Association Study of <b><i>GABRG2</i></b> Polymorphisms with Suicidal Behaviour in Schizophrenia Patients with Alcohol Use Disorder
Bibliographic record
Abstract
BACKGROUND: Schizophrenia is a severe neuropsychiatric disorder where the role of γ-aminobutyric acid (GABA), an inhibitory neurotransmitter, has been implicated in its aetiopathophysiology. Several genes coding for GABAA subunits, including the GABRG2 gene that encodes the γ2 subunit, are clustered at 5q31-q35, a chromosomal region that is associated with schizophrenia in genome scan studies. We recently reported GABRG2 to be associated with schizophrenia in our case-control and family samples. METHODS: We tested eight single-nucleotide polymorphisms spanning the GABRG2 gene for an association with suicidal behaviour in our schizophrenia sample of European ancestry (n = 197), taking into account history of alcohol abuse or dependence. RESULTS: We found the haplotypes of the rs183294 and rs209356 markers to be significantly associated with history of suicide attempt (p < 0.01) as well as suicide specifier scores (p < 0.05). The association appeared to be originating in patients with a history of alcohol dependence or abuse. CONCLUSIONS: Taken together, the results of the present study suggest that GABRG2 may be involved in suicidal behaviour in schizophrenia patients with alcohol dependence or abuse, but replications are required. These results may help in the discovery of novel treatments for alcoholism and/or prevention of suicide.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".