Year: 2026
Type: article
Study design: Observational Study
Abstract: Despite advances in brain biomarkers using neural networks, the effects of body mass on brain structure have been neglected, particularly in connection with noncommunicable diseases. Here, we isolated brain biomarkers of body mass index (BMI) and evaluated their association with disease states. We applied deep learning on T1-weighted MRI scans to predict BMI from six independent cohorts and achieved strong within-cohort and reduced external performance. In a longitudinal follow-up subset, the model successfully tracked BMI changes over 2.3 years, with stronger sensitivity to BMI increases, and for obese participants. Next, we used the learned brain biomarkers to infer lifestyle factors and diagnoses related to cardiometabolic and pulmonary conditions. Strikingly, brain-based models showed superior discriminative power compared to BMI itself for detecting disorders without a primary neurological etiology. Inspection of learned patterns revealed that predictions were driven by white matter signals in the cerebellum, corpus callosum and brainstem, which on their own detected disorders as well as the full model. The existence of dynamic brain BMI signatures, and their detection of systemic disease consistently above BMI, suggest the possibility of shared mechanisms linking metabolic state and brain structure.
Source: npj Digital Medicine
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,090
Funders: U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Sanofi, Massachusetts General Hospital, Biogen, University of Southern California, Teva Pharmaceutical Industries, Celgene, F. Hoffmann-La Roche, Meso Scale Diagnostics, University of Minnesota, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Neurocrine Biosciences, Verily Life Sciences, Voyager Therapeutics, Eisai, Centre d'Imagerie BioMédicale, Servier, H. Lundbeck A/S, Sun Pharma, IXICO, National Institutes of Health, Genentech, Allergan, Avid Radiopharmaceuticals, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Canadian Institutes of Health Research, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Dental and Craniofacial Research
Awards: G100845555, G1012222616, G1298807586, G1554142629, G1593117279, G1650819308, G1880935189, G2100670906, G2152643862, G2189010064, G2340207221, G2423387114, G2471646051, G2522063444, G2835601961, G29951154, G3131374986, G3216574877, G3512028809, G3553156159, G3710456697, G3752451908, G3870774570, G3908963977, G3966393351, G43180419, G4501223628, G4778110799, G4800177743, G5207404921, G5209990037, G528601746, G5365730499, G5654639750, G5740349702, G613619302, G6173816828, G6210868510, G6371410416, G6412110892, G6447063303, G6719828067, G6792506723, G6899163935, G6948409098, G72415811, G7298697282, G764699806, G7799614282, G781725486, G8228018387, G8281378126, G839208290, G8852128998, G8895907669, G8897063270, G8957659042, G9000039018, G9000122335, G9000313548
OpenAlex ID: W7218479376
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