Lifestyle and BrainAGE in adult depression.
8 affiliations
- 1Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
- 2Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada.
- 3Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- 4Centre for Addiction and Mental Health, Toronto, ON, Canada.
- 5Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- 6Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada. [email protected].
- 7Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada. [email protected].
- 8Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. [email protected].
Abstract
This study investigates how heterogeneity in lifestyle and physical fitness shapes patterns of brain ageing in depression. The study sample included medically healthy adults from the UK Biobank (44-82 years) with a history of depression (n = 896) and non-psychiatric controls (n = 36,206). Heterogeneity through Discriminative Analysis (HYDRA) was used to derive data-driven subgroups within the depression sample based on 224 behavioural and physical health features. Global and voxel-based brain-age-gap-estimates (brainAGE) computed from structural neuroimaging data were used for personalized assessment of brain ageing. Four depression clusters were identified: the "balanced-active" cluster (n = 253) characterized by an active lifestyle and balanced diet; the "low metabolic risk-active" cluster (n = 178) characterized by a health-conscious dietary and exercise lifestyle; the "high metabolic risk-sedentary" cluster (n = 315) who had higher body mass, poor diet, and sedentary behaviour; and the "frailty-moderately active" cluster (n = 150) who had a varied diet but coupled with physical frailty. Mood symptoms were lowest in the "balanced-active" cluster and highest in the "high metabolic risk-sedentary" cluster. While depression overall was associated with minimally accelerated global and local brain ageing in fronto-limbic regions, the "high metabolic risk-sedentary" cluster showed additional, regionally specific acceleration in prefrontal, parahippocampal, and thalamic areas. This work underscores the importance of lifestyle and fitness heterogeneity when examining associations between depression and neurobiological ageing and supports lifestyle-informed stratification as a pathway toward more targeted intervention strategies.
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BibTeX
@article{sanford2026lifestyle,
title = {{Lifestyle and BrainAGE in adult depression.}},
author = {Nicole Sanford and Yuetong Yu and Ruiyang Ge and Shalaila S Haas and Liisa A M Galea and Sophia Frangou},
journal = {Translational psychiatry},
year = {2026},
month = jul,
doi = {10.1038/s41398-026-04297-8},
url = {https://europepmc.org/article/MED/42907451},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Lifestyle and BrainAGE in adult depression.
AU - Nicole Sanford
AU - Yuetong Yu
AU - Ruiyang Ge
AU - Shalaila S Haas
AU - Liisa A M Galea
AU - Sophia Frangou
PY - 2026
DA - 2026/07/01
JO - Translational psychiatry
DO - 10.1038/s41398-026-04297-8
UR - https://europepmc.org/article/MED/42907451
AB - This study investigates how heterogeneity in lifestyle and physical fitness shapes patterns of brain ageing in depression. The study sample included medically healthy adults from the UK Biobank (44-82 years) with a history of depression (n = 896) and non-psychiatric controls (n = 36,206). Heterogeneity through Discriminative Analysis (HYDRA) was used to derive data-driven subgroups within the depression sample based on 224 behavioural and physical health features. Global and voxel-based brain-age-gap-estimates (brainAGE) computed from structural neuroimaging data were used for personalized assessment of brain ageing. Four depression clusters were identified: the "balanced-active" cluster (n = 253) characterized by an active lifestyle and balanced diet; the "low metabolic risk-active" cluster (n = 178) characterized by a health-conscious dietary and exercise lifestyle; the "high metabolic risk-sedentary" cluster (n = 315) who had higher body mass, poor diet, and sedentary behaviour; and the "frailty-moderately active" cluster (n = 150) who had a varied diet but coupled with physical frailty. Mood symptoms were lowest in the "balanced-active" cluster and highest in the "high metabolic risk-sedentary" cluster. While depression overall was associated with minimally accelerated global and local brain ageing in fronto-limbic regions, the "high metabolic risk-sedentary" cluster showed additional, regionally specific acceleration in prefrontal, parahippocampal, and thalamic areas. This work underscores the importance of lifestyle and fitness heterogeneity when examining associations between depression and neurobiological ageing and supports lifestyle-informed stratification as a pathway toward more targeted intervention strategies.
SN - 2158-3188
ER -