School of Criminal Justice, The University of Cincinnati, USA; Institute for Interdisciplinary Data Science, The University of Cincinnati, USA.
Soc Sci Res. 2019 Aug;82:137-147. doi: 10.1016/j.ssresearch.2019.04.008. Epub 2019 Apr 28.
This study takes a socio-genomic approach to examine the complex relationships among three important socioeconomic outcomes: educational attainment, occupational status, and wealth. Using more than 8,000 genetic samples from the Health and Retirement study, it first estimates the collective influence of genetic variants across the whole human genome to each of the three socioeconomic outcomes. It then tests genetic correlations among three socioeconomic outcomes, and examines the extent to which genetic influences on occupational status and wealth are mediated by educational attainment. Analyses using the genomic-relatedness-matrix restricted maximum likelihood method show significant genetic correlations among the three outcomes, and provide evidence for both mediated and independent genetic influences. A polygenic score analysis demonstrates the utility of findings in socio-genomic studies to address genetic confounding in causal relationships among the three socioeconomic outcomes.
本研究采用社会基因组学方法，探讨三个重要的社会经济结果（教育程度、职业地位和财富）之间的复杂关系。利用来自健康与退休研究的 8000 多个基因样本，本研究首先估计了整个人类基因组中遗传变异对这三个社会经济结果的综合影响。然后，它测试了三个社会经济结果之间的遗传相关性，并检验了教育程度对职业地位和财富的遗传影响在多大程度上是通过教育程度来介导的。使用基因组相关性矩阵限制最大似然法的分析显示，这三个结果之间存在显著的遗传相关性，并为遗传的中介和独立影响提供了证据。多基因分数分析证明了社会基因组学研究中的发现对于解决这三个社会经济结果之间因果关系中的遗传混杂问题的有用性。
