Associations between epigenetic age and brain age in young people

TL;DR

This study explores how biological age, measured through epigenetic and brain imaging data, relates in young people and finds limited connections between these age measures.

Contribution

The study is one of the first to investigate the relationship between epigenetic and brain age measures in young individuals.

Findings

Little evidence was found for an association between brain age and epigenetic age measures.

Smoking and BMI were linked to specific epigenetic age measures but not brain age.

Depressive symptoms and cognitive ability were unrelated to biological age measures.

Abstract

Recent research suggests biological age, based on epigenetic or neuroimaging measures, may predict health traits in adulthood more accurately than chronological age. However, it is unclear if these findings apply earlier in life. We aimed to characterise the performance and interdependence between measures of biological age in young people, leveraging a longitudinal subsample from the population-based ALSPAC cohort (n = 386). We derived four epigenetic age measures from blood samples in young people (17–19 years) and a measure of brain age derived from structural neuroimaging data (18–24 years). We examined associations between measures of biological age, and relationships with five measures of physical, cognitive and mental health (8–18 years). We found little evidence for an association between brain age and epigenetic age measures, after accounting for age, sex, cell type, array and study (beta range: -0.59 to 0.59, all p > 0.05). Increased smokingDNAm was associated with advanced epigenetic age (PACE and Zhang clock), and increased BMIsds with advanced EpiAgeHorvath(diff) (all p < 0.05), but not brain age. Depressive symptoms and cognitive ability were unrelated to all measures of biological age. Our findings highlight the variability of epigenetic- and brain-based age measures in young people, emphasizing the importance of tracking ageing in younger populations.

The online version contains supplementary material available at 10.1038/s41598-025-11350-x.

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