADIA-HFpEF trial recruits a more homogeneous metabolic/inflammatory phenotype HFpEF-like population with or without elevated NT-proBNP levels. HFpEF patients who have CMR evidence of structural cardiomyopathies or myocardial ECV > $29\%$ are excluded, thereby directing enrollment towards HFpEF patients without prominent myocardial interstitial fibrosis and therefore high diastolic LV stiffness related to increased titin-based cardiomyocyte stiffness [42].
In the present study, we demonstrate that NP levels can be used to identify distinct stages of cardiac structural and functional remodeling in patients with HFpEF. Low NP levels identify an earlier stage of myocardial disease progression, with diastolic LV dysfunction characterized by impaired relaxation, LA remodeling and dysfunction and minor ECM remodeling. In contrast, high NP levels identify a more advanced stage of myocardial disease progression, with similar concentric remodeling and impaired relaxation, but elevated LV stiffness and more advanced LA and ECM remodeling. Therefore, NP levels in HFpEF could aid in improving phenotypic and pathophysiologic stratification and may potentially also be of interest for improving patient selection for individualized therapeutic inroads.
## 4.1. Study Population
Data of chronic HFpEF patients ($$n = 152$$) were derived from their routine outpatient clinic visits at OLVG hospital, Amsterdam, from January 2016 onwards. All patients presented with symptoms of dyspnoea (New York Heart Association (NYHA) Class II to III), LVEF ≥ $50\%$ and echocardiographic evidence of LV diastolic dysfunction, according to the American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) criteria and European Society of Cardiology—Heart Failure Association (ESC-HFA) consensus recommendation for HFpEF diagnosis [4,43]. To enhance the validation of HFpEF diagnosis, at least one of the HFA-PEFF [4] and H2FPEF [44] diagnostic probability scores had to be positive. In case of an intermediate HFA-PEFF and/or H2FPEF score, diastolic stress testing was performed using rest/exercise (cycle ergometry) right heart catheterization to confirm or reject the diagnosis. Plasma NT-proBNP was obtained at the time of echocardiography and determined with a standard immunoassay (Cobas, Elecsys NT-proBNP II, Roche, Basel, Switzerland). To minimize the confounding effects of an acute HF episode on NT-proBNP levels, the study population consisted exclusively of stable, chronic HFpEF patients without obstructive coronary artery disease (CAD). Exclusion criteria were infiltrative or hypertrophic obstructive cardiomyopathy, hemodynamically significant uncorrected obstructive or regurgitant valvular heart disease and presence of CAD evident from inducible ischemia on noninvasive testing or from a history of previous myocardial infarction. Finally, to exclude alternative causes of dyspnea, only patients with hemoglobin levels > 7 mmol/L and spirometry (FEV1/FVC > $80\%$) were included. The study was conducted in accordance with the Declaration of Helsinki, approved by the institutional review board of OLVG hospital, Amsterdam and data inclusion for use in research was approved by all study participants.
## 4.2. Echocardiography
Echocardiographic examinations were performed on a GE Vivid9 ultrasound machine (General Electric Medical Systems, Horten, Norway) using a specific protocol involving 2-dimensional (2D), M-mode, Doppler, tissue Doppler and 2D speckle tracking (STE) imaging in accordance with current recommendations [45]. LA volumes were assessed using the biplane area–length method from apical 2- and 4-chamber views and were indexed to body surface area (LA volume and LA volume index, LAVI). LA volumes were measured at LV end-systole (max LAVI), at the onset of A-wave mitral inflow (pre-A LAVI) and at LV end-diastole (min LAVI). LA phasic functions were calculated as: LA global ef = [(max LAVI − min LAVI)/max LAVI × 100] (reservoir function); LA passive ef = [(max LAVI − pre-A LAVI)/max LAVI × 100] (conduit function); and LA active ef = [(pre-A LAVI − min LAVI)/pre-A LAVI × 100] (pump function) [25]. LA compliance was calculated as LA global ef/E/E′ [26]. LAVI pre-A, LA passive and active ef could not be reliably assessed in 12 patients with chronic atrial fibrillation (AF), who were then excluded from the analysis for these parameters. RV systolic function was assessed from tricuspid annular plane systolic excursion (TAPSE); fractional area change (FAC), measured using the apical four chamber view on 2D echocardiography; and RV free wall strain, assessed by STE. Doppler assessment of the tricuspid valve systolic jet velocity (TR velocity) was obtained in both parasternal and apical 4-chamber views. RAV was measured at end-systole (max RAV) in apical 4-chamber view.
