Regional brain morphology and current antidepressant use: findings from 32 international cohorts from the ENIGMA major depressive disorder working group
Bibliographic record
Abstract
The understanding of how antidepressant (AD) use is associated with brain structure in individuals with major depressive disorder (MDD) remains incomplete. We aimed to examine the association between AD medication use and brain morphology in relation to age and sex by pooling structural neuroimaging and clinical data from 32 cohorts within the ENIGMA-MDD working group. Interaction effects of group (2076 cases with current AD use (AD), 1495 cases not currently taking AD (nAD) and 5125 healthy controls (HC)) with age and sex, and main effects of group on regional brain structure (cortical surface area and thickness, and subcortical volume) were examined. Additionally, we examined the effect of AD type (SSRI, SNRI or mirtazapine) and duration of use on brain morphology. Younger individuals in the AD group showed lower bilateral middle temporal gyrus thickness compared to nAD and HC, but this was not seen in older individuals (crossover around 50 years). Lower hippocampal volume and thinner inferior temporal gyrus were shown in AD compared to nAD. These effects were independent of group differences in disease-course-related measures, but were driven by depressive symptom severity. Greater bilateral rostral anterior cingulate thickness was found in individuals older than approximately 40 years taking mirtazapine compared to individuals taking SSRIs or SNRIs. Evidence for subtle structural brain differences in temporal and limbic regions in individuals with MDD who currently use AD medication were found compared to those not currently taking AD medication. Future longitudinal studies are needed to determine the causality of these associations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".