Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts.

The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.

Tobacco smoke exposure, the lower airways microbiome and outcomes of ventilated children.

BACKGROUND: Tobacco smoke exposure increases the risk and severity of lower respiratory tract infections in children, yet the mechanisms remain unclear. We hypothesized that tobacco smoke exposure would modify the lower airway microbiome. METHODS: Secondary analysis of a multicenter cohort of 362 children between ages 31 days and 18 years mechanically ventilated for >72 h. Tracheal aspirates from 298 patients, collected within 24 h of intubation, were evaluated via 16 S ribosomal RNA sequencing. Smoke exposure was determined by creatinine corrected urine cotinine levels ≥30 µg/g. RESULTS: Patients had a median age of 16 (IQR 568) months. The most common admission diagnosis was lower respiratory tract infection (53%). Seventy-four (20%) patients were smoke exposed and exhibited decreased richness and Shannon diversity. Smoke exposed children had higher relative abundances of Serratia spp., Moraxella spp., Haemophilus spp., and Staphylococcus aureus. Differences were most notable in patients with bacterial and viral respiratory infections. There were no differences in development of acute respiratory distress syndrome, days of mechanical ventilation, ventilator free days at 28 days, length of stay, or mortality. CONCLUSION: Among critically ill children requiring prolonged mechanical ventilation, tobacco smoke exposure is associated with decreased richness and Shannon diversity and change in microbial communities. IMPACT: Tobacco smoke exposure is associated with changes in the lower airways microbiome but is not associated with clinical outcomes among critically ill pediatric patients requiring prolonged mechanical ventilation. This study is among the first to evaluate the impact of tobacco smoke exposure on the lower airway microbiome in children. This research helps elucidate the relationship between tobacco smoke exposure and the lower airway microbiome and may provide a possible mechanism by which tobacco smoke exposure increases the risk for poor outcomes in children.

Quantitation of Ten Urinary Nicotine Metabolites, Including 4-Hydroxy-4-(3-pyridyl) Butanoic Acid, a Product of Nicotine 2'-Oxidation, and CYP2A6 Activity in Japanese Americans, Native Hawaiians, and Whites.

Smoking intensity varies across smokers and is influenced by individual variability in the metabolism of nicotine, the major addictive agent in tobacco. Therefore, lung cancer risk, which varies by racial ethnic group, is influenced by the primary catalyst of nicotine metabolism, cytochrome P450 2A6 (CYP2A6). In smokers, CYP2A6 catalyzes nicotine 5'-oxidation. In vitro, CYP2A6 also catalyzes, to a much lower extent, 2'-oxidation, which leads to the formation of 4-hydroxy-4-(3-pyridyl) butanoic acid (hydroxy acid). The urinary concentration of hydroxy acid has been quantified in only a few small studies of White smokers. To quantitatively assess the importance of nicotine 2'-oxidation in smokers, an LC-MS/MS-based method was developed for the analysis of nicotine and ten metabolites in urine. The concentrations of nicotine and these metabolites were measured in 303 smokers (99 Whites, 99 Native Hawaiians, and 105 Japanese Americans), and the relative metabolism of nicotine by four pathways was determined. Metabolism by these pathways was also compared across quartiles of CYP2A6 activity (measured as the plasma ratio of 3-hydroxycotinine to cotinine). As reported previously and consistent with their average CYP2A6 activity, nicotine 5'-oxidation was highest in Whites and lowest in Japanese Americans. Nicotine N-glucuronidation and N-oxidation increased with decreasing CYP2A6 activity. However, the relative urinary concentration of hydroxy acid (mean, 2.3%; 95% CI, 2.2-2.4%) did not vary by ethnic group or by CYP2A6 activity. In summary, CYP2A6 is not an important catalyst of nicotine 2'-oxidation in smokers, nor does nicotine 2'-oxidation compensate for decreased CYP2A6 activity.

The Impact of Reducing Nicotine Content on Adolescent Cigarette Smoking and Nicotine Exposure: Results From a Randomized Controlled Trial.

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.

Increased Levels of the Acrolein Metabolite 3-Hydroxypropyl Mercapturic Acid in the Urine of e-Cigarette Users.

Carcinogen and toxicant uptake by e-cigarette users have not been fully evaluated. In the study reported here, we recruited 30 e-cigarette users, 63 nonsmokers, and 33 cigarette smokers who gave monthly urine samples over a period of 4-6 months. Their product use status was confirmed by measurements of exhaled CO, urinary total nicotine equivalents, cyanoethyl mercapturic acid (CEMA), and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol. Urinary biomarkers of exposure to the carcinogens acrolein (3-hydroxypropyl mercapturic acid, 3-HPMA), benzene (S-phenyl mercapturic acid, SPMA), acrylonitrile (CEMA), and a combination of crotonaldehyde, methyl vinyl ketone, and methacrolein (3-hydroxy-1-methylpropyl mercapturic acid, HMPMA) were quantified at each visit. Data from subject visits with CEMA > 27 pmol/mL were excluded from the statistical analysis of the results because of possible unreported exposures to volatile combustion products such as secondhand cigarette smoke or marijuana smoke exposure; this left 22 e-cigarette users with 4 or more monthly visits and all 63 nonsmokers. Geometric mean levels of 3-HPMA (1249 versus 679.3 pmol/mL urine) were significantly higher (P = 0.003) in e-cigarette users than in nonsmokers, whereas levels of SPMA, CEMA, and HMPMA did not differ between these two groups. All analytes were significantly higher in cigarette smokers than in either e-cigarette users or nonsmokers. The results of this unique multimonth longitudinal study demonstrate consistent significantly higher uptake of the carcinogen acrolein in e-cigarette users versus nonsmokers, presenting a warning signal regarding e-cigarette use.

Association of Urinary Biomarkers of Smoking-Related Toxicants with Lung Cancer Incidence in Smokers: The Multiethnic Cohort Study.

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. See related commentary by Etemadi et al., p. 289.

Predicting nicotine metabolism across ancestries using genotypes.

BACKGROUND: There is a need to match characteristics of tobacco users with cessation treatments and risks of tobacco attributable diseases such as lung cancer. The rate in which the body metabolizes nicotine has proven an important predictor of these outcomes. Nicotine metabolism is primarily catalyzed by the enzyme cytochrone P450 (CYP2A6) and CYP2A6 activity can be measured as the ratio of two nicotine metabolites: trans-3'-hydroxycotinine to cotinine (NMR). Measurements of these metabolites are only possible in current tobacco users and vary by biofluid source, timing of collection, and protocols; unfortunately, this has limited their use in clinical practice. The NMR depends highly on genetic variation near CYP2A6 on chromosome 19 as well as ancestry, environmental, and other genetic factors. Thus, we aimed to develop prediction models of nicotine metabolism using genotypes and basic individual characteristics (age, gender, height, and weight). RESULTS: We identified four multiethnic studies with nicotine metabolites and DNA samples. We constructed a 263 marker panel from filtering genome-wide association scans of the NMR in each study. We then applied seven machine learning techniques to train models of nicotine metabolism on the largest and most ancestrally diverse dataset (N=2239). The models were then validated using the other three studies (total N=1415). Using cross-validation, we found the correlations between the observed and predicted NMR ranged from 0.69 to 0.97 depending on the model. When predictions were averaged in an ensemble model, the correlation was 0.81. The ensemble model generalizes well in the validation studies across ancestries, despite differences in the measurements of NMR between studies, with correlations of: 0.52 for African ancestry, 0.61 for Asian ancestry, and 0.46 for European ancestry. The most influential predictors of NMR identified in more than two models were rs56113850, rs11878604, and 21 other genetic variants near CYP2A6 as well as age and ancestry. CONCLUSIONS: We have developed an ensemble of seven models for predicting the NMR across ancestries from genotypes and age, gender and BMI. These models were validated using three datasets and associate with nicotine dosages. The knowledge of how an individual metabolizes nicotine could be used to help select the optimal path to reducing or quitting tobacco use, as well as, evaluating risks of tobacco use.

Quantitation of DNA Adducts Resulting from Acrolein Exposure and Lipid Peroxidation in Oral Cells of Cigarette Smokers from Three Racial/Ethnic Groups with Differing Risks for Lung Cancer.

The Multiethnic Cohort Study has demonstrated that the risk for lung cancer in cigarette smokers among three ethnic groups is highest in Native Hawaiians, intermediate in Whites, and lowest in Japanese Americans. We hypothesized that differences in levels of DNA adducts in oral cells of cigarette smokers would be related to these differing risks of lung cancer. Therefore, we used liquid chromatography-nanoelectrospray ionization-high resolution tandem mass spectrometry to quantify the acrolein-DNA adduct (8R/S)-3-(2'-deoxyribos-1'-yl)-5,6,7,8-tetrahydro-8-hydroxypyrimido[1,2-a]purine-10(3H)-one (γ-OH-Acr-dGuo, 1) and the lipid peroxidation-related DNA adduct 1,N6-etheno-dAdo (εdAdo, 2) in DNA obtained by oral rinse from 101 Native Hawaiians, 101 Whites, and 79 Japanese Americans. Levels of urinary biomarkers of nicotine, acrolein, acrylonitrile, and a mixture of crotonaldehyde, methyl vinyl ketone, and methacrolein were also quantified. Whites had significantly higher levels of γ-OH-Acr-dGuo than Japanese Americans and Native Hawaiians after adjusting for age and sex. There was no significant difference in levels of this DNA adduct between Japanese Americans and Native Hawaiians, which is not consistent with the high lung cancer risk of Native Hawaiians. Levels of εdAdo were modestly higher in Whites and Native Hawaiians than in Japanese Americans. The lower level of DNA adducts in the oral cells of Japanese American cigarette smokers than Whites is consistent with their lower risk for lung cancer. The higher levels of εdAdo, but not γ-OH-Acr-dGuo, in Native Hawaiian versus Japanese American cigarette smokers suggest that lipid peroxidation and related processes may be involved in their high risk for lung cancer, but further studies are required.

Assessing tobacco smoke exposure in pregnancy from self-report, urinary cotinine and NNAL: a validation study using the New Hampshire Birth Cohort Study.

OBJECTIVES: Accurate assessment of tobacco smoke exposure is key to evaluate its effects. We sought to validate and establish cut-offs for self-reported smoking and secondhand smoke (SHS) exposure during pregnancy using urinary cotinine and 4-(methylnitrosamino)-1-(-3-pyridyl)-1-butanol (NNAL) in a large contemporary prospective study from the USA, with lower smoking prevalence than has previously been evaluated. DESIGN: Prospective birth cohort. SETTING: Pregnancy clinics in New Hampshire and Vermont, USA. PARTICIPANTS: 1396 women enrolled in the New Hampshire Birth Cohort Study with self-reported smoking, urinary cotinine, NNAL and pregnancy outcomes. PRIMARY AND SECONDARY OUTCOME MEASURES: Cut-offs for urinary cotinine and NNAL concentrations were estimated from logistic regression models using Youden's method to predict SHS and active smoking. Cotinine and NNAL were each used as the exposure in separate multifactorial models for pregnancy outcomes. RESULTS: Self-reported maternal smoking was: 72% non-smokers, 5.7% ex-smokers, 6.4% SHS exposure, 6.2% currently smoked, 10% unreported. Cotinine and NNAL levels were low and highly intercorrelated (r=0.91). Geometric mean cotinine, NNAL were 0.99 ng/mL, 0.05 pmol/mL, respectively. Cotinine cut-offs for SHS, current smoking were 1.2 ng/mL and 1.8 ng/mL (area under curve (AUC) 95% CI: 0.52 (0.47 to 0.57), 0.90 (0.85 to 0.94)). NNAL cut-off for current smoking was 0.09 pmol/mL (AUC=0.82 (95% CI 0.77 to 0.87)). Using cotinine and NNAL cut-offs combined gave similar AUC to cotinine alone, 0.87 (95% CI 0.82 to 0.91). Cotinine and NNAL gave almost identical effect estimates when modelling pregnancy outcomes. CONCLUSIONS: In this population, we observed high concordance between self-complete questionnaire smoking data and urinary cotinine and NNAL. With respect to biomarkers, either cotinine or NNAL can be used as a measure of tobacco smoke exposure overall but only cotinine can be used to detect SHS.

