Multiethnic Prediction of Nicotine Biomarkers and Association with Nicotine Dependence

ABSTRACTBackgroundThe nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers will extend biomarker studies to cohorts without measured biomarkers and enable tobacco-related behavioral and exposure research.MethodsWe screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants and age, ethnicity and sex, and cigarettes per day (CPD) (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2,239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles, and evaluated external validity using behavioral outcomes in 1,864 treatment-seeking smokers in two ethnic groups.ResultsThe genomic regions with the most selected and trained variants for measured biomarkers were chr19q13.2 (uNMR, without and with CPD) and chr15q25.1 and chr10q25.3 (TNE, without and with CPD). We observed ensemble correlations between measured and predicted biomarker values for the uNMR and TNE without (with CPD) of 0.67 (0.68), and 0.65 (0.72) in the training sample. We observed inconsistency in penalized regression models of TNE (with CPD) with fewer variants at chr15q25.1 selected and trained. In treatment-seeking smokers, predicted uNMR (without CPD) was significantly associated with CPD, and predicted TNE (without CPD) with CPD, Time-To-First-Cigarette, and Fagerström total score.ConclusionsNicotine metabolites, genome-wide data and statistical learning approaches develop novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations help define genetically-influenced components of nicotine dependence.IMPLICATIONSWe demonstrate development of robust models and multiethnic prediction of the urinary nicotine metabolite ratio and total nicotine equivalents using statistical and machine learning approaches. Trained variants in models for both biomarkers include top-ranked variants in multiethnic genome-wide studies of smoking behavior, nicotine metabolites and related disease. Association of the two predicted nicotine biomarkers with Fagerstr□m Test for Nicotine Dependence items support models of nicotine biomarkers as predictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data.

Relationship Between Nicotine Dependence Scores and Nicotine, Cotinine, 3′-Hydroxycotinine and Nicotine Metabolite Ratio in Chinese Male Smokers

Summary Smoking is mainly sustained by nicotine dependence (ND), which varies across ethnic groups principally due to genetic as well as environmental factors. The Fagerström Test for Nicotine Dependence (FTND) and biomarkers of tobacco exposure are two important approaches to assess ND. However, the relationship between ND and FTND of Chinese smokers has not been studied. The aim of this study was to assess the relationship between FTND scores and nicotine, cotinine, 3′-hydroxycotinine (3HC) and nicotine metabolite ratio (NMR, the concentration ratio of 3HC to cotinine) in Chinese smokers. FTND was carried out and general characteristics were collected using a self-administered smoking questionnaire with 289 smokers. Nicotine, cotinine and 3HC in urine were simultaneously determined by liquid chromatography–mass spectrometry/mass spectrometry (LC-MS/MS). The concentrations of nicotine, cotinine and 3HC in the urine of smokers with a high FTND score were higher than in the urine of those with a low FTND score. There were significant correlations between urinary biomarker and FTND scores. Except for FTND item 2 (difficulty to refrain), the other items showed significant associations with the urinary biomarkers. No relationship was found between the nicotine metabolite ratio (NMR, 3′-hydroxycotinine/cotinine) and FTND scores or general characteristics of the participants. In conclusion, biomarkers of tobacco exposure levels are significantly associated with FTND scores. However, FTND Item 2 and NMR were not found to be associated with nicotine dependence in Chinese smokers.

Pregnant Smokers Receiving Opioid Agonist Therapy Have an Elevated Nicotine Metabolite Ratio: A Replication Study

Introduction Pregnant women exposed chronically to opioids smoked more cigarettes per day (CPD) and had a higher nicotine metabolite ratio (NMR), 3-hydroxycotinine/cotinine, a biomarker of nicotine metabolism and clearance, than those not receiving opioids. We examined CPD and NMR in a group of pregnant smokers, a quarter of whom were receiving opioid agonist therapy (OAT). Aims and Methods Pregnant smokers recruited to participate in a placebo-controlled trial of bupropion for smoking cessation provided a blood sample for measurement of NMR. Results Half (52.4%) of the 124 women with NMR data were African American. OAT-treated women (n = 34, 27.4%; 27 receiving methadone and 7 buprenorphine) were more likely to be white (79% vs. 30%, p < .001) and to have a lower mean PHQ-9 total score (2.91 [SD = 2.83] vs. 4.83 [SD = 3.82], p = .007). OAT-treated women reported smoking more CPD (9.50 [SD = 5.26] vs. 7.20 [SD = 3.65], p = .005) and had higher NMR (0.78 [SD = 0.36] vs. 0.56 [SD = 0.25], p = .001) than the non-OAT-treated group. In a linear regression analysis adjusting for race, depression severity, and CPD, NMR was greater in the OAT group (p = .025), among whom the daily methadone-equivalent dosage correlated with NMR (Spearman’s ρ = 0.49, p = .003). Conclusions Consistent with the findings of Oncken et al. (2019), we found that OAT smokers smoked more and had higher NMR than non-OAT smokers. As higher NMR is associated with a reduced likelihood of smoking cessation, the effects on NMR of both pregnancy and OAT could contribute to a lower smoking cessation rate in pregnant smokers receiving chronic opioid therapy. Implications We replicated the finding that the NMR is significantly greater among pregnant smokers receiving OAT than those not receiving this treatment for opioid use disorder. Furthermore, we found that the dosage of the OAT was significantly associated with the NMR level. These findings may contribute to a poorer response to smoking cessation treatment in pregnant women treated with OAT, particularly those receiving high-dose therapy, and raise the question of whether novel approaches are needed to treat smoking in this subgroup of pregnant smokers.

Associations Between Nicotine Metabolite Ratio and Gender With Transitions in Cigarette Smoking Status and E-Cigarette Use: Findings Across Waves 1 and 2 of the Population Assessment of Tobacco and Health (PATH) Study

Introduction Nicotine metabolite ratio (NMR), the ratio of trans 3′-hydroxycotinine to cotinine, is a biomarker of nicotine metabolism. Discrepant findings among clinical trials and population-based studies warrant replication on whether higher NMR, or faster nicotine metabolism, is associated with quitting cigarette smoking. Associations of NMR and e-cigarette use are largely unknown, as well as the relationship between NMR and gender on quitting cigarette smoking or e-cigarette use. Methods The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative, longitudinal cohort study assessing tobacco use in the US population. In the current study, the PATH (waves 1 and 2; adult interviews) was used to evaluate longitudinal predictions in relationships among NMR and gender and their association with transitions (quit vs. current stable) in cigarette smoking status and e-cigarette use status across waves 1 and 2 of the PATH study. Results NMR and gender were not significantly associated with quit behavior for combustible cigarettes. Regarding e-cigarettes, a significant two-way interaction demonstrated that women with higher NMR were less likely to quit e-cigarette use compared to women with lower NMR (odds ratio [OR] = 0.10, 95% confidence interval [CI] = 0.02–0.57; p = .01). Conclusions Findings identify that women with faster nicotine metabolism were 10 times less likely to quit e-cigarettes compared to women with slower nicotine metabolism across waves 1 and 2 of the PATH study. Results suggest that NMR may be used as a biomarker for transitions in e-cigarette quit behavior for women. Implications Findings identify that women with faster nicotine metabolism were 10 times less likely to quit e-cigarettes compared to women with slower nicotine metabolism. Results suggest that NMR may be used as a biomarker for transitions in e-cigarette quit behavior for women. Establishing parameters for NMR collection and for the use of NMR as a biomarker for cigarette smoking behavior and e-cigarette use is an important next step, and may have implications for early intervention and treatment for cessation.