Search

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.

Introduction Approximately the same percentage of male high school students in the United States currently uses conventional smokeless tobacco as smokes cigarettes, resulting in toxin exposure. Methods This study assessed tobacco product use (smokeless, combustible, and electronic cigarettes) and nicotine and carcinogen exposures in a sample of 594 male rural high school baseball players—a population traditionally at risk for smokeless tobacco use. Salivary specimens were assayed for cotinine (a biomarker of nicotine exposure) and urine specimens for 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL, a biomarker of the carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) using liquid chromatography–tandem mass spectrometry. Results The prevalence of past 30-day use of any tobacco product was 29%. Past 7-day smokeless tobacco use (prevalence: 13%) was associated with the highest levels of cotinine and NNAL observed in the sample, whether smokeless tobacco was used exclusively (geometric means: cotinine 11.1 ng/mL; NNAL 31.9 pg/mg-creatinine) or in combination with combustible products (geometric means: cotinine 31.6 ng/mL; NNAL 50.0 pg/mg creatinine). Cotinine and NNAL levels were incrementally higher in each increasing category of smokeless tobacco use frequency. However, observed levels were lower than previously reported for adults, likely reflecting less smokeless use per day among adolescents. Conclusions Based on these biomarker observations, adolescents who use conventional smokeless tobacco products are exposed to substantial levels of nicotine and NNK. Although exposed to lower levels than adult smokeless users, the findings are concerning given the young age of the sample and tendency for smokeless tobacco users to increase use intensity over time. Implications This study demonstrates that adolescents using smokeless tobacco are exposed to levels of nicotine and NNK that increase with use frequency and that exceed exposures among peers using other tobacco products. Youth smokeless tobacco use in the United States has not declined along with youth smoking prevalence, giving greater importance to this health concern. To reduce youth (and adult) exposures, needed actions include effective smokeless tobacco use prevention, potentially in combination with reducing the levels of harmful and potentially harmful chemicals in smokeless tobacco products currently popular among adolescents.

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.

Author(s): Goniewicz, Maciej L; Gawron, Michal; Smith, Danielle M; Peng, Margaret; Jacob, Peyton; Benowitz, Neal L | Abstract: IntroductionElectronic cigarettes (e-cigarettes) are purported to deliver nicotine aerosol without any toxic combustion products present in tobacco smoke. In this longitudinal within-subjects observational study, we evaluated the effects of e-cigarettes on nicotine delivery and exposure to selected carcinogens and toxicants.MethodsWe measured seven nicotine metabolites and 17 tobacco smoke exposure biomarkers in the urine samples of 20 smokers collected before and after switching to pen-style M201 e-cigarettes for 2 weeks. Biomarkers were metabolites of 13 major carcinogens and toxicants in cigarette smoke: one tobacco-specific nitrosamine (NNK), eight volatile organic compounds (1,3-butadiene, crotonaldehyde, acrolein, benzene, acrylamide, acrylonitrile, ethylene oxide, and propylene oxide), and four polycyclic aromatic hydrocarbons (naphthalene, fluorene, phenanthrene, and pyrene). Changes in urine biomarkers concentration were tested using repeated measures analysis of variance.ResultsIn total, 45% of participants reported complete abstinence from cigarette smoking at 2 weeks, while 55% reported continued smoking. Levels of total nicotine and some polycyclic aromatic hydrocarbon metabolites did not change after switching from tobacco to e-cigarettes. All other biomarkers significantly decreased after 1 week of using e-cigarettes (p l .05). After 1 week, the greatest percentage reductions in biomarkers levels were observed for metabolites of 1,3-butadiene, benzene, and acrylonitrile. Total NNAL, a metabolite of NNK, declined by 57% and 64% after 1 and 2 weeks, respectively, while 3-hydroxyfluorene levels declined by 46% at week 1, and 34% at week 2.ConclusionsAfter switching from tobacco to e-cigarettes, nicotine exposure remains unchanged, while exposure to selected carcinogens and toxicants is substantially reduced.ImplicationsTo our knowledge, this is the first study that demonstrates that substituting tobacco cigarettes with an e-cigarette may reduce user exposure to numerous toxicants and carcinogens otherwise present in tobacco cigarettes. Data on reduced exposure to harmful constituents that are present in tobacco cigarettes and e-cigarettes can aid in evaluating e-cigarettes as a potential harm reduction device.

