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Introduction This study examined user behavior, e-cigarette dependence, and device characteristics on nicotine intake among users of pod-mod e-cigarettes. Aims and Methods In 2019–2020, people who use pod-mods in the San Francisco Bay Area completed questionnaires and provided a urine sample for analysis of total nicotine equivalents (TNE). The relationship between TNE and e-cigarette use, e-cigarette brands, e-liquid nicotine strength, e-cigarette dependence, and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), as a measure of combustible cigarette exposure, were examined. Results Of 100 participants (64% male, 71% in the 18–34 age group, 45% white), 53 used JUUL primarily, 12 used Puff Bar primarily, and 35 used other brands, including Suorin; 48 participants reported current cigarette smoking. Participants most often reported use of e-liquid with 4.5%–6.0% nicotine (68%), fruit (35%), tobacco (28%), and menthol or mint flavors (26%), used e-cigarettes on 25.5 (SD = 6.3) days a month, 10.2 (SD = 14.2) times a day, and 40% used 1–2 pods/cartridges per week. In bivariate analysis, urinary TNE was higher with greater frequency (days used) and intensity (number of pods used) of e-cigarette use, e-cigarette dependence, and combustible cigarette use. In multivariable analysis, days of e-cigarette use in the last 30 days, number of pods used per week, and NNAL levels were significantly associated with TNE. There was no significant impact of e-liquid nicotine strength on TNE. Conclusions Nicotine intake among people who used pod-mod e-cigarettes increased with e-cigarette consumption and e-cigarette dependence, but not with e-liquid nicotine strength. Our findings may inform whether FDA adopts a nicotine standard for e-cigarettes. Implications The study examined how device and user characteristics influence nicotine intake among pod-mod e-cigarette users. Nicotine intake increased with frequency (days of e-cigarette use in past 30 days) intensity of use (number of pods used per day) and e-cigarette dependence but not with the flavor or nicotine concentration of the e-liquids. Regulation of nicotine concentration of e-liquids is unlikely to influence nicotine exposure among adult experienced pod-mod users.

ObjectiveIn an urban adolescent population, we evaluated sources of exposure to secondhand smoke exposure (SHS), examined differences in exposure by race/ethnicity, age and sex, and determined the relationship between exposure source(s) and the biomarkers cotinine and NNAL.MethodsParticipants were recruited from a public hospital-based outpatient clinic in San Francisco, CA, USA.ResultsOf a sample of N=298 adolescents screened, 235 were biologically confirmed to be exposed to tobacco smoke. Of those, N=16 were active smokers and N=219 were exposed to SHS; 91 (39%) were heavily SHS exposed (median cotinine=0.76 ng/mL) and 128 (54%) had light SHS exposure (median cotinine=0.11 ng/mL). Within those SHS exposed, the most common source of exposure was in a public area. No significant racial/ethnic differences were found, although African American adolescents were more likely to live in a home that allowed smoking. Older adolescents were more likely to be exposed across several difference sources, and females more likely to be exposed in a car and in public areas. Past 7-day exposure in the home, in a car, and current blunt use were significantly related to biomarkers of exposure.ConclusionsUrban adolescents are exposed to SHS across a variety of sources. Although exposure in a public area is most common, exposure in the home and in cars significantly influences tobacco biomarker levels. Interventions to reduce exposure would have the greatest impact in this population if they focused on reducing exposure in the home and in cars. History of blunt use is a strong determinant of tobacco exposure.

Background Nicotine, the pharmacologically active substance in both tobacco and many electronic cigarette (e-cigarette) liquids, is responsible for the addiction that sustains cigarette smoking. With 8 million deaths worldwide annually, smoking remains one of the major causes of disability and premature death. However, nicotine also plays an important role in smoking cessation strategies. Objectives The aim of this study was to develop a comprehensive, whole-body, physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model of nicotine and its major metabolite cotinine, covering various routes of nicotine administration, and to simulate nicotine brain tissue concentrations after the use of combustible cigarettes, e-cigarettes, nicotine gums, and nicotine patches. Methods A parent–metabolite, PBPK/PD model of nicotine for a non-smoking and a smoking population was developed using 91 plasma and brain tissue concentration–time profiles and 11 heart rate profiles. Among others, cytochrome P450 (CYP) 2A6 and 2B6 enzymes were implemented, including kinetics for CYP2A6 poor metabolizers. Results The model is able to precisely describe and predict both nicotine plasma and brain tissue concentrations, cotinine plasma concentrations, and heart rate profiles. 100% of the predicted area under the concentration–time curve (AUC) and maximum concentration (Cmax) values meet the twofold acceptance criterion with overall geometric mean fold errors of 1.12 and 1.15, respectively. The administration of combustible cigarettes, e-cigarettes, nicotine patches, and nicotine gums was successfully implemented in the model and used to identify differences in steady-state nicotine brain tissue concentration patterns. Conclusions Our PBPK/PD model may be helpful in further investigations of nicotine dependence and smoking cessation strategies. As the model represents the first nicotine PBPK/PD model predicting nicotine concentration and heart rate profiles after the use of e-cigarettes, it could also contribute to a better understanding of the recent increase in youth e-cigarette use. Electronic supplementary material The online version of this article (10.1007/s40262-020-00880-4) contains supplementary material, which is available to authorized users.

Background As of March 2019, JUUL electronic cigarettes are the most popular e-cigarette on the U.S. market, but little is known of nicotine exposure and dependence on JUUL and user experience. Methods JUUL users participated in a community-based study involving questionnaires, saliva collection and a qualitative interview. Results Fifteen participants were enrolled (80% male, 53% White) and had an average age of 29.8 (standard deviation = 10) years. Daily exposure to nicotine assessed via salivary cotinine was similar to those reported for other e-cigarette and tobacco cigarette users in general. The majority reported low to moderate nicotine dependence. Qualitative interview themes included: the importance of social networks in adoption and use of the product; device features such as small size and vapor cloud reinforced product use; the product provided satisfaction compared to a tobacco cigarette; and a perceived sense of addiction to the product. Conclusions JUUL e-cigarettes expose users to levels of nicotine similar to other e-cigarettes but may be more satisfying due to unique device features. JUUL may be quite acceptable to tobacco cigarette smokers who are seeking to quit. However, it holds addictive potential and can reinforce long-term nicotine use.

ObjectiveWaterpipe tobacco (WPT; hookah) use is common in pregnant and reproductive-age women. Sweet flavours contribute to the appeal of WPT and are a potential regulatory target. This study investigated use, preferences and perceptions of WPT flavours in pregnant WPT users, and the impact of flavour preferences on preconception/prenatal WPT use and exposure biomarkers.Methods58 pregnant WPT users (mean age=27 years) completed a detailed interview regarding their WPT flavours use, preferences and perceptions. Biomarkers of nicotine and carcinogen exposure (eg, cotinine, benzene, butadiene) were also collected.Results55% of participants were dual/poly WPT users (ie, reported use of one or more other tobacco products in addition to WPT). Pregnant WPT users reported nearly exclusive use of flavoured WPT, with greater use of menthol/mint (68%) followed by fruit flavours (48%) (pConclusionsThis is the first study of WPT flavour use, preferences and perceptions in pregnant women. Use of and preference for menthol/mint and fruit WPT flavours in this vulnerable population could be considered in regulating WPT flavours to protect the health of women and children.

Introduction Accurate measurement of nicotine exposure from cigarette smoke is important in studying disease risk and level of dependence. Urine total nicotine equivalents, the molar sum of nicotine and six metabolites (NE7), accounts for more than 90% of a nicotine dose and is independent of individual metabolic differences. However, measuring NE7 is technically difficult and costly. We compared NE7, the gold standard of nicotine intake, with different combinations of fewer urinary nicotine metabolites. We also examined the impact of individual differences in nicotine metabolic rate, sex, and race on strength of association with NE7. Methods Urine samples from 796 daily smokers, who participated across five clinical studies, were assayed for nicotine and/or metabolites. Associations with NE7 were assessed by regression and Bland–Altman analyses. Results Overall, the molar sum of urine [cotinine + 3′-hydroxycotinine (3HC)] (NE2) and [nicotine + cotinine + 3HC] (NE3) were strongly correlated with NE7 (r = .97 and .99, respectively). However, in slow metabolizers NE2 was less predictive of NE7, whereas NE3 was equally robust. Urine total cotinine was also strongly correlated with NE7 (r = .87). Conclusions Urine NE3 is a robust biomarker of daily nicotine intake, independently of individual metabolic differences, whereas NE2 is less accurate in slow metabolizers. Our findings inform the selection of more rigorous and cost-effective measures to assess nicotine exposure in tobacco research studies. Implications The molar sum of urine total nicotine, cotinine and 3HC (NE3) is a robust biomarker of daily nicotine intake, independently of individual metabolic differences, and performs as well as measuring seven nicotine metabolites (NE7). The sum of cotinine and 3HC (NE2) is less accurate in slow metabolizers. Our findings inform the selection of more rigorous and cost-effective measures to assess nicotine exposure in tobacco research studies.

