Kimberly Frost-Pineda

Biomarkers of Potential Harm Among Adult Smokers and Nonsmokers in the Total Exposure Study

INTRODUCTION There is overwhelming medical and scientific consensus that cigarette smoking causes lung cancer, heart disease, emphysema, and other serious diseases in smokers. In the Total Exposure Study, 29 biomarkers of potential harm (BOPH) were measured in a cross-sectional sample of 3,585 adult smokers (AS) and 1,077 nonsmokers (NS). The BOPH included markers of oxidative stress, inflammation, platelet activation, endothelial function, lipid metabolism, hematology, metabolism, the cardiovascular system, lung function, kidney function, and liver function. METHODS Multiple stepwise regression was used to examine the effect of demographic factors (age, gender, body mass index [BMI], and race) and smoking (number of cigarettes smoked per day or nicotine equivalents [NE] per 24 hr and smoking duration) on each BOPH. RESULTS As compared with NS, AS had >10% higher levels of 8-epi-prostaglandin F(2α) (8-epi-PG F(2α), 42%), 11-dehydrothromboxane B₂ (11-DHTB, 29%), white blood cell (WBC) count (19%), high-sensitivity C-reactive protein (15%), triglycerides (16%), and alkaline phosphatase (11%) and had 18% lower total bilirubin. Multiple stepwise regression revealed that although NE (milligrams per 24 hours) was statistically significant for 18 of the 29 BOPH, it was the most important factor only for WBCs and 11-DHTB. Smoking duration was the most important factor for forced expiratory volume in 1 second. In contrast, BMI was the most important factor for 12 BOPH. CONCLUSIONS These results contribute to the understanding of the relationship between tobacco smoking and potential biological effects.

Evaluation of biomarkers of exposure to selected cigarette smoke constituents in adult smokers switched to carbon-filtered cigarettes in short-term and long-term clinical studies

Cigarette smoke is a complex aerosol that includes a gas vapor phase and a particulate phase. Inclusion of activated carbon in the cigarette filter can reduce some of the gas-phase smoke constituents implicated as toxicologically relevant. The present study evaluated exposure to selected gas-phase constituents when adult smokers switched to prototype cigarettes with a highly activated carbon filter. Smokers (N = 160) in two separate studies were randomized to continue to smoke conventional cigarettes (either a 6-mg or 11-mg FTC tar product), to smoke test cigarettes containing carbon filters (comparable tar levels), or to stop smoking. After completing 8 days in controlled smoking conditions (short-term studies), smokers had the option to continue in 24-week long-term ambulatory studies with unrestricted smoking. Urinary excretion of mercapturic acid metabolites of 1,3-butadiene, acrolein, and benzene; nicotine and five of its metabolites, total NNAL, and 1-hydroxypyrene were measured at baseline in the conventional cigarette group, in all groups in the short-term studies, and every 4 weeks in the long-term studies. In the short-term studies, statistically significant reductions (>70%, p<.001) in gas-phase biomarker levels were observed in the test cigarette group for both tar level products compared with the conventional cigarette group. These reductions were similar to those observed in the stop-smoking groups. The reductions continued consistently (p<.001) throughout the long-term studies. Switching to test cigarettes minimally affected the particulate-phase biomarkers. Statistically significant and consistent reductions in selected gas vapor phase biomarkers were observed when smokers switched to activated carbon filter cigarettes.

Relationship between Biomarkers of Cigarette Smoke Exposure and Biomarkers of Inflammation, Oxidative Stress, and Platelet Activation in Adult Cigarette Smokers

Background: Cigarette smoking is a risk factor for several diseases, including cardiovascular disease, chronic obstructive pulmonary disease, and lung cancer, but the role of specific smoke constituents in these diseases has not been clearly established. Methods: The relationships between biomarkers of potential harm (BOPH), associated with inflammation [white blood cell (WBC), high sensitivity C-reactive protein (hs-CRP), fibrinogen, and von Willebrand factor (vWF)], oxidative stress [8-epi-prostaglandin F2α (8-epiPGF2α)] and platelet activation [11-dehydro-thromboxin B2 (11-dehTxB2)], and machine-measured tar yields (grouped into four categories), biomarkers of exposure (BOE) to cigarette smoke: nicotine and its five metabolites (nicotine equivalents), 4-methylnitrosamino-1-(3-pyridyl)-1-butanol (total NNAL), carboxyhemoglobin, 1-hydroxypyrene, 3-hydroxypropylmercapturic acid, and monohydroxybutenyl-mercapturic acid, were investigated in 3,585 adult smokers and 1,077 nonsmokers. Results: Overall, adult smokers had higher levels of BOPHs than nonsmokers. Body mass index (BMI), smoking duration, tar category, and some of the BOEs were significant factors in the multiple regression models. Based on the F value, BMI was the highest ranking factor in the models for WBC, hs-CRP, fibrinogen, and 8-epiPGF2α, respectively, and gender and smoking duration for 11-dehTxB2 and vWF, respectively. Conclusions: Although several demographic factors and some BOEs were statistically significant in the model, the R2 values indicate that only up to 22% of the variability can be explained by these factors, reflecting the complexity and multifactorial nature of the disease mechanisms. Impact: The relationships between the BOEs and BOPHs observed in this study may help with the identification of appropriate biomarkers and improve the design of clinical studies in smokers. Cancer Epidemiol Biomarkers Prev; 20(8); 1760–9. ©2011 AACR.

