Brain morphology mediators of the link between childhood trauma and bipolar disorder: a large-scale international analysis
Bibliographic record
Abstract
Childhood trauma is a risk factor for bipolar disorder, but the biological mechanisms of this association remain incompletely defined. Gray matter differences observed after trauma exposure overlap with those reported in bipolar disorder, suggesting that the association between childhood trauma and bipolar disorder might be mediated through brain morphology. Our goal was to determine whether cortical thickness, cortical surface or subcortical volume mediate the association between childhood trauma and bipolar disorder. We leveraged a large multi-site dataset from the ENIGMA Bipolar Disorder Working Group, comprising of 1,031 participants with bipolar disorder and 2,221 controls from 19 international cohorts. To identify brain morphology mediators of the association of childhood trauma and bipolar disorder, we used high-dimensional mediation analysis and validated our results using leave-one-site-out cross-validation and permutation testing for significance. Severity of childhood trauma was directly associated with higher likelihood of having a bipolar disorder diagnosis (median coefficient 0.841, 95% CI: [0.834, 0.851], p<0.001). Significant mediators were hippocampal volume (0.004, 95% CI: [0.002, 0.005], p<0.001), medial orbitofrontal gray matter thickness (0.002, 95% CI: [0.002, 0.003], p<0.001), and superior frontal gyrus gray matter thickness (0.002, 95% CI: [0, 0.005], p<0.001). Our results show that the severity of childhood trauma exposure is associated with bipolar disorder diagnosis in part through a smaller hippocampus, thinner cortex in the medial orbitofrontal gyrus and thinner cortex in the superior frontal gyrus. The identification of this mechanistic pathway improves our etiologic understanding of bipolar disorder and could help to identify those at risk and enable the development of new interventions.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".