ObjectiveIt 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.MethodWe 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.ResultsConcentration 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.ConclusionsFor 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.

Electronic nicotine delivery systems (ENDS) such as e-cigarettes and heated tobacco products are novel battery-operated devices that deliver nicotine without combustion of tobacco. Because cigarette smoking is sustained by nicotine addiction and the toxic combustion products are mainly responsible for the harmful effects of smoking, ENDS could be used to promote smoking cessation while exposing users to lower levels of toxicants compared with conventional cigarettes. The currently available evidence from clinical and observational studies indicates a potential role of e-cigarettes as smoking cessation aids, although many continue to use e-cigarettes long after quitting smoking. Nicotine and toxicant delivery vary considerably by device and depend on the characteristics of the e-liquid formulation. Because smokers tend to titrate their nicotine intake to maintain their desired pharmacologic effects, device and liquid characteristics need to be considered when using ENDS as an aid to quit smoking. Factors potentially limiting their use are the currently still unknown long-term safety of these products and concerns regarding widespread use among youth. Implications of clinical pharmacology data on ENDS for the cigarette endgame and regulation by the U.S. Food and Drug administration are discussed.

Background Cardiovascular safety is an important consideration regarding the benefits versus risks of electronic cigarette use (EC) for public health. The single‐use cardiovascular effects of EC have been well studied but may not reflect effects of ad libitum use throughout the day. We aimed to compare the circadian hemodynamic effects as well as 24‐hour biomarkers of oxidative stress, and platelet aggregation and inflammation, with ad libitum cigarette smoking (CS) versus EC versus no tobacco product use. Methods and Results Thirty‐six healthy dual CS and EC users participated in a crossover study in a confined research setting. Circadian heart rate, blood pressure and plasma nicotine levels, 24‐hour urinary catecholamines, 8‐isoprostane and 11‐dehydro‐thromboxane B2, and plasma interleukin‐6 and interleukin‐8 were compared in CS, EC, and no nicotine conditions. Over 24 hours, and during daytime, heart rate and blood pressure were higher in CS and EC compared with no tobacco product conditions ( P P Conclusions CS and EC had similar 24‐hour patterns of hemodynamic effects compared with no tobacco product, with a higher average heart rate with CS versus EC, and similar effects on biomarkers of inflammation. EC may pose some cardiovascular risk, particularly to smokers with underlying cardiovascular disease, but may also provide a harm reduction opportunity for smokers willing to switch entirely to EC. Registration URL: https://www.clinicaltrials.gov ; Unique Identifier: NCT02470754.

Highlights • No study estimated the impact of e-cig and cig prices on e-cig and cig sales in CA. • Cig prices were positively associated with reusable e-cig sales. • Reusable e-cig prices were positively associated with disposable e-cig sales., Although numerous studies have examined the impact of cigarette prices on cigarette demand, research examining the impact of e-cigarette and cigarette prices on e-cigarette demand is relatively limited. This study estimated the impact of e-cigarette and cigarette prices on e-cigarette and cigarette sales in California. Using the 2012–2017 Nielsen Retail Scanner Data, we constructed e-cigarette prices, cigarette prices, and per capita e-cigarette and cigarette sales by year, quarter, and Nielsen scantrack market in California. E-cigarettes were categorized as disposable or reusable. Separate fixed-effects models estimated the impact of e-cigarette and cigarette prices on per capita disposable e-cigarette, reusable e-cigarette, and cigarette sales controlling for year, quarter, market, and smoke-free air law coverage. Average prices were $5.86 per pack of 20 cigarettes, $9.80 per disposable e-cigarette, and $19.11 per reusable e-cigarette. When prices of disposable e-cigarettes, reusable e-cigarettes, and cigarettes increased by 1%, per capita sales of the products decreased by 0.37%, 0.20%, and 0.21% respectively. Cigarette prices were positively associated with per capita sales of reusable e-cigarettes, indicating reusable e-cigarettes are substitutes for cigarettes. Reusable e-cigarette prices were positively associated with per capita sales of disposable e-cigarettes, indicating disposable e-cigarettes are substitutes for reusable e-cigarettes. No statistically significant association was found between disposable/reusable e-cigarette prices and cigarette sales. Our results suggest that raising prices of disposable e-cigarettes, reusable e-cigarettes, and cigarettes such as via tobacco excise tax increases would result in reduced sales for the products. Policymakers should consider the substitution between e-cigarettes and cigarettes when designing tobacco control policies.

Introduction We illustrate the differential impact of common analysis approaches to handling urinary creatinine, a measure for urine dilution, on relationships between race, gender, and biomarkers of exposure measured in spot urine. Methods In smokers, spot urine levels of total nicotine equivalents (TNE, sum of total nicotine, total cotinine, and total 3′-hydroxycotinine) and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) overall and per cigarette were examined. Relationships between race (African Americans [AA] n = 373, Whites n = 758) or gender (males n = 629, females n = 502) and TNE or NNAL were examined using the following approaches to handling creatinine: (1) unadjusted/unstandardized; (2) standardization; (3) adjustment as a covariate. Significance was considered at p < .05 Results Creatinine was higher in AA versus Whites (1.19 vs. 0.96 mg/mL; p < .0001) and in males versus females (1.21 vs. 0.84 mg/mL; p < .0001). Independent of how creatinine was handled, TNE was lower among AA than Whites (TNE ratios AA vs. Whites: 0.67–0.84; p’s < .05). Unadjusted TNE per cigarette was higher among AA versus Whites (ratio 1.12; p = .0411); however, the relationship flipped with standardization (ratio 0.90; p = .0360) and adjustment (ratio 0.95; p = .3165). Regarding gender, unadjusted TNE was higher among males versus females (ratio 1.13; p = .0063), but the relationship flipped with standardization (ratio 0.79; p < .0001) or adjustment (ratio 0.89; p = .0018). Unadjusted TNE per cigarette did not differ across gender (ratio 0.98; p = .6591), but lower levels were found in males versus females with standardization (ratio 0.68; p < .0001) and adjustment (ratio 0.74; p < .0001). NNAL displayed similar patterns. Conclusions Relationships between race, gender, and spot urine levels of biomarkers of exposure can vary greatly based on how creatinine is handled in analyses. Implications Lack of appropriate methods can lead to discrepancies across reports on variability of urinary biomarkers by race and gender. We recommend that for any analyses of biomarkers of exposure measure in spot urine samples across race, gender, or other population subgroups that differ in urinary creatinine levels, sensitivity analyses comparing the different methods for handling urinary creatinine should be conducted. If methods result in discrepant findings, this should be clearly noted and discussed.

Author(s): Harvanko, Arit M; St Helen, Gideon; Nardone, Natalie; Addo, Newton; Benowitz, Neal L | Abstract: Background and aimsRelative pharmacological effects of e-cigarettes and cigarettes during 24nhours of ad-libitum use have not been described. In this study, 24-hour blood plasma nicotine concentrations and 48-hour subjective effects with use of cigarettes and e-cigarettes were measured among dual users.DesignTwo-arm within-subject cross-over design with preferred e-cigarette or cigarette ad-libitum use over 48nhours.SettingHospital research ward in San Francisco, California, USA.ParticipantsThirty-six healthy dual users of e-cigarettes and cigarettes (nn=n8, 25% females).MeasurementsTwenty-four-hour blood plasma nicotine and cotinine concentrations and 48-hour self-reported nicotine withdrawal symptoms and rewarding effects.FindingsAnalyses used analysis of variance (ANOVA)-based mixed models with order of product (e-cigarette or cigarette) and product type (combustible cigarette or type of e-cigarette) as fixed effects, and subject as a repeated effect. During a 24-hour period, e-cigarettes produced lower nicotine exposure than cigarettes for the majority of users, although 25% received more nicotine from e-cigarettes, which was predicted by more frequent e-cigarette use or greater dependence. Compared to cigarette smoking, nicotine exposure for variable-power tank users was similar, while cig-a-like (t(30) n=n2.71, Pn=n0.011, dn=n0.745) and fixed-power tank users (t(30) n=n3.37, Pn=n0.002, dn=n0.993) were exposed to less nicotine. Cigarettes were rated higher than e-cigarettes on some desirable subjective effects (e.g. psychological reward, t(322) n=n7.24 Pnln0.001, dn=n0.432), but withdrawal symptom reduction was comparable. No differences were found between e-cigarette types, but Bayes factors indicate that these measures were insensitive.ConclusionsDuring a 24-hour period in a hospital setting in the United States, nicotine exposure for dual users of e-cigarettes and cigarettes was similar when using cigarettes or variable-power tank devices only but was lower for those using cig-a-like or fixed-power devices only. Despite lower nicotine levels, all types of e-cigarette were effective in preventing withdrawal symptoms. E-cigarettes were rated less rewarding than cigarettes.

