Sex differences in brain structure among adolescents with bipolar disorder
Bibliographic record
Abstract
OBJECTIVES: Bipolar disorder (BD) is twice as prevalent amongst female as amongst male adolescents. Thus far, little is known regarding the neurostructural substrates underlying this disparity. We therefore examined sex differences in neurostructural magnetic resonane imaging (MRI) phenotypes amongst adolescents with BD. METHODS: T1-weighted structural MRI was acquired from 44 BD (25 female [F] and 19 male [M]) and 58 (28 F and 30 M) healthy control (HC) adolescents (13-21 years old). Whole-brain and region-of-interest (ROI) analyses examined structural volume and cortical thickness using FreeSurfer. ROIs included the ventrolateral prefrontal cortex (vlPFC), anterior cingulate cortex (ACC), amygdala and hippocampus. General linear models evaluated sex-by-diagnosis interactions, controlling for age and intracranial volume. RESULTS: = 0.01). Sex differences in HCs were found in the SMG (M > F) and IPL (F > M). In BD, sex differences were reversed and of smaller magnitude in the SMG (M < F) and of greater magnitude in the IPL (F > M), driven by trends towards smaller SMG and IPL in BD vs HC male participants (P = .05 and .14). Whole-brain analyses for cortical thickness, and ROI analyses for volume and cortical thickness, were not significant. CONCLUSIONS: Normative sex differences may be disrupted in adolescent BD in the SMG and IPL, heteromodal association network hubs responsible for higher order integration of cognitive and emotional processing. Unexpectedly, these findings may inform our understanding of aberrant brain structure in adolescent BD male patients, rather than female patients. Future work should focus on replication, as well as the impact of puberty status and sex hormones on measures of brain structure and function.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".