Pan-Epigenetic Age Prediction in Mammals.

Zane Koch, Adam Li, Trey Ideker

Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, California, USA.Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, California, USA. · pubmed

Paper

Abstract

Epigenetic remodeling is a hallmark of aging, yet which epigenetic layers are most affected during aging-and the extent to which they are interrelated-is not well understood. Here, we perform a comprehensive analysis of epigenetic aging encompassing 6 histone marks and DNA methylation measured across 12 tissues from > 1000 humans and mice. We identify a synchronized pattern of age-related changes across these epigenetic layers, with all changes converging upon a common set of genes. Notably, an epigenetic clock based on these genes can accurately predict age using data from any layer (Spearman ρ: 0.70 in humans, 0.81 in mice). Applying this "pan-epigenetic" clock, we observe that histone modification and DNA methylation profiles agree in the prediction of which individuals are aging more rapidly or slowly. These results demonstrate that epigenetic modifications are subject to coordinated remodeling over the lifespan, offering a unified view of epigenetic aging.

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Research summary

The paper claims that a pan-epigenetic clock can accurately predict age across different epigenetic layers in mammals. This research is relevant as it addresses the underlying mechanisms of aging through epigenetic changes, contributing to the understanding of aging processes and potential interventions.

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