Is 24h nicotine equivalents a surrogate for smoke exposure based on its relationship with other biomarkers of exposure?

UNLABELLED: Nicotine and its 5 major metabolites (Nicotine equivalents, NE) may serve as a surrogate biomarker for smoke exposure. OBJECTIVE: To investigate the relationship between nicotine equivalents (NE) and biomarkers of exposure (BOE) to cigarette smoke. METHODS: Data from nine controlled studies in 916 adult smokers were used. BOEs to nicotine, NNK, pyrene, acrolein, benzene, 1,3-butadiene and CO were used. RESULTS: Among all the factors investigated (NE, cigarette type, age, gender, BMI and study), NE was the most statistically significant factor for all biomarker relationships. Weak to moderate relationships (0.32 ≤ R(2) ≤ 0.65) were found between NE and the BOEs. CONCLUSIONS: Based on the relationships with BOEs, NE may be considered as a surrogate biomarker of total cigarette smoke exposure.

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.

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.

Adaptive regression modeling of biomarkers of potential harm in a population of U.S. adult cigarette smokers and nonsmokers.

BACKGROUND: This article describes the data mining analysis of a clinical exposure study of 3585 adult smokers and 1077 nonsmokers. The analysis focused on developing models for four biomarkers of potential harm (BOPH): white blood cell count (WBC), 24 h urine 8-epi-prostaglandin F2alpha (EPI8), 24 h urine 11-dehydro-thromboxane B2 (DEH11), and high-density lipoprotein cholesterol (HDL). METHODS: Random Forest was used for initial variable selection and Multivariate Adaptive Regression Spline was used for developing the final statistical models RESULTS: The analysis resulted in the generation of models that predict each of the BOPH as function of selected variables from the smokers and nonsmokers. The statistically significant variables in the models were: platelet count, hemoglobin, C-reactive protein, triglycerides, race and biomarkers of exposure to cigarette smoke for WBC (R-squared = 0.29); creatinine clearance, liver enzymes, weight, vitamin use and biomarkers of exposure for EPI8 (R-squared = 0.41); creatinine clearance, urine creatinine excretion, liver enzymes, use of Non-steroidal antiinflammatory drugs, vitamins and biomarkers of exposure for DEH11 (R-squared = 0.29); and triglycerides, weight, age, sex, alcohol consumption and biomarkers of exposure for HDL (R-squared = 0.39). CONCLUSIONS: Levels of WBC, EPI8, DEH11 and HDL were statistically associated with biomarkers of exposure to cigarette smoking and demographics and life style factors. All of the predictors together explain 29%-41% of the variability in the BOPH.

The effect of menthol containing cigarettes on adult smokers' exposure to nicotine and carbon monoxide.

UNLABELLED: There is limited information comparing biomarkers of exposure (BOE) to cigarette smoke in menthol (MS) and non-menthol cigarette smokers (NMS). OBJECTIVE: To compare BOE to nicotine and carbon monoxide in MS and NMS. METHODS: Cross-sectional, observational, ambulatory, multi-centre study in 3341 adult cigarette smokers. Nicotine equivalents (NE) in 24h urine, NE/cigarette, COHb and serum cotinine were measured. Statistical analyses included analysis of variance and Wilcoxon test. RESULTS: Analyses of variance revealed no statistically significant effects of mentholated cigarettes on NE/24h, COHb, serum cotinine and NE/cigarette. On average MS smoked 15.0 and NMS 16.8 cigarettes/day. The unadjusted mean differences were as follows: MS had lower NE/24h (5.4%) and COHb (3.2%), higher serum cotinine (3.0%) and NE/cigarette (5.7%) than NMS. African-Americans MS smoked 40% fewer cigarettes, showed lower NE/24h (24%) and COHb (10%) and higher NE/cig (29%) and serum cotinine (8%) levels than their White counterparts. CONCLUSIONS: Smoking mentholated cigarettes does not increase daily exposure to smoke constituents as measured by NE and COHb. These findings are consistent with the majority of epidemiological studies indicating no difference in smoking related risks between MS and NMS.

Short term effects of reduced exposure to cigarette smoke on white blood cells, platelets and red blood cells in adult cigarette smokers.

