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IMPACT OF CYP2A6 GENETIC VARIATION ON NICOTINE METABOLISM AND SMOKING BEHAVIOURS IN LIGHT SMOKING
POPULATIONS OF BLACK-AFRICAN DESCENT
By
Man Ki Ho
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Graduate Department of Pharmacology and Toxicology
University of Toronto
© Copyright by Man Ki Ho 2011
ii
IMPACT OF CYP2A6 GENETIC VARIATION ON NICOTINE METABOLISM AND
SMOKING BEHAVIOURS IN LIGHT SMOKING POPULATIONS OF BLACK-
AFRICAN DESCENT
Man Ki Ho
Doctor of Philosophy
Graduate Department of Pharmacology and Toxicology University of Toronto
2011
ABSTRACT
Populations of Black-African descent have slower rates of nicotine and cotinine metabolism,
smoke fewer cigarettes (~10 cigarettes/day), and have higher incidences of tobacco-related
illnesses compared to Caucasians. Cytochrome P450 2A6 (CYP2A6) is the main enzyme
involved in the metabolism of nicotine and its proximal metabolite cotinine, as well as tobacco-
specific nitrosamines. Genetic polymorphisms in CYP2A6 contribute to the large variability
observed in rates of nicotine metabolism. Reduced CYP2A6 activity has been associated with
fewer cigarettes smoked, higher quit rates, and lower lung cancer risk in predominantly moderate
to heavy-smoking (~20–30 cigarettes/day) Caucasians. CYP2A6 genetic variants and their
impact on smoking behaviours have not been well studied among individuals of Black-African
descent. The main objectives herein were to identify and characterize new CYP2A6 variants that
may explain the slower rates of metabolism, and determine whether CYP2A6 variation is a
predictor of smoking phenotypes in this population. Furthermore, we examined whether
previously validated biomarkers of tobacco exposure have limitations among individuals of
iii
Black-African descent given their low and sporadic smoking patterns. A new CYP2A6 variant
(CYP2A6*23) was found in individuals of Black-African descent recruited for a nicotine
pharmacogenetic-pharmacokinetic study. CYP2A6*23 reduced activity towards nicotine and
coumarin in vitro and was associated with slower rates of CYP2A6 kinetics in vivo. In a clinical
trial of African-American light smokers, CYP2A6 slow metabolizers were more successful at
smoking cessation compared to normal metabolizers, although no differences in cigarette
consumption were found. Two common biochemical markers of tobacco smoke exposure,
cotinine and exhaled carbon monoxide, were weakly correlated with self-reported cigarette
consumption. These biomarkers were not substantially affected by variables previously shown
to alter amount smoked and/or rates of cotinine metabolism such as gender, age, body mass
index or smoking menthol cigarettes. However, CYP2A6 slow metabolizers had significantly
higher cotinine without smoking more cigarettes. Identification and characterization of novel
variants adds to our understanding of nicotine pharmacokinetic differences between racial/ethnic
minority groups and improves accuracy of CYP2A6 genotype groupings for genetic association
studies. Furthermore, better insight into the biological factors associated with smoking
behaviours will aid in the development of more efficacious targeted treatments for this
understudied population.
iv
ACKNOWLEDGEMENTS
As author of this thesis, I would like to acknowledge the people who contributed their time and
efforts to this work. Firstly, I would like to thank my supervisor Dr. Rachel F. Tyndale for her
support, encouragement and guidance. She has provided me with an invaluable learning
experience and I am grateful for her mentorship.
I would also like to thank all of my colleagues in the lab for their technical assistance, theoretical
guidance, and moral support. In particular, I would like to thank Ewa Hoffmann, Qian Zhou and
Zhao Bin for their contributions to my projects.
I am grateful for my committee members Drs. Albert Wong and Usoa Busto for sharing their
time and knowledge, as well as providing helpful suggestions and comments for improvement. I
would also like to thank Drs. Jasjit Ahluwalia and Kola Okuyemi for their collaborations.
I would like to thank my parents (Patrick and Florence Ho), my sister (Man Ying Ho), and all the
wonderful friends I made over the years for their unconditional support and encouragement.
Finally I am graciously indebted to the Natural Sciences and Engineering Research Council of
Canada, the Canadian Institutes of Health Research – Interdisciplinary Capacity Enhancement
Scholars Program, the Canadian Tobacco Control Research Initiative and the University of
Toronto for providing the financial support without which my continued success in this program
would not have been possible.
v
TABLE OF CONTENTS ABSTRACT .................................................................................................................................... ii
ACKNOWLEDGEMENTS ........................................................................................................... iv
TABLE OF CONTENTS ................................................................................................................ v
LIST OF PUBLICATIONS ........................................................................................................... xi
LIST OF TABLES ....................................................................................................................... xiii
LIST OF FIGURES ..................................................................................................................... xiv
LIST OF ABBREVIATIONS ....................................................................................................... xv
STATEMENT OF RESEARCH PROBLEM .............................................................................. xvi
MAIN RESEARCH OBJECTIVES ............................................................................................ xix
GENERAL INTRODUCTION
SECTION 1: SMOKING AND NICOTINE
1.1 Prevalence ....................................................................................................................... 1
1.2 Health consequences of smoking .................................................................................... 3
1.3 Heritability of smoking behaviours ................................................................................ 5
1.4 Neurobiology of tobacco addiction ................................................................................. 6
1.4.1 Brain reward pathway ............................................................................................. 6
1.4.2 Nicotinic acetylcholine receptors ............................................................................ 8
1.4.3 Other targets implicated in tobacco addiction ...................................................... 10
1.5 Nicotine: the main addictive substance in cigarettes .................................................... 11
1.5.1 Nicotine reinforcement ......................................................................................... 11
1.5.2 Nicotine-titration hypothesis ................................................................................. 13
1.5.3 Other compounds in tobacco smoke with addictive properties ............................ 16
1.6 Nicotine pharmacokinetics ............................................................................................ 17
1.6.1 Absorption and distribution .................................................................................. 17
1.6.2 Nicotine metabolism ............................................................................................. 17
1.6.3 Nicotine C-oxidation and contribution by CYP2A6 ............................................. 18
1.6.3.1 In vitro studies................................................................................................... 20
1.6.3.2 In vivo studies ................................................................................................... 21
1.6.4 Other enzymes involved in nicotine metabolism .................................................. 22
1.6.5 Pharmacological actions of nicotine metabolites .................................................. 24
1.7 Tobacco dependence ..................................................................................................... 25
vi
1.7.1 Acquisition of dependence .................................................................................... 25
1.7.2 Diagnostic scales for tobacco dependence ............................................................ 26
1.8 Smoking cessation ........................................................................................................ 27
1.8.1 Treatments available ............................................................................................. 27
1.8.1.1 Pharmacotherapies ............................................................................................ 27
1.8.1.2 Non-pharmacological interventions .................................................................. 31
1.9 Biomarkers of tobacco smoke ....................................................................................... 32
1.9.1 Common indicators of exposure ........................................................................... 32
SECTION 2: LIGHT SMOKING
2.1 Prevalence ..................................................................................................................... 33
2.2 Health consequences ..................................................................................................... 35
2.3 Demographics ............................................................................................................... 35
2.3.1 Ethnic minorities ................................................................................................... 35
2.3.2 Females ................................................................................................................. 36
2.3.3 Young adults ......................................................................................................... 36
2.4 Tobacco dependence ..................................................................................................... 37
2.4.1 Smoking characteristics ........................................................................................ 37
2.4.2 Interventions for smoking cessation ..................................................................... 38
2.5 African-American light smokers ................................................................................... 39
2.5.1 Demographics ....................................................................................................... 39
2.5.2 Smoking initiation ................................................................................................. 39
2.5.3 Cigarette consumption .......................................................................................... 40
2.5.4 Use of menthol cigarettes...................................................................................... 41
2.5.5 Smoking cessation ................................................................................................ 43
2.5.6 Health disparities .................................................................................................. 43
SECTION 3: CYP2A6
3.1 CYP2 gene family .......................................................................................................... 45
3.1.1 Evolutionary origins of CYP2ABFGST gene cluster ............................................ 46
3.1.2 CYP2A subfamily .................................................................................................. 47
3.1.3 CYP2A tissue expression ...................................................................................... 48
vii
3.1.4 CYP2A6 substrates ............................................................................................... 48
3.1.4.1 Tobacco-specific nitrosamines.......................................................................... 50
3.2 Genetic variability in CYP2A6 activity ........................................................................ 51
3.2.1 Inter-individual and inter-ethnic variability .......................................................... 51
3.2.2 Currently identified CYP2A6 variants and their functional consequences ........... 52
3.3 Other influences of CYP2A6 activity ........................................................................... 53
3.3.1 Gender/hormonal effects ....................................................................................... 53
3.3.2 Age ........................................................................................................................ 59
3.3.3 CYP2A6 inhibitors and inducers .......................................................................... 60
3.3.3.1 Pharmaceutical agents ....................................................................................... 60
3.3.3.2 Menthol ............................................................................................................. 61
3.3.3.3 Smoking/nicotine .............................................................................................. 62
3.3.3.4 Dietary............................................................................................................... 63
3.4 Other sources of variability in nicotine clearance rates ................................................ 64
3.5 Phenotype indicators of CYP2A6 activity .................................................................... 65
3.5.1 COT/NIC............................................................................................................... 65
3.5.2 3HC/COT .............................................................................................................. 66
3.5.3 Formation of 7-hydroxycoumarin ......................................................................... 67
3.6 Association of CYP2A6 variation with smoking behaviours ....................................... 68
3.6.1 Smoking initiation ................................................................................................. 68
3.6.2 Cigarette consumption .......................................................................................... 69
3.6.3 Smoking cessation ................................................................................................ 70
3.6.3.1 Case-control gene association studies ............................................................... 70
3.6.3.2 Clinical trials ..................................................................................................... 70
3.6.3.3 CYP2A6 inhibition to aid smoking cessation ................................................... 73
3.6.4 Lung Cancer .......................................................................................................... 74
STATEMENT OF RESEARCH HYPOTHESES ........................................................................ 75
CHAPTER 1: A NOVEL CYP2A6 ALLELE, CYP2A6*23, IMPAIRS ENZYME FUNCTION IN
VITRO AND IN VIVO AND DECREASES SMOKING IN A POPULATION OF BLACK-
AFRICAN DESCENT
Abstract ..................................................................................................................................... 77
Introduction ............................................................................................................................... 78
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Materials and Methods .............................................................................................................. 80
Results ....................................................................................................................................... 86
Discussion ................................................................................................................................. 94
Significance to thesis ................................................................................................................ 96
CHAPTER 2: ASSOCIATION OF NICOTINE METABOLITE RATIO AND CYP2A6
GENOTYPE WITH SMOKING CESSATION TREATMENT IN AFRICAN-AMERICAN
LIGHT SMOKERS
Abstract ..................................................................................................................................... 99
Introduction ............................................................................................................................... 99
Materials and Methods ............................................................................................................ 102
Results ..................................................................................................................................... 105
Discussion ............................................................................................................................... 118
Significance to thesis .............................................................................................................. 123
Supplementary information .................................................................................................... 125
CHAPTER 3: UTILITY AND RELATIONSHIPS OF BIOMARKERS OF SMOKING IN
AFRICAN-AMERICAN LIGHT SMOKERS
Abstract ................................................................................................................................... 127
Introduction ............................................................................................................................. 127
Materials and Methods ............................................................................................................ 130
Results ..................................................................................................................................... 133
Discussion ............................................................................................................................... 142
Significance to thesis .............................................................................................................. 149
GENERAL DISCUSSION
SECTION 1: IDENTIFYING AND DETERMINING THE FUNCTIONAL IMPACT OF
NOVEL CYP2A6 GENETIC VARIANTS
1.1 African-Americans: a population with rich genetic diversity ..................................... 151
1.1.1 Origins of genetic variation in modern Homo sapiens ....................................... 151
1.1.2 The African Diaspora: Origins of African-Americans ....................................... 151
1.1.3 Evolutionary forces driving genetic diversity ..................................................... 153
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1.1.4 Genetic association studies in African-Americans ............................................. 154
1.1.4.1 Utility and limitations of self-reports of racial/ethnic ancestry ...................... 154
1.1.4.2 Importance of performing studies in different racial/ethnic groups ............... 155
1.2 Origins of CYP2A6 polymorphisms............................................................................ 157
1.2.1 Types of genetic polymorphisms ........................................................................ 157
1.2.2 Discovery of novel CYP2A6 alleles .................................................................... 158
1.2.3 Evolution of CYPs and their genetic variants ..................................................... 159
1.3 Comparison of CYP2A6 genetic variability between racial/ethnic groups ................. 161
1.4 Functional consequences of CYP2A6 genetic variants ............................................... 162
1.5 Other biological sources of variability in CYP2A6 activity ....................................... 163
1.5.1 Polymorphisms in POR....................................................................................... 163
1.5.2 Polymorphisms in transcription factors .............................................................. 164
1.5.3 Epigenetics .......................................................................................................... 165
1.5.4 mRNA silencing (microRNA) ............................................................................ 166
1.6 Utility of genotype versus phenotype measures of CYP2A6 activity ........................ 167
SECTION 2: IMPACT OF CYP2A6 GENETIC VARIATION ON SMOKING BEHAVIOURS
IN AFRICAN-AMERICAN LIGHT SMOKERS
2.1. Smoking initiation ....................................................................................................... 169
2.1.1. Factors associated with smoking initiation in African-Americans ..................... 169
2.2. Cigarette consumption ................................................................................................ 170
2.2.1. Light smoking behaviours among African-Americans ....................................... 170
2.2.2. Comparisons between African-American light and moderate/heavy smokers ... 172
2.3. Tobacco dependence ................................................................................................... 173
2.3.1. Dependence in African-American light smokers ................................................ 173
2.3.2. Models of tobacco dependence ........................................................................... 174
2.3.2.1. Reinforcement theories ............................................................................... 174
2.3.2.2. Classical conditioning theories ................................................................... 175
2.3.2.3. Importance of social and cultural contexts ................................................. 176
2.4. Smoking cessation ...................................................................................................... 178
2.4.1. Impact of CYP2A6 on smoking cessation .......................................................... 179
2.4.2. Gender differences in smoking cessation outcomes in African-Americans ....... 181
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2.4.3. Improving treatment outcomes for smoking cessation ....................................... 182
2.5. Utility of biomarkers of tobacco exposure among African-Americans ...................... 184
CONCLUSIONS......................................................................................................................... 187
REFERENCES ........................................................................................................................... 189
APPENDICES ............................................................................................................................ 221
xi
LIST OF PUBLICATIONS
Research articles in thesis Chapter 1: Ho MK, Mwenifumbo JC, Zhao B, Gillam EMJ, Tyndale RF. A novel CYP2A6 allele, CYP2A6*23, impairs enzyme function in vitro and in vivo and decreases smoking in a population of Black-African descent. Pharmacogenetics and Genomics. 2008. 18(1): 67-75. Chapter 2: Ho MK, Mwenifumbo JC, Al Koudsi N, Okuyemi KS, Ahluwalia JS, Benowitz NL, Tyndale RF. Association of nicotine metabolite ratio and CYP2A6 genotype with smoking cessation in African-American light smokers. Clinical Pharmacology and Therapeutics. 2009; 85(6): 635-43. Chapter 3: Ho MK, Faseru B, Choi WS, Nollen NL, Mayo MS, Thomas JL, Okuyemi KS, Ahluwalia JS, Benowitz NL, Tyndale RF. Utility and relationships of biomarkers of smoking in African-American light smokers. Cancer Epidemiol Biomarkers Prev. 2009 Dec;18(12):3426-34. Additional publications from doctoral work attached in the Appendices Research articles Mwenifumbo JC, Al Koudsi N, Ho MK, Zhou Q, Hoffmann EB, Sellers EM, Tyndale RF. Novel and established CYP2A6 alleles alter in vivo nicotine metabolism in a population of black African descent. Human Mutation. 2008. 29(5): 679 – 88. Review articles Ho MK, Goldman D, Heinz A, Kaprio J, Kreek MJ, Li MD, Munafò MR, Tyndale RF. Breaking barriers in the genomics and pharmacogenetics of drug addiction. Clinical Pharmacology and Therapeutics. Clin Pharmacol Ther. 2010 Dec;88(6):779-91. Ho MK, Tyndale RF. Role of CYP2A6 genetic variation on smoking behaviours and clinical implications. ASCO Education Book 2008. Ho MK, Tyndale RF. Overview of the pharmacogenomics of cigarette smoking. Pharmacogenomics J. 2007, 7(2): 81-98.
xii
Online publications Siu ES, Al Koudsi N, Ho MK, Tyndale RF. New Frontiers in the Treatment and Management of Smoking Cessation. Cyberounds Psychiatry Neuroscience website. http://www.cyberounds.com. Posted Nov 2006. Siu ES, Al Koudsi N, Ho MK, Tyndale RF. Smoking, Quitting and Genetics. The Doctor Will See You Now website. http://www.thedoctorwillseeyounow.com/articles/behaviour/smoking_14. Posted Nov 2006. Conference presentations Ho MK, Wall T, Myers M, Tyndale RF. Influence of CYP2A6 and CYP2B6 genetic variation on smoking in Asian-American college students. Oral presentation for the annual Interdisciplinary Capacity Enhancement (ICE) Team Meeting. Apr 2009; Vaudreuil-Dorion, Québec. Abstracts presented Ho MK, Faseru B, Choi WS, Nollen NL, Mayo MS, Thomas JL, Okuyemi KS, Ahluwalia JS, Benowitz NL, Tyndale RF. Utility and relationships of biomarkers of smoking in African-American light smokers. Ho MK, Mwenifumbo JC, Zhou Q, Hoffmann EB, Okuyemi KS, Ahluwalia JS, Benowitz NL, Tyndale RF. CYP2A6 activity and its association with baseline smoking behaviours and treatment outcomes in a clinical trial of African-American light smokers. Ho MK, Tyndale RF, Spitz MR, Bondy M, Wilkinson A. Characterization of CYP2A6 and CYP2B6 genetic variants in a Mexican-American population. Ho MK, Mwenifumbo J, Sellers EM, Tyndale RF. Characterization of a novel CYP2A6 allele and its impact on nicotine metabolism and smoking behaviours in African-Canadians.
xiii
LIST OF TABLES
General introduction Page Table 1.1 A list of genes that have been implicated in tobacco
addiction. 12
Table 3.1 List of CYP2A6 substrates 49
Table 3.2 Description of CYP2A6 alleles and their predicted functional impact
54 – 57
Table 3.3 CYP2A6 allele frequencies in various racial/ethnic populations
58
Chapter 1 Table 1 Allele frequency of CYP2A6*23 by ethnicity 87
Table 2 CYP2A6*23 genotype groups and their mean adjusted 3HC/COT ratio
87
Table 3 Kinetic parameters of CYP2A6 wildtype and variant constructs for nicotine
90
Chapter 2 Table 1 Factors that influence the 3HC/COT in CYP2A6*1/*1
individuals 105
Table 2 CYP2A6 genotypes and associated 3HC/COT ratios 107 Table 3 CYP2A6 allele frequencies in African-Americans in this
population compared to our previous study in individuals of Black-African descent
108
Table 4 Logistic regression analyses of predictors of CO-verified quit rates at EOT (week 8) and follow-up (week 26)
116
Supplementary Table 1
Participant demographics 126
Chapter 3 Table 1 Participant characteristics 133 Table 2 Variables that influences CPD, expired CO or plasma COT
levels 136 – 137
Table 3 Correlations (r) between biomarkers and cigarette consumption by variables
140
Table 4 Multiple linear regression models of the predictors of CPD, expired CO and plasma COT
141
xiv
LIST OF FIGURES
General introduction Page Figure 1.1 Prevalence of current smoking by ethnicity and gender 2 Figure 1.2 Schematic of circadian changes in plasma nicotine levels 14 Figure 1.3 Quantitative schematic of the various nicotine metabolism
pathways 19
Figure 3.1 Human CYP2ABFGST gene cluster on chromosome 19q13.2.
47
Figure 3.2 Quit rates by 3HC/COT quartiles in clinical trials 72 Chapter 1 Figure 1 CYP2A6.23 had substantially reduced catalytic activity
towards nicotine and coumarin in vitro 89
Figure 2 CYP2A6.17 and CYP2A6.23, but not CYP2A6.16, have reduced in vitro nicotine C-oxidation
90
Figure 3 CYP2A6*23 decreased the rates of nicotine metabolism in vivo, as measured by the 3HC/COT ratio
92
Figure 4 Individuals with the CYP2A6*23 allele trended to having a lower likelihood of being current smokers
92
Chapter 2 Figure 1A CYP2A6 genotypes and their associated unadjusted
3HC/COT ratios 109
Figure 1B The unadjusted 3HC/COT ratio was significantly associated with CYP2A6 genotype groupings.
111
Figure 1C The 3HC/COT ratio adjusted by gender 111
Figure 2 (A - F) Association of CYP2A6 activity with smoking indices. 113
Figure 3 (A - F) Association of CYP2A6 activity and smoking abstinence 115
Chapter 3 Figure 1 (A - C) Histogram of self-reported CPD and biomarkers 135
Figure 1 (D - H) Correlations between self-reported CPD and biomarkers 135
Figure 2 (A - F) Relationship between CYP2A6 activity, CPD, expired CO, and plasma COT.
138
xv
LIST OF ABBREVIATIONS
3HC trans-3'-hydroxycotinine 3HC/COT Ratio of trans-3'-hydroxycotinine to cotinine AUC Area-under-the-curve BMI Body mass index CAR Constitutive androstane receptor CNVs Copy number variants CO Carbon monoxide COPD Chronic obstructive pulmonary disease COT Cotinine CPD Cigarettes per day CYP Cytochrome P450 CYP2A6 Cytochrome P450 2A6 dNTPs Deoxyribonucleoside triphosphates E.coli Escherichia coli EOT End-of-treatment ETS Environmental tobacco smoke FMO3 Flavin-containing monooxygenase 3 FTND Fagerström Test for Nicotine Dependence HE Health education counseling HNF4-α Hepatic nuclear factor 4 - α hNPR* Human NADPH-cytochrome P450 reductase MI Motivational interview counseling NAc Nucleus accumbens nAChRs Nicotinic acetylcholine receptors NNAL 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol NNK 4-(methylnitrosamino)-1-(3-pyridyl)-butanone NNN N-nitrosonornicotine NRT Nicotine replacement therapy PCR Polymerase chain reaction POR* NADPH-cytochrome P450 reductase PXR Pregnane X receptor SNPs Single nucleotide polymorphisms SXR Steroid/xenobiotic receptor UGTs Uridine diphosphate-glucuronosyltransferases UTR Untranslated region VTA Ventral tegmental area
* Note the gene name for NADPH-cytochrome P450 reductase is officially denoted POR, although a number of studies have referred to it as hNPR.
xvi
STATEMENT OF RESEARCH PROBLEM
Tobacco smoking remains a leading cause of preventable disease and death worldwide. While
tobacco control efforts have greatly reduced the prevalence of smoking, a substantial portion
(approximately 20%) of North Americans continue to smoke, and this will remain so unless
additional measures are taken to reduce smoking initiation and increase cessation among current
smokers (Schroeder et al.). Smoking is a complex behaviour involving multiple biological and
environmental risk factors. Identifying the genetic predictors of tobacco addiction has been the
focus of much research, and a great deal of progress has been made in recent years due to
advancements in our knowledge of the human genome. In particular, improvements in
technology have allowed for efficient screening and identification of sources of genetic
variability between individuals.
Nicotine is the main psychoactive compound responsible for the highly addictive properties of
tobacco smoke (Mcmorrow et al., 1983; Scherer, 1999; Benowitz, 2010). Genetic
polymorphisms in CYP2A6, the main enzyme responsible for nicotine metabolism, have been
shown to alter the rates of nicotine metabolism and smoking behaviours (Malaiyandi, Sellers et
al., 2005). In 2004 and 2005, two large sequencing projects of several racial/ethnic minority
populations identified a number of single nucleotide polymorphisms in CYP2A6, although the
functional consequences of these variants were not elucidated in these studies (Solus Jf, 2004;
Haberl and Anwald B, 2005). Many of these variants were found exclusively in African-
Americans, a unique population with slower rates of nicotine and cotinine metabolism that suffer
disproportionately from smoking-related illnesses, particularly lung cancer, despite smoking
fewer cigarettes compared to Caucasians (Benowitz et al., 1999; Haiman et al., 2006). As such,
unidentified sources of CYP2A6 genetic variation in this racial/ethnic group may in part explain
their distinctive rates of metabolism and smoking patterns.
xvii
Tobacco control efforts and changing social norms have altered smoking patterns in Westernized
countries over the past 25 years. The rising costs of cigarettes as a result of increased taxation,
as well as comprehensive smoking bans, have greatly reduced smoking prevalence and
consumption. The average age-adjusted cigarettes smoked daily reported by adults in the United
States have declined substantially from 1980 to 2000, going from 25.1 to 16.7 in males and 21.5
to 13.2 in females (Duval et al., 2008). Non-daily and light smoking patterns are particularly
prevalent among racial/ethnic minority groups. For example, among current smokers, 51.4% of
African-Americans reported daily use and smoked an average of 9.3 cigarettes per day compared
to 68.5% of Caucasian reporting daily use and smoking an average of 14.9 cigarettes per day
(Office of Applied Studies et al., 2006).
Classic models of tobacco dependence based on observations in moderate and/or heavy (i.e. pack
a day) smokers of Caucasian ancestry suggest that continual maintenance of blood and brain
nicotine levels are necessary for avoidance of withdrawal symptoms. As such, smoking
behaviours need to occur at regular intervals over the course of the day due to the fast removal of
nicotine from the body. However, these theories do not account for the phenomenon of non-
daily smoking and light smoking patterns of 10 or fewer cigarettes per day. This has important
implications as even smokers with low levels of consumption have difficulty quitting (Okuyemi
Ks et al., 2002), and primary pharmacotherapies for smoking cessation have been based on the
need for nicotine replacement or mimicking of nicotine’s effect among abstinent smokers.
Nearly all of the clinical trials published to date demonstrating the efficacy of these
pharmacotherapies have excluded smokers consuming 10 or fewer cigarettes per day, and it is
unknown whether these medications would be efficacious among light smoking populations.
Investigations into the biological factors underlying smoking behaviours among light smokers,
xviii
particularly in understudied racial/ethnic minority groups such as African-Americans, are
warranted.
xix
MAIN RESEARCH OBJECTIVES
There are gaps in our current understanding of CYP2A6 genetic variation in relation to nicotine
metabolism and smoking behaviours. Much progress has been made in identifying novel
CYP2A6 genetic variants in recent years, particularly among populations of Black-African
descent; however, functional characterization of these variants remains incomplete. A better
understanding of the genetic differences in nicotine metabolism between racial/ethnic groups
may potentially explain their unique smoking patterns, as well as improve future genetic studies
by reducing the heterogeneity within the wildtype group. In addition, the association of CYP2A6
genetic variation with smoking behaviours has been found predominantly in moderate to heavy
smokers of Caucasian ancestry. There is a need to determine whether these findings can be
extrapolated to light smoking populations in order to better understand the mechanisms of
dependence and factors motivating tobacco addiction in this growing segment of smokers.
Thus, the main objectives of this thesis are to:
• Identify and determine the functional consequences of novel CYP2A6 genetic variants
• Determine whether CYP2A6 genetic variation influences cigarette consumption, smoking
cessation and the utility of biomarkers of smoking in light smokers, with a focus on
populations of Black-African descent
1
GENERAL INTRODUCTION
SECTION 1: SMOKING AND NICOTINE
1.1 Prevalence
Tobacco smoking remains a leading cause of preventable illness, disability, and death (World
Health Organization, 2009). Despite the numerous negative health effects associated with
cigarette smoking, and tobacco control efforts aimed to reduce its accessibility and
acceptability, a substantial number of individuals continue to smoke. Adult cigarette
smoking has been declining in North America, with prevalence reduced by nearly half from
the mid-1960s to mid-1990s (World Health Organization, 2002). However, the rate of
decline in smoking prevalence has slowed in recent years and appears to have reached a
plateau, with approximately 21% of adults in North America currently reported as smokers
(Health Canada, 2008; Centers for Disease Control and Prevention, 2009; Benowitz, 2010;
National Cancer Institute et al., 2010).
There are considerable differences in smoking prevalence between racial/ethnic groups.
Rates of smoking are highest among American Indians/Alaskan Natives (32.4%), followed
by Caucasians (22.0%), African-Americans (21.3%), Hispanics (15.8%) and Asian-
Americans (9.9%) (Centers for Disease Control and Prevention, 2009) (Figure 1.1).
Smoking prevalence also tends to be higher among males compared to females (Figure 1.1)
(Hatsukami et al., 2008; Centers for Disease Control and Prevention, 2009). According to a
2008 survey, 23.1% of men were smokers in the United States compared to 18.3% of
women, with even greater differences observed among certain ethnic groups (Centers for
Disease Control and Prevention, 2009). Smoking is also more prevalent among those of
poorer socioeconomic status (Bobak et al., 2000) with highest rates observed in those without
a high school diploma (27.5%), or with only high school equivalency (41.3%), and lowest
2
rates observed among those with a graduate degree (5.7%) (Centers for Disease Control and
Prevention, 2009).
Figure 1.1: Prevalence of current smoking by ethnicity and gender. Current smoking is
defined as having smoked at least 100 lifetime cigarettes and reporting smoking every day or
some days at the time of interview. By definition Caucasians refers to individuals self-
reported as non-Hispanic Whites and African-Am refers to individuals self-reported as non-
Hispanic Blacks. Am-Ind refers to American-Indians, AK Natives refers to Alaskan Natives,
and Asian-Am refers to Asian-Americans. Data adapted from the 2008 National Health
Interview Survey (United States) (Centers for Disease Control and Prevention, 2009).
3
The global prevalence of smoking varies from 5% in some countries to more than 55% in
others (Hatsukami, Stead et al., 2008). Of particular concern is the rising rate of tobacco
consumption in developing countries such as China, India, and parts of Latin America and
Africa (World Health Organization, 2002; World Health Organization, 2009). Of the 1.3
billion smokers worldwide, more than 80% live in low- to middle-income nations where
smoking and its associated illnesses will add to the already existing health burdens and poor
quality of life in these countries (Gajalakshmi Ck et al., 2000).
1.2 Health consequences of smoking
Tobacco smoking is responsible for an estimated 5 million deaths each year worldwide, and
one out of two lifetime smokers will die from smoking-related illnesses (Doll R et al., 2004).
There are over 4,000 compounds in cigarette smoke, many of which have harmful effects on
health, including carbon monoxide, ammonia, hydrogen cyanide, and acrolein (World Health
Organization, 2002). Numerous carcinogenic compounds are also present in tobacco smoke;
of the 69 carcinogens identified, 11 are known human carcinogens and an additional seven
are likely to be carcinogenic in humans (National Cancer Institute). Evidence for a causal
relationship between smoking and cancer has been accumulating since the late 1930s. The
2004 Surgeon General Report concluded that smoking causes 30% of all cancer deaths,
accounting for approximately 80 to 90% of deaths attributed to lung cancer and
approximately 60 to 90% of deaths from upper aerodigestive cancers (Centers for Disease
Control and Prevention, 1998; U.S. Department of Health and Human Services, 2004;
National Cancer Institute, National Institutes of Health et al., 2010). Cigarette smoking is
also the cause of numerous respiratory and cardiovascular ailments, being responsible for 75
to 90% of chronic obstructive pulmonary disease (COPD) related deaths, 20 to 25% of
coronary heart disease deaths, and 18% of deaths from stroke (Centers for Disease Control
4
and Prevention, 1998; National Cancer Institute, National Institutes of Health et al., 2010).
Exposure to environmental tobacco smoke (ETS) also causes lung cancer and respiratory
problems in healthy non-smokers (Centers for Disease Control and Prevention, 1998). In
addition, maternal smoking during pregnancy, or ETS exposure in utero, has numerous
adverse effects on the fetus including increased risk for premature birth, low birth rates,
Sudden Infant Death Syndrome, birth defects and possible long-term physical and mental
effects (World Health Organization, 2002). In summary, tobacco smoking has immense
economic costs to society with an estimated $168 billion spent annually on health care
expenditures and loss in productivity in the United States alone (Office of National Drug
Control Policy, 2004).
The risk for many smoking-related illnesses, including cancers, cardiovascular diseases and
COPD has been shown to depend on dose, at least to some extent (Garfinkel et al., 1988; Us
Department of Health Education and Welfare, 1990; Jiménez-Ruiz C et al., 1998; Mucha et
al., 2006). Those who smoke 10 or fewer cigarettes per day (CPD) have 5.5-times the risk of
developing lung cancer compared to nonsmokers, with the comparative risk increasing to
approximately 14-times for those smoking 20 to 30 CPD and further to 22-times for those
smoking in excess of 31 CPD (Garfinkel and Stellman, 1988; Jiménez-Ruiz C, Kunze M et
al., 1998). The risk of myocardial infarction and death is greater among those with more
cumulative cigarettes smoked (Us Department of Health Education and Welfare, 1984;
Jiménez-Ruiz C, Kunze M et al., 1998). Similarly, reductions in ventilatory function are
seen in those smoking 1 to 10 CPD, although the effect is even greater among those smoking
more than 20 CPD (Us Department of Health and Human Services, 1984; Jiménez-Ruiz C,
Kunze M et al., 1998).
5
1.3 Heritability of smoking behaviours
Tobacco smoking is a complex behaviour with various stages including initiation,
experimentation, progression to regular use, cessation and relapse. While environmental
factors such as familial, peer, and social/cultural influences undoubtedly affect one’s
smoking behaviour, numerous studies have also demonstrated a substantial genetic
contribution. Large variations in estimation of the heritability of “ever” smoking, a broad
phenotype that can encompass those who have only tried cigarettes once to regular heavy
smokers, have been reported in the ranges of 11 to 78% (Ho et al., 2007; Rose et al., 2009).
Once smoking is initiated, the heritability for persistence to regular smoking has been
estimated at 28 to 84%, for number of cigarettes smoked at 45 to 86%, for diagnosed nicotine
dependence at 31 to 75%, for severity of nicotine withdrawal symptoms at 26 to 48% and for
smoking cessation at 50 to 58% (Ho and Tyndale, 2007; Rose, Broms et al., 2009; Ho et al.,
2010). It is notable that the heritability for the different behavioural stages of smoking (e.g.
initiation vs. persistence) only partially overlap, suggesting some genes are specific to one
smoking phenotype while others contribute to multiple aspects of smoking (Rose, Broms et
al., 2009). Variability in these estimates likely results, at least in part, from differences in
age and gender of participants. There is some evidence that the genetic influence on
likelihood of smoking increases with age as one progresses from early adolescence to young
adulthood (Rose, Broms et al., 2009). For example, a longitudinal study of adolescent twins
found the heritability of tobacco use increased from 15% at initial assessments (ages 13 to
18) to 35% at final follow-up (ages 20 to 25) (White et al., 2003). Some studies have
suggested a greater genetic influence on smoking among females although these results have
not been consistently reported (Rose, Broms et al., 2009). One meta-analysis found modest
differences in the heritability of smoking initiation and persistence between male versus
female twins (Li et al., 2003), although more recent studies did not report such findings
6
(Broms et al., 2006; Rose, Broms et al., 2009). Cohort effects and inconsistent phenotype
definitions may also contribute to the wide variability observed in heritability estimates.
1.4 Neurobiology of tobacco addiction
A common feature of all drugs with addiction liability is their ability to activate the
mesolimbic brain reward pathway which evolved to respond to “natural” rewards critical for
species survival such as food and sex (Ross et al., 2009). Repetitive drug use alters the
normal function of this circuitry, resulting in neuroadaptive changes and a new homeostatic
balance that underlies persistent drug-seeking behaviour and compulsive drug use despite
harmful consequences.
Nicotine is the major alkaloid in Nicotiana plants cultivated for tobacco products, where it
likely acts as natural insecticide (Tomizawa et al., 2003). It is the main psychoactive
substance in tobacco smoke that sustains addiction, and is readily absorbed into the arterial
circulation via inhalation through the lungs. Through this route, nicotine rapidly enters the
brain in an estimated 10 – 20 seconds; this likely contributes to the highly addictive potential
of tobacco smoke and makes it the most reinforcing and dependence-producing form of
nicotine administration (Hukkanen, Jacob et al., 2005). Nicotine acts upon nicotinic
acetylcholine receptors (nAChRs), which are located throughout the body and centrally in the
brain, to mediate a number of physiological and psychological effects.
1.4.1 Brain reward pathway
Nicotine activates dopaminergic neurons in the ventral tegmental area (VTA) of the midbrain
projecting to the nucleus accumbens (NAc) (Nestler, 2005; Changeux). This can occur
directly via interactions with nAChRs on dopaminergic neurons, as well as indirectly via
7
inhibitory and excitatory inputs coming into the VTA from other sources (such as
GABAergic and glutamatergic interneurons) (Mansvelder et al., 2002). Dopamine release
via this pathway signals a pleasurable experience and is critical in mediating drug-induced
reward; chemical or anatomical lesions of dopaminergic neurons in the VTA abolish nicotine
self-administration in rats (Corrigall et al., 1992). Dopaminergic neurons in the VTA also
project to the prefrontal cortex, amygdala, and hippocampus, regions that are important for
associative learning processes such as addiction (Nestler, 2005; Changeux).
In addition to dopamine, other neurotransmitters such as γ-aminobutyric acid, glutamate,
opioid peptides, serotonin, acetylcholine, norepinephrine, and endocannabinoids are also
released via nicotine’s binding to presynaptic nAChRs (Wonnacott, 1997; Benowitz, 2008).
These neurotransmitters contribute to the various other effects mediated by nicotine
including enhancement of cognitive functions, learning and memory processes, mood
modulation, anxiolytic effects, improvement of fine motor abilities, analgesia, and appetite
suppression (Benowitz, 2008; Heishman et al.).
Prolonged repeated exposure to nicotine results in long-lasting alterations of neuronal
function and synaptic plasticity of the brain reward circuitry (Mao et al., 2010). Classical
theories of dependence suggest these neuroadaptations form the basis of tolerance and
sensitization that leads to withdrawal symptoms and cravings upon smoking abstinence
(Watkins et al., 2000). Chronic tolerance, where increasing doses are needed to achieve the
same drug effect, has been demonstrated for the subjective, cardiovascular, and performance
enhancing effects of nicotine in humans (Perkins et al., 1994). Repeated drug use can also
result in sensitization, whereby enhanced response to subsequent drug exposure is observed.
Increased locomotor response (Clarke et al., 1983; Benwell et al., 1992; Shim et al., 2001)
8
and increased dopamine release in the NAc in response to nicotine administration (Benwell
and Balfour Dj, 1992; Cadoni et al., 2000; Shim, Javaid et al., 2001; Rahman et al., 2003)
have been reported in animals following chronic nicotine treatment, although sensitization in
humans has not been well established (Difranza et al., 2007). Upon abstinence, cravings and
withdrawal symptoms emerge that often oppose the effects of nicotine such as difficulty
concentrating, irritability, depressed mood, restlessness, anxiety, increased appetite and
insomnia (Benowitz, 2008).
1.4.2 Nicotinic acetylcholine receptors
Nicotinic acetylcholine receptors are transmembrane, ligand-gated, pentameric cation
channels composed of some combination of nine α (α2 – α10) and three β (β2 – β4) subunits.
The number of binding sites for brain nAChRs vary depending on subunit composition with
heteromeric receptors having two sites between alpha and beta subunits while homomeric
receptors can have up to five sites per pentamer (Penton et al., 2009). Most brain nAChRs
are located pre-synaptically where they modulate the release of neurotransmitters, although
some are also located post-synaptically (Gotti et al., 2009).
Upon binding of nicotine or the endogenous ligand acetylcholine, a conformational change
occurs and the channel opens to allow the permeation of sodium, potassium, and in some
cases calcium ions (Picciotto et al., 2008). Activation of the receptor is quickly followed by
desensitization wherein a second conformational change closes the channel and renders it
non-functional (Picciotto, Addy et al., 2008). Receptors in the desensitized state have higher
affinity towards ligands even though the channel no longer opens in response to agonist
binding (Picciotto, Addy et al., 2008). The rates of desensitization and recovery may differ
9
by pre- and post-synaptic nAChRs, or by different neuronal populations (Picciotto, Addy et
al., 2008).
Studies have shown that different combinations of α and β subunits result in neuronal
receptors with different pharmacological and functional properties (Penton and Lester, 2009).
These various nAChRs differ in their affinity for ligands, electrophysiological properties,
calcium permeability and upregulation by nicotine (Govind et al., 2009). High-affinity
nicotine binding sites are located in discrete regions throughout the brain, with the highest
densities found in the VTA and NAc (Azam et al., 2002). Animal studies have determined
that receptors with α4 and β2 subunits comprise approximately 90% of the high-affinity
nicotine binding sites in the brain (Flores et al., 1992), and mouse knockout models for these
subunits suggest they are critical for nicotine self-administration and nicotine-induced
dopamine release (Picciotto et al., 1998; Tapper et al., 2004). There are also other high-
affinity nicotine binding sites that have not been as well characterized which include α3, α5,
α6, α7, β3 and β4 subunits in various combinations (Wang et al., 1996; Gerzanich et al.,
1998; Kuryatov et al., 2000; Grinevich et al., 2005).
In moderate to heavy daily smokers, cigarettes are smoked regularly during the day to
maintain nicotine at elevated levels in the plasma (10 to 50 ng/ml) since nicotine has a
relatively short half-life at approximately one to two hours (Benowitz et al., 1994; Hukkanen,
Jacob et al., 2005). It has been shown that human β2-containing nAChRs become nearly
fully occupied after smoking one cigarette (Brody et al., 2006). The activation and
desensitization of nAChRs from smoking over the course of the day, and resensitization of
these receptors during overnight abstinence, likely alter states of neuronal activity and play
an important role in the behavioural effects of nicotine.
10
Chronic exposure to nicotine results in a number of neuroadaptive changes, many of which
are mediated through nAChRs (Gotti, Clementi et al., 2009). An increased number of high-
affinity nicotine binding sites are found following long-term exposure to nicotine in post-
mortem human brains of smokers (Benwell et al., 1988; Breese et al., 1997; Perry et al.,
1999), human cell lines (K-177 cells, a human embryonic kidney cell line stably expressing
α4 and β2 nAChR subunits) (Buisson et al., 2001) and rodent animal models (Marks et al.,
1983; Schwartz et al., 1983; Yates et al., 1995; Nguyen et al., 2003; Perry et al., 2007).
Several mechanisms have been proposed for the nicotine-induced upregulation of nAChRs
including decreased receptor turnover, increased assembly or maturation, increased
trafficking of receptors to cell surface, or slower subunit degradation (Govind, Vezina et al.,
2009). Chronic nicotine treatment may also potentially induce subunit stoichiometry changes
or receptor conformational changes (Govind, Vezina et al., 2009). It is notable that nicotine
acts on a variety of nAChRs of different subtype combinations, and the effect of chronic
nicotine exposure can differ depending on receptor subunit, cell type and brain region (Gotti,
Clementi et al., 2009).
1.4.3 Other targets implicated in tobacco addiction
In general, genes implicated in tobacco addiction can be categorized into those that influence
the liability to experiment with the drug in the first place, and those that are involved in the
biological processes underlying addiction once the individual has been exposed to the drug.
As such, genes that are related to personality traits (such as impulsivity, risk-taking or
response to stress) may predispose one to experimentation. Alternatively, genes encoding
proteins in the brain reward system (such as receptors, transporters and metabolic enzymes of
the neurotransmitter systems) and enzymes involved in nicotine metabolism may contribute
11
to the initial, immediate subjective and physiological reaction to tobacco smoke, thus
determining whether use will continue and escalate into development of dependence. A list
of genes implicated in tobacco dependence and smoking behaviours can be found in Table
1.1. These targets were hypothesized based on the current understanding of the neurobiology
underlying tobacco addiction. Genome-wide association studies without a priori hypotheses
have also identified a number of new genetic loci related to smoking phenotypes. For
example, the cell adhesion molecule neurexin 1 (NRXN1) has been associated with nicotine
dependence (Bierut et al., 2007; Nussbaum et al., 2008). These novel targets provide
additional insights into the neurobiology underlying addiction, although further assessments
of their functional impact are still necessary.
1.5 Nicotine: the main addictive substance in cigarettes
Nicotine has long been implicated as the main compound responsible for the highly addictive
properties of tobacco smoke; this has been supported by several lines of evidence.
1.5.1 Nicotine reinforcement
Historically, only tobacco products containing nicotine have been used habitually by
individuals over long periods of time. Cigarettes with nicotine removed, or that have ultra-
low nicotine yield, have not been used extensively by the public, although other nicotine-
containing products such as chewing tobacco and snuff are widely used (Benowitz, 2008).
