Association of a Functional Polymorphism in Neuropeptide Y With Antipsychotic-Induced Weight Gain in Schizophrenia Patients
Bibliographic record
Abstract
Significant body weight gain (BWG) is a serious adverse effect of a number of antipsychotic drugs. Previous studies have demonstrated an influence of clozapine, but not haloperidol, on neuropeptide Y (NPY) expression in the hypothalamus. Because NPY is a potent orexigenic peptide stimulating food intake, and genetic variation of the gene has been shown to influence development of obesity, we investigated the impact of NPY polymorphisms on antipsychotic-induced BWG.We analyzed 5 polymorphisms in the NPY gene (rs10551063, rs16147, rs5573, rs5574, and rs16475) in schizophrenia subjects (n = 226), treated mostly with clozapine and olanzapine for up to 14 weeks. Association was tested using analysis of covariance with change (%) from baseline weight as the dependent variable and duration of treatment and baseline body weight as covariates.In patients of European ancestry who received either clozapine or olanzapine, significant genotypic and allelic association of rs16147 with weight change was observed (P(corrected) = 0.012 and 0.018, respectively). Carriers of the C allele gained significantly more weight compared with individuals with TT genotype (CC + CT vs TT; 5.82% ± 5.6% vs 2.25% ± 4.8%; P= 0.001). Similarly, 2 other polymorphisms (rs5573 and rs5574) were also significantly associated with weight change (P(corrected) = 0.018 and 0.03). In addition, we observed a significant gene-gene interaction between the rs16147 in NPY and rs806378 in cannabinoid receptor 1 (P(corrected) = 0.011).Our observation of association of NPY polymorphisms gives further evidence for a genetic influence on antipsychotic-induced BWG and suggests a role of NPY gene in influencing this complex adverse effect.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".