Dopamine D4 receptor gene variation moderates the efficacy of bupropion for smoking cessation

The association of genetic polymorphisms within the dopaminergic system with nicotine dependence: A narrative review

Nicotine, the main compound in cigarettes, leads to smoking addiction. Nicotine acts on the limbic dopamine reward loop in the midbrain by binding to nicotinic acetylcholine receptors, promoting the release of dopamine, and resulting in a rewarding effect or satisfaction. This satisfaction is essential for continued and compulsive tobacco use, and therefore dopamine plays a crucial role in nicotine dependence. Numerous studies have identified genetic polymorphisms of dopaminergic pathways which may influence susceptibility to nicotine addiction. Dopamine levels are greatly influenced by synthesis, storage, release, degradation, and reuptake-related genes, including genes encoding tyrosine hydroxylase, dopamine decarboxylase, dopamine transporter, dopamine receptor, dopamine 3-hydroxylase, catechol-O-methyltransferase, and monoamine oxidase. In this paper, we review research progress on the effects of polymorphisms in the above genes on downstream smoking behavior and nicotine dependence, to offer a theoretical basis for the elucidation of the genetic mechanism underlying nicotine dependence and future personalized treatment for smoking cessation.

A scoping review of smoking cessation pharmacogenetic studies to advance future research across racial, ethnic, and ancestral populations

Abstinence rates among smokers attempting to quit remain low despite the wide availability and accessibility of pharmacological smoking cessation treatments. In addition, the prevalence of cessation attempts and abstinence differs by individual-level social factors such as race and ethnicity. Clinical treatment of nicotine dependence also continues to be challenged by individual-level variability in effectiveness to promote abstinence. The use of tailored smoking cessation strategies that incorporate information on individual-level social and genetic factors hold promise, although additional pharmacogenomic knowledge is still needed. In particular, genetic variants associated with pharmacological responses to smoking cessation treatment have generally been conducted in populations with participants that self-identify as White race or who are determined to be of European genetic ancestry. These results may not adequately capture the variability across all smokers as a result of understudied differences in allele frequencies across genetic ancestry populations. This suggests that much of the current pharmacogenetic study results for smoking cessation may not apply to all populations. Therefore, clinical application of pharmacogenetic results may exacerbate health inequities by racial and ethnic groups. This scoping review examines the extent to which racial, ethnic, and ancestral groups that experience differences in smoking rates and smoking cessation are represented in the existing body of published pharmacogenetic studies of smoking cessation. We will summarize results by race, ethnicity, and ancestry across pharmacological treatments and study designs. We will also explore current opportunities and challenges in conducting pharmacogenomic research on smoking cessation that encourages greater participant diversity, including practical barriers to clinical utilization of pharmacological smoking cessation treatment and clinical implementation of pharmacogenetic knowledge.

Antidepressants for smoking cessation

BACKGROUND

The pharmacological profiles and mechanisms of antidepressants are varied. However, there are common reasons why they might help people to stop smoking tobacco: nicotine withdrawal can produce short-term low mood that antidepressants may relieve; and some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction.

OBJECTIVES

To assess the evidence for the efficacy, harms, and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, most recently on 29 April 2022.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in people who smoked, comparing antidepressant medications with placebo or no pharmacological treatment, an alternative pharmacotherapy, or the same medication used differently. We excluded trials with fewer than six months of follow-up from efficacy analyses. We included trials with any follow-up length for our analyses of harms.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard Cochrane methods. Our primary outcome measure was smoking cessation after at least six months' follow-up. We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Our secondary outcomes were harms and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropouts due to treatment. We carried out meta-analyses where appropriate.

