Possible association of the pro‐melanin‐concentrating hormone gene with <i>a greater</i> body mass index as a side effect of the antipsychotic olanzapine
Bibliographic record
Abstract
Following our report of a linkage at 12q24 with a phenotype of obesity under antipsychotics, we tested the pro-melanin-concentrating hormone (PMCH) candidate gene for a possible association in humans with the body mass index (BMI; kg/m2) in unrelated schizophrenic patients (SZ) receiving antipsychotics (N = 300) and in controls (CTL; N = 150). Subjects were classified in obese (OB) (BMI > or = 30 kg/m2), overweight (25 < or = BMI < 30 kg/m2), and normal weight (BMI < 25 kg/m2) groups. Single nucleotide polymorphisms (SNP) rs7973796 and rs11111201, located 5' at -4.5 kb and 3' at +1.8 kb, respectively, of PMCH were genotyped. Interaction effects of genotypes and antipsychotic treatment on BMI were tested in a covariance analysis with age and gender as covariates. Interaction effects on the prevalence of obesity were tested in a logistic regression analysis. For subjects under 50 years, the effect of the rs7973796 genotype on BMI differed between the SZ patients taking olanzapine and CTL group (interaction P = 0.025). Olanzapine-treated SZ patients carrying the ancestral homozygote genotype showed a higher BMI for rs7973796 (P = 0.016 with the LSMeans t-test) than the variant homozygotes. Accordingly, the ORs for obesity associated with rs7973796 genotypes differed in the SZ patients taking olanzapine compared to the CTL group (interaction P = 0.0094). The G allele was associated with an increase in the odds of obesity in SZ patients taking olanzapine. No association was observed for those over 50 years, or for rs11111201. These results suggest that the common allele of PMCH rs7973796 may be associated with a greater BMI in olanzapine-treated SZ patients.
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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 | 0.000 | 0.000 |
| 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".