Nicotine has reinforcing properties as demonstrated by self-administration paradigms and
conditioned place preference models in a number of rodent and non-human primate species
(Le Foll et al., 2009). However, nicotine self-administration is highly dependent upon
experimental conditions (such as state of food-deprivation, exposure to drug prior to testing,
rate of drug administration, dose, handling history, or presence of environmental
12
Table 1.1: A list of genes that have been implicated in tobacco addiction. References in (Ho, Goldman D et al., 2010).
Protein or enzyme (Gene name) Smoking phenotype Dopamine D2 receptor (DRD2/ANKK1) Smoking initiation, persistence, cigarette
consumption, cessation
Dopamine D4 receptor (DRD4) Smoking risk, time to first cigarette, craving and response to smoking cues, nicotine dependence
Dopamine transporter 1 (SLC6A3, DAT1)
Smoking risk
Monoamine oxidase-A (MAO-A) Cigarette consumption, smoking risk, nicotine dependence
Tyrosine hydroxylase (TH)
Smoking risk
Dopamine β-hydroxylase (DBH)
Smoking risk, nicotine dependence, cessation
Catechol-O-methyltransferase (COMT)
Smoking risk, nicotine dependence, cessation
Serotonin transporter (SLC6A4, 5HTT, SERT) Smoking risk, cigarette consumption, dependence
Tryptophan hydroxylase 1, 2 (TPH1, 2)
Age of smoking initiation, risk of smoking
μ1 - opioid receptor (OPRM1)
Smoking cessation
Nicotinic acetylcholine receptor – α4 subunit (CHRNA4)
Nicotine dependence
Nicotinic acetylcholine receptor – α5, α3, β4 subunits (CHRNA5, A3, B4 gene cluster on chromosome 15)
Nicotine dependence, cigarette consumption, lung cancer and COPD risk
Cytochrome P450 2A6 (CYP2A6)
Smoking risk, cigarette consumption, cessation
Cytochrome P450 2B6 (CYP2B6)
Smoking cessation
13
cues), with results varying by species and across laboratories (Le Foll and Goldberg, 2009).
In contrast, intravenous self-administration of drugs and conditioned place preference have
been readily demonstrated for other drugs including psychostimulants and opioids over a
wide range of conditions (Le Foll and Goldberg, 2009). This suggests that nicotine alone
may be a relatively weak reinforcer, and there is evidence showing it may also enhance the
reinforcement properties of non-nicotine stimuli (Chaudhri et al., 2006). Stimuli that are
initially neutral can develop reinforcing values as they are repeatedly paired with nicotine
through Pavlovian associative conditioning processes (Chaudhri, Caggiula et al., 2006).
A number of laboratory experiments have shown that humans will self-administer
intravenous nicotine (Henningfield Je, 1983; Henningfield Je, 1983; Rose et al., 2003;
Harvey et al., 2004; Sofuoglu et al., 2007). However, the results of these studies need to be
regarded with caution as they contain small sample sizes, and many participants were
multiple-drug users who also readily administered saline in some cases (Dar et al., 2004).
1.5.2 Nicotine-titration hypothesis
Nicotine has a short elimination half-life of approximately one to two hours (Hukkanen,
Jacob et al., 2005), and smokers are thought to smoke regularly over the course of the day to
maintain plasma nicotine levels in the body (Figure 1.2) (Mcmorrow and Foxx Rm, 1983;
Russell, 1987). This observed pattern of regular daily smoking forms the basis of a model
for tobacco dependence that emphasizes avoidance of withdrawal as the driving force behind
continued use (Shadel et al., 2000; Shiffman, 2009).
14
Figure 1.2: Schematic of circadian changes in plasma nicotine levels. This figure illustrates
the changes in nicotine plasma levels in individuals smoking at regular intervals over the
course of a day (approximately 20 to 30 cigarettes per day). The upper dotted line represents
the threshold level of nicotine needed to produce arousal and pleasure while the lower dotted
line represents the threshold level of nicotine needed to prevent withdrawal symptoms. The
first cigarettes of the day have the most pleasurable effects, and as tolerance to these effects
develops, subsequent cigarettes are smoked as a means to maintain nicotine levels and
prevent withdrawal symptoms. Overnight abstinence allows for resensitization of nAChRs
and response to subsequent nicotine intake. Modified from (Benowitz, 1992).
There are several lines of evidence supporting the nicotine-titration or nicotine-uptake-
regulation hypothesis. Alterations of nicotine renal excretion rates change smoking
behaviours. Urinary acidification using ammonium chloride increased renal clearance by
208%, reduced average blood nicotine concentration by 15%, and increased daily intake of
nicotine from smoking by 18% (Schachter et al., 1977; Benowitz et al., 1985). In contrast,
15
urinary alkalization using sodium bicarbonate reduced smoking (Cherek et al., 1982).
Alterations in smoking behaviours were also observed when smokers switched between
cigarettes that differed in their nicotine yields (Scherer, 1999). Smoking behaviour was
generally increased when nicotine yields were lowered, as indicated by increased puff
volume, duration, number of puffs, and exhaled carbon monoxide (CO) levels per cigarette
(Kozlowski et al.; Gust et al., 1982; Benowitz et al., 1983; Sepkovic et al., 1984; Scherer,
1999; Strasser et al., 2007). Conversely, smoking was reduced when using cigarettes
enriched with nicotine (Dunn Pj et al., 1978; Fagerström, 1982; Scherer, 1999). Methoxalen
is a known inhibitor of CYP2A6, the main enzyme involved in nicotine metabolism
(Maenpaa et al., 1993). Methoxalen increased the bioavailability of a co-administered oral
nicotine dose and together they decreased the desire to smoke, the amount smoked, and the
total number of puffs taken more than oral nicotine given alone (Sellers et al., 2000).
One further line of evidence is the reduction of smoking behaviours by nicotine
supplementation. Administration of nicotine prior to ad libitum smoking reduces the amount
of nicotine intake, cigarettes consumed, exhaled CO levels, and latency to smoking the next
cigarette (Benowitz et al., 1990; Perkins et al., 1992; Benowitz et al., 1998; Scherer, 1999).
Furthermore, nicotine replacement therapy as gum, patch, inhaler or nasal spray formulation
is a first-line smoking cessation aid (Stead et al., 2008). A number of studies have also tested
the effects of mecamylamine, a nAChR antagonist, on smoking behaviours. Chronic
treatment with mecamylamine results in an immediate, transient increase in smoking
behaviours during the first few days, likely as compensatory response in an attempt to obtain
the desired effects of smoking (Rose et al., 1997; Scherer, 1999; Rose, Behm et al., 2003).
This is followed by a gradual reduction in smoking as the reinforcing effects of smoking are
blocked and behavioural extinction occurs (Rose and Corrigall, 1997; Scherer, 1999; Rose,
16
Behm et al., 2003). Similarly, the nAChR partial agonist varenicline can be used to aid
smoking cessation; it is thought to work by mimicking the effects of nicotine through its
agonist effects, thereby alleviating withdrawal symptoms (Tonstad et al.; Mcneil et al.,
2010). In addition, varenicline can attenuate the rewarding effects of nicotine derived from
subsequent lapses of cigarette smoking by competitively inhibiting nicotine binding to
nAChRs (Tonstad and Rollema; Mcneil, Piccenna L et al., 2010).
1.5.3 Other compounds in tobacco smoke with addictive properties
While nicotine appears to be the main addictive substance in tobacco smoke, there is
evidence that other compounds may also be of importance. Chronic exposure to tobacco
smoke reduces the activity of monoamine oxidase A and B by 30 to 40% compared to non-
smokers or former smokers (Fowler et al., 1996; Fowler et al., 1996; Fowler et al., 1998;
Fowler et al., 1999). These enzymes catabolize the oxidation of dopamine, serotonin and
norepinephrine; increased levels of these neurotransmitters in the synapses likely contribute
to the addiction liability of tobacco smoke by altering reward, mood, and anxiety processes.
Acetaldehyde, a component of tobacco smoke, can form condensation products with biogenic
amines to produce tetrahydroisoquinolines (e.g. salsolinol) and β-carbolines (e.g. harman)
which are known inhibitors of monoamine oxidase (Fowler, Volkow Nd et al., 1996; Fowler,
Volkow et al., 1996; Fowler, Volkow Nd et al., 1998; Fowler, Wang et al., 1999). Indeed,
acetaldehyde has reinforcing properties in rodent behavioural models, increasing activity of
dopaminergic neurons in the VTA, and potentiating the reinforcing properties of nicotine
(Talhout et al., 2007; Le Foll and Goldberg, 2009). However, it remains to be validated
whether these effects of acetaldehyde occur at concentrations found in the brains of human
smokers (Talhout, Opperhuizen et al., 2007; Le Foll and Goldberg, 2009).
17
1.6 Nicotine pharmacokinetics
1.6.1 Absorption and distribution
Most cigarettes contain 10 to 14 mg of nicotine and, on average, 1 to 1.5 mg is absorbed
systemically during smoking (Hukkanen, Jacob et al., 2005). During smoking, nicotine is
rapidly absorbed from the small airways and alveoli due to their large surface area. Nicotine
is a weak base with pKa of approximately 8.0, and absorption across membranes in the lungs
is highly dependent on pH (Hukkanen, Jacob et al., 2005). Blood and brain concentrations of
nicotine rise rapidly during smoking; this rapid rate of absorption allows smokers to titrate
the nicotine dose as needed and underlies the highly reinforcing and dependence-producing
nature of cigarette smoke.
Nicotine plasma levels sampled in smokers during the afternoon typically range from 10 to
50 ng/ml (Hukkanen, Jacob et al., 2005). Smoking a single cigarette increases venous
nicotine blood concentrations by 5 to 30 ng/ml, with blood levels peaking at the end of
smoking and declining rapidly over the next 20 minutes as a result of tissue distribution
(Hukkanen, Jacob et al., 2005; Benowitz et al., 2009). Nicotine is 69% ionized and 31%
unionized in the bloodstream, with less than 5% protein-bound (Benowitz et al., 1982).
Nicotine is extensively distributed to body tissues with the highest affinity for liver, kidney,
spleen, lung and brain and lowest affinity for adipose tissue (Hukkanen, Jacob et al., 2005).
The plasma half-life of nicotine is approximately one to two hours (Benowitz and Jacob P
3rd, 1994), and the terminal half-life is approximately 11 hours, as measured from urinary
metabolites, due to the slow release of nicotine from body tissue stores (Jacob 3rd et al.,
1999).
1.6.2 Nicotine metabolism
18
Nicotine is eliminated via extensive hepatic metabolism; it is a high extraction drug and
undergoes a significant first-pass effect with oral bioavailability estimated at approximately
20 to 45% (Benowitz et al., 1991). The various pathways by which nicotine is removed in
humans are presented in Figure 1.3. The majority of nicotine (70 to 80%) undergoes C-
oxidation to form cotinine along with five other primary metabolites (Benowitz and Jacob P
3rd, 1994; Hukkanen, Jacob et al., 2005). Cotinine is also metabolized to a number of
compounds, with the majority undergoing oxidation to trans-3-hydroxycotinine (3HC)
(Bowman et al., 1962; Neurath Gb et al., 1988). Quantitatively, 3HC and its glucuronide
conjugate are the primary nicotine metabolites found in the urine of smokers, representing 40
to 60% of the nicotine dose (Byrd et al., 1992; Benowitz et al., 1994). Free cotinine and its
glucuronide also represent a substantial portion of the urinary metabolites found at
approximately 22 to 32%, while free and glucuronidated nicotine represent 11 to 15% of the
recovered nicotine dose (Byrd, Chang et al., 1992; Benowitz, Jacob et al., 1994).
1.6.3 Nicotine C-oxidation and contribution by CYP2A6
Nicotine is converted into cotinine by two enzymatic steps. CYP2A6 metabolizes nicotine
into an unstable nicotine-Δ1’(5’)-iminium ion intermediate that is rapidly metabolized to
cotinine by aldehyde oxidase in a reaction that is not rate-limiting (Brandange et al., 1979).
Cotinine is further metabolized to 3HC; this reaction is also primarily mediated through
CYP2A6 (Nakajima et al., 1996). Several lines of evidence have demonstrated that CYP2A6
is the main enzyme involved in the metabolism of nicotine and cotinine.
19
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20
1.6.3.1 In vitro studies
A predominant role of CYP2A6 in nicotine metabolism has been substantiated by studies
using human liver microsomes. Levels of CYP2A6 immunoreactive protein were highly
correlated with rates of nicotine C-oxidation activity (r = 0.60 to 0.94), with up to 88% of the
variability in activity accounted for by CYP2A6 protein levels (Nakajima et al., 1996;
Messina et al., 1997; Yamazaki et al., 1999). Nicotine C-oxidation was inhibited more than
75% using a monoclonal CYP2A6 antibody (Nakajima, Yamamoto et al., 1996; Messina,
Tyndale et al., 1997; Yamazaki, Inoue et al., 1999) while antibodies towards CYP2E1,
CYP2B1, CYP2D6 or CYP3A2 had no such effects (Messina, Tyndale et al., 1997).
Nicotine C-oxidation was also inhibited by more than 85% using coumarin (Nakajima,
Yamamoto et al., 1996; Messina, Tyndale et al., 1997; Yamazaki, Inoue et al., 1999), a
commonly used probe drug that is converted to 7-hydroxycoumarin selectively by CYP2A6
(Pelkonen et al., 2000). In contrast, substrates specific towards CYP1A, CYP2B6, CYP2C9,
CYP2C19, CYP2D6 and CYP2E1 did not inhibit nicotine C-oxidation activity (Nakajima,
Yamamoto et al., 1996; Messina, Tyndale et al., 1997; Yamazaki, Inoue et al., 1999).
Cotinine formation correlated well with formation of 7-hydroxycoumarin (r = 0.83) and
trans-3’-hydroxycotinine (r = 0.74) (Nakajima, Yamamoto et al., 1996). Of the hepatic
CYPs, cDNA-expressed CYP2A6 had the greatest capacity for nicotine C-oxidation, with
CYP2B6 and CYP2D6 showing minor metabolic activity (Yamazaki, Inoue et al., 1999).
Similar experiments using human liver microsomes suggest the metabolism of cotinine into
3HC is exclusively mediated by CYP2A6 (Nakajima, Yamamoto T et al., 1996). Cotinine
3’-hydroxylase activity was highly correlated with levels of CYP2A6 immunoreactive
protein (r = 0.76), but was not significantly correlated with liver content of CYP2B,
CYP2C8, CYP2C9, CYP2E1, CYP3A4 and CYP4A (Nakajima, Yamamoto T et al., 1996).
21
Cotinine 3’-hydroxylation was nearly abolished through competition by coumarin while
inhibitors selective for other CYPs showed no effect (Nakajima, Yamamoto T et al., 1996).
CYP2A6 monoclonal antibodies reduced cotinine 3’-hydroxylation by 64% to 69%.
Cotinine 3’-hydroxylation was significantly correlated with coumarin-7-hydroxylation (r =
0.89), and cDNA-expressed CYP2A6 mediated cotinine 3’-hydroxylation while CYP1A1,
CYP1A2, CYP2B6, CYP2D6, CYP2E1, and CYP3A4 had no detectable activity (Nakajima,
Yamamoto T et al., 1996).
1.6.3.2 In vivo studies
Further support for a role of CYP2A6 in nicotine metabolism has been found from in vivo
studies examining the metabolic profile in individuals who are homozygous for the
CYP2A6*4 gene deletion allele and thus completely lack functioning enzyme. Cotinine was
not detected in the plasma of these individuals two hours following oral nicotine intake
(Kwon et al., 2001; Nakajima et al., 2001). Similar results have been observed in other
studies showing greatly reduced cotinine levels, representing approximately 10% of total
metabolites, in the urine of smokers completely lacking CYP2A6 enzyme (Kitagawa et al.,
1999; Yang et al., 2001). Another study examined the urinary metabolite profile in
nonsmokers following administration of nicotine gum. Among those with fully functioning
CYP2A6, unchanged nicotine and nicotine N-glucuronide represented 25 to 30% of the
excreted urinary metabolites, with cotinine and cotinine-derived metabolites consisting of 58
to 67% of the excreted urinary metabolites (Yamanaka et al., 2004). In contrast,
approximately 68 to 70% of nicotine was excreted unchanged or as nicotine N-glucuronide in
CYP2A6*4/*4 individuals (n = 2), with trace amounts of cotinine or cotinine N-glucuronide
(2 to 3%), and no 3HC or its O-glucuronide detected (Yamanaka, Nakajima et al., 2004).
Nicotine N-oxide also represented 25 to 30% of the excreted urinary metabolites in
22
individuals lacking CYP2A6, suggesting some re-routing of nicotine elimination via this
pathway (Yamanaka, Nakajima et al., 2004). While other minor pathways may contribute to
the metabolism of nicotine in the absence of CYP2A6, the rate of removal of nicotine from
the body is still greatly reduced. In CYP2A6*4/*4 individuals, the mean area-under-the-
curve (AUC) for nicotine was increased by 3.6-fold, the AUC of cotinine was reduced by 15-
fold, and the half-life of nicotine was extended from 2 to 11 hours compared to those with
fully active CYP2A6 (Nakajima et al., 2000; Nakajima et al., 2005). Individuals categorized
as CYP2A6 intermediate or slow metabolizers, according to their CYP2A6 genotypes, also
had significantly higher AUC values for nicotine (Xu et al., 2002; Mwenifumbo, Al Koudsi
N et al., 2008) and lower AUC values for cotinine (Xu, Rao et al., 2002).
1.6.4 Other enzymes involved in nicotine metabolism
Nicotine, cotinine and 3HC undergo substantial glucuronidation whereby glucuronic acid is
enzymatically attached to the substrate, making the conjugated compounds more water-
soluble and readily excreted. This reaction is mediated by uridine diphosphate-
glucuronosyltransferases (UGTs). Rates of nicotine and cotinine N-glucuronidation were
highly correlated in vitro (r = 0.95) suggesting the same isoforms were responsible for both
reactions (Nakajima et al., 2002). Earlier studies have suggested the involvement of
UGT1A4, UGT1A9 and UGT2B7 (Kuehl et al., 2003); however, more recent studies have
implicated UGT2B10 as the major isoform involved in the N-glucuronidation of nicotine and
cotinine (Chen et al., 2007; Kaivosaari et al., 2007). UGT2B10 may also contribute to the
detoxification of several tobacco-specific nitrosamines via glucuronidation (Chen et al.,
2008; Chen et al., 2008). While 3HC can undergo N- and O-glucuronidation in human liver
microsomes (Kuehl et al., 2003; Yamanaka et al., 2005), only 3HC O-glucuronide has been
identified in the urine of smokers (Byrd et al., 1994). The rate of 3HC O-glucuronidation
23
was not correlated with the rates of nicotine or cotinine N-glucuronidation (Kuehl and
Murphy, 2003); thus, the O-glucuronidation of 3HC is likely catalyzed by a different
enzyme, and evidence suggests UGT2B7 is involved in this reaction (Yamanaka, Nakajima
et al., 2005).
There is large inter-individual and inter-ethnic variability in the rates of nicotine and cotinine
N-glucuronidation. In studies using human liver microsomes, the rates of nicotine N-
glucuronidation varied by approximately 22-fold and the rates of cotinine N-glucuronidation
varied by approximately 89-fold (Nakajima and Yokoi T, 2005). A trimodal distribution for
nicotine N-glucuronidation and bimodal distribution for cotinine N-glucuronidiation was
found in African-Americans while an unimodal distribution for both of these reactions was
found among Caucasians (Benowitz, Perez-Stable et al., 1999). This suggests there are some
African-Americans with particularly slow N-glucuronidation activity towards nicotine and
cotinine (Benowitz, Perez-Stable et al., 1999), and indeed, African-Americans excreted a
lower proportion of nicotine and cotinine as their glucuronide conjugates compared to
Caucasians (18 vs. 29% for nicotine glucuronidation, 41 vs. 62% for cotinine
glucuronidation) (Berg et al., 2010). Interestingly, the distribution of 3HC O-
glucuronidation was unimodal for both racial/ethnic groups (Benowitz, Perez-Stable et al.,
1999).
A genetic polymorphism altering enzyme function in UGT2B10 was recently identified. The
UGT2B10*2 (199 G>T, D67Y) reduced-function allele has been associated with slower rates
of nicotine and cotinine N-glucuronidation in human liver microsomes (Chen, Blevins-
Primeau et al., 2007; Chen, Dellinger Rw et al., 2008) and an approximately 20% decrease in
the excretion of nicotine and cotinine as their glucuronide conjugate in vivo (Berg, Mason et
24
al., 2010; Berg et al.). Although further studies are needed to evaluate the impact of
UGT2B10 genetic variability on nicotine clearance rates and smoking phenotypes, one recent
study suggests individuals with UGT2B10*1/*2 have lower total excreted nicotine
equivalents, an indicator of nicotine intake, compared to wildtype individuals (Berg, Von
Weymarn et al.).
A portion of absorbed nicotine is also eliminated as nicotine N’-oxide; approximately 4 to
7% of absorbed nicotine is found as nicotine N’-oxide in the urine of smokers (Byrd, Chang
et al., 1992; Benowitz, Jacob et al., 1994), and in individuals lacking CYP2A6, up to 31% of
absorbed nicotine is excreted as this metabolite (Yamanaka, Nakajima et al., 2004).
Nicotine N’-oxide is formed by flavin-containing monooxygenase 3 (FMO3); large
variability in the protein and activity levels have been reported, ranging nine- and six-fold,
respectively (Overby et al., 1997). A number of polymorphisms in the FMO3 gene have
been identified although their functional consequences, particularly toward nicotine N’-
oxidation, are unclear. Loss-of-function FMO3 variants have been identified in individuals
with trimethylaminuria, an inherited disorder also known as fish odor syndrome, although
such variants are likely extremely rare (Cashman et al., 2001).
1.6.5 Pharmacological actions of nicotine metabolites
Intravenous infusion of cotinine to plasma levels seen in moderate to heavy smokers did not
result in any physiological effects (i.e. changes in heart rate, blood pressure, skin
temperature), nor were any subjective effects reported (i.e. increased tension or anxiety,
depression, anger, hostility, vigor, confusion, or fatigue) (Benowitz et al., 1983; Zevin et al.,
2000). Oral administration of cotinine to achieve plasma levels that are up to 10-times higher
than those observed in smokers resulted in similar physiological and subjective effects as the
25
placebo control (Hatsukami et al., 1997). In this study, cotinine did not affect heart rate,
blood pressure, skin temperature, food intake or sleeping patterns, and changes in mood or
subjective effects were not reported (Hatsukami, Grillo et al., 1997). Cotinine does not up-
regulate nAChRs in the brain (Terry Jr et al., 2005) but it can evoke DA release from rat
striatal slices, albeit with much lower potency compared to nicotine (EC50 of 30 μM for
cotinine versus EC50 of 0.1 to 4.0 μM for nicotine) (Dwoskin et al., 1999). Similarly, 3HC
has been infused intravenously into smokers during abstinence without any significant
changes in heart rate or blood pressure (Benowitz et al., 2001). Subjective effects were not
consistently reported, although no placebo control was used in this study (Benowitz and
Peyton J Iii, 2001). Together, this suggests that cotinine and 3HC are unlikely to contribute to
the psychoactive effects mediated by nicotine.
Studies in rats have shown that nornicotine accumulates in the brain following repeated
nicotine exposure (Ghosheh et al., 2001) because it has a substantially longer half-life at
approximately 8 hours (Kyerematen Ga et al., 1990; Hukkanen, Jacob et al., 2005). Receptor
binding studies have shown that nornicotine can bind to nAChRs with high affinity and in
vitro can evoke DA release from rat nucleus accumbens slices, although with lower potency
(EC50 = 0.48 to 3.0 μM) compared to nicotine (EC50 = 70 nM) (Reavill et al., 1988; Green et
al., 2001). Nornicotine can also maintain i.v. self-administration in rats and induce
locomotor stimulation; however, these effects were weak and did not occur at
pharmacologically relevant concentrations (Bardo et al., 1999; Dwoskin et al., 1999).
1.7 Tobacco dependence
1.7.1 Acquisition of dependence
26
The majority of smoking experimentation and initiation occurs during adolescence;
approximately 80% of current smokers started smoking prior to age 18 (Giovino, 1999;
Centers for Disease Control and Prevention, 2006). Even though over 50% of young adults
in the United States have experimented with tobacco at least once (Centers for Disease
Control and Prevention, 2002; Pergadia et al., 2006; Centers for Disease Control and
Prevention, 2010), only a portion of those who have ever tried cigarettes (25-35%) will
become addicted regular smokers (Centers for Disease Control and Prevention, 1998). In
addition to the genetic factors that contribute to smoking initiation and progression to
dependence, a number of environmental factors have been identified. Studies have
demonstrated the importance of social-environmental factors such as familial and peer
influences (Simons-Morton, 2002; Vink et al., 2003), parental monitoring (Simons-Morton,
2002), academic achievements (Wilkinson et al., 2007), socioeconomic status (Soteriades et
al., 2003), initial reactions to the first cigarette (Pomerleau et al., 1993; Difranza et al., 2007),
tobacco industry marketing and access to tobacco (e.g. local cigarette taxation rate) (Evans et
al., 1995; Robinson et al., 1997). Various psychological factors and personality traits such as
impulsivity, novelty-seeking and risk taking, low self-esteem, depressed mood/affect
disorder, maladaptive coping skills and attitudes and beliefs about the benefits of smoking
have also been identified as predictors of smoking among adolescents (Wills et al., 1995;
Baker et al., 2004).
1.7.2 Diagnostic scales for tobacco dependence
A number of diagnostic scales have been created in an attempt to provide quantitative
assessment of the severity of tobacco dependence. Tobacco addiction is a complex, multi-
faceted disorder, and the various measures each have their advantages and limitations (Piper
et al., 2006). The Fagerström Test for Nicotine Dependence (FTND) (Heatherton et al.,
27
1991), the most widely used measure of tobacco dependence, was primarily developed as a
measure of physical dependence (Piper, Mccarthy et al., 2006). The FTND has utility due to
its adequate test-retest reliability and acceptable predictive validity of the success of smoking
cessation attempts and smoking relapse (Piper, Mccarthy et al., 2006). Its brevity and ease of
administration also makes it useful in clinical and epidemiological contexts. There is
generally low concordance between the FTND with formal diagnostic systems such as
Diagnostic Statistical Manual-IV (DSM-IV) and International Classification of Diseases-10
(ICD-10), suggesting these various measures are capturing slightly different aspects of
tobacco dependence (Hughes et al., 2004). More comprehensive scales have been developed
recently, such as the Nicotine Dependence Syndrome Scale (NDSS) and Wisconsin
Inventory of Smoking Dependence Motives (WISDM-68), that are multidimensional and
cover greater depth in the types of questions asked (Piper et al., 2004; Piper et al., 2008).
1.8 Smoking cessation
Tobacco addiction is a chronic, relapsing illness; more than 80% of moderate to heavy
smokers who attempt to quit without aid relapse within a month, with only 3 to 5%
maintaining long-term abstinence each year (Hughes et al., 2004). On average, four to five
quit attempts are typically made before successful long-term abstinence is achieved; as such,
smoking cessation is a difficult and complex process. Although a variety of methods have
been developed to aid smoking cessation (e.g. pharmacotherapy and behavioural counseling),
the currently available treatments are still rather limited in efficacy.
1.8.1 Treatments available
1.8.1.1 Pharmacotherapies
28
There are currently three types of drugs for smoking cessation approved by Health Canada.
These include various formulations of nicotine replacement therapy, bupropion (Zyban®)
and varenicline (Champix ®) (The Canadian Lung Association, 2010).
Nicotine replacement therapy (NRT)
NRT is the most commonly used pharmacotherapy for smoking cessation, providing an
alternative source of nicotine to reduce the intensity of nicotine withdrawal symptoms and
blunt the reinforcing effects of inhaled nicotine from cigarette smoke should a lapse occur.
NRT is currently offered in various formulations that are available over-the-counter
including chewing gum, transdermal patch, and lozenges, while the nicotine nasal spray or
oral inhaler are available with a prescription. While these preparations are buffered to
alkaline pH to increase the absorption of nicotine through cell membranes, the rise in
nicotine brain and blood levels is more gradual, without the sharp peaks observed from
smoking that are important for its addiction liability (Benowitz et al., 1988; Hukkanen, Jacob
et al., 2005). NRT provides low-level replacement of nicotine, with ad libitum use of these
products resulting in plasma levels that are one- to two-thirds of the levels achieved from
moderate to heavy cigarette smoking (Hukkanen, Jacob et al., 2005). For the chewing gum,
lozenges, nasal spray and oral inhaler, nicotine absorption takes place primarily through the
mucosa of the oral and nasal cavity rather than the lungs (Benowitz et al., 1987; Benowitz,
Jacob P 3rd et al., 1991; Compton et al., 1997; Hukkanen, Jacob et al., 2005). The
bioavailability for these products is estimated at 50 to 80% as a portion of nicotine is often
swallowed and undergoes extensive first-pass hepatic metabolism (Benowitz, Jacob P 3rd et
al., 1987; Benowitz, Jacob P 3rd et al., 1991; Compton, Sandborn Wj et al., 1997; Hukkanen,
Jacob et al., 2005). Nicotine is also well absorbed from the skin, with its rate of release from
a transdermal patch being dependent on skin permeability and the rate of diffusion of
29
nicotine through the polymer matrix. An estimated 68 to 100% of the amount of nicotine
released from the transdermal nicotine patch is absorbed into the body (Gupta et al., 1993;
Fant et al., 2000; Hukkanen, Jacob et al., 2005). This variability is likely due to some
evaporation of nicotine occurring from the exposed edges of the patch once it is applied on
the skin (Gupta, Benowitz et al., 1993).
Meta-analyses of randomized clinical trials have shown NRT significantly improves the
likelihood of smoking cessation compared to placebo, increasing the percentage of successful
quitters at 6 months from approximately 10% for the placebo treatment arm to approximately
17% for NRT treatment (Mcneil, Piccenna L et al., 2010). A large meta-analysis of 132 trials
found the relative risk of abstinence for any form of NRT compared to placebo control was
1.58 (95% confidence interval 1.50 to 1.66), ranging from 1.43 for nicotine gum, 1.66 for
transdermal patch, 1.90 for inhaler, 2.00 for oral lozenges, to 2.02 for nicotine nasal spray
(Stead, Perera R et al., 2008). There is evidence that the 4 mg gum was more efficacious
than the 2 mg gum, but the efficacy of nicotine patch did not differ by dose (Stead, Perera R
et al., 2008). The adverse effects related to NRT use vary by type of formulation and include
skin irritation (patch), sleep disturbances (24 hour patch), local irritation of nose or throat,
sneezing and coughing (spray), and hiccups (inhaler) (Mcneil, Piccenna L et al., 2010).
Bupropion (Zyban®)
Bupropion (Zyban®) was originally developed as an atypical antidepressant; however, it has
also proven effective in aiding smoking cessation in both depressed and non-depressed
smokers (Hayford et al., 1999; Smith et al., 2003; Cox et al., 2004; Hughes et al., 2007) It
has been shown to reduce cravings and relieve certain withdrawal symptoms associated with
smoking abstinence such as mood disturbances, difficulty concentrating and irritability
30
(Shiffman et al., 2000; Durcan et al., 2002). The neurobiological mechanism(s) by which it
aids smoking cessation is not well understood; it can act as a noncompetitive antagonist
towards brain nAChRs (Fryer et al., 1999; Slemmer et al., 2000), bind to striatal dopamine
transporters and prevent dopamine reuptake (Learned-Coughlin et al., 2003), as well as
inhibit the firing of noradrenergic neurons in the locus coeruleus at concentrations reached
during smoking cessation treatment (Cooper et al., 1994). 6’-Hydroxybupropion, the
primary metabolite of bupropion, is also pharmacologically active (Siu et al., 2007).
Randomized clinical trials have shown the quit rates observed at 6 months from bupropion
treatment are approximately 17% compared to an average of 9% in the placebo group
(Mcneil, Piccenna L et al., 2010). A meta-analysis of 36 trials for bupropion found the
relative risk for long-term abstinence at 6 months was 1.69 (95% confidence interval 1.53 to
1.85) as compared to placebo (Hughes et al., 2007).
Varenicline (Champix ®)
Varenicline (Champix ®) is a partial agonist for the α4β2 nAChRs (Mcneil, Piccenna L et al.,
2010). Randomized clinical trials have shown that the long-term abstinence rates reported at
6 months were approximately 26% for varenicline treatment compared to approximately 11%
for the placebo treatment (Cahill et al., 2008; Mcneil, Piccenna L et al., 2010). A meta-
analysis of seven trials found the relative risk of long-term abstinence at 6 months for
varenicline treatment was 2.33 (95% confidence interval 1.95 to 2.8) compared to placebo
(Cahill, Stead Lf et al., 2008). The relative risk of long-term abstinence at 12 months for
varenicline treatment was 1.5 (95% confidence interval 1.22 to 1.88) compared to bupropion
treatment in three clinical trials (Cahill, Stead Lf et al., 2008). One open-label trial also
found the relative risk of long-term abstinence at 12 months was 1.3 (95% confidence
31
interval 1.01 to 1.71) for varenicline treatment compared to nicotine patch treatment (Aubin
et al., 2008).
There is evidence that concomitant uses of different types of medication may have additional
benefits compared to monotherapy. Meta-analyses found that combining nicotine patch with
a rapid titratable form of NRT (such as nasal spray) or bupropion was more effective than
monotherapy alone (Shah et al., 2008; Stead, Perera R et al., 2008).
1.8.1.2 Non-pharmacological interventions
In addition to pharmacological options, various non-pharmacological approaches are useful
in aiding smoking cessation. Counseling is provided in most clinical trials in addition to the
pharmacological agents tested, and the quit rates observed in the placebo treatment arms are
often reflective of the effects that counseling alone had on smoking cessation. The most
common form is cognitive behavioural therapy; its overall goal is to help smokers identify
and break the association between environmental and social cues that motivate their
smoking, as well as to teach coping strategies for dealing with stress associated with nicotine
withdrawal (Black Jh 3rd).
Cognitive behavioural therapies
Current guidelines for smoking cessation treatment in the United States recommend a
combination of counseling and pharmacotherapy as this was more effective than either alone
(odds ratio = 1.4, 95% confidence interval 1.2 – 1.6) (Fiore et al., 2008; Hajek P et al., 2009).
One widely used form of cognitive behavioural counseling is motivational interviewing; it is
designed to help people explore and resolve uncertainties about their behaviour to help them
change their behaviour and encourage their self-efficacy to quit. One meta-analysis showed
32
motivational interviewing increases the likelihood of abstinence (relative risk 1.27, 95% CI
1.13 – 1.42) compared to brief advice (Lai et al., 2010). Other types of cognitive behavioural
counseling methods include health education, which provides information such as the
addictive nature of nicotine, health consequences of smoking and benefits of quitting, and
advice on developing concrete strategies to quit (Ahluwalia et al., 2006).
1.9 Biomarkers of tobacco smoke
The number of cigarettes smoked per day is often used as a proxy measure for toxin
exposure, level of addiction, or level of disease risk; however, self-report of cigarette usage
has a number of limitations. The way in which cigarettes are smoked can vary widely
between individuals; for example, differences exist in the number of puffs taken per
cigarette, puff interval and frequency, puff volume, depth of inhalation, duration of inhalation
and the blocking of filter vents (Scherer, 1999). As such, objective indicators of tobacco
smoke exposure are necessary. Biochemical validation of tobacco exposure is of great utility
in verifying smoking abstinence in clinical trials or recruitment into research studies given
the potential reporting bias of self-reported cigarette consumption. Biomarkers of cigarette
consumption are also important in epidemiological studies for assessing and quantifying the
dose-related risk of tobacco-related illnesses.
1.9.1 Common indicators of exposure
Two commonly used biomarkers of tobacco smoke exposure are cotinine and exhaled CO.
Cotinine is detected in a number of biological fluids; it has a long half-life (13 to 19 hours)
and is highly specific to nicotine exposure, although not necessarily cigarette smoke as
individuals consuming alternative sources of tobacco or nicotine replacement therapy also
have detectable cotinine (Benowitz and Jacob P 3rd, 1994; Benowitz et al., 2002). Exhaled
33
CO is a byproduct of tobacco combustion and can be readily measured, although it has a
short half-life (1 to 4 hours) and is not specific to tobacco smoke due to contributions from
environmental sources (such as vehicle exhaust) and endogenous formation from heme
catabolism (Benowitz, Peyton J Iii et al., 2002). Non-smokers living in urban environments
typically have exhaled CO levels of 3 to 5 ppm, and may be as high as 7 ppm in some cases
(Jones et al., 2006; Scherer, 2006). Endogenous CO formation is estimated to result in
approximately 0.7% carboxyhemoglobin levels in blood (Coburn et al., 1965), which
corresponds to approximately 0.3 ppm of exhaled CO (Scherer, 2006). A number of other
biomarkers have been proposed, although these also have advantages and limitations.
Tobacco-specific alkaloids anabasine and anatabine have high tobacco specificity, long half-
lives and are not present in NRTs (Benowitz, Peyton J Iii et al., 2002). However, these
metabolites are found at less than 5% of nicotine or cotinine levels detected in the urine of
smokers, and cost-effective methods for their detection remain to be developed (Benowitz,
Peyton J Iii et al., 2002). Relatively simple and affordable assays are available to detect
thiocyanate, a combustion product of hydrogen cyanide; however, it is limited by its lack of
specificity due to its presence in dietary sources (Benowitz, Peyton J Iii et al., 2002).
SECTION 2: LIGHT SMOKING
2.1 Prevalence
The models developed to understand tobacco dependence were based primarily on
observations in moderate to heavy smokers, and there is a paucity of research on tobacco use
and the manifestation of tobacco dependence among non-daily users or light smokers.
National surveys of tobacco use in the United States did not include questions for non-daily
smoking until 1992 (Shiffman, 2009). Among current adult smokers in the United States,
34
recent estimates of non-daily smoking ranges from 20% to over 30% (Hassmiller et al., 2003;
Office of Applied Studies and Substance Abuse and Mental Health Services Administration,
2006). An additional 25 to 30% of current adult smokers report smoking 10 or fewer CPD
(Kandel et al., 2000; Trinidad et al., 2009). Similar prevalence has been reported by the
Canadian Tobacco Use Monitoring Survey, with 20 to 25% of current adult smokers
reporting non-daily use and 33% of current adult smokers consuming 10 or fewer CPD
(Health Canada, 2008). Together, this suggests a substantial proportion of the smoking
population in North America use non-daily or exhibit light smoking patterns (i.e. 10 or fewer
CPD). Non-daily smoking is also highly prevalent in other parts of the world; at least two-
thirds of the smokers in developing countries such as Mexico, Ecuador and Guatemala are
non-daily users (World Health Organization, 2007).
Epidemiological surveys from recent years suggest that although overall smoking prevalence
has been declining in North America (Health Canada, 2008; Centers for Disease Control and
Prevention, 2009; Benowitz, 2010; National Cancer Institute, National Institutes of Health et
al., 2010), the prevalence of non-daily smoking has been on the rise. In the United States, the
percentage of current adult smokers reporting non-daily use increased from 16% in 1998 to
22% in 2009 (Wortley et al., 2003; Centers for Disease Control and Prevention, 2010).
Similarly, the percentage of current adult smokers reporting non-daily use increased from
17% in 1998 to 25% in 2008 in Canada (Health Canada, 2008). The reported number of
cigarettes smoked per day has also been declining among daily smokers. The average CPD
smoked by adults in the United States decreased considerably from 25.1 in males and 21.5 in
females in 1980, to 16.7 in males and 13.2 in females by 2000 (Duval, Jacobs Jr et al., 2008).
Similar trends have been reported in Canada with the average CPD among adults declining
from 20.6 in 1985 to 14.9 in 2008 (Health Canada, 2008). These changes are likely the result
35
of immense tobacco control efforts limiting smoking via bans, taxation, and denormalization
of the behaviour.
2.2 Health consequences
There is no safe level of smoking, and even light smokers are at a significantly elevated risk
for developing smoking-related illnesses. Light smokers have an increased risk of cancer,
cardiovascular disease, and total mortality compared to never smokers. In a Norwegian
population, smoking one to four CPD significantly increased the risk of mortality from
ischemic heart disease by approximately 3-times, from lung cancer in females by
approximately 5-times, and from any cause by approximately 1.5 times compared to never
smokers (Bjartveit et al., 2005). Light smokers consuming between three to nine CPD also
have approximately 2.1 times higher risk of myocardial infarction compared to non-smokers
(Prescott et al., 2002). In addition, light smokers have a higher risk for gastrointestinal
cancers and higher incidence of a number of other illnesses including respiratory ailments,
cataracts, and compromised reproductive health (Schane et al., 2010).
2.3 Demographics
2.3.1 Ethnic minorities
Ethnic minorities currently constitute approximately 25% of the American population and
this proportion is expected to grow to approximately 50% by 2050 (Okuyemi Ks, Harris Kj et
al., 2002). Smoking prevalence and levels of cigarette consumption vary widely among
racial/ethnic minority groups in the United States. While approximately 40% of Caucasian
current smokers reported non-daily use or smoking 10 or fewer CPD, as much as 67% of
African-Americans, 72% of Asian-Americans, and 76% of Hispanic-Americans reported
smoking at these levels (Trinidad, Perez-Stable et al., 2009). Similar findings have been
36
found in earlier surveys, suggesting ethnic differences in cigarette consumption have existed
since at least the early 1990s (Husten et al., 1998; Hassmiller, Warner Ke et al., 2003;
Trinidad, Perez-Stable et al., 2009).
2.3.2 Females
Females generally smoke fewer CPD compared to males (Okuyemi et al., 2001; Health
Canada, 2008; Tong et al., 2009; Trinidad, Perez-Stable et al., 2009). The factors motivating
smoking behaviours appear to differ between the genders, with females being more likely to
smoke to relieve stress and negative affect (Mermelstein, 1999; Perkins et al., 1999; Piper et
al., 2001). They are also more responsive to the sensory component of cigarettes and to
environmental cues to smoke (e.g. under certain social situations) (Mermelstein, 1999;
Perkins, Donny E et al., 1999; Piper, Welsch et al., 2001). In addition, pregnancy can also
greatly influence smoking behaviours. Among females who continue to smoke during
pregnancy, an estimated 25 to 50% reported a significant reduction in cigarette consumption
(Floyd et al., 1993).
2.3.3 Young adults
The majority of smokers begin experimentation prior to age 18, and only a portion of those
who ever try cigarettes will progress to regular smoking. It takes approximately two years to
establish stable smoking patterns following initial experimentation (Difranza et al., 2005). In
a national survey of American high school students in Grades 9 to 12, 19.5% of respondents
reported current smoking, defined as having smoked cigarettes on at least one day during the
past 30 days prior to survey. Only 11.2% of respondents reported ever smoking daily, and
just 7.8% of current smokers consumed more than 10 CPD on the days that they did smoke
(Centers for Disease Control and Prevention, 2010). A large proportion of adolescent current
37
smokers (50.8%) had tried to quit in the 12 months preceding the survey (Centers for Disease
Control and Prevention, 2010). Thus, light smoking among adolescents and young adults
likely represents a transitory phase that smokers progress through prior to either establishing
a regular smoking pattern, reducing their consumption levels, or quitting (Okuyemi Ks,
Harris Kj et al., 2002). However, while light smoking appears to be a transitory phase in
some cases, there are groups of individuals who maintain this low level of consumption
throughout their smoking career. It is not yet clear why some progress to heavier daily
smoking patterns while others maintain low levels of consumption.
2.4 Tobacco dependence
2.4.1 Smoking characteristics
Light smoking behaviours challenge traditional theories of tobacco addiction, as smoking at
regular intervals over the course of the day was believed to be necessary in order to maintain
sufficient nicotine levels in the body and avoid the development of withdrawal symptoms.
The majority of Caucasian smokers consume a pack of cigarettes or more daily, although
approximately 5% of total current smokers are considered to be light smokers who smoke
five or fewer CPD on at least four days of the week. A limited number of studies have
examined tobacco dependence among light smokers of Caucasian ancestry and found that
they do not appear to exhibit characteristic features of tobacco dependence in contrast to
Caucasian moderate to heavy smokers (Shiffman, 1989; Shiffman et al., 1995). Caucasian
light smokers do not report withdrawal symptoms during smoking abstinence, have less
cravings for cigarettes and fewer urges to smoke between cigarettes, are less likely to smoke
even when ill or in places where it is forbidden, and have a longer latency to first cigarette in
the morning (Shiffman, 1989; Shiffman et al., 2006). However, these Caucasian light
smokers inhale cigarette smoke with similar smoking topography, show similar
38
cardiovascular responses to cigarettes, absorb equal amounts of nicotine and appear to
eliminate nicotine at similar rates as heavier smokers (Shiffman et al., 1990; Brauer et al.,
1996). It is unlikely these Caucasian light smokers are smoking to maintain plasma nicotine
levels due to the long time interval between each cigarette smoked (Shiffman et al., 1992).
