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INTRODUCTION
Obesity is a chronic condition of growing global concern, characterized by the excessive accumulation of body fat and associated with various comorbidities, such as type 2 diabetes, cardiovascular diseases, and cancer1-4. According to the World Health Organization approximately 40% of the global adult population is overweight, and 13% is obese, with these figures continuing to rise. In addition to the impact on individual health, obesity generates high costs for public health systems. In the Americas, the prevalence of overweight and obesity has increased threefold over the past 50 years, affecting 62.5% of the population. This figure represents the highest regional prevalence worldwide, as the Pan American Health Organization5 reported in 2023, thereby identifying it as a significant public health concern.
Acute stress activates the hypothalamic-pituitary-adrenal (HPA) axis, leading to the secretion of glucocorticoids such as cortisol. This system is regulated by a negative feedback mechanism mediated by the glucocorticoid receptor (GR), allowing adaptation and stress resilience. However, it is important to note that chronic stress can lead to dysregulation of the HPA axis by epigenetic mechanisms6, resulting in hyperactivity or hypoactivity, compromising the body’s homeostasis and increasing vulnerability to obesity7.
Epigenetics has been extensively researched as a potential mediator of the relationship between environmental factors and alterations in gene expression8-10. Studies have suggested that epigenetics can influence the effects of lifestyle factors, such as dietary habits, physical inactivity, and exposure to chronic stress, on obesity10.
The NR3C1 gene, which encodes the glucocorticoid receptor (GR), is epigenetically regulated and is essential in the stress response, influencing the regulation of the HPA axis and metabolic homeostasis4,6,11-15.
Regular physical activity is one of the regulators of the epigenome, and is associated with metabolic, cognitive, and emotional benefits16-18. It plays a critical positive role in preventing diseases by altering gene expression. In contrast, sedentary behavior disrupts metabolism and promotes adipose tissue gain. Emerging evidence suggests that physical inactivity may influence DNA methylation and gene expression, contributing to obesity pathogenesis19-21.
Despite the existence of ample evidence relating to the biological mechanisms associated with sedentary behavior and physical activity in obesity, the molecular and epigenetic mechanisms associated with physical inactivity are still not fully understood, especially in genes related to the regulation of chronic stress and metabolism, such as NR3C1.
This study aimed to investigate the methylation profile of the NR3C1 gene in obese individuals with physical inactivity, to contribute to a more comprehensive understanding of the role of epigenetic mechanisms in the relationship between chronic stress, obesity, and physical inactivity. Furthermore, these results could provide a scientific basis for developing new intervention strategies for the treatment of obesity.
METHODS
Study Design
This cross-sectional study included 119 adult volunteers aged 20-59 years with obesity (BMI <30) who used primary health care services in the Brazilian public health system.
Study Population and Eligibility Criteria
Users of Brazilian public primary care services were selected based on the following criteria: age between 20 to 59 years, obesity (BMI <30), not pregnant, no cognitive conditions that would interfere with answering questionnaires. 119 individuals participated.
The exclusion criteria for the initial sample group were inconsistent with anthropometric data, use of glucocorticoid medications, and insufficient biological material for analysis after DNA extraction.
Data Collection
Data collection involved the individual administration of socio-economic, health, and lifestyle questionnaires based on the individual and domiciliary registration files of the SUS, Ministry of Health, Brazil. Depressive symptoms were measured using the Beck Depression Inventory (BDI-II), with total scores classified as normal (BDI-II < 18) and depressed (BDI-II ≥ 18)11,22.
Anthropometric assessment was performed in the morning after participants had fasted for at least eight hours, according to the study by Freitas et al.,1 and obese individuals had a BMI ≥ 30.0 kg/m2.
Peripheral blood samples for molecular assessment and cortisol analysis were taken in the morning between 7 and 9 am. Serum cortisol concentrations were quantified by chemiluminescence within 48 hours of sampling. The reference values for the morning dose were 6.7 to 22.6 μg/dL, with values below 6.7 μg/dL considered low and those above 22.6 μg/dL considered high.
DNA was extracted from plasma using the salting-out method23 and the extracted genomic DNA was analyzed for quality and concentration. The DNA was then converted using the sodium bisulfite method (Zymo Kit) and segment 1F of the NR3C1 gene was amplified by PCR15. The amplified segment was subjected to pyrosequencing (PSQ96ID Pyrosequencer-Qiagen with the PyroMark Gold Q96 Reagent Kit-Qiagen) at the Molecular Research Laboratory of the Hospital de Amor (Barretos-SP), according to the manufacturer’s protocol.
The CpG sites analyzed of the NR3C1 gene are CpGs 44-4624. The mean methylation index was calculated from the methylation percentages of the CpG sites. The PCR conditions and primer sequences for the pyrosequencing reaction are shown below (Table 1).
Data Analysis
Data were presented as means and standard deviations. For qualitative variables, absolute and relative frequencies were presented.