Exposure to thirdhand smoke (THS) is a newly described health risk. Evidence supports its widespread presence in indoor environments. However, its genotoxic potential, a critical aspect in risk assessment, is virtually untested. An important characteristic of THS is its ability to undergo chemical transformations during aging periods, as demonstrated in a recent study showing that sorbed nicotine reacts with the indoor pollutant nitrous acid (HONO) to form tobacco-specific nitrosamines (TSNAs) such as 4-(methylnitrosamino)-4-(3-pyridyl)butanal (NNA) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). The goal of this study was to assess the genotoxicity of THS in human cell lines using two in vitro assays. THS was generated in laboratory systems that simulated short (acute)- and long (chronic)-term exposures. Analysis by liquid chromatography-tandem mass spectrometry quantified TSNAs and common tobacco alkaloids in extracts of THS that had sorbed onto cellulose substrates. Exposure of human HepG2 cells to either acute or chronic THS for 24h resulted in significant increases in DNA strand breaks in the alkaline Comet assay. Cell cultures exposed to NNA alone showed significantly higher levels of DNA damage in the same assay. NNA is absent in freshly emitted secondhand smoke, but it is the main TSNA formed in THS when nicotine reacts with HONO long after smoking takes place. The long amplicon-quantitative PCR assay quantified significantly higher levels of oxidative DNA damage in hypoxanthine phosphoribosyltransferase 1 (HPRT) and polymerase β (POLB) genes of cultured human cells exposed to chronic THS for 24h compared with untreated cells, suggesting that THS exposure is related to increased oxidative stress and could be an important contributing factor in THS-mediated toxicity. The findings of this study demonstrate for the first time that exposure to THS is genotoxic in human cell lines.

INTRODUCTION Measuring adherence to smoking cessation pharmacotherapy is important to evaluating its effectiveness. Blood levels are considered the most accurate measure of adherence but are invasive and costly. Pill counts and self-report are more practical, but little is known about their relationship to blood levels. This study compared the validity of pill count and self-report against plasma varenicline concentration for measuring pharmacotherapy adherence. METHODS Data were obtained from a randomized pilot study of varenicline for smoking cessation among African American smokers. Adherence was measured on Day 12 via plasma varenicline concentration, pill count, 3-day recall, and a visual analogue scale (VAS; adherence was represented on a line with two extremes "no pills" and "all pills"). RESULTS The sample consisted of 55 African American moderate to heavy smokers (average 16.8 cigarettes/day, SD = 5.6) and 63.6% were female. Significant correlations (p < .05) were found between plasma varenicline concentration and pill count (r = .56), 3-day recall (r = .46), and VAS (r = .29). Using plasma varenicline concentration of 2.0 ng/ml as the cutpoint for adherence, pill count demonstrated the largest area under the receiver operating characteristic curve (AUC = 0.85, p = .01) and had 88% sensitivity (95% CI = 75.0-95.0) and 80% specificity (95% CI = 30.0-99.0) for detecting adherence. CONCLUSIONS Of 3 commonly used adherence measures, pill count was the most valid for identifying adherence in this sample of African American smokers. Pill count has been used across other health domains and could be incorporated into treatment to identify nonadherence, which, in turn, could maximize smoking cessation pharmacotherapy use and improve abstinence rates.

INTRODUCTION Black smokers are reported to have higher lung cancer rates and greater tobacco dependence at lower levels of cigarette consumption compared to non-Hispanic White smokers. We studied the relationship between cigarettes per day (CPD) and biomarkers of nicotine and carcinogen exposure in Black and White smokers. METHODS In 128 Black and White smokers, we measured plasma nicotine and its main proximate metabolite cotinine, urine nicotine equivalents, 4-(methylnitrosamino)-1-(3)pyridyl-1-butanol (NNAL), and polycyclic aromatic hydrocarbon (PAH) metabolites. RESULTS The dose-response between CPD and nicotine equivalents, and NNAL and PAH was flat for Black but positive for White smokers (Race × CPD interaction, all ps < .05). Regression estimates for the Race × CPD interactions were 0.042 (95% CI 0.013-0.070), 0.054 (0.023-0.086), and 0.028 (0.004-0.052) for urine nicotine equivalents, NNAL, and PAHs, respectively. In contrast there was a strong correlation between nicotine equivalents and NNAL and PAH independent of race. Nicotine and carcinogen exposure per individual cigarette was inversely related to CPD. This inverse correlation was stronger in Black compared to White smokers and stronger in menthol compared to regular cigarette smokers (not mutually adjusted). CONCLUSIONS Our data indicate that Blacks on average smoke cigarettes differently than White smokers such that CPD predicts smoke intake more poorly in Black than in White smokers.