Smoking among these Caucasian light smokers appeared to be less associated with mood
states, and does not appear to be just a social activity (Shiffman, 1989; Shiffman and Paty J,
2006). Rather, smoking appears to be often associated with indulgent activities such as
relaxation, socialization, eating and drinking alcohol or coffee (Shiffman and Paty J, 2006).
It is notable that these studies have only been done in Caucasian light smokers consuming
five or fewer CPD and findings may not be extrapolated to light smokers of other
racial/ethnic populations. Furthermore, light smokers are a heterogeneous population, and
the factors influencing smoking behaviours probably differ between individuals smoking five
or fewer CPD compared to those smoking 6 to 10 CPD.
2.4.2 Interventions for smoking cessation
The process of smoking cessation among light smokers is not well understood due to the
general misconception that they are able to quit successfully on their own. As such, they
have been excluded from nearly all of the clinical trials for smoking cessation published to
date. However, it is becoming more evident that these smokers have difficulty achieving and
maintaining abstinence. There is currently one published clinical trial that tests the efficacy
of 2 mg nicotine gum and counseling specifically in African-Americans smoking 10 or fewer
CPD (Ahluwalia, Okuyemi et al., 2006). Nicotine gum did not significantly improve the
likelihood of abstinence compared to placebo, although health education counseling resulted
in significantly higher quit rates compared to motivational interview counseling (Ahluwalia,
Okuyemi et al., 2006). In general, only 15 to 30% of the participants were able to quit
39
smoking even with formal treatment in this study, which is comparable to the quit rates
observed in other clinical trials of Caucasian or African-American moderate to heavy
smokers (Ahluwalia et al., 2002; Stead, Perera R et al., 2008).
2.5 African-American light smokers
Tobacco-related health disparities exist between racial/ethnic groups. These include
differences in smoking initiation rates, current use, amount consumed, quitting success, and
health consequences of smoking. In particular, African-Americans experience
disproportionately higher incidences of tobacco-related illnesses such as lung cancer despite
their lower self-reported levels of cigarette consumption. Addressing the lack of research
and inequalities in health care for this particular group of light smokers is necessary to reduce
the disparities that currently exist (Fagan et al., 2007).
2.5.1 Demographics
According to the 2007 United States census, 12.4% of individuals reported themselves as
African-American or Black (Grieco, 2009). Eight percent of African-Americans are foreign-
born with the majority migrating from the Caribbean or Africa (Grieco, 2009). Current
smoking prevalence among African-Americans (21.3%) is similar to that in Caucasians
(22.0%) (Figure 1.1) (Centers for Disease Control and Prevention, 2009). However, the
proportion of current smokers reporting non-daily use was greater among African-Americans
(23.8%) compared to Caucasians (16.6%). The proportion of current smokers who smoke 10
or fewer CPD was also greater among African-Americans (42.7%) compared to Caucasians
(23.8%) (Trinidad, Perez-Stable et al., 2009).
2.5.2 Smoking initiation
40
African-Americans have a delayed onset of smoking initiation, with many experimenting and
developing regular smoking patterns after age 18 or during young adulthood, whereas this
typically occurs during early- to mid-adolescence for Caucasians (Robinson, Klesges Rc et
al., 1997; Griesler et al., 1998; Everett et al., 1999; Ellickson et al., 2004; Trinidad et al.,
2004; Trinidad et al., 2004; Fagan, Moolchan Et et al., 2007; Centers for Disease Control and
Prevention, 2010; Centers for Disease Control and Prevention, 2010). Only 9.5% of African-
American high school students reported smoking on at least one day of the past month,
compared to 18.0% of Hispanics and 22.5% of Caucasians who reported doing so (Centers
for Disease Control and Prevention, 2010). One longitudinal study also found that African-
American adolescents had a greater tendency to stop smoking instead of progressing to more
regular smoking patterns compared to Caucasians or Hispanics (Ellickson, Orlando et al.,
2004).
2.5.3 Cigarette consumption
Among African-Americans adults, more than 40% of males and 60% of females smoke 10 or
fewer CPD (Haiman, Stram et al., 2006). However, in spite of the lower cigarette
consumption among African-American smokers, they have higher plasma cotinine levels
compared to Caucasian smokers (Caraballo et al., 1998; Benowitz, Perez-Stable et al., 1999;
Moolchan et al., 2006; Signorello et al., 2009). African-American smokers also have higher
plasma cotinine levels compared to Mexican-American smokers who reported similar levels
of cigarette consumption (Caraballo, Giovino et al., 1998). One possible explanation is that
African-Americans have slower rates of cotinine metabolism, resulting in an accumulation of
cotinine per cigarette smoked. There is evidence to suggest that African-Americans have
slower rates of cotinine clearance and higher intake of nicotine per cigarette compared to
Caucasians (Perez-Stable et al., 1998). African-Americans may also have greater exposure
41
to tobacco smoke per reported cigarette as a result of deeper inhalation or greater preference
for menthol cigarettes that contain higher nicotine and tar content.
2.5.4 Use of menthol cigarettes
Menthol was first used as a cigarette flavoring in the late 1920s, adding a pleasant taste and
cooling sensation to cigarette smoke (Garten et al., 2003). Approximately 75% of African-
American smokers prefer menthol cigarettes compared to 25 to 30% of Caucasian smokers
(Centers for Disease Control and Prevention, 1998; Balbach et al., 2003). This is likely due
to advertising campaigns beginning in the 1960s that specifically targets African-American
smokers with culturally-sensitive images and messages strongly promoting the use of
menthol cigarettes (Balbach, Gasior et al., 2003; Gardiner, 2004). However, this marketing
strategy appears to be specific to the United States as only 8% of individuals of Black-
African descent in Canada report smoking menthol cigarettes (Mwenifumbo et al., 2008).
Menthol has a short half-life of approximately 1 hour, and it undergoes extensive
glucuronidation by UGT1A4 and UGT2B7 (Coffman et al., 1998; Heck, 2010). Menthol
does not appear to have any direct toxicological or carcinogenic effects when administered
alone (National Cancer Institute, 1979; Murthy et al., 1991; Bhatia et al., 2008), although the
cooling and anti-tussive effects of menthol may reduce the irritation by cigarette smoke,
allowing for deeper inhalation and larger puff volumes. In addition, it has been proposed that
menthol may allow for greater absorption of toxins by increasing the permeability of cell
membranes, and that menthol itself may be converted to carcinogenic compounds following
pyrolysis (Schmeltz et al., 1968; Kitagawa et al., 1999; Werley et al., 2007). While
activation of cold thermoreceptors (e.g. TRPM8) in the respiratory tract by menthol may
42
result in the perception of increased airflow (Bandell et al., 2006), there does not seem to be
any actual changes in nasal patency or resistance to airflow (Garten and Falkner, 2003).
A number of experimental studies have tested the effect of menthol cigarettes on smoking
topography (such as puff volume or number of puffs) with inconsistent results. Some studies
suggest more intense inhalation (Miller et al., 1994; Ahijevych et al., 1999), others show no
change (Ahijevych et al., 1996) and some suggest less intense inhalation among those who
smoke menthol versus regular cigarettes (Nil et al., 1989; Jarvik et al., 1994; Mccarthy et al.,
1995). Menthol cigarette smokers were found to have higher exhaled CO values compared
to regular cigarette smokers in some studies (Miller, Jarvik et al., 1994; Clark et al., 1996),
although other studies have reported lower exhaled CO levels (Ahijevych, Gillespie et al.,
1996), or no differences (Nil and Battig, 1989; Jarvik, Tashkin et al., 1994; Mccarthy,
Caskey et al., 1995). Similarly, discrepancies in the effect of menthol cigarettes on cotinine
levels have been reported. Some studies suggest menthol cigarette smokers have higher
cotinine and cotinine per cigarette levels even after adjustment for race (Clark, Gautam et al.,
1996; Ahijevych and Parsley, 1999; Wang et al., 2010), whereas other studies did not find
such differences (Ahijevych et al., 1994; Ahijevych, Gillespie et al., 1996; Mustonen et al.,
2005). It is notable that many of these studies contained small sample sizes and/or also
included Caucasian smokers in some cases which may complicate interpretation of the
results.
Numerous studies have examined the role of menthol cigarettes on smoking initiation and
cessation, although results from these studies have also been inconsistent (Hyland et al.,
2002; Muscat et al., 2002; Moolchan, 2004; Okuyemi et al., 2004; Okuyemi et al., 2007;
Heck, 2010). The greater use of menthol cigarettes among African-Americans has been
43
proposed to contribute to their disproportionately higher incidence of smoking-related
illnesses. However, a number of case-control studies failed to demonstrate that smoking
menthol cigarettes substantially alters the risk of smoking-related illnesses (including
cardiovascular and respiratory diseases, lung or esophageal cancers) after adjustment for age,
race, gender and amount smoked (Hebert et al., 1989; Kabat et al., 1991; Kabat et al., 1994;
Sidney et al., 1995; Carpenter et al., 1999; Stewart Jh 4th, 2001; Brooks et al., 2003;
Stellman et al., 2003).
2.5.5 Smoking cessation
More than 70% of African-American adult smokers have indicated that they would like to
quit smoking completely (Centers for Disease Control and Prevention, 1998). However,
despite their willingness to quit, African-Americans appear to be less successful at quitting
smoking compared to Caucasians. Epidemiological studies have found that African-
Americans have a lower quit ratio, defined as the proportion of ever smokers who have quit
smoking, compared to Caucasians (Novotny et al., 1988; Royce et al., 1993; Centers for
Disease Control and Prevention, 1998; King et al., 2004; Haiman, Stram et al., 2006; Fu et
al., 2008). This observation that African-Americans were less likely to be former smokers
compared to Caucasians remained even after controlling for demographic factors (such as
gender, age, marital status, and socioeconomic status) or smoking characteristics (such as
amount of cigarettes smoked per day, time to first cigarette in the morning, and age of
smoking initiation) (Novotny, Warner et al., 1988; King, Polednak et al., 2004; Fu, Kodl et
al., 2008).
2.5.6 Health disparities
44
The rates of many smoking-related cancers have been declining for all racial/ethnic groups
since the early 1990s. However, morbidity and mortality from smoking-related cancers still
remain highest among African-Americans despite their lower cigarette consumption and
delayed onset of smoking compared to Caucasians. African-Americans have higher
incidence and mortality from cancers of the lung, oral cavity, pancreas, esophagus and larynx
(Stewart Jh 4th, 2001; Edwards et al., 2005; Haiman, Stram et al., 2006; Fagan, Moolchan Et
et al., 2007). In fact, the death rate for all cancers combined is 35% higher in African-
American males and 18% higher in African-American females compared to Caucasian males
and females, respectively (Ries et al., 2006; American Cancer Society, 2008). The
racial/ethnic disparity of lung cancer is particularly evident among African-American males,
where incidence and mortality rates were 40 to 60% higher compared to Caucasian males
(Stewart Jh 4th, 2001; Haiman, Stram et al., 2006; Ries, Harkins D et al., 2006; Fagan,
Moolchan Et et al., 2007; American Cancer Society, 2008).
Racial/ethnic disparities in cancer mortality have been attributed to socioeconomic
inequalities that influence cancer prevention, time to detection, and access to quality health
care (Centers for Disease Control and Prevention, 1998; Delancey et al., 2008). Differences
in environmental correlates of socioeconomic status such as dietary habits, occupational
exposure and general health outcomes may, in part, account for the observed disparities
(Centers for Disease Control and Prevention, 1998). African-Americans have historically
had greater occupational exposure to carcinogens by working in industries such as steel and
rubber manufacturing, textiles and shipbuilding (Stewart Jh 4th, 2001). It is also possible
that African-Americans have a greater biological sensitivity towards developing tobacco-
related cancers. In addition to CYP2A6, other polymorphic xenobiotic metabolizing
enzymes such as CYP1A1, CYP2A13, CYP2D6, CYP2E1, UGTs and glutathione S-
45
transferases may contribute to carcinogenesis by activating procarcinogens or detoxifying
carcinogenic and mutagenic agents (El-Zein et al., 1997; Stewart Jh 4th, 2001). Racial/ethnic
differences in the activity of these activating or detoxifying enzymes may in part explain the
disparities in cancer rates, although studies to support this have not yet been performed.
In addition to cancers, tobacco smoking is the main cause of several non-malignant
respiratory illnesses. African-Americans have had lower rates of chronic bronchitis,
emphysema and COPD in the past (Centers for Disease Control and Prevention, 1998),
although more recent data suggests mortality rates from COPD have been rising faster in
African-Americans than in Caucasians (Kirkpatrick et al., 2009). There is evidence that
African-Americans with COPD are less likely to utilize medical services and account for
lower medical costs compared to Caucasians with COPD, providing a possible explanation
for the disparities in mortality rates (Shaya et al., 2009).
SECTION 3: CYP2A6
3.1 CYP2 gene family
The cytochromes P450 (CYP) are a superfamily of heme-containing mono-oxygenases
involved in numerous endogenous processes such as the metabolism of fatty acids,
cholesterol, steroids and eicosanoids, as well as the detoxification or bioactivation of a wide
range of xenobiotics. Members of the same CYP family (e.g. CYP2) share more than 40%
amino acid identity while members of the same CYP subfamily (e.g. CYP2A) share more
than 55% amino acid identity (Anzenbacher et al., 2001). There are presently 57 active CYP
genes identified, with the CYP1, CYP2 and CYP3 families of enzymes having the greatest
contribution to xenobiotic metabolism (Nelson et al., 2004; Ingelman-Sundberg, 2005). Of
46
these, the CYP2 family is the largest and most diverse; the CYP2ABFGST gene cluster is
located in an approximately 500 kb region on chromosome 19q13.2 and consists of numerous
genes and pseudogenes of high sequence similarity (Figure 3.1).
3.1.1 Evolutionary origins of CYP2ABFGST gene cluster
Various CYP gene subfamilies (e.g. CYP2C, CYP2D, CYP2J, CYP3A, and CYP4F) are
scattered across the genome, representing older duplication events that have been separated
by chromosomal arrangements over time, while genes within a subfamily tend to be
physically clustered as they are derived from a series of more recent tandem duplications
(Nelson, Zeldin et al., 2004). However, two CYP gene clusters (CYP2ABFGST and
CYP4ABXZ) contain a series of mixed subfamilies that likely arose from more complicated
molecular evolutionary events. The human CYP2ABFGST gene cluster is thought to
originate from an initial series of tandem duplications followed by inverted duplication,
further tandem duplications and insertion of CYP2B6 and CYP2B7P (Hoffman et al., 2001)
(Figure 3.1).
Detailed analyses of the CYP2ABFGST cluster in mouse (chromosome 7), rat (chromosome
1), and non-human primates (chromosome 19) have been performed. It is believed that this
gene cluster originated in a common ancestor of primates and rodents with a single “founder”
locus for each of the six CYP2 subfamilies that duplicated early in mammalian evolution (Hu
et al., 2008). Rodents evolutionarily diverged from primates approximately 85 million years
ago and accordingly the arrangement of the CYP2ABFGST cluster is more closely related
between mice and rats than to humans (Wang et al., 2003; Hu, Wang et al., 2008).
Comparison of the gene cluster in humans and chimpanzees, who diverged evolutionarily
around 7 million years ago, suggests it has undergone only small-scale chromosomal
47
rearrangements, while a substantially different arrangement of the locus is found in Rhesus
macaques who diverged approximately 25 to 30 million years ago (Hoffman et al., 2007).
Figure 3.1: Human CYP2ABFGST gene cluster on chromosome 19q13.2. Each triangle
represents a gene and the orientation of each gene is illustrated with transcription occurring
5’ to 3’ in the direction of each triangle. Shading indicates genes that belong to the same
subfamily. A number of inactive pseudogenes are found in this cluster (CYP2T2P, 2F1P,
CYP2A7, CYP2G1P, CYP2A18PC/PN, CYP2B7P, CYP2G2P, and CYP2T3P). Insertion of
CYP2B6 and CYP2B7P separates the CYP2A18 pseudogene into two segments. Figure is not
drawn to scale. Modified from (Hoffman and Nelson Dr, 2001).
3.1.2 CYP2A subfamily
There are three full CYP2A genes found in humans: CYP2A6, CYP2A7, and CYP2A13. The
CYP2A6 and CYP2A7 loci arose from tandem duplications; each gene is approximately 6.7
kb and they are physically separated by less than 6 kb of unique sequence (Hoffman and
Nelson Dr, 2001). The CYP2A subfamily of genes has an extremely high degree of sequence
identity; CYP2A6 has 95% identical gene sequence (including exons and introns) and 94%
identical amino acid sequence to CYP2A7 (Hoffman and Nelson Dr, 2001). Similarly, the
gene sequence of CYP2A13 is 85% identical to CYP2A6 and 90% identical to CYP2A7, while
the amino acid sequence of CYP2A13 is 93% identical to CYP2A6 and 90% identical to
CYP2A7 (Hoffman and Nelson Dr, 2001).
48
3.1.3 CYP2A tissue expression
CYP2A6 is primarily expressed in the liver, representing 1 to 10% of total liver CYP content
(Pelkonen, Rautio et al., 2000). Low levels of CYP2A6 mRNA have also been detected in
the nasal olfactory mucosa (Su et al., 1996; Koskela et al., 1999), lung, skin, coronary
arteries, esophagus, and breast (Hukkanen et al., 2002; Hukkanen, Jacob et al., 2005).
Similarly, low levels of CYP2A6 protein have also been detected in the nasal olfactory
mucosa (Su, Sheng et al., 1996), lung, larynx, esophagus, and breast (Hukkanen, Pelkonen et
al., 2002; Hukkanen, Jacob et al., 2005). Messenger RNA transcripts of CYP2A7 have been
found in human livers; however, the protein lacks heme binding ability and is enzymatically
inactive (Yamano et al., 1990; Ding et al., 1995). CYP2A13 is primarily expressed in the
respiratory tract (nasal epithelium, trachea, and lungs) (Su et al., 2000; Zhu et al., 2006) with
very low levels detected in the liver (Koskela, Hakkola et al., 1999). CYP2A13 can also
metabolize nicotine and cotinine efficiently in vitro; the Km of CYP2A13 towards nicotine is
20.2 μM compared to 26 μM for CYP2A6, and the Km of CYP2A13 for cotinine is 45.2 μM
compared to 265 μM for CYP2A6 (Nakajima, Yamamoto et al., 1996; Bao et al., 2005).
However, nicotine undergoes primarily hepatic metabolism and metabolism by CYP2A13 in
the lungs is not likely to substantially reduce its systemic levels. This is supported by the
observation that individuals completely lacking the CYP2A6 enzyme (e.g. those with
CYP2A6*4/*4 genotype) have much higher nicotine plasma levels and AUC values
compared to individuals with fully active CYP2A6 (Nakajima, Yamagishi et al., 2000; Xu,
Rao et al., 2002; Nakajima and Yokoi T, 2005; Mwenifumbo, Al Koudsi N et al., 2008)
3.1.4 CYP2A6 substrates
In addition to nicotine and cotinine, CYP2A6 contributes to the metabolism of a limited
number of compounds including several therapeutic agents and toxins (Table 3.1). CYP2A6
49
Table 3.1: List of CYP2A6 substrates. Modified from (Raunio et al., 2001). Substrate Source/usage Reaction Nicotine Present in tobacco plants, nicotine replacement
therapy Hydroxylation
Cotinine Nicotine metabolite Hydroxylation Coumarin Used to treat lymphoedema in some European
countries Hydroxylation
Tegafur Anti-neoplastic prodrug that is activated to 5-fluorouracil by CYP2A6
Hydroxylation
Letrozole Anti-neoplastic drug (aromatase inhibitor for breast cancer treatment) that is inactivated by CYP2A6
Oxidation
Methyoxyflurane Anesthetic Dehalogenation Halothane Anesthetic Reduction SM-12502 Novel platelet-activating factor receptor antagonist Oxidation Losigamone Anti-convulsant Oxidation Valproic acid Anti-convulsant, mood stabilizer Oxidation NNK Tobacco-specific nitrosamine Hydroxylation NNN Tobacco-specific nitrosamine Hydroxylation NDEA Carcinogen Mutagenic MTBE Carcinogen Demethylation MOCA Toxin/suspected carcinogen Oxidation Quinoline Toxin Oxidation Inhibitors Methoxalen Selegiline Tranylcypromine Isoflavones Grapefruit juice Starfruit juice Inducers Phenobarbital Oral contraceptives containing estrogen Broccoli Rifampin Dexamethasone
Abbreviations: (+)-cis-3,5-dimethyl-2-(3-pyridyl)thiazolidin-4-one hydrochloride (SM-
12502); 4-(methylnitrosamino)-1-(3-pyridyl)-butanone (NNK) and N-nitrosonornicotine
(NNN); N- nitrosodiethylamine (NDEA); methyl tert-butyl ether (MTBE); 4,4k-
methylenebis(2-chloroaniline) (MOCA). CYP2A6 contributes a large role in the metabolism
of nicotine, cotinine, coumarin, tegafur, letrozole and SM-12502. The other compounds
listed are likely partially metabolized by CYP2A6 or their metabolic pathways have not been
thoroughly studied to date.
50
has a relatively compact, narrow and hydrophobic active site; as such, the substrates for this
enzyme also tend to be small and planar (Yano et al., 2005). There are relatively few
clinically used pharmaceutical agents that are metabolized extensively and/or selectively by
CYP2A6 in comparison to CYP2D6, CYP3A4 or CYP2C9/18/19, which together are
responsible for the metabolism of 80-90% of all clinically used drugs (Wrighton et al., 1996;
Anzenbacher and Anzenbacherová, 2001; Zhou et al., 2009). Crystallography and in silico
simulations have suggested that CYP2A6 is rather rigid in terms of flexibility and
malleability that can limit substrate entry, accommodation into the active site, and product
release (Skopaliì�K et al., 2008). This is in contrast to CYP3A4 which has a greater degree
of flexibility and malleability and accordingly, a much broader range of substrates
(Skopaliì�K, Anzenbacher et al., 2008).
3.1.4.1 Tobacco-specific nitrosamines
A number of tobacco-alkaloid derived nitrosamines have been detected in both unburned
tobacco and tobacco smoke resulting from combustion. Of these, N-nitrosonornicotine
(NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-butanone (NNK) and its major metabolite 4-
(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) are among the most prevalent and
carcinogenic compounds in tobacco smoke (Hecht, 1998). Numerous studies have shown
these compounds can induce cancers in a variety of species (Hecht, 1998). In particular,
NNK has been shown to be a potent and selective inducer of lung adenocarcinomas and
NNN can induce esophageal and nasal tumors in rodents (Hoffmann et al., 1984; Anderson et
al., 1989; Padma et al., 1989; Rivenson et al., 1989; Furukawa et al., 1994; Hecht, 1998).
These tobacco-specific nitrosamines are procarcinogens and require metabolic activation to
form reactive intermediates. NNN can be metabolically activated to reactive intermediates
capable of forming DNA adducts via 2’- and 5’-α-hydroxylation (Chen et al., 1978; Hecht et
51
al., 1986; Hecht, 1998), while NNK and NNAL are metabolized to reactive intermediates via
α-hydroxylation (Hecht et al., 1980; Guo et al., 1992; Hecht, 1998). A number of CYP
enzymes have been implicated in these reactions; cDNA-expressed CYP2A6 and CYP2A13
catalyzed the 5’-hydroxylation of NNN with similar catalytic efficiency in vitro (Wong et al.,
2004). CYP2B6 and CYP2A6 were found to have the highest affinity towards NNK in
human liver microsomes (Patten et al., 1996; Dicke et al., 2005). However, the catalytic
efficiency of cDNA-expressed CYP2A13 towards NNK is approximately 30 to 50-fold
greater than that for CYP2A6 (Su, Bao et al., 2000; He et al., 2004), and the presence of this
enzyme in the respiratory system suggests it may contribute significantly to local
bioactivation and carcinogenesis. In vitro studies using lung microsomes have shown that
CYP2A13 levels but not CYP2A6 were correlated with rates of NNK activation in samples
that have high CYP2A13 expression (Zhang et al., 2007). Individuals with higher pulmonary
expression of CYP2A13 may be at an increased risk of developing tobacco-related cancers,
although it should be noted that CYP2A6 protein was detected in 90% of the samples
whereas CYP2A13 was detected in only 12% of the samples, suggesting CYP2A6 may have
a greater contribution in most individuals (Zhang, D'agostino et al., 2007).
3.2 Genetic variability in CYP2A6 activity
3.2.1 Inter-individual and inter-ethnic variability
Large inter-individual variability in CYP2A6 activity exists; human liver microsomes have
more than 50-fold variation in mRNA, protein expression and activity (Pelkonen, Rautio et
al., 2000). Although factors such as gender, and presence of inducers or inhibitors, may
contribute to the variation in enzyme activity, the observed variability has mainly been
attributed to genetic polymorphisms in CYP2A6. Pharmacokinetic studies in twins have
demonstrated a substantial genetic contribution to the variability in the rates of nicotine
52
clearance, with the heritability of total rates of nicotine clearance and clearance of nicotine
via the cotinine pathway estimated at approximately 60% (Swan et al., 2005). Similar
studies have shown that approximately 67% of the variability in the plasma ratio of 3HC to
cotinine (3HC/COT), a phenotypic indicator of CYP2A6 activity, can be attributed to
additive genetic influence (Swan et al., 2009).
CYP2A6 expression and activity vary widely across ethnic groups (Malaiyandi, Sellers et al.,
2005; Mwenifumbo and Tyndale, 2007). For example, liver microsomes from Japanese
donors have lower levels of CYP2A6 protein and activity compared to Caucasians (Shimada
et al., 1996). Furthermore, the rate of nicotine clearance was found to be 18% slower for
Asian-Americans (Benowitz et al., 2002) and 13% slower for African-Americans (Benowitz,
Perez-Stable et al., 1999) compared with Caucasians. In these studies, the rate of cotinine
clearance was also found to be 31% slower for Asian-Americans (Benowitz, Perez-Stable et
al., 2002) and 32% slower for African-Americans (Benowitz, Perez-Stable et al., 1999).
3.2.2 Currently identified CYP2A6 variants and their functional consequences
The CYP2A6 gene consists of nine exons and eight introns, encoding 494 amino acids.
CYP2A6 is highly polymorphic, and much progress has been made in recent years in the
identification of new CYP2A6 genetic variants. There are currently 37 numbered alleles
known, compared to the 22 numbered alleles that were recognized back in 2005
(http://www.cypalleles.ki.se/). These genetic variations include single nucleotide
polymorphisms (SNPs), nucleotide insertions and deletions, gene conversions, gene deletions
and gene duplications. Some alleles encode enzymes that have abolished function (e.g.
CYP2A6*2, CYP2A6*4), others reduce activity (e.g. CYP2A6*9, CYP2A6*12) and the gene
duplication alleles (CYP2A6*1x2A,*1x2B) increase activity (Rao et al., 2000; Benowitz et al.,
53
2006). Numerous in vitro and in vivo studies have demonstrated that CYP2A6 genetic
variants are associated with reduced rates of nicotine clearance (Benowitz, Swan et al., 2006)
and lower rates of CYP2A6 activity using phenotypic indicators (Johnstone et al., 2006;
Malaiyandi et al., 2006; Malaiyandi et al., 2006; Nakajima, Fukami et al., 2006;
Peamkrasatam S et al., 2006; Mwenifumbo Jc et al., 2008). A description of these variants
and their effects on enzyme function can be found in Table 3.2, while a summary of their
frequencies in various racial/ethnic populations is listed in Table 3.3. The frequency of these
alleles varies greatly between racial/ethnic groups, reflecting the large degree of inter-ethnic
variability in the rates of nicotine metabolism (Benowitz, Perez-Stable et al., 1999; Benowitz,
Perez-Stable et al., 2002; Nakajima, Fukami et al., 2006). The percentage of individuals with
slow CYP2A6 metabolism (less than 50% activity), as predicted by frequencies of alleles that
encode enzymes with reduced- or loss-of-function, ranges from approximately 10% in
Caucasians to approximately 60% in Japanese in accordance with the slower rates of nicotine
metabolism observed in Asians compared to Caucasians (Mwenifumbo et al., 2009).
3.3 Other influences of CYP2A6 activity
3.3.1 Gender/hormonal effects
In a pharmacokinetic study where participants were given intravenous infusions of isotope-
labeled nicotine and cotinine, nicotine clearance rates were 20% higher in females compared
to males (Benowitz et al., 2006). This difference was enhanced in females taking estrogen-
containing oral contraceptives, who had 44% higher rates of nicotine clearance compared to
males, whereas females not taking these drugs had only 13% higher rates of clearance
compared to males (Benowitz, Lessov-Schlaggar Cn et al., 2006).
54
Alle
le
Gen
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Lo
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Des
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Act
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* C
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R
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1-17
58
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C
YP2
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In v
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YP2A
6
Unk
now
n
CYP
2A6*
1F
5717
C>T
Ex
on 8
--
- Sy
nony
mou
s SN
P (P
408P
)
Unk
now
n
CYP
2A6*
1G
5717
C>T
,582
5A>G
Ex
on 8
, in
tron
8 --
- Sy
nony
mou
s SN
P (P
408P
) and
intro
nic
SNP
Unk
now
n
CYP
2A6*
1H
-745
A>G
5’
UTR
--
- SN
P lo
cate
d in
a p
utat
ive
CYP
2A6
prom
oter
regi
on a
nd is
thou
ght t
o di
srup
t a C
CA
AT
box.
In v
itro,
the
trans
crip
tion
of th
e hu
man
CYP
2A6
prom
oter
with
the
-745
A>G
var
iant
is si
gnifi
cant
ly re
duce
d by
22%
Red
uced
?
CYP
2A6*
1J
-101
3A>G
, -74
5A>G
5’
UTR
--
-
Unk
now
n C
YP2A
6*1K
H
aplo
type
of
vario
us
syno
nym
ous c
hang
es
---
---
-130
1A>C
, -12
89G
>A, -
1199
_-11
98in
s316
bpA
lu, -
686A
>G; 5
1G;
431C
>T; 1
620T
>C; 1
779G
>A; 2
483G
>A; 2
994T
>C; 3
378C
>T; 3
904G
>A
4074
delA
; 566
8A; 6
354T
>C; 7
160A
>G
Unk
now
n
CYP
2A6*
1L
Gen
e co
nver
sion
with
C
YP2A
7 at
707
3-70
82
---
---
U
nkno
wn
CYP
2A6*
1x2A
G
ene
dupl
icat
ion
---
---
Bre
akpo
int o
ccur
s at i
ntro
n 8
– 3’
UTR
Incr
ease
d
CYP
2A6*
1x2B
G
ene
dupl
icat
ion
---
---
Bre
akpo
int o
ccur
s at 5
.2 –
5.6
kb
dow
nstre
am fr
om st
op c
odon
Incr
ease
d
CYP
2A6*
2 17
99T>
A
Exon
3
L160
H
In v
itro,
the
enzy
me
fails
to in
corp
orat
e he
me
and
is in
activ
e. I
n vi
vo, t
his
alle
le a
ppea
rs in
activ
e.
Inac
tive
CYP
2A6*
4A-H
G
ene
dele
tion
---
---
Hyb
rid a
llele
thou
ght t
o oc
cur b
y un
equa
l hom
olog
ous c
ross
over
. A
nu
mbe
r of c
ross
over
regi
ons h
as b
een
iden
tifie
d w
ithin
intro
n 8
to 5
.2 –
5.6
kb
dow
nstre
am o
f the
stop
cod
on in
the
3’U
TR
Inac
tive
CYP
2A6*
5 65
82G
>T
Exon
9
G47
9V
In v
itro,
exp
ress
ed e
nzym
e is
uns
tabl
e; o
nly
trace
am
ount
of e
nzym
e an
d
coum
arin
7-h
ydro
xyla
tion
activ
ity w
ere
dete
cted
. In
viv
o, li
mite
d da
ta
sugg
ests
inac
tive
alle
le
Inac
tive
Tabl
e 3.
2: D
escr
iptio
n of
CYP
2A6
alle
les a
nd th
eir p
redi
cted
func
tiona
l im
pact
55
Alle
le
Gen
e ch
ange
Lo
catio
n A
min
o ac
id
Des
crip
tion
Act
ivity
* C
YP2A
6*6
1703
G>A
Ex
on 3
R
128Q
A
rg12
8 is
hig
hly
cons
erve
d am
ong
CY
P450
s and
is th
ough
t to
be im
porta
nt
for p
rope
r hem
e bi
ndin
g an
d ho
lopr
otei
n co
nfor
mat
ion.
In v
itro,
the
expr
esse
d en
zym
e ha
s gre
atly
redu
ced
coum
arin
7-h
ydro
xyla
tion
activ
ity.
In v
ivo,
lim
ited
data
sugg
ests
inac
tive
alle
le
Red
uced
CYP
2A6*
7 65
58T>
C
Exon
9
I471
T W
hen
expr
esse
d in
E.c
oli a
nd su
bjec
ted
to h
eat t
reat
men
t (37˚C
), th
e en
zym
e en
code
d by
this
var
iant
was
less
stab
le th
an it
s wild
type
co
unte
rpar
t. A
lso,
the
varia
nt la
cked
nic
otin
e C
-oxi
dase
act
ivity
whi
le
mai
ntai
ning
~60
% o
f cou
mar
in 7
-hyd
roxy
lase
act
ivity
. In
vivo
, ind
ivid
uals
w
ith th
is a
llele
hav
e de
crea
sed
nico
tine
and
norm
al c
oum
arin
met
abol
ism
Inac
tive
CYP
2A6*
8 66
00G
>T
Exon
9
R48
5L
In v
itro,
the
expr
esse
d en
zym
e en
code
d ha
s nor
mal
nic
otin
e C
-oxi
datio
n ac
tivity
. In
vivo
, lim
ited
data
sugg
ests
no
effe
ct o
n ni
cotin
e m
etab
olis
m
Act
ive
CYP
2A6*
9A, B
-4
8T>G
5’
TATA
bo
x --
- In
vitr
o, th
e SN
P re
sulte
d in
a 5
0% d
ecre
ase
in tr
ansc
riptio
n ac
tivity
, and
lo
wer
mR
NA
, pro
tein
and
act
ivity
leve
ls w
ere
obse
rved
in h
uman
live
r m
icro
som
es.
In v
ivo,
this
alle
le re
duce
d ni
cotin
e m
etab
olis
m
Red
uced
CYP
2A6*
10
6558
T>C
, 660
0G>T
Ex
on 9
I4
71T,
R
485L
C
YP2A
6*10
con
tain
s var
iatio
ns in
am
ino
acid
resi
dues
lyin
g w
ithin
or
clos
e to
subs
trate
reco
gniti
on si
te 6
(SR
S-6)
, a h
ighl
y co
nser
ved
regi
on.
In
vitr
o st
udie
s hav
e no
t bee
n do
ne. I
n vi
vo, i
ndiv
idua
ls w
ith th
is a
llele
hav
e im
paire
d ni
cotin
e an
d co
umar
in m
etab
olis
m
Inac
tive
CYP
2A6*
11
3391
T>C
Ex
on 5
S2
24P
In v
itro
the
enzy
me
resu
lted
in ~
50%
dec
reas
e in
Vm
ax w
hen
usin
g te
gafu
r as
a su
bstra
te.
In v
ivo,
lim
ited
data
sugg
ests
redu
ced
activ
ity
Red
uced
CYP
2A6*
12A-
C
Exon
1-2
CY
P2A
7,
Exon
3-9
CY
P2A
6 --
- 10
am
ino
acid
su
bstit
utio
n
This
var
iant
resu
lt fr
om a
n un
equa
l cro
ssov
er e
vent
bet
wee
n C
YP2
A6
and
CYP
2A7
in in
tron
2. I
n vi
tro,
the
expr
esse
d pr
otei
n le
vel a
nd c
oum
arin
7-
hydr
oxyl
atio
n ac
tivity
was
dec
reas
ed 4
0-50
%. I
n vi
vo, t
his a
llele
app
ears
to
redu
ce fu
nctio
n
Red
uced
CYP
2A6*
13
13G
>A
Exon
1
G5R
In
viv
o, li
mite
d da
ta su
gges
ts re
duce
d fu
nctio
n
Red
uced
?
CYP
2A6*
14
86G
>A
Exon
1
S29N
In
viv
o, li
mite
d da
ta su
gges
ts n
o ch
ange
in fu
nctio
n
Act
ive?
CYP
2A6*
15
2134
A>G
Ex
on 4
K
194E
In
viv
o, li
mite
d da
ta su
gges
ts re
duce
d fu
nctio
n to
war
ds n
icot
ine.
In v
itro,
th
is a
llele
app
ears
to b
e fu
lly fu
nctio
nal t
owar
ds c
oum
arin
.
Red
uced
?
Tabl
e 3.
2: D
escr
iptio
n of
CYP
2A6
alle
les a
nd th
eir p
redi
cted
func
tiona
l im
pact
(con
tinue
d)
56
Alle
le
Gen
e ch
ange
Lo
catio
n A
min
o ac
id
Des
crip
tion
Act
ivity
* C
YP2A
6*16
21
61C
>A
Exon
4
R20
3S
In v
itro,
exp
ress
ed e
nzym
e di
d no
t alte
r act
ivity
tow
ards
nic
otin
e or
co
umar
in.
In v
ivo,
lim
ited
data
sugg
ests
no
chan
ge in
func
tion.
Act
ive?
CYP
2A6*
17
5065
G>A
Ex
on 7
V
365M
In
vitr
o, th
e ex
pres
sed
enzy
me
had
redu
ced
activ
ity to
war
ds n
icot
ine
and
coum
arin
. In
viv
o, th
is a
llele
app
ears
to b
e in
activ
e to
war
ds n
icot
ine
Inac
tive
CYP
2A6*
18A-
C
5668
A>T
Ex
on 8
Y
392F
In
vitr
o, th
e ex
pres
sed
enzy
me
had
norm
al a
ctiv
ity to
war
ds n
icot
ine
but
redu
ced
activ
ity to
war
ds c
oum
arin
. In
viv
o, li
mite
d da
ta su
gges
ts n
orm
al
activ
ity to
war
ds n
icot
ine
Act
ive?
CYP
2A6*
19
5668
A>T
, 655
8T>C
Ex
on 8
, 9
Y39
2F,
I471
T In
vitr
o, th
e ex
pres
sed
enzy
me
had
redu
ced
activ
ity to
war
ds n
icot
ine
and
coum
arin
. In
viv
o, li
mite
d da
ta su
gges
ts th
is a
llele
hav
e re
duce
d ac
tivity
to
war
ds n
icot
ine
Red
uced
?
CYP
2A6*
20
2141
-214
2 A
A
dele
tion,
pre
mat
ure
stop
cod
on
Exon
4
Trun
cate
d pr
otei
n In
vitr
o, n
o ac
tivity
was
det
ecte
d by
the
expr
esse
d en
zym
e. In
viv
o, th
is
alle
le a
ppea
rs to
be
inac
tive
Inac
tive
CYP
2A6*
21
6573
A>G
Ex
on 9
K
476R
In
viv
o an
d in
vitr
o, th
is a
llele
app
ears
to b
e fu
lly fu
nctio
nal
A
ctiv
e
CYP
2A6*
22
1794
C>G
, 179
8C>A
Ex
on 3
D
158E
, L1
60I
In v
itro,
this
alle
le a
ppea
rs to
hav
e re
duce
d fu
nctio
n to
war
ds c
oum
arin
R
educ
ed?
CYP
2A6*
23
2161
C>T
Ex
on 4
R
203C
In
vitr
o, th
is a
llele
app
ears
to h
ave
redu
ced
activ
ity to
war
ds n
icot
ine
and
coum
arin
. In
viv
o, li
mite
d da
ta su
gges
ts th
e al
lele
has
redu
ced
activ
ity o
r is
inac
tive
Red
uced
? In
activ
e?
CYP
2A6*
24
594G
>C, 6
458A
>T
Exon
2, 9
V
110L
, N
438Y
In
vitr
o, th
e ex
pres
sed
enzy
me
appe
ars t
o be
uns
tabl
e. In
viv
o, li
mite
d da
ta
sugg
ests
the
alle
le h
as re
duce
d ac
tivity
or i
s ina
ctiv
e
Red
uced
? In
activ
e?
CYP
2A6*
25
1672
T>C
Ex
on 3
F1
18L
In v
itro,
the
expr
esse
d en
zym
e ap
pear
s to
be fu
lly fu
nctio
nal.
In v
ivo,
lim
ited
data
sugg
ests
the
alle
le h
as re
duce
d ac
tivity
or i
s ina
ctiv
e
Red
uced
? In
activ
e?
CYP
2A6*
26
1672
T>C
, 170
3G>T
17
11T>
G
Exon
3
F118
L,
R12
8L,
S131
A
In v
itro,
the
expr
esse
d en
zym
e ap
pear
s to
be in
activ
e. In
viv
o, li
mite
d da
ta
sugg
ests
the
alle
le h
as re
duce
d ac
tivity
or i
s ina
ctiv
e R
educ
ed?
Inac
tive?
CYP
2A6*
27
1672
T>C
21
62 –
216
3 G
C>A
fr
ames
hift
Exon
3
Exon
4
F118
L,
R20
3-fr
ames
hift
In v
itro,
the
expr
esse
d en
zym
e ap
pear
s to
be in
activ
e. In
viv
o, li
mite
d da
ta
sugg
ests
the
alle
le h
as re
duce
d ac
tivity
or i
s ina
ctiv
e R
educ
ed?
Inac
tive?
CYP
2A6*
28
5745
A>G
, 575
0G>C
Ex
on 8
N
418D
, E4
19D
In
vitr
o, th
e ex
pres
sed
enzy
me
appe
ars t
o b
e fu
lly fu
nctio
nal .
In v
ivo,
lim
ited
data
sugg
ests
the
alle
le h
as re
duce
d ac
tivity
or i
s ina
ctiv
e R
educ
ed?
Inac
tive?
Tabl
e 3.
2: D
escr
iptio
n of
CYP
2A6
alle
les a
nd th
eir p
redi
cted
func
tiona
l im
pact
(con
tinue
d)
57
Alle
le
Gen
e ch
ange
Lo
catio
n A
min
o ac
id
Des
crip
tion
Act
ivity
* C
YP2A
6*29
N
ot re
leas
ed y
et
CYP
2A6*
30
Not
rele
ased
yet
C
YP2A
6*31
16
A>C
Ex
on 1
M
6L
This
alle
le h
as n
ot b
een
char
acte
rized
in v
itro
or in
viv
o U
nkno
wn
CYP
2A6*
32
Not
rele
ased
yet
C
YP2A
6*33
N
ot re
leas
ed y
et
CYP
2A6*
34
Exon
1 –
4 o
f C
YP2
A7,
Exo
n 5
– 9
of C
YP2
A6
---
21 a
min
o ac
id c
hang
es
This
alle
le h
as n
ot b
een
char
acte
rized
in v
itro
or in
viv
o U
nkno
wn
CYP
2A6*
35
6458
A>T
Ex
on 9
N
438Y
In
vitr
o, th
e ex
pres
sed
enzy
me
appe
ars t
o be
uns
tabl
e. In
viv
o, li
mite
d da
ta
sugg
ests
the
alle
le h
as re
duce
d ac
tivity
or i
s ina
ctiv
e R
educ
ed?
Inac
tive?
Tabl
e 3.
2: D
escr
iptio
n of
CYP
2A6
alle
les a
nd th
eir p
redi
cted
func
tiona
l im
pact
(con
tinue
d)
All
nucl
eotid
e se
quen
ce n
umbe
ring
are
base
d on
+1
with
ref
eren
ce t
o th
e A
TG s
tart
site
on
the
refe
renc
e ge
nom
ic s
eque
nce
NG
_000
008.
7. *
Act
ivity
tow
ards
nic
otin
e C
-oxi
datio
n. D
ata
mod
ified
from
(Mw
enifu
mbo
et a
l., 2
007;
Ben
owitz
et a
l., 2
009;
Ho
et a
l.,
2009
; Tio
ng K
h et
al.,
201
0).
58
CYP
2A6
alle
le
non-
His
pani
c w
hite
s A
fric
an-A
mer
ican
s Ja
pane
se
Chi
nese
K
orea
ns
CYP
2A6*
1B1-
17
28.8
– 3
5.0
11.9
– 1
6.4
48.4
– 5
4.6
43.2
– 5
1.3
57.0
C
YP2A
6*2
1.1
– 5.
