A polygenic score for body mass index is associated with depressive symptoms via early life stress: Evidence for gene-environment correlation

Evaluating the association between lifestyle factors and heel bone mineral density in different inflammatory states

Rationale

It is unclear whether lifestyle factors affect bone mineral density (BMD) during different inflammatory states.

Objective

This study investigated the effects of coffee consumption, vitamin D (VD) intake, smoking, and alcohol consumption on heel BMD in adults with different inflammatory states.

Methods

The phenotypic data from 249,825 participants were analyzed using the UK Biobank cohort. The inflammatory status was evaluated using C-reactive protein (CRP) levels and the systemic immune-inflammation index. Linear regression analysis was used to examine the association between coffee consumption, VD, smoking, alcohol consumption, and heel BMD in adults with different inflammatory states. Linear regression models were used to analyze the interaction between inflammation and the four lifestyle factors with respect to their influence on heel BMD in adults.

Results

Our findings revealed that VD was positively associated with adult heel BMD (β = 2.41 × 10-2, SE = 5.14 × 10-3, P = 2.72 × 10-6), while alcohol consumption and smoking were negatively associated with adult heel BMD. Coffee was negatively associated with adult heel BMD in low inflammatory states (β = -1.27 × 10-2, SE = 4.79 × 10-3, P = 8.00 × 10-3), while there was no association between coffee and adult heel BMD in high inflammatory states. Overall, it was found that these four lifestyle factors interacted negatively with inflammatory states.

Conclusion

Our study suggests that VD is positively associated with adult heel BMD and that alcohol consumption and smoking are negatively associated with adult heel BMD. Coffee may reverse the adverse effects of inflammation on BMD when the patient is in a highly inflammatory state, thus acting as a protective agent against heel BMD in adults.

Polygenic Scores and Networks of Psychopathology Symptoms

Importance

Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology.

Objective

To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms.

Design, Setting, and Participants

Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included.

Main Outcomes and Measures

Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS.

Results

Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041).

Conclusions and Relevance

Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Plant-based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort

OBJECTIVE

The study's objective was to examine whether adherence to three plant-based dietary indices (PDIs) mediated or moderated genetic susceptibility to obesity.

METHODS

Baseline participants were 7037 adults (57% women, aged 55.6 ± 7.7 years) from the CARTaGENE cohort of Quebec adults. Two polygenic risk scores for BMI (PRS-BMI), 92 single-nucleotide polymorphisms and 2 million single-nucleotide polymorphisms, and three plant-based scores were calculated (overall, healthy, and unhealthy). Follow-up participants were 2258 adults with data on obesity outcomes, measured 6 years later. General linear models were used to examine the relationships between PRSs and PDI scores on obesity outcomes. Causal mediation analyses were conducted to assess mediation and interaction models.

RESULTS

The overall- and healthy-PDIs and PRSs were significantly associated with obesity outcomes. Adherence to PDIs did not mediate or moderate genetic susceptibility to obesity. Associations between PRSs and obesity outcomes were partly mediated by meat intake cross-sectionally and whole grains intake among males both cross-sectionally and longitudinally. Higher meat intake had a positive association with obesity outcomes, whereas higher whole grains intake had an inverse association.

CONCLUSIONS

These findings suggest that components of a plant-based diet and a shift away from animal products, specifically meat, might be beneficial for nutrition interventions, particularly among individuals with higher genetic risk of obesity.

Polygenic and environmental determinants of tics in the Avon Longitudinal Study of Parents and Children

Tourette syndrome (TS) is caused by multiple genetic and environmental factors. Yet, little is known about the interplay of these factors in the occurrence of tics. We investigated whether polygenic risk score (PRS) of TS and pregnancy-related factors together enhance the explained variance of tic occurrence in the Avon Longitudinal Study of Parents and Children (Ncases  = 612; Ncontrols  = 4,201; 50% male; mean age 13.8 years). We included a cumulative adverse pregnancy risk score, maternal anxiety and depression, and maternal smoking and alcohol use during pregnancy. We investigated possible joint effects of genetic and pregnancy-related risk factors using a multivariable approach, and explored mediation effects between the pregnancy-related risk factors in explaining tic presence. The PRS and the cumulative adverse pregnancy risk score, maternal anxiety, or maternal depression explained significantly more variance of tic presence compared to models including only the PRS. Furthermore, we found that the cumulative adverse pregnancy risk score mediated the association between several pregnancy-related factors (maternal anxiety, depression, and smoking) and tics. The combination of a PRS and pregnancy-related risk factors explained more variance of tics in a general population cohort compared to studying these factors in isolation.

