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Background: After accounting for smoking history, lung cancer incidence is greater in African Americans than Whites. In the multiethnic cohort, total nicotine equivalents (TNE) are higher in African Americans than Whites at similar reported cigarettes per day. Greater toxicant uptake per cigarette may contribute to the greater lung cancer risk of African Americans. Methods: In a nested case-control lung cancer study within the Southern Community Cohort, smoking-related biomarkers were measured in 259 cases and 503 controls (40% White; 56% African American). TNE, the trans-3-hydroxycotinine/cotinine ratio, 4-(methylnitrosamino)-1-3-(pyridyl)-1-butanol (NNAL), mercapturic acid metabolites of volatile organic compounds, phenanthrene metabolites, cadmium (Cd), and (Z)-7-(1R,2R,3R,5S)-3,5-dihydroxy-2-[(E,3S)-3-hydroxyoct-1-enyl]cyclopenyl]hept-5-enoic acid were quantified in urine. Unconditional logistic regression was used to estimate the ORs and 95% confidence intervals (CI) for each biomarker and lung cancer risk. Results: TNE, NNAL, and Cd were higher in cases than controls (adjusted for age, race, sex, body mass index, and cigarettes per day). Among cases, these levels were higher in African Americans compared with Whites. After accounting for age, sex, body mass index, and pack-years, a one-SD increase in log-TNE (OR = 1.30; 95% CI, 1.10-1.54) and log-NNAL (OR = 1.27; 95% CI, 1.03-1.58 with TNE adjustment) was associated with lung cancer risk. In this study, in which NNAL concentration is relatively high, the association for log-TNE was attenuated after adjustment for log-NNAL. Conclusions: Smoking-related biomarkers provide additional information for lung cancer risk in smokers beyond smoking pack-years. [ABSTRACT FROM AUTHOR]

Introduction As the science base around the potential benefits of a reduced-nicotine standard for cigarettes grows, information on the potential effects on adolescent smokers is a high priority. The aim of this randomized trial was to test the influence of 3-week exposure to reduced nicotine cigarettes in a sample of adolescent daily smokers. Aims and Methods In this double-blind, two-arm, randomized controlled trial (NCT0258731), following a 1-week baseline, adolescent daily smokers not currently intending to quit (ages 15–19 years, n = 66 randomized) were urn randomized to use either very low nicotine content (VLNC; 0.4 mg/g; n = 33) or normal nicotine content (NNC, 15.8 mg/g; n = 33) research cigarettes for 3 weeks. Participants attended five study sessions at our clinical laboratory. The primary outcome was average total cigarettes smoked per day (CPD; including both study and non-study cigarettes) at week 3. Results Stepwise regression results demonstrated that compared with NNC cigarettes (n = 31), assignment to VLNC cigarettes (n = 29), was associated with 2.4 fewer CPD on average than NNC assignment (p <.05) week 3 when controlling for covariates (p <.01, Cohen's d = 0.52 n = 60 completed all procedures). VLNC cigarettes were also associated with lower levels of craving reduction than NNC cigarettes (Questionnaire on Smoking Urges Factor 2, p <.05). No group differences were found for secondary outcomes. Conclusions Adolescent participants assigned to VLNC use for 3 weeks smoked fewer total CPD relative to the NNC group. Overall, data suggest that a VLNC policy would reduce cigarette smoking in adolescents who smoke, but high rates of incomplete adherence suggest that youth may seek alternative sources of nicotine in this scenario. Implications The US Food and Drug Administration may enact a reduced-nicotine product standard that would affect all commercially available cigarettes. One important population affected by this policy would be adolescents who smoke. This study, the first clinical trial of VLNC cigarettes in adolescents, demonstrates that adolescents switched to VLNC cigarettes for 3 weeks reduced their CPD relative to the normal-nicotine cigarette control group, without leading to increased respiratory symptoms or increased withdrawal. Biomarkers indicated the use of other sources of nicotine, suggesting that such a policy will need to consider approaches to assist in transitioning away from smoking. [ABSTRACT FROM AUTHOR]