A Randomized Trial of Nicotine versus No-nicotine E-cigarettes Among African American Smokers: Changes in Smoking and Tobacco Biomarkers.

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.

Multiethnic Prediction of Nicotine Biomarkers and Association With Nicotine Dependence.

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.

Biochemistry of nicotine metabolism and its relevance to lung cancer.

Nicotine is the key addictive constituent of tobacco. It is not a carcinogen, but it drives smoking and the continued exposure to the many carcinogens present in tobacco. The investigation into nicotine biotransformation has been ongoing for more than 60 years. The dominant pathway of nicotine metabolism in humans is the formation of cotinine, which occurs in two steps. The first step is cytochrome P450 (P450, CYP) 2A6-catalyzed 5'-oxidation to an iminium ion, and the second step is oxidation of the iminium ion to cotinine. The half-life of nicotine is longer in individuals with low P450 2A6 activity, and smokers with low activity often decrease either the intensity of their smoking or the number of cigarettes they use compared with those with "normal" activity. The effect of P450 2A6 activity on smoking may influence one's tobacco-related disease risk. This review provides an overview of nicotine metabolism and a summary of the use of nicotine metabolite biomarkers to define smoking dose. Some more recent findings, for example, the identification of uridine 5'-diphosphoglucuronosyltransferase 2B10 as the catalyst of nicotine N-glucuronidation, are discussed. We also describe epidemiology studies that establish the contribution of nicotine metabolism and CYP2A6 genotype to lung cancer risk, particularly with respect to specific racial/ethnic groups, such as those with Japanese, African, or European ancestry. We conclude that a model of nicotine metabolism and smoking dose could be combined with other lung cancer risk variables to more accurately identify former smokers at the highest risk of lung cancer and to intervene accordingly.

Ethnic Differences of Urinary Cadmium in Cigarette Smokers from the Multiethnic Cohort Study.

The Multiethnic Cohort Study (MEC) has demonstrated racial/ethnic differences in smoking-associated lung cancer risk. As part of the ongoing effort to characterize exposure to cigarette smoke constituents and better understand risk differences, we evaluated Cd exposure as it is a known lung carcinogen. We quantified urinary cadmium (Cd) by inductively coupled plasma mass spectrometry in a subset of 1956 current smokers from MEC. Ethnic-specific geometric means (GM) were compared adjusting for age at urine collection, sex, creatinine (natural log), education, and smoking (urinary total nicotine equivalents [TNE] and smoking duration). Self-reported questionnaire data, including occupation, were also considered. Latinos and Native Hawaiians had the highest GM urinary Cd (0.871 and 0.836 ng/mL, respectively) followed by Japanese Americans and African Americans (0.811 ng/mL and 0.807, respectively) and Whites (0.736 ng/mL). Patterns in race/ethnicity were consistent by sex such that females had the highest GM urinary Cd. When further adjusting for categorical occupational Cd exposure, racial/ethnic differences of Cd remained (p = 0.009). Findings suggest differences in urinary Cd among smokers across different racial/ethnic groups exist and highlight the importance in considering environmental sources of Cd exposure beyond smoking. These finding lay ground for future studies of individual characteristics that are associated with lower risk for cancer despite higher carcinogenic exposures.

