Estimating cross-population genetic correlations of causal effect sizes.
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Abstract | 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 , the cross-population correlation of joint-fit effect sizes at genotyped SNPs. However, the value of depends both on the cross-population correlation of true causal effect sizes ( ) 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 as a function of LD in each population. By applying existing methods to obtain estimates of , we can use this ratio to estimate . Our estimates of 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. |
Year of Publication | 2019
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Journal | Genet Epidemiol
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Volume | 43
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Issue | 2
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Pages | 180-188
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Date Published | 2019 Mar
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ISSN | 1098-2272
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DOI | 10.1002/gepi.22173
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PubMed ID | 30474154
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PubMed Central ID | PMC6375794
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Grant list | MC_QA137853 / MRC_ / Medical Research Council / United Kingdom
R01 HG006399 / HG / NHGRI NIH HHS / United States
T32 GM007753 / GM / NIGMS NIH HHS / United States
R01 HG006399 / NH / NIH HHS / United States
MC_PC_17228 / MRC_ / Medical Research Council / United Kingdom
K25 HL121295 / HL / NHLBI NIH HHS / United States
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