Background: While cigarette smoking is the leading cause of lung cancer, the majority of smokers do not develop the disease over their lifetime. The inter-individual differences in risk among smokers may in part be due to variations in exposure to smoking-related toxicants. Methods: Using data from a subcohort of 2,309 current smokers at the time of urine collection from the Multiethnic Cohort Study, we prospectively evaluated the association of ten urinary biomarkers of smoking-related toxicants [total nicotine equivalents (TNE), a ratio of total trans-3′-hydroxycotinine (3-HCOT)/cotinine (a phenotypic measure of CYP2A6 enzymatic activity), 4-(methylnitrosamino)-1-3-(pyridyl)-1-butanol (NNAL), S-phenylmercapturic acid (SPMA), 3-hydroxypropyl mercapturic acid (3-HPMA), phenanthrene tetraol (PheT), 3-hydroxyphenanthrene (PheOH), the ratio of PheT/PheOH, cadmium (Cd), and (Z)-7-(1R,2R,3R,5S)-3,5-dihydroxy-2-[(E,3S)-3-hydroxyoct-1-enyl]cyclopenyl]hept-5-enoic acid (8-iso-PGF2α)] with lung cancer risk (n = 140 incident lung cancer cases over an average of 13.4 years of follow-up). Lung cancer risk was estimated using Cox proportional hazards models. Results: After adjusting for decade of birth, sex, race/ethnicity, body mass index, self-reported pack-years, creatinine, and urinary TNE (a biomarker of internal smoking dose), a one SD increase in log total 3-HCOT/cotinine (HR, 1.33; 95% CI, 1.06-1.66), 3-HPMA (HR, 1.41; 95% CI, 1.07-1.85), and Cd (HR, 1.45; 95% CI, 1.18-1.79) were each associated with increased lung cancer risk. Conclusions: Our study demonstrates that urinary total 3-HCOT/cotinine, 3-HPMA, and Cd are positively associated with lung cancer risk. These findings warrant replication and consideration as potential biomarkers for smoking-related lung cancer risk. Impact: These biomarkers may provide additional information on lung cancer risk that is not captured by self-reported smoking history or TNE. [ABSTRACT FROM AUTHOR]

Introduction: The objective of this clinical trial was to compare the effects of e-cigarettes with and without nicotine on patterns of combustible cigarette use and biomarkers of exposure to tobacco toxicants among African American smokers.Methods: African American smokers (n = 234) were enrolled in a 12-week, single blind, randomized controlled trial and assigned to ad lib use of nicotine e-cigarettes with or without menthol (2.4% nicotine [equivalent to combustible cigarettes], n = 118), or no-nicotine e-cigarettes (n = 116) for 6 weeks. Surveys were administered at baseline, 2, 6, and 12 weeks, and urinary biomarkers 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and total nicotine equivalents (TNE) were assessed at baseline and 6 weeks.Results: Participants smoked an average of 11.4 cigarettes per day (CPD) and 88% used menthol cigarettes at baseline. At Week 6, the nicotine group reported using e-cigarettes 9.1 times per day compared to 11.4 times in the no-nicotine group (p = 0.42). Combustible cigarette smoking decreased 3.0 CPD in the nicotine group compared to 2.7 CPD in the no-nicotine group (p = 0.74). Neither TNE nor NNAL changed significantly between baseline and Week 6. There were no differences in nicotine withdrawal symptoms between treatment groups. Smoking reduction persisted in both groups at Week 12.Conclusions: Contrary to our hypotheses, nicotine e-cigarettes did not significantly reduce the use of combustible cigarettes compared to no-nicotine e-cigarettes in this cohort of African American smokers. Findings suggest e-cigarettes are modestly associated with the decreased use of combustible cigarettes among non-treatment seeking smokers, regardless of nicotine content, but without a reduction in tobacco toxicants.Implications: Although e-cigarettes have the potential to reduce harm if substituted for combusted cigarettes (or if they promoted cessation) because of lower levels of tobacco toxicants, this study suggests ad lib use of e-cigarettes among African American smokers, with or without nicotine, results in modest smoking reduction but does not change toxicant exposure in a cohort where smoking cessation or reduction is not the goal. These data suggest that testing future harm reduction interventions using e-cigarettes should include more specific behavioral change coaching, including substituting for or completely stopping combusted cigarettes.Clinical Trial Registration: ClinicalTrials.gov - NCT03084315. [ABSTRACT FROM AUTHOR]

Introduction: The nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers.Aims and Methods: We screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, 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 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups.Results: The genomic regions with the most selected and included 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 included. 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.Conclusions: Nicotine metabolites, genome-wide data, and statistical learning approaches developed novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations helped define genetically influenced components of nicotine dependence.Implications: We demonstrate development of robust models and multiethnic prediction of the uNMR and TNE using statistical and machine learning approaches. Variants included in trained models for nicotine 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 Fagerström Test for Nicotine Dependence items supports 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. [ABSTRACT FROM AUTHOR]

