The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.
M, S., SR, M., L, W., J, F.P., L, D., E, C., L, S., A, N., M, A., & K, F. (2026). The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.. Psychological medicine. https://doi.org/10.1017/S0033291726104905
M S, SR M, L W, J FP, L D, E C, et al. The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.. Psychological medicine. 2026; doi: 10.1017/S0033291726104905
M S, SR M, L W, et al. The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.[J]. Psychological medicine. 2026. DOI: 10.1017/S0033291726104905.
@article{m2026,
author = {Selitser M and McWhinney SR and Wu L and Fraiha-Pegado J and Dietze L and Corkum E and Selitser L and Nunes A and Alda M and Franke K},
title = {The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.},
journal = {Psychological medicine},
year = {2026},
doi = {10.1017/S0033291726104905},
note = {PMID: 42312342},
}
TY - JOUR AU - Selitser M AU - McWhinney SR AU - Wu L AU - Fraiha-Pegado J AU - Dietze L AU - Corkum E AU - Selitser L AU - Nunes A AU - Alda M AU - Franke K TI - The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders. T2 - Psychological medicine PY - 2026 DO - 10.1017/S0033291726104905 AN - PMID:42312342 ER -
BACKGROUND: Bipolar disorders (BD) rank among the most disabling conditions, affecting millions worldwide. Cognitive impairment in BD is linked with brain changes and worse functional outcomes. Obesity and metabolic syndrome (MetSy) are overrepresented in BD and are associated with more pronounced brain structural and cognitive alterations in the general population. Here, we studied for the first time the contribution of metabolic dysfunction to both brain and cognitive alterations in BD. METHODS: We recruited 163 participants (76 individuals with BD, 87 controls). We used principal component analysis (PCA) to derive a composite measure of metabolic health from WHR, BMI, HOMA-IR, HbA1c, TGC, HDL, LDL, systolic, diastolic BP, and to derive a composite cognitive measure from the California Verbal Learning Test and Digit Span. Brain structure was indexed using machine-learning-predicted BrainAGE derived from T1-weighted MRI. RESULTS: Obesity, hypertension, insulin resistance, and dyslipidemia contributed most strongly to variance in metabolic health in this sample. This MetSy-associated risk cluster predicted higher BrainAGE (β = 0.75 ± 0.29, p = 0.011) and lower cognitive performance (β = -0.19 ± 0.09, p = 0.037), accounting for 30% of the association between BD and higher BrainAGE and 25% of the association between BD and worse cognitive performance. These effects were independent of symptoms, medications, illness course, and duration. CONCLUSIONS: MetSy, particularly obesity, was closely linked with brain/cognitive impairments in BD. While the need for metabolic monitoring should be informed by the diagnosis of BD, screening for MetSy can also help track brain health and cognitive functioning.