Cited by 213Epigenetics and DNA MethylationTelomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model Organisms

Associations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study

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Crimmins, Eileen M, Thyagarajan, Bharat, Levine, Morgan E, Weir, David R, Faul, Jessica·2021·The Journals of Gerontology: Series A

Abstract

Background: Many DNA methylation-based indicators have been developed as summary measures of epigenetic aging. We examine the associations between 13 epigenetic clocks, including 4 second generation clocks, as well as the links of the clocks to social, demographic, and behavioral factors known to be related to health outcomes: sex, race/ethnicity, socioeconomic status, obesity, and lifetime smoking pack-years. Methods: The Health and Retirement Study is the data source which is a nationally representative sample of Americans over age 50. Assessment of DNA methylation was based on the EPIC chip and epigenetic clocks were developed based on existing literature. Results: The clocks vary in the strength of their relationships with age, with each other and with independent variables. Second generation clocks trained on health-related characteristics tend to relate more strongly to the sociodemographic and health behaviors known to be associated with health outcomes in this age group. Conclusions: Users of this publicly available data set should be aware that epigenetic clocks vary in their relationships to age and to variables known to be related to the process of health change with age.

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  • Gendered caregiving expectations may heighten stress for grandfathers, while women's generally slower epigenetic aging may buffer effects.

    “Gendered caregiving expectations may heighten stress for grandfathers, while women’s generally slower epigenetic aging may buffer effects (Crimmins et al., 2021; Park, 2009).”

    From Grandparent Caregiving and Epigenetic Aging among Midlife and Older Adults in the United States (2026) · cites this paper as Crimmins et al., 2021

    The Discussion (page unavailable) says most, though not all, epigenetic clocks indicate accelerated aging among men, supporting the comparison that women generally age more slowly by these measures. The paper does not address caregiving expectations, stress in grandfathers, or whether women's epigenetic aging buffers caregiving effects. (LLM, conf=0.88)

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  • Women have slower rates of epigenetic aging than men across most epigenetic clocks.

    “Notwithstanding, studies suggest that women have slower rates of epigenetic aging than men across most epigenetic clocks (epigenetic aging clocks will be described in a later section; Crimmins et al., 2021).”
  • The DNAm GrimAge clock shows consistently stronger associations with various measures of age-related dysfunction, including heart disease, frailty, and cognitive and physical decline, compared to other clocks.

    “The DNAm GrimAge clock shows consistently stronger associations with various measures of age-related dysfunction, including heart disease, frailty, and cognitive and physical decline, compared to other clocks47,48,50,64–72.”

    From Measuring biological age using omics data (2022) · cites this paper as [69]

  • Age gaps in second-generation mortality-optimized clocks (Zhang, PhenoAge, GrimAge) also correlate only mildly with each other.

    “Age gaps in second-generation mortality-optimized clocks (Zhang, PhenoAge, GrimAge) also correlate only mildly with each other69,151.”

    From Measuring biological age using omics data (2022) · cites this paper as [69]

  • Age gaps from first-generation epigenetic clocks (Hannum, Horvath, Lin, Weidner, Vidal-Bralo) only mildly correlate with each other (r = 0.1-0.5).

    “Despite all being modelled and trained on the chronological age of individuals, mostly from blood cells, age gaps from first-generation epigenetic clocks (Hannum, Horvath, Lin, Weidner, Vidal-Bralo) seem to only mildly correlate with each other (r = 0.1–0.5)69,151.”

    From Measuring biological age using omics data (2022) · cites this paper as [69]

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Authors
Crimmins, E. M., Thyagarajan, B., Levine, M. E., Weir, D. R., & Faul, J.
Affiliations
  • University of Southern California (US)
  • University of Minnesota (US)
  • Yale University (US)
  • University of Michigan (US)
Corresponding author
Crimmins, Eileen M
Venue
The Journals of Gerontology: Series A
Published
2021-01-16
Volume
76
Issue
6
Pages
1117-1123
ISSN
  • 1079-5006 (ISSN-L)
  • 1758-535X
OpenAlex
W3121574040
Cited by
213
References
33
Citations by year
2026: 29 · 2025: 56 · 2024: 42 · 2023: 41 · 2022: 35 · 2021: 10
FWCI
10.12
Type
journal article
Language
en
Open access
Locations
  • The Journals of Gerontology Series A (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Funders
  • National Institute on Aging (R01 AG AG060110)
  • Health and Retirement Study (NIA U01 AG009740)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
Keywords
epigenetic clocks, DNA methylation, epigenetic aging, sex differences, race and ethnicity, socioeconomic status, obesity, pack-years, age, older adults, Health and Retirement Study
MeSH terms
Age Factors, Aged, Aging, Biological Clocks, Educational Status, Female, Humans, Male, Obesity, Sex Factors, Smoking, Socioeconomic Factors, United States, Health Behavior, DNA Methylation, Epigenesis, Genetic, Racial Groups

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