Estimating cross-population genetic correlations of causal effect sizes

Recent studies have examined the genetic correlations of single-nucleotide polymorphism (SNP) effect sizes across pairs of populations to better understand the genetic architectures of complex traits. These studies have estimated.g, the cross-population correlation of joint-fit effect sizes at genotyped SNPs. However, the value of.g depends both on the cross-population correlation of true causal effect sizes (.b) and on the similarity in linkage disequilibrium (LD) patterns in the two populations, which drive tagging effects. Here, we derive the value of the ratio.g /.b as a function of LD in each population. By applying existing methods to obtain estimates of.g, we can use this ratio to estimate.b. Our estimates of.b were equal to 0.55 (SE = 0.14) between Europeans and East Asians averaged across nine traits in the Genetic Epidemiology Research on Adult Health and Aging data set, 0.54 (SE = 0.18) between Europeans and South Asians averaged across 13 traits in the UK Biobank data set, and 0.48 (SE = 0.06) and 0.65 (SE = 0.09) between Europeans and East Asians in summary statistic data sets for type 2 diabetes and rheumatoid arthritis, respectively. These results implicate substantially different causal genetic architectures across continental populations.