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 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>g</mml:mi></mml:msub> </mml:math> , the cross-population correlation of joint-fit effect sizes at genotyped SNPs. However, the value of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>g</mml:mi></mml:msub> </mml:math> depends both on the cross-population correlation of true causal effect sizes ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>b</mml:mi></mml:msub> </mml:math> ) 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 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>g</mml:mi></mml:msub> <mml:mo>/</mml:mo> <mml:msub><mml:mi>ρ</mml:mi> <mml:mi>b</mml:mi></mml:msub> </mml:math> as a function of LD in each population. By applying existing methods to obtain estimates of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>g</mml:mi></mml:msub> </mml:math> , we can use this ratio to estimate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>b</mml:mi></mml:msub> </mml:math> . Our estimates of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>ρ</mml:mi> <mml:mi>b</mml:mi></mml:msub> </mml:math> 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.