## 4.3. Cardiac Magnetic Resonance
CMR examination of 71 HFpEF patients was performed within 6 months from echocardiography on a Philips 1.5-T scanner (Ingenia 1.5T, Koninklijke Philips N.V., Amsterdam, the Netherlands). All scans were performed following a protocol consisting of functional analysis, T1-weighted images and late gadolinium enhancement. T1-mapping images were obtained using a modified look-locker inversion recovery (MOLLI) sequence before and fifteen minutes after intravenous gadolinium administration. Images were obtained in short-axis on basal, midventricular and apical section. Post-processing evaluation of T1-mapping values and ECV was performed using dedicated software (IntelliSpace Portal version 10, Koninklijke Philips N.V., Amsterdam, the Netherlands). T1-mapping analysis was performed on short-axis images on basal, mid, and apical slices. Images were manually contoured in native and post-contrast images by an investigator and verified by a magnetic resonance imaging level 3 cardio-radiologist. Papillary muscles were excluded from myocardial tissue. The equation used for ECV measurement was the following [46]:ECV=(1−hematocrit)×T1myocardium post-contrast−1−T1myocardium native−1T1blood post-contrast−1−T1blood native−1
## 4.4. Statistical Analysis
Data are shown as mean and standard deviation (continuous data) or as count and percentage (categorical data). Because NT-proBNP, lateral E/E′ and T1-mapping indices distributions were skewed, they are reported as medians and interquartile ranges. We categorized patients into two groups according to the median value of NT-proBNP, and we used multivariate linear regression analysis to compare the groups in terms of clinical characteristics and echocardiographic measures. For this analysis, we used predefined models to adjust for potential confounders. A minimally adjusted model included age (years), sex, plasma creatinine (mg/dL) and body mass index (BMI, kg/m2) (model 1). The fully adjusted model additionally included systolic blood pressure (mmHg), use of beta blockers (yes/no) and use of loop and thiazide diuretics (yes/no).
We also assessed associations of log-transformed NT-proBNP as a continuous variable with echocardiographic measures and with log-transformed CMR T1-mapping indices. A sensitivity analysis was performed by stratifying and comparing patients according to the NT-proBNP cut-off recommended for risk enrichment in HFpEF trials (=360 pg/mL) [24]. All analyses were performed using SPSS Statistics, version 22.0 (IBM Corp, IBM SPSS Statistics for Windows, Armonk, NY, USA). All reported p values were two-sided and values ≤0.05 were considered statistically significant.
## 5. Study Limitations
Some limitations of this study should be considered. First, sexes were not equally distributed in our study population, which mostly consisted of women. Although it is well known that women outnumber men in HFpEF, the proportion of women in our study is higher than other reports, and this might induce difficulties with the comparison of results across studies. A possible explanation for this distribution may be the applied stratification of patients, with the exclusion of patients with obstructive CAD and cardiomyopathies. Second, the size of the overall study population and of the subgroup undergoing CMR is relatively small; however, these patients were well-phenotyped with NP, a comprehensive echocardiographic analysis and myocardial tissue characteristics. Furthermore, the subgroup of patients undergoing CMR showed clinical and echocardiographic characteristics comparable to the overall study population. Third, CMR was not performed on the same day as echocardiography and biomarker assessment, which may create differences in loading conditions. However, the NT-proBNP measurement was repeated the day of the CMR examination, and this value was used for comparison with T1-mapping indices. Furthermore, our study included multiple echocardiographic markers, such as LA volumes, that reflect long-term exposure to LV filling pressure as well as measures of myocardial remodeling and tissue composition that are not affected by changes in volume status and do not vary in the short-term.
## 6. Conclusions
Compared to HFpEF patients with lower NT-proBNP plasma levels, those with higher NT-proBNP levels had comparable LV structure and LV relaxation but higher LV stiffness and ECV on CMR imaging in a study population with a comorbidity-driven HFpEF phenotype. The latter suggests that patients with high NT-proBNP have a more advanced stage of LV and LA remodeling with more severe myocardial ECM remodeling.
As NT-proBNP reflects the severity of cardiac dysfunction and remodeling in HFpEF, it may potentially serve a contributory role in improving pathophysiologic and therapeutic stratification in patients with HFpEF.
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|
---
title: 'Increased incidence and improved survival in endometrial cancer in Sweden
1960–2014: a population-based registry survey'
authors:
- Filip Herbst
- Paul W. Dickman
- Louise Moberg
- Thomas Högberg
- Christer Borgfeldt
journal: BMC Cancer
year: 2023
pmcid: PMC10045609
doi: 10.1186/s12885-023-10746-0
license: CC BY 4.0
---
# Increased incidence and improved survival in endometrial cancer in Sweden 1960–2014: a population-based registry survey
## Abstract
### Background
An investigation of trends of incidence and net survival (NS) for endometrial cancer in Sweden.