3 0.
4 –
0.9
0 0
0 C
YP2A
6*4A
-H
0 –
4.2
0.9
– 2.
7 17
.0 –
24.
2 4.
9 –
15.1
10
.8
CYP
2A6*
5 0
– 0.
3 0
0 0.
5 –
1.2
0.5
CYP
2A6*
6 0
0 0
– 0.
4 0
0 C
YP2A
6*7
0 0
9.8
– 12
.5
5.7
– 9.
8 9.
4 –
9.8
CYP
2A6*
8 0
0 0
– 1.
1 0
– 1.
5 0
– 1.
2 C
YP2A
6*9A
, B
5.2
– 8.
0 7.
2 –
9.6
19.0
– 2
0.3
15.6
– 1
5.7
19.6
– 2
2.3
CYP
2A6*
10
0 0
2.2
– 3.
2 1.
7 –
4.3
1.0
– 4.
1 C
YP2A
6*11
0
0 0.
5 0
0.7
CYP
2A6*
12A-
C
0 –
3.0
0 –
0.4
0 –
0.8
0 0
CYP
2A6*
13
0 0
1.1
– 1.
2 0
0.2
CYP
2A6*
14
3.5
– 5.
7 1.
4 –
2.5
0
0 0
CYP
2A6*
15
0 0
– 1.
1 1.
0 –
2.2
1.4
1.2
– 7.
4 C
YP2A
6*16
0.
3 1.
2 –
1.7
0 –
1.1
1.3
0 –
5.3
CYP
2A6*
17
0 7.
1 –
10.5
0
0 0
CYP
2A6*
18A-
C
1.1
- 2.1
0
0
0 0.
5 C
YP2A
6*19
0
0 0
0 1
CYP
2A6*
20
0 1.
1 –
1.7
0
0 C
YP2A
6*21
0
– 2.
3 0
- 0.6
0
3.4
0 C
YP2A
6*22
0.
3 0
0 0
0 C
YP2A
6*23
0
1.1
– 2.
0 0
0 0
CYP
2A6*
24
0 0.
7 –
2.3
0 0
0 C
YP2A
6*25
0
0.5
– 1.
2 0
0 0
CYP
2A6*
26
0 0.
7 0
0 0
CYP
2A6*
27
0 0.
2 –
0.7
0 0
C
YP2A
6*28
0
0.9
– 2.
4 0
0
CYP
2A6*
31
0 1.
3 0
0 0
CYP
2A6*
34
0 0
Not
e: A
llele
was
dis
cove
red
in o
ne A
sian
indi
vidu
al th
roug
h se
quen
cing
C
YP2A
6*35
0
2.5
– 2.
9 0.
8 0.
5
Tabl
e 3.
3: C
YP2A
6 al
lele
freq
uenc
ies i
n va
rious
raci
al/e
thni
c po
pula
tions
D
ata
mod
ified
from
(Mw
enifu
mbo
and
Tyn
dale
, 200
7).
59
Similarly, cotinine clearance rates were 32% higher in all females, 61% higher in females
taking estrogen-containing contraceptives and 24% higher in females not taking these drugs
compared to males (Benowitz, Lessov-Schlaggar Cn et al., 2006). Nicotine and cotinine
half-lives were also shorter in females, with greater effects in those taking estrogen-
containing oral contraceptives (Benowitz, Lessov-Schlaggar Cn et al., 2006). A number of
other studies have found higher 3HC/COT in females, indicating enhanced CYP2A6 enzyme
function (Benowitz, Lessov-Schlaggar Cn et al., 2006; Johnstone, Benowitz et al., 2006;
Kandel et al., 2007; Mwenifumbo et al., 2007). A 1.9-fold higher level of CYP2A6 mRNA,
2.0-fold higher level of CYP2A6 protein and 1.5-fold higher rates of nicotine C-oxidation
activity were found in human liver microsomes of females compared to males (Al Koudsi et
al., 2010).
Neither nicotine nor cotinine pharmacokinetics appear to differ by phases of the menstrual
cycle (i.e. follicular vs. luteal) in healthy non-smoking females (Hukkanen et al., 2005).
However, pregnancy has a substantial effect on rates of nicotine and cotinine clearance,
being increased by 60% and 140%, respectively, compared to post-partum (Dempsey et al.,
2002). Together, these results suggest that sex hormones (most likely estrogen) substantially
increase CYP2A6 activity and rates of nicotine and cotinine clearance, with fastest activity
observed among those taking oral contraceptives or during pregnancy where levels of
hormones are highest. Mechanistically, the CYP2A6 promoter region contains a putative
estrogen response element at -2.4 kb and it has been demonstrated in vitro that estradiol can
induce CYP2A6 in an estrogen receptor-α dependent manner (Higashi et al., 2007).
3.3.2 Age
60
In general, the capacity for hepatic drug metabolism declines among the elderly, mostly as a
result of diminished blood flow and liver volume (Schmucker et al., 1990; Wynne, 2005).
This is particularly important for high extraction drugs, such as nicotine, where the liver has
great potential capacity to metabolize the compound and clearance rates are dependent on the
rate of hepatic blood flow. Indeed, slower rates of nicotine clearance have been found
among the elderly (65 to 76 years of age), with total clearance reduced by 23% and renal
clearance reduced by 49% compared to young adults (22 to 43 years of age) (Molander et al.,
2001). No age-related decreases in CYP2A6 protein or activity levels have been found in
human liver microsomes collected from individuals aged 2 to 64 (Parkinson et al., 2004; Al
Koudsi, Hoffmann et al.). In vivo, there is also no age-related differences in the 3HC/COT
ratio or nicotine pharmacokinetics among individuals of Black-African descent aged 22 to 59
years old (Mwenifumbo, Sellers et al., 2007). However, one study of Caucasians aged 25 to
65 reported the 3HC/COT ratio was significantly associated with age, with the ratio
increasing by 2% for every 5-year increase in age (Johnstone, Benowitz et al., 2006).
3.3.3 CYP2A6 inhibitors and inducers
3.3.3.1 Pharmaceutical agents
The prototypical CYP inducers such as rifampicin, dexamethasone, and phenobarbital can
induce CYP2A6 in human primary hepatocytes, although there is wide variability in response
(Hukkanen, Jacob et al., 2005). Rifampicin is a well-known activator of the nuclear
receptors pregnane X receptor (PXR), and phenobarbital is an activator of the constitutive
androstane receptor (CAR). These transcription factors recruit other coactivators to enhancer
regions of their target genes, mediating gene transcription of numerous xenobiotic-
metabolizing enzymes. PXR and CAR can dimerize with retinoid X receptor-α (RXRα) to
potentially bind at DR4-like response elements found at -6.6 kb, -5.4 kb and -4.6 kb of
61
CYP2A6 (Itoh et al., 2006). PXR was shown to interact with peroxisome proliferator-
activated receptor-γ coactivator 1α (PGC-1α) at the DR4-like response elements at -5.4 kb
and -4.6 kb of CYP2A6 to increase transcription (Itoh, Nakajima et al., 2006). The induction
of CYP2A6 by dexamethasone occurs through the glucocorticoid receptor interacting with
hepatic nuclear factor 4-α (HNF4-α) at the HNF4-response element located within -95 to +12
kb of the CYP2A6 promoter region (Onica et al., 2008). Another study found response
elements for HNF-4α, CCAAT-box/enhancer binding protein α and β (C/EBPα, C/EBPβ),
and octamer transcription factor-1 (Oct-1) within -112 to -61 kb of the promoter region that
are important in regulating the basal expression of CYP2A6 (Pitarque et al., 2005).
A variety of compounds can inhibit CYP2A6 activity in vitro including methoxsalen
(Maenpaa, Sigusch et al., 1993), pilocarpine (Kimonen et al., 1995), clotrimazole (Draper et
al., 1997), miconazole (Draper, Madan et al., 1997), tranylcypromine (Zhang et al., 2001)
and tryptamine (Zhang, Kilicarslan et al., 2001). Only methoxsalen and tranylcypromine
have been shown to inhibit nicotine and coumarin metabolism in vivo (Sellers et al., 2003),
although these compounds are not selective and can also inhibit other CYPs (Hukkanen,
Jacob et al., 2005).
3.3.3.2 Menthol
Menthol, and several related compounds, can inhibit nicotine C-oxidation and coumarin 7-
hydroxylation in vitro using human liver microsomes, albeit modestly (Macdougall et al.,
2003). A cross-over study of African-American and Caucasian smokers showed that
smoking menthol cigarettes reduces the total and nonrenal nicotine clearance by
approximately 10% compared to smoking non-menthol cigarettes (Benowitz et al., 2004).
This likely occurred by a reduction in the oxidative metabolism of nicotine via the cotinine
62
pathway, although nicotine glucuronidation may also be affected (Benowitz, Herrera et al.,
2004). Studies in human liver microsomes suggest menthol can inhibit the glucuronidation
of NNAL, and menthol cigarette smokers had less NNAL excreted as its glucuronide
conjugate via this detoxification pathway (Muscat et al., 2009).
3.3.3.3 Smoking/nicotine
Cigarette smoke increases the metabolism for a number of substrates; it contains
polyaromatic hydrocarbons that are known to be strong inducers of CYP1A1 and CYP1A2,
with possible effects on CYP2E1 and glucuronidation pathways (Zevin et al., 1999; Kroon,
2007). However, cigarette smokers were found to have slower rates of nicotine and cotinine
clearance (Benowitz et al., 1993), suggesting the development of functional tolerance rather
than metabolic tolerance contributes to the escalating amount of tobacco consumption that
occurs during smoking initiation. Cross-over studies have demonstrated that nicotine
clearance was increased by 14% and 36% following four and seven days of smoking
abstinence, respectively (Lee et al., 1987; Benowitz et al., 2000). In African-Americans
recruited for a nicotine pharmacokinetic study, smokers had slower rates of nicotine
metabolism as represented by approximately 25% higher estimated nicotine AUC compared
to non-smokers (Mwenifumbo, Sellers et al., 2007). Similarly, smokers have slower rates of
coumarin 7-hydroxylation in vivo compared to nonsmokers (Iscan et al., 1994; Poland et al.,
2000), suggesting the inhibitory effect of tobacco smoke is specific towards CYP2A6
activity.
Studies have attempted to identify the compound(s) present in tobacco smoke with inhibitory
effects on CYP2A6. In non-human primates, nicotine treatment for 21 days resulted in
downregulation of CYP2A6 mRNA and protein in the liver, as well as reduced nicotine C-
63
oxidation activity in liver microsomes (Schoedel et al., 2003). β-Nicotyrine, a minor alkaloid
found in tobacco, was also found to be a mechanism-based inhibitor of CYP2A6 in vitro
(Denton et al., 2004). In contrast, pretreatment with cotinine for four days to achieve levels
seen in very heavy smokers (approximately 900 ng/ml) did not alter the rates of nicotine
clearance in a crossover study of healthy non-smokers, suggesting cotinine is not inhibiting
or decreasing the expression of CYP2A6 (Zevin et al., 1997). Similarly, inhalation of carbon
monoxide to achieve carboxyhemoglobin levels similar to those derived from smoking did
not alter the pharmacokinetic dispositions of nicotine or cotinine (Benowitz and Jacob,
2000).
3.3.3.4 Dietary
A number of dietary compounds alter CYP activity. Grapefruit juice has a number of
clinically relevant drug interactions as it is a strong inhibitor of CYP3A4 and can also inhibit
CYP1A1/2 and CYP2C (Nowack, 2008). In vivo, grapefruit juice (300 to 1000 ml) inhibited
the metabolism of coumarin and delayed the excretion of 7-hydroxycoumarin in the urine
(Merkel et al., 1994; Runkel et al., 1997). The exact compound(s) responsible for CYP2A6
inhibition is not yet known, although bergamottin has been shown to be a mechanism-based
inhibitor of CYP3A4 (Nowack, 2008).
Other plant products can also alter CYP2A6 activity; consumption of wheatgrass juice by
vegans has been associated with reduced coumarin metabolism (Rauma et al., 1996).
Isoflavones, which are found mainly in soy products, can inhibit CYP1A1, CYP1B1,
CYP2E1 and CYP3A4 (Helsby et al., 1998; Roberts et al., 2004; Nowack, 2008). The
isoflavones daidzein, genistein, and glycitein inhibited nicotine C-oxidation in vitro and soy
supplementation was associated with reduced ratio of cotinine to nicotine (COT/NIC), a
64
phenotype indicator of CYP2A6 activity (Nakajima et al., 2006). Starfruit juice inhibited the
activity of a number of CYP enzymes in human liver microsomes with the greatest effect on
CYP2A6 (Zhang et al., 2007). CYP2A6 activity was shown to be induced following
consumption of a standard diet of broccoli (500 g daily) for six days (Hakooz et al., 2007).
3.4 Other sources of variability in nicotine clearance rates
Hepatic blood flow can be altered by a number of physiological events such as meals,
posture, exercise or drugs. As nicotine is a high extraction drug, the rate of nicotine
metabolism is also affected with a 17% variation observed over the course of the day (Gries
et al., 1996). Hepatic blood flow is increased by 30% and nicotine clearance is increased by
40% following meals, with maximal effects observed at 30 to 60 minutes post-ingestion
(Gries, Benowitz et al., 1996). The slowest rates of nicotine clearance are observed during
the evening from 6:00 pm to 3:00 am due to reductions in cardiac output and hepatic blood
flow from decreased physical activity and the supine position during sleep (Gries, Benowitz
et al., 1996).
Polymorphisms in other genes involved in nicotine metabolism (such as UGTs and FMO3)
have been identified; however, their contributions to nicotine disposition kinetics have not
been investigated to a great extent. Twin studies have also demonstrated significant
heritability in the rates of glucuronidation and in the renal clearance of nicotine and cotinine
(Benowitz et al., 2008; Lessov-Schlaggar et al., 2009). Pathological conditions such as viral
hepatitis and alcoholic liver cirrhosis can impair nicotine and coumarin metabolism (Pasanen
et al., 1997; Langmann et al., 2000; Hukkanen, Jacob et al., 2005), while kidney failure
decreases both renal and metabolic clearance of nicotine and cotinine by up to 50%
65
(Molander et al., 2000). This is potentially due to the formation of uremic toxins that may
downregulate CYP2A6 expression or act as CYP2A6 inhibitors.
3.5 Phenotypic indicators of CYP2A6 activity
Phenotyping for drug metabolizing enzymes is often used as a non-invasive method to
quantitatively assess their activity in vivo. The procedure typically involves administration of
a probe drug that is a substrate of the enzyme and detection of the proximal metabolites
produced via the pathway of interest at a specific time following drug administration.
Several phenotypic indicators have been used to assess CYP2A6 activity.
3.5.1 COT/NIC
The capacity for cotinine formation from nicotine, as represented by the COT/NIC ratio, has
been used as a measure of CYP2A6 activity despite a number of limitations. While nicotine
and cotinine are found in smokers, the ratio derived from metabolites present during ad
libitum smoking is a poor measure of CYP2A6 activity as it is highly dependent on the time
of the last cigarette as a result of the long half-life of cotinine (approximately 16 to 19 hours)
relative to nicotine (approximately one to two hours) (Benowitz, Jacob P 3rd et al., 1991;
Benowitz and Jacob P 3rd, 1993). As such, the levels of nicotine rise and decline rapidly
following cigarette smoking whereas the levels of cotinine tend to remain fairly stable
(Hukkanen, Jacob et al., 2005). The COT/NIC ratio can be used to assess activity in non-
smokers and abstinent smokers by administration of a nicotine dose, typically through
chewing of nicotine gum, and detection of metabolites in plasma two hours later (Kwon and
Nakajima M, 2001; Nakajima, Kwon et al., 2001). However, nicotine needs to be
administered to individuals who have been abstinent from nicotine-containing products (i.e.
tobacco, NRTs) for prolonged periods of time (at least 14 days) to allow for the removal of
66
cotinine derived from these sources, which may be a potential challenge in phenotyping
current smokers (Kwon and Nakajima M, 2001; Nakajima, Kwon et al., 2001). In addition,
while this ratio measures the metabolites directly related to nicotine metabolism,
approximately 10% of cotinine formed from nicotine is mediated by enzymes other than
CYP2A6, thus limiting its specificity (Messina, Tyndale et al., 1997; Yamazaki, Inoue et al.,
1999).
3.5.2 3HC/COT
The ratio of 3HC to cotinine (3HC/COT) has been used as a proxy measure of CYP2A6
activity as the conversion of cotinine into 3HC is mediated exclusively by CYP2A6
(Nakajima, Yamamoto T et al., 1996; Dempsey et al., 2004; Yamanaka, Nakajima et al.,
2004). The half-life of 3HC is approximately 5 hours; however, the half-life of 3HC
generated from cotinine is approximately 16 to 19 hours as its elimination rate is formation-
dependent and thus matches the longer half-life of cotinine (Benowitz and Peyton J Iii,
2001). As such, the levels of 3HC from cotinine are proportional to its formation rate and
independent of its own elimination rate, with the levels of 3HC and cotinine declining in
parallel over time. As the formation rate is due to CYP2A6 activity, the ratio is a useful
representation of CYP2A6 function. Because of the long half-life of these metabolites, the
3HC/COT ratio can be derived from baseline ad libitum smoking as it is not limited by the
time of last cigarette (among regular smokers). Salivary and plasma 3HC/COT derived from
either baseline smoking, or administration of isotope-labeled nicotine or cotinine, have been
highly correlated with the rates of oral nicotine clearance (r = 0.70 to 0.95) in smokers and
non-smokers (Dempsey, Tutka et al., 2004).
67
The 3HC/COT ratio is generally fairly stable with little intra-individual variation observed
due to circadian fluctuations or by sampling times over the course of the day or week, and it
is not affected by sample storage at room temperature for up to seven days (Lea et al., 2006).
The 3HC/COT ratio is also not greatly altered by variations in smoking patterns or nicotine
intake. Using computer modeling and pharmacokinetic parameters derived from
experimental studies, the 3HC/COT ratio hypothetically collected from spot saliva samples
was predicted to be stable across four different types of daily smoking patterns (Levi et al.,
2007). Furthermore, the urinary 3HC/COT ratio from ad libitum smoking generally did not
change during an eight-week period of smoking reduction (Mooney et al., 2008). The ratio
also did not fluctuate substantially when cigarette consumption was gradually reduced by
75% during a NRT-assisted smoking reduction and maintenance phase over a period of 12
weeks (Mooney, Li et al., 2008).
3.5.3 Formation of 7-hydroxycoumarin
Coumarin 7-hydroxylation is commonly used in vitro and in vivo as a probe drug for
CYP2A6 activity as this reaction is specifically mediated by this enzyme (Pelkonen, Rautio
et al., 2000). Following oral administration, 95 to 98% of coumarin is rapidly excreted as 7-
hydroxycoumarin glucuronide with a half-life of approximately one hour (Ritschel et al.,
1981). Phenotyping studies of CYP2A6 activity were performed where coumarin was
administered either orally or intravenously with detection of total 7-hydroxycoumarin
following deconjugation using β-glucuronidase in the urine or plasma over various time
points (Rautio et al., 1992; Xu, Rao et al., 2002; Peamkrasatam S, Sriwatanakul K et al.,
2006). Because of its rapid and extensive metabolism, coumarin is an excellent phenotypic
indicator for distinguishing those with enzyme function from those with no activity;
however, it is a poor indicator for discriminating among the range of CYP2A6 activity (i.e.
68
normal vs. intermediate vs. slow) (Xu, Rao et al., 2002; Peamkrasatam S, Sriwatanakul K et
al., 2006). Coumarin is used in the treatment of lymphedema although its use has been
banned in some countries due to reported cases of rare idiosyncratic hepatotoxicity (Farinola
et al., 2005). CYP2A in rats has poor metabolic capacities for coumarin 7-hydroxylation
(Hitoshi et al., 1993; Yamazaki et al., 1994). Rather, coumarin is metabolized via 3,4-
epoxidation to form a cytotoxic o-hydroxy-phenylacetylacetaldehyde (o-HPA) metabolite in
rats (Lake, 1999; Vassallo et al., 2004). It has been proposed that this alternative routing of
coumarin metabolism may be the mechanism of toxicity for coumarin among individuals
who lack functioning CYP2A6 (Hadidi et al., 1997).
3.6 Association of CYP2A6 variation with smoking behaviours
Nicotine has an important role in mediating the addictive properties of tobacco smoke; thus,
it has been hypothesized that individual differences in the rates of nicotine metabolism will
influence tobacco dependence and smoking behaviours. A number of studies have associated
genetic variability in CYP2A6 with a range of smoking behaviours.
3.6.1 Smoking initiation
Adult smokers with CYP2A6 genetic variants leading to reduced- or loss-of-function have
reported earlier ages of smoking initiation compared to normal metabolizers (13.0 vs.14.3
years of age) (Schoedel et al., 2004). Despite the limitations of retrospective data, only two
longitudinal studies examining the effect of CYP2A6 variation on the acquisition of tobacco
dependence and smoking behaviours in adolescents have been published to date (O'loughlin
et al., 2004; Audrain-Mcgovern et al., 2007). In a cohort of Caucasian adolescents followed
from Grades 7 to 11, CYP2A6 slow metabolizers were found to have 3-fold higher risk of
dependence, as measured by International Classification of Diseases – 10 (O'loughlin,
69
Paradis et al., 2004; Karp I, 2006). However, a second prospective study of Caucasian
adolescents followed from Grades 9 to 12 found CYP2A6 slow metabolizers progressed in
levels of dependence, as measured by the modified Fagerström Tolerance Questionnaire, at
slower rates with the increase in dependence levels reaching a plateau faster compared to
normal metabolizers (Audrain-Mcgovern, Koudsi et al., 2007). This may be due to different
measures of nicotine dependence, methods of analyses, or baseline characteristics between
the two samples. Interestingly, both of these studies report that once dependent, adolescents
with slow CYP2A6 activity were associated with lower levels of cigarette consumption,
resembling the observation in adults (see section 3.6.2) (O'loughlin, Paradis et al., 2004).
3.6.2 Cigarette consumption
It has been hypothesized that individuals with slow CYP2A6 activity will need to smoke less
often in order to maintain nicotine levels in the body so as to avoid withdrawal symptoms.
Indeed, a number of studies have found an association between reduced CYP2A6 activity
and lower cigarette consumption. This finding has been reported primarily in moderate to
heavy smokers of Caucasian (Pianezza et al., 1998; Rao, Hoffmann et al., 2000; Benowitz et
al., 2003; Schoedel, Hoffmann Eb et al., 2004; Johnstone, Benowitz et al., 2006; Malaiyandi,
Lerman et al., 2006; Derby et al., 2008) and Japanese ancestry (Minematsu et al., 2003;
Fujieda et al., 2004; Kubota et al., 2006; Minematsu et al., 2006; Derby, Cuthrell et al.,
2008). A meta-analysis found a significant association of CYP2A6 slow metabolism group
with reduced cigarette consumption (Munafo et al., 2004) even though not all studies have
replicated these findings (Zhang et al., 2001; Ando et al., 2003). In addition, moderate to
heavy Caucasian smokers who were CYP2A6 slow metabolizers had lower levels of exhaled
CO and cotinine (Rao, Hoffmann et al., 2000), and significantly smaller puff volumes
(Strasser et al., 2007) compared to normal metabolizers.
70
3.6.3 Smoking cessation
3.6.3.1 Case-control gene association studies
Several case-control studies have reported a significantly higher prevalence of CYP2A6 slow
metabolizers among non-smokers, typically defined as having ever tried smoking but never
becoming dependent, compared to smokers (Pianezza, Sellers et al., 1998; Iwahashi et al.,
2004; Schoedel, Hoffmann Eb et al., 2004). These results from cross-sectional studies can be
interpreted in several ways. CYP2A6 slow metabolizers may be less likely to become
dependent regular smokers, although more research is needed to address this possibility. It
may also be that CYP2A6 slow metabolizers are more likely to quit, and indeed several case-
control studies have found a higher prevalence of CYP2A6 slow metabolizers among former
smokers (Gu et al., 2000; Tang et al., 2009). While it is not yet clear how CYP2A6 activity
influences smoking acquisition or cessation processes, there is evidence to suggest CYP2A6
slow metabolizers may be less dependent. Among adult smokers, CYP2A6 slow
metabolizers have lower FTND scores (Kubota, Nakajima-Taniguchi et al., 2006) and were
less likely to smoke the first cigarette of the day within five minutes of waking (Kubota,
Nakajima-Taniguchi et al., 2006; Malaiyandi, Lerman et al., 2006).
3.6.3.2 Clinical trials
There are three smoking cessation clinical trials published to date where CYP2A6 activity
was associated with quitting success. Lerman et al. reported that among individuals assigned
nicotine transdermal patch treatment, those with 3HC/COT ratios in the slowest quartile (i.e.
the lowest 25th percentile, indicative of slowest CYP2A6 activity) were significantly more
likely to quit compared to those with 3HC/COT ratios in the fastest quartile at both week 8
end-of-treatment (46% vs. 28%) and 6-months follow-up (30% vs. 11%) (Figure 3.3A)
(Lerman et al., 2006). This finding was further replicated in an independent sample
71
comparing standard (8 weeks) versus extended (24 weeks) nicotine transdermal patch
treatment (Lerman et al., 2010). Following 8 weeks of standard treatment, individuals with
3HC/COT ratios in the slowest quartile had higher quit rates (42%) than those with faster
CYP2A6 activity (27 to 30%) (Schnoll et al., 2009).
The greater smoking cessation success among CYP2A6 slow metabolizers may be due in
part to their higher plasma nicotine levels obtained from the nicotine patch in comparison to
normal metabolizers (Malaiyandi, Lerman et al., 2006). Interestingly, CYP2A6 slow
metabolizers achieved similar quit rates as normal metabolizers when assigned to nicotine
nasal spray treatment, a form of NRT where dosages can be titrated according to needs
(Figure 3.3B) (Lerman, Tyndale et al., 2006). CYP2A6 slow metabolizers reported using
fewer doses of the nasal spray per day and attained similar nicotine plasma levels as normal
metabolizers (Malaiyandi, Lerman et al., 2006).
In the placebo treatment arm of a clinical trial testing the efficacy of bupropion, individuals
with 3HC/COT ratios in the slowest quartile had the highest quit rates (32%) compared to
those with 3HC/COT ratios in the fastest quartile (10%) at end-of-treatment (Figure 3.3C)
(Patterson et al., 2008). In contrast, the quit rates did not differ by CYP2A6 activity for
individuals taking bupropion (Figure 3.3D) (Patterson, Schnoll et al., 2008). At 6-months
follow-up, similar trends were observed where individuals with 3HC/COT ratios in the
slowest quartile had higher quit rates compared to those with 3HC/COT in the fastest quartile
for placebo treatment, although this no longer remained significant (Patterson, Schnoll et al.,
2008).
It is notable that these three clinical trials included primarily Caucasian moderate to heavy
72
Fig 3.2: Quit rates by 3HC/COT quartiles in clinical trials for smoking cessation. A)
CYP2A6 slow metabolizers (3HC/COT in the 1st quartile) had significantly higher quit rates
at both end-of-treatment and at 6 months follow-up (p = 0.005) (Lerman, Tyndale et al.,
2006). B) The 3HC/COT ratio was not significantly associated with smoking cessation at
either end-of-treatment or 6 months follow-up for individuals treated with nicotine spray (p =
0.68) (Lerman, Tyndale et al., 2006). C, D) CYP2A6 slow metabolizers (3HC/COT in the 1st
quartile) had significantly higher quit rates (p = 0.02), and there was a significant interaction
between treatment arm and the 3HC/COT ratio at end-of-treatment (p = 0.04). Bupropion
significantly improved quit rates compared to placebo for individuals with fastest rates of
CYP2A6 activity (3HC/COT in the 4th quartile) at both end-of-treatment (p = 0.005) and 6
months follow-up (p = 0.02) (Patterson, Schnoll et al., 2008).
73
smokers. Total withdrawal scores and dependence scores at baseline did not significantly
differ by CYP2A6 activity in these studies. However, among those who were abstinent from
smoking following one week of nicotine transdermal patch treatment, individuals with higher
3HC/COT ratios reported having more intense cravings for cigarettes (Lerman, Tyndale et
al., 2006).
3.6.3.3 CYP2A6 inhibition to aid smoking cessation
CYP2A6 inhibitors have clinical utility as they may be used to phenocopy the effects of
CYP2A6 genetic slow metabolizers and increase the likelihood of smoking cessation. The
limited efficacy of currently available NRT formulations are likely due in part to the low-
level of nicotine replacement with large variability observed in plasma drug levels
(Benowitz, Jacob P 3rd et al., 1987; Benowitz, Jacob P 3rd et al., 1991; Compton, Sandborn
Wj et al., 1997; Hukkanen, Jacob et al., 2005), as well as the poor adherence rates reported
(Shiffman et al., 2002; World Health Organization, 2003; Schneider et al., 2004; Lam et al.,
2005; Schneider et al., 2005; Okuyemi et al.). The use of orally ingested nicotine as a form
of pharmacotherapy, which may enhance adherence rates, is possible with the concurrent
administration of a CYP2A6 inhibitor in order to reduce the substantial first-pass effect of
nicotine (Sellers et al., 2003).
CYP2A6 inhibition has the additional benefit of reducing exposure to toxins in tobacco
smoke among current smokers by decreasing the amount of cigarettes consumed and
decreasing bioactivation of tobacco-specific nitrosamines procarcinogens (Sellers, Tyndale et
al., 2003). Administration of the CYP2A6 inhibitor methoxalen concurrently with 4 mg of
oral nicotine resulted in plasma nicotine levels that were 70 to 80% higher those when
nicotine was administered with placebo (Sellers, Kaplan et al., 2000). In addition,
74
methoxalen co-administered with a 4 mg oral nicotine dose decreased the desire to smoke,
decreased the amount smoked (as indicated by 24% reduction in number of cigarettes
smoked, 24% reduction in grams of tobacco burned and 50% reduction in exhaled CO), and
decreased the total number of puffs taken by 25% compared to the oral nicotine given alone
(Sellers, Kaplan et al., 2000; Sellers et al., 2000). Furthermore, smokers receiving
methoxalen while maintaining their regular smoking patterns had significantly more NNK
metabolized to the NNAL-glucuronide metabolite compared to those receiving placebo,
suggesting a rerouting of CYP2A6-mediated NNK bioactivation through this detoxification
pathway (Sellers, Ramamoorthy et al., 2003).
3.6.4 Lung Cancer
CYP2A6 slow metabolizers may have reduced bioactivation of tobacco-specific
procarcinogens, and they may also have lower exposure to harmful substances in tobacco
smoke due to reduced cigarette consumption and shorter lifetime smoking duration
(Schoedel, Hoffmann Eb et al., 2004). To date, 13 studies have examined whether CYP2A6
genetic polymorphisms were associated with altered lung cancer risk. In general, CYP2A6
alleles that reduce or abolish enzyme activity appear to have a protective effect against lung
cancer (Rossini et al., 2008; Rodriguez-Antona et al., 2010). A meta-analysis found the
CYP2A6*4 deletion allele was protective against tobacco-related cancers compared to
wildtype CYP2A6*1 individuals among Asian populations (OR = 0.25, 95% CI = 0.16–0.39)
(Rodriguez-Antona, Gomez et al., 2010). A few studies have also examined the association
of CYP2A6 slow metabolism towards esophageal squamous cell carcinoma, and oral,
stomach, liver, colorectal, nasopharyngeal and neuroblastoma cancers (Rossini, De Almeida
Simao et al., 2008). While these studies have not consistently reported a protective effect,
this may be attributed to a lack of sufficient statistical power in some cases.
75
STATEMENT OF RESEARCH HYPOTHESES
The reduced rates of nicotine metabolism in populations of Black-African descent cannot be
explained by currently known CYP2A6 genetic variants. In Chapter 1, we hypothesize there are
unidentified and uncharacterized SNPs with important functional consequences still present
among populations of Black-African descent. Specifically, we hypothesize the novel
CYP2A6*23 allele, a nonsynonymous SNP (2161C>T) encoding an amino acid change of
Arg203Cys, will reduce enzyme function.
The biological factors associated with light smoking behaviours are not well known. Chapter 2
examines the association of CYP2A6 genetic variants with smoking behaviours in a clinical trial
of African-American light smokers. We hypothesize that recently identified and established
CYP2A6 variants categorized into predicted CYP2A6 genotype groups (normal, intermediate or
slow metabolizers) will be significantly associated with the 3HC/COT ratio. We also hypothesize
that females will have higher 3HC/COT, indicative of faster CYP2A6 activity, smokers of
menthol cigarettes will have lower 3HC/COT, and body mass index (BMI) and age will not alter
CYP2A6 activity. Finally, we hypothesize that CYP2A6 slow metabolizers will smoke fewer
cigarettes per day and be more successful at smoking cessation.
The light and sporadic smoking patterns, and slower rates of cotinine metabolism in this
population, will likely have important implications on the utility of biomarkers of smoking
exposure. In Chapter 3, we hypothesize that exhaled carbon monoxide will be a poor biomarker
for distinguishing between smokers and non-smokers, that exhaled carbon monoxide and plasma
cotinine will be weakly correlated with self-reports of cigarette consumption, and that CYP2A6
activity, gender, smoking menthol cigarettes, BMI, and age will alter levels of self-reported
cigarette consumption, exhaled CO or plasma cotinine.
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CHAPTER 1: A NOVEL CYP2A6 ALLELE, CYP2A6*23, IMPAIRS ENZYME FUNCTION IN
VITRO AND IN VIVO AND DECREASES SMOKING IN A POPULATION OF BLACK-
AFRICAN DESCENT
Man Ki Ho, Jill C. Mwenifumbo, Bin Zhao, Elizabeth M.J. Gillam, Rachel F. Tyndale
Reprinted with permission from Wolters Kluwer Health: Pharmacogenetics and Genomics,
18(1):67-76, 2008. © 2010 All rights reserved.
Dr. Rachel F. Tyndale designed the human experimental study with the original goal of studying
the effect of genetic polymorphisms in CYP2A6 on nicotine pharmacokinetics. Dr. Elizabeth
M.J. Gillam kindly provided the bicistronic expression construct containing the full-length
cDNA of CYP2A6 and human NADPH-CYP reductase. Bin Zhao performed the HPLC
analyses to detect product formation from nicotine C-oxidation and coumarin 7-hydroxylation
assays. Dr. Jill C. Mwenifumbo provided guidance for database management of participants in
the human experimental study and extracted the DNA from blood samples with the aid of Ewa
B. Hoffmann and Qian Zhou. All other experimental work including development of genotyping
assays and screening of DNA samples, DNA sequencing, site-directed mutagenesis, expression
of CYP2A6 construct, and in vitro enzyme activity assays was performed by MKH. Data
analysis and manuscript writing were performed by MKH.
77
Abstract
Objectives: CYP2A6 is the main enzyme involved in nicotine metabolism in humans. We have
identified a novel allele, CYP2A6*23 (2161C>T, R203C), in individuals of Black-African
descent and investigated its impact on enzyme activity and association with smoking status.
Methods: Wildtype and variant enzymes containing amino acid changes R203C (CYP2A6*23),
R203S (CYP2A6*16) and V365M (CYP2A6*17) were expressed in Escherichia coli. The effect
of CYP2A6*23 in vivo was examined in individuals of Black-African descent given 4 mg oral
nicotine.
Results: CYP2A6*23 occurred at an allele frequency of 2.0% in individuals of Black-African
descent (N = 560 alleles, 95% confidence interval 0.8% - 3.1%) and was not detected in
Caucasians (N = 334 alleles), Chinese (N = 288 alleles) or Japanese (N = 104 alleles). In vitro,
CYP2A6.23 had greatly reduced activity towards nicotine C-oxidation similar to CYP2A6.17, as
well as reduced coumarin 7-hydroxylation. Conversely, CYP2A6.16 did not differ in activity
compared to the wildtype enzyme. The trans-3’-hydroxycotinine to cotinine ratio, a phenotypic
measure of CYP2A6 activity in vivo, was lower in CYP2A6*1/*23 and CYP2A6*23/*23
individuals (mean adjusted ratio of 0.60, n = 5) compared to CYP2A6*1/*1 individuals (mean
adjusted ratio of 1.21, n = 150) (p < 0.04). CYP2A6*23 trended towards a higher allele
frequency in nonsmokers (3.1%, N = 9/286 alleles) compared to smokers (0.7%, N = 2/274
alleles) (p = 0.06).
Conclusions: These results suggest the novel CYP2A6*23 allele impairs enzyme function in
vitro and in vivo and trends toward an association with lower risk of smoking.
78
Introduction
Nicotine is responsible for the majority of the psychoactive and highly addictive properties of
cigarettes (2000). In humans, ~80% of absorbed nicotine is converted into cotinine and the
majority of this reaction (~90%) is mediated by the hepatic enzyme cytochrome P450 2A6
(CYP2A6) (Benowitz and Jacob P 3rd, 1994; Messina, Tyndale et al., 1997). Cotinine is further
metabolized to trans-3’-hydroxycotinine and this reaction is entirely mediated by CYP2A6
(Nakajima, Yamamoto T et al., 1996). CYP2A6 is also the main enzyme metabolizing
therapeutic compounds such as coumarin (Pelkonen, Rautio et al., 2000), tegafur (Ikeda et al.,
2000), and SM-12502 (Nunoya et al., 1996), and it can bioactivate tobacco smoke
procarcinogens such as N’-nitrosonornicotine (NNN) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-
butanone (NNK) (Yamazaki et al., 1992).
Large interindividual and interethnic differences in nicotine metabolism have been reported in
vitro and in vivo (reviewed in (Malaiyandi, Sellers et al., 2005)). CYP2A6 is highly
polymorphic, with 22 numbered alleles and numerous single nucleotide polymorphisms (SNPs)
identified so far (http://www.cypalleles.ki.se/cyp2a6.htm). Characterization of CYP2A6 variants
is needed because CYP2A6 polymorphisms altering nicotine metabolism may be important
determinants of smoking behaviours. Several, but not all, studies have found that individuals
with CYP2A6 alleles impairing enzyme activity are less likely to be current smokers (Schoedel,
Hoffmann Eb et al., 2004; Malaiyandi, Sellers et al., 2005).
Differences in nicotine metabolism, smoking behaviours and incidence of tobacco-related
illnesses have been observed between ethnic groups. Compared to Caucasians, individuals of
Black-African descent have a significantly reduced fractional conversion of nicotine to cotinine,
reduced metabolic clearance of nicotine to cotinine and higher plasma levels of cotinine for
79
similar cigarette consumption (Perez-Stable, Herrera et al., 1998; Benowitz, Perez-Stable et al.,
1999). Together, this suggests reduced nicotine and cotinine metabolism, likely as a result of
genetic variations in CYP2A6. Interestingly, populations of Black-African descent are also
characterized by unique smoking patterns. Despite having a similar prevalence of current
smoking as Caucasians (Centers for Disease Control and Prevention, 2005), populations of
Black-African descent report later ages of smoking initiation (Trinidad, Gilpin et al., 2004;
Trinidad, Gilpin et al., 2004) and lower cigarette consumption (Centers for Disease Control and
Prevention, 1998; National Survey on Drug Use and Health, 2006). Furthermore, populations of
Black-African descent suffer from disproportionately higher rates of most tobacco-related
illnesses (Centers for Disease Control and Prevention, 1998), such as lung cancer (National
Center for Chronic Disease Prevention and Health Promotion, 1998; Haiman, Stram et al., 2006),
despite their lower levels of smoking.
In this study, we identified a novel CYP2A6 allele (CYP2A6*23) with a SNP at 2161C>T
(GenBank accession number NG_000008.7) in exon 4 corresponding to an amino acid change
R203C in a population of Black-African descent. We discovered this variant while designing a
genotyping assay for the previously identified CYP2A6*16 allele (Kiyotani et al., 2002), which
occurs at the same locus (2161C>A, R203S). Primers were designed for both the C>A and C>T
nucleotide change as there had been initial confusion to the specific change found in
CYP2A6*16. The effect of CYP2A6*23 on enzyme function was determined in vitro using an
Escherichia coli (E.coli) heterologous expression system. We compared it to CYP2A6*16,
which encodes a different amino acid change at the same position, and to CYP2A6*17, a
previously characterized reduced-activity allele (Fukami et al., 2004). Furthermore, we examined
the effect of CYP2A6*23 on nicotine metabolism in vivo and its association with smoking status.
80
Materials and Methods
Participants
Adults of Black-African descent were recruited from Toronto, Ontario; detailed descriptions of
the population and experimental protocol can be found elsewhere (Mwenifumbo, Sellers et al.,
2007). Briefly, male and female current smokers and tried nonsmokers were recruited. Smokers
were defined as smoking ≥ 100 lifetime cigarettes and currently smoking at least 5 days of the
week while tried nonsmokers had smoked 1 – 99 lifetime cigarettes but were never regular
smokers. Plasma nicotine, cotinine (COT) and trans-3’-hydroxycotinine (3HC) levels were
measured following administration of an oral nicotine dose (4 mg capsule). The 3HC/COT ratio,
calculated from plasma levels collected at 270 minutes after dosing, has been previously verified
as an indicator of CYP2A6 activity (Dempsey, Tutka et al., 2004). Caucasian (n = 167), Chinese
(n = 144) and Japanese (n = 52) individuals recruited for a separate study on CYP2A6 genetic
variation and smoking behaviours (Schoedel, Hoffmann Eb et al., 2004) were also genotyped for
CYP2A6*23. The research protocol was approved and monitored by the University of Toronto
Ethics Review Office and the Institutional Review Board Services (Aurora, ON).
Genotyping assay
Blood samples were stored at -20˚C, and genomic DNA was extracted and stored at -20˚C until
use (GenElute Mammalian Genomic DNA Kit, Sigma-Aldrich Co., Mississauga, ON). A novel
two-step allele specific polymerase chain reaction (PCR) assay was developed for CYP2A6*23.
A fragment of CYP2A6 between intron 3 to intron 5 was amplified using the primers: forward
(2A6exin3F) 5’ – GGC ACT GGC GGT GAG CAG – 3’ and reverse (2A6in5R) 5’ – GGC CTG
TGT CAT CTG CCT – 3’. The reaction mixture contained: 50 ng of genomic DNA, 1X Taq
buffer with KCl, 200 μM deoxyribonucleoside triphosphates (dNTPs), 1.5 mM MgCl2, 125 nM
81
of each primer, 1.25 U of Taq Polymerase (MBI Fermentas, Burlington, ON) and H2O for a total
volume of 25 μl. The reaction conditions were as follows: initial denaturation at 95˚C for 1 min.,
denaturation at 95˚C for 15 sec., annealing at 58˚C for 30 sec., and extension at 72˚C for 2 min.
for 30 cycles, followed by final extension step at 72˚C for 7 min. (MJ Research PCR Cycler PTC
200; Waltham, MA). The product from this first amplification served as the template for a
second allele-specific reaction using the primers: forward (2A6in3F) 5’ – CTG CCT CCT GGA
ATT CTG AC – 3’and a reverse primer specific to 2161C (2A6ex42161AWR, 5’ – GGA AGA
TTC CTA GCA TCA TGC G – 3’) or to 2161T (2A6ex42161AVR, 5’ – GGA AGA TTC CTA
GCA TCA TGC A – 3’). The reaction mixture contained: 0.8 μl of template, 1X Taq buffer with
(NH4)2SO4, 1.0 mM of MgCl2, 75 nM of each primer, 1.25 U of Taq Polymerase and H2O for a
total volume of 25 μl. The reaction conditions were: initial denaturation at 95˚C for 1 min.,
denaturation at 95˚C for 15 sec., annealing at 57˚C for 10 sec., and extension at 72˚C for 30 sec.
for 20 cycles. The PCR products were separated by electrophoresis on a 1.2% agarose gel
stained with ethidium bromide. Subjects had been genotyped for known CYP2A6 variants
(CYP2A6*1B,*2, *4A & D, *9, *12, *14, *15, *17, *20, *21, *24, *25, *26, *27, *28, *29).
DNA sequence analyses
We confirmed the detection of CYP2A6*23 by our genotyping assay, and determined its
haplotype by sequencing all CYP2A6 exons and exon-intron borders in two heterozygous
individuals (CYP2A6*1/*23) and a homozygous individual (CYP2A6*23/*23). A 9.2 kb
fragment spanning -1.4 kb upstream and 7.8 kb downstream of the +1 ATG start site of CYP2A6
was amplified from genomic DNA using long-PCR. The primers for long-PCR were: forward
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(2A65Pr1F) 5’ – ACC TAG ACT TAA TCT TCC CGT ATA C – 3’ and reverse (2A6R0) 5’ –
AGG TCA TCT AGA TTT TCT CCT ACA – 3’. The product was subcloned into pCR®-XL-
TOPO plasmid (TOPO® XL PCR Cloning Kit, Invitrogen Canada Inc., Burlington, ON). DNA
sequencing was performed with an ABI 3730XL DNA analyzer at the Centre for Applied
Genomics (Toronto, ON).
