Bidirectional relationship between epigenetic age and stroke, dementia, and late-life depression

Cyprien A. Rivier (), Natalia Szejko, Daniela Renedo, Santiago Clocchiatti-Tuozzo, Shufan Huo, Adam Havenon, Hongyu Zhao, Thomas M. Gill, Kevin N. Sheth and Guido J. Falcone ()
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Cyprien A. Rivier: Yale School of Medicine
Natalia Szejko: Medical University of Warsaw
Daniela Renedo: Yale School of Medicine
Santiago Clocchiatti-Tuozzo: Yale School of Medicine
Shufan Huo: Yale School of Medicine
Adam Havenon: Yale School of Medicine
Hongyu Zhao: Yale School of Public Health
Thomas M. Gill: Yale School of Medicine
Kevin N. Sheth: Yale School of Medicine
Guido J. Falcone: Yale School of Medicine

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract Chronological age is an imperfect estimate of molecular aging. Epigenetic age, derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. We examine the bidirectional relationship between epigenetic age and brain health events (stroke, dementia, late-life depression) using data from 4,018 participants. Participants with a prior brain health event are 4% epigenetically older (β = 0.04, SE = 0.01), indicating these conditions are associated with accelerated aging beyond that captured by chronological age. Additionally, a one standard deviation increase in epigenetic age is associated with 70% higher odds of experiencing a brain health event in the next four years (OR = 1.70, 95% CI = 1.16–2.50), suggesting epigenetic age acceleration is not just a consequence but also a predictor of poor brain health. Mendelian Randomization analyses replicate these findings, supporting their causal nature. Our results support using epigenetic age as a biomarker to evaluate interventions aimed at preventing and promoting recovery after brain health events.

Date: 2025
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DOI: 10.1038/s41467-024-54721-0

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