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Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging
Adam Li, Zane Koch, Trey Ideker
Journal of Internal Medicine · 2022 · ▲ 112 citations
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(definition) predictions to telomere(definition) attrition, cellular senescence(definition))." style="text-decoration:underline dotted; text-underline-offset:2px; cursor:help;">hallmarks of aging(definition); 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.
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- 10.1111/joim.13533
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- 2026-07-22 MST
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APA
Li, A., Koch, Z., & Ideker, T. (2022). Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging. <em>Journal of Internal Medicine</em>. https://doi.org/10.1111/joim.13533
Vancouver
Li A, Koch Z, Ideker T. Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging. Journal of Internal Medicine. 2022. doi:10.1111/joim.13533.
BibTeX
@article{adam2022Epigen,
title = {Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging},
author = {Adam Li and Zane Koch and Trey Ideker},
journal = {Journal of Internal Medicine},
year = {2022},
doi = {10.1111/joim.13533},
}
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