Associations between common genetic variants and income provide insights about the socioeconomic health gradient
Author:
Kweon Hyeokmoon, Burik Casper A.P., Ning Yuchen, Ahlskog Rafael, Xia Charley, Abner Erik, Bao Yanchun, Bhatta Laxmi, Faquih Tariq O., de Feijter Maud, Fisher Paul, Gelemanović Andrea, Giannelis Alexandros, Hottenga Jouke-Jan, Khalili Bita, Lee Yunsung, Li-Gao Ruifang, Masso Jaan, Myhre Ronny, Palviainen Teemu, Rietveld Cornelius A., Teumer Alexander, Verweij Renske M., Willoughby Emily A., Agerbo Esben, Bergmann Sven, Boomsma Dorret I., Børglum Anders D., Brumpton Ben M., Davies Neil Martin, Esko Tõnu, Gordon Scott D., Homuth Georg, Ikram M. Arfan, Johannesson Magnus, Kaprio Jaakko, Kidd Michael P., Kutalik Zoltán, Kwong Alex S.F., Lee James J., Luik Annemarie I., Magnus Per, Marques-Vidal Pedro, Martin Nicholas G., Mook-Kanamori Dennis O., Mortensen Preben Bo, Oskarsson Sven, Pedersen Emil M., Polašek Ozren, Rosendaal Frits R., Smart Melissa C., Snieder Harold, van der Most Peter J., Vollenweider Peter, Völzke Henry, Willemsen Gonneke, Beauchamp Jonathan P., DiPrete Thomas A., Linnér Richard Karlsson, Lu Qiongshi, Morris Tim T., Okbay Aysu, Harden K. Paige, Abdellaoui Abdel, Hill W. David, de Vlaming Ronald, Benjamin Daniel J., Koellinger Philipp D.ORCID
Abstract
AbstractWe conducted a genome-wide association study (GWAS) on income among individuals of European descent and leveraged the results to investigate the socio-economic health gradient (N=668,288). We found 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes. Our GWAS-derived polygenic index captures 1 - 4% of income variance, with only one-fourth attributed to direct genetic effects. A phenome-wide association study using this polygenic index showed reduced risks for a broad spectrum of diseases, including hypertension, obesity, type 2 diabetes, coronary atherosclerosis, depression, asthma, and back pain. The income factor showed a substantial genetic correlation (0.92,s.e. = .006) with educational attainment (EA). Accounting for EA’s genetic overlap with income revealed that the remaining genetic signal for higher income related to better mental health but reduced physical health benefits and increased participation in risky behaviours such as drinking and smoking.
Publisher
Cold Spring Harbor Laboratory
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