This study investigated the influence of the rate of nicotine metabolism, as indicated by the nicotine metabolite ratio (NMR), on tobacco dependence. We stratified 136 smokers on the basis of saliva NMR as fast (n = 65) and slow (n = 71) metabolizers. Two “loading cigarettes” were smoked after overnight, and a “reward cigarette” was smoked after 6 hours of daytime, abstinence. Blood nicotine concentrations, expired carbon monoxide, withdrawal/craving, and reward questionnaires were collected before/after smoking and during daytime abstinence. Compared with slow metabolizers, fast metabolizers had a shorter nicotine elimination half-life (P < 0.001), lower plasma nicotine concentrations (P < 0.001), and higher withdrawal/craving scores (P < 0.05) for most times during daytime abstinence, indicating that fast metabolizers are likely smoking more to relieve withdrawal symptoms (negative reinforcement). Reward/satisfaction scores were similar in fast and slow metabolizers, suggesting that faster nicotine metabolism, assessed by NMR, is not associated with greater positive reinforcement. CYP2A6 normal (n = 82) and reduced (n = 42) genotype predicted plasma nicotine concentrations but not withdrawal symptoms.

BackgroundPhilip Morris International (PMI) currently claims that its heated tobacco product, IQOS, reduces health risk by reducing users’ exposure to harmful and potentially harmful constituents present in tobacco smoke. Given the tobacco industry’s long history of misrepresenting and obfuscating research, independent assessment of PMI’s claims is important. Analysis of Accord, a failed but strikingly similar precursor to IQOS, may help contextualise PMI’s claims in its Modified Risk Tobacco Product (MRTP) application.MethodsWe analysed previously secret internal Philip Morris (PM) and PMI documents, public communications and MRTP application.ResultsPM marketed Accord as a ‘cleaner’ tobacco product in an attempt to address smokers’ growing health concerns without making explicit health claims. While PM communications asserted that Accord reduced users’ exposure to harmful constituents, company scientists and executives consistently stressed to both regulators and the public that such reductions did not render Accord safer. IQOS’s design and marketing are similar to Accord’s. On the basis of aerosol chemistry data, IQOS reduces user exposure to some compounds compared with Accord but raises them for others.DiscussionIQOS appears to be a variant of Accord without consistent improvements in exposure to aerosol toxic compounds. In contrast to PM’s past claims for Accord, PMI now claims in its MRTP application that IQOS reduces health risk. This shift in stance is likely not the result of any toxicological difference between Accord and IQOS, but rather a change in the social and regulatory landscape permitting these claims.

BackgroundNew electronic heated tobacco products are being introduced in the global market and are gaining popularity. In 2016, Philip Morris International, Inc. (PMI) submitted a modified risk tobacco product (MRTP) application to the Food and Drug Administration (FDA) to market IQOS in the USA with claims of reduced exposure and reduced risk.MethodsWe examined PMI’s MRTP application, specifically sections on aerosol chemistry and human exposure assessment, to assess the validity of PMI’s claims of reduced exposure and risk.FindingsPMI reported levels for only 40 of 93 harmful and potentially harmful constituents (HPHCs) on FDA’s HPHC list in IQOS mainstream aerosol. All substances in PMI’s list of 58 constituents (PMI-58) were lower in IQOS emissions compared with mainstream smoke of 3R4F reference cigarettes. However, levels of 56 other constituents, which are not included in the PMI-58 list or FDA’s list of HPHCs, were higher in IQOS emissions; 22 were >200% higher and seven were >1000% higher than in 3R4F reference cigarette smoke. PMI’s studies also show significantly lower systemic exposure to some HPHCs from use of IQOS compared with smoking combustible cigarettes.ConclusionPMI’s data appear to support PMI’s claim that IQOS reduces exposure to HPHCs. However, PMI’s data also show significantly higher levels of several substances that are not recognised as HPHCs by the FDA in IQOS emissions compared with combustible cigarette smoke. The impact of these substances on the overall toxicity or harm of IQOS is not known.

Objective The primary objective of this pilot study was to describe the impact of e-cigarette liquid flavors on experienced e-cigarette users’ vaping behavior. Methods 11 males and 3 females participated in a 3-day inpatient crossover study using e-cigarettes with strawberry, tobacco, and their usual brand e-liquid. Nicotine levels were nominally 18 mg/mL in the strawberry and tobacco e-liquids and ranged between 3–18 mg/mL in the usual brands. On each day, participants had access to the study e-cigarette (KangerTech mini ProTank 3, 1.5 Ohms, 3.7 V) and the assigned e-liquid during a 90-minute videotaped ad libitum session. Results Average puff duration was significantly longer when using the strawberry e-liquid (3.2 ± 1.3 s, mean ± SD) compared to the tobacco e-liquid (2.8 ± 1.1 s) but the average number of puffs was not significantly different (strawberry, 73 ± 35; tobacco, 69 ± 46). Compared to the strawberry- and tobacco-flavored e-liquids, average puff duration was significantly longer (4.3 ± 1.6 s) and the average number of puffs was significantly higher (106 ± 67 puffs) when participants used their usual brand of e-liquid. Participants generally puffed more frequently in small groups of puffs (1–5 puffs) with the strawberry compared to the tobacco e-liquid and more frequently in larger groups (>10 puffs) with their usual brand. The strength of the relationship between vaping topography and nicotine intake and exposure were not consistent across e-liquids. Conclusion Vaping behavior changes across e-liquids and influences nicotine intake. Research is needed to understand the mechanisms that underlie these behavioral changes, including e-liquid pH and related sensory effects, subjective liking, and nicotine effects.

To describe the effect of e-liquid flavors on nicotine intake and pharmacology of e-cigarettes.11 males and 3 females participated in a 3-day inpatient crossover study with strawberry, tobacco, and their usual flavor e-liquid. Nicotine levels were nominally 18mg/mL in the strawberry (pH 8.29) and tobacco (pH 9.10) e-liquids and ranged between 3-18mg/mL in the usual brands (mean pH 6.80). Each day consisted of a 15-puff session followed by 4h of abstinence, then 90min of ad libitum use. Subjects used a KangerTech mini ProTank 3.After 15 puffs, the amount of nicotine inhaled and systemically retained were not significantly different between the strawberry and tobacco e-liquids but plasma AUC(0→180) was significantly higher with the strawberry e-liquid. While not significantly different, Cmax was 22% higher and various early time point AUCs to measure rate of rise of nicotine in blood ranged between 17 and 23% higher with the strawberry e-liquid compared to the tobacco e-liquid. During ad libitum use, systemic exposure to nicotine (AUC(0→90)) was the same for the tobacco and usual brand e-liquids but were both significantly lower than after using the strawberry e-liquid. The usual flavors were more liked and satisfying than the strawberry and tobacco e-liquids.Flavors influence nicotine exposure through flavor liking, may affect rate of nicotine absorption possibly through pH effects, and contribute to heart rate acceleration and subjective effects of e-cigarettes. E-cigarette users titrate their nicotine exposure but the extent of titration may vary across flavors.

