Association between BDNF levels and suicidal behaviour: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Suicidal behaviour is a complex phenomenon with a multitude of risk factors. Brain-derived neurotrophic factor (BDNF), a protein crucial to nervous system function, may be involved in suicide risk. The objective of this systematic review is to evaluate and summarize the literature examining the relationship between BDNF levels and suicidal behaviour. METHODS: A predefined search strategy was used to search MEDLINE, EMBASE, PsychINFO, and CINAHL from inception to December 2015. Studies were included if they investigated the association between BDNF levels and suicidal behaviours (including completed suicide, attempted suicide, or suicidal ideation) by comparing BDNF levels in groups with and without suicidal behaviour. Only the following observational studies were included: case-control and cohort studies. Both clinical- and community-based samples were included. Screening, data extraction, and risk of bias assessment were conducted in duplicate. RESULTS: Six-hundred thirty-one articles were screened, and 14 were included in the review. Three studies that assessed serum BDNF levels in individuals with suicide attempts and controls were combined in a meta-analysis that showed no significant association between serum BDNF and suicide attempts. The remaining 11 studies were not eligible for the meta-analysis and provided inconsistent findings regarding associations between BDNF and suicidal behaviour. CONCLUSIONS: The findings of the meta-analysis indicate that there is no significant association between serum BDNF and attempted suicide. The qualitative review of the literature did not provide consistent support for an association between BDNF levels and suicidal behaviour. The evidence has significant methodological limitations. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015015871.
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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".