Demographic history mediates the effect of stratification on polygenic scores.
Demographic history mediates the effect of stratification on polygenic scores.
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人口统计学历史调节了分层对多基因得分的影响。
DOI：
10.7554/elife.61548
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发表时间：
2020-11-17
期刊：
影响因子：
7.7
通讯作者：
Mathieson I
中科院分区：
文献类型：
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作者：
Zaidi AA;Mathieson I
人群分层继续使全基因组关联研究（GWAS）的结果产生偏倚。当这些结果用于构建多基因评分时，即使是微小的偏差也会累积导致大的误差。为了研究剩余分层的影响，我们模拟GWAS下的现实模型的人口历史。我们发现，当人口结构是最近的，它不能被纠正使用常见的变异的主成分，因为他们是没有信息的最近的历史。因此，多基因得分是有偏见的，因为它们概括了环境结构。从罕见的变异或身份的血统段计算的主成分可以纠正这种分层的某些类型的环境影响。虽然基于家庭的研究不受分层的影响，但确定GWAS变异但重新估计兄弟姐妹效应大小的混合方法减少了分层，但没有消除分层。我们表明，人口分层的影响不仅取决于等位基因频率和环境结构，还取决于人口统计历史。
Population stratification continues to bias the results of genome-wide association studies (GWAS). When these results are used to construct polygenic scores, even subtle biases can cumulatively lead to large errors. To study the effect of residual stratification, we simulated GWAS under realistic models of demographic history. We show that when population structure is recent, it cannot be corrected using principal components of common variants because they are uninformative about recent history. Consequently, polygenic scores are biased in that they recapitulate environmental structure. Principal components calculated from rare variants or identity-by-descent segments can correct this stratification for some types of environmental effects. While family-based studies are immune to stratification, the hybrid approach of ascertaining variants in GWAS but reestimating effect sizes in siblings reduces but does not eliminate stratification. We show that the effect of population stratification depends not only on allele frequencies and environmental structure but also on demographic history.