DNA methylation-based measures of biological age: meta-analysis predicting time to death
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Aging | doi:10.18632/aging.101020. Brian H. Chen, Riccardo E. Marioni, Elena Colicino, Marjolein J. Peters, Cavin K. Ward-Caviness, Pei-Chien Tsai, Nicholas S. Roetker, Allan C. Just, Ellen W. Demerath, Weihua Guan, Jan Bressler, Myriam Fornage, Stephanie Studenski, Amy R. Vandiver, Ann Zenobia Moore, Toshiko Tanaka, Douglas P. Kiel, Liming Liang, Pantel Vokonas, Joel Schwartz, Kathryn L. Lunetta, Joanne M. Murabito, Stefania Bandinelli, Dena G. Hernandez, David Melzer, Michael Nalls, Luke C. Pilling, Timothy R. Price, Andrew B. Singleton, Christian Gieger, Rolf Holle, Anja Kretschmer, Florian Kronenberg, Sonja Kunze, Jakob Linseisen, Christine Meisinger, Wolfgang Rathmann, Melanie Waldenberger, Peter M. Visscher, Sonia Shah, Naomi R. Wray, Allan F. McRae, Oscar H. Franco, Albert Hofman, André G. Uitterlinden, Devin Absher, Themistocles Assimes, Morgan E. Levine, Ake T. Lu, Philip S. Tsao, Lifang Hou, JoAnn E. Manson, Cara L. Carty, Andrea Z. LaCroix, Alexander P. Reiner, Tim D. Spector, Andrew P. Feinberg, Daniel Levy, Andrea Baccarelli, Joyce van Meurs, Jordana T. Bell, Annette Peters, Ian J. Deary, James S. Pankow, Luigi Ferrucci, Steve Horvath
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Individuals with positive age gaps, termed age acceleration, are at greater risk of mortality and some diseases of ageing such as heart disease, metabolic syndrome and certain cancers.
“These hypotheses have been supported by observations that individuals with positive age gaps, termed age acceleration, are at greater risk of mortality and some diseases of ageing such as heart disease, metabolic syndrome and certain cancers46–50.”
From Measuring biological age using omics data (2022) · cites this paper as [46]
Mortality risk has shown an overall weak and variable association with DNA methylation clocks.
“However, mortality risk, which is widely used as a measure of ‘global’ biological age, has shown an overall weak and variable association with these clocks46,58, which raises questions as to what biology they actually measure.”
From Measuring biological age using omics data (2022) · cites this paper as [46]
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DNA Methylation Biomarkers in Aging and Age-Related Diseases
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Epigenetic aging in major depressive disorder
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Self-citationUnderlying features of epigenetic aging clocks in vivo and in vitro.
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Self-citationPlasma proteomic biomarker signature of age predicts health and life span
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Self-citationDistinct biological ages of organs and systems identified from a multi-omics study
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Determinants of accelerated metabolomic and epigenetic aging in a UK cohort
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GWAS of epigenetic aging rates in blood reveals a critical role for TERT
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Self-citationA multi-tissue full lifespan epigenetic clock for mice
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Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis
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Self-citationChange in the Rate of Biological Aging in Response to Caloric Restriction: CALERIE Biobank Analysis
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Epigenetics and Oxidative Stress in Aging
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The nasal methylome as a biomarker of asthma and airway inflammation in children
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Self-citationMethylation-Based Biological Age and Breast Cancer Risk
Kresovich, J. K., Xu, Z., O’Brien, K. M., Weinberg, C. R., Sandler, D. P., & Taylor, J. A. (2019) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djz020 · Cited by 189 · see citing works
The accelerated aging phenotype: The role of race and social determinants of health on aging
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DNA methylation dynamics in aging: how far are we from understanding the mechanisms?