Author(s): Taghavi, Taraneh; St Helen, Gideon; Benowitz, Neal L; Tyndale, Rachel F | Abstract: ObjectivesNicotine metabolism rates differ considerably among individuals, even after controlling for variation in the major nicotine-metabolizing enzyme, CYP2A6. In this study, the impact of genetic variation in alternative metabolic enzymes and transporters on nicotine and cotinine (COT) pharmacokinetics and smoking was investigated.MethodsWe examined the impact of UGT2B10, UGT2B17, FMO3, NAT1, and OCT2 variation on pharmacokinetics and smoking (total nicotine equivalents and topography) before and after stratifying by CYP2A6 genotype in 60 African American (AA) smokers who received a simultaneous intravenous infusion of deuterium-labeled nicotine and COT.ResultsVariants in UGT2B10 and UGT2B17 were associated with urinary glucuronidation ratios (glucuronide/free substrate). UGT2B10 rs116294140 was associated with significant alterations in COT and modest alterations in nicotine pharmacokinetics. These alterations, however, were not sufficient to change nicotine intake or topography. Neither UGT2B10 rs61750900, UGT2B17*2, FMO3 rs2266782, nor NAT1 rs13253389 altered nicotine or COT pharmacokinetics among all individuals (n=60) or among individuals with reduced CYP2A6 activity (n=23). The organic cation transporter OCT2 rs316019 significantly increased nicotine and COT Cmax (P=0.005, 0.02, respectively) and decreased nicotine clearance (P=0.05). UGT2B10 rs116294140 had no significant impact on the plasma or urinary trans-3'-hydroxycotinine/COT ratio, commonly used as a biomarker of CYP2A6 activity.ConclusionWe found that polymorphisms in genes other than CYP2A6 represent minor sources of variation in nicotine pharmacokinetics, insufficient to alter smoking in AAs. The change in COT pharmacokinetics with UGT2B10 rs116294140 highlights the UGT2B10 gene as a source of variability in COT as a biomarker of tobacco exposure among AA smokers.

Background Assessing the prevalence and level of exposure (dose) of tobacco and marijuana use is important in studies of harm from use of these substances. We used biochemical analysis of urine to quantitatively assess exposure to nicotine and delta 9-tetrahydrocannabinol (THC) in adolescents receiving medical care in a public hospital Methods Participants were 686 adolescents between 12 and 21 years old seen at Zuckerberg San Francisco General Hospital between 2012 and 2014. Urine samples were assayed using high sensitivity liquid chromatographic assays for cotinine, a major metabolite of nicotine, and 11-nor-9-carboxy-delta 9-THC (THC−COOH), a major metabolite of THC. A commonly used immunoassay screen for THC−COOH was also performed. Results The THC−COOH immunoassay substantially underestimated THC exposure, as measured with the high sensitivity assay. THC use was detected in 25% of participants, with higher prevalence with increasing age and in non-Hispanic blacks. Active tobacco smokers had an 80% prevalence of THC use (odds ratio for cigarette smoking predicting THC use 13.2). Urine cotinine and THC−COOH were significantly correlated (r = 0.60). Conclusions The use of a high sensitivity chromatographic urine assay provides a much more complete picture of adolescent tobacco use compared to a commonly used immunoassay. The immunoassay provides high specificity but moderate sensitivity. We confirm high concordance of tobacco and marijuana use and the high predictive value of cigarette smoking in predicting marijuana use, and provide novel data on the quantitative correlation between level of exposure to nicotine and THC. Quantitative screening of nicotine and THC exposure may enhance our understanding of addiction and harm from single and dual product use.

Comparisons of systemic exposure to toxicants during monitored cigarette smoking, electronic cigarette (e-cigarette) use, and abstention are needed to enhance our understanding of the risks of e-cigarette use (vaping). In a cross-over study, we measured 10 mercapturic acid metabolites of volatile organic compounds (VOCs) in 24-hour urine samples collected from 36 dual users (8 women) of e-cigarettes and cigarettes during 2 days of ad libitum vaping or cigarette-only use, and 2 days of enforced abstention. Concentrations of VOC metabolites were higher during smoking compared with vaping, except for the methylating agents' metabolite. The fold-difference in concentrations when smoking relative to vaping ranged from 1.31 (1.06–1.61; geometric mean, 95% confidence interval; 1,3-butadiene) to 7.09 (5.88–8.54; acrylonitrile). Metabolites of acrylamide [fold difference of 1.21 (1.03–1.43)] and benzene [1.46 (1.13–1.90)] were higher during vaping compared with abstention. The 1,3-butadiene and propylene oxide metabolites were higher in variable-power tank users compared with users of cig-a-likes. E-cigarettes expose users to lower levels of toxic VOCs compared with cigarette smoking, supporting their harm reduction potential among smokers. However, some e-cigarettes expose users to VOCs such as acrylamide, benzene, and propylene oxide, and may pose health risks to nonsmoking users. The results of our study will inform regulators in assessing e-cigarettes with respect to the balance between its potential harm reduction for adult smokers and risk to nonsmoking users.

Objective The study objective was to identify biobehavioral variables associated with greater intake of nicotine and a tobacco carcinogen among Black light smokers who smoke 1 to 10 cigarettes per day (CPD). Methods We analyzed baseline data collected from 426 Black light smokers enrolled in Kick It at Swope III (KIS III), a smoking cessation trial for Black smokers. We examined differences in concentrations of tobacco biomarkers, including urinary total nicotine equivalents (TNE) and total 4-(methylnitrosamino)-1-(3)pyridyl-1-butanonol (NNAL; a human carcinogen), across gender, age, plasma nicotine metabolite ratio (NMR), CPD, and measures of tobacco dependence, including time to first cigarette (TFC), using ANOVA. Results Tobacco biomarker levels were significantly higher among those who smoked more CPD (6–10 vs 1–5 CPD) and those with greater reported physical dependence on tobacco. Concurrently, those who smoked 1–5 CPD smoked each cigarette more intensely than those who smoked 6–10 CPD. While we found no gender differences overall, among those who smoked 1–5 CPD, women had higher NNAL levels compared to men. The rate of nicotine metabolism, measured by the nicotine metabolite ratio, was not significantly related to TNE or NNAL levels. Conclusion Among Black Light smokers, higher cigarette consumption and greater physical dependence—but not rate of nicotine metabolism, menthol use, or socioeconomic status—were associated with greater toxicant exposure and thus a likely increased risk of tobacco-related diseases. The lack of data on light smokers, and specifically on Blacks, make this observation important given the disproportionate burden of lung cancer in this population.

Introduction Dual use of electronic cigarettes (e-cigarettes) and combustible cigarettes is a major public health issue. It is generally accepted that exclusive e-cigarette use is less harmful than exclusive combustible cigarette use, but most e-cigarette users continue to smoke combustible cigarettes as well. To what extent the use of e-cigarettes reduces harm in people who continue to smoke combustible cigarettes has been debated. The aim of this study was to explore the utility of biomarkers as measures of dual use. Methods In two human studies of participants who used e-cigarettes only or both combustible cigarettes and e-cigarettes, we measured urine concentrations of the metabolites of nicotine (total nicotine equivalents) as well as two biomarkers of tobacco exposure: 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a tobacco-specific carcinogen metabolite, and nicotelline, a tobacco alkaloid not found in significant concentrations in e-cigarette products. Results The presence of nicotine metabolites indicates either e-cigarette or combustible cigarette use. Nicotelline (half-life of 2–3 hours) indicates recent combustible cigarette use and NNAL (half-life of 10 days or more), indicates combustible cigarette use occurring within several weeks prior to sample collection. Conclusions Nicotelline and NNAL are useful biomarkers for combustible tobacco use in users e-cigarettes. The application of these biomarkers provides a tool to help assess whether, or to what extent, dual use of e-cigarettes and combustible cigarettes reduces harm compared to sole use of combustible cigarettes. These biomarkers can also verify exclusive use of e-cigarettes over short (24 hour) or long (several week) time periods. Implications: To what extent dual use of e-cigarettes and combustible cigarettes reduce harm compared to smoking combustible cigarettes only is of considerable public health interest. We show that the levels of the minor tobacco alkaloid nicotelline and the nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) are extremely low in electronic cigarette fluids. The urine biomarkers nicotelline and the NNK metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) are indicative of cigarette smoking and can be used to assess recent and past smoking in dual users.

Author(s): St Helen, Gideon; Nardone, Natalie; Addo, Newton; Dempsey, Delia; Havel, Christopher; Jacob, Peyton; Benowitz, Neal L | Abstract: AimTo describe systemic nicotine exposure and subjective effects of electronic cigarettes (e-cigarettes) in people who use both e-cigarettes and cigarettes (dual users), including within-subject comparisons of e-cigarette and cigarette use.DesignTwo-arm, counterbalanced cross-over study. Participants used their usual brand of e-cigarette or cigarette during a standardized session in a 2-week study.SettingHospital research ward, San Francisco, CA, USA.ParticipantsThirty-six healthy (eight women, 28 men) participants.MeasurementsPlasma nicotine was analyzed by gas chromatography-tandem mass spectrometry; nicotine withdrawal, urge to smoke and vape, affective states, craving, satisfaction and psychological reward were measured by standardized questionnaires.FindingsCompared with cigarettes, average maximum plasma nicotine concentration (Cmax ) was lower with e-cigarettes [6.1 ± 5.5 ng/ml, mean ± standard deviation (SD) versus 20.2 ± 11.1 ng/ml, P l 0.001] and time of maximal concentration (Tmax ) was longer (6.5 ± 5.4 versus 2.7 ± 2.4 minutes, P l 0.001). Use of both products resulted in a reduction in the severity of withdrawal symptoms, negative affect and urge to use either product. E-cigarettes were less rewarding and satisfying and reduced craving to a lesser degree than cigarettes. We were not able to detect any differences in withdrawal symptoms, affective states and urge to smoke cigarettes between e-cigarette and cigarette use.ConclusionSystemic nicotine exposure was, on average, lower with single use of e-cigarettes compared with cigarettes, and e-cigarettes were judged to be less satisfying and rewarding and reduced craving less than cigarettes.

Author(s): St Helen, Gideon; Ross, Kathryn C; Dempsey, Delia A; Havel, Christopher M; Jacob, Peyton; Benowitz, Neal L | Abstract: ObjectiveTo characterize vaping behavior and nicotine intake during ad libitum e-cigarette access.MethodsThirteen adult e-cigarette users had 90 minutes of videotaped ad libitum access to their usual e-cigarette. Plasma nicotine was measured before and every 15 minutes after the first puff; subjective effects were measured before and after the session.ResultsAverage puff duration and interpuff interval were 3.5±1.4 seconds (±SD) and 118±141 seconds, respectively. 12% of puffs were unclustered puffs while 43%, 28%, and 17% were clustered in groups of 2-5, 6-10, and g10 puffs, respectively. On average, 4.0±3.3 mg of nicotine was inhaled; the maximum plasma nicotine concentration (Cmax) was 12.8±8.5 ng/mL. Among the 8 tank users, number of puffs was positively correlated with amount of nicotine inhaled, Cmax, and area under the plasma nicotine concentration-time curve (AUC0→90min) while interpuff interval was negatively correlated with Cmax and AUC0→90.ConclusionVaping patterns differ from cigarette smoking. Plasma nicotine levels were consistent with intermittent dosing of nicotine from e-cigarettes compared to the more bolus dosing from cigarettes. Differences in delivery patterns and peak levels of nicotine achieved could influence the addictiveness of e-cigarettes compared to conventional cigarettes.

Background: African American (AA) smokers experience greater tobacco-related disease burden than Whites, despite smoking fewer cigarettes per day (CPD). Understanding factors that influence daily nicotine intake in AA smokers is an important step toward decreasing tobacco-related health disparities. One factor of interest is smoking topography, or the study of puffing behavior. Aims: (i) to create a model using puff characteristics, nicotine dependence, and nicotine metabolism to predict daily nicotine exposure, and (ii) to compare puff characteristics and nicotine intake from two cigarettes smoked at different times to ensure the reliability of the puff characteristics included in our model. Methods: Sixty AA smokers smoked their preferred brand of cigarette at two time points through a topography device. Plasma nicotine, expired CO, and changes in subjective measures were measured before and after each cigarette. Total nicotine equivalents (TNE) was measured from 24-hour urine collected during ad libitum smoking. Results: In a model predicting daily nicotine exposure, total puff volume, CPD, sex, and menthol status were significant predictors (R2 = 0.44, P < 0.001). Total puff volume was significantly greater and inter-puff intervals were significantly shorter after ad lib smoking compared with the first cigarette of the day, but puffing behaviors for both cigarettes were highly correlated (r range = 0.69–0.89, P < 0.001) within-subjects. Conclusion: This is the first study, to our knowledge, to show that puff characteristics of individual cigarettes are predictive of daily nicotine intake. Impact: These findings enhance our understanding of the relationship between smoking behavior and nicotine intake in AA smokers. Cancer Epidemiol Biomarkers Prev; 25(6); 936–43. ©2016 AACR.

Millions of Americans use e-cigarettes. Despite their popularity, little is known about their health effects. Some suggest that e-cigarettes likely confer lower risk compared to combustible tobacco cigarettes, because they do not expose users to toxicants produced through combustion. Proponents of e-cigarette use also tout the potential benefits of e-cigarettes as devices that could help combustible tobacco cigarette smokers to quit and thereby reduce tobacco-related health risks. Others are concerned about the exposure to potentially toxic substances contained in e-cigarette emissions, especially in individuals who have never used tobacco products such as youth and young adults. Given their relatively recent introduction, there has been little time for a scientific body of evidence to develop on the health effects of e-cigarettes.Public Health Consequences of E-Cigarettes reviews and critically assesses the state of the emerging evidence about e-cigarettes and health. This report makes recommendations for the improvement of this research and highlights gaps that are a priority for future research.

Author(s): St Helen, Gideon; Havel, Christopher; Dempsey, Delia A; Jacob, Peyton; Benowitz, Neal L | Abstract: AimsTo measure the systemic retention of nicotine, propylene glycol (PG) and vegetable glycerin (VG) in electronic cigarette (e-cigarette) users, and assess the abuse liability of e-cigarettes by characterizing nicotine pharmacokinetics.DesignE-cigarette users recruited over the internet participated in a 1-day research ward study. Subjects took 15 puffs from their usual brand of e-cigarette. Exhaled breath was trapped in gas-washing bottles and blood was sampled before and several times after use.SettingSan Francisco, California, USA.ParticipantsThirteen healthy, experienced adult e-cigarette users (six females and seven males).MeasurementsPlasma nicotine was analyzed by gas chromatography-mass spectrometry (GC-MS/MS) and nicotine, VG and PG in e-liquids and gas traps were analyzed by LC-MS/MS. Heart rate changes and subjective effects were assessed.FindingsE-cigarettes delivered an average of 1.33 (0.87-1.79) mg [mean and 95% confidence interval (CI)] of nicotine, and 93.8% of the inhaled dose, 1.22 (0.80-1.66) was systemically retained. Average maximum plasma nicotine concentration (Cmax ) was 8.4 (5.4-11.5) ng/ml and time of maximal concentration (Tmax ) was 2-5 minutes. One participant had Tmax of 30 minutes. 84.4% and 91.7% of VG and PG, respectively, was systemically retained. Heart rate increased by an average of 8.0 beats per minute after 5 minutes. Withdrawal and urge to smoke decreased and the e-cigarettes were described as satisfying.ConclusionsE-cigarettes can deliver levels of nicotine that are comparable to or higher than typical tobacco cigarettes, with similar systemic retention. Although the average maximum plasma nicotine concentration in experienced e-cigarette users appears to be generally lower than what has been reported from tobacco cigarette use, the shape of the pharmacokinetic curve is similar, suggesting addictive potential.

Although evidence suggests associations between maternal exposure to air pollution and adverse birth outcomes, pregnant women's exposure to household air pollution in developing countries is understudied. Personal exposures of pregnant women (N = 100) in Trujillo, Peru, to air pollutants and their indoor concentrations were measured. The effects of stove-use-related characteristics and ambient air pollution on exposure were determined using mixed-effects models. Significant differences in 48-hour kitchen concentrations of particulate matter (PM2.5), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations were observed across fuel types (p < 0.05). Geometric mean PM2.5 concentrations where 112 μg/m(3) (confidence limits [CLs]: 52, 242 μg/m(3)) and 42 μg/m(3) (21, 82 μg/m(3)) in homes where wood and gas were used, respectively. PM2.5 exposure was at levels that recent exposure-response analyses suggest may not result in substantial reduction in health risks even in homes where cleaner burning gas stoves were used.