### Methods
Morphologically verified endometrial carcinoma diagnosed 1960 to 2014 were collected from the nation-wide Swedish Cancer Registry. Endometrial cancer patients were assessed with regards to time trends for incidence and 54,825 cases remained for survival analyses. Cases diagnosed 1995 to 2014 were categorized according to detailed morphology and from 2005 to 2014 FIGO stage was also categorized.
### Results
There was a trend of increasing incidence of endometrial carcinoma for women above 55 years of age. NS was improved at 5- and 10-year follow-up. The 5-year net survival in 2010–2014 was $86\%$. The most prominent improvement in NS was found in the elderly women above 75 years of age.
### Conclusions
This study observed increased incidence of endometrial cancer in Sweden from 1960 to 2014. The progress in diagnostics and treatment, seem to have improved the net survival, especially in elderly women.
## Background
Uterine corpus carcinoma, or endometrial carcinoma, is the 6th most common cancer in women in Sweden, and worldwide. Globally the incidence is increasing mainly due to increased life expectancy and obesity [1]. In Sweden approximately 1400 women are diagnosed annually [2, 3]. Thanks to early symptoms and diagnosis, the survival rate is high. In Sweden, in 2016 the 5-year and 10-year survival rates were $84.2\%$ and $80.7\%$ respectively [3]. The Swedish Cancer Registry has been collecting national data since 1958. The registration of malignant, premalignant and certain benign tumors is mandatory and more than $96\%$ of new cases are registered [4].
Endometrial carcinomas are often categorized into two groups, type I and type II. Type I, which is the most common (80–$90\%$), has a better prognosis, is hormone dependent and is associated with hyperestrogenism. Type I has a high to intermediate differentiation (grade 1–2) and endometrioid morphology. By contrast, type II (10–$20\%$) is generally hormone independent with worse prognosis. Type II includes endometrioid cancer with low degree of differentiation (grade 3), serous carcinoma, clear cell cancer, carcinosarcomas/ malignant mixed Müllerian tumor, dedifferentiated and undifferentiated cancer [2].
There are several risk factors associated with endometrioid endometrial cancer including obesity, diabetes, hypertension and nulliparity [1, 2]. Unopposed estrogen treatment increases the risk while estrogen treatment in combination with continuous progesterone, such as in combined contraceptives has been proven to be protective. [ 1, 2, 5, 6]. Tamoxifen treatment in breast cancer patients has also been shown to increase the risk of endometrial cancer [1, 2].
The most important prognostic factor in endometrial cancer is stage. Stage also determines recommended treatment. In Sweden staging is performed according to the International Federation of Gynecology and Obstetrics (FIGO) surgical staging system stage I-IV, with subcategories. However, registration of stage was not introduced into the Swedish Cancer Registry until 2004.
Surgery is the keystone in the treatment of endometrial cancer [1]. Adjuvant radiation therapy has not been proven effective on overall survival but has been shown to reduce pelvic recurrence [7, 8]. Adjuvant chemotherapy on the other hand has been found to increase survival and is recommended for patients where the risk of recurrence is significant. [ 9].
The aim of this study was to investigate long term trends of incidence and net survival (NS) for endometrial cancer in Sweden, and in later time periods with regards to stage and morphology.
## Methods
The population-based nationwide Swedish Cancer Registry started registration in 1958. The registry contains data about gender, personal identification number, domicile, date of diagnosis, tumor site, histological type, stage at diagnosis, basis of diagnosis, reporting hospital and department. The Swedish Cancer Registry receives data once yearly from six regional registries associated with regional cancer centers covering the whole country. It is compulsory for clinicians, pathologists and cytologists to independently register all patients with premalignant and malignant conditions and certain benign tumors. This secures the high coverage of the registry [10]. The tumor site was in 1958–1986 coded according to International Classification of Diseases—7 (ICD-7), 1987–1992 according to ICD-9, 1993–2004 according to International Classification of Disease of Oncology 2 (ICD-O/2) and from 2005 according to ICD-O/3. The codes were translated to ICD-7 for the entire time-period to enable comparability over time. Morphological codes are available during the whole period as the older World Health Organization histology code (WHO/HS/CAN/C24.1). A more detailed morphology coding according to ICD-O/2 was used 1993 to 2004, and since 2005 ICD-O/3 has been used. Since 2004 information about stage has been collected [10]. The completeness of the Swedish Cancer *Registry is* over $96\%$ [4] and nearly all uterine cancer cases were verified by morphology [10]. Since Swedish residents all have a unique identification number, the follow-up of the patients in the registry is close to complete until time of death or emigration [11]. This was done by linking the data with data from the Swedish Cause of Death Registry using the Swedish personal identification numbers.
