Association Study of GABAA α2 Receptor Subunit Gene Variants in Antipsychotic-Associated Weight Gain
Bibliographic record
Abstract
Schizophrenia treatment has been hampered by undesirable adverse effects, including weight gain and associated complications. Recent candidate gene studies have been exploring the appetite regulation pathways in antipsychotic-associated weight gain (AAWG) with some promising leads. Genome-wide association studies of obesity have pointed to a number of potential candidate genes, such as MC4R, that were later found to be shared with AAWG. GABAA α2 receptor subunit (GABRA2) was another potential candidate gene for obesity from genome-wide association studies; however, it has not been explored in AAWG. We examined 9 single nucleotide polymorphisms across the GABRA2 gene. Prospective weight change was assessed for a total of 160 schizophrenia patients of European ancestry. The rs279858 marker was associated with percent weight change, with the patients homozygous for the TT genotype experiencing higher percentage weight gain on average than the C allele carriers (P = 0.009). When we performed the analysis considering each clinical site using a meta-analytic method, the results remained statistically significant (P = 1.4e-4). These findings became even more significant when we considered only patients taking clozapine or olanzapine, the 2 medications with higher risk for weight gain (P < 1e-10). GABRA2 genetic variants may play a role in predicting AAWG. However, replication in larger and independent samples is required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".