The interaction between genetics and tobacco consumption in light smokers

Transcription

1 The interaction between genetics and tobacco consumption in light smokers by Zixing Zhu A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Pharmacology and Toxicology University of Toronto Copyright by Zixing Zhu 2014

2 The interaction between genetics and tobacco consumption in light smokers Abstract Zixing Zhu Doctor of Philosophy Department of Pharmacology and Toxicology University of Toronto 2014 Smoking is the largest preventable cause of death globally. In North America, although the overall smoking prevalence has been declining, an increasing number of smokers consume less than 10 cigarettes per day and are referred to as light smokers. Today, light smokers represent more than 30% of the smoking population and are at risk for smoking related mortality and morbidity. For example, light smokers have approximately 15 times higher risk of developing chronic obstructive pulmonary disease and approximately 20 times higher risk of developing lung cancer compared to non-smokers. Yet despite the high prevalence and substantial negative health consequences, light smokers are generally excluded from smoking related studies. Genetic variants in CYP2A6, encoding for the major nicotine-metabolizing enzyme, and CHRNA5-A3- B4, encoding for α5, α3 and β4 nicotinic receptors, are associated with altered tobacco consumption in heavy smokers, yet little is known about the influence of CYP2A6 and CHRNA5- A3-B4 genetic variants on tobacco consumption and smoking cessation in light smokers. In a cross sectional study of 400 Alaska Native individuals, we demonstrated that light smokers had similar nicotine exposure (as indicated by their urinary total nicotine equivalents) as heavy smokers despite self-reporting lower number of cigarettes per day. Like heavy smokers, these ii

3 light smokers titrated their tobacco consumption according to their CYP2A6 activity and CHRNA5-A3-B4 genotype. In addition, gene variants in CYP2A6 and CHRNA5-A3-B4 acted in combination to modify tobacco consumption. Furthermore, our biomarker analyses showed that variation in CYP2A6 metabolic activity, such as those that exist between CYP2A6 genotypes or the sexes, altered cotinine removal to a greater extent than cotinine formation. As a result, cotinine accumulates in individuals with lower CYP2A6 activity resulting in substantially higher cotinine levels for a given tobacco exposure. Overall, the characterization of tobacco consumption levels and the genetic contribution to tobacco consumption in light smokers improved our understanding of smoking behaviors in this increasingly prevalent population and could aid the development of more efficacious smoking cessation strategies. iii

4 ACKNOWLEDGMENTS First, I would like to acknowledge my doctorial supervisor, Dr. Rachel Tyndale, for introducing me to the field of pharmacogenetics and for providing a stimulating and resourceful environment for pharmacogenetic research. Her devotion and wisdom are truly inspiring. I am immensely grateful for her constant support and encouragement throughout my candidature, even during experimental setbacks and delays. I am thankful for the opportunities to work with Dr. Jasjit Ahluwalia, Dr. Neal Benowitz, Ms. Caroline Renner, and Dr. Lisa Cox during my thesis studies. Their professionalism, insight and advice were truly invaluable to me. Special thanks to Dr. Albert Wong and Dr. Jack Uetrecht, my thesis committee members and mentors, for sharing their insights about the clinical implications of pharmacogenetics with me and constantly challenging me to make the findings more clinically relevant. It was a pleasure to have them on my committee. I would also like to thank my colleagues in the pharmacogenetics laboratory. Especially to Ewa Hoffmann and Qian Zhou for their technical expertise and personal encouragement. Furthermore, I would like to thank Nael Al Koudsi, Manki Ho, Jibran Khokhar, Catherine Wassenaar, Matt Binnington, Meghan Chenoweth, and Mark Piliguian for their friendship and advice. Without their companionship and support, my doctorial experience would not be nearly as enjoyable. Finally, I would not be able to complete my doctorial without the support, love and encouragement of my parents. Thank you for standing by me, and always believing in me. Life threw me many curve balls over the years; I am deeply indebted for the continuous support and inspiration from my fiancée, Clair Yang. Her work ethic and dedication are what I have always admired and can only hope to emulate. iv

5 TABLE OF CONTENTS ACKNOWLEDGMENTS... iv TABLE OF CONTENTS... v LIST OF PUBLICATIONS... x LIST OF TABLES... xiii LIST OF FIGURES... xv LIST OF ABBREVIATIONS... xviii LIST OF APPENDICES... xix STATEMENT OF RESEARCH PROBLEM... xx MAIN RESEARCH OBJECTIVES... xxi 1 GENERAL INTRODUCTION Epidemiology of Tobacco Smoking Prevalence The Health Consequences Cancers Respiratory and Cardiovascular Diseases Other Health Consequences Benefits of Smoking Cessation The Clinical and Molecular Neurobiology of Nicotine Dependence Clinical Features of Nicotine Dependence Positive Reinforcements: The Psychoactive Effects of Smoking Negative Reinforcements: Nicotine Withdrawal Titration of Smoking Behaviors Measurements of Nicotine Dependence Mechanisms of Nicotine Dependence Molecular Biology of Nicotinic Receptors The Role of α4β2 nachr in Nicotine Dependence The Role of α7 nachr in Nicotine Dependence The Role of α5, α3 and β4 nachrs in Nicotine Dependence v

6 1.3 Nicotine Pharmacokinetics Absorption and Distribution Metabolism The Primary Metabolites of Nicotine Pharmacology of Nicotine Metabolites The Secondary Metabolites of Nicotine Using the 3HC to COT Ratio as A Marker of CYP2A6 Activity Non- Genetic Sources of Variation in Nicotine Pharmacokinetics Non- Genetic Factors Contribute to Variation in Nicotine Pharmacokinetics by Altering CYP2A6 Activity Non- Genetic Factors Contribute to Variation in Nicotine Pharmacokinetics by Altering Hepatic Blood Flow Renal Clearance of Nicotine Markers of Tobacco Consumption Self- Report Cigarettes Per Day Cotinine Total Nicotine Equivalents NNAL Genetic Influence of Smoking Behaviors in Heavy Smokers Heritability of Smoking Behaviors Variants in Nicotine Pharmacodynamic Genes Alter Tobacco Consumption in Heavy Smokers CHRNA5- A3- B4 and Nicotine Dependence CHRNA5- A3- B4 and Tobacco Consumption CHRNA5- A3- B4 and Health Consequences of Smoking CHRNA5- A3- B4 and Body Weight Variants in Nicotine Pharmacokinetic Genes Alter Tobacco Consumption in Heavy Smokers CYP2A6 and Nicotine Pharmacokinetics CYP2A6 Gene Variants and Nicotine Metabolism CYP2A6 and Interethnic Variability in Nicotine Metabolism CYP2A6 and Tobacco Consumption in Heavy Smokers CYP2A6 and Smoking Cessation Outcomes in Heavy Smokers CYP2A6 and Health Consequences of Smoking Light Smokers vi

7 1.6.1 Prevalence Health Consequences Smoking Characteristics Smoking Cessation Smokeless Tobacco Prevalence Health Consequences Alaska Native Tobacco Users: Light Smoking and Smokeless Tobacco Use STATEMENT OF RESEARCH HYPOTHESES CHAPTER 1: ALASKA NATIVE SMOKERS AND SMOKELESS TOBACCO USERS WITH SLOWER CYP2A6 ACTIVITY HAVE LOWER TOBACCO CONSUMPTION, LOWER TOBACCO- SPECIFIC NITROSAMINE EXPOSURE AND LOWER TOBACCO- SPECIFIC NITROSAMINE BIOACTIVATION Abstract Introduction Material and Methods Results Discussion Significance to Thesis CHAPTER 2: THE ABILITY OF PLASMA COTININE TO PREDICT NICOTINE AND CARCINOGEN EXPOSURE IS ALTERED BY DIFFERENCES IN CYP2A6: THE INFLUENCE OF GENETICS, RACE AND SEX Abstract Introduction Material and Methods Results Discussion Significance to Thesis CHAPTER 3: CHRNA5- A3- B4 GENETIC VARIANTS ALTER NICOTINE INTAKE AND INTERACT WITH TOBACCO USE TO INFLUENCE BODY WEIGHT IN ALASKA NATIVE TOBACCO USERS vii

8 4.1 Abstract Introduction Material and methods Results Discussion Significance to Thesis GENERAL DISCUSSION Strengths and Limitations of Tobacco Consumption Biomarkers Strengths and Limitations of Self- Report CPD and Self- Report Chews per Day Strengths and Limitations of CO and Cotinine as Biomarkers of Tobacco Consumption and Smoking Status Limitations of TNE as a Biomarker of Tobacco Consumption Sum of Plasma COT and 3HC as A Biomarker of Tobacco Consumption Limitations of NNAL: Variability in the Metabolism What Did the Biomarkers Tell Us About Smoking Behaviors in Light Smokers and Smokeless Tobacco Users? Light Smokers Had Similar Total Nicotine Intake to that in Heavy Smokers Smokeless Tobacco Users Are Exposed to High Levels of TSNA: An Undesirable Harm Reduction Approach Iqmik Delivers High Levels of Nicotine and Low Levels of TSNA Future Research: Modifications to Existing Tobacco Dependence Scales Genetics of Nicotine Dependence in Light Smokers and Smokeless Tobacco Users CYP2A Predicting Nicotine Clearance Using CYP2A6 Genotype and NMR Phenotype The Association between CYP2A6 Gene Variants and Tobacco Consumption in Light Smokers and Smokeless Tobacco Users CYP2A6 s Role in Determining Tobacco Related Disease Risks CYP2A6 s Role in Determining Smoking Cessation Outcomes CHRNA5- A3- B The Association between CHRNA5- A3- B4 and Tobacco Consumption in Light Smokers The Functional Consequences of CHRNA5- A3- B4 Variants Implications: Is the Association Between CHRNA5- A3- B4 Variants and Lung Cancer Directly Mediated by Altered Tobacco Consumption? Implications for Smoking Cessation viii

9 5.4 Conclusions BIBLIOGRAPHY APPENDICES ix

10 Research article in the thesis LIST OF PUBLICATIONS Chapter 1: ZHU, A. Z., M. J. Binnington, et al. (2013). Alaska Native smokers and smokeless tobacco users with slower CYP2A6 activity have lower tobacco consumption, lower tobaccospecific nitrosamine exposure and lower tobacco-specific nitrosamine bioactivation. Carcinogenesis 34(1): Chapter 2: ZHU, A. Z., C. Renner, et al. (2013). The ability of plasma cotinine to predict nicotine and carcinogen exposure is altered by differences in CYP2A6: the influence of genetics, race and sex. Cancer Epidemiol Biomarkers Prev Apr; 22(4): Chapter 3: ZHU, A. Z., C. Renner, et al. (2013). CHRNA5-A3-B4 genetic variants alter nicotine intake and interact with tobacco use to influence body weight in Alaska Native tobacco users Addiction 108(10): Additional publications from doctoral work attached in the Appendices RESEARCH ARTICLES Binnington, J. M., ZHU, A.Z. et al. (2012). "CYP2A6 and CYP2B6 genetic variation and its association with nicotine metabolism in South Western Alaska Native people." Pharmacogenet Genomics 22(6): (Appendix A) ZHU, A. Z., L. S. Cox, et al. (2012). "CYP2B6 and Bupropion's Smoking-Cessation Pharmacology: The Role of Hydroxybupropion." Clin Pharmacol Ther 92(6): (Appendix B) Benowitz, N. L., ZHU, A.Z. et al. (2013). "Influence of CYP2B6 genetic variants on plasma and urine concentrations of bupropion and metabolites at steady state." Pharmacogenet Genomics. 23(3): (Appendix C) ZHU, A. Z., Zhou, Q., et al. (2013). Variation in trans-3 -hydroxycotinine glucuronidation does not alter the nicotine metabolite ratio or nicotine intake in African American smokers. PLoS One 8(8): e (Appendix D) ZHU, A. Z., Zhou, Q., et al. (2013). Association of CHRNA5-A3-B4 SNP rs with smoking cessation therapy response in African American smokers. Clin Pharmacol Ther (Under review) (Appendix E) Piliguian, M., ZHU, A. Z., et al. (2013). Novel CYP2A6 variants identified in African Americans are associated with slow nicotine metabolism in vitro and in vivo Pharmacogenetics and Genomics (In press) (Appendix F) x

11 REVIEW ARTICLES Khokhar, J. Y., C. S. Ferguson, ZHU, A. Z. et al. (2010). "Pharmacogenetics of drug dependence: role of gene variations in susceptibility and treatment." Annu Rev Pharmacol Toxicol 50: BOOK CHAPTERS Zhu, A. Z. X. and R. F. Tyndale (2012). Nicotine Metabolism and its Implications. Metabolism of Drugs and Other Xenobiotics. P. Anzenbacher and U. M. Zanger, Wiley-VCH Verlag GmbH & Co. KGaA: Conference Presentations Oral Presentation: ZHU, A.Z. et al., CHRNA5-A3-B4 Gene Variants Interact With Tobacco Use to Influence Body Weight in Alaska Native Tobacco Users. March Annual Meeting for Society of Nicotine & Tobacco Research, Boston, MA USA. PA3-3 Symposium Presentation: ZHU, A.Z. et al., Hydroxybupropion concentration, mediated by CYP2B6 activity, is a major determinant of bupropion efficacy for smoking cessation. March Annual Meeting for Society of Nicotine & Tobacco Research, Houston, TX USA. Symposium 5E Symposium Presentation: ZHU, A.Z. et al., Reduced CYP2A6 activity increases tobacco consumption and NNAL levels: a study in Alaska Native smokers and smokeless tobacco users. March Annual Meeting for Society of Nicotine & Tobacco Research, Houston, TX USA. Symposium 2D Oral Presentation: ZHU, A.Z. et al., Hydroxybupropion level is a major determinant of bupropion s smoking cessation efficacy- the pharmacogenetic role of CYP2B6. Addiction Research Seminar: Pharmacogenetics of tobacco addiction, treatment and related illness, Toronto, ON Oral Presentation: ZHU, A.Z. et al., Hydroxybupropion concentration, mediated by CYP2B6 activity, is a major determinant of bupropion efficacy for smoking cessation. July 2011 NIH Pharmacogenomics Research Network Seminar. Oral Presentation: ZHU, A.Z. et al., The Effect of CYP2B6 Genetic Variation on in vivo Bupropion Pharmacokinetics & Smoking Cessation Outcomes May 2011 Vision in Pharmacology, Toronto, ON, Canada-Best Presentation Award Abstract Presented Poster Presentation: ZHU, A.Z. et al., The Ability of Plasma Cotinine to Predict Tobacco Exposure is Altered by Differences in CYP2A6: the influence of genetics and sex -- Annual Meeting for Society of Nicotine & Tobacco Research, Boston, MA USA. Pos3-148 xi

12 Poster Presentation: ZHU, A.Z. et al., CHRNA5-A3-B4 Genetic Variants Alter Tobacco Consumption in Alaska Native Tobacco Users. -- Annual Meeting for Society of Nicotine & Tobacco Research, Boston, MA USA. Pos1-129 Poster Presentation: ZHU, A.Z. et al., The Utility of Cotinine as a Biomarker of Tobacco Exposure is Altered by Gender and CYP2A6 Genotype: A Pharmacokinetic and Pharmacogenetic Investigation. --14th Conference of the Society for Research on Nicotine and Tobacco -Europe Chapter. Sept Helsinki, Finland. Pos-P29. Travel award winner Poster Presentation: ZHU, A.Z. et al., Common CYP2B6 Genetic Variants Alter the Rates of Nicotine C-Oxidation POS5-68 Feb th Annual Meeting for Society of Nicotine & Tobacco Research, Toronto ON, Canada Poster Presentation: ZHU, A.Z. et al., African Americans Have Unique Genetic Variation in CYP2B6: Implications for Smoking Cessation. July 2010-Canadian Society of Pharmacology Meeting, Toronto, ON, Canada Poster Presentation: ZHU, A.Z. et al., Unique Genetic Variation in CYP2B6 Among African Americans: Potential Impact on Bupropion Pharmacokinetics. April 2010-ISSX Genetic Polymorphisms in Drug Disposition Meeting, Indianapolis, IN, USA Poster Presentation: ZHU, A.Z. et al., African Americans Differ in Frequencies of CYP2B6 Genetic Variants: Potential Impact on Smoking Cessation. - Feb 2010-Society for Research on Nicotine and Tobacco Meeting, Baltimore, MD, USA xii

13 LIST OF TABLES Table 1 The Fagerstrom test for nicotine dependence (Heatherton et al. 1991) Table 2 CYP2A6 alleles, their allele frequencies and in vitro and in vivo impacts on nicotine clearance Table 3 Baseline demographics by plasma NMR strata and CYP2A6 genotype Table 4 Urinary and plasma nicotine exposure biomarkers by plasma nicotine metabolite ratio (NMR) stratum and CYP2A6 genotype in smokers Table 5 Urinary and plasma nicotine exposure biomarkers by plasma nicotine metabolite ratio (NMR) stratum and CYP2A6 genotype in commercial smokeless tobacco users and iqmik users Table 6 Urinary procarcinogen biomarker levels in smokers, commercial smokeless tobacco users, and iqmik users Table 7 The effect of NMR stratum or CYP2A6 genotype on urinary NNAL level was eliminated after controlling for tobacco consumption Table 8 NNN levels were significantly higher in smokers with slower CYP2A6 activity when tobacco consumption was controlled for Table 9 Descriptive participant characteristics Table 10 Regression analyses of the predictive ability of cotinine and CYP2A6 genotype (or sex) on tobacco and tobacco-derived carcinogen exposure (Study 2) Table 11 A list of the SNP markers selection Table 12 The association between CHRNA5-A3-B4 SNPs and CPD, FTDN, COT, TNE, NNAL and BMI (Additive models) Table 13 The association between rs BMI (Additive model) xiii

14 Table 14 A summary of the limitations of common tobacco biomarkers Table 15 An example of potential modifications to the FTND to incorporate biomarker data. 151 xiv

15 LIST OF FIGURES Figure 1 Smoking contributes substantially to the top eight causes of mortality globally Figure 2 The effects of smoking on the survival of British doctors Figure 3 The effects of smoking on the relative risk of death from 30 most common specific causes of death Figure 4 Blood nicotine concentration versus time profiles after cigarette smoking, oral snuff, chewing tobacco, and nicotine gum Figure 5 Nicotine s metabolic profile in humans Figure 6 Factors influencing nicotine metabolism in vivo Figure 7 Relative risks of lung cancer and chronic obstructive pulmonary disease Figure 8 Tobacco users with slower CYP2A6 activity have lower nicotine intake Figure 9 Total tobacco consumption, and nicotine s metabolic profile, differed between NMR strata (A) and CYP2A6 genotypes (B) in cigarette smokers (n=141) Figure 10 Reduced CYP2A6 activity had a greater impact on cotinine removal than cotinine formation (Study 1) Figure 11 The effects of CYP2A6 activity on nicotine and cotinine pharmacokinetics Figure 12 Cotinine s ability to predict tobacco exposure was different between CYP2A6 genotypes (Study 2) Figure 13 Cotinine s ability to predict tobacco exposure was different between NMR strata (Study 2) Figure 14 Cotinine to TNE ratio significantly differ between individuals with difference CYP2A6 activity xv

16 Figure 15 Cotinine s ability to predict tobacco specific nitrosamines exposure (as indicated by NNAL levels) was different between CYP2A6 genotypes (Study 2) Figure 16 TNE s ability to predict tobacco specific nitrosamines exposure is independent of CYP2A6 genotype (Study 2) Figure 17 Cotinine s ability to predict polycyclic aromatic hydrocarbon exposure (as indicated by 1-hydroxypyrene) was different between CYP2A6 genotypes (Study 2) Figure 18 Cotinine s ability to predict polycyclic aromatic hydrocarbon exposure (as indicated by 1-hydroxyfluorene) was different between CYP2A6 genotypes (Study 2) Figure 19 Males (n=54), who have reduced CYP2A6 activity compared to females (n=127), had a greater ratio of cotinine formation over cotinine removal, which would result in the accumulation of cotinine and higher cotinine levels at a given tobacco exposure in male smokers (Study 1) Figure 20 Among the CYP2A6 normal metabolizers (Study 1, n=148), males, who have reduced CYP2A6 activity compared to females, had a greater ratio of cotinine formation over removal Figure 21 Cotinine's ability to predict tobacco exposure was different between the sexes Figure 22 A nicotine patch study: abstinent individuals with slower NMR have higher steady state plasma cotinine compared to individuals with faster NMR after receiving the same 21 mg nicotine patch Figure 23 Observed CHRNA5-A3-B4 haplotype structure in Alaska Native people Figure 24 The association between rs with A) cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1-hydroxypryrene Figure 25 The association (by dominate models) between rs with A) cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1-hydroxypryrene xvi

17 Figure 26 The association between rs with A) plasma cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1-hydroxypryrene Figure 27 The association between rs with A) cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1-hydroxypryrene Figure 28 The combined impact of genetic variants in CHRNA5-A3-B4 and CYP2A6 activity on urinary TNE levels among the total tobacco user group Figure 29 The combined impact of rs in CHRNA5-A3-B4 and CYP2A6 activity on urinary TNE levels Figure 30 The association between tobacco consumption and BMI Figure 31 Rs was significantly associated with BMI in the total tobacco user group, but not in the non-tobacco user group Figure 32 The relationship between self-report CPD and nicotine intake per cigarette (calculated as TNE divided by CPD) Figure 33 The relationship between self-report chews per day and nicotine intake per chew (calculated as TNE divided by chews per day) in Alaska Native commerical smokeless tobacco users Figure 34 Nicotine intake in light smokers vs. heavy smokers Figure 35 Smokeless tobacco users are exposed to higher levels of NNAL than smokers Figure 36 Modified FTND with biomarker data strongly predicted smoking cessation xvii

18 LIST OF ABBREVIATIONS 3HC 3'-hydroxycotinine 3HC/COT Ratio of 3'-hydroxycotinine to cotinine BMI Body mass index CDC Centers for Disease Control and Prevention CO Carbon monoxide COPD Chronic obstructive pulmonary disease CPD Cigarettes per day Cre Creatinine CYP Cytochrome P450 CYP2A6 Cytochrome P450 2A6 CYP2A6 NM CYP2A6 Normal Metabolizers CYP2A6 RM CYP2A6 Reduced Metabolizers ELISA Enzyme-linked Immunosorbent Assay FMO3 Flavin-containing monooxygenase 3 IQR Interquartile Range LC/MS Liquid Chromatography Mass Spectrometry MAF Minor Allele Frequency nachrs Nicotinic acetylcholine receptors NMR Nicotine Metabolite Ratio NNAL 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol NNK 4-(methylnitrosamino)-1-(3-pyridyl)-butanone NNN N-nitrosonornicotine PCR Polymerase chain reaction PFC Prefrontal cortex POMC Pro-opiomelanocortin SNPs Single nucleotide polymorphisms TNE Total nicotine equivalents TSNA Tobacco Specific Nitrosamines UGT Uridine diphosphate-glucuronosyltransferases VTA Ventral tegmental area xviii

19 LIST OF APPENDICES Appendix A: CYP2A6 and CYP2B6 genetic variation and its association with nicotine metabolism in South Western Alaska Native people. Appendix B: CYP2B6 and Bupropion's Smoking-Cessation Pharmacology: The Role of Hydroxybupropion. Appendix C: Influence of CYP2B6 genetic variants on plasma and urine concentrations of bupropion and metabolites at steady state. Appendix D: Variation in trans-3 -hydroxycotinine glucuronidation does not alter the nicotine metabolite ratio or nicotine intake in African American smokers. Appendix E: Association of CHRNA5-A3-B4 SNP rs with smoking cessation therapy response in African American smokers. Appendix F: Novel CYP2A6 variants identified in African Americans are associated with slow nicotine metabolism in vitro and in vivo xix

20 STATEMENT OF RESEARCH PROBLEM Tobacco smoking results in more than 6 million premature deaths each year, representing one of the greatest public health challenges of all time. World Health Organization predicted that smoking will kill one billion people over the course of the 21 st century. Today, ~20% of adults smoke in North America, resulting in more than $100 billion in health care costs annually. In recent years, a large proportion of smokers have started to smoke fewer cigarettes per day or have switched to less harmful tobacco products such as smokeless tobacco. Today, more than 30% of the current smokers in North America are light smokers. Light smokers are still at increased risk for smoking related mortality and morbidity. For example, they have approximately 15 times higher risk of developing chronic obstructive pulmonary disease and approximately 20 times higher risk of developing lung cancer than non-smokers. Yet despite their increased prevalence and still elevated disease risks, light smokers are generally excluded from clinical trials and most types of epidemiological studies. Nicotine is the main psychoactive compound in tobacco. Twin studies have indicated that genetics play an important role in determining tobacco consumption and the ability to quit smoking. Previously, genetic variants in CYP2A6, encoding the main nicotine-metabolizing enzyme, and CHRNA5-A3-B4, encoding three nicotinic receptors in the brain, have been associated with altered tobacco consumption and smoking cessation in Caucasian heavy smokers; but their influences on tobacco consumption have not been demonstrated in light smokers or smokeless tobacco users of other ethnicities. This lack of association could be due to both the lack of research in light smokers and smokeless tobacco users as well as the accuracy of the tobacco consumption biomarkers used in previous studies. The studies presented in this thesis utilized a theoretically stronger biomarker of nicotine consumption, total nicotine equivalents (TNE), to investigate the contribution of genetics to tobacco consumption in light smokers and smokeless tobacco users. Using TNE, we will assess the impact of genetic variants in CYP2A6 and CHRNA5-A3-B4 on tobacco consumption, alone or in combination, in light smokers and smokeless tobacco users. These investigations will provide insight into the levels, and mechanisms, of nicotine dependence in light smokers and smokeless tobacco users. xx

21 MAIN RESEARCH OBJECTIVES Tobacco smoking is one of the largest public health challenges of our time. While the contribution of genetics to smoking behaviors has been extensively studied in heavy smokers, little is known about the influence of genetic variation in nicotine metabolism on tobacco consumption in light smokers and smokeless tobacco users, despite their increasing prevalence. The first objective of this thesis was to characterize the phenotypic influence of CYP2A6 gene variants on nicotine metabolic profiles, smoking behaviors and carcinogen exposures in light smokers. By studying the influence of CYP2A6 gene variants on tobacco consumption in light smokers, we discovered that reduced function CYP2A6 gene variants were associated with lower urinary TNE and higher plasma cotinine. The opposite effects on urinary TNE and plasma cotinine were in agreement with the findings of a large body of literature. Together, these data suggested that cotinine might not be an accurate biomarker of tobacco consumption. The second objective of this thesis was to provide a mechanistic explanation for the systematic variation in cotinine levels observed in different smoking populations. In addition to CYP2A6, gene variants in CHRNA5-A3-B4, encoding for the α5, α3, and β4 nicotinic receptors, also influence tobacco consumption in heavy smokers. Progress has been made in identifying the independent CHRNA5-A3-B4 signals associated with tobacco consumption in Caucasian heavy smokers. However, these associations have not been investigated in light smokers. The third objective of this thesis was to determine whether CHRNA5-A3-B4 gene variants influence tobacco consumption in light smokers as seen in heavy smokers. Furthermore, we also investigated whether CYP2A6 variants and CHRNA5-A3- B4 variants act in combination to alter tobacco consumption. These studies allowed us to improve our understanding of the mechanisms of nicotine dependence in light smokers with the long-term goal of improving prevention and cessation approaches for this prevalent, but understudied population. Some of our pharmacogenetic data regarding smoking cessation in light smokers are attached in the Appendices. xxi

22 1 GENERAL INTRODUCTION 1.1 Epidemiology of Tobacco Smoking Prevalence Currently, there are approximately 1.3 billion smokers, and nearly 6 million smoking-induced deaths each year worldwide (Wipfli et al. 2009). Global smoking related mortality is higher than tuberculosis, HIV/AIDS and malaria combined, making it the largest cause of preventable death. Adult smoking prevalence in North America had been decreasing from the mid 1960s to the mid 1990s (e.g. from ~50% to 25%), but has stabilized at ~20% for the last ten years (Centers for Disease Control and Prevention 2012). Today, smoking prevalence differs substantially between sexes, ethnicities and socioeconomic classes. In the United States, 21.6% of adult men smoke whereas only 16.5% adult women smoke (Centers for Disease Control and Prevention 2008). In addition, smoking prevalence is 32% in American Indians/Alaska Natives, 20% in Non-Hispanic Whites and African Americans, and 10% in Asian Americans. Variation in smoking prevalence is also noted between socioeconomic classes. Roughly 29% of adults who live below the poverty level smoke in the United States compared with the 18% in adults who live above the poverty level (Centers for Disease Control and Prevention 2009; Centers for Disease Control and Prevention 2012) The Health Consequences Tobacco smoking has numerous negative health effects and is the largest cause of preventable death globally (Fig. 1). The World Health Organization estimates that smoking has killed 100 million people in the 20 th century and will kill 1 billion more in the 21 st century (assuming the current smoking prevalence) with about 80% of these deaths occurring in developing countries (World Health Organization et al. 2008). In North America, smoking accounts for one in five deaths each year (Benowitz 2010). Even more striking, for every smoking related death, another 20 smokers suffer from smoking related diseases (U.S Department of Health and Human Services 2010). It has been estimated that, in the United States alone, tobacco smoking costs society an estimated $168 billion in health care expenditures and productivity loss annually (Office of National Drug Control Policy. 2004). 1

23 Tobacco use is a major cause of cancer, cardiovascular disease and pulmonary disease. It is also a contributing factor to infections of the respiratory tract, adverse postoperative events and delayed wound healing (United States Public Health Service. Office of the Surgeon General. 2004). One of the difficulties in studying the health consequences of tobacco smoking is that it may take 40 to 50 years for the negative health impacts of tobacco smoking to mature. Therefore, the most convincing epidemiological data about the health consequences of smoking are generally from cohorts, which follow a large number of participants over many years. One of the most cited of these is the British Doctors study where the health information for male doctors in the United Kingdom was collected repeatedly over a 50-year period from 1951 to 2001 (Doll et al. 1954; Doll et al. 2004). In this study, the smokers generally smoked regularly for more than 40 years, which gave a good estimation of the health impacts of persistent smoking (Doll et al. 2004). The probability of a smoker dying prematurely (before the age of 70) was 43% compared to the 20% observed in the never smokers (Fig. 2). Overall, smoking resulted in a leftward shift of approximately 10 years in life expectancy (Fig. 2) (Doll et al. 2004). The findings of the British Doctors study were replicated subsequently by studies with more diverse participant composition. For example, a cohort study that followed more than 1.5 million participants in the United States showed that the probability of dying before the age of 80 was 62% for smokers compared with 30% in people who had never smoked, which represented an approximately 11 year reduction in life expectancy among smokers (Jha et al. 2013). The Global Adult Tobacco Survey showed that of the 30 most common causes of death in developed counties, 23 were increased substantially in smokers with the most substantial increase (21.4 times higher) seen with lung cancer (Pirie et al. 2013). This study estimated that the probability of dying before the age of 80 was 53% in smokers compared with 22% in the never smokers, which also represented an 11 year reduction in life expectancy (Pirie et al. 2013). 2

24 Millions of death (2005) Other tobacco caused diseases Ischemic heart disease Cerebrova scular disease Figure 1 Smoking contributes substantially to the top eight causes of mortality globally. Hatched areas represent the proportion of death that was attributed to smoking. Adapted from World Health Organization s report on the global tobacco epidemic (World Health Organization et al. 2008). 100 Lower respiratory infections Chronic obstructive pulmonary disease HIV/AIDS Cigarette smokers 20% 43% Diarrheal disease Persons who never smoked 10 yr Tuberculosis Never smokers Trachea, bronchus, lung cancer Tobacco use Figure 2 The effects of smoking on the survival of British doctors. Study of British doctors indicated that smoking resulted in a 10 year average loss of life expectancy. Adapted from Doll et al., 2004 and Peto et al., 2010 (Doll et al. 2004; Peto et al. 2010). 3

25 Cancers Smoking can lead to a spectrum of negative health consequences (Fig. 3); cancers are among the most notable of these. There are over 4000 chemicals in cigarette smoke, and more than 60 of them are carcinogenic (Hecht 2003). In American smokeless tobacco or unburned tobacco, there are at least 16 known human carcinogens (Hecht 2003). In addition, hundreds of other toxic chemicals, including tumor promoters, co-carcinogens, oxidants, free radicals and inflammatory agents are also delivered to the body during the smoking process (Hecht 2003). Once in the body, the carcinogens and their metabolites bind to DNA, resulting in covalent DNA adducts and mutations in the genome. When these mutations affect the function of crucial genes, such as tumor suppressors and oncogenes, normal cellular growth is altered, resulting in the development of cancer (Centers for Disease Control and Prevention 1989; Hecht 2003; United States Public Health Service. Office of the Surgeon General. 2004; Hecht et al. 2009; Hecht 2012). Smoking and smokeless tobacco use induce a diverse array of different cancers including those of the lungs, oral cavity, nasal cavity, larynx, oropharynx, hypopharynx, esophagus, stomach, bladder, ureter, kidney, cervix, and myeloid leukemia (United States Public Health Service. Office of the Surgeon General. 2004). 4

26 Number of deaths Current smoker Never smoker RR (95% CI) Chronic lung disease (J40 44) ( ) Cancer of lung (C34) ( ) Aortic aneurysm (I71) ( ) Intestinal ischaemia (K55) ( ) Cancer of mouth, pharynx, larynx, nasal cavity, or sinuses (C00 14,30 32) ( ) Coronary heart disease (I21 25) ( ) Cirrhosis or alcoholic liver (K70,74) ( ) Cancer of bladder (C67) ( ) Cancer of oesophagus (C15) ( ) Pneumonia (J12 18) ( ) Cerebrovascular disease (I60 69) ( ) Cancer of pancreas (C25) ( ) Cancer of kidney (C64) ( ) Cancer of stomach (C16) ( ) Diabetes (E10 14) ( ) External causes* (V01 Y98) ( ) Pulmonary fibrosis (J84 1) ( ) Cancer of liver (C22) ( ) Venous thromboembolism (I26,80 82) ( ) Leukaemia (C91 95) ( ) Motor neurone disease (G12 2) ( ) Cancer of large intestine (C18 20) ( ) Non Hodgkin lymphoma (C82 85) ( ) Cancer of breast (C50) ( ) Brain tumours (C71,D43) ( ) Cancer of ovary (C56) ( ) Multiple myeloma (C90) ( ) Alzheimer's and dementia (F03,G30) ( ) Melanoma (C43) ( ) Cancer of endometrium (C54) ( ) Figure 3 The effects of smoking on the relative risk of death from 30 most common specific causes of death. Adapted from Pirie et al., 2013 (Pirie et al. 2013). Figure 2: 30 most common specific causes of death (ICD-10): 12-year relative risk, current versus never-smoker The most notable smoking induced cancers is lung cancer. The association between smoking and lung cancer was first conclusively demonstrated during the 1950s by the combination of powerful epidemiologic evidence from the British Doctors study as well as experimental evidence from animals treated with cigarette tar (Wynder et al. 1953; Doll et al. 1954; Doll et al. 5

27 1956). Today, lung cancer is the second most common cancer and accounts for 12% of all new cases of cancer globally with smoking contributing to up to 90% of these new lung cancer cases (Centers for Disease Control and Prevention 1989; United States Public Health Service. Office of the Surgeon General. 2004; van Meerbeeck et al. 2011). The relative risk of developing lung cancer is 21 to 25 times higher in smokers compared to never smokers (Pirie et al. 2013; Thun et al. 2013), and the risk is directly proportioned to cigarette per day (CPD) and with duration of smoking (Brownson et al. 1992). Of note, this risk of developing lung cancer decreases after smoking cessation compared with those who continued to smoke (Khuder et al. 2001). Even with all of the therapeutic advances in the last 50 years, lung cancer remains one of the most deadly types of cancer with a five-year survival rate of only 15%. It results in roughly 160,000 deaths in the United States each year (Jemal et al. 2011). Lung cancer can be classified into two histological subtypes. Roughly 20% of lung cancer cases are classified as small cell lung cancer, and the other 80%, which include adenocarcinoma, squamous cell carcinoma, large cell carcinoma and bronchoalveolar cell carcinoma, are collectively called non-small cell lung cancer (Travis et al. 2011). Historically, 95% of the cases of small cell lung cancer were directly attributed to tobacco smoking, whereas adenocarcinoma was considered to be minimally related to tobacco smoking (Doll et al. 1957). However, current evidence suggests that the recent increase in adenocarcinoma incidence is smoking related and may reflect the change in smoking behaviors over the recent decades (Thun et al. 1997). Among the lung carcinogens in tobacco, tobacco specific nitrosamines (TSNA), such as 4- (methylnitrosamino)-1-(3)pyridyl-1-butanone (NNK) and N-nitrosonornicotine (NNN), are consistently associated with the development of lung cancer, particularly adenocarcinoma, in animal models (Schuller et al. 1990; Hoffmann et al. 1996). TSNAs are prevalent and potent carcinogens derived from nicotine and related compounds (Hecht 2003). TSNAs induce tumors in every animal model tested, and can induce lung tumors independent of the route of administration in rodents (Hecht 2002). Once absorbed, TSNAs are bioactivated (metabolized) by CYPs to their α-hydroxyl metabolites, which are then spontaneously converted to diazonium ions, which can result in covalent DNA adduct formation (Hecht 1998). In the case of NNK, CYP2B6 exhibits the highest α-hydroxylation activity in vitro with an affinity roughly ten times higher (i.e. a lower K m ) than CYP2A6 (Jalas et al. 2005). In contrast, the α-hydroxylation of 6

28 NNN is thought to be primarily mediated by CYP2A6 (Kushida et al. 2000; Wong et al. 2005). Individuals vary extensively in their TSNA metabolism, possibly due to genetic variations in these and other carcinogen metabolizing enzymes (Harris et al. 1976; Hecht 2003; Stepanov et al. 2008; Ter-Minassian et al. 2012). This may contribute to the individual variability in cancer risk observed between smokers. Chapter 1 investigates the role of genetic variants in xenobiotic metabolizing enzymes on TSNA metabolism Respiratory and Cardiovascular Diseases Although lung cancer is most often associated with smoking, a substantial amount of smoking related mortality is due to respiratory and cardiovascular diseases (Fig. 1). Smoking is the largest cause of chronic bronchitis and also increases the risk of dying from chronic bronchitis (Koop et al. 1982; United States Public Health Service. Office of the Surgeon General. 2004; Koop et al. 2006). Smoking is responsible for 75 to 90% of chronic obstructive pulmonary disease (COPD) related deaths (Schroeder 2013; Thun et al. 2013). Interestingly, the rate of death from COPD continues to increase among smokers in contrast to the reduction observed among never smokers (Thun et al. 2013), which is unlikely to be explained by the improved ability to diagnose COPD (because earlier detection of COPD should affect the disease prevalence rather than the rate of death). This suggests the possibility that the engineering modifications to cigarettes (to promote deeper inhalation) over the last 50 years might increase the lung parenchyma s exposure to tobacco smoke and the severity of smoking related COPD (Thun et al. 2013). Smoking is a major cause of cardiovascular disease. Smoking is responsible for 20 to 25% of coronary heart disease deaths and 18% of stroke deaths (Koop et al. 1982; United States Public Health Service. Office of the Surgeon General. 2004; Koop et al. 2006). Smoking is associated with a 6.5 times higher risk of death from aortic aneurysm, 4.5 times higher risk of death from coronary heart disease, 3.0 times higher risk of death from cerebrovascular disease, and 1.5 times higher risk of death from venous thromboembolism; smoking is also a significant risk factor for atherosclerosis (Koop et al. 1982; United States Public Health Service. Office of the Surgeon General. 2004; Koop et al. 2006; Pirie et al. 2013). Additionally, smoking can multiplicatively interact with other cardiovascular disease risk factors (such as elevated cholesterol or hypertension). Observations from the Pooling Project (an international consortium of cohort studies) suggested that smoking, elevated cholesterol and hypertension were each associated with 7

29 an increase of ~30 cardiac events per 1000 individuals in a 10 year period. But the cardiac event risk was dramatically greater in individuals with all three risk factors (190 events per 1000 individuals in a period of 10 years)(pooling Group of the American Heart Association 1978). Thus, there is a significant toxic effect of smoking on the homeostatic balance of the cardiovascular system and robust associations between smoking and cardiovascular diseases Other Health Consequences Smoking also has deleterious effects on human reproduction. Female smokers have an increased risk of delayed conception and infertility (Augood et al. 1998). Even among the female smokers who are able to conceive, smoking during pregnancy is associated with increased risk of premature rupture of membranes, placental abruption, placenta previa and preterm delivery (Harger et al. 1990; Williams et al. 1992). Furthermore, infants born to mothers who smoked during pregnancy have lower birth weights than infants with mothers who did not smoke (Butler et al. 1972; Sexton et al. 1984; Brooke et al. 1989). The risk of stillbirth and neonatal death are also increased among the infants with mothers who smoked during pregnancy (Winbo et al. 2001; Kristensen et al. 2005). Involuntary exposure to tobacco smoke (i.e. secondhand smoke) can lead to numerous undesirable health consequences, such as cancer and respiratory diseases in healthy nonsmokers. The risk of developing lung cancer in non-smokers who are exposed to secondhand smoke is 20 to 30% higher than those who are not exposed. Secondhand smoking results in an estimate of 3400 lung cancer deaths in the United States each year (United States. Surgeon- General's Office. 2006). Together, current evidence suggests that smoking can lead to a large number of negative health consequences. The next section will briefly discuss the benefits of smoking cessation Benefits of Smoking Cessation Smoking duration correlates positively with the risk of developing smoking related diseases. Smoking cessation at any age has substantial health benefits. For example, a study with more than 200,000 participants demonstrated that smokers who had quit between the ages of 25 to 34, 35 to 44 or gained about 10, 9 and 6 years of life respectively compared with those who continued to smoke (Jha et al. 2013). Similarly, another meta-analysis with more than 500,000 8

30 participants demonstrated similar effects of smoking cessation (Thun et al. 2013). Smokers who quit smoking generally have a large reduction in their lung cancer risk compared to the smokers who continue to smoke (Centers for Disease Control and Prevention 1989; United States Department of Health and Human Services 1990). Even smoking cessation at 60 years of age can lower the cumulative risk of lung cancer from 16% to about 10% (United States Public Health Service. Office of the Surgeon General. 2004; Jha et al. 2013). Smoking cessation has also been associated with a significant reduction in cardiovascular disease risk (Critchley et al. 2003). The risk of developing cardiovascular disease is reduced by 50% after 1 year of smoking abstinence (United States Public Health Service. Office of the Surgeon General. 2004). After 15 years of smoking abstinence, former smokers risk of developing cardiovascular disease is similar to never smokers (United States Public Health Service. Office of the Surgeon General. 2004). Among people who have been diagnosed with cardiovascular disease, smoking cessation greatly reduced (often by 50%) the risk of death (United States Public Health Service. Office of the Surgeon General. 2004). Despite the significant benefits of smoking cessation, only 3% of smokers successfully quit each year (Benowitz 2010). Thus, there is a pressing need for more effective smoking cessation strategies. A better fundamental understanding of the mechanisms behind smoking will likely lead to more effective smoking cessation strategies. 1.2 The Clinical and Molecular Neurobiology of Nicotine Dependence Nicotine is the main psychoactive ingredient of tobacco (Benowitz 2009). It is highly addictive via inhalation and is responsible for the reinforcing properties of tobacco (Isaac et al. 1972; Koop et al. 1982; Henningfield et al. 1983; McMorrow et al. 1983). Nicotine, in its pure form, is selfadministered by a number of rodent species and non-human primate species (Jaffe et al. 1978; Henningfield et al. 1983; Henningfield et al. 1983; Corrigall et al. 1992). It is also intravenously self-administered by human smokers in laboratory settings with an inverted U-shaped dose response relationship as seen in animals (Henningfield et al. 1983; Harvey et al. 2004) Clinical Features of Nicotine Dependence Smokers smoke to obtain positive reinforcement (such as the enhancements of mood and mental functions) and to avoid the negative reinforcement of nicotine withdrawal (Dani et al. 1996). 9

31 Positive Reinforcements: The Psychoactive Effects of Smoking Although there are many chemical additives in commercial cigarettes engineered to enhance their addictiveness (Henningfield et al. 2004), nicotine is the principle addictive component in tobacco. Smoking is a rapid route of nicotine administration. During smoking, the rapid rate of nicotine absorption into pulmonary circulation, and subsequently into the brain, cause a strong subjective feeling of rush and reinforcing effects. Clinically, smokers report that smoking induces pleasure and reduces stress and anxiety (Hatsukami et al. 2008; Benowitz 2010). Laboratory studies suggested that smoking can improve concentration, reaction time, and performance in many cognitive tests among smokers (Knott et al. 2009; Benowitz 2010). The smoking process allows precise dosing of nicotine to obtain the desirable reinforcing effects (or relief of withdrawal) (Benowitz 2010). Nicotine is sometimes considered a relatively weak reinforcer compared to other drugs of abuse such as cocaine and psychostimulants (Caggiula et al. 2002). Many of smoking s rewarding effects are mediated by smoking related cues (Caggiula et al. 2002). Smokers learn to associate the rewarding effects of smoking with smoking related cues, such as sight, taste, and smell of cigarettes as well as specific situations (e.g. a meal or with alcohol), mood (e.g. unpleasant mood and irritability), and environmental factors (e.g. a particular location) (Rose 2006). Nicotine enhances the behavioral responses to smoking related cues and makes them more salient (Olausson et al. 2004). The importance of smoking related cues in smoking behavior is supported by human brain imaging data. The presence of smoking related cues activates a number of cortical regions in the brain including the insula (Franklin et al. 2007). Smokers with damages to the insula, such as from brain trauma, were able to stop smoking more easily compared to smokers with brain trauma that did not affect the insula (Naqvi et al. 2007). This suggests that activation of the insula by smoking related cues may play an essential role in the maintenance of smoking in regular smokers. In agreement with the data from human smokers, the nicotine self-administration behaviors of animals are also highly dependent on the presence of contingent cues, such as light and sound (Caggiula et al. 2002). Together, existing data suggest that both nicotine s pharmacological effects and smoking related cues contribute to the positive reinforcing effects of smoking. 10

32 Negative Reinforcements: Nicotine Withdrawal The negative reinforcing effects of nicotine withdrawal also play an important role in nicotine dependence. Clinically, nicotine withdrawal is associated with anger, anxiety, depressed mood, difficulty concentrating, irritability, insomnia, and restlessness (Hughes et al. 1986; Hughes 2007). Some studies, but not others, have also suggested that nicotine withdrawal is associated with constipation, cough, dizziness, increased dreaming, mouth ulcers, nausea, and sore throat (Hughes 2007). Withdrawal symptoms typically peak during the first week of smoking abstinence and gradually decrease over the next 2 to 4 weeks (Hughes et al. 1990; Hughes 2007). Smokers report that smoking relieves the withdrawal symptoms by modulating arousal and mood, and improving concentration, reaction time and performance (Knott et al. 2011). The avoidance of these withdrawal symptoms is a major driving force behind the observed pattern of regular daily smoking and smoking relapse Titration of Smoking Behaviors Smokers tend to smoke the same number of cigarettes at fixed intervals from day to day to maintain a desired level of nicotine in the body and to avoid nicotine withdrawal (McMorrow et al. 1983). When the availability of nicotine is altered, smokers alter their smoking behaviors to compensate for the change. For example, smokers smoke more cigarettes and take bigger puffs when switched from regular to low nicotine yield cigarettes (Herning et al. 1981; Benowitz et al. 1983). Conversely, they smoke fewer cigarettes when switched to nicotine-enriched cigarettes (Fagerstrom 1982; Scherer 1999). Also consistent with this, pharmacokinetic manipulations of nicotine clearance alter smoking behaviors. For example, urinary acidification, which ion traps nicotine and increases nicotine s renal clearance, results in an 18% increase in daily nicotine consumption (Schachter et al. 1977; Benowitz et al. 1985). In contrast, urinary alkalization, which decreases nicotine s renal clearance, reduces smoking (Benowitz et al. 1985). Pretreatment with nicotine (via transdermal patch) greatly reduces subsequent cigarette consumption and increases the latency to smoking the next cigarette during ad libitum smoking (Benowitz et al. 1998; Scherer 1999). Together this suggests that smokers try to maintain a desirable plasma nicotine level (and presumably brain levels) by altering smoking behaviors in response to the availability of nicotine. 11

33 1.2.2 Measurements of Nicotine Dependence Nicotine dependence is a complex, multifactorial disorder. In order to measure the severity of nicotine dependence quantitatively, a number of measures/scales have been developed. The Fagerstrom Test for Nicotine Dependence (FTND) is a widely used measure of nicotine dependence (Table 1)(Heatherton et al. 1991). The FTND focuses on physical dependence and is weighted heavily toward questions such as How many cigarettes per day do you smoke and How soon after you wake up do you smoke your first cigarette? (Piper et al. 2006). The FTND is easy to administer, has good reproducibility over time and is predictive of smoking relapse during smoking cessation attempts (Piper et al. 2006). A shorter version of the FTND, Heaviness of Smoking Index (HSI), is also used to measure the level of nicotine dependence in smokers (Kozlowski et al. 1994). HSI only contains two questions, time to first cigarette and cigarettes per day, and has shown good concordance with the FTND (Perez-Rios et al. 2009). Other measures, such as the diagnostic criteria from Diagnostic Statistical Manual-IV and International Classification of Diseases-10 capture other aspects of nicotine dependence, such as the cognitive and behavioral effects, and these scales generally have low concordance with the FTND (Hughes et al. 2004). Recently, a few other scales, such as the Nicotine Dependence Syndrome Scale and Wisconsin Inventory of Smoking Dependence Motives, have been developed to more comprehensively cover the multidimensional nature of nicotine dependence (Piper et al. 2004; Piper et al. 2008), but these scales have not yet been widely adapted. 12

34 Table 1 The Fagerstrom test for nicotine dependence (Heatherton et al. 1991). The maximum score is 10 with higher scores indicating greater nicotine dependence. A score of greater than 5 indicates high level of nicotine dependence (Moolchan et al. 2002). Points How soon after you wake up do you smoke your first cigarette? Within 5 min min min 1 After 60 min 0 Do you find it difficult to refrain from smoking in places where it is forbidden e.g., in church, at the library, in cinema? Yes 1 No 0 Which cigarette would you hate most to give up? The first one in the morning 1 All others 0 How many cigarettes per day do you smoke? Do you smoke more frequently during the first hours after waking than you do during the rest of the day? Yes 1 No 0 Do you smoke if you are so ill that you are in bed most of the day? Yes 1 No Mechanisms of Nicotine Dependence During smoking, particles carry nicotine into the lungs, where it is absorbed into the blood circulation. It is then quickly transported to the brain where it activates nicotinic acetylcholine receptors (nachr). Many brain circuits, particularly the mesolimbic dopamine reward pathway which projects from the ventral tegmental area (VTA) to the prefrontal cortex (PFC) and nucleus accumbens (NAc), are involved in nicotine addiction (Koob 2006). The activation of mesolimbic dopamine neurons by nicotine is mediated both directly by the activation of nachr on dopamine neurons in the VTA, and indirectly by modulating GABA and glutamate inputs onto dopamine neurons (Laviolette et al. 2004). The ability of nicotine to modulate the mesolimbic dopamine 13

35 pathway to signal for pleasurable experiences is critical for the reinforcing effects of smoking (Corrigall et al. 1992; Le Foll et al. 2006). Here, the role of neuronal nachrs in the activation of mesolimbic dopamine pathway will be discussed Molecular Biology of Nicotinic Receptors nachrs are pentameric (5 subunits) structures with a centrally located cation channel (Changeux 2010). Twelve different neuronal nachr subunit genes have been identified, including nine alpha genes (α2- α10) and three beta genes (β2- β4) (Changeux 2010). With some exceptions, most brain nachrs are located presynaptically and modulate the release of other neurotransmitters (Gotti et al. 2009). Nicotine and tobacco research has historically focused on the high affinity, slow desensitization heteromeric α4β2 nachrs expressed in the mesolimbic dopamine pathway and the low affinity, high Ca 2+ permeability homomeric α7 nachrs expressed in the hippocampus and cortex regions (Changeux 2010). More recently, genome wide association studies and subsequent animal studies have suggested the potential importance of nachrs consisting of the α5, α3 and β4 subunits in governing tobacco consumption and other smoking behaviors (Amos et al. 2008; Hung et al. 2008; Thorgeirsson et al. 2008; Saccone et al. 2009; Wu et al. 2009; Jackson et al. 2010; Saccone et al. 2010; Fowler et al. 2011) The Role of α4β2 nachr in Nicotine Dependence The activation of α4β2 nachrs on the mesolimbic dopamine neurons plays an essential role in the acquisition and maintenance of nicotine dependence. Genetically modified mice lacking either the α4 or β2 subunits did not self-administer nicotine; the nicotine self-administration behavior was restored when α4 or β2 subunits were re-expressed (using viral vectors) in the VTA (Picciotto et al. 1998; Epping-Jordan et al. 1999; Maskos et al. 2005; Pons et al. 2008). This is unlikely to be a result of generally altered learning behaviors as β2 knockout mice readily selfadministered cocaine, but stopped their self-administration behavior when the cocaine was switched to nicotine (Picciotto et al. 1998; Epping-Jordan et al. 1999). In agreement with the self-administration data, β2 knockout mice did not show nicotine conditioned place preference or nicotine discrimination (Walters et al. 2006). Conversely, the overexpression of the α4 gene results in nicotine hyper-sensitive mice, which displayed nicotine conditioned place preference at 50 times lower dose compared to wild type mice (Tapper et al. 2004). In addition, the current 14

36 FDA approved pharmacotherapies to promote smoking cessation (nicotine replacement therapy, bupropion and varenicline) all demonstrate some affinity toward the α4β2 nachrs with varenicline displaying the highest selectivity toward this receptor combination (Slemmer et al. 2000; Gonzales et al. 2006). Together, these suggest that α4β2 nachrs play an essential role in nicotine dependence The Role of α7 nachr in Nicotine Dependence The low affinity, high Ca 2+ permeability homomeric α7 nachrs may not be directly involved in nicotine s rewarding effects, but may play a role in modulating the motivation to obtain nicotine. Genetically modified mice lacking functional α7 did not exhibit altered nicotine selfadministration behaviors, nicotine induced conditioned place preference or nicotine discrimination (Stolerman et al. 2004; Walters et al. 2006). However, local infusions of α- conotoxin, a selective α7 antagonist, into the nucleus accumbens shell or anterior cingulate cortex increased the breakpoints of nicotine self-administration under a progressive ratio schedule, suggesting that a reduction in α7 function in these brain regions increases the motivation to obtain nicotine (Brunzell et al. 2012). In agreement, varenicline, a full agonist at α7 nachrs, is an effective treatment to promote smoking cessation in humans and generally decreases the motivation to obtain nicotine (Gonzales et al. 2006; Mihalak et al. 2006; Siu et al. 2007). Together, these data suggest that the α7 subunit is not directly involved in nicotine s rewarding effects, but may play an important role in modulating the motivation to obtain nicotine The Role of α5, α3 and β4 nachrs in Nicotine Dependence The role of the α5, α3 and β4 subunits in nicotine dependence is relatively unknown. This is partially due to the fact that the α5 and α3 subunits are obligate accessory subunits and cannot form functional nachrs by themselves (Berrettini et al. 2012). However, a number of genome wide association studies published in 2008 suggested a strong association between genetic variants in the CHRNA5-A3-B4 gene cluster, which encodes the α5, α3 and β4 subunits, with CPD and lung cancer risk (Amos et al. 2008; Hung et al. 2008; Thorgeirsson et al. 2008)(details in later sections). Subsequent research showed that genetically modified animals lacking the α5 subunit and animals with overexpressed β4 subunit (using a viral vector) displayed enhanced 15

