Socioeconomic Deprivation Index Is Associated With Psychiatric Disorders: An Observational and Genome-wide Gene-by-Environment Interaction Analysis in the UK Biobank Cohort

Ye, Jing; Wen, Yan; Sun, Xifang; Chu, Xuan; Li, Ping; Cheng, Bolun; Cheng, Shiqiang; Liu, Li; Zhang, Lu; Ma, Mei; Qi, Xin; Liang, Chujun; Kafle, Om Prakash; Jia, Yumeng; Wu, Cuiyan; Wang, Sen; Wang, Xi; Ning, Yujie; Sun, Shaodong; Zhang, Feng

doi:10.1016/j.biopsych.2020.11.019

Cited by 69 publications

(45 citation statements)

References 52 publications

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“… 116 Possible biological mechanisms included differing profile of individuals with bipolar disorders and schizophrenia 117 and their genetic variability across human leukocyte antigens that could contribute to differences in immune responses to SARS-CoV-2 infections. 118 Alternatively, relevant societal factors may include socio-economic deprivation, social isolation 119 and barriers to accessing healthcare services for COVID-19 in individuals with mental health disorders and neurodevelopmental disorders. 120 Possible mechanisms for the link of ischaemic stroke and COVID-19 risk may again be due to the pro-inflammatory environment and increased coagulation factors.…”

Section: Discussionmentioning

confidence: 99%

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies

Luo

Liang

Wong

et al. 2022

International Journal of Epidemiology

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Background To summarize modifiable factors for coronavirus disease 2019 (COVID-19) suggested by Mendelian randomization studies. Methods In this systematic review, we searched PubMed, EMBASE and MEDLINE, from inception to 15 November 2021, for Mendelian randomization studies in English. We selected studies that assessed associations of genetically predicted exposures with COVID-19-related outcomes (severity, hospitalization and susceptibility). Risk of bias of the included studies was evaluated based on the consideration of the three main assumptions for instrumental variable analyses. Results We identified 700 studies through systematic search, of which 50 Mendelian randomization studies were included. Included studies have explored a wide range of socio-demographic factors, lifestyle attributes, anthropometrics and biomarkers, predisposition to diseases and druggable targets in COVID-19 risk. Mendelian randomization studies suggested that increases in smoking, obesity and inflammatory factors were associated with higher risk of COVID-19. Predisposition to ischaemic stroke, combined bipolar disorder and schizophrenia, attention-deficit and hyperactivity disorder, chronic kidney disease and idiopathic pulmonary fibrosis was potentially associated with higher COVID-19 risk. Druggable targets, such as higher protein expression of histo-blood group ABO system transferase (ABO), interleukin (IL)-6 and lower protein expression of 2′-5′ oligoadenylate synthetase 1 (OAS1) were associated with higher risk of COVID-19. There was no strong genetic evidence supporting the role of vitamin D, glycaemic traits and predisposition to cardiometabolic diseases in COVID-19 risk. Conclusion This review summarizes modifiable factors for intervention (e.g. smoking, obesity and inflammatory factors) and proteomic signatures (e.g. OAS1 and IL-6) that could help identify drugs for treating COVID-19.

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Section: Discussionmentioning

confidence: 99%

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies

Luo

Liang

Wong

et al. 2022

International Journal of Epidemiology

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Section: Introductionmentioning

confidence: 73%

“…TDI has been often used as covariates, such as in the longitudinal study investigating the impact of sleep duration and fragmentation on physical and mental health [ 27 ]. In our previous study evaluating the epidemiologic associations between the TDI and common psychiatric disorders or traits, we found that the trends of association remained still significant after adjusting for household income, suggesting the distinct role of TDI in relation to psychiatric diseases independent of income poverty [ 28 ]. Interestingly, Culver et al pointed out that environmental exposures could modify the association between causal genetic variants and human disease by providing the necessary substrates or exerting an influence on the effect of specific genes [ 29 ].…”

Section: Introductionmentioning

confidence: 99%

Associations between genetic loci, environment factors and mental disorders: a genome-wide survival analysis using the UK Biobank data

