DNA methylation-based measures of biological age: meta-analysis predicting time to death

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, Nalls, Michael, Pilling, Luke C., Price, Timothy R., Singleton, Andrew B., Gieger, Christian, Holle, Rolf, Kretschmer, Anja, Kronenberg, Florian, Kunze, Sonja, Linseisen, Jakob, Meisinger, Christine, Rathmann, Wolfgang, Waldenberger, Melanie, Visscher, Peter M., Shah, Sonia, Wray, Naomi R., McRae, Allan F., Franco, Oscar H., Hofman, Albert, Uitterlinden, Andre 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., Reiner, Alexander P., Spector, Tim D., Feinberg, Andrew P., Levy, Daniel, Baccarelli, Andrea, van Meurs, Joyce, Bell, Jordana T., Peters, Annette, Deary, Ian J., Pankow, James S., Ferrucci, Luigi and Horvath, Steve (2016) DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging, 8 9: 1844-1865. doi:10.18632/aging.101020

Author 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
Nalls, Michael
Pilling, Luke C.
Price, Timothy R.
Singleton, Andrew B.
Gieger, Christian
Holle, Rolf
Kretschmer, Anja
Kronenberg, Florian
Kunze, Sonja
Linseisen, Jakob
Meisinger, Christine
Rathmann, Wolfgang
Waldenberger, Melanie
Visscher, Peter M.
Shah, Sonia
Wray, Naomi R.
McRae, Allan F.
Franco, Oscar H.
Hofman, Albert
Uitterlinden, Andre 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.
Reiner, Alexander P.
Spector, Tim D.
Feinberg, Andrew P.
Levy, Daniel
Baccarelli, Andrea
van Meurs, Joyce
Bell, Jordana T.
Peters, Annette
Deary, Ian J.
Pankow, James S.
Ferrucci, Luigi
Horvath, Steve
Title DNA methylation-based measures of biological age: meta-analysis predicting time to death
Journal name Aging   Check publisher's open access policy
ISSN 1945-4589
Publication date 2016-01-01
Sub-type Article (original research)
DOI 10.18632/aging.101020
Open Access Status Not yet assessed
Volume 8
Issue 9
Start page 1844
End page 1865
Total pages 22
Place of publication Albany, NY, United States
Publisher Impact Journals LLC
Language eng
Formatted 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 ≤ 8.2 x 10-9), independent of chronological age, even after adjusting for additional risk factors (p < 5.4 x 10-4), 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≤ 7.5 x 10-43). 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.
Keyword All-cause mortality
DNA methylation
Epigenetic clock
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Brain Institute Publications
UQ Diamantina Institute Publications
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Citation counts: TR Web of Science Citation Count  Cited 29 times in Thomson Reuters Web of Science Article | Citations
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