MAIN RESULTS

We included a total of 124 studies (48,832 participants) in this review, with 10 new studies added to this update version. Most studies recruited adults from the community or from smoking cessation clinics; four studies focused on adolescents (with participants between 12 and 21 years old). We judged 34 studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk of bias did not change clinical interpretation of the results.  There was high-certainty evidence that bupropion increased smoking cessation rates when compared to placebo or no pharmacological treatment (RR 1.60, 95% CI 1.49 to 1.72; I2 = 16%; 50 studies, 18,577 participants). There was moderate-certainty evidence that a combination of bupropion and varenicline may have resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). However, there was insufficient evidence to establish whether a combination of bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.17, 95% CI 0.95 to 1.44; I2 = 43%; 15 studies, 4117 participants; low-certainty evidence). There was moderate-certainty evidence that participants taking bupropion were more likely to report SAEs than those taking placebo or no pharmacological treatment. However, results were imprecise and the CI also encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 23 studies, 10,958 participants). Results were also imprecise when comparing SAEs between people randomised to a combination of bupropion and NRT versus NRT alone (RR 1.52, 95% CI 0.26 to 8.89; I2 = 0%; 4 studies, 657 participants) and randomised to bupropion plus varenicline versus varenicline alone (RR 1.23, 95% CI 0.63 to 2.42; I2 = 0%; 5 studies, 1268 participants). In both cases, we judged evidence to be of low certainty. There was high-certainty evidence that bupropion resulted in more trial dropouts due to AEs than placebo or no pharmacological treatment (RR 1.44, 95% CI 1.27 to 1.65; I2 = 2%; 25 studies, 12,346 participants). However, there was insufficient evidence that bupropion combined with NRT versus NRT alone (RR 1.67, 95% CI 0.95 to 2.92; I2 = 0%; 3 studies, 737 participants) or bupropion combined with varenicline versus varenicline alone (RR 0.80, 95% CI 0.45 to 1.45; I2 = 0%; 4 studies, 1230 participants) had an impact on the number of dropouts due to treatment. In both cases, imprecision was substantial (we judged the evidence to be of low certainty for both comparisons). Bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.73, 95% CI 0.67 to 0.80; I2 = 0%; 9 studies, 7564 participants), and to combination NRT (RR 0.74, 95% CI 0.55 to 0.98; I2 = 0%; 2 studies; 720 participants). However, there was no clear evidence of a difference in efficacy between bupropion and single-form NRT (RR 1.03, 95% CI 0.93 to 1.13; I2 = 0%; 10 studies, 7613 participants). We also found evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I2 = 16%; 6 studies, 975 participants), and some evidence that bupropion resulted in superior quit rates to nortriptyline (RR 1.30, 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants), although this result was subject to imprecision. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion may increase SAEs (moderate-certainty evidence when compared to placebo/no pharmacological treatment). There is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with people receiving placebo or no pharmacological treatment. Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo, although bupropion may be more effective. Evidence also suggests that bupropion may be as successful as single-form NRT in helping people to quit smoking, but less effective than combination NRT and varenicline. In most cases, a paucity of data made it difficult to draw conclusions regarding harms and tolerability. Further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over other licensed smoking cessation treatments; namely, NRT and varenicline. However, it is important that future studies of antidepressants for smoking cessation measure and report on harms and tolerability.

The Streetlight Effect: Reappraising the Study of Addiction in Light of the Findings of Genome-wide Association Studies

Drug dependence has long been thought to have a genetic component. Research seeking to identify the genetic basis of addiction has gone through important transitions over its history, in part based upon the emergence of new technologies, but also as the result of changing perspectives. Early research approaches were largely dictated by available technology, with technological advancements having highly transformative effects on genetic research, but the limitations of technology also affected modes of thinking about the genetic causes of disease. This review explores these transitions in thinking about the genetic causes of addiction in terms of the "streetlight effect," which is a type of observational bias whereby people search for something only where it is easiest to search. In this way, the genes that were initially studied in the field of addiction genetics were chosen because they were the most "obvious," and formed current understanding of the biological mechanisms underlying the actions of drugs of abuse and drug dependence. The problem with this emphasis is that prior to the genomic era the vast majority of genes and proteins had yet to be identified, much less studied. This review considers how these initial choices, as well as subsequent choices that were also driven by technological limitations, shaped the study of the genetic basis of drug dependence. While genome-wide approaches overcame the initial biases regarding which genes to choose to study inherent in candidate gene studies and other approaches, genome-wide approaches necessitated other assumptions. These included additive genetic causation and limited allelic heterogeneity, which both appear to be incorrect. Thus, the next stage of advancement in this field must overcome these shortcomings through approaches that allow the examination of complex interactive effects, both gene × gene and gene × environment interactions. Techniques for these sorts of studies have recently been developed and represent the next step in our understanding of the genetic basis of drug dependence.

A 5-Factor Framework for Assessing Tobacco Use Disorder

Cigarette use is the leading cause of preventable death in the United States. Despite the well documented dangers of smoking, nearly 20% of adults report regular use of tobacco. A majority desire to discontinue but the long-term cessation success rate remains near 4%. One challenge to reducing the prevalence of tobacco use is an incomplete understanding of the individual correlates that reinforce continued use. Evidence from research on nicotine and tobacco suggests that Tobacco Use Disorder is a complex, and multifactorial condition. Personality traits, comorbidities, habits and lifestyle, genetics, socioeconomic status, and mental and physical health all contribute to the risk for dependence and to the likelihood of quitting. This perspective review provides an overview of some common factors that contribute to liability risk for Tobacco Use Disorder and a framework for assessing individual tobacco users. The framework includes 5 areas that research suggests contribute to continued tobacco use: nicotine addiction, psychological influences, behavioral dependencies, neurobiological factors, and social reinforcement. Nicotine addiction includes drug-seeking behavior and the role of withdrawal avoidance. Psychological and emotional states contribute to a perceived reliance on tobacco. Behavioral dependence is reinforced by associative and non-associative learning mechanisms. Neurobiological factors include genetic variables, variations in neurotransmitters and receptors, pharmacogenetics, and interaction between psychiatric illnesses and nicotine use and dependence. Finally, social reinforcement of smoking behavior is explained by a network phenomenon and consistent visual cues to smoke. A comprehensive assessment of individual tobacco users will help better determine appropriate treatment options to achieve improved efficacy and outcomes.

Antidepressants for smoking cessation

BACKGROUND

Whilst the pharmacological profiles and mechanisms of antidepressants are varied, there are common reasons why they might help people to stop smoking tobacco. Firstly, nicotine withdrawal may produce depressive symptoms and antidepressants may relieve these. Additionally, some antidepressants may have a specific effect on neural pathways or receptors that underlie nicotine addiction.

OBJECTIVES

To assess the evidence for the efficacy, safety and tolerability of medications with antidepressant properties in assisting long-term tobacco smoking cessation in people who smoke cigarettes.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Specialized Register, which includes reports of trials indexed in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO, clinicaltrials.gov, the ICTRP, and other reviews and meeting abstracts, in May 2019.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) that recruited smokers, and compared antidepressant medications with placebo or no treatment, an alternative pharmacotherapy, or the same medication used in a different way. We excluded trials with less than six months follow-up from efficacy analyses. We included trials with any follow-up length in safety analyses.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard Cochrane methods. We also used GRADE to assess the certainty of the evidence. The primary outcome measure was smoking cessation after at least six months follow-up, expressed as a risk ratio (RR) and 95% confidence intervals (CIs). We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Where appropriate, we performed meta-analysis using a fixed-effect model. Similarly, we presented incidence of safety and tolerance outcomes, including adverse events (AEs), serious adverse events (SAEs), psychiatric AEs, seizures, overdoses, suicide attempts, death by suicide, all-cause mortality, and trial dropout due to drug, as RRs (95% CIs).

