Bidirectional relationship between epigenetic age and brain health events.
Cyprien A RivierNatalia SzejkoDaniela RenedoSantiago Clocchiatti-TuozzoShufan HuoAdam de HavenonHongyu ZhaoThomas M GillKevin Navin ShethGuido FalconePublished in: Research square (2024)
Chronological age offers an imperfect estimate of the molecular changes that occur with aging. Epigenetic age, which is derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. This study examines the bidirectional relationship between epigenetic age and the occurrence of brain health events (stroke, dementia, and late-life depression). Using data from the Health and Retirement Study, we analyzed blood samples from over 4,000 participants to determine how epigenetic age relates to past and future brain health events. Study participants with a prior brain health event prior to blood collection were 4% epigenetically older (beta 0.04, SE 0.01), suggesting that these conditions are associated with faster aging than that captured by chronological age. Furthermore, a one standard deviation increase in epigenetic age was associated with 70% higher odds of experiencing a brain health event in the next four years after blood collection (OR 1.70, 95%CI 1.16-2.50), indicating that epigenetic age is not just a consequence but also a predictor of poor brain health. Both results were replicated through Mendelian Randomization analyses, supporting their causal nature. Our findings support the utilization of epigenetic age as a useful biomarker to evaluate the role of interventions aimed at preventing and promoting recovery after a brain health event.
Keyphrases
- dna methylation
- public health
- healthcare
- mental health
- gene expression
- resting state
- white matter
- health information
- health promotion
- functional connectivity
- genome wide
- physical activity
- human health
- risk assessment
- electronic health record
- climate change
- atrial fibrillation
- depressive symptoms
- artificial intelligence
- deep learning
- single molecule
- long noncoding rna