37 nicotine self-administration behaviors, suggesting these subunits play a role in modulating nicotine s reinforcing effects (Fowler et al. 2011; Frahm et al. 2011). 1.3 Nicotine Pharmacokinetics Nicotine pharmacokinetics is an important determinant of smoking behaviors due to a smoker s tendency to maintain a desired nicotine level. Smoking is a fast, efficient and highly addictive route of nicotine administration. In comparison, nicotine replacement therapies, used to promote smoking cessation, deliver nicotine slowly and have low abuse liability (Houtsmuller et al. 2003). This section will focus on the absorption of nicotine via tobacco smoking, the distribution of nicotine in the body, and the metabolism and renal excretion of nicotine Absorption and Distribution About 10 to 14 mg of nicotine is found in a typical cigarette and 1 to 1.5 mg is absorbed into the body during the smoking process (Benowitz et al. 1984; Kozlowski et al. 1998). Nicotine has a weakly basic pka of 8.0 and its absorption kinetics are highly ph dependent since essentially only unionized nicotine can cross membranes and be absorbed. During smoking, nicotine is carried by tar droplets (also known as particulate matter), which have a ph between 6.0 to 7.8, into the respiratory tract (Pankow et al. 2003). At this ph range, 1% to 36% of nicotine is in the unionized form and can readily cross the biological membrane in the small airways and alveoli of the lungs and be rapidly absorbed into the blood stream (Pankow et al. 2003). After a puff, it takes about 10 to 20 seconds for nicotine to reach the brain and activate the nachrs on the mesolimbic dopamine neurons and other brain regions (Henningfield et al. 1993; Rose et al. 2010). This rapid absorption of nicotine into the brain makes smoking one of the most reinforcing routes of nicotine administration (Henningfield et al. 1993). In addition, the short time needed for nicotine to reach the brain allows smokers to precisely control the depth of inhalation, puff volume, and number of puffs per cigarette to reach a desirable nicotine level (Herning et al. 1983). In contrast to smoking, chewing (in the case of smokeless tobacco) is a comparatively slower way of delivering nicotine. The absorption of nicotine from smokeless tobacco is also highly ph 16

38 dependent. Therefore, chewing tobacco generally has a very basic ph to reduce ionization and maximize the absorption of nicotine across the buccal mucosa (Benowitz 1988). On average, a typical size smokeless tobacco chew delivers about 4.5 mg of nicotine to the body and a typical size snuff delivers on average 3.6 mg of nicotine to the body, whereas only 1.0 mg nicotine is delivered to the body from smoking a cigarette (Benowitz 1988). Nicotine s absorption from smokeless tobacco occurs more slowly than the absorption from smoking, but the peak venous concentrations are very similar (Benowitz 1988; Benowitz et al. 1988; Benowitz 1997). In contrast to the rapidly falling nicotine concentrations after smoking, the nicotine concentrations were stable during, and after, the use of smokeless tobacco reflecting the continued absorption of nicotine to the systemic circulation even after the smokeless tobacco is removed from the mouth (Benowitz et al. 1988; Benowitz 1997). Thus, nicotine exposure is prolonged after smokeless tobacco use. Fig. 4 illustrates the pharmacokinetic profile of nicotine after cigarette smoking (top left) and chewing tobacco (bottom left). Figure 4 Blood nicotine concentration versus time profiles after cigarette smoking, oral snuff, chewing tobacco, and nicotine gum. The shaded bars represent the duration of tobacco consumption. Adapted from Benowitz et al.,

39 After absorption, nicotine is distributed into a number of different body tissues, which is reflected by the large volume of distribution (2.6 L/kg) (Benowitz et al. 1991; Benowitz et al. 1994). Nicotine is not protein bound in the plasma (< 5%), and the distribution half-life is around 8 minutes in humans (Benowitz et al. 1991). The arterial concentration of nicotine after consuming a cigarette is usually between 20 to 60 ng/ml (Armitage et al. 1975; Henningfield et al. 1993; Rose et al. 1999; Lunell et al. 2000). The venous concentration of nicotine after consuming a cigarette generally ranges from 10 to 50 ng/ml (Benowitz 1990; Schneider et al. 2001). The mean increase in venous nicotine concentration after consuming a cigarette is around 11 ng/ml (Fig. 4)(Benowitz et al. 1988; Patterson et al. 2003), but this can be as high as 30 ng/ml depending on how a cigarette is smoked (Lunell et al. 2000; Schneider et al. 2001) Metabolism The Primary Metabolites of Nicotine In humans, the majority of absorbed nicotine is metabolized before excretion. Nicotine is metabolized to a number of primary metabolites including cotinine, nicotine N -oxide, nornicotine, and nicotine N -glucuronide (Fig. 5), and minor metabolites such as nicotine isomethonium ion and 2 -hydroxynicotine. 18

40 N + N Nornicotine % N + OH O O OH O - OH N H N Norcotinine 1-2% N O - Cotinine N-Oxide 2-5% N H O N Nicotine N-Glucuronide 3-5% O O - O O HO N + CYP2B6 CYP2A6 CYP2A13 OH OH UGT2B10 UGT1A9? UGT1A4? N N Nicotine 8-10% Cotinine 10-15% N UGT2B10 UGT1A9? UGT1A4? O Cotinine N-Glucuronide 12-17% N N N O N FMO3 CYP2A6 CYP2B6? Others? Aldehyde oxidases CYP2A6 OH 3'-hydroxycotinine 33-40% O N N + O - Nicotine N'-Oxide 4-7% N N + Nicotine- 1'(5') -Iminium Ion UGT2B17 UGT2B7 UGT1A9 N HO HO OH O - 3'-Hydroxycotinine O-Glucuronide 7-9% N O O O O Figure 5 Nicotine s metabolic profile in humans. The percentage below each metabolite is an estimate of the average excretion of this metabolite as a percentage of total urinary nicotine equivalents or the nicotine dose. This figure represents broad estimations as the data were gathered by different studies using various methods. Bold indicates compound of interest (Brandange et al. 1979; Byrd et al. 1992; Cashman et al. 1992; Benowitz et al. 1994; Nakajima et al. 1996; Nakajima et al. 1996; Messina et al. 1997; Benowitz et al. 2002; Hukkanen et al. 2005; Yamanaka et al. 2005; Chen et al. 2007; Kaivosaari et al. 2007; Berg et al. 2010). Cotinine is the main metabolite of nicotine in humans. Approximately 70 to 80% of the absorbed nicotine is metabolized to cotinine (Benowitz et al. 1994; Mwenifumbo et al. 2010; Zhu et al. 2013). The metabolism of nicotine to cotinine is a two-step process. The first step is a CYP mediated oxidation of nicotine to nicotine-δ 1 (5 ) -iminium ion (Murphy 1973; Peterson et al. 1987; Obach et al. 1990), and the second step involves the conversion of nicotine-δ 1 (5 ) -iminium 19

41 ion to cotinine by aldehyde oxidase I (Brandange et al. 1979; Gorrod et al. 1982). The second step is generally not a rate-limiting step in cotinine formation (Brandange et al. 1979; Obach et al. 1990). In humans, CYP2A6 is responsible for 90% of the nicotine C-oxidation to cotinine (Nakajima et al. 1996; Messina et al. 1997; Yamazaki et al. 1999). A number of in vitro metabolism studies demonstrated that the rate of nicotine C-oxidation correlated highly with hepatic CYP2A6 protein levels and coumarin 7-hydroxylase activity (a phenotypic marker for CYP2A6 activity) in human liver microsomes (Berkman et al. 1995; Nakajima et al. 1996; Messina et al. 1997). In addition, cdna expressed CYP2A6 enzyme demonstrates the highest rate of cotinine formation among all CYPs (Nakajima et al. 1996), and CYP2A6 inhibitory antibodies and chemical inhibitors prevent cotinine formation from nicotine (Nakajima et al. 1996; Messina et al. 1997). The essential role of CYP2A6 in nicotine C-oxidation is also supported by in vivo studies. Individuals with two copies of the CYP2A6 deletion allele have very low plasma cotinine levels after nicotine administration (Nakajima et al. 2000; Kwon et al. 2001; Nakajima et al. 2001; Xu et al. 2002; Dempsey et al. 2004; Mwenifumbo et al. 2010), and excrete very small amounts of cotinine or cotinine metabolites in urine (Kitagawa et al. 1999; Yang et al. 2001; Zhang et al. 2002). Methoxsalen, a chemical inhibitor of CYP2A6, can significantly reduce the metabolism of nicotine in vivo (Sellers et al. 2000; Sellers et al. 2003). In addition to CYP2A6, other CYPs may also play a small role in nicotine C-oxidation. For example, cdna expressed CYP2B6 can catalyze nicotine C-oxidation, but with an affinity that is 10 times lower than CYP2A6 (i.e. higher Km) (Yamazaki et al. 1999). This observation is also supported by data from human liver bank analysis. No correlation between nicotine C-oxidation activity and CYP2B6 protein levels was observed after adjusting for CYP2A6 protein levels in human livers (Al Koudsi et al. 2010). CYP2A13 can also mediate nicotine C-oxidation in vitro (Bao et al. 2005; Murphy et al. 2005). However, the contribution of CYP2A13 to systemic nicotine C-oxidation is small due to the limited hepatic expression of this enzyme (Koskela et al. 1999; Su et al. 2000). In humans, 4 to 7% of nicotine is eliminated in urine as nicotine N -oxide (Benowitz et al. 1994), and the formation of nicotine N -oxide is thought to be mediated by flavin-containing 20

42 monooxygenase 3 (FMO3, Fig. 5) (Cashman et al. 1992; Park et al. 1993). In humans, less than 1% of nicotine is eliminated as nornicotine in urine (Byrd et al. 1992; Benowitz et al. 1994). In human liver microsomes, the rate of nicotine N-demethylation is biphasic with contributions from CYP2B6 to the high affinity site and CYP2A6 to the low affinity site (Yamanaka et al. 2005). In addition to the oxidative pathways, nicotine can also undergo phase II glucuronidation to nicotine N -β-glucuronide (Byrd et al. 1992; Benowitz et al. 1994). In humans, about 3 to 5% of nicotine is eliminated as nicotine N -β-glucuronide in urine (Benowitz et al. 1994). However, this percentage may be higher in individuals with reduced nicotine C-oxidation (Yamanaka et al. 2004). The rates of nicotine and cotinine glucuronidation are highly correlated, suggesting that the same uridine 5'-diphosphoglucuronosyl transferase (UGT) isoform mediates the conjugation of both nicotine and cotinine (Benowitz et al. 1994; Nakajima et al. 2002). Recent evidence suggests that nicotine and cotinine glucuronidation are largely mediated by UGT2B10 (Chen et al. 2007; Kaivosaari et al. 2007; Berg et al. 2010). Other minor nicotine metabolic pathways include the 2 -hydroxylation of nicotine to produce 4- (methylamino)-1-(3-pyridyl)-1-butanone (Hecht et al. 2000). This pathway is interesting as 4- (methylamino)-1-(3-pyridyl)-1-butanone can be converted to carcinogenic nitrosamines (Hecht et al. 2000). However, the formation of nitrosamines (from nicotine) is not detected in individuals who were treated for an extended period of time with nicotine transdermal patch (Stepanov et al. 2009), suggesting that this may not be a pathway with much clinical relevance Pharmacology of Nicotine Metabolites Some of nicotine s primary metabolites have pharmacological activity and some are essentially inactive. Cotinine generally does not have much activity and is unlikely to contribute to nicotine s pharmacological actions. Administration of high doses of cotinine (10-times higher than those observed in smokers) did not result in any notable physiological changes (i.e. changes in heart rate, blood pressure, and skin temperature) or subjective changes (i.e. increased tension or anxiety) (Benowitz et al. 1983; Hatsukami et al. 1997; Zevin et al. 2000). Cotinine also does not activate nachrs to evoke dopamine release (Dwoskin et al. 1999). An in vitro study suggested that cotinine can activate the PI3K/AKT pathway and promote lung tumorigenesis by 21

43 its anti-apoptotic effects (Nakada et al. 2012). However, the contribution of cotinine to smoking s carcinogenic effects has not been demonstrated in vivo. In contrast to cotinine, nornicotine, which is a minor nicotine metabolite (<1%), binds to nachrs with high affinity and can evoke dopamine release in rat brain slices (Reavill et al. 1988; Green et al. 2001). Rats also self-administer nornicotine (Bardo et al. 1999). In vivo studies suggest that nornicotine can accumulate in rat brain following repeated nicotine exposure due to its long half-life (8 hours) (Kyerematen et al. 1990; Ghosheh et al. 2001; Hukkanen et al. 2005). However, the pharmacological effects of nornicotine in humans have not been demonstrated. Therefore, it is hard to quantify the contribution of nornicotine to nicotine s pharmacology in humans The Secondary Metabolites of Nicotine Although the majority of nicotine is metabolized to cotinine, only a small percentage of cotinine is excreted unchanged (Benowitz et al. 1984; Benowitz et al. 1994). In humans, most of the cotinine is metabolized to 3 -hydroxycotinine (3HC). This results in approximately 40 to 50% of absorbed nicotine being excreted as 3HC and its glucuronide in urine (McKennis et al. 1964; Benowitz et al. 1994; Neurath 1994). The formation of 3 -hydroxycotinine from cotinine is catalyzed exclusively by CYP2A6 in humans as demonstrated both in vitro and in vivo. cdna expressed CYP2A6 has a very high cotinine 3 hydroxylase activity, and in human liver microsomes cotinine 3 -hydroxylase activity is highly correlated with CYP2A6 protein levels and with coumarin 7 -hydroxylase activity (Nakajima et al. 1996). Both inhibitory antibodies, and chemical inhibitors of CYP2A6, inhibit 3HC formation from cotinine in human liver microsomes (Nakajima et al. 1996) and no 3HC is detected in individuals who are homozygous for the CYP2A6 deletion allele (Dempsey et al. 2004; Mwenifumbo et al. 2010) Using the 3HC to COT Ratio as A Marker of CYP2A6 Activity The ratio of 3 -hydroxycotinine to cotinine (3HC/COT ratio, also known as the nicotine metabolite ratio or NMR) is often used as a non-invasive probe for CYP2A6 activity and nicotine clearance in vivo. Cotinine has a long half-life (16 hours) and plasma cotinine levels show little fluctuation in regular smokers (Lea et al. 2006). 3HC has a much shorter half-life compared to cotinine (5 hours) (Benowitz et al. 1983; Benowitz et al. 2001), and at steady state, 22

44 the elimination rate of 3HC is essentially formation-limited. Therefore, the NMR is stable over time and highly reproducible in regular smokers (Lea et al. 2006; St Helen et al. 2012). As a phenotypic marker, the NMR has high predictive validity and several technical advantages. The NMR is highly predictive of total nicotine clearance in vivo, making it useful as a surrogate measure of total nicotine clearance (Dempsey et al. 2004). In contrast to most of the phenotypic probes for enzymes, the NMR can be assessed from a single smoker s plasma sample without the administration of a probe drug and subsequent assessments of metabolites at a specified time (Levi et al. 2007). The NMR also shows little temporal fluctuation, samples can be taken at any time of the day (Lea et al. 2006; Levi et al. 2007) Non-Genetic Sources of Variation in Nicotine Pharmacokinetics A number of non-genetic factors can alter nicotine pharmacokinetic in humans (Fig. 6). These factors generally alter nicotine metabolism via either altering CYP2A6 activity or changing hepatic blood flow (Fig. 6). Some common non-genetic factors contributing to the variability in nicotine pharmacokinetics will be discussed here. Hepatic Blood flow Nicotine Cotinine 3 Hydroxycotinine Sleep Meals Age - + +/- Xenobiotics and diet +/- CYP2A6 enzymatic activity - + Inhibitors +/- Female +/- Ethnicity + - Genetic Inducers Smoking and menthol Figure 6 Factors influencing nicotine metabolism in vivo. A number of factors, including genetics, gender, pregnancy, age, meals, diet, smoking and xenobiotics can influence nicotine metabolism. These factors generally affect nicotine 23

45 metabolism by either influencing hepatic blood flow or CYP2A6 mediated nicotine metabolism. Adapted from Zhu et al., To understand the variability in nicotine pharmacokinetics, it is important to note that nicotine is a high extraction drug, in contrast to its primary metabolite cotinine (Benowitz et al. 1983). The intrinsic clearance (V max /K m ) of nicotine is 1.69 µl/min/mg protein in human liver microsomes, which is 10 times faster than the 0.16 µl /min/mg protein of cotinine (Nakajima et al. 1996; Nakajima et al. 1996). For a high extraction drug, such as nicotine, its metabolism is relatively more dependent on hepatic blood flow and less dependent on drug-metabolizing enzyme activity (Hukkanen et al. 2005). In comparison, the metabolism of a low extraction drug, such as cotinine, is highly dependent on drug-metabolizing enzyme activity and less dependent on hepatic blood flow. Therefore, comparing the effects of a factor (i.e. gender or age) on nicotine metabolism relative to cotinine metabolism can help to determine the underlying process that this factor alters. Factors that alter CYP2A6 activity are likely associated with greater alterations in cotinine metabolism than nicotine metabolism. In contrast, factors that alter hepatic blood flow are likely associated with greater alterations in nicotine metabolism than cotinine metabolism Non-Genetic Factors Contribute to Variation in Nicotine Pharmacokinetics by Altering CYP2A6 Activity The influences of several physiological and environmental factors on CYP2A6 activity and nicotine metabolism will be discussed, with particular focus on the contribution of estrogen to the gender difference in nicotine metabolism and the influence of CYP2A6 inducers and inhibitors on in vivo nicotine metabolism Gender Females, on average, have faster nicotine and cotinine metabolism compared to males (Benowitz et al. 2006). The fact that metabolism of both nicotine and cotinine are higher in females suggests that this increase is due to an alteration in CYP2A6 activity, as alterations in hepatic blood flow would only affect nicotine metabolism but not cotinine metabolism. In support of this hypothesis, females have a higher 3HC/COT ratio (suggesting faster CYP2A6 mediated 3HC formation) compared to males (Johnstone et al. 2006; Ho et al. 2009), and livers from females have significantly higher CYP2A6 mrna, protein, and activity compared to livers from males (Al Koudsi et al. 2010). 24

46 The higher CYP2A6 activity in females is mediated by their comparatively higher estrogen levels. Estrogen can increase the transcription of CYP2A6 in vitro via an estrogen receptor dependent transcriptional up-regulation (Higashi et al. 2007). Estrogen-containing oral contraceptives increase CYP2A6 activity and the clearance of both nicotine and cotinine (Krul et al. 1998; Benowitz et al. 2006), while progesterone-containing contraceptives do not (Benowitz et al. 2006). Furthermore, menopausal or postmenopausal women, who have low estrogen levels, have similar nicotine and cotinine clearance compared to men (Benowitz et al. 2006). Yet the comparatively low nicotine and cotinine clearance was enhanced by estrogen containing hormone replace therapy (Benowitz et al. 2006). Together, these data suggest that the increase in nicotine and cotinine metabolism in females is due to the higher estrogen levels resulting in higher CYP2A6 activity Xenobiotics CYP2A6 activity and nicotine metabolism can also be altered by the exposure to xenobiotics. CYP2A6 activity is induced by a number of prototypical CYP inducers, such as rifampicin, dexamethasone and phenobarbital (Kyerematen et al. 1990; Maurice et al. 1991; Sotaniemi et al. 1995; Mattes et al. 1997; Rae et al. 2001; Madan et al. 2003; Al Koudsi et al. 2010). In particular, rifampicin treatment increases both CYP2A6 mrna and activity in human primary hepatocytes by 2 to 8 folds (Meunier et al. 2000; Rae et al. 2001; Madan et al. 2003). Interestingly, rifampicin has also been shown to act as an inhibitor of CYP2A6 (Xia et al. 2002), which may explain some of the variability observed in CYP2A6 activity upon rifampicin treatments. Phenobarbital, another prototypical CYP inducer, can also induce CYP2A6 (Madan et al. 2003; Al Koudsi et al. 2010). Liver microsomes from patients who are exposed to phenobarbital exhibit higher levels of CYP2A6 protein than unexposed patients (Cashman et al. 1992). Experiments in primary hepatocytes suggest that phenobarbital treatment can significantly induce nicotine C-oxidation activity in as little as two days (Kyerematen et al. 1990). The induction of nicotine metabolism by xenobiotics such as rifampicin and phenobarbital is mediated by nuclear receptor dependent transcriptional activation of CYP2A6 (Donato et al. 2000; Rae et al. 2001; Maglich et al. 2002). Rifampicin and phenobarbital bind to, and activate, the pregnane X receptor and the constitutive active androstane receptor respectively. These nuclear receptors then translocate to the nucleus where they dimerize with the retinoid X receptor 25

47 α, and bind to the DR4 sites upstream of the CYP2A6 gene to increase its transcription (Itoh et al. 2006). Xenobiotics can also inhibit CYP2A6 activity and nicotine metabolism. A number of compounds such as methoxsalen, menthol, tryptamine, coumarin, tranylcypromine and selegiline, can inhibit nicotine C-oxidation in vitro with some selectivity for CYP2A6 (Nakajima et al. 1996; Messina et al. 1997; Le Gal et al. 2001; Taavitsainen et al. 2001; Zhang et al. 2001; MacDougall et al. 2003; Siu et al. 2008). Clinically, oral methoxsalen administration inhibits the first pass metabolism of oral nicotine (Sellers et al. 2000), and decreases the clearance of nicotine following subcutaneous nicotine injections (Sellers et al. 2003). Methoxsalen administration can also reduce the number of cigarettes smoked, indicating titration of tobacco consumption to compensate for lower nicotine clearance (Sellers et al. 2003) Non-Genetic Factors Contribute to Variation in Nicotine Pharmacokinetics by Altering Hepatic Blood Flow Variation in hepatic blood flow can also contribute significantly to the variation in nicotine pharmacokinetics. The influence of factors altering hepatic blood flow on nicotine metabolism is discussed in this section with a particular focus on the influence of age and circadian rhythm Age and Circadian Rhythm Age does not alter nicotine metabolism in adolescents and adults (Shimada et al. 1994; Gourlay et al. 1996; Al Koudsi et al. 2010). However, slower nicotine metabolism is observed in neonates and the elderly. The half-life of nicotine is longer in neonates than in adults, but the half-life of cotinine is similar in neonates and adults (Leong et al. 1998; Dempsey et al. 2000; Dempsey et al. 2013). Since cotinine clearance is less dependent on hepatic blood flow compared to nicotine and is unaltered in neonates, the reduction of nicotine metabolism in neonates is more likely explained by a reduction in hepatic blood flow (Gow et al. 2001). This is supported by the observation that hepatic CYP2A6 protein levels are only slightly lower in neonates compared with adults (Tateishi et al. 1997). In adolescents and adults, no correlation between age and CYP2A6 protein level and activity has been observed (Parkinson et al. 2004; Al Koudsi et al. 2010), suggesting a limited impact of age on nicotine metabolism. Furthermore, no differences in steady state nicotine plasma concentrations are observed between different adult age groups 26

48 receiving the same dose of nicotine (Gourlay et al. 1996; Mwenifumbo et al. 2007). In agreement with this, the rate of coumarin metabolism is similar across a wide age range (Shimada et al. 1994; Pasanen et al. 1997), suggesting CYP2A6 activity does not change with age. In the elderly, the clearance of nicotine is slower (Molander et al. 2001), most likely due to a reduction in hepatic blood flow (Hukkanen et al. 2005), since no age-associated reduction in the CYP2A6 protein or in vitro nicotine metabolism have been reported (Messina et al. 1997; Al Koudsi et al. 2010). Circadian variation in nicotine metabolism has also been reported (Gries et al. 1996). Nicotine metabolism increases after a meal as hepatic blood flow increases (Lee et al. 1989; Gries et al. 1996), and decreases during sleep as hepatic blood flow decreases (Hukkanen et al. 2005). Consequently, nicotine clearance can vary by as much as 17% between 7:00 PM and 3:00 AM (Gries et al. 1996) Renal Clearance of Nicotine The renal clearance of nicotine is a relatively minor route of nicotine clearance (Fig. 5); only 8 to 10% of an intravenously administered nicotine dose is excreted unchanged, whereas the majority of nicotine is metabolized before excretion (Neurath 1994; Hukkanen et al. 2005). Nicotine is excreted from the body by glomerular filtration and tubular secretion. The normal nicotine renal clearance rate is highly dependent on urinary ph, but is normally in the range of 35 to 123 ml/min (Benowitz et al. 1999; Benowitz et al. 2000; Hukkanen et al. 2006). In acidic urine, where nicotine is highly ionized and little tubular reabsorption occurs, nicotine renal clearance rates can be as high as 600 ml/min (Benowitz et al. 1985). In contrast, in basic urine where nicotine is largely unionized and tubular reabsorption is increased, the renal clearance of nicotine can be as low as 17 ml/min (Benowitz et al. 1985). Twin studies suggest a significant genetic contribution to the variation in nicotine renal clearance (Benowitz et al. 2008). However, the molecular mechanism is largely unknown. In vitro experiments suggested that variation in the polymorphic organic cation transporter 2 might play a role (Benowitz et al. 2008). 27

49 1.4 Markers of Tobacco Consumption Self-Report Cigarettes Per Day Self-report number of cigarettes smoked per day (CPD) is the most commonly used tobacco and carcinogen exposure indicator in epidemiological studies. Like many self-report measurements, CPD has significant limitations. CPD exhibits a notable degree of number preference -- smokers are generally biased to report CPD in packs (i.e. half a pack per day or a pack per day)(klesges et al. 1995). Additionally, CPD does not reflect how much of a cigarette is smoked nor the depth of smoking inhalation or puff volumes. In fact, the levels of nicotine and carcinogen intake per cigarette are inversely related to CPD, which is likely due to the fact that heavier smokers reduce the intensity of smoking/depth of inhalation compared to lighter smokers (Joseph et al. 2005). This makes CPD a particularly weak indicator of tobacco consumption in light smokers as the greatest variation in nicotine intake per cigarette is observed in light smokers (Malaiyandi et al. 2006; Ho et al. 2009; Benowitz et al. 2011). Thus, objective markers of tobacco consumption generally provide better estimations of nicotine intake than CPD Cotinine Cotinine is used as an objective index of tobacco and tobacco-derived carcinogen exposure. The use of cotinine is particularly useful because it overcomes the issue of the wide inter-individual variability in depth of inhalation, and number of puffs per cigarette (Benowitz et al. 2011). A number of studies in heavy smokers have observed significant correlations between plasma cotinine levels and CPD with correlation coefficients ranging from 0.3 to 0.8 (Perez-Stable et al. 1995; Domino et al. 2002; Mustonen et al. 2005; Scherer et al. 2007). A weaker correlation between plasma cotinine levels and CPD is observed in light smokers with only 17% of the variation in plasma cotinine level accounted for by CPD (Ho et al. 2009). In addition to being a tobacco consumption biomarker, plasma cotinine levels are used extensively to distinguish smokers from non-smokers. Since non-smokers can sometimes be exposed to low levels of nicotine via secondhand smoke and have detectable plasma cotinine levels (Jarvis et al. 1987; 2002; Benowitz et al. 2009), a plasma cotinine cutoff of 14 ng/ml is used to distinguish smokers from non-smokers; this cut off can also be used to verify smoking status in light smokers (Ho et al. 2009). 28

50 Despite its popularity, plasma cotinine has some significant limitations as a biomarker of tobacco consumption; the correlation between plasma cotinine levels and nicotine intake differs among different groups of smokers. For example, the findings with plasma cotinine sometimes contradict the findings with other indicators of tobacco exposure in genetic association studies. Caucasian heavy smokers with reduced function CYP2A6 alleles smoke fewer CPD compared with those without any reduced function CYP2A6 alleles, reflecting smokers tendency to titrate tobacco consumption to obtain a desired level of nicotine in the body (see later sections) (Schoedel et al. 2004; Wassenaar et al. 2011). Yet despite smoking fewer CPD, smokers with reduced function CYP2A6 alleles have similar plasma cotinine levels as those without any reduced function CYP2A6 alleles (Strasser et al. 2011). Another example is found in studies of African American light smokers, where similar levels of CPD are reported between those with reduced function CYP2A6 alleles and those without any reduced function CYP2A6 allele, but significantly higher plasma cotinine levels are observed in those with reduced function CYP2A6 alleles (Ho et al. 2009). Furthermore, gene variants at the CYP2A6 loci, which are associated with decreased lung cancer risk, are paradoxically associated with increased plasma cotinine levels (Timofeeva et al. 2011). Plasma cotinine levels also vary between the sexes. The male participants of the National Health and Nutrition Examination Surveys have significantly higher plasma cotinine levels compared to the female participants even after adjusting for CPD, machine-determined nicotine delivery of cigarettes, race, age, body mass index, poverty status, and the use of either menthol or regular cigarettes (Gan et al. 2008). Furthermore, notable variation in cotinine levels is also observed between races. African American smokers generally have higher plasma cotinine levels compared to Caucasian smokers after adjusting for CPD and the machine-determined nicotine delivery of cigarettes (Wagenknecht et al. 1990), which could be partially due to the slower cotinine clearance in African Americans compared to Caucasians (Perez-Stable et al. 1998). Overall, the observed systemic variation in plasma cotinine levels among CYP2A6 genotypes, the sexes and races suggests that using plasma cotinine levels as means of assessing tobacco consumption has significant flaws and may result in systemic bias. Chapter 2 will discuss the precise molecular mechanism of this phenomenon. 29

51 1.4.3 Total Nicotine Equivalents Total nicotine equivalents (TNE) is the urinary molar sum of nicotine and 8 of its major metabolites, including nicotine, nicotine glucuronide, cotinine, cotinine glucuronide, 3HC, 3HC glucuronide, nicotine N oxide, nornicotine, and cotinine N oxide (St Charles et al. 2006)(see Fig. 5). Together, these 9 analytes account for more than 90% of a transdermally administered nicotine dose (Benowitz et al. 1994). A 6 analytes version of TNE (without nicotine N oxide, nornicotine, and cotinine N oxide) is sometimes used in the literature, and generally correlates highly with the 9 analytes version (Zhu et al. 2013). The creatinine corrected spot urinary TNE is highly predictive of the nicotine dose (Benowitz et al. 2010). The correlation between creatinine corrected TNE and administered nicotine dose is stronger than the correlation observed between plasma cotinine levels and administered nicotine dose (Benowitz et al. 2010). Urinary TNE also has some additional advantages compared to plasma cotinine. Analytically, the urinary concentrations of nicotine metabolites are generally higher (often four to five-fold higher) than that found in plasma, which make analytical detection more sensitive. Most importantly, variability in the metabolism of nicotine and its metabolites has little effect on the validity of TNE as a biomarker of nicotine dose due to its inclusion of all nicotine metabolites (Benowitz et al. 2010). Due to these advantages, we used TNE as a reference biomarker of tobacco consumption in the thesis chapters NNAL In addition to TNE, the urinary levels of NNAL (4-(methylnitrosamino)-1-(3-pyridyl)-1- butanol), which is a reductive metabolite of the highly carcinogenic NNK, is also used as a biomarker of tobacco and tobacco related carcinogen exposure. As discussed in earlier sections, TSNA, particularly NNK, is a class of strong human carcinogens which can induce tumors of the pancreas, nasal cavity, liver and lungs in experimental animals (Hecht 1998). The direct measurement of NNK levels in humans is difficult due to its extensive metabolism to NNAL that results in low NNK levels. Therefore, urinary levels of NNAL and NNAL glucuronide are used as an indicator of NNK and tobacco smoke exposure. Urinary NNAL is a more precise predictor of lung cancer risk than self-report smoking history (Yuan et al. 2009). The NNAL levels are strongly associated with the risk of developing lung cancer in smokers (Church et al. 2009; Yuan et al. 2009). Those smokers who were in the highest tertile of urinary NNAL levels had 9-fold 30

52 higher risk of developing lung cancer compared to those in the lowest tertile of urinary NNAL levels, even after adjusting for smoking history and tobacco consumption (Yuan et al. 2009). As a biomarker, urinary NNAL has a number of desirable characteristics and some limitations. It is highly specific to tobacco exposure and is found only in people who use tobacco or are exposed to secondhand tobacco smoke (Yuan et al. 2009). NNAL also has a long half-life in humans (7-10 days), which makes it a desirable biomarker of tobacco exposure especially in light smokers (Benowitz et al. 2010; Goniewicz et al. 2011; Ter-Minassian et al. 2012). A limitation of NNAL is that variable NNK metabolism may alter NNAL levels without altering tobacco consumption (Ter-Minassian et al. 2012). However, the contribution of variable NNK metabolism to the observed NNAL levels in smokers is still unclear. Urinary NNAL levels will only be used in the thesis chapters to represent exposure to TSNA. 1.5 Genetic Influence of Smoking Behaviors in Heavy Smokers Heritability of Smoking Behaviors A large body of evidence, including twin and adoption studies, demonstrates a significant genetic contribution to ad libitum smoking behaviors and the ability to quit smoking. The heritability estimations for the genetic contribution to daily tobacco consumption are usually higher than 50% (Swan et al. 1997; True et al. 1997; Kendler et al. 2000; Vink et al. 2004; Ho et al. 2007), and the heritability of smoking cessation is approximately 50% (Xian et al. 2003). Variations in a number of genes can influence smoking behaviors in heavy smokers. Most of these genes can be classified into either nicotine pharmacodynamic genes or in nicotine s pharmacokinetic genes Variants in Nicotine Pharmacodynamic Genes Alter Tobacco Consumption in Heavy Smokers Variations in many genes involved in nicotine s pharmacodynamic pathways are associated with alterations in tobacco consumption and nicotine dependence as assessed primarily in heavy smokers. Candidate gene studies suggested that the genes encoding for the α4 and β2 nachr subunits, DOPA decarboxylase, GABA receptor subunits, and catechol-o-methyltransferase are significantly associated with tobacco consumption (Feng et al. 2004; Beuten et al. 2005; Li et al. 2005; Ma et al. 2005; Beuten et al. 2006; Lou et al. 2006; Yu et al. 2006). However, most of 31

53 these gene loci are not consistently replicated in genome wide association studies in Caucasians, which involve more than 100,000 subjects. This discrepancy is likely due to small sample sizes, small effect sizes and genetic heterogeneity of the original studies (Consortium 2010; Liu et al. 2010; Thorgeirsson et al. 2010). A number of genome wide association studies have identified significant associations between the chromosome 15q25 CHRNA5-A3-B4 gene cluster (which encodes for α5, α3, and β4 nachr subunits) and lung cancer risk in Caucasians (Amos et al. 2008; Hung et al. 2008; Thorgeirsson et al. 2008). Subsequent analyses have suggested that this association between CHRNA5-A3-B4 and lung cancer risk is at least partially mediated though altered tobacco consumption (Bierut 2009; Keskitalo et al. 2009; Saccone et al. 2009; Munafo et al. 2012). Genetic variants in CHRNA5-A3-B4 will be used here to illustrate the contribution of nicotine pharmacodynamic genes on smoking behaviors CHRNA5-A3-B4 and Nicotine Dependence CHRNA5-A3-B4 and Tobacco Consumption A significant association between CHRNA5-A3-B4 gene variants and nicotine dependence (i.e. FTND scores) was first observed by Saccone et al. (Saccone et al. 2007). In this study, the minor allele A of rs (which correlates highly with rs in Caucasians, r 2 >0.98) was significantly associated with increased FTND scores (Saccone et al. 2007). This association between rs /rs and smoking behaviors was subsequently replicated in a genome wide association study, which also demonstrated significant associations between rs /rs and smoking related diseases (lung cancer, COPD and peripheral arterial disease) (Thorgeirsson et al. 2008; Siedlinski et al. 2011). Since then, rs /rs has been consistently associated with nicotine dependence and tobacco consumption in Caucasian heavy smokers (Keskitalo et al. 2009; Saccone et al. 2010; Thorgeirsson et al. 2010; Chen et al. 2012). At least three independent loci in CHRNA5-A3-B4 are associated with tobacco consumption in Caucasian heavy smokers. The most commonly implicated locus is rs /rs (sometimes referred to as Bin A or Locus 1 ). Each copy of the A allele of rs is associated with an increase of roughly 1 CPD, ng/ml in cotinine, and a 1.3 fold higher odds ratio of developing lung cancer (Le Marchand et al. 2008; Keskitalo et 32

54 al. 2009; Wassenaar et al. 2011; Munafo et al. 2012). The association between rs /rs and objective tobacco consumption biomarkers is generally stronger than the association observed between rs /rs and CPD. For example, rs /rs accounted for five times greater variance in cotinine levels than in CPD (Keskitalo et al. 2009). In addition to rs /rs , two loci in CHRNA5-A3-B4 are also independently associated with tobacco consumption in Caucasian smokers. Those include rs and correlated SNPs (sometimes referred to as Bin B or Locus 3 ), and rs and correlated SNPs (sometimes referred to as Bin C or Locus 2 ) (Saccone et al. 2010; Chen et al. 2012). Associations between CHRNA5-A3-B4 gene variants and other aspects of smoking behaviors, such as smoking initiation and smoking cessation, have also been observed. However, those associations are less consistently replicated compared to the associations observed with tobacco consumption. In terms of smoking initiation, rs /rs has been associated with a higher risk of being a regular smoker, which is partially attributed to the more positive first smoking experience in individuals with the minor A allele (Sherva et al. 2008). However, subsequent research failed to replicate this association between rs /rs and smoking initiation (Lips et al. 2010; Kaur-Knudsen et al. 2011). This discrepancy may be due to inconsistent definitions of smoking initiation between the studies. A more precise definition of smoking initiation in a prospective cohort design could clarify the association between CHRNA5- A3-B4 gene variants and smoking initiation. With regards to smoking cessation, significant associations between CHRNA5-A3-B4 gene variants and smoking cessation have been reported. However, it is not clear whether the influence of CHRNA5-A3-B4 gene variants on smoking cessation is independent of the type of pharmacological treatments (i.e. cessation in general, or just a particular pharmacological therapy). One study suggested that the association between CHRNA5-A3-B4 variants rs (Bin A) or rs (Bin B) and smoking cessation is primarily observed among smokers treated with the placebo treatment, and is not observed among those who received active pharmacological therapy (Chen et al. 2012). In contrast, another study reported a significant association between CHRNA5-A3-B4 variants rs and smoking cessation outcomes in smokers who received nicotine replacement therapy with little effect observed in the placebo arm 33

55 (Munafo et al. 2011). A recent study reported significant associations between CHRNA5-A3-B4 variants and smoking cessation outcomes in both placebo and nicotine replacement therapy arms but the effects were in opposite directions when compared with the earlier studies (Bergen et al. 2013). Gene variants in CHRNA5-A3-B4 have also been associated with altered varenicline side effect profiles (King et al. 2012). Some of these discrepancies could be due to variation in clinical trial design (i.e. sample sizes, inclusion/exclusion criteria, statistical adjustments for covariates, the use of behavior counseling and different follow up periods). Therefore, the precise pharmacogenetic impacts of CHRNA5-A3-B4 gene variants on smoking cessation are not yet clear CHRNA5-A3-B4 and Health Consequences of Smoking CHRNA5-A3-B4 gene variants are associated with increased risk for smoking related diseases such as bladder cancer, upper aerodigestive tract cancers (including lung cancer) and COPD (Young et al. 2008; Pillai et al. 2009; Lambrechts et al. 2010; Lips et al. 2010; Kaur-Knudsen et al. 2011). The most robust association between CHRNA5-A3-B4 gene variants and smoking related diseases is observed with lung cancer. Rs /rs is associated with lung cancer across a range of histological types (adenocarcinoma, squamous cell carcinoma, large cell and small cell carcinoma) and ethnicities (Caucasians, African Americans and Asians) (Amos et al. 2008; Hung et al. 2008; Sherva et al. 2008; Spitz et al. 2008; Shiraishi et al. 2009; Amos et al. 2010; Lips et al. 2010; Saccone et al. 2010; Truong et al. 2010; Jaworowska et al. 2011; Kaur- Knudsen et al. 2011; Sakoda et al. 2011; Timofeeva et al. 2011). After adjusting for rs /rs , two additional loci in CHRNA5-A3-B4, rs (Bin B) and rs (Bin C) are also significantly associated with lung cancer risks in Caucasians (Saccone et al. 2010). Despite the consistent association, it is still not clear whether the association between CHRNA5-A3-B4 gene variants and lung cancer is (at least partially) mediated directly via altering cell proliferation and survival (Brennan et al. 2011) or exclusively mediated indirectly via altering tobacco consumption (Munafo et al. 2012). Some studies observed associations between CHRNA5-A3-B4 gene variants and lung cancer even after adjusting for smoking quantity (Kaur-Knudsen et al. 2011; Wassenaar et al. 2011), which suggests that at least some variants may directly alter cell proliferation and survival. Others failed to observe a significant association between CHRNA5-A3-B4 gene variants and lung cancer in never smokers, which 34

56 suggests that these variants alter lung cancer risk by altering tobacco consumption (Girard et al. 2010). Some of these discrepancies may be due to the difficulty in correctly classifying former smokers and never smokers using self-report data. A large lung cancer study of correctly classified never smokers exposed to environmental tobacco smoke and other environmental lung carcinogens may be needed to convincingly demonstrate whether CHRNA5-A3-B4 gene variants directly contribute to lung carcinogenesis CHRNA5-A3-B4 and Body Weight In addition to its role in modulating tobacco consumption and the health consequences of smoking, CHRNA5-A3-B4 gene variants may also play a role in modulating body weight. Tobacco smoking regulates body weight in smokers due to nicotine s ability to increase metabolic rate and suppress the compensatory increase in appetite and feeding (Audrain- McGovern et al. 2011). Smokers usually weigh less than nonsmokers and typically gain 4 to 5 kg when they stop smoking (Seeley et al. 2011). Tobacco s ability to regulate body weight is partially mediated by the activation of α3β4 nicotinic receptors located on the POMC (Proopiomelanocortin) neurons in the arcuate nucleus of the hypothalamus by nicotine (Audrain- McGovern et al. 2011; Mineur et al. 2011). Since CHNRA5-A3-B4 encodes for the α3β4 nicotinic receptors, it is possible that CHRNA5-A3-B4 gene variants can modulate nicotine s ability to regulate body weight by altering α3β4 nicotinic receptor function. A CHRNA5-A3-B4 variant, rs , which alters nicotine intake, is associated with altered body weight (Freathy et al. 2011). Yet it is not clear whether this association is an indirect effect of rs on altering nicotine intake, or a direct effect of rs on altering nicotine s effect on body weight by modulating nicotinic receptor function (Freathy et al. 2011). This topic will be the subject of investigation in Chapter Variants in Nicotine Pharmacokinetic Genes Alter Tobacco Consumption in Heavy Smokers CYP2A6 and Nicotine Pharmacokinetics There is a significant heritable (~60%) contribution to nicotine clearance and metabolism (Swan et al. 2005). Genetic variation in the main nicotine-metabolizing enzyme, CYP2A6, contributes extensively to this high heritability as outlined below. 35

57 CYP2A6 Gene Variants and Nicotine Metabolism A substantial amount of inter-individual variation is observed in hepatic CYP2A6 mrna levels, protein levels and in vitro catalytic activity (Dempsey et al. 2004; Mwenifumbo et al. 2007; Al Koudsi et al. 2010). The human CYP2A6 gene contains 9 exons and spans 6700 base pairs on chromosome 19 (Hoffman et al. 1995). Currently, 38 numbered and two duplication alleles have been identified ( CYP2A6 variant alleles with lower activity can be classified into either loss of function alleles or reduced function alleles based on both in vitro and in vivo metabolism data (Table 2). CYP2A6 slow metabolizers are defined as individuals with one or more copies of loss of function alleles or two copies of reduced function alleles. Individuals with one copy of a reduced function allele are considered intermediate metabolizers (Schoedel et al. 2004; Mwenifumbo et al. 2008; Ho et al. 2009). In some studies, slow and intermediate metabolizers are grouped together as reduced metabolizers to maximize statistical power. The most profound effects of CYP2A6 genetic variantion on nicotine metabolism are observed in individuals with two loss of function CYP2A6 alleles. For example, individuals with two copies of the CYP2A6*4 allele, which is the CYP2A6 whole gene deletion allele (Nunoya et al. 1998; Nunoya et al. 1999; Nunoya et al. 1999; Oscarson et al. 1999; Oscarson et al. 1999), have higher nicotine plasma levels, higher peak nicotine levels and lower oral nicotine clearance compared to those without any CYP2A6*4 alleles following an oral nicotine administration (Xu et al. 2002; Dempsey et al. 2004). Furthermore, CYP2A6*4/*4 individuals excrete no 3HC and only 11 to 15% of the cotinine that wild type individuals excrete after receiving the same amount of nicotine or following a similar amount of smoking (Kitagawa et al. 1999; Yang et al. 2001; Dempsey et al. 2004; Mwenifumbo et al. 2010). Currently, while many of the variant alleles identified have a substantial impact on nicotine metabolism, only a small percentage of the inter-individual variation in nicotine metabolism can be explained by characterized CYP2A6 variants, and there is significant variability in nicotine metabolism among people without known CYP2A6 variants (Dempsey et al. 2004). Thus, the phenotypic marker, NMR, is useful as it can account for the known and unknown genetic variants, as well as the environmental influences on CYP2A6 activity in vivo. 36

58 Table 2 CYP2A6 alleles, their allele frequencies and in vitro and in vivo impacts on nicotine clearance. =Increased; =Decreased. Alleles Allele Frequencies (%) Allele description CYP2A6*1A Caucasians African American Korean Japanese Chinese CYP2A6*1B CYP2A6*1D CYP2A6* CYP2A6*4# CYP2A6* CYP2A6* The reference allele Higher transcription by mrna stabilization. Associated with faster nicotine clearance in vivo. 50% lower transcription in vitro. Unclear impact in vivo. Unstable, fails to incorporate heme and inactive protein in vitro. Inactive in vivo. Deletion of CYP2A6 gene caused by unequal crossover. Inactive in vivo. Unstable and inactive enzyme in vitro. Unclear impact in vivo. Unstable enzyme in vitro. Inactive towards nicotine in vivo. CYP2A6* Unclear in vivo impact. CYP2A6* Lower transcription in vitro. Reduced activity in vivo. 37 In vitro activity None None In vivo grouping Loss Loss Loss *1/*9:Reduced *9/*9:Loss CYP2A6* Inactive in vivo. Loss Reference (Yamano et al. 1990; Oscarson et al. 1999; Gambier et al. 2005; Gyamfi et al. 2005; Nakajima et al. 2006; Nurfadhlina et al. 2006; Wang et al. 2006; Mwenifumbo et al. 2008) (Pitarque et al. 2004; von Richter et al. 2004; Nakajima et al. 2006) (Yamano et al. 1990; Benowitz et al. 1995; Oscarson et al. 1999; Benowitz et al. 2001; Schoedel et al. 2004) (Nunoya et al. 1998; Nunoya et al. 1999; Oscarson et al. 1999; Ariyoshi et al. 2000; Schoedel et al. 2004; Gambier et al. 2005; Gyamfi et al. 2005; Huang et al. 2005; Minematsu et al. 2006; Nakajima et al. 2006) (Oscarson et al. 1999; Schoedel et al. 2004; Gyamfi et al. 2005; Huang et al. 2005; Nakajima et al. 2006; Nurfadhlina et al. 2006) (Ariyoshi et al. 2001; Xu et al. 2002; Yoshida et al. 2002; Schoedel et al. 2004; Gyamfi et al. 2005; Minematsu et al. 2006; Nakajima et al. 2006; Nurfadhlina et al. 2006) (Xu et al. 2002; Yoshida et al. 2002; Gyamfi et al. 2005; Mwenifumbo et al. 2005; Nakajima et al. 2006; Nurfadhlina et al. 2006) (Yoshida et al. 2002; Pitarque et al. 2004; Schoedel et al. 2004; Benowitz et al. 2006; Malaiyandi et al. 2006; Minematsu et al. 2006; Nakajima et al. 2006) (Xu et al. 2002; Yoshida et al. 2002; Gyamfi et al. 2005; Mwenifumbo et

59 CYP2A6* CYP2A6* CYP2A6* CYP2A6* CYP2A6* Lower activity in vitro. Unclear impact in vivo. Unstable enzyme in vitro. Reduced activity in vivo. Likely to exhibit reduced activity as it has the same -48T>G SNP as CYP2A9*9. Unclear impact in vivo. Likely to exhibit normal activity. Likely to exhibit reduced activity as it has the same -48T>G SNP as CYP2A9*9. CYP2A6* Unclear impact in vivo. CYP2A6* CYP2A6* CYP2A6* CYP2A6* CYP2A6* CYP2A6* *1/*12:Reduced *12/*12:Loss al. 2005; Nakajima et al. 2006; Nurfadhlina et al. 2006) (Daigo et al. 2002; Nakajima et al. 2006) (Oscarson et al. 2002; Schoedel et al. 2004; Benowitz et al. 2006; Nakajima et al. 2006; Audrain-McGovern et al. 2007) (Kiyotani et al. 2002; Haberl et al. 2005; Nakajima et al. 2006) (Kiyotani et al. 2002; Nakajima et al. 2006; Bloom et al. 2013) (Kiyotani et al. 2002; Haberl et al. 2005; Nakajima et al. 2006) (Kiyotani et al. 2002; Nakajima et al. 2006) Lower activity in vitro. Inactive in vivo. Loss Similar nicotine C- oxidation activity as the (Fukami et al. 2005) wild type in vitro. Lower nicotine C- oxidation activity in vitro. Likely to exhibit reduced activity as it has (Fukami et al. 2005) the same 6558T>C SNP as CYP2A6*7 and CYP2A6*10. Truncated protein in vitro. Inactive in vivo. None Loss Similar activity toward nicotine in vivo. Likely to exhibit reduced activity in vivo as it alters the same (Haberl et al. 2005) amino acid as (Fukami et al. 2004; Nakajima et al. 2006) (Fukami et al. 2005; Mwenifumbo et al. 2008; Ho et al. 2009) (Haberl et al. 2005; Al Koudsi et al. 2006) 38

60 CYP2A9*2. CYP2A6* Lower activity in vitro. (Ho et al. 2008; Mwenifumbo et al. Inactive in vivo. Loss 2008; Ho et al. 2009) CYP2A6*24 1 Similar nicotine C- (Mwenifumbo et al. 2008; Ho et al. oxidation activity as the 2009) wild type in vitro. CYP2A6* Similar nicotine C- oxidation activity as the (Mwenifumbo et al. 2008; Ho et al. Loss wild type in vitro. 2009) Inactive in vivo. CYP2A6* No detectable protein in vitro. Associated with (Mwenifumbo et al. 2008; Ho et al. greatly reduced activity Loss 2009) in vivo. CYP2A6* No detectable protein in (Mwenifumbo et al. 2008; Ho et al. vitro. Inactive in vivo. Loss 2009) CYP2A6* Similar nicotine C- oxidation activity as the (Mwenifumbo et al. 2008; Ho et al. wild type in vitro. 2009) Inconsistent in vivo impact. CYP2A6*31 1 Associated with reduced activity Loss Unpublished observation CYP2A6*34 Likely exhibits lower CYP2A6 activity Reduced? /Loss? Unpublished observation CYP2A6* Decreased thermal stability and activity in vitro. inactive in vivo. Loss (Al Koudsi et al. 2009; Ho et al. 2009) CYP2A6* Unclear impact in vivo (Bloom et al. 2011) CYP2A6*1X Gene duplication A Unclear impact in vivo. (Rao et al. 2000) CYP2A6*1X Gene duplication B Unclear impact in vivo. (Rao et al. 2000; Fukami et al. 2007) 39

61 CYP2A6 and Interethnic Variability in Nicotine Metabolism There is substantial interethnic variation in nicotine metabolism, which can be attributed to the genetic differences observed in CYP2A6. The frequency of CYP2A6 alleles varies substantially between ethnicities; loss of/reduced function CYP2A6 alleles are more prevalent in Asians, followed by African Americans, and then Caucasians (Malaiyandi et al. 2005; Mwenifumbo et al. 2007). The combined frequency of individuals with at least one copy of loss of/reduced function CYP2A6 alleles is 55%, 47% and 23% for Asians, African Americans and Caucasians respectively (Nakajima et al. 2006; Ho et al. 2009; Mwenifumbo et al. 2009; Lerman et al. 2010). The higher frequency of loss of/reduced function CYP2A6 alleles contributes to the lower CYP2A6 protein levels and activity in Asian liver microsomes compared to Caucasian liver microsomes (Shimada et al. 1996). These genetic findings are supported by the interethnic variation observed in in vivo nicotine pharmacokinetics. Asian Americans and African Americans metabolize nicotine and cotinine more slowly than Caucasian Americans (Benowitz et al. 1999; Benowitz et al. 2002). The interethnic variation in CYP2A6 may explain some of the differences in tobacco consumption and smoking related mortalities observed between different ethnicities (Benowitz et al. 2002) CYP2A6 and Tobacco Consumption in Heavy Smokers Tobacco consumption is closely regulated by CYP2A6 mediated nicotine clearance. Dependent smokers maintain a desired nicotine level in the body and cigarette craving is negatively associated with plasma nicotine concentration (Jarvik et al. 2000). Therefore, smokers with reduced CYP2A6 function tend to consume less tobacco to maintain desirable levels of nicotine in the body. Consistent with this, CYP2A6 slow metabolizers smoke fewer CPD, are less likely to smoke within 5 min after waking, have reduced inhalation depth, and are less nicotine dependent compared to CYP2A6 normal metabolizers (Pianezza et al. 1998; Gu et al. 2000; Schoedel et al. 2004; Malaiyandi et al. 2006; Strasser et al. 2007). On the other hand, individuals with faster CYP2A6 activity, such as those with duplication alleles or the gain of function CYP2A6*1B, have higher tobacco consumption, again suggesting that smokers titrate tobacco consumption according to their CYP2A6 activity and resulting nicotine clearance (Rao et al. 2000; Nakajima et al. 2001; Tyndale et al. 2002). Together, these data suggest that the rate of nicotine clearance could have a profound influence on smoking behaviors. 40

62 CYP2A6 and Smoking Cessation Outcomes in Heavy Smokers Genetic variants in CYP2A6 can significantly alter smokers ability to quit smoking and their response to smoking cessation pharmacotherapies. For example, slower nicotine metabolism (by NMR or by CYP2A6 genotype) is associated with higher smoking cessation rates in placebotreated individuals (i.e. without the aid of a pharmacotherapy)(patterson et al. 2008; Ho et al. 2009). This is consistent with CYP2A6 slow metabolizers higher likelihood of being former smokers compared with current smokers (Gu et al. 2000; Iwahashi et al. 2004; Schoedel et al. 2004). Furthermore, individuals with low NMR (indicative of slow CYP2A6 activity), or CYP2A6 slow metabolizers by genotype, have significantly better smoking cessation rates on nicotine patch compared to individuals with normal CYP2A6 activity (Lerman et al. 2006; Malaiyandi et al. 2006; Lerman et al. 2010). This is likely due to the higher nicotine plasma concentrations in the CYP2A6 slow metabolizers as well as the slow metabolizers higher unaided smoking cessation rates. Interestingly, no difference in quit rates was observed between CYP2A6 slow metabolizers and normal metabolizers receiving nicotine nasal spray treatment (Lerman et al. 2006; Malaiyandi et al. 2006). This may be due to the fact that the subjects receiving nicotine nasal spray altered the amount of spray usage to titrate their plasma nicotine levels according to their different rates of nicotine metabolism (i.e. the CYP2A6 slow metabolizers used less nicotine spray) (Malaiyandi et al. 2006). Moreover, no associations were found between CYP2A6 activity and the clinical response to bupropion (not a CYP2A6 substrate) therapy (Patterson et al. 2008). Together, these data strongly suggest that the rate of nicotine C-oxidation can have significant effects on smoking cessation outcomes CYP2A6 and Health Consequences of Smoking Besides altering smoking behaviors, reduced CYP2A6 activity is associated with decreased risk for smoking related diseases. Specifically, reduced function CYP2A6 gene variants have been associated with lower risk of developing lung cancer and COPD in smokers (Timofeeva et al. 2011; Wassenaar et al. 2011). The association between reduced function CYP2A6 gene variants and decreased lung cancer risk is mediated by both reduced tobacco consumption and lower carcinogen metabolism. Reduced CYP2A6 mediated nicotine metabolism results in lower CPD and consequently lower carcinogen exposure (Schoedel et al. 2004; Strasser et al. 2011; Wassenaar et al. 2011). Additionally, the procarcinogenic TSNAs in tobacco require metabolic 41

