Dataset Information

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]

PMID: 27690265

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Project description:Study questionAre reproductive characteristics associated with genome-wide DNA methylation and epigenetic age?Summary answerOur data suggest that increasing parity is associated with differences in blood DNA methylation and small increases in epigenetic age.What is known alreadyA study of 397 young Filipino women (ages 20-22) observed increasing epigenetic age with an increasing number of pregnancies.Study design, size, durationWe used data from 2356 non-Hispanic white women (ages 35-74) enrolled in the Sister Study cohort.Participants/materials, setting, methodsData on reproductive history were ascertained via questionnaire. Of the 2356 women, 1897 (81%) reported at least one live birth. Among parous women, 487 (26%) women reported ever experiencing a pregnancy complication. Three epigenetic clocks (i.e. Hannum, Horvath and Levine) and genome-wide methylation were measured in DNA from whole blood using Illumina's HumanMethylation450 BeadChip. We estimated association β-values and 95% CIs using linear regression.Main results and the role of chanceAll three epigenetic clocks showed weak associations between number of births and epigenetic age (per live birth; Hannum: β = 0.16, 95% CI = 0.02, 0.29, P = 0.03; Horvath: β = 0.12, 95% CI = -0.04, 0.27, P = 0.14; Levine: β = 0.27, 95% CI = 0.08, 0.45, P = 0.01); however, additional adjustment for current BMI attenuated the associations. Among parous women, a history of abnormal glucose tolerance during pregnancy was associated with increased epigenetic age by the Hannum clock (β = 0.96; 95% CI = 0.10, 1.81; P = 0.03) and Levine clocks (β = 1.69; 95% CI = 0.54, 2.84; P < 0.01). In epigenome-wide analysis, increasing parity was associated with methylation differences at 17 CpG sites (Bonferroni corrected P≤ 1.0 × 10-7).Limitations, reasons for cautionWe relied on retrospective recall to ascertain reproductive history and pregnancy complications.Wider implications of the findingsOur findings suggest that parity is associated with small increases in epigenetic age and with DNA methylation at multiple sites in the genome.Study funding/competing interest(s)This research was supported by the Intramural Research program of the NIH, National Institute of Environmental Health Sciences (Z01-ES049033, Z01-ES049032 and Z01-ES044055). None of the authors have a conflict of interest.Trial registration numberNot applicable.

Project description:BackgroundIndividuals who are socioeconomically disadvantaged are at increased risk for aging-related diseases and perform less well on tests of cognitive function. The weathering hypothesis proposes that these disparities in physical and cognitive health arise from an acceleration of biological processes of aging. Theories of how life adversity is biologically embedded identify epigenetic alterations, including DNA methylation (DNAm), as a mechanistic interface between the environment and health. Consistent with the weathering hypothesis and theories of biological embedding, recently developed DNAm algorithms have revealed profiles reflective of more advanced aging and lower cognitive function among socioeconomically-at-risk groups. These DNAm algorithms were developed using blood-DNA, but social and behavioral science research commonly collect saliva or cheek-swab DNA. This discrepancy is a potential barrier to research to elucidate mechanisms through which socioeconomic disadvantage affects aging and cognition. We therefore tested if social gradients observed in blood DNAm measures could be reproduced using buccal-cell DNA obtained from cheek swabs.ResultsWe analyzed three DNAm measures of biological aging and one DNAm measure of cognitive performance, all of which showed socioeconomic gradients in previous studies: the PhenoAge and GrimAge DNAm clocks, DunedinPACE, and Epigenetic-g. We first computed blood-buccal cross-tissue correlations in n = 21 adults (GEO111165). Cross-tissue correlations were low-to-moderate (r = .25 to r = .48). We next conducted analyses of socioeconomic gradients using buccal DNAm data from SOEP-G (n = 1128, 57% female; age mean = 42 yrs, SD = 21.56, range 0-72). Associations of socioeconomic status with DNAm measures of aging were in the expected direction, but were smaller as compared to reports from blood DNAm datasets (r = - .08 to r = - .13).ConclusionsOur findings are consistent with the hypothesis that socioeconomic disadvantage is associated with DNAm indicators of worse physical health. However, relatively low cross-tissue correlations and attenuated effect sizes for socioeconomic gradients in buccal DNAm compared with reports from analysis of blood DNAm suggest that in order to take full advantage of buccal DNA samples, DNAm algorithms customized to buccal DNAm are needed.

Dataset Information

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

Publications

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

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