Associations between common genetic variants and income provide insights about the socio-economic health gradient

Hyeokmoon Kweon; Casper A P Burik; Yuchen Ning; Rafael Ahlskog; Charley Xia; Erik Abner; Yanchun Bao; Laxmi Bhatta; Tariq O Faquih; Maud de Feijter; Paul Fisher; Andrea Gelemanović; Alexandros Giannelis; Jouke-Jan Hottenga; Bita Khalili; Yunsung Lee; Ruifang Li-Gao; Jaan Masso; Ronny Myhre; Teemu Palviainen; Cornelius A Rietveld; Alexander Teumer; Renske M Verweij; Emily A Willoughby; Esben Agerbo; Sven Bergmann; Dorret I Boomsma; Anders D Børglum; Ben M Brumpton; Neil Martin Davies; Tõnu Esko; Scott D Gordon; Georg Homuth; M Arfan Ikram; Magnus Johannesson; Jaakko Kaprio; Michael P Kidd; Zoltán Kutalik; Alex S F Kwong; James J Lee; Annemarie I Luik; Per Magnus; Pedro Marques-Vidal; Nicholas G Martin; Dennis O Mook-Kanamori; Preben Bo Mortensen; Sven Oskarsson; Emil M Pedersen; Ozren Polašek; Frits R Rosendaal; Melissa C Smart; Harold Snieder; Peter J van der Most; Peter Vollenweider; Henry Völzke; Gonneke Willemsen; Jonathan P Beauchamp; Thomas A DiPrete; Richard Karlsson Linnér; Qiongshi Lu; Tim T Morris; Aysu Okbay; K Paige Harden; Abdel Abdellaoui; W David Hill; Ronald de Vlaming; Daniel J Benjamin; Philipp D Koellinger

doi:10.1038/s41562-024-02080-7

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Associations between common genetic variants and income provide insights about the socio-economic health gradient

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Associations between common genetic variants and income provide insights about the socio-economic health gradient

Hyeokmoon Kweon, Casper A P Burik, Yuchen Ning, Rafael Ahlskog, Charley Xia, Erik Abner, Yanchun Bao, Laxmi Bhatta, Tariq O Faquih, Maud de Feijter, …

Nature Human Behaviour, Vol.9, pp.794-805

2025-04

DOI: https://doi.org/10.1038/s41562-024-02080-7

PMID: 39875632

Abstract

We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.

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Title: Associations between common genetic variants and income provide insights about the socio-economic health gradient
Creators: Hyeokmoon Kweon - Vrije Universiteit Amsterdam
Casper A P Burik - Vrije Universiteit Amsterdam
Yuchen Ning - Vrije Universiteit Amsterdam
Rafael Ahlskog - Uppsala University
Charley Xia - University of Edinburgh
Erik Abner - University of Tartu
Yanchun Bao - University of Essex
Laxmi Bhatta - Norwegian University of Science and Technology
Tariq O Faquih - Leiden University Medical Center
Maud de Feijter - Erasmus MC
Paul Fisher - University of Essex
Andrea Gelemanović - University of Split
Alexandros Giannelis - University of Minnesota
Jouke-Jan Hottenga - Vrije Universiteit Amsterdam
Bita Khalili - University of Lausanne
Yunsung Lee - Norwegian Institute of Public Health
Ruifang Li-Gao - Leiden University Medical Center
Jaan Masso - University of Tartu
Ronny Myhre - Norwegian Institute of Public Health
Teemu Palviainen - University of Helsinki
Cornelius A Rietveld - Erasmus University Rotterdam
Alexander Teumer - Universitätsmedizin Greifswald
Renske M Verweij - Erasmus University Rotterdam
Emily A Willoughby - University of Minnesota
Esben Agerbo - Aarhus University
Sven Bergmann - University of Lausanne
Dorret I Boomsma - Vrije Universiteit Amsterdam
Anders D Børglum - Aarhus University
Ben M Brumpton - Norwegian University of Science and Technology
Neil Martin Davies - University of Bristol
Tõnu Esko - University of Tartu
Scott D Gordon - QIMR Berghofer Medical Research Institute
Georg Homuth - Universität Greifswald
M Arfan Ikram - Erasmus MC
Magnus Johannesson - Stockholm School of Economics, Department of Economics
Jaakko Kaprio - University of Helsinki
Michael P Kidd - RMIT University
Zoltán Kutalik - University of Lausanne
Alex S F Kwong - MRC Epidemiology Unit
James J Lee - University of Minnesota
Annemarie I Luik - Erasmus University Medical Center
Per Magnus - Norwegian Institute of Public Health
Pedro Marques-Vidal - University of Lausanne
Nicholas G Martin - Medical Research Council
Dennis O Mook-Kanamori - Erasmus MC
Preben Bo Mortensen - Aarhus University
Sven Oskarsson - Uppsala University
Emil M Pedersen - Aarhus University
Ozren Polašek - University of Split
Frits R Rosendaal - Leiden University Medical Center
Melissa C Smart - University of Essex
Harold Snieder - University Medical Center Groningen
Peter J van der Most - University Medical Center Groningen
Peter Vollenweider - Trimbos Institute
Henry Völzke - Universitätsmedizin Greifswald
Gonneke Willemsen - Vrije Universiteit Amsterdam
Jonathan P Beauchamp - George Mason University
Thomas A DiPrete - Columbia University
Richard Karlsson Linnér - Vrije Universiteit Amsterdam
Qiongshi Lu - University of Wisconsin–Madison
Tim T Morris - University of Bristol
Aysu Okbay - Vrije Universiteit Amsterdam
K Paige Harden - The University of Texas at Austin
Abdel Abdellaoui - University of Amsterdam
W David Hill - University of Edinburgh
Ronald de Vlaming - Vrije Universiteit Amsterdam
Daniel J Benjamin - University of Southern California
Philipp D Koellinger - Vrije Universiteit Amsterdam
Publication Details: Nature Human Behaviour, Vol.9, pp.794-805
Publisher: Nature Research
Copyright: © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format,as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Academic Unit: Department of Economics
Language: English
Resource Type: Journal article

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Associations between common genetic variants and income provide insights about the socio-economic health gradient

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