Association of the Nicotine Metabolite Ratio and CHRNA5/CHRNA3 Polymorphisms With Smoking Rate Among Treatment-Seeking Smokers

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.

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Genome-Wide Association of the Laboratory-Based Nicotine Metabolite Ratio in Three Ancestries

Nicotine & Tobacco Research ◽

10.1093/ntr/ntw117 ◽

2016 ◽

Vol 18 (9) ◽

pp. 1837-1844 ◽

Cited By ~ 22

Author(s):

James W. Baurley ◽

Christopher K. Edlund ◽

Carissa I. Pardamean ◽

David V. Conti ◽

Ruth Krasnow ◽

...

Keyword(s):

Genome Wide Association ◽

Genome Wide ◽

Metabolite Ratio ◽

Nicotine Metabolite Ratio

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Opioid Use and Rate of Nicotine Metabolism Among Pregnant Smokers

Nicotine & Tobacco Research ◽

10.1093/ntr/ntz073 ◽

2019 ◽

Vol 22 (6) ◽

pp. 1046-1050 ◽

Cited By ~ 3

Author(s):

Cheryl Oncken ◽

Erin L Mead ◽

Ellen A Dornelas ◽

Chia-Ling Kuo ◽

Heather Z Sankey ◽

...

Keyword(s):

Smoking Cessation ◽

Clinical Significance ◽

Methadone Maintenance ◽

Nicotine Metabolism ◽

Opioid Use ◽

Pregnant Smokers ◽

Metabolite Ratio ◽

Race Ethnicity ◽

Opioid Users ◽

Nicotine Metabolite Ratio

Abstract Introduction Smokers who use opioids smoke more cigarettes per day (CPD) than non-opioid users, which could be due to the effects of opioids on nicotine metabolism. Moreover, nicotine metabolism increases during pregnancy, potentially making quitting more difficult for pregnant smokers. We examined nicotine metabolism and its association with opioid use (OU) and CPD in pregnant smokers. Methods We recruited pregnant women who smoked at least 5 CPD for a clinical trial of smoking cessation. Plasma nicotine metabolite ratio (NMR; trans-3′-hydroxycotinine (3HC)/cotinine)—a biomarker of nicotine metabolism—OU (involving methadone, buprenorphine, fentanyl, oxycodone, or tramadol), and CPD were assessed at baseline. We used linear regression to examine the associations between log-transformed NMR, OU, and CPD, adjusting for race/ethnicity and menthol smoking. Results Among 129 pregnant smokers, 25 (19%) were opioid users; most were maintained on methadone (n = 14). Compared to non-OU smokers, OU smokers had higher median CPD (10.0 vs. 7.0, p = .0007), serum 3HC (81.0 vs. 42.0 ng/mL, p = .0001), and NMR (0.63 vs. 0.43, p < .0001). In addition, methadone-maintained smokers had a higher median NMR than non-OU smokers (0.66 vs. 0.43, p = .0004). Adjusting for covariates, log-transformed NMR was greater in OU smokers (p = .012), specifically methadone-maintained smokers (p = .024), than non-OU smokers. Conclusions Our preliminary results show that OU is associated with a higher NMR in pregnant smokers. A larger study sample is needed to replicate this finding, examine potential mechanisms, and determine its clinical significance. Implications Among pregnant smokers, we observed that nicotine metabolism was significantly faster among opioid users—the majority of whom were on methadone maintenance—compared to nonusers, which could have implications for smoking cessation. Further studies are needed to replicate this finding, evaluate potential mechanisms, and determine its clinical significance.

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Stability of the Nicotine Metabolite Ratio in ad Libitum and Reducing Smokers

Cancer Epidemiology Biomarkers & Prevention ◽

10.1158/1055-9965.epi-08-0242 ◽

2008 ◽

Vol 17 (6) ◽

pp. 1396-1400 ◽

Cited By ~ 28

Author(s):

M. E. Mooney ◽

Z.-z. Li ◽

S. E. Murphy ◽

P. R. Pentel ◽

C. Le ◽

...

Keyword(s):

Metabolite Ratio ◽

Ad Libitum ◽

Nicotine Metabolite Ratio

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The effect of body mass index on smoking behaviour and nicotine metabolism: a Mendelian randomization study

10.1101/299834 ◽

2018 ◽

Cited By ~ 3

Author(s):

Amy E. Taylor ◽

Rebecca C. Richmond ◽

Teemu Palviainen ◽

Anu Loukola ◽

Jaakko Kaprio ◽

...

Keyword(s):

Body Mass Index ◽

Dna Methylation ◽

Body Mass ◽

Mendelian Randomization ◽

Causal Effect ◽

Smoking Initiation ◽

Smoking Behaviour ◽

Bidirectional Association ◽

Metabolite Ratio ◽

Nicotine Metabolite Ratio

AbstractBackgroundGiven clear evidence that smoking lowers weight, it is possible that individuals with higher body mass index (BMI) smoke in order to lose or maintain their weight.Methods and FindingsWe undertook Mendelian randomization analyses using 97 genetic variants associated with BMI. We performed two sample Mendelian randomization analyses of the effects of BMI on smoking behaviour in UK Biobank (N=335,921) and the Tobacco and Genetics consortium genomewide association study (GWAS) (N≤74,035) respectively, and two sample Mendelian randomization analyses of the effects of BMI on cotinine levels (N≤4,548) and nicotine metabolite ratio (N≤1,518) in published GWAS, and smoking-related DNA methylation in the Avon Longitudinal Study of Parents and Children (N≤846).In inverse variance weighted Mendelian randomization analysis, there was evidence that higher BMI was causally associated with smoking initiation (OR for ever vs never smoking per one SD increase in BMI: 1.19, 95% CI: 1.11 to 1.27) and smoking heaviness (1.45 additional cigarettes smoked per day per SD increase in BMI, 95% CI: 1.03 to 1.86), but little evidence for a causal effect with smoking cessation. Results were broadly similar using pleiotropy robust methods (MR-Egger, median and weighted mode regression). These results were supported by evidence for a causal effect of BMI on DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) locus. There was no strong evidence that BMI was causally associated with cotinine, but suggestive evidence for a causal negative association with the nicotine metabolite ratio.ConclusionsThere is a causal bidirectional association between BMI and smoking, but the relationship is likely to be complex due to opposing effects on behaviour and metabolism. It may be useful to consider BMI and smoking together when designing prevention strategies to minimise the effects of these risk factors on health outcomes.

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