ArticleTranslational psychiatry2022
Polygenic risk scores for schizophrenia and major depression are associated with socio-economic indicators of adversity in two British community samples.
Article in Translational psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Machine learning and natural language processing for the identification of potential mental disorders among school-age children: a prospective birth cohort study.BMC medicine · 2026Article
- Genotypic and socioeconomic risks for depressive symptoms in two U.S. cohorts spanning early to older adulthood.Journal of psychopathology and clinical science · 2025Article
- Geographical variation in treated psychotic and other mental disorders in Finland by region and urbanicity.Social psychiatry and psychiatric epidemiology · 2024Article
- Article
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Authors and funding
5 authors at 2 institutions in 1 country.
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Abstract
Schizophrenia (SCZ) and major depressive disorder (MDD) are complex psychiatric disorders which contribute substantially to the global burden of disease. Both psychopathologies are heritable with some genetic overlap between them. Importantly, SCZ and MDD have also been found to be associated with environmental risk factors. However, rather than being independent of genetic influences, exposure to environmental risk factors may be under genetic control, known as gene-environment correlation (rGE). In this study we investigated rGE in relation to polygenic risk scores for SCZ and MDD in adults, derived from large genome-wide association studies, across two different British community samples: Understanding Society (USoc) and the National Child Development Study (NCDS). We tested whether established environmental risk factors for SCZ and/or MDD are correlated with polygenic scores in adults and whether these associations differ between the two disorders and cohorts. Findings partially overlapped between disorders and cohorts. In NCDS, we identified a significant correlation between the genetic risk for MDD and an indicator of low socio-economic status, but no significant findings emerged for SCZ. In USoc, we replicated associations between indicators of low socio-economic status and the genetic propensity for MDD. In addition, we identified associations between the genetic susceptibility for SCZ and being single or divorced. Results across both studies provide further evidence that the genetic risk for SCZ and MDD were associated with common environmental risk factors, specifically MDD's association with lower socio-economic status.
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