Data from 59,432 cases of endometrial carcinomas (ICD-7 172) from 1960 to 2014 was retrieved from the Swedish Cancer Registry and assessed with regards to time trends for incidence. Sarcomas and carcinosarcomas are registered under site code ICD-7 174, why they were not included. Of the retrieved patients 4,607 cases were excluded based on the following exclusion criteria; age < 18 years old, autopsy cases, cases without PAD/cytology, benign morphology or non-carcinomas, duplicate registrations, only year of death registered, zero or negative observation time (Fig. 1). These exclusion criteria left 54,825 cases of endometrial carcinomas for survival analyses. Fig. 1Flow chart of patients who met inclusion and exclusion criteria for survival analyses
## Statistical analyses
Incidence rates were age-standardized to the World Standard population 2000–2025 to facilitate international comparisons [12]. Survival time was measured from date of diagnosis until date of death, date of emigration, or May 7th 2020. We estimated net survival in a relative survival framework, which is standard approach for population-based studies of cancer patient survival [13]. Net survival is the probability of surviving beyond a given time without dying of the disease under study in a hypothetical scenario where the disease under study is the only possible cause of death. Net survival is preferred for comparing cancer patient survival between countries or within a single country since it is independent of mortality due to other causes. There are two frameworks available to estimate net survival; relative- and cause-specific. Relative survival is generally favored for population-based studies [14].
We estimated net survival using flexible parametric models [15]. Expected mortality rates for women, stratified by age and calendar year, were retrieved from the Human Mortality Database (http://www.mortality.org) based on data from Statistics Sweden. The model included the main effects of age at diagnosis (categorized as 18–44, 45–54, 55–64, 65–74, and > 75 years), morphology (high risk versus low risk; Table 1), year of diagnosis (1960–2014) as restricted cubic spline with 3 degrees of freedom, all three two-way interactions between age, year of diagnosis, and morphology, and time-varying effects of age, morphology, age*morphology and age*year. The baseline cumulative excess hazard was modelled as a restricted cubic spline with 5 degrees of freedom and the time-varying effects were modelled using 2 degrees of freedom. Based on this model, we estimated temporal trends in net survival within each age group along with age-standardized net survival using the International Cancer Survival Standard (ICSS) population number 1 [16]. We also estimated the difference in age-standardized net-survival between the two morphologic types, and relating to stage and morphologic types. The analytic process for age-standardization is illustrated (using publicly