MAIN RESULTS

We included 115 studies (33 new to this update) in this review; most recruited adult participants from the community or from smoking cessation clinics. We judged 28 of the studies to be at high risk of bias; however, restricting analyses only to studies at low or unclear risk did not change clinical interpretation of the results. There was high-certainty evidence that bupropion increased long-term smoking cessation rates (RR 1.64, 95% CI 1.52 to 1.77; I2 = 15%; 45 studies, 17,866 participants). There was insufficient evidence to establish whether participants taking bupropion were more likely to report SAEs compared to those taking placebo. Results were imprecise and CIs encompassed no difference (RR 1.16, 95% CI 0.90 to 1.48; I2 = 0%; 21 studies, 10,625 participants; moderate-certainty evidence, downgraded one level due to imprecision). We found high-certainty evidence that use of bupropion resulted in more trial dropouts due to adverse events of the drug than placebo (RR 1.37, 95% CI 1.21 to 1.56; I2 = 19%; 25 studies, 12,340 participants). Participants randomized to bupropion were also more likely to report psychiatric AEs compared with those randomized to placebo (RR 1.25, 95% CI 1.15 to 1.37; I2 = 15%; 6 studies, 4439 participants). We also looked at the safety and efficacy of bupropion when combined with other non-antidepressant smoking cessation therapies. There was insufficient evidence to establish whether combination bupropion and nicotine replacement therapy (NRT) resulted in superior quit rates to NRT alone (RR 1.19, 95% CI 0.94 to 1.51; I2 = 52%; 12 studies, 3487 participants), or whether combination bupropion and varenicline resulted in superior quit rates to varenicline alone (RR 1.21, 95% CI 0.95 to 1.55; I2 = 15%; 3 studies, 1057 participants). We judged the certainty of evidence to be low and moderate, respectively; in both cases due to imprecision, and also due to inconsistency in the former. Safety data were sparse for these comparisons, making it difficult to draw clear conclusions. A meta-analysis of six studies provided evidence that bupropion resulted in inferior smoking cessation rates to varenicline (RR 0.71, 95% CI 0.64 to 0.79; I2 = 0%; 6 studies, 6286 participants), whilst there was no evidence of a difference in efficacy between bupropion and NRT (RR 0.99, 95% CI 0.91 to 1.09; I2 = 18%; 10 studies, 8230 participants). We also found some evidence that nortriptyline aided smoking cessation when compared with placebo (RR 2.03, 95% CI 1.48 to 2.78; I2 = 16%; 6 studies, 975 participants), whilst there was insufficient evidence to determine whether bupropion or nortriptyline were more effective when compared with one another (RR 1.30 (favouring bupropion), 95% CI 0.93 to 1.82; I2 = 0%; 3 studies, 417 participants). There was no evidence that any of the other antidepressants tested (including St John's Wort, selective serotonin reuptake inhibitors (SSRIs), monoamine oxidase inhibitors (MAOIs)) had a beneficial effect on smoking cessation. Findings were sparse and inconsistent as to whether antidepressants, primarily bupropion and nortriptyline, had a particular benefit for people with current or previous depression.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that bupropion can aid long-term smoking cessation. However, bupropion also increases the number of adverse events, including psychiatric AEs, and there is high-certainty evidence that people taking bupropion are more likely to discontinue treatment compared with placebo. However, there is no clear evidence to suggest whether people taking bupropion experience more or fewer SAEs than those taking placebo (moderate certainty). Nortriptyline also appears to have a beneficial effect on smoking quit rates relative to placebo. Evidence suggests that bupropion may be as successful as NRT and nortriptyline in helping people to quit smoking, but that it is less effective than varenicline. There is insufficient evidence to determine whether the other antidepressants tested, such as SSRIs, aid smoking cessation, and when looking at safety and tolerance outcomes, in most cases, paucity of data made it difficult to draw conclusions. Due to the high-certainty evidence, further studies investigating the efficacy of bupropion versus placebo are unlikely to change our interpretation of the effect, providing no clear justification for pursuing bupropion for smoking cessation over front-line smoking cessation aids already available. However, it is important that where studies of antidepressants for smoking cessation are carried out they measure and report safety and tolerability clearly.

The VNTR 48 bp Polymorphism in the DRD4 Gene Is Associated with Higher Tobacco Smoking in Male Mexican Mestizo Smokers with and without COPD

Cigarette smoking is influenced by nicotine’s effects on dopaminergic activity, which appear to be moderated by genetic variation, particularly a variable number tandem repeat (VNTR, 48 bp) polymorphism in the third exon of the dopamine receptor gene (DRD4). Smokers with the VNTR ≥7 repeats (long, L allele) report markedly increased participation in some smoking behaviors; hence, our aim was to evaluate the association of the L allele in Mexican Mestizo smokers with and without COPD. The DRD4 VNTR 48 bp was genotyped in 492 Mexican Mestizo smokers: 164 COPD patients (≥20 cigarettes per day, cpd), 164 heavy smokers without COPD (HS, ≥20 cpd) and 164 light smokers without COPD (LS, 1–10 cpd). In the dominant model analysis (SL + LL vs. SS), men in the COPD and HS groups showed a statistical difference compared to LS (p = 0.01, OR = 2.06, CI 95% 1.17–3.64 and p = 0.05, OR = 1.88, CI 95% 1.03–3.45, respectively). In addition, by clustering smokers >20 cpd (COPD + HS) and comparing with the LS group, we found an association with increased risk of higher tobacco smoking p = 0.01, OR = 1.99, CI 95% 1.18–3.34. In conclusion, the long allele (L) in the VNTR of the DRD4 gene is associated with the risk of presenting higher tobacco smoking in male Mexican Mestizo smokers.