INTRODUCTION Secondhand smoke (SHS) contains respiratory irritants and has the potential to adversely affect adults with chronic obstructive pulmonary disease (COPD), but few studies have evaluated the impact of SHS on COPD. METHODS We used data from 72 nonsmoking participants in a cohort study of COPD. Urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) was measured as an indicator of longer term SHS exposure, whereas urine cotinine was assessed as a measure of more recent exposure. The impact of SHS exposure on COPD-related health status was examined using multivariate linear regression (controlling for age, sex, race, educational attainment, and smoking history). Health status was measured using a validated COPD severity score, reported dyspnea, a standard health status measure (Short Form-12), and activity restriction. RESULTS The urine NNAL-to-creatinine ratio (per interquartile increment) was associated with greater COPD severity (mean score increase 1.7 points; 95% CI 0.6-2.8; p = .0003). Higher urine NNAL was also related to greater dyspnea, poorer physical health status, and more restricted activity (p < or = .05 in all cases). When considered simultaneously, longer term exposure (NNAL) had a greater negative impact on COPD status than shorter term exposure (cotinine). DISCUSSION Urine NNAL can be used to estimate longer term SHS exposure and negatively affects a number of health outcomes among adults with COPD. Screening for and prevention of SHS exposure among persons with COPD may be beneficial.

Plasma or saliva cotinine concentrations are used widely as biomarkers of secondhand smoke (SHS) exposure and have been associated with the risk of SHS-related disease. Concentrations of cotinine and other nicotine metabolites are considerably higher in urine than in plasma or saliva, making chemical analysis easier. In addition, urine is often more convenient to collect in some SHS exposure studies. The optimal use of nicotine metabolites in urine, singly or in combination, with or without correction for urine creatinine concentration, to estimate plasma cotinine concentration with low-level nicotine exposure has not been determined.We dosed 36 nonsmokers with 100, 200, or 400 microg deuterium-labeled nicotine (simulating exposure to SHS) by mouth daily for 5 days and then measured plasma and urine cotinine and metabolites at various intervals over 24 hr.A plasma cotinine concentration of 1 ng/ml corresponds on average to a daily intake of 100 microg nicotine. Cotinine concentrations in urine averaged four to five times those in plasma. Correction of urine cotinine for creatinine concentration improved the correlation between urine and plasma cotinine. Measuring multiple cotinine metabolites in urine did not improve the correlation with plasma cotinine, compared with the use of urine cotinine alone.Measurement of urine cotinine corrected for creatinine concentration appears to be the best predictor of plasma cotinine.

Gamma-hydroxybutyric acid (GHB) is used as an illicit drug and is implicated in drug-facilitated sexual assault, but it also has some therapeutic uses. Detection of GHB in urine is important for forensic testing and could be of clinical benefit in overdose management. Urine GHB concentration-time profiles have not been well-characterized or correlated with doses used therapeutically. GHB levels were measured by gas chromatography–mass spectrometry in urine collected over 24 h from 16 adults administered single doses of 50 mg/kg GHB (Xyrem®) alone and combined with 0.6 g/kg ethanol. Peak GHB urine concentrations averaged 150–200 mg/L and occurred in the 0–3 h urine collection. Significant variability in GHB urine levels between individuals was observed. Caucasians had lower urine concentrations than other races/ethnicities (p = 0.03). Men had lower GHB levels than women in the first 3 h after dosing (p = 0.038). Coingestion of ethanol did not significantly affect renal clearance of GHB, but urine GHB concentrations were lower in the first 3 h when ethanol and GHB were coingested (p = 0.039). At a proposed cut-off of 10 mg/L to distinguish endogenous versus exogenous GHB levels, 12.5% of the samples collected from 3 to 6 h, 81.3% of samples collected from 6 to 12 h, and 100% of urine specimens collected from 12 to 24 h were below this level. We conclude that the detection time for GHB in urine may be shorter than the previously reported 12-h window in some people taking therapeutic doses of GHB.

Dietary supplements that contain Ma Huang (ephedra alkaloids) and guarana (caffeine) are widely marketed and used in the U.S. for weight loss and athletic performance enhancement, despite a lack of adequate research on the pharmacology of these botanical stimulants. We developed and applied a novel liquid chromatography-tandem mass spectrometry (LC-MS-MS) method to quantitate the various ephedra alkaloids found in dietary supplements that contain Ephedra species. The quantities of ephedrine, pseudoephedrine, norephedrine, norpseudoephedrine, methylephedine, methylpseudoephedrine, and caffeine were determined for 35 commercial dietary supplements and compared with the amounts listed on the product labels. The total ephedra alkaloid content ranged from 5.97 mg to 29.3 mg per serving. Two supplement brands did not list the quantity of ephedra alkaloids on the label, and four did not list the amount of caffeine per serving. Of the products tested, 31% contained110% of the total ephedra alkaloids listed on the label, and 6% of the supplements contained90% of the listed amount. For caffeine, 86% of the product lots that listed the caffeine amount contained less than 90% of the labeled quantity. No products contained110% of the declared caffeine content. The total ephedra alkaloid content varied significantly from lot to lot in 5 of 9 products. Three product brands contained proportions of alkaloids that exceeded amounts reported for E. sinica, including one that was 98% ephedrine, one that had 10% norpseudoephedrine, and one that contained an average of 13% methylephedrine. We conclude that product inconsistency is common among some commercially available dietary supplements that contain ephedra alkaloids and caffeine.