available data for melanoma where the exposure of interest is sex rather than morphology) at http://pauldickman.com/software/stata/age-standardise-standsurv/. The statistical analyses were performed using Stata version 17 (StataCorp, TX, USA). For comparisons of grouped data, the chi2-analysis was used. Table 1Morphology related to time periodsMorphologyICD-O/21995–992000–042005–092010–14TotalAdenocarcinoma (a)$\frac{8140}{35}$,460 ($92.0\%$)5,972 ($93.2\%$)6,183 ($92.4\%$)6,001 ($88.4\%$)23,616 ($91.5\%$)*Papillary serous* cystadenocarcinoma (b)$\frac{8460}{3116}$ ($2.0\%$)150 ($2.3\%$)220 ($3.3\%$)332 ($4.9\%$)818 ($3.2\%$)Clear cell adenocarcinoma (b)$\frac{8310}{384}$ ($1.4\%$)88 ($1.4\%$)102 ($1.5\%$)167 ($2.5\%$)441 ($1.7\%$)*Serous cystadenocarcinoma* (b)$\frac{8441}{31}$ ($0.02\%$)3 ($0.1\%$)11 ($0.2\%$)168 ($2.5\%$)183 ($0.7\%$)Carcinoma, undifferentiated (b)$\frac{8020}{337}$ ($0.6\%$)46 ($0.7\%$)40 ($0.6\%$)35 ($0.5\%$)158 ($0.6\%$)*Adenosquamous carcinoma* (a)$\frac{8560}{357}$ ($1.0\%$)59 ($0.9\%$)30 ($0.5\%$)10 ($0.2\%$)156 ($0.6\%$)*Papillary adenocarcinoma* (a)$\frac{8260}{380}$ ($1.4\%$)35 ($0.6\%$)18 ($0.3\%$)3 ($0.04\%$)136 ($0.5\%$)*Mucinous adenocarcinoma* (a)$\frac{8480}{343}$ ($0.7\%$)14 ($0.2\%$)39 ($0.6\%$)20 ($0.3\%$)116 ($0.5\%$)*Endometrioid adenocarcinoma* (a)$\frac{8380}{322}$ ($0.4\%$)14 ($0.2\%$)9 ($0.1\%$)19 ($0.3\%$)64 ($0.3\%$)Carcinoma (b)$\frac{8010}{310}$ ($0.2\%$)10 ($0.2\%$)18 ($0.3\%$)17 ($0.3\%$)55 ($0.2\%$)Squamous cell carcinoma (b)$\frac{8070}{36}$ ($0.1\%$)10 ($0.16\%$)9 ($0.1\%$)4 ($0.1\%$)29 ($0.1\%$)Adenocarcinoma with squamous metaplasia (a)$\frac{8570}{313}$ ($0.2\%$)2 ($0.03\%$)7 ($0.1\%$)1 ($0.01\%$)23 ($0.1\%$)*Neuroendocrine carcinoma* (b)$\frac{8246}{30}$ ($0.0\%$)0 ($0.0\%$)1 ($0.01\%$)7 ($0.1\%$)8 ($0.03\%$)*Mucinous cystadenocarcinoma* (a)$\frac{8470}{31}$ ($0.02\%$)1 ($0.02\%$)0 ($0.0\%$)5 ($0.1\%$)7 ($0.03\%$)Small cell carcinoma (b)$\frac{8041}{30}$ ($0.0\%$)1 ($0.02\%$)3 ($0.04\%$)1 ($0.01\%$)5 ($0.02\%$)Carcinoma, anaplastic (b)$\frac{8021}{31}$ ($0.02\%$)0 ($0.0\%$)1 ($0.01\%$)1 ($0.01\%$)3 ($0.01\%$)Mesonephroma, malignant (c)$\frac{9110}{32}$ ($0.03\%$)0 ($0.0\%$)0 ($0.0\%$)0 ($0.0\%$)2 ($0.01\%$)Adenoid cystic carcinoma (c)$\frac{8200}{30}$ ($0.0\%$)1 ($0.02\%$)0 ($0.0\%$)0 ($0.0\%$)1 ($0.0\%$)Cystadenocarcinoma (a)$\frac{8440}{30}$ ($0.0\%$)0 ($0.0\%$)1 ($0.01\%$)0 ($0.0\%$)1 ($0.0\%$)Large cell carcinoma (c)$\frac{8012}{30}$ ($0.0\%$)0 ($0.0\%$)1 ($0.01\%$)0 ($0.0\%$)1 ($0.0\%$)Transitional cell carcinoma (c)$\frac{8120}{30}$ ($0.0\%$)0 ($0.0\%$)1 ($0.01\%$)0 ($0.0\%$)1 ($0.0\%$)Total5,933 ($100.0\%$)6,406 ($100.0\%$)6,694 ($100.0\%$)6,791 ($100.0\%$)25,824 ($100.0\%$)(a) Low risk ($$n = 24$$,119), (b) High Risk ($$n = 1$$,700), (c) Other ($$n = 5$$)
## Results
In total 59,432 cases of endometrial carcinomas, diagnosed from 1960–2014, meeting the inclusion criteria, were identified. After exclusions (Fig. 1) 54,825 remained for survival analyses.