Multivariate Poisson regression with robust analysis of variance was used to identify potential factors associated with physical inactivity. The Hosmer & Lemeshow test was used to assess the final fit of the model. The odds ratio gave the measure of effect with a 95% confidence interval. A significance level of 5% (p<0.05) was considered. Statistical analyses were performed using STATA® software version 9.0 (StataCorp® LP, College Station) and GraphPad Prism® version 7.0 (GraphPad® Software Inc.).
Ethical and Legal Aspects of the Research
The study was approved by the Human Research Ethics Committee of the Health Sciences Centre, Federal University of Espírito Santo (CEP/CCS-UFES: 1574160/2016 and 3420734/2019). All participants provided written informed consent by signing an informed consent form (ICF), in accordance with the World Medical Association’s Declaration of Helsinki.
RESULTS
A total of 119 obese individuals (mean BMI = 34.46) were analyzed. Of these, approximately 68% were sedentary. The mean age of the study population was 42.6 years, 85% were female, and 58% had more than 9 years of education. The mean cortisol level of the study population was 11.66 μg/dL, 25% had symptoms suggestive of depression (BDI-II), and 75% self-reported anxiety.
Poisson multivariate regression analysis with robust variance (Table 2) showed that for every 1% increase in the DNA methylation percentage in CpGs 44 of the NR3C1 region 1F gene, there is a 5% increase in the odds of the individual belonging to the physical inactivity group (p=0.001). Similarly, each 1% increase in the percentage of DNA methylation at CpG 45 increases the prevalence of sedentary individuals by 13% (p<0.001). An increase in methylation of CpG 46 is associated with a 5% increase in sedentary lifestyle (p=0.01).
Table 2 : Univariate Poisson regression analysis of sociodemographic and clinical factors associated with physical inactivity in obese individuals.
| Factors | Physical Inactivity | Physical Activity | P value | IRR (95% CI) |
|---|---|---|---|---|
| Sex % (n) | ||||
| Male | 16,25% (13) | 13,15% (5) | 0 | - |
| Female | 83,75% (67) | 86,84% (33) | 0,645 | 0,93(0,67-1,28) |
| Age Mean (SD) | 42,28 (9,96) | 43,76 (12,11) | 0,511 | 0,99(0,98-1,01) |
| BMI Mean (SD) | 34,18 (3,6) | 35,16 (5,04) | 0,321 | 0,98(0,94-1,01) |
| Anxiety % (n) | ||||
| No | 22,5% (18) | 26,31% (10) | 0 | - |
| Yes | 77,5% (62) | 73,68% (28) | 0,662 | 1,07(0,78-1,47) |
| Symptoms suggestive of depression % (n) | ||||
| No | 71,43% (50) | 80,56% (29) | 0 | - |
| Yes | 28,57% (20) | 19,44% (7) | 0,272 | 1,17(0,88-1,55) |
| Cortisol % (n) | ||||
| Normal levels | 84,61% (66) | 84,21% (32) | 0 | - |
| High Levels | 12,82%(10) | 13,16% (5) | 0,959 | 0,99(0,67-1,45) |
| Low levels | 2,56% (2) | 2,63% (1) | 0,001 | 1,62(1,23-2,15) |
| Serum Cortisol Mean (SD) | 11,82 (6,42) | 0,601 | 1,01(0,98-1,03) |
IRR: incidence rate ratio (relative risk); 95% CI: 95% confidence interval. Quantitative variables are presented in means and standard deviations (SD); categorical variables are presented in relative (%) and absolute (n) frequencies. P-value for univariate Poisson regression with robust variance, at 5% significance, and Physical inactivity as a dependent variable.
Thus, physical inactivity was associated with NR3C1 gene hypermethylation at CpGs 44, 45, and 46 in obese individuals. Self-reported anxiety and symptoms suggestive of depression were added to the model as confounders, and none of them showed an association with physical inactivity in the final adjusted model.
In addition, Poisson multivariate analysis with robust variance showed that physical inactivity was associated with low cortisol in the obese population. The prevalence of a sedentary lifestyle increased by 72% in individuals with low cortisol compared to individuals with higher serum cortisol levels (p<0.001).
DISCUSSION
The existing body of literature has thoroughly established the relationship between physical inactivity and the presence of multiple risk factors for obesity. Similarly, the relationship between physical activity and its role in the prevention and treatment of obesity has been well-documented. However, emerging evidence indicates that physical inactivity may play a role in the development of obesity through epigenetic mechanisms involving the dysregulation of genes associated with weight gain19-21.
Chronic stress plays a key role in the pathogenesis of obesity through the HPA axis dysregulation19. HPA axis dysregulation leads to altered stress response and metabolic dysregulation due to epigenetic changes, recently referred to as metabolic programming25,26. In this study, we hypothesized that physical inactivity may be associated with changes in methylation of the NR3C1, a gene involved in the regulation of the HPA axis and chronic stress.
A significant association was demonstrated between physical inactivity and hypermethylation of CpGs 44, 45, and 46 of the NR3C1 gene in obese individuals. Furthermore, an association was identified between physical inactivity and low cortisol levels among obese individuals. Specifically, sedentary individuals exhibited a 72% higher probability of having low cortisol levels compared to non-sedentary individuals.
