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Meta-Analysis
. 2019 Apr 11;11(1):62.
doi: 10.1186/s13148-019-0656-7.

The epigenetic clock as a predictor of disease and mortality risk: a systematic review and meta-analysis

Peter D Fransquet  1   2 , Jo Wrigglesworth  1 , Robyn L Woods  1 , Michael E Ernst  3   4 , Joanne Ryan  5   6   7
Affiliations
Meta-Analysis

The epigenetic clock as a predictor of disease and mortality risk: a systematic review and meta-analysis

Peter D Fransquet et al. Clin Epigenetics. .

Abstract

Background: Ageing is one of the principal risk factors for many chronic diseases. However, there is considerable between-person variation in the rate of ageing and individual differences in their susceptibility to disease and death. Epigenetic mechanisms may play a role in human ageing, and DNA methylation age biomarkers may be good predictors of age-related diseases and mortality risk. The aims of this systematic review were to identify and synthesise the evidence for an association between peripherally measured DNA methylation age and longevity, age-related disease, and mortality risk.

Methods: A systematic search was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Using relevant search terms, MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsychINFO databases were searched to identify articles meeting the inclusion criteria. Studies were assessed for bias using Joanna Briggs Institute critical appraisal checklists. Data was extracted from studies measuring age acceleration as a predictor of age-related diseases, mortality or longevity, and the findings for similar outcomes compared. Using Review Manager 5.3 software, two meta-analyses (one per epigenetic clock) were conducted on studies measuring all-cause mortality.

Results: Twenty-three relevant articles were identified, including a total of 41,607 participants. Four studies focused on ageing and longevity, 11 on age-related disease (cancer, cardiovascular disease, and dementia), and 11 on mortality. There was some, although inconsistent, evidence for an association between increased DNA methylation age and risk of disease. Meta-analyses indicated that each 5-year increase in DNA methylation age was associated an 8 to 15% increased risk of mortality.

Conclusion: Due to the small number of studies and heterogeneity in study design and outcomes, the association between DNA methylation age and age-related disease and longevity is inconclusive. Increased epigenetic age was associated with mortality risk, but positive publication bias needs to be considered. Further research is needed to determine the extent to which DNA methylation age can be used as a clinical biomarker.

Keywords: Age-related disease; Ageing; Biological age; DNA methylation; Epigenetic clock; Longevity; Mortality; Systematic review.

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Conflict of interest statement

Ethics approval and consent to participate

Ethics approval was given within each individual study included in this review.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Prisma flow diagram
Fig. 2
Fig. 2
Forest plots for Horvath and Hannum meta-analyses. Meta-analyses used HR and standard errors collected from seven of the nine studies measuring associations between age acceleration for a AAHa and b AAH, and all-cause mortality. HR and 95% CI’s were calculated independently via a univariate Cox regression model and combined to provide a total value of risk. ARIC, Atherosclerosis Risk in Communities Studies; BLSA, Baltimore Longitudinal Study of Ageing; InCHIANTI, Invecchiare in Chianti, ageing in the Chianti area; KORA, Cooperative Health Research in the Augsburg Region; Rotterdam: The Rotterdam Study; WHI, Women’s Health Initiative; FHS, Framingham Heart Study; LBC1921, Lothian Birth Cohort 1921; LBC1936 Lothian Birth Cohort 1936; LSADT, NAS, US Department of Veterans Affairs’ Normative Ageing Study
Fig. 3
Fig. 3
Funnel plots for Horvath and Hannum meta-analyses
See this image and copyright information in PMC

References

    1. Ho JY, Hendi AS. Recent trends in life expectancy across high income countries: retrospective observational study. BMJ (Clinical research ed). 2018;362:k2562. - PMC - PubMed
    1. Kontis V, Bennett JE, Mathers CD, Li G, Foreman K, Ezzati M. Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. Lancet (London, England) 2017;389(10076):1323–1335. doi: 10.1016/S0140-6736(16)32381-9. - DOI - PMC - PubMed
    1. Stambler I, Jin K, Lederman S, Barzilai N, Olshansky SJ, Omokaro E, Barratt J, Anisimov VN, Rattan S, Yang S, et al. Aging health and R&D for healthy longevity must be included into the WHO work program. Aging Dis. 2018;9(2):331–333. doi: 10.14336/AD.2017.1120. - DOI - PMC - PubMed
    1. Lopez-Otin C, Blasco MA, Partridge L, Serrano M, Kroemer G. The hallmarks of aging. Cell. 2013;153(6):1194–1217. doi: 10.1016/j.cell.2013.05.039. - DOI - PMC - PubMed
    1. Fraga MF, Ballestar E, Paz MF, Ropero S, Setien F, Ballestar ML, Heine-Suner D, Cigudosa JC, Urioste M, Benitez J, et al. Epigenetic differences arise during the lifetime of monozygotic twins. Proc Natl Acad Sci U S A. 2005;102(30):10604–10609. doi: 10.1073/pnas.0500398102. - DOI - PMC - PubMed

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