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Cited by 1,012Genetics, Aging, and Longevity in Model OrganismsAging and Gerontology ResearchTelomeres, Telomerase, and Senescence

Quantification of biological aging in young adults

Open access
Belsky, Daniel W., Caspi, Avshalom, Houts, Renate, Cohen, Harvey J., Corcoran, David L., Danese, Andrea, Harrington, HonaLee, Israel, Salomon +7 more·2015·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.1506264112PMC PMC4522793
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Abstract

Significance: The global population is aging, driving up age-related disease morbidity. Antiaging interventions are needed to reduce the burden of disease and protect population productivity. Young people are the most attractive targets for therapies to extend healthspan (because it is still possible to prevent disease in the young). However, there is skepticism about whether aging processes can be detected in young adults who do not yet have chronic diseases. Our findings indicate that aging processes can be quantified in people still young enough for prevention of age-related disease, opening a new door for antiaging therapies. The science of healthspan extension may be focused on the wrong end of the lifespan; rather than only studying old humans, geroscience should also study the young.

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  • In humans, aging processes such as proinflammation and cognitive decline begin in midlife.

    “Interestingly, emerging evidence also suggests that in humans the aging processes, such as proinflammation and cognitive decline, begin in midlife(Ferrucci et al. 2005, Belsky et al. 2015).”

    From miR‐186 is decreased in aged brain and suppresses <scp>BACE</scp>1 expression (2016) · cites this paper as Belsky et al. 2015

    The paper’s Discussion reports age-related biomarker changes from ages 26 to 38, and its brain-aging section reports cognitive decline associated with older Biological Age at age 38. This supports aging and cognitive decline being detectable by midlife, but the passages do not establish proinflammation specifically or that these processes begin in midlife rather than earlier. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Authors
Belsky, D. W., Caspi, A., Houts, R., Cohen, H. J., Corcoran, D. L., Danese, A., Harrington, H., Israel, S., Levine, M. E., Schaefer, J. D., Sugden, K., Williams, B., Yashin, A. I., Poulton, R., & Moffitt, T. E.
Affiliations
  • Duke University (US)
  • King's College London (GB)
  • Hebrew University of Jerusalem (IL)
  • University of California, Los Angeles (US)
  • University of Otago (NZ)
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2015-07-06
Volume
112
Issue
30
Pages
E4104-10
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.1506264112
PMC
PMC4522793
OpenAlex
W2126104386
Cited by
1,012
References
7
Citations by year
2026: 88 · 2025: 104 · 2024: 131 · 2023: 115 · 2022: 82 · 2021: 111 · 2020: 82 · 2019: 82 · 2018: 93 · 2017: 49 · 2016: 51 · 2015: 22
FWCI
28.83
Type
journal article
Language
en
Open access
Licence
www.pnas.org/site/misc/userlicense.xhtml (vor)
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • Research Portal (King's College London) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • DukeSpace (Duke University) (submittedVersion, cc-by-nc-nd)
Funders
  • HHS | NIH | National Institute on Aging (AG032282, AG048895, AG000029, AG028716)
  • Medical Research Council (MR/K00381X)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
  • Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
Keywords
biological aging, young adults, aging biomarkers, pace of aging, physical fitness, cognitive decline, brain aging, self-rated health, rejuvenation therapy
MeSH terms
Adult, Aging, Cognition, Cross-Sectional Studies, Humans, Life Expectancy, Longitudinal Studies, Middle Aged, Regression Analysis, Time Factors, Biomarkers

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