Association of the Nicotine Metabolite Ratio and CHRNA5/CHRNA3 Polymorphisms With Smoking Rate Among Treatment-Seeking Smokers
Bibliographic record
Abstract
INTRODUCTION: Genome-wide association studies have linked single-nucleotide polymorphisms (SNPs) in the CHRNA5/A3/B4 gene cluster with heaviness of smoking. The nicotine metabolite ratio (NMR), a measure of the rate of nicotine metabolism, is associated with the number of cigarettes per day (CPD) and likelihood of cessation. We tested the potential interacting effects of these two risk factors on CPD. METHODS: Pretreatment data from three prior clinical trials were pooled for analysis. One thousand and thirty treatment seekers of European ancestry with genotype data for the CHRNA5/A3/B4 SNPs rs578776 and rs1051730 and complete data for NMR and CPD at pretreatment were included. Data for the third SNP, rs16969968, were available for 677 individuals. Linear regression models estimated the main and interacting effects of genotype and NMR on CPD. RESULTS: We confirmed independent associations between the NMR and CPD as well as between the SNPs rs16969968 and rs1051730 and CPD. We did not detect a significant interaction between NMR and any of the SNPs examined. CONCLUSIONS: This study demonstrates the additive and independent association of the NMR and SNPs in the CHRNA5/A3/B4 gene cluster with smoking rate in treatment-seeking smokers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".