“S-LDXR: Population-Specific Causal Disease Effect Sizes in Functionally Important Regions Impacted by Selection”, 2021-02-17 (; similar):
Many diseases exhibit population-specific causal effect-sizes with trans-ethnic genetic correlations substantially less than 1, limiting trans-ethnic polygenic risk prediction.
We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases & complex traits in East Asians (average n = 90K) and Europeans (average n = 267K) with:
an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes.
Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.