TY - JOUR
T1 - Associations between epigenetic age and brain age in young people
AU - Sanders, Faye
AU - Baltramonaityte, Vilte
AU - Donohoe, Gary
AU - Davies, Neil M.
AU - Dunn, Erin C.
AU - Cecil, Charlotte A.M.
AU - Walton, Esther
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/7/22
Y1 - 2025/7/22
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105011349872
U2 - 10.1038/s41598-025-11350-x
DO - 10.1038/s41598-025-11350-x
M3 - Article
C2 - 40695906
AN - SCOPUS:105011349872
SN - 2045-2322
VL - 15
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 26609
ER -
