Exposome-wide patterns predict brain health in aging
Clinical Snapshot
PICO Framework
| P — Population | UK Biobank participants (middle-aged and older adults) |
| I — Intervention | Exposome variables (261 factors across biomedical, environmental, lifestyle, socio-affective, and early life domains) |
| C — Comparator | Not applicable (predictive modelling study) |
| O — Outcomes | Brain Age Gap (BAG) as indicator of grey matter health |
Bottom Line
This large UK Biobank study demonstrates that comprehensive exposome factors can predict brain health in ageing, with cardiovascular health, bone health, alcohol, smoking, nutrition, and diabetes showing the strongest associations with Brain Age Gap. The findings support a holistic approach to brain health promotion, emphasising early prevention of cardiovascular and metabolic conditions. While the cross-sectional design limits causal inference, the results align with established knowledge about vascular contributions to cognitive health. For Australian clinicians, this reinforces the importance of integrated preventive care addressing cardiovascular risk factors, lifestyle modifications, and metabolic health as key strategies for promoting lifelong brain health. The study's machine learning approach, while innovative, requires validation in diverse populations and translation into practical clinical tools.
Key Findings
P Value: Not reported
Effect Size: Not specified in abstract
Primary Outcome: Brain Age Gap prediction from exposome variables
Nnt Or Sensitivity: Prediction accuracy not specified
Confidence Interval: Not reported
Clinical Application
Moderate - requires comprehensive health assessment but uses readily available clinical and lifestyle data Highly relevant to Australian preventive health initiatives, aligns with RACGP guidelines on cardiovascular risk assessment and healthy ageing strategies Middle-aged and older adults in primary care and preventive medicine settings
Abstract
Promoting brain health is vital for well-being and reducing healthcare burdens. Brain health as measured with the Brain Age Gap (BAG) - the difference between chronological and predicted brain age- relates to many factors. However, a holistic view, integrating the range of factors an individual brain is exposed to, is missing for understanding how the exposome shapes brain health. After computing BAG as an indicator of grey matter (GM) health, we predicted it using machine learning based on 261 exposome variables (spanning biomedical, environmental, lifestyle, socio-affective, and early life domains) in UK Biobank participants. Exposome data can predict GM health with factors pertaining to cardiovascular and bone health, along with alcohol and smoking, nutrition and diabetes showing greater contribution to the prediction. In such domains, life period and duration of exposure appeared crucial. These findings call for early prevention in cardiovascular and metabolic health to promote life-long brain health.
References
- 1.Mahdipour, M., Maleki Balajoo, S., Raimondo, F., Wu, J., Nicolaisen-Sobesky, E., More, S., Hoffstaedter, F., Schwender, H., Tahmasian, M., Eickhoff, S. B., & Genon, S. (2026). Exposome-wide patterns predict brain health in aging. Nature Communications. https://doi.org/10.1038/s42256-019-0138-9
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