Blood protein levels predict leading incident diseases and mortality in UK Biobank

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, ascertained over 16 years of electronic health linkage in the UK Biobank (N=49,234). We report 3,123 associations between 1,052 protein levels and incident diseases (PBonferroni < 5.4x10-6). Forty four proteins are indicators of eight or more morbidities. Next, protein-based scores (ProteinScores) are developed using penalised Cox regression. When applied to test sets, eight ProteinScores improve Area Under the Curve (AUC) estimates for the 10-year onset of incident outcomes (PBonferroni < 0.0025) beyond age, sex and additional health and lifestyle covariates. The type 2 diabetes ProteinScore outperforms HbA1c (P = 5.7x10-12), a clinical marker used to monitor and diagnose type 2 diabetes. A maximal type 2 diabetes model including the ProteinScore, HbA1c and a polygenic risk score has AUC = 0.90 and Precision-Recall AUC = 0.76. These data characterise early proteomic contributions to major age-related disease.

Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults

“…Previous studies have identified circulating proteins associated with chronological age (Moaddel et al 2021;Sathyan et al 2020;Tanaka et al 2018), mortality (Orwoll et al 2018;Eiriksdottir et al 2021), and chronic diseases (Gadd et al 2023;Carrasco-Zanini et al 2023).…”

“…Previous studies have identified circulating proteins associated with chronological age 14 and chronic diseases 15 . A protein-based score has shown significant improvements in risk classification even after accounting for common risk factors.…”

Plasma proteomic profiles of UK Biobank participants with multiple sclerosis

“…2 The fact that plasma NFL was the protein most strongly and consistently associated with MS in our study across a range of sensitivity analyses is a reassuring positive control. 16 In addition to the established markers of neuroaxonal damage NFL and GFAP, we identify elevation of several plasma proteins in MS patients, including cytokines and cytokine receptors (IL22, IL17RB, and IL15), proteins involved in lysosomal processing (LAMP3, CTSF), and regulators of monocyte/microglial function (MERTK, LILRB4). 12,[32][33][34][35][36] While these findings suggest a variety of plausible targets for therapeutic intervention in MS, most of these alterations were observed in other autoimmune disorders and/or neurodegenerative conditions, suggesting that they are unlikely to be of significant diagnostic value in distinguishing MS from alternative conditions.…”

“…UK Biobank-a large long-term biobank study of >500,000 British adults-has recently applied the Olink proximity extension assay technology to measure the plasma level of $3000 proteins in >50,000 of its participants, providing an invaluable resource for examining the associations between genetics, protein levels, and health outcomes. [14][15][16] The prevalence of MS in UK Biobank is similar to the UK population (0.5%), and so this resource is also of significant value for MS proteomics research. 17 In this study, we analyzed proteomic data from MS cases and healthy controls in UK Biobank to search for proteomic signatures associated with MS disease status and with MS severity.…”

Epigenetic Contributions to Clinical Risk Prediction of Cardiovascular Disease

“…These include GDF15 (growth differentiation factor 15), NT-proBNP (N-terminal pro-Btype natriuretic peptide), and ADM (adrenomedullin). [4][5][6][7] An established and highly sensitive marker of myocardial damage is cardiac troponin. 8 It is a complex of 3 proteins, namely, cTnI (cardiac troponin I), cTnT (cardiac troponin T), and cTnC (cardiac troponin C) regulating the contraction of the cardiac muscle.…”