Exposure to environmental tobacco smoke may increase a person's risk of lung cancer. Inhaling sidestream smoke, the smoke from the smoldering end of a cigarette, can cause people to metabolize a known lung carcinogen. Five nonsmoking men were exposed to sidestream cigarette smoke in two identical controlled experiments. Before and after exposure to the smoke, their urine was analyzed for two metabolites of a carcinogen called NNK. NNK has been shown to cause a type of lung cancer, adenocarcinoma, in rodents. The urine content of the NNK metabolites was an average of 10 times higher after exposure to sidestream smoke. The urine was also analyzed for cotinine, a nicotine metabolite. The cotinine levels after exposure were an average of 19 times higher. The amount of environmental tobacco smoke to which these men were exposed was similar to levels in a smoke-filled bar.

Although it is well established that human cytochrome P450 1 family enzymes are induced by cigarette smoking through activation of the Ah receptor, it is not known whether this leads to increased metabolic activation or detoxification of carcinogenic polycyclic aromatic hydrocarbons (PAH), which are present in cigarette smoke and the general environment. We gave oral doses of deuterated phenanthrene ([D10]Phe), a non-carcinogenic surrogate of carcinogenic PAH such as benzo[ a ]pyrene, to smokers (N = 170, 1 or 10 μg doses) and non-smokers (N = 57, 1 μg dose). Bioactivation products (dihydrodiol and tetraol) and detoxification products (phenols) of [D10]Phe were determined in 6-h urine to obtain a comprehensive metabolic profile. Cigarette smoking increased the bioactivation of [D10]Phe and decreased its detoxification resulting in significantly different metabolic patterns between smokers and non-smokers (P < 0.01), consistent with increased cancer risk in smokers. The Phe bioactivation ratios ([D10]PheT/total [D9]OHPhe) were significantly higher (2.3 (P < 0.01) to 4.8 (P < 0.001) fold) in smokers than non-smokers. With solid human in vivo evidence, our results for the first time demonstrate that cigarette smoking enhances the metabolic activation of Phe, structurally representative of carcinogenic PAH, in humans, strongly supporting their causal role in cancers caused by smoking. The results suggest potential new methods for identifying smokers who could be at particularly high risk for cancer. [ABSTRACT FROM AUTHOR]

Introduction: Participant noncompliance, in which participants do not follow their assigned treatment protocol, has long complicated the interpretation of randomized clinical trials. No gold standard has been identified for detecting noncompliance, but in some trials participants' biomarkers can provide objective information that suggests exposure to non-study treatments. However, existing methods are limited to retrospectively detecting noncompliance at a single time point based on a single biomarker measurement. We propose a novel method that can leverage participants' full biomarker history to detect noncompliance across multiple time points. Conditional on longitudinal biomarker data, our method can estimate the probability of compliance at (1) a single time point of the trial, (2) all time points, and (3) a future time point. Methods: Across time points, we model the biomarker as a mixture density with (latent) components corresponding to longitudinal patterns of compliance. To estimate the mixture density, we fit mixed effects models for both compliance and the biomarker. We use the mixture density to derive compliance probabilities that condition on the longitudinal biomarker data. We evaluate our compliance probabilities by simulation and apply them to a trial in which current smokers were asked to only smoke low nicotine study cigarettes (Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2). In the simulation, we investigated three different effects of compliance on the biomarker, as well as the effect of misspecification of the covariance structures. We compared probability estimators (1) and (2) to those that ignore the longitudinal correlation in the data according to area under the receiver operating characteristic curve. We evaluated estimator (3) by plotting its calibration lines. For Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2, we compared estimators (1) and (3) to a probability estimator of compliance at the last time point that ignores the longitudinal correlation. Results: In the simulation, for both compliance at the last time point and at all time points, conditioning on the longitudinal biomarker data uniformly raised area under the receiver operating characteristic curve across all three compliance effect scenarios. The gains in area under the receiver operating characteristic curve were smaller under misspecification. The calibration lines for the prediction of compliance closely followed 45°, though with additional variability under misspecification. For compliance at the last time point of Center for the Evaluation of Nicotine in Cigarettes Project 1 Study 2, conditioning on participants' full biomarker history boosted area under the receiver operating characteristic curve by three percentage points. The prediction probabilities somewhat accurately approximated the non-longitudinal compliance probabilities. Discussion: Compared to existing methods that only use a single biomarker measurement, our method can account for the longitudinal correlation in the biomarker and compliance to more accurately identify noncompliant participants. Our method can also use participants' biomarker history to predict compliance at a future time point. [ABSTRACT FROM AUTHOR]