Meng

Chu

et al. 2022

Transl Psychiatry

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It is well-accepted that both environment and genetic factors contribute to the development of mental disorders (MD). However, few genetic studies used time-to-event data analysis to identify the susceptibility genetic variants associated with MD and explore the role of environment factors in these associations. In order to detect novel genetic loci associated with MD based on the time-to-event data and identify the role of environmental factors in them, this study recruited 376,806 participants from the UK Biobank cohort. The MD outcomes (including overall MD status, anxiety, depression and substance use disorders (SUD)) were defined based on in-patient hospital, self-reported and death registry data collected in the UK Biobank. SPACOX approach was used to identify the susceptibility loci for MD using the time-to-event data of the UK Biobank cohort. And then we estimated the associations between identified candidate loci, fourteen environment factors and MD through a phenome-wide association study and mediation analysis. SPACOX identified multiple candidate loci for overall MD status, depression and SUD, such as rs139813674 (P value = 8.39 × 10–9, ZNF684) for overall MD status, rs7231178 (DCC, P value = 2.11 × 10–9) for depression, and rs10228494 (FOXP2, P value = 6.58 × 10–10) for SUD. Multiple environment factors could influence the associations between identified loci and MD, such as confide in others and felt hated. Our study identified novel candidate loci for MD, highlighting the strength of time-to-event data based genetic association studies. We also observed that multiple environment factors could influence the association between susceptibility loci and MD.

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“…Additionally, we’ll conduct a causal effect analysis based on one specific biological pathway by integrating data of genetic variation, epigenetic variation, and environmental factors. Second, the Townsend deprivation index (TDI) was indicated to be associated with depression [ 42 , 43 ]. However, we couldn’t add this factor as a covariate in the linear mixed effects model, because we didn’t investigate the corresponding information of TDI during the epidemiological survey.…”

Section: Discussionmentioning

confidence: 99%

Genome-wide DNA methylation and gene expression analyses in monozygotic twins identify potential biomarkers of depression

Wang

et al. 2021

Transl Psychiatry

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Depression is currently the leading cause of disability around the world. We conducted an epigenome-wide association study (EWAS) in a sample of 58 depression score-discordant monozygotic twin pairs, aiming to detect specific epigenetic variants potentially related to depression and further integrate with gene expression profile data. Association between the methylation level of each CpG site and depression score was tested by applying a linear mixed effect model. Weighted gene co-expression network analysis (WGCNA) was performed for gene expression data. The association of DNA methylation levels of 66 CpG sites with depression score reached the level of P < 1 × 10−4. These top CpG sites were located at 34 genes, especially PTPRN2, HES5, GATA2, PRDM7, and KCNIP1. Many ontology enrichments were highlighted, including Notch signaling pathway, Huntington disease, p53 pathway by glucose deprivation, hedgehog signaling pathway, DNA binding, and nucleic acid metabolic process. We detected 19 differentially methylated regions (DMRs), some of which were located at GRIK2, DGKA, and NIPA2. While integrating with gene expression data, HELZ2, PTPRN2, GATA2, and ZNF624 were differentially expressed. In WGCNA, one specific module was positively correlated with depression score (r = 0.62, P = 0.002). Some common genes (including BMP2, PRDM7, KCNIP1, and GRIK2) and enrichment terms (including complement and coagulation cascades pathway, DNA binding, neuron fate specification, glial cell differentiation, and thyroid gland development) were both identified in methylation analysis and WGCNA. Our study identifies specific epigenetic variations which are significantly involved in regions, functional genes, biological function, and pathways that mediate depression disorder.

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Socioeconomic Deprivation Index Is Associated With Psychiatric Disorders: An Observational and Genome-wide Gene-by-Environment Interaction Analysis in the UK Biobank Cohort

Cited by 69 publications

References 52 publications

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies

Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies

Associations between genetic loci, environment factors and mental disorders: a genome-wide survival analysis using the UK Biobank data

Genome-wide DNA methylation and gene expression analyses in monozygotic twins identify potential biomarkers of depression

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