Construction of CYP2A6 expression plasmids
The bicistronic construct with the full length cDNA of CYP2A6 and human NADPH-CYP
reductase (hNPR) inserted into the pCW expression vector (8537 bp) (Gillam et al., 1999) was
derived from the cognate monocistronic construct prepared by Soucek et al. (Soucek, 1999), in
which the native CYP2A6 sequence was changed to encode Ala at the second position with only
silent nucleotide changes elsewhere in the N-terminus. The SNPs 2161C>T (CYP2A6*23),
2161C>A (CYP2A6*16) and 5065G>A (CYP2A6*17) were introduced into the expression
constructs using the QuikChange® II XL Site-Directed Mutagenesis Kits (Stratagene, La Jolla,
CA). Primers used in the mutagenesis reactions were: 2161C>T (5' – AGT TCC TGT CAC TGT
TGT GCA TGA TGC TAG GAA TC – 3', 5' – GAT TCC TAG CAT CAT GCA CAA CAG
TGA CAG GAA CT – 3'), 2161C>A (5' – AGT TCC TGT CAC TGT TGA GCA TGA TGC
TAG GAA TC – 3', 5' – GAT TCC TAG CAT CAT GCT CAA CAG TGA CAG GAA CT – 3'),
5065G>A (5' – ATC CAA AGA TTT GGA GAC ATG ATC CCC ATG AGT TTG G – 3', 5' –
CCA AAC TCA TGG GGA TCA TGT CTC CAA ATC TTT GGA T – 3'). A negative control
was created using BamHI to remove 802 bp from the 5’ end of the CYP2A6 cDNA (total length
of 1485 bp). The products were separated by gel electrophoresis and the remaining plasmid
(7735 bp) was extracted and re-ligated. The variant constructs were confirmed by sequencing
using an ABI 3730XL DNA analyzer at the Centre for Applied Genomics (Toronto, ON).
83
Expression of CYP2A6 constructs in E.coli
The constructs encoding CYP2A6 and hNPR were expressed in E.coli as described previously
(Pritchard Mp et al., 2006). DH5α cells (Invitrogen, Burlington, ON) were transformed with
wildtype and variant constructs and a starter culture was grown in Luria-Bertani medium
containing ampicillin (100 μg/ml) overnight at 37˚C with shaking at 200 rpm. The starter culture
was diluted (1:100) in 100 ml of terrific broth containing ampicillin (100 μg/ml), 1.0 mM
thiamine, and 0.5 mM δ-aminolevulinic acid. The cultures were incubated at 30˚C with shaking
at 120 rpm for 4 – 6 hours, with induction initiated by the addition of 1.0 mM isopropyl β-D-
thiogalactopyranoside. The cultures were incubated for a further 19 – 22 hours at 30˚C and
shaking at 120 rpm. Membrane fractions were prepared as described in (Pritchard Mp,
Mclaughlin L et al., 2006) with minor modifications. Briefly, the pelleted bacteria were
resuspended in buffer (50 mM Tris-HCl, 0.1 mM EDTA, 0.1 mM dithiothreitol, pH 7.4) and
digested with lysozyme (0.25 mg/ml) for 60 min. The spheroplast was pelleted, sonicated, and
centrifuged at 12,000 x g for 12 min. The supernatant was centrifuged for 110,000 x g for 90
min, and the pellet containing the membrane fraction was resuspended in 1.15% KCl and stored
at -80˚C until use. All constructs were initiated for expression concurrently and processed for
immunoblotting and activity at the same time. Batch processing was performed to reduce
construct to construct differences in degradation.
Immunoblotting
Total amount of membrane protein was measured by the Bradford protein assay (Bio-Rad Labs,
Mississauga, ON) and the amount of CYP2A6 protein in the membrane preparations was
determined by immunoblotting as previously described (Schoedel, Sellers et al., 2003). A
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standard curve was constructed using CYP2A6 expressed by a baculovirus-infected insect cell
system (BD Gentest, San Jose, CA). The bacteria membrane preparations and baculovirus-
expressed CYP2A6 were serially diluted to establish linear range of detection.
Enzyme assays for nicotine and coumarin
Nicotine C-oxidation and coumarin 7-hydroxylation were determined as previously described
(Nakajima, Yamamoto et al., 1996; Siu et al., 2006). Briefly, the reaction mixture contained 20
nM of CYP2A6, 20 nM of expressed cytochrome b5 (Invitrogen, Burlington, ON), 50 mM Tris-
HCl buffer (pH 7.4) and substrate. Two substrate concentrations of nicotine (30 and 300 μM) or
coumarin (5 and 50 μM) were initially used to screen for catalytic activity. Subsequently, full
kinetic analyses were performed with nicotine, our main substrate of interest, ranging from 1 –
500 μM. Mouse liver cytosol (1.2 mg protein/ml) was added to the nicotine C-oxidation reaction
as a source of aldehyde oxidase; this was added in excess so that CYP-mediated oxidation would
be rate-limiting (Cashman et al., 1992; Siu, Wildenauer Db et al., 2006). The mixture was pre-
warmed for 2 min. and the reaction was initiated by the addition of 1 mM NADPH. The mixture
was incubated at 37˚C for 45 min. for nicotine C-oxidation and 30 min. for coumarin 7-
hydroxylation, and the reaction was stopped with 4% Na2CO3. The amount of cotinine and trans-
3’-hydroxycotinine formed were detected by high-pressure liquid chromatography (HPLC) as
previously described (Siu, Wildenauer Db et al., 2006).
To detect 7-hydroxycoumarin formation, 5 μl of 20% (w/v) of trichloroacetic acid was added to
the samples. 10 μl of 4-hydroxycoumarin (1 mg/ml) was also added as an internal standard. The
samples were centrifuged at 13,000 rpm for 10 min. and 100 μl of the supernatant was analyzed
by HPLC. Coumarin and its metabolite 7-hydroxycoumarin were separated on the ZORBAX SB
85
C18 Column (250 × 4.6 mm I.D.; particle size, 5 μm) from Agilent Technologies Inc.
(Mississauga, ON) at a flow-rate of 1 ml/min., with a mobile phase of acetonitrile, water and
acetic acid (25 : 75 : 0.1, v/v) and detected at 315 nm. The concentrations of coumarin and 7-
hydroxycoumarin were determined from standard curves created by spiking drug-free bacterial
membrane preparations with known amounts of coumarin (0.2 – 10 μg/ml) and 7-
hydroxycoumarin (50 – 1000 ng/ml). The within-day precisions were 2.4 – 12.8% for coumarin
and 2.6 – 8.3% for 7-hydroxycoumarin, and the between-day precisions were 4.2 – 7.7% for
coumarin and 5.9 – 13.7% for 7-hydroxycoumarin.
Bioinformatics
Linkage disequilibrium of CYP2A6*23 to other genotyped CYP2A6 variants was determined
using Haploview (version 3.32) (Barrett et al., 2005). We used SIFT and PMUT, bioinformatics
programs that predict whether nonsynonymous SNPs will affect enzyme function or structure
based on physicochemical properties and evolutionary conservation of the amino acid changes,
to examine how CYP2A6*23 may be affecting enzyme function (Ng et al., 2001; Ferrer-Costa et
al., 2005).
Statistics
The catalytic activities of the in vitro expressed wildtype and variant enzymes were compared
using one-way ANOVA with the Bonferroni correction for post-hoc analyses. In ethnic groups
where the allele frequency of CYP2A6*23 was zero, the score method was used to calculate
confidence intervals (Wilson, 1927). A comparison of the CYP2A6*23 allele frequencies
between ethnic groups, differences in the distribution of the CYP2A6*23 allele in nonsmokers
versus smokers, and the Hardy-Weinberg equilibrium were calculated using Fisher’s Exact Test.
Consistent with previous studies, gender (Benowitz, Lessov-Schlaggar Cn et al., 2006) and
86
smoking status (Benowitz and Jacob P 3rd, 1993; Benowitz and Jacob, 2000) were found to
affect the rate of nicotine metabolism in our population of Black-African descent, as indicated by
the 3HC/COT ratio (Mwenifumbo, Sellers et al., 2007). Thus, the metabolic ratio was adjusted
by dividing the value from each individual with the overall mean from their respective group
(e.g. female nonsmokers, male nonsmokers, female smokers, male smokers). The effect of
genotype on the adjusted 3HC/COT ratio was examined by a two-tailed independent t-test. A
multiple linear regression model was also used to examine the impact of CYP2A6*23 genotype
on the unadjusted 3HC/COT ratio while controlling for the effect of smoking status and gender.
The unadjusted 3HC/COT ratio was not normally distributed according to the Kolmogorov-
Smirnov test and was log-transformed for the regression model. All statistical analyses were
performed using SPSS (Windows version 14.0) and GraphPad Prism (Windows version 2.0).
Results
CYP2A6*23 was found in populations of Black-African descent
Among the individuals of Black-African descent genotyped for CYP2A6*23 (n = 280), nine
heterozygous and one homozygous individuals were found. Thus, CYP2A6*23 occurred at an
allele frequency of 2.0% (95% confidence interval 0.8 – 3.1%, Table 1); genotype frequencies
did not deviate from Hardy-Weinberg equilibrium (p = 0.821). Five of the ten individuals with
CYP2A6*23 had other CYP2A6 variants (Table 2); CYP2A6*23 was not found in linkage
disequilibrium with any of the other CYP2A6 variants genotyped in this population when
analyzed with Haploview (version 3.32) (Barrett, Fry B et al., 2005), and no other
nonsynonymous SNPs were found in linkage with CYP2A6*23 in the samples sequenced.
CYP2A6*23 was not detected in Caucasian (N = 334 alleles), Chinese (N = 288 alleles) or
Japanese individuals (N = 104 alleles) (Table 1). The allele frequency of CYP2A6*23 in
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individuals of Black-African descent significantly differed from Caucasians and Chinese (p <
0.05, Table 1).
Table 1: Allele frequency of CYP2A6*23 by ethnicity
Ethnicity Allele
frequency (%)
Total # of
alleles
95% Confidence
Intervals
p-values a
Black-African descent 2.0 560 0.8 – 3.1% ---
Caucasian 0 334 0 – 1.1% 0.01
Chinese 0 288 0 – 1.3% 0.02
Japanese 0 104 0 – 3.6% 0.23 a The allele frequency of CYP2A6*23 in each ethnic group was compared against the value found in individuals of Black-African descent.
Table 2: CYP2A6*23 genotype groups and their mean adjusted 3HC/COT ratio
Allele Genotype n
Mean adjusted
3HC/COT SD
% of
wildtype p-values a
*23 *1/*1 150 1.210 0.634 100 0.04
*1/*23 4 0.756 0.540 62.4
*23/*23 1 0 0 0
*17 *1/*1 150 1.210 0.634 100 <0.001
*1/*17 19 0.672 0.468 55.5
*17/*17 3 0.109 0.095 9.1
>1 variant *1/*1 150 1.210 0.634 100 0.02
*17/*23 2 0.259 0.366 21.4
*20/*23 2 0.555 0.512 45.8
*9/*23 1 1.032 0 85.2 a The adjusted 3HC/COT ratio was compared between wildtype individuals (CYP2A6*1/*1) to other genotype groups combined using a two-tailed independent t-test.
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CYP2A6*23 reduced enzyme activity towards nicotine and coumarin in vitro
The specific content of CYP2A6 was similar between CYP2A6.1 (0.11 pmol CYP2A6/μg
membrane protein), CYP2A6.16 (0.12 pmol CYP2A6/μg of membrane protein) and CYP2A6.17
(0.12 pmol CYP2A6/μg membrane protein), although CYP2A6.23 was expressed at lower levels
(0.07 pmol CYP2A6/μg membrane protein) (Fig. 1A). The negative construct did not produce
any detectable CYP2A6 protein. Subsequent enzyme assays with the wildtype and variant
constructs were performed using equivalent amounts of CYP2A6 (20 nM).
We initially screened the activities of the wildtype and variant constructs towards nicotine and
coumarin at two concentrations (Fig. 1B, C). There was a significant difference in activities of
the constructs at 30 μM of nicotine (F = 29.0, p < 0.001), 300 μM of nicotine (F = 35.9, p <
0.001), and 50 μM of coumarin (F = 28.3, p < 0.01). Both CYP2A6.23 and CYP2A6.17 had
significantly lower activity towards nicotine compared to CYP2A6.1 at 30 μM (p < 0.01) and
300 μM (p < 0.001) of substrate. CYP2A6.23 also had significantly reduced activity towards 50
μM of coumarin (p < 0.01) while CYP2A6.17 retained similar activity as the wildtype enzyme.
CYP2A6.16 had similar activities as CYP2A6.1 towards nicotine and coumarin at both
concentrations tested (Fig. 1B, C).
We then performed full kinetic analyses on nicotine, our main substrate of interest. CYP2A6.23
and CYP2A6.17 had reduced activity towards nicotine in vitro while CYP2A6.16 had similar
activity as CYP2A6.1 (Fig. 2). The apparent Km values did not significantly differ between the
wildtype and variant constructs (F = 3.0, p = 0.083), though it trended towards higher values for
CYP2A6.17 (p = 0.09, Table 3). However, there was a significant difference in Vmax (F = 35.2,
p < 0.001) and Vmax/Km (F = 19.0, p < 0.001) between the constructs. Vmax was significantly
89
lower for CYP2A6.23 (p < 0.001) and CYP2A6.17 (p < 0.01) compared to CYP2A6.1.
Likewise, Vmax/Km was significantly lower for CYP2A6.23 (p < 0.001) and CYP2A6.17 (p <
0.01) compared to CYP2A6.1. There was no significant difference in Vmax and Vmax/Km between
CYP2A6.23 and CYP2A6.17, or between CYP2A6.16 and CYP2A6.1.
90
Figure 1: CYP2A6.23 had substantially reduced catalytic activity towards nicotine
and coumarin in vitro. A) Immunoblot shows the expression of CYP2A6 protein from
the wildtype and variant constructs. The amount of total membrane protein loaded is as
labeled and ranged from 0.5 – 2.0 μg for CYP2A6.1, CYP2A6.16 and CYP2A6.17,
while CYP2A6.23 was loaded at 0.75 – 4.0 μg. Detection of CYP2A6 constructs was
linear by immunoblotting at lower amounts loaded, and was used to calculate the
amount of CYP2A6 detected by comparison to the standard (not shown). B)
CYP2A6.17 and CYP2A6.23 have reduced cotinine formation from nicotine (30 and
300 μM) while CYP2A6.16 had similar activity as CYP2A6.1. C) CYP2A6.23 had
reduced 7-hydroxycoumarin formation from coumarin (5 and 50 μM) while CYP2A6.16
and CYP2A6.17 had similar activity as CYP2A6.1. No product formation was found
using the negative construct. The data are presented as mean ± SEM for nicotine C-
oxidation (n = 3) and coumarin 7-hydroxylation (n = 2). * p < 0.01, ** p < 0.001 when
compared to CYP2A6.1.
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Figure 2: CYP2A6.17 and CYP2A6.23, but not CYP2A6.16, have reduced in vitro nicotine C-oxidation. A representative plot is shown, and the curve was fitted to the Michaelis-Menten equation using non-linear regression in GraphPad Prism (version 2.0).
Table 3: Kinetic parameters of CYP2A6 wildtype and variant constructs for nicotine
Km (μM)a Vmax Vmax/Km
(pmol•min-1•pmol CYP2A6-1) (nL•min-1•pmol CYP2A6-1) CYP2A6.1 58.3 ± 6.5 5.5 ± 0.5 97.3 ± 11.6
CYP2A6.16 73.6 ± 6.1 5.1 ± 0.2 71.4 ± 7.7
CYP2A6.17 88.9 ± 6.8 2.6 ± 0.2 * 29.6 ± 4.2*
CYP2A6.23 77.7 ± 10.4 1.4 ± 0.2 ** 18.4 ± 2.3 **
a Kinetic parameters were calculated using non-linear regression in GraphPad Prism (version 2.0). Data are presented as mean ± SEM of parameters calculated from three or four independent experiments. * p < 0.01, ** p < 0.001 when compared to CYP2A6.1.
92
CYP2A6*23 decreased the rate of nicotine metabolism in vivo in a population of Black-
African descent
The 3HC/COT is a validated phenotypic measure of CYP2A6 activity and rates of nicotine
metabolism (Dempsey, Tutka et al., 2004), with previous studies finding a significant association
between the ratio and CYP2A6 genotype (Benowitz, Swan et al., 2006; Malaiyandi, Goodz et al.,
2006; Malaiyandi, Lerman et al., 2006). Because the 3HC/COT ratio did not differ significantly
from CYP2A6*1/*1 individuals in this population of Black-African descent, the wildtype group
(*1/*1) included individuals with the CYP2A6*1B allele. The adjusted 3HC/COT ratio was
significantly lower in individuals with at least one CYP2A6*23 allele and no other variants (n =
5) in comparison to CYP2A6*1/*1 individuals (n = 150) (p < 0.04, Fig. 3). A gene-dose effect
was observed such that CYP2A6*1/*23 heterozygous individuals had ~40% loss in enzyme
activity compared to CYP2A6*1/*1 individuals, while one CYP2A6*23/*23 homozygous
individual did not produce any 3HC (Fig. 3). A similar impact of CYP2A6*23 was observed in a
multivariate linear regression model with the log(3HC/COT) as the dependent variable and
including smoking status and gender as predicting variables (R2 = 0.355, p < 0.04). It is notable
that the five individuals with CYP2A6*23 in addition to other genetic variants also had
significantly lower 3HC/COT ratios compared to the wildtype group (p < 0.02, Table 2).
CYP2A6*23 was associated with a lower likelihood of being a current adult smoker
CYP2A6*23 trended towards a higher frequency in nonsmokers (3.1%, N = 9/286 alleles)
compared to smokers (0.7%, N = 2/274 alleles) (p = 0.06, Fig. 4). Individuals with CYP2A6*23
were approximately 4 – 5 times less likely to be smokers when all individuals with CYP2A6*23
were taken into account (odds ratio = 0.23). The magnitude of the effect was the same when
analyses were restricted to individuals with only CYP2A6*1/*1, CYP2A6*1/*23, and
CYP2A6*23/*23 (odds ratio = 0.18, p = 0.11).
93
Figure 3: CYP2A6*23 decreased the rates of nicotine metabolism in vivo, as measured by the 3HC/COT ratio. The number of individuals in each genotype group is shown in parentheses on the x-axis. The data are presented as mean ± SD. Individuals with other CYP2A6 genetic variants (CYP2A6*2, *4A & D, *9, *12, *14, *15, *17, *20, *21, *24, *25, *26, *27, *28, *29) were excluded from the wildtype and CYP2A6*23 genotype groups.
Figure 4: Individuals with the CYP2A6*23 allele trended to having a lower likelihood of being current smokers. The allele frequency of CYP2A6*23 was calculated from the 280 genotyped individuals in the study, including 143 nonsmokers and 137 smokers
94
Discussion We have identified a novel CYP2A6 allele, CYP2A6*23, which is found in populations of Black-
African descent but not in Caucasians, Chinese and Japanese. Two recently described alleles,
CYP2A6*17 and CYP2A6*20, have also been identified exclusively in this population (Fukami,
Nakajima et al., 2004; Fukami et al., 2005). These genetic variants may help explain the reduced
rates of nicotine metabolism in individuals of Black-African descent compared to Caucasians
(Perez-Stable, Herrera et al., 1998; Benowitz, Perez-Stable et al., 1999).
We have demonstrated that CYP2A6*23 (2161C>T, R203C) impairs both nicotine C-oxidation
and coumarin 7-hydroxylation in vitro. CYP2A6.23 had a significantly reduced Vmax towards
nicotine, and the intrinsic clearance (Vmax/Km) was reduced to 19% of the wildtype enzyme.
This is in agreement with the observation that in vivo, the 3HC/COT ratio is reduced in
individuals with the CYP2A6*23 allele. CYP2A6*23 may be affecting enzyme function through
alteration in substrate binding. Molecular modeling indicates Arg203 may be important in the
orientation of Phe209, a residue critical for coumarin binding and possibly involved in nicotine
binding (Lewis et al., 1999; Kiyotani et al., Oct 23-27, 2005). In addition, CYP2A6.23 had a
lower level of expression in vitro compared to the other constructs used in this study, which may
also contribute to the lower activity observed in vivo.
In contrast to CYP2A6*23 (2161C>T, R203C), CYP2A6*16 (2161C>A, R203S) did not appear
to affect enzyme function. Our in vitro data suggest CYP2A6.16 has similar rates of nicotine
and coumarin metabolism as the wildtype enzyme. Furthermore, Nakajima et al. recently
reported that CYP2A6*16 did not affect rates of nicotine metabolism in vivo (Nakajima, Fukami
et al., 2006). These data suggest the functional impact of CYP2A6*23 (Cys203) differs from that
of CYP2A6*16 (Ser203). The wildtype residue (Arg203) is positively charged and hydrophilic
95
while Cys203 is neutral and hydrophobic and Ser203 is neutral and hydrophilic. Furthermore,
the bioinformatics program SIFT and PMUT (Ng and Henikoff, 2001; Ferrer-Costa, Gelpi et al.,
2005) predicted the amino acid change in CYP2A6*23 as not tolerated while CYP2A6*16 was
predicted to be benign.
Interestingly, CYP2A6*23 impaired nicotine C-oxidation to at least the same extent as
CYP2A6*17 both in vitro and in vivo. Similar to expressed CYP2A6.23, CYP2A6.17 had a
significantly reduced Vmax towards nicotine, with Vmax/Km reduced to 30% of the wildtype
enzyme. This is in agreement with a previous study where CYP2A6.17 expressed in E.coli did
not alter Km but reduced Vmax towards nicotine, with Vmax/Km reduced to 40% of the wildtype
construct (Fukami, Nakajima et al., 2004). In vivo, the 3HC/COT ratio in heterozygous
individuals for CYP2A6*17 is reduced to approximately 55% of wildtype activity, while
homozygous individuals of CYP2A6*17 had approximately 9% of wildtype activity. This is
consistent with previous studies using the COT/NIC ratio as a biomarker (Nakajima, Fukami et
al., 2006), and together these data strongly suggest the CYP2A6*17 allele results in reduced
nicotine metabolism. We also observed that the impact of CYP2A6.17 is substrate-dependent
such that it did not differ in coumarin 7-hydroxylation compared to the wildtype enzyme.
Accordingly, a previous study found CYP2A6.17 expressed in E.coli had an increased Km but no
change in Vmax towards coumarin (Fukami, Nakajima et al., 2004).
A trend was observed where individuals with CYP2A6*23 were less likely to be current adult
smokers. Several case-control studies have associated CYP2A6 genetic variations leading to
impaired activity with a lower likelihood of smoking (Pianezza, Sellers et al., 1998; Tyndale et
al., 2001; Schoedel Ka et al., 2004), though negative findings have also been reported (Tan et al.,
2001; Zhang, Amemo K et al., 2001; Ando, Hamajima et al., 2003). A greater understanding of
96
CYP2A6 genetic variation through identification and characterization of novel variants,
particularly among different ethnic groups, will allow for better replication of genetic case-
control association studies.
In summary, we have discovered a novel CYP2A6 allele, occurring predominantly in a
population of Black-African descent, which impairs enzyme activity in vitro and in vivo and may
be associated with a lower risk of smoking. An understanding of the genetic factors that
contribute to nicotine pharmacokinetics in populations of Black-African descent is important
given their unique smoking patterns and higher incidence of tobacco-related illnesses.
Significance to thesis
In this chapter, a new CYP2A6 genetic variant was identified among individuals of Black-
African descent that reduces enzyme activity in vitro and in vivo. Much progress has been made
in recent years towards our characterization of CYP2A6 genetic variants, particularly among
populations of Black-African descent. In addition to CYP2A6*23, our group identified and
determined the functional impact of six new CYP2A6 alleles consisting of nonsynonymous SNPs
that were found predominantly in populations of Black-African descent. Many of these alleles
reduced or completely abolished enzyme function (Appendix C) (Mwenifumbo et al., 2008; Al
Koudsi et al., 2009; Mwenifumbo et al., 2010).
This chapter adds to our current understanding of the genetic factors that contribute to the
observed variability in rates of nicotine metabolism among populations of Black-African
descent. Identification of CYP2A6 genetic variants that are detrimental to enzyme function will
help explain the slower rates of nicotine and cotinine clearance observed in this population
(Benowitz, Perez-Stable et al., 1999). In addition, determining the functional impact of CYP2A6
97
genetic variants will help reduce the heterogeneity of assigned CYP2A6 genotype groups for
genetic association studies of smoking behaviours performed in populations of Black-African
descent. This will improve our ability to replicate and interpret the results from these studies,
allowing us to gain a better understanding of how genetic variability in CYP2A6 influences
smoking behaviours in this group.
98
CHAPTER 2: ASSOCIATION OF NICOTINE METABOLITE RATIO AND CYP2A6
GENOTYPE WITH SMOKING CESSATION TREATMENT IN AFRICAN-AMERICAN
LIGHT SMOKERS
Man Ki Ho, Jill C. Mwenifumbo, Nael Al Koudsi, Kolawole S. Okuyemi, Jasjit S. Ahluwalia,
Neal L. Benowitz, Rachel F. Tyndale
Reprinted by permission from Macmillan Publishers Ltd: Clinical Pharmacology and
Therapeutics, 85(6):635-43, 2009. © 2010 All rights reserved.
Drs. Kolawole Okuyemi, Jasjit Ahluwalia, Neal Benowitz and Rachel Tyndale designed and
recruited the participants in this clinical trial with the primary aim of testing the efficacy of 2 mg
nicotine gum and two different counseling methods for smoking cessation in a population of
African-American light smokers. The levels of nicotine, cotinine and trans-3-hydroxycotinine in
plasma samples were determined in the laboratory of Dr. Neal Benowitz. MKH performed a
substantial portion of the DNA extraction and CYP2A6 genotyping, with the assistance of Dr. Jill
Mwenifumbo, Dr. Nael Al Koudsi, Ewa Hoffmann, and Qian Zhou. MKH also identified the
key research questions to be addressed, performed all of the statistical analyses and wrote the
manuscript.
99
Abstract
Cytochrome P450 2A6 (CYP2A6) is the main nicotine metabolizing enzyme in humans. We
investigated the relationships between CYP2A6 genotype, baseline plasma 3HC/COT (a
phenotypic marker of CYP2A6 activity), and smoking behaviours in African-American light
smokers. Cigarette consumption, age of initiation, and dependence scores did not differ between
3HC/COT quartiles or CYP2A6 genotype groups. Slow metabolizers (both genetic and
phenotypic) had significantly higher plasma nicotine levels suggesting cigarette consumption
was not reduced to adjust for slower rates of nicotine metabolism. Individuals in the slowest
3HC/COT quartile had higher quit rates with both placebo and nicotine gum treatments (OR
1.85, 95% CI 1.08-3.16, p = 0.03). Similarly, the slowest CYP2A6 genotype group had higher
quit rates, although this did not reach significance (OR 1.61, 95% CI 0.95-2.72, p = 0.08).
3HC/COT ratio, and possibly CYP2A6 genotype, may be useful in the future for personalizing
the choice of smoking cessation treatment for African-American light smokers.
Introduction
While overall smoking rates in North America have declined considerably, there are a growing
number of smokers who maintain low levels of cigarette consumption. Light smoking is more
prevalent particularly among adolescents, females and some racial/ethnic minority groups. For
example, the majority of African-Americans consume ≤10 cigarettes per day (CPD) (Kandel et
al., 2000), yet they report high levels of dependence and have difficulty quitting (Centers for
Disease Control and Prevention, 1993; Royce, Hymowitz et al., 1993). Further, African-
Americans have disproportionately higher incidences of tobacco-related illnesses such as lung
cancer (Centers for Disease Control and Prevention, 1998; Haiman, Stram et al., 2006), which
may be partly explained by their greater use of mentholated cigarettes with higher nicotine and
tar yields (Us Department of Health and Human Services, 1998), deeper inhalation patterns
100
(Clark, Gautam et al., 1996), and altered rates of nicotine and nitrosamine metabolism
(Benowitz, Perez-Stable et al., 1999; Muscat et al., 2005).
Nicotine is primarily responsible for the highly addictive properties of tobacco smoke (Benowitz,
1999). The majority (~80%) of nicotine (NIC) is inactivated to cotinine (COT) (Benowitz and
Jacob P 3rd, 1994), and ~90% of this reaction is mediated by the hepatic enzyme cytochrome
P450 2A6 (CYP2A6) (Messina, Tyndale et al., 1997). Cotinine is further metabolized to trans-
3’-hydroxycotinine (3HC) primarily by CYP2A6 (Nakajima, Yamamoto T et al., 1996;
Dempsey, Tutka et al., 2004). In addition, CYP2A6 can bioactivate tobacco-specific
precarcinogens including (methyl-nitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N’-
nitrosonornicotine (NNN) (Yamazaki, Inui et al., 1992).
The gene encoding CYP2A6 is highly polymorphic, with 36 numbered alleles and numerous
single nucleotide polymorphisms (SNPs) identified so far
(http://www.cypalleles.ki.se/cyp2a6.htm). Large inter-ethnic and inter-individual variations in
CYP2A6 activity have been reported (Mwenifumbo and Tyndale, 2007). This has been mainly
attributed to genetic variations in CYP2A6, although environmental influences (e.g. diet) may
also contribute through enzyme induction or inhibition. For example, estrogen has been found to
induce CYP2A6 in vitro (Higashi, Fukami et al., 2007), and females have faster rates of in vivo
nicotine metabolism compared to males (Benowitz, Lessov-Schlaggar Cn et al., 2006).
Since dependent smokers regulate the amount smoked to maintain plasma and brain nicotine
levels (Mcmorrow and Foxx Rm, 1983), variations in CYP2A6 activity is predicted to alter
smoking behaviors. Individuals with CYP2A6 alleles encoding enzymes with decreased- or loss-
of-function metabolize nicotine at a slower rate (Rao, Hoffmann et al., 2000; Benowitz, Swan et
101
al., 2006; Mwenifumbo, Al Koudsi et al., 2008), and have been associated with lower risk of
being a smoker in adults (Schoedel, Hoffmann Eb et al., 2004), lower cigarette consumption
(Rao, Hoffmann et al., 2000; Schoedel, Hoffmann Eb et al., 2004), reduced smoking intensity
(Rao, Hoffmann et al., 2000; Strasser, Malaiyandi et al., 2007), and reduced withdrawal
symptoms during abstinence (Kubota, Nakajima-Taniguchi et al., 2006). In addition, CYP2A6
slow metabolizers achieved higher quit rates in clinical trials (Lerman, Tyndale et al., 2006;
Patterson, Schnoll et al., 2008; Schnoll et al., 2009), were more likely to be former smokers in a
case-control study (Gu, Hinks et al., 2000), and had shorter durations of smoking suggestive of
greater quit success (Schoedel, Hoffmann Eb et al., 2004). However, these studies have been
mainly in heavy smoking individuals of European- or Asian-ancestry. There is a paucity of
research on the role of CYP2A6 variation and smoking in light smoking populations such as
African-Americans. Interestingly, African-Americans have slower rates of nicotine and cotinine
metabolism compared to European-Americans (Benowitz, Perez-Stable et al., 1999), and our lab
recently identified novel CYP2A6 variants in this population that are associated with lower
enzyme activity (Mwenifumbo, Al Koudsi et al., 2008). It follows that variation in CYP2A6
activity may also contribute to the unique smoking patterns observed in this group.
The large variation in CYP2A6 activity and numerous CYP2A6 alleles indicates the need for a
phenotypic measure for population studies. The 3HC/COT ratio has been validated as a
phenotypic marker of CYP2A6 activity as the conversion of COT to 3HC is specific to CYP2A6
(Nakajima, Yamamoto T et al., 1996; Dempsey, Tutka et al., 2004). The ratio of these nicotine
metabolites is highly correlated with rates of nicotine clearance (r = 0.70 - 0.95) (Dempsey,
Tutka et al., 2004), and has been associated with CYP2A6 genotype in several studies (Johnstone,
Benowitz et al., 2006; Malaiyandi, Goodz et al., 2006; Mwenifumbo, Al Koudsi et al., 2008).
However, these studies have been primarily in heavy smoking individuals of European-ancestry,
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and it is unknown whether the 3HC/COT ratio derived from baseline ad libitum smoking will
also be a good phenotypic measure of CYP2A6 activity in African-American light smokers
where smoking can be both low and irregular in frequency.
Few smoking cessation clinical trials have focused on African-Americans as treatment studies
typically exclude light smokers. A recent study, entitled Kick it at Swope-II (KIS-II), evaluated
the efficacy of nicotine replacement therapy (2 mg nicotine gum vs. placebo) and counseling
sessions (health education (HE) vs. motivational interviewing (MI)) in 755 African-American
light smokers (Ahluwalia, Okuyemi et al., 2006). Nicotine gum did not increase quit rates
compared to placebo at week 26 follow-up, although those receiving HE were significantly more
likely to quit compared to those receiving MI. Thus, further investigations of the biological
factors underlying smoking behaviors in light smoking populations are warranted.
Here, we first investigated whether CYP2A6 genotype is related to the 3HC/COT ratio derived
from baseline smoking in treatment seeking African-American light smokers enrolled in KIS-II.
We then determined whether CYP2A6 variation, as indicated by genotype and the 3HC/COT
ratio, is associated with baseline smoking behaviors and treatment outcomes. This is the largest
study to date examining the role of CYP2A6 variation in smoking behaviors among African-
American light smokers, with the additional benefit of having genetic and phenotypic measures
available.
Materials and Methods
Study design
A detailed description of the study design and participant recruitment has been described
elsewhere (Ahluwalia, Okuyemi et al., 2006). Briefly, individuals (n = 755) self-identified as
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“African-American” or “Black” were randomized into a double-blind, placebo-controlled study
at a community health center in Kansas City, Missouri. This study consisted of four treatment
arms (n ~189 each) of either placebo or nicotine gum (2 mg), along with either HE or MI
counseling. Inclusion criteria included: ≥18 years of age, smoked ≤10 CPD for at least 6 months
prior to enrolment, smoked at least 25 of the last 30 days, and interested in quitting smoking in
the next 2 weeks.
Drug treatment continued for 8 weeks and the dosing regimen was based on the participant’s
baseline cigarette consumption as described previously (Ahluwalia, Okuyemi et al., 2006). Six
counseling sessions were provided, and all participants were followed for a total of 26 weeks.
The research protocol was approved and monitored by the University of Toronto Ethics Review
Office and the University of Kansas Human Subjects Committee.
Measurements
Demographic information, smoking history, and severity of nicotine dependence were collected
at randomization. Plasma sample was also taken at randomization and the levels of NIC, COT
and 3HC from baseline smoking were determined by methods described previously (Dempsey,
Tutka et al., 2004).
CYP2A6 genotyping assays
Blood samples for genetic analyses were available from 618 of the 755 participants who
consented to genetic testing. Established CYP2A6 alleles (CYP2A6*1B, *2, *4, *9, *12, *17,
*20) and novel alleles that were recently identified in a population of Black-African descent
(CYP2A6*23, *24, *25, *26, *27, *28, *35) were genotyped using a two-step allele-specific
polymerase chain reaction assay as previously described (Goodz et al., 2002; Ho et al., 2008;
104
Mwenifumbo Jc, Al Koudsi N et al., 2008; Al Koudsi, Ahluwalia Js et al., 2009). The
genotyping assay for CYP2A6*1B was revised because SNPs occurring at a high frequency in
this population were found at the location of the primers used in the previous assay
(Mwenifumbo et al., 2010). An assay that detects CYP2A6*4A and*4D, as well as the recently
identified gene deletions CYP2A6*4E – H, will be reported elsewhere (Mwenifumbo, Zhou et
al., 2010).
Statistical analyses
The 3HC/COT ratio was not normally distributed and was log-transformed for all statistical
analyses. Chi-squared test was used to test for Hardy-Weinberg equilibrium, to examine
differences in allele frequencies in this sample compared to previously reported values in a
population of Black-African descent, and to test for differences in quit rates by CYP2A6 activity
groups. Univariate ANOVA was used to assess differences in 3HC/COT between CYP2A6
genotype groups, and to test the association of CYP2A6 activity with CPD, CO levels, nicotine
plasma levels, age of regular smoking, and dependence scores. Univariate ANOVA was also
used to examine if differences in baseline variables exists between the total participants and
those with 3HC/COT data, genotype data, and both 3HC/COT and genotypes. Bonferroni
correction was used for post-hoc analyses. Multiple logistic regression models were used to
assess the association of CYP2A6 genotype and 3HC/COT quartiles on quit rates at EOT and
follow-up. All statistical analyses of treatment effects were performed on an intent-to-treat basis
and those lost during follow-up were counted as smokers.
105
Results
Participant characteristics
There was no significant difference in participant characteristics (gender, age, body mass index
(BMI), smoking mentholated cigarettes, CPD, exhaled carbon monoxide (CO), baseline plasma
NIC and COT, age of regular smoking, or dependence severity) between the total population (n =
755), the subset of participants with 3HC/COT data (n = 646), those with genotype data (n =
588), and those with both genotype and 3HC/COT data (n = 495) (Supplementary Table 1, pg.
126).
Variables that influence the 3HC/COT ratio
To examine other factors that may influence the 3HC/COT ratio independent of CYP2A6 genetic
variation, an analysis was performed including only CYP2A6*1/*1 individuals (n = 246). The
3HC/COT ratio was significantly higher in females, increased with age, and was higher in those
with lower BMI (Table 1). Individuals who smoked mentholated cigarettes also had
significantly lower 3HC/COT ratios (p < 0.05). In a multivariate regression model, gender, age
and BMI remained independently associated with the 3HC/COT ratio (p < 0.05, Table 1).
CYP2A6 genotypes and associations with 3HC/COT
CYP2A6*1B has been associated with faster enzyme activity in European-Americans
(Mwenifumbo et al., 2007), although no difference was observed previously in individuals of
Black-African descent (Mwenifumbo Jc, Al Koudsi N et al., 2008). We used a newly revised
CYP2A6*1B genotyping assay to account for SNPs occurring at a high frequency in this
population that confounded our previous assay (Mwenifumbo, Zhou et al., 2010), and found
individuals with CYP2A6*1B had significantly higher 3HC/COT ratios even after controlling for
gender, age and BMI as covariates (F(2, 238) = 5.1, p < 0.01, Table 2).
106
Table 1: Factors that influence the 3HC/COT in CYP2A6*1/*1 individuals (n = 246) Mean 3HC/COT SD N p – value
Univariate analyses
Gender
Males 0.37 0.19 79 0.02
Females 0.46 0.32 167
Age
20 – 29 0.35* 0.20 22 0.002
30 – 39 0.37* 0.20 72
40 – 49 0.43 0.24 80
50 – 59 0.48 0.35 52
60 – 77 0.63 0.43 20
r 0.22 0.001
BMI 1
Low (< 29.7) 0.46 0.3 122 0.05
High (≥ 29.7) 0.40 0.3 122
r -0.16 0.01
Smoke mentholated cigarettes
Yes 0.41 0.27 190 0.02
No 0.50 0.31 56
Multivariate regression analyses 2
Standardized β 95% CI p – value
Gender 0.15 0.005 – 0.044 0.01
Age 0.24 0.001 – 0.002 < 0.001
BMI - 0.16 - 0.003 – 0.000 0.01
Mentholated cigarettes - 0.08 - 0.036 – 0.008 0.22 1 BMI was categorized by the median value of 29.7. r = Spearman’s correlation coefficient
between BMI and 3HC/COT. BMI data were not available for two participants. 2 R2 = 0.12. Age and BMI were included as continuous variables.
* denotes significant difference (p < 0.05) from the oldest age group (60 – 77). r = Spearman’s
correlation coefficient between age and 3HC/COT.
107
To examine the functional impact of other CYP2A6 variants, individuals with CYP2A6*1B were
included in the wildtype reference group, as this allows us to compare our results with those
reported previously (Mwenifumbo Jc, Al Koudsi N et al., 2008), and this genotype was not
associated here with altered baseline smoking variables or treatment outcomes.
Consistent with earlier studies (Benowitz, Swan et al., 2006; Mwenifumbo Jc, Al Koudsi N et
al., 2008), heterozygous individuals with established alleles, CYP2A6*4, *17 and *20, had ~40 –
60% activity remaining, while heterozygous individuals with CYP2A6*9 and *12 had ~50 – 75%
activity remaining (Fig. 1A, Table 2). Heterozygous individuals with alleles recently identified
in individuals of Black-African descent (CYP2A6*25, *26, *27 and *35) (Mwenifumbo Jc, Al
Koudsi N et al., 2008) also had ~40 – 60% activity remaining (Fig. 1A, Table 2). Given the low
prevalence of these novel variants, the larger size of this current study provides further evidence
of their in vivo functional impact. CYP2A6*2, *23, *24 and *28 were associated with 3HC/COT
ratios higher than expected (Fig. 1A, Table 2). Thus, in agreement with previous studies in other
racial/ethnic groups (Johnstone, Benowitz et al., 2006; Malaiyandi, Goodz et al., 2006), there is
generally a good concordance between CYP2A6 genotype and 3HC/COT as a phenotypic
measure. The frequencies of the genotypes did not deviate significantly from Hardy-Weinberg
equilibrium (p > 0.10). CYP2A6 allele frequencies in this sample of African-Americans did not
significantly differ from those reported in Canadian individuals of Black-African descent, with
the exception of CYP2A6*28 (Table 3).
108
Table 2: CYP2A6 genotypes and associated 3HC/COT ratios1 Allele Genotype N Mean 3HC/COT SD % p – value
CYP2A6*1B *1/*1 169 0.40 0.29 100 0.007
*1/*1B 62 0.49 0.26 123
*1B/*1B 15 0.50 0.26 125
Reference 2 *1/*1 246 0.43 0.28 100 ---
CYP2A6*2 *1/*2 5 0.31 0.16 72 0.29
CYP2A6*4 *1/*4 14 0.21 0.09 49 0.001
CYP2A6*9 *1/*9 70 0.32 0.29 74 < 0.001
*9/*9 10 0.15 0.10 35
CYP2A6*12 *1/*12 4 0.23 0.11 53 0.06
CYP2A6*17 *1/*17 49 0.26 0.15 61 < 0.001
*17/*17 5 0.06 0.03 14
CYP2A6*20 *1/*20 13 0.17 0.11 40 < 0.001
*20/*20 1 0.18 --- 42
CYP2A6*23 *1/*23 7 0.38 0.12 88 0.56
CYP2A6*24 *1/*24 3 0.37 0.16 86 0.50
CYP2A6*25 *1/*25 7 0.22 0.06 51 0.10
CYP2A6*26 *1/*26 4 0.23 0.11 54 0.09
CYP2A6*27 *1/*27 8 0.18 0.07 42 0.001
CYP2A6*28 *1/*28 16 0.73 0.71 170 0.007
CYP2A6*35 *1/*35 20 0.26 0.09 61 < 0.001
*35/*35 1 0.18 --- 42
> 1 variant 3 --- 39 0.15 0.08 35 < 0.001 1 Univariate analyses including gender, age, and BMI as covariates. Comparisons were made
with the CYP2A6*1/*1 individuals as the reference group as was done previously (Mwenifumbo
Jc, Al Koudsi N et al., 2008). In cases where there is only one individual who is homozygous for
the variant, they are combined with the heterozygous variant group for analyses. 2 Individuals with CYP2A6*1B were included in the reference group. 3 Compound heterozygotes, such as individuals with CYP2A6*4/*17 genotypes, were grouped as
having > 1 variant.
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Table 3: CYP2A6 allele frequencies in African-Americans in this population compared to our previous study in individuals of Black-African descent African-Americans
(n = 1236 alleles)
Black-African descent1
(n = 560 alleles)
CYP2A6 allele Frequency (%) Frequency (%) p – value
CYP2A6*1B 18.22 18.3 0.95
CYP2A6*2 0.9 0.4 0.22
CYP2A6*4 1.9 2.7 0.33
CYP2A6*9 9.6 7.2 0.09
CYP2A6*12 0.4 0.0 0.33
CYP2A6*17 8.0 7.3 0.61
CYP2A6*20 1.5 1.1 0.51
CYP2A6*23 1.1 2.0 0.16
CYP2A6*24 0.7 1.3 0.28
CYP2A6*25 0.9 0.5 0.43
CYP2A6*26 0.7 0.7 0.97
CYP2A6*27 0.7 0.2 0.15
CYP2A6*28 2.4 0.9 0.03
CYP2A6*35 2.9 2.5 0.62 1Data previously published in (Mwenifumbo Jc, Al Koudsi N et al., 2008) and (Al Koudsi,
Ahluwalia Js et al., 2009) 2CYP2A6*1B was genotyped only in individuals without other CYP2A6 variants examined in this
study (n = 297).
