Simulation benchmarks of ePRS. Colors and line styles denote model type throughout the figure: blue, ePRS; orange, pruning and thresholding (P+T); black, elastic net (EN); and green, PRS derived from source GWAS summary statistics. Lines show smoothed mean performance across values of r_g, and points indicate the values of r_g at which performance was evaluated. In panel B, the red dashed horizontal line indicates random classification performance (AUC = 0.5). In panel C, the darker blue line indicates ePRS fitted using the true genetic correlation, and light blue indicates ePRS fitted using a fixed, misspecified genetic correlation. (A) ePRS demonstrates superior predictive performance against P+T, EN using the target phenotype cohort, and external GWAS summary statistics defined on the source phenotype (source). The simulated heritability of the target phenotype is h² ≈ 0.7. (B) ePRS demonstrates stronger predictive capacity in differentiating between disease subtypes compared to conventional approaches including P+T and EN regression. Using GWAS summary statistics from the general phenotype would fail to distinguish between different subtypes, resulting in an AUC of 0.5, which is equivalent to random guessing (red dashed line). (C) Robustness of ePRS to misspecification of the genetic correlation r_g. The x-axis shows the true genetic correlation used to generate simulated data, whereas ePRS is fit using either a fixed r_g = 0.5 (light blue dashed curve) or the true r_g (blue). EN is used as a reference because EN does not utilize r_g. Misspecification leads to only modest attenuation in ePRS performance (blue/light blue remain close over the x-axis), and ePRS remains above EN except when the source and target phenotypes are uncorrelated. The simulated heritability of the target phenotype is h² ≈ 0.7. (AUC) Area under the curve, (GWAS) genome-wide association study, (h²) heritability, and (r_g) genetic correlation.