Does Dual Use Jeopardize the Potential Role of Smokeless Tobacco in Harm Reduction

INTRODUCTION The use of smokeless tobacco as part of a strategy to reduce the harm from cigarette smoking is a topic of debate within the tobacco control and public health communities. One concern voiced regarding endorsement of such a tactic is the possibility of actually increasing harm should current smokers adopt dual cigarette/smokeless tobacco use (dual use), which could lead to unintended consequences by perpetuating cigarette smoking, diminishing tobacco cessation, or increasing tobacco-related harm. METHODS Here, we review the available literature on health effects and trajectories of use among dual users from a variety of U.S. and European epidemiological studies. RESULTS These data suggest that there are not any unique health risks associated with dual use of smokeless tobacco products and cigarettes, which are not anticipated or observed from cigarette smoking alone. Furthermore, studies show that dual users smoke fewer cigarettes than exclusive smokers, and studies of tobacco use patterns over time (tobacco use trajectory data) indicate that dual users are more likely than exclusive cigarette smokers to cease smoking. CONCLUSIONS Overall, the concern about dual use appears to be contradicted by the evidence in the literature that dual use of smokeless tobacco and cigarettes may result in reduction in smoking-related harm as smoking intensity is decreased and smoking cessation increases.

The relationship between smoking machine derived tar yields and biomarkers of exposure in adult cigarette smokers in the US

UNLABELLED Comprehensive data on human exposure to smoke constituents from different machine-measured tar yield cigarettes is limited. METHODS This study used a stratified, cross-sectional, multi-center design to estimate biomarkers of exposure (BOE) from nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), pyrene, CO, acrolein, and 1,3-butadiene and their relationship to tar yield categories of cigarette in adult smokers in the U.S. 3625 adults smokers were enrolled into four tar categories < or =2.9 mg (T1), 3.0-6.9 mg (T2), 7.0-12.9 mg (T3), and > or =13.0mg (T4). Biomarkers were measured in blood (carboxyhemoglobin, 4-aminobiphenyl-hemoglobin (4-ABP-Hb)-adducts, serum cotinine) and 24h urine (nicotine and five metabolites, calculated as nicotine equivalents (NE), NNAL, 1-OH-pyrene, 3-HPMA, MHBMA and DHBMA). Data were analyzed using analysis of covariance (ANCOVA). RESULTS Tar was a significant factor for most biomarkers in the ANCOVA models. The largest least square mean differences between tar categories was 35% for NE per day, 28% for NE per cigarette, 36% for serum cotinine, 42% for NNAL per day, 29% for NNAL per cigarette, 26% for 1-OHP, 24% for COHb, 14% for 3-HPMA and 40% for 4-ABP-Hb. Variability in BOE ranged from 41% to 154% CV. CONCLUSIONS There was a statistically significant effect of machine-measured tar yield on most BOE, which were generally lower with lower tar yield.

The relationship between nicotine dependence scores and biomarkers of exposure in adult cigarette smokers.

BACKGROUND Tobacco dependence is a multidimensional phenomenon. The Fagerström Test for Nicotine Dependence (FTND) is a widely administered six-item questionnaire used as a measure of nicotine dependence. It has been suggested that this test may not represent the entire spectrum of factors related to dependence. Also the relationship of this test with biomarkers of exposure to cigarette smoke has not been extensively studied. METHODS Data from a multi-center, cross-sectional, ambulatory study of US adult smokers (the Total Exposure Study, TES) was analyzed. The FTND score and a number of additional questions related to smoking behavior, from an adult smoker questionnaire (ASQ) completed by 3585 adult smokers in the TES were analyzed. The 24-h urine nicotine equivalents, serum cotinine and blood carboxyhemoglobin were measured as biomarkers of exposure (BOE) to nicotine and carbon monoxide. Cigarette butts returned were collected during the 24-h urine collection period. RESULTS The FTND showed moderate correlations with BOE, while selected questions from ASQ although statistically significant, had weaker correlations. FTND scores showed substantially weaker correlations without the question about cigarettes smoked per day (CPD). CPD and time to first cigarette (TTFC) had the most impact on BOE. CONCLUSION Additional questions from ASQ did not appear to contribute towards refining the FTND test. The correlation of the FTND scores with nicotine and carbon monoxide seems to be primarily driven by CPD. CPD and TTFC were the most important factors correlating with exposure.

