Effects of childhood adversity on the volumes of the amygdala subnuclei and hippocampal subfields in individuals with major depressive disorder
Bibliographic record
Abstract
Background: Reductions in total hippocampus volume have frequently been reported in MRI studies in major depressive disorder (MDD), but reports of differences in total amygdala volume have been inconsistent. Childhood maltreatment is an important risk factor for MDD in adulthood and may affect the volume of the hippocampus and amygdala. In the present study, we examined associations between the volumes of the amygdala subnuclei and hippocampal subfields and history of childhood maltreatment in participants with MDD. Methods: We recruited 35 patients who met the DSM-IV criteria for MDD and 35 healthy controls. We acquired MRI data sets on a 4.7 T Varian Inova scanner. We manually delineated the amygdala subnuclei (lateral, basal and accessory basal nuclei, and the cortical and centromedial groups) and hippocampal subfields (cornu ammonis, subiculum and dentate gyrus) using reliable volumetric methods. We assessed childhood maltreatment using the Childhood Trauma Questionnaire in participants with MDD. Results: In participants with MDD, a history of childhood maltreatment had significant negative associations with volume in the right amygdala, anterior hippocampus and total cornu ammonis subfield bilaterally. For volumes of the amygdala subnuclei, such effects were limited to the basal, accessory basal and cortical subnuclei in the right hemisphere, but they did not survive correction for multiple comparisons. We did not find significant effects of MDD or antidepressant treatment on volumes of the amygdala subnuclei. Limitations: Our study was a cross-sectional study. Conclusion: Our results provide evidence of negative associations between history of childhood maltreatment and volumes of medial temporal lobe structures in participants with MDD. This may help to identify potential mechanisms by which maltreatment leads to clinical impacts.
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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) | 0.001 | 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".