To date, GWAS have been overwhelmingly limited to individuals of European ancestries [52]. Because of variation in allele frequencies and linkage disequilibrium (LD) patterns, PGS often lose predictive accuracy when there is mismatch between the ancestries of the discovery GWAS and target sample [53, 54]. COGA includes participants of both African and European ancestries, thus we used PRS-CSx [55], a method that integrates GWAS summary statistics from well-powered GWAS (typically of European ancestries) with those from other populations to improve the predictive power of PGS in the participants of African ancestries in COGA. PRS-CSx employs a Bayesian approach to correct GWAS summary statistics for the non-independence of SNPs in LD. We converted PGS into Z-scores for ease of interpretation
