Blood protein assessment of leading incident diseases and mortality in the UK Biobank
Danni A. Gadd, Robert F. Hillary, Zhana Kuncheva, Tasos Mangelis, Yipeng Cheng, Manju Dissanayake, Romi Admanit, Jake Gagnon, Tin-Chi Lin, Kyle Ferber, Heiko Runz, Biogen Biobank Team, Kyle L. Ferber, Christopher N. Foley, Riccardo E. Marioni, Benjamin B. Sun
Abstract
The circulating proteome offers insights into the biological pathways that underlie disease. Here, we test relationships between 1,468 Olink protein levels and the incidence of 23 age-related diseases and mortality in the UK Biobank (n = 47,600). We report 3,209 associations between 963 protein levels and 21 incident outcomes. Next, protein-based scores (ProteinScores) are developed using penalized Cox regression. When applied to test sets, six ProteinScores improve the area under the curve estimates for the 10-year onset of incident outcomes beyond age, sex and a comprehensive set of 24 lifestyle factors, clinically relevant biomarkers and physical measures. Furthermore, the ProteinScore for type 2 diabetes outperforms a polygenic risk score and HbA1c-a clinical marker used to monitor and diagnose type 2 diabetes. The performance of scores using metabolomic and proteomic features is also compared. These data characterize early proteomic contributions to major age-related diseases, demonstrating the value of the plasma proteome for risk stratification.