Drivers of genetic heterogeneity and their impact on polygenic risk prediction

摘要 全基因组关联研究已经让我们了解了复杂性状的遗传结构。 通过识别常见的遗传风险变异体，来预防和控制疾病。通常情况下，许多遗传变异赋予小的 风险的增加是人群中疾病变异的基础。总结这些遗传风险变异的影响 可以通过计算多基因风险分数(PR)来衡量个人的遗传易感性。 在识别处于遗传风险分布极端的个体方面，PRS显示出临床前景。然而， 在风险分层中使用PRS的潜在好处可能会因以下方面的损失而减少 非欧洲血统的群体。RPS通常是根据在欧洲进行的GWA计算的 由于样本量较大，样本数量较大，可能会对总体产生影响。源自欧洲GWA的PR在#年遭受最大损失 非洲人口的预测能力。目前我们不知道这种预测能力丧失的原因。 研究限制可转移性的因素将为今后的研究开发提供参考 更具普遍性的PR。由于在非洲血统的个体中进行的GWA很少，因此该建议 将在目标1中在撒哈拉以南非洲人口中进行身高GWA，以帮助我们了解 一种复杂性状在非洲不同人群中的遗传结构。通过目标1中的Gwas，Genetic 非非洲人群中不存在的影响身高的变异可能会被发现。在目标2中，该提案将 研究群体间连锁不平衡(LD)结构的差异在限制 可转让性。Gwas依赖于基因分型标记和因果变异之间的LD，因此变异 包括在PR中的数据不一定是因果关系。测试共享因果变量在标记方面的差异 种群之间的差异限制了群体间的可转移性，这项建议将确定差异标记的实例 欧洲人和非洲人之间的因果变异以及一个基因座上的多个关联被掩盖的情况 在欧洲人中是高LD，在非洲人中可以用低LD来询问。在目标3中，这项提案将研究 导致不同祖先共有的变异效应大小差异的机制，特别是 基因与基因(GxG)和基因与环境(GxE)的相互作用。效果大小差异最大的变种 将研究欧洲人和非洲人之间相互影响的证据。的GXG交互 候选变种将根据其本地基因组血统进行测试。GxE交互将使用两个 有相似祖先但生活在农村或城市环境中的地位不同的群体。总而言之，这些分析 将有助于我们理解LD结构以及GxG和GxE相互作用在限制 可跨人口转移的可转移性。

Abstract Genome-wide association studies (GWAS) have informed us about the genetic architecture of complex traits and diseases by identifying common genetic risk variants. Typically many genetic variants conferring small increases in risk underlie disease variation in a population. Summarizing the effects of these genetic risk variants can measure an individual’s genetic predisposition, which is done by calculating a polygenic risk score (PRS). PRS show clinical promise in identifying individuals at the extremes of the genetic risk distribution. However, the potential benefits of using PRS in risk stratification may be curtailed due to loss of predictive power of PRS in groups of non-European ancestry. PRS are commonly calculated from GWAS conducted in European populations because of large sample sizes. PRS derived from European GWAS suffer the greatest loss in predictive power in African populations. Currently we do not know the reasons for this loss of predictive power. Investigating the factors limiting the transferability of PRS will inform future avenues of research into developing more generalizable PRS. Since few GWAS have been conducted in African ancestry individuals, the proposal will perform a GWAS in Sub-Saharan African populations for height in Aim 1 to contribute to our knowledge of the genetic architecture of a complex trait in diverse African populations. Through the GWAS in Aim 1, genetic variation not present in non-African populations that affects height can be uncovered. In Aim 2, the proposal will investigate the role of differences in linkage disequilibrium (LD) structure across populations in limiting the transferability of PRS. GWAS rely on LD between a genotyped marker and the causal variant, so the variants included in a PRS are not necessarily causal. To test whether differences in the tagging of shared causal variants between populations limit the transferability of PRS, this proposal will identify instances of differential tagging of causal variants between Europeans and Africans and cases where multiple associations at a locus are obscured by high LD in Europeans, which can be interrogated with low LD in Africans. In Aim 3, this proposal will study the mechanisms driving differences in effect size of variants shared across ancestries, specifically the role of gene by gene (GxG) and gene by environment (GxE) interactions. Variants with the most disparate effect sizes between Europeans and Africans will be examined for evidence of interaction effects. GxG interactions for a candidate variant will be tested based on its local genomic ancestry. GxE interactions will be tested using two groups of similar ancestry but differing by status of living in a rural or urban environment. In all, these analyses will inform our understanding of the roles of LD structure and GxG and GxE interactions in limiting the transferability of PRS across populations.