| Summary: | It is important to study the genetics of complex traits in diverse populations. Here, we introduce covariate-adjusted linkage
disequilibrium (LD) score regression (cov-LDSC), a method to estimate SNP-heritability (h2
g) and its enrichment in
homogenous and admixed populations with summary statistics and in-sample LD estimates. In-sample LD can be
estimated from a subset of the genome-wide association studies samples, allowing our method to be applied efficiently to
very large cohorts. In simulations, we show that unadjusted LDSC underestimates h2
g by 10–60% in admixed populations; in
contrast, cov-LDSC is robustly accurate. We apply cov-LDSC to genotyping data from 8124 individuals, mostly of admixed
ancestry, from the Slim Initiative in Genomic Medicine for the Americas study, and to approximately 161 000 Latino-ancestry
individuals, 47 000 African American-ancestry individuals and 135 000 European-ancestry individuals, as classified by
23andMe. We estimate h2
g and detect heritability enrichment in three quantitative and five dichotomous phenotypes, making this, to our knowledge, the most comprehensive heritability-based analysis of admixed individuals to date. Most
traits have high concordance of h2
g and consistent tissue-specific heritability enrichment among different populations.
However, for age at menarche, we observe population-specific heritability estimates of h2
g. We observe consistent patterns of
tissue-specific heritability enrichment across populations; for example, in the limbic system for BMI, the
per-standardized-annotation effect size τ∗ is 0.16 ± 0.04, 0.28 ± 0.11 and 0.18 ± 0.03 in the Latino-, African American- and
European-ancestry populations, respectively. Our approach is a powerful way to analyze genetic data for complex traits from
admixed populations.
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