Discrimination Exposure and Polygenic Risk for Obesity in Adulthood: Testing Gene-Environment Correlations and Interactions

INTRODUCTION

Exposure to discrimination has emerged as a risk factor for obesity. It remains unclear, however, whether the genotype of the individual can modulate the sensitivity or response to discrimination exposure (gene × environment interaction) or increase the likelihood of experiencing discrimination (gene-environment correlation).

METHODS

This was an observational study of 4,102 white/European Americans in the Health and Retirement Study with self-reported, biological assessments, and genotyped data from 2006 to 2014. Discrimination was operationalized using the average of nine Everyday Discrimination Scale items. Polygenic risk scores (PRSs) for body mass index (BMI) and waist circumference (WC) were calculated using the weighted sum of risk alleles based on studies conducted by the Genetic Investigation of Anthropometric Traits (GIANT) consortium.

RESULTS

We found that greater PRS-BMI was significantly associated with more reports of discrimination (β = 0.04 ± 0.02; p = 0.037). Further analysis showed that measured BMI partially mediated the association between PRS-BMI and discrimination. There was no evidence that the association between discrimination and BMI, or the association between discrimination and WC, differed by PRS-BMI or PRS-WC, respectively.

CONCLUSION

Our findings suggest that individuals with genetic liability for obesity may experience greater discrimination in their lifetime, consistent with a gene-environment correlation hypothesis. There was no evidence of a gene-environment interaction. More genome-wide association studies in diverse populations are needed to improve generalizability of study findings. In the meantime, prevention and clinical intervention efforts that seek to reduce exposure to all forms of discrimination may help reduce obesity at the population level.

Early socioeconomic adversity and young adult diabetic risk: an investigation of genetically informed biopsychosocial processes over the life course

The present study investigated a comprehensive model that integrates contributions of early socioeconomic adversity (ESA) and multiple polygenic scores (PGSs) through different mechanisms leading to diabetic risk in early adulthood. The study used prospective, longitudinal data from the National Longitudinal Study of Adolescent and Adult Health (Add Health) with a sample of 5,728 youth of European ancestry. The results showed that both ESA and PGSs were involved in different mechanisms. ESA contributed additively to educational failures, BMI, depressive symptoms, and diabetes risk over the life course (an additive process). Also, ESA launched a cascading process that connected these outcomes in a successively contingent manner. In addition to ESA, youths' multiple PGSs directly contributed to educational, psychological, and BMI outcomes. Multiple PGSs for education, BMI, and type 2 diabetes influenced not only youth outcomes that they were supposed to predict directly but also additional youth outcomes showing biological pleiotropy. The findings highlight the value of incorporating molecular genetic information into longitudinal developmental life course research and provide insight into malleable characteristics and appropriate timing for interventions addressing youth developmental and health outcomes.

Favourable Lifestyle Protects Cognitive Function in Older Adults With High Genetic Risk of Obesity: A Prospective Cohort Study

The relationship between body mass index (BMI) and cognitive impairment remains controversial, especially in older people. This study aims to confirm the association of phenotypic and genetic obesity with cognitive impairment and the benefits of adhering to a healthy lifestyle. This prospective study included 10,798 participants (aged ≥ 50 years) with normal cognitive function from the Health and Retirement Study in the United States. Participants were divided into low (lowest quintile), intermediate (quintiles 2–4), and high (highest quintile) groups according to their polygenic risk score (PRS) for BMI. The risk of cognitive impairment was estimated using Cox proportional hazard models. Higher PRS for BMI was associated with an increased risk, whereas phenotypic obesity was related to a decreased risk of cognitive impairment. Never smoking, moderate drinking, and active physical activity were considered favourable and associated with a lower risk of cognitive impairment compared with current smoking, never drinking, and inactive, respectively. A favourable lifestyle was associated with a low risk of cognitive impairment, even in subjects with low BMI and high PRS for BMI. This study suggest that regardless of obesity status, including phenotypic and genetic, adhering to a favourable lifestyle is beneficial to cognitive function.

