A Longitudinal Study of the Relationships Between Mood Symptoms, Body Mass Index, and Serum Adipokines in Bipolar Disorder
Bibliographic record
Abstract
OBJECTIVE: There is a bidirectional relationship between obesity and mood disorders, with each increasing the risk of developing the other. This relationship suggests that they have overlapping pathophysiologic mechanisms. Adipose tissue-derived hormones, or adipokines, regulate appetite and metabolism and have activity in limbic brain regions, making them potential shared etiologic factors between elevated body mass index (BMI) and mood disorders. However, the precise relationships between BMI, mood, and adipokines are unknown. METHODS: We measured the serum levels of adiponectin, lipocalin-2, resistin, adipsin, and leptin in 53 people with early-stage DSM-IV-defined bipolar disorder, diagnosed with the Mini-International Neuropsychiatric Interview, and 22 healthy comparison subjects. Participants were followed at the University of British Columbia Mood Disorders Centre between June 2004 and June 2012. We were primarily interested in determining, in patients, (1) whether BMI and recent mood episodes predicted adipokine levels and (2) whether adipokine levels in turn predicted subsequent mood relapses and change in BMI. RESULTS: Using linear regression, we found that (1) past-6-month mood episodes predicted lower adiponectin (β = -0.385, P = .04) and adipsin (β = -0.376, P = .03) levels and higher lipocalin-2 levels (β = 0.411, P = .03), (2) BMI did not predict adipokine levels, and (3) treatment with second-generation antipsychotics was associated with higher resistin levels (β = 0.482, P < .01). Furthermore, lower adiponectin (β = -0.353, P = .01) and leptin (β = -0.332, P = .02) levels predicted depressive relapse over 12 months, while higher adipsin (β = 0.496, P < .01) and leptin (β = 0.421, P < .01) levels predicted BMI gain. CONCLUSIONS: Our results suggest that mood episodes and medication treatment contribute to adipokine abnormalities in bipolar disorder and that adipokines influence psychiatric illness course and BMI change. Adipokines may represent a novel pathophysiologic mechanism linking elevated BMI and mood disorders and deserve further study as potential mood-regulating molecules.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".