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


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.

SUBMITTER: Chen BH 

PROVIDER: S-EPMC5076441 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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

Chen Brian H BH   Marioni Riccardo E RE   Colicino Elena E   Peters Marjolein J MJ   Ward-Caviness Cavin K CK   Tsai Pei-Chien PC   Roetker Nicholas S NS   Just Allan C AC   Demerath Ellen W EW   Guan Weihua W   Bressler Jan J   Fornage Myriam M   Studenski Stephanie S   Vandiver Amy R AR   Moore Ann Zenobia AZ   Tanaka Toshiko T   Kiel Douglas P DP   Liang Liming L   Vokonas Pantel P   Schwartz Joel J   Lunetta Kathryn L KL   Murabito Joanne M JM   Bandinelli Stefania S   Hernandez Dena G DG   Melzer David D   Nalls Michael M   Pilling Luke C LC   Price Timothy R TR   Singleton Andrew B AB   Gieger Christian C   Holle Rolf R   Kretschmer Anja A   Kronenberg Florian F   Kunze Sonja S   Linseisen Jakob J   Meisinger Christine C   Rathmann Wolfgang W   Waldenberger Melanie M   Visscher Peter M PM   Shah Sonia S   Wray Naomi R NR   McRae Allan F AF   Franco Oscar H OH   Hofman Albert A   Uitterlinden André G AG   Absher Devin D   Assimes Themistocles T   Levine Morgan E ME   Lu Ake T AT   Tsao Philip S PS   Hou Lifang L   Manson JoAnn E JE   Carty Cara L CL   LaCroix Andrea Z AZ   Reiner Alexander P AP   Spector Tim D TD   Feinberg Andrew P AP   Levy Daniel D   Baccarelli Andrea A   van Meurs Joyce J   Bell Jordana T JT   Peters Annette A   Deary Ian J IJ   Pankow James S JS   Ferrucci Luigi L   Horvath Steve S  

Aging 20160901 9


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  ...[more]

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