Figure 3.

Prediction R² of the PRS trained based on GWAS summary data from PAGE + UKBB + BBJ on non-EUR validation individuals from PAGE

Discovery GWASs include GWAS from PAGE (AFR N_GWAS = 7,775–13,699, AMR N_GWAS = 13,894–17,558), BBJ (EAS N_GWAS = 70,657–158,284), and UKBB (EUR N_GWAS = 315,133–355,983). The validation dataset consists of individuals of EUR (N = 17,457–19,030), AFR (N = 7,954–8,598), EAS (N = 1,752–1,921), or SAS (N = 9,385–10,288) origin in UKBB. We used genotype data from the 1000 Genomes Project (498 EUR, 659 AFR, 347 AMR, 503 EAS, and 487 SAS) as the LD reference dataset. All methods were evaluated on the ∼2.0 million SNPs that are available in HapMap 3 + MEGA, except for PRS-CSx, which is evaluated based on the HapMap 3 SNPs only, as implemented in their software. Ancestry- and trait-specific GWAS sample sizes, number of SNPs included, and validation sample sizes are summarized in Table S7. A random half of the validation individuals is used as the tuning set to tune model parameters as well as train the SL in CT-SLEB and MUSSEL or the linear combination model in weighted C + T, weighted LDpred2, and PRS-CSx. The other half of the validation set is used as the testing set to report R² values and the corresponding 95% bootstrap CIs for PRSs on each ancestry, after adjusting for whether the sample is from BioMe and the top ten genetic principal components for BMI, and additionally the age at lipid measurement and sex. Detailed results are reported in Table S17.