Patterns of Co-occurring Developmental Failures in Adolescence: Socioeconomic and Genetic Antecedents and Health Outcomes in Adulthood

This study investigates (1) conjoint latent classes of adolescent co-occurring developmental problems (obesity, depressive symptoms, and low educational attainment), (2) socioeconomic and genetic influences on these classes of adolescents' problem trajectories, and (3) physical health consequences of those latent classes. Data from the National Longitudinal Study of Adolescent to Adult Health (Add Health; N = 9,107; mean age = 15.5 years; Female = 52.9 per cent) were used to identify classes of early socioeconomic adversity and conjoint trajectory groups of co-occurring developmental problems. Profiles of social antecedents, genetic endowments (polygenic scores), and physical health outcomes in young adulthood were compared across identified four conjoint trajectory risk groups (overall high-risk, overall low-risk, BMI-risk or obesity, low education-risk). The results showed that youth with overall high-risk and BMI/education-specific risk trajectory groups were more likely to be Black or Hispanic, reported more adverse socioeconomic characteristics and genetic endowment, and averaged significantly poorer physical health in young adulthood compared with youth in the overall low-risk problem trajectory group. Less pronounced differences emerged between the high-risk and problem-specific-risk groups. The findings highlight heterogeneity in adolescent co-occurring developmental problems. Adolescent heterogeneous problem co-development is associated with background socioeconomic and genetic characteristics and physical health in young adulthood.

Body mass index interacts with a genetic-risk score for depression increasing the risk of the disease in high-susceptibility individuals

Depression is strongly associated with obesity among other chronic physical diseases. The latest mega- and meta-analysis of genome-wide association studies have identified multiple risk loci robustly associated with depression. In this study, we aimed to investigate whether a genetic-risk score (GRS) combining multiple depression risk single nucleotide polymorphisms (SNPs) might have utility in the prediction of this disorder in individuals with obesity. A total of 30 depression-associated SNPs were included in a GRS to predict the risk of depression in a large case-control sample from the Spanish PredictD-CCRT study, a national multicentre, randomized controlled trial, which included 104 cases of depression and 1546 controls. An unweighted GRS was calculated as a summation of the number of risk alleles for depression and incorporated into several logistic regression models with depression status as the main outcome. Constructed models were trained and evaluated in the whole recruited sample. Non-genetic-risk factors were combined with the GRS in several ways across the five predictive models in order to improve predictive ability. An enrichment functional analysis was finally conducted with the aim of providing a general understanding of the biological pathways mapped by analyzed SNPs. We found that an unweighted GRS based on 30 risk loci was significantly associated with a higher risk of depression. Although the GRS itself explained a small amount of variance of depression, we found a significant improvement in the prediction of depression after including some non-genetic-risk factors into the models. The highest predictive ability for depression was achieved when the model included an interaction term between the GRS and the body mass index (BMI), apart from the inclusion of classical demographic information as marginal terms (AUC = 0.71, 95% CI = [0.65, 0.76]). Functional analyses on the 30 SNPs composing the GRS revealed an over-representation of the mapped genes in signaling pathways involved in processes such as extracellular remodeling, proinflammatory regulatory mechanisms, and circadian rhythm alterations. Although the GRS on its own explained a small amount of variance of depression, a significant novel feature of this study is that including non-genetic-risk factors such as BMI together with a GRS came close to the conventional threshold for clinical utility used in ROC analysis and improves the prediction of depression. In this study, the highest predictive ability was achieved by the model combining the GRS and the BMI under an interaction term. Particularly, BMI was identified as a trigger-like risk factor for depression acting in a concerted way with the GRS component. This is an interesting finding since it suggests the existence of a risk overlap between both diseases, and the need for individual depression genetics-risk evaluation in subjects with obesity. This research has therefore potential clinical implications and set the basis for future research directions in exploring the link between depression and obesity-associated disorders. While it is likely that future genome-wide studies with large samples will detect novel genetic variants associated with depression, it seems clear that a combination of genetics and non-genetic information (such is the case of obesity status and other depression comorbidities) will still be needed for the optimization prediction of depression in high-susceptibility individuals.

