Genetic interactions in the adrenergic system genes: analysis of antipsychotic‐induced weight gain
Bibliographic record
Abstract
UNLABELLED: Atypical antipsychotics (AP) have high affinity for many neurotransmitter receptors. Among these receptors, APs are antagonist at α-adrenergic and β-adrenergic receptors, and this pharmacological property has been postulated to be involved in the mechanism of action of these drugs with respect to both clinical response and adverse effects. OBJECTIVE: We tested the hypotheses that AP-induced weight gain is associated with genetic variation in adrenergic receptors and pathway enzymes. We analyzed nine genetic polymorphisms across seven adrenergic genes (ADRA1A, ADRA2A, ADRA2C, ADRB3, DBH, MAOA and COMT). METHODS: One hundred thirty-nine patients with schizophrenia were prospectively assessed for AP-induced weight gain. The HelixTree software (Golden Helix, Bozeman, MT, USA) was employed to detect differences in genotypic distribution between weight gainer and non-weight gainer groups. Furthermore, for the dopamine β-hydroxylase haplotype, we were able to obtain both the molecular and the statistical phases, analyzing the phenotype considering both phases. RESULTS: Weight gain was not associated with any adrenergic gene. CONCLUSIONS: Our results suggest that genetic polymorphisms in the adrenergic system may not play a major role in AP-induced weight gain; however, adrenergic 2A receptor gene that produced previously the most consistent associations with this phenotype showed a significant interaction with the monoamine oxidase A in weight gainers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".