110
Fig.
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111
CYP2A6 genotype grouping strategy
Due to the large number of low prevalence CYP2A6 alleles, participants were categorized by the
predicted rate of CYP2A6 activity based on their genotype. This was done according to the
grouping strategy used in previous studies (Benowitz, Swan et al., 2006; Mwenifumbo Jc, Al
Koudsi N et al., 2008). Individuals with CYP2A6*28 were excluded from this analysis due to
extreme range in 3HC/COT values (Fig. 1A), suggesting some may also have gain-of-function
copy number variants which is under current investigation. CYP2A6 gene duplications
(CYP2A6*1x2A, *1x2B) leading to increased enzyme function have been described (Rao,
Hoffmann et al., 2000; Fukami et al., 2007). However, these duplications are rare in African-
Americans, occurring at < 2% allele frequencies. We genotyped 343 samples for CYP2A6*1x2A,
and 28 samples with high 3HC/COT ratios for CYP2A6*1x2B but did not find any individuals
with these gene duplication alleles.
Individuals with one copy of the decrease-of-function alleles (CYP2A6*9 and*12) were grouped
as IMs (n = 78). Individuals with two copies of the decrease-of-function alleles, one or two
copies of loss-of-function alleles (CYP2A6*2, *4, *17, *20, *23, *24,*25, *26, *27 and *35), or
one decrease-of-function allele with one loss-of-function allele were grouped as SMs (n = 213).
Although the genotype for CYP2A6*2, *23 and *24 were not in agreement with the phenotype
measure (3HC/COT), these individuals were categorized as SMs based on previous studies
demonstrating their functional impact (Benowitz, Swan et al., 2006; Ho, Mwenifumbo Jc et al.,
2008; Mwenifumbo Jc, Al Koudsi N et al., 2008).
3HC/COT was associated with CYP2A6 genotype
The 3HC/COT ratio was significantly associated with the CYP2A6 genotype groupings (F(2,
492) = 52.6, p < 0.001), and remained significant after controlling for gender, age and BMI as
112
covariates (F(2, 485) = 58.7, p < 0.001). The mean 3HC/COT ratio (± 95% CI) in the CYP2A6
genotype groups were: NM = 0.43 ± 0.04, IM = 0.32 ± 0.07, SM = 0.22 ± 0.02. The 3HC/COT
ratio was significantly lower in intermediate and slow metabolizers (IMs and SMs, respectively)
compared to the normal metabolizers (NMs) (p < 0.001, Fig. 1B). When we adjusted the ratio
for gender (mean ± 95% CI: NM = 1.27 ± 0.10, IM = 0.95 ± 0.20, SM = 0.64 ± 0.06, Fig 1C), we
observed similar adjusted values as were reported previously in our population of Black-African
descent (mean ± 95% CI: NM = 1.18 ± 0.10, IM = 0.77 ± 0.15, SM = 0.51 ± 0.10) (Mwenifumbo
Jc, Al Koudsi N et al., 2008).
Fig 1B) The unadjusted 3HC/COT ratio was significantly associated with CYP2A6 genotype groupings. Statistical analyses were performed on the log-transformed ratio with gender, age and BMI as covariates. It should be noted that since only 18 individuals were predicted to be poor metabolizers (completely lacking CYP2A6 function due to having two copies of loss-of-function alleles), they were combined with those predicted to have 10-50% activity to form the SM group. Fig 1C) The 3HC/COT ratio was also adjusted by gender as illustrated in our previous papers (Ho, Mwenifumbo Jc et al., 2008; Mwenifumbo Jc, Al Koudsi N et al., 2008). Adjustments were made by dividing each ratio by the mean value of their respective gender. For example, a male individual with an adjusted ratio greater than one indicates values that are higher than the mean ratio of all males. NM = normal metabolizers, IM = intermediate metabolizers, SM = slow metabolizers. The 3HC/COT when adjusted for the covariates (gender, BMI, and age) found to be significant in this population, using regression analyses, is as follows (mean ± 95%CI): NM = 0.44 ± 0.03, IM = 0.31 ± 0.05, SM = 0.22 ± 0.03). *** p < 0.001 when compared to the NMs. ## p < 0.01 when compared to IMs. The number of individuals are listed on the x – axis.
113
CYP2A6 activity and baseline smoking behaviours
The self-reported cigarettes per day (CPD) was not associated with CYP2A6 genotype groups
(F(2,585) = 0.26, p = 0.77) or 3HC/COT quartiles (F(3, 642) = 0.25, p = 0.86) (Fig. 2A, B).
Exhaled CO levels, a biochemical measure of cigarette smoke exposure, was also not associated
with CYP2A6 genotype groups (F(2, 584) = 3.0, p = 0.05) or 3HC/COT quartiles (F(3, 641) =
1.6, p = 0.18) (Fig. 2C, D).
In contrast to observations in heavy smokers (Schoedel, Hoffmann Eb et al., 2004), slow
CYP2A6 activity was associated with higher plasma NIC levels suggesting individuals were not
altering their cigarette intake to compensate for different rates of NIC metabolism. CYP2A6
SMs had significantly higher baseline plasma nicotine levels compared to NMs (F (2, 585) = 6.0,
p = 0.003) (Fig. 2E). Similarly, plasma NIC levels progressively increased corresponding to
3HC/COT quartiles (that is, with decreasing CYP2A6 activity), such that levels are lowest in the
first quartile (fastest CYP2A6 activity) and highest in the fourth quartile (slowest CYP2A6
activity) (F(3, 642) = 9.8, p < 0.001) (Fig. 2F). Plasma nicotine levels were significantly higher
among slow metabolizers in both males and females.
Neither CYP2A6 genotype (F(2, 584) = 0.08, p = 0.92) nor the 3HC/COT quartiles (F(3, 640) =
0.43, p = 0.73) were associated with age of onset of regular smoking. Tobacco dependence was
assessed by the Cigarette Dependence Scale (CDS) (Etter et al., 2003) and the Fagerström Test
for Nicotine Dependence (FTND) (Heatherton, Kozlowski Lt et al., 1991). CYP2A6 genotype
was not associated with scores from the CDS (F(2, 585) = 0.33, p = 0.72) or FTND (F(2, 585) =
0.37, p = 0.69). The 3HC/COT quartiles were also not associated with scores from the CDS
(F(3, 642) = 0.39, p =0.76) or FTND (F(3, 642) = 0.24, p = 0.87). Gender, age and BMI did not
alter any of the relationships listed above when included separately in the analysis as covariates.
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Fig. 2: Association of CYP2A6 activity with smoking indices. A, B) CYP2A6 genotype and 3HC/COT were not associated with self-reported CPD. C, D) CYP2A6 genotype and 3HC/COT were not associated with expired CO. E) CYP2A6 genotype was associated with nicotine plasma levels. **p < 0.01 when compared to NMs. F) 3HC/COT was associated with nicotine plasma levels. *p < 0.05, **p < 0.01 and *** p < 0.001 when compared to the 1st quartile. Individuals with 3HC/COT values in the 1st quartile have the fastest CYP2A6 activity, while those in the 4th quartile have the slowest CYP2A6 activity. Data are presented as mean ± 95% confidence interval. The number of individuals are listed on the x – axis.
115
CYP2A6 activity and smoking abstinence
Seven-day point prevalence abstinence – defined as having smoked no cigarettes, not even a puff
– for the previous 7 days, was assessed at week 8 (end-of-treatment, EOT) and week 26 (follow-
up), and verified by exhaled CO levels (≤ 10 ppm). Variables previously reported to be
predictors of abstinence in this population (counseling, gender, income, age, and BMI) (Nollen et
al., 2006), as well as drug treatment, were included in a multiple logistic regression model.
Consistent with previous analyses in this population (Nollen, Mayo Ms et al., 2006), MI
counseling and lower income (≤ $1,800) were associated with lower odds of quitting while male
gender, older age and higher BMI were associated with greater odds of quitting at both EOT and
follow-up (Table 4). CYP2A6 SMs trended towards being significantly more likely to quit
smoking at both EOT (p = 0.10) and follow-up (p = 0.08) compared to IMs and NMs combined
(Table 4, Fig. 3A). Individuals with the slowest 3HC/COT quartile trended towards having
greater odds of quitting at EOT (p = 0.08) and were significantly more likely to quit at follow-up
(p = 0.03) (Table 4, Fig. 3B). The effect of CYP2A6 activity on quit success appeared to be
more pronounced in females (Fig. 3C, D), and was observed in both the placebo and nicotine
gum arms among females (Fig. 3 E, F), but the gender interaction was not significant.
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Fig. 3: Association of CYP2A6 activity and smoking abstinence. A, B) Association of CYP2A6 genotype and 3HC/COT quartiles with CO-verified quit rates at EOT and follow-up. The NMs and IMs were pooled for analyses and compared to SMs. Individuals with highest 3HC/COT ratios in quartiles 1st to 3rd were pooled for analyses, and compared to individuals with 3HC/COT ratios in the lowest 25th percentile (4th quartile, slowest activity). C, D) Association of CYP2A6 genotype and 3HC/COT quartiles with CO-verified quit rates at EOT and follow-up by gender. E, F) Association of CYP2A6 genotype and 3HC/COT quartiles with CO-verified quit rates at EOT and follow-up by treatment arm. Only data in females is shown for Fig. 3E and F. The p-values listed were derived from univariate analyses of quit rates by categories of CYP2A6 activities; the results from the multivariate analysis is presented in Table 4.
117
Table 4: Logistic regression analyses of predictors of CO-verified quit rates at EOT (week 8) and follow-up (week 26) EOT Follow-up
Predictor1 Odds
ratio
95% CI p Odds
ratio
95% CI P
A) Genotype, n = 588
Genotype (SM)2 1.54 0.92 – 2.57 0.10 1.61 0.95 – 2.72 0.08
Drug (placebo) 0.62 0.41 – 0.93 0.02 0.62 0.40 – 0.94 0.03
Counseling (MI) 0.61 0.41 – 0.92 0.02 0.57 0.37 – 0.87 0.009
Gender (males) 1.68 0.99 – 2.85 0.05 1.83 1.07 – 3.15 0.03
Age 1.04 1.02 – 1.06 < 0.001 1.03 1.01 – 1.05 0.003
BMI 1.03 1.00 – 1.05 0.05 1.03 1.00 – 1.06 0.04
Income (≤ $1800) 0.59 0.39 – 0.88 0.01 0.74 0.49 – 1.13 0.16
B) 3HC/COT, n = 646
Quartile (slowest)3 1.61 0.94 – 2.76 0.08 1.85 1.08 – 3.16 0.03
Drug (placebo) 0.76 0.51 – 1.11 0.15 0.90 0.60 – 1.34 0.59
Counseling (MI) 0.72 0.49 – 1.06 0.10 0.56 0.37 – 0.83 0.005
Gender (males) 1.59 0.98 – 2.58 0.06 1.33 0.80 – 2.22 0.28
Age 1.04 1.02 – 1.06 < 0.001 1.03 1.01 – 1.05 0.002
BMI 1.01 0.99 – 1.04 0.32 1.02 0.99 – 1.05 0.14
Income (≤ $1800) 0.63 0.43 – 0.93 0.02 0.66 0.44 – 0.99 0.04 1 The odds ratio provided refers to the variable listed in brackets beside each categorical predictor. 2 The NM and IM group were combined for analyses and compared against the SM group. 3 Individuals in quartiles 1 to 3 (highest 3HC/COT ratios) were combined for analyses and compared against individuals in the 4th quartile (lowest 3HC/COT ratios).
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Discussion
This is the first study examining the relationship between CYP2A6 activity and smoking
behaviours in African-American light smokers. We provided further evidence that the
3HC/COT ratio derived from ab libitum smoking is a good phenotypic measure of CYP2A6
activity in this population as there was a good concordance with CYP2A6 genotypes. Our results
also suggest that in this sample of light smokers, cigarette consumption was not lowered to fully
compensate for slower rates of nicotine metabolism, and rather, higher plasma nicotine levels
were observed in slow metabolizers. The group with the slowest CYP2A6 activity trended
towards increased cessation success at EOT which reached significance at follow-up. This
suggests that slow CYP2A6 activity, and the resulting higher plasma nicotine levels, may
influence some aspect of the addiction process leading to greater cessation.
The 3HC/COT ratio is particularly useful as a phenotypic measure of CYP2A6 activity because
COT has a relatively long elimination half-life (~13 – 19 hours) and the level of 3HC is
formation-dependent (Benowitz and Jacob P 3rd, 1994). The 3HC/COT ratio, where metabolites
were derived from ab libitum smoking, is independent of the time of sampling (Lea, Dickson S et
al., 2006), does not vary widely within individuals over time (Lea, Dickson S et al., 2006;
Mooney, Li et al., 2008), and has been associated with CYP2A6 genotypes in heavy smoking
individuals of European-ancestry (Malaiyandi, Goodz et al., 2006). Our results and those in our
previous study (Mwenifumbo, Sellers et al., 2007; Mwenifumbo Jc, Al Koudsi N et al., 2008)
also indicate the ratio has good concordance with CYP2A6 genotype and rates of nicotine
metabolism in light smoking populations of Black-African descent. Our observation that the
CYP2A6*2, *23, *24 and *28 alleles were associated with 3HC/COT ratios higher than predicted
is likely due to other sources of variability in genotype and phenotype, combined with the small
number of individuals with these alleles. We estimated that to detect a 50% reduction in
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3HC/COT from the wildtype reference group (mean = 0.43) with a power of 0.80, assuming a
standard deviation of 0.25, we would need 11 individuals who have the variant of interest. There
may also be other unidentified genetic variation, such as gene duplications, and/or individuals
may have been exposed to CYP2A6 inducers. Information regarding the use of oral
contraceptives, a known CYP2A6 inducer (Benowitz, Lessov-Schlaggar Cn et al., 2006), was not
collected in this study.
The finding that the 3HC/COT ratio is higher in females is in agreement with previous data
(Benowitz, Lessov-Schlaggar Cn et al., 2006; Mwenifumbo, Sellers et al., 2007). Our
observation that the 3HC/COT ratio increases with age suggests CYP2A6 activity may be
increased among the elderly (Johnstone, Benowitz et al., 2006). BMI has also been negatively
correlated with the 3HC/COT ratio previously (Mooney, Li et al., 2008; Swan Ge et al., 2008),
though the relationship between obesity and CYP2A6 activity or nicotine pharmacokinetics have
not been well examined. Mentholated cigarettes have been shown to reduce nicotine metabolism
in smokers (Benowitz, Herrera et al., 2004). It is notable that mentholated cigarette smokers
were younger than non-mentholated cigarette smokers (42.5 vs. 50.0, p < 0.001). Thus, the
modest reduction in 3HC/COT among mentholated cigarette smokers may be attributed to an age
effect on CYP2A6 activity. Smoking menthol cigarettes did not significantly affect the ratio
after controlling for age, gender and BMI. In summary, in addition to CYP2A6 genetic variation,
male gender, younger age and higher BMI were also associated with slower CYP2A6 activity.
Because of the short half-life of nicotine, heavy smokers smoke regularly over the course of the
day to maintain sufficient levels in the body to avoid withdrawal symptoms. Accordingly,
smokers change their smoking behaviour when nicotine yield of cigarettes or rates of nicotine
elimination are altered experimentally (Scherer, 1999). However, light smokers, including our
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study population, are not smoking at regular intervals over the course of the day, and thus, their
plasma nicotine levels likely fluctuate widely. Accordingly, there was no relationship between
cigarette consumption and CYP2A6 activity, and SMs had higher plasma nicotine levels than
NMs, indicating a lack of full compensation for altered rates of nicotine metabolism. There is
evidence that smoking in chippers (≤ 5 CPD) is under greater stimulus control, i.e. smoking is
highly influenced by social and sensory motives and tends to be associated with specific
activities, such as after meals or drinking alcohol (Shiffman and Paty J, 2006). However, these
studies of chippers represent a distinct subset of smokers of European-ancestry, and further
investigation into the factors driving light smoking in African-Americans is necessary.
We did not observe a relationship between CYP2A6 activity and age of onset of regular
smoking. In any case, this is a relatively weak measure because it is generally limited by recall
bias. Similarly, while we did not see a relationship between CYP2A6 activity and CDS or
FTND scores, tobacco dependence is a complex, multi-dimensional construct and there are likely
aspects of dependence that were not captured by these scales, such as cravings to smoke. It was
recently reported that those with slow CYP2A6 activity may smoke less in response to cravings
and were less influenced by smoking-related cues (Piper, Mccarthy et al., 2008). Given the large
sample size of our study, it is unlikely that our negative findings result from a lack of statistical
power since associations have been reported in smaller studies of heavy smokers of European-
descent (Schoedel, Hoffmann Eb et al., 2004; Kubota, Nakajima-Taniguchi et al., 2006).
The finding that individuals with slow CYP2A6 activity had greater success at quitting
(significant at follow-up) is in agreement with recent findings in clinical trials of heavy smoking
individuals of European-ancestry. Individuals with 3HC/COT ratios in the slowest quartile had
significantly greater odds of quitting in the placebo arm of one study (Patterson, Schnoll et al.,
121
2008), which was further augmented by treatment with transdermal nicotine patch in another
study (Lerman, Tyndale et al., 2006) that was recently replicated (Schnoll, Patterson et al.,
2009). The observation of slow CYP2A6 activity and higher quit rates in the placebo arm of this
and the previous study suggests greater likelihood of cessation even in the absence of nicotine.
This is consistent with the observation that CYP2A6 slow metabolizers were more likely to be
former smokers (Gu, Hinks et al., 2000) and had shorter smoking durations (Schoedel, Hoffmann
Eb et al., 2004). The higher quit rates among CYP2A6 slow metabolizers were observed
primarily in females in this study. Because our sample had disproportionately more females
(67%), further replication of this effect in a sample with a larger number of males is necessary.
It is notable that significant associations between CYP2A6 activity and quit rates were observed
when individuals were identified by the 3HC/COT quartiles (p = 0.03 at follow-up, Table 4), and
only trended towards significance when categorized by CYP2A6 genotypes (p = 0.10 at EOT and
p = 0.08 at follow-up, Table 4). Given the large number of participants and the substantial
portion of African-Americans defined as genetically slow metabolizers (~36%), our study should
have been sufficiently powered. The difference between these two measures may be that the
ratio takes into account other sources of variation and/or because of additional unidentified
alleles. Large variation in the phenotype is observed among those defined as CYP2A6*1/*1 (i.e.
those without identified variants, Fig. 1A), suggesting additional variants may still be present.
Thus, CYP2A6 genotypes may have similar utility as 3HC/COT quartiles in predicting smoking
cessation in African-American light smokers in the future, particularly as we gain a better
understanding of the genetic variations in CYP2A6 in this population.
The results from the current and other recent retrospective studies (Lerman, Tyndale et al., 2006;
Patterson, Schnoll et al., 2008; Schnoll, Patterson et al., 2009) suggest that CYP2A6 activity may
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have important clinical utility in determining the type of smoking cessation treatment prescribed.
For example, individuals with faster CYP2A6 activity might be encouraged to use
pharmacotherapy to aid their quit attempts, given their lower quit rates on placebo compared to
slower metabolizers. In contrast, slow metabolizers may do well with behavioural therapy alone
and/or with nicotine patch treatment but may not benefit greatly from bupropion (Lerman,
Tyndale et al., 2006; Patterson, Schnoll et al., 2008; Schnoll, Patterson et al., 2009). Prospective
clinical trials have not yet been performed to directly assess whether the rate of CYP2A6 activity
will have utility in the personalization of smoking cessation therapy.
One of the strengths of this study is that we were able to associate CYP2A6 activity with
smoking behaviours and treatment outcomes using both genotype and phenotype measures in a
large population. A limitation of this study is that it was secondary analyses of a clinical trial
designed to test the efficacy of nicotine gum and counseling, and there was an overrepresentation
of females. In addition, this treatment-seeking sample of African-American light smokers may
not be representative of the general population as they are likely smokers who had difficulty
quitting in the past. Further studies are also necessary to determine whether the results are
applicable to other racial/ethnic populations, such as Hispanics, where light smoking is also
prevalent (Office of Applied Studies and Substance Abuse and Mental Health Services
Administration, 2006).
In conclusion, this study provides further evidence that the 3HC/COT ratio can serve as a
phenotypic marker of CYP2A6 activity, and gives new insights into the role of CYP2A6 in light
smoking in African-Americans. Confirmation of the validity of the 3HC/COT ratio derived from
baseline smoking as a phenotypic marker in light smoking populations will expand its utility for
future studies. Secondly, the ability of some individuals to maintain low levels of cigarette
123
consumption contradicts classical theories of tobacco addiction as driven by physical
dependence, and further research is needed to examine the biological and psychosocial context
underlying light smoking behaviours. There is no safe level of smoking, and a better
understanding of the phenomenon will lead to more effective intervention methods for this
unique group of smokers.
Significance to thesis
In our large sample of African-American light smokers, we confirmed the association between
CYP2A6 genotype groups and the 3HC/COT ratio derived from ad libitum smoking. This
provides further support that 3HC/COT is a good indicator of CYP2A6 activity in this
population. Furthermore, females, individuals with lower BMI, and those in the oldest age group
(aged 60 to 77) had significantly higher 3HC/COT, while this ratio did not differ between those
who smoke menthol or regular cigarettes. Identifying sources of variability in rates of CYP2A6
activity is important in helping explain the slower rates of nicotine and cotinine metabolism in
this population.
This study is the first to examine the role of CYP2A6 on smoking behaviours in African-
American light smokers. The ability of these individuals to maintain low levels of consumption
cannot be explained by prevailing theories of tobacco dependence, and very little is known about
the biological factors associated with smoking behaviours in this population. In contrast to
moderate to heavy smokers of Caucasian ancestry, CYP2A6 activity was not a predictor of the
amount of cigarettes smoked. However, similar to previous findings in moderate to heavy
smokers of Caucasian ancestry, slow CYP2A6 activity was associated with increased likelihood
of smoking cessation among this sample of African-American light smokers. Thus, these
smokers do not appear to be altering cigarette consumption to maintain nicotine levels, yet
124
CYP2A6 activity remained a predictor of smoking cessation. This suggests the processes
underlying tobacco dependence differ between CYP2A6 slow and normal metabolizers,
presumably as a result of varying nicotine levels, although the precise mechanism(s) by which
this is occurring is not yet clear.
An additional benefit of this study is that both CYP2A6 genotype and phenotype measures were
available as indicators of CYP2A6 activity. Similar results were observed using either measures
of CYP2A6 activity, although the effect of CYP2A6 genotype on smoking abstinence only
trended towards significance. Determining whether genotype or phenotype measures are better
predictors of smoking cessation is important as the rate of CYP2A6 activity may potentially be
used to optimize treatment paradigms for African-American light smokers in the future. This
treatment-seeking population of African-American light smokers achieved poor quit rates in
spite of their high motivation to quit, providing further support that these smokers have difficulty
quitting despite their lower levels of cigarette consumption. This highlights the complexity of
tobacco dependence and the need to develop successful smoking cessation intervention programs
for this understudied group of smokers.
125
Supplementary information Supplementary Table 1: Participant demographics. Data are presented as mean (SD). Total
n = 755 3HC/COT n = 646
Genotype n = 588
Genotype and 3HC/COT n = 495
Gender, % females 66.9% 68.0% 67.5% 69.7% Age, yrs 45.1 (10.7) 45.1 (10.9) 44.9 (10.9) 45.0 (11.2)
Range 19 – 81 19 – 81 19 – 81 19 – 81
BMI 30.6 (8.1) 30.5 (8.0) 30.6 (8.0) 30.5 (8.0) Range 14 – 74 14 – 74 14 – 74 14 – 74
Menthol cigarettes, % yes 81.7% 80.3% 82.8% 81.0% CPD 7.6 (3.2) 7.6 (3.1) 7.5 (3.4) 7.6 (3.3)
Range 0 – 30 0 – 30 0 – 30 0 – 30
Baseline CO, ppm 13.9 (8.9) 13.8 (8.8) 14.0 (9.2) 13.9 (9.3) Range 0 – 69 0 – 69 0 – 69 0 – 69
Baseline NIC, ng/ml 12.1 (8.9) 12.3 (8.9) 12.2 (8.9) 12.4 (9.0)
Range 0.5 – 46 0.5 – 46 0.5 – 46 0.5 – 46
Baseline COT, ng/ml 244.2 (154.4) 249.8 (153.6) 245.5 (157.5) 252.9 (158.4) Range 5 – 938 5 – 938 5 – 938 5 – 938
Age of regular smoking 21.1 (6.9) 21.1 (6.8) 21.2 (7.1) 21.2 (6.9)
Range 7 – 55 7 – 55 7 – 55 7 – 55
CDS 15.0 (3.7) 15.0 (3.7) 15.0 (3.7) 15.0 (3.7) Range 4 – 22 4 – 22 4 – 22 4 – 22
FTND 2.9 (1.8) 2.9 (1.8) 2.9 (1.8) 2.9 (1.8)
Range 0 – 9 0 – 9 0 – 9 0 – 9
126
CHAPTER 3: UTILITY AND RELATIONSHIPS OF BIOMARKERS OF SMOKING IN
AFRICAN-AMERICAN LIGHT SMOKERS
Man Ki Ho, Babalola Faseru, Won S. Choi, Nicole L. Nollen, Matthew S. Mayo,
Janet L. Thomas, Kolawole S. Okuyemi, Jasjit S. Ahluwalia, Neal L. Benowitz, Rachel F.
Tyndale
Reprinted with permission from American Association for Cancer Research: Cancer
Epidemiology Biomarkers and Prevention, 18(12): 3426-3434, 2009. © 2010 All rights reserved.
Drs. Kolawole Okuyemi, Jasjit Ahluwalia, Neal Benowitz and Rachel Tyndale designed and
recruited the participants in this clinical trial with the primary aim of testing the efficacy of 2 mg
nicotine gum and two different counseling methods for smoking cessation in a population of
African-American light smokers. The levels of nicotine, cotinine and trans-3-hydroxycotinine in
plasma samples were determined in the laboratory of Dr. Neal Benowitz. Drs. Babalola Faseru,
Won S. Choi, Nicole L. Nollen, Matthew S. Mayo, Janet L. Thomas were responsible for storing
and maintaining the database of information collected from participants, and provided helpful
feedback for the preparation of the manuscript. MKH performed a substantial portion of the
DNA extraction and CYP2A6 genotyping, was responsible for determining the research questions
of interest, performed all statistical analyses and wrote the manuscript.
127
Abstract
While expired carbon monoxide (CO) and plasma cotinine (COT) have been validated as
biomarkers of self-reported cigarettes per day (CPD) in heavy smoking Caucasians, their utility
in light smokers is unknown. Further, variability in CYP2A6, the enzyme that mediates
formation of COT from nicotine (NIC) and its metabolism to trans-3’-hydroxycotinine (3HC),
may limit the usefulness of COT. We assessed whether CO and COT are correlated with CPD in
African-American light smokers (≤10CPD, n=700), a population with known reduced CYP2A6
activity and slow COT metabolism. We also examined whether gender, age, BMI, smoking
mentholated cigarettes or rate of CYP2A6 activity, by genotype and phenotype measures
(3HC/COT), influence these relationships. At baseline, many participants (42%) exhaled CO
≤10ppm, the traditional cutoff for smoking, while few (3.1%) had COT below the cutoff of
≤14ng/ml; thus COT appears to be a better biomarker of smoking status in this population. CPD
was weakly correlated with CO and COT (r = 0.32–0.39, p<0.001), and those reporting fewer
CPD had higher CO/cigarette and COT/cigarette, although the correlation coefficients between
these variables were also weak (r = -0.33 and -0.08, p < 0.05). The correlation between CPD and
CO was not greatly increased when analyzed by CYP2A6 activity, smoking mentholated
cigarettes or age, although it appeared stronger in females (r = 0.38 vs.0.21, p<0.05) and obese
individuals (r = 0.38 vs.0.24, p<0.05). Together, these results suggest that CO and COT are
weakly associated with self-reported cigarette consumption in African-American light smokers,
and that these relationships are not substantially improved when variables previously reported to
influence these biomarkers are considered.
Introduction
Biomarkers of cigarette smoke exposure have been utilized to confirm self-reported smoking
measurements. Two commonly used measures are cotinine (COT) and exhaled carbon
128
monoxide (CO). COT, a metabolite of nicotine (NIC), is detected in a number of biological
fluids (i.e. plasma, saliva and urine) and is highly specific to NIC exposure (Benowitz, Peyton J
Iii et al., 2002). However, COT is not specific to cigarette smoke as individuals exposed to
alternative sources of tobacco or nicotine replacement therapy will also have detectable COT
(Benowitz, Peyton J Iii et al., 2002). The traditional cut-off value for differentiating smokers
from non-smokers is plasma or salivary COT levels of ≤ 14 ng/ml (Jarvis et al., 1987; Benowitz,
Peyton J Iii et al., 2002). COT has a relatively long half-life (13 – 19 hrs) and reflects exposure
to tobacco within the past 3 – 4 days (Benowitz, Peyton J Iii et al., 2002; Hukkanen, Jacob et al.,
2005). CO is a byproduct of the combustion of tobacco, and a cutoff value for CO of ≤ 10 ppm
is traditionally used to distinguish smokers from non-smokers (Benowitz, Peyton J Iii et al.,
2002; Scherer, 2006). However, CO is not specific to tobacco smoke exposure and contributions
from environmental sources (such as vehicle exhaust) and endogenous formation of CO from
heme catabolism can limit its use (Scherer, 2006). CO has a short half-life of approximately 1 –
4 hours (Scherer, 2006) and reflects more recent exposure to smoking; it is highly dependent on
the time of the last cigarette.
Several prior studies have confirmed the utility of both COT and CO levels to verify self-
reported cigarette consumption, with correlation coefficients ranging from 0.3 – 0.8 (Perez-
Stable et al., 1995; Domino et al., 2002; Mustonen, Spencer Sm et al., 2005; Scherer, 2006).
However, these studies have been performed primarily among Caucasian moderate to heavy
smokers. It is unknown whether these biomarkers are representative of cigarette consumption
among light smokers where smoking levels are lower and occur at irregular intervals. In
particular, the short half-life of CO, and its lack of specificity, may make it difficult to
differentiate light smoking from non-smoking. While the longer half-life of COT may make it a
suitable marker among light smokers, it may be influenced by variable rates of its metabolism.
129
COT is the main proximate metabolite of nicotine (NIC) (Benowitz and Jacob P 3rd, 1994), and
COT itself is further metabolized to trans-3’-hydroxycotinine (3HC) (Nakajima, Yamamoto T et
al., 1996; Dempsey, Tutka et al., 2004). The conversion of NIC to COT, and COT to 3HC, are
primarily mediated by the enzyme cytochrome P450 2A6 (CYP2A6) (Messina, Tyndale et al.,
1997). Large interindividual variability in CYP2A6 activity has been reported (Mwenifumbo and
Tyndale, 2007). The gene encoding CYP2A6 is highly polymorphic, with 38 numbered alleles
identified so far (http://www.cypalleles.ki.se/cyp2a6.htm). To aid in population studies, the
3HC/COT ratio (which can be measured in plasma, saliva or urine), has been validated as a
phenotypic indicator of CYP2A6 activity (Dempsey, Tutka et al., 2004). COT levels are
potentially influenced by a number of factors that alter CYP2A6 activity, including genetic
variation, the presence of enzyme inducers or inhibitors, body mass index (BMI), age, and
gender. For instance, African-Americans have higher COT plasma levels than Caucasian
smokers even after controlling for number of cigarettes smoked (Caraballo, Giovino et al., 1998).
This can be partly attributed to their slower rates of COT metabolism (Benowitz, Perez-Stable et
al., 1999); approximately 50% of African-Americans have decrease- or loss-of-function CYP2A6
genetic variants compared to approximately 20% of Caucasians (Mwenifumbo and Tyndale,
2007; Ho, Mwenifumbo et al., 2009). Furthermore, a large proportion of African-Americans
smoke mentholated cigarettes, and it has been suggested that the cooling sensation may result in
deeper, longer inhalation and larger puff volumes (Werley, Coggins et al., 2007). Some studies,
but not all, have found higher CO and COT levels among mentholated cigarette users (Werley,
Coggins et al., 2007).
There is also evidence menthol can inhibit CYP2A6 in vitro and mentholated cigarette smokers
have slower rates of NIC metabolism (Macdougall, Fandrick et al., 2003; Benowitz, Herrera et
130
al., 2004). Individuals with higher BMI have been found to have lower COT levels (Perez-
Stable, Benowitz Nl et al., 1995; Ahijevych et al., 2002), and older age has been associated with
higher levels of COT (Swan et al., 1993; Patterson et al., 2003). Females are known to have
faster rates of NIC and COT metabolism (Benowitz, Lessov-Schlaggar Cn et al., 2006), with
estrogen being an inducer of CYP2A6 (Higashi, Fukami et al., 2007).
In this study, we examined whether biomarkers derived from ad libitum smoking are associated
with self-reported cigarette consumption in a population of African-American light smokers, a
population with unique smoking characteristics. The need for validated biomarkers for this
specific population is warranted as the prevalence of light smoking is particularly common
among African-Americans, with up to 50% reporting ≤ 10 CPD compared to 18-20% of the
general smoking population (Okuyemi Ks, Harris Kj et al., 2002). We also examined whether
variables previously known to affect biomarker levels, such as rate of CYP2A6 activity (by
genotype and 3HC/COT phenotype measure), gender, smoking mentholated cigarettes, BMI or
age influenced these relationships. While CYP2A6 genotype was not found to substantially
influence the relationships between biomarkers and cigarette consumption in a previous study of
Caucasian heavy smokers (Malaiyandi, Goodz et al., 2006), the proportion of individuals with
CYP2A6 genetic variants was low. It is possible that the high prevalence of CYP2A6 decrease-
or loss-of function genetic variants and slower rates of COT metabolism among African-
Americans may play a greater role in this population.
Materials and Methods
Study design
131
A detailed description of the study design and participant recruitment can be found elsewhere
(Ahluwalia, Okuyemi et al., 2006; Ho, Mwenifumbo et al., 2009). Briefly, participants (n = 755)
were randomized into a double-blind, placebo-controlled smoking cessation study at a
community health centre in Kansas City, Missouri. Participants (≥ 18 years of age) self-
identified as “African-American” or “Black”, smoked ≤10 CPD for at least 6 months prior to
enrollment, and smoked at least 25 of the past 30 days were recruited. The research protocol was
approved by the University of Toronto Ethics Review Office and the University of Kansas
Human Subjects Committee.
Baseline assessment
Information regarding the participant’s demographic, smoking and psychosocial characteristics
have been described in detail elsewhere (Nollen, Mayo Ms et al., 2006). Age, gender, and BMI
were collected at randomization. Participants were asked about their smoking patterns, including
the number of CPD, mentholated vs. non-mentholated cigarette use, depth of inhalation, and
number of years smoked. Participants were asked to estimate their cigarette consumption by the
question: “During the past 7 days, on those days that you smoked, what was the average number
of cigarettes smoked per day?” Although all of the participants recruited into the clinical trial
reported smoking ≤ 10 CPD on the eligibility questionnaire, a small subset of participants
reported consuming zero or > 10 CPD during the past week during the randomization assessment
(n = 55) and thus were excluded from analyses in the current study.
Biochemical measures
A blood sample was collected at randomization to determine the levels of NIC and its
metabolites, and for genotyping purposes. Plasma levels of NIC, COT and 3HC were
determined using the methods described elsewhere (Dempsey, Tutka et al., 2004), although 3HC
132
levels were only available for a subset of the participants (n = 602 out of 700). Expired CO
levels were measured by a handheld portable CO monitor (Bedfont Micro Smokerlyzer, Kent,
England).
CYP2A6 genotyping
CYP2A6 genotyping for this population was performed using two-step allele-specific polymerase
chain reaction assays as described previously (Ho, Mwenifumbo et al., 2009). A subset of the
total participants consented to have their blood sampled for genetic analyses, and genotyping
data was available for 570 of the 700 participants. Participants were genotyped for CYP2A6*1B,
*2, *4, *9, *12, *17, *20, *23, *24, *25, *26, *27, *28, and *35 (Ho, Mwenifumbo et al., 2009).
Individuals were categorized into groups based on their predicted effects of their CYP2A6
genotypes on rates of activity as previously described (Ho, Mwenifumbo et al., 2009). Those
with one copy of the decrease-of-function alleles (CYP2A6*9 and *12) were grouped as
intermediate metabolizers (n = 70). Individuals with two copies of the decrease-of-function
alleles, one or two copies of loss-of-function alleles (CYP2A6*2, *4, *17, *20, *23, *24, *25,
*26, *27 and *35), or one decrease-of-function allele with one loss-of-function allele were
grouped as slow metabolizers (n = 197). Normal metabolizers (n = 275) were individuals
without these genetic variants. Those with CYP2A6*1B (n = 89) were also included in the normal
metabolizer group as previously described (Ho, Mwenifumbo et al., 2009). Individuals with
CYP2A6*28 (n = 28) were excluded from analyses due to extreme range in 3HC/COT values,
suggesting some may also have gain-of-function copy number variants which is currently under
investigation.
Statistical analyses
133
Statistical analyses were performed using SPSS statistical software, version 16.0. The data
(CPD, CO, NIC, COT, 3HC, 3HC/COT, BMI) were not normally distributed according to the
Kolmogorov-Smirnov test and were log-transformed when appropriate. Pearsons’s correlation
coefficient was used to examine the relationships between log-transformed CPD, CO, and COT
with CO/cigarette, COT/cigarette. Differences in log-transformed CPD, CO or COT between
gender, use of mentholated cigarettes, and BMI as categorized by those considered obese (BMI ≥
30) versus non-obese (BMI < 30), were tested using the t-test for independent samples.
Differences in CPD, CO or COT between CYP2A6 genotype groups, 3HC/COT quartiles, and
age categories were examined using univariate analysis of variance with Bonferroni correction
for post hoc analyses. Pearson’s correlations between log-transformed CPD, CO or COT with
age and log-transformed 3HC/COT and BMI as continuous variables were also examined.
Differences between Pearson’s correlation coefficients were tested using the Fisher r-to-z
transformation. A multiple linear regression model was used to examine the predictors of
baseline CPD, CO and COT. Variables included in the model were significant in univariate
analyses (p < 0.10), and variables that were not normally distributed (CPD, CO, COT, BMI,
3HC/COT) were log-transformed in the analyses.
Results
Participant demographics
A summary of the participant demographics, smoking history and biochemical measures can be
found in Table 1. The study sample was overrepresented by females (66.7%), and the majority
smoked menthol cigarettes (81.3%). A histogram of the CPD, expired CO and plasma COT
from baseline smoking is found in Fig. 1 A-C. Many participants (42%, n = 294) had expired
CO values of ≤ 10 ppm, the traditional cutoff for differentiating between smokers from non-
smokers. In contrast, few individuals had plasma COT levels below the widely used cutoff value
134
of 14 ng/ml (3.1%, n = 22) (Benowitz, Peyton J Iii et al., 2002; Hukkanen, Jacob et al., 2005), or
below the cutoff of 20 ng/ml used to verify smoking abstinence in this clinical trial (3.9%, n =
27) (Ahluwalia, Okuyemi et al., 2006).
Table 1: Participant characteristics
N§ Mean SD Min Max CPD 700 7.2 2.4 1.0 10.0 Expired CO (ppm) 699 13.7 8.7 0.0 69.0 Plasma NIC (ng/ml) 699 12.1 8.8 0.5 46.4 Plasma COT (ng/ml) 699 243.7 152.8 5.0 937.8 Plasma 3HC (ng/ml) 602 74.5 63.7 1.2 720.0 Age (yrs) 698 45.0 10.7 19.1 81.3 BMI 697 30.5 8.0 14.0 73.5 N§ % Gender
Males 233 33.3 Females 467 66.7
Mentholated cigs
Yes 569 81.3 No 131 18.7
Depth of inhalation (Self-reported)
Deep into chest 163 23.4 Partly into chest 220 31.5
To back of throat 143 20.5 To back of mouth 129 18.5
Puff only 43 6.2 §
Number of participants with data available for each variable. SD = standard deviations
Relationship between expired CO, plasma COT and CPD
CPD was significantly, albeit weakly, correlated with expired CO (Pearson’s r = 0.32, p < 0.001)
and with plasma COT (Pearson’s r = 0.39, p < 0.001) (Fig 1D, E). Expired CO and plasma COT
were also significantly correlated with each other (Pearson’s r = 0.60, p < 0.001) (fig 1F). We
examined the ratio of expired CO or plasma COT to self-reported values of cigarettes smoked as
indicators of the extent of inhalation. CPD was poorly correlated with CO/cigarette (Pearson’s r
= -0.33, p < 0.001, fig 1G) and COT/cigarette (Pearson’s r = -0.08, p < 0.05, fig 1H).
135
Variables that influence CPD, expired CO and plasma COT
CYP2A6 slow metabolizers, as defined by genotype, had significantly higher plasma COT levels
compared to normal metabolizers (p < 0.01), although CYP2A6 genotype was not associated with
CPD or expired CO levels (Table 2, Fig. 2 A-C). Similarly, individuals with 3HC/COT ratios in
quartile 1, representing those with slowest rate of CYP2A6 activity, also had significantly higher
plasma COT levels compared to those in quartiles 2 – 4 (p < 0.001), although the 3HC/COT ratio
was not significantly associated with either CPD or expired CO (Table 2, Fig. 2 D-F). CYP2A6
slow metabolizers by genotype were also found to have significantly higher plasma NIC (p <
0.001) and 3HC levels (p < 0.001), and those in the slowest 3HC/COT quartile had significantly
higher plasma NIC and 3HC levels compared to those with the fastest metabolic activity (p <
0.001).
No gender difference was found for CPD or expired CO, though females trended towards higher
plasma COT levels (p = 0.09, Table 2). Those who smoked mentholated cigarettes trended
towards reporting fewer CPD compared to those who did not (p = 0.05), although no difference
was found for expired CO or plasma COT levels between mentholated and non-mentholated
cigarette smokers. Obese individuals (BMI ≥ 30) smoked fewer cigarettes (p < 0.05) and had
136
Fig 1 (A – C): Histogram of self-reported CPD and the biomarkers expired CO and plasma COT
for study participants (n = 700). Cutoff values of expired CO at ≤ 10 ppm and plasma COT
levels of ≤ 14 ng/ml have been traditionally used to differentiate smokers from non-smokers.
Correlations are weak but significant between expired CO with CPD (D), plasma COT with CPD
(E), and plasma COT with CO (F). Correlations are also significant between CO/cigarette with
CPD (G) and COT/cigarette with CPD (H). Each point represents an individual. r = Pearson’s
correlation coefficient. Analyses were performed on log-transformed variables (CPD, expired
CO, plasma COT) although raw data is plotted.
137
Tabl
e 2:
Var
iabl
es th
at in
fluen
ces C
PD, e
xpire
d C
O o
r pla
sma
CO
T le
vels
CPD
Ex
pire
d C
O (p
pm)
Plas
ma
CO
T (n
g/m
l) V
aria
ble
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e C
YP2A
6 ge
noty
pe
NM
7.
04
2.51
27
5 0.
85
14.3
3 9.
24
274
0.13
22
1.74
14
6.31
27
5 0.
002
IM
6.97
2.
56
70
11
.94
6.90
70
249.
17
149.
06
70
SM
7.
14
2.44
19
7
13.5
3 9.
22
197
2
72.6
3*
165.
17
197
3HC
/CO
T ra
tio
Pear
son’
s r
p-va
lue
Pear
son’
s r
p-va
lue
Pear
son’
s r
p-va
lue
Cor
rela
tions
0.
001
0.98
-0
.06
0.12
-0
.28
<0.0
01
C
ateg
oric
al
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e Fa
stes
t - Q
uarti
le 4
7.
22
2.50
15
1 0.
98
12.9
5 9.
35
151
0.28
18
9.25
12
7.20
15
1 <0
.001
Q
uarti
le 3
7.
28
2.48
15
0
14.4
5 9.
72
150
25
5.45
14
7.85
15
0
Qua
rtile
2
7.07
2.
35
151
14
.10
8.52
15
1
265.
94
146.
61
151
S
low
est -
Qua
rtile
1
7.22
2.
44
150
12
.89
6.88
15
0
278
.62†
170.
57
150
Gen
der
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e M
ales
7.
04
2.55
23
3 0.
27
13.4
2 8.
19
233
0.63
23
1.79
15
0.28
23
3 0.
09
Fem
ales
7.
20
2.38
46
7
13.8
8 8.
