Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging
- PMID: 35726002
- DOI: 10.1111/joim.13533
Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging
Abstract
Numerous studies have shown that epigenetic age-an individual's degree of aging based on patterns of DNA methylation-can be computed and is associated with an array of factors including diet, lifestyle, genetics, and disease. One can expect that still further associations will emerge with additional aging research, but to what end? Prediction of age was an important first step, but-in our view-the focus must shift from chasing increasingly accurate age computations to understanding the links between the epigenome and the mechanisms and physiological changes of aging. Here, we outline emerging areas of epigenetic aging research that prioritize biological understanding and clinical application. First, we survey recent progress in epigenetic clocks, which are beginning to predict not only chronological age but aging outcomes such as all-cause mortality and onset of disease, or which integrate aging signals across multiple biological processes. Second, we discuss research that exemplifies how investigation of the epigenome is building a mechanistic theory of aging and informing clinical practice. Such examples include identifying methylation sites and the genes most strongly predictive of aging-a subset of which have shown strong potential as biomarkers of neurodegenerative disease and cancer; relating epigenetic clock predictions to hallmarks of aging; and using longitudinal studies of DNA methylation to characterize human disease, resulting in the discovery of epigenetic indications of type 1 diabetes and the propensity for psychotic experiences.
Keywords: CpG; aging; epigenetics; longevity; methylation.
© 2022 The Association for the Publication of the Journal of Internal Medicine.
References
-
- Jabbari K, Bernardi G. Cytosine methylation and CpG, TpG (CpA) and TpA frequencies. Gene. 2004;333:143-9.
-
- Mugal CF, Ellegren H. Substitution rate variation at human CpG sites correlates with non-CpG divergence, methylation level and GC content. Genome Biol. 2011;12:R58.
-
- Ehrlich M, Gama-Sosa MA, Huang LH, Midgett RM, Kuo KC, Mccune RA, et al. Amount and distribution of 5-methylcytosine in human DNA from different types of tissues of cells. Nucleic Acids Res. 1982;10:2709-21.
-
- Stadler MB, Murr R, Burger L, Ivanek R, Lienert F, Schöler A, et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature. 2011;480:490-5.
-
- Deaton AM, Bird A. CpG islands and the regulation of transcription. Genes Dev. 2011;25:1010-22.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical