Joint and distinct neural structure and function deficits in major depressive disorder with suicidality: a multimodal meta-analysis of MRI studies
Bibliographic record
Abstract
Background: Suicide risk is a major concern for patients with major depressive disorder (MDD). Neuroimaging studies have demonstrated that patients with MDD with suicidal ideation or suicide attempt (MDD-S) are accompanied by neurostructural or functional abnormalities, but there is no consensus of opinion on neural substrate alterations involved in MDD-S. Methods: We performed a whole-brain multimodal meta-analysis of existing magnetic resonance imaging (MRI) studies to identify conjoint and separate alterations of grey matter volume (GMV) and spontaneous brain activity characteristics (regional homogeneity and amplitude of low-frequency fluctuations) between patients with MDD-S and patients with MDD without suicidal ideation or suicidal attempt (MDD-NS) via the seed-based d mapping software. We excluded studies that used other modalities, had overlapping data, or had insufficient information. Results: Our systematic search identified 13 structural MRI studies (471 patients with MDD-S and 508 patients with MDD-NS) and 16 resting-state functional MRI studies (704 patients with MDD-S and 554 patients with MDD-NS) published up to Dec. 5, 2023. Compared with patients with MDD-NS, those with MDD-S showed increased GMV with hypoactivity in the left postcentral gyrus, decreased GMV with hypoactivity in the right inferior parietal gyri, decreased GMV with hyperactivity in the right insula, and separate GMV and functional changes within the bilateral parietal, occipital, and frontal lobes, and the left thalamus. Limitations: We were unable to analyze the association between brain features and clinical detail because of a lack of data. Included studies showed considerable heterogeneity and publication bias. Conclusion: These findings provide a comprehensive overview of brain morphological and spontaneous functional impairments linked to impulsivity, impaired positive reward modulation, emotional disturbances, abnormal emotional processing, and cognitive deficits in MDD-S. These results support an understanding of the relationship between neural substrates and clinical symptoms in MDD-S, and these alterations provide useful insight into pathophysiological mechanisms and intervention strategies to decrease suicide risk in MDD.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.027 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".