Biological, Psychological, and Social Determinants of Depression: A Review of Recent Literature

Depression is one of the leading causes of disability, and, if left unmanaged, it can increase the risk for suicide. The evidence base on the determinants of depression is fragmented, which makes the interpretation of the results across studies difficult. The objective of this study is to conduct a thorough synthesis of the literature assessing the biological, psychological, and social determinants of depression in order to piece together the puzzle of the key factors that are related to this condition. Titles and abstracts published between 2017 and 2020 were identified in PubMed, as well as Medline, Scopus, and PsycInfo. Key words relating to biological, social, and psychological determinants as well as depression were applied to the databases, and the screening and data charting of the documents took place. We included 470 documents in this literature review. The findings showed that there are a plethora of risk and protective factors (relating to biological, psychological, and social determinants) that are related to depression; these determinants are interlinked and influence depression outcomes through a web of causation. In this paper, we describe and present the vast, fragmented, and complex literature related to this topic. This review may be used to guide practice, public health efforts, policy, and research related to mental health and, specifically, depression.

Evaluating the associations of adult heel BMD with birth weight and growth parameters at age 10 in UK Biobank cohort

OBJECTIVE

This study was aimed to evaluate the associations of adult heel bone mineral density (BMD) with birth weight and growth parameters at the age of ten years.

METHODS

The analysis data (97178-178,494 subjects) was derived from the UK Biobank cohort. Birth weight, comparative body size and height size at the age of ten years were determined by self-report. The heel BMD was estimated by the Quantitative Ultrasound Index through the calcaneus. Linear regression analysis was applied to test the associations of adult heel BMD with birth weight and growth parameters at the age of ten years, respectively. Age, sex, body mass index and 10 principle components (PC) of population structure were used as covariates in the regression analysis of total samples. In sex-specific analysis, age, body mass index and 10 PC were used as covariates.

RESULTS

We observed significant associations of heel BMD with birth weight (b = -0.020, P = 1.974 × 10^-13), comparative body size (b = 0.020, P = 2.539 × 10^-6) and comparative height size (b = -0.020, P = 5.892 × 10^-11) at the age of ten years in total samples. In females, birth weight (b = -0.040, P = 2.870 × 10^-24) and comparative height size (b = -0.040, P = 2.034 × 10^-20) were statistically associated with adult heel BMD. In males, comparative body size appeared to be associated with adult heel BMD (b = 0.030, P = 1.590 × 10^-7).

CONCLUSION

Our study results support the predictive effects of birth weight and growth parameters at the age of ten years on adult heel BMD. We also observed sex-specific association between adult heel BMD and growth parameters at the age of ten years.

The Meaning of "Cause" in Genetics

Causation has multiple distinct meanings in genetics. One reason for this is meaning slippage between two concepts of the gene: Mendelian and molecular. Another reason is that a variety of genetic methods address different kinds of causal relationships. Some genetic studies address causes of traits in individuals, which can only be assessed when single genes follow predictable inheritance patterns that reliably cause a trait. A second sense concerns the causes of trait differences within a population. Whereas some single genes can be said to cause population-level differences, most often these claims concern the effects of many genes. Polygenic traits can be understood using heritability estimates, which estimate the relative influences of genetic and environmental differences to trait differences within a population. Attempts to understand the molecular mechanisms underlying polygenic traits have been developed, although causal inference based on these results remains controversial. Genetic variation has also recently been leveraged as a randomizing factor to identify environmental causes of trait differences. This technique-Mendelian randomization-offers some solutions to traditional epidemiological challenges, although it is limited to the study of environments with known genetic influences.

Inflammation and Insulin Resistance as Risk Factors and Potential Therapeutic Targets for Alzheimer's Disease

Overnutrition and modern diets containing high proportions of saturated fat are among the major factors contributing to a low-grade state of inflammation, hyperglycemia and dyslipidemia. In the last decades, the global rise of type 2 diabetes and obesity prevalence has elicited a great interest in understanding how changes in metabolic function lead to an increased risk for premature brain aging and the development of neurodegenerative disorders such as Alzheimer's disease (AD). Cognitive impairment and decreased neurogenic capacity could be a consequence of metabolic disturbances. In these scenarios, the interplay between inflammation and insulin resistance could represent a potential therapeutic target to prevent or ameliorate neurodegeneration and cognitive impairment. The present review aims to provide an update on the impact of metabolic stress pathways on AD with a focus on inflammation and insulin resistance as risk factors and therapeutic targets.

Association between herpes simplex virus 1 exposure and the risk of depression in UK Biobank

BACKGROUND

Herpes simplex virus-1 (HSV-1) infection is reported to be associated with depression. But limited efforts were made to investigate the relationship between HSV-1 infection and the risk of depression, especially from the genetic perspective.

