Analyses of nicotine metabolism biomarker genetics stratified by sex in African and European Americans
Bibliographic record
Abstract
Nicotine is inactivated by the polymorphic CYP2A6 enzyme to cotinine and then to 3'hydroxycotinine. The Nicotine Metabolite Ratio (NMR; 3'hydroxycotinine/cotinine) is a heritable nicotine metabolism biomarker, varies with sex and ancestry, and influences smoking cessation and disease risk. We conducted sex-stratified genome-wide association studies of the NMR in European American (EA) and African American (AA) smokers (NCT01314001, NCT00666978). In EA females (n = 389) and males (n = 541), one significant (P < 5e-8) chromosome 19 locus was found (top variant: rs56113850, CYP2A6 (intronic), for C vs. T: females: beta = 0.67, P = 7.5e-22, 21.8% variation explained; males: beta = 0.75, P = 1.2e-37, 26.1% variation explained). In AA females (n = 503) and males (n = 352), the top variant was found on chromosome 19 but differed by sex (females: rs11878604, CYP2A6 (~ 16 kb 3'), for C vs. T: beta = - 0.71, P = 6.6e-26, 16.2% variation explained; males: rs3865454, CYP2A6 (~ 7 kb 3'), for G vs. T: beta = 0.64, P = 1.9e-19, 18.9% variation explained). In AA females, a significant region was found on chromosome 12 (top variant: rs12425845: P = 5.0e-9, TMEM132C (~ 1 Mb 5'), 6.1% variation explained) which was not significant in AA males. In AA males, significant regions were found on chromosomes 6 (top variant: rs9379805: P = 4.8e-9, SLC17A2 (~ 8 kb 5'), 8.0% variation explained) and 16 (top variant: rs77368288: P = 3.5e-8, ZNF469 (~ 92 kb 5'), 7.1% variation explained) which were not significant in AA females. Further investigation of these associations outside of chromosome 19 is required, as they did not replicate. Understanding how sex and ancestry influence nicotine metabolism genetics may improve personalized approaches for smoking cessation and risk prediction for tobacco-related diseases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".