The rate of nicotine metabolism is hypothesized to be a determinant of how much a person smokes. That is, rapid metabolizers would be expected to need more nicotine and, therefore, smoke more than slow metabolizers. Nicotine is metabolized extensively by the liver enzyme CYP2A6, primarily to cotinine. Cotinine is itself metabolized by CYP2A6 to 3'-hydroxycotinine (3-HC). The ratio of metabolite to parent (i.e., 3-HC:cotinine) would be expected to reflect CYP2A6 activity. We measured the ratio of 3-HC:cotinine in the urine of 72 smokers. This ratio was significantly correlated with the number of cigarettes smoked per day (r=.33, p=.005), though not with the Fagerström Test for Nicotine Dependence. This finding supports the hypothesis that the rate of nicotine metabolism is a determinant of the level of cigarette consumption and supports the use of the 3-HC:cotinine ratio as a noninvasive marker of nicotine metabolism.

In order to evaluate race as a possible factor affecting the incorporation of drugs into human hair, 2 mg/kg deuterium-labeled cocaine (cocaine-d5) was administered intranasally to nine male non-Caucasian volunteers under controlled laboratory conditions. Sequential blood samples were collected for up to three days, and scalp hair samples were collected at 24 and 72 h after dosing and at monthly intervals for up to 12 months. The samples were then analyzed by gas chromatography-mass spectrometry for cocaine-d5 and benzoylegonine-d5 (BZE-d5). The amounts of cocaine-d5 found in the hair of these non-Caucasian subjects were compared with the amounts of cocaine-d5 found in the hair of Caucasian subjects who received the same cocaine dose under identical conditions as part of a study we reported previously. The non-Caucasians in the present study had approximately 2.7 times more cocaine-d5 in their hair than the Caucasian subjects in the earlier study. In five of the non-Caucasian subjects, cocaine-d5 could be detected in hair within 24 h after dosing. Curiously, we were unable to detect any cocaine-d5 in one of the non-Caucasian subject's hair at any time after dosing even though cocaine-d5 was in plasma at the expected levels. The results from these studies suggest there may be a racial bias in the incorporation of cocaine into human hair; however, the data are not conclusive because of the relatively small sample size.

Deuterium-labeled cocaine (cocaine-d5) was administered intravenously and/or intranasally in doses of 0.6-4.2 mg/kg to 25 human volunteers under laboratory clinical conditions. Sequential blood samples were collected for up to 3 days, and hair samples were collected for up to 10 months. Samples were analyzed by gas chromatography-mass spectrometry (GC-MS) for cocaine-d5 and its major metabolite, benzoylecgonine-d5 (BZE-d5). The parent drug, cocaine-d5, was the predominant analyte in hair, whereas BZE-d5 was the major analyte in blood, especially at later time periods. The amount of cocaine-d5 incorporated into hair ranged from 0.1 to 5 ng/mg hair, whereas the amount of BZE-d5 was approximately one-sixth of that concentration. The threshold dose for detection was estimated to be 25-35 mg of drug administered intravenously. A single dose could be detected for 2-6 months. Subjects receiving the same dose differed (from two to 12 times as much depending upon how it was measured) in the amount of cocaine-d5 incorporated into their hair. Non-Caucasians, in particular, incorporated more cocaine-d5 in hair than did Caucasians. Also, segmental analysis of the samples revealed considerable intersubject variability in the time drug first appeared in hair and the rate at which the drug moved along the hair shaft with time. These interindividual differences could not be explained by differences in plasma pharmacokinetics. Considered together, these results suggest that cocaine incorporation into hair may occur by way of multiple mechanisms--by way of sweat and sebum, for example--and at various times during the hair growth cycle. Thus, hair analysis using GC-MS appears to be a very sensitive method for detecting cocaine ingestion. However, within the range of doses used in the present study, hair does not provide a particularly accurate record of either the amount, time, or duration of drug use.

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.

The illicit synthesis of the popular drug 3,4-methylenedioxyamphetamine (MDA) has frequently called upon the precursor piperonylacetone, which is reductively aminated with ammonium hydroxide. The term "piperonylacetone" has been used for two distinct chemical entities in the chemical literature, vis., 3,4-methylenedioxyphenylacetone or 3,4-methylenedioxybenzylacetone. It is only the first of these two chemicals which will give rise to MDA. The second chemical has been made commercially available as piperonylacetone and, employing the usual recipes, produces 1-(3,4-methylenedioxyphenyl)-3-aminobutane. This amine could be mistaken for MDA if only simple presumptive tests are employed. This latter base is largely unexplored pharmacologically and toxicologically and, as it may reasonably appear in illicit drug traffic misrepresented as MDA, it may well represent a clinical problem of unforseeable consequences.