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

Abstract

SummaryBackgroundBeyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might therefore offer useful information for the testing and ultimately clinical use of gerotherapeutics. Using a large proteomic cohort in the UK Biobank (UKB), we aimed to develop a proteomic aging clock for all-cause mortality risk as a proxy of biological age (BA).MethodsParticipants in the UK Biobank Pharma Proteomics Project (UKB PPP) were included with ages between 39 and 70 years (n=53,021). Data were split into a training (70%, n=37,115) and a test set (30%, n=15,906), including 2,923 plasma proteins assessed using the Olink Explore 3072 assay®. We developed a proteomic aging clock (PAC) for all-cause mortality risk as a surrogate of BA using a combination of Least Absolute Shrinkage and Selection Operator (LASSO) penalized Cox regression and Gompertz proportional hazards models. The validation for PAC included assessing its age-adjusted associations with, and predictions for all-cause mortality and 18 incident diseases, and head-to-head comparisons with two biological age measures (PhenoAge and BioAge) and leukocyte telomere length (LTL). Additionally, a functional analysis was performed to identify gene sets and tissues enriched with genes associated with BA deviation, based on different BA measures.FindingsThe Spearman correlation between PAC proteomic age and chronological age was 0.76. 10.9% of the combined training and test samples died during a mean follow-up of 13.3 years (SD=2.2), with the mean age at death 70.1 years (SD=8.1). PAC proteomic age, after controlling for age and other covariates, showed stronger associations than PhenoAge, BioAge, and LTL, with mortality and multiple incident diseases in the test set sample and in disease-free participants, such as mortality, heart failure, pneumonia, delirium, Chronic Obstructive Pulmonary Disease (COPD), and dementia. Additionally, PAC proteomic age showed higher predictive power for the conditions above compared to chronological age, PhenoAge, and BioAge, based on Harrell’s C-statistics. Proteins associated with PAC proteomic age deviation (from chronological age) are enriched in various hallmarks of biological aging, including immunoinflammatory responses, cellular senescence, extracellular matrix remodeling, cellular response to stressors, and vascular biology.InterpretationPAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases. The diverse hallmark gene sets linked with PAC proteomic age deviation highlight the potential efficacy of geroscience-guided interventions. Further validation is essential to ascertain the use of PAC across different settings.FundingAccess to UK Biobank data was granted under application no. 92647 “Research to Inform the Field of Precision Gerontology” (PI: Richard H. Fortinsky), funded by the Claude D. Pepper Older American Independence Centers (OAIC) program: P30AG067988 (MPIs: George A. Kuchel and Richard H. Fortinsky). CLK, BSD, RHF, and GAK are partially supported by P30AG067988. JLA has a UK National Institute for Health and Care Research (NIHR) Advanced Fellowship (NIHR301844).Research in contextProteomic aging clocks have been developed using the BA surrogate of chronological age, but their validation remains limited. None had been developed using the surrogate of all-cause mortality risk, which is believed more sensitive to changes in biological aging processes. We relied on two recent comprehensive review papers1,2and expanded our search on PubMed and Google Scholar for English articles, using keywords including “biomarkers of aging”, “biological age predictors”, “biological age deviation”, “accelerated biological aging”, “methylation clocks”, “proteomic clocks”, “UK Biobank biomarkers”, “UK Biobank Pharma Proteomics Project”, “PhenoAge”, “BioAge”, “telomere length”, “SASP index”, and “composite aging biomarkers”.Added value of this studyTo the best of our knowledge, PAC is the first proteomic aging clock developed for all-cause mortality risk as a surrogate of BA, using the largest dataset of proteins and individuals in the world. Our results expand previous findings by showing that PAC age acceleration strongly predicts not only all-cause mortality but also several incident disease outcomes, with a follow-up exceeding a decade and a substantial sample size to ensure adequate statistical power.Implications of all the available evidenceDue to its associations and predictive value for all-cause mortality and multiple incident diseases, PAC has the potential to serve as a valuable tool for assessing the effects of geoscience-guided interventions. It facilitates the evaluation of risk for multiple conditions in a disease-free population; thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.

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