Impact of CYP2A6 Activity on Nicotine Reinforcement and Cue-Reactivity in Daily Smokers
Bibliographic record
Abstract
INTRODUCTION: Variation in CYP2A6, the primary enzyme responsible for nicotine metabolism, is associated with nicotine dependence, cigarette consumption, and abstinence outcomes in smokers. The impact of CYP2A6 activity on nicotine reinforcement and tobacco cue-reactivity, mechanisms that may contribute to these previous associations, has not been fully evaluated. AIMS AND METHODS: CYP2A6 activity was indexed using 3 genetic approaches in 104 daily smokers completing forced-choice and cue-induced craving tasks assessing nicotine reinforcement and tobacco cue-reactivity, respectively. First, smokers were stratified by the presence or absence of reduced/loss-of-function CYP2A6 gene variants (normal vs. reduced metabolizers). As nicotine metabolite ratio (NMR) is a reliable biomarker of CYP2A6 activity, our second and third approaches used additional genetic variants identified in genome-wide association studies of NMR to create a weighted genetic risk score (wGRS) to stratify smokers (fast vs. slow metabolizers) and calculate a wGRS-derived NMR. RESULTS: Controlling for race and sex, normal metabolizers (vs. reduced) selected a greater proportion of puffs from nicotine-containing cigarettes (vs. denicotinized) on the forced-choice task (p = .031). In confirmatory analyses, wGRS-based stratification (fast vs. slow metabolizers) produced similar findings. Additionally, wGRS-derived NMR, which correlated with actual NMR assessed in a subset of participants (n = 55), was positively associated with the proportion of puffs from nicotine-containing cigarettes controlling for race and sex (p = .015). None of the CYP2A6 indices were associated with tobacco cue-reactivity in minimally deprived smokers. CONCLUSIONS: Findings suggest increased nicotine reinforcement is exhibited by smokers with high CYP2A6 activity, which may contribute to heavier smoking and poorer cessation outcomes previously reported in faster metabolizers. IMPLICATIONS: CYP2A6 activity is a key determinant of smoking behavior and outcomes. Therefore, these findings support the targeting of CYP2A6 activity, either therapeutically or as a clinically relevant biomarker in a precision medicine approach, for tobacco use disorder treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.001 | 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 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".