受选择影响的功能重要区域中特定人群因果疾病效应大小。
Population-specific causal disease effect sizes in functionally important regions impacted by selection.
机构信息
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
出版信息
Nat Commun. 2021 Feb 17;12(1):1098. doi: 10.1038/s41467-021-21286-1.
Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.
许多疾病表现出特定人群的因果效应大小，跨种族遗传相关性显著低于 1，限制了跨种族多基因风险预测。我们开发了一种新的方法 S-LDXR，用于在基因组注释中对平方跨种族遗传相关性进行分层，并将 S-LDXR 应用于东亚人（平均 N=90K）和欧洲人（平均 N=267K）的 31 种疾病和复杂特征的全基因组汇总统计数据，平均跨种族遗传相关性为 0.85。我们确定，在背景选择统计量的前 quintile 中，平方跨种族遗传相关性减少了 0.82×（s.e. 0.01），这意味着因果效应大小在特定人群中更为特定。因此，因果效应大小在功能重要区域（包括保守和调节区域）中更具人群特异性。在特异性表达基因周围的区域中，因果效应大小在皮肤和免疫基因中最具人群特异性，而在大脑基因中最不具有人群特异性。我们的结果可能可以通过受选择影响的基因座（特别是正选择）的更强的基因-环境相互作用来解释。
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