63 activation by CYPs to form their reactive metabolites, which are then spontaneously converted to diazonium ions and react with DNA. The metabolic activation of NNN is mediated by CYP2A6 (Kushida et al. 2000; Wong et al. 2005). Therefore, individuals with reduced CYP2A6 activity have less activation of NNN as will be discussed in Chapter 1. CYP2A6 slow metabolizers have a decreased risk of lung cancer even after adjusting for the amount of cigarettes smoked (Fujieda et al. 2004; Wassenaar et al. 2011). Thus, reduced CYP2A6 activity decreases lung cancer risk by both decreasing tobacco consumption and TSNA activation. 1.6 Light Smokers Prevalence Historically, smoking and tobacco research has focused on heavy smokers. The United States National tobacco survey did not contain any questions about light smokers and non-daily smokers until 1992 (Shiffman 2009). Over the past 30 years, although the overall smoking prevalence has decreased, an increased proportion of smokers have started to smoke fewer CPD (Centers for Disease Control and Prevention 2008). The average CPD smoked by adult smokers in the United States decreased from 26 in 1989 to 16 in 2009 (Filion et al. 2012). The majority of the reduction occurred before the year 2000 with little change observed since 2000 (Duval et al. 2008). In the United States, about 30% of current smokers are light smokers who smoke less than 10 CPD (Kandel et al. 2000; Trinidad et al. 2009). Similar trends are reported in the Canadian population; the average tobacco consumption among Canadian smokers is 14.4 with nearly 40% light smokers (Health Canada 2011). The prevalence of light smoking can vary widely by sex, age and ethnicity. Light smoking is particularly prevalent in young people, educated people, females and ethnic minorities (Hassmiller et al. 2003; Wortley et al. 2003). Although the percentage of light smokers increased among both sexes from 2001 to 2011, this increase is more pronounced in females. In fact, around 62.6% of adult Canadian female smokers are light smokers (Health Canada 2007; Health Canada 2008; Health Canada 2011). Variation in the prevalence of light smoking is also observed between ethnic populations. As much as 67% of African-Americans, 72% of Asian Americans, and 76% of Hispanic Americans are light smokers compared to the 40% in Non- Hispanic Whites (Trinidad et al. 2009). Light smoking is also highly prevalent globally. The 42

64 mean CPD in Indian male smokers is 6.1, and as much as two-thirds of the smokers in developing countries are light smokers (Giovino et al. 2012) Health Consequences Although the risks of many smoking related diseases are dose dependent (Garfinkel et al. 1988; Jimenez-Ruiz et al. 1998; Mucha et al. 2006), it is generally believed that there is no safe level of smoking. Women who smoke less than 10 cigarettes per day had a two times higher overall mortality rate compared to non-smokers (Pirie et al. 2013). Light smoking has been associated with a 20 times greater risk of developing COPD, a 15.5 times greater risk of developing lung cancer (see Fig. 7)(Thun et al. 1997), a 3 times greater risk of death from ischemic heart disease, a 2.1 times greater risk for myocardial infarction, as well as higher risks of developing gastrointestinal cancers compared to never smokers (Jimenez-Ruiz et al. 1998; Prescott et al. 2002; Bjartveit et al. 2005; Schane et al. 2010). Lung cancer COPD Relative Risk (95% CI) Relative Risk (95% CI) < < Cigarettes Per Day Cigarettes Per Day Figure 7 Relative risks of lung cancer and chronic obstructive pulmonary disease in light smokers (<10 CPD) in comparison with heavy smokers. This figure was plotted using data Published by Thun et al.,

65 1.6.3 Smoking Characteristics Light smokers have distinct smoking characteristics compared with moderate to heavy smokers (Shiffman 1989; Shiffman et al. 1995). Light smokers do not exhibit the characteristic features of tobacco/nicotine dependence observed in heavy smokers and they generally score very low on the FTND scale (which is designed for heavy smokers) (Shiffman 1989; Shiffman et al. 1995; Okuyemi et al. 2002; Ho et al. 2009). In addition, light smokers tend to smoke their first cigarette later in the morning than heavy smokers, and generally do not smoke when ill or in places where smoking is prohibited (Shiffman 1989; Shiffman et al. 2006). They also do not report many withdrawal symptoms during smoking abstinence, suggesting nicotine withdrawal plays a relatively limited role in determining the smoking patterns of light smokers (Shiffman 1989; Shiffman et al. 2006). Heavy smokers smoke at regular intervals to maintain sufficient nicotine levels in the body and to avoid nicotine withdrawal. The low frequency of smoking in light smokers makes it difficult to maintain sufficient plasma nicotine levels to avoid nicotine withdrawal (Shiffman et al. 1992). It is possible that light smokers are either more sensitive to nicotine or clear nicotine more slowly than heavy smokers. However, this is not supported by clinical evidence. Light smokers generally show similar cardiovascular responses to cigarettes, and appear to eliminate nicotine at similar rates compared to heavy smokers (Shiffman et al. 1990; Brauer et al. 1996), suggesting that nicotine s pharmacokinetics and pharmacodynamics are not significantly different in light smokers. Overall, it appears that, unlike heavy smokers, light smokers do not maintain stable plasma nicotine levels. This characteristic makes light smokers distinct from heavy smokers and a novel population in the study of the role of genetics in smoking behaviors Smoking Cessation Despite the prevalence and health consequences associated with light smoking, there is little data on the efficacy of smoking cessation interventions for this group since most clinical trials exclude light smokers. Light smokers are more likely to perceive quitting as not very difficult compared to heavy smokers (Owen et al. 1995), and less likely to receive professional help from physicians to stop smoking (Kotz et al. 2013). Yet smoking cessation can be very difficult in light smokers, possibly more difficult than heavy smokers. Light smokers usually report repeated unsuccessful quit attempts, and the unaided smoking cessation rate is lower in light smokers 44

66 compared to heavy smokers at 6 month (Ahluwalia et al. 2002; Ahluwalia et al. 2006). This could be due, at least in part, to the lower perception of risk associated with light smoking (Owen et al. 1995). Furthermore, a number of clinical trials also suggested that light smokers do not respond to smoking cessation pharmacotherapies, including nicotine replacement therapy and bupropion, as well as heavy smokers do (Ahluwalia et al. 2002; Ahluwalia et al. 2006; Cox et al. 2012; de Dios et al. 2012). This could be due to light smokers low adherence to smoking cessation medications (manuscript attached in Appendix B (Zhu et al. 2012)). Together, these data suggest that there is a pressing need for more efficacious smoking cessation treatments in light smokers. A better understanding of the mechanisms behind light smoking behaviors may lead to more efficacious smoking cessation strategies. 1.7 Smokeless Tobacco Prevalence In the United States, about 7% of men and 0.3% of women are regular smokeless tobacco users (Hatsukami et al. 2004; Minematsu et al. 2006; Phillips et al. 2009; Centers for Disease Control and Prevention 2010). In Canada, 8% of Canadian adults have tried smokeless tobacco products, but the prevalence of regular smokeless tobacco use is under 1% (Health Canada 2007; Health Canada 2008; Health Canada 2011). Like smoking, there are substantial gender, ethnic and socioeconomic differences in the prevalence of smokeless tobacco use. Particularly, smokeless tobacco use is more prevalent in males, young non-hispanic Whites, those with less than high school education, those living in the southern United States, and those living in rural areas (Tomar 2003) Health Consequences Although generally perceived as a safer alternative to smoking due to the lack of combustion, smokeless tobacco can cause serious health consequences. Smokeless tobacco in North America contains more than 30 carcinogens (IARC Working Group on the Evaluation of Carcinogenic Risks to Humans 2007; Boffetta et al. 2008). Among these carcinogens, TSNA levels are higher than those found in cigarette products (Benowitz et al. 2012). Clinically, smokeless tobacco users have a higher risk of developing oral and lung cancers compared to people who do not use any tobacco products (IARC Working Group on the Evaluation of Carcinogenic Risks to Humans 45

67 2007; Boffetta et al. 2008). In a study that compared the risk of developing lung and oral cancers between smokers who had switched to North American brands of smokeless tobacco and smokers who had quit smoking completely, the relative risks of lung cancer and oral cancer were 1.5 and 2.6 times higher in the smokeless tobacco group respectively (Henley et al. 2007). Smokeless tobacco is sometimes marketed as a harm reduction method for cigarette smokers who can not quit smoking (Hatsukami et al. 2004). This is largely supported by data from Sweden, where a significant reduction in tobacco related morbidity and mortality has been attributed to the high popularity of the low TSNA oral snuffs (Henley et al. 2007). However, it is important to note that the North American brands of smokeless tobacco are cured differently, resulting in a much higher nitrosamine content. Therefore, the utility of using smokeless tobacco as a harm reduction method in North American smokers is questionable. 1.8 Alaska Native Tobacco Users: Light Smoking and Smokeless Tobacco Use This thesis focuses on Alaska Native tobacco users as an example population of light smokers and smokeless tobacco users. Tobacco use is prevalent in Alaska Native peoples. In fact, American Indians and Alaska Natives reported the highest rate of tobacco use of any ethnic groups in the United States (United States Public Health Service. Office of the Surgeon General. 1998; Behavioral Risk Factor Surveillance System 2008). The prevalence of smoking in Alaska Native individuals is 43.5% compared to the United States National average of 20%. The prevalence of light smoking is also high (85%) in Alaska Native smokers (Trinidad et al. 2009; Renner et al. 2013). Alaska Native light smokers share many characteristics compared to other populations of light smokers (e.g. young, lower incomes and without high school diploma) (Smith et al. 2010). In addition to light smoking, Alaska Native individuals, especially women, also exhibit a high prevalence of smokeless tobacco use in the forms of commercial chewing tobacco and iqmik (which is a homemade smokeless tobacco product containing fire-cured tobacco leaves with ash generated from burning the fungus)(renner et al. 2005). A significant portion of Alaska Native individuals believe that the health risks associated with iqmik are lower compared with smoking and commercial chewing tobacco (Renner et al. 2005). 46

68 Due to the high prevalence of light smoking and smokeless tobacco use, and the similar smoking characteristics compared to other populations of light smokers, Alaska Native tobacco users serve as a useful representative population for studying the genetic influence on the smoking behaviors in light smokers and smokeless tobacco users. 47

69 1.9 STATEMENT OF RESEARCH HYPOTHESES In Chapter 1 Alaska Native smokers and smokeless tobacco users with slower CYP2A6 activity have lower tobacco consumption, lower tobacco-specific nitrosamine exposure and lower tobacco-specific nitrosamine bioactivation. We hypothesize that light smokers and smokeless tobacco users with lower CYP2A6 activity will have lower tobacco consumption as measured by urinary TNE. We also hypothesize that the tobacco users with lower CYP2A6 activity will have lower urinary NNAL levels, reflecting lower tobacco consumption, and higher urinary NNN levels, reflecting reduced NNN metabolic activation. In Chapter 2 The ability of plasma cotinine to predict nicotine and carcinogen exposure is altered by differences in CYP2A6: the influence of genetics, race, and sex. We hypothesize that lower CYP2A6 activity will decrease cotinine clearance and alter the quantitative relationship between plasma cotinine with nicotine or tobacco-derived carcinogen exposure in smokers. In Chapter 3 CHRNA5-A3-B4 genetic variants alter nicotine intake and interact with tobacco use to influence body weight in Alaska Native tobacco users. We hypothesize that (1) genetic variants in CHRNA5-A3-B4 alter tobacco consumption and tobacco-derived carcinogen exposure in Alaska Native light smokers as seen in heavy smokers; (2) CHRNA5-A3- B4 gene variants are associated with altered body weight, even after controlling for nicotine intake. 48

70 2 CHAPTER 1: ALASKA NATIVE SMOKERS AND SMOKELESS TOBACCO USERS WITH SLOWER CYP2A6 ACTIVITY HAVE LOWER TOBACCO CONSUMPTION, LOWER TOBACCO-SPECIFIC NITROSAMINE EXPOSURE AND LOWER TOBACCO-SPECIFIC NITROSAMINE BIOACTIVATION Andy Z.X. Zhu, Matthew J. Binnington, Caroline C. Renner, Anne P. Lanier, Dorothy K. Hatsukami, Irina Stepanov, Clifford H. Watson, Connie S. Sosnoff, Neal L. Benowitz and Rachel F. Tyndale Reprinted with permission from American Association for Cancer Research: Carcinogenesis 34(1): All rights reserved. DKH, APL, CCR, NLB and RFT designed the overall study. APL and CCR recruited the participants. NLB determined the levels of nicotine, cotinine and trans-3-hydroxycotinine in plasma. IS determined the levels of NNN. CSS and CHW determined the levels of urinary nicotine metabolites. AZZ performed the DNA extraction from blood and plated the DNA for genotyping. MJB and AZZ conducted the genotyping. AZZ merged and maintained a study database and performed all analyses and modeling. AZZ and RFT wrote the manuscript. 49

71 2.1 Abstract Nicotine, the psychoactive ingredient in tobacco, is metabolically inactivated by CYP2A6 to cotinine. CYP2A6 also activates procarcinogenic tobacco-specific nitrosamines (TSNA). Genetic variation in CYP2A6 is known to alter smoking quantity and lung cancer risk in heavy smokers. Our objective was to investigate how CYP2A6 activity influences tobacco consumption and procarcinogen levels in light smokers and smokeless tobacco users. Cigarette smokers (n=141), commercial smokeless tobacco users (n=73), and iqmik users (n=20) were recruited in a crosssectional study of Alaska Native peoples. The participants CYP2A6 activity was measured by both endophenotype and genotype, and their tobacco and procarcinogen exposure biomarker levels were also measured. Smokers, smokeless tobacco users and iqmik users with lower CYP2A6 activity had significantly lower urinary total nicotine equivalents (TNE) and NNAL levels (a biomarker of TSNA exposure). Levels of NNN, a TSNA metabolically bioactivated by CYP2A6, were higher in smokers with lower CYP2A6 activities. Light smokers and smokeless tobacco users with lower CYP2A6 activity reduce their tobacco consumption in ways (e.g. inhaling less deeply) that are not reflected by self-report indicators. Tobacco users with lower CYP2A6 activity are exposed to lower procarcinogen levels (lower NNAL levels) and have lower procarcinogen bioactivation (as indicated by the higher urinary NNN levels suggesting reduced clearance), which is consistent with a lower risk of developing smoking related cancers. This study demonstrates the importance of CYP2A6 in the regulation of tobacco consumption behaviors, procarcinogen exposure and metabolism in both light smokers and smokeless tobacco users. 50

72 2.2 Introduction Smoking is the largest preventable cause of lung cancer. American Indians and Alaska Native people have the highest prevalence of tobacco usage among all ethnic groups in the U.S.A. (Behavioral Risk Factor Surveillance System 2008). On average Alaska Native smokers consume fewer cigarettes per day (CPD) compared to Caucasians(United States Public Health Service. Office of the Surgeon General. 1998), yet the incidence of lung cancer among Alaska Native people is higher than the U.S. national average (Centers for Disease Control and Prevention 2003; Centers for Disease Control and Prevention 2010). In addition to smoking, a significant proportion of Alaska Native people use commercial smokeless tobacco products and iqmik. The latter is a homemade smokeless tobacco product containing alkaline ash (Renner et al. 2005). We investigated whether genetic variation in CYP2A6, a nicotine and tobacco specific nitrosamine metabolizing enzyme, alters tobacco consumption and procarcinogen levels which could influence the risk of developing lung cancer in this population. Nicotine is the main psychoactive ingredient in tobacco. Genetic variants influencing the pharmacokinetics and pharmacodynamics of nicotine are associated with altered tobacco consumption and lung cancer risk (Thorgeirsson et al. 2010; Wassenaar et al. 2011). In humans, the majority of nicotine is metabolized to cotinine (COT) by CYP2A6 (Nakajima et al. 1996). COT is then metabolized to trans-3 -hydroxycotinine (3HC) exclusively by CYP2A6 (Nakajima et al. 1996). The human CYP2A6 gene is highly polymorphic: about 25% of Caucasians, 50% of African Americans, and 60% of Asians have at least one copy of a reduced function CYP2A6 allele (Mwenifumbo et al. 2007; Ho et al. 2009; Lerman et al. 2010). CYP2A6 genotype significantly alters nicotine clearance, and has been associated with altered tobacco consumption and tobacco related lung cancer risk (Benowitz et al. 2006; Wassenaar et al. 2011). In addition to CYP2A6 genotype, the ratio of 3HC to COT (also known as the nicotine metabolite ratio, NMR) is an in vivo endophenotype of CYP2A6 activity (Dempsey et al. 2004). The NMR is stable throughout the day and correlates highly with in vivo nicotine clearance (Dempsey et al. 2004; Lea et al. 2006). Caucasian smokers who have one or more reduced function CYP2A6 allele(s) (i.e. CYP2A6 reduced metabolizers, RM), or have lower plasma NMR, generally smoke fewer CPD and are less nicotine dependent compared to genotypical normal metabolizers (NM) or smokers with higher plasma NMR (Schoedel et al. 2004; Wassenaar et al. 2011). However, such 51

73 differences in CPD and nicotine dependence scores by CYP2A6 genotype or NMR are not observed in some light smoking populations, such as African Americans (Ho et al. 2009). This may be due to the limited sensitivity of tobacco consumption indicators like CPD and carbon monoxide in these light smokers (Mwenifumbo et al. 2007; Ho et al. 2009). The influence of CYP2A6 genetic variation on smokeless tobacco use has never been investigated. CPD, carbon monoxide levels and plasma COT are widely used indicators of nicotine and tobacco consumption in smokers, however they have significant limitations. For example, CPD is subject to reporting bias and does not account for the inter-individual differences in the depth of smoke inhalation or other smoking topography measures. This is particularly relevant in light smokers as the level of nicotine intake per cigarette is inversely related to reported CPD (Benowitz et al. 2011). Carbon monoxide has a short half-life, which limits its utility in sporadic/light smokers (Ho et al. 2009), and it is not an indicator of smokeless tobacco use. Plasma COT is specific to nicotine exposure, has a relatively long half-life, and in heavy smokers correlates with tobacco consumption (Benowitz et al. 2011). However, since COT is both formed and removed at different rates by CYP2A6, reduced function CYP2A6 variants may alter COT clearance more substantially than nicotine clearance, thus limiting the utility of COT as a biomarker of nicotine exposure. Recently urinary TNE, which represents the summation of urinary nicotine and its metabolites (nicotine, nicotine glucuronide, COT, COT glucuronide, 3HC, 3HC glucuronide, nicotine-n-oxide, cotinine-n-oxide, and nornicotine), has been used as an alternative biomarker of nicotine consumption (Scherer et al. 2007; Le Marchand et al. 2008). TNE accounts for about 90% of a transdermally administered nicotine dose (Benowitz et al. 1994), and creatinine-adjusted (e.g. per mg Cre) spot urinary TNE correlates strongly with daily nicotine consumption (Benowitz et al. 2010). The advantage of urinary TNE is that metabolites from non-cyp2a6 enzymatic pathways are also accounted for, such that TNE is not influenced by the rate of metabolism via CYP2A6. In this study, urinary TNE was used as the primary biomarker of nicotine consumption to evaluate the influence of CYP2A6 activity on nicotine consumption in smokers and smokeless tobacco users. Tobacco use is associated with an elevated risk of developing cancer (Hecht 2003). Nicotine itself is not carcinogenic, but the structurally related tobacco-specific nitrosamines (TSNA) such as 4-(methylnitrosamino)-1-(3)pyridyl-1-butanone (NNK) and N-nitrosonornicotine (NNN) are 52

74 (Hecht 2003). Once absorbed, these nitrosamines are bioactivated by cytochrome P450s to their α-hydroxyl metabolites, which are then spontaneously converted to diazonium ions and can result in DNA adducts. In the case of NNK, it is α-hydroxylated by CYP2B6 with an affinity roughly ten times higher (i.e. a lower K m ) than that of CYP2A6 (Jalas et al. 2005). In contrast, the α-hydroxylation of NNN is thought to be primarily mediated by CYP2A6 (Kushida et al. 2000; Wong et al. 2005). Individuals vary extensively in their procarcinogen exposure and metabolism (Harris et al. 1976; Hecht 2003; Stepanov et al. 2008). Urinary biomarkers can provide information on the intake and metabolism of procarcinogens. In the case of NNK, it is rapidly metabolized in humans and has not been detected in urine (Hecht et al. 1999). Hence total urinary (methylnitrosamino)-1-(3)pyridyl-1-butanol (NNAL), a reductive metabolite of NNK, is commonly used as a biomarker of NNK intake (Hecht 2003). NNAL has a long halflife, and urinary NNAL levels are stable and highly specific to tobacco exposure (Hecht 2003; Goniewicz et al. 2011). The long half-life (7 to 10 days) is especially important in light smokers as it provides an estimate of procarcinogen exposure averaged over an extended period of time (Shiffman 1989; Goniewicz et al. 2009). Like other markers of tobacco smoke exposure, urinary NNAL levels in smokers are dose-dependently associated with the risk of tobacco-related cancers (Yuan et al. 2009). In contrast to NNK, the procarcinogenic NNN can be directly measured in urine and its levels have been associated with the risk of developing esophageal cancer (Yuan et al. 2011). Since CYP2A6 plays a larger role in the metabolic activation of NNN versus NNK, we used urinary NNAL levels as a biomarker of NNK intake and exposure, whereas we used urinary NNN levels as a biomarker of residual, unmetabolized NNN. In this study, we used plasma NMR as the endophenotype of CYP2A6 activity. NMR accounts for both inherited and non-inherited variations in CYP2A6 activity (Binnington et al. 2012), which makes it a more thorough representation of the current rate of nicotine clearance than CYP2A6 genotype. As NMR can be influenced by exposure to inhibitors or inducers we also used CYP2A6 genotype; this dual approach also confirms that genetic variation in CYP2A6 is the major influence on the smoking behavior differences observed in individuals with different NMR endophenotypes. Using both the NMR endophenotype and CYP2A6 genotype, we tested the hypothesis that light smokers and smokeless tobacco users with lower CYP2A6 activity (i.e. in the lower NMR stratum or CYP2A6 reduced metabolizers, RM) have lower tobacco consumption as measured by urinary total nicotine equivalents (TNE), a biomarker of daily nicotine 53

75 consumption. We also tested the hypothesis that individuals with lower CYP2A6 activity will have lower urinary NNAL levels, reflecting lower tobacco consumption, and higher urinary NNN levels, reflecting reduced NNN metabolism. 2.3 Material and Methods Study Design A detailed description of recruitment procedures, participant characteristics and tobacco related behaviors has been reported previously (Renner et al. 2013). Briefly, 234 Yupik tobacco users were recruited in local villages near Bristol Bay, Alaska. Male and female (55%) current smokers (n=141), commercial smokeless tobacco users (n=73) and iqmik users (n=20) aged between 18 and 65 were eligible for this study; these are the same subjects as previously described except that two smokers with a mixed Yupik ancestry were not included in the current genetic analysis (Binnington et al. 2012). The research protocol was approved by the Alaska Area IRB, the Bristol Bay Area Health Corporation Board, the IRB at the University of California San Francisco, the IRB at the Centers for Disease Control and Prevention and the University of Toronto Ethics Review office. CYP2A6 genotyping As previously described (Binnington et al. 2012), DNA was extracted from blood (n=234) using the Genelute purification kit according to the manufacturer s instructions (Sigma-Aldrich Ltd. Oakville, Ontario, Canada). Prevalent CYP2A6 alleles with altered function (CYP2A6: *2, *4, *7, *9, *10, *12, *17 and *35) were genotyped by two-step allele specific PCR reactions according to previously reported methods (Schoedel et al. 2004; Mwenifumbo et al. 2005; Ho et al. 2009). Those individuals with one or two copies of a reduced function allele (*2, *4, *7, *9, *10, *12, *17 and *35) were classified as CYP2A6 RM (Mwenifumbo et al. 2008; Ho et al. 2009). Nicotine metabolite and procarcinogen exposure measurements Blood and urine samples were collected for the measurement of nicotine and its metabolites, as well as urinary total NNAL (i.e. NNAL and NNAL-glucuronide) and NNN (i.e. NNN and NNNglucuronide) levels. Plasma COT and 3HC levels, and urinary nicotine, nicotine metabolites, 54

76 NNAL and NNN levels were quantified by liquid chromatography-tandem mass spectrometry as previously described (Dempsey et al. 2004; Jacob et al. 2008; Bernert et al. 2011). Statistical Analyses Statistical analyses were performed using Stata statistical package version 11 (StataCorp, College Station, TX). NMR stratification was performed by a median split of plasma NMR within each tobacco product group. Participants who were in the higher NMR stratum were considered the faster CYP2A6 activity group, while those in the lower NMR stratum were considered the lower CYP2A6 activity group. The biochemical measures (nicotine, nicotine metabolites, NNN, and NNAL levels) were not normally distributed, thus pairwise comparisons were performed by non-parametric Wilcoxon s tests. Also for this reason, regression analyses were conducted using log-transformed data. 2.4 Results Alaska Native smokers with lower CYP2A6 activity exhibited lower tobacco consumption Baseline demographics (e.g. age, gender, and body mass index) did not differ between plasma NMR strata or CYP2A6 genotype groups (Table 3). Lower tobacco consumption was observed in individuals with slower NMRs. Specifically, urinary TNE levels were significantly lower in smokers in the slower (n=71) versus faster (n=70) plasma NMR stratum (56.3 vs nmol/mg Cre, respectively. P=0.006, Fig. 8 and Table 4). Similar results by NMR strata were observed with a 6 item TNE (i.e. nicotine, nicotine glucuronide, COT, COT glucuronide, 3HC and 3HC glucuronide), which is sometimes used as an alternative to the 9 item TNE (Table 4) (Benowitz et al. 2011). The TNE levels did not significantly differ between CYP2A6 genotypes (63.8 vs nmol/mg Cre in CYP2A6 RM and NM, respectively. Fig. 8 and Table 4). Alaska Native commercial smokeless tobacco users with lower CYP2A6 activity exhibited lower tobacco consumption Consistent with observations in smokers, commercial smokeless tobacco users in the slower (n=37) versus faster (n=36) plasma NMR stratum had 54% lower TNE (64.2 vs nmol/mg Cre, respectively. P=0.02, Fig. 8 and Table 5). Similar effects of NMR strata could be observed 55

77 with the 6 item TNE (Table 5). The TNE levels did not significantly differ between CYP2A6 genotypes (69.8 vs nmol/mg Cre in CYP2A6 RM and CYP2A6 NM respectively, P=0.08. Fig. 8 and Table 5). 56

78 Table 3 Baseline demographics by plasma NMR strata and CYP2A6 genotype. Smoker (n=141) Plasma NMR Strata Slower n=71 mean (SD) Faster n=70 mean (SD) P CYP2A6 genotypes Reduced n=62 mean (SD) Normal n=79 mean (SD) Age 35.1 (14.5) 37.7 (14.7) (15.3) 34.3 (12.8) 0.13 BMI 28.8 (5.6) 27.5 (6.6) (6.0) 27.8 (6.3) 0.31 Age of initiation 17.5 (6.4) 17.0 (4.5) (7.2) 16.6 (3.7) 0.25 Years smoked 17.6 (13.1) 20.7 (14.3) (14.3) 17.7 (13.2) 0.18 FTND 2.2 (1.9) 2.8 (2.1) (1.8) 2.6 (2.2) 0.60 Commercial Smokeless tobacco users (n=73) Slower n=37 mean (SD) Faster n=36 mean (SD) P Reduced n=34 mean (SD) Normal n=39 mean (SD) Age 37.0 (12.5) 42.1 (12.3) (12.5) 41.6 (12.4) 0.21 BMI 30.5 (7.7) 29.1 (6.4) (8.1) 29.8 (5.8) 0.45 Age of initiation 17.9 (6.7) 21.5 (1.8) (6.7) 21.3 (10.7) 0.35 Years of usage 19.2 (11.9) 20.6 (13.3) (12.2) 20.3 (13.0) 0.99 Iqmik users Slower Faster Reduced Normal (n=20) n=10 n=10 P n=9 n=11 P mean (SD) mean (SD) mean (SD) mean (SD) Age 42.1 (18.4) 43.6 (16.4) (18.2) 41.1 (16.5) 0.62 BMI 29.2 (5.1) 28.7 (6.5) (4.3) 29.9 (6.6) 0.38 Age of initiation 30.8 (18.5) 19.3 (13.6) (20.8) 21.9 (13.1) 0.37 Years of usage 11.3 (12.8) 24.3 (16.9) (17.6) 19.2 (15.5) 0.68 BMI = body mass index; FTND = Fagerstrom Test for Nicotine Dependence. Statistical comparisons were made by Wilcoxon s test P P

79 A: NMR B: CYP2A6 Genotype 200 Slower activity Faster activity 200 Reduced Normal Total Nicotine Equivalents (9 Items) (Mean ± 95% CI nmol/mg Creatinine) P=0.006 P= n Smokers Commercial Iqmik Chew 0 n Smokers Commercial Iqmik Chew Figure 8 Tobacco users with slower CYP2A6 activity have lower nicotine intake. A). by plasma NMR strata or B). by CYP2A6 genotypes. The statistical comparisons were made by Wilcoxon s test. 58

80 Table 4 Urinary and plasma nicotine exposure biomarkers by plasma nicotine metabolite ratio (NMR) stratum and CYP2A6 genotype in smokers. Plasma NMR strata CYP2A6 genotypes Slower, n=71 Faster, n=70 Reduced, n=62 Normal, n=79 % of % of % of % of urinary Absolute urinary Absolute urinary Absolute urinary Absolut Smokers nicotine P values nicotine values nicotine P (n=141) absol. P abs % values nicotine e values P equivale % ol. mean equivalen mean equivalent mean equivalent mean nts (SD) ts (SD) s (SD) s (SD) recovere recovered recovered recovered d Urinary (nmol/mg Cre) TNE (9- items) 56.3 (35.3) 79.2 (53.6) (38.2) 70.7 (52.3) TNE (6- items)* 49.5 (31.7) 73.6 (50.1) (34.6) 65.5 (49.1) Total nicotine 12.0 (14.2) 18.0 (14.6) 7.3 (8.0) 8.1 (6.3) (14.6) 16.9 (15.2) 7.5 (8.4) 10.1 (8.2) Free 8.8 (12.3) 12.5 (12.9) 5.5 (7.1) 5.9 (6.0) (12.7) 11.7 (12.9) 5.5 (7.4) 7.3 (7.8) Glucuro nide 3.2 (3.4) 5.5 (4.2) 1.8 (1.5) 2.2 (1.4) (3.5) 5.2 (4.5) 2.0 (1.7) 2.8 (2.0) Total COT 17.7 (13.0) 31.4 (9.2) 19.9 (14.8) 24.3 (6.4) (13.4) 30.1 (9.7) 18.7 (14.4) 26.1 (7.5) Free 8.9 (8.4) 14.6 (6.7) 9.4 (8.7) 11.1 (4.5) (8.9) 13.9 (7.0) 8.9 (8.3) 12.1 (4.8) Glucuro nide 8.8 (5.6) 16.8 (6.3) 10.5 (7.0) 13.1 (4.1) (5.6) 16.1 (6.2) 9.8 (7.0) 14.0 (4.9) Total 3HC 19.8 (13.3) 38.6 (15.4) 46.3 (33.2) 60.6 (11.8) (17.8) 41.2 (17.6) 39.3 (33.3) 56.0 (14.6) Free 17.2 (11.7) 33.8 (13.7) 39.4 (27.6) 51.5 (9.6) (16.1) 35.8 (15.6) 33.4 (27.5) 47.9 (11.7) Glucuro 2.7 (2.7) 5.0 (4.6) 6.9 (6.6) 9.1 (4.9) (3.1) 5.5 (4.8) 6.0 (6.5) 8.3 (5.1)

81 nide Nornicot ine 0.5 (0.4) 0.8 (0.4) 0.4 (0.3) 0.5 (0.2) (0.4) 0.8 (0.4) 0.4 (0.3) 0.6 (0.3) Nicotine -N- Oxide 4.5 (4.8) 7.7 (6.2) 2.8 (2.6) 3.4 (2.0) (5.0) 7.6 (6.5) 2.6 (2.3) 4.0 (2.8) Cotinine -N- Oxide 1.8 (1.1) 3.5 (1.4) 2.4 (1.5) 3.1 (0.7) (1.2) 3.5 (1.4) 2.2 (1.5) 3.2 (0.9) CPD 6.7 (4.4) 8.3 (5.9) (4.9) 7.7 (5.5) Plasma (ng/ml) COT 171 (101) 170 (110) (96) 165 (112) HC 45.9 (33.6) (77.2) (46.3) 91.2 (76.8) HC/CO T (0.105) (0.296) *Compared to TNE (9-items), TNE (6-items) did not included nornicotine, nicotine-n-oxide, and cotinine-n-oxide. Gluc=glucuronide. P % = the P values from Wilcoxon s tests when the metabolites were normalized to % of urinary total nicotine equivalents. P absol = the P values from Wilcoxon s tests when the absolute urinary recovery values were compared. Bold values indicate statistically significant differences between the groups by Wilcoxon s test. Levels were compared between the normal metabolizers and the reduced metabolizers (individuals with at least one copy of reduced function CYP2A6 alleles) or between the faster plasma NMR stratum and the slower plasma NMR stratum (median split) (0.175) (0.330)

82 Table 5 Urinary and plasma nicotine exposure biomarkers by plasma nicotine metabolite ratio (NMR) stratum and CYP2A6 genotype in commercial smokeless tobacco users and iqmik users. Plasma NMR strata CYP2A6 genotypes Slower, n=37 Faster, n=36 Reduced, n=34 Normal, n=39 % of % of % of % of Commer urinary urinary urinary urinary cial Absolute Absolute Absolute Absolute nicotine nicotine P smokeles abs nicotine nicotine P values values P absol equivale % values values equivale ol. equivale equivale. s tobacco mean mean mean mean nts nts nts nts (n=73) (SD) (SD) (SD) (SD) recovere recovere recovere recovere P % d d d d Urinary (nmol/mg Cre) TNE (9-Items) 64.2 (44.3) 99.0 (74.4) (54.6) 91.5 (68.7) TNE (6- Items)* 57.2 (39.1) 91.7 (69.4) (49.4) 84.2 (64.1) Total nicotine 10.5 (11.1) 15.0 (9.9) 9.7 (11.7) 8.5 (5.7) (11.8) 15.2 (10.4) 9.1 (11.0) 8.9 (5.4) Free 7.5 (9.7) 9.9 (8.9) 7.1 (10.4) 6.0 (5.4) (10.0) 10.4 (9.3) 6.7 (10.1) 5.9 (5.0) Glucuron ide 3.0 (2.1) 5.1 (2.3) 2.6 (2.6) 2.6 (1.4) (2.8) 4.8 (2.4) 2.4 (1.7) 3.0 (1.9) Total COT 22.1 (15.9) 34.3 (8.0) 24.4 (17.4) 25.1 (6.8) (18.7) 33.3 (8.5) 23.4 (14.7) 26.8 (7.7) Free 11.7 (10.3) 17.7 (8.5) 10.7 (7.9) 10.9 (4.1) (10.3) 16.8 (8.9) 11.0 (8.2) 12.2 (5.2) Glucuron ide 10.3 (7.2) 16.6 (6.0) 13.8 (10.8) 14.2 (5.3) (10.5) 16.5 (5.8) 12.3 (8.2) 14.5 (5.7) Total 3HC 24.6 (16.2) 39.8 (15.3) 57.6 (45.2) 59.2 (10.0) (24.0) 41.2 (16.5) 51.7 (43.5) 56.5 (12.0) Free 22.0 (14.9) 35.5 (14.4) 49.5 (37.9) 51.9 (11.4) (20.6) 36 (15.4) 45 (36.4) 50.2 (12.1) Glucuron 2.7 (2.6) 4.5 (3.8) 8.2 (8.4) 7.4 (4.6) (4.7) 5.3 (4.4) 6.7 (7.9) 6.5 (4.4)

83 ide Nornicot ine 0.6 (0.4) 0.9 (0.4) 0.6 (0.5) 0.5 (0.2) (0.5) 0.9 (0.5) 0.6 (0.4) 0.6 (0.3) Nicotine- N-Oxide 4.2 (4.0) 6.1 (3.6) 3.6 (3.1) 3.5 (2.2) (3.7) 5.6 (3.6) 3.9 (3.4) 4.1 (2.8) Cotinine- N-Oxide 2.3 (1.7) 3.8 (1.3) 3.1 (2.3) 3.2 (0.6) (1.9) 3.8 (1.3) 2.8 (2.2) 3.1 (0.6) Chew per day 6.3 (7.8) 5.2 (3.3) (8.0) 4.9 (3.4) Can per week 1.7 (1.3) 1.6 (1.6) (1.5) 1.5 (1.4) Plasma (ng/ml) COT 223 (116) 223 (148) 3HC 58 (36) 137 (95) 3HC/CO T NMR Iqmik users (n=20) (0.092) (0.275) Slower, n=10 Faster, n=10 % of % of urinary urinary Absolute Absolute nicotine nicotine values values equivale equivale mean mean nts nts (SD) (SD) recovere recovere d d Urinary (nmol/mg Cre) TNE (9-Items) TNE (6- items)* (129) 213 (135) (55) 119 (94) P abs ol. P % (0.135) (0.319) Reduced, n=9 Normal, n=11 % of % of urinary urinary Absolute Absolute nicotine nicotine values values equivale equivale mean mean nts nts (SD) (SD) recovere recovere d d (53.0) (38.7) (35.3) (55.7) (47.9) (37.3) (30.9) (53.1) P absol P %. Total 15.3 (8.1) 13.6 (6.1) 17.1 (10.2) 11.6 (5.7) (3.2) 14.2 (4.8) 15.8 (12.1) 11.3 (6.5)

84 nicotine Free 10.3 (6.8) 8.5 (5.2) 13.4 (10.9) 8.8 (6.6) (4.5) 9.1 (4.8) 12.8 (11.6) 8.3 (6.7) Glucuron ide 5.1 (3.7) 5.1 (4.1) 3.7 (3.1) 2.8 (2.6) (4.3) 5.1 (4.4) 3.1 (1.7) 3.0 (2.6) Total COT 34.3 (13.0) 32.0 (10.6) 31.2 (13.3) 23.0 (8.8) (13.2) 30.3 (7.7) 28.4 (11.5) 25.2 (12.2) Free 16.8 (9.3) 14.5 (4.5) 13.5 (8.3) 9.5 (4.8) (9.9) 13.0 (5.0) 13.4 (7.8) 11.1 (5.3) Glucuron ide Total 3HC 17.5 (5.7) 17.5 (8.1) 17.7 (8.2) 13.5 (7.1) (8.1) 17.2 (7.1) 14.9 (4.4) 14.1 (8.2) (37.0) 43.6 (15.1) 80.8 (29.1) 58.2 (10.6) (23.0) 44.7 (10.6) 76.5 (41.5) 56.0 (16.1) Free 52.4 (38.6) 40.9 (16.2) 69.4 (26.2) 50.1 (11.6) (23.9) 41.0 (11.4) 67.9 (39.1) 49.3 (16.1) Glucuron ide Nornicot ine Nicotine- N-Oxide Cotinine- N-Oxide Chew per day Can per week Plasma (ng/ml) 369 COT (198) 160 3HC (108) 3HC/CO T NMR (0.144) 2.4 (4.8) 2.6 (3.8) 11.4 (7.0) 8.1 (3.8) (8.0) 3.7 (5.3) 8.7 (6.9) 6.7 (3.7) (0.6) 0.8 (0.2) 0.8 (0.4) 0.6 (0.2) (0.4) 0.8 (0.1) 0.8 (0.5) 0.6 (0.3) (4.3) 6.8 (2.5) 4.8 (2.7) 3.5 (1.8) (4.0) 6.5 (2.8) 4.9 (3.1) 4.0 (2.2) (2.1) 3.3 (0.9) 4.2 (1.3) 3.1 (1.0) (2.0) 3.6 (0.8) 3.5 (1.4) 2.9 (1.0) (1.4) 4.6 (2.9) (1.1) 4.5 (2.9) (1.7) 1.0 (0.6) (0.3) 1.5 (1.6) (201) 246 (230) (0.367) (244) 135 (126) (0.207) 318 (140) 280 (214) (0.447)

85 *Compared to TNE (9-items), TNE (6-items) did not included nornicotine, nicotine-n-oxide, and cotinine-n-oxide. Gluc=glucuronide. P % = the P values from Wilcoxon s tests when the metabolites were normalized to % of urinary total nicotine equivalents. P absol = the P values from Wilcoxon s tests when the absolute urinary recovery values were compared. Bold values indicate statistically significant differences between the groups by Wilcoxon s test. Levels were compared between the normal metabolizers and the reduced metabolizers (individuals with at least one copy of reduced function CYP2A6 alleles) or between the faster plasma NMR stratum and the slower plasma NMR stratum (median split). 64

86 Alaska Native iqmik users with lower CYP2A6 activity had lower tobacco consumption Among the small number of iqmik users, nineteen percent lower TNE levels were observed in those in the slower (n=10) compared to faster (n=10) plasma NMR stratum (117.2 vs nmol/mg Cre respectively, P=0.023, Fig. 8 and Table 5). However, no significant difference in TNE levels was observed by CYP2A6 genotype group (Table 5). Urinary nicotine metabolite profiles differed between CYP2A6 activity groups in smokers Fig. 9A shows the total and proportional level of nicotine and each metabolite in smokers urine (n=141) by plasma NMR stratum, illustrating the dominant role of CYP2A6 in the metabolic removal of nicotine. Smokers in the slower plasma NMR stratum excreted 72% of their TNE via the CYP2A6-mediated COT pathways (i.e. COT and its metabolites, darker shades, Fig. 9A), whereas more than 85% of TNE was excreted via the COT pathway among smokers in the faster plasma NMR stratum (P<0.0001, Fig. 9A). As a result, smokers in the slower plasma NMR stratum excreted a significantly higher percentage of consumed nicotine (i.e. TNE) as free nicotine, nicotine glucuronide, nornicotine and nicotine-n-oxide (P<0.05, Table 4 and Fig. 9A) and a significantly lower percentage as 3HC and its glucuronide (P <0.001, Table 4 and Fig. 9A). Urinary nicotine metabolite profiles among smokers also differed between CYP2A6 genotype groups (Fig. 9B and Table 4). Urinary nicotine metabolite profiles differed between CYP2A6 activity groups in commercial smokeless tobacco and iqmik users Similar to Alaska Native smokers, commercial smokeless tobacco users and iqmik users in the slower plasma NMR stratum excreted 78% of their TNE via the COT pathway, whereas more than 85% of TNE were excreted via the COT pathway in individuals in the faster plasma NMR stratum (P<0.01, Table 5). Similar to the results observed using plasma NMR stratum, urinary nicotine metabolite profiles also differed by CYP2A6 genotype group in commercial smokeless tobacco users and iqmik users (Table 5). 65

87 A 3HC2Gluc$ 5%$ Free$Nico)ne$ 13%$ Nico)ne$Glu$ 6%$ 3HC2Gluc$ 9%$ Free$Nico)ne$ Nico)ne$Glu$ 6%$ 2%$ Nornico)ne$ 1%$ Nico)ne2N2 oxide$ 3%$ Nornico)ne$ 1%$ Free$Co)nine$ 11%$ Free$3HC$ 33%$ Nico)ne2N2 oxide$ 8%$ Co)nine2Gluc$ 13%$ Co)nine2N2 oxide$ 3%$ Co)nine2Gluc$ 16%$ Free$Co)nine$ 15%$ Free$3HC$ 52%$ Co)nine2N2 oxide$ 3%$ Mean TNE=56.3 nmol/mg Cre NMR slower P=0.006 Mean TNE=79.2 nmol/mg Cre NMR faster B Free$3HC$ 36%$ 3HC2Gluc$ 5%$ Free$Nico)ne$ 12%$ Nico)ne$Glu$ 6%$ Nornico)ne$ 1%$ Nico)ne2N2 oxide$ 8%$ 3HC2Gluc$ 8%$ Free$Nico)ne$ 7%$ Nico)ne$Glu$ 3%$ Nornico)ne$ 1%$ Nico)ne2N2 oxide$ 4%$ Free$Co)nine$ 12%$ Co)nine2N2 oxide$ 3%$ Co)nine2Gluc$ 16%$ Mean TNE=63.8 nmol/mg Cre CYP2A6 Reduced Free$Co)nine$ 14%$ Free$3HC$ 48%$ Co)nine2N2 oxide$ 3%$ Mean TNE=70.7 nmol/mg Cre CYP2A6 Normal Co)nine2 Gluc$ 14%$ Figure 9 Total tobacco consumption, and nicotine s metabolic profile, differed between NMR strata (A) and CYP2A6 genotypes (B) in cigarette smokers (n=141). The total size of pie charts represents the amount of total urinary nicotine equivalents (TNE). The precentage of TNE recovered as each nicotine metabolite is represented by the size. 66

88 Neither Plasma NMR strata nor CYP2A6 genotypes were associated with self-report indicators of tobacco consumption or plasma COT levels Despite the 41% difference in tobacco consumption as indicated by TNE, Alaska Native smokers in the slower versus faster plasma NMR stratum reported smoking similar CPD (6.7 vs. 8.3, respectively, non-significant) and had similar plasma COT levels (235 vs. 213 ng/ml, respectively, non-significant, Table 4). There were also no significant differences between plasma NMR strata in the number of chews per day, the number of cans of smokeless tobacco used per week (standard Copenhagen sized cans), or the levels of plasma COT in commercial smokeless tobacco users or iqmik users (Table 5). Likewise, CYP2A6 genotype was not associated with differences in self-report indicators of tobacco consumption or plasma COT levels in smokers, commercial smokeless tobacco users or iqmik users (Table 4 and 5). Urinary NNAL levels trended lower in individuals with lower CYP2A6 activity There were 27% and 18% difference in urinary NNAL levels between NMR strata and CYP2A6 genotype groups respectively, but they were not significant (1.1 vs. 1.4 pmol/mg Cre in the slower and faster plasma NMR stratum, respectively; 1.1 vs. 1.3 pmol/mg in CYP2A6 RM and NM, respectively, Table 6). Among the commercial smokeless tobacco users, we observed 62% lower NNAL levels in the slower compared to the faster plasma NMR stratum (4.5 vs. 7.3 pmol/mg Cre, respectively, P=0.01, Table 6). A similar difference in magnitude was also observed between CYP2A6 genotypes (4.6 vs. 7.1 pmol/mg Cre in CYP2A6 RM and NM, respectively, P=0.006, Table 6). No difference in NNAL levels was observed between NMR strata or CYP2A6 genotypes among the small iqmik group (Table 6). As expected, the effects of NMR strata and CYP2A6 genotypes on NNAL levels (a measure of exposure) were eliminated when nicotine dose (TNE) was controlled for (Table 7 A and B). Urinary NNN levels were higher in smokers with lower CYP2A6 activity As total tobacco consumption (i.e. TNE) differed between NMR strata, we compared urinary NNN levels while controlling for TNE. NNN levels were higher in slower than faster NMR strata (B=0.41, β=0.17, 95%CI= , P=0.04, Table 8A). A 39% difference in NNN levels between NMR strata was observed when not controlling for tobacco dose, but this did not reach 67

89 statistically significance (0.182 vs fmol/mg Cre, respectively, non-significant, Table 6). Significantly higher urinary NNN levels were observed in CYP2A6 RM compared to CYP2A6 NM (0.230 vs fmol/mg Cre, respectively, P=0.05, Table 6), which was also greater when TNE was controlled for (by CYP2A6 genotype: B=0.60, β=0.24, 95%CI= , P=0.003, Table 8A). Among the commercial smokeless tobacco users, urinary NNN levels were moderately, but non-significantly, higher in those with slower compared to faster plasma NMR (0.126 vs fmol/mg Cre, respectively, Table 6), and the difference between the two groups increased when TNE was controlled for (by plasma NMR strata: B=0.41, β=0.18, 95%CI= , P=0.09, Table 8B). No difference in NNN levels was observed between CYP2A6 genotype groups among the commercial smokeless tobacco users (0.119 vs fmol/mg Cre in CYP2A6 RM and CYP2A6 NM, respectively, P=0.67; regression analysis by CYP2A6 genotype: B=-0.06, β=-0.03, 95%CI= , P=0.793, Table 6, 8B). No difference in urinary NNN levels was observed by NMR stratum or CYP2A6 genotype group among iqmik users (Table 6). 68

90 Table 6 Urinary procarcinogen biomarker levels in smokers, commercial smokeless tobacco users, and iqmik users. Plasma NMR strata CYP2A6 genotypes Slower Faster Reduced Normal Smokers n=71 n=70 n=62 n=79 P n=141 mean mean mean mean (SD) (SD) (SD) (SD) NNAL (pmol/mg Cre.) (0.8) (1.2) (0.8) (1.2) NNN (fmol/mg Cre.) (0.390) (0.200) (0.450) (0.093) Commercial smokeless tobacco users n=73 NNAL (pmol/mg Cre.) NNN (fmol/mg Cre.) Iqmik users n=20 NNAL (pmol/mg Cre.) NNN (fmol/mg Cre.) Slower n=37 mean (SD) 4.5 (3.6) (0.114) Slower n=10 mean (SD) 0.8 (0.6) Faster n=36 mean (SD) 7.3 (6.0) (0.088) Faster n=10 mean (SD) 0.7 (0.3) P P 0.65 Reduced n=34 mean (SD) 4.6 (4.0) (0.119) Reduced n=9 mean (SD) 0.9 (0.51) Normal n=39 mean (SD) 7.1 (5.6) (0.084) Normal n=11 mean (SD) 0.7 (0.42) (1.95) (0.195) (0.211) (1.87) Bold values indicate statistically significant differences between the groups by Wilcoxon s test. NNAL = 4-(methylnitrosamino)-1-(3) pryridyl-1-butanol; NNN = N-Nitrosonornicotine 0.71 P P P

91 Table 7 The effect of NMR stratum or CYP2A6 genotype on urinary NNAL level was eliminated after controlling for tobacco consumption. Predictors of NNAL NMR strata R 2 =0.40 B β 95% CI P A Smokers P<0.001 TNE (increasing, per nmol) , NMR (slower strata) , Age (Increasing) , CYP2A6 Genotype R 2 =0.39 P<0.001 B β 95% CI P TNE (increasing, per nmol) , CYP2A6 Genotype (Reduced) , Age (Increasing) , NMR strata R 2 =0.65 P<0.001 B β 95% CI P TNE (increasing, per nmol) , B NMR (slower strata) , Commerci Age (Increasing) , al CYP2A6 Genotype smokeless R 2 B β 95% CI P =0.67 P<0.001 tobacco TNE (increasing, per nmol) , CYP2A6 Genotype (Reduced) , Age (Increasing) , B is the unstandardized coefficient. β is the standardized coefficient (i.e. standardized to a variance of 1). The B and β provided refers to the variables listed in brackets beside each categorical predictor. The NNAL levels were log-transformed to obtain normal distribution. 70

92 Table 8 NNN levels were significantly higher in smokers with slower CYP2A6 activity when tobacco consumption was controlled for. Predictors of NNN Plasma NMR R 2 =0.30 B β 95% CI P A Smokers B Commerci al smokeless tobacco P<0.001 TNE (increasing, per nmol) , NMR (slower strata) , Age (Increasing) , CYP2A6 Genotype B β 95% CI P R 2 =0.33 P<0.001 TNE (increasing, per nmol) , CYP2A6 Genotype (Reduced) , Age (Increasing) , Plasma NMR R 2 =0.36 P<0.001 B β 95% CI P TNE (increasing, per nmol) , NMR (slower strata) , Age (Increasing) , CYP2A6 Genotype R 2 =0.33 P<0.001 B β 95% CI P TNE (increasing, per nmol) , CYP2A6 Genotype (Reduced) , Age (Increasing) , B is the unstandardized coefficient. β is the standardized coefficient (i.e. standardized to a variance of 1). The B and β provided refer to the variables listed in brackets beside each categorical predictor. The NNN levels were log-transformed to obtain a normal distribution. 71

93 2.5 Discussion This study revealed three novel findings, each supporting the key role of CYP2A6 in influencing tobacco consumption and the risk of developing tobacco related disease. First, Alaska Native smokers, who smoked on average less than 10 CPD (i.e. light smokers), titrated their daily tobacco consumption (i.e. TNE) according to their CYP2A6 activities similarly to previous observations among Caucasian heavier smokers (Wassenaar et al. 2011). Second, variation in CYP2A6 activity was associated with altered levels of tobacco use among commercial smokeless tobacco users and iqmik users. Third, Alaska Native smokers and smokeless tobacco users with lower CYP2A6 activities excreted lower levels of NNAL, reflecting lower NNK exposure as a result of their lower tobacco consumption and they may possess reduced NNN metabolic activation (inferred through higher residual urinary NNN levels). Together, lower tobacco and procarcinogen consumption and lower procarcinogen bioactivation would be expected to decrease the risk of tobacco-related cancers in individuals with lower CYP2A6 activities, consistent with a lower risk seen among heavy smoking Caucasians (Wassenaar et al. 2011). In this study, the levels of urinary TNE in Alaska Native smokers were comparable to those among Caucasian heavy smokers despite smoking less than 10 CPD (6-item TNE: 61.4 nmol/mg Cre in Alaska Native smokers vs nmol/mg Cre in Caucasian smokers with ~20 CPD) (Le Marchand et al. 2008; Benowitz et al. 2011). This suggests that Alaska Native smokers inhaled each cigarette more deeply and/or for a longer duration, resulting in similar amounts of nicotine (and presumably procarcinogens) exposure to that observed in Caucasian heavy smokers despite smoking fewer CPD (Benowitz et al. 2012). Several studies have observed that cigarette smokers with lower CYP2A6 activities smoke fewer CPD (Schoedel et al. 2004; Wassenaar et al. 2011), but this difference in CPD has not been observed in light smoking populations such as African Americans (Ho et al. 2009), nor was it observed in this Alaska Native group. Smokers who consume comparatively fewer cigarettes typically inhale more intensely than smokers who consume more cigarettes, hence nicotine and procarcinogen intake per cigarette is inversely related to numbers of reported CPD (Benowitz et al. 2011). In the present study, smokers with lower CYP2A6 activity (i.e. slower plasma NMR stratum or CYP2A6 RM) had lower TNE levels while reporting similar daily cigarette use. This suggests that Alaska Native smokers with lower CYP2A6 activity reduced their nicotine consumption per cigarette to compensate for their slower 72

94 nicotine inactivation, presumably by inhaling smaller and/or fewer puffs, a phenomenon observed previously in heavier smokers (Strasser et al. 2007). The 41% reduction in TNE between NMR strata in Alaska Native smokers was larger than the 28% reduction in CPD observed in Caucasian heavy smokers between CYP2A6 genotypes (6), suggesting consumption differences between CYP2A6 activity groups, when measured more accurately, could be larger than those predicted by CPD (Wassenaar et al. 2011). Substantial inter-subject variation in TNE levels was observed between NMR strata and CYP2A6 genotypes in the iqmik users. This is likely due to variation in the preparation procedures (e.g. content of the basic ash and premastication) and chewing behavior (chew duration and whether swallows the iqmik juice) (Renner et al. 2005). Due to these differences, biochemical markers such as TNE provide a better measure of nicotine exposure than the self-report iqmik consumption measures. In the current study, the effect of NMR strata on urinary TNE was stronger than the effect of CYP2A6 genotype likely reflecting a closer relationship of NMR (versus CYP2A6 genotype) to the phenotype of interest, CYP2A6 activity. This is most likely because of the influence of gender, BMI, and dietary inducers/inhibitors on CYP2A6 activity (Ho et al. 2009; Al Koudsi et al. 2010). Further, there may be novel CYP2A6 genetic variants among the Alaska Native people, which were not investigated in our study (Binnington et al. 2012). To the best of our knowledge, this is the first demonstration of tobacco consumption titration by CYP2A6 activity among smokeless tobacco users. The consumption differences between plasma NMR strata among the commercial smokeless tobacco users were slightly larger than those observed in smokers (54% versus 41% lower TNE, respectively). This may be a reflection of slower nicotine absorption from smokeless tobacco versus cigarette smoking (Benowitz 1997), which could allow for a longer period of time for metabolism to occur thereby increasing the effect of differences in the rates of nicotine metabolism. Although urinary TNE levels differed by CYP2A6 activity group among Alaska Native smokers and commercial smokeless tobacco users, plasma COT levels did not. Plasma COT is often used as a biomarker of nicotine exposure, however it is both metabolically formed and removed by CYP2A6. Lower CYP2A6 activity might differentially reduce the relative rates of COT formation versus COT removal resulting in the accumulation of COT among slower CYP2A6 73

95 metabolizers. Thus plasma COT might over-estimate nicotine dose in individuals with lower CYP2A6 activities. In addition to influencing tobacco consumption, genetic variation in CYP2A6 can also alter lung cancer risk (Wassenaar et al. 2011). Some earlier studies in Caucasians did not find an association between CYP2A6 and the risk for developing lung cancer (Rossini et al. 2008). However these studies did not genotype the majority of loss of function CYP2A6 variants and suffered from reduced power (Rossini et al. 2008). In recent studies, with more comprehensive genotyping, significant associations between CYP2A6 and the risk for developing lung cancer have been found (Fujieda et al. 2004; Wassenaar et al. 2011). This may be due to differences in both tobacco consumption and in procarcinogen metabolic activation by CYP2A6 genotype. Tobacco specific nitrosamines such as NNK, NNN and NNAL are all potent procarcinogens (Hecht 2003). Commercial smokeless tobacco users with lower CYP2A6 activity had lower NNAL levels, which was eliminated when controlling for TNE levels, suggesting that the lower NNAL levels are a result of lower tobacco consumption rather than differences in NNK metabolism. In fact, we observed no evidence that variation in CYP2A6 activity had any effect on NNAL levels beyond the effect of CYP2A6 on tobacco consumption: the relative amount of NNK eliminated via the NNAL pathway did not differ between CYP2A6 activity groups in our study consistent with human genetic association studies (Ter-Minassian et al. 2012). Higher NNN levels were observed in the smokers with lower CYP2A6 activity, which was even greater after controlling for nicotine intake (i.e. TNE). We speculate that the lower CYP2A6 activity resulted in lower NNN clearance (i.e. lower bioactivation) resulting in higher levels of urinary NNN. CYP2A6 mediates the α-hydroxylation of NNN to genotoxic metabolites (Wong et al. 2005). If not detoxified, these genotoxic metabolites can covalently bind to DNA which can result in mutations. This is consistent with human transfection studies in which a higher degree of NNN induced mutagenesis was observed in the CYP2A6 transfected cells than the control cells (Kushida et al. 2000). More research is needed to understand the role of urinary NNN as a predictor of tobacco-related cancers cancer risk to date, a dose dependent relationship has only been seen for esophageal cancer (Yuan et al. 2011). 74

96 There are limitations to our study. Our study only included Alaska Native individuals and the application of the findings to other race/ethnicities requires further investigation. Secondly, this study had a relatively small smokeless tobacco group, particularly for individuals who exclusively used iqmik. Together our data indicate that Alaska Native light smokers and smokeless tobacco users titrate their tobacco consumption according to CYP2A6 activity. Previous failures to see evidence of titration by CYP2A6 activity among light smokers may be due to the poor sensitivity of the tobacco consumption indictors used (e.g. CPD). Furthermore, consistent with the lower tobacco consumption, individuals with lower CYP2A6 activities also had lower procarcinogen exposure (i.e. NNK and NNAL). In addition, lower CYP2A6 activity was associated with higher NNN levels suggesting reduced bioactivation. Together these findings support a reduced risk of tobacco related cancers for slow, versus fast, CYP2A6 metabolizers, in both smokers and smokeless tobacco users. 75

97 2.6 Significance to Thesis This chapter contributes to the literature in three ways. First, it demonstrated that variation in CYP2A6 activity significantly alter tobacco consumption in light smokers. This suggests that light smokers titrate their tobacco consumption to maintain desirable nicotine levels in the body as seen with heavy smokers. This would imply that the associations between CYP2A6 gene variants and smoking related disease risk/cessation outcomes previously observed in heavy smokers are likely applicable to light smokers as well. Secondly, this study demonstrated that smokeless tobacco users titrate their tobacco consumption according to their CYP2A6 activity. About 7% of men in the United States use smokeless tobacco, yet little is known about the genetic influences on smokeless tobacco use behaviors. This is the first study to demonstrate that genetic variation can significantly influence smokeless tobacco use. Lastly, this study also provided evidence that variation in CYP2A6 activity is associated with altered carcinogen bioactivation (as indicated by the higher NNN levels in individuals with reduced CYP2A6 activity). Individuals with reduced CYP2A6 activity are at a lower risk of developing lung cancer even after adjusting for tobacco consumption. This study suggests that reduced carcinogenic TSNA activation could contribute to this association. 76

98 3 CHAPTER 2: THE ABILITY OF PLASMA COTININE TO PREDICT NICOTINE AND CARCINOGEN EXPOSURE IS ALTERED BY DIFFERENCES IN CYP2A6: THE INFLUENCE OF GENETICS, RACE AND SEX Andy Z.X. Zhu, Caroline C. Renner, Dorothy K. Hatsukami, Gary E. Swan, Caryn Lerman, Neal L. Benowitz, and Rachel F. Tyndale Reprinted with permission from American Association for Cancer Research: Cancer Epidemiol Biomarkers Prev 22(4): All rights reserved. GES, NLB and RFT conducted the pharmacokinetic study. CCR, DKH, NLB and RFT conducted the cross sectional study. CL, NLB and RFT conducted the clinical trial. AZZ determined the experimental questions and derived the mathematical equations. AZZ performed all analyses and modeling. AZZ and RFT wrote the manuscript. 77

99 3.1 Abstract Background: Cotinine, a nicotine metabolite, is a biomarker of tobacco, nicotine and carcinogen exposure. However a given cotinine level may not represent the same tobacco exposure; for example, African Americans have higher cotinine levels than Caucasians after controlling for exposure. Methods: Cotinine levels are determined by the amount of cotinine formation and the rate of cotinine removal which are both mediated by the enzyme CYP2A6. Since CYP2A6 activity differs by sex (estrogen induces CYP2A6) and genotype, their effect on cotinine formation and removal were measured in non-smoking Caucasians (Study 1, n=181) infused with labeled nicotine and cotinine. The findings were then extended to ad libitum smokers (Study 2, n=163). Results: Study 1: Reduced CYP2A6 activity altered cotinine formation less than cotinine removal resulting in ratios of formation to removal of 1.31 and 1.12 in CYP2A6 reduced and normal metabolizers (P=0.01), or 1.39 and 1.12 in males and females (P=0.001), suggesting an overestimation of tobacco exposure in slower metabolizers. Study 2: Cotinine again overestimated tobacco and carcinogen exposure by 25% in CYP2A6 reduced metabolizers ( 2 fold between some genotypes) and in males. Conclusions: In people with slower, relative to faster, CYP2A6 activity cotinine accumulates resulting in substantial differences in cotinine levels for a given tobacco exposure. Impact: Cotinine levels may be misleading when comparing those with differing CYP2A6 genotypes within a race, between races with differing frequencies of CYP2A6 gene variants (i.e. African Americans have higher frequencies of reduced function variants contributing to their higher cotinine levels) or between the sexes. 78

100 3.2 Introduction In humans, cotinine is metabolically formed from nicotine in a reaction catalyzed by CYP2A6 and is further metabolized to trans-3 -hydroxycotinine (3HC) by CYP2A6 (Nakajima et al. 1996; Nakajima et al. 1996). Cotinine is routinely used as an objective index of tobacco and tobacco-derived carcinogen exposure. The use of cotinine is particularly useful because of wide individual variability in the relationship between self-report cigarettes smoked per day and systemic exposure to tobacco and tobacco-derived carcinogen (Benowitz et al. 2011). Higher plasma cotinine levels have been associated with increased lung cancer risk (Boffetta et al. 2006), and variation in cotinine levels have recently been used as evidence that the mechanism mediating the association between genetic variation in CHRNA5-A3-B4 and lung cancer risk is almost entirely through the modulation of tobacco consumption (Munafo et al. 2012). The systemic intake of nicotine is correlated with exposure to tobacco-derived carcinogen (Benowitz et al. 2011). When used as a biomarker of tobacco-derived carcinogen exposure, it is generally assumed that plasma cotinine levels reflect intake of nicotine, and that variability in the relationship between cotinine levels and nicotine intake is random among smokers. However, some research suggests that a particular level of cotinine does not predict the same level of tobacco exposure among different groups of smokers. For example, directional inconsistencies have been observed between plasma cotinine levels and other indicators of tobacco exposure in genetic association studies involving CYP2A6. Caucasian smokers with one or more reduced function CYP2A6 alleles (i.e. CYP2A6 reduced metabolizers, or RM) smoke fewer cigarettes per day compared to the CYP2A6 normal metabolizers (NM), consistent with titration of smoke intake to obtain desired levels of nicotine in the body (Schoedel et al. 2004; Wassenaar et al. 2011). Yet despite smoking fewer cigarettes per day, smokers with reduced CYP2A6 activity have similar plasma cotinine levels compared to the smokers with faster CYP2A6 activity (Strasser et al. 2011). Another example is found in studies of African American light smokers, where similar levels of cigarettes per day are reported between CYP2A6 genotypes (i.e. CYP2A6 RM have similar cigarettes per day compared to CYP2A6 NM), but the plasma cotinine levels are significantly higher in CYP2A6 RM compared to CYP2A6 NM (Ho et al. 2009). Furthermore, gene variants at the CYP2A6 loci (i.e. tag SNPs) that are associated with decreased lung cancer risk are paradoxically associated with increased, rather than decreased, plasma cotinine levels 79

101 (Timofeeva et al. 2011). These observations suggest that CYP2A6 reduced activity genotype may increase plasma cotinine levels in addition to its role in reducing nicotine inactivation, tobacco consumption and nitrosamine metabolic activation (Zhu et al. 2013). Variation in plasma cotinine levels is also observed between the sexes. The male participants of the National Health and Nutrition Examination Surveys have significantly higher plasma cotinine levels compared to the female participants even after adjusting for cigarettes per day, machine-determined nicotine delivery of cigarettes, race, age, body mass index, poverty status, and the use of either menthol or regular cigarettes (Gan et al. 2008). Since CYP2A6 activity differs between the sexes, this systematic variation in cotinine levels between the sexes could be the result of the difference in CYP2A6 activity (Al Koudsi et al. 2010). Notable variation in cotinine levels is also observed between races. African American smokers generally have higher plasma cotinine levels compared to Caucasian smokers after adjusting for the number of cigarettes smoked per day and the machine-determined nicotine delivery in cigarettes (Wagenknecht et al. 1990), which could be partially due to the slower cotinine clearance in African Americans compared to Caucasians (Perez-Stable et al. 1998). Since the prevalence of CYP2A6 RM is high in African Americans compared to Caucasians, it is possible that the racial variation in cotinine levels originates from the difference in CYP2A6 activities between racial groups. Steady state plasma cotinine levels are determined by three factors: the daily intake of nicotine, the fraction of nicotine converted to cotinine (f NIC COT), and the systemic clearance of cotinine. The steady state plasma cotinine level is described by the following equation: [COT plasma ] = Dose NIC f NIC COT Cl COT where COT plasma represents the steady state plasma cotinine levels, Dose nic is the daily nicotine intake. f NIC COT is the fraction of nicotine converted to cotinine (i.e. cotinine formation), and Cl COT represents systemic plasma cotinine clearance (i.e. cotinine removal) (Benowitz 1996). Hence, the steady state plasma cotinine levels are proportional to the ratio of f NIC COT/Cl COT and the Dose nic. Cotinine is both formed and removed by CYP2A6. Thus, both f NIC COT and cotinine 80

102 clearance are highly dependent on CYP2A6 activity. We hypothesize that reduced CYP2A6 activity will increase the ratio of f NIC COT/Cl COT, and alter the quantitative relationship between plasma cotinine and nicotine and tobacco-derived carcinogen exposure in cigarette smokers. In this study, we use CYP2A6 genotype as the primary indicator of CYP2A6 activity. CYP2A6 genetic variants are known to alter in vivo CYP2A6 activity as well as nicotine and cotinine clearance (Oscarson et al. 2002; Xu et al. 2002; Fukami et al. 2004; Benowitz et al. 2006; Mwenifumbo et al. 2007; Ho et al. 2008; Mwenifumbo et al. 2008). In addition to CYP2A6 genotype, we also use the nicotine metabolite ratio (NMR) as a secondary indicator of CYP2A6 activity (Dempsey et al. 2004). For the evaluation of nicotine intake in ad libitum smokers, we use urinary total nicotine equivalents (TNE) (Wang et al. 2011). For the evaluation of tobaccoderived carcinogen in ad libitum smokers, we used total urinary (methylnitrosamino)-1-(3) pyridyl-1-butanol (NNAL), 1-hydroxyfluorene and 1-hydroxypyrene levels (Yuan et al. 2011; StHelen et al. 2012). 3.3 Material and Methods Study design Data for the present analysis were taken from two studies that have been previously published (Benowitz et al. 2006; Benowitz et al. 2012). Study 1: The pharmacokinetics of nicotine and cotinine were characterized in 181 non-smoking Caucasian male and female sets of twins (both monozygotic and dizygotic). Demographic variable comparisons are shown in table 9. A comprehensive description of the study procedures has been published previously (Swan et al. 2004; Swan et al. 2005). Briefly, participants received a simultaneous 30-minute infusion of deuterium-labeled nicotine and cotinine in the fasting condition. Blood samples were collected for the measurement of labeled nicotine and cotinine for determination of pharmacokinetic parameters and DNA was extracted for CYP2A6 genotyping. The cotinine and 3HC levels were measured in the 480-minute plasma sample for determination of the NMR (Benowitz et al. 2006). The nicotine and cotinine clearance were estimated as follows: 81

103 Cl NIC = Dose NIC d 2 AUC NIC d 2 Cl COT = Dose COT d 4 AUC COT d 4 Where Cl is the total body clearance, NIC is nicotine, COT is cotinine, dose is the infusion dose, and AUC is the area under the plasma concentration-time curve extrapolated to infinity. f NIC ->COT was estimated as follows: f NIC COT = AUC COT d 2 Dose NIC d 2 Cl COT d 4 Study 2: The relationship between plasma cotinine, nicotine intake and carcinogen exposure was studied in daily ad libitum smokers (table 9). In a cross sectional study of 163 Alaska Native smokers, the plasma cotinine levels urinary TNE, total NNAL and PAH metabolites were measured. A comprehensive description of the study procedures has been published elsewhere (Benowitz et al. 2012). 82

104 Table 9 Descriptive participant characteristics. 1. Pharmacokinetic Study 2. Ad libitum smoking study N Male 29.9% 43.6% Smoking status Non-smokers All smokers Race (%) All Caucasians All Alaska Native people Age (years) Mean (SD) Baseline cigarette per day Mean (SD) Study descriptions Outcome measures 37.7 (11.9) 36.0 (14.4) N/A 7.8 (5.2) Examines the source of variability in nicotine and cotinine pharmacokinetics f NIC COT Cotinine clearance Study 1 by CYP2A6 genotype Examines tobacco consumption behaviors in Alaska Native smokers during ad libitum smoking. Urinary TNE, NNAL, 1- hydroxyprene and 1- hydroxyfluorene Plasma cotinine levels CYP2A6 Reduced metabolizers (n=33) CYP2A6 Normal metabolizers (n=148) Age (Years) 36 (32,40) 38 (36,40) Sex 70% 70% (% Females) Weight (kg) 75 (70,81) 71 (69,74) Race 100% 100% (% Caucasians) Smoking status Non-smokers Non-smokers Study 1 by sex Males Females (n=54) (n=127) Age (Years) 40 (37,44) 37 (34,39) CYP2A6 genotype (% Reduced metabolizers) 19% 18% Weight (kg) 83 (80,86) 67 (65,69) Race (% Caucasians) 100% 100% Smoking status All non-smokers All non-smokers Study 2 by CYP2A6 genotype CYP2A6 Reduced metabolizers (n=33) CYP2A6 Normal metabolizers (n=148) Age (Years) 38 (34,41) 35 (32,38) Sex (% Females) 53% 47% Weight (kg) 75 (71,78) 77 (72,81) Race (% Alaska Native people) 100% 100% Smoking status Current smokers Current smokers Study 2 by sex Males Females (n=92) (n=71) Age

105 (Years) (33,39) (33,40) CYP2A6 genotype (% Reduced metabolizers) 34% 54% Weight (kg) 72 (68,76) 81 (77,85) Race (% Alaska Native people) 100% 100% Smoking status All current smokers All current smokers Values are mean (95% confident interval) unless otherwise noted. Bold values indicate statistical significance. Tobacco and tobacco derived carcinogen exposure biomarkers To evaluate the quantitative relationship between plasma cotinine and tobacco exposure in cigarette smokers, we used urinary total nicotine equivalents (TNE) from Study 2 participants as the reference biomarker of nicotine and tobacco exposure as it is the summation of multiple nicotine metabolic pathways. TNE is the total urinary level of nicotine and 8 of its metabolites (i.e. nicotine, nicotine glucuronide, cotinine, cotinine glucuronide, 3HC, 3HC glucuronide, nicotine-n-oxide, cotinine-n-oxide, and nornicotine). Together, the 9 analytes account for about 90% of nicotine (determined from a transdermal administered nicotine dose (Benowitz et al. 1994)), and creatinine adjusted spot urinary TNE correlates with daily tobacco consumption (Benowitz et al. 2010). TNE is not influenced by the different rates of nicotine and cotinine metabolism since it measures the nicotine metabolites generated via different metabolic pathways. To investigate the relationship between plasma cotinine levels and tobacco-derived carcinogen exposure, we used total urinary (methylnitrosamino)-1-(3) pyridyl-1-butanol (NNAL) levels as the biomarker for tobacco specific nitrosamines exposure in study 2 participants (Hecht 2003). NNAL is a reductive metabolite of the highly carcinogenic 4-(methylnitrosamino)-1-(3) pyridyl- 1-butanone (NNK); prediagnostic levels are associated with subsequent lung cancer risk (Church et al. 2009). We also investigated the relationship between plasma cotinine levels and exposure to another class of tobacco-related carcinogens which are not nicotine-derived, the polycyclic aromatic hydrocarbons (Hecht 2003). The urinary levels of two hydroxylated polycyclic aromatic hydrocarbons, 1-hydroxypyrene and 1-hydroxyfluorene, were used as biomarkers of polycyclic aromatic hydrocarbons exposure. 1-Hydroxypyrene levels have been directly associated with 84

106 cancer risk (Kamangar et al. 2005), and recent evidence suggests that 1-hydroxyfluorene is more specific to tobacco exposure than 1-hydroxypyrene (StHelen et al. 2012). CYP2A6 genotyping Prevalent CYP2A6 alleles with altered function were genotyped by two step-allele specific PCR reactions in the Pharmacogenetics laboratory at CAMH and University of Toronto as previously reported (Schoedel et al. 2004; Mwenifumbo et al. 2005; Mwenifumbo et al. 2008; Ho et al. 2009). Those individuals with one or two copies of reduced function allele (*2, *4, *7, *9, *10, *12, *17 and *35) were classified as CYP2A6 RM (Mwenifumbo et al. 2005; Mwenifumbo et al. 2008; Ho et al. 2009). The measurement of CYP2A6 activity The in vivo CYP2A6 activity was measured using NMR, which is the ratio between plasma 3HC and cotinine. NMR is widely used as an in vivo indicator of CYP2A6 activity (Dempsey et al. 2004; Lerman et al. 2006; Ho et al. 2009; Lerman et al. 2010). In the context of our data analysis, the use of NMR may be confounded with plasma cotinine since it uses plasma cotinine as the denominator. Thus, we use NMR to extend our findings with CYP2A6 genotype as it is a continuous variable and for comparisons to the literature. Tobacco and tobacco-derived carcinogen exposure measurements Plasma nicotine, cotinine and 3HC levels, as well as urinary nicotine and metabolites, total NNAL, and PAH metabolites were quantified by gas/liquid chromatography-tandem mass spectrometry in the Clinical Pharmacology Laboratory at the University of California San Francisco as previously described (Jacob et al. 1991; Dempsey et al. 2004; Jacob et al. 2007; Jacob et al. 2008; Bernert et al. 2011). NMR stratification was done by a median split of plasma NMR within each study population; participants who were in the higher NMR stratum were considered the faster CYP2A6 activity group, while those in the lower NMR stratum were considered the slower CYP2A6 activity group. Statistical analysis 85

107 Statistical analyses were performed using R statistical package (version 2.13, R foundation for statistical computing, In study 1 statistical comparisons between CYP2A6 genotypes and sex were performed using mixed-effect linear regressions. All analyses controlled for non-independence of data in twin pairs by modeling twining as a random effect (Benowitz et al. 2006). Spearman s correlation was used to evaluate the relationship between 1) NMR and f NIC COT/Cl COT ; 2) NMR and cotinine to TNE ratio; 3) Plasma cotinine and urinary TNE, NNAL, 1-hydroxypyrene and 1-hydroxyflurene. Fisher s r to z transformation was used to compare the correlation coefficients. To minimize the influence of potential confounders such as race and smoking status on cotinine pharmacokinetics, the effects of CYP2A6 genotype and sex were examined within non-smoking Caucasians in Study Results CYP2A6 Reduced function genetic variants decreased cotinine removal more than cotinine formation (Study 1) Fig. 10A compares cotinine formation (f NIC COT) between CYP2A6 genotypes in non-smoking Caucasians. CYP2A6 RM (n=33) had significantly lower f NIC COT compared to CYP2A6 NM (n=148). In CYP2A6 RM, 67% of the nicotine dose was metabolized to cotinine compared to the 77% in CYP2A6 NM, a 15% relative reduction, P=0.001 (Fig. 10A). CYP2A6 RM also had lower cotinine clearance compared to the CYP2A6 NM (0.58 ml/min/kg in CYP2A6 RM versus 0.77 ml/min/kg in CYP2A6 NM, a 33% reduction, P=0.01, Fig. 10B). The ratio of the fractional conversion of nicotine (reflecting cotinine formation) to cotinine clearance (reflecting cotinine removal), f NIC COT/Cl COT, was significantly higher in CYP2A6 RM compared to CYP2A6 NM (1.31 in CYP2A6 RM versus in CYP2A6 NM, P=0.01, Fig. 10C). Of note, the resulting f NIC COT /CL COT ratio is the conversion factor, or average correction needed in plasma cotinine levels to accurately indicate the same nicotine dose (Fig. 10D). These genetic differences were consistent in both males and females (Fig. 11A-F). In agreement with the findings between CYP2A6 genotypes, statistically significant differences in f NIC COT, cotinine clearance and f NIC COT/Cl COT were observed when comparing the faster versus the slower NMR strata (Fig. 11G-H). There was a significant inverse correlation between NMR (i.e. a continuous measure of 86

108 CYP2A6 activity) and f NIC COT/Cl COT, suggesting the effect size is even larger when comparing the two extreme ends of CYP2A6 activity (Rho=-0.57, P<0.0001). A B C 100 P= P= P=0.01 f NIC COT (%) CL COT (ml/min/kg) f NIC COT / CL cot Reduced Normal CYP2A6 genotype 0.0 Reduced Normal CYP2A6 genotype 0.5 Reduced Normal CYP2A6 genotype D DoseNIC = [COTplasma] fnic COT CLCOT Figure 10 Reduced CYP2A6 activity had a greater impact on cotinine removal than cotinine formation (Study 1). This would result in the accumulation of cotinine and higher cotinine levels at a given tobacco exposure. A. CYP2A6 reduced metabolizers metabolized (n=33) a significantly lower amount of nicotine to cotinine compared to CYP2A6 normal metabolizers (n=148). B. CYP2A6 reduced metabolizers (n=33) had lower cotinine clearance (CL COT ) compared to CYP2A6 normal metabolizers (n=148). C. The f NIC COT/CL COT ratio was higher in CYP2A6 reduced metabolizers (n=33) compared to CYP2A6 normal metabolizers (n=148). Data presented as mean ± 95% confidence interval. D. The f NIC COT/CL COT ratio is the conversion factor between plasma cotinine levels and the actual nicotine dose. 87

109 f NIC COT (%) f NIC COT (%) f NIC COT (%) A D G n=10 P<0.01 n=44 0 Reduced Normal CYP2A6 genotype 100 P= n=23 0 Reduced Normal CYP2A6 genotype 100 P< n=88 n=104 n=87 CL COT (ml/min/kg) CL COT (ml/min/kg) Males only B n=10 P=0.09 n= Reduced Normal CYP2A6 genotype f NIC COT / CL cot Females only E 1.0 P< n=23 n= Reduced Normal CYP2A6 genotype f NIC COT / CL cot C F All Participants H I CL COT (ml/min/kg) n=88 P<0.001 n=87 f NIC COT / CL cot n=10 P=0.22 n= Reduced Normal CYP2A6 genotype n=23 P<0.05 n= Reduced Normal CYP2A6 genotype n=88 P<0.001 n=87 Slower Faster NMR stratum 0.0 Slower Faster NMR stratum 0.5 Slower Faster NMR stratum Figure 11 The effects of CYP2A6 activity on nicotine and cotinine pharmacokinetics. Within the male participants (Study 1): A. CYP2A6 RM (n=10) metabolized a significantly lower amount nicotine to cotinine compared to CYP2A6 NM (n=44). B. CYP2A6 RM (n=10) had lower cotinine clearance (CL COT ) compared to CYP2A6 NM (n=44). C. The f NIC COT/CL COT ratio was higher in CYP2A6 RM compared to CYP2A6 NM. Within the female participants (Study 1): D. CYP2A6 RM metabolized a significantly lower amount of nicotine to cotinine compared to CYP2A6 NM. E. CYP2A6 RM had lower cotinine clearance (CL COT ) compared to CYP2A6 NM. F. The f NIC COT/CL COT ratio was higher in CYP2A6 RM compared to CYP2A6 NM. With all participants (Study 1): G. Individuals with slower NMR metabolized a significant lower amount of nicotine to cotinine compared to the individuals with faster NMR. H. Individuals with slower NMR had lower cotinine clearance (CL COT ) compared to the individuals with faster NMR. I. f NIC COT/CL COT was higher among individuals in the slower NMR stratum compared to the individuals in the faster NMR stratum. Data presented as mean ± 95% confidence interval. 88

110 Different relationships between plasma cotinine and tobacco exposure were observed between smokers with different CYP2A6 genotype groups (Study 2) Next, the quantitative relationship between plasma cotinine and nicotine intake in smokers was investigated. Demographic variable comparisons are shown in table 9. Independent regression lines between urinary TNE and plasma cotinine were constructed in CYP2A6 RM and NM (n=74 and n=89, respectively). As illustrated by fig. 12, the slope of the regression line in CYP2A6 RM was significantly lower compared to the slope in CYP2A6 NM (slope: 0.33 in CYP2A6 RM versus 0.42 in CYP2A6 NM, P=0.001, Fig. 12). Statistical significance is demonstrated by a significant interaction between CYP2A6 genotype and cotinine levels in the linear regression analysis presented in table 10A. A similar difference in regression line slopes was observed between the NMR strata (Fig. 13). There was a significant inverse correlation between NMR, a continuous measure of CYP2A6 activity, and the cotinine to TNE ratio (Rho=-0.46, P<0.0001). These observations indicate that cotinine predicts nicotine intake, and therefore tobacco consumption, differently in smokers with reduced compared to normal CYP2A6 activity. As illustrated by fig. 12, a 300 ng/ml (which is equivalent to 1702 nmol/l) cotinine level was indicative of a 125 nmol nicotine equivalents exposure in CYP2A6 NM, whereas the same cotinine level was indicative of roughly 100 nmol exposure in CYP2A6 RM. Alternatively, at 100 nmol tobacco exposure, CYP2A6 RM would have 300 ng/ml plasma cotinine levels, whereas the CYP2A6 NM would have only 240 ng/ml. This is a 25% difference (60 ng/ml or 340 nmol/l) in cotinine levels between CYP2A6 genotype groups. Since reduced metabolizers include those with a range of decreased activity combined together, the 25% reflects an average difference (Fig. 14A). As illustrated by some specific genotypes, or quartiles of NMR, these differences in cotinine estimates of dose can be 2 fold when comparing between the extremes of CYP2A6 activity or among different genotypes (fig. 14B and fig. 14C). 89

111 Total Nicotine Equivalents ( nmol/mg Creatinine) Normal Combine Reduced At 100 nmol tobacco exposure Rho=0.81 P < Slope=0.416±0.018 Rho=0.73 P < Slope=0.376±0.013 Rho=0.67 # P < Slope=0.331±0.017 Cotinine levels in CYP2A6 NM at 100 nmol exposure Cotinine (ng/ml) Cotinine levels in CYP2A6 RM at 100 nmol exposure Figure 12 Cotinine s ability to predict tobacco exposure was different between CYP2A6 genotypes (Study 2). The slope between urinary TNE and plasma cotinine was significantly lower in CYP2A6 reduced metabolizers (n=74) compared to that of CYP2A6 normal metabolizers (n=89, table 10A), suggesting the quantitative relationship between cotinine and tobacco exposure (i.e. TNE) differed between CYP2A6 genotypes. # indicates statistical significant difference in Spearman s Rho compared to the CYP2A6 normal metabolizers. The numbers after the slopes are standard error. Of note, the strength of correlations between plasma cotinine and urinary TNE in the CYP2A6 RM was significantly weaker than in CYP2A6 NM (Fisher s r to Z transformation: P<0.01). 90

112 Table 10 Regression analyses of the predictive ability of cotinine and CYP2A6 genotype (or sex) on tobacco and tobacco-derived carcinogen exposure (Study 2). Y=TNE r 2 =0.86 P< B β 95% CI P Cotinine A (Increasing, per ng/ml) to CYP2A6 genotype (reduced) to Interaction term to Y=NNAL r 2 =0.78 P< B β 95% CI P Cotinine B (Increasing, per ng/ml) to CYP2A6 genotype (reduced) to Interaction term to Y=NNAL r 2 =0.84 P< B β 95% CI P TNE (increasing, per C nmol) to CYP2A6 genotype (reduced) to Interaction term to Y=1-hydroxyfluorene r 2 =0.73 P< B β 95% CI P Cotinine (increasing, per ng/ml) to D CYP2A6 genotype (reduced) to Interaction term to Y= 1-hydroxypyrene r 2 =0.38 P< B β 95% CI P Cotinine (Increasing, per ng/ml) to E CYP2A6 genotype (reduced) to to Interaction term Y=TNE 91

113 F r 2 =0.85 P< B β 95% CI P Cotinine (Increasing, per ng/ml) to Sex (males) to Interaction term to Total Nicotine Equivalents (9 Items) (nmol/mg Creatinine) Faster Combine Slower At 100 nmol tobacco exposure ρ=0.79 P < Slope=0.450±0.019 ρ=0.73 P < Slope=0.376±0.013 ρ=0.75 P < Slope=0.310±0.014 Cotinine levels in faster NMR stratum at 100 nmol exposure Cotinine (ng/ml) Cotinine levels in slower NMR stratum at 100 nmol exposure Figure 13 Cotinine s ability to predict tobacco exposure was different between NMR strata (Study 2). The slope between urinary TNE and plasma cotinine was lower in CYP2A6 RM compared to that of CYP2A6 NM, suggesting cotinine over estimates tobacco exposure in CYP2A6 RM. Regression analysis was not performed due to the interrelatedness of plasma cotinine and NMR (i.e. NMR is the ratio 3HC to plasma cotinine levels). The numbers after the slopes are standard error. 92

114 A B C 6 P= P< COT/TNE 3 COT/TNE 3 n=29 COT/TNE 3 n= n=74 n= n=6 n=20 n= n=41 n=41 n=40 0 Reduced Normal CYP2A6 genotype 0 Slower Faster CYP2A6 genotype *9/*4 *1/*4 *1/*9 *1/*1 0 1st 2nd 3rd 4th Slower Faster NMR quartiles Figure 14 Cotinine to TNE ratio significantly differ between individuals with difference CYP2A6 activity. A). The cotinine to TNE ratio (i.e. cotinine levels per nicotine intake) was significantly lower in CYP2A6 NM compared to the CYP2A6 RM. (Study 2) B). The cotinine to TNE ratio decreased with CYP2A6 genotypes with increasing activity (Study 2). As illustrated using some different CYP2A6 genotypes, containing reduced function (*9) or loss of function (*4) allele compared to the wild type individuals (*1/*1). Of note, individuals who are fully null for CYP2A6 (i.e. these with two copies of gene deletions, CYP2A6*4/*4) had unexpectedly lower COT to TNE ratio compared to the wild-type individuals (*1/*1, data not shown), suggesting the minor remaining cotinine formation pathway (likely CYP2B6 or CYP2A13) is considerably slower than the low affinity cotinine removal pathway (likely UGT2B10 glucuronidation or renal clearance). C). The cotinine to TNE ratio decreased by NMR quartiles (Study 2). Data presented as mean ± 95% confident intervals. Statistical comparisons were performed by Mann Whitney or Kruskal-Wallis tests. 93

115 Different relationships between plasma cotinine and tobacco specific nitrosamine exposures were observed in smokers with different CYP2A6 genotype groups (Study 2) Next, we investigated the quantitative relationship between plasma cotinine and tobacco specific nitrosamines exposure in smokers. As seen with TNE, the slope of the regression line between urinary NNAL and plasma cotinine in CYP2A6 RM was significantly lower compared to the slope in CYP2A6 NM (slope: in CYP2A6 RM versus in CYP2A6 NM, P=0.003, fig. 15. Statistical significance demonstrated by a significant interaction term in the linear regression analysis presented in table 10B). These results demonstrated that that cotinine levels predict NNAL levels, and therefore nitrosamine exposure, differently in smokers with reduced compared to normal CYP2A6 activity. As illustrated by fig. 15, a 300 ng/ml (which is equivalent to 1702 nmol/l) cotinine level was indicative of a 510 pg/mg creatinine NNAL exposure in CYP2A6 NM, whereas the same cotinine level was indicative of roughly 375 pg/mg creatinine NNAL exposure in CYP2A6 RM. Alternatively, at 375 pg/mg creatinine NNAL exposure, CYP2A6 RM would have 300 ng/ml plasma cotinine levels, whereas the CYP2A6 NM would have only 225 ng/ml. The magnitude of the CYP2A6 genotype effect (25%) on plasma cotinine levels was similar to that observed with TNE as the exposure marker; as with the TNE biomarker this is an underestimation of effect size for some genotype or phenotype comparisons (see figure 14). To determine whether the above observations were unique to plasma cotinine, independent regression lines between urinary NNAL and urinary TNE levels were constructed in CYP2A6 RM and NM. The slope of the regression lines did not differ between CYP2A6 genotypes (fig 16, and table 10C), indicating that as expected TNE s relationship to tobacco specific nitrosamines exposure in smokers was independent of CYP2A6 genotype. Together this demonstrates that the impact of CYP2A6 genotype on plasma cotinine levels was specific to cotinine as an exposure biomarker. 94

116 NNAL (pg/mg creatinine) Normal Combine Reduced Rho=0.69 P< Slope =1.69±0.09 Rho=0.59 P< Slope =1.49±0.06 Rho=0.50 P< Slope =1.28± Cotinine (ng/ml) Figure 15 Cotinine s ability to predict tobacco specific nitrosamines exposure (as indicated by NNAL levels) was different between CYP2A6 genotypes (Study 2). The slope between urinary NNAL levels and plasma cotinine was significantly lower in CYP2A6 reduced metabolizers (n=74) compared to that of CYP2A6 normal metabolizers (n=89, table 10). This suggested the quantitative relationship between cotinine and tobacco specific nitrosamines exposure differed between CYP2A6 genotypes. The numbers after the slopes are standard error. 95

117 NNAL (pg/mg creatinine) Reduced Combine Normal ρ=0.74 P< Slope =3.91±0.17 ρ=0.74 P< Slope =3.70±0.22 ρ=0.74 P< Slope =3.83± Total Nicotine Equivalents (9 Items) (nmol/mg Creatinine) Figure 16 TNE s ability to predict tobacco specific nitrosamines exposure is independent of CYP2A6 genotype (Study 2). 96

118 Different relationships between plasma cotinine and polycyclic aromatic hydrocarbon exposure were observed in smokers with different CYP2A6 genotype groups (Study 2) Next, we investigated the quantitative relationship between plasma cotinine and polycyclic aromatic hydrocarbon exposure in smokers. As illustrated by fig. 17 and fig. 18, the slopes of the regression lines in CYP2A6 RM were lower compared to the slope in CYP2A6 NM (1- hydroxyfluorene slopes: in CYP2A6 RM vs in CYP2A6 NM, P=0.013, fig. 18 and table 10D; 1-hydroxypyrene slopes: in CYP2A6 RM versus in CYP2A6 NM, P=0.079, Fig. 17 and table 10E). Males had a greater reduction in cotinine clearance than in cotinine formation (Study 1) Because CYP2A6 activity differs between the sexes, we investigated the impact of sex on cotinine formation and cotinine clearance. The f NIC COT did not differ between the sexes (74% in males compared to 75% in females, non-significant, Fig. 19A). However males had a significantly lower cotinine clearance compared to females (0.58 versus 0.81 ml/min/kg in males and females, respectively, P<0.001, Fig. 19B). A significantly higher f NIC COT / CL COT ratio, which is the conversion factor between plasma cotinine levels and the nicotine dose (Fig. 10D), was observed in males compared to females (1.39 versus 1.12 in males and females, respectively, P=0.001, Fig. 19C). As observed with the entire study population, similar impacts of sex on f NIC COT, cotinine clearance and f NIC COT / CL COT could be observed when examined only within the subgroup of CYP2A6 NM (i.e. excluding the CYP2A6 RM, Fig. 20). Different relationships between plasma cotinine and tobacco exposure were observed in male smokers compared to female smokers (Study 2) Independent regression lines between urinary TNE and plasma cotinine were constructed by sex. The slope of the regression line in males was significantly lower compared to the slope in females (0.34 in males versus 0.42 in females, P=0.01, Fig. 21 and Table 10F). The magnitude of the sex effect on cotinine levels was similar to the effect of CYP2A6 genotype. At 100 nmol tobacco exposure, there is a 25% difference in plasma cotinine levels (60 ng/ml or 340 nmol/l) between the sexes. As observed with the entire study population, similar impacts of sex could be 97

119 observed when examined within just the CYP2A6 NM (slopes: 0.36±0.02 in males versus 0.54±0.03 in females, P=0.001). Figure 17 Cotinine s ability to predict polycyclic aromatic hydrocarbon exposure (as indicated by 1-hydroxypyrene) was different between CYP2A6 genotypes (Study 2). The slope between 1-hydroxypyrene levels and plasma cotinine was lower in CYP2A6 reduced metabolizers (n=74) compared to that of CYP2A6 normal metabolizers (n=89, table 10E). The numbers after the slopes are standard error. 98

120 1-hydroxyfluorene (pmol/mg creatinine) Normal Combine Reduced ρ=0.63 P< Slope =0.0271±0.001 ρ=0.56 P< Slope=0.0256±0.001 ρ=0.49 P< Slope =0.0237± Cotinine (ng/ml) Figure 18 Cotinine s ability to predict polycyclic aromatic hydrocarbon exposure (as indicated by 1-hydroxyfluorene) was different between CYP2A6 genotypes (Study 2). The slope between 1-hydroxyfluorene levels and plasma cotinine was significantly lower in CYP2A6 reduced metabolizers (n=74) compared to that of CYP2A6 normal metabolizers (n=89, supplementary table 10D). The numbers after the slopes are standard error. 99

121 f NIC COT (%) A 100 N.S CL COT (ml/min/kg) B P<0.001 f NIC COT / CL cot C 1.7 P< Males Females 0.0 Males Females 0.5 Males Females Figure 19 Males (n=54), who have reduced CYP2A6 activity compared to females (n=127), had a greater ratio of cotinine formation over cotinine removal, which would result in the accumulation of cotinine and higher cotinine levels at a given tobacco exposure in male smokers (Study 1). A). The f NIC COT did not differ between the sexes. B). Males had significantly lower Cl COT compared to the females. C). Males had a higher f NIC COT/CL COT compared to females indicating an over-estimation of nicotine dose for their cotinine levels. Data presented as mean ± 95% confidence interval. 100

122 f NIC COT (%) A N.S. n=44 n=104 CL COT (ml/min/kg) B P< n=104 n=44 f NIC COT / CL cot C n=44 P< n=104 Males Females 0.0 Males Females Males Females Figure 20 Among the CYP2A6 normal metabolizers (Study 1, n=148), males, who have reduced CYP2A6 activity compared to females, had a greater ratio of cotinine formation over removal. This would result in the accumulation of cotinine and higher cotinine levels at a given tobacco exposure in male smokers. A). The f NIC COT did not differ between the sexes. B). Males had significantly lower Cl COT compared to the females. C). Males had a higher f NIC COT/CL COT compared to females. Data presented as mean ± 95% confidence interval. 0.5 Only CYP2A6 Normal Metabolizers 101

123 Total Nicotine Equivalents ( nmol/mg Creatinine) Females Combine Males At 100 nmol tobacco exposure Rho=0.73 P < Slope=0.421±0.021 Rho=0.73 P < Slope=0.376±0.13 Rho=0.78 P < Slope=0.336±0.014 Cotinine levels in Females at 100 nmol exposure Cotinine levels in males at 100 nmol exposure Cotinine (ng/ml) Figure 21 Cotinine's ability to predict tobacco exposure was different between the sexes. The slope between urinary TNE and plasma cotinine was significantly lower in males (n=71) compared with that of females (n=92, Table 10F), suggesting cotinine overestimates tobacco exposure (i.e., TNE) in males compared with females (Study 2). The numbers after the slopes are standard error. 3.5 Discussion Our analyses demonstrate that variation in CYP2A6 metabolic activity, such as those that exist between CYP2A6 genotypes or the sexes, may alter cotinine removal (i.e. cotinine clearance) to a different extent than cotinine formation (i.e. f NIC COT). Individuals with lower CYP2A6 activities, such as CYP2A6 RM and males, have higher ratios of cotinine formation to cotinine removal (i.e. f NIC COT / CL COT ) compared to individuals with faster CYP2A6 activity, such as CYP2A6 NM and females. Thus, the quantitative relationship between plasma cotinine and tobacco and tobacco derived carcinogen exposures in smokers varies between those with different CYP2A6 activity. 102

124 The pharmacokinetic mechanism The greater effect of altered CYP2A6 activity on cotinine clearance compared to formation is likely related to differences in nicotine and cotinine s hepatic metabolism. Nicotine exhibits a higher hepatic extraction ratio compared to cotinine, which is largely due to differences in their intrinsic clearances. The intrinsic clearance (V max /K m ) of nicotine is 1.69 µl/min/mg protein in human liver microsomes, which is 10 times faster than the 0.16 µl/min/mg protein of cotinine (Benowitz et al. 1983; Nakajima et al. 1996; Nakajima et al. 1996; Hukkanen et al. 2005). For drugs like nicotine, with high extraction ratios, clearance is determined in large part by liver blood flow and is less affected by changes in liver enzymatic activity. In contrast for low extraction drugs like cotinine clearance is largely affected by changes in liver enzymatic activity. This differential impact of variation in CYP2A6 activity is consistent with previous observations on the effects of CYP2A6 induction. Estrogen induces CYP2A6 protein expression in humans (Higashi et al. 2007). During pregnancy, when estrogen levels are elevated, the clearance of nicotine increases by 60% whereas the clearance of cotinine increased by 140% (Dempsey et al. 2002). Thus, higher CYP2A6 activity during pregnancy has a greater effect on cotinine clearance than nicotine clearance. CYP2A6, sex and race Consistent with a higher f NIC COT / CL COT ratio predicting higher cotinine levels for the same tobacco and tobacco-derived carcinogen exposure (equation 1), we observed different quantitative relationships between cotinine and tobacco and tobacco-derived carcinogen exposure in smokers with reduced CYP2A6 activities (CYP2A6 RM and males). These observations provide a mechanistic explanation for the systematic variation in plasma cotinine levels previously observed between CYP2A6 genotypes, the sexes and possibly races (Gan et al. 2008; Ho et al. 2009; Timofeeva et al. 2011). Our observations explain the directional inconsistencies between cotinine and other indicators of tobacco consumption in genetic association studies involving CYP2A6 (Ho et al. 2009; Timofeeva et al. 2011). Due to the higher f NIC COT/CL COT ratio, CYP2A6 RM would have higher plasma cotinine levels upon the same tobacco exposure compared to the CYP2A6 NM. This masks, or reduces, the true size of the effect of CYP2A6 genotype on tobacco consumption based 103

125 on plasma cotinine (i.e. CYP2A6 RM have higher cotinine levels with lower tobacco consumption). These results could also explain why the same CYP2A6 genetic variants have been associated with lower lung cancer risk while having paradoxically higher plasma cotinine levels (Timofeeva et al. 2011). Similarly, during transdermal nicotine patch treatment (i.e. one week after starting treatment) steady state plasma cotinine levels in biochemically confirmed abstinent individuals (Lerman et al. 2006) were inversely related to the pre-treatment CYP2A6 activity (Fig. 22). The 25% (50 ng/ml) average differences in cotinine levels between participants with faster and slower CYP2A6 activity (NMR) was in agreement with the effect size observed in smokers in study 2. The difference double to 50% (100 ng/ml) when comparing those in the first versus fourth quartile of CYP2A6 activity. Thus for the same systemic nicotine exposure (delivered by 21mg patch for all participants), the individuals with slower CYP2A6 activity had higher steady state cotinine levels than the individuals with faster CYP2A6 activity (Fig. 22). 104

126 350 P=0.007 Plasma cotinine levels (ng/ml) Slower Stratum Mean n=58 n=29 P=0.006 n=29 n=29 Faster Stratum Mean n=61 n= st 2nd 3rd 4th Slower Faster NMR quartiles Figure 22 A nicotine patch study: abstinent individuals with slower NMR have higher steady state plasma cotinine compared to individuals with faster NMR after receiving the same 21 mg nicotine patch. The solid black bar represents the mean cotinine levels for the faster NMR stratum (on a median split). The dashed-bar represents the mean cotinine levels for the slower NMR stratum. The analyses were done in the biochemically verified abstinent individuals only. Statistical comparisons were performed by non-parametric Kruskal-Wallis (all 4 quartiles) or Mann- Whitney tests (between the faster and slower strata). Data presented as mean ± 95% confidence interval. 105

127 Our results could explain the systematic variation in plasma cotinine levels between the sexes (Raunio et al. 2001). Due to the lower average estrogen levels, males have lower CYP2A6 protein expression and activity compared to females (Al Koudsi et al. 2010). Thus, males have higher f NIC COT/CL COT ratios, which suggest that males would have higher plasma cotinine levels compared to females with similar tobacco exposure. Finally, our observation could also explain the differences in plasma cotinine levels between Caucasians and African Americans even when controlling for tobacco exposure. About 50% of African Americans are CYP2A6 RM compared to the 20% in Caucasians (Haberl et al. 2005). Therefore, African Americans have, on average, higher f NIC COT/CL COT ratios compared to Caucasians, resulting in higher plasma cotinine levels for similar tobacco exposure. Implications for cancer research Plasma cotinine is often used as an objective, non-self-report, indicator of tobacco exposure in smoking-related cancer research. However, there could be a 25% or greater variation in plasma cotinine levels following the same tobacco and tobacco-derived carcinogen exposure depending on CYP2A6 genotype or in the presence of other inducers/inhibitors of CYP2A6 activity. To put this difference in perspective, Munafò et al. reported that each risk allele in rs , a single nucleotide polymorphism in the α5 nicotinic acetylcholine receptor, is associated with a nmol/l (or 24 ng/ml) increase in plasma cotinine levels, which in turn was predicted to increase lung cancer risk by 1.3 times (Munafo et al. 2012). Our data suggest that the difference between CYP2A6 genotypes (or sex) would be approximately 340 nmol/l (or 60 ng/ml) at 100 nmol tobacco exposure (or roughly 375 pg/mg Cre NNAL). Hence, cotinine levels alone, without considering CYP2A6 activity, may not provide the most accurate information regarding tobacco and tobacco-derived carcinogen exposure in smokers, particularly when comparing groups with different frequencies of CYP2A6 genotypes (or race) or sex. Biomarkers of nicotine intake such as TNE that are less dependent on individual differences in nicotine metabolism or biomarkers of toxicants that are more directly involved in the carcinogenic process, will enhance our understanding of the contribution of variable levels of tobacco consumption on lung cancer risk. 106

128 In conclusion, the quantitative relationship between plasma cotinine level and tobacco and tobacco-derived carcinogen exposure differs among groups with different levels of CYP2A6 activity. These comparison groups include the different CYP2A6 genotype groups within a race (e.g. CYP2A6 RM versus CYP2A6 NM among Caucasians) and different races with distinct prevalence of CYP2A6 RM (e.g. Caucasians with 20% CYP2A6 RM versus African Americans with 50% CYP2A6 RM). Furthermore, groups with different estrogen levels may also have variation in cotinine levels unrelated to differences in tobacco exposure. Those include different sexes, or those with varying pregnancy and menopause statuses. Therefore cotinine levels, as a quantitative marker of tobacco and tobacco-derived carcinogen exposure, are not directly comparable between CYP2A6 genotypes, sexes, and races. 107

129 3.6 Significance to Thesis This chapter contributes to the existing literature in two ways. First, it provided some caveats when using cotinine as a biomarker of tobacco consumption. Plasma cotinine is often used as an objective, non-self report, biomarker of tobacco consumption in smoking-related research. There are currently more than publications, including epidemiological studies, clinical trials, genetic studies and laboratory studies, which used cotinine as a biomarker of tobacco consumption and exposure to secondhand smoke. The findings of this chapter suggest that cotinine has significant limitations as a biomarker of tobacco consumption. There could be a 25% or greater variation in plasma cotinine levels following the same tobacco consumption. Second, the findings of this chapter provided a mechanistic explanation for the inconsistent findings in the field of nicotine biomarkers. In chapter 1, we observed that higher CYP2A6 activity was paradoxically associated with higher TNE levels (suggesting higher tobacco consumption) and lower cotinine levels (suggesting lower tobacco consumption). The findings of chapter 2 provided a mechanistic explanation for this paradoxical finding. Our findings in chapter 2 suggested that the utilization of better biomarkers, such as TNE (which is less dependent on individual differences in nicotine metabolism) or NNAL (which is more directly involved in the carcinogenic process), could enhance our understanding of the contribution of tobacco consumption to disease risks. 108

130 4 CHAPTER 3: CHRNA5-A3-B4 GENETIC VARIANTS ALTER NICOTINE INTAKE AND INTERACT WITH TOBACCO USE TO INFLUENCE BODY WEIGHT IN ALASKA NATIVE TOBACCO USERS Andy Z. X. Zhu, Caroline C. Renner, Dorothy K. Hatsukami, Neal L. Benowitz & Rachel F. Tyndale Reprinted with permission from the Society for the Study of Addiction: Addiction 108(10): All rights reserved. DKH, CCR, NLB and RFT designed the study. CCR recruited the participants. NLB determined the levels of tobacco consumption biomarkers. AZZ performed the DNA extraction from blood and plated the DNA for genotyping. AZZ designed the haplotype tagging block and conducted the genotyping. AZZ performed all analyses and modeling. AZZ and RFT wrote the manuscript. 109

131 4.1 Abstract Aims: Gene variants in CHRNA5-A3-B4, which encodes for the α5, α3 and β4 nicotinic receptor subunits, are associated with altered smoking behaviors in Caucasians. Little is known about CHRNA5-A3-B4 and its association with smoking behaviors and weight in Alaska Native people; a population with high prevalence but low levels of tobacco consumption, a greater prevalence of smokeless tobacco use, and high rates of obesity. We investigated CHRNA5-A3-B4 genetic architecture and its association with nicotine intake and obesity in Alaska Native people. Design, Setting, Participants: A cross sectional study of 400 Alaska Native individuals including 290 tobacco users of which 163 were cigarette smokers. Measurements: CHRNA5-A3-B4 genotype, body weight, and tobacco consumption biomarkers such as plasma cotinine and urinary total nicotine equivalents (TNE). Findings: Alaska Native people have a unique CHRNA5-A3-B4 genetic architecture. In 290 Alaska Native tobacco users, the G allele of rs578776, which uniquely tagged a 30kb haplotype in CHRNA5-A3-B4, was prevalent (16%) and significantly associated with nicotine intake (20% higher plasma cotinine, P<0.001, 16% higher TNE, P=0.076), while rs was not associated with nicotine intake. Rs acted in combination with CYP2A6, the main nicotine-metabolizing enzyme, to increase TNE by 1.8 fold compared to the low risk group (P<0.001). Furthermore a CHRNB4 variant, rs , was significantly associated with increased BMI (P<0.01) in the tobacco users even after controlling for differences in nicotine intake (P<0.01). Conclusions: Genetic variants in CHRNA5-A3-B4 alter nicotine intake and BMI in a population with distinct genetic structure, smoking behaviors and prevalence of obesity. 110

132 4.2 Introduction Smoking and obesity are the greatest preventable causes of premature death. Alaska Native people experience a higher incidence rate of lung cancer than the United States national average (Centers for Disease Control and Prevention 2010), despite reporting on average lower tobacco consumption compared to Caucasian Americans (United States Public Health Service. Office of the Surgeon General. 1998) as observed in our study population of the Alaska Native smokers in the Bristol Bay region (Renner et al. 2013). More than 70% of Alaska Native adults are also considered over-weight or obese (Behavioral Risk Factor Surveillance System 2008). Although smoking and obesity appear to be distinct epidemics with different etiologies, smoking and body weight are intertwined in many ways. Here we investigate whether gene variants in the α5, α3, and β4 nicotinic acetylcholine receptor gene cluster (CHRNA5-A3-B4) are associated with nicotine intake and weight in Alaska Native people as previously observed in Caucasian smokers (Thorgeirsson et al. 2008; Freathy et al. 2011). Nicotine is the major psychoactive component of tobacco. A number of independent genome wide association studies demonstrate a significant association between CHRNA5-A3-B4 gene variants and self-reported smoking quantity as well as with the incidence rate of lung cancer (Amos et al. 2008; Hung et al. 2008; Thorgeirsson et al. 2008; Thorgeirsson et al. 2010). Currently, most association studies are conducted in Caucasians; little is known about the haplotype structure of CHRNA5-A3-B4 and its relationship with nicotine intake in racial minority groups such as Alaska Native people. Multiple independent studies have identified a strong association between tobacco consumption and rs and its correlated SNP rs (Thorgeirsson et al. 2008; Keskitalo et al. 2009; Saccone et al. 2009; Thorgeirsson et al. 2010). For example, the AA genotype of rs is associated with an increase of roughly one cigarette per day (CPD), ng/ml in cotinine, 15 nmol in nicotine equivalents and a 1.6 fold higher odds ratio of developing lung cancer when compared to the GG/GA genotype group (Le Marchand et al. 2008; Keskitalo et al. 2009; Wassenaar et al. 2011; Munafo et al. 2012). In addition to rs rs , other independent SNPs in CHRNA5-A3-B4 have also been reported to affect self-reported smoking 111

133 quantity after adjusting for the effect of rs rs (Chen et al. 2012). These include rs and correlated SNPs as well as rs and correlated SNPs (Saccone et al. 2010). The first objective of our study was to characterize the haplotype structure of CHRNA5-A3-B4 gene cluster in Alaska Native people and to evaluate the impact of genetic variants in CHRNA5- A3-B4 on nicotine intake and tobacco-derived carcinogen exposure. Variation in CHRNA5-A3- B4 and CYP2A6, the latter is the main nicotine-metabolizing enzyme, were previously shown in Caucasians to act in combination to alter CPD (and lung cancer risk) (Wassenaar et al. 2011). Here, we directly compared the quantitative effects of the variants in these two genes on selfreport and objective biomarkers of nicotine intake. Our second objective was to explore the association between CHRNA5-A3-B4 gene variants and body weight. Like smoking, the prevalence of obesity is very high (37.5%) in Alaska Native people, and another 34.3% are considered overweight (Behavioral Risk Factor Surveillance System 2008). Nicotine both increases metabolic rate and suppresses the expected compensatory increase in appetite and feeding. Smokers on average weigh less than nonsmokers; and smokers typically gain 4 to 5 kg when they stop smoking (Seeley et al. 2011). This can be attributed to the activation of sympathetic nervous system peripherally and nicotine s ability to activate α3β4 nicotinic receptors located on POMC (Pro-opiomelanocortin) neurons in the arcuate nucleus of the hypothalamus centrally (Audrain-McGovern et al. 2011; Mineur et al. 2011). Since CHNRA5-A3-B4 encodes for the α3β4 nicotinic receptor, it is possible that CHRNA5-A3-B4 gene variants can modulate nicotine s ability to regulate body weight by altering α3β4 nicotinic receptor function. Previous research suggests that a nicotine intake altering CHRNA5-A3-B4 variant, rs , is associated with altered body weight (Freathy et al. 2011). Yet it is not clear whether this association is an indirect effect of rs altering nicotine intake or a direct effect of rs altering nicotine s effect on body weight, possibly by modulating nicotinic receptor function (Freathy et al. 2011). In this study, we seek to replicate and extend the association between CHRNA5-A3-B4 variants and body weight by looking at the impact of CHRNA5-A3-B4 variants on body weight with, and without, controlling for nicotine intake. Together, these findings will further our understanding of the role of genetic variations in the nicotinic receptor genes in two pressing public health issues, smoking and obesity. 112

134 4.3 Material and methods Study Design A detailed description of recruitment procedures, participant demographics and tobacco related behaviors has been reported previously (Renner et al. 2013). Briefly, 400 Alaska Native individuals were recruited in local villages near Bristol Bay, Alaska. The total current tobacco user group (n=290) included 163 cigarette smokers, 76 commercial smokeless tobacco users, 20 iqmik (a type of smokeless tobacco used with alkaline ash) users, and 31 mixed products users. The non-tobacco user group included 82 former smokers and 28 never users. Ethics approval was obtained from Alaska Area IRB, the Bristol Bay Area Health Corporation Board and Ethics Committee, UCSF and the University of Toronto. CHRNA5-A3-B4 Genotyping Seventeen SNPs in the CHRNA5-A3-B4 gene cluster were genotyped using Applied Biosystem Taqman genotyping assays. The CHRNA5-A3-B4 SNPs were selected to 1) represent loci which have been previously associated with smoking behavior (e.g. rs rs ; rs588765, and rs rs578776) and 2) tag the region between CHRNA5 and CHRNA3 (where most of the previous significant associations with smoking behavior have been observed) based on the CHB (Han Chinese) and JPT (Japanese) datasets of the International Hapmap Project release #28. The position and minor allele frequency of the genotyped SNPs are listed on Table

135 Table 11 A list of the SNP markers selection Marker Reference GRCh37 Contig. NCBI Hapmap/ABI MAF Primer and Gene dbsnp ID MAF Number Position Position Pos. Alleles probes Caucasians Africans Asian 1 PSMA4 rs A/G 0.05 (G) 0.36 (G) 0.18 (G) 0.17 (G) C _10 2 rs T/G 0.14(T) 0.34 (T) 0.20 (T) 0.11 (T) C 18826_10 3 rs A/C 0.04 (C) 0.40 (C) (C) C _10 4 rs A/G 0.18 (A) 0.37 (A) 0.42 (A) 0.18 (A) C _10 CHRNA5 5 rs G/A 0.22 (G) 0.21 (A) 0.26 (A) 0.43 (G) C 5865_10 6 rs T/A 0.22 (T) 0.21 (A) 0.27 (A) 0.42 (T) C 5866_10 7 rs A/G 0.03 (A) 0.42 (A) 0.00(A) 0.03 (A) C _20 8 rs A/G 0.16 (G) 0.24 (A) 0.34 (G) 0.19 (G) C _10 9 rs A/G 0.03 (A) 0.40 (A) 0.11 (A) 0.03 (A) C _20 10 rs G/C 0.17 (G) 0.20 (C) 0.33 (G) 0.23 (C) C _10 11 CHRNA3 rs C/T 0.05 (T) 0.43 (T) 0.19 (T) 0.25 (T) C _10 12 rs G/C 0.21 (C) 0.20 (G) 0.34 (G) 0.26 (C) C _10 13 rs C/T 0.21 (T) 0.21 (C) 0.34 (C) 0.27 (T) C _10 14 rs T/C 0.12 (C) 0.45 (C) 0.36 (C) 0.28 (C) C _10 15 rs C/T 0.26 (T) 0.27 (T) 0.12 (T) 0.40 (T) C _10 CHRNB4 16 rs T/G 0.21 (G) 0.18 (T) 0.32 (G) 0.21 (G) C _10 17 rs C/T 0.35 (T) 0.00 (C) 0.00 (C) 0.40 (C) C _10

136 The measurement of CYP2A6 activity We estimated in vivo CYP2A6 activity previously using the plasma ratio of tran-3 - hydroxycotinine to cotinine (also known as nicotine metabolite ratio, NMR) (Binnington et al. 2012). Using a median split of plasma NMR within the total tobacco user group (n=290) as described previously (Zhu et al. 2013), participants who were in the higher NMR stratum were considered the faster CYP2A6 activity group, while those in the lower NMR stratum were considered the lower CYP2A6 activity group. Plasma and urinary biomarkers We used a panel of biomarkers to assess nicotine intake and tobacco-derived carcinogen exposure. To evaluate nicotine intake, plasma cotinine as well as the urinary sum of nicotine and 8 of its metabolites is known as total nicotine equivalents (TNE) and accounts for about 90% of an administered nicotine dose (Benowitz et al. 1994). Total urinary 4-(methylnitrosamino)-1-(3- pyridyl)-1-butanol (NNAL) was used to evaluate tobacco specific nitrosamine exposure (Hecht 2003; Church et al. 2009). 1-Hydroxyfluorene was used in this study as a biomarker of tobacco related polycyclic aromatic hydrocarbons exposure (StHelen et al. 2012). Plasma cotinine and tran-3 -hydroxycotinine levels, as well as urinary TNE, total NNAL, and 1-hydroxyfluorene were quantified by gas/liquid chromatography-tandem mass spectrometry as previously described (Dempsey et al. 2004; Jacob et al. 2007; Jacob et al. 2008; Bernert et al. 2011). Statistical Analyses Statistical analyses were performed using R version 2.14 (R foundation for statistical computing). The association between CHRNA5-A3-B4 gene variants and biomarkers of tobacco and tobacco derived carcinogen exposure were assessed by PLINK (Purcell et al. 2007). Haplotyping results of CHRNA5-A3-B4 were obtained using the Haploview software (Barrett et al. 2005). The biomarkers (plasma cotinine, urinary TNE, NNAL and 1-hydroxyfluorene levels) were normalized by log transformation before statistical analyses. With regard to nicotine intake and tobacco derived carcinogen exposure, no multiple comparison adjustments were used since we considered our analyses a replication and extension of previous findings in a new racial population. Since there were 12 independent loci, we considered P values below (i.e. 115

137 0.05/12) statistically significant for the assessment of the association between CHRNA5-A3-B4 and BMI. 4.4 Results The CHRNA5-A3-B4 gene cluster structure in Alaska Native people The minor allele frequency of the 17 genotyped SNPs in comparison to other racial groups is listed in Table 11. All SNPs were in Hardy-Weinberg equilibrium. A haplotype analysis revealed a 30 KB region of high linkage disequilibrium (LD) between CHRNA5 and CHRNA3 (i.e. a haplotype block between rs and rs , Fig. 23). Within this haplotype block, four haplotypes with a prevalence of more than 1% were identified (Fig. 23 Insert), the total prevalence of these four haplotypes was 99.9% in the 400 participants. The most common haplotype, with a 77.6% frequency, was designated as haplotype A. The remaining haplotypes were designated to haplotype B, C and D according to their prevalence respectively. As illustrated by the insert of fig. 23, these four haplotypes could be discerned by a few tag SNPs. For example, haplotype A was uniquely tagged by rs569207, and haplotype B was uniquely tagged by rs

138 Figure 23 Observed CHRNA5-A3-B4 haplotype structure in Alaska Native people. The shade and number in the squares indicate the D score. Insert: A haplotype analysis revealed a 30kb region of high linkage disequilibrium between CHRNA5 and CHRNA3.Within this haplotype block, four haplotypes with a prevalence of more than 1% were identified. These four haplotype could be discerned by a few tag SNPs. For example, haplotype A was uniquely tagged by rs (marker #5), while haplotype B was uniquely tagged by rs (marker #8) 117

139 The association between gene variants in CHRNA5-A3-B4 and nicotine intake The associations (by additive models) between CHRNA5-A3-B4 gene variants and nicotine intake and tobacco-derived carcinogen exposure are primarily evaluated in the total tobacco users group (n=290). The associations within the smokers (n=163) and smokeless tobacco users (n=76) are also presented to illustrate the effect in these subgroups. The results are summarized in Table 12 with a few key findings outlined below. Rs578776: The G allele of rs578776, which uniquely identified haplotype B in Alaska Native people, was significantly associated with higher cotinine levels in the total tobacco users group and in the cigarette smokers (Fig. 24A and Table 12). As illustrated by fig. 24A, each G allele of rs was associated with a roughly 20% (33 ng/ml) increase in plasma cotinine levels in the total tobacco users group and a roughly 22% (33 ng/ml) increase in the smokers (P<0.001 and P=0.008, respectively). When evaluated by a dominant model (i.e. AG and GG groups combined), rs was weakly associated with plasma cotinine levels in the smokeless tobacco group (P=0.06, Fig. 25A). In addition to cotinine, weak associations between rs and urinary TNE were also observed among the total tobacco user group and among the smokers (P=0.076 and P=0.05, respectively. Fig. 24B). Rs was also significantly associated with CPD among the smokers. The average CPD was 7.2 for the AA genotype, 8.6 for the AG genotype and 11.7 for the GG genotype (P=0.02, Table 12). No significant associations between rs and urinary NNAL or 1-hydroxyfluorene levels were observed (Fig. 24C and D). The associations were similar when assessed by dominant models (i.e. pooling the AG and GG genotypes, Table 12). Individuals with the G allele of rs exhibited a greater, although non-significant, odds ratio of being a current smoker than a former smoker (OR=1.72, P=0.06, n=163 and 82 respectively). Rs : rs is a nonsynonymous (amino acid change: D398N) variant previously associated with nicotine intake in Caucasians thought to alter α5 nicotinic receptor function (Bierut et al. 2008; Fowler et al. 2011). The prevalence of the A allele of rs , and the correlated rs , was low (3%) in Alaska Native people compared to Caucasians (~38% according to the Hapmap project). Similar to the Caucasian populations of the international Hapmap project, rs was in very low LD with rs in Alaska Native 118

140 people (r 2 =0.15). While rs had what appeared to be a large impact on nicotine intake (Fig. 26), this did not reach significance at least in part due to the low prevalence and power to detect the association. The GA genotype of rs , compared to the GG genotype, was non-significantly associated with 1.51 fold (89 ng/ml) higher plasma cotinine in the total tobacco user group and 1.46 fold (73 ng/ml) higher plasma cotinine in the smokers (Fig. 26A). The GA genotype of rs was also non-significantly associated with 16% (10 nmol/mg Cre) higher urinary TNE levels in the total tobacco user group and 38% (21 nmol/mg Cre) higher TNE levels in the smokers (Fig. 26B). Associations of similar directions and magnitudes could also be observed with urinary NNAL and 1-hydroxyflurene (Fig. 26C and Fig. 26D). The A allele of rs was found at a greater frequency in the current smokers compared to the former smokers, although this difference did not reach statistical significance (6.1% vs. 3.7%, n=163 and 82 respectively). Of note, the association between plasma cotinine levels and rs remained significant after adjusting for rs or excluding the participants with at least one A variant allele of rs (data not shown). Rs588765: rs and correlated SNPs have previously been associated with increased risk of heavy smoking (Chen et al. 2012). In our study, no significant associations were observed between rs and nicotine intake with/without adjusting for the effect of rs and/or rs (Fig. 27). 119

141 Table 12 The association between CHRNA5-A3-B4 SNPs and CPD, FTDN, COT, TNE, NNAL and BMI (Additive models) Marker Number dbsnp ID Tobacco users (n=290) Smokers (n=163) MAF COT TNE NNAL PAH BMI MAF CPD FTND COT TNE NNAL PAH BMI 1 rs (G) (G) (G) (G) rs (C) rs (C) (C) (G) (G) rs (A) (T) (A) rs (G) (C) (C) (G) rs (T) (T) (T) (T) rs (A) (A) rs (G) (G) (G) (G) (G) (G) rs (A) (A) (A) rs (G) (G) (G) (G) (G) (G) rs (T) (T) (T) (T) rs (C) (C) (C) (C) (C) rs (T) (T) (T) (T) (T) rs (C) (C) rs (T) (T) rs (G) (G) rs (T) (T) The risk alleles are indicated in the parentheses. MAF= Minor allele frequency. PAH=1-hydroxyflurenene levels. 120

142 rs A Plasma Cotinine (ng/ml) Median ± IQR P<0.001 P=0.008 P=0.076 P=0.05 B Urinary TNE (nmol/ mg Cre) Median ± IQR C Urinary NNAL (pmol/mg Cre) Median ± IQR n=194 n=90 n=6 n=107 n=53 n=3 n=55 n=19 n=2 0 AA AG GG AA AG GG AA AG GG Total tobacco users Smokers Smokeless n=194 n=90 n=6 n=107 n=53 n=3 n=55 n=19 n=2 0 AA AG GG AA AG GG AA AG GG Total tobacco users Smokers Smokeless D Urinary 1-hydroxyflurene (pg/ml) Median ± IQR n=194 n=90 n=6 n=107 n=53 n=3 n=55 n=19 n=2 0 AA AG GG AA AG GG AA AG GG Total tobacco users Smokers Smokeless n=194 n=90 n=6 n=107 n=53 n=3 n=55 n=19 n=2 0 AA AG GG AA AG GG AA AG GG Total tobacco users Smokers Smokeless Figure 24 The association between rs with A) cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1- hydroxypryrene. IQR= interquartile range. The P-values were obtained from additive models. 121

143 rs A 400 P=0.005 P=0.02 P=0.06 B 120 P=0.22 P=0.15 P=0.94 C Plasma Cotinine (ng/ml) Median ± IQR Urinary NNAL (pmol/mg Cre) Median ± IQR n=194 n=96 n=107 n=56 n=55 n=21 AA AG/GG AA AG/GG AA AG/GG Total tobacco users Smokers Smokeless P=0.91 P=0.69 P= n=194 n=96 n=107 n=56 n=55 n=21 AA AG/GG AA AG/GG AA AG/GG Total tobacco users Smokers Smokeless D Urinary TNE (nmol/ mg Cre) Median ± IQR Urinary 1-hydroxyflurene (pg/ml) Median ± IQR n=194 n=96 n=107 n=56 n=55 n=21 AA AG/GG AA AG/GG AA AG/GG Total tobacco users Smokers Smokeless P=0.08 P=0.22 P= n=194 n=96 n=107 n=56 n=55 n=21 AA AG/GG AA AG/GG AA AG/GG Total tobacco users Smokers Smokeless Figure 25 The association (by dominate models) between rs with A) cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1-hydroxypryrene. IQR= interquartile range. The P-values were obtained from dominant models. 122

144 A 400 rs B 120 Plasma Cotinine (ng/ml) Median ± IQR Urinary TNE (nmol/ mg Cre) Median ± IQR C Urinary NNAL (pmol/mg Cre) Median ± IQR n=273 n=17 n=153 n=10 n=70 n=6 0 GG GA GG GA GG GA Total tobacco users Smokers Smokeless n=273 n=17 n=153 n=10 n=70 n=6 0 GG GA GG GA GG GA Total tobacco users Smokers Smokeless D n=273 n=17 n=153 n=10 n=70 n=6 0 GG GA GG GA GG GA Total tobacco users Smokers Smokeless Urinary 1-hydroxyflurene (pg/ml) Median ± IQR n=273 n=17 n=153 n=10 n=70 n=6 0 GG GA GG GA GG GA Total tobacco users Smokers Smokeless Figure 26 The association between rs with A) plasma cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1-hydroxypryrene. IQR= interquartile range 123

145 rs A 400 B 120 Plasma Cotinine (ng/ml) Median ± IQR C Urinary NNAL (pmol/mg Cre) Median ± IQR n=194 n=90 n=6 n=107 n=53 n=1 n=60 n=15 n=1 0 GG GT TT GG GT TT GG GT TT Total tobacco users Smokers Smokeless n=194 n=90 n=6 n=107 n=53 n=1 n=60 n=15 n=1 0 GG GT TT GG GT TT GG GT TT Total tobacco users Smokers Smokeless D Urinary TNE (nmol/ mg Cre) Median ± IQR Urinary 1-hydroxyflurene (pg/ml) Median ± IQR n=209 n=79 n=2 n=114 n=48 n=1 n=60 n=15 n=1 0 GG GT TT GG GT TT GG GT TT Total tobacco users Smokers Smokeless n=194 n=90 n=6 n=107 n=53 n=1 n=60 n=15 n=1 0 GG GT TT GG GT TT GG GT TT Total tobacco users Smokers Smokeless Figure 27 The association between rs with A) cotinine levels B) Urinary TNE C) Urinary NNAL D) Urinary 1- hydroxypryrene. IQR= interquartile range. 124

146 Combined influence of CHRNA5-A3-B4 and CYP2A6 activity on nicotine intake Next, we examined the combined influence of gene variants in CHRNA5-A3-B4 and altered CYP2A6 activity on nicotine intake. Since CYP2A6 activity can influence the quantitative relationship between nicotine intake and cotinine levels (Zhu et al. 2013), urinary TNE was used as the primary tobacco exposure biomarker. The analyses focused on the total tobacco user group (n=290) for sufficient statistical power. The effects of rs and CYP2A6 activity, alone or together, on tobacco intake are shown in fig. 28. To assess the combined influence of CHRNA5-A3-B4 and CYP2A6, we assigned the tobacco users into one of three risk groups. The low risk group included participants with both rs AA genotype and slower CYP2A6 activity. Participants with either rs AG/GG genotype or faster CYP2A6 activity were assigned to the intermediate risk group. Participants with both rs AG/GG genotype and faster CYP2A6 activity were considered the high risk group. As illustrated in fig. 28, urinary TNE levels were significant different between the low risk group (mean=47 nmol TNE/Cre), the intermediate risk group (mean=69.2 nmol TNE/Cre) and the high risk group (84.4 nmol TNE/Cre, Kruskal-Wallis test: P=0.0003, Fig 28). Urinary TNE levels also increased with the number of risk genotypes in a linear trend (Jonckheere Trend Test: P=2.6*10-5 ). Due to the low prevalence of rs , our ability to evaluate the combined effect of rs and CYP2A6 activity in this study was limited (Fig. 29). 125

147 120 P= P< TNE (nmol/ mg Cre) Median ± IQR n=194 n=96 AA AG/GG CHRNA5-A3-B4 rs n=145n=145 Slower Faster CYP2A6 activity groups n=89 n=161 n=40 Low Intermed. High CHRNA5-A3-B4 and CYP2A6 combined risk groups Figure 28 The combined impact of genetic variants in CHRNA5-A3-B4 and CYP2A6 activity on urinary TNE levels among the total tobacco user group. The low risk group included participants with both rs AA genotype and slower CYP2A6 activity. Participants with either rs AG/GG genotype or faster CYP2A6 activity were assigned to the intermediate risk group. Participants with both rs AG/GG genotype and faster CYP2A6 activity were considered as the high risk group. IQR= interquartile range. The P- values were obtained by non-parametric comparisons (Mann-Whitney or Kruskal-Wallis). 126

148 120 P= P< TNE (nmol/ mg Cre) Median ± IQR n=273 n=17 GG GA CHRNA5-A3-B4 rs n=145n=145 Slower Faster CYP2A6 activity groups n=135 n=148 n=6 Low Intermed. High CHRNA5-A3-B4 and CYP2A6 combined risk groups Figure 29 The combined impact of rs in CHRNA5-A3-B4 and CYP2A6 activity on urinary TNE levels. The P-values were obtained by non-parametric comparisons (Mann-Whitney tests or Kruskal- Wallis tests). The association between CHRNA5-A3-B4 gene variants and BMI The total tobacco users had significantly lower BMI compared to the non-tobacco group (Fig. 30A, P<0.001). Among the total tobacco user group, there was a significant inverse correlation between plasma cotinine levels and BMI, suggesting nicotine dose dependently reduced body weight (Rho=-0.128, P=0.04, Fig. 30B). Notably, the Y-intercept of the regression line is 30.4 kg/m 2, which is the same as the average BMI of the non-tobacco user group. Similar correlation coefficients could be observed when examined in smokers (Rho=-0.117, P=0.15) or the commercial smokeless tobacco users (Rho=-0.133, P=0.27). Neither of the nicotine intake 127

149 altering SNPs, rs and rs , were associated with BMI in the total tobacco user group or in the smokers only (Table 12). Adjusting for cotinine levels did not improve the associations between rs or rs with BMI. On the other hand rs , a CHRNB4 SNP with a 36% allele frequency which was not associated with altered nicotine intake in Alaska Native people (Table 12), was associated with BMI in the total tobacco user group (P=0.006, Table 12). The association was even stronger after adjusting for plasma cotinine levels (P=0.0035, Fig. 31, Table 13). Adjusting for the nicotine intake altering SNPs, such as rs578776, did not change the strength of the association. Rs was not significantly associated with BMI in the non-tobacco user group (Fig. 31). A BMI Median ± IQR 50 P< B BMI Rho=-0.128, P=0.04 Y= X Nonusers Tobacco Users Plasma cotinine levels (ng/ml) Figure 30 The association between tobacco consumption and BMI. A). Non-tobacco user group have higher BMI than the tobacco users. B). BMI negatively correlated with plasma cotinine levels within the total tobacco user group, suggesting a dose dependent relationship between nicotine intake and body weight. 128

150 40 N.S. P=0.006 P COT Adj = N.S. N.S. 35 BMI Median ± IQR n=53 n=44 n=13 n=126n=121 n=43 n=68 n=69 n=26 n=36 n=29 n=10 CC CT TT CC CT TT CC CT TT CC CT TT Non-tobacco users Tobacco users Smokers Smokeless Figure 31 Rs was significantly associated with BMI in the total tobacco user group, but not in the non-tobacco user group. Similar directions of effect were observed between rs and BMI within the smokers and smokeless users. The P-value of the total tobacco user group was derived from an additive model after adjusting for plasma cotinine levels (Table 13). P COT adj. = The P value of rs after adjusting plasma cotinine levels. Table 13 The association between rs BMI (Additive model). Predictors of BMI r 2 =0.055 P=0.002 B 95% CI P Cotinine (Increasing, per ng/ml) rs (Per T allele) to to

151 4.5 Discussion We characterized the gene structure of CHRNA5-A3-B4 among Alaska Native people. In addition, we identified a significant association between rs and nicotine intake. Secondly, we demonstrated that CHRNA5-A3-B4 gene variants, particularly rs578776, could act in combination with CYP2A6 to modify nicotine intake. Thirdly, we demonstrated that rs , a CHRNA5-A3-B4 gene variant which did not alter nicotine intake, was associated with altered body weight among tobacco users. Haplotype The haplotype analyses of CHRNA5-A3-B4 identified both similarities and differences between Alaska Native people and Caucasians. For example, rs and rs were in high degree of linkage disequilibrium in Alaska Native people as seen in Caucasians. However, the allele frequency of rs rs variant SNPs was substantially lower (at 3%) compared to Caucasians (~38%), and was similar to that observed in the Asian populations (at 3%) of the International Hapmap project. In contrast to rs rs , the LD between rs and rs was weak in Alaska Native people compared to the high degree of LD previously observed in Caucasians (Chen et al. 2012). Associations with nicotine intake We demonstrated a significant association between rs (representing haplotype B in Alaska Native people) and nicotine intake. The G allele of rs was associated with increased nicotine intake in Alaska Native people as previously seen in Asians and Caucasians (Chen et al. 2012). Of note, the allele frequency of the rs G allele was much lower in Alaska Native people than in Caucasians. In fact, the G allele is the major allele of rs in Caucasians whereas it is the minor allele of rs in Alaska Native people. Rs and its correlated SNPs generally exhibit the strongest association with nicotine intake in Caucasians and other racial groups (Chen et al. 2012; Munafo et al. 2012). In Alaska Native people, the GA genotype of rs was associated with a roughly 73 ng/ml increase in plasma cotinine, which is within the previously reported range of 24 to 100 ng/ml (Keskitalo et al. 2009; Munafo et al. 2012). Due to the low prevalence of rs in Alaska 130

152 Native people, the difference between GG and GA genotypes was not significant. Overall, while the effect size of rs on nicotine intake was larger than rs (Plasma cotinine in smokers: 73 vs. 33 ng/ml, respectively), the overall impact on nicotine intake is likely to be smaller than rs in Alaska Native people due to the allele frequencies. Associations in combination with CYP2A6 In our study, CYP2A6 and CHRNA5-A3-B4 acted in combination to increase nicotine intake. Of note, the combined low-risk group had lower nicotine intake compared to either the AA group of rs or the slower CYP2A6 activity group alone and the combined high risk group had higher nicotine intake compared to either the AG/GG group of rs or the faster CYP2A6 activity group alone. Consistent with previous observation in Caucasians (Wassenaar et al. 2011), we observed that CYP2A6 activity had a greater influence on nicotine intake than CHRNA5-A3-B4 gene variants, which was particularly obvious among the smokeless tobacco users. We have previously shown that these Alaska Native smokeless tobacco users with faster CYP2A6 activity have higher nicotine intake compared to the smokeless tobacco users with slower CYP2A6 activity (Zhu et al. 2013). However, in the present analyses, we did not observe any significant associations between CHRNA5-A3-B4 gene variants and nicotine intake in the smokeless tobacco users. Thus, it is interesting that among Caucasians CHRNA5-A3-B4 gene variants generally have a bigger effect on lung cancer risk than CYP2A6 (Wassenaar et al. 2011). This suggests that the CHRNA5-A3-B4 gene variants may modulate lung cancer risk by mechanisms in addition to their effects on smoking behavior, such as directly altering cell proliferation and survival (Brennan et al. 2011). The prevalence of the protective CYP2A6 and CHRNA5-A3-B4 alleles were higher in Alaska Native people than in Caucasians, suggesting the protective CYP2A6 and CHRNA5-A3-B4 alleles may contribute to the low level of self-report smoking in Alaska Native people and that other genes or environmental factors may be responsible for the higher risk for lung cancer. Association with BMI The Alaska Native non-tobacco user group had, on average, higher BMI compared to the total tobacco user group. Within the tobacco users, there was a significant negative relationship between nicotine intake and BMI, supporting a negative dose response relationship between 131

153 nicotine intake and body weight (Mineur et al. 2011). The negative dose response relationship is consistent with the known effects of nicotine to increase metabolic rate and suppress appetite (Mineur et al. 2011). Genetic variants in CHRNA5-A3-B4 have been associated with BMI (Freathy et al. 2011), however, it was not clear whether this genetic association was mediated indirectly by the effect of CHRNA5-A3-B4 genetic variants on nicotine intake or directly by altering nicotine s effect on the nicotinic receptor pharmacodynamic target. In this study rs578776, which altered nicotine intake, was not directly associated with BMI, suggesting the effect of rs on nicotine intake was not strong enough to alter BMI. Interestingly, there was a direct role of another CHRNA5-A3-B4 genetic variants in modulating BMI. We demonstrated rs , a prevalent β4 SNP which was not associated with nicotine intake, could alter nicotine s ability to modulate body weight even after controlling for plasma cotinine. A possible explanation is that rs results in altered β4 nicotinic receptor subunit function, reducing nicotine s ability to suppress eating. Conclusion Together, we found an association between CHRNA5-A3-B4 gene variants and nicotine intake in Alaska Native people. This is novel since the gene structure and SNP prevalence in Alaska Native people differ from Caucasians, and the level and type of nicotine intake also differ. We observed that rs578776, which uniquely tags haplotype B, was significantly associated with nicotine intake. Due to the high prevalence of rs in Alaska Native people, it may play a more important role in governing nicotine intake than rs We also demonstrated that variation in pharmacokinetic (i.e. CYP2A6) and pharmacodynamic (i.e. nicotinic receptors) genes could act in combination to increase nicotine intake. Lastly, we provided evidence that there is a dose response relationship between nicotine intake and body weight, and genetic variants in the CHRNA5-A3-B4 can modulate body weight in smokers directly without altering nicotine intake. A limitation of the current study with respect to generalizability is that the findings may not be representative of the entire Alaska Native population as we only recruited from one region in southwest Alaska. Since most of our participants were Yupik, Alaska Native people from other regions with different ethnic backgrounds could have different CHRNA5-A3- B4 gene structures. In summary, our data indicate that genetic variation in CHRNA5-A3-B4 can modulate both nicotine intake and body weight in tobacco users. These findings provide 132

154 important insights about the contribution of CHRNA5-A3-B4 to variation in both tobacco and obesity, the two most prevalent causes of preventable death and disease. 133

155 4.6 Significance to Thesis This chapter extends the findings of previous chapters and contributes to the existing literature in three ways. First, the findings of this chapter demonstrated that gene variants in nicotine pharmacodynamic genes, such as CHRNA5-A3-B4, significantly alter tobacco consumption in light smokers. This chapter also presented the combined effects of CHRNA5-A3- B4 variants and CYP2A6 variants on tobacco consumption. Of note CYP2A6 variants had a similar, if not bigger, effect on tobacco consumption compared to CHRNA5-A3-B4 variants. This suggests that the higher lung cancer risk associated with CHRNA5-A3-B4 variants, compared to CYP2A6 variants, may not be exclusively mediated by altered tobacco consumption. Alterations in cell signaling pathways may also contribute to the higher lung cancer risk associated with CHRNA5-A3-B4 variants. Secondly, this study also highlights the importance of race specific genetic association studies. In Caucasian heavy smokers, rs and rs have previously been associated with altered tobacco consumption. This chapter demonstrated that rs has little importance in governing tobacco consumption in Alaska Native light smokers largely due to the low allele frequency. In contrast, rs578776, which had a smaller influence on tobacco consumption in Caucasians compared to rs , played an important role in governing tobacco consumption in Alaska Native smokers Lastly, the finding that gene variants in CHRNA5-A3-B4 could significantly alter nicotine s ability to alter bodyweight is both novel and has some important clinical implications. CHRNA5-A3-B4 variants have previously been associated with BMI, but the mechanism was unclear. This study demonstrated that CHRNA5-A3-B4 could influence BMI beyond the influence on altering tobacco consumption. Our findings, in combination with previous animal experiments, suggest that the α3β4 nachr could be an important drug target for the treatment of obesity (Mineur et al. 2011). 134

156 5 GENERAL DISCUSSION The specific contributions of the thesis findings to the literature were previously discussed in Chapters 2, 3 and 4. The broad implications of the overall thesis findings to nicotine and tobacco research will be the focus of this general discussion section, along with proposals for future research directions. 5.1 Strengths and Limitations of Tobacco Consumption Biomarkers The strengths and limitations of tobacco consumption biomarkers are summarized in Table 14. This section provides some recommendations about biomarker selection in smoking studies. Table 14 A summary of the limitations of common tobacco biomarkers Biomarker Best use Limitations Self-Report Measurements (e.g. CPD) Carbon Monoxide Cotinine TNE NNAL Plasma COT+3HC When biomarkers cannot be obtained Verifying smoking status in subjects treated with nicotine replacement therapy Evaluating tobacco consumption when urinary samples are not available; Verifying smoking status Evaluating tobacco consumption Evaluating TSNA exposure Evaluating tobacco consumption Reporting bias; Variable nicotine intake per cigarette Short half-life; low specificity Variation in cotinine clearance; ELISA method may over estimate. Expansive; Limited Access; Creatinine adjustment Variation in the metabolism of NNK to NNAL Specificity toward tobacco Halflife For evaluating tobacco consumption For evaluating smoking status High N/A Poor Poor Low High High High Short Long Long Long Unknown High Long Poor in infrequent smokers; Questionable in frequent smokers Reasonable in both infrequent and frequent smokers Good in both infrequent and frequent smokers Good in both infrequent and frequent smokers Unknown, likely good Poor in infrequent smokers; Good in frequent smokers Good in both infrequent and frequent smokers Unknown, likely good Good in frequent smokers; Unknown in infrequent smokers Unknown, likely good 135

157 5.1.1 Strengths and Limitations of Self-Report CPD and Self-Report Chews per Day Smoking is a complex behavior and there is a lot of variability in daily tobacco consumption between smokers (Centers for Disease Control and Prevention 2008). In clinical and epidemiological studies, self-report CPD is often used as an indicator of daily tobacco consumption. However, as illustrated by a series of analyses presented in Chapter 1, self-report CPD gives a biased and inaccurate estimation of tobacco consumption, particularly in light/infrequent smokers (less than 10 CPD). Fig. 32 illustrates two major weaknesses of CPD. First, the amount of nicotine extracted per cigarette varies among smokers. Among smokers who consumed less than 15 CPD, there is a significant negative correlation between self-report CPD and the amount of nicotine intake per cigarette (Fig. 32). This suggests that the smokers who smoked fewer CPD extracted more nicotine per cigarette than the smokers who consumed more CPD. Among the smokers who smoked more than 15 CPD, the amount of nicotine intake per cigarette was less variable (Fig. 32). This finding suggests that CPD may still have some utility as an indicator of tobacco consumption in heavy smokers. The second major weakness of using CPD as an indicator of tobacco consumption is number bias. As illustrated by Fig. 32, smokers were more likely to report their CPD in the multiples of 5 cigarettes (i.e. most smokers reported 5, 10, 15, 20, 25 or 30 CPD). This number bias limits the ability of CPD to capture the fine differences in tobacco consumption and could make CPD an ordinal variable rather than a ratio variable during statistical analyses. 136

158 TNE/Cigarette (nmol/ mg Cre) Spearman's Correlation:P< Spearman's Correlation: P< Cigarettes per day Figure 32 The relationship between self-report CPD and nicotine intake per cigarette (calculated as TNE divided by CPD). This graph is compiled based on data from Chapter 1. It illstrates two major weaknesses of selfreport CPD as an indictor of tobacco consumpion: 1) variation in nicotine intake per cigarette. 2) substantial number bias toward 5, 10, 15, 20 and 30. TNE=Total nicotine equivalents. Self-report chews per day and cans of smokeless tobacco consumed per week are often used as a measurement of smokeless tobacco consumption. Chews per day and cans of smokeless tobacco consumed per week show considerable variability in the amount of nicotine intake per chew or per can (Fig. 33). There is a significant negative correlation between self-report chews per day and the amount of nicotine intake per chew (Fig. 33). This suggests that the smokeless tobacco users who consumed fewer chews per day extracted more nicotine per chew, hence chews per day may not give an accurate estimation of tobacco consumption. Furthermore, Alaska Native smokeless tobacco users reported consuming 1.6 cans of commercial smokeless tobacco per week in comparison to the 3.6 cans per week reported by Caucasian smokeless tobacco users in the United States (Mushtaq et al. 2012). This suggests that Alaska Native smokeless tobacco users are light smokeless tobacco users as being on average light smokers. However, despite consuming only 40% of the smokeless tobacco as Caucasians, Alaska Native smokeless tobacco 137

159 users exhibit similar cotinine levels as the Caucasian smokeless tobacco users in the United States (223 ng/ml in Alaska Natives vs. 200 to 260 ng/ml in Caucasians) (Gritz et al. 1981; SRNT Subcommittee on Biochemical Verification 2002; Mushtaq et al. 2012). This suggests that using self-report cans of commercial smokeless tobacco per week as an indicator of smokeless tobacco consumption underestimate the nicotine exposure in Alaska Native individuals. 30 TNE/Chew (nmol/ mg Cre) Rho = P= Chews per day Figure 33 The relationship between self-report chews per day and nicotine intake per chew (calculated as TNE divided by chews per day) in Alaska Native commerical smokeless tobacco users. This graph is compiled from data in Chapter 1. Like with CPD, there is a significant negative correlation between chews per day and the amount of nicotine intake per chew. However, unlike CPD, there is no apparent number bias in chews per day. TNE=Total nicotine equivalents. Overall, the existing data suggest that self-report gives an inaccurate estimation of tobacco consumption in both smokers and smokeless tobacco users. The use of objective biomarkers would capture more of the quantitative aspects of tobacco consumption and would improve our understanding of the dose response relationships between tobacco consumption and tobacco related diseases. 138

160 5.1.2 Strengths and Limitations of CO and Cotinine as Biomarkers of Tobacco Consumption and Smoking Status Due to the inaccuracy of self-report tobacco consumption, biomarkers are used as objective indictors of tobacco consumption, secondhand smoke exposure, and smoking status. CO and cotinine are the most widely used tobacco consumption biomarkers. Here we discuss their strengths and limitations. CO is a by-product of tobacco combustion and can be readily measured in smokers at a low cost (SRNT Subcommittee on Biochemical Verification 2002; Jatlow et al. 2008). CO is a reasonable tobacco consumption biomarker in heavy smokers but has significant limitations in light/infrequent smokers due to its half-life and specificity. In humans, CO has a relatively short half-life (1 to 4 hours depending on the level of physical activity) and can come from sources other than tobacco exposure (SRNT Subcommittee on Biochemical Verification 2002). Detectable levels of CO can be obtained from environmental sources (such as the exhaust from burning fossil fuel) as well as from endogenous formation of CO via the metabolism of heme (SRNT Subcommittee on Biochemical Verification 2002). As a result, CO s signal to noise ratio in light/infrequent smokers is small as they do not smoke frequently enough to generate CO levels above background levels. This is supported by the observation that non-smokers living in major urban centers have exhaled CO levels of up to 7 ppm (Jones et al. 2006; Scherer 2006), yet 42% of African American light/infrequent smokers have exhaled CO levels below 10 ppm (Ho et al. 2009). The short half-life and low specificity also limit CO s ability to verify smoking status in light/infrequent smokers. Together, these data suggest that CO is not a useful exposure index of tobacco consumption in light/infrequent smokers. Cotinine is the major metabolite of nicotine and can be detected in various biological fluids (e.g. plasma, urine and saliva) in smokers. Cotinine has good specificity toward tobacco and correlates with nicotine intake (Rickert et al. 1981; Benowitz et al. 1983). Cotinine has a long half-life (12-16 hours), which increases it utility in light/infrequent smokers. However, as illustrated by Chapter 2, steady state plasma cotinine levels can give a biased estimation of tobacco consumption; differing CYP2A6 activity can result in more than a 25% bias in cotinine levels. In addition, some very commonly used immunoassays overestimate cotinine concentrations due to cross-reactivity with other nicotine metabolites (Schepers et al. 1988; 139

161 Anderson et al. 1991; Zuccaro et al. 1997). This makes comparisons between studies with different analytical methods very difficult. Despite its shortcomings as a biomarker of tobacco consumption, cotinine is very useful for verifying smoking status. In heavy smokers, cotinine has 96%-97% sensitivity and % specificity for verifying smoking status (SRNT Subcommittee on Biochemical Verification 2002). Cotinine is also a better indictor of smoking status in light/infrequent smokers due to its long half-life (Ho et al. 2009). For an initial cotinine level of 200 ng/ml (a level typically observed in light/infrequent smokers), it would take four half-lives (roughly 3 days) for the cotinine level to decline below the 14 ng/ml cutoff. Therefore, cotinine levels below 14 ng/ml are indicative of smoking abstinence for at least 2 or 3 days. In agreement with this hypothesis, only 3.1% of ad libitum African American light/infrequent smokers had cotinine levels below the 14 ng/ml cutoff, suggesting cotinine has good specificity in light/infrequent smokers (Benowitz et al. 2009). Overall, cotinine is better than CO and self-report measures for verifying smoking status in both heavy and light/infrequent smokers Limitations of TNE as a Biomarker of Tobacco Consumption While we argued that TNE is a better biomarker of tobacco consumption compared to self-report CPD, CO and cotinine in the thesis chapters, TNE also has some limitations. The first limitation is the cost and accessibility. There are significant analytical costs associated with the measurement of nicotine and 5-8 of its metabolites. Some of the metabolites exist in relatively low concentrations, warranting the use of LC/MS systems. This requirement for LC/MS analysis can limit the utility of TNE (due to the high cost). The second limitation of spot urinary TNE is the need for creatinine adjustment. Although TNE measurement in a 24 hour-urine sample correlates highly with tobacco consumption, spot urinary TNE is generally used for convenience with creatinine adjustments to correct for variable dilution among spot samples. Traditionally, this approach has been used in populations without much diversity and has worked well. However, creatinine adjustments may introduce significant bias in studies with multiple demographic groups. In an analysis of more than individuals, age, sex, race, and body mass index were all significant predictors of urinary creatinine levels (Barr et al. 2005). African Americans had 5-10% higher urinary creatinine levels compared with Caucasians and males had ~20% higher urinary creatinine levels compared with females. Therefore, urinary creatinine 140

162 levels (and perhaps creatinine adjusted TNE) are best compared among individuals within similar demographic groups. However, it is worth noting that, in a predominantly Caucasian study which administered known doses of nicotine daily for 5 days, the creatinine adjusted urinary TNE predicted the nicotine dose better than plasma cotinine (creatinine adjusted TNE r=0.8, plasma cotinine r=0.75)(benowitz et al. 2010). In the same study, creatinine adjusted TNE also predicted the nicotine dose better than unadjusted TNE (Benowitz et al. 2010). These results suggest that the bias introduced by creatinine adjustments are smaller than the bias introduced by variable dilution of the urine. Even with the creatinine bias, TNE was a better biomarker than cotinine. Analytically, the systematic differences in creatinine can be partially corrected using a multiple regression analysis with urinary creatinine added as an independent variable. This approach allows urinary TNE concentration to be appropriately adjusted for creatinine, and statistical inference of other predictors in the model is independent of creatinine levels (Barr et al. 2005) Sum of Plasma COT and 3HC as A Biomarker of Tobacco Consumption The current gold standard for measuring nicotine dose is the molar sum of all nicotine metabolites in a 24 hour-urine collection (i.e. TNE in 24 hour urine) (Benowitz et al. 2010; Wang et al. 2011). However, due to the practical difficulties of collecting a 24 hour-urine sample, plasma measurements may be a more practical approach. Additionally, plasma volumes are relatively constant between people. Therefore, there is no need for dilution adjustments, which is commonly conducted on urine samples by adjusting creatinine. Nicotine, cotinine and 3HC can be readily measured in the plasma (Benowitz et al. 1993; Benowitz et al. 2001; Hukkanen et al. 2005). In a regular smoker, plasma nicotine concentrations are generally lower than 10 ng/ml and the sum of cotinine and 3HC is higher than 300 ng/ml (Zhu et al. 2013). Plasma nicotine levels also tend to fluctuate (reflecting peak to trough variation) in smokers during the day due to its short half-life and frequent administration. Therefore, we propose to use the plasma sum of cotinine and 3HC (the addition of 3HC compensates for the effect of CYP2A6 activity on cotinine clearance) as a measurement of nicotine dose in smokers. The plasma sum of cotinine and 3HC has limited influenced by variation in CYP2A6 activity and is completely independent of variation in urinary creatinine levels. In studies that evaluated the ability of 141

163 various biomarkers to estimate nicotine dose, the sum of plasma cotinine and plasma 3HC correlated with nicotine dose better than plasma cotinine alone (Malaiyandi et al. 2006; Benowitz et al. 2010). This correlation was not significantly influenced by the time of sampling (Benowitz et al. 2010). These observations suggest that the sum of plasma cotinine and 3HC may have some utility as a tobacco consumption biomarker. However, some validation research, such as the characterization of the role of variation in rates of glucuronidation, is required before plasma cotinine plus 3HC can be recommended as a biomarker of tobacco consumption Limitations of NNAL: Variability in the Metabolism Urinary total NNAL is often used as an indictor of TSNA exposure in tobacco users. Urinary total NNAL is associated with lung cancer risk in smokers and leukoplakia risk in smokeless tobacco users (Kresty et al. 1996; Yuan et al. 2011). Like other biomarkers of tobacco consumption, urinary total NNAL has its limitations (Maser et al. 1996; Maser 1998). It is known that urinary total NNAL levels increase with CPD, but with considerable variability (Joseph et al. 2005; Lubin et al. 2007). Although some of this variability can be explained by the variation in puff volume and depth of inhalation, individual variability in NNK metabolism (NNAL is a metabolite of NNK) could also play a role. It has been demonstrated that freshly isolated human non-tumor lung tissue exhibited a wide range of variability in the metabolism of NNK to NNAL, which was likely due to genetic variation (Smith et al. 1999). Gene variants in HSD11B1 (encoding for 11- β-hydroxylsteroid dehydrogenase type 1, which converts NNK to R- NNAL) and AKR1C4 (encoding for an aldo-keto-reductase, which converts NNK to S-NNAL) were significantly associated with urinary total NNAL levels (Ter-Minassian et al. 2012). Thus, genetic variation in NNK metabolism could alter NNAL levels, decreasing the ability of NNAL to reflect NNK exposure. Diet and xenobiotic exposure may also influence urinary total NNAL. For example, watercress consumption inhibits CYP1A2 mediated NNK α-hydroxylation pathway, thereby promoting the conversion of NNK to NNAL (Hecht et al. 1995). In contrast, smokers who were exposed to indole-3-carbinol had lower urinary total NNAL levels, which was likely due to the induction of CYP1A2 which reduces NNK levels and subsequent the metabolism to NNAL (Taioli et al. 1997). Taken together, these data suggest that NNAL levels are altered by genetic variation in NNK metabolism, and may not always reflect the entirety of TSNA exposure. 142

164 Ultimately, the selection of tobacco biomarkers should be determined by the study objectives. Table 14 summarized the strengths and limitations of common tobacco biomarkers and gave biomarker recommendations. Base on the findings of this thesis, TNE is recommended for evaluating tobacco consumption in both frequent and infrequent smokers, while cotinine is recommended for verifying smoking status in both frequent and infrequent smokers. A proper selection of tobacco biomarkers will likely enhance our understanding of smoking behaviors and the risk associated with tobacco consumption. 5.2 What Did the Biomarkers Tell Us About Smoking Behaviors in Light Smokers and Smokeless Tobacco Users? Light Smokers Had Similar Total Nicotine Intake to that in Heavy Smokers Previous epidemiological studies in light smokers commonly did not include any biomarker measurements and relied on self-report tobacco consumption measures. One of the unique aspects of the publications in this thesis was the inclusion of multiple biomarker measurements. The biomarker levels suggested that, despite reporting fewer CPD, light smokers had very similar total nicotine intake to those in heavy smokers. A TNE level of approximately 60 nmol/mg Cre was observed in Alaska Native light smokers. This was comparable to the 63 nmol/mg Cre observed in Caucasian heavy smokers (Fig. 34)(Le Marchand et al. 2008; Benowitz et al. 2011). Similarly, the TNE level observed in African American light smokers was approximately 58 nmol/mg Cre (Zhu et al., unpublished observations), which suggests that the observation within Alaska Native light smokers may be generalizable to other populations of light smokers as well. Together, the biomarker data suggest that, although classified as light smokers according to self-report CPD, these Alaska Native and African American light smokers had very similar nicotine intake compared to Caucasian heavy smokers. Therefore, classifying smokers according to self-report CPD may not generate an accurate picture of their tobacco consumption and tobacco related disease risk. The similar total nicotine intake observed in light and heavy smokers suggests that light smokers extract a greater amount of nicotine per cigarette than heavy smokers (perhaps by either inhaling more deeply or smoking a greater proportion of the cigarette). Hence, they would be described 143

165 more appropriately as infrequent smokers rather than light smokers. There are a few possible explanations for the distinct smoking behavior observed in these light and infrequent smokers. A Nicotine Intake B Cigarettes per Day C Nicotine Intake Per Cigarette TNE Mean ± 95% CI (nmol/mg Cre) Cigarettes per Day Mean ± 95% CI TNE per Cig. Mean ± 95% CI (nmol/mg Cre) Caucasian Heavy Smokers Alaska Native Light Smokers African American Light Smokers 0 Caucasian Heavy Smokers Alaska Native Light Smokers African American Light Smokers 0 Caucasian Heavy Smokers Alaska Native Light Smokers African American Light Smokers Figure 34 Nicotine intake in light smokers vs. heavy smokers. A). Alaska Native and African American light smokers had similar nicotine intake (as indicated by TNE) as found in Caucasian heavy smokers. B). Alaska Native and African American light smokers had lower daily cigarette consumption compared to Caucasian heavy smokers. C). Alaska Native and African American light smokers extract more nicotine per cigarette than Caucasian heavy smokers do. The Caucasian tobacco consumption data were obtained from Benowitz et al., 2011 (Benowitz et al. 2011). The African American tobacco consumption data were from unpublished observation from Zhu et al. The study was described by Zhu et al., TNE=Total nicotine equivalents. The first possibility is that light/infrequent smokers have fewer smoking opportunities than heavy smokers do. It is known that smokers with fewer smoking opportunities, such as those who work in buildings with an indoor smoking ban, tend to take more puffs per cigarette to extract more nicotine (Chapman et al. 1997). Thus, they compensate for the fewer smoking opportunities by increasing the amount of nicotine intake per cigarette. In agreement, we observed that the Alaska Native smokers who cannot smoke inside of their homes tend to extract more nicotine per cigarette (TNE=11.1 nmol/mg Cre/cig.) than smokers who can smoke inside of their homes (TNE=6.8 nmol/mg Cre/cig.) (Data compiled from Zhu et al. 2013)(Zhu et al. 2013). 144

166 Together, these observations suggest that the low CPD and high nicotine intake per cigarette in light/infrequent smokers could be a result of fewer smoking opportunities. However, it is unlikely that this possibility entirely accounts for the higher nicotine intake per cigarette in Alaska Native light/infrequent smokers since many participants were recruited from fishing villages and likely work outdoors for the fishing industry. Another possible explanation for the high nicotine intake per cigarette is that the economic status of light/infrequent smokers dictates their cigarette consumption. Many of the light/infrequent smoking populations, such as Alaska Native peoples and African Americans experience substantial socioeconomic disparities. For example, Alaska Native peoples and African Americans commonly have lower educational attainment and lower median household income compared to Caucasians in the United States (U.S. Bureau of the Census 2004; U.S. Bureau of the Census 2005; Institute of Social and Economic Research University of Alaska Anchorage 2009). Since socioeconomic status is an important determinant of smoking behaviors (Novotny et al. 1988; Townsend et al. 1994; Graham et al. 1999), it is possible that the low CPD and high nicotine intake per cigarette observed in light/infrequent smokers is due to their inability to afford more cigarettes in comparison to Caucasian smokers. Unfortunately, this hypothesis could not be directly tested in our Alaska Native study as income levels were not collected in the baseline survey. However, in a study of African American light/infrequent smokers that was described by the manuscript attached within Appendix B, the amount of nicotine intake per cigarette did not significantly differ between different household income levels (Zhu et al., unpublished observation). Furthermore, light/infrequent smoking is also prevalent in Asian Americans, who have higher than average household income in the United States (U.S. Bureau of the Census 2004; U.S. Bureau of the Census 2005). Therefore, lower economic status cannot fully account for the high nicotine intake per cigarette observed in light/infrequent smoking populations. Ultimately, a large study (such as the southern community cohort study (Signorello et al. 2005)) that compares nicotine intake per cigarette between light and heavy smokers (i.e. less than 10 vs. more than 10 CPD) could give a precise estimation of the contribution of economic status to the distinct smoking behaviors in light/infrequent smokers. Cultural and societal influences may be another possible explanation for the high nicotine intake per cigarette observed in light/infrequent smokers. For example, Asians living in China and 145

167 Japan tend to consume more CPD than Asians living in the United States, as smoking is more socially accepted and even encouraged for males in China and Japan (Giovino et al. 2012). Likewise, individuals of African descent who were born in the Caribbean or Africa are less likely to be ever or current smokers than those born in the United States (Taylor et al. 1997; King et al. 2000; Bennett et al. 2008). Furthermore, strong identification with the African American culture, including growing up in predominantly African American communities, is a strong predictor of being a current smoker (Klonoff et al. 1994; Klonoff et al. 1996; Klonoff et al. 1999). It is possible that growing up, initiating smoking and progressing to be a smoker in a light smoking environment can have a substantial influence on one s smoking behaviors making him/her more likely to smoke fewer cigarettes but extract a higher amount of nicotine per cigarette. Therefore, cultural influences may play an important role on smoking behaviors than biological differences between light and heavy smoking populations (Shadel et al. 2000). Lastly, there are genetic factors that may enable light/infrequent smokers to extract more nicotine per cigarette. As described in the introduction, light/infrequent smokers eliminate nicotine at similar rates compared to heavy smokers and show similar cardiovascular responses to cigarette smoking (Shiffman et al. 1990; Brauer et al. 1996). Thus, variations in nicotine metabolism or nachrs are unlikely to explain the difference in nicotine intake per cigarette observed between light and heavy smokers. An alternative possible explanation is genetic variation in the sensitivity of aversive chemosensory receptors to nicotine during smoking. Nicotine activates the chemosensory TRPA1 channel in the respiratory epithelium and causes irritation and in some cases a strong burning sensation (Thuerauf et al. 2006; Talavera et al. 2009). Genetic variants in TRPA1 may alter the response of the TRPA1 channel toward nicotine, allowing some individuals to intake high levels of nicotine without experiencing as much irritation and burning sensations. Interestingly, a non-synonymous SNP located in exon 1 of TRPA1 gene, rs , is found at a higher allele frequency in African Americans compared to Caucasians (Uhl et al. 2011). If rs results in lower functional activation of TRPA1 channel by nicotine, it is possible that this would allow a greater proportion of African American smokers to extract more nicotine per cigarette without experiencing as many aversive effects. In agreement with the idea that variation in nicotine s chemosensory response can alter nicotine intake per cigarette, African American light/infrequent smokers prefer to smoke cigarettes containing menthol, which is an antagonist of TRPA1 channel (King et al. 2000; Landrine et al. 2005; Allen et al. 2007; Talavera 146

