Drivers of genetic heterogeneity and their impact on polygenic risk prediction

遗传异质性的驱动因素及其对多基因风险预测的影响

基本信息

批准号：
10314395
负责人：
Dan Ju
金额：
$ 4.6万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10314395
关键词：
Address Affect Africa African Automobile Driving Clinical Complex Data Disease Disease model Environment Ethnic group European Exhibits Future Gene Frequency Genes Genetic Genetic Heterogeneity Genetic Models Genetic Predisposition to Disease Genetic Risk Genetic Variation Genetic study Genome Genomic medicine Genomics Genotype Ghana Height Heterogeneity Human Genetics Individual Intervention Investments Linkage Disequilibrium Measures Meta-Analysis Methodology Modeling Niger Pattern Phenotype Population Population Heterogeneity Privatization Publishing Quantitative Trait Loci Reporting Research Risk Role Sample Size Sampling Scanning Single Nucleotide Polymorphism Map Structure Testing Variant base biobank causal variant cohort disorder risk ethnic diversity gene environment interaction gene interaction genetic architecture genetic variant genome wide association study genome-wide improved novel polygenic risk score risk prediction risk stratification risk variant rural environment standing height statistics trait urban setting

项目摘要

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.

抽象的全基因组协会研究（GWAS）已将复杂性状的遗传结构告知我们和疾病通过识别常见的遗传风险变异。通常许多遗传变体会议很小人群中疾病差异的风险增加。总结这些遗传风险变体的影响可以测量个人的遗传易感性，这是通过计算多基因风险评分（PRS）来完成的。 PRS在识别遗传风险分布极端的个体方面显示出临床希望。但是，在风险分层中使用PRS的潜在好处可能会因PR的预测能力损失而受到限制一群非欧洲血统。 PR通常是根据欧洲进行的GWA计算的种群由于样本量较大。源自欧洲GWA的公关损失最大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。调查限制PRS可转移性的因素将为未来的研究途径提供开发的途径更具普遍的PR。由于非洲血统个人很少进行GWAS，因此该提议将在撒哈拉以南非洲人口中进行AIM 1的高度，以促进我们对我们的了解非洲潜水人群中复杂特征的遗传结构。通过AIM 1中的GWAS，通用可以发现影响身高的非非洲种群中不存在的变异。在AIM 2中，该提议将研究跨种群的连锁二序列（LD）结构差异在限制限制的作用 PR的可转移性。 GWAS依赖于基因分型标记和因果变体之间的LD，因此变体 PR中包含的不一定是因果关系。测试共享因果变体标记的差异是否存在在人群之间限制了PR的可转移性，该建议将确定差异标签的实例欧洲人与非洲人之间的因果变异，以及在一个基因座的多个关联的案例在欧洲人中，高LD在非洲人中可以用低LD询问。在AIM 3中，该建议将研究促进祖先共享变体大小的差异的机制，特别是基因（GXG）和基因通过环境（GXE）相互作用。效果最大尺寸的变体欧洲人和非洲人之间将检查是否有相互作用的证据。 GXG相互作用候选变体将根据其局部基因组血统进行测试。 GXE相互作用将使用两个一群类似的祖先，但在农村或城市环境中生活的状况有所不同。总之，这些分析将告知我们对LD结构以及GXG和GXE相互作用在限制限制LD结构的作用的理解 PR跨种群的可转移性。