<scp>BDNF</scp> and <scp>BMI</scp> effects on brain structures of bipolar offspring: results from the global mood and brain science initiative
Bibliographic record
Abstract
Objective To compare brain‐derived neurotrophic factor ( BDNF ) levels between offspring of individuals with bipolar disorders ( BD ) and healthy controls ( HC s) and investigate the effects of BDNF levels and body mass index ( BMI ) on brain structures. Method Sixty‐seven bipolar offspring and 45 HC s were included (ages 8‐28). Structural images were acquired using 3.0 Tesla magnetic resonance imaging. Serum BDNF levels were measured using enzyme‐linked immunosorbent assay. Multivariate and univariate analyses of covariance were conducted. Results Significantly higher BDNF levels were observed among bipolar offspring, relative to HC s ( P > 0.025). Offspring status moderated the association between BDNF and BMI (F 1 =4.636, P = 0.034). After adjustment for relevant covariates, there was a trend for a significant interaction of group and BDNF on neuroimaging parameters (Wilks’λ F 56,94 =1.463, P = 0.052), with significant effects on cerebellar white matter and superior and middle frontal regions. Brain volume and BDNF were positively correlated among HC s and negatively correlated among bipolar offspring. Interactions between BDNF and BMI on brain volumes were non‐significant among HC s (Wilks’λ F 28,2 =2.229, P = 0.357), but significant among bipolar offspring (Wilks’λ F 28,12 =2.899, P = 0.028). Conclusion Offspring status and BMI moderate the association between BDNF levels and brain structures among bipolar offspring, underscoring BDNF regulation and overweight/obesity as key moderators of BD pathogenesis.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".