168 et al. 2009). It is possible that menthol blocks the irritations associated with nicotine inhalation and promotes greater nicotine intake per cigarette in African American light/infrequent smokers. However, it is worth noting that light smoking can also be prevalent in populations who do not use menthol cigarettes. Currently, studies have yielded inconsistent results when comparing the amount of nicotine intake in menthol smokers and non-menthol smokers (Clark et al. 1996; Heck 2009; Muscat et al. 2009). This could be due to the limitations of the biomarker measurements used. Thus, further studies investigating the association between TRPA1 gene variants and tobacco consumption are needed to clarify the role of TRPA1 channel and menthol in determining nicotine intake in smokers Smokeless Tobacco Users Are Exposed to High Levels of TSNA: An Undesirable Harm Reduction Approach Our biomarker data revealed that smokeless tobacco users are exposed to high levels of carcinogenic TSNAs (Chapter 2), which suggests that smokeless tobacco has minimal utility as a harm reduction strategy in smokers in comparison to smoking cessation. In recent years, the idea that smokeless tobacco products could be used as a harm reduction approach has been actively debated. The benefits of smokeless tobacco products are largely supported by data from Sweden where a significant reduction in tobacco-related mortality and morbidity has been attributed to the extensive replacement of cigarette smoking with oral snus (a kind of smokeless tobacco) (Vainio et al. 2003; Hatsukami et al. 2004). The use of smokeless tobacco products has two major benefits. First, the lack of combustion eliminated users exposure to toxic combustion products from cigarettes such as carbon monoxide, acrolein and PAHs (Hatsukami et al. 2004). The low exposure to toxic combustion products could reduce smokeless tobacco users risk of developing pulmonary diseases such as COPD, emphysema and lung cancer. Second, data from several Swedish cohorts suggested the use of oral snus could promote smoking cessation (Tillgren et al. 1996; Lindstrom et al. 2002; Lindstrom et al. 2002; Rodu et al. 2003), which would further reduce the risk of smoking related diseases. However, it is important to note that the smokeless tobacco products are cured differently in Sweden compared to those found in North America. This different production process results in very different TSNA levels (Hecht 2002). The levels of TSNA in popular American smokeless tobacco brands are 40 to 60 µg/g, which is 15 to 20 times higher than the 2.8 µg/g found in popular Swedish brands (cigarette 147

169 tobacco has 5-10 µg/g)(connolly et al. 1986; Brunnemann et al. 2002; Stepanov et al. 2012). In agreement with this idea, we observed that urinary NNAL level, a marker of TSNA exposure, was 4 times higher in smokeless tobacco users (who used North American brands of smokeless tobacco) compared with cigarette smokers (see Chapter1 and Fig. 35). Higher NNAL levels, a biomarker of TSNA exposure, have been associated with a higher risk of developing a number of smokeless tobacco related cancers including pancreatic, oral and esophageal cancers (Luo et al. 2007; Boffetta et al. 2008). Therefore, on the basis of NNAL levels alone, smokeless tobacco users in North American may not have a substantially lower risk for tobacco related cancers compared to smokers. A 1500 NNAL B 25 NNAL per nicotine intake Urinary NNAL Mean ± 95% CI (pmol/mg Cre) Urinary NNAL/TNE Mean ± 95% CI Cigarette Smokers Smokeless Tobacco Users 0 Cigarette Smokers Smokeless Tobacco Users Figure 35 Smokeless tobacco users are exposed to higher levels of NNAL than smokers. A). Smokeless tobacco users are exposed to higher levels of TSNA than smokers. B). After normalizing for nicotine intake (i.e. total nicotine equivalents), smokeless tobacco users are exposed to higher levels of TSNA than smokers. 148

170 NNAL=4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol; TSNA=tobacco specific nitrosamines; TNE=Total nicotine equivalents Overall, our results suggest that the use of smokeless tobacco products as harm reduction alternatives to smoking in North America would require additional proof of concept studies. Although smokeless tobacco use can have significant public health benefits as the lack of combustion eliminates the generation of secondhand smoke, it can also act as a gateway product for adolescents to cigarette smoking and increase tobacco consumption by allowing tobacco use in environments where cigarette smoking would normally be restricted Iqmik Delivers High Levels of Nicotine and Low Levels of TSNA In agreement with data from Caucasian commercial smokeless tobacco users (Wennmalm et al. 1991; Hecht et al. 2007), Alaska Native commercial smokeless tobacco users have similar levels of nicotine intake as Alaska Native smokers. In contrast, the nicotine intake (TNE level) in iqmik users was strikingly higher compared to the nicotine intake in smokers. Likewise, a previous study found that pregnant iqmik users had higher cotinine levels compared to pregnant smokers (Hurt et al. 2005). Since iqmik and commercial smokeless tobacco have similar nicotine content and both have reported similar chews per day (Benowitz et al. 2012), the higher nicotine intake observed in the iqmik users is likely the result of greater nicotine absorption. As discussed in the introduction, a basic chemical environment promotes nicotine absorption. Iqmik has a highly basic ph (ph=~11) whereas commercial smokeless tobacco s ph is in the range of 5-8 (Renner et al. 2005). At iqmik s ph, about 99.9% of nicotine is unionized which can be rapidly absorbed by the buccal mucosa, resulting in high nicotine intake. Interestingly, iqmik users had lower TNSA exposure compared to smokers and commercial smokeless tobacco users (Benowitz et al. 2012). This was consistent with the lower TSNA levels observed with this product Future Research: Modifications to Existing Tobacco Dependence Scales The FTND is the most commonly used scale to assess tobacco dependence in nicotine and tobacco research. The FTND was developed in Caucasian heavy smokers; it measures the level of physical dependence to nicotine and the willingness to obtain nicotine to relieve or avoid withdrawal symptoms (Piper et al. 2008). One of the most importance characteristics of the FTND is its strong predictive ability of smoking cessation in Caucasian heavy smokers (Baker et 149

171 al. 2007). Light/infrequent smokers generally score very low (~3) on the FTND scale (Cox et al. 2012; Renner et al. 2013), which would suggest that they are not as dependent to nicotine and should have a higher rate of smoking cessation. However, clinical trial data suggest that light/infrequent smokers have just as much difficulty quitting as heavy smokers (Ahluwalia et al. 2002; Ahluwalia et al. 2006; Cox et al. 2012). When recounting their most recent quit attempts, light/infrequent smokers did not have longer abstinence periods before relapsing compared to heavy smokers (Choi et al. 2004). Furthermore, the unaided cessation rates observed in light/infrequent smokers were very similar to the unaided cessation rates observed in heavy smokers (Ahluwalia et al. 2002; Ahluwalia et al. 2006; Cox et al. 2012). These data suggest that the light/infrequent smokers are still highly dependent on nicotine and current tobacco dependence scales may not accurately reflect the level of nicotine dependence in light smokers. A major issue with dependence scales in light/infrequent smokers is that the scales are heavily weighted toward self-report CPD. As we have shown previously, self-report CPD does not accurately reflect nicotine intake in light/infrequent smokers. A previous study has suggested a rescaling of the self-report CPD can better capture the level of tobacco consumption in light/infrequent smokers (Mwenifumbo et al. 2011). However, the rescaled FTND was no more predictive of smoking cessation in light/infrequent smokers than the original FTND (Fig. 36A&B). It is possible that these scales can still capture some other aspects of nicotine dependence rather than predicting smoking cessation. Here we propose modifications to the FTND to incorporate biomarker data. Table 15 provides an example of the type of modifications that could be made to the FTND to better predict smoking cessation. Preliminary analyses of two clinical trials in light/infrequent smokers suggested that the modified FTND with biomarker data was more predictive of smoking cessation outcomes than the original FTND (Fig. 36C&D, P<0.0001, Zhu et al., unpublished observations). The precise weighting of the points will need to be determined to maximize predictability. 150

172 Table 15 An example of potential modifications to the FTND to incorporate biomarker data. The point system represents broad estimations rather than precise regression classifications. *This question replaced How many cigarettes per day do you smoke?. TNE can also be used for this question. <25nmol/mg Cre = 0; 26-50nmol/mg Cre = 1; 51-75nmol/mg Cre = 2; >76nmol/mg Cre = 3. **This question replaced Do you smoke if you are so ill that you are in bed most of the day? and Do you smoke more frequently during the first hours after waking than you do during the rest of the day?. Points How soon after you wake up do you smoke your first cigarette? Within 5 min min min 1 After 60 min 0 Do you find it difficult to refrain from smoking in places where it is forbidden e.g., in church, at the library, in cinema Yes 1 No 0 Which cigarette would you hate most to give up? The first one in the morning 1 All others 0 *What is the baseline plasma cotinine level (in ng/ml by LC/MS or HPLC method)? **Do you smoke mentholated cigarettes? Yes 2 No 0 151

173 A B C D % Abstinence 30 OR=0.64 P= n=344 FTND n= Rescaling CPD 30 OR=0.61 P=0.07 n=330 n=211 Modified FTND with Cotinine OR=0.40 P< n=273 n= Modified FTND with TNE n=226 OR=0.48 P<0.01 n=196 0 Low High FTND 0 Low High Rescaled FTND 0 Low High 0 Low High Modified FTND Modified FTND Figure 36 Modified FTND with biomarker data strongly predicted smoking cessation. A). The ability of original FTND to predict smoking cessation in African American light/infrequent smokers. Note that all the light/infrequent smokers will score zero for the question How many cigarettes per day do you smoke? in the traditional FTND. B). The ability of the rescaled FTND to predict smoking cessation in African American light smokers (Mwenifumbo et al. 2011). C). The ability of the modified FTND with plasma cotinine biomarker data to predict smoking cessation in African American light/infrequent smokers. D). The ability of the modified FTND with TNE biomarker data to predict smoking cessation in African American light/infrequent smokers. Low vs. High FTND was classified using a median split. The Odds ratios (OR) used the low FTND group as the reference group. For example, a 0.4 OR indicated that the high FTND group had 0.4 times the odds of quitting compared to the low FTND group. 152

174 5.3 Genetics of Nicotine Dependence in Light Smokers and Smokeless Tobacco Users CYP2A Predicting Nicotine Clearance Using CYP2A6 Genotype and NMR Phenotype In Chapter 1 and 3, the association between CYP2A6 genotype and tobacco consumption was weaker than the association of NMR and tobacco consumption. Currently, both CYP2A6 genotype and phenotypic (using NMR) measurements, are used to estimate in vivo nicotine clearance. In this section, we discuss the limitations of using CYP2A6 genotype, or using NMR, to estimate CYP2A6 activity and nicotine clearance. There are a number of limitations of using CYP2A6 genotype to estimate in vivo nicotine clearance. First, many reduced function CYP2A6 alleles are rare (i.e. allele frequency 1.0%). Since the combined frequency of all these rare alleles is significant, selectively genotyping could reduce the statistical power in many racial/ethnic populations. Therefore, the comprehensive genotyping of these alleles requires significant time and cost. Secondly, it is often hard to accurately characterize the functional impact of rare alleles on nicotine clearance due to the limitations of the in vitro expression systems and the low number of individuals with these variants. This problem is not unique to CYP2A6; similar challenges have been reported with other xenobiotic metabolizing enzymes such as CYP2D6 (Kirchheiner 2008). The third limitation is that CYP2A6 genotype does not account for the influence of non-genetic factors on nicotine clearance (as described in the introduction). For example, the known effects of CYP2A6 genotype account for a small amount of the total variance in nicotine metabolism (Al Koudsi et al. 2010), suggesting that environmental factors (as well as unidentified genetic variants) also contribute to the variation in nicotine clearance. The limitations of using CYP2A6 genotype to predict nicotine clearance are generally solved by using NMR, as NMR can account for both genetic and environmental variability in nicotine metabolism. However, it is important to note that NMR has some limitations as well. First, NMR is technically a measure of cotinine clearance (i.e. the ratio of 3HC/COT). Although the NMR generally correlates highly with rates of nicotine clearance (Dempsey et al. 2004; Benowitz et al. 153

175 2006; Johnstone et al. 2006; Malaiyandi et al. 2006; Malaiyandi et al. 2006), it is possible that some CYP2A6 variants could alter the clearance of cotinine differently from the clearance of nicotine (and other substrates). Thus, it remains undetermined whether the NMR is a good indicator of the metabolic clearance of other CYP2A6 substrates such as tegafur and letrozole. Secondly, the steady state 3HC levels are determined by both the rate of 3HC formation and the rate of 3HC clearance. Thus, slow rates of 3HC clearance could increase plasma 3HC levels for a given cotinine level, resulting in higher NMRs compared to those with normal rates of 3HC clearance. This effect of variable 3HC clearance on NMR is not related to nicotine clearance or CYP2A6 activity and could reduce the clinical utility of NMR. Our recent analysis demonstrates that variation in 3HC glucuronidation, including that caused by UGT2B17 gene deletions, did not significantly alter NMR, and is therefore unlikely to affect the ability of NMR to predict nicotine clearance in smoking studies (Zhu et al. 2013). This study provides further support that NMR is a reliable indicator of CYP2A6 mediated nicotine clearance (Zhu et al. 2013) (Manuscript attached in Appendix D). Lastly, while NMR can be readily measured in smokers during ad libitum smoking in regular smokers, it is not possible to measure NMR without drug (nicotine or cotinine) administration in former or never smokers. Likewise, it cannot provide information about the pharmacogenetic role of CYP2A6 during tegafur and letrozole treatment in nonsmokers. Ultimately, the choice of CYP2A6 genotype or NMR is determined by the study population, the availability of biological specimens, and the study objectives. NMR should be used in studies that want to capture transient changes in nicotine clearance, such as from temporary exposure to inducers or inhibitors. In contrast, CYP2A6 genotype should be used to predict long-term nicotine clearance as it is not influenced by the transient effects of CYP2A6 inducers and inhibitors The Association between CYP2A6 Gene Variants and Tobacco Consumption in Light Smokers and Smokeless Tobacco Users This thesis also demonstrated that light/infrequent smokers titrate their nicotine intake according to their CYP2A6 activity. Previously, a number of studies have demonstrated that heavy smokers with slower CYP2A6 activity smoked fewer CPD (Schoedel et al. 2004; Wassenaar et al. 2011). However, this difference in CPD by CYP2A6 activity groups had not been observed in light 154

176 smoking populations such as African Americans (Ho et al. 2009). In this thesis, we demonstrated that the lack of association between CPD and CYP2A6 activity in light/infrequent smokers was due to their highly variable nicotine intake per cigarette. When TNE was used as a biomarker of tobacco consumption, we observed a 41% reduction in tobacco consumption (by TNE, but not with CPD) in individuals with slower CYP2A6 activity. This suggests that light/infrequent smokers with slower CYP2A6 activity reduced their nicotine intake per cigarette to compensate for the slower nicotine inactivation, possibly by taking smaller puff volumes as previously observed (Strasser et al. 2007). This thesis also demonstrates, for the first time, that smokeless tobacco users titrate their tobacco consumption according to their rates of nicotine metabolism. Interestingly, the magnitude of CYP2A6 s effect on tobacco consumption was larger in smokeless tobacco users when compared with tobacco smokers (54% reduction in TNE in smokeless tobacco users with slower CYP2A6 activity; 41% reduction in TNE in smokers with slower CYP2A6 activity). This may be a reflection of the slower nicotine absorption from smokeless tobacco, which could allow for a longer period of time for metabolism to occur thereby increasing the effect of differences in the rate of nicotine metabolism. Overall, the data presented in this thesis suggest that genetic variation in CYP2A6 influences tobacco consumption in light/infrequent smokers and smokeless tobacco users as previously observed in heavy smokers. Therefore, previously reported CYP2A6 genetic findings in heavy smokers were extended here to light/infrequent smokers and smokeless tobacco users CYP2A6 s Role in Determining Tobacco Related Disease Risks The findings of this thesis illustrate the dual roles (tobacco consumption and carcinogen activation) of CYP2A6 in influencing tobacco related carcinogen exposure. First, CYP2A6 genetic variants alter carcinogen exposure as the result of an alteration in tobacco consumption. In Chapter 1, we observed that the tobacco users with slower CYP2A6 activity had lower carcinogenic NNAL levels compared to the tobacco users with faster CYP2A6 activity, which was due to differences in tobacco consumption. These data suggest that the lower tobacco consumption observed in individuals with slower CYP2A6 activity reduces their risk of tobacco related diseases. 155

177 The second mechanism by which variation in CYP2A6 can modify tobacco related disease risk is through differential carcinogen metabolism. In Chapter 1, we observed higher NNN levels in smokers with slower CYP2A6 activity even after controlling for TNE. This suggests that NNN clearance was lower in individuals with slower CYP2A6 activity. Mechanistically, CYP2A6 is known to mediate the 5 -hydroxylation of NNN to genotoxic metabolites (Wong et al. 2005). Transfecting human CYP2A6 into a bacteria system resulted in a higher degree of mutagenesis upon NNN exposure (Kushida et al. 2000). Thus, we speculate that the slower CYP2A6 activity results in lower NNN 5 -hydroxylation, and more NNN was excreted in urine unmetabolized. Since bioactivation is required for NNN to exert its genotoxic effects, the reduced NNN bioactivation will reduce genotoxic metabolite formation and the risk of tobacco related cancers in individuals with slower CYP2A6 activity. This is supported by the human epidemiological evidence that CYP2A6 slow metabolizers exhibit a lower odds ratio of lung cancer, even when controlling for quantities smoked (Wassenaar et al. 2011). Overall, our findings indicate that individuals with slower CYP2A6 activity have lower tobacco consumption and lower carcinogen bioactivation compared to individuals with faster CYP2A6 activity. This could lead to lower carcinogenic reactive intermediate exposure and reduced tobacco related cancer risk (Wassenaar et al. 2011) CYP2A6 s Role in Determining Smoking Cessation Outcomes A number of clinical trials and epidemiological studies strongly suggest that genetic variants in xenobiotic metabolizing enzymes, such as CYP2A6, can significantly affect smoking cessation outcomes in heavy smokers (Lerman et al. 2006; Patterson et al. 2008). Due to the similar total nicotine intake between heavy and light smokers, these CYP2A6 pharmacogenetic findings are likely applicable to light/infrequent smokers as well. Smokers with slower CYP2A6 activity respond better to transdermal nicotine patch therapy than smokers with faster CYP2A6 activity (Lerman et al. 2006; Lerman et al. 2010). This finding suggests that smokers with slower CYP2A6 activity should be treated with nicotine patches (perhaps for an extended duration). In comparison, CYP2A6 activity does not alter the treatment response to bupropion (Patterson et al. 2008). Therefore smokers with faster CYP2A6 activity should be treated with bupropion rather than nicotine replacement therapy. Stratifications by additional genes may further improve the smoking cessation outcomes in smokers with faster CYP2A6 activity. Bupropion is metabolized 156

178 to hydroxybupropion by a genetically polymorphic enzyme CYP2B6. Animal studies suggest that hydroxybupropion is pharmacologically active. We demonstrated, in a real-world outpatient clinical trial, that higher hydroxybupropion levels, but not bupropion levels, increased smokingcessation rates (Zhu et al. 2012). Genetic variation in CYP2B6 was identified as a significant source of variation in hydroxybupropion levels (Zhu et al. 2012; Benowitz et al. 2013). The findings indicate that personalized/stratified bupropion therapy based on hydroxybupropion levels or CYP2B6 genotype may substantially improve bupropion s therapeutic efficacy (Manuscripts attached in Appendix B). Ultimately, we would recommend testing CYP2B6 genotypes in individuals with faster CYP2A6 activity, and treat individuals with slower CYP2B6 activity with varenicline (another non-nicotine smoking cessation treatment) and individuals with faster CYP2B6 activity with bupropion. This could further improve smoking cessation outcomes CHRNA5-A3-B The Association between CHRNA5-A3-B4 and Tobacco Consumption in Light Smokers In Chapter 3, we presented novel findings with regards to CHRNA5-A3-B4 variants and nicotine intake in light/infrequent smokers. The quantitative aspects of our CHRNA5-A3-B4 findings have been discussed in the discussion section of Chapter 3. Here we focus on the functional role of CHRNA5-A3-B4 gene variants and the implications of our findings The Functional Consequences of CHRNA5-A3-B4 Variants Despite extensive evidence for the association between CHRNA5-A3-B4 variants and smoking behaviors, there is very little known about the molecular impact of these variants on nachr function. Most of the research has focused on the α5 subunit, which mediates nicotine s aversive effects in the medial habenula (Fowler et al. 2011). It has been hypothesized that the CHRNA5- A3-B4 variants associated with higher nicotine intake reduce the function of α5-containing nachr, resulting in a deficiency of α5 mediated aversive signaling particularly at high nicotine doses. This increases the ratio of nicotine reward to the aversive effects of nicotine at high nicotine doses. Rs is a nonsynonymous variant in exon 5 of CHRNA5 which results in an amino acid change of aspartic acid to asparagine at codon 398. The A allele of rs has a 38% allele frequency in Caucasians, but is rare in African Americans and Asians 157

179 (International Hapmap Project). The variant A allele of rs (encoding for asparagine) is associated with higher nicotine intake in many racial populations including Alaska Native peoples (Saccone et al. 2009; Wassenaar et al. 2011; Chen et al. 2012; Zhu et al. 2013). Bioinformatically, rs was predicted to be benign based on the chemical effects of the amino acid substitution and the evolutionary conservation of the surrounding amino acid sequence (genetics.bwh.harvard.edu/pph2). However, in vitro functional characterization suggests that this variant can alter α5 receptor function both in terms of receptor permeability and receptor desensitization. For instance, when human α5 nachr subunits with either the wildtype (398D, aspartic acid) or the variant (398N, asparagine) allele were expressed in Xenopus oocytes, the 398N allele resulted in lower Ca 2+ permeability in response to 10 µm acetylcholine when α4 and β2 were used as concatemers, but not when the α5 subunit was combined with α3 (Kuryatov et al. 2011). These observations were replicated in HEK293T cells co-expressing human α5, α4 and β2 subunits (Bierut et al. 2008). In addition to modulating nachr permeability, rs can also influence the desensitization of α5 containing nachr. The variant allele (398N) desensitized much faster after exposure to 3 µm acetylcholine than the wild-type allele when α4 and β2 were used as concatemers in Xenopus oocytes (Kuryatov et al. 2011). Again, this was not observed when the α3 subunits were expressed as concatemers. Together, the lower Ca 2+ permeability and faster desensitization suggested that the variant A allele (398N) of rs may increase nicotine intake by reducing (α4β2) 2 α5 nachr function, resulting in lower nicotine associated aversive effects. This hypothesis suggested that a positive allosteric (i.e. increase (α4β2) 2 α5 function) modulator at (α4β2) 2 α5 function may have some utility in reducing nicotine consumption and possibly promoting smoking cessation. In comparison to rs , less is known about the functional consequences of rs which was significantly associated with tobacco consumption in Chapter 3. Rs is not in linkage disequilibrium with rs in Caucasians (Chen et al. 2012). This lack of linkage disequilibrium is also observed in Alaska Native individuals (Chapter 3). Hence, it is unlikely that the association between rs and nicotine intake is mediated by the aspartic acid to asparagine amino acid substitution of rs There is some evidence that rs is associated with decreased CHRNA5 mrna expression. In Caucasians, rs is in linkage disequilibrium with rs (International Hapmap Project). The C allele of rs (which is in linkage disequilibrium with the risk A allele of rs578776) was significantly 158

180 associated with a 40% reduction in CHRNA5 mrna expression in postmortem brain (Wang et al. 2009; Saccone et al. 2010; Chen et al. 2012). This finding suggests that the A allele of rs may be associated with lower CHRNA5 expression, which would result in lower aversive effects in response to nicotine and enhanced nicotine intake. Due to the limited number of functional studies, it is difficult to interpret the neurobiology underlying the associations between genetic variation in CHRNA5-A3-B4 and tobacco consumption. Future studies in the CHRNA5-A3-B4 field should focus on identifying and functionally characterizing the causal variants (which are responsible for the altered function) that are in linkage with the tag SNPs. For example, it is unlikely that intronic variants like rs and rs directly alter CHRNA5 mrna transcription or stability. Thus, sequencing individuals with the variant allele of rs or rs may lead to the identification of novel promoter variants that are responsible for the altered CHRNA5 mrna levels. These findings could be followed up with bioinformatic binding site simulation, in vitro expression studies as well as ex vivo studies. This information will enhance our understanding of the molecular mechanism of nicotine addiction, allowing for the optimization and development of effective smoking cessation treatments Implications: Is the Association Between CHRNA5-A3-B4 Variants and Lung Cancer Directly Mediated by Altered Tobacco Consumption? As described in the introduction, the mechanism responsible for the association between CHRNA5-A3-B4 and lung cancer risk has been debated since the initial genome-wide association studies were conducted (Hung et al. 2008; Thorgeirsson et al. 2008; Consortium 2010; Liu et al. 2010; Thorgeirsson et al. 2010). While some publications argue the association between CHRNA5-A3-B4 gene variants and lung cancer risk is exclusively the result of altered tobacco consumption, others believe that CHRNA5-A3-B4 can directly contribute to lung carcinogenesis by altering cell migration and survival. The strongest evidence suggesting that the association between CHRNA5-A3-B4 gene variants and lung cancer risk is exclusively mediated by tobacco consumption is from the association between CHRNA5-A3-B4 gene variants and plasma cotinine levels. Munafò et al. reported that 159

181 each risk allele of rs was associated with a 24 ng/ml increase in plasma cotinine levels, which completely accounted for the 1.3 times higher lung cancer risk associated with rs (Munafo et al. 2012). However, as we have demonstrated in Chapter 2, cotinine levels often give a biased picture of tobacco consumption. There could be a 25% variation in plasma cotinine levels following the same tobacco and tobacco-derived carcinogen exposure depending on CYP2A6 activity. Therefore, it is hard to interpret cotinine data without considering CYP2A6 activity. Studies using TNE (which is less dependent on individual differences in nicotine metabolism) or NNAL (which is more directly involved in the carcinogenic process) will likely enhance our understanding of the contribution of tobacco consumption to the association CHRNA5-A3-B4 and lung cancer risk. The effect size comparisons of Chapter 3 provide some indirect evidence that the association between CHRNA5-A3-B4 and lung cancer risk is not entirely mediated by tobacco consumption. For example, variation in CYP2A6 activity has a bigger effect on tobacco consumption than either rs or rs in Alaska Native tobacco users, which is consistent with previous observations in Caucasian heavy smokers (Wassenaar et al. 2011). Slower CYP2A6 activity results in a 40% reduction in tobacco consumption, whereas CHRNA5-A3-B4 variants rs and rs result in 30% and 20% reduction in tobacco consumption respectively. This is interesting because these CHRNA5-A3-B4 variants have a bigger impact on lung cancer risk than CYP2A6 (Wassenaar et al. 2011). This suggests the possibility that CHRNA5-A3-B4 variants have additional effects on lung carcinogenesis beyond altering tobacco consumption. This hypothesis is supported by data from never smokers. In a large study of 3500 lung cancer cases and 3300 controls in China, the effect of CHRNA5-A3-B4 variants on lung cancer were very similar among never and current smokers (OR=1.44 in never smokers and 1.42 in current smokers)(wu et al. 2009). Similar effects of CHRNA5-A3-B4 on lung cancer risk among the never smokers and current smokers were also observed in the Japanese population (Shiraishi et al. 2009). Together, these data suggested that CHRNA5-A3-B4 variants could play a direct role in lung carcinogenesis since they also affect lung cancer risk in never smokers who do not alter their nitrosamine exposure by altering tobacco consumption. CHRNA5-A3-B4 variants could directly contribute to lung carcinogenesis by two mechanisms. Firstly, α5 and α3 containing nachrs, such as α3α5β2 heteropentamers, are highly expressed at 160

182 the wound edge of the bronchial mucosa injured by inhaling toxic substances and play an important role during wound repair (Grando 2006; Tournier et al. 2006; Schuller 2009). Polymorphisms resulting in low cell motility may lead to more persistent mucosal damage and inflammation, which could make mucosal cells more susceptible to precursor lesions. Secondly, CHRNA5-A3-B4 variants may modulate cancer-cell survival, invasion and metastasis. For example, CHRNA3 gene is systematically hypermethylated and down-regulated in lung cancers, and overexpression of CHRNA3 in lung cancer cells results in apoptosis, suggesting that lower CHRNA3 function provides cancer cells with a survival advantage (Lam et al. 2007; Paliwal et al. 2010). Currently, it is unclear how CHRNA5-A3-B4 variants affect these processes at the molecular level. Nevertheless, these data suggest that there is a biological role for nachrs in lung carcinogenesis, and it is likely that the association between CHRNA5-A3-B4 variants and lung cancer is mediated by both tobacco consumption and altered cell survival and signaling in the lungs Implications for Smoking Cessation In contrast to the consistent associations between CHRNA5-A3-B4 variants and tobacco consumption, the pharmacogenetic impact of CHRNA5-A3-B4 variants on smoking cessation have not been consistently reported. A number of genome-wide association studies have attempted to determine the genetic and pharmacogenetic contribution to smoking cessation (Uhl et al. 2007; Uhl et al. 2008; Uhl et al. 2010). However, none of those studies observed significant associations between CHRNA5-A3-B4 variants and smoking cessation. In agreement with the genome-wide association studies, candidate gene studies in German and Korean populations also revealed no association between CHRNA5-A3-B4 gene variants and smoking cessation (Breitling et al. 2010; Li et al. 2010). Recently, more focused candidate gene studies (with more comprehensive CHRNA5-A3-B4 SNP genotyping) reported a few associations between CHRNA5-A3-B4 variants and smoking cessation (Munafo et al. 2011; Chen et al. 2012; Bergen et al. 2013). However, it is not clear whether the influence of CHRNA5-A3-B4 gene variants on smoking cessation is independent of the type of pharmacological treatments (i.e. cessation in general, or just a particular pharmacological therapy)(munafo et al. 2011; Chen et al. 2012; Bergen et al. 2013). Furthermore, one important caveat when comparing these pharmacogenetic smoking cessation studies is that CHRNA5-A3-B4 risk alleles alter tobacco consumption and 161

183 FTND in smokers, but not all studies accounted for this. Higher CPD or FTND has been associated with increased difficulty in quitting (Dale et al. 2001; Berrettini et al. 2007). Thus, the association between CHRNA5-A3-B4 and smoking cessation may be mediated by altered dependence rather than direct interactions with smoking cessation pharmacotherapies. We recently investigated the association of CHRNA5-A3-B4 variants with smoking cessation in light/infrequent smokers (manuscript attached in Appendix E). In two independent smoking cessation trials of 1295 African American light/infrequent smokers, we observed that rs occurred at a low allele frequency and was not associated with smoking cessation, suggesting that it has low pharmacogenetic importance in African American light/infrequent smokers. In contrast to the lack of effect with rs , we observed a consistent association between the A allele of rs and lower abstinence in active pharmacological treatment after controlling for differences in CPD and FTND, but not with the participants who received the placebo treatment. Since a significant association between rs and smoking behaviors has only been reported in African Americans, it is still untested whether this finding can be applied to other ethnic populations of smokers. Overall, the pharmacogenetic role of CHRNA5- A3-B4 variants and smoking cessation remains inconsistent and larger clinical trials are needed to clarify the associations. 5.4 Conclusions Our findings contribute significantly to the existing literature on the genetic influence of nicotine dependence in light/infrequent smokers and smokeless tobacco users. Significant associations between genetic variants and smoking behaviors had not previously been demonstrated in light/infrequent smokers. Our data suggest that the lack of association was likely due to the limitations of the tobacco consumption biomarkers that were used. Using improved biomarkers of tobacco consumption, we demonstrated that variants in both pharmacokinetic and pharmacodynamic genes can significantly alter tobacco consumption in light/infrequent smokers and smokeless tobacco users. Specifically, we illustrated that light/infrequent smokers and smokeless tobacco users with lower CYP2A6 activity consume less tobacco; they also have lower urinary NNAL levels and reduced NNN metabolism. Furthermore, we showed that genetic variants in CHRNA5-A3-B4 alter tobacco consumption and tobacco- 162

184 derived carcinogen exposure in light/infrequent smokers. Overall, both CYP2A6 and CHRNA5- A3-B4 genetic variants alter tobacco consumption in light/infrequent smokers as previously seen in heavy smokers. The findings of this thesis provided mechanistic insight about smoking behaviors in light/infrequent smokers and smokeless tobacco users, which may enhance smoking cessation. Modifications to the existing scales of nicotine dependence to incorporate biomarker data will likely improve our ability to predict smoking cessation treatment outcomes in light/infrequent smokers. Future studies should focus on exploring individualized smoking cessation treatment strategies based on genetics and biomarkers in light/infrequent smokers. 163

185 6 BIBLIOGRAPHY Ahluwalia, J. S., K. J. Harris, et al. (2002). "Sustained-release bupropion for smoking cessation in African Americans: a randomized controlled trial." JAMA 288(4): Ahluwalia, J. S., K. Okuyemi, et al. (2006). "The effects of nicotine gum and counseling among African American light smokers: a 2 x 2 factorial design." Addiction 101(6): Al Koudsi, N., J. S. Ahluwalia, et al. (2009). "A novel CYP2A6 allele (CYP2A6*35) resulting in an amino-acid substitution (Asn438Tyr) is associated with lower CYP2A6 activity in vivo." Pharmacogenomics J 9(4): Al Koudsi, N., E. B. Hoffmann, et al. (2010). "Hepatic CYP2A6 levels and nicotine metabolism: impact of genetic, physiological, environmental, and epigenetic factors." Eur J Clin Pharmacol 66(3): Al Koudsi, N., J. C. Mwenifumbo, et al. (2006). "Characterization of the novel CYP2A6*21 allele using in vivo nicotine kinetics." Eur J Clin Pharmacol 62(6): Al Koudsi, N. and R. F. Tyndale (2010). "Hepatic CYP2B6 is altered by genetic, physiologic, and environmental factors but plays little role in nicotine metabolism." Xenobiotica 40(6): Allen, B., Jr. and J. B. Unger (2007). "Sociocultural correlates of menthol cigarette smoking among adult African Americans in Los Angeles." Nicotine Tob Res 9(4): Amos, C. I., I. P. Gorlov, et al. (2010). "Nicotinic acetylcholine receptor region on chromosome 15q25 and lung cancer risk among African Americans: a case-control study." J Natl Cancer Inst 102(15): Amos, C. I., X. Wu, et al. (2008). "Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1." Nat Genet 40(5): Anderson, I. G., C. J. Proctor, et al. (1991). "Comparison of the measurement of serum cotinine levels by gas chromatography and radioimmunoassay." Analyst 116(7): Ariyoshi, N., M. Miyazaki, et al. (2001). "A single nucleotide polymorphism of CYP2b6 found in Japanese enhances catalytic activity by autoactivation." Biochem Biophys Res Commun 281(5): Ariyoshi, N., Y. Takahashi, et al. (2000). "Structural characterization of a new variant of the CYP2A6 gene (CYP2A6*1B) apparently diagnosed as heterozygotes of CYP2A6*1A and CYP2A6*4C." Pharmacogenetics 10(8): Armitage, A. K., C. T. Dollery, et al. (1975). "Absorption and metabolism of nicotine from cigarettes." Br Med J 4(5992):

186 Audrain-McGovern, J., N. Al Koudsi, et al. (2007). "The role of CYP2A6 in the emergence of nicotine dependence in adolescents." Pediatrics 119(1): e Audrain-McGovern, J. and N. L. Benowitz (2011). "Cigarette smoking, nicotine, and body weight." Clin Pharmacol Ther 90(1): Augood, C., K. Duckitt, et al. (1998). "Smoking and female infertility: a systematic review and meta-analysis." Hum Reprod 13(6): Baker, T. B., M. E. Piper, et al. (2007). "Time to first cigarette in the morning as an index of ability to quit smoking: implications for nicotine dependence." Nicotine Tob Res 9 Suppl 4: S Bao, Z., X. Y. He, et al. (2005). "Metabolism of nicotine and cotinine by human cytochrome P450 2A13." Drug Metab Dispos 33(2): Bardo, M. T., T. A. Green, et al. (1999). "Nornicotine is self-administered intravenously by rats." Psychopharmacology (Berl) 146(3): Barr, D. B., L. C. Wilder, et al. (2005). "Urinary creatinine concentrations in the U.S. population: implications for urinary biologic monitoring measurements." Environ Health Perspect 113(2): Barrett, J. C., B. Fry, et al. (2005). "Haploview: analysis and visualization of LD and haplotype maps." Bioinformatics 21(2): Behavioral Risk Factor Surveillance System (2008). "Alaska Behavioral Risk Factor Survey 2008 Annual Report." Health Risks in Alaska Among Adults. Bennett, G. G., K. Y. Wolin, et al. (2008). "Nativity and cigarette smoking among lower income blacks: results from the Healthy Directions Study." J Immigr Minor Health 10(4): Benowitz, N., M. L. Goniewicz, et al. (2010). "Urine cotinine underestimates exposure to the tobacco-derived lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone in passive compared with active smokers." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 19(11): Benowitz, N. L. (1988). "Nicotine and smokeless tobacco." CA Cancer J Clin 38(4): Benowitz, N. L. (1990). "Clinical pharmacology of inhaled drugs of abuse: implications in understanding nicotine dependence." NIDA Res Monogr 99: Benowitz, N. L. (1996). "Cotinine as a biomarker of environmental tobacco smoke exposure." Epidemiologic Reviews 18(2):

187 Benowitz, N. L. (1997). "Systemic absorption and effects of nicotine from smokeless tobacco." Adv Dent Res 11(3): Benowitz, N. L. (2009). "Pharmacology of nicotine: addiction, smoking-induced disease, and therapeutics." Annu Rev Pharmacol Toxicol 49: Benowitz, N. L. (2010). "Nicotine addiction." N Engl J Med 362(24): Benowitz, N. L., J. T. Bernert, et al. (2009). "Optimal serum cotinine levels for distinguishing cigarette smokers and nonsmokers within different racial/ethnic groups in the United States between 1999 and 2004." Am J Epidemiol 169(2): Benowitz, N. L., K. M. Dains, et al. (2010). "Urine menthol as a biomarker of mentholated cigarette smoking." Cancer Epidemiol Biomarkers Prev 19(12): Benowitz, N. L., K. M. Dains, et al. (2011). "Racial differences in the relationship between number of cigarettes smoked and nicotine and carcinogen exposure." Nicotine Tob Res 13(9): Benowitz, N. L., K. M. Dains, et al. (2010). "Estimation of nicotine dose after low-level exposure using plasma and urine nicotine metabolites." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 19(5): Benowitz, N. L., C. Griffin, et al. (2001). "Deficient C-oxidation of nicotine continued." Clin Pharmacol Ther 70(6): 567. Benowitz, N. L., S. M. Hall, et al. (1983). "Smokers of low-yield cigarettes do not consume less nicotine." N Engl J Med 309(3): Benowitz, N. L. and P. Jacob, 3rd (1984). "Daily intake of nicotine during cigarette smoking." Clin Pharmacol Ther 35(4): Benowitz, N. L. and P. Jacob, 3rd (1985). "Nicotine renal excretion rate influences nicotine intake during cigarette smoking." J Pharmacol Exp Ther 234(1): Benowitz, N. L. and P. Jacob, 3rd (1993). "Nicotine and cotinine elimination pharmacokinetics in smokers and nonsmokers." Clin Pharmacol Ther 53(3): Benowitz, N. L. and P. Jacob, 3rd (1994). "Metabolism of nicotine to cotinine studied by a dual stable isotope method." Clin Pharmacol Ther 56(5): Benowitz, N. L. and P. Jacob, 3rd (2000). "Effects of cigarette smoking and carbon monoxide on nicotine and cotinine metabolism." Clin Pharmacol Ther 67(6): Benowitz, N. L. and P. Jacob, 3rd (2001). "Trans-3'-hydroxycotinine: disposition kinetics, effects and plasma levels during cigarette smoking." Br J Clin Pharmacol 51(1):

188 Benowitz, N. L., P. Jacob, 3rd, et al. (1991). "Stable isotope studies of nicotine kinetics and bioavailability." Clin Pharmacol Ther 49(3): Benowitz, N. L., P. Jacob, 3rd, et al. (1994). "Nicotine metabolic profile in man: comparison of cigarette smoking and transdermal nicotine." J Pharmacol Exp Ther 268(1): Benowitz, N. L., P. Jacob, 3rd, et al. (1995). "Deficient C-oxidation of nicotine." Clin Pharmacol Ther 57(5): Benowitz, N. L., F. Kuyt, et al. (1983). "Cotinine disposition and effects." Clin Pharmacol Ther 34(5): Benowitz, N. L., C. N. Lessov-Schlaggar, et al. (2008). "Genetic influences in the variation in renal clearance of nicotine and cotinine." Clin Pharmacol Ther 84(2): Benowitz, N. L., C. N. Lessov-Schlaggar, et al. (2006). "Female sex and oral contraceptive use accelerate nicotine metabolism." Clin Pharmacol Ther 79(5): Benowitz, N. L., E. J. Perez-Stable, et al. (1999). "Ethnic differences in N-glucuronidation of nicotine and cotinine." J Pharmacol Exp Ther 291(3): Benowitz, N. L., E. J. Perez-Stable, et al. (2002). "Slower metabolism and reduced intake of nicotine from cigarette smoking in Chinese-Americans." J Natl Cancer Inst 94(2): Benowitz, N. L., H. Porchet, et al. (1988). "Nicotine absorption and cardiovascular effects with smokeless tobacco use: comparison with cigarettes and nicotine gum." Clin Pharmacol Ther 44(1): Benowitz, N. L., C. Renner, et al. (2012). "Exposure to Nicotine and Carcinogens among South Western Alaskan Native Cigarette Smokers and Smokeless Tobacco User." Cancer Epidemiol Biomarkers Prev 21(6): Benowitz, N. L., K. E. Schultz, et al. (2009). "Prevalence of smoking assessed biochemically in an urban public hospital: a rationale for routine cotinine screening." Am J Epidemiol 170(7): Benowitz, N. L., G. E. Swan, et al. (2006). "CYP2A6 genotype and the metabolism and disposition kinetics of nicotine." Clin Pharmacol Ther 80(5): Benowitz, N. L., S. Zevin, et al. (1998). "Suppression of nicotine intake during ad libitum cigarette smoking by high-dose transdermal nicotine." J Pharmacol Exp Ther 287(3): Benowitz, N. L., A. Z. Zhu, et al. (2013). "Influence of CYP2B6 genetic variants on plasma and urine concentrations of bupropion and metabolites at steady state." Pharmacogenet Genomics 23(3):

189 Berg, J. Z., J. Mason, et al. (2010). "Nicotine metabolism in African Americans and European Americans: variation in glucuronidation by ethnicity and UGT2B10 haplotype." J Pharmacol Exp Ther 332(1): Bergen, A. W., H. S. Javitz, et al. (2013). "Nicotinic acetylcholine receptor variation and response to smoking cessation therapies." Pharmacogenet Genomics 23(2): Berkman, C. E., S. B. Park, et al. (1995). "In vitro-in vivo correlations of human (S)-nicotine metabolism." Biochem Pharmacol 50(4): Bernert, J. T., J. R. Alexander, et al. (2011). "Time course of nicotine and cotinine incorporation into samples of nonsmokers' beard hair following a single dose of nicotine polacrilex." Journal of analytical toxicology 35(1): 1-7. Berrettini, W. H. and G. A. Doyle (2012). "The CHRNA5-A3-B4 gene cluster in nicotine addiction." Mol Psychiatry 17(9): Berrettini, W. H., E. P. Wileyto, et al. (2007). "Catechol-O-methyltransferase (COMT) gene variants predict response to bupropion therapy for tobacco dependence." Biol Psychiatry 61(1): Beuten, J., J. Z. Ma, et al. (2005). "Single- and multilocus allelic variants within the GABA(B) receptor subunit 2 (GABAB2) gene are significantly associated with nicotine dependence." American journal of human genetics 76(5): Beuten, J., T. J. Payne, et al. (2006). "Significant association of catechol-o-methyltransferase (COMT) haplotypes with nicotine dependence in male and female smokers of two ethnic populations." Neuropsychopharmacology 31(3): Bierut, L. J. (2009). "Nicotine dependence and genetic variation in the nicotinic receptors." Drug and alcohol dependence 104 Suppl 1: S Bierut, L. J., J. A. Stitzel, et al. (2008). "Variants in nicotinic receptors and risk for nicotine dependence." The American journal of psychiatry 165(9): Binnington, J. M., A. Z. Zhu, et al. (2012). "CYP2A6 and CYP2B6 genetic variation and its association with nicotine metabolism in South Western Alaska Native people." Pharmacogenet Genomics 22(6): Bjartveit, K. and A. Tverdal (2005). "Health consequences of smoking 1-4 cigarettes per day." Tob Control 14(5): Bloom, A. J., O. Harari, et al. (2013). "A compensatory effect upon splicing results in normal function of the CYP2A6*14 allele." Pharmacogenet Genomics 23(3): Bloom, J., A. L. Hinrichs, et al. (2011). "The contribution of common CYP2A6 alleles to variation in nicotine metabolism among European-Americans." Pharmacogenet Genomics 21(7):

190 Boffetta, P., S. Clark, et al. (2006). "Serum cotinine level as predictor of lung cancer risk." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 15(6): Boffetta, P., S. Hecht, et al. (2008). "Smokeless tobacco and cancer." The lancet oncology 9(7): Brandange, S. and L. Lindblom (1979). "The enzyme "aldehyde oxidase" is an iminium oxidase. Reaction with nicotine delta 1'(5') iminium ion." Biochem Biophys Res Commun 91(3): Brauer, L. H., D. Hatsukami, et al. (1996). "Smoking topography in tobacco chippers and dependent smokers." Addict Behav 21(2): Breitling, L. P., D. Twardella, et al. (2010). "Prospective association of dopamine-related polymorphisms with smoking cessation in general care." Pharmacogenomics 11(4): Brennan, P., P. Hainaut, et al. (2011). "Genetics of lung-cancer susceptibility." The lancet oncology 12(4): Brooke, O. G., H. R. Anderson, et al. (1989). "Effects on birth weight of smoking, alcohol, caffeine, socioeconomic factors, and psychosocial stress." BMJ 298(6676): Brownson, R. C., J. C. Chang, et al. (1992). "Gender and histologic type variations in smokingrelated risk of lung cancer." Epidemiology 3(1): Brunnemann, K. D., J. Qi, et al. (2002). "Chemical profile of two types of oral snuff tobacco." Food Chem Toxicol 40(11): Brunzell, D. H. and J. M. McIntosh (2012). "Alpha7 nicotinic acetylcholine receptors modulate motivation to self-administer nicotine: implications for smoking and schizophrenia." Neuropsychopharmacology 37(5): Butler, N. R., H. Goldstein, et al. (1972). "Cigarette smoking in pregnancy: its influence on birth weight and perinatal mortality." Br Med J 2(5806): Byrd, G. D., K. M. Chang, et al. (1992). "Evidence for urinary excretion of glucuronide conjugates of nicotine, cotinine, and trans-3'-hydroxycotinine in smokers." Drug Metab Dispos 20(2): Caggiula, A. R., E. C. Donny, et al. (2002). "Importance of nonpharmacological factors in nicotine self-administration." Physiol Behav 77(4-5): Cashman, J. R., S. B. Park, et al. (1992). "Metabolism of nicotine by human liver microsomes: stereoselective formation of trans-nicotine N'-oxide." Chem Res Toxicol 5(5):

191 Centers for Disease Control and Prevention (1989). "The Surgeon General's 1989 Report on Reducing the Health Consequences of Smoking: 25 Years of Progress." MMWR Morb Mortal Wkly Rep 38 Suppl 2: Centers for Disease Control and Prevention (2003). "Cancer mortality among American Indians and Alaska Natives--United States, " MMWR. Morbidity and mortality weekly report 52(30): Centers for Disease Control and Prevention (2008). "Cigarette smoking among adults--united States, 2007." MMWR. Morbidity and mortality weekly report 57(45): Centers for Disease Control and Prevention (2009). "Cigarette smoking among adults and trends in smoking cessation - United States, 2008." MMWR Morb Mortal Wkly Rep 58(44): Centers for Disease Control and Prevention (2010). "Racial/Ethnic disparities and geographic differences in lung cancer incidence States and the District of Columbia, " MMWR. Morbidity and mortality weekly report 59(44): Centers for Disease Control and Prevention (2010). "State-specific prevalence of cigarette smoking and smokeless tobacco use among adults --- United States, 2009." MMWR Morb Mortal Wkly Rep 59(43): Centers for Disease Control and Prevention (2012). "Current cigarette smoking among adults - United States, 2011." MMWR Morb Mortal Wkly Rep 61(44): Changeux, J. P. (2010). "Nicotine addiction and nicotinic receptors: lessons from genetically modified mice." Nat Rev Neurosci 11(6): Chapman, S., S. Haddad, et al. (1997). "Do work-place smoking bans cause smokers to smoke "harder"? Results from a naturalistic observational study." Addiction 92(5): Chen, G., A. S. Blevins-Primeau, et al. (2007). "Glucuronidation of nicotine and cotinine by UGT2B10: loss of function by the UGT2B10 Codon 67 (Asp>Tyr) polymorphism." Cancer Res 67(19): Chen, L. S., T. B. Baker, et al. (2012). "Interplay of genetic risk factors (CHRNA5-CHRNA3- CHRNB4) and cessation treatments in smoking cessation success." The American journal of psychiatry 169(7): Chen, L. S., N. L. Saccone, et al. (2012). "Smoking and genetic risk variation across populations of European, Asian, and African American ancestry--a meta-analysis of chromosome 15q25." Genet Epidemiol 36(4): Choi, W. S., K. S. Okuyemi, et al. (2004). "Comparison of smoking relapse curves among African-American smokers." Addict Behav 29(8):

192 Church, T. R., K. E. Anderson, et al. (2009). "A prospectively measured serum biomarker for a tobacco-specific carcinogen and lung cancer in smokers." Cancer Epidemiol Biomarkers Prev 18(1): Clark, P. I., S. Gautam, et al. (1996). "Effect of menthol cigarettes on biochemical markers of smoke exposure among black and white smokers." Chest 110(5): Connolly, G. N., D. M. Winn, et al. (1986). "The reemergence of smokeless tobacco." N Engl J Med 314(16): Consortium, T. T. a. G. (2010). "Genome-wide meta-analyses identify multiple loci associated with smoking behavior." Nature genetics 42(5): Corrigall, W. A., K. B. Franklin, et al. (1992). "The mesolimbic dopaminergic system is implicated in the reinforcing effects of nicotine." Psychopharmacology (Berl) 107(2-3): Cox, L. S., N. L. Nollen, et al. (2012). "Bupropion for smoking cessation in African American light smokers: a randomized controlled trial." J Natl Cancer Inst 104(4): Critchley, J. A. and S. Capewell (2003). "Mortality risk reduction associated with smoking cessation in patients with coronary heart disease: a systematic review." JAMA 290(1): Daigo, S., Y. Takahashi, et al. (2002). "A novel mutant allele of the CYP2A6 gene (CYP2A6*11 ) found in a cancer patient who showed poor metabolic phenotype towards tegafur." Pharmacogenetics 12(4): Dale, L. C., E. D. Glover, et al. (2001). "Bupropion for smoking cessation : predictors of successful outcome." Chest 119(5): Dani, J. A. and S. Heinemann (1996). "Molecular and cellular aspects of nicotine abuse." Neuron 16(5): de Dios, M. A., B. J. Anderson, et al. (2012). "Project Impact: a pharmacotherapy pilot trial investigating the abstinence and treatment adherence of Latino light smokers." J Subst Abuse Treat 43(3): Dempsey, D., P. Jacob, 3rd, et al. (2000). "Nicotine metabolism and elimination kinetics in newborns." Clin Pharmacol Ther 67(5): Dempsey, D., P. Jacob, 3rd, et al. (2002). "Accelerated metabolism of nicotine and cotinine in pregnant smokers." J Pharmacol Exp Ther 301(2): Dempsey, D., P. Tutka, et al. (2004). "Nicotine metabolite ratio as an index of cytochrome P450 2A6 metabolic activity." Clin Pharmacol Ther 76(1):

193 Dempsey, D. A., N. C. Sambol, et al. (2013). "CYP2A6 Genotype but not Age Determines Cotinine Half-Life in Infants and Children." Clin Pharmacol Ther 94(3): Doll, R. and A. B. Hill (1954). "The mortality of doctors in relation to their smoking habits; a preliminary report." Br Med J 1(4877): Doll, R. and A. B. Hill (1956). "Lung cancer and other causes of death in relation to smoking; a second report on the mortality of British doctors." Br Med J 2(5001): Doll, R., A. B. Hill, et al. (1957). "The significance of cell type in relation to the aetiology of lung cancer." British journal of cancer 11(1): Doll, R., R. Peto, et al. (2004). "Mortality in relation to smoking: 50 years' observations on male British doctors." BMJ 328(7455): Domino, E. F. and L. Ni (2002). "Clinical phenotyping strategies in selection of tobacco smokers for future genotyping studies." Prog Neuropsychopharmacol Biol Psychiatry 26(6): Donato, M. T., P. Viitala, et al. (2000). "CYP2A5/CYP2A6 expression in mouse and human hepatocytes treated with various in vivo inducers." Drug Metab Dispos 28(11): Duval, S., D. R. Jacobs, Jr., et al. (2008). "Trends in cigarette smoking: the Minnesota Heart Survey, through " Nicotine Tob Res 10(5): Dwoskin, L. P., L. Teng, et al. (1999). "(S)-(-)-Cotinine, the major brain metabolite of nicotine, stimulates nicotinic receptors to evoke [3H]dopamine release from rat striatal slices in a calcium-dependent manner." J Pharmacol Exp Ther 288(3): Epping-Jordan, M. P., M. R. Picciotto, et al. (1999). "Assessment of nicotinic acetylcholine receptor subunit contributions to nicotine self-administration in mutant mice." Psychopharmacology (Berl) 147(1): Fagerstrom, K. O. (1982). "Effects of a nicotine-enriched cigarette on nicotine titration, daily cigarette consumption, and levels of carbon monoxide, cotinine, and nicotine." Psychopharmacology (Berl) 77(2): Feng, Y., T. Niu, et al. (2004). "A common haplotype of the nicotine acetylcholine receptor alpha 4 subunit gene is associated with vulnerability to nicotine addiction in men." American journal of human genetics 75(1): Filion, K. B., L. M. Steffen, et al. (2012). "Trends in smoking among adults from 1980 to 2009: the Minnesota heart survey." Am J Public Health 102(4): Fowler, C. D., Q. Lu, et al. (2011). "Habenular alpha5 nicotinic receptor subunit signalling controls nicotine intake." Nature 471(7340):

