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 1,459 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 (Rg=0.17 to 0.19) and telomere length (Rg=-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.

Publication Details

Journal
Apollo (University of Cambridge)
Published
2025-04-01
DOI
https://doi.org/10.17863/cam.117431
Primary Topic
Bone health and treatments
Type
article
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article

Genetic determinants of proteomic aging

Apollo (University of Cambridge)
Bone health and treatments
article

Genetic determinants of proteomic aging

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 1,459 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 (Rg=0.17 to 0.19) and telomere length (Rg=-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.

Apollo (University of Cambridge)
Good health and well-being
Openalex Percentile: Top 41%
Bone health and treatments
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Genetic determinants of proteomic aging · Apollo (University of Cambridge) (2025) | TGRS Research Map | TGRS