UNLABELLED: Previous studies indicate that cigarette smokers have a 5-30% higher white blood cell counts (WBC) compared to non-smokers and higher red blood cell counts. METHODS: This study was to pool hematology data from three similar studies and analyze the data for effects on WBC, its subpopulations, platelets, red blood cell count (RBC) and hematocrit in adult cigarette smokers three days after using an electrically heated cigarette smoking system (EHCSS) as a potential reduced exposure product (PREP) or no-smoking compared to smoking a conventional cigarette. RESULTS: Lower exposure to cigarette smoke in adult, long term smokers, by using an EHCSS or stopping smoking, leads to statistically significant decreases of up to 9% in WBC, neutrophils, lymphocytes, platelets, RBC and hematocrit within three days. Switching from CC-smoking to EHCSS-smoking or no-smoking resulted in lower WBC and vice versa within 3 days. CONCLUSION: This clinical model may be used as a screening tool to find new technologies that could provide insights on changes in inflammation resulting from the change in cigarette smoke.

Population estimates for biomarkers of exposure to cigarette smoke in adult U.S. cigarette smokers.

INTRODUCTION: There are about 4,800 different chemical constituents in cigarette smoke. Therefore, the total systemic exposure evaluation of the population of smokers to cigarette smoke is challenging. Measurement of biomarkers as surrogates of cigarette smoke constituents is a realistic approach to assess exposure. OBJECTIVE: To estimate cigarette smoke exposure of the U.S. smoker population. METHODS: Stratified, cross-sectional, multicenter design (39 sites in 31 states); 3,585 adult cigarette smokers and 1,077 nonsmokers. Biomarkers were determined from 24-hr urine collections or blood samples. Population estimates were generated by weighting sample data with weights from a large U.S. probability sample (Behavioral Risk Factor Surveillance System). RESULTS: The adult smoker population estimates for tobacco-specific biomarkers were nicotine equivalents 13.3 mg/24 hr (SE 0.14), serum cotinine 184 ng/ml (1.8), and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol 439 ng/24 hr (5.5). The population estimates for smokers and nonsmokers for nontobacco-specific biomarkers were 1-hydroxypyrene 317 (6.8) and 110 (7.1) ng/24 hr, 4-aminobiphenyl Hb adducts 43.1 (1.04) and 11.4 (1.5) pg/g Hb, carboxyhemoglobin 5.26(0.04) in percent of hemoglobin saturation and 1.45(0.02), 3-hydroxypropylmercapturic acid 2,030 (24) and 458 (17) microg/24 hr, monohydroxy-butenyl-mercapturic acid 3.61 (0.1) and 0.30 (0.02) microg/24 hr, and dihydroxy-butyl-mercapturic acid 556 (4.9) and 391 (5.5) microg/24 hr. On average, young adult smokers had lower exposure than older smokers; female smokers had lower exposure than males, and Black smokers had lower exposure than Whites. DISCUSSION: This study estimated the population exposure to cigarette smoke constituents in adult U.S. smokers and identified significant differences between subpopulations. The data may serve as a reference for monitoring the impact of changes in cigarette consumption and the introduction of potentially reduced exposure cigarettes.

Heart rate variability increases with reductions in cigarette smoke exposure after 3 days.

BACKGROUND: Smoking has been shown to influence the tone of the autonomic nervous system as reflected by heart rate variability (HRV). To date, no information is available as to whether 24-hour HRV might differentiate users of different tobacco products. OBJECTIVE: To assess the differences in HRV derived from the 24-hour electrocardiogram (ECG) following the use of 2 tobacco products of potentially different exposures. METHODS: Thirty adult Caucasian male smokers (mean age: 42.8 + 5.7 years) smoking 20 to 40 cigarettes/ day were randomized in a 3-way crossover study design to either smoke a conventional cigarette (CC, tar: 11 mg, Nic: 0.8 mg), to use the Electrically Heated Cigarette Smoking System (EHCSS: tar: 5 mg, Nic: 0.3 mg, according to the Federal Trade Commission [FTC]), or to stop smoking (NS) for 3 days each. The 24 hours ECGs were recorded during the last 24 hours of each exposure period. RESULTS: A 24-hour ECG showed highest mean values for standard deviation of all normal-to-normal heart beat (NN) intervals (SDNN), standard deviation of all 5-minute averaged NN intervals in a 24-hour period (SDANN), mean of the standard deviations of the NN intervals calculated from all 5-minute segments in a 24-hour period (SDNNI), percentage (P) of all NN intervals that differ by 50 milliseconds of all NN (PNN50%), the square root of the mean of all squared differences between adjacent NN intervals in 24-hour period (RMSSD), and total number of all NN intervals divided by the height of the histogram of all NN intervals measured on a discrete scale with bins of 7 x 8125 ms (1/128 seconds; HRVTI) when participants stopped smoking followed by the use of the reduced exposure product and CC. CONCLUSION: Heart rate variability tended to increase with reduced smoke exposure.