We examined the relationship between the tobacco industry and the journal Regulatory Toxicology and Pharmacology (RTP) using the Truth Tobacco Industry Documents Library and internet sources. We determined the funding relationships, and categorised the conclusions of all 52 RTP papers on tobacco or nicotine between January 2013 and June 2015, as “positive”, “negative” or “neutral” for the tobacco industry. RTP’s editor, 57% (4/7) of associate editors and 37% (14/38) of editorial board members had worked or consulted for tobacco companies. Almost all (96%, 50/52) of the papers had authors with tobacco industry ties. Seventy-six percent (38/50) of these papers drew conclusions positive for industry; none drew negative conclusions. The two papers by authors not related to the tobacco industry reached conclusions negative to the industry (p

Background: Many adolescents are exposed to tobacco smoke, from either active smoking (CS) or secondhand smoke (SHS) exposure. Tobacco-specific biomarkers of exposure include cotinine (detects use in past 2–4 days) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL; detects use for a month or longer). NNAL is expected to detect more intermittent tobacco exposure. We compared NNAL and cotinine as biomarkers of exposure to tobacco in urban adolescents and determined the optimal NNAL cutoff point to distinguish CS from SHS exposure. Methods: Surplus urine samples, collected from 466 adolescents attending pediatric well or urgent care visits at Zuckerberg San Francisco General Hospital in 2013 to 2014, were assayed for cotinine and NNAL. Results: Ninety-four percent of adolescents had measurable levels of NNAL compared with 87% for cotinine. The optimal NNAL cutoff point to distinguish CS from SHS was 9.6 pg/mL by latent class or 14.4 pg/mL by receiver-operating characteristic analysis. Cotinine and NNAL were strongly correlated, but the correlation slopes differed for active versus SHS-exposed adolescents. Among nonsmokers, NNAL levels were significantly higher in African American (median, 3.3 pg/mL) compared with other groups (0.9–1.9 pg/mL), suggesting greater exposure to SHS. Conclusions: Urine NNAL screening finds a large majority (94%) of urban adolescents are exposed to tobacco. African Americans are exposed to higher levels of SHS than other ethnic/racial groups. Impact: SHS is associated with significant medical morbidity in adolescents. Routine biochemical screening with NNAL or cotinine detects high prevalence of SHS exposure and should be considered as a tool to reduce SHS exposure in high-risk populations. Cancer Epidemiol Biomarkers Prev; 27(3); 254–61. ©2018 AACR.

Accurate and reliable measurements of exposure to tobacco products are essential for identifying and confirming patterns of tobacco product use and for assessing their potential biological effects in both human populations and experimental systems. Due to the introduction of new tobacco-derived products and the development of novel ways to modify and use conventional tobacco products, precise and specific assessments of exposure to tobacco are now more important than ever. Biomarkers that were developed and validated to measure exposure to cigarettes are being evaluated to assess their use for measuring exposure to these new products. Here, we review current methods for measuring exposure to new and emerging tobacco products, such as electronic cigarettes, little cigars, water pipes, and cigarillos. Rigorously validated biomarkers specific to these new products have not yet been identified. Here, we discuss the strengths and limitations of current approaches, including whether they provide reliable exposure estimates for new and emerging products. We provide specific guidance for choosing practical and economical biomarkers for different study designs and experimental conditions. Our goal is to help both new and experienced investigators measure exposure to tobacco products accurately and avoid common experimental errors. With the identification of the capacity gaps in biomarker research on new and emerging tobacco products, we hope to provide researchers, policymakers, and funding agencies with a clear action plan for conducting and promoting research on the patterns of use and health effects of these products.

Background Blacks bear a disproportionate burden of smoking-related diseases and experience greater difficulty quitting smoking than Whites. Nicotine has a high affinity for melanin, and it has been hypothesized that melanin levels might influence nicotine pharmacokinetics and enhance dependence. The aim of this study was to evaluate the hypothesis that melanin affects nicotine disposition kinetics in humans. Methods Forty-four Black participants were administered intravenous infusions of deuterium-labeled nicotine and cotinine. Plasma concentrations of nicotine and cotinine were measured, and pharmacokinetic parameters were estimated. The constitutive and facultative melanin indexes were measured using a dermaspectrophotometer. Results The median constitutive melanin index was 60.7 (32.8-134.7) and the median facultative melanin index 68.1 (38.6-127.1). The mean (±SD) nicotine elimination half-life was 136 minutes (±33.5), clearance was 1237 mL/min (±331), and Vss was 204 L (±66), or 2.6 L/kg (±0.7). No evidence of significant differences was found in nicotine pharmacokinetic parameters by comparing participants in different melanin index quartiles (outliers with very high melanin index had similar pharmacokinetic values to others). Differences were not statistically significant when adjusted for age, BMI, sex and CYP2A6 genotype or the nicotine metabolite ratio (NMR), and no evidence of significant correlations were found between melanin (facultative or constitutive) and the pharmacokinetic parameters of nicotine or cotinine or tobacco dependence measures. Conclusions Based on our finding in this group of Black smokers, we could not confirm the hypothesis that melanin significantly affects nicotine disposition kinetics or measures of tobacco dependence.

Author(s): Benowitz, Neal L; Jain, Shonul; Dempsey, Delia A; Nardone, Natalie; Helen, Gideon St; Jacob, Peyton | Abstract: IntroductionRoutine biochemical assessment of tobacco smoke exposure could lead to more effective interventions to reduce or prevent secondhand smoke (SHS)-related disease in adolescents. Our aim was to determine using urine cotinine (major nicotine metabolite) measurement the prevalence of tobacco smoke exposure among adolescents receiving outpatient care at an urban public hospital.MethodsSurplus urine was collected in 466 adolescents attending pediatric or urgent care clinics at Zuckerberg San Francisco General Hospital, serving families with lower levels of income and education, in 2013-2014. The majority were Hispanic or African American. Urine cotinine cut points of 0.05 to 0.25 ng/ml, 0.25 to 30 ng/ml, and 30 ng/ml were used to classify subjects as light SHS or thirdhand smoke exposed, SHS or light/intermittent active users, and active tobacco users, respectively.ResultsAmong subjects 87% were exposed, including 12% active smoking, 46% SHS and 30% lightly exposed. The SHS exposed group adjusted geometric mean cotinine values were significantly higher in African Americans (1.48 ng/ml) compared to other groups (0.56-1.13 ng/ml).ConclusionsIn a city with a low smoking prevalence (12%), a large majority (87%) of adolescents seen in a public hospital clinic are exposed to tobacco. This is much higher than reported in national epidemiological studies of adolescents, which used a plasma biomarker. Since SHS is associated with significant respiratory diseases and parents and adolescents underreport exposure to SHS, routine biochemical screening should be considered as a tool to reduce SHS exposure. The clinical significance of light exposure needs to be investigated.ImplicationsUrine biomarker screening found that a large majority (87%) of adolescents treated in an urban public hospital are exposed to tobacco. Since SHS is associated with significant respiratory diseases and parents and adolescents underreport exposure to SHS, routine biochemical screening should be considered as a tool to reduce SHS exposure.

Author(s): Benowitz, Neal L; St Helen, Gideon; Dempsey, Delia A; Jacob, Peyton; Tyndale, Rachel F | Abstract: ObjectiveThe rate of nicotine metabolism, determined primarily by CYP2A6 activity, influences tobacco dependence and smoking-induced disease risk. The prevalence of CYP2A6 gene variants differs by race, with greater numbers in African Americans compared with Caucasians. We studied nicotine disposition kinetics and metabolism by the CYP2A6 genotype and enzymatic activity, as measured by the nicotine metabolite ratio (NMR), in African American smokers.MethodsParticipants were administered intravenous infusions of deuterium-labeled nicotine and cotinine. Plasma and urine concentrations of nicotine and metabolites were measured and pharmacokinetic parameters were estimated.ResultsPharmacokinetic parameters and urine metabolite excretion data were analyzed by CYP2A6 genotype and by NMR. A number of gene variants were associated with markedly reduced nicotine and cotinine clearances. NMR was strongly correlated with nicotine (r=0.72) and cotinine (r=0.80) clearances. Participants with higher NMR excreted significantly greater nicotine C-oxidation and lower non-C-oxidation products compared with lower NMR participants.ConclusionCYP2A6 genotype, NMR, and nicotine pharmacokinetic data may inform studies of individual differences in smoking behavior and biomarkers of nicotine exposure.