Environmental tobacco smoke (ETS) evaluation of a third-generation electrically heated cigarette smoking system (EHCSS)

This sub-study of a randomized, controlled, forced-switching, open-label, parallel-group, clinical study compared environmental tobacco smoke (ETS) produced when 60 male and female adult smokers switched to a third-generation electrically heated cigarette smoking system (EHCSS), continued to smoke a conventional cigarette (CC), or stopped smoking (No-smoking). Concentrations of air constituents including respirable suspended particulate (RSP), carbon monoxide (CO), ammonia and total volatile organic compounds (TVOCs) and ETS markers including solanesol-related particulate matter (Sol-PM), ultraviolet absorbing particulate matter (UVPM), fluorescent particulate matter (FPM), nicotine and 3-ethenyl pyridine (3-EP) were measured in a ventilated, furnished conference room over a 2-h period on separate occasions for each smoking condition. When the EHCSS was used, concentrations of CO and most ETS markers were in the same range as during no-smoking. Concentrations of ammonia were reduced by 41% and concentrations of other selected constituents of ETS were reduced by 87-99% in the air of a room in which EHCSS cigarettes were smoked as compared to concentrations in the same room when conventional cigarettes were smoked. Switching from conventional cigarette smoking to the EHCSS resulted in substantial reductions in concentrations of several markers of environmental tobacco smoke.

Factors affecting exposure to nicotine and carbon monoxide in adult cigarette smokers.

Exposure to cigarette smoke among smokers is highly variable. This variability has been attributed to differences in smoking behavior as measured by smoking topography, as well as other behavioral and subjective aspects of smoking. The objective of this study was to determine the factors affecting smoke exposure as estimated by biomarkers of exposure to nicotine and carbon monoxide (CO). In a multi-center cross-sectional study of 3585 adult smokers and 1077 adult nonsmokers, exposure to nicotine and CO was estimated by 24h urinary excretion of nicotine and five of its metabolites and by blood carboxyhemoglobin, respectively. Number of cigarettes smoked per day (CPD) was determined from cigarette butts returned. Puffing parameters were determined through a CreSS® micro device and a 182-item adult smoker questionnaire (ASQ) was administered. The relationship between exposure and demographic factors, smoking machine measured tar yield and CPD was examined in a statistical model (Model A). Topography parameters were added to this model (Model B) which was further expanded (Model C) by adding selected questions from the ASQ identified by a data reduction process. In all the models, CPD was the most important and highest ranking factor determining daily exposure. Other statistically significant factors were number of years smoked, questions related to morning smoking, topography and tar yield categories. In conclusion, the models investigated in this analysis, explain about 30-40% of variability in exposure to nicotine and CO.

A Well-Mixed Computational Model for Estimating Room Air Levels of Selected Constituents from E-Vapor Product Use

Concerns have been raised in the literature for the potential of secondhand exposure from e-vapor product (EVP) use. It would be difficult to experimentally determine the impact of various factors on secondhand exposure including, but not limited to, room characteristics (indoor space size, ventilation rate), device specifications (aerosol mass delivery, e-liquid composition), and use behavior (number of users and usage frequency). Therefore, a well-mixed computational model was developed to estimate the indoor levels of constituents from EVPs under a variety of conditions. The model is based on physical and thermodynamic interactions between aerosol, vapor, and air, similar to indoor air models referred to by the Environmental Protection Agency. The model results agree well with measured indoor air levels of nicotine from two sources: smoking machine-generated aerosol and aerosol exhaled from EVP use. Sensitivity analysis indicated that increasing air exchange rate reduces room air level of constituents, as more material is carried away. The effect of the amount of aerosol released into the space due to variability in exhalation was also evaluated. The model can estimate the room air level of constituents as a function of time, which may be used to assess the level of non-user exposure over time.

Cigarettes With Different Nicotine Levels Affect Sensory Perception and Levels of Biomarkers of Exposure in Adult Smokers

INTRODUCTION Few clinical studies involving cigarettes have provided a comprehensive picture of smoke exposure, test article characterization, and insights into sensory properties combined. The purpose of these pilot studies was to determine whether cigarettes with different levels of nicotine but similar tar levels would affect sensory experience or smoking behavior so as to significantly alter levels of selected biomarkers of exposure (BOE). METHODS In 2 confined, double-blind studies, 120 adult smokers switched from Marlboro Gold cigarettes at baseline to either 1 of 2 lower nicotine cigarettes or 1 of 2 higher nicotine cigarettes and then to the other cigarette after 5 days. Urinary excretion of exposure biomarkers (nicotine equivalents [NE], total and free 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol [NNAL], 1-hydroxypyrene, and 3-hydroxypropyl mercapturic acid) as well as carboxyhemoglobin and plasma cotinine were measured at baseline, Day 5, and Day 10. Daily cigarette consumption was monitored and sensory characteristics were rated for each cigarette. RESULTS With higher nicotine yield, urine NE, urine total NNAL, and plasma cotinine increased while nonnicotine BOE decreased without changes in cigarette consumption. In contrast, with lower nicotine yield, urine NE, urine total NNAL, and plasma cotinine dropped while nonnicotine BOE and cigarettes per day increased. Higher nicotine cigarettes were rated harsher and stronger than at baseline while lower nicotine cigarettes were less strong. All 4 test cigarettes were highly disliked. CONCLUSIONS These studies demonstrate that abrupt increases or decreases in nicotine and the resulting sensory changes impact BOE through changes in intensity or frequency of smoking.