Localizing Components of Shared Transethnic Genetic Architecture of Complex Traits from GWAS Summary Data

Abstract

Despite strong transethnic genetic correlations reported in the literature for many complex traits, the non-transferability of polygenic risk scores across populations suggests the presence of population-specific components of genetic architecture. We propose an approach that models GWAS summary data for one trait in two populations to estimate genome-wide proportions of population-specific/shared causal SNPs. In simulations across various genetic architectures, we show that our approach yields approximately unbiased estimates with in-sample LD and slight upward-bias with out-of-sample LD. We analyze nine complex traits in individuals of East Asian and European ancestry, restricting to common SNPs (MAF > 5%), and find that most common causal SNPs are shared by both populations. Using the genome-wide estimates as priors in an empirical Bayes framework, we perform fine-mapping and observe that high-posterior SNPs (for both the population-specific and shared causal configurations) have highly correlated effects in East Asians and Europeans. In population-specific GWAS risk regions, we observe a 2.83 enrichment of shared high-posterior SNPs, suggesting that population-specific GWAS risk regions harbor shared causal SNPs that are undetected in the other GWASs due to differences in LD, allele frequencies, and/or sample size. Finally, we report enrichments of shared high-posterior SNPs in 53 tissue-specific functional categories and find evidence that SNP-heritability enrichments are driven largely by many low-effect common SNPs.

Low generalizability of polygenic scores in African populations due to genetic and environmental diversity

“…This is consistent with causal genetic effects tending to be similar across populations but with LD and allele frequency differences modifying marginal effect size estimates (Martin et al, 2019) . This is also consistent with trans-ethnic genetic correlations tending to be close to or not significantly different from 1 (Brown et al, 2016;Shi et al, 2020) . The most rapid path to closing gaps in PRS transferability is to increase the inclusion of GWAS participants from populations most divergent from those already routinely studied.…”

Genetic analyses support the contribution of mRNA N6-methyladenosine (m6A) modification to human disease heritability

“…Studies have suggested that associations with complex traits, especially causal variants, are broadly shared across populations 80 . A systematic study with multiple complex traits estimated that more than 80% of causal variants are shared between Europeans and Asians 81 . In another study, TWAS on asthma using eQTL models trained on data from Europeans and Africans gave broadly similar results 82 .…”

The influence of evolutionary history on human health and disease

“…As the genetic information available from diverse populations increases, we can specifically map the genetics of traits in different populations and more precisely define disease risk on an individual basis 167 , 168 . However, we emphasize that environmental and social factors are major determinants of disease risk that often contribute more than genetics, and thus must be prioritized.…”