Evidence map›Paper›PMID 38747160›Full record

ArticleAging cell2024

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

Chia-Ling Kuo, Zhiduo Chen, Peiran Liu, Luke C Pilling, Janice L Atkins, Richard H Fortinsky, George A Kuchel, Breno S Diniz

Abstract read
In one paragraph

Article in Aging cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Proteomic Markers of Aging and Longevity: A Systematic Review.International journal of molecular sciences · 2024
    Pooled it
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  8. Functional, molecular, and digital measurements of biological age.The Journal of clinical investigation · 2026
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  17. Histone modification clocks for robust cross-species biological age prediction and elucidating senescence regulation.Proceedings of the National Academy of Sciences of the United States of America · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Chia-Ling KuoDepartment of Public Health Sciences, University of Connecticut Health Center, Farmington, Connecticut, USA.ORCID 0000-0003-4452-2380
Zhiduo ChenUConn Center on Aging, University of Connecticut Health Center, Farmington, Connecticut, USA.
Peiran LiuThe Cato T. Laurencin Institute for Regenerative Engineering, University of Connecticut Health Center, Farmington, Connecticut, USA.
Luke C PillingEpidemiology and Public Health Group, Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK.
Janice L AtkinsEpidemiology and Public Health Group, Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK.ORCID 0000-0003-4919-9068
Richard H FortinskyUConn Center on Aging, University of Connecticut Health Center, Farmington, Connecticut, USA.
George A KuchelUConn Center on Aging, University of Connecticut Health Center, Farmington, Connecticut, USA.ORCID 0000-0001-8387-7040
Breno S DinizDepartment of Public Health Sciences, University of Connecticut Health Center, Farmington, Connecticut, USA.

Funding

Research Education ComponentP30AG067988 · NIA · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI Richard H Fortinsky, GEORGE A KUCHEL · 2021 to 2026
$9.5M
National Institute for Health and Care Research NIHR301844NIA NIH HHS P30 AG067988NIA NIH HHS P30AG067988
6 · The paper itself

Abstract

Beyond 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. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2923 plasma proteins assessed using the Olink Explore 3072 assay®. 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death of 70.1 years. The Spearman correlation between PAC proteomic age and chronological age was 0.77. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC proteomic age deviation were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that biological age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, 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.

Indexed as

AgingProteomicsAdultAgedBiomarkersFemaleHumansMaleMiddle AgedBiomarkersaccelerated biological agingBioAgebiological age deviationcomposite aging biomarkersleukocyte telomere lengthPhenoAgeUK biobank pharma proteomics project

Identifiers

PMID38747160
PMCPMC11320350

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.