Blood protein assessment of leading incident diseases and mortality in the UK Biobank

Danni A. Gadd(Edinburgh Cancer Research), Robert F. Hillary(Edinburgh Cancer Research), Zhana Kuncheva(Optimat (United Kingdom)), Tasos Mangelis(Optimat (United Kingdom)), Yipeng Cheng(Edinburgh Cancer Research), Manju Dissanayake(Optimat (United Kingdom)), Romi Admanit(Biogen (United States)), Jake Gagnon(Biogen (United States)), Tin-Chi Lin(Biogen (United States)), Kyle Ferber(Biogen (United States)), Heiko Runz(Biogen (United States)), Biogen Biobank Team(Optimat (United Kingdom)), Kyle L. Ferber(Biogen (United States)), Christopher N. Foley(Biogen (United States)), Riccardo E. Marioni(Edinburgh Cancer Research), Benjamin B. Sun(Biogen (United States))
Nature Aging
July 10, 2024
Cited by 127Open Access
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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.


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