From genes to treatments: a systematic review of the pharmacogenetics in smoking cessation

Smoking cessation treatment outcomes may be heavily influenced by genetic variations among smokers. Therefore, identifying specific variants that affect response to different pharmacotherapies is of major interest to the field. In the current study, we systematically review all studies published in or after the year 1990 which examined one or more gene-drug interactions for smoking cessation treatment. Out of 644 citations, 46 articles met the inclusion criteria for the systematic review. We summarize evidence on several genetic polymorphisms (CHRNA5-A3-B4, CYP2A6, DBH, CHRNA4, COMT, DRD2, DRD4 and CYP2B6) and their potential moderating pharamacotherarpy effects on patient cessation efficacy rates. These findings are promising and call for further research to demonstrate the effectiveness of genetic testing in personalizing treatment decision-making and improving outcome.

Pathways to precision medicine in smoking cessation treatments

Cigarette smoking is highly addictive and modern genetic research has identified robust genetic influences on nicotine dependence. An important step in translating these genetic findings to clinical practice is identifying the genetic factors affecting smoking cessation in order to enhance current smoking cessation treatments. We reviewed the significant genetic variants that predict nicotine dependence, smoking cessation, and response to cessation pharmacotherapy. These data suggest that genetic risks can predict smoking cessation outcomes and moderate the effect of pharmacological treatments. Some pharmacogenetic findings have been replicated in meta-analyses or in multiple smoking cessation trials. The variation in efficacy between smokers with different genetic markers supports the notion that personalized smoking cessation intervention based upon genotype could maximize the efficiency of such treatment while minimizing side effects, thus influencing the number needed to treat (NNT) and the number needed to harm. In summary, as precision medicine is revolutionizing healthcare, smoking cessation may be one of the first areas where genetic variants may identify individuals at increased risk. Current evidence strongly suggests that genetic variants predict cessation failure and that cessation pharmacotherapy effectiveness is modulated by biomarkers such as nicotinic cholinergic receptor α5 subunit (CHRNA5) genotypes or nicotine metabolism ratio (NMR). These findings strengthen the case for the development and rigorous testing of treatments that target patients with different biological risk profiles.

Pharmacotherapy for smoking cessation: effects by subgroup defined by genetically informed biomarkers

BACKGROUND

Smoking cessation therapies are not effective for all smokers, and researchers are interested in identifying those subgroups of individuals (e.g. based on genotype) who respond best to specific treatments.

OBJECTIVES

To assess whether quit rates vary by genetically informed biomarkers within pharmacotherapy treatment arms and as compared with placebo. To assess the effects of pharmacotherapies for smoking cessation in subgroups of smokers defined by genotype for identified genome-wide significant polymorphisms.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group specialised register, clinical trial registries, and genetics databases for trials of pharmacotherapies for smoking cessation from inception until 16 August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that recruited adult smokers and reported pharmacogenomic analyses from trials of smoking cessation pharmacotherapies versus controls. Eligible trials included those with data on a priori genome-wide significant (P < 5 × 10-8) single-nucleotide polymorphisms (SNPs), replicated non-SNPs, and/or the nicotine metabolite ratio (NMR), hereafter collectively described as biomarkers.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. The primary outcome was smoking abstinence at six months after treatment. The secondary outcome was abstinence at end of treatment (EOT). We conducted two types of meta-analyses- one in which we assessed smoking cessation of active treatment versus placebo within genotype groups, and another in which we compared smoking cessation across genotype groups within treatment arms. We carried out analyses separately in non-Hispanic whites (NHWs) and non-Hispanic blacks (NHBs). We assessed heterogeneity between genotype groups using T², I², and Cochrane Q statistics.

MAIN RESULTS

Analyses included 18 trials including 9017 participants, of whom 6924 were NHW and 2093 NHB participants. Data were available for the following biomarkers: nine SNPs (rs1051730 (CHRNA3); rs16969968, rs588765, and rs2036527 (CHRNA5); rs3733829 and rs7937 (in EGLN2, near CYP2A6); rs1329650 and rs1028936 (LOC100188947); and rs215605 (PDE1C)), two variable number tandem repeats (VNTRs; DRD4 and SLC6A4), and the NMR. Included data produced a total of 40 active versus placebo comparisons, 16 active versus active comparisons, and 64 between-genotype comparisons within treatment arms.For those meta-analyses showing statistically significant heterogeneity between genotype groups, we found the quality of evidence (GRADE) to be generally moderate. We downgraded quality most often because of imprecision or risk of bias due to potential selection bias in genotyping trial participants. Comparisons of relative treatment effects by genotypeFor six-month abstinence, we found statistically significant heterogeneity between genotypes (rs16969968) for nicotine replacement therapy (NRT) versus placebo at six months for NHB participants (P = 0.03; n = 2 trials), but not for other biomarkers or treatment comparisons. Six-month abstinence was increased in the active NRT group as compared to placebo among participants with a GG genotype (risk ratio (RR) 1.47, 95% confidence interval (CI) 1.07 to 2.03), but not in the combined group of participants with a GA or AA genotype (RR 0.43, 95% CI 0.15 to 1.26; ratio of risk ratios (RRR) GG vs GA or AA of 3.51, 95% CI 1.19 to 10.3). Comparisons of treatment effects between genotype groups within pharmacotherapy randomisation armsFor those receiving active NRT, treatment was more effective in achieving six-month abstinence among individuals with a slow NMR than among those with a normal NMR among NHW and NHB combined participants (normal NMR vs slow NMR: RR 0.54, 95% CI 0.37 to 0.78; n = 2 trials). We found no such differences in treatment effects between genotypes at six months for any of the other biomarkers among individuals who received pharmacotherapy or placebo.