98
466
24
9.60
15
3.84
46
6
M
enth
ol c
igs
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e Y
es
7.07
2.
46
569
0.05
13
.49
8.28
56
9 0.
51
242.
93
150.
55
568
0.55
N
o 7.
53
2.32
13
1
14.7
4 10
.42
131
24
6.84
16
2.71
13
1
B
MI
Pear
son’
s r
p-va
lue
Pear
son’
s r
p-va
lue
Pear
son’
s r
p-va
lue
Cor
rela
tions
-0
.03
0.39
-0
.11
0.
004
0.00
3 -0
.19
<0.0
01
C
ateg
oric
al
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e Lo
w (<
30.
0)
7.35
2.
41
381
0.02
14
.35
8.74
38
0 0.
01
268.
19
156.
37
380
<0.0
01
Hig
h (≥
30.
0)
6.90
2.
46
316
12
.97
8.70
31
6
213.
57
142.
65
316
138
Tabl
e 2
(con
tinue
d)
CPD
Ex
pire
d CO
(ppm
) Pl
asm
a CO
T (n
g/m
l) V
aria
ble
Age
Pe
arso
n’s r
p-
valu
e Pe
arso
n’s r
p-
valu
e Pe
arso
n’s r
p-
valu
e Co
rrela
tions
0.
05
0.21
-0
.001
0.
97
0.04
0.
34
Ca
tego
rical
M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
19 –
29
6.32
2.
27
60
0.18
11
.72
5.68
60
0.
95
226.
17
147.
88
60
0.42
30
– 3
9 7.
20
2.36
14
8
14.1
4 9.
80
148
24
1.29
14
9.26
14
8
40 –
49
7.16
2.
48
280
13
.75
8.54
28
0
239.
85
158.
70
279
50
– 5
9 7.
41
2.45
15
8
13.7
7 8.
30
157
25
5.99
15
1.70
15
8
60 –
77
7.04
2.
51
52
14
.29
10.3
1 52
248.
82
141.
69
52
Dep
th o
f Inh
alat
ion
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e In
to c
hest
7.31
2.
45
383
0.13
14
.00
9.08
38
3 0.
61
242.
19
156.
54
382
0.50
Pu
ff/th
roat
onl
y 6.
96
2.43
31
5
13.3
9 8.
30
315
24
5.78
14
8.78
31
5
O
ther
smok
ers a
t ho
me
Mea
n SD
N
p-
valu
e M
ean
SD
N
p-va
lue
Mea
n SD
N
p-
valu
e
Yes
7.
00
2.37
42
6 0.
61
13.4
1 8.
28
425
0.79
25
6.01
16
0.08
42
6 0.
19
No
7.24
2.
48
274
13
.93
9.00
27
4
235.
75
147.
58
273
*
deno
tes
stat
istic
al s
igni
fican
ce in
pla
sma
CO
T le
vels
in N
Ms
vs. S
Ms;
† de
note
s st
atis
tical
sig
nific
ance
in p
lasm
a C
OT
leve
ls in
Qua
rtile
4 (f
aste
st a
ctiv
ity) v
s. Q
uarti
le 1
(slo
wes
t act
ivity
). N
o si
gnifi
cant
diff
eren
ces i
n pl
asm
a C
OT
leve
ls w
ere
foun
d be
twee
n IM
vs. N
M o
r SM
s, or
bet
wee
n th
e ot
her q
uarti
les.
Raw
dat
a ar
e lis
ted
alth
ough
sta
tistic
al a
naly
ses
wer
e pe
rfor
med
on
log-
trans
form
ed
data
for C
PD, e
xpire
d C
O a
nd p
lasm
a C
OT.
NM
= n
orm
al m
etab
oliz
ers,
IM =
inte
rmed
iate
met
abol
izer
s, SM
= s
low
met
abol
izer
s,
SD =
stan
dard
dev
iatio
n.
139
Fig 2: Relationship between CYP2A6 activity, CPD, expired CO, and plasma COT. Self-
reported CPD and expired CO did not differ by CYP2A6 genotype (A, B) or 3HC/COT quartiles
(D, E), while CYP2A6 slow metabolizers had significantly higher plasma COT levels compared
to normal metabolizers (* p < 0.01, C) and those in the slowest 3HC/COT quartile (1st quartile)
had significantly higher plasma COT levels compared to those in the fastest quartile (4th quartile)
(#, p < 0.001, F). NM = normal metabolizers, IM = intermediate metabolizers, SM = slow
metabolizers. Analyses were performed on log-transformed variables (CPD, expired CO, plasma
COT) although raw data are plotted.
140
lower levels of expired CO (p < 0.05) and COT (p < 0.001). BMI was not significantly
correlated with CPD, but a negative correlation was found between BMI and expired CO (p <
0.01), and between BMI and plasma COT (p < 0.001). CPD, expired CO and plasma COT were
not significantly associated with age, either by correlation analyses or when examined
categorically. We did not find significant differences in CPD, expired CO or plasma COT by
self-reported inhalation patterns or the presence of other smokers in the home (Table 2).
Variables that influence relationships between CPD and expired CO with NIC and its
metabolites
The correlation coefficients between CPD and expired CO with plasma NIC and its metabolites
were not greatly altered by CYP2A6 genotype or 3HC/COT quartiles (Table 3). Similarly, these
relationships were generally not altered when analyzed separately by gender, mentholated
cigarettes, BMI or age. However, it is notable that the correlation between CPD and expired CO
was stronger in females compared to males (Pearson’s r = 0.38 vs. 0.21, respectively, p < 0.05)
and in obese (BMI ≥ 30) compared to non-obese individuals (Pearson’s r = 0.38 vs. 0.24,
respectively, p < 0.05). No difference was observed for the correlations between CPD and
plasma COT by gender or BMI.
In a multiple regression model including the predictors of CPD that were significant in univariate
analyses (p < 0.10), plasma COT (β = 0.31) and expired CO (β = 0.13) remained significant (p <
0.01) while age and BMI were no longer significant, and the trend of mentholated cigarette use
associating with fewer CPD remained (Table 4). Together, these predictors accounted for 17%
of the variance in CPD.
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Table 3: Correlations (r) between biomarkers and cigarette consumption by variables When analyzed separately by variables of interest Total
population (n = 700)
CYP2A6*1/*1 only
(n = 275)
CYP2A6 variants only
(n = 267)
3HC/COT§ Quartiles 2 – 4
(n = 451)
Slowest quartile§
(n = 151) CPD Expired CO 0.32 0.30 0.33 0.28 0.36 Plasma NIC 0.31 0.33 0.33 0.30 0.22 Plasma COT 0.39 0.40 0.44 0.39 0.33 Plasma 3HC§ 0.31 0.36 0.31 0.39 0.27 Expired CO Plasma NIC 0.63 0.65 0.61 0.61 0.61 Plasma COT 0.60 0.62 0.59 0.59 0.50 Plasma 3HC§ 0.45 0.52 0.39 0.54 0.44
Total population (n = 700)
Males
(n = 233)
Females
(n = 467)
Smoke non-mentholated cigs
(n = 131)
Smoke mentholated cigs
(n = 569) CPD Expired CO 0.32 0.21 0.38 0.38 0.30 Plasma NIC 0.31 0.31 0.31 0.32 0.31 Plasma COT 0.39 0.36 0.41 0.37 0.40 Plasma 3HC§ 0.31 0.21# 0.36 0.36 0.30 Expired CO Plasma NIC 0.63 0.63 0.63 0.65 0.62 Plasma COT 0.60 0.63 0.59 0.59 0.61 Plasma 3HC§ 0.45 0.33 0.50 0.46 0.45
Total population (n = 700)
Low BMI (< 30.0) (n = 381)
High BMI (≥ 30.0)
(n = 316)
Younger age (< 44.8)
(n = 349)
Older age (> 44.8) (n = 349)
CPD ExpiredCO 0.32 0.24 0.38 0.27 0.35 Plasma NIC 0.31 0.27 0.34 0.28 0.34 Plasma COT 0.39 0.34 0.43 0.36 0.42 Plasma 3HC§ 0.31 0.29 0.33 0.31 0.32 Expired CO Plasma NIC 0.63 0.61 0.64 0.66 0.59 Plasma COT 0.60 0.54 0.65 0.61 0.59 Plasma 3HC§ 0.45 0.40 0.51 0.54 0.38
Values listed are Pearson’s correlation coefficients calculated on log-transformed variables (CPD, expired CO, plasma NIC, COT, 3HC); all were significant at p < 0.001 with the exception of the value marked as #, which was significant at p < 0.01. §3HC data were available for a subset of the participants only.
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Table 4: Multiple linear regression models of the predictors of CPD, expired CO and plasma COT Dependent variable: CPD (n = 700), R2 = 0.17 Predictor B 95% CI Standardized β p-value Plasma COT 0.15 0.11 – 0.19 0.32 <0.001 Expired CO 0.09 0.03 – 0.15 0.12 0.004 Mentholated cigs -0.03 -0.06 – 0.00 -0.07 0.05 BMI 0.08 -0.04 – 0.20 0.05 0.21 Non-mentholated cigarette users were coded as 0. Variables that were not normally distributed (CPD, expired CO, plasma COT, BMI) were log-transformed in the analyses.
Discussion
In this population of African-American light smokers, where approximately one-third consume ≤
5 CPD, two commonly used biomarkers of cigarette smoke exposure, expired CO and plasma
COT, were significantly correlated with self-reported CPD. However, the strength of the
correlations were relatively weak (r ~ 0.31 – 0.37), and in a multiple regression model, only
~17% of the variance in CPD was explained by plasma COT and expired CO. This is in contrast
to heavy smoking Caucasian populations, where correlation coefficients from 0.3 – 0.8 have
been reported (Perez-Stable, Benowitz Nl et al., 1995; Domino and Ni L, 2002; Mustonen,
Spencer Sm et al., 2005; Scherer, 2006). Self-reported number of cigarettes smoked per day is a
limited indicator of exposure as there is a nonlinear relationship between biomarkers and CPD,
with a plateau observed at higher levels of consumption (>20 – 25 CPD) (Joseph et al., 2005).
Heavy smokers reporting consumption at these levels appear to smoke each cigarette with less
intensity (Joseph, Hecht et al., 2005; Malaiyandi, Goodz et al., 2006). Thus, self-reported
measures of CPD may not be representative of exposure particularly at extremely high or low
levels of smoking.
It would have been ideal to compare our findings with a matched group of Caucasian light
smokers from a clinical trial (e.g. treatment seekers) to determine whether the weaker
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correlations between the biomarkers and self-reported cigarette consumption in this study were
reflective of variables that were specific to African-Americans, or resulted from the narrow range
in cigarettes consumed. However, established light smoking patterns among adults are less
common among Caucasians, and the clinical trial from which participants in the current study
was drawn is the only published one to date to have recruited specifically light smokers (≤ 10
CPD) (Stead, Perera R et al., 2008). To partially address this issue, we analyzed a subset of
Caucasian smokers that reported ≤ 10 CPD in our previously published biomarkers paper
(Malaiyandi, Goodz et al., 2006). Despite the considerably smaller numbers in this subset
analyses (N = 40 vs. 152) the correlation coefficients appeared higher in the Caucasian light
smokers. Specifically, the Pearson’s correlation coefficient between CO with CPD (r = 0.37, p =
0.02) was similar, while the correlations between COT with CPD (r = 0.51, p < 0.001), and CO
with COT (r = 0.77, p < 0.001) were stronger than in African American light smokers (r = 0.32,
0.39 and 0.60 respectively, Fig 1). The correlations between CO and CPD were improved when
the total sample of Caucasians in that study (n = 152, mean CPD = 19.4) (Malaiyandi, Goodz et
al., 2006) was examined (r = 0.60, p < 0.001), although the relationships between COT and CPD
(r = 0.53, p < 0.001) and CO with COT (r = 0.74, p < 0.001) remained similar. Thus, it appears
that COT may be a poorer biomarker of cigarette consumption in African-American light
smokers compared to Caucasians, and as expected CO appears poorly correlated with CPD in all
light smokers. Furthermore, in a subset of heavy-smoking, treatment-seeking African-
Americans, in which these variables were available, recruited for a clinical trial testing the
efficacy of bupropion (n = 93) (Ahluwalia, Harris et al., 2002), both CO and COT were poorly
correlated with self-reported cigarette consumption (r = 0.20, p = 0.05 for CO with CPD, and r =
0.05, p = 0.62 for COT with CPD). Together this suggests that CO is a poor correlate of cigarette
consumption in light smokers in general, while COT is a poor correlate of cigarette consumption
among African-American smokers.
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Traditional cutoff levels of expired CO and plasma COT for differentiating between smokers and
nonsmokers have previously been determined primarily in heavy smoking Caucasian populations
(Jarvis, Tunstall-Pedoe H et al., 1987; Waage et al., 1992). Our results suggest that using
expired CO ≤ 10 ppm to verify smoking status in light smokers may result in misclassification of
smokers as nonsmokers, as ~40% of our treatment-seeking sample of smokers had expired CO
levels below this limit. In contrast, very few individuals (3.1%) had plasma COT levels below
the traditional cutoff of 14 ng/ml. This cutoff value was determined more than 20 years ago
when there were high levels of secondhand smoke (Jarvis, Tunstall-Pedoe H et al., 1987).
Recently, it was suggested that the plasma COT cutoff should be further reduced to 3 ng/ml, with
optimal cutoff revised to 6 ng/ml for African-Americans (Benowitz et al., 2009). This revised
cutoff of 6 ng/ml would misclassify only 2.5% of smokers as nonsmokers in this sample. While
further studies will be needed to precisely determine the optimal cutoff points for expired CO
and plasma COT among African-American light smokers, our study suggests plasma COT may
be a better indicator of smoking status than expired CO.
The second objective of this study was to determine whether other variables (i.e. CYP2A6
activity, gender, age, BMI, smoking mentholated cigarettes) influence biomarker levels (expired
CO, plasma COT) or their relationships to self-reported CPD. Individuals with slow CYP2A6
activity, as indicated by genotype and 3HC/COT, had significantly higher plasma COT levels
despite similar intake as represented by self-reported CPD and expired CO values. COT
clearance rates were previously found to be reduced by ~35% in individuals with CYP2A6
genetic variants (Benowitz, Swan et al., 2006), and in this study, COT levels are ~20 – 30%
higher in individuals with slow CYP2A6 activity. Despite its substantial effect on COT levels
however, CYP2A6 activity did not greatly alter the correlations between NIC or its metabolites
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with self-reported CPD or expired CO levels, similar to what was observed in our previous study
of Caucasian heavy smokers (Malaiyandi, Goodz et al., 2006).
Individuals with higher BMI were found to have significantly lower plasma COT levels (r = -
0.19), as well as lower NIC (r = -0.16) and 3HC (r = -0.26) in this study. A negative correlation
between BMI and COT levels has been previously reported (r = -0.16 to -0.36) (Perez-Stable,
Benowitz Nl et al., 1995; Ahijevych, Tyndale Rf et al., 2002). It is possible that differences in
BMI may result in altered volumes of distribution for NIC and its metabolites, thus resulting in
altered plasma levels. The volume of distribution for NIC and COT have been correlated with
total body weight and lean body mass (r = 0.23 – 0.67), although no significant correlation was
found between the volume of distribution with adipose mass (Benowitz, Perez-Stable et al.,
1999). BMI has also been negatively associated with the 3HC/COT ratio (Mooney, Li et al.,
2008; Swan Ge, Lessov-Schlaggar Cn et al., 2008; Ho, Mwenifumbo et al., 2009), suggesting
obesity and rate of CYP2A6 activity may be related, although this has not been examined
explicitly. While the lower plasma COT levels in individuals with higher BMI may also be
interpreted as lower exposure to cigarette smoke, this is unlikely as BMI was not significantly
associated with expired CO or CPD in multiple regression analyses. As such, it is yet unclear
whether the relationship between BMI and COT represents altered rates of COT metabolism
(altered CYP2A6 activity), or volume of distribution, or a combination of both. Interestingly,
expired CO appeared to be a better measure of exposure in obese individuals (BMI ≥ 30.0) as the
correlation to CPD appeared stronger in these individuals.
It has been proposed that the cooling sensation associated with smoking mentholated cigarettes
allows for increased smoke intake. Thus, this may contribute to the higher COT levels and
disproportionately higher incidences of tobacco-related illnesses among African-Americans, who
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because of the influence of marketing campaigns in the 1960s, predominantly smoke
mentholated cigarettes (Balbach, Gasior et al., 2003). However, while some cross-sectional and
experimental studies have found higher CO and COT levels among mentholated cigarette
smokers, this has not been consistently replicated (Werley, Coggins et al., 2007). Studies finding
an effect were generally of small sample size, and included both heavy-smoking Caucasians and
African-Americans. In this current study of African-American light smokers, mentholated
cigarette users did not have significantly higher expired CO or plasma COT levels despite our
large sample, with 131 non-menthol smokers examined. Thus, cigarette mentholation did not
appear to contribute to increased intensity of cigarette smoking or increased absorption of
nicotine in our sample of African-American light smokers.
No differences in CPD, expired CO or plasma COT were found by age, in contrast to previous
findings where older individuals had higher COT levels (Swan, Habina K et al., 1993; Patterson,
Benowitz et al., 2003). In general, drug metabolism is thought to decrease by age (Wynne,
2005), and while NIC clearance rates are reduced in the elderly (age >65), this has been
attributed to age-related changes in hepatic blood flow as no differences in CYP2A6 protein by
age have been observed (Benowitz et al., 2009). The renal clearance of COT is also reduced in
the elderly, although pharmacokinetic parameters such as area-under-the-curve and elimination
half-lives are not altered (Molander, Hansson et al., 2001). Accordingly, the relationships
between NIC or its metabolites with CPD or expired CO did not greatly differ among
mentholated cigarette users or by age.
We did not find any gender differences in CPD, expired CO, or plasma COT. However, in the
present study the proportion of variance in CPD explained by expired CO was more than tripled
in females compared to males (14.4% vs. 4.4%, respectively). This was unlikely due to
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differences in the type of cigarettes smoked, as there was no difference in prevalence of
mentholated cigarette use by gender. A number of studies have reported gender differences in
smoking topography, with males taking larger and longer puffs compared to females (Battig et
al., 1982; Eissenberg et al., 1999; Melikian et al., 2007). However, we did not observe any
differences in CO/cigarette or COT/cigarette by gender in this population (p > 0.10). Among
African-American light smoking males, there may be more variability in the manner in which
cigarettes are smoked, resulting in weaker relationships between self-reported CPD and expired
CO.
One limitation of our study is that it relied on secondary analyses performed on participants that
were originally recruited for a clinical trial on smoking cessation, and may not be representative
of African-American light smokers in the general population. Thus, biochemical measures were
collected randomly from ad libitum smoking and the time of the last cigarette may have been a
significant source of variation, particularly for expired CO where the half-life is short. It is
possible that this treatment-seeking sample may have attempted to stop smoking prior to the start
of the trial; however, we excluded from these analyses any participants that reported smoking
zero cigarettes within the past seven days prior to the collection of biochemical data. That said,
we cannot exclude the possibility that there may have been a selection bias as participants were
light smokers who were highly motivated to quit smoking and had difficulty quitting in the past.
Thus, they may be more dependent or smoke cigarettes differently from other non-treatment
seeking light smokers. In addition, participants may have underreported their cigarette
consumption to meet the inclusion criteria for the clinical trial. The average plasma COT levels
derived from ad libitum smoking (244 ng/ml) is similar to those found previously in a heavier
smoking population of African-Americans (292 ng/ml) recruited for a clinical trial of smoking
cessation at the same community health centre as the current study, with an inclusion criterion of
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smoking at least 10 CPD (mean = 17 CPD) (Ahluwalia, Harris et al., 2002). It is also possible
that self-reported CPD is a poor measure of average cigarette consumption among individuals at
this low level of smoking, which may in part explain their weak correlations to the biomarkers.
In a previous study of an African-Canadian light smoking population (median of 8 CPD), we
found some discrepancies of cigarette consumption when it was reported as cigarettes per day,
versus cigarettes per week (CPW), versus cigarettes per month (CPM) (Mwenifumbo JC,
Tyndale RF, personal communications). For example, one individual reported consuming 6
CPD, but 18 CPW and 60 CPM. Thus, in light smokers where daily smoking is variable and
smoking may occur at irregular intervals, CPD may be a poor indicator of consumption and
alternative measures of self-report, such as timeline follow-back procedures (Brown et al., 1998),
need to be tested. It is also notable that a large portion of the participants (45%) reported puffing
or inhaling as far as the throat only. While self-reported measures of depth of inhalation may not
be representative of actual smoking behaviours (Tobin Mj et al., 1982), this may be another
source of variability in cigarette exposure among these light smokers.
In summary, the results from this study suggest that the commonly used biomarkers of cigarette
smoke exposure, expired CO and plasma COT, are significantly but weakly correlated with self-
reported CPD. Furthermore, these relationships are not greatly altered by variables that were
previously reported to have an influence on these parameters, such as CYP2A6 activity, smoking
mentholated cigarettes or age, although the relationships may differ slightly by gender and BMI.
The proportion of variance in CPD explained by expired CO and plasma COT was generally
lower than that observed in heavy Caucasian smokers even after accounting for these variables,
suggesting these biomarkers are limited as indicators of cigarette smoke exposure among
African-American light smokers.
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Our study suggests that expired CO may be a poor indicator of smoking status as many smokers
had expired CO levels below the traditionally defined cutoff level. While plasma COT may be
useful in ascertaining smoking status in this population, the level is highly influenced by the rate
of CYP2A6 activity, and it is also a poor indicator of the levels of smoke exposure. This
suggests the rate of CYP2A6 activity needs to be considered when COT is used as a biomarker
of intake in African-American populations, where there are higher proportions of individuals
with reduced rates of CYP2A6 activity compared to Caucasians. A number of other biomarkers
such as thiocyanate or the tobacco alkaloids anabasine and anatabine have also been proposed
(Benowitz, Peyton J Iii et al., 2002); however, these also have their own set of limitations in
terms of specificity, sensitivity and cost for detection. Validated biomarkers are important for
ascertaining smoking status before recruitment into research studies or clinical trials for smoking
cessation, or for verifying abstinence among light smokers. In addition, validated biomarkers of
cigarette smoke exposure are also necessary for the proper assessment of the dose-related risk of
smoking and health outcomes in epidemiological studies of African-Americans, a population that
have been reported to have a disproportionately elevated risk of developing tobacco-related
illnesses despite lower levels of self-reported cigarette consumption (Centers for Disease Control
and Prevention, 1998; Haiman, Stram et al., 2006).
Significance to thesis
Biomarkers of exposure to tobacco smoke are needed due to the limitations of self-reports.
Common biomarkers of tobacco smoke exposure have only been previously validated in
Caucasian moderate to heavy smokers. This is the first study to examine the relationship
between biomarkers and self-reported cigarette consumption, and investigate variables that may
influence either tobacco smoke exposure or cotinine metabolism in a light smoking population.
Validating appropriate biomarkers of tobacco smoke exposure among African-Americans is
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particularly important given their low and sporadic patterns of smoking, their greater use of
menthol cigarettes which may result in greater tobacco smoke exposure, and their slower rates of
cotinine metabolism.
The finding that exhaled CO is a poor biomarker has important implications as it is commonly
used to ascertain smoking status in clinical trials. Exhaled CO is the only available method of
biochemically validating smoking abstinence in research studies that administer NRT to
participants as cotinine cannot be used in these cases. Exhaled CO and cotinine were weakly
correlated with self-reported cigarette consumption, and the correlations between the two
biomarkers themselves were also poor. Factors previously shown to alter tobacco smoke
exposure and/or cotinine metabolism (i.e. gender, menthol cigarettes, BMI, or age) did not
account for additional variability in exhaled CO or cotinine levels, although CYP2A6 activity
significantly altered cotinine level. Furthermore, the correlations between the biomarkers and
cigarette consumption did not improve after accounting for these variables. This suggests that
previously validated biomarkers of tobacco smoke exposure have limitations among African-
American light smokers. Determining appropriate biomarkers to quantify tobacco exposure in
this population is necessary in light of their higher risk of tobacco-related illnesses despite lower
self-reported cigarette consumption. It remains to be determined whether this paradox is the
result of African-Americans having greater exposure to tobacco smoke than is subjectively
reported, whether they have greater biological sensitivity towards developing tobacco-related
illnesses such as cancer, or whether disparities in demographic variables (e.g. socioeconomic
status) may be contributing.
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GENERAL DISCUSSION
SECTION 1: IDENTIFYING AND DETERMINING THE FUNCTIONAL IMPACT OF
NOVEL CYP2A6 GENETIC VARIANTS
1.1 African-Americans: a population with rich genetic diversity
1.1.1 Origins of genetic variation in modern Homo sapiens
Current paleontological and genetic data support the “Recent African Origin” model that
proposes anatomically modern Homo sapiens evolved in Africa approximately 200 000 years
ago and dispersed globally within the past 100 000 years (Campbell et al., 2010). The size of
the ancestral population leaving Africa has been estimated at 1000-1500 males and females
based on autosomal microsatellite loci, mitochondrial DNA, and X- and Y- chromosome re-
sequencing data (Liu et al., 2006; Garrigan et al., 2007). The geographic expansion of this
small ancestral group of modern humans resulted in a large population bottleneck that greatly
reduced the genetic diversity in subsequent populations. Indeed, higher levels of nucleotide
and haplotype diversity have been reported among African populations (Campbell and
Tishkoff, 2010), with non-African populations becoming less genetically diverse as they are
found at increasing distance away from Africa (Tishkoff et al., 2009). Multiple forms of
genetic variation including SNPs, microsatellite markers and large structural changes appear
to be shared between various racial/ethnic populations, suggesting they existed in modern
humans prior to their migration out of Africa (Redon et al., 2006; Korbel et al., 2007). Thus,
there was likely one single major migration event occurring out of Africa, or multiple
migrations from a single genetically homogeneous ancestral population, rather than
migrations from multiple genetically distinct sources (Reed et al., 2006; Campbell et al.,
2008; Campbell and Tishkoff, 2010).
1.1.2 The African Diaspora: Origins of African-Americans
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According to recent census data, individuals of Black-African descent comprise 2.5% of the
Canadian population (Statistics Canada, 2006) and 12.4% of the American population
(Grieco, 2009). Populations of Black-African descent in North America today can trace their
recent origins back to Africa, with large waves of migration occurring during the Trans-
Atlantic Slave Trade beginning in the 15th century. The precise estimates vary, but
documentation suggests approximately 11-13 million slaves were brought over to the
Americas with the majority originating from West Africa (Thomas, 1997). As a result of
their complex history, African-Americans are an admixed population with an average of 80%
African ancestry and 20% European ancestry (Parra et al., 1998; Halder et al., 2009; Bryc et
al., 2010). The degree of admixture can vary widely between individuals, with estimates
ranging from as much as 99% to less than 1% African ancestry (Halder, Yang et al., 2009;
Bryc, Auton et al., 2010). Historical records and genetic evidence suggest the admixture
began fairly recently within the past 20 generations (Lohmueller et al.).
As a result of their genetic ancestry and complex demographic history, African-Americans
are also a population with high levels of genetic diversity (Campbell and Tishkoff, 2010). In
a large sequencing study of 3873 genes, African-Americans had the highest number of SNPs
found in comparison to Caucasians, Latino/Hispanics, and Asians (Guthery et al., 2007).
African-Americans also had the highest percentage of rare SNPs, with 64% of the SNPs
identified occurring at a minor allele frequency of less than 5% (Guthery, Salisbury et al.,
2007). Moreover, 44% of all SNPs were found specifically in this population (Guthery,
Salisbury et al., 2007). Similarly, African-Americans had the highest number of SNPs found
in a large-scale gene sequencing project of CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8,
CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4 and CYP3A5 in comparison to Caucasians
or Asians (Solus Jf, 2004). As such, African-Americans are a genetically diverse population
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with a large number of unique genetic variants, each occurring at low frequencies. The
functional effects for many of these genetic variants remain to be characterized.
1.1.3 Evolutionary forces driving genetic diversity
The human genome has 3.2 billion base pairs that are 99.9% identical; the 0.1% variability
represents the 10 to 15 million SNPs that differ between individuals (Kruglyak et al., 2001;
Venter et al., 2001). This genetic diversity is the result of various evolutionary processes
including genetic drift and natural selection. Genetic drift is the change in allele frequency
from one generation to the next as a result of random sampling processes. It is not driven by
environmental or adaptive pressures and may result in beneficial, deleterious or neutral
changes (Miller et al., 2009). The consequences of genetic drift are particularly apparent
when population sizes are dramatically reduced, such as during population bottlenecks or
founder effects (Miller, Vandome et al., 2009). Alternatively, genetic loci may be the target
of natural selection whereby variants with favorable adaptive fitness are maintained and
deleterious variants are removed (Bamshad et al., 2003). Genetic drift processes tend to
influence the level of diversity across the genome (Tishkoff et al., 2003), whereas natural
selection tends to act upon specific genetic loci (Tishkoff and Verrelli, 2003).
It may be difficult to distinguish between neutral and adaptive human genetic variation as
both genetic drift and selection are almost always acting simultaneously within populations
(Tishkoff and Verrelli, 2003). A number of methods have been developed to determine if
patterns of genetic variation are the result of selective pressures (Tishkoff and Verrelli,
2003). Under neutral evolutionary processes, new genetic variants require a long time to
reach high frequency in a population, and the surrounding linkage disequilibrium decays
substantially as a result of recombination (Sabeti et al., 2002; Bamshad and Wooding, 2003;
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Nielsen, 2005; Tang et al., 2007; Luca et al.). In contrast, variants under positive selection
will increase in allele frequency rapidly such that recombination does not substantially alter
the associated haplotype relationships (Sabeti, Reich et al., 2002; Bamshad and Wooding,
2003; Nielsen, 2005; Tang, Thornton et al., 2007; Luca, Perry et al.). As such, some
statistical models used to identify regions of selection test whether the allele has unusually
long patterns of linkage disequilibrium compared to other regions in the genome (Sabeti,
Reich et al., 2002; Bamshad and Wooding, 2003; Nielsen, 2005; Ennis, 2007; Tang,
Thornton et al., 2007; Oleksyk et al.; Luca, Perry et al.). Neutral variants that are in linkage
disequilibrium with the genetic variant under selection are more likely to be maintained in
the population, resulting in an excess of low frequency variants (Sabeti, Reich et al., 2002;
Bamshad and Wooding, 2003; Nielsen, 2005; Tang, Thornton et al., 2007; Luca, Perry et al.).
Other statistical models used to identify signatures of selection examine the degree of genetic
variability within the region of interest (Sabeti, Reich et al., 2002; Bamshad and Wooding,
2003; Nielsen, 2005; Tang, Thornton et al., 2007; Luca, Perry et al.). In addition, genetic
variants that do not alter protein expression or activity likely reflect neutral evolutionary
processes whereas functional variants are predicted to be under greater adaptive pressures. A
number of statistical models have been used to compare the degree of divergence or
conservation of genetic variants within and between species (Sabeti, Reich et al., 2002;
Bamshad and Wooding, 2003; Nielsen, 2005; Tang, Thornton et al., 2007; Luca, Perry et al.).
1.1.4 Genetic association studies in African-Americans
1.1.4.1 Utility and limitations of self-reports of racial/ethnic ancestry
The use of self-reported race/ethnicity as a surrogate biological construct has been the topic
of much debate, particularly as it may be inadvertently viewed as promoting notions of
biological determinism and justification for the mistreatment of one group by another. While
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it has been argued that racial/ethnic categorization is primarily a socially and culturally-
defined construct, it cannot be denied that diseases affect populations differentially.
Furthermore, categorization based on similarity of random genetic markers has been shown
to correlate well to ancestral continent of the origin and to self-defined racial/ethnic group
(Rosenberg et al., 2002; Tang et al., 2005). The sociocultural and socioeconomic factors
contributing to the epidemiology and health disparities of complex diseases such as tobacco
addiction are also likely similar among self-defined racial/ethnic populations (Collins, 1996;
Betancourt et al., 2003). Racial/ethnic identities may also serve as a proxy for shared beliefs
and acceptable behavioural norms for the use of cigarettes, alcohol and other drugs of abuse
(Castro, 2004).
1.1.4.2 Importance of performing studies in different racial/ethnic groups
Genetic association studies for complex diseases have mainly been performed among
individuals of Caucasian ancestry, even though much information can be gained from this
type of research in other racial/ethnic populations. The prevalence of complex diseases
including tobacco addiction differ widely across racial/ethnic groups, and unique genetic
factors may be contributing to the disease phenotype among these different groups (Fagan,
Moolchan Et et al., 2007). The effect sizes of genetic risk variants may differ across
racial/ethnic populations. Furthermore, the frequency of genetic risk variants may differ
between populations, or they may have different functional effects depending on their
haplotype relationship with other genetic variants. Different haplotypes of the chemokine
receptor gene CCR5 have been associated with altered rates of HIV-1 progression in
Caucasians compared to African-Americans (Gonzalez et al., 1999). In addition, the effects
of CYP2D6 genetic variants on enzyme function differ between African-Americans and
Caucasians as a result of differences in haplotype relationships (Gaedigk et al., 2002). Thus,
156
examination of genetic factors previously associated with tobacco addiction phenotypes
among Caucasians in other racial/ethnic populations is necessary to validate their
generalizability and relevance, as well as account for any population-specific gene by
environment interactions.
One challenge of performing genetic association studies in admixed populations such as
African-Americans is the possibility of population stratification. Spurious associations (either
false positives or negatives) between risk alleles and outcomes may be found if cases and
controls are sampled from an admixed population where the proportion of ancestry differs in
individuals, and the frequency of outcome and risk alleles examined differs between these
ancestral populations (Thomas et al., 2002; Wacholder et al., 2002). Several statistical
methods have been proposed to account for this potential confound. Structured Association
and Genomic Control methods use ancestry informative markers that are located throughout
the genome and are unlinked to the candidate locus of interest to estimate the ancestry of
individuals within a sample and test whether they differ between cases and controls (Li et al.;
Enoch et al., 2006; Need et al., 2009; Wang et al., 2010).
While we were not able to account for the possibility of population substructure within our
sample, this highlights the importance of replication of genetic association studies.
Participants recruited from a community health care center in Kansas City for our clinical
trial of light smokers were self-reported as African-American or Black ethnicity.
Approximately 60% of the sample reported having three or more grandparents of African
heritage, while the other 40% had mixed or unknown grandparent ancestry. In spite of this,
the frequency of CYP2A6 alleles that tend to be more representative of European or African
ancestry did not differ according to self-reported grandparent ancestry. Similarly, the
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distribution of CYP2A6 normal, intermediate and slow metabolizers did not differ by the
ancestry of grandparents. Thus, there does not appear to be a disproportionate distribution of
African or European ancestry among the various CYP2A6 metabolizer groups. CYP2A6
allele frequencies were also comparable between African-Americans in this study and those
reported in a population of Black-African descent recruited from Canada (Appendix C),
suggesting our sample of African-Americans was not likely to be distinctly admixed.
Furthermore, we were able to corroborate our results using both genetic and phenotype
(3HC/COT) data.
1.2 Origins of CYP2A6 polymorphisms
1.2.1 Types of genetic polymorphisms
Within the past five years, the number of identified CYP2A6 alleles has increased from 22 to
37 (http://www.cypalleles.ki.se/cyp2a6.htm). CYP2A6 is located on chromosome 19q13.2, a
region with a high rate of recombination (Wang et al., 2009). Many of the known CYP2A6
genetic variants are single nucleotide conversions, truncations, duplications, or chimeras
resulting from mispairing or unequal crossovers between CYP2A6 and the nearby CYP2A7
locus during meiotic recombination (Hoffman and Hu, 2007). This suggests high rates of
recombination exist even between tandem pairs of paralogs (i.e. CYP2A6 and CYP2A7)
within the CYP2ABFGST gene cluster. In contrast, allelic variants of the polymorphic
CYP2A13, which does not have a nearby paralog, are mainly single nucleotide base
substitutions (Hoffman and Hu, 2007).
Copy number variants (CNVs), whereby DNA segments ranging in size from thousands to
several million base pairs exist in variable number of copies, have also been the recent focus
of much research attention. CNVs were initially thought to be rare events. However,
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currently annotated CNVs cover approximately 29% of the genome and more than 5600
CNV loci have been identified (http://projects.tcag.ca/variation) (Iafrate et al., 2004; Mcelroy
et al., 2009). As such, CNVs are a major source of human diversity with a potentially large
impact on function. Seven versions of the CYP2A6 deletion allele and two versions of the
CYP2A6 duplication allele, each with a different crossover junction, have been identified to
date. Genetic polymorphisms in other CYP enzymes that result in variable copies of the gene
have also been identified. For example, individuals can have anywhere from 0 to 13
functional copies of the CYP2D6 gene (Ingelman-Sundberg et al., 2007).
While the functional characterization of genetic variation has primarily focused on
nonsynonymous SNPs encoding amino acid changes, cis-acting genetic polymorphisms that
influence gene expression may also be functionally significant. Synonymous SNPs may
contribute to differences in gene expression by altering mRNA splicing or mRNA turnover
rates (Johnson et al., 2005). Evidence for allelic expression imbalance, whereby expression
of the paternal and maternal copies of the gene differs due to the presence of genetic
polymorphism(s) on one of the alleles, have been reported for CYP3A4 (Hirota et al., 2004),
CYP1A2 (Ghotbi et al., 2009), CYP2D6 (Johnson et al., 2008), MAO-A (Pinsonneault et al.,
2006), TPH2 (Lim et al., 2006; Johnson, Zhang et al., 2008), OPRM1 (Zhang et al., 2005;
Johnson, Zhang et al., 2008) and DRD2 receptors (Zhang et al., 2007; Johnson, Zhang et al.,
2008).
1.2.2 Discovery of novel CYP2A6 alleles
African-Americans are an admixed population with contributions from both European and
African ancestry. Therefore, unique allele frequencies and patterns of linkage disequilibrium
are present in their genomes. The high levels of genetic diversity among populations of
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Black-African descent suggest there are likely unidentified sources of variations with
functional consequences. Within the past five years, seven new numbered CYP2A6 genetic
alleles consisting of SNPs have been identified (CYP2A6*23, CYP2A6*24, CYP2A6*25,
CYP2A6*26, CYP2A6*27, CYP2A6*28, and CYP2A6*35) (Appendix C), in addition to
several new deletion alleles and a novel duplication allele, among populations of Black-
African descent (Ho, Mwenifumbo Jc et al., 2008; Mwenifumbo, Al Koudsi N et al., 2008;
Al Koudsi, Ahluwalia Js et al., 2009; Mwenifumbo, Zhou Q et al., 2010). Many of these
have substantial impact on reducing enzyme function and appear to be found specifically in
this population, which may help explain the slower rates of nicotine and cotinine clearance
observed between African-Americans and Caucasians. Large sequencing projects have likely
identified the more common genetic variants in this population and full gene sequencing of
phenotypic outliers will result in the discovery of additional rarer alleles. The development
of a copy number variation assay for this gene will also help identify large structural variants
such as gene deletions and duplications with crossover junctions that are not detected using
currently available genotyping assays.
1.2.3 Evolution of CYPs and their genetic variants
Cytochromes P450 were thought to have emerged in an ancestral prokaryotic species as early
as 1.5 billion years ago (Lewis et al., 1998). These enzymes are found in virtually every
living species and have undergone extensive expansion and modification (Ingelman-
Sundberg, 2005). The number of CYP2 genes quickly expanded approximately 400 million
years ago when animals first became land-bound and presumably began consuming
terrestrial plant forms (Nebert, 1997). Considerable inter-individual and inter-ethnic
differences in CYP enzyme expression and function are observed among humans. The
domestication of plants and animals approximately 10 000 years ago led to a rapid increase
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in human population size, with these new food sources becoming available at the same time
as the development of new cultural environments and the spread of new infectious diseases
(Sabeti, Reich et al., 2002). Many important genetic adaptations in humans were thought to
have arisen at this time (Sabeti, Reich et al., 2002).
Genetic variability in CYP enzymes is likely the result of both random genetic drift due to
migration of populations, as well as adaptive responses due to selection. Because of their
roles in the detoxification of xenobiotics, including dietary plant toxins, CYP enzymes are
likely targets of natural selection (Bamshad and Wooding, 2003). Genetic variation in
CYP2D6, an enzyme that metabolizes a number of plant alkaloids but does not appear to be
readily inducible, may have been a result of selection (Ingelman-Sundberg, 2005; Ingelman-
Sundberg, 2005). Genetic variants resulting in multiple copies of active CYP2D6 genes are
prevalent among individuals in North-East Africa, suggesting selection may have played a
role in increasing the variety of food sources that can be consumed, particularly under
detrimental environmental conditions (Ingelman-Sundberg, 2005; Ingelman-Sundberg,
2005). The pattern of SNPs found in a 3.7 kb sequence in the 5’-regulatory region of the
CYP1A2 gene is also indicative of recent positive selection (Wooding et al., 2002).
It is plausible that CYP2A6 was the target of natural selection. The gene deletion allele is
highly prevalent among Asian populations, with approximately 4% of Chinese and
approximately 12% of Japanese individuals completely lacking functional copies of CYP2A6
(Mwenifumbo and Tyndale, 2007). However, these individuals do not appear to suffer from
any deleterious effects, and deletion of the homologous gene Cyp2a5 in mice does not result
in lethality or developmental deficits (Tomizawa and Casida, 2003). In addition, the gene
duplication alleles are not commonly found, occurring at less than 2% allele frequency across
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various racial/ethnic populations (Schoedel, Hoffmann Eb et al., 2004; Nakajima, Fukami et
al., 2006; Fukami, Nakajima et al., 2007). Endogenous substrates of CYP2A6 have not been
identified, although Cyp2a5 in mice was found to contribute to the metabolism of bilirubin
under conditions of oxidative stress induced by cadmium (Abu-Bakar et al., 2005). A
combination of neutral genetic drift processes and adaptive selection likely contributed to the
large variability in CYP2A6 allele frequencies observed between different racial/ethnic
groups. Future studies investigating potential evidence of positive selection will help clarify
its role in shaping the variability observed in CYP2A6.
1.3 Comparison of CYP2A6 genetic variability between racial/ethnic groups
Racial/ethic differences in the frequencies of CYP2A6 alleles and rates of nicotine and
cotinine metabolism have been observed (Mwenifumbo and Tyndale, 2007). CYP2A6
genetic variants that are known to reduce enzyme function occur at low frequencies in
Caucasians but are found in a much larger proportion of African-Americans and Asians.
Accordingly, nicotine and cotinine clearance are fastest among Caucasian individuals and
reduced by 20 to 25% in African-Americans and Chinese-Americans (Benowitz, Perez-
Stable et al., 1999; Benowitz, Perez-Stable et al., 2002). Interestingly, the profile of CYP2A6
variants varies widely between Asians and African-Americans. Approximately 50 to 60% of
Asians have CYP2A6 genetic variants known to reduce enzyme function. This is primarily
due to the high frequency of the gene deletion allele CYP2A6*4 and the loss-of-function SNP
CYP2A6*7. In contrast, 35 to 40% of African-Americans have CYP2A6 variants known to
reduce enzyme function, although many of these occur at less than 2% allele frequency (e.g.
CYP2A6*23, CYP2A6*24, CYP2A6*25, CYP2A6*26, CYP2A6*27, CYP2A6*28, and
CYP2A6*35). This suggests that different evolutionary processes may have been responsible
for the distribution of CYP2A6 genetic variants across various racial/ethnic populations.
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1.4 Functional consequences of CYP2A6 genetic variants
Determining the functional consequences of genetic variants will provide a biological
rationale for how the gene may be associated with disease states. Bioinformatic programs
can be used to predict the effect of an amino acid change based on its physicochemical
properties, and phylogenetic analyses can determine its degree of evolutionary conservation.
SNPs can alter enzyme function through various mechanisms. These include alterations in
the affinity of the enzyme for substrate binding or product release, a shift in the orientation of
substrate with the heme moiety, or ability of the enzyme to interact with required co-enzymes
and co-factors to facilitate the electron transport chain during the CYP catalytic cycle. SNPs
can also affect enzyme stability or heme incorporation, alter rates of transcription, or disrupt
mRNA processing.
Interestingly, CYP2A6*23 (2161C>T, Arg203Cys) was found to reduce enzyme activity
whereas CYP2A6*16 (2161 C>A, Arg203Ser) did not alter function. While the precise
mechanism to explain this observation remains to be elucidated, molecular modeling
suggests Arg203 is located on the outer surface of the enzyme (Kiyotani, Fujieda M et al.,
Oct 23-27, 2005). The side chains of Ser (CYP2A6*16) and Cys (CYP2A6*23) are both
substantially smaller than the wildtype Arg residue. It is possible that the reactive Cys
residue in CYP2A6*23 may be hindering activity by forming Cys-Cys disulfide bonds with
other proteins or other Cys residues in CYP2A6. Cys203 could potentially disrupt the critical
interactions between CYP2A6 with NADPH-CYP reductase (POR) or cytochrome b5, and
evidence for altered interactions between POR and other CYP enzymes have been reported.
