Chapter title |
DNA Methylation as a Biomarker of Aging in Epidemiologic Studies
|
---|---|
Chapter number | 12 |
Book title |
Cancer Epigenetics for Precision Medicine
|
Published in |
Methods in molecular biology, September 2018
|
DOI | 10.1007/978-1-4939-8751-1_12 |
Pubmed ID | |
Book ISBNs |
978-1-4939-8750-4, 978-1-4939-8751-1
|
Authors |
Unhee Lim, Min-Ae Song |
Abstract |
Cancer is largely an aging disease. Accelerated biological aging may be the strongest predictor of cancer and other chronic disease risks. In the absence of reliable and quantifiable biomarkers of aging to date, it has long been observed that tumorigenesis shares distinct epigenetic alterations with the aging process. Recently, epigenetic age estimates have been developed based on the availability of genome-wide DNA methylation profiles, by applying in the prediction formula the methylation level at a subset of highly predictive methylation sites, called epigenetic clock. These DNA methylation age estimates have produced remarkably strong correlations with chronological age, with a small deviation and high reproducibility across different age groups and study populations. Moreover, an increasing number of epidemiologic studies have demonstrated an independent association of DNA methylation age or the extent of acceleration with mortality and various aging-related conditions, even after accounting for differences in chronological age and other risk factors. Although epigenetic profiles are known to be tissue-specific, both target tissue- and multiple tissue-derived estimates appear to perform well to capture what is thought to be the cumulative epigenetic drift that represents a multifactorial degenerative process across tissues and organisms. Further refinement of the epigenetic age estimates is anticipated over time to accommodate a better technological coverage of the methylome and a better understanding of the biology underlying predictive regions. Epidemiologic principles will remain critical for the evaluation of research findings involving, for example, different study populations, design, follow-up time, and quality of covariate data. Overall, the epigenetic age estimates are an exciting development with useful implications for biomedical research of healthy aging and disease prevention and control. |
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