METHODS

In UK Biobank cohort, linear and logistic regression analyses were first performed to test the association of HSV-1 seropositivity/antibody with depression, including depression status (N = 2951) and Patient Health Questionnaire (PHQ) score (N = 2839). Using individual genotypic and phenotypic data from the UK Biobank, genome-wide environmental interaction study (GWEIS) was then conducted by PLINK2.0 to evaluate gene × HSV-1 interacting effect on the risk of depression. Finally, gene set enrichment analysis was conducted to identify the biological pathways involved in the observed gene × HSV-1 interaction for depression.

RESULT

In UK Biobank cohort, significant associations were observed between depression status and HSV-1 (odds ratio [OR] = 1.09; 95% confidence interval [CI], 1.02-1.16; P = 2.40 × 10^-2 for HSV-1 antibody and OR = 1.28; 95% CI, 1.12-1.47, P = 2.59 × 10^-3 for HSV-1 seropositivity). GWEIS revealed four significant gene × HSV-1 interaction signals for PHQ score (all P < 5.0 × 10^-8 ) and the leading loci was SULF2 (rs6094791, P = 8.60 × 10^-9 ). Pathway analyses identified 21 pathways for PHQ score and 19 for depression status, including multiple neural development- and immune-related ones, such as KEGG_NEUROACTIVE_LIGAND_RECEPTOR_INTERACTION (false discovery rate [FDR] = 3.18 × 10^-2 ) for depression and LU_AGING_BRAIN_UP (FDR = 4.21 × 10^-2 ) for PHQ score.

CONCLUSION

Our results suggested that HSV-1 was associated with the risk of depression, which was modulated by the several genes that were related to the nerve development or immune function.

Vitamin D polygenic score is associated with neuroticism and the general psychopathology factor

Vitamin D, used here to refer to both 25-hydroxyvitamin D, the main circulating form of the vitamin, and 1,25-hydroxyvitamin D, the biologically active form, has been shown to influence brain development and function. Consistent with these findings, low levels of vitamin D have been implicated in various mental disorders, including depression, schizophrenia, and autism. Recently, a shared variance across multiple categories of mental health disorders has been identified and shown to be genetically influenced. This shared variance, thought to represent a general risk for psychopathology, has been termed the p factor. Individuals with high p factor scores are characterized by high neuroticism and low agreeableness and conscientiousness. Here, we investigated the links between vitamin D polygenic scores - derived from the latest genome-wide association study of circulating vitamin D (25-hydroxyvitamin D) levels - the Big Five personality traits (neuroticism, agreeableness, conscientiousness, openness-to-experience, and extraversion), and the p factor, in a sample of 522 (278 women, mean age 20 ± 1 years) non-Hispanic Caucasians. Vitamin D polygenic scores were significantly and negatively associated with neuroticism and the p factor, even after correcting for multiple comparisons, and controlling for sex, age, ancestry, socioeconomic status, and body mass index. Based on previous research implicating neuroticism as a risk factor for psychopathology, mediation was tested. Results showed a significant indirect effect from the vitamin D polygenic score to the p factor via neuroticism. Our findings support a genetic link between vitamin D levels, neuroticism, and the p factor, but due to the cross-sectional nature of our data, future studies are needed to clarify the causal associations between these phenotypes.

The E Is in the G: Gene-Environment-Trait Correlations and Findings From Genome-Wide Association Studies

Genome-wide association studies (GWASs) have shown that pleiotropy is widespread (i.e., the same genetic variants affect multiple traits) and that complex traits are polygenic (i.e., affected by many genetic variants with very small effect sizes). However, despite the growing number of GWASs, the possible contribution of gene-environment correlations (rGEs) to pleiotropy and polygenicity has been mostly ignored. rGEs can lead to environmentally mediated pleiotropy or gene-environment-trait correlations (rGETs), given that an environment that is affected by one genetically influenced phenotype, can in turn affect a different phenotype. By adding correlations with environmentally mediated genetic variants, rGETs can contribute to polygenicity. Socioeconomic status (SES) and the experience of stressful life events may, for example, be involved in rGETs. Both are genetically influenced and have been associated with a myriad of physical and mental disorders. As a result, GWASs of these disorders may find the genetic correlates of SES and stressful life events. Consequently, some of the genetic correlates of physical and mental disorders may be modified by public policy that affects environments such as SES and stressful life events. Thus, identifying rGETs can shed light on findings from GWASs and have important implications for public health.