When predicting into the EUR population, PRS-CSx provided a consistent but marginal improvement over LDpred2 (median relative increase in R2: 4.7%) and PRS-CS (median relative increase in R2: 5.2%), likely due to the limited power of the BBJ GWAS relative to the UKBB GWAS in EUR prediction. The benefit of the coupled prior in this case was also limited, as reflected by a small improvement of PRS-CSx relative to PRS-CS-mult (median relative increase in R2: 2.2%; Fig. 3a, left panel; Supplementary Table 11), which was consistent with the observations in simulations. When the target population was EAS, however, PRS-CSx substantially increased the prediction accuracy relative to single-discovery methods: the median relative improvements in R2 were 52.3% and 32.9% when compared with LDpred2 and PRS-CS trained on UKBB GWAS, and 69.8% and 74.4% when compared with LDpred2 and PRS-CS trained on BBJ GWAS, suggesting that PRS-CSx can leverage large-scale EUR GWAS to improve the prediction in non-EUR populations. PRS-CSx also had a median improvement of 10.5% (two-sided Wilcoxon signed-rank test Pwilcoxon=3.90E-4) and 8.3% (Pwilcoxon=2.84E-6) relative to LDpred2-mult and PRS-CS-mult, respectively, demonstrating
