Fig. 3

PRS performance comparisons via UK Biobank. In this study, UK Biobank’s primary purpose is to evaluate the scale effect, defined as the marginal gain of performance due to the size of the discovery set. To this end, two variables representative for high heritability, namely hypertension, and height, are analyzed. For experimental purposes, we intentionally design three discovery sets with different sizes, 300k, 60k, and 9k, which approximately correspond to the discovery set sizes of the full UK Biobank dataset, IGAP, and ADSP, respectively. For convenience, we abbreviate the discovery and test sets as D and T. ΔAUC and ΔR² denote the additive gain from introducing the PRS term to Model II (refer to Materials and Methods for details). (A) A larger D size results in higher prediction performances (ΔAUC and ΔR²), demonstrating the scale effect as hypothesized. However, in the three sample sizes, a smaller subset of T rarely degrades ΔAUC or ΔR², but it had an impact on the significance level P, perhaps intuitively. As the highest heritability (Fig. 1C) foretells, the height variable applied in PRS showed a greater impact on the prediction model than hypertension, as indicated by higher ΔR² and –log(P). (B) When the number of SNPs varies with 100% of T used, most metrics show improvements until 50k SNPs are used, which plateaus. The number of SNPs in the x-axis denotes number of the LD pruned SNPs selected in the order from the lowest P-value thresholds. That is, the lower number of SNP in the left side means the stricter P value threshold and the right-most side is the most generous P value threshold (P < 0.5). (C) Although the size of D with 100% of T used shows a linear correlation with PRS performances, proving the hypothesized scale effect, the improvements are not dramatic. For instance, ΔR² increases by approximately 0.0000125 and 0.0000083 per 3k of D