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DNA methylation predicts age and provides insight into exceptional longevity of bats
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Self-citationBiT age: A transcriptome‐based aging clock near the theoretical limit of accuracy
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DNA methylation-based age clocks: From age prediction to age reversion
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An epigenetic aging clock for dogs and wolves
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Self-citationCell‐free DNA as a biomarker of aging
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Accelerated epigenetic aging in Werner syndrome
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Dynamic DNA methylation during aging: A "prophet" of age-related outcomes
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DNA Methylation Clocks and Their Predictive Capacity for Aging Phenotypes and Healthspan
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Self-citationAn epigenetic predictor of death captures multi-modal measures of brain health
Hillary, R. F., Stevenson, A. J., Cox, S. R., McCartney, D. L., Harris, S. E., Seeboth, A., Higham, J., Sproul, D., Taylor, A. M., Redmond, P., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-019-0616-9 · Cited by 139 · see citing works
Self-citationAdversity exposure during sensitive periods predicts accelerated epigenetic aging in children
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Systematic underestimation of the epigenetic clock and age acceleration in older subjects
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“Epigenetic clocks”: Theory and applications in human biology
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Clonal hematopoiesis associated with epigenetic aging and clinical outcomes
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Self-citationMolecular Mechanisms of Vascular Health: Insights From Vascular Aging and Calcification
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Self-citationA meta-analysis of genome-wide association studies of epigenetic age acceleration
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Self-citationEstrogen and COVID-19 symptoms: Associations in women from the COVID Symptom Study
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Self-citationMitochondrial metabolism and DNA methylation: a review of the interaction between two genomes
Lopes, A. F. C. (2020) · Clinical Epigenetics · doi:10.1186/s13148-020-00976-5 · Cited by 127 · see citing works
Cellular reprogramming and epigenetic rejuvenation
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An integrative study of five biological clocks in somatic and mental health
Jansen, R., Han, L. K., Verhoeven, J. E., Aberg, K. A., van den Oord, E. C., Milaneschi, Y., & Penninx, B. W. (2021) · eLife · doi:10.7554/elife.59479 · Cited by 127 · see citing works
Dietary Intervention Modifies DNA Methylation Age Assessed by the Epigenetic Clock
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Genetic architecture of epigenetic and neuronal ageing rates in human brain regions
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Self-citation
- Authors
- Chen, B. H., Marioni, R. E., Colicino, E., Peters, M. J., Ward-Caviness, C. K., Tsai, P.-C., Roetker, N. S., Just, A. C., Demerath, E. W., Guan, W., Bressler, J., Fornage, M., Studenski, S., Vandiver, A. R., Moore, A. Z., Tanaka, T., Kiel, D. P., Liang, L., Vokonas, P., Schwartz, J., Lunetta, K. L., Murabito, J. M., Bandinelli, S., Hernandez, D. G., Melzer, D., Nalls, M., Pilling, L. C., Price, T. R., Singleton, A. B., Gieger, C., Holle, R., Kretschmer, A., Kronenberg, F., Kunze, S., Linseisen, J., Meisinger, C., Rathmann, W., Waldenberger, M., Visscher, P. M., Shah, S., Wray, N. R., McRae, A. F., Franco, O. H., Hofman, A., Uitterlinden, A. G., Absher, D., Assimes, T., Levine, M. E., Lu, A. T., Tsao, P. S., Hou, L., Manson, J. E., Carty, C. L., LaCroix, A. Z., Reiner, A. P., Spector, T. D., Feinberg, A. P., Levy, D., Baccarelli, A., van Meurs, J., Bell, J. T., Peters, A., Deary, I. J., Pankow, J. S., Ferrucci, L., & Horvath, S.
- Affiliations
- National Institutes of Health (US)
- The University of Queensland (AU)
- Columbia University (US)
- Erasmus MC (NL)
- Helmholtz Munich (DE)
- King's College London (GB)
- University of Minnesota (US)
- The University of Texas Health Science Center at Houston (US)
- Baylor College of Medicine (US)
- Johns Hopkins University (US)
- Beth Israel Deaconess Medical Center (US)
- Harvard University (US)
- Boston University (US)
- Geriatric Unit, Usl Centro Toscana Florence, Italy
- University of Exeter (GB)
- Laboratory of Neurogenetics, Intramural Research Program, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Innsbruck Medical University (AT)
- Deutsches Diabetes-Zentrum e.V. (DE)
- Institute of Epidemiology II, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA
- HudsonAlpha Institute for Biotechnology (US)
- University of California, Los Angeles (US)
- VA Palo Alto Health Care System (US)
- Northwestern University (US)
- Children's National (US)
- University of California San Diego (US)
- University of Washington (US)
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, ; USA
- Department of Internal Medicine, Erasmus University Medical Centre, Rotterdam, 3000 CA, The Netherlands
- Corresponding author
- Horvath, Steve
- ORCID
- Chen, Brian H.
- Marioni, Riccardo E.
- Colicino, Elena
- Peters, Marjolein J.
- Ward-Caviness, Cavin K.
- Tsai, Pei-Chien
- Roetker, Nicholas S.
- Just, Allan C.
- Demerath, Ellen W.
- Guan, Weihua
- Bressler, Jan
- Fornage, Myriam
- Studenski, Stephanie
- Vandiver, Amy R.
- Moore, Ann Zenobia
- Tanaka, Toshiko
- Kiel, Douglas P.
- Liang, Liming
- Vokonas, Pantel
- Schwartz, Joel
- Lunetta, Kathryn L.
- Murabito, Joanne M.
- Bandinelli, Stefania
- Hernandez, Dena G.
- Melzer, David
- Pilling, Luke C.
- Singleton, Andrew B.
- Gieger, Christian
- Holle, Rolf
- Kronenberg, Florian
- Kunze, Sonja
- Linseisen, Jakob
- Rathmann, Wolfgang
- Visscher, Peter M.
- Shah, Sonia
- Wray, Naomi R.
- McRae, Allan F.
- Franco, Oscar H.
- Uitterlinden, André G.
- Absher, Devin
- Assimes, Themistocles
- Levine, Morgan E.
- Lu, Ake T.
