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

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.

Fig. 1. Overview of study design and main results.

1^st Stage: We evaluate the association between a history of brain health events (stroke, dementia or late-life depression) and epigenetic age acceleration using a cross-sectional study design. Epigenetic age is derived from DNA methylation data collected from venous blood in 2016. 2^nd Stage: We evaluate the association between accelerated epigenetic age and the risk of subsequent brain health events using a prospective study design. We leverage Mendelian Randomization analyses to assess the causality of the associations described in steps 1&2 using genetic variants as instruments. MR = Mendelian Randomization. Created in BioRender. Falcone, G. (2024) BioRender.com/c48z976.

Fig. 2. Flowchart of Health and Retirement Study participants inclusion.

The effects of brain health events on epigenetic age (Stage 1) are studied in all participants with DNAm data. The effects of epigenetic age on subsequent brain health events (Stage 2) are studied in participants with DNAm and follow-up data, excluding those with a history of prior events. Genetic associations for epigenetic age are conducted in participants with both genetic and DNAm data. Genetic associations for brain health events are conducted in all participants with genetic data.

Fig. 3. Associations between epigenetic age and brain health events (stroke, dementia, late-life depression).

A. Cross-sectional analysis: percentage of change in epigenetic ages following a brain health event after adjusting for chronological age, sex, race and ethnicity, hypertension, diabetes, smoking, BMI, history of heart attack, coronary artery disease, angina, or congestive heart failure. N = 4018. Data are presented as linear regression coefficients and 95% confidence intervals. Clocks displayed in red belong to the second generation of epigenetic clocks. B Longitudinal analysis: Odds Ratios of brain health events per one standard deviation increase in epigenetic age adjusting for chronological age, sex, and race and ethnicity. The second-generation epigenetic clocks are highlighted in red. N = 2,967. Data are presented as odds ratios and 95% confidence intervals. Clocks displayed in red belong to the second generation of epigenetic clocks. Source data are provided as a Source Data file.

Fig. 4. Flowchart of Stage 1 genetic analyses.

Summary statistics from genome-wide association studies (GWAS) of stroke, Alzheimer’s disease, and depression were clumped to identify significant genetic variants, which were then pooled. The pooled variants underwent further clumping to ensure their independence, with palindromic variants excluded. The associations between these genetic instruments and brain health outcomes, as well as epigenetic age, were analyzed in HRS participants. Finally, Mendelian Randomization analyses were performed to estimate the causal effect of brain health events on epigenetic age.

Fig. 5. Flowchart of Stage 2 genetic analyses.

Summary statistics from genome-wide association studies (GWAS) of several epigenetic clocks were clumped to identify significant genetic variants, which were then pooled. The pooled variants underwent further clumping to ensure their independence, with palindromic variants excluded. The associations between these genetic instruments and epigenetic age, as well as brain health outcomes were analyzed in HRS participants. Finally, Mendelian Randomization analyses were performed to estimate the causal effect of epigenetic age acceleration on the risk of brain health events.