The ePRS improves model stability
| Standard error of model performance across 100 bootstrapped samples | |||
|---|---|---|---|
| rg between source/target phenotypes | ePRS | EN | P+T |
| 0.1 | 9.7% | 12.5% | 11.2% |
| 0.3 | 8.5% | 11.1% | 10.3% |
| 0.5 | 8.3% | 11.2% | 8.8% |
| 0.7 | 7.3% | 10.5% | 7.1% |
| 0.9 | 6.0% | 10.9% | 5.1% |
[i] Across all levels of genetic correlation, the ePRS shows smaller standard errors compared with elastic net (EN), which does not leverage genome-wide association study summary statistics defined on external sources. rg represents the genetic correlation between the source and target phenotypes, whereas model instability is measured by the standard error of the coefficient of determination (R2) across 100 bootstrapped samples. The most stable model for each rg is shown in bold. Although pruning and thresholding (P+T) demonstrates greater stability when the source and target phenotypes are highly correlated, the ePRS outperforms P+T in both prediction tasks: juvenile myoclonic epilepsy risk prediction and subtype differentiation, as shown in Figure 1, A and B.