DNA methylation-based measures of biological age: meta-analysis predicting time to death
Brian H. Chen,Riccardo E. Marioni,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,Myriam Fornage,Stephanie A. Studenski,Amy R. Vandiver,Ann Zenobia Moore,Toshiko Tanaka,Douglas P. Kiel,Liming Liang,Pantel S. Vokonas,Joel Schwartz,Kathryn L. Lunetta,Kathryn L. Lunetta,Joanne M. Murabito,Joanne M. Murabito,Stefania Bandinelli,Dena G. Hernandez,David Melzer,Mike A. Nalls,Luke C. Pilling,Timothy Ryan 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,Peter M. Visscher,Sonia Shah,Naomi R. Wray,Allan F. McRae,Oscar H. Franco,Albert Hofman,Albert Hofman,André G. Uitterlinden,Devin Absher,Themistocles L. Assimes,Morgan E. Levine,Ake T. Lu,Philip S. Tsao,Philip S. Tsao,Lifang Hou,JoAnn E. Manson,Cara L. Carty,Andrea Z. LaCroix,Alexander P. Reiner,Alexander P. Reiner,Tim D. Spector,Andrew P. Feinberg,Daniel Levy,Andrea A. Baccarelli,Andrea A. Baccarelli,Joyce B. J. van Meurs,Jordana T. Bell,Annette Peters,Ian J. Deary,James S. Pankow,Luigi Ferrucci,Steve Horvath +74 more
- 28 Sep 2016
- Vol. 8, Iss: 9, pp 1844-1865
TL;DR: Evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors is strengthened and estimates that incorporate information on blood cell counts lead to highly significant associations with all- Cause mortality are demonstrated.
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Abstract: Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10-9), independent of chronological age, even after adjusting for additional risk factors (p<5.4x10-4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10-43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.
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Citations
An epigenetic biomarker of aging for lifespan and healthspan
Morgan E. Levine,Ake T. Lu,Austin Quach,Brian H. Chen,Themistocles L. Assimes,Stefania Bandinelli,Lifang Hou,Andrea A. Baccarelli,James D. Stewart,Yun Li,Eric A. Whitsel,James G. Wilson,Alex P. Reiner,Abraham Aviv,Kurt Lohman,Yongmei Liu,Luigi Ferrucci,Steve Horvath +17 more
- 01 Apr 2018
TL;DR: A new epigenetic biomarker of aging, DNAm PhenoAge, is developed that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease.
DNA methylation-based biomarkers and the epigenetic clock theory of ageing
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TL;DR: Biomarkers of ageing based on DNA methylation data enable accurate age estimates for any tissue across the entire life course and link developmental and maintenance processes to biological ageing, giving rise to a unified theory of life course.
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TL;DR: Using large scale validation data from thousands of individuals, it is demonstrated that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death, and a novel measure of epigenetic age acceleration, AgeAccelGrim.
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TL;DR: Key challenges to understand clock mechanisms and biomarker utility are discussed, including dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models.
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