Microglial Dysregulation and Suicidality: A Stress-Diathesis Perspective
Bibliographic record
Abstract
According to the stress-diathesis model of suicidal behavior, completed suicide depends on the interaction between psychosocial stressors and a trait-like susceptibility. While there are likely multiple biological processes at play in suicidal behavior, recent findings point to over-activation of microglia, the resident macrophages of the central nervous system, as implicated in stress-induced suicidal behavior. However, it remains unclear how microglial dysregulation can be integrated into a clinical model of suicidal behavior. Therefore, this narrative review aims to (1) examine the findings from human post-mortem and neuroimaging studies that report a relationship between microglial activation and suicidal behavior, and (2) update the clinical model of suicidal behavior to integrate the role of microglia. A systematic search of SCOPUS, PubMed, PsycINFO, and Embase databases revealed evidence of morphological alterations in microglia and increased translocator protein density in the brains of individuals with suicidality, pointing to a positive relationship between microglial dysregulation and suicidal behavior. The studies also suggested several pathological mechanisms leading to suicidal behavior that may involve microglial dysregulation, namely (1) enhanced metabolism of tryptophan to quinolinic acid through the kynurenine pathway and associated serotonin depletion; (2) increased quinolinic acid leading to excessive N-methyl-D-aspartate-signaling, resulting in potential disruption of the blood brain barrier; (3) increased quinolinic acid resulting in higher neurotoxicity, and; (4) elevated interleukin 6 contributing to loss of inhibition of glutamatergic neurons, causing heightened glutamate release and excitotoxicity. Based on these pathways, we reconceptualized the stress-diathesis theory of suicidal behavior to incorporate the role of microglial activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".