Cited by 166Genetics, Aging, and Longevity in Model OrganismsAdvanced Proteomics Techniques and ApplicationsAging and Gerontology Research

Systematic review and analysis of human proteomics aging studies unveils a novel proteomic aging clock and identifies key processes that change with age

Johnson, Adiv A., Shokhirev, Maxim N., Wyss-Coray, Tony, Lehallier, Benoit·2020·Ageing Research Reviews

Abstract

The development of clinical interventions that significantly improve human healthspan requires robust markers of biological age as well as thoughtful therapeutic targets. To promote these goals, we performed a systematic review and analysis of human aging and proteomics studies. The systematic review includes 36 different proteomics analyses, each of which identified proteins that significantly changed with age. We discovered 1,128 proteins that had been reported by at least two or more analyses and 32 proteins that had been reported by five or more analyses. Each of these 32 proteins has known connections relevant to aging and age-related disease. GDF15, for example, extends both lifespan and healthspan when overexpressed in mice and is additionally required for the anti-diabetic drug metformin to exert beneficial effects on body weight and energy balance. Bioinformatic enrichment analyses of our 1,128 commonly identified proteins heavily implicated processes relevant to inflammation, the extracellular matrix, and gene regulation. We additionally propose a novel proteomic aging clock comprised of proteins that were reported to change with age in plasma in three or more different studies. Using a large patient cohort comprised of 3,301 subjects (aged 18-76 years), we demonstrate that this clock is able to accurately predict human age.

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Crossref · 10.1016/j.arr.2020.101070

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  • Follow-up studies have shown that dozens of proteins identified in plasma proteomic ageing clocks directly regulate lifespan, and hundreds have biological connections to the health status of different organs.

    “Follow-up studies have shown that dozens of proteins identified in plasma proteomic ageing clocks directly regulate lifespan, and hundreds have biological connections to the health status of different organs98,99.”

    From Measuring biological age using omics data (2022) · cites this paper as [98]

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Authors
Johnson, A. A., Shokhirev, M. N., Wyss-Coray, T., & Lehallier, B.
Affiliations
  • Nikon (United States) (US)
  • Salk Institute for Biological Studies (US)
  • Stanford Medicine (US)
Corresponding author
Johnson, Adiv A.
Venue
Ageing Research Reviews
Publisher
Elsevier BV
Published
2020-07
Volume
60
Pages
101070
ISSN
1568-1637 (ISSN-L)
OpenAlex
W3017299963
Cited by
166
References
187
Citations by year
2026: 22 · 2025: 33 · 2024: 29 · 2023: 21 · 2022: 28 · 2021: 24 · 2020: 9
FWCI
2.58
Type
journal article
Language
en
Open access
closed
Locations
  • Ageing Research Reviews (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institute on Handicapped Research (BTRU-2014-10024)
  • British Heart Foundation (RG/13/13/30194)
  • NOMIS Stiftung
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
Keywords
biological age, aging, plasma proteomics, healthspan, GDF15, metformin, inflammation, extracellular matrix, gene expression regulation, age prediction, age-related diseases
MeSH terms
Aged, Aging, Animals, Gene Expression Regulation, Humans, Longevity, Biomarkers, Proteomics, Mice

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