Exome sequencing identifies genes for socioeconomic status in 350,770 individuals

X Xin-Rui Wu (Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University) L Liu Yang B Bang-Sheng Wu (Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University) W Wei-Shi Liu (Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University) Y Yue-Ting Deng (Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University) J Ju-Jiao Kang (Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University) Q Qiang Dong B Barbara J. Sahakian (Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University) J Jian-Feng Feng (Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University) W Wei Cheng J Jin-Tai Yu (Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University)

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

Volume / Issue Vol. 122, Issue 2
Published January 14, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (11)

X

Xin-Rui Wu

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University

L

Liu Yang

B

Bang-Sheng Wu

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University

W

Wei-Shi Liu

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University

Y

Yue-Ting Deng

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University

J

Ju-Jiao Kang

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University

Q

Qiang Dong

B

Barbara J. Sahakian

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University

J

Jian-Feng Feng

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University

W

Wei Cheng

J

Jin-Tai Yu

Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Fudan University