CYP2A6 and CYP2B6: Sources of Variation and their Role in Nicotine Metabolism
Bibliographic record
Abstract
Nicotine is the primary substance in tobacco causing addiction. In humans the majority (70-80%) of nicotine is inactivated to cotinine in a reaction predominantly catalyzed by CYP2A6 (80-90%), with a minor possible role for CYP2B6. Substantial interindividual variability is observed in the rate of nicotine’s inactivation to cotinine and this variation contributes to differences in smoking behaviors (e.g. cigarette consumption). Twin studies suggest an important genetic contribution to the variability in nicotine metabolism. However in 2004, genetic variation in CYP2A6 and CYP2B6 accounted for only a small portion of the variability suggesting gaps in our knowledge. Our objective was to identify additional genetic and non-genetic sources of variability in CYP2A6 expression/activity, CYP2B6 expression, and nicotine to cotinine metabolism in vivo and/or in vitro. Participants included individuals from different world populations phenotyped for CYP2A6 activity either following oral nicotine administration or using metabolite ratios derived from baseline smoking. Genotyping and sequencing were utilized to identify and characterize multiple new CYP2A6 alleles. In total 17 novel CYP2A6 alleles were identified, many of which were found predominantly among individuals of black African descent and exhibited lower CYP2A6 activity. In addition, human livers were assessed for CYP2A6 and CYP2B6 expression and nicotine to cotinine metabolism. The mechanisms underlying the lower CYP2A6 activity associated with some of the variant CYP2A6 alleles included either a reduction in hepatic CYP2A6 protein expression, an alteration of CYP2A6’s structural property, or a combination of both. DNA methylation was not associated with altered hepatic CYP2A6 expression/activity. Livers from female donors were associated with higher CYP2A6 and CYP2B6 protein expression compared to male livers, while age did not influence the expression of either CYP. Finally, CYP2B6 and its prevalent altered function genetic variant (CYP2B6*6) did not influence nicotine to cotinine metabolism. Identification of factors that contribute to the variability in CYP2A6 and nicotine metabolism is important to improve future association studies between CYP2A6 genotype, nicotine metabolism, and smoking behaviors. In addition, this information could provide the potential to personalize therapy in order to improve the clinical efficacy of nicotine, particularly as a smoking cessation aid.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".