Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm
Open accessPublished version of a preprint
Abstract
Biological aging is the gradual, progressive decline in system integrity that occurs with advancing chronological age, causing morbidity and disability. Measurements of the pace of aging are needed as surrogate endpoints in trials of therapies designed to prevent disease by slowing biological aging. We report a blood-DNA-methylation measure that is sensitive to variation in pace of biological aging among individuals born the same year. We first modeled change-over-time in 18 biomarkers tracking organ-system integrity across 12 years of follow-up in n = 954 members of the Dunedin Study born in 1972–1973. Rates of change in each biomarker over ages 26–38 years were composited to form a measure of aging-related decline, termed Pace-of-Aging. Elastic-net regression was used to develop a DNA-methylation predictor of Pace-of-Aging, called DunedinPoAm for Dunedin(P)ace(o)f(A)ging(m)ethylation. Validation analysis in cohort studies and the CALERIE trial provide proof-of-principle for DunedinPoAm as a single-time-point measure of a person’s pace of biological aging.
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The DunedinPoAm DNAm clock had stronger, more significant associations with age-related phenotypes, including physical functioning, cognition, self-rated health and mortality, than the DNAm PhenoAge clock.
“This clock had stronger, more significant associations with age-related phenotypes, including physical functioning, cognition, self-rated health and mortality, than the DNAm PhenoAge clock.”
From Measuring biological age using omics data (2022) · cites this paper as [73]
The DunedinPoAm DNAm clock was trained to more directly predict an individual's ageing rate using longitudinal data.
“More recently, Belsky et al.73 built the DunedinPoAm DNAm clock, an exciting development that, unlike many previous clocks that were trained to predict an individual’s current ageing state from cross-sectional data, was trained to more directly predict an individual’s ageing rate using longitudinal data.”
From Measuring biological age using omics data (2022) · cites this paper as [73]
Belsky et al. developed a DNA methylation clock surrogate for longitudinal health and biomarker measurements to more directly predict an individual's ageing rate instead of relying on cross-sectional measures of relative biological age.
“Here, the authors developed a DNA methylation clock surrogate for longitudinal health and biomarker measurements to more directly predict an individual’s ageing rate instead of relying on cross-sectional measures of relative biological age.”
From Measuring biological age using omics data (2022) · cites this paper as [73]
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References 81 · Cited by 652
Research works printed but not linked: 1
- Belsky DW 2020 Code for "Quantification of the pace of biological aging in humans through a blood test: The DunedinPoAm DNA methylation algorithm" GitHub 9e34563 https://github.com/danbelsky/DunedinPoAm_eLife2020 PMC7282814 32367804
- Authors
- Belsky, D. W., Caspi, A., Arseneault, L., Baccarelli, A., Corcoran, D. L., Gao, X., Hannon, E., Harrington, H. L., Rasmussen, L. J., Houts, R., Huffman, K., Kraus, W. E., Kwon, D., Mill, J., Pieper, C. F., Prinz, J. A., Poulton, R., Schwartz, J., Sugden, K., Vokonas, P., Williams, B. S., & Moffitt, T. E.
- Affiliations
- Columbia University (US)
- Duke University (US)
- King's College London (GB)
- University of Exeter Medical School, College of Medicine and Health, Exeter, United Kingdom
- Department of Psychology and Neuroscience, Duke University, Durham, United States
- University of Exeter (GB)
- University of Otago (NZ)
- Harvard University (US)
- Boston University (US)
- Corresponding author
- Belsky, Daniel W
- ORCID
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2020-05-05
- Volume
- 9
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC7282814
- OpenAlex
- W3022131036
- Cited by
- 652
- References
- 81
- Citations by year
- 2026: 132 · 2025: 149 · 2024: 118 · 2023: 80 · 2022: 107 · 2021: 51 · 2020: 15
- FWCI
- 20.52
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion, cc-by)
- Funders
- Medical Research Council (MR/P005918/1, G1002190)
- National Institute on Aging (R01AG032282, U24AG047121, R01AG061378, R21AG054846)
- National Institute of Child Health and Development (R01HD077482)
- CIFAR (CBD Network Fellowship)
- Jacobs Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Aging › Genetics, Aging, and Longevity in Model Organisms
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Keywords
- DNA methylation, blood biomarkers, surrogate endpoints, Dunedin Study, aging interventions, epigenetic aging
- MeSH terms
- Adult, Aged, Aged, 80 and over, Aging, Algorithms, Chronic Disease, Cognition, Female, Humans, Male, Middle Aged, Risk Factors, DNA Methylation, Cognitive Dysfunction
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