The number of endometrial cancer cases doubled during the studied time period (Table 2) and the crude incidence increased from $\frac{16.2}{100}$ 000 women in 1960 to $\frac{28.6}{100}$ 000 in 2014. The share of cases in the younger age groups, < 55 years of age, have decreased over time from $31\%$ in the first decade, to $9\%$ at the end of the study period. The decrease was also found in absolute numbers despite an increasing population. The increase in incidence was also observed after age standardization to the World Health Organization 2000–2025 standard population, from 1960 to 2005, after which there was a slight decrease (Fig. 2). High risk endometrial cancers such as clear cell adenocarcinomas and serous carcinomas increased in incidence since 2005 (Fig. 2). There was a gradual shift in age at onset (Fig. 3). The age-specific incidence decreases in the younger age groups but increases substantially in women above 60 years of age. Table 2Number of women diagnosed with endometrial carcinoma, and eligible for survival analyses in age-groups related to time periods1960-691970-791980-891990-992000-092010-14TOTALMEDIAN AGE (RANGE)60 (23–95)62 (22–97)64 (24–96)68 (20–105)69 (23–104)69 (25–99)66 (20–105)AGE GROUPS:18–44337 ($5.0\%$)312 ($3.8\%$)250 ($2.8\%$)168 ($1.5\%$)178 ($1.4\%$)120 ($1.8\%$)1,365 ($2.5\%$)45–541,772 ($26.3\%$)1,946 ($23.8\%$)1,327 ($15.0\%$)1,315 ($11.8\%$)1,057 ($8.1\%$)487 ($7.2\%$)7,904 ($14.4\%$)55–642,107 ($31.3\%$)2,557 ($31.3\%$)2,875 ($32.5\%$)2,916 ($26.1\%$)3,478 ($26.6\%$)1,613 ($23.8\%$)15,546 ($28.4\%$)65–741,698 ($25.2\%$)2,130 ($26.0\%$)2,611 ($29.5\%$)3,690 ($33.0\%$)4,087 ($31.2\%$)2,348 ($34.6\%$)16,564 ($30.2\%$)75 +816 ($12.1\%$)1,234 ($15.1\%$)1,783 ($20.2\%$)3,090 ($27.6\%$)4,300 ($32.8\%$)2,223 ($32.7\%$)13,446 ($24.5\%$)TOTAL6,730 ($100.0\%$)8,179 ($100.0\%$)8,846 ($100.0\%$)11,179 ($100.0\%$)13,100 ($100.0\%$)6,791 ($100.0\%$)54,825 ($100.0\%$)Fig. 2Age-standardized incidence of endometrial carcinomas per 100,000 women standardized to the world population. High risk morphology (as specified in Table 1 (b)) also shown separately from 1995–2014. Lowess = locally weighted scatterplot smoothingFig. 3Age-specific incidence rates of endometrial cancer per 100,000 women according to time periods In 2010–2014 $80\%$ of the patients were diagnosed in stage I or II (Table 3). There was an improvement in registration of stage between the two time periods with the percentage of patients with missing stage decreasing from 21 to $5\%$. There was a decrease in stage II ($p \leq 0.0001$) and a slight increase in stage I cases ($p \leq 0.0001$). There was also an increase in stage IV cases ($p \leq 0.0001$).Table 3FIGO stage of endometrial carcinoma related to time periods. Difference between the two time periods is shown with non stage cases (missing) excluded to enable comparisonsFIGO STAGE2005-092010-14TOTALDIFFERENCE*I3859 ($57.7\%$)4924 ($72.5\%$)8783 ($65.1\%$) + $3.2\%$ ($p \leq 0.0001$)II721 ($10.8\%$)517 ($7.6\%$)1238 ($9.2\%$)- $5.6\%$ ($p \leq 0.0001$)III507 ($7.6\%$)640 ($9.4\%$)1147 (8,$5\%$) + $0.3\%$ ($$p \leq 0.56$$)IV203 ($3.0\%$)382 ($5.6\%$)585 ($4.3\%$) + $3.1\%$ ($p \leq 0.0001$)MISSING1404 ($21.0\%$)328 ($4.8\%$)1732 ($12.9\%$)TOTAL6694 ($100.0\%$)6791 ($100.0\%$)13,485 ($100.0\%$)*Difference between the two periods in percentage in each stage (excluding missing) and p-value for test of statistical significance within each stage There was a trend of improved survival over the entire study period regarding both 1-, 2- (not shown), 5- and 10-year net survival (NS) rates for women above 55 years of age (Fig. 4). The youngest age groups have excellent survival during the whole period. For women under 45 years of age there was a drop in NS during the 1990s. Fig. 4Time trends for 5- (a.) and 10-year (b.) net survival according to age groups The survival trends for low- and high risk morphologies are shown in Fig. 5. There is a great difference in 5-year NS for low- and high risk morphologies with low risk morphologies approaching $90\%$, and high risk morphologies approaching $60\%$ 5 year NS at the end of the period. Fig. 5Trends for 5-year net survival standardized to the International Cancer Survival Standard (ICCS-1) for low risk versus high-risk morphology. $95\%$ confidence intervals are shown as shadowed areas
The NS is significantly worse for high risk morphology patients also when separated into stage I-II versus stage III-IV (Fig. 6). 5-year NS in with low risk morphology stage I-II is approximately $95\%$, and in high risk morphology stage III-IV only $30\%$.Fig. 6Trends for 5-year net survival standardized to the International Cancer Survival Standard (ICCS-1), for low risk versus high-risk morphology, and early FIGO stage I-II and advanced FIGO stage III-IV. $95\%$ confidence intervals showed as shadowed areas The majority of excess mortality occurred during the first three years after diagnosis for both low risk morphology patients (endometrioid endometrial cancer) and high-risk morphology patients (non-endometrioid endometrial cancer) (Fig. 7). The NS in endometrioid patients was improved from 1995–1999 to 2010–2014 with NS of approximately $89\%$ at 5 years and only slightly decreased during further follow up. In morphological high-risk tumors, the NS was not significantly increased, approximately $57\%$ at 5 years. Fig. 7Net Survival (lines) with confidence intervals (shadowed areas) in low- risk morphology (endometrioid endometrial cancer) compared with high-risk morphology (serous and clear cell endometrial cancer)
## Discussion
This study observed an increased incidence of endometrial cancer from 1960 to 2005, and thereafter a small decline. Increased incidence has also been shown in other European countries such as the UK and Norway [17, 18]. This is however not consistent with for example the US, where incidence declined 1975–1987, was stable 1987–2006 and increased slightly 2007–2017[19]. In Denmark incidence increased 1943–1983 after which it decreased somewhat, and thereafter stabilized [18].