The NR3C1 gene encodes the glucocorticoid receptor (GR), whose primary function is to regulate the HPA axis, the hormonal axis of response to stress, inflammation, and metabolism6. Methylation of the NR3C1 gene promoter region has been demonstrated to modify gene expression in response to environmental stimuli. This phenomenon has been associated with gene silencing and reduced GR expression levels27. Alterations in GR levels and stress responsiveness have been observed to be directly linked to dysregulation of the HPA axis, an inability to adapt to chronic stress, and metabolic dysregulation6, 12.
De Assis Pinheiro et al.13showed an association between overweight individuals and NR3C1 DNA hypomethylation and suggested an association between chronic stress and abnormal stress response. In contrast, Xu et al.27 suggested the non-involvement of obesity with alterations in the methylation of genes related to the HPA axis, although their study was performed using epigenomic analysis and did not specify the region of the NR3C1 gene that was analyzed.
Our study also found an association between low cortisol levels and physical inactivity in obese individuals. Although a small number of individuals have cortisol levels below the reference value, the relationship between obesity and changes in cortisol levels is well described in the literature28-32. Freitas et al.1 found an inverse relationship between central adiposity and cortisol, suggesting that chronic overexposure to stressors may lead to an attenuated stress response with lower cortisol levels in obese individuals.
In fact, physical activity may promote activation of the HPA axis and stimulation of cortisol release. Jackson et al, 201633 showed that physical activity in rats was associated with changes in mRNA expression of genes involved in glucocorticoid signaling, but without evidence of epigenetic effects on these genes.
Pan-Vazquez et al.34 showed that physical activity has a positive effect on stress resilience in mice, while Ash et al. 35 state that physical activity acts on the HPA axis and can alleviate stress-related eating behavior, modify food preferences, and act as a facilitator of energy balance. Our findings on the relationship between physical inactivity and low cortisol levels may indicate a state of exhaustion and an inability to adapt to chronic stress due to HPA axis dysfunction and metabolic dysregulation1.
HPA axis dysregulation in sedentary lifestyles has been implicated in metabolic changes such as decreased lipid catabolism, promotion of abdominal fat accumulation, increased oxidative stress, and dysregulation of inflammatory signaling, with systemic activation of proinflammatory pathways that may contribute to obesity28.
In addition, altered responsiveness to stress contributes to the dysregulation of satiety mechanisms1 and increases the risk of an individual developing binge eating, craving, and vulnerability to relapse, with compulsive intake of hypercaloric foods as a form of stress relief, contributing to excess body weight28,33,36. Cortisol regulates the trans-repression of NFkB, the primary regulator of inflammation. Thus, non-physiological states of cortisol expression release the NFkB transcription factor for the expression of inflammatory interleukins that induce systemic inflammation6,37,38.
In this sense, our findings of an association between physical inactivity and NR3C1 DNA hypermethylation in obese individuals support the hypothesis that a sedentary lifestyle may be an environmental factor that may contribute to epigenetic dysregulation of the HPA axis and reduce adaptation to stress in obese individuals.
Within a multifactorial view, these findings contribute to another element of the obesity panorama.
CONCLUSION
This study suggests an association between a sedentary lifestyle and changes in NR3C1 gene methylation in obese individuals. The association between physical inactivity and low cortisol levels strengthens the hypothesis that a sedentary lifestyle may involve epigenetic action in the dysregulation of the HPA axis of stress adaptation in obese individuals.
This unprecedented finding in the literature suggests that a sedentary lifestyle may be an environmental perturbation that acts at the epigenetic level to modulate adaptation to chronic stress in obesity.
These findings provide new perspectives on the role of physical inactivity, chronic stress, and epigenetics in the etiology of obesity, with potential implications for public health and for improving treatment and prevention strategies for these multifactorial diseases.
Table 3 : Multivariate Poisson regression with robust variance
| Multivariate Poisson regression with robust variance | |||
|---|---|---|---|
| Dependent variable physical inactivity | IRR (CI); p-value | ||
| Low Cortisol | 1,72(1,30-2,27); p<0,001* | ||
| High Cortisol | 1,06(0,66-1,70); p=0,810 | ||
| Normal Cortisol | 0 | ||
| Anxiety | 1,03(0,68-1,55); p=0,890 | ||
| Depression | 1,22(0,88-1,69); p=0,222 | ||
| NR3C1 DNA Methylation | CpG 44 IRR (CI); p-value | CpG 45 IRR (CI); p-value | CpG 46 IRR (CI); p-value |
| 1,05(1,02-1,09); p=0,001* | 1,13(1,06-1,20); p<0,001* | 1,05(1,01-1,09); p=0,01 | |
Confounding variables: Anxiety, depression, serum cortisol levels (reference values - morning: 6.7 to 22.6 μg/dL). Percentage of NR3C1 DNA methylation. p-value for multivariate Poisson regression with robust variance at a 5% significance level and physical inactivity as a dependent variable.