- Tsao, Philip S.
- Hou, Lifang
- Manson, JoAnn E.
- Carty, Cara L.
- LaCroix, Andrea Z.
- Spector, Tim D.
- Feinberg, Andrew P.
- Levy, Daniel
- Baccarelli, Andrea
- Bell, Jordana T.
- Peters, Annette
- Deary, Ian J.
- Pankow, James S.
- Ferrucci, Luigi
- Horvath, Steve
- Venue
- Aging
- Publisher
- Impact Journals, LLC
- Published
- 2016-09-28
- Volume
- 8
- Issue
- 9
- Pages
- 1844-1865
- ISSN
- 1945-4589 (ISSN-L)
- PMC
- PMC5076441
- OpenAlex
- W2421283105
- Cited by
- 1,126
- References
- 39
- Citations by year
- 2026: 82 · 2025: 107 · 2024: 132 · 2023: 103 · 2022: 141 · 2021: 153 · 2020: 117 · 2019: 114 · 2018: 97 · 2017: 74 · 2016: 4
- FWCI
- 8.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Aging (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- eScholarship (California Digital Library) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Site cant be reached (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion)
- OPUS (Augsburg University) (submittedVersion, cc-by)
- Funders
- U.S. Department of Health and Human Services (HHSN268201100002C, HHSN2682011 00003C, 5RC2HL102419, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C, HHSN 268201100001C, HHSN268201500001I, HHSN268201100046C, HHSN268201100004C, HHSN-271-2011-00004C)
- U.S. Department of Veterans Affairs
- Brigham and Women's Hospital
- Ohio State University
- Wake Forest University
- University of Pittsburgh
- Wellcome Trust (FP7/2007–2013)
- Scottish Government
- National Institute for Health and Care Research (FP7/2007–2013, NF-SI-0507-10228, NF-SI-0514-10027)
- Age UK (MR/K026992/1)
- King's College London
- European Commission (2007–2013, FP7 2007-2013, FP7/2007, 305280)
- University of Edinburgh (MR/K026992/1)
- German-Israeli Foundation for Scientific Research and Development
- University of Queensland
- ZonMw
- Bundesministerium für Bildung und Forschung
- Erasmus Medisch Centrum (014-93-015)
- Bundesministerium für Gesundheit
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (FP7 2007-2013, 911-03-012, 175.010.2005.011, 917103521)
- Centre for Cognitive Ageing and Cognitive Epidemiology (MR/K026992/1)
- National Institutes of Health (HHSN268201100012C, FP7/2007-2013, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C,HHSN268201100004C, and HHSN271201100004C, HHSN268201100008C, HHSN268201100006C, HHSN268201100004C, HHSN26820- 1100005C, HHSN268201100007C, HHSN268201100046C, HHSN271201100004C, HHSN268201100011C, HHSN268201100001C, HHSN268201100010C, HHSN268201100002C, n01hc25195-41-0-1, HHSN268201100009C, HHSN268201100003C, HHSN268201500001I, N01-HC 25195)
- Directorate for Biological Sciences
- University at Buffalo
- Medical Research Council (MR/K026992/1, MR/M013111/1)
- Biotechnology and Biological Sciences Research Council (MR/K026992/1)
- Economic and Social Research Council (ES/N000404/1)
- Helmholtz Zentrum München
- Münchner Zentrum für Gesundheitswissenschaften
- National Institute on Aging (HHSN-271-2011-00004C,, R01AG029451, N01-HC-25195, R01AG042187, U34AG051425, RF1AG036042, R01AG042511)
- National Heart, Lung, and Blood Institute (HHSN268201 100012C, HHSN268201100007I, HHSN268201100007C, HHSN2682 01100008C, HH-SN-268201100006C, HHSN268201100011C, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C,HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C, HHSN2682011-00005I, HHSN2682011-00001I, HHSN2682011-00002I, N01‐HC25195, HHSN268201100004C, HHSN268201500001I, HHSN2682011-00009I, HHSN268201100005C, HHSN268201500001C, HHSN268201100005G, HHSN268201100010C, HHSN271201100004C, HHSN2682011‐00004I, HHSN26820-1100002C, HHSN268201100011I, N01-HC-025195, 60442456, HHSN268201100046C, HHSN26820 1100009C, HHSN268201100001C, HHSN2682011-00008I, HHSN268201100003C, RC2HL102419)
- National Institute of General Medical Sciences (T32GM007309)
- National Institute of Environmental Health Sciences (R00ES023450, R01ES025225, R01ES021733, R01ES015172, P30ES023515)
- Center for Information Technology
- NHLBI Division of Intramural Research
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- DNA methylation, biological age, epigenetic clocks, time to death, mortality prediction, mortality risk
- MeSH terms
- Aging, Female, Humans, Male, Mortality, Risk Factors, Logistic Models, Survival Analysis, T-Lymphocyte Subsets, DNA Methylation, Epigenesis, Genetic, Racial Groups
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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