The Cys98 residue in CYP3A4 is critical for enzyme stability, and substitutions with Trp or
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Phe altered protein conformation and decreased the binding affinity to POR, resulting in
reduced coupling efficiency towards NAPDH oxidation (Wen et al., 2006).
Similar to genetic variation in other CYP enzymes (Mo et al., 2009; Watanabe et al., 2010),
the functional effects of CYP2A6 genetic variants may differ depending on the substrate
examined. CYP2A6*17 encodes an enzyme with reduced catalytic activity towards nicotine,
but it appeared to have normal activity towards coumarin in vitro (Fukami, Nakajima et al.,
2004). CYP2A6*7 and CYP2A6*18 also differentially altered the metabolism of nicotine
compared to coumarin (Ariyoshi et al., 2001; Fukami et al., 2005). Thus, the functional
consequences of CYP2A6 genetic variants towards other substrates such as tobacco-related
nitrosamines (NNK and NNN) should also be tested directly given the impact of these
variants may differ from those reported towards nicotine.
1.5 Other biological sources of variability in CYP2A6 activity
Genetic variability in POR, the required co-enzyme for CYP function, may potentially affect
the activity of all CYP enzymes. Genetic variability in the transcription factors responsible
for CYP2A6 expression may also contribute to the large variability observed in CYP2A6
activity. Furthermore, gene expression is more complex than initially thought, with various
additional layers of regulation identified in recent years including epigenetic and miRNA
modulations (Ingelman-Sundberg, Sim et al., 2007). These alternative sources of variation
can potentially contribute to the large differences observed in CYP2A6 expression and
activity between individuals.
1.5.1 Polymorphisms in POR
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The CYP catalytic cycle involves cycles of oxidation and reduction of the heme iron in
conjunction with substrate binding and oxygen activation, with POR supporting the electron
transport chain that supplies two electrons from NADPH (Gibson et al., 2001). Genetic
polymorphisms in POR and their contribution to variability in xenobiotic metabolism have
been gaining attention. POR knockout mice die during embryonic development (Shen et al.,
2002) and liver-specific deletion of POR results in greatly disrupted hepatic drug metabolism
(Gu et al., 2003; Henderson et al., 2003). POR deficiency has been associated with altered
steroidogenesis, congenital malformations and syndromes involving altered skeletal
development in humans (Scott et al., 2008; Miller et al., 2009). The effects of 35 known
POR genetic variants was recently tested in vitro, including some variants that had been
previously associated with disease states (Agrawal et al., 2008). Thirteen of the POR genetic
variants examined had no drug metabolizing capabilities when reconstituted with CYP1A2 or
CYP2C19, and many other variants had substantially lowered levels of activity (Agrawal,
Huang et al., 2008). Although POR genetic variants with complete loss-of-function are rare,
the frequency of POR genetic variants with less severe functional effects and their impact on
xenobiotic metabolizing enzyme activity remains to be determined.
1.5.2 Polymorphisms in transcription factors
Inter-individual variability in expression or activity of xenobiotic metabolizing enzymes is
under the transcriptional control of nuclear hormone receptors. In an analysis of human
livers, the mRNA levels of various xenobiotic metabolizing enzymes including CYP2A6,
CYP2B6, CYP2C8, CYP2C9, CYP2C19, MRP2, OATP2, and UGT1A1 were found to be
significantly correlated (Wortham et al., 2007). The mRNA levels of the transcription factors
CAR, HNF4α and steroid/xenobiotic receptor (SXR) were also significantly correlated with
mRNA levels of these xenobiotic metabolizing enzymes, suggesting they are co-regulated at
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the transcriptional level (Wortham, Czerwinski M et al., 2007). A number of SNPs and
alternative splice variants in CAR and PXR have been recently identified (Wang et al., 2007;
Lamba, 2008; Wang et al., 2008). However the implications of these genetic variations on
xenobiotic metabolism in vivo, particularly in combination with genetic polymorphisms in
xenobiotic metabolizing enzymes, remain to be explored. A recent study found two
haplotypes in the 3’-UTR of PXR was associated with altered oral clearance rates of
midazolam in vivo, with greatest effects observed in African-Americans (Oleson et al.).
1.5.3 Epigenetics
Epigenetic regulation of gene expression involves heritable or acquired modifications of
DNA (e.g. methylation) or its associated proteins (e.g. histone acetylation) (Renthal et al.,
2008). Expression of CYPs can be altered by epigenetic modifications. For example, the
methylation status of CYP1A1, CYP1A2, CYP1B1 and CYP2W1 has been associated with
altered expression in tumors (Hammons et al., 2001; Tokizane et al., 2005; Karlgren et al.,
2006; Okino et al., 2006; Gomez et al., 2007; Ghotbi, Gomez et al., 2009; Habano et al.,
2009). Environmental factors can also influence epigenetic processes. Smoking alters the
methylation status of CYP1A1, with lowest levels found in heavy smokers and highest levels
found in non-smokers (Anttila et al., 2003).
Evidence for epigenetic modulation has been reported for the CYP2A subfamily; CYP2A13
expression in a human lung cancer cell line was increased following treatment with a
demethylating agent and a histone deacetylase inhibitor (Ling et al., 2007). DNA
methylation status at two potential CpG sites in CYP2A6, one within a DR4-like element at -
5.5 bp and another within intron 2 to exon 3 at 1.6 to 1.9 kb, did not differ among human
liver bank samples with high versus low levels of CYP2A6 expression and activity (Al
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Koudsi, Hoffmann et al., 2010). While this study did not conclusively provide evidence for
epigenetic regulation of CYP2A6 expression, only two probable sites were examined. There
are many other CpG-dense sites within CYP2A6 that can possibly serve as targets of
methylation, and other types of epigenetic regulation, such as histone acetylation, may also
be of importance.
1.5.4 mRNA silencing (microRNA)
MicroRNAs (miRNA) are small non-coding RNA molecules (approximately 21 to 25
nucleotides in length) that bind to complementary sequences in the 3’-UTR of target mRNA
transcripts, thereby inhibiting gene expression by degrading mRNA or suppressing
translation (Meltzer, 2005). MicroRNAs regulate genes involved in various cell processes
including proliferation, morphogenesis, apoptosis and differentiation (Ingelman-Sundberg,
Sim et al., 2007). Genetic polymorphisms occurring at miRNA binding sites on the mRNA,
or within miRNAs themselves, may also contribute to variable expression of xenobiotic
metabolizing enzymes. CYP1B1 has an extremely long 3’-UTR (approximately 3kb),
containing regions of high levels of conservation, and its expression can be modulated by
miR-27b (Tsuchiya et al., 2006). Although the length of the 3’-UTR of CYP2A6 mRNA is
only 257 bp (Gilmore et al., 2001), the miRNA Registry Release 16.0 has identified a
number of putative miRNAs that may interact with this region via complementary binding
(Griffithsâ€�Jones, 2004). It is notable that the 3’-UTR of CYP2A6 can also affect the
stability of mRNA through other mechanisms (Ross, 1995). For example, the CYP2A6*1B
allele, consisting of a 58 bp gene conversion in the 3’-UTR with CYP2A7, has been
associated with increased mRNA stability (Ariyoshi et al., 2000; Wang et al., 2006). While
the mechanism for this is unclear, a number of nuclear proteins such as the heterogeneous
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nuclear ribonucleoprotein A1 (hnRNP A1) can interact with the 3’-UTR of CYP2A6 and
increase its stability (Gilmore, Rotondo et al., 2001; Christian et al., 2004).
1.6 Utility of genotype versus phenotype measures of CYP2A6 activity
Currently, both genotype and phenotype measures are available as proxy measures of
CYP2A6 activity, although each has its own set of advantages and limitations. Advances in
DNA sequencing and genotyping technologies have greatly improved our ability to detect
CYP2A6 genetic variants in recent years. However, several issues continue to limit the utility
of CYP2A6 genotype (Altman, 2009; Schickedanz et al., 2009). The low frequencies of
genetic variants in some racial/ethnic populations may reduce the statistical power of studies.
Secondly, some discordance in the genotype-phenotype relationship remains as a result of
incomplete functional characterization of known genetic variants and the existence of
unidentified variants. Similar challenges have been reported for other xenobiotic
metabolizing enzymes. CYP2D6 has been extensively studied, with over 80 alleles identified
to date, yet development of a consistent and unified framework for the categorization of
individuals according to predicted phenotype has proven difficult (Kirchheiner, 2008).
Although currently identified CYP2D6 genotypes greatly alter enzyme activity, they account
for only a fraction of the observed variability in phenotype (approximately 60%) despite the
fact that this enzyme is not regulated by any known environmental or endogenous compound
(Ingelman-Sundberg, 2005; Frank et al., 2007; Kirchheiner, 2008).
The 3HC/COT phenotype measure has the advantage of being able to account for both
genetic and environmental sources of CYP2A6 variability. While this ratio can be derived
from metabolites present in smokers as a result of ad libitum smoking, administration of a
probe drug is required to determine the rate of enzyme activity among those who are not
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exposed to tobacco smoke such as former or never smokers. Furthermore, the 3HC/COT
ratio is technically a measure of cotinine metabolism. The 3HC/COT ratio is highly
correlated with rates of nicotine clearance and is generally in good concordance with
CYP2A6 genotypes (Dempsey, Tutka et al., 2004; Benowitz, Swan et al., 2006; Johnstone,
Benowitz et al., 2006; Malaiyandi, Goodz et al., 2006; Malaiyandi, Lerman et al., 2006;
Mwenifumbo et al., 2007; Mwenifumbo, Al Koudsi et al., 2008). As such, the 3HC/COT
ratio appears to be a good indicator of CYP2A6 activity towards nicotine for the majority of
individuals. However, it remains to be determined whether this ratio is a good indicator of
activity towards other CYP2A6 substrates such as tobacco-specific nitrosamines or clinically
used pharmaceuticals such as tegafur and letrozole (Ikeda, Yoshisue et al., 2000; Tomizawa
and Casida, 2003). In addition, phenotype measures can be limited if the environmental
stimulus altering enzyme function is only transient, such as temporary exposure to inducers
or inhibitors. In contrast, genetic information is stable throughout the lifetime of an
individual. Finally, the greater cost and time associated with detecting metabolite levels in
biological matrices may limit the use of phenotype measures in large-scale population
studies.
As such, the choice of which measure to use ultimately depends on several factors, such as
the purpose of study, sample population of interest, and budget and/or time constraints.
Collection of both genetic and phenotype information in our clinical trial of African-
American light smokers, and a recent smoking cessation trial in Caucasians (Lerman, Jepson
et al., 2010), has the additional benefit of accounting for limitations in either measure, thus
further aiding interpretation of the results.
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SECTION 2: IMPACT OF CYP2A6 GENETIC VARIATION ON SMOKING
BEHAVIOURS IN AFRICAN-AMERICAN LIGHT SMOKERS
2.1. Smoking initiation
2.1.1. Factors associated with smoking initiation in African-Americans
The majority of smoking initiation occurs during adolescence; however, African-Americans
consistently report later ages of smoking initiation compared to Caucasians, with a large
proportion of individuals reporting onset at ages 18 to 20 instead of the early teen years
(Kandel et al., 2004; Trinidad, Gilpin et al., 2004; Trinidad, Gilpin et al., 2004).
Furthermore, only 10% of African-American high school students reported smoking at least
one cigarette in the past month whereas 23% of Caucasian students reported doing so
(Centers for Disease Control and Prevention, 2010). Potential reasons for this delayed onset
of smoking have been explored. Even though peer influence is often a strong predictor of
smoking initiation among Caucasians, this was not associated with current and lifetime
smoking among African-American youths (Landrine et al., 1994; Griesler and Kandel, 1998;
Gritz et al., 1998; Mermelstein, 1999). Parental smoking, weaker parent-child relationships
and inconsistent discipline are also known to contribute to problem behaviours such as
smoking during adolescence (Skinner et al., 2009), although the influence of parental
smoking on smoking has not been as consistently found among African-American
adolescents as with Caucasian adolescents (Hu et al., 1995; Griesler and Kandel, 1998; Gritz,
Prokhorov et al., 1998; Mermelstein, 1999). African-American youths may be protected
from smoking initiation as they appear to receive stronger anti-smoking messages from
parents compared to Caucasians, with stricter parental guidelines set and clearly stated
consequences for smoking (Mermelstein, 1999; Skinner, Haggerty et al., 2009). As such,
African-Americans may have more protective factors against the development of smoking
initiation during adolescence that may in part explain the observed delay in onset.
170
Interestingly, African-American adolescents also have lower rates of alcohol and illicit drug
use compared to Caucasians, suggesting that these protective effects may also influence
initiation of other drugs of abuse (Szapocznik et al., 2007).
2.2. Cigarette consumption
2.2.1. Light smoking behaviours among African-Americans
A higher proportion of African-American smokers consume 10 or fewer CPD compared to
Caucasians although reasons for this are not well known. African-Americans experience
substantial socioeconomic disparities; they have the lowest education attainment, highest
poverty rates, and lowest median income compared to all other racial/ethnic groups (Us
Bureau of the Census et al., 2004; Us Bureau of the Census et al., 2005). Socioeconomic
status is an important determinant of smoking behaviours (Novotny, Warner et al., 1988;
Townsend et al., 1994; Graham et al., 1999). African-Americans were more likely than
Caucasians to report that cigarette tax increases had some impact on their smoking
behaviours, resulting in smoking reduction and increased quit attempts (Frieden et al., 2005).
In addition, African-Americans are more likely to illegally purchase single cigarettes which
may contribute to their lower levels of daily consumption (Klonoff et al., 1994). However,
differences in socioeconomic status are unlikely to fully account for the unique smoking
patterns observed among African-Americans. Light smoking is also highly prevalent among
individuals of Black-African descent in Canada, who are biologically similar to African-
Americans, yet income and employment status were not associated with smoking status or
the amount of cigarettes smoked per day (Mwenifumbo, Sellers et al., 2008).
It is possible that African-Americans are biologically more sensitive to the effects of
nicotine. It has been hypothesized that the slower rates of nicotine metabolism among
171
African-Americans contribute to their lower levels of cigarette consumption, although
differences in the function of nAChRs or modulation of the brain reward pathway by nicotine
may also play a role. In a focus group of adult African-American light smokers who have
smoked an average of 7 CPD for 22 years, many individuals reported they had great
difficulty smoking a whole cigarette at a time and that smoking a cigarette too fast or too
many consecutively made them feel dizzy and light-headed (Okuyemi et al., 2003). Many
also reported smoking while in the presence of food or alcohol, and that smoking is often
dependent on cigarette availability (Okuyemi, Scheibmeir et al., 2003). Furthermore, a
recent study examined the acoustic startle reflex, a reliable index of how emotional stimuli
are processed, in response to images of smoking-related cues or images designed to trigger
positive or negative affect among African-Americans and Caucasians (Lam et al., 2008).
Following acute nicotine administration, African-Americans had increased positive affect
when exposed to images of smoking-related cues while Caucasians had decreased negative
affect when exposed to unpleasant images (Lam, Robinson et al., 2008). Thus, nicotine may
differentially alter emotional processing between the two racial/ethnic groups, suggesting
relapse may be more likely to occur in response to smoking-related cues for African-
Americans, whereas Caucasians may be more susceptible to relapse under situations that
invoke negative affect (Lam, Robinson et al., 2008).
There is evidence to suggest that the lower cigarette consumption among African-Americans
compared to Caucasians is apparent even during the initial learning stages of smoking. In a
longitudinal study of males aged 10 to 25, African-Americans had lower prevalence rates of
cigarette use and reported smoking fewer cigarettes at virtually every age compared to
Caucasians (White et al., 2004). For Caucasians, the quantity of cigarettes smoked increased
most rapidly from ages 13 to 15 and peaked at ages 20 to 22 at approximately 20 CPD. In
172
contrast, among African-Americans, cigarette consumption increased most rapidly between
ages 17 to 18, with use also peaking at age 20 but at approximately 10 CPD (White, Nagin et
al., 2004). As such, African-Americans appear to increase their cigarette consumption levels
at a later age, and do not reach the high levels of use that are observed among Caucasians.
2.2.2. Comparisons between African-American light and moderate/heavy smokers
A limited number of studies have drawn comparisons between African-American light (10 or
fewer CPD) and moderate (11 to 19 CPD) to heavy (20 or more CPD) smokers to better
understand the factors contributing to light smoking patterns in this racial/ethnic group.
African-American light smokers were more likely to be females, initiated smoking at a later
age, and smoked for a shorter duration compared to African-American moderate to heavy
smokers (Okuyemi, Ahluwalia et al., 2001; Okuyemi et al., 2004). African-American light
smokers also had greater positive affect, less depressive symptoms according to the CES-D
scale, and lower scores on the Perceived Stress Scale compared to African-American
moderate to heavy smokers (Businelle et al., 2009).
In terms of smoking patterns, African-American light smokers were less likely to smoke their
first cigarette of the day within 30 minutes of waking and had lower dependence scores
compared to African-American moderate to heavy smokers (Choi et al., 2004; Businelle,
Kendzor et al., 2009). These light smokers were equally willing to participate in a formal
smoking cessation program, were more motivated to quit, and had greater confidence in their
ability to quit compared to moderate to heavy smokers (Okuyemi, Ahluwalla et al., 2004;
Businelle, Kendzor et al., 2009). In spite of this, African-American light smokers had just as
much difficulty quitting as those with higher levels of consumption. African-American light
smokers remained abstinent for similar durations as moderate to heavy smokers prior to
173
relapsing according to retrospective reports of their most recent quit attempts (Choi,
Okuyemi et al., 2004). Furthermore, the low quit rates in our clinical trial of African-
American light smokers were comparable to the quit rates observed in a clinical trial of
African-American moderate to heavy smokers (Ahluwalia, Harris et al., 2002; Ahluwalia,
Okuyemi et al., 2006).
2.3. Tobacco dependence
2.3.1. Dependence in African-American light smokers
The Fagerström Test for Nicotine Dependence (FTND), the most commonly used scale to
assess tobacco dependence, was developed primarily as a measure of physical dependence
that focuses on smoking as a way to acquire nicotine in order to relieve or avoid withdrawal
symptoms. However, dependence is a multi-dimensional construct and newer measures,
such as the Nicotine Dependence Syndrome Scale and Wisconsin Inventory of Smoking
Dependence Motives, have been developed to better capture the many other aspects of
dependence. For example, these measures also examine the withdrawal symptoms and
cravings present during abstinence, the contexts under which smoking occurs (e.g. in
response to mood or under certain social or environmental situations), and the importance of
the sensory experience of smoking (Piper, Piasecki et al., 2004; Shiffman et al., 2004).
These other components are likely to be important in the manifestation of tobacco
dependence, particularly among light smokers. Indeed, in a sample of light smokers (average
12 CPD) from Switzerland, the FTND appeared to be measuring no more than the number of
cigarettes smoked per day (Etter et al., 1999). When three dependence scales (FTND, ICD-
10 and DSM-IV) were administered to a sample of Black-African descent, individuals were
not consistently defined as dependent using these various measures, suggesting they may be
capturing distinct sub-populations of smokers and/or different dimensions of dependence
174
(personal communications). Tobacco dependence has not been well defined among African-
Americans and further research is needed to identify the factors motivating smoking
behaviours in this population.
2.3.2. Models of tobacco dependence
A number of models have been proposed to explain tobacco dependence; some of these were
initially derived from observations of alcohol, stimulant or opiate dependence (Shadel,
Shiffman et al., 2000; Glautier, 2004; Tiffany St et al., 2004). The dependence models that
have been proposed are not mutually exclusive and can be present in different individuals in
various degrees. The traditional negative reinforcement model of tobacco dependence,
whereby use is mainly driven by physical dependence and avoidance of withdrawal effects,
has limitations in explaining light smoking behaviours. Some of the other theories that have
been proposed may help explain how individuals can sustain low levels of consumption, yet
appear to have great difficulty stopping use.
2.3.2.1. Reinforcement theories
Negative reinforcement models suggest tobacco dependence is driven by smokers attempting
to avoid or relieve the aversive withdrawal symptoms that develop during abstinence
(Eissenberg, 2004). In contrast, positive reinforcement models propose that the immediate
rewarding effects of smoking lead to further repetition of the behaviour (Shadel, Shiffman et
al., 2000). The role of positive rather than negative reinforcing properties of smoking may be
more important in maintaining the behaviour among light smokers. The low and sporadic
smoking patterns observed in light smokers likely result in plasma nicotine levels that
fluctuate widely over the course of the day due to the short half-life of nicotine (Benowitz
and Jacob P 3rd, 1994). Cigarette consumption did not differ according to the rate of
175
nicotine metabolism among African-American light smokers, in contrast to observations in
Caucasian moderate to heavy smokers (Rao, Hoffmann et al., 2000; Schoedel, Hoffmann Eb
et al., 2004). This suggests that strict regulation of nicotine plasma levels, presumably to
avoid the development of withdrawal symptoms, is not a significant determinant of smoking
behaviours in this population.
2.3.2.2. Classical conditioning theories
Drug dependence is an associative learning process involving classical Pavlovian
conditioning (Shadel, Shiffman et al., 2000; Glautier, 2004; Tiffany St, Conklin Ca et al.,
2004). Drugs with physiological and subjective effects that are repeatedly administered
within the same context will result in the context itself being able to elicit effects in the
absence of the drug (Caggiula et al., 2002; Chaudhri, Caggiula et al., 2006). Although
nicotine is thought to be the primary reinforcer present in tobacco smoke, it has relatively
weak reinforcing properties when administered alone (Caggiula, Donny et al., 2002;
Chaudhri, Caggiula et al., 2006). As such, it has been proposed that nicotine can enhance the
reinforcing properties of non-pharmacological stimuli associated with the drug (Caggiula,
Donny et al., 2002; Chaudhri, Caggiula et al., 2006). These non-nicotine components
include social reinforcement, emotional reinforcement, and reinforcement derived from
sensory modalities such as the sight, taste, and smell associated with cigarette smoking
(Chaudhri, Caggiula et al., 2006). Exposure to these smoking related cues can strongly
enhance the urge to smoke and is often a cause of relapse (Van Gucht et al.; Perkins et al.,
1994).
Smoking denicotinized cigarettes can relieve craving and withdrawal symptoms, presumably
because of the reinforcing properties of the non-nicotine components of smoking, although
176
individuals will prefer cigarettes that contain nicotine if given a choice (Shahan et al., 1999;
Rose et al., 2004; Chaudhri, Caggiula et al., 2006). Studies that test whether denicotinized
cigarettes can satisfy cravings, or if they are preferred to a similar degree as cigarettes
containing nicotine, in African-American light smokers will be useful in determining the role
of nicotine in maintaining smoking behaviours. In addition, ecological momentary
assessments that ask smokers to report their smoking experiences in real-time over the course
of the day on a hand-held computer will be useful in determining the mood states and
environmental contexts associated with smoking in African-American light smokers. Such
studies will help identify the cues that are important motivators of smoking behaviours
within a naturalistic setting.
The ability of nicotine to enhance the reinforcing properties of non-nicotine stimuli has
important implications as smoking is a complex behaviour involving more than just the
acquisition and maintenance of nicotine levels. For intervention methods to successfully aid
smoking cessation, they need to account for these other behavioural components that may be
particularly salient among light smokers.
2.3.2.3. Importance of social and cultural contexts
The expression of tobacco dependence is contingent upon numerous sociocultural factors.
Societal factors can influence drug dependence by limiting access through pricing, taxes and
legality of use (Shadel, Shiffman et al., 2000). Cultural perceptions of smoking, such as
smoking to facilitate social interactions or smoking as a sign of social distinction, are also
important determinants of use (Shadel, Shiffman et al., 2000). Acculturation, the process by
which individuals from foreign countries adopt the cultural and social norms of their host
country, can also be a strong predictor of smoking behaviours. African-Americans born in the
177
Caribbean or Africa are less likely to be ever or current smokers compared to those born in
the United States (Taylor et al., 1997; King et al., 1999; Bennett et al., 2008). Individuals
who identify more strongly with African-American culture, such as having similar family
values and practices, childhood experiences or growing up in predominantly African-
American communities, were more likely to be smokers (Klonoff et al., 1996; Klonoff et al.,
1999). African-Americans were also more likely to smoke menthol cigarettes if they believed
most African-American smokers preferred this type of cigarettes (Allen et al., 2007). The
tobacco industry has also targeted marketing strategies at African-Americans, with menthol
cigarette brands such as Kool and Newport heavily advertised in magazines oriented towards
these readers (King Iii et al., 2000; Landrine et al., 2005).
Variability in the rate of nicotine metabolism may contribute to differences in smoking
patterns between racial/ethnic groups. However, sociocultural contexts are also of
considerable importance, and the influence of CYP2A6 on smoking behaviours is likely highly
contingent on the environmental context. The lower daily cigarette consumption observed
among African-Americans would be predicted given their slower rates of nicotine metabolism
compared to Caucasians (Benowitz, Perez-Stable et al., 1999; Benowitz, Perez-Stable et al.,
2002; Trinidad, Perez-Stable et al., 2009). In contrast, Hispanics have similar rates of nicotine
metabolism as Caucasians, yet they report lower daily cigarette consumption (Trinidad, Perez-
Stable et al., 2009). Smoking behaviours among Hispanics is strongly associated with the
degree of acculturation, with those who identify more strongly with mainstream culture in the
United States being more likely to smoke and consuming greater number of cigarettes daily
(Wilkinson et al., 2005). As another example, Asians living in their home countries (e.g.
China and Japan) tend to have high levels of cigarette consumption, despite their slow rates of
nicotine metabolism, as smoking is socially and culturally accepted and even encouraged for
178
males in these countries (Yang et al., 1999; World Health Organization, 2002). It is notable
that among these Asian moderate to heavy smokers, CYP2A6 slow metabolizers reported
smoking fewer cigarettes per day compared to normal metabolizers. Further investigations are
needed to determine whether CYP2A6 is associated with cigarette consumption among Asian-
Americans, who tend to be light smokers unlike their counterparts back in their native home
countries.
2.4. Smoking cessation
Numerous studies have found that African-Americans were less likely to quit smoking
compared to Caucasians (Novotny, Warner et al., 1988; King, Polednak et al., 2004; Agrawal
et al., 2008; Fu et al., 2008; Piper et al., 2010). Few studies have explored the perceptions
about smoking, motivations for smoking cessation or experiences with previous quit attempts
specifically among African-American light smokers. In a focus group of African-American
light smokers, the main reasons listed for wanting to quit smoking included restrictions at
home and concerns of exposing children to secondhand smoke, as well as general health
concerns such as fear of developing cancer, wanting to stay physically fit and having fresher
breath (Okuyemi, Scheibmeir et al., 2003). Concerns about future quit attempts were
expressed due to the failures of past attempts, with many reporting they were able to abstain
from smoking for only a few days before relapsing as a result of withdrawal symptoms such
as anxiety and irritability (Okuyemi, Scheibmeir et al., 2003).
The African-American light smokers enrolled in our clinical trial had made an average of
three previous quit attempts in the past year despite strong motivation and confidence to quit
smoking (Okuyemi et al., 2007; Okuyemi et al., 2007). Variables that have been associated
with more successful treatment outcomes in Caucasian moderate to heavy smokers, such as
179
being male and older age (Sherman et al., 1996; Wetter et al., 1999; Ferguson et al., 2003;
Grandes et al., 2003), were also predictors of higher abstinence rates in African-American
light smokers (Nollen, Mayo Ms et al., 2006). Furthermore, post-cessation weight gain,
which is often a cause of relapse during quit attempts among Caucasian moderate to heavy
smokers, may also influence the ability to achieve abstinence in African-American light
smokers (Parsons et al., 2009). Individuals with concerns of weight changes from smoking
cessation were less confident in their ability to refrain from smoking (Thomas et al., 2008).
Moreover, individuals with higher BMI were more likely to quit smoking (Nollen, Mayo Ms
et al., 2006), which may be due in part to their fewer smoking-related weight control
expectancies or slower rates of nicotine metabolism (Thomas, Pulvers et al., 2008). Low
socioeconomic status, another predictor of poorer smoking cessation outcomes among
Caucasian moderate to heavy smokers, was also associated with abstinence in African-
American light smokers (Nides et al., 1995; Gilman et al., 2003; Broms et al., 2004).
African-American light smokers with income of less than $1 800 per month were
significantly less likely to quit smoking compared to those with higher income (Nollen,
Mayo Ms et al., 2006).
2.4.1. Impact of CYP2A6 on smoking cessation
Based on studies in moderate to heavy smoking Caucasians, the higher smoking cessation
rates among CYP2A6 slow metabolizers was originally thought to result from their lower
number of cigarettes smoked daily. Fewer repetitions of smoking over the course of the day
should allow for easier extinction of the behaviour. While lower levels of cigarette
consumption is generally associated with increased likelihood of smoking cessation (Hellman
et al., 1991; Hymowitz et al., 1997), it is notable that in previous clinical trials of smoking
cessation among Caucasian moderate to heavy smokers, the higher quit rates among
180
CYP2A6 slow metabolizers remained even after accounting for amount of cigarettes smoked
at baseline (Lerman, Tyndale et al., 2006; Patterson, Schnoll et al., 2008; Lerman, Jepson et
al., 2010). It is possible that the higher quit rates among CYP2A6 slow metabolizers may be
a reflection of how dependence is manifested in these individuals. Previous work has found
that CYP2A6 slow metabolizers report fewer cravings (Piper, Mccarthy et al., 2008),
experience less severe withdrawal symptoms (Kubota, Nakajima-Taniguchi et al., 2006) and
are less likely to smoke within five minutes of waking (Kubota, Nakajima-Taniguchi et al.,
2006; Malaiyandi, Lerman et al., 2006).
Interestingly, among African-American light smokers, slow CYP2A6 activity was associated
with an increased likelihood of smoking cessation even though cigarette consumption did not
differ according to the rates of nicotine metabolism. While the mechanisms underlying these
observations remain to be elucidated, it is possible that even among African-American light
smokers, CYP2A6 slow metabolizers have less severe withdrawal symptoms and cravings
compared to normal metabolizers, allowing them to maintain abstinence better. Further
studies in laboratory and naturalistic settings are needed to elucidate how CYP2A6 activity
influences smoking cessation in both light and moderate to heavy smokers. For example,
tests of cognitive function and attentional biases, as well as responses to smoking-related
cues during smoking abstinence, may provide further insight into the processes occurring
during cessation attempts that contribute to cravings and subsequent relapse.
Tobacco addiction results from a series of neuroadaptative changes leading to alterations in
the function of the brain reward system (Kreek et al., 1998; Mao and Mcgehee, 2010). Our
findings suggest that although smoking behaviours among these African-American light-
smoking adults do not appear to be primarily driven by the maintenance of nicotine levels,
181
variability in the levels of nicotine may have been an important determinant in how the brain
reward system was modulated during the early learning stages of smoking. There is evidence
to support a role for CYP2A6 in the acquisition of tobacco dependence among Caucasian
adolescents (O'loughlin, Paradis et al., 2004; Audrain-Mcgovern, Koudsi et al., 2007); it
would be of interest to determine how this gene contributes to the acquisition of tobacco
dependence in African-Americans.
2.4.2. Gender differences in smoking cessation outcomes in African-Americans
It has been proposed that males are more likely to smoke for pharmacological reinforcement
mediated by nicotine, while females are more likely to smoke for psychological
reinforcement gained through social interactions and stress alleviation (Perkins, 1996;
Perkins, 2001). Gender differences in smoking cessation have been reported, and there is
some evidence to suggest females are less successful at quitting compared to males (Perkins,
2001; Schnoll et al., 2009). While conflicting data exist to support gender differences in
withdrawal symptoms, hormonal changes during the menstrual cycle may mimic or
exacerbate symptoms such as irritability and moodiness, increasing the chance of relapse
(Carpenter et al., 2006).
Unique biological predispositions for tobacco dependence may also contribute to gender
differences in smoking behaviours. Several examples of gene by gender effects with
smoking cessation outcomes have been reported. The COMT Val105/158Met allele has been
associated with smoking abstinence among Caucasian females but not males in two
independent samples including a clinical trial for NRT and a case-control study of former and
current smokers (Colilla S et al., 2005). COMT can contribute to estrogen metabolism by
inactivating 2-hydroxy-estrogens via methylation (Creveling, 2003), and estrogen was found
182
to regulate the expression of COMT such that lower levels of the enzyme were found in
females compared to males (Harrison et al., 2007). In addition, the AA genotype of the
OPRM1 118 A>G SNP (N40E) was associated with higher smoking abstinence rates among
Caucasian males whereas females with this genotype had the lowest quit rates (Munafo et al.,
2007). A haplotype by gender effect in a longitudinal study of African-American smokers
was reported where the GTG haplotype within the dopamine D2 receptor gene
(DRD2/ANKK1) was associated with greater smoking cessation among males but not females
(David et al.). CYP2A6 activity was associated with smoking cessation outcomes in our
sample of African-American females, although these effects were not significantly different
among the males. CYP2A6 can be induced by estrogens and females have higher rates of
nicotine clearance (Benowitz, Lessov-Schlaggar Cn et al., 2006; Higashi, Fukami et al.,
2007). As such, the impact of CYP2A6 on smoking behaviours may be more pronounced
among females compared to males. However, the effect of CYP2A6 on smoking cessation
did not differ by gender in studies of Caucasian moderate to heavy smokers (Lerman,
Tyndale et al., 2006; Patterson, Schnoll et al., 2008; Lerman, Jepson et al., 2010). While this
gene by gender effect may be a specific finding among African-Americans, it is notable that
there was an over-representation of females in the study, and the analyses in males may have
been underpowered. Therefore, further replication of these findings among African-
Americans is necessary.
2.4.3. Improving treatment outcomes for smoking cessation
Our clinical trial of African-American light smokers is the first to examine the efficacy of
pharmacotherapy and two forms of behavioural counseling for smoking cessation in this
group. Treatment adherence is a strong predictor of smoking cessation outcome (Stapleton et
al., 1995; Shiffman, Rolf et al., 2002) and the World Health Organization reports adherence
183
rates for smoking cessation treatments vary from 5 to 96% (World Health Organization,
2003). Approximately 72% of the participants in our study were adherent to the counseling
program by attending at least 5 of the 6 counseling sessions (Ahluwalia, Okuyemi et al.,
2006; Okuyemi, Zheng et al.). In contrast, only 36% of the sample reported adherence to
gum (nicotine or placebo), defined as using 75% or more of the total prescribed gum over the
8 week treatment period (Okuyemi, Zheng et al.). The poor adherence to the 2 mg nicotine
gum may have contributed to its lack of efficacy (Okuyemi, Zheng et al.). A low adherence
rate to gum treatment is consistent with previous reports in other racial/ethnic groups and
may be reflective of improper usage of the gum leading to insufficient nicotine replacement,
and undesirable effects of the gum such as dislike of its taste (Shiffman, Rolf et al., 2002;
Schneider, Olmstead et al., 2004; Lam, Abdullah et al., 2005; Schneider, Terrace et al.,
2005). Factors associated with greater adherence to gum use among African-American light
smokers included higher BMI, more quit attempts in the past year, higher baseline exhaled
CO, and higher perceived stress (Okuyemi, Zheng et al., 2010). The lack of efficacy of the 2
mg nicotine gum in aiding smoking cessation among African-American light smokers cannot
be generalized to higher doses of gum or other formulations of NRT, and further
investigations are needed to determine their efficacy in this population. Additional studies
are also needed to determine if other forms of pharmacotherapies (i.e. bupropion or
varenicline) are beneficial in aiding smoking cessation for this population.
African-American light smokers are likely a heterogeneous group, representing individuals
who were once heavier smokers, those who are still progressing to heavier smoking, and
those who have maintained low levels of consumption throughout their smoking careers. In
an analysis of the African-American light smokers in our clinical trial, 18% of the sample
quit smoking while 41% reduced their cigarette consumption by an average of 5.8 CPD by
184
week 26 follow-up (Berg et al.). Predictors of cessation compared to reduction included
enrolment into the health education counseling, older age, being male, lower baseline
cigarettes smoked, lower baseline cotinine levels, higher nicotine dependence scores, higher
BMI, lower levels of stress and higher scores on negative social impression (Berg, Thomas et
al.). Smoking reduction is an important step towards successful cessation (Hyland et al.,
2005; Broms et al., 2008), and gradual reduction of cigarettes smoked prior to target quit
date, as opposed to quitting abruptly, may be an alternative approach for encouraging
smokers to quit (Lindson et al., 2010). The observation that a large proportion of African-
American light smokers were able to reduce their cigarette consumption suggests such
methods may be useful in helping these individuals quit.
The high level of consent for genetic testing (83%) suggests that this population is receptive
to the idea of using genetic research to advance our understanding of how individual
differences contribute to smoking behaviours and how such knowledge may be eventually
used to improve treatment outcomes (Cox et al., 2007). Based on clinical trials in moderate
to heavy Caucasian smokers, it appears that CYP2A6 slow metabolizers would respond well
to nicotine patch therapy in conjunction with counseling, whereas alternative treatment such
as bupropion should be considered for CYP2A6 faster metabolizers (Lerman, Tyndale et al.,
2006; Patterson, Schnoll et al., 2008; Schnoll, Patterson et al., 2009; Lerman, Jepson et al.,
2010). The efficacy of non-NRT pharmacotherapies, such as bupropion and varenicline,
remains to be tested in African-American light smokers. Further studies into the biological
and environmental factors that are predictive of smoking in this population will lead to the
development of more efficacious intervention methods.
2.5. Utility of biomarkers of tobacco exposure among African-Americans
185
Cigarette smoking is a complex behaviour with large variability observed in smoking
topography. As such, self-reports of consumption levels are subjective and can be biased
indicators of tobacco smoke exposure. A number of biomarkers have been proposed for a
variety of purposes. For instance, biomarkers are often used to verify smoking abstinence in
clinical trials of smoking cessation or for research studies, and in large-scale population
health surveys. Biomarkers are also useful for studying the effects of environmental tobacco
smoke exposure on health outcomes and validating claims of reduced harm for new tobacco
products.
Biochemical verification is often used to control for the tendency to over-report smoking
abstinence in clinical trials for smoking cessation. In our clinical trial of African-American
light smokers, exhaled CO was collected at end-of-treatment (week 8), and both exhaled CO
and plasma cotinine were collected at follow-up (week 26) to verify smoking abstinence. At
week 26, 26% of the sample reported abstinence, 21% of the sample were abstinent as
verified by exhaled CO and only 13% of the sample were abstinent as verified by plasma
cotinine (Ahluwalia, Okuyemi et al., 2006). This suggests that many individuals may have
been incorrectly classified as abstinent when using exhaled CO to validate smoking status.
As such, cotinine may be a more useful biomarker for verifying smoking abstinence
compared to exhaled CO in African-American light smokers due to its short half-life and
contributions from environmental sources (Scherer, 2006). However, exhaled CO is often
used as the sole method for biochemical verification of smoking status in clinical trials given
its detection is much simpler and cheaper compared to cotinine (Benowitz, Peyton J Iii et al.,
2002; Jatlow et al., 2008). Our data suggest cotinine should be used to verify smoking
abstinence in light smokers whenever possible, and among individuals exposed to NRT,
186
other biomarkers such as the nicotine-related alkaloids anabasine and anatabasine may have
greater utility (Benowitz, Peyton J Iii et al., 2002).
Biomarkers of tobacco smoke exposure are needed among African-American light smokers
given their higher incidences of tobacco-related illnesses in spite of lower self-reported
cigarette consumption (Ries, Harkins D et al., 2006; American Cancer Society, 2008;
Kirkpatrick and Dransfield Mt, 2009). Higher cotinine plasma levels, and cotinine per
cigarette, have been observed among African-American smokers (Caraballo, Giovino et al.,
1998; Benowitz, Perez-Stable et al., 1999; Moolchan and Franken Fh, 2006; Signorello, Cai
et al., 2009). One interpretation is that African-Americans have greater exposure to tobacco
smoke despite lower self-reported consumption. Alternatively, our study suggests rates of
CYP2A6 activity can also significantly alter cotinine levels in this population, with slow
metabolizers having significantly higher cotinine levels. In contrast, among Caucasian
moderate to heavy smokers where only a small proportion of individuals are CYP2A6 slow
metabolizers, cotinine levels are reflective of the number of cigarettes smoked per day, and
CYP2A6 slow metabolizers have significantly lower cotinine levels compared to normal
metabolizers (Rao, Hoffmann et al., 2000).
It has been proposed that the higher prevalence of menthol cigarette use by African-
Americans contributes to the disproportionately higher rates of tobacco-related illnesses
among this group, although findings have not been uniformly supported across studies
(Sidney et al., 1995; Werley, Coggins et al., 2007; Heck, 2010). The cooling effect of
menthol is thought to result in deeper inhalation patterns, and there is some evidence to
support that menthol cigarette smokers have higher exhaled CO and cotinine levels (Clark,
Gautam et al., 1996). However, these findings have also been mixed (Werley, Coggins et al.,
187
2007; Heck, 2009; Muscat, Chen et al., 2009; Heck, 2010), and exhaled CO or cotinine levels
were similar between menthol cigarette smokers and those who smoke regular cigarettes in
our large study of African-American light smokers. A recent study reported that other
biomarkers of tobacco exposure such as NNAL and thiocyanate did not differ between
menthol and regular cigarette smokers (Muscat, Chen et al., 2009). However, the ratio of
NNAL-glucuronide to NNAL was lower among menthol smokers, suggesting they may have
reduced detoxification of this carcinogen (Muscat, Chen et al., 2009). The addition of
menthol to cigarettes has been controversial as it may potentially increase the risk of adverse
health effects. Clarification of the effect of menthol on tobacco smoke exposure is essential
particularly since the Food and Drug Administration now has some authority in the
regulation of tobacco products, including the ability to ban this additive from cigarettes.
CONCLUSIONS
Individuals of Black-African descent have high levels of genetic diversity as a result of their
complex demographic history, and their genomes contain a high number of unique genetic
variants, with each occurring at a low frequency in the population. Until recently, the
CYP2A6 gene has not been extensively studied in populations of Black-African descent. We
have identified many new CYP2A6 genetic variants in the past five years that help account
for the slower rates of nicotine and cotinine metabolism observed in this population. Our
study is also the first to examine the impact of CYP2A6 on smoking behaviours in African-
American light smokers. The results found herein suggest CYP2A6 activity has a unique
influence on smoking behaviours in this population. For example, African-American light
smokers do not appear to alter their cigarette consumption to maintain constant plasma
nicotine levels, and nicotine gum was not successful in aiding smoking cessation. Thus, the
188
factors that are salient in motivating smoking behaviours in this population remain to be
determined. Elucidation of the mechanisms underlying the greater ability of CYP2A6 slow
metabolizers to quit smoking will also provide a better understanding of how tobacco
dependence is manifested in African-American light smokers. In addition, biomarkers
previously validated in Caucasian moderate to heavy smokers have a number of limitations
in African-American light smokers. Given the higher risk of tobacco-related illnesses among
African-Americans despite their lower self-reported cigarette consumption, it is of utmost
importance to assess the actual exposure level of this population to tobacco smoke and the
harmful compounds within.
189
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APPENDICES
Appendix A: Ho MK, Tyndale RF. Overview of the pharmacogenomics of cigarette smoking. Pharmacogenomics J., 2007. 7(2): 81-98. Reprinted with permission from Macmillan Publishers Ltd: Pharmacogenomics Journal, © 2010. All rights reserved. Appendix B: Ho MK, Tyndale RF. Role of CYP2A6 genetic variation on smoking behaviors and clinical implications. ASCO Education Book 2008. Reprinted with permission. © 2010 American Society of Clinical Oncology. All rights reserved. Appendix C: Mwenifumbo JC, Al Koudsi N, Ho MK, Zhou Q, Hoffmann EB, Sellers EM, Tyndale RF. Novel and established CYP2A6 alleles alter in vivo nicotine metabolism in a population of Black-African descent. Human Mutation. 2008. 29(5): 679 – 88. Reprinted with permissions © John Wiley and Sons. All rights reserved. Appendix D: Ho MK, Goldman D, Heinz A, Kaprio J, Kreek MJ, Li MD, Munafò MR, Tyndale RF. Breaking barriers in the genomics and pharmacogenetics of drug addiction. Clinical Pharmacology & Therapeutics. 2010. 88(6): 779-91. Reprinted by permission from Macmillan Publishers Ltd: Clinical Pharmacology & Therapeutics, © 2010. All rights reserved.