生命银行
糖尿病
疾病
入射(几何)
蛋白质组
医学
比例危险模型
危险分层
2型糖尿病
内科学
生物信息学
生物
内分泌学
光学
物理
作者
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,Christopher N. Foley,Riccardo E. Marioni,Benjamin B. Sun
出处
期刊:Nature Aging
日期:2024-07-10
卷期号:4 (7): 939-948
被引量:36
标识
DOI:10.1038/s43587-024-00655-7
摘要
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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