Alcohol consumption, depression, overweight and cortisol levels as determining factors for NR3C1 gene methylation

The NR3C1 glucocorticoid receptor (GR) gene is a component of the stress response system, which can be regulated by epigenetic mechanisms. NR3C1 methylation has been associated with trauma and mental issues, including depression, post-traumatic stress, anxiety, and personality disorders. Previous studies have reported that stressful events are involved in NR3C1 gene methylation, suggesting that its regulation under environmental effects is complex. The present study aimed to analyze associations involving stressors such as socioeconomic status, health conditions, and lifestyle in relation to NR3C1 methylation in adults. This study included 386 individual users of the Brazilian Public Unified Health System (SUS), and evaluated socioeconomic and health conditions, body mass index, cortisol levels, and lifestyle. Data were correlated with NR3C1 methylation, determined using DNA pyrosequencing. The results showed that alcohol consumption, overweight, and high cortisol levels were related to NR3C1 demethylation, while depression was related to its methylation. Habits, lifestyle, and health status may influence NR3C1 gene regulation via methylation, revealing the complexity of environmental impacts on NR3C1 methylation.

Population characteristics. This study was made up of a convenient sample of 386 individuals aged between 20 and 59 years who were users of the Brazilian Primary Health Care Units. Based on individual SUS registration forms, data were collected through individual interviews that evaluated socioeconomic, health, and lifestyle conditions. Low-income was defined as a per capita income/day less than US$5 (5 American dollars) 45 . Marital status, age, working conditions, and education (< 8 years, 8-11 years, and higher education) were also analyzed.
To assess habits and lifestyle features such as alcohol and tobacco consumption, in addition to leisure and physical activity, a structural questionnaire was applied based on the Research Directorate Work Coordination and Income Questionnaire for residents of households from the National Health Survey (NHS) 46 .
In this evaluation, the possible responses to alcohol and tobacco consumption were: (1) currently consuming, (2) used in the past, (3) never used, and for statistical analysis, responses were dichotomized into current consumption: no/yes. In addition, regarding leisure and physical activity, the possible answers for their activity were: (1) weekly, (2) biweekly, (3) monthly, and (4) not performed, dichotomized into yes/no activity.
In the same questionnaire, we addressed self-perceived health status in which the possible answers were: (1) very good, (2) good, (3) regular, (4) bad, (5) very bad, and were dichotomized into: good or very good/regular or poor health for statistical modeling.
Symptoms suggestive of depression were assessed using the Beck Depression Inventory-II (BDI-II) 47 . Values were categorized according to Gomes-Oliveira et al. 48 considering normal or mild mood disorders (BDI-II < 17), and symptoms suggestive of depression (BDI-II ≥ 17).
Anthropometric assessment was carried out by qualified professionals using the Food and Nutrition Surveillance System (SISVAN) 49 , which collects information for directing public policies of the Brazilian Unified Health System (SUS). Information such as weight and height were collected, and from the obtained data, body mass index (BMI) was calculated and classified according to the World Health Organization 50 .
