Exome sequencing identifies genes for socioeconomic status in 350,770 individuals
Abstract
Socioeconomic status (SES) is a critical factor in determining health outcomes and is influenced by genetic and environmental factors. However, our understanding of the genetic structure of SES remains incomplete. Here, we conducted a large-scale exome study of SES markers (household income, occupational status, educational attainment, and social deprivation) in 350,770 individuals. For rare coding variants, we identified 56 significant associations by gene-based collapsing tests, unveiling 7 additional SES-associated genes ( NRN1 , CCDC36 , RHOB , EP400 , NCAM1, TPTEP2-CSNK1E , and LINC02881 ). Exome-wide single common variant analysis revealed nine lead single-nucleotide polymorphisms (SNPs) associated with household income and 34 lead SNPs associated with EduYears, replicating previous GWAS findings. The gene–environment correlations had a substantial impact on the genetic associations with SES, as indicated by the significantly increased P values in several associations after controlling for geographic regions. Furthermore, we observed the pleiotropic effects of SES-associated genetic factors on a wide range of health outcomes, such as cognitive function, psychosocial status, and diabetes. This study highlights the contribution of coding variants to SES and their associations with health phenotypes.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (11)
Xin-Rui Wu
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University
Liu Yang
Bang-Sheng Wu
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University
Wei-Shi Liu
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University
Yue-Ting Deng
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University
Ju-Jiao Kang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University
Qiang Dong
Barbara J. Sahakian
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University
Jian-Feng Feng
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University
Wei Cheng
Jin-Tai Yu
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University