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.

Quantitation of N'-nitrosonornicotine (NNN) in smokers' urine by liquid chromatography-tandem mass spectrometry.

The tobacco-specific nitrosamine N'-nitrosonornicotine (NNN) is carcinogenic to humans (IARC Group 1). Assessing the tobacco smoke-related exposure to NNN by suitable biomarkers is of interest for risk evaluation. Recently, NNN and NNN-N-glucuronide have been quantified in urine of smokers. However, it is unknown what percentage of the absorbed dose of NNN is excreted as total NNN (sum of free and conjugated NNN) in urine of smokers. We developed a sensitive method based on liquid chromatography with tandem mass spectrometry with deuterium-labeled internal standard for the determination of total NNN in human urine. The limit of quantitation of the method was 2 pg/mL with a calibration line linear up to 256 pg/mL. In a study with 16 smokers in which the respiratory retention of NNN was measured through controlled smoking, we found that on average about 1% of the pulmonary NNN dose was excreted in 24 h urine as total NNN.

Respiratory retention of nicotine and urinary excretion of nicotine and its five major metabolites in adult male smokers.

Urinary excretion of nicotine and its five major metabolites (nicotine-N-glucuronide, cotinine, cotinine-N-glucuronide, trans-3'-hydroxycotinine, and trans-3'-hydroxycotinine-O-glucuronide), expressed as nicotine equivalents (NE), has been used as a biomarker of smoking-related nicotine exposure. In this open-label, single center study, we investigated the relationship between nicotine retention from smoking and urinary excretion of NE in adult smokers. After a 4-day washout period, 16 adult male smokers smoked 6 cigarettes per day for four consecutive days according to three predefined smoking patterns: no inhalation (Pattern A), normal inhalation (Pattern B), and deep inhalation (Pattern C). The amount of nicotine retained in the respiratory tract during smoking was estimated from the difference between the amounts of nicotine delivered and exhaled. The daily excretion of urinary NE was measured in 24h urine samples by LC-MS/MS. The mean (+/-S.D.) amount of nicotine retained was 0.126+/-0.167, 0.960+/-0.214, and 1.070+/-0.223mg/cig for Patterns A, B, and C, respectively. The mean (+/-S.D.) relative retention (the amount retained relative to the amount delivered) was 11.2+/-14.7%, 98.0+/-1.6%, and 99.6+/-0.3% for Patterns A, B, and C, respectively. On the fourth day of smoking, an average of 86+/-20% of the total daily amount of retained nicotine was recovered as NE in 24h urine. Nicotine equivalents was treated as a single component and the data was described by a first-order elimination pharmacokinetic model which assumed instantaneous input and distribution. Based on this model, the elimination half-life of NE was 19.4+/-2.6h, and the NE excretion had reached approximately 96% of the steady state levels by Day 4. Our results suggest that most of the nicotine inhaled from a cigarette is retained (> or =98%) in the lung, and at steady state, daily urine NE excretion reflects approximately 90% of the retained nicotine dose from cigarette smoking.

A new method for estimating the retention of selected smoke constituents in the respiratory tract of smokers during cigarette smoking.