Differences in exposure to toxic and/or carcinogenic volatile organic compounds between Black and White cigarette smokers.

OBJECTIVE: It is unclear why Black smokers in the United States have elevated risk of some tobacco-related diseases compared to White smokers. One possible causal mechanism is differential intake of tobacco toxicants, but results across studies are inconsistent. Thus, we examined racial differences in biomarkers of toxic volatile organic compounds (VOCs) present in tobacco smoke. METHOD: We analyzed baseline data collected from 182 Black and 184 White adult smokers who participated in a randomized clinical trial in 2013-2014 at 10 sites across the United States. We examined differences in urinary levels of ten VOC metabolites, total nicotine equivalents (TNE), and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), controlling for covariates such as cigarettes per day (CPD), as well as differences in VOCs per TNE to assess the extent to which tobacco exposure, and not metabolic factors, accounted for racial differences. RESULTS: Concentration of metabolites of acrolein, acrylonitrile, ethylene oxide, and methylating agents were significantly higher in Blacks compared to Whites when controlled for covariates. Other than the metabolite of methylating agents, VOCs per TNE did not differ between Blacks and Whites. Concentrations of TNE/CPD and VOCs/CPD were significantly higher in Blacks. Menthol did not contribute to racial differences in VOC levels. CONCLUSIONS: For a given level of CPD, Black smokers likely take in higher levels of acrolein, acrylonitrile, and ethylene oxide than White smokers. Our findings are consistent with Blacks taking in more nicotine and toxicants per cigarette smoked, which may explain their elevated disease risk relative to other racial groups.

Cigarette smoking enhances the metabolic activation of the polycyclic aromatic hydrocarbon phenanthrene in humans.

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.

Detecting participant noncompliance across multiple time points by modeling a longitudinal biomarker.

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.

UGT2B10 Genotype Influences Serum Cotinine Levels and Is a Primary Determinant of Higher Cotinine in African American Smokers.

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.

Urinary Cyanoethyl Mercapturic Acid, a Biomarker of the Smoke Toxicant Acrylonitrile, Clearly Distinguishes Smokers From Nonsmokers.

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.

Relationships between the Nicotine Metabolite Ratio and a Panel of Exposure and Effect Biomarkers: Findings from Two Studies of U.S. Commercial Cigarette Smokers.

BACKGROUND: We examined the nicotine metabolite ratio's (NMR) relationship with smoking intensity, nicotine dependence, and a broad array of biomarkers of exposure and biological effect in commercial cigarette smokers. METHODS: Secondary analysis was conducted on two cross-sectional samples of adult, daily smokers from Wave 1 (2013-2014) of the Population Assessment of Tobacco Use and Health (PATH) Study and baseline data from a 2014-2017 randomized clinical trial. Data were restricted to participants of non-Hispanic, white race. The lowest quartile of NMR (<0.26) in the nationally representative PATH Study was used to distinguish slow from normal/fast nicotine metabolizers. NMR was modeled continuously in secondary analysis. RESULTS: Compared with slow metabolizers, normal/fast metabolizers had greater cigarettes per day and higher levels of total nicotine equivalents, tobacco-specific nitrosamines, volatile organic componds, and polycyclic aromatic hydrocarbons. A novel finding was higher levels of inflammatory biomarkers among normal/fast metabolizers versus slow metabolizers. With NMR modeled as a continuous measure, the associations between NMR and biomarkers of inflammation were not significant. CONCLUSIONS: The results are suggestive that normal/fast nicotine metabolizers may be at increased risk for tobacco-related disease due to being heavier smokers, having higher exposure to numerous toxicants and carcinogens, and having higher levels of inflammation when compared with slow metabolizers. IMPACT: This is the first documentation that NMR is not only associated with smoking exposure but also biomarkers of biological effects that are integral in the development of tobacco-related disease. Results provide support for NMR as a biomarker for understanding a smoker's exposure and potential risk for tobacco-related disease.