194 Frahm, S., M. A. Slimak, et al. (2011). "Aversion to Nicotine Is Regulated by the Balanced Activity of beta4 and alpha5 Nicotinic Receptor Subunits in the Medial Habenula." Neuron 70(3): Franklin, T. R., Z. Wang, et al. (2007). "Limbic activation to cigarette smoking cues independent of nicotine withdrawal: a perfusion fmri study." Neuropsychopharmacology 32(11): Freathy, R. M., G. R. Kazeem, et al. (2011). "Genetic variation at CHRNA5-CHRNA3- CHRNB4 interacts with smoking status to influence body mass index." Int J Epidemiol 40(6): Fujieda, M., H. Yamazaki, et al. (2004). "Evaluation of CYP2A6 genetic polymorphisms as determinants of smoking behavior and tobacco-related lung cancer risk in male Japanese smokers." Carcinogenesis 25(12): Fukami, T., M. Nakajima, et al. (2005). "A novel CYP2A6*20 allele found in African-American population produces a truncated protein lacking enzymatic activity." Biochem Pharmacol 70(5): Fukami, T., M. Nakajima, et al. (2005). "Characterization of novel CYP2A6 polymorphic alleles (CYP2A6*18 and CYP2A6*19) that affect enzymatic activity." Drug Metab Dispos 33(8): Fukami, T., M. Nakajima, et al. (2007). "A novel duplication type of CYP2A6 gene in African- American population." Drug Metab Dispos 35(4): Fukami, T., M. Nakajima, et al. (2004). "A novel polymorphism of human CYP2A6 gene CYP2A6*17 has an amino acid substitution (V365M) that decreases enzymatic activity in vitro and in vivo." Clin Pharmacol Ther 76(6): Gambier, N., A. M. Batt, et al. (2005). "Association of CYP2A6*1B genetic variant with the amount of smoking in French adults from the Stanislas cohort." Pharmacogenomics J 5(4): Gan, W. Q., S. B. Cohen, et al. (2008). "Sex-related differences in serum cotinine concentrations in daily cigarette smokers." Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco 10(8): Garfinkel, L. and S. D. Stellman (1988). "Smoking and lung cancer in women: findings in a prospective study." Cancer Res 48(23): Ghosheh, O. A., L. P. Dwoskin, et al. (2001). "Accumulation of nicotine and its metabolites in rat brain after intermittent or continuous peripheral administration of [2'-(14)C]nicotine." Drug Metab Dispos 29(5):

195 Giovino, G. A., S. A. Mirza, et al. (2012). "Tobacco use in 3 billion individuals from 16 countries: an analysis of nationally representative cross-sectional household surveys." Lancet 380(9842): Girard, N., E. Lou, et al. (2010). "Analysis of genetic variants in never-smokers with lung cancer facilitated by an Internet-based blood collection protocol: a preliminary report." Clin Cancer Res 16(2): Goniewicz, M. L., M. D. Eisner, et al. (2011). "Comparison of Urine Cotinine and the Tobacco- Specific Nitrosamine Metabolite 4-(Methylnitrosamino)-1-(3-Pyridyl)-1-Butanol (NNAL) and Their Ratio to Discriminate Active From Passive Smoking." Nicotine Tob Res 13(3): Goniewicz, M. L., C. M. Havel, et al. (2009). "Elimination kinetics of the tobacco-specific biomarker and lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol." Cancer Epidemiol Biomarkers Prev 18(12): Gonzales, D., S. I. Rennard, et al. (2006). "Varenicline, an alpha4beta2 nicotinic acetylcholine receptor partial agonist, vs sustained-release bupropion and placebo for smoking cessation: a randomized controlled trial." JAMA 296(1): Gorrod, J. W. and A. R. Hibberd (1982). "The metabolism of nicotine-delta 1'(5')-iminium ion, in vivo and in vitro." Eur J Drug Metab Pharmacokinet 7(4): Gotti, C., F. Clementi, et al. (2009). "Structural and functional diversity of native brain neuronal nicotinic receptors." Biochem Pharmacol 78(7): Gourlay, S. G. and N. L. Benowitz (1996). "The benefits of stopping smoking and the role of nicotine replacement therapy in older patients." Drugs Aging 9(1): Gow, P. J., H. Ghabrial, et al. (2001). "Neonatal hepatic drug elimination." Pharmacol Toxicol 88(1): Graham, H. and G. Der (1999). "Patterns and predictors of tobacco consumption among women." Health Educ Res 14(5): Grando, S. A. (2006). "Cholinergic control of epidermal cohesion." Exp Dermatol 15(4): Green, T. A., P. A. Crooks, et al. (2001). "Contributory role for nornicotine in nicotine neuropharmacology: nornicotine-evoked [3H]dopamine overflow from rat nucleus accumbens slices." Biochem Pharmacol 62(12): Gries, J. M., N. Benowitz, et al. (1996). "Chronopharmacokinetics of nicotine." Clin Pharmacol Ther 60(4): Gritz, E. R., V. Baer-Weiss, et al. (1981). "Plasma nicotine and cotinine concentrations in habitual smokeless tobacco users." Clin Pharmacol Ther 30(2):

196 Gu, D. F., L. J. Hinks, et al. (2000). "The use of long PCR to confirm three common alleles at the CYP2A6 locus and the relationship between genotype and smoking habit." Ann Hum Genet 64(Pt 5): Gyamfi, M. A., M. Fujieda, et al. (2005). "High prevalence of cytochrome P450 2A6*1A alleles in a black African population of Ghana." Eur J Clin Pharmacol 60(12): Haberl, M., B. Anwald, et al. (2005). "Three haplotypes associated with CYP2A6 phenotypes in Caucasians." Pharmacogenet Genomics 15(9): Harger, J. H., A. W. Hsing, et al. (1990). "Risk factors for preterm premature rupture of fetal membranes: a multicenter case-control study." Am J Obstet Gynecol 163(1 Pt 1): Harris, C. C., H. Autrup, et al. (1976). "Interindividual variation in binding of benzo[a]pyrene to DNA in cultured human bronchi." Science 194(4269): Harvey, D. M., S. Yasar, et al. (2004). "Nicotine serves as an effective reinforcer of intravenous drug-taking behavior in human cigarette smokers." Psychopharmacology (Berl) 175(2): Hassmiller, K. M., K. E. Warner, et al. (2003). "Nondaily smokers: who are they?" Am J Public Health 93(8): Hatsukami, D. K., M. Grillo, et al. (1997). "Safety of cotinine in humans: physiologic, subjective, and cognitive effects." Pharmacol Biochem Behav 57(4): Hatsukami, D. K., C. Lemmonds, et al. (2004). "Smokeless tobacco use: harm reduction or induction approach?" Prev Med 38(3): Hatsukami, D. K., L. F. Stead, et al. (2008). "Tobacco addiction." Lancet 371(9629): Health Canada (2007). "Health Canada: Canadian Tobacco Use Monitoring Survey." Health Canada (2008). "Health Canada, National Clearinghouse on Tobacco and Health, Canadian Centre for Substance Abuse." Health Canada (2011). "Canadian Tobacco Use Monitoring Survey." Heatherton, T. F., L. T. Kozlowski, et al. (1991). "The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire." British journal of addiction 86(9): Hecht, S. S. (1998). "Biochemistry, biology, and carcinogenicity of tobacco-specific N- nitrosamines." Chem Res Toxicol 11(6): Hecht, S. S. (2002). "Human urinary carcinogen metabolites: biomarkers for investigating tobacco and cancer." Carcinogenesis 23(6):

197 Hecht, S. S. (2003). "Tobacco carcinogens, their biomarkers and tobacco-induced cancer." Nature reviews. Cancer 3(10): Hecht, S. S. (2012). "Lung carcinogenesis by tobacco smoke." International journal of cancer. Journal international du cancer 131(12): Hecht, S. S., S. G. Carmella, et al. (1999). "Quantitation of urinary metabolites of a tobaccospecific lung carcinogen after smoking cessation." Cancer Res 59(3): Hecht, S. S., S. G. Carmella, et al. (2007). "Similar exposure to a tobacco-specific carcinogen in smokeless tobacco users and cigarette smokers." Cancer Epidemiol Biomarkers Prev 16(8): Hecht, S. S., F. L. Chung, et al. (1995). "Effects of watercress consumption on metabolism of a tobacco-specific lung carcinogen in smokers." Cancer Epidemiol Biomarkers Prev 4(8): Hecht, S. S., J. B. Hochalter, et al. (2000). "2'-Hydroxylation of nicotine by cytochrome P450 2A6 and human liver microsomes: formation of a lung carcinogen precursor." Proc Natl Acad Sci U S A 97(23): Hecht, S. S., F. Kassie, et al. (2009). "Chemoprevention of lung carcinogenesis in addicted smokers and ex-smokers." Nat Rev Cancer 9(7): Heck, J. D. (2009). "Smokers of menthol and nonmenthol cigarettes exhibit similar levels of biomarkers of smoke exposure." Cancer Epidemiol Biomarkers Prev 18(2): Henley, S. J., C. J. Connell, et al. (2007). "Tobacco-related disease mortality among men who switched from cigarettes to spit tobacco." Tob Control 16(1): Henningfield, J. E., N. L. Benowitz, et al. (2004). "Reducing tobacco addiction through tobacco product regulation." Tob Control 13(2): Henningfield, J. E. and S. R. Goldberg (1983). "Nicotine as a reinforcer in human subjects and laboratory animals." Pharmacol Biochem Behav 19(6): Henningfield, J. E. and R. M. Keenan (1993). "Nicotine delivery kinetics and abuse liability." J Consult Clin Psychol 61(5): Henningfield, J. E., K. Miyasato, et al. (1983). "Cigarette smokers self-administer intravenous nicotine." Pharmacol Biochem Behav 19(5): Herning, R. I., R. T. Jones, et al. (1981). "Puff volume increases when low-nicotine cigarettes are smoked." Br Med J (Clin Res Ed) 283(6285): Herning, R. I., R. T. Jones, et al. (1983). "How a cigarette is smoked determines blood nicotine levels." Clin Pharmacol Ther 33(1):

198 Higashi, E., T. Fukami, et al. (2007). "Human CYP2A6 is induced by estrogen via estrogen receptor." Drug Metab Dispos 35(10): Ho, M. K., B. Faseru, et al. (2009). "Utility and relationships of biomarkers of smoking in African-American light smokers." Cancer Epidemiol Biomarkers Prev 18(12): Ho, M. K., J. C. Mwenifumbo, et al. (2009). "Association of nicotine metabolite ratio and CYP2A6 genotype with smoking cessation treatment in African-American light smokers." Clin Pharmacol Ther 85(6): Ho, M. K., J. C. Mwenifumbo, et al. (2008). "A novel CYP2A6 allele, CYP2A6*23, impairs enzyme function in vitro and in vivo and decreases smoking in a population of Black- African descent." Pharmacogenet Genomics 18(1): Ho, M. K. and R. F. Tyndale (2007). "Overview of the pharmacogenomics of cigarette smoking." Pharmacogenomics J 7(2): Hoffman, S. M., P. Fernandez-Salguero, et al. (1995). "Organization and evolution of the cytochrome P450 CYP2A-2B-2F subfamily gene cluster on human chromosome 19." J Mol Evol 41(6): Hoffmann, D., A. Rivenson, et al. (1996). "The biological significance of tobacco-specific N- nitrosamines: smoking and adenocarcinoma of the lung." Crit Rev Toxicol 26(2): Houtsmuller, E. J., J. E. Henningfield, et al. (2003). "Subjective effects of the nicotine lozenge: assessment of abuse liability." Psychopharmacology (Berl) 167(1): Huang, S., D. G. Cook, et al. (2005). "CYP2A6, MAOA, DBH, DRD4, and 5HT2A genotypes, smoking behaviour and cotinine levels in 1518 UK adolescents." Pharmacogenet Genomics 15(12): Hughes, J. R. (2007). "Effects of abstinence from tobacco: valid symptoms and time course." Nicotine Tob Res 9(3): Hughes, J. R., S. W. Gust, et al. (1990). "Effect of dose on nicotine's reinforcing, withdrawalsuppression and self-reported effects." J Pharmacol Exp Ther 252(3): Hughes, J. R. and D. Hatsukami (1986). "Signs and symptoms of tobacco withdrawal." Arch Gen Psychiatry 43(3): Hughes, J. R., A. H. Oliveto, et al. (2004). "Concordance of different measures of nicotine dependence: two pilot studies." Addict Behav 29(8): Hukkanen, J., P. Jacob, 3rd, et al. (2005). "Metabolism and disposition kinetics of nicotine." Pharmacol Rev 57(1):

199 Hukkanen, J., P. Jacob, 3rd, et al. (2006). "Effect of grapefruit juice on cytochrome P450 2A6 and nicotine renal clearance." Clin Pharmacol Ther 80(5): Hung, R. J., J. D. McKay, et al. (2008). "A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25." Nature 452(7187): Hurt, R. D., C. C. Renner, et al. (2005). "Iqmik--a form of smokeless tobacco used by pregnant Alaska natives: nicotine exposure in their neonates." J Matern Fetal Neonatal Med 17(4): IARC Working Group on the Evaluation of Carcinogenic Risks to Humans (2007). "Smokeless tobacco and some tobacco-specific N-nitrosamines." IARC Monogr Eval Carcinog Risks Hum 89: Institute of Social and Economic Research University of Alaska Anchorage (2009). "The Changing Economic Status of Alaska Natives, " Isaac, P. F. and M. J. Rand (1972). "Cigarette smoking and plasma levels of nicotine." Nature 236(5345): Itoh, M., M. Nakajima, et al. (2006). "Induction of human CYP2A6 is mediated by the pregnane X receptor with peroxisome proliferator-activated receptor-gamma coactivator 1alpha." J Pharmacol Exp Ther 319(2): Iwahashi, K., C. Waga, et al. (2004). "Whole deletion of CYP2A6 gene (CYP2A6AST;4C) and smoking behavior." Neuropsychobiology 49(2): Jackson, K. J., M. J. Marks, et al. (2010). "Role of alpha5 nicotinic acetylcholine receptors in pharmacological and behavioral effects of nicotine in mice." The Journal of pharmacology and experimental therapeutics 334(1): Jacob, P., 3rd, C. Havel, et al. (2008). "Subpicogram per milliliter determination of the tobaccospecific carcinogen metabolite 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol in human urine using liquid chromatography-tandem mass spectrometry." Analytical chemistry 80(21): Jacob, P., 3rd, M. Wilson, et al. (2007). "Determination of phenolic metabolites of polycyclic aromatic hydrocarbons in human urine as their pentafluorobenzyl ether derivatives using liquid chromatography-tandem mass spectrometry." Analytical chemistry 79(2): Jacob, P., 3rd, L. Yu, et al. (1991). "Selected ion monitoring method for determination of nicotine, cotinine and deuterium-labeled analogs: absence of an isotope effect in the clearance of (S)-nicotine-3',3'-d2 in humans." Biological mass spectrometry 20(5): Jaffe, J. H. and M. B. Kanzler (1978). "Tobacco and nicotine self-administration in humans: the evolution of a methodology." NIDA Res Monogr(20):

200 Jalas, J. R., S. S. Hecht, et al. (2005). "Cytochrome P450 enzymes as catalysts of metabolism of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, a tobacco specific carcinogen." Chem Res Toxicol 18(2): Jarvik, M. E., D. C. Madsen, et al. (2000). "Nicotine blood levels and subjective craving for cigarettes." Pharmacol Biochem Behav 66(3): Jarvis, M. J., H. Tunstall-Pedoe, et al. (1987). "Comparison of tests used to distinguish smokers from nonsmokers." Am J Public Health 77(11): Jatlow, P., B. A. Toll, et al. (2008). "Comparison of expired carbon monoxide and plasma cotinine as markers of cigarette abstinence." Drug Alcohol Depend 98(3): Jaworowska, E., J. Trubicka, et al. (2011). "Smoking related cancers and loci at chromosomes 15q25, 5p15, 6p22.1 and 6p21.33 in the Polish population." PLoS One 6(9): e Jemal, A., F. Bray, et al. (2011). "Global cancer statistics." CA Cancer J Clin 61(2): Jha, P., C. Ramasundarahettige, et al. (2013). "21st-century hazards of smoking and benefits of cessation in the United States." N Engl J Med 368(4): Jimenez-Ruiz, C., M. Kunze, et al. (1998). "Nicotine replacement: a new approach to reducing tobacco-related harm." Eur Respir J 11(2): Johnstone, E., N. Benowitz, et al. (2006). "Determinants of the rate of nicotine metabolism and effects on smoking behavior." Clin Pharmacol Ther 80(4): Jones, A. Y. and P. K. Lam (2006). "End-expiratory carbon monoxide levels in healthy subjects living in a densely populated urban environment." Sci Total Environ 354(2-3): Joseph, A. M., S. S. Hecht, et al. (2005). "Relationships between cigarette consumption and biomarkers of tobacco toxin exposure." Cancer Epidemiol Biomarkers Prev 14(12): Kaivosaari, S., P. Toivonen, et al. (2007). "Nicotine glucuronidation and the human UDPglucuronosyltransferase UGT2B10." Mol Pharmacol 72(3): Kamangar, F., P. T. Strickland, et al. (2005). "High exposure to polycyclic aromatic hydrocarbons may contribute to high risk of esophageal cancer in northeastern Iran." Anticancer Res 25(1B): Kandel, D. B. and K. Chen (2000). "Extent of smoking and nicotine dependence in the United States: " Nicotine Tob Res 2(3): Kaur-Knudsen, D., S. E. Bojesen, et al. (2011). "Nicotinic acetylcholine receptor polymorphism, smoking behavior, and tobacco-related cancer and lung and cardiovascular diseases: a cohort study." J Clin Oncol 29(21):

201 Kendler, K. S., L. M. Thornton, et al. (2000). "Tobacco consumption in Swedish twins reared apart and reared together." Arch Gen Psychiatry 57(9): Keskitalo, K., U. Broms, et al. (2009). "Association of serum cotinine level with a cluster of three nicotinic acetylcholine receptor genes (CHRNA3/CHRNA5/CHRNB4) on chromosome 15." Human molecular genetics 18(20): Khuder, S. A. and A. B. Mutgi (2001). "Effect of smoking cessation on major histologic types of lung cancer." Chest 120(5): King, C., 3rd, M. Siegel, et al. (2000). "Exposure of black youths to cigarette advertising in magazines." Tob Control 9(1): King, D. P., S. Paciga, et al. (2012). "Smoking cessation pharmacogenetics: analysis of varenicline and bupropion in placebo-controlled clinical trials." Neuropsychopharmacology 37(3): Kirchheiner, J. (2008). "CYP2D6 phenotype prediction from genotype: which system is the best?" Clin Pharmacol Ther 83(2): Kitagawa, K., N. Kunugita, et al. (1999). "The significance of the homozygous CYP2A6 deletion on nicotine metabolism: a new genotyping method of CYP2A6 using a single PCR- RFLP." Biochem Biophys Res Commun 262(1): Kiyotani, K., M. Fujieda, et al. (2002). "Twenty one novel single nucleotide polymorphisms (SNPs) of the CYP2A6 gene in Japanese and Caucasians." Drug Metab Pharmacokinet 17(5): Klesges, R. C., M. Debon, et al. (1995). "Are self-reports of smoking rate biased? Evidence from the Second National Health and Nutrition Examination Survey." J Clin Epidemiol 48(10): Klonoff, E. A., J. M. Fritz, et al. (1994). "The problem and sociocultural context of singlecigarette sales." JAMA 271(8): Klonoff, E. A. and H. Landrine (1996). "Acculturation and cigarette smoking among African American adults." Journal of behavioral medicine 19(5): Klonoff, E. A. and H. Landrine (1999). "Acculturation and cigarette smoking among African Americans: replication and implications for prevention and cessation programs." Journal of behavioral medicine 22(2): Knott, V., A. Heenan, et al. (2011). "Electrophysiological evidence of nicotine's distracterfiltering properties in non-smokers." J Psychopharmacol 25(2): Knott, V. J., K. Bolton, et al. (2009). "Effects of acute nicotine on event-related potential and performance indices of auditory distraction in nonsmokers." Nicotine Tob Res 11(5):

202 Koob, G. F. (2006). "The neurobiology of addiction: a neuroadaptational view relevant for diagnosis." Addiction 101 Suppl 1: Koop, C. E. and J. Luoto (1982). ""The Health Consequences of Smoking: Cancer," overview of a report of the Surgeon General." Public Health Rep 97(4): Koop, C. E. and J. Luoto (2006). ""The health consequences of smoking: cancer," overview of a report of the Surgeon General " Public Health Rep 121 Suppl 1: ; discussion 268. Koskela, S., J. Hakkola, et al. (1999). "Expression of CYP2A genes in human liver and extrahepatic tissues." Biochem Pharmacol 57(12): Kotz, D., M. C. Willemsen, et al. (2013). "Light smokers are less likely to receive advice to quit from their GP than moderate-to-heavy smokers: a comparison of national survey data from the Netherlands and England." Eur J Gen Pract 19(2): Kozlowski, L. T., N. Y. Mehta, et al. (1998). "Filter ventilation and nicotine content of tobacco in cigarettes from Canada, the United Kingdom, and the United States." Tob Control 7(4): Kozlowski, L. T., C. Q. Porter, et al. (1994). "Predicting smoking cessation with self-reported measures of nicotine dependence: FTQ, FTND, and HSI." Drug Alcohol Depend 34(3): Kresty, L. A., S. G. Carmella, et al. (1996). "Metabolites of a tobacco-specific nitrosamine, 4- (methylnitrosamino)- 1-(3-pyridyl)-1-butanone (NNK), in the urine of smokeless tobacco users: relationship between urinary biomarkers and oral leukoplakia." Cancer Epidemiol Biomarkers Prev 5(7): Kristensen, J., M. Vestergaard, et al. (2005). "Pre-pregnancy weight and the risk of stillbirth and neonatal death." BJOG 112(4): Krul, C. and G. Hageman (1998). "Analysis of urinary caffeine metabolites to assess biotransformation enzyme activities by reversed-phase high-performance liquid chromatography." J Chromatogr B Biomed Sci Appl 709(1): Kuryatov, A., W. Berrettini, et al. (2011). "Acetylcholine receptor (AChR) alpha5 subunit variant associated with risk for nicotine dependence and lung cancer reduces (alpha4beta2)alpha5 AChR function." Molecular pharmacology 79(1): Kushida, H., K. Fujita, et al. (2000). "Metabolic activation of N-alkylnitrosamines in genetically engineered Salmonella typhimurium expressing CYP2E1 or CYP2A6 together with human NADPH-cytochrome P450 reductase." Carcinogenesis 21(6): Kwon, J. T., M. Nakajima, et al. (2001). "Nicotine metabolism and CYP2A6 allele frequencies in Koreans." Pharmacogenetics 11(4):

203 Kyerematen, G. A., M. Morgan, et al. (1990). "Metabolism of nicotine by hepatocytes." Biochem Pharmacol 40(8): Lam, D. C., L. Girard, et al. (2007). "Expression of nicotinic acetylcholine receptor subunit genes in non-small-cell lung cancer reveals differences between smokers and nonsmokers." Cancer research 67(10): Lambrechts, D., I. Buysschaert, et al. (2010). "The 15q24/25 susceptibility variant for lung cancer and chronic obstructive pulmonary disease is associated with emphysema." Am J Respir Crit Care Med 181(5): Landrine, H., E. A. Klonoff, et al. (2005). "Cigarette advertising in Black, Latino, and White magazines, : an exploratory investigation." Ethn Dis 15(1): Laviolette, S. R. and D. van der Kooy (2004). "The neurobiology of nicotine addiction: bridging the gap from molecules to behaviour." Nat Rev Neurosci 5(1): Le Foll, B. and S. R. Goldberg (2006). "Nicotine as a typical drug of abuse in experimental animals and humans." Psychopharmacology (Berl) 184(3-4): Le Gal, A., Y. Dreano, et al. (2001). "Human cytochrome P450 2A6 is the major enzyme involved in the metabolism of three alkoxyethers used as oxyfuels." Toxicol Lett 124(1-3): Le Marchand, L., K. S. Derby, et al. (2008). "Smokers with the CHRNA lung cancer-associated variants are exposed to higher levels of nicotine equivalents and a carcinogenic tobaccospecific nitrosamine." Cancer research 68(22): Lea, R. A., S. Dickson, et al. (2006). "Within-subject variation of the salivary 3HC/COT ratio in regular daily smokers: prospects for estimating CYP2A6 enzyme activity in large-scale surveys of nicotine metabolic rate." J Anal Toxicol 30(6): Lee, B. L., P. Jacob, 3rd, et al. (1989). "Food and nicotine metabolism." Pharmacol Biochem Behav 33(3): Leong, J. W., N. D. Dore, et al. (1998). "The elimination half-life of urinary cotinine in children of tobacco-smoking mothers." Pulm Pharmacol Ther 11(4): Lerman, C., C. Jepson, et al. (2010). "Genetic Variation in Nicotine Metabolism Predicts the Efficacy of Extended-Duration Transdermal Nicotine Therapy." Clin Pharmacol Ther 87(5): Lerman, C., R. Tyndale, et al. (2006). "Nicotine metabolite ratio predicts efficacy of transdermal nicotine for smoking cessation." Clin Pharmacol Ther 79(6): Levi, M., D. A. Dempsey, et al. (2007). "Prediction methods for nicotine clearance using cotinine and 3-hydroxy-cotinine spot saliva samples II. Model application." J Pharmacokinet Pharmacodyn 34(1):

204 Li, M. D., J. Beuten, et al. (2005). "Ethnic- and gender-specific association of the nicotinic acetylcholine receptor alpha4 subunit gene (CHRNA4) with nicotine dependence." Hum Mol Genet 14(9): Li, M. D., D. Yoon, et al. (2010). "Associations of variants in CHRNA5/A3/B4 gene cluster with smoking behaviors in a Korean population." PLoS One 5(8): e Lindstrom, M. and S. O. Isacsson (2002). "Long term and transitional intermittent smokers: a longitudinal study." Tob Control 11(1): Lindstrom, M. and S. O. Isacsson (2002). "Smoking cessation among daily smokers, aged years: a longitudinal study in Malmo, Sweden." Addiction 97(2): Lips, E. H., V. Gaborieau, et al. (2010). "Association between a 15q25 gene variant, smoking quantity and tobacco-related cancers among individuals." Int J Epidemiol 39(2): Liu, J. Z., F. Tozzi, et al. (2010). "Meta-analysis and imputation refines the association of 15q25 with smoking quantity." Nat Genet 42(5): Lou, X. Y., J. Z. Ma, et al. (2006). "Gene-based analysis suggests association of the nicotinic acetylcholine receptor beta1 subunit (CHRNB1) and M1 muscarinic acetylcholine receptor (CHRM1) with vulnerability for nicotine dependence." Hum Genet 120(3): Lubin, J. H., N. Caporaso, et al. (2007). "The association of a tobacco-specific biomarker and cigarette consumption and its dependence on host characteristics." Cancer Epidemiol Biomarkers Prev 16(9): Lunell, E., L. Molander, et al. (2000). "Site of nicotine absorption from a vapour inhaler-- comparison with cigarette smoking." Eur J Clin Pharmacol 55(10): Luo, J., W. Ye, et al. (2007). "Oral use of Swedish moist snuff (snus) and risk for cancer of the mouth, lung, and pancreas in male construction workers: a retrospective cohort study." Lancet 369(9578): Ma, J. Z., J. Beuten, et al. (2005). "Haplotype analysis indicates an association between the DOPA decarboxylase (DDC) gene and nicotine dependence." Hum Mol Genet 14(12): MacDougall, J. M., K. Fandrick, et al. (2003). "Inhibition of human liver microsomal (S)- nicotine oxidation by (-)-menthol and analogues." Chem Res Toxicol 16(8): Madan, A., R. A. Graham, et al. (2003). "Effects of prototypical microsomal enzyme inducers on cytochrome P450 expression in cultured human hepatocytes." Drug Metab Dispos 31(4):

205 Maglich, J. M., C. M. Stoltz, et al. (2002). "Nuclear pregnane x receptor and constitutive androstane receptor regulate overlapping but distinct sets of genes involved in xenobiotic detoxification." Mol Pharmacol 62(3): Malaiyandi, V., S. D. Goodz, et al. (2006). "CYP2A6 genotype, phenotype, and the use of nicotine metabolites as biomarkers during ad libitum smoking." Cancer Epidemiol Biomarkers Prev 15(10): Malaiyandi, V., C. Lerman, et al. (2006). "Impact of CYP2A6 genotype on pretreatment smoking behaviour and nicotine levels from and usage of nicotine replacement therapy." Mol Psychiatry 11(4): Malaiyandi, V., E. M. Sellers, et al. (2005). "Implications of CYP2A6 genetic variation for smoking behaviors and nicotine dependence." Clin Pharmacol Ther 77(3): Maser, E. (1998). "11Beta-hydroxysteroid dehydrogenase responsible for carbonyl reduction of the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone in mouse lung microsomes." Cancer Res 58(14): Maser, E., E. Richter, et al. (1996). "The identification of 11 beta-hydroxysteroid dehydrogenase as carbonyl reductase of the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3- pyridyl)-1-butanone." Eur J Biochem 238(2): Maskos, U., B. E. Molles, et al. (2005). "Nicotine reinforcement and cognition restored by targeted expression of nicotinic receptors." Nature 436(7047): Mattes, W. B. and A. P. Li (1997). "Quantitative reverse transcriptase/pcr assay for the measurement of induction in cultured hepatocytes." Chem Biol Interact 107(1-2): Maurice, M., S. Emiliani, et al. (1991). "Isolation and characterization of a cytochrome P450 of the IIA subfamily from human liver microsomes." Eur J Biochem 200(2): McKennis, H., Jr., S. L. Schwartz, et al. (1964). "Alternate Routes in the Metabolic Degradation of the Pyrrolidine Ring of Nicotine." J Biol Chem 239: McMorrow, M. J. and R. M. Foxx (1983). "Nicotine's role in smoking: an analysis of nicotine regulation." Psychol Bull 93(2): Messina, E. S., R. F. Tyndale, et al. (1997). "A major role for CYP2A6 in nicotine C-oxidation by human liver microsomes." J Pharmacol Exp Ther 282(3): Meunier, V., M. Bourrie, et al. (2000). "Expression and induction of CYP1A1/1A2, CYP2A6 and CYP3A4 in primary cultures of human hepatocytes: a 10-year follow-up." Xenobiotica 30(6): Mihalak, K. B., F. I. Carroll, et al. (2006). "Varenicline is a partial agonist at alpha4beta2 and a full agonist at alpha7 neuronal nicotinic receptors." Mol Pharmacol 70(3):

206 Minematsu, N., H. Nakamura, et al. (2006). "Limitation of cigarette consumption by CYP2A6*4, *7 and *9 polymorphisms." Eur Respir J 27(2): Mineur, Y. S., A. Abizaid, et al. (2011). "Nicotine decreases food intake through activation of POMC neurons." Science 332(6035): Molander, L., A. Hansson, et al. (2001). "Pharmacokinetics of nicotine in healthy elderly people." Clin Pharmacol Ther 69(1): Moolchan, E. T., A. Radzius, et al. (2002). "The Fagerstrom Test for Nicotine Dependence and the Diagnostic Interview Schedule: do they diagnose the same smokers?" Addict Behav 27(1): Mucha, L., J. Stephenson, et al. (2006). "Meta-analysis of disease risk associated with smoking, by gender and intensity of smoking." Gend Med 3(4): Munafo, M. R., E. C. Johnstone, et al. (2011). "CHRNA3 rs genotype and short-term smoking cessation." Nicotine Tob Res 13(10): Munafo, M. R., M. N. Timofeeva, et al. (2012). "Association between genetic variants on chromosome 15q25 locus and objective measures of tobacco exposure." J Natl Cancer Inst 104(10): Murphy, P. J. (1973). "Enzymatic oxidation of nicotine to nicotine 1'(5') iminium ion. A newly discovered intermediate in the metabolism of nicotine." J Biol Chem 248(8): Murphy, S. E., V. Raulinaitis, et al. (2005). "Nicotine 5'-oxidation and methyl oxidation by P450 2A enzymes." Drug Metab Dispos 33(8): Muscat, J. E., G. Chen, et al. (2009). "Effects of menthol on tobacco smoke exposure, nicotine dependence, and NNAL glucuronidation." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 18(1): Mushtaq, N., L. A. Beebe, et al. (2012). "Determinants of salivary cotinine concentrations among smokeless tobacco users." Nicotine Tob Res 14(10): Mustonen, T. K., S. M. Spencer, et al. (2005). "The influence of gender, race, and menthol content on tobacco exposure measures." Nicotine Tob Res 7(4): Mwenifumbo, J. C., N. Al Koudsi, et al. (2008). "Novel and established CYP2A6 alleles impair in vivo nicotine metabolism in a population of Black African descent." Hum Mutat 29(5): Mwenifumbo, J. C., C. N. Lessov-Schlaggar, et al. (2008). "Identification of novel CYP2A6*1B variants: the CYP2A6*1B allele is associated with faster in vivo nicotine metabolism." Clin Pharmacol Ther 83(1):

207 Mwenifumbo, J. C., M. G. Myers, et al. (2005). "Ethnic variation in CYP2A6*7, CYP2A6*8 and CYP2A6*10 as assessed with a novel haplotyping method." Pharmacogenet Genomics 15(3): Mwenifumbo, J. C., E. M. Sellers, et al. (2007). "Nicotine metabolism and CYP2A6 activity in a population of black African descent: impact of gender and light smoking." Drug Alcohol Depend 89(1): Mwenifumbo, J. C. and R. F. Tyndale (2007). "Genetic variability in CYP2A6 and the pharmacokinetics of nicotine." Pharmacogenomics 8(10): Mwenifumbo, J. C. and R. F. Tyndale (2009). "Molecular genetics of nicotine metabolism." Handb Exp Pharmacol(192): Mwenifumbo, J. C. and R. F. Tyndale (2011). "DSM-IV, ICD-10 and FTND: Discordant Tobacco Dependence Diagnoses in Adult Smokers." Journal of Addiction Research & Therapy 02(01). Mwenifumbo, J. C., Q. Zhou, et al. (2010). "New CYP2A6 gene deletion and conversion variants in a population of Black African descent." Pharmacogenomics 11(2): Nakada, T., K. Kiyotani, et al. (2012). "Lung tumorigenesis promoted by anti-apoptotic effects of cotinine, a nicotine metabolite through activation of PI3K/Akt pathway." J Toxicol Sci 37(3): Nakajima, M., T. Fukami, et al. (2006). "Comprehensive evaluation of variability in nicotine metabolism and CYP2A6 polymorphic alleles in four ethnic populations." Clin Pharmacol Ther 80(3): Nakajima, M., J. T. Kwon, et al. (2001). "Relationship between interindividual differences in nicotine metabolism and CYP2A6 genetic polymorphism in humans." Clin Pharmacol Ther 69(1): Nakajima, M., E. Tanaka, et al. (2002). "Characterization of nicotine and cotinine N- glucuronidations in human liver microsomes." Drug Metab Dispos 30(12): Nakajima, M., S. Yamagishi, et al. (2000). "Deficient cotinine formation from nicotine is attributed to the whole deletion of the CYP2A6 gene in humans." Clin Pharmacol Ther 67(1): Nakajima, M., T. Yamamoto, et al. (1996). "Characterization of CYP2A6 involved in 3'- hydroxylation of cotinine in human liver microsomes." J Pharmacol Exp Ther 277(2): Nakajima, M., T. Yamamoto, et al. (1996). "Role of human cytochrome P4502A6 in C-oxidation of nicotine." Drug Metab Dispos 24(11):

208 Naqvi, N. H., D. Rudrauf, et al. (2007). "Damage to the insula disrupts addiction to cigarette smoking." Science 315(5811): Neurath, G. B. (1994). "Aspects of the oxidative metabolism of nicotine." Clin Investig 72(3): Novotny, T. E., K. E. Warner, et al. (1988). "Smoking by blacks and whites: socioeconomic and demographic differences." Am J Public Health 78(9): Nunoya, K., T. Yokoi, et al. (1998). "A new deleted allele in the human cytochrome P450 2A6 (CYP2A6) gene found in individuals showing poor metabolic capacity to coumarin and (+)-cis-3,5-dimethyl-2-(3-pyridyl)thiazolidin-4-one hydrochloride (SM-12502)." Pharmacogenetics 8(3): Nunoya, K., T. Yokoi, et al. (1999). "Homologous unequal cross-over within the human CYP2A gene cluster as a mechanism for the deletion of the entire CYP2A6 gene associated with the poor metabolizer phenotype." J Biochem 126(2): Nunoya, K. I., T. Yokoi, et al. (1999). "A new CYP2A6 gene deletion responsible for the in vivo polymorphic metabolism of (+)-cis-3,5-dimethyl-2-(3-pyridyl)thiazolidin-4-one hydrochloride in humans." J Pharmacol Exp Ther 289(1): Nurfadhlina, M., K. Foong, et al. (2006). "CYP2A6 polymorphisms in Malays, Chinese and Indians." Xenobiotica 36(8): Obach, R. S. and H. van Vunakis (1990). "Radioimmunoassay of nicotine-delta 1'(5')-iminium ion, an intermediate formed during the metabolism of nicotine to cotinine." Drug Metab Dispos 18(4): Office of National Drug Control Policy. (2004). The economic costs of drug abuse in the united states, Washington, D.C., Executive Office of the President Publication No Okuyemi, K. S., K. J. Harris, et al. (2002). "Light smokers: issues and recommendations." Nicotine Tob Res 4 Suppl 2: S Olausson, P., J. D. Jentsch, et al. (2004). "Repeated nicotine exposure enhances responding with conditioned reinforcement." Psychopharmacology (Berl) 173(1-2): Oscarson, M., R. A. McLellan, et al. (2002). "Characterization of a novel CYP2A7/CYP2A6 hybrid allele (CYP2A6*12) that causes reduced CYP2A6 activity." Hum Mutat 20(4): Oscarson, M., R. A. McLellan, et al. (1999). "Identification and characterisation of novel polymorphisms in the CYP2A locus: implications for nicotine metabolism." FEBS Lett 460(2):

209 Oscarson, M., R. A. McLellan, et al. (1999). "Characterisation and PCR-based detection of a CYP2A6 gene deletion found at a high frequency in a Chinese population." FEBS Lett 448(1): Owen, N., P. Kent, et al. (1995). "Low-rate smokers." Prev Med 24(1): Paliwal, A., T. Vaissiere, et al. (2010). "Aberrant DNA methylation links cancer susceptibility locus 15q25.1 to apoptotic regulation and lung cancer." Cancer research 70(7): Pankow, J. F., A. D. Tavakoli, et al. (2003). "Percent free base nicotine in the tobacco smoke particulate matter of selected commercial and reference cigarettes." Chem Res Toxicol 16(8): Park, S. B., P. Jacob, 3rd, et al. (1993). "Stereoselective metabolism of (S)-(-)-nicotine in humans: formation of trans-(s)-(-)-nicotine N-1'-oxide." Chem Res Toxicol 6(6): Parkinson, A., D. R. Mudra, et al. (2004). "The effects of gender, age, ethnicity, and liver cirrhosis on cytochrome P450 enzyme activity in human liver microsomes and inducibility in cultured human hepatocytes." Toxicol Appl Pharmacol 199(3): Pasanen, M., Z. Rannala, et al. (1997). "Hepatitis A impairs the function of human hepatic CYP2A6 in vivo." Toxicology 123(3): Patterson, F., N. Benowitz, et al. (2003). "Individual differences in nicotine intake per cigarette." Cancer Epidemiol Biomarkers Prev 12(5): Patterson, F., R. A. Schnoll, et al. (2008). "Toward personalized therapy for smoking cessation: a randomized placebo-controlled trial of bupropion." Clin Pharmacol Ther 84(3): Perez-Rios, M., M. I. Santiago-Perez, et al. (2009). "Fagerstrom test for nicotine dependence vs heavy smoking index in a general population survey." BMC Public Health 9: 493. Perez-Stable, E. J., N. L. Benowitz, et al. (1995). "Is serum cotinine a better measure of cigarette smoking than self-report?" Prev Med 24(2): Perez-Stable, E. J., B. Herrera, et al. (1998). "Nicotine metabolism and intake in black and white smokers." JAMA 280(2): Peterson, L. A., A. Trevor, et al. (1987). "Stereochemical studies on the cytochrome P-450 catalyzed oxidation of (S)-nicotine to the (S)-nicotine delta 1'(5')-iminium species." J Med Chem 30(2): Peto, R., G. Whitlock, et al. (2010). "Effects of obesity and smoking on U.S. life expectancy." N Engl J Med 362(9): ; author reply

210 Phillips, C. V. and K. K. Heavner (2009). "Smokeless tobacco: the epidemiology and politics of harm." Biomarkers 14 Suppl 1: Pianezza, M. L., E. M. Sellers, et al. (1998). "Nicotine metabolism defect reduces smoking." Nature 393(6687): 750. Picciotto, M. R., M. Zoli, et al. (1998). "Acetylcholine receptors containing the beta2 subunit are involved in the reinforcing properties of nicotine." Nature 391(6663): Pillai, S. G., D. Ge, et al. (2009). "A genome-wide association study in chronic obstructive pulmonary disease (COPD): identification of two major susceptibility loci." PLoS genetics 5(3): e Piper, M. E., D. E. McCarthy, et al. (2006). "Assessing tobacco dependence: a guide to measure evaluation and selection." Nicotine Tob Res 8(3): Piper, M. E., D. E. McCarthy, et al. (2008). "Assessing dimensions of nicotine dependence: an evaluation of the Nicotine Dependence Syndrome Scale (NDSS) and the Wisconsin Inventory of Smoking Dependence Motives (WISDM)." Nicotine Tob Res 10(6): Piper, M. E., T. M. Piasecki, et al. (2004). "A multiple motives approach to tobacco dependence: the Wisconsin Inventory of Smoking Dependence Motives (WISDM-68)." J Consult Clin Psychol 72(2): Pirie, K., R. Peto, et al. (2013). "The 21st century hazards of smoking and benefits of stopping: a prospective study of one million women in the UK." Lancet 381(9861): Pitarque, M., O. von Richter, et al. (2004). "A nicotine C-oxidase gene (CYP2A6) polymorphism important for promoter activity." Hum Mutat 23(3): Pons, S., L. Fattore, et al. (2008). "Crucial role of alpha4 and alpha6 nicotinic acetylcholine receptor subunits from ventral tegmental area in systemic nicotine self-administration." J Neurosci 28(47): Pooling Group of the American Heart Association (1978). "Relationship of blood pressure, serum cholesterol, smoking habit, relative weight and ECG abnormalities to incidence of major coronary events: final report of the pooling project. The pooling project research group." J Chronic Dis 31(4): Prescott, E., H. Scharling, et al. (2002). "Importance of light smoking and inhalation habits on risk of myocardial infarction and all cause mortality. A 22 year follow up of men and women in The Copenhagen City Heart Study." J Epidemiol Community Health 56(9): Purcell, S., B. Neale, et al. (2007). "PLINK: a tool set for whole-genome association and population-based linkage analyses." American journal of human genetics 81(3):

211 Rae, J. M., M. D. Johnson, et al. (2001). "Rifampin is a selective, pleiotropic inducer of drug metabolism genes in human hepatocytes: studies with cdna and oligonucleotide expression arrays." J Pharmacol Exp Ther 299(3): Rao, Y., E. Hoffmann, et al. (2000). "Duplications and defects in the CYP2A6 gene: identification, genotyping, and in vivo effects on smoking." Mol Pharmacol 58(4): Raunio, H., A. Rautio, et al. (2001). "Polymorphisms of CYP2A6 and its practical consequences." Br J Clin Pharmacol 52(4): Reavill, C., P. Jenner, et al. (1988). "High affinity binding of [3H] (-)-nicotine to rat brain membranes and its inhibition by analogues of nicotine." Neuropharmacology 27(3): Renner, C. C., C. Enoch, et al. (2005). "Iqmik: a form of smokeless tobacco used among Alaska natives." Am J Health Behav 29(6): Renner, C. C., A. P. Lanier, et al. (2013). "Tobacco use among southwestern Alaska Native people." Nicotine Tob Res 15(2): Rickert, W. S. and J. C. Robinson (1981). "Estimating the hazards of less hazardous cigarettes. II. Study of cigarette yields of nicotine, carbon monoxide, and hydrogen cyanide in relation to levels of cotinine, carboxyhemoglobin, and thiocyanate in smokers." J Toxicol Environ Health 7(3-4): Rodu, B., B. Stegmayr, et al. (2003). "Evolving patterns of tobacco use in northern Sweden." J Intern Med 253(6): Rose, J. E. (2006). "Nicotine and nonnicotine factors in cigarette addiction." Psychopharmacology (Berl) 184(3-4): Rose, J. E., F. M. Behm, et al. (1999). "Arterial nicotine kinetics during cigarette smoking and intravenous nicotine administration: implications for addiction." Drug Alcohol Depend 56(2): Rose, J. E., A. G. Mukhin, et al. (2010). "Kinetics of brain nicotine accumulation in dependent and nondependent smokers assessed with PET and cigarettes containing 11C-nicotine." Proc Natl Acad Sci U S A 107(11): Rossini, A., T. de Almeida Simao, et al. (2008). "CYP2A6 polymorphisms and risk for tobaccorelated cancers." Pharmacogenomics 9(11): Saccone, N. L., R. C. Culverhouse, et al. (2010). "Multiple independent loci at chromosome 15q25.1 affect smoking quantity: a meta-analysis and comparison with lung cancer and COPD." PLoS genetics 6(8). 190

212 Saccone, N. L., T. H. Schwantes-An, et al. (2010). "Multiple cholinergic nicotinic receptor genes affect nicotine dependence risk in African and European Americans." Genes, brain, and behavior 9(7): Saccone, N. L., J. C. Wang, et al. (2009). "The CHRNA5-CHRNA3-CHRNB4 nicotinic receptor subunit gene cluster affects risk for nicotine dependence in African-Americans and in European-Americans." Cancer research 69(17): Saccone, S. F., A. L. Hinrichs, et al. (2007). "Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs." Hum Mol Genet 16(1): Sakoda, L. C., M. M. Loomis, et al. (2011). "Chromosome 15q variants, diet, and lung cancer susceptibility in cigarette smokers." Cancer Causes Control 22(3): Schachter, S., L. T. Kozlo-ski, et al. (1977). "2. Effects of urinary ph on cigarette smoking." J Exp Psychol Gen 106(1): Schane, R. E., P. M. Ling, et al. (2010). "Health effects of light and intermittent smoking: a review." Circulation 121(13): Schepers, G. and R. A. Walk (1988). "Cotinine determination by immunoassays may be influenced by other nicotine metabolites." Arch Toxicol 62(5): Scherer, G. (1999). "Smoking behaviour and compensation: a review of the literature." Psychopharmacology (Berl) 145(1): Scherer, G. (2006). "Carboxyhemoglobin and thiocyanate as biomarkers of exposure to carbon monoxide and hydrogen cyanide in tobacco smoke." Exp Toxicol Pathol 58(2-3): Scherer, G., J. Engl, et al. (2007). "Relationship between machine-derived smoke yields and biomarkers in cigarette smokers in Germany." Regul Toxicol Pharmacol 47(2): Schneider, N. G., R. E. Olmstead, et al. (2001). "The nicotine inhaler: clinical pharmacokinetics and comparison with other nicotine treatments." Clin Pharmacokinet 40(9): Schoedel, K. A., E. B. Hoffmann, et al. (2004). "Ethnic variation in CYP2A6 and association of genetically slow nicotine metabolism and smoking in adult Caucasians." Pharmacogenetics 14(9): Schroeder, S. (2013). "Smoking-related mortality in the United States." N Engl J Med 368(18): Schuller, H. M. (2009). "Is cancer triggered by altered signalling of nicotinic acetylcholine receptors?" Nat Rev Cancer 9(3):

213 Schuller, H. M., H. P. Witschi, et al. (1990). "Pathobiology of lung tumors induced in hamsters by 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and the modulating effect of hyperoxia." Cancer Res 50(6): Seeley, R. J. and D. A. Sandoval (2011). "Neuroscience: weight loss through smoking." Nature 475(7355): Sellers, E. M., H. L. Kaplan, et al. (2000). "Inhibition of cytochrome P450 2A6 increases nicotine's oral bioavailability and decreases smoking." Clin Pharmacol Ther 68(1): Sellers, E. M., Y. Ramamoorthy, et al. (2003). "The effect of methoxsalen on nicotine and 4- (methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) metabolism in vivo." Nicotine Tob Res 5(6): Sexton, M. and J. R. Hebel (1984). "A clinical trial of change in maternal smoking and its effect on birth weight." JAMA 251(7): Shadel, W. G., S. Shiffman, et al. (2000). "Current models of nicotine dependence: what is known and what is needed to advance understanding of tobacco etiology among youth." Drug Alcohol Depend 59 Suppl 1: S9-22. Sherva, R., K. Wilhelmsen, et al. (2008). "Association of a single nucleotide polymorphism in neuronal acetylcholine receptor subunit alpha 5 (CHRNA5) with smoking status and with 'pleasurable buzz' during early experimentation with smoking." Addiction 103(9): Shiffman, S. (1989). "Tobacco "chippers"--individual differences in tobacco dependence." Psychopharmacology 97(4): Shiffman, S. (2009). "Light and intermittent smokers: background and perspective." Nicotine Tob Res 11(2): Shiffman, S., L. B. Fischer, et al. (1990). "Nicotine exposure among nondependent smokers." Arch Gen Psychiatry 47(4): Shiffman, S. and J. Paty (2006). "Smoking patterns and dependence: contrasting chippers and heavy smokers." J Abnorm Psychol 115(3): Shiffman, S., J. A. Paty, et al. (1995). "Nicotine withdrawal in chippers and regular smokers: subjective and cognitive effects." Health psychology : official journal of the Division of Health Psychology, American Psychological Association 14(4): Shiffman, S., M. Zettler-Segal, et al. (1992). "Nicotine elimination and tolerance in nondependent cigarette smokers." Psychopharmacology (Berl) 109(4): Shimada, T., H. Yamazaki, et al. (1996). "Ethnic-related differences in coumarin 7- hydroxylation activities catalyzed by cytochrome P4502A6 in liver microsomes of Japanese and Caucasian populations." Xenobiotica 26(4):

214 Shimada, T., H. Yamazaki, et al. (1994). "Interindividual variations in human liver cytochrome P-450 enzymes involved in the oxidation of drugs, carcinogens and toxic chemicals: studies with liver microsomes of 30 Japanese and 30 Caucasians." J Pharmacol Exp Ther 270(1): Shiraishi, K., T. Kohno, et al. (2009). "Contribution of nicotine acetylcholine receptor polymorphisms to lung cancer risk in a smoking-independent manner in the Japanese." Carcinogenesis 30(1): Siedlinski, M., M. H. Cho, et al. (2011). "Genome-wide association study of smoking behaviours in patients with COPD." Thorax 66(10): Signorello, L. B., M. K. Hargreaves, et al. (2005). "Southern community cohort study: establishing a cohort to investigate health disparities." J Natl Med Assoc 97(7): Siu, E. C. and R. F. Tyndale (2007). "Non-nicotinic therapies for smoking cessation." Annu Rev Pharmacol Toxicol 47: Siu, E. C. and R. F. Tyndale (2008). "Selegiline is a mechanism-based inactivator of CYP2A6 inhibiting nicotine metabolism in humans and mice." J Pharmacol Exp Ther 324(3): Slemmer, J. E., B. R. Martin, et al. (2000). "Bupropion is a nicotinic antagonist." J Pharmacol Exp Ther 295(1): Smith, G. B., A. Castonguay, et al. (1999). "Biotransformation of the tobacco-specific carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) in freshly isolated human lung cells." Carcinogenesis 20(9): Smith, J. J., E. D. Ferucci, et al. (2010). "Tobacco use among Alaska Native people in the EARTH study." Nicotine Tob Res 12(8): Sotaniemi, E. A., A. Rautio, et al. (1995). "CYP3A4 and CYP2A6 activities marked by the metabolism of lignocaine and coumarin in patients with liver and kidney diseases and epileptic patients." Br J Clin Pharmacol 39(1): Spitz, M. R., C. I. Amos, et al. (2008). "The CHRNA5-A3 region on chromosome 15q is a risk factor both for nicotine dependence and for lung cancer." J Natl Cancer Inst 100(21): SRNT Subcommittee on Biochemical Verification (2002). "Biochemical verification of tobacco use and cessation." Nicotine Tob Res 4(2): St Charles, F. K., G. R. Krautter, et al. (2006). "A comparison of nicotine dose estimates in smokers between filter analysis, salivary cotinine, and urinary excretion of nicotine metabolites." Psychopharmacology (Berl) 189(3):

215 St Helen, G., M. Novalen, et al. (2012). "Reproducibility of the nicotine metabolite ratio in cigarette smokers." Cancer Epidemiol Biomarkers Prev 21(7): Stepanov, I., S. G. Carmella, et al. (2009). "Evidence for endogenous formation of N'- nitrosonornicotine in some long-term nicotine patch users." Nicotine Tob Res 11(1): Stepanov, I., A. Knezevich, et al. (2012). "Carcinogenic tobacco-specific N-nitrosamines in US cigarettes: three decades of remarkable neglect by the tobacco industry." Tob Control 21(1): Stepanov, I., P. Upadhyaya, et al. (2008). "Extensive metabolic activation of the tobacco-specific carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone in smokers." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 17(7): StHelen, G., M. L. Goniewicz, et al. (2012). "Exposure and kinetics of polycyclic aromatic hydrocarbons (PAHs) in cigarette smokers." Chem Res Toxicol 25(4): Stolerman, I. P., S. Chamberlain, et al. (2004). "The role of nicotinic receptor alpha 7 subunits in nicotine discrimination." Neuropharmacology 46(3): Strasser, A. A., N. L. Benowitz, et al. (2011). "Nicotine metabolite ratio predicts smoking topography and carcinogen biomarker level." Cancer Epidemiol Biomarkers Prev 20(2): Strasser, A. A., V. Malaiyandi, et al. (2007). "An association of CYP2A6 genotype and smoking topography." Nicotine Tob Res 9(4): Su, T., Z. Bao, et al. (2000). "Human cytochrome P450 CYP2A13: predominant expression in the respiratory tract and its high efficiency metabolic activation of a tobacco-specific carcinogen, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone." Cancer Res 60(18): Swan, G. E., N. L. Benowitz, et al. (2004). "Pharmacogenetics of nicotine metabolism in twins: methods and procedures." Twin research : the official journal of the International Society for Twin Studies 7(5): Swan, G. E., N. L. Benowitz, et al. (2005). "Nicotine metabolism: the impact of CYP2A6 on estimates of additive genetic influence." Pharmacogenet Genomics 15(2): Swan, G. E., D. Carmelli, et al. (1997). "Heavy consumption of cigarettes, alcohol and coffee in male twins." J Stud Alcohol 58(2): Taavitsainen, P., R. Juvonen, et al. (2001). "In vitro inhibition of cytochrome P450 enzymes in human liver microsomes by a potent CYP2A6 inhibitor, trans-2-phenylcyclopropylamine 194

216 (tranylcypromine), and its nonamine analog, cyclopropylbenzene." Drug Metab Dispos 29(3): Taioli, E., S. Garbers, et al. (1997). "Effects of indole-3-carbinol on the metabolism of 4- (methylnitrosamino)-1-(3-pyridyl)-1-butanone in smokers." Cancer Epidemiol Biomarkers Prev 6(7): Talavera, K., M. Gees, et al. (2009). "Nicotine activates the chemosensory cation channel TRPA1." Nat Neurosci 12(10): Tapper, A. R., S. L. McKinney, et al. (2004). "Nicotine activation of alpha4* receptors: sufficient for reward, tolerance, and sensitization." Science 306(5698): Tateishi, T., H. Nakura, et al. (1997). "A comparison of hepatic cytochrome P450 protein expression between infancy and postinfancy." Life Sci 61(26): Taylor, K. L., J. F. Kerner, et al. (1997). "Ever vs never smoking among an urban, multiethnic sample of Haitian-, Caribbean-, and U.S.-born blacks." Prev Med 26(6): Ter-Minassian, M., K. Asomaning, et al. (2012). "Genetic variability in the metabolism of the tobacco-specific nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) to 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL)." International journal of cancer. Journal international du cancer 130(6): Thorgeirsson, T. E., F. Geller, et al. (2008). "A variant associated with nicotine dependence, lung cancer and peripheral arterial disease." Nature 452(7187): Thorgeirsson, T. E., D. F. Gudbjartsson, et al. (2010). "Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior." Nat Genet 42(5): Thuerauf, N., K. Markovic, et al. (2006). "The influence of mecamylamine on trigeminal and olfactory chemoreception of nicotine." Neuropsychopharmacology 31(2): Thun, M. J., B. D. Carter, et al. (2013). "50-year trends in smoking-related mortality in the United States." N Engl J Med 368(4): Thun, M. J., C. A. Lally, et al. (1997). "Cigarette smoking and changes in the histopathology of lung cancer." J Natl Cancer Inst 89(21): Tillgren, P., B. J. Haglund, et al. (1996). "The sociodemographic pattern of tobacco cessation in the 1980s: results from a panel study of living condition surveys in Sweden." J Epidemiol Community Health 50(6): Timofeeva, M. N., J. D. McKay, et al. (2011). "Genetic polymorphisms in 15q25 and 19q13 loci, cotinine levels, and risk of lung cancer in EPIC." Cancer Epidemiol Biomarkers Prev 20(10):

