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bioRxiv · 10.64898/2026.07.31.741967

Global Structural Brain-Age in Adolescence: Application of an Established Method to Short-Interval, Longitudinal Data

Boyes, A.·Han, L. K.·Crethar, M.·Silk, T.·Vijayakumar, N.·Hermens, D. F.
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Abstract

Brain-age estimates from grey matter structure provide a promising tool to examine the neurobiology of mental health. However, whether existing models generalise to longitudinal adolescent data remains unclear. The CentileBrain Global-BrainAGE Lifespan Model, was applied to N=138 participants (74 females, 64 males) from the Longitudinal Adolescent Brain Study. Participants completed 2-14 MRI scans between the ages of 12-17 years (752 datapoints). Model fit, prediction accuracy and longitudinal consistency were examined. Results showed moderate-to-good longitudinal consistency and reliability, consistent with high-performing cross-sectional age-to-brain-age correlations in youth cohorts. However, the model systematically overestimated brain-age changes relative to chronological changes, and prediction accuracy was unstable, with the mean absolute error increasing with age. Despite sex-specific brain-age calculations, on average, females showed older brain-ages compared with males. Further, younger adolescents were underpredicted, while older adolescents were overpredicted, indicating that standard model adjustments and assumptions may not be applicable.

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Boyes, A., Han, L. K., Crethar, M., Silk, T., Vijayakumar, N., Hermens, D. F.. 2026-08-05. Global Structural Brain-Age in Adolescence: Application of an Established Method to Short-Interval, Longitudinal Data. https://doi.org/10.64898/2026.07.31.741967

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