GWAS can provide insights into the genetic architecture of human traits, including SNP heritability and genetic correlation. Several methods have been proposed for estimating these parameters from genotype data (Supplemental Table S4; Supplemental Methods Section V), but estimation and interpretation of these quantities is more challenging in diverse populations. Heritability estimates may differ between populations due to variation in both environmental factors and population genetic forces. Cross-population differences in phenotype measurement (Section XI) may further complicate interpretation. In evaluating shared genetic variance across populations, genetic correlation between groups can be defined either as the correlation of allelic effect sizes (genetic-effect correlation) or the correlation of the relative contribution to total phenotypic variance (genetic-impact correlation), and for all variants or for common variants present in a study. Each value is potentially informative, but divergence in allele frequencies and LD patterns between populations will lead to differences between these parameters (Galinsky et al., 2019).
