Genetic determinants of proteomic aging

Changes in the proteome and its dysregulation have long been known to be a hallmark of aging. We derived a proteomic aging trait using data on 1459 plasma proteins from 44,435 UK Biobank individuals measured using an antibody-based assay. This metric is strongly associated with four age-related disease outcomes, even after adjusting for chronological age. Survival analysis showed that one-year older proteomic age, relative to chronological age, increases all-cause mortality hazard by 13 percent. We performed a genome-wide association analysis of proteomic age acceleration (proteomic aging trait minus chronological age) to identify its biological determinants. Proteomic age acceleration showed modest genetic correlations with four epigenetic clocks (R<sub>g</sub> = 0.17 to 0.19) and telomere length (R<sub>g</sub> = -0.2). Once we removed associations that were explained by a single pQTL, we were left with three signals mapping to BRCA1, POLR2A and TET2 with apparent widespread effects on plasma proteomic aging. Genetic variation at these three loci has been shown to affect other omics-related aging measures. Mendelian randomisation analyses showed causal effects of higher BMI and type 2 diabetes on faster proteomic age acceleration. This supports the idea that obesity and other features of metabolic syndrome have an adverse effect on the processes of human aging.

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Publication Details

Journal
npj Aging
Published
2025-04-26
DOI
https://doi.org/10.1038/s41514-025-00205-4
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.00

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article

Genetic determinants of proteomic aging

Ken K. Ong, John R. B. Perry, Katherine A. Kentistou, Felix R. Day et al.
npj Aging
Epigenetics and DNA Methylation
article

Genetic determinants of proteomic aging

Ken K. Ong, John R. B. Perry, Katherine A. Kentistou, Felix R. Day, Yajie Zhao, Alexander Mörseburg
article en

Abstract

Changes in the proteome and its dysregulation have long been known to be a hallmark of aging. We derived a proteomic aging trait using data on 1459 plasma proteins from 44,435 UK Biobank individuals measured using an antibody-based assay. This metric is strongly associated with four age-related disease outcomes, even after adjusting for chronological age. Survival analysis showed that one-year older proteomic age, relative to chronological age, increases all-cause mortality hazard by 13 percent. We performed a genome-wide association analysis of proteomic age acceleration (proteomic aging trait minus chronological age) to identify its biological determinants. Proteomic age acceleration showed modest genetic correlations with four epigenetic clocks (R<sub>g</sub> = 0.17 to 0.19) and telomere length (R<sub>g</sub> = -0.2). Once we removed associations that were explained by a single pQTL, we were left with three signals mapping to BRCA1, POLR2A and TET2 with apparent widespread effects on plasma proteomic aging. Genetic variation at these three loci has been shown to affect other omics-related aging measures. Mendelian randomisation analyses showed causal effects of higher BMI and type 2 diabetes on faster proteomic age acceleration. This supports the idea that obesity and other features of metabolic syndrome have an adverse effect on the processes of human aging.

npj AgingVol. 11(1)
University of Cambridge (GB), Wellcome/MRC Institute of Metabolic Science (GB), MRC Epidemiology Unit (GB)
Wellcome, Wellcome Trust, Medical Research Council, Medical Research Foundation
Good health and well-being
Openalex Percentile: Top 92%
Epigenetics and DNA Methylation
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