Many human cancers are caused by environmental and lifestyle factors. Biomarkers of exposure and risk developed by our team have provided critical data on internal exposure to toxic and genotoxic chemicals and their connection to cancer in humans. This review highlights our research using biomarkers to identify key factors influencing cancer risk as well as their application to assess the effectiveness of exposure intervention and chemoprevention protocols. The use of these biomarkers to understand individual susceptibility to the harmful effects of tobacco products is a powerful example of the value of this type of research and has provided key data confirming the link between tobacco smoke exposure and cancer risk. Furthermore, this information has led to policy changes that have reduced tobacco use and consequently, the tobacco-related cancer burden. Recent technological advances in mass spectrometry led to the ability to detect DNA damage in human tissues as well as the development of adductomic approaches. These new methods allowed for the detection of DNA adducts in tissues from patients with cancer, providing key evidence that exposure to carcinogens leads to DNA damage in the target tissue. These advances will provide valuable insights into the etiologic causes of cancer that are not tobacco-related. [ABSTRACT FROM AUTHOR]

Introduction: Cyanoethyl mercapturic acid (CEMA) is a urinary metabolite of acrylonitrile, a toxicant found in substantial quantities in cigarette smoke, but not in non-combusted products such as e-cigarettes or smokeless tobacco and rarely in the diet or in the general human environment. Thus, we hypothesized that CEMA is an excellent biomarker of combusted tobacco product use.Aims and Methods: We tested this hypothesis by analyzing CEMA in the urine of 1259 cigarette smokers (urinary cotinine ≥25 ng/mL) and 1191 nonsmokers. The analyses of CEMA and cotinine were performed by validated liquid chromatography-tandem mass spectrometry methods. Logistic regression was fit for log-transformed CEMA to construct the receiver operating characteristic curve.Results: We found that a CEMA cutpoint of 27 pmol/mL urine differentiated cigarette smokers from nonsmokers with sensitivity and specificity greater than 99%. The use of different cotinine cutpoints to define smokers (10-30 ng/mL) had little effect on the results.Conclusions: CEMA is a highly reliable urinary biomarker to identify users of combusted tobacco products such as cigarettes as opposed to users of non-combusted products, medicinal nicotine, or nonusers of tobacco products.Implications: CEMA can be used to distinguish users of combusted tobacco products from non-combusted products such as e-cigarettes, smokeless tobacco, and medicinal nicotine. Levels of CEMA in the urine of people who use these non-combusted products are extremely low, in contrast to cotinine. [ABSTRACT FROM AUTHOR]

Background: Cotinine is the most widely used biomarker of tobacco exposure. At similar smoking levels, African Americans have higher serum cotinine than Whites. UGT2B10-catalyzed cotinine glucuronidation impacts these levels, and African Americans often have low UGT2B10 activity due to a high prevalence of a UGT2B10 splice variant (rs2942857). Methods: Two UGT2B10 SNPs (rs6175900 and rs2942857) were genotyped in 289 African Americans and 627 White smokers. Each smoker was assigned a genetic score of 0, 1, or 2 based on the number of variant alleles. Total nicotine equivalents (TNE), the sum of nicotine and six metabolites, and serum cotinine and 3'-hydroxycotinine were quantified. The contribution of UGT2B10 genetic score to cotinine concentration was determined. Results: Serum cotinine was significantly higher in smokers with UGT2B10 genetic scores of 2 versus 0 (327 ng/mL vs. 221 ng/mL; P < 0.001); TNEs were not different. In a linear regression model adjusted for age, gender, cigarettes per day, TNE, race, and CYP2A6 activity, geometric mean cotinine increased 43% between genetic score 2 versus 0 (P < 0.001). A 0.1 increase in the CYP2A6 activity ratio, 3'-hydroxycotinine/cotinine, resulted in a 6% decrease in cotinine. After adjustment for UGT2B10 genotype and the other covariants, there was no significant difference in serum cotinine by race. Conclusions: UGT2B10 genotype is a major contributor to cotinine levels and explains the majority of high serum cotinine in African American smokers. Impact: Cotinine levels in smokers may greatly overestimate tobacco exposure and potentially misinform our understanding of ethnic/racial difference in tobacco-related disease if UGT2B10 genotype is not taken into account. [ABSTRACT FROM AUTHOR]