The net survival improved gradually from the 1960s to 2014 with a 5 year NS increasing from $69\%$ to $86\%$. The most prominent improvement in NS was found in the elderly women above 75 years of age. Improved survival has also been seen in Norway, Denmark and Finland [18]. In contrast there has been a decrease in survival in the United States [20].
There are several factors that likely contribute to the increase in incidence of endometrial cancer during the study period. The average lifespan in women increased from 74.9 to 84.1 years and the population above 65 years increased by a factor of 2.3 [21]. The median age at diagnosis increased from 60 to 69 years of age. The number of cases of endometrial cancer doubled during the studied period while the female population during this time increased only by $30\%$ [21]. The ageing population affects the increase in crude incidence, but the increase is also observed in the age standardized incidence. There is a general shift over time towards diagnosis at an older age, with not only an increasing incidence at older ages but also a decrease of cases in women less than 55 years of age, where the decrease is not only in shares but also in absolute numbers. This is not likely to be explained by the use of combined oral contraceptives considering their long-term protective potential [5]. The protective effect should then likely be seen also at older ages. There is however a trend towards use of oral contraceptives and intrauterine devices with progestins at younger ages which may reduce the incidence [22]. Age standardization to World Health Organization 2000–2025 standard population was chosen to facilitate international comparisons. Since the Swedish population is significantly older, the incidence would have been greater if we had chosen to age standardize to a Swedish population. Furthermore, the upward shift in age at diagnosis (shown in Fig. 3) affects the increase in incidence. Since incidence is decreased at lower ages and increased at higher ages the increase in incidence is not as visible when the material is age standardized to a younger population such as the World Health Organization 2000–2025 standard population.
There have been significant changes in the prevalence of risk factors over time. Obesity increases among Swedish women and the prevalence of body mass index of ≥ 30 kg/m2 has increased from $7\%$ in 1985 to 11–$13\%$ in 2000 and $17\%$ in 2012 [23, 24]. Parity has decreased from an average of 2,17 children/woman in 1960 to 1,88 in 2014 [21]. Smoking has been shown to be protective against endometrial cancer [1, 2] and the rate of smoking has gradually decreased in Sweden during the study period [25]. Sales of menopausal hormone therapy increased rapidly in Sweden from the late 1980s to peak in 1999 and thereafter declined dramatically until 2017 [26]. Of menopausal hormone therapy sold in 1999, $59\%$ was as fixed combinations of estrogen and gestagens and $41\%$ as unopposed estrogen or in combination with gestagen via separate prescriptions [26]. The changes in menopausal hormone therapy cannot clearly be seen to affect the incidence in this material. This may be due to the fact that unopposed estrogen was not widely spread, or the effect may be hidden in other changes over time.
Improved diagnostical efficacy with transvaginal ultrasonography and endometrial biopsies have probably contributed to the increased incidence with fewer missed endometrial cancer cases. The registered increase in clear cell carcinomas and serous carcinomas is likely a reflection of a shift in morphological diagnostics. Diagnostic advances have been made especially in immunohistochemistry. P53 helps to identify serous adenocarcinoma [27] and Napsin A may be used as a marker for clear cell carcinomas [28].
There has been variation over time in the number of hysterectomies performed on benign indications, which affects the incidence of endometrial cancer, since a previous hysterectomy protects from the disease. There was an increase in hysterectomies performed from $\frac{178}{100}$ 000 in 1987 to $\frac{232}{100}$ 000 in 1999. After this, the number of hysterectomies went down to $\frac{210}{100}$ 000 in 2003 and has thereafter continued to decrease by another $16\%$ until 2019 [29, 30]. The peak in hysterectomies was around the same time there was a peak in prescribed menopausal hormone therapy.
