Weight gain as a risk factor for progressive neurochemical abnormalities in first episode mania patients: a longitudinal magnetic resonance spectroscopy study
Bibliographic record
Abstract
Abstract Background We previously reported that bipolar disorder (BD) patients with clinically significant weight gain (CSWG; ⩾7% of baseline weight) in the 12 months after their first manic episode experienced greater limbic brain volume loss than patients without CSWG. It is unknown whether CSWG is also a risk factor for progressive neurochemical abnormalities. Methods We investigated whether 12-month CSWG predicted greater 12-month decreases in hippocampal N -acetylaspartate (NAA) and greater increases in glutamate + glutamine (Glx) following a first manic episode. In BD patients ( n = 58) and healthy comparator subjects (HS; n = 34), we measured baseline and 12-month hippocampal NAA and Glx using bilateral 3-Tesla single-voxel proton magnetic resonance spectroscopy. We used general linear models for repeated measures to investigate whether CSWG predicted neurochemical changes. Results Thirty-three percent of patients and 18% of HS experienced CSWG. After correcting for multiple comparisons, CSWG in patients predicted a greater decrease in left hippocampal NAA (effect size = −0.52, p = 0.005). CSWG also predicted a greater decrease in left hippocampal NAA in HS with a similar effect size (−0.53). A model including patients and HS found an effect of CSWG on Δleft NAA ( p = 0.007), but no diagnosis effect and no diagnosis × CSWG interaction, confirming that CSWG had similar effects in patients and HS. Conclusion CSWG is a risk factor for decreasing hippocampal NAA in BD patients and HS. These results suggest that the well-known finding of reduced NAA in BD may result from higher body mass index in patients rather than BD diagnosis.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".