Meta-analysis of central and peripheral γ-aminobutyric acid levels in patients with unipolar and bipolar depression
Bibliographic record
Abstract
BACKGROUND: Many studies have measured central and peripheral γ-aminobutyric acid (GABA) levels in patients with depression. We performed a meta-analysis to provide an objective overview of GABA changes in those with unipolar or bipolar depression. METHODS: After a systematic database search, original data were extracted with the help of seminal authors to calculate standardized mean differences. We compared GABA levels between patients with current major depressive episodes and controls, between euthymic patients and controls, and in patients before and after treatment. We performed meta-regressions to explore the influence of demographic and clinical variables on GABA significant mean differences. RESULTS: For unipolar depression, central and peripheral GABA levels were diminished in currently depressed patients, but normal in euthymic patients, compared with the healthy controls. For bipolar disorder, GABA levels were diminished in medication-free patients, but seemed to be normalized in medicated patients, compared with the healthy controls. We found no significant association with demographic or clinical variables. LIMITATIONS: There was a great heterogeneity across studies, probably because of the substantial variation of clinical characteristics in the included samples. Many subanalyses were performed to assess how the diagnosis, medications, or the type of measurements of peripheral or central GABA levels may affect the main results. CONCLUSION: The GABA levels evolved differentially in patients with unipolar and bipolar disorders. Our results suggest that GABA levels could represent a biomarker of symptomatic states in patients with unipolar disorder and would be normalized by mood stabilizers in those with bipolar disorder.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.035 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".