Author(s): St Helen, Gideon; Dempsey, Delia; Wilson, Margaret; Jacob, Peyton; Benowitz, Neal L | Abstract: AimsTo investigate the relationships between tobacco dependence, biomarkers of nicotine and carcinogen exposure and biomarkers of nicotine and carcinogen exposure per cigarette in back and white smokers.Design, setting and participantsA total of 204 healthy black (n = 69) and white (n = 135) smokers were enrolled into two clinical studies.MeasurementNicotine equivalents (nicotine and its metabolites), 4-(methylnitrosamino)-1-(3)pyridyl-1-butanol (NNAL) and polycyclic aromatic hydrocarbon (PAH) metabolites were measured in urine. The Fagerstrom Test for Nicotine Dependence (FTND) and time to first cigarette (TFC) measured tobacco dependence.FindingsAverage TFC and FTND for blacks and whites were not significantly different. Urine NNAL and nicotine equivalents increased with increasing FTND in whites but did not increase in blacks (race × FTND interaction, both P l 0.031). The interaction term was not significant for PAHs. An inverse relationship was seen between FTND and nicotine equivalents, NNAL and PAH metabolites per cigarette in blacks but remained flat in whites (race × FTND interaction, all P ≤ 0.039). Regardless of dependence (low dependence, TFC g15 minutes; high dependence, TFC ≤15 minutes), FTND and TFC were not correlated significantly with urine nicotine equivalents and carcinogen exposure in blacks. We found moderate correlations between FTND and TFC and nicotine equivalents and carcinogen exposure among whites of low dependence and non-significant correlations among whites of high dependence.ConclusionIn the United States, tobacco dependence measures were related linearly to nicotine intake and carcinogen exposure in white but not in black smokers. The relationship between dependence measures and tobacco biomarkers in black smokers regardless of level of dependence resembled highly dependent white smokers.

Background: The nicotine metabolite ratio (NMR or 3-hydroxycotinine/cotinine) has been used to phenotype CYP2A6-mediated nicotine metabolism. Our objectives were to analyze (i) the stability of NMR in plasma, saliva, and blood in various storage conditions, (ii) the relationship between NMRs derived from blood, plasma, saliva, and urine, and (iii) the reproducibility of plasma NMR in ad libitum cigarette smokers. Methods: We analyzed data from four clinical studies. In studies 1 and 2, we assessed NMR stability in saliva and plasma samples at room temperature (∼22°C) over 14 days and in blood at 4°C for up to 72 hours. In studies 2 and 3, we used Bland–Altman analysis to assess agreement between blood, plasma, saliva, and urine NMRs. In study 4, plasma NMR was measured on six occasions over 44 weeks in 43 ad libitum smokers. Results: Reliability coefficients for stability tests of NMR in plasma and saliva at room temperature were 0.97 and 0.98, respectively, and 0.92 for blood at 4°C. Blood NMR agreed consistently with saliva and plasma NMRs but showed more variability in relation to urine NMR. The reliability coefficient for repeated plasma NMR measurements in smokers was 0.85. Conclusion: The NMR is stable in blood, plasma, and saliva at the conditions tested. Blood, plasma, and saliva NMRs are similar whereas urine NMR is a good proxy for these NMR measures. Plasma NMR was reproducible over time in smokers. Impact: One measurement may reliably estimate a smoker's NMR for use as an estimate of the rate of nicotine metabolism. Cancer Epidemiol Biomarkers Prev; 21(7); 1105–14. ©2012 AACR.

Background: Volatile organic compounds (VOC) from tobacco smoke are associated with cancer, cardiovascular, and respiratory diseases. The objective of this study was to characterize the exposure of nonsmokers to VOCs from secondhand smoke (SHS) in vehicles using mercapturic acid metabolites. Methods: Fourteen nonsmokers were individually exposed in the backseat to one hour of SHS from a smoker seated in the driver's seat who smoked three cigarettes at 20-minute intervals in a stationary car with windows opened by 10 cm. Baseline and 0- to 8-hour postexposure mercapturic acid metabolites of nine VOCs were measured in urine. Air-to-urine VOC ratios were estimated on the basis of respirable particulate matter (PM2.5) or air nicotine concentration, and lifetime excess risk (LER) of cancer death from exposure to acrylonitrile, benzene, and 1,3-butadiene was estimated for adults. Results: The greatest increase in 0- to 8-hour postexposure concentrations of mercapturic acids from baseline was MHBMA-3 (parent, 1,3-butadiene; 2.1-fold), then CNEMA (acrylonitrile; 1.7-fold), PMA (benzene; 1.6-fold), MMA (methylating agents; 1.6-fold), and HEMA (ethylene oxide; 1.3-fold). The LER of cancer death from exposure to acrylonitrile, benzene, and 1,3-butadiene in SHS for 5 hours a week ranged from 15.5 × 10−6 to 28.1 × 10−6 for adults, using air nicotine and PM2.5 to predict air VOC exposure, respectively. Conclusion: Nonsmokers have significant intake of multiple VOCs from breathing SHS in cars, corresponding to health risks that exceed the acceptable level. Impact: Smoking in cars may be associated with increased risks of cancer, respiratory, and cardiovascular diseases among nonsmokers. Cancer Epidemiol Biomarkers Prev; 23(12); 2774–82. ©2014 AACR.

In studying the effects of exposure to secondhand smoke (SHS), concentrations of cotinine (the proximate metabolite of nicotine), measured in plasma, urine or saliva, are widely used as indicators of nicotine exposure [1].In interpreting the concentrations of cotinine in non-smokers relative to concentrations in smokers, the assumption is made that the pharmacokinetics of nicotine and cotinine are independent of the level of nicotine exposure. Published pharmacokinetic data on nicotine and cotinine are based on administration of nicotine and cotinine tosmokersandnon-smokersindosesconsistentwithcigarette smoking,which are much higher than those relevant to SHS [2].It is possible that the kinetics and metabolism of nicotine are different at low doses compared with higher doses. It is reported, for example, that the half-life of cotinine is longer after cessation of SHS exposure than after cessation of active smoking [3]. Nicotine is metabolized to cotinine primarily by the liver enzyme CYP2A6 [4].The same enzyme also metabolizescotininetotrans-3′-hydroxycotinine.Theclearancesof nicotine and cotinine and the activity of CYP2A6 are quite variable among individuals [5, 6]. Genetic variation explains some of the variability, with a number of CYP2A6 gene variants known to be associated with reduced enzymatic activity resulting in slow metabolism of nicotine and cotinine [7].The level of enzymatic activity could influence whetherthenicotineclearanceisdose-dependentinaparticular person. For example, dose-dependence is more likely when enzyme activity low. For this reason, we also assessed CYP2A6 genotype to examine its influence on dose-dependent pharmacokinetics.

Background: Water pipe tobacco smoking is spreading globally and is increasingly becoming popular in the United States, particularly among young people. Although many perceive water pipe smoking to be relatively safe, clinical experimental studies indicate significant exposures to tobacco smoke carcinogens following water pipe use. We investigated biomarkers of nicotine intake and carcinogen exposure from water pipe smoking in the naturalistic setting of hookah bars. Methods: Fifty-five experienced water pipe users were studied before and after smoking water pipe in their customary way in a hookah bar. Urine samples were analyzed for nicotine, cotinine, the tobacco-specific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and mercapturic acid metabolites of volatile organic compounds (VOC). Results: We found an average 73-fold increase in nicotine, 4-fold increase in cotinine, 2-fold increase in NNAL, and 14% to 91% increase in VOC mercapturic acid metabolites immediately following water pipe smoking. We saw moderate to high correlations between changes in tobacco-specific biomarkers (nicotine, cotinine, and NNAL) and several mercapturic acid metabolites of VOCs. Conclusion: Water pipe smoking in a hookah bar is associated with significant nicotine intake and carcinogen exposure. Impact: Given the significant intake of nicotine and carcinogens, chronic water pipe use could place users at increased risk of cancer and other chronic diseases. Cancer Epidemiol Biomarkers Prev; 23(6); 1055–66. ©2014 AACR.

Introduction: The nicotine metabolite ratio (NMR), the ratio of trans-3'-hydroxycotinine (3-HC) to cotinine, has been used as a biomarker of the rate of CYP2A6-mediated nicotine metabolism. While stable in smokers who maintain constant smoking consumption, since smoking has been shown to inhibit nicotine metabolism and this inhibition could be mediated by the nicotine in the smoke, NMR could change during nicotine reduction. The objective of this study was to determine the reproducibility (or stability) of plasma NMR in smokers of progressively reduced nicotine content (RNC) cigarettes. Methods: We analyzed data from subjects in a clinical trial of smoking progressively RNC cigarettes. Plasma NMR in 30 smokers whose plasma cotinine levels had decreased by at least 50% from the use of the first test cigarette (12 mg nicotine content) to the final test cigarette (1 mg nicotine content) was measured on 4 occasions over a period of 24 weeks. Results: Plasma cotinine and 3-HC decreased by an average of 85% and 84%, respectively, following the use of the first type of RNC cigarette to the last type. Plasma NMR had an average absolute change of 28.5% over the same period. Using repeated measures analysis, changes in plasma NMR over time were not significant with or without controlling for the effects of age, body mass index, gender, and race (p = .24 and p = .23, respectively). The reliability coefficient for repeated measurements of plasma NMR was .72. The average within-subject coefficient of variation for plasma NMR was 21.6% (SD = 12.0%). Conclusion: The plasma NMR is relatively stable over time as nicotine levels decline in smokers of progressively RNC cigarettes. © The Author 2013. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.