217 Tomar, S. L. (2003). "Trends and patterns of tobacco use in the United States." Am J Med Sci 326(4): Tournier, J. M., K. Maouche, et al. (2006). "alpha3alpha5beta2-nicotinic acetylcholine receptor contributes to the wound repair of the respiratory epithelium by modulating intracellular calcium in migrating cells." Am J Pathol 168(1): Townsend, J., P. Roderick, et al. (1994). "Cigarette smoking by socioeconomic group, sex, and age: effects of price, income, and health publicity." BMJ 309(6959): Travis, W. D., E. Brambilla, et al. (2011). "International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society: international multidisciplinary classification of lung adenocarcinoma: executive summary." Proc Am Thorac Soc 8(5): Trinidad, D. R., E. J. Perez-Stable, et al. (2009). "Intermittent and light daily smoking across racial/ethnic groups in the United States." Nicotine Tob Res 11(2): True, W. R., A. C. Heath, et al. (1997). "Genetic and environmental contributions to smoking." Addiction 92(10): Truong, T., R. J. Hung, et al. (2010). "Replication of lung cancer susceptibility loci at chromosomes 15q25, 5p15, and 6p21: a pooled analysis from the International Lung Cancer Consortium." Journal of the National Cancer Institute 102(13): Tyndale, R. F. and E. M. Sellers (2002). "Genetic variation in CYP2A6-mediated nicotine metabolism alters smoking behavior." Ther Drug Monit 24(1): U.S Department of Health and Human Services (2010). How Tobacco Smoke Causes Disease: The Biology and Behavioral Basis for Smoking-Attributable Disease: A Report of the Surgeon General. Atlanta (GA). U.S. Bureau of the Census (2004). "Educational attainment in the United States: Economics and Statistics Administration.". U.S. Bureau of the Census (2005). "Income, poverty and health coverage in the United States." Uhl, G. R., T. Drgon, et al. (2010). "Genome-wide association for smoking cessation success in a trial of precessation nicotine replacement." Mol Med 16(11-12): Uhl, G. R., Q. R. Liu, et al. (2007). "Molecular genetics of nicotine dependence and abstinence: whole genome association using 520,000 SNPs." BMC Genet 8: 10. Uhl, G. R., Q. R. Liu, et al. (2008). "Molecular genetics of successful smoking cessation: convergent genome-wide association study results." Arch Gen Psychiatry 65(6): Uhl, G. R., D. Walther, et al. (2011). "Menthol preference among smokers: association with TRPA1 variants." Nicotine Tob Res 13(12):

218 United States Department of Health and Human Services (1990). "The Surgeon General's 1990 Report on The Health Benefits of Smoking Cessation. Executive Summary." MMWR Recomm Rep 39(RR-12): i-xv, United States Public Health Service. Office of the Surgeon General. (1998). "Tobacco Use Among U.S. Racial/Ethnic Minority Groups African Americans, American Indians and Alaska Natives, Asian Americans and Pacific Islanders, and Hispanics: A Report of the Surgeon General.". United States Public Health Service. Office of the Surgeon General. (2004). The health consequences of smoking : a report of the Surgeon General, U.S. Dept. of health and Human Services, Public Health Service. United States. Surgeon-General's Office. (2006). The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta (GA). Vainio, H. and E. Weiderpass (2003). "Smokeless tobacco: harm reduction or nicotine overload?" Eur J Cancer Prev 12(2): van Meerbeeck, J. P., D. A. Fennell, et al. (2011). "Small-cell lung cancer." Lancet 378(9804): Vink, J. M., A. L. Beem, et al. (2004). "Linkage analysis of smoking initiation and quantity in Dutch sibling pairs." Pharmacogenomics J 4(4): von Richter, O., M. Pitarque, et al. (2004). "Polymorphic NF-Y dependent regulation of human nicotine C-oxidase (CYP2A6)." Pharmacogenetics 14(6): Wagenknecht, L. E., G. R. Cutter, et al. (1990). "Racial differences in serum cotinine levels among smokers in the Coronary Artery Risk Development in (Young) Adults study." American journal of public health 80(9): Walters, C. L., S. Brown, et al. (2006). "The beta2 but not alpha7 subunit of the nicotinic acetylcholine receptor is required for nicotine-conditioned place preference in mice." Psychopharmacology (Berl) 184(3-4): Wang, J., Q. Liang, et al. (2011). "Is 24h nicotine equivalents a surrogate for smoke exposure based on its relationship with other biomarkers of exposure?" Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals 16(2): Wang, J., M. Pitarque, et al. (2006). "3'-UTR polymorphism in the human CYP2A6 gene affects mrna stability and enzyme expression." Biochem Biophys Res Commun 340(2): Wang, J. C., C. Cruchaga, et al. (2009). "Risk for nicotine dependence and lung cancer is conferred by mrna expression levels and amino acid change in CHRNA5." Human molecular genetics 18(16):

219 Wassenaar, C. A., Q. Dong, et al. (2011). "Relationship Between CYP2A6 and CHRNA5- CHRNA3-CHRNB4 Variation and Smoking Behaviors and Lung Cancer Risk." Journal of the National Cancer Institute 103(17): Wennmalm, A., G. Benthin, et al. (1991). "Relation between tobacco use and urinary excretion of thromboxane A2 and prostacyclin metabolites in young men." Circulation 83(5): Williams, M. A., R. Mittendorf, et al. (1992). "Cigarettes, coffee, and preterm premature rupture of the membranes." Am J Epidemiol 135(8): Winbo, I., F. Serenius, et al. (2001). "Maternal risk factors for cause-specific stillbirth and neonatal death." Acta Obstet Gynecol Scand 80(3): Wipfli, H. and J. M. Samet (2009). "Global economic and health benefits of tobacco control: part 1." Clin Pharmacol Ther 86(3): Wong, H. L., S. E. Murphy, et al. (2005). "Cytochrome P450 2A-catalyzed metabolic activation of structurally similar carcinogenic nitrosamines: N'-nitrosonornicotine enantiomers, N- nitrosopiperidine, and N-nitrosopyrrolidine." Chemical research in toxicology 18(1): World Health Organization and Research for International Tobacco Control (2008). WHO report on the global tobacco epidemic, 2008 : the MPOWER package. Geneva, World Health Organization. Wortley, P. M., C. G. Husten, et al. (2003). "Nondaily smokers: a descriptive analysis." Nicotine Tob Res 5(5): Wu, C., Z. Hu, et al. (2009). "Genetic variants on chromosome 15q25 associated with lung cancer risk in Chinese populations." Cancer research 69(12): Wynder, E. L., E. A. Graham, et al. (1953). "Experimental production of carcinoma with cigarette tar." Cancer Res 13(12): Xia, X. Y., R. X. Peng, et al. (2002). "In vitro metabolic characteristics of cytochrome P-450 2A6 in Chinese liver microsomes." Acta Pharmacol Sin 23(5): Xian, H., J. F. Scherrer, et al. (2003). "The heritability of failed smoking cessation and nicotine withdrawal in twins who smoked and attempted to quit." Nicotine Tob Res 5(2): Xu, C., Y. S. Rao, et al. (2002). "An in vivo pilot study characterizing the new CYP2A6*7, *8, and *10 alleles." Biochem Biophys Res Commun 290(1): Yamanaka, H., M. Nakajima, et al. (2005). "CYP2A6 AND CYP2B6 are involved in nornicotine formation from nicotine in humans: interindividual differences in these contributions." Drug Metab Dispos 33(12):

220 Yamanaka, H., M. Nakajima, et al. (2004). "Metabolic profile of nicotine in subjects whose CYP2A6 gene is deleted." Eur J Pharm Sci 22(5): Yamano, S., J. Tatsuno, et al. (1990). "The CYP2A3 gene product catalyzes coumarin 7- hydroxylation in human liver microsomes." Biochemistry 29(5): Yamazaki, H., K. Inoue, et al. (1999). "Roles of CYP2A6 and CYP2B6 in nicotine C-oxidation by human liver microsomes." Arch Toxicol 73(2): Yang, M., N. Kunugita, et al. (2001). "Individual differences in urinary cotinine levels in Japanese smokers: relation to genetic polymorphism of drug-metabolizing enzymes." Cancer Epidemiol Biomarkers Prev 10(6): Yoshida, R., M. Nakajima, et al. (2002). "Genetic polymorphisms in human CYP2A6 gene causing impaired nicotine metabolism." Br J Clin Pharmacol 54(5): Young, R. P., R. J. Hopkins, et al. (2008). "Lung cancer gene associated with COPD: triple whammy or possible confounding effect?" Eur Respir J 32(5): Yu, Y., C. Panhuysen, et al. (2006). "Intronic variants in the dopa decarboxylase (DDC) gene are associated with smoking behavior in European-Americans and African-Americans." Hum Mol Genet 15(14): Yuan, J. M., Y. T. Gao, et al. (2011). "Urinary levels of cigarette smoke constituent metabolites are prospectively associated with lung cancer development in smokers." Cancer research 71(21): Yuan, J. M., A. D. Knezevich, et al. (2011). "Urinary levels of the tobacco-specific carcinogen N'-nitrosonornicotine and its glucuronide are strongly associated with esophageal cancer risk in smokers." Carcinogenesis 32(9): Yuan, J. M., W. P. Koh, et al. (2009). "Urinary levels of tobacco-specific nitrosamine metabolites in relation to lung cancer development in two prospective cohorts of cigarette smokers." Cancer research 69(7): Zevin, S., P. Jacob, et al. (2000). "Clinical pharmacology of oral cotinine." Drug Alcohol Depend 60(1): Zhang, W., T. Kilicarslan, et al. (2001). "Evaluation of methoxsalen, tranylcypromine, and tryptamine as specific and selective CYP2A6 inhibitors in vitro." Drug Metab Dispos 29(6): Zhang, X., K. Ameno, et al. (2002). "Effects of whole deletion of CYP2A6 on nicotine metabolism in humans." Drug Chem Toxicol 25(2): Zhu, A. Z., M. J. Binnington, et al. (2013). "Alaska Native smokers and smokeless tobacco users with slower CYP2A6 activity have lower tobacco consumption, lower tobacco-specific 199

221 nitrosamine exposure and lower tobacco-specific nitrosamine bioactivation." Carcinogenesis 34(1): Zhu, A. Z., L. S. Cox, et al. (2012). "CYP2B6 and Bupropion's Smoking-Cessation Pharmacology: The Role of Hydroxybupropion." Clin Pharmacol Ther 92(6): Zhu, A. Z., C. C. Renner, et al. (2013). "CHRNA5-A3-B4 genetic variants alter nicotine intake and interact with tobacco use to influence body weight in Alaska Native tobacco users." Addiction 108(10): Zhu, A. Z., C. C. Renner, et al. (2013). "The ability of plasma cotinine to predict nicotine and carcinogen exposure is altered by differences in CYP2A6: the influence of genetics, race, and sex." Cancer Epidemiol Biomarkers Prev 22(4): Zhu, A. Z., Q. Zhou, et al. (2013). "Variation in trans-3'-hydroxycotinine glucuronidation does not alter the nicotine metabolite ratio or nicotine intake." PLoS One 8(8): e Zuccaro, P., S. Pichini, et al. (1997). "Interference of nicotine metabolites in cotinine determination by RIA." Clin Chem 43(1):

222 7 APPENDICES 201

223 Appendix A: Full text: Binnington, J. M., et al. (2012). "CYP2A6 and CYP2B6 genetic variation and its association with nicotine metabolism in South Western Alaska Native people." Pharmacogenet Genomics 22(6): OBJECTIVES: Alaska Native (AN) people have a high prevalence of tobacco use and associated morbidity and mortality when compared with the general USA population. Variations in the CYP2A6 and CYP2B6 genes, encoding enzymes responsible for nicotine metabolic inactivation and procarcinogen activation, have not been characterized in AN and may contribute toward the increased risk. METHODS: AN people (n=400) residing in the Bristol Bay region of South Western Alaska were recruited for a cross-sectional study on tobacco use. They were genotyped for CYP2A6*1X2A, *1X2B, *1B, *2, *4, *7, *8, *9, *10, *12, *17, *35 and CYP2B6*4, *6, *9 and provided plasma and urine samples for the measurement of nicotine and metabolites. RESULTS: CYP2A6 and CYP2B6 variant frequencies among the AN Yupik people (n=361) were significantly different from those in other ethnicities. Nicotine metabolism [as measured by the plasma and urinary ratio of metabolites trans-3'-hydroxycotinine to cotinine (3HC/COT)] was significantly associated with CYP2A6 (P<0.001), but not CYP2B6 genotype (P=0.95) when controlling for known covariates. It was noteworthy that the plasma 3HC/COT ratios were high in the entire Yupik people, and among the Yupik CYP2A6 wild-type participants, they were substantially higher than those in previously characterized racial/ethnic groups (P<0.001 vs. Caucasians and African Americans). CONCLUSION: Yupik AN people have a unique CYP2A6 genetic profile that associated strongly with in-vivo nicotine metabolism. More rapid CYP2A6-mediated nicotine and nitrosamine metabolism in the Yupik people may modulate the risk of tobacco-related diseases. 202

224 Appendix B: Full text: Zhu, A. Z., et al. (2012). "CYP2B6 and Bupropion's Smoking-Cessation Pharmacology: The Role of Hydroxybupropion." Clin Pharmacol Ther 92(6): Bupropion is indicated to promote smoking cessation. Animal studies suggest that the pharmacologic activity of bupropion can be mediated by its major metabolite, hydroxybupropion. We measured plasma bupropion and its metabolite levels in a double-blind, placebo controlled, randomized smoking-cessation trial. Among the treatment-adherent individuals, higher hydroxybupropion concentrations (per mug/ml) resulted in better smoking-cessation outcomes (week 3, 7, and 26 odds ratio (OR) = 2.82, 2.96, and 2.37, respectively, P = ); this was not observed with bupropion levels (OR = , P = ). Genetic variation in CYP2B6, the enzyme that metabolizes bupropion to hydroxybupropion, was identified as a significant source of variability in hydroxybupropion formation. Our data indicate that hydroxybupropion contributes to the pharmacologic effects of bupropion for smoking cessation, and that variability in response to bupropion treatment is related to variability in CYP2B6- mediated hydroxybupropion formation. These findings suggest that dosing of bupropion to achieve a hydroxybupropion level of 0.7 mug/ml or increasing bupropion dose for CYP2B6 slow metabolizers could improve bupropion's cessation outcomes. 203

225 Appendix C: Full text: Benowitz, N. L., et al. (2013). "Influence of CYP2B6 genetic variants on plasma and urine concentrations of bupropion and metabolites at steady state." Pharmacogenet Genomics 23(3): BACKGROUND: Bupropion, an antidepressant and smoking cessation medication, is metabolized to hydroxybupropion (HB), an active metabolite, primarily by CYP2B6. OBJECTIVES: To compare plasma concentrations of bupropion and metabolites at steady state in healthy volunteers with and without CYP2B6 genetic variants. METHODS: In a genotype-guided study of 42 healthy individuals, we measured the plasma and urine concentrations of bupropion and its metabolites, HB, threohydrobupropion, and erythrohydrobupropion after 7 days of sustained-release bupropion dosing. RESULTS: CYP2B6*6 and *18 gene variants were associated with ~33% reduced concentrations of HB, with no effects on concentrations of bupropion or other metabolites. We could account for 50% of the variation in HB concentrations in a model including genotype and sex. CONCLUSION: As HB is active and its steady-state concentrations are more than 10 times higher than bupropion, CYP2B6 variants are likely to affect pharmacological activity. Because of the large individual variation within the genotype group, the use of therapeutic drug monitoring for dose optimization may be necessary. 204

226 Appendix D: Full text: Zhu, A. Z., et al. (2013). "Variation in trans-3'-hydroxycotinine glucuronidation does not alter the nicotine metabolite ratio or nicotine intake." PLoS One 8(8): e BACKGROUND: CYP2A6 metabolizes nicotine to its primary metabolite cotinine and also mediates the metabolism of cotinine to trans-3'-hydroxycotinine (3HC). The ratio of 3HC to cotinine (the "nicotine metabolite ratio", NMR) is an in vivo marker for the rate of CYP2A6 mediated nicotine metabolism, and total nicotine clearance, and has been associated with differences in numerous smoking behaviors. The clearance of 3HC, which affects the NMR, occurs via renal excretion and metabolism by UGT2B17, and possibly UGT2B10, to 3HCglucuronide. We investigated whether slower 3HC glucuronidation alters NMR, altering its ability to predict CYP2A6 activity and reducing its clinical utility. METHODS: Plasma NMR, three urinary NMRs, three urinary 3HC glucuronidation phenotypes and total nicotine equivalents were examined in 540 African American smokers. The UGT2B17 gene deletion and UGT2B10*2 were genotyped. RESULTS: The UGT2B17 gene deletion, but not UGT2B10*2 genotype, was associated with slower 3HC glucuronidation (indicated by three 3HC-glucuronidation phenotypes), indicating its role in this glucuronidation pathway. However, neither lower rates of 3HC glucuronidation, nor the presence of a UGT2B17 and UGT2B10 reduced function allele, altered plasma or urinary NMRs or levels of smoking. CONCLUSIONS: Variation in 3HC glucuronidation activity, including these caused by UGT2B17 gene deletions, did not significantly alter NMR and is therefore unlikely to affect the clinical utility of NMR in smoking behavior and cessation studies. This study demonstrates that NMR is not altered by differences in the rate of 3HC glucuronidation, providing further support that NMR is a reliable indicator of CYP2A6 mediated nicotine metabolism. 205

227 ! Appendix E: Association of CHRNA5-A3-B4 SNP rs with smoking cessation therapy response in African American smokers. 206

228 ! ABSTRACT (150/150) Robust associations between CHRNA5-A3-B4 variants and smoking behaviors exist, however the association with smoking abstinence is less understood, particularly among African Americans. In 1295 African Americans enrolled in two clinical trials, we investigated the association between CHRNA5-A3-B4 and smoking abstinence. A consistent association between rs [a] and lower abstinence during active pharmacotherapy was observed. Rs [A] was associated with lower abstinence with nicotine gum (during-treatment: OR=0.31&P<0.001; end of treatment (EOT): OR=0.51&P=0.02), bupropion (during-treatment: OR=0.54&P=0.05; EOT: OR=0.59&P=0.08) and both together (during-treatment: OR=0.42&P<0.001; EOT: OR=0.55&P=0.004). Additionally, rs588765[t] was associated with abstinence with gum during treatment (OR=2.31&P<0.01). Rs occurred at a low frequency and was not consistently associated with abstinence. CHRNA5-A3-B4 variants were not associated with tobacco consumption and adjustments for smoking behaviors did not alter the associations between rs and smoking abstinence. Together, our data suggest that CHRNA5-A3-B4 variants are not associated with baseline smoking, but influence smoking abstinence during active pharmacotherapy in African Americans. 207

229 ! INTRODUCTION Tobacco smoking is the largest preventable cause of premature death in the United States. There are currently 45 millions smokers in the U.S, and only 3% of them are able to quit smoking each year (1). Twin studies have estimated that the heritability of smoking cessation is roughly 50%, suggesting that genetic factors play an important role in determining smoking cessation outcomes (2). A number of genes have been significantly associated with smoking cessation outcomes in Caucasians (3-5). However, relatively few studies have focused on African American smokers despite their comparatively higher risks of smoking-related morbidity and mortality (6). Nicotine exerts its pharmacologic effects by acting on nicotinic cholinergic receptors in the brain. In Caucasians, multiple independent SNPs (single-nucleotide polymorphisms) in the CHRNA5-A3-B4 gene cluster, which encodes for the α5, α3 and β4 subunits of the nicotinic acetylcholine receptor (nachr), have been associated with smoking quantity (7-11) and smoking cessation outcomes (12-16). These loci included rs and correlated SNPs (sometimes referred as Bin A or Locus 1 ), rs and correlated SNPs (sometimes referred as Bin B or Locus 3 ), and rs and correlated SNPs (sometimes referred as Bin C or Locus 2 ) (11, 17). However, it is not clear whether the influence of CHRNA5-A3-B4 gene variants on smoking cessation is a general effect on smoking cessation (i.e. would alter cessation in placebo treatment), is independent of the specific type of pharmacological treatment (ie would alters all active treatments) or alters cessation for specific pharmacological treatments (i.e nicotine patch). One study suggested that the association between CHRNA5-A3-B4 variants (rs [Bin A] and rs [Bin B]) and smoking cessation is primarily observed among smokers treated with placebo, and was not observed among those who received active pharmacological therapy (15). In contrast, another study reported significant associations 208

230 ! between CHRNA5-A3-B4 variant (rs which is in high linkage disequilibrium with rs ) and smoking cessation outcomes in smokers who were receiving nicotine replacement therapy with little effect observed in the placebo arm (13). A recent study also observed a treatment by genotype interaction on smoking cessation outcomes (i.e. the genotype effects are in opposite directions for placebo vs. nicotine replacement therapy) (18). In African Americans, the associations between CHRNA5-A3-B4 gene variants and smoking behaviors are not as well understood. While some studies reported positive associations between rs and smoking behaviors in African American smokers (11), other studies were not able to replicate this finding (19, 20). The low allele frequency of rs (0% to 8% in African Americans compared to 38% to 40% in Caucasians) could contribute to this discrepancy. However, a very large genome-wide meta-analysis in African American smokers (N=32,389) identified a significant association between rs within CHRNA5-A3-B4 and self-reported cigarettes per day (CPD) but no significant associations between rs or rs and CPD (19). We are not aware of any studies that have investigated the association between CHRNA5-A3-B4 gene variants and smoking cessation in African American smokers. Here we used two placebo controlled clinical trials to compare the influence of CHRNA5- A3-B4 variants on smoking cessation outcomes in African Americans treated with placebo and active pharmacological treatments. We hypothesized that there would be a significant association between CHRNA5-A3-B4 gene variants and smoking cessation outcomes in the active pharmacological treatment arms as previously reported by Munafò and colleagues (13). Since rs occurs at a relatively low allele frequency in African Americans, we focused initially on rs , which has previously been significantly associated with CPD and lung cancer risk in African American (19, 21); we then extended the investigation to rs , rs and rs

231 ! RESULTS: Descriptive data of the participants Among the 1295 participants (6, 22), 1143 DNA samples were extracted from blood and genotyped (609 in Study 1 and 534 in Study 2). All four of the genotyped SNPs were in Hardy- Weinberg equilibrium (all P>0.05, Supplementary Table S1). Rs ( Bin A ), rs ( Bin B ), and rs ( Bin C ) were selected to represent three different haplotype bins which were previously associated with smoking behaviors (11). Rs was selected for its role in influencing smoking behaviors in African Americans (19). Rs had a minor allele frequency of 21.3%. Rs had a minor allele frequency of 5.7%. Rs had a minor allele frequency of 31.7%. Rs had a minor allele frequency of 47.9%. These four SNPs were in low linkage disequilibrium (all r 2 = ) suggesting that they were independent of each other (Supplementary Table S1). None of the four genotyped SNPs were significantly associated with baseline demographics, CPD, % smoking mentholated cigarettes, baseline plasma cotinine levels (except with rs in study 2 but not study 1), baseline total nicotine equivalents levels, levels of nicotine dependence or treatment group assignment (Table 1 & Supplementary Table S2). Associations of CHRNA5-A3-B5 variants with smoking abstinence Fig. 1 summarizes the association between CHRNA5-A3-B4 variants and smoking abstinence rates among the participants who received the active nicotine gum treatment (Fig. 1A), the active bupropion treatment (Fig. 1B), any active pharmacological treatment (Fig. 1C), or the placebo treatment (Fig.1D). For additive models please see Supplementary Fig. S1). Some notable associations are highlighted below. Association between rs and smoking abstinence 210

232 ! The A allele of rs was significantly associated with lower abstinence rates in participants who received active pharmacological treatments. Nicotine gum. Among the participants who received the nicotine gum treatment, rs was significantly associated with lower abstinence rates during treatment and weakly at end of treatment (during treatment OR=0.31, 95%CI= , P<0.001; end of treatment OR=0.51, 95%CI= , P= Fig.1A). Adjusting for age, sex, baseline CPD, menthol status and type of counseling sessions did not meaningfully alter the odds ratio between rs and smoking abstinence (adjusted during treatment OR=0.29, 95%CI= , P<0.001; adjusted end of treatment OR=0.48, 95%CI= , P=0.02. Fig.2A). The number needed to treat (NTT) were 6.3 and 14.6 for the GG and the GA/AA group respectively during the nicotine gum treatment. At the end of the nicotine gum treatment, NTT was 13.5 for the GG group (nicotine gum treatment had no benefit in the GA/AA group). Bupropion. As found with nicotine gum, the A allele of rs trended toward a significant association with lower smoking abstinence rates during treatment and at end of treatment among the participants who received active bupropion treatment (during treatment OR=0.54, 95%CI= , P=0.054; end of treatment OR=0.59, 95%CI= , P=0.08. Fig.1B). Adjusting for age, sex, baseline CPD, and menthol status did not meaningfully alter the odds ratios between rs and smoking abstinence (adjusted during treatment OR=0.56, 95%CI= , P=0.07; adjusted end of treatment: OR=0.61, 95%CI= , P=0.12. Fig.2B). During the bupropion treatment, the NTT was 13.6 for the GG group (bupropion treatment had no benefit in the GA/AA group). At the end of the bupropion treatment, NTT were 6.2 and 8.8 for the GG and the GA/AA group, respectively. Combined analyses. In agreement with our primary hypothesis, the A allele of rs was significantly associated with lower smoking abstinence rates during treatment 211

233 ! and at end of treatment among the participants who received any active pharmacological treatments (during treatment OR=0.42, 95%CI= , P<0.001; end of treatment OR=0.55, 95%CI= , P= Fig.1C). Adjusting for age, sex, baseline CPD, menthol status, type of counseling sessions and type of pharmacological treatment did not meaningfully alter the association between rs and smoking abstinence (Adjusted during treatment OR=0.42, 95%CI= , P<0.001; adjusted end of treatment OR=0.55, 95%CI= , P= Fig.2C). No statistically significant association between rs and smoking abstinence was observed at any time-point in the placebo arm (Fig. 1D) even after adjusting for age, sex, baseline CPD, menthol status, and type of counseling sessions (Fig.2C). The association of rs and smoking abstinence In addition to rs , rs was significantly associated with smoking abstinence, but only during treatment. Nicotine gum. The T allele of rs was significantly associated with smoking abstinence during treatment among the participants who received nicotine gum (OR=2.31, 95%CI= , P=0.008 Fig. 1A). Adjusting for age, sex, baseline CPD, menthol status and type of counseling sessions did not alter the association between rs and smoking abstinence (adjusted OR=2.39, 95%CI= , P= Fig.3A). Bupropion. We did not observe any consistent association between rs and smoking abstinence in the bupropion treatment group (Fig.3B) Combined analyses. The T allele of rs was significantly associated with smoking abstinence during treatment among the participants who received active pharmacological treatments (OR=1.85, 95%CI= , P= Fig.1C). Adjusting for age, sex, baseline 212

234 ! CPD, menthol status, type of counseling sessions and type of pharmacological treatment did not meaningfully alter the association between rs and smoking abstinence (adjusted during treatment OR=1.81, 95%CI= , P= Fig.3C). Among the participants who received the placebo treatment (Fig.1D), the T allele of rs was significantly associated with abstinence during treatment (OR=0.49, 95%CI= ; P= Fig.1D). There was also a significant treatment (combined active vs. combined placebo) by rs genotype interaction during treatment (OR=3.75, 95%CI= ; P<0.001). Adjusting for age, sex, baseline CPD, menthol status, and type of counseling sessions did not meaningfully alter the odds ratio between rs and smoking abstinence during treatment (adjusted OR=0.47, 95%CI= , P= Fig.3C). The association of rs and smoking abstinence Fig. 4 summarized the association between smoking abstinence and rs with and without baseline demographic adjustments. In these two clinical trials of African American smokers, we did not observe any consistent association between rs and smoking abstinence (Fig. 4). DISCUSSION We reported novel findings of an association between a CHRNA5-A3-B4 gene variant and smoking abstinence in African Americans. We identified a consistent association between the A allele of rs and lower rates of smoking abstinence during active pharmacotherapy treatment in African American light smokers. CHRNA5-A3-B4 and smoking behaviors Gene variants in CHRNA5-A3-B4, particularly rs and correlated SNPs, have 213

235 ! been consistently associated with heaviness of smoking and the levels of nicotine dependence in Caucasians (9-11, 23). In contrast to a recent meta-analysis in African American smokers (19), we did not observe any significant association between CHRNA5-A3-B4 variants, particularly rs , and baseline smoking behaviors, including self-reported CPD, plasma cotinine levels or urinary total nicotine equivalents. This was unexpected since our study, although smaller in size compared to the meta-analysis, had objective biomarker data. Since it is well known that self-reported CPD does not account for the depth of inhalation and is a relatively weak marker of tobacco exposure (24), we expected the accuracy of biomarker data to compensate for the smaller sample size (N=1142). One reason for the lack of association between tobacco exposure and rs in our study may be that the previous meta-analyses included a substantial number of former smokers whereas our studies included only current smokers (19). It was previously observed that the influence of CHRNA5-A3-B4 gene variants on self-reported CPD is stronger in the former smokers compared to the current smokers (see Table S7 of Amos et al. study (8)). It is also possible that the lower number of cigarettes smoked per day by light smokers in the current study (mean=7.7) in contrast to the previous metaanalysis (mean ranged from ) mitigated the expression of the underlining biological processes caused by the CHRNA5-A3-B4 gene variants on smoking level. However, it is important to note that CPD is a poor marker of tobacco consumption, susceptible to reporting and recalling biases and insensitive to smoking topography. The average cotinine levels, which is an more objective marker of tobacco consumption, in our study (mean=240 ng/ml, standard deviation=138) were comparable to previously observed in Caucasian and American African heavy smokers (mean 170 ng/ml) (24). Previous studies in the CHRNA5-A3-B4 field have suggested objective biomarkers are more sensitive than CPD (7). We have previously shown that CHRNA5-A3-B4 variants are significantly associated with cotinine levels in as few as 163 smokers (25). Therefore, we believe that the accuracy of biomarkers (versus self-report CPD) 214

236 ! compensates for the smaller size of our study. CHRNA5-A3-B4 and smoking abstinence In Caucasians, a number of studies have examined the association between CHRNA5- A3-B4 gene variants and clinical trial outcomes for quitting smoking. These studies have varied in whether the predominant effect of CHRNA5-A3-B4 gene variants was in the placebo arm, a specific treatment arm, or in all active treatment arms more generally (13, 15, 18). Our observations regarding rs and smoking abstinence in African American smokers are in agreement with a previous report by Munafò and colleagues in Caucasians with rs (13). Both studies reported significant associations between CHRNA5-A3-B4 gene variants and abstinence 1) primarily in the active pharmacological therapy groups, with little effect observable within the placebo arm, and 2) only during treatment (no association remains at follow up, after active treatment had stopped). Of note, in Caucasians rs is in high linkage disequilibrium with rs (r 2 =0.90). Therefore, rs may be a better pharmacogenetic marker for smoking cessation than rs /rs as it predicts similar relapse risks in both Caucasians and African Americans. The α5 nachr subunit mediates an inhibitory effect of nicotine on brain reward systems (26). Mice with lower α5 nachr function exhibited increased nicotine intake (26). Since rs was previously associated with increased nicotine intake in African Americans (19), it is likely that rs (or SNPs in high linkage disequilibrium) results in lower α5 nachr function. Both nicotine gum and bupropion could have inhibitory effects on nicotine reward since both of them can bind to the nachr (27, 28). The inhibitory effects of nicotine gum and bupropion may be weaker in individuals with rs (due to their lower α5 function), reducing the efficacy of these treatments. 215

237 ! Our findings with rs and smoking abstinence in African American smokers are very similar to previous findings in Caucasian smokers (18). Both studies observed that the T allele of rs was associated with lower abstinence in the placebo group and higher abstinence when receiving nicotine replacement therapy (with significant interactions). However, the association between rs and smoking abstinence was still observed at 6-month follow up in Caucasians, but not in African American smokers. This could be partially due to the relatively low smoking abstinence rates in African American smokers at 6-month follow up compared with the Caucasian smokers. We did not observe any consistent association between rs and smoking abstinence in this study. It is also worth noting that the direction of the association between rs and smoking abstinence in African Americans was in the opposite direction compared with in Caucasians (18). The A allele of rs was associated lower abstinence with nicotine gum treatment and higher abstinence with placebo treatment in our study of African American smokers. In comparison, the A allele of rs was associated with higher abstinence with nicotine replacement therapy and lower abstinence with placebo treatment in Caucasians (18). It is possible that different linkage disequilibrium/haplotype structures between African Americans and Caucasians contributes to this discrepancy. Overall, our smoking abstinence data and the relatively low prevalence of rs in African American would suggest that rs has very little pharmacogenetic importance in African American smokers. In contrast to the study published by Chen and colleagues (15), we did not observe any long lasting association between CHRNA5-A3-B4 gene variants and smoking abstinence rates in participants who received the placebo treatment. This discrepancy was unlikely to be the results of limited power since the current present investigation had a much bigger placebo group compared to the study by Chen and colleagues (566 in our combined studies versus 132 in the 216

238 ! Chen et al., study (15)). It is possible the effects of the tag SNPs are different among different ethnic groups due to the distinct haplotype structures. Interestingly, adjusting for CPD had little influence on the association between the CHRNA5-A3-B4 gene variants and abstinence in our study and in a number of previous studies which evaluated the association between CHRNA5-A3-B4 gene variants and smoking abstinence (13, 18). This suggests that the influence of CHRNA5-A3-B4 gene variants on smoking abstinence is not related to their modest effect size on altering tobacco consumption. In addition, the impact of rs remained unaltered when we controlled for CYP2A6 and/or CYP2B6 genotype, suggesting the impact of rs on cessation was independent of variation in nicotine or bupropion metabolism. Lastly, our findings suggested that roughly 60% of African Americans (i.e. individuals with rs [g] allele) would benefit greatly from active smoking cessation treatments, whereas the 40% with the rs [a] allele may not. This demonstrates the potential value of pharmacogenetic approaches in improving smoking cessation outcomes among African American smokers (29, 30). Strength and Limitations A major strength of our study is that the smoking status (and baseline level of smoking) was biochemically verified. Our selection of African American light smokers can be viewed as both a strength and limitation. African Americans smokers experience disproportionately higher risks of smoking-related morbidity and mortality compared to Caucasians (31). However, very little is known about the efficacy of standard smoking cessation treatments in this population, particularly among light smokers who make up more than 50% of the African American smokers. However, the inclusion of light smokers may limit the generalizability of our findings to other groups. In addition, the placebo arm in both trials had relatively low smoking abstinence rates, 217

239 ! the low number of abstinence events could limit the statistical power to evaluate these associations. The low number of abstinent individuals also limited our ability to evaluate the effects of multiple SNPs in the same model. Another limitation was that we did not have reliable (biochemically verified) time of relapse data in this study, which could provide some time course information about the effect of rs on smoking cessation. Population stratification is an important issue in genetic association studies. A limitation of this study was that we did not have ancestry informative markers to statistically control for population stratification. However, as improving smoking cessation treatments for Africa Americans is our goal, we believe that the limitations due to admixture are balanced against the need to improve smoking cessation in this population. Eliminating individuals who are modestly admixed, but would still self-identify as African Americans, could greatly reduce the clinical applicability of our findings. Overall, our findings indicate that gene variants in CHRNA5-A3-B4 affect smoking abstinence in African Americans during the pharmacological treatment phase, but not during follow-up, even after adjusting for baseline smoking behaviors. The association between rs and smoking abstinence was observed with both nicotine gum and bupropion making it difficult to use for treatment personalization. Further studies should focus on understanding the mechanism(s) underlying this association in order to optimize the efficacy of smoking cessation treatments. MATERIALS AND METHODS: Study descriptions We evaluated the association between the CHRNA5-A3-B4 variants and smoking cessation outcomes in two independent smoking cessation trials. Both trials were conducted in 218

240 ! African American light smokers ( 10 CPD) at the same community health center and the enrollment criteria were similar. These trials were focused on light smokers because 1) more than 50% of African American smokers are light smokers, and 2) little is known about the pharmacology and pharmacogenetics of smoking cessation treatments in this population. Nicotine gum study (Study 1): This study was a randomized double-blind, placebocontrolled trial to evaluate the efficacy of nicotine gum (2 mg) in African American light smokers (6). Eligible participants self-identified as African American or Black, were at least 18 years old, had smoked 10 or fewer CPD for at least 6 months prior to enrollment, and smoked on at least 25 of last 30 days. This study consisted of four treatment arms (N=~190 each): 1) nicotine gum with health education (HE) counseling; 2) nicotine gum with motivational interviewing (MI) counseling; 3) placebo with HE and 4) placebo with MI. The nicotine gum treatment lasted 8 weeks, and six counseling sessions were provided to each participant. The participants were followed for a total of 26 weeks (6 months). Bupropion study (Study 2): This study was a randomized double-blind, placebocontrolled trial to evaluate the efficacy of bupropion (300 mg per day, total N=540) in African American light smokers (22). Eligibility criteria were similar to Study 1 and included exclusion based on contraindication of bupropion use. Bupropion use lasted 7 weeks and HE counseling was similar to Study 1. The participants were followed for a total of 26 weeks (6 month). Both studies were approved by the University of Kansas Human Subject Committee, the University of Toronto Ethics Review Office, and the University of California San Francisco Human Research Protection Program. Both studies assessed age, sex, menthol use, baseline CPD, baseline plasma cotinine, Fagerstrom Test for Nicotine Dependence (FTND). Study 2 also assessed urinary total nicotine equivalents, which is the total urinary level of nicotine and 8 of its metabolites. The analytical 219

241 ! procedures were described previously (32). Together, the 9 analytes account for about 90% of nicotine dose (33), and creatinine adjusted spot urinary TNE correlates with daily tobacco consumption (34). Smoking abstinence Biochemically verified abstinence was assessed during treatment (Week 1 for Study 1 and week 3 for the Study 2), at end of treatment (Week 8 for Study 1 and week 7 for Study 2) and at 6-month follow-up (6 month for both Study 1 and Study 2). In Study 1, abstinence was verified by exhaled CO levels of lower than 10 ppm. In Study 2, abstinence was verified by having salivary cotinine levels less than 15 ng/ml. All statistical analyses were performed on an intent-to-treatment basis, and subjects lost during follow-up were considered smokers. Genotyping CHRNA5-A3-B4 SNPs were genotyped using ABI Viia 7 real time PCR machine (Applied Biosystems, Foster City, CA). The genotyping reaction was performed with 5 µl TaqMan GTXpress master mix and 5 µl of water containing 10 ng of DNA and 0.25 µl of 40x Taqman SNP genotyping assay (see Supplementary Table S1 for the specific probes used for each SNP). The allele discrimination data were analyzed by Viia 7 software version 1.2. All genotyping results included in our analyses had call quality values above Statistical Analyses The comparisons of baseline demographic variables were performed by Mann Whitney tests or Chi 2 tests. Evaluation of the association between the dichotomized SNPs (rs [gg=0 and GA/AA=1]; rs [gg=0 and AG/AA=1]; rs588765[cc=0 and CT/TT=1]; and rs578776[aa=0 and AG/GG=1].) and smoking abstinence were conducted using logistic regression. Modeling the influence of the variants as additive resulted in very similar 220

242 ! statistical results compared to modeling the influence of the variants as dichotomized valuable (results shown in Supplementary Fig.S1). Logistic regressions were used to evaluate the association between rs or rs and smoking abstinence after adjusting for age, sex, baseline CPD, menthol status, the type of counseling sessions (Study 1) and other CHRNA5-A3-B4 SNPs. Adjusting for other CHRNA5-A3-B4 variants (such as rs ) did not alter the associations between rs and rs with smoking abstinence (Supplementary Fig. S2, S3&S4). The P-values were not adjusted for multiple comparisons. Because there were 4 independent SNPs, we considered P-values below (i.e. 0.05/4) to be statistically significant. The number needed to treat represents the average number of patients needed to treat with the active versus placebo pharmacotherapy to prevent one patient from smoking relapse. Statistical analyses were performed using Stata 12 (StataCorp, College Station, TX). STUDY HIGHLIGHTS (145/150) What is the current knowledge of the topic? Smoking is a major cause of preventable death globally. Smoking cessation at any age has substantial health benefits. What question did this study address? While the association between variants in CHRNA5-A3-B4 (a nicotinic receptor gene cluster) and smoking has been explored previously, the association between CHRNA5-A3-B4 variants and smoking cessation is poorly understood, particularly among African Americans. What this study adds to our knowledge? 221

243 ! In African American smokers, this study demonstrated that a common variant in CHRNA5-A3-B4 is associated with significantly lower smoking cessation rates during active pharmacological treatment. How this might change clinical pharmacology and therapeutics? This study suggests that roughly 60% of African Americans would benefit greatly from active smoking cessation treatments, whereas the other 40% may not. This illustrates the potential value of pharmacogenetic approaches in improving smoking cessation outcomes among African American smokers. 222

244 ! Acknowledgements We acknowledge the support of NIH grant CA to fund this study, National Center for Minority Health Disparities grant 1P60MD (JSA), the Endowed Chair in Addiction for the Department of Psychiatry (RFT), CIHR grant MOP86471 (RFT), Ontario Graduate Scholarship (AZZ), CAMH and the CAMH foundation (RFT), NIH PGRN grants DA (RFT, NB), DA (SPD) and DA (NB), the Canada Foundation for Innovation (#20289 and #16014) and the Ontario Ministry of Research and Innovation (RFT). The authors would like to thank Kelly Li for her technical assistance. Conflict of Interest NLB serves as a consultant to several pharmaceutical companies that market smoking cessation medications and has been a paid expert witness in litigation against tobacco companies. SPD is a scientific advisor to Genophen. RFT has participated in one-day advisory meetings for Novartis and McNeil. 223

245 ! (1)! Benowitz,!N.L.!Nicotine!addiction.!N"Engl"J"Med!!362,! !(2010).! (2)! Xian,!H."et"al.!The!heritability!of!failed!smoking!cessation!and!nicotine! withdrawal!in!twins!who!smoked!and!attempted!to!quit.!nicotine"tob"res!!5,! !(2003).! (3)! Gold,!A.B.,!Wileyto,!E.P.,!Lori,!A.,!Conti,!D.,!Cubells,!J.F.!&!Lerman,!C.! Pharmacogenetic!association!of!the!galanin!receptor!(GALR1)!SNP! rs !with!smoking!cessation.!neuropsychopharmacology!!37,!168378! (2012).! (4)! Hutchison,!K.E."et"al.!CHRNA4!and!tobacco!dependence:!from!gene!regulation! to!treatment!outcome.!arch"gen"psychiatry!!64,! !(2007).! (5)! Lerman,!C."et"al.!Role!of!functional!genetic!variation!in!the!dopamine!D2! receptor!(drd2)!in!response!to!bupropion!and!nicotine!replacement!therapy! for!tobacco!dependence:!results!of!two!randomized!clinical!trials.! Neuropsychopharmacology!!31,!231742!(2006).! (6)! Ahluwalia,!J.S."et"al.!The!effects!of!nicotine!gum!and!counseling!among!African! American!light!smokers:!a!2!x!2!factorial!design.!Addiction!!101,!883791! (2006).! (7)! Munafo,!M.R."et"al.!Association!between!genetic!variants!on!chromosome! 15q25!locus!and!objective!measures!of!tobacco!exposure.!J"Natl"Cancer"Inst!! 104,!74078!(2012).! (8)! Amos,!C.I."et"al.!Genome7wide!association!scan!of!tag!SNPs!identifies!a! susceptibility!locus!for!lung!cancer!at!15q25.1.!nat"genet!!40,!616722!(2008).! (9)! Thorgeirsson,!T.E."et"al.!A!variant!associated!with!nicotine!dependence,!lung! cancer!and!peripheral!arterial!disease.!nature!!452,!638742!(2008).! (10)! Thorgeirsson,!T.E."et"al.!Sequence!variants!at!CHRNB37CHRNA6!and!CYP2A6! affect!smoking!behavior.!nat"genet!!42,!448753!(2010).! (11)! Chen,!L.S."et"al.!Smoking!and!genetic!risk!variation!across!populations!of! European,!Asian,!and!African!American!ancestry77a!meta7analysis!of! chromosome!15q25.!genetic"epidemiology!!36,!340751!(2012).! (12)! Freathy,!R.M."et"al.!A!common!genetic!variant!in!the!15q24!nicotinic! acetylcholine!receptor!gene!cluster!(chrna57chrna37chrnb4)!is! associated!with!a!reduced!ability!of!women!to!quit!smoking!in!pregnancy.! Hum"Mol"Genet!!18,!292277!(2009).! (13)! Munafo,!M.R.,!Johnstone,!E.C.,!Walther,!D.,!Uhl,!G.R.,!Murphy,!M.F.!&!Aveyard,! P.!CHRNA3!rs !genotype!and!short7term!smoking!cessation.!Nicotine" Tob"Res!!13,!98278!(2011).! (14)! Sarginson,!J.E."et"al.!Markers!in!the!15q24!nicotinic!receptor!subunit!gene! cluster!(chrna57a37b4)!predict!severity!of!nicotine!addiction!and!response! to!smoking!cessation!therapy.!am"j"med"genet"b"neuropsychiatr"genet!!156b,! !(2011).! (15)! Chen,!L.S."et"al.!Interplay!of!genetic!risk!factors!(CHRNA57CHRNA37CHRNB4)! and!cessation!treatments!in!smoking!cessation!success.!am"j"psychiatry!!169,! !(2012).! (16)! King,!D.P."et"al.!Smoking!cessation!pharmacogenetics:!analysis!of!varenicline! and!bupropion!in!placebo7controlled!clinical!trials.! Neuropsychopharmacology!!37,!641750!(2012).! 224

246 ! (17)! Saccone,!N.L."et"al.!Multiple!independent!loci!at!chromosome!15q25.1!affect! smoking!quantity:!a!meta7analysis!and!comparison!with!lung!cancer!and! COPD.!PLoS"Genet!!6,!!(2010).! (18)! Bergen,!A.W."et"al.!Nicotinic!acetylcholine!receptor!variation!and!response!to! smoking!cessation!therapies.!pharmacogenet"genomics!!23,!947103!(2013).! (19)! David,!S.P."et"al.!Genome7wide!meta7analyses!of!smoking!behaviors!in!African! Americans.!Translational"psychiatry!!2,!e119!(2012).! (20)! Li,!M.D.,!Xu,!Q.,!Lou,!X.Y.,!Payne,!T.J.,!Niu,!T.!&!Ma,!J.Z.!Association!and! interaction!analysis!of!variants!in!chrna5/chrna3/chrnb4!gene!cluster! with!nicotine!dependence!in!african!and!european!americans.!am"j"med" Genet"B"Neuropsychiatr"Genet!!153B,!745756!(2010).! (21)! Amos,!C.I."et"al.!Nicotinic!acetylcholine!receptor!region!on!chromosome! 15q25!and!lung!cancer!risk!among!African!Americans:!a!case7control!study.!J" Natl"Cancer"Inst!!102,! !(2010).! (22)! Cox,!L.S."et"al.!Bupropion!for!smoking!cessation!in!African!American!light! smokers:!a!randomized!controlled!trial.!j"natl"cancer"inst!!104,!29078!(2012).! (23)! Liu,!J.Z."et"al.!Meta7analysis!and!imputation!refines!the!association!of!15q25! with!smoking!quantity.!nat"genet!!42,!436740!(2010).! (24)! Benowitz,!N.L.,!Dains,!K.M.,!Dempsey,!D.,!Wilson,!M.!&!Jacob,!P.!Racial! differences!in!the!relationship!between!number!of!cigarettes!smoked!and! nicotine!and!carcinogen!exposure.!nicotine"tob"res!!13,!772783!(2011).! (25)! Zhu,!A.Z.,!Renner,!C.C.,!Hatsukami,!D.K.,!Benowitz,!N.L.!&!Tyndale,!R.F.! CHRNA57A37B4!genetic!variants!alter!nicotine!intake!and!interact!with! tobacco!use!to!influence!body!weight!in!alaska!native!tobacco!users.! Addiction!!108,! !(2013).! (26)! Fowler,!C.D.,!Lu,!Q.,!Johnson,!P.M.,!Marks,!M.J.!&!Kenny,!P.J.!Habenular!alpha5! nicotinic!receptor!subunit!signalling!controls!nicotine!intake.!nature!!471,! !(2011).! (27)! Berrettini,!W.H.!&!Doyle,!G.A.!The!CHRNA57A37B4!gene!cluster!in!nicotine! addiction.!mol"psychiatry!!17,!856766!(2012).! (28)! Slemmer,!J.E.,!Martin,!B.R.!&!Damaj,!M.I.!Bupropion!is!a!nicotinic!antagonist.!J" Pharmacol"Exp"Ther!!295,!32177!(2000).! (29)! Zhu,!A.Z."et"al.!CYP2B6!and!Bupropion's!Smoking7Cessation!Pharmacology:! The!Role!of!Hydroxybupropion.!Clin"Pharmacol"Ther!!92,!77177!(2012).! (30)! Ho,!M.K."et"al.!Association!of!nicotine!metabolite!ratio!and!CYP2A6!genotype! with!smoking!cessation!treatment!in!african7american!light!smokers.!clin" Pharmacol"Ther!!85,!635743!(2009).! (31)! Haiman,!C.A."et"al.!Ethnic!and!racial!differences!in!the!smoking7related!risk!of! lung!cancer.!n"engl"j"med!!354,!333742!(2006).! (32)! Zhu,!A.Z."et"al.!Alaska!Native!smokers!and!smokeless!tobacco!users!with! slower!cyp2a6!activity!have!lower!tobacco!consumption,!lower!tobacco7 specific!nitrosamine!exposure!and!lower!tobacco7specific!nitrosamine! bioactivation.!carcinogenesis!!34,!937101!(2013).! (33)! Benowitz,!N.L.,!Jacob,!P.,!3rd,!Fong,!I.!&!Gupta,!S.!Nicotine!metabolic!profile!in! man:!comparison!of!cigarette!smoking!and!transdermal!nicotine.!j"pharmacol" Exp"Ther!!268,! !(1994).! 225

247 ! (34)! Benowitz,!N.L.,!Dains,!K.M.,!Dempsey,!D.,!Havel,!C.,!Wilson,!M.!&!Jacob,!P.,!3rd.! Urine!menthol!as!a!biomarker!of!mentholated!cigarette!smoking.!Cancer" Epidemiol"Biomarkers"Prev!!19,!301379!(2010).!! 226

248 !! Table 1. CHRNA5-A3-B4 variants are not significantly associated with baseline smoking behaviors Study 1 Study 2 Rs GG GA AA P- Values GG GA AA n Baseline cigarettes per ( day ( ) ( ) ( ) ( ) ( ) 8.6) Plasma Cotinine (ng/ml) Urinary total nicotine equivalent 1 (nmol/ mg Cre) FTND 238 ( ) 2.8 ( ) 257 ( ) 3.0 ( ) N/A 262 ( ) 3.5 ( ) ( ) 62.7 ( ) 3.2 ( ) 239 ( ) 50.7 ( ) 3.1 ( ) 214 ( ) 60.5 ( ) 3.4 ( ) Rs GG GA AA P- Values GG GA AA n Baseline cigarettes per ( (1.1- day ( ) ( ) ( ) ( ) 13.9) 13.6) Plasma Cotinine (ng/ml) Urinary total nicotine equivalent 1 (nmol/ mg Cre) FTND Baseline cigarettes per day 245 ( ) 2.92 ( ) 253 ( ) 2.94 ( ) N/A 230 ( ) 4.0 ( ) ( ) 59 (53-65) 3.2 ( ) 225 ( ) 51 (41-62) 2.9 ( ) 288 ( ) 68 ( ) 4.0 ( ) Rs CC CT TT P- values CC CT TT n ( ( ) ( ) ( ) ( ) 8.5) Plasma Cotinine (ng/ml) Urinary total nicotine equivalent 1 (nmol/ mg Cre) FTND 251 ( ) 2.9 ( ) 242 (223-26) 3.0 ( ) N/A 243 ( ) 2.9 ( ) ( ) 61 (51-71) 3.2 ( ) 235 ( ) 57 (50-63) 3.2 ( ) 7.6 ( ) 251 ( ) 55 (47-64) 3.1 ( ) Rs AA GA GG P- values AA GA GG n Baseline cigarettes per ( day ( ) ( ) ( ) ( ) ( ) 8.4) Plasma Cotinine (ng/ml) Urinary total nicotine equivalent 1 (nmol/ mg Cre) FTND 243 ( ) 2.8 ( ) 240 ( ) 2.9 ( ) N/A 263 ( ) 3.2 ( ) Data presented as Mean (95% Confident Interval) ( ) 54 (48-60) 3.1 ( ) 221 ( ) 57 ( ) 3.2 ( ) 255 ( ) 64 (49-79) 3.2 ( ) P- Values P- Values P- values P- values

249 ! 1 The urinary total nicotine equivalents were only available for a subset of individuals in Study 2. FTND=Fagerstrom Test for Nicotine Dependence Figure legends Figure 1. The associations (dominant model) between CHRNA5-A3-B5 variants and smoking abstinence in African Americans smokers. A) Among the participants who received active nicotine gum treatment (Study 1). B) Among the participants who received active bupropion treatment (Study 2). C) Among the participants who received active pharmacological treatments (combined analysis). D) Among the participants who received placebo (combined analysis). Figure 2. The A allele of rs was associated with lower smoking cessation rates in African American smokers receiving nicotine gum treatment and bupropion. OR unadj. = unadjusted odds ratio of quitting for the GA&AA genotype group compared to the GG genotype. OR adj. = odds ratio of quitting for the GA&AA genotype group compared to the GG genotype after adjusting for age, sex, baseline CPD, menthol status and type of counseling session. A significant genotype by treatment interaction was observed during treatment (P<0.01). Figure 3. The T allele of rs was associated with smoking abstinence in African American smokers receiving nicotine gum treatment and bupropion. OR unadj. = unadjusted odds ratio of quitting for the CT&TT genotype group compared to the CC genotype. OR adj. = odds ratio of quitting for the CT&TT genotype group compared to the CC genotype after adjusting for age, sex, baseline CPD, menthol status and type of counseling sessions. Figure 4. Rs was not consistently associated with smoking abstinence in African American smokers receiving nicotine gum treatment and bupropion. OR unadj. = unadjusted odds ratio of quitting for the GA&AA genotype group compared to the GG genotype. OR adj. = odds ratio of quitting for the GA&AA genotype group compared to the GG genotype after adjusting for age, sex, baseline CPD, menthol status and type of counseling sessions. 228

250 ! 229

251 ! 230

252 ! 231

253 ! 232