When comparing the distribution of stage over time there was a decrease in stage II and an increase in stage I cases (Table 3). There was also an increase in stage IV cases. These increases are still obvious when comparing shares of the staged cases, excluding the unstaged cases to eliminate the bias of a larger staged share in the later period. The FIGO stage I cases then increased from $72.95\%$ to $76.19\%$ and FIGO stage IV cases from $3.84\%$ to $5.91\%$. The lack of completeness in reporting stage during 2005–2009 compared with 2010–2014 makes conclusions more uncertain, but the decrease in stage II cases can logically not be a result of underreporting during the first period. The decrease in stage II- and increase in stage I-cases may be due to earlier diagnosis before progression from stage I. If this is true, coming studies should evaluate reasons for patients and doctors delay in patients with stage II or more to improve early discovery. The increase in stage IV could be due to improved diagnostics causing a shift upwards in stage when signs of spread become visible with improved imaging, such as more frequent use of CT-scan.
The trend of increased NS was observed for the whole study period. For reasons unknown, but maybe due to patients’ and doctors’ delay, the improved NS could not be found in the youngest patients. Since this group is small, the overall NS has however greatly improved. There have been several advances in the treatment of endometrial cancer during the study period, such as introduction of platinum-based chemotherapy in the 1980s [31]. The long-term continuing improvement is likely a combination of many small improvements happening over time, ranging from improved knowledge of prognostic factors and their importance in choice of treatment, to improved surgical methods gradually being implemented [32]. In Sweden the treatment of endometrial cancer has traditionally been characterized by a liberal use of both preoperative and postoperative radiation [33]. This tradition was broken by a treatment program in the Southern Health Care Region 1993 to 1996 [34], which minimized radiation therapy and showed no detrimental effect on survival. Since then, the use of adjuvant radiotherapy has gradually diminished and is reserved to a rather small fraction of patients with adverse prognostic factors. Other changes in treatment came after the implementation of the first Swedish National Guidelines for endometrial cancer in 2011. Preoperative high-risk tumors, defined as non-endometrioid histology (serous, clear cell carcinoma or carcinosarcoma), endometrioid adenocarcinoma FIGO grade 3, or non-diploid tumors, were recommended to be treated with a lymphadenectomy of the pelvic and para-aortic regions (up to the left renal vein) in addition to hysterectomy and salpingo-oophorectomy. Postoperatively, patients with high-risk histology and negative nodes were recommended chemotherapy ± brachytherapy and those with positive nodes or no lymphadenectomy were offered chemotherapy + external beam radiotherapy.
There were substantial differences in NS for different age groups with worse prognosis in the elderly, even though other causes of death were excluded in this way of analyzing NS. Similar observations have been made for other cancers, and a performance status with co-morbidity in older age may contribute to patients not being able to cope with treatment or complications of treatment as well as younger individuals [35]. It has previously been shown that the median age at onset is higher in type II endometrial cancer, which has a higher mortality rate [36], which likely contributes. Women above 75 years of age showed the greatest improvement of NS over time which may be accounted to improved treatment of co-morbidity and refined treatment both with minimal invasive surgery as well as improved chemotherapy treatment [34]. Improved anesthesiological methods and a changed attitude towards treatment of old women may also have contributed to improved NS in the older women. The lesser survival rates for women under 45 years of age might be due to delayed diagnosis, since abnormal bleedings before menopause may be less likely to be investigated.
This study is a nationwide, population-based study spanning 55 years, which combined with the high quality of the Swedish Cancer Register, with > $96\%$ coverage and very high morphological verification in the later period of the study [4, 12], are major strengths. Detailed morphology was not registered before 1993 and stage not before 2004. Therefore, trends for specific morphologies and stages could not be assessed for the full study period. Furthermore, the absence of central pathology is a limitation of the study.
There have been various changes in the classification of especially uterine sarcomas, why sarcomas were excluded. Carcinosarcomas are nowadays regarded and classified as high-risk carcinomas [1, 37]. They are however registered in the Cancer Registry together with sarcomas under site code ICD-7 174. Carcinosarcomas make up less than $5\%$ of all uterine malignancies in other studies [37] and in the Swedish Quality Register for Gynecological Cancer 2010–2018 carcinosarcomas accounted for $3\%$ of the endometrial cancers (personal communication).
## Conclusions
The incidence of endometrial cancer in Sweden has increased over the last 60 years. However, with improvement in treatment of the disease, and possibly due to earlier diagnosis, net survival has improved substantially among women aged 55 years and older at diagnosis.
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