AUTHORS' CONCLUSIONS

We did not identify widespread differential treatment effects of pharmacotherapy based on genotype. Some genotype groups within certain ethnic groups may benefit more from NRT or may benefit less from the combination of bupropion with NRT. The reader should interpret these results with caution because none of the statistically significant meta-analyses included more than two trials per genotype comparison, many confidence intervals were wide, and the quality of this evidence (GRADE) was generally moderate. Although we found evidence of superior NRT efficacy for NMR slow versus normal metabolisers, because of the lack of heterogeneity between NMR groups, we cannot conclude that NRT is more effective for slow metabolisers. Access to additional data from multiple trials is needed, particularly for comparisons of different pharmacotherapies.

Pharmacogenetic Optimization of Smoking Cessation Treatment

Worldwide, approximately one billion people smoke cigarettes. Cigarette smoking persists in part because long-term smoking cessation rates are modest on existing treatments. Smoking cessation outcomes are influenced by genetic factors, including genetic variation in enzymes that metabolize nicotine and smoking cessation medications, as well as in receptor targets for nicotine and treatment medications. For example, smokers with genetically slow nicotine metabolism have higher cessation success on behavioural counseling and nicotine patches compared with smokers with genetically fast nicotine metabolism. In this review, we highlight new progress in our understanding of how genetic variation in the pharmacological targets of nicotine and smoking cessation medications could be used to tailor smoking cessation therapy, increase quit rates, and reduce tobacco-related harm.

Dopaminergic genetic variation moderates the effect of nicotine on cigarette reward

RATIONALE

Cigarette smoking is influenced by nicotine’s effects on dopaminergic activity in the mesocorticolimbic pathway. This activity appears to be moderated by genetic variation, specifically a variable number tandem repeat (VNTR) polymorphism in the third exon of the dopamine receptor gene (DRD4).

OBJECTIVE

We examined whether this polymorphism along with three DRD4 single-nucleotide polymorphisms (SNPs: rs936460, rs936461, and rs12280580) moderate the influence of nicotine on subjective responses to cigarettes.

METHODS

White, non-Hispanic smokers (n = 96, cigarettes/day ≥15) attended two double-blind, counterbalanced experimental sessions, each preceded by overnight smoking abstinence. Participants smoked four nicotine (8.9 mg) or placebo (1.0 mg) cigarettes per session, with each cigarette followed by completion of the modified Cigarette Evaluation Questionnaire (mCEQ).

RESULTS

We examined the mCEQ composite score via 2 × 2 × 4 ANOVAs with genotype (major homozygotes versus minor carriers) as the between-subject factor and nicotine content and smoking bout as within-subject factors. Although DRD4 VNTR variation did not moderate overall nicotine response, there was a moderation of nicotine response over successive cigarettes. Smokers with fewer than seven repeats for the DRD4 VNTR reported markedly reduced craving, increased satisfaction, and a greater calming effect in response to earlier smoked nicotine cigarettes, whereas those with seven or more repeats did not. In addition, minor carriers for all three DRD4 SNPs displayed blunted overall response to nicotine.

CONCLUSION

These findings provide support for DRD4 variation as an informative predictor of subjective responses to nicotine. We discuss how these data may lead to improved tailoring of smoking cessation pharmacotherapies.

Pharmacogenetics of nicotine addiction: role of dopamine

The neurotransmitter dopamine (DA) plays a central role in addictive disorders, including nicotine addiction. Specific DA-related gene variants have been studied to identify responsiveness to treatment for