Individual-level brain phenotypes in first-episode mania: normative modelling of brain morphometry and brainAGE
Bibliographic record
Abstract
Background Brain morphological alterations in bipolar disorder are well documented, particularly in chronic cases. This study focuses on first-episode mania (FEM) to quantify neuroanatomical changes at early stages of the disorder. Aims To assess deviations from normative brain morphometry and age-related brain changes in patients with FEM. Method Pretrained models, based on large, independent healthy samples, were applied to structural brain images from FEM patients ( n = 83) and healthy individuals ( n = 61). Normative deviation z -scores were computed for regional brain morphometry, along with global and voxel-level brain–age-gap estimates (G-brainAGE and L-brainAGE, respectively). The proportions of infranormal ( z < −1.96) and supranormal ( z > 1.96) deviations were measured for both groups. Ridge regression and support vector machine models were used to evaluate whether z -scores predicted symptom severity, IQ or diagnosis. Case-control differences in L-brainAGE and correlations between G-brainAGE and clinical features were analysed. Results Both FEM and healthy individuals showed similar proportions of infra- and supranormal deviations in regional measures. Morphometric data, whether observed or normative, did not significantly predict clinical outcomes or diagnosis. Mean G-brainAGE in FEM was −1.04 (s.d. 3.26) years and negatively correlated with age of onset, while L-brainAGE did not differ significantly between groups. Conclusions Regional morphometry and local brain-ageing metrics in FEM patients aligned with normative ranges, suggesting minimal abnormalities in early bipolar disorder. However, subtle delays in global brain ageing may reflect variation based on the age of onset, highlighting a potential area for further exploration.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".