Table 1.
Prediction accuracy of 15 different approaches to construct PRS in the analyses of LDL in the African cohort of UK Biobank
| Model | Predicted R2of PRS | Mean difference between top 10% and bottom 10% PRS |
|---|---|---|
| Single-source PRS methods | ||
| PT (UKBB) | 0.012 (0.004, 0.023) | 0.388 (0.199, 0.564) |
| Lsum (UKBB) | 0.033 (0.019, 0.048) | 0.625 (0.423, 0.779) |
| TL-PRS-Lsum (UKBB) | 0.058 (0.040, 0.079) | 0.779 (0.602, 0.943) |
| PRS-CS (UKBB) | 0.022 (0.012, 0.037) | 0.552 (0.369, 0.714) |
| TL-PRS-CS (UKBB) | 0.028 (0.015, 0.044) | 0.506 (0.343, 0.721) |
| PT (BBJ) | 0.028 (0.018, 0.045) | 0.474 (0.326, 0.639) |
| Lsum (BBJ) | 0.048 (0.032, 0.067) | 0.595 (0.456, 0.770) |
| TL-PRS-Lsum (BBJ) | 0.068 (0.048, 0.090) | 0.795 (0.625, 0.967) |
| PRS-CS (BBJ) | 0.023 (0.012, 0.036) | 0.421 (0.274, 0.602) |
| TL-PRS-CS (BBJ) | 0.028 (0.016, 0.044) | 0.565 (0.389, 0.733) |
| Multi-source PRS methods | ||
| PT-multi | 0.030 (0.019, 0.046) | 0.531 (0.405, 0.715) |
| Lsum-multi | 0.052 (0.036, 0.073) | 0.727 (0.581, 0.895) |
| MTL-PRS-Lsum | 0.068 (0.047, 0.088) | 0.926 (0.727, 1.073) |
| PRSCSx | 0.037 (0.022, 0.054) | 0.662 (0.483, 0.823) |
| MTL-PRS-CS | 0.044 (0.028, 0.062) | 0.721 (0.569, 0.908) |
The bootstrap confidence interval is shown in the parentheses. For single-source PRS methods, the training GWAS summary source is shown in the parentheses. The approach with highest predicted R2 is highlighted using italics. UKBB, UK Biobank; BBJ, BioBank Japan.