Increased body mass index makes an impact on brain white-matter integrity in adults with remitted first-episode mania
Bibliographic record
Abstract
BACKGROUND: Obesity is increasingly prevalent in bipolar disorder (BD) but data about the impact of elevated body mass index (BMI) on brain white-matter integrity in BD are sparse. Based on extant literature largely from structural magnetic resonance imaging (MRI) studies, we hypothesize that increased BMI is associated with decreased fractional anisotropy (FA) in the frontal, temporal, parietal and occipital brain regions early in the course of BD. METHOD: A total of 26 euthymic adults (12 normal weight and 14 overweight/obese) with remitted first-episode mania (FEM) and 28 controls (13 normal weight and 15 overweight/obese) matched for age, handedness and years of education underwent structural MRI and diffusion tensor imaging scans. RESULTS: There are significant effects of diagnosis by BMI interactions observed especially in the right parietal lobe (adjusted F(1,48) = 5.02, p = 0.030), occipital lobe (adjusted F(1,48) = 10.30, p = 0.002) and temporal lobe (adjusted F(1,48) = 7.92, p = 0.007). Specifically, decreased FA is found in the right parietal (F(1,48) = 5.864, p = 0.023) and occipital lobes (F(1,48) = 4.397, p = 0.047) within overweight/obese patients compared with normal-weight patients with FEM. Compared with overweight/obese controls, decreased FA is observed in right parietal (F(1,48) = 6.708, p = 0.015), temporal (F(1,48) = 10.751, p = 0.003) and occipital (F(1,48) = 9.531, p = 0.005) regions in overweight/obese patients with FEM. CONCLUSIONS: Our findings suggest that increased BMI affects temporo-parietal-occipital brain white-matter integrity in FEM. This highlights the need to further elucidate the relationship between obesity and other neural substrates (including subcortical changes) in BD which may clarify brain circuits subserving the association between obesity and clinical outcomes in BD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".