The objective of this study was to assess the utility of urinary Clara cell protein (CC16) as a biomarker of increased lung epithelial permeability in non-smokers exposed to outdoor secondhand smoke. Twenty-eight healthy non-smoking adults visited outdoor patios of a restaurant and a bar where non-participants smoked and an open-air control with no smokers on three weekend days in a crossover study; subjects visited each site once for 3 h. Urine samples were collected at baseline, immediately post exposure and next morning, and analyzed for CC16. Changes in CC16 across location types or with cigarette count were analyzed using mixed-effect models, which included all subjects and stratified by gender. Urinary CC16 was higher in males (n=9) compared with females (n=18) at all measurement occasions (P

Objectives The objectives of this study were: (1) to characterise the exposure of non-smokers exposed to secondhand smoke (SHS) in a vehicle using biomarkers, (2) to describe the time course of the biomarkers over 24 h, and (3) to examine the relationship between tobacco biomarkers and airborne concentrations of SHS markers. Methods Eight non-smokers were individually exposed to SHS in cars with fully open front windows and closed back windows over an hour from a smoker who smoked three cigarettes at 20 min intervals. The non-smokers sat in the back seat on the passenger side, while the smoker sat in the driver9s seat. Plasma cotinine and urine cotinine, 3-hydroxycotinine (3HC) and 4-(methylnitrosoamino)-(3-pyridyl)-1-butanol (NNAL) were compared in samples taken at baseline (BL) and several time-points after exposure. Nicotine, particulate matter (PM 2.5 ) and carbon monoxide (CO) were measured inside and outside the vehicle and ventilation rates in the cars were measured. Results Average plasma cotinine and the molar sum of urine cotinine and 3HC (COT+3HC) increased four-fold, urine cotinine increased six-fold and urine NNAL increased ∼27 times compared to BL biomarker levels. Plasma cotinine, urine COT+3HC and NNAL peaked at 4–8 h post-exposure while urine cotinine peaked within 4 h. Plasma cotinine was significantly correlated to PM 2.5 (Spearman correlation r s =0.94) and CO (r s =0.76) but not to air nicotine. The correlations between urine biomarkers, cotinine, COT+3HC and NNAL, and air nicotine, PM 2.5 and CO were moderate but non-significant (r s range = 0.31–0.60). Conclusions Brief SHS exposure in cars resulted in substantial increases in levels of tobacco biomarkers in non-smokers. For optimal characterisation of SHS exposure, tobacco biomarkers should be measured within 4–8 h post-exposure. Additional studies are needed to better describe the relationship between tobacco biomarkers and environmental markers of SHS.

Author(s): Havel, Christopher M; Benowitz, Neal L; Jacob, Peyton; St Helen, Gideon | Abstract: IntroductionCharacterization of aerosols generated by electronic cigarettes (e-cigarettes) is one method used to evaluate the safety of e-cigarettes. While some researchers have modified smoking machines for e-cigarette aerosol generation, these machines are either not readily available, not automated for e-cigarette testing or have not been adequately described. The objective of this study was to build an e-cigarette vaping machine that can be used to test, under standard conditions, e-liquid aerosolization and nicotine and toxicant delivery.MethodsThe vaping machine was assembled from commercially available parts, including a puff controller, vacuum pump, power supply, switch to control current flow to the atomizer, three-way value to direct air flow to the atomizer, and three gas dispersion tubes for aerosol trapping. To validate and illustrate its use, the variation in aerosol generation was assessed within and between KangerTech Mini ProTank 3 clearomizers, and the effect of voltage on aerosolization and toxic aldehyde generation were assessed.ResultsWhen using one ProTank 3 clearomizer and different e-liquid flavors, the coefficient of variation (CV) of aerosol generated ranged between 11.5% and 19.3%. The variation in aerosol generated between ProTank 3 clearomizers with different e-liquid flavors and voltage settings ranged between 8.3% and 16.3% CV. Aerosol generation increased linearly at 3-6V across e-liquids and clearomizer brands. Acetaldehyde, acrolein, and formaldehyde generation increased markedly at voltages at or above 5V.ConclusionThe vaping machine that we describe reproducibly aerosolizes e-liquids from e-cigarette atomizers under controlled conditions and is useful for testing of nicotine and toxicant delivery.ImplicationsThis study describes an electronic cigarette vaping machine that was assembled from commercially available parts. The vaping machine can be replicated by researchers and used under standard conditions to generate e-cigarette aerosols and characterize nicotine and toxicant delivery.

Background: With an increase in indoor smoking bans, many smokers smoke outside establishments and near their entrances, which has become a public health concern. Objectives: We characterized the exposure of nonsmokers to secondhand smoke (SHS) outside a restaurant and bar in Athens, Georgia, where indoor smoking is banned, using salivary cotinine and urinary 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL). Methods: In a crossover study, we assigned 28 participants to outdoor patios of a restaurant and a bar and an open-air site with no smokers on three weekend days; participants visited each site once and stayed for 3 hr. We collected saliva and urine samples immediately before and after the visits (postexposure) and on the following morning and analyzed samples for cotinine and total NNAL, respectively. Regression models were fitted and changes in biomarkers were contrasted between locations. Results: Postexposure and preexposure geometric mean salivary cotinine concentrations differed by 0.115 ng/mL [95% confidence interval (CI): 0.105, 0.126)] and by 0.030 ng/mL (95% CI: 0.028, 0.031) for bar and restaurant visits, respectively. There were no significant post- and preexposure differences in cotinine levels after control site visits, and changes after bar and restaurant site visits were significantly different from changes after control site visits (p < 0.001). Results comparing next-day and preexposure salivary cotinine levels were similar. Next-day creatinine-corrected urinary NNAL concentrations also were higher than preexposure levels following bar and restaurant visits [1.858 pg/mg creatinine higher (95% CI: 0.897, 3.758) and 0.615 pg/mg creatinine higher (95% CI: 0.210, 1.761), respectively], and were significantly different from changes after the control visits (p = 0.005). Conclusion: Salivary cotinine and urinary NNAL increased significantly in nonsmokers after outdoor SHS exposure. Our findings indicate that such exposures may increase risks of health effects associated with tobacco carcinogens.

Introduction The rate of nicotine metabolism, estimated by the nicotine metabolite ratio (NMR), is an important determinant of tobacco dependence. This study investigated the effect of NMR on smoking behavior due to nicotine reinforcement during ad libitum smoking. Aims and Methods As part of a larger study, participants were stratified based on saliva NMR as fast and slow metabolizers. After smoking a cigarette and measuring nicotine blood concentrations, participants smoked as desired over a 90-minute period. Analysis included time to first cigarette, total number of cigarettes, total number of puffs, and weight of tobacco consumed. Results Sixty-one (48%) participants were fast metabolizers and 66 (52%) slow metabolizers by NMR. No significant differences were found regarding the smoking topography variables by NMR. Normal metabolizers by genotype (n = 79) had a shorter time to first cigarette than reduced metabolizers (n = 39; p = .032). Blacks smoked fewer cigarettes (p = .008) and took fewer total puffs (p = .002) compared with Whites. Among Whites, fast metabolizers by NMR had a shorter time to first cigarette compared with slow metabolizers (p = .014). Among fast metabolizers, Whites had, compared with Blacks, shorter latency to first cigarette (p = .003) and higher number of total puffs (p = .014) and cigarettes smoked (p = .014). Baseline cigarettes per day and nicotine elimination half-life significantly predicted topography outcomes. Conclusions Saliva NMR did not predict cigarette reinforcement during a relatively brief period of ad libitum smoking. Differences were seen by race, with White fast metabolizers by NMR having shorter time to first cigarettes compared with slow metabolizers. Implications After a 90-minute period of nicotine abstinence, NMR was not significantly associated with smoking reinforcement. Slow and fast metabolizers had similar time to first cigarette, number of cigarettes smoked, total number of puffs, and tobacco consumed; however, within-race differences show that within Whites, fast metabolizers had a faster time to first cigarette than slow metabolizers.