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
Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Department of Government, Uppsala University, Uppsala, Sweden.
Nat Hum Behav. 2025 Apr;9(4):794-805. doi: 10.1038/s41562-024-02080-7. Epub 2025 Jan 28.
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.
我们对欧洲血统个体（N = 668,288）的收入进行了全基因组关联研究，以调查社会经济地位与健康差异之间的关系。我们确定了162个与各种收入衡量指标背后的共同遗传因素相关的基因组位点，所有这些位点的效应大小都很小（收入因素）。我们的多基因指数解释了1%-5%的收入差异，其中只有四分之一是由于直接遗传效应。使用该指数进行的全表型组关联研究表明，高血压、肥胖症、2型糖尿病、抑郁症、哮喘和背痛等疾病的风险降低。收入因素与受教育程度具有显著的遗传相关性（0.92，标准误 = 0.006）。考虑到受教育程度与收入的遗传重叠后发现，剩余的遗传信号与更好的心理健康相关，但与身体健康下降以及饮酒和吸烟等风险行为增加有关。这些发现突出了遗传因素对收入和健康的复杂影响。
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