Dataset Information

A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study.

ABSTRACT:

Background

Mental disorders are largely socially determined, yet the combined impact of multidimensional social factors on the two most common mental disorders, depression and anxiety, remains unclear.

Methods

We constructed a polysocial risk score (PsRS), a multidimensional social risk indicator including components from three domains: socioeconomic status, neighborhood and living environment and psychosocial factors. Supported by the UK Biobank cohort, we randomly divided 110 332 participants into the discovery cohort (60%; n = 66 200) and the replication cohort (40%; n = 44 134). We tested the associations between 13 single social factors with Patient Health Questionnaire (PHQ) score, Generalized Anxiety Disorder Scale (GAD) score and self-reported depression and anxiety. The significant social factors were used to calculate PsRS for each mental disorder by considering weights from the multivariable linear model. Generalized linear models were applied to explore the association between PsRS and depression and anxiety. Genome-wide environmental interaction study (GWEIS) was further performed to test the effect of interactions between PsRS and SNPs on the risk of mental phenotypes.

Results

In the discovery cohort, PsRS was positively associated with PHQ score (β = 0.37; 95% CI = 0.35-0.38), GAD score (β = 0.27; 95% CI = 0.25-0.28), risk of self-reported depression (OR = 1.29; 95% CI = 1.28-1.31) and anxiety (OR = 1.19; 95% CI = 1.19-1.23). Similar results were observed in the replication cohort. Emotional stress, lack of social support and low household income were significantly associated with the development of depression and anxiety. GWEIS identified multiple candidate loci for PHQ score, such as rs149137169 (ST18) (P_discovery = 1.08 × 10^-8, P_replication = 3.25 × 10^-6) and rs3759812 (MYO9A) (P_discovery = 3.87 × 10^-9, P_replication = 6.21 × 10^-5). Additionally, seven loci were detected for GAD score, such as rs114006170 (TMPRSS11D) (P_discovery = 1.14 × 10^-9, P_replication = 7.36 × 10^-5) and rs77927903 (PIP4K2A) (P_discovery = 2.40 × 10^-9, P_replication = 0.002).

Conclusions

Our findings reveal the positive effects of multidimensional social factors on the risk of depression and anxiety. It is important to address key social disadvantage in mental health promotion and treatment.

SUBMITTER: Pan C

PROVIDER: S-EPMC10704948 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study.

Pan Chuyu C Liu Li L Cheng Shiqiang S Yang Xuena X Meng Peilin P Zhang Na N He Dan D Chen Yujing Y Li Chun'e C Zhang Huijie H Zhang Jingxi J Zhang Zhen Z Cheng Bolun B Wen Yan Y Jia Yumeng Y Liu Huan H Zhang Feng F

Journal of global health 20231208

<h4>Background</h4>Mental disorders are largely socially determined, yet the combined impact of multidimensional social factors on the two most common mental disorders, depression and anxiety, remains unclear.<h4>Methods</h4>We constructed a polysocial risk score (PsRS), a multidimensional social risk indicator including components from three domains: socioeconomic status, neighborhood and living environment and psychosocial factors. Supported by the UK Biobank cohort, we randomly divided 110 33 ...[more]

PMID: 38063329

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Project description:Anxiety and depression in children and adolescents warrant special attention as a public health issue given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17) and IMAGEN (EUROPE, age of 14). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school risk had the most significant and consistent impact across all three cohorts. Both meta and mega-analysis identified a novel SNP rs79878474 in chr11p15 to be the most promising SNP associated with anxiety and depression. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine and a trend of enrichment in the cerebellum. Our findings provide evidence of consistent environmental impact from early life stress and school risks on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels along with the potential role of the cerebellum region, which are worthy of further investigation.

Dataset Information

A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study.

Background

Methods

Results

Conclusions

Publications

A multidimensional social risk atlas of depression and anxiety: An observational and genome-wide environmental interaction study.

Similar Datasets

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