The abstract is read at the publisher; the summary is JClub's.
Joint genomic-proteomic models integrating PRS and ProRS improve complex trait prediction in 36,903 UK Biobank participants, increasing R² by 0.09–0.66 and AUC by 0.06–0.17 beyond PRS alone.
- Why it matters: PRS and circulating proteins may capture complementary biology, but it was unclear whether ProRS adds value beyond PRS, how missing proteomics affects performance, and whether gains hold across populations and disease stages.
- What they did: The study built an imputation and ensemble framework combining PRS and ProRS across 11 continuous and disease traits, testing five imputation methods where expectation-maximization performed best.
- The result: Joint models outperformed PRS-only and ProRS-only in European-ancestry validation and showed similar gains in non-European populations; mediation suggested 55%–81% of PRS lipid-trait associations run through ProRS.
The findingWhy it mattersWhat they didThe result
AI summary of the abstract · may contain errors · not medical advice · read the paper.