This report describes a new method for estimating the retention of selected mainstream smoke constituents in the respiratory tract of adult smokers during cigarette smoking. Both particulate-phase (PP) constituents including nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), and N'-nitrosonornicotine (NNN), two tobacco-specific nitrosamines (TSNA), and gas-vapor-phase (GVP) constituents including carbon monoxide (CO), isoprene (IP), acetaldehyde (AA), and ethylene, were studied. To estimate the amounts of smoke constituents delivered during smoking, we used predetermined linear relationships between the measured cigarette filter solanesol content and machine-generated mainstream deliveries of these selected compounds. To determine the amounts of smoke constituents exhaled, the expired breath was directed through a Cambridge filter pad (CFP) attached to an infrared spectrometer. PP compounds were trapped on the CFP for later analysis and GVP compounds were analyzed in near real time. The smokers' respiratory parameters during smoking, such as inhalation/exhalation volume and time, were monitored using LifeShirt(R), a respiratory inductive plethysmography (RIP) device. The retention of each smoke constituent, expressed as a percentage, was then calculated as the difference between the amount delivered (estimated) and the amount exhaled relative to the amount delivered. We studied 16 adult male smokers who smoked cigarettes according to 3 predefined smoking patterns: no inhalation (pattern A), normal inhalation (pattern B), and deep inhalation (pattern C). For the three PP constituents, the mean retentions for pattern A ranged between 10 and 20%; and while the mean retentions of the two TSNAs were significantly higher for pattern C (84% for NNK and 97% for NNN) than those for pattern B (63% for NNK and 84% for NNN), the mean retentions of nicotine were basically the same between patterns B and C, which were both greater than 98%. For the GVP constituents, the retentions were similar between pattern B and pattern C, although different constituents were retained to different degrees (average values of 33%, 52%, 79%, and 99% for ethylene, IP, CO, and AA, respectively). The differences in the retention between different constituents could be interpreted in terms of each constituent's physical properties such as volatility and solubility. In conclusion, the method described is suitable for studying the retention of selected mainstream smoke constituents in the respiratory tract of smokers.

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 F(2α) (8-epiPGF(2α))] and platelet activation [11-dehydro-thromboxin B(2) (11-dehTxB(2))], 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-epiPGF(2α), respectively, and gender and smoking duration for 11-dehTxB(2) and vWF, respectively. CONCLUSIONS: Although several demographic factors and some BOEs were statistically significant in the model, the R(2) 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.

A randomized, controlled exposure study in adult smokers of full flavor Marlboro cigarettes switching to Marlboro Lights or Marlboro Ultra Lights cigarettes.

Rationale. To date no state-of-the-art clinical study has been conducted to address the question as to whether switching to lower tar cigarettes reduces exposure to smoke constituents in humans. Methods. Randomized, controlled, forced switching study in 225 adult smokers of full flavor Marlboro (MFF) cigarettes for 8 days with a 24-week follow-up. Subjects smoked MFF (a 15-mg Federal Trade Commission (FTC) tar cigarette) at baseline and were randomized to smoke 11-mg Marlboro Lights (ML) or 6-mg Marlboro Ultra Lights (MUL) cigarettes. Biomarkers of exposure to nicotine, 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), pyrene, CO, benzene, acrolein, and mutagenic substances were measured. Results. In the short-term phase, switching from MFF to ML showed statistically significant decreases in nicotine exposure (-13%) and non-significant increases in CO exposure (+6%), while switching from MFF to MUL showed statistically significant decreases in nicotine (-27%) and CO (-13%) exposure. Both nicotine and CO biomarkers trended similarly in the 24-week follow-up as in the short-term phase. The other biomarkers of cigarette smoke constituents followed the same trend as nicotine at the end of the 24-week follow-up. Conclusions. Switching smokers to lower FTC tar yield cigarettes, on average, reduces nicotine and other biomarkers considered surrogates of tar exposure.

The effect of cigarette burn time on exposure to nicotine and carbon monoxide in adult smokers.

Cigarette burn time (CBT), conventionally defined as the time a cigarette burns during smoking, can be affected by cigarette design and smoking behavior. A previous study showed a strong negative correlation between CBT and nicotine yield under machine smoking conditions. This study for the first time examined the relationship of CBT and exposure to nicotine and carbon monoxide in adult smokers in a controlled clinical study. 24h nicotine equivalents excretion (NE), carboxyhemoglobin (COHb) and CBT were measured in two groups of 20 adults smoking Marlboro Lights and 20 adults smoking Marlboro Ultra on two consecutive days. Approximately 20% of the total variability in CBT was attributed to cigarette brand, 34% to smokers and 1% to study day. The exposure index, defined as the number of cigarettes smoked per day divided by average daily CBT for each smoker, accounted for a large proportion of the total variability in NE (R(2)=0.79-0.91) and COHb (R(2)=0.85-0.90). We conclude that CBT has an important influence on levels of NE and COHb in adult smokers. CBT, along with the number of cigarettes smoked per day, can be used to estimate adult smokers' exposure to nicotine and carbon monoxide.