Blood analysis. For analysis of cortisol and vitamin D levels and DNA methylation, 10 mL of peripheral blood was collected from patients by venipuncture after fasting for at least 8 h as instructed by community health agents (CHA). In a tube containing ethylenediaminetetraacetic acid (EDTA) anticoagulant, 3 mL of the sample was transferred for molecular analysis, and 2 mL into a tube containing NaF (sodium fluoride) anticoagulant for vitamin D analysis. The remaining blood was transferred to a tube without anticoagulant but containing a separating gel to obtain serum to determine cortisol levels. The tube contents were homogenized by inversion 5-8 times, and stored in refrigerated coolers over the range of − 2 to 8 °C. Blood samples for biochemical evaluation of cortisol and vitamin D levels were transported to Hermes Pardini Laboratory, Belo Horizonte, MG, while samples for DNA extraction were transported to the Biotechnology Laboratory, at the Center for Exact, Natural and Health Sciences, at the Federal University of Espírito Santo (CCENS/UFES).
Cortisol levels and vitamin D abundance were quantified by chemiluminescence, with reference values for morning cortisol levels of 6.7-22.6 μg/dL 17  Quantitative pyrosequencing methylation assay. Of all samples with good DNA quality and concentration, a subsample of 285 patients was randomly assigned to undergo pyrosequencing methylation assays.
Sodium-bisulfite conversion of 1 μg of DNA was performed using the EpiTect Bisulfite Kit (Qiagen, Valencia, CA, USA), following the manufacturer's recommendations. Pyrosequencing methylation assays were performed as previously described 53,54 .
PCR product quality was checked on 2% agarose gels using GelRed (Uniscience). Pyrosequencing was performed using a PSQ 96 ID Pyrosequencer (Qiagen, Valencia, CA, USA) with PyroMark Gold Q96 Reagent Kit (Qiagen), according to the manufacturer's protocol. All pyrosequencing conditions are listed in Table 1.
A single pyrosequencing reaction was performed for each individual, and the reaction was evaluated for quality. The percentage of methylation was recorded for each CpG from 40 to 47, individually and on average, evaluated in PyroMark Q96 ID Software 2.5 version 2.5.10.7, using default software settings. In this study, we considered all methylation levels detected in pyrosequencing to classify individuals as methylated or unmethylated, when they presented methylation at any percentage above zero.
A representative scheme of the amplified 1F region of NR3C1 and the eight CpGs site-specific analyzed using bisulfite-pyrosequencing assays are shown in Fig. 1.
Statistical analysis. Data were analyzed using Chi-squared tests in a 2 × 2 contingency table and a statistical significance level of 5%. Quantitative data are expressed as median and interquartile ranges.
Results of quantitative analysis of NR3C1 gene methylation did not follow a normal distribution, even after exponential conversion. In this manner, the methylation data were dichotomized. The mean methylation values of CGs segment from 40 to 47 were calculated for qualitative analysis such that values > 0 were categorized as methylated, and values equal to 0 were categorized as unmethylated. Then, applied bivariate analyses were performed Table 1. PCR and Pyrosequencing primers and conditions.

PCR primer Conditions
Forward 5′-TTT TTT TTT TGA AGT TTT TTTA-3 www.nature.com/scientificreports/ using Poisson regression models with robust variance, with the dependent variable being methylation of the segment, and as explanatory variables socioeconomic aspects, health, and lifestyle, as well as suggestive symptoms of depression. After data characterization, independent variables were recategorized dichotomously according to the classifications in normal state/altered states before being included in the multivariate study model. Predictive variables that achieved p values lower than 0.20 (p < 0.20) were inserted into the multivariate Poisson regression model with robust variance. The backward method was used, and those variables with less significance (greater p value) were removed one by one from the model. The procedure was repeated until all variables present in the model were statistically significant (p < 0.05). The Hosmer-Lemeshow test was used to verify the fit of the final model. The prevalence ratio (PR) with 95% confidence interval (95% CI) was used as an effect measure. For all analyses, a significance level of 5% was adopted. Statistical analyses were performed using SPSS software (v.13.0 for Windows) and Stata v.11.0.

Results
Socioeconomic profile. Our results were obtained from a total of 285 individuals evaluated by pyrosequencing of the NR3C1 1F region; 198 individuals did not show any percentage of methylation detected, whereas 87 exhibited measurable percentages of methylation. The median methylation level was 0.0 (0.0-12.9%). Table 2 presents a population description, which was divided into unmethylated and methylated. Individuals were predominantly female (80.6%), 75% lived with a partner, and the median age was 42.5 (33.7-52.0) years. Most of them had < 8 years of formal education (46.4%), low income (70.2%), did not drink, smoke, or perform physical or leisure activities.
Methylation analysis of NR3C1. The average methylation index was calculated from CpG sites methylation percentages. These percentages were dichotomized into unmethylated (0% methylation) and methylated (values > 0% methylated).
From variables in the Bivariate Poisson regression with values p < 0.20, the multivariate model was designed. The results showed that methylation is associated with alcohol consumption, depression, BMI, and high cortisol levels ( Table 4).
As observed in Table 4, alcohol consumption was associated to 70% decrease in the prevalence of methylation (1-0.30 × 100); being overweight showed a 34% lower prevalence of methylation than not being overweight (1-0.66 × 100), and high cortisol was associated with a lower prevalence of methylation, however with a measure of low effect PR = 0.09 -5 . In contrast, depression exhibited the opposite effect, being directly related to methylation with prevalence of 55% higher than non-depressed individuals (1.55 times more prevalent).
The final model was statistically significant (p < 0.001), presenting a pseudo r 2 = 0.0759 and, after adjustment by Hosmer and Lemeshow, showed good adherence (p = 0.99).

Discussion
This study presents individuals with low income, low education, and predominantly of female gender. Our goal was to establish a broader assessment of factors related to NR3C1 gene methylation, such as socioeconomic aspects, health, and lifestyle.
We have shown that alcohol consumption, overweight, and high cortisol levels are related to NR3C1 nonmethylation, while depression is related to its methylation. Argentieri et al. 16 presented a series of studies that related hyper-or hypomethylation with specific CpG methylation of this gene.
Few studies have evaluated the relationship between methylation patterns and alcohol consumption. It was expected that alcohol as a stressor factor could stimulate the HPA axis by increasing cortisol levels and NR3C1 methylation. Gatta et al. 24 reported hypermethylation of NR3C1 exon 1H in the prefrontal cortex of individuals with alcohol abuse disorders compared with that in a control group. However, our data showed low levels of NR3C1 1F region methylation. Corroborating our findings, Dogan et al. 25 showed a relationship between alcohol consumption and decreased levels of NR3C1 methylation in a 64-patient cohort.
Studies have demonstrated that alcohol consumption may lead to HPA axis alterations, with glucocorticoid release modifications 55,56 . Here, we showed association between alcohol consumption and NR3C1 methylation, which indicated that alcohol-mediated modulation of the HPA axis may occur through epigenetic changes.
Although self-reporting of alcohol consumption was insufficient to control its effects on NR3C1 methylation, our finding is relevant because alcohol represents a large fraction of the drugs consumed by the world population, and the epigenetic effects induced by its consumption are still little known.
Our analysis showed an association between suggestive symptoms of depression, as evaluated by Beck scores ≥ 17, with increased methylation at NR3C1 40-47 1F CpGs sites. Other authors have associated methylation alterations in the 1F region CpG 36-39 sites with depressive status in adolescents 57 and in CpGs 36-44 on maternal exposure to gestational stress and depression in children 58 .
In addition, other authors have studied the 1F region, showing hypomethylation involving CpGs 35-47, with hypomethylation specifically of CpG 43 associated with depression 59 . There are also studies addressing the 1F region showing hypomethylation of CpGs 35-39 in individuals with depression 19 . However, the present study provides new information that individuals with depressive symptoms, and frequent use of the public health system, exhibit methylation of the NR3C1 1F region.
In this manner, it is possible that NR3C1 methylation is associated with depression, in that NR3C1 gene methylation may indicate lower mRNA levels and GR expression, leading to imbalanced HPA axis modulation, which could result in abnormal responses to stress, and increase susceptibility to depression 33 www.nature.com/scientificreports/ Furthermore, high cortisol levels were associated with non-methylation, but with a very low prevalence ratio (Table 4). High levels of cortisol have already been related to NR3C1 gene methylation in maternal and postnatal gestational exposure to childhood stress 14,33,60 .In our study, only 8 individuals presented high cortisol levels, while the others had normal or low levels, but which may not be representative.
On the contrary, multivariate analysis of risk factors showed that being overweight is associated with non-methylation, with a prevalence ratio of 0.67, indicating that being overweight reduces the prevalence of