Genetic and environmental influences on the ratio of 3′hydroxycotinine to cotinine in plasma and urine
Bibliographic record
Abstract
OBJECTIVES: The ratio of trans-3'hydroxycotinine/cotinine (3HC/COT) is a marker of CYP2A6 activity, an important determinant of nicotine metabolism. This analysis sought to conduct a combined genetic epidemiologic and pharmacogenetic investigation of the 3HC/COT ratio in plasma and urine. METHODS: One hundred and thirty-nine twin pairs [110 monozygotic and 29 dizygotic] underwent a 30-min infusion of stable isotope-labelled nicotine and its major metabolite, cotinine, followed by an 8-h in-hospital stay. Blood and urine samples were taken at regular intervals for analysis of nicotine, cotinine, and metabolites. DNA was genotyped to confirm zygosity and for variation in the gene for the primary nicotine metabolic enzyme, CYP2A6 (variants genotyped: *1B, *1 x 2, *2, *4, *9, *12). Univariate biometric analyses quantified genetic and environmental influences on each measure in the presence and absence of covariates, including measured CYP2A6 genotype. RESULTS: There was a substantial amount of variation in the free 3HC/COT ratio in plasma (6 h postinfusion) attributable to additive genetic influences (67.4%, 95% confidence interval=55.9-76.2%). The heritability estimate was reduced to 61.0 and 49.4%, respectively, after taking into account the effect of covariates and CYP2A6 genotype. In urine (collected over 8 h), the estimated amount of variation in the 3HC/COT ratio attributable to additive genetic influences was smaller (47.2%, 95% confidence interval=0-67.2%) and decreased to 44.6 and 42.0% after accounting for covariates and genotype. CONCLUSION: Additive genetic factors are prominent in determining variation in plasma 3HC/COT but less so in determining variation in urine 3HC/COT.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".