Variation in P450 oxidoreductase (POR) A503V and flavin-containing monooxygenase (FMO)-3 E158K is associated with minor alterations in nicotine metabolism, but does not alter cigarette consumption
Bibliographic record
Abstract
The rates of nicotine metabolism differ widely, even after controlling for genetic variation in the major nicotine-metabolizing enzyme, CYP2A6. Genetic variants in an additional nicotine-metabolizing enzyme, flavin-containing monooxygenase (FMO)-3, and an obligate microsomal CYP-supportive enzyme, cytochrome P450 oxidoreductase (POR), were investigated. We examined the impact of FMO3 E158K and POR A503V before and after stratifying by CYP2A6 metabolism group. In 130 nonsmokers of African descent who received 4 mg oral nicotine, FMO3 158K trended toward slower nicotine metabolism in reduced CYP2A6 metabolizers (P=0.07) only, whereas POR 503V was associated with faster CYP2A6 activity (nicotine metabolite ratio) in normal (P=0.03), but not reduced, CYP2A6 metabolizers. Neither FMO3 158K nor POR 503V significantly altered the nicotine metabolic ratio (N=659), cigarette consumption (N=667), or urine total nicotine equivalents (N=418) in smokers of African descent. Thus, FMO3 E158K and POR A503V are minor sources of nicotine metabolism variation, insufficient to appreciably alter smoking.
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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 | 0.000 |
| 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 | 0.000 | 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".