Identification of Novel CYP2A6*1B Variants: The CYP2A6*1B Allele is Associated With Faster In Vivo Nicotine Metabolism
Bibliographic record
Abstract
Cytochrome P450 2A6 (CYP2A6) is the human enzyme responsible for the majority of nicotine's metabolism. CYP2A6 genetic variants contribute to the interindividual and interethnic variation in nicotine metabolism. We examined the association between the CYP2A6*1B variant and nicotine's in vivo metabolism. Intravenous infusions of deuterium-labeled nicotine were administered to 292 volunteers, 163 of whom were White and did not have common CYP2A6 variants, other than CYP2A6*1B. We discovered three novel CYP2A6*1B variants in the 3'-flanking region of the gene that can confound genotyping assays. We found significant differences between CYP2A6*1A/*1A, CYP2A6*1A/*1B, and CYP2A6*1B/*1B groups in total nicotine clearance (17.2+/-5.2, 19.0+/-6.4, and 20.4+/-5.9, P<0.02), non-renal nicotine clearance (16.4+/-5.0, 18.5+/-6.2, and 19.8+/-5.7, P<0.01), and the plasma trans-3'-hydroxycotinine/cotinine ratio (0.26+/-0.1, 0.26+/-0.1, and 0.34+/-0.1, P<0.001). There were also differences in total nicotine (29.4+/-12.9, 25.8+/-0.12.9, and 22.4+/-12.4, P<0.01), cotinine (29.2+/-8.1, 32.2+/-9.1, and 33.0+/-6.6, P<0.01) and trans-3'-hydroxycotinine (32.4+/-9.1, 34.2+/-12.3, and 41.3+/-11.3, P<0.001) excreted in the urine. We report evidence that CYP2A6*1B genotype is associated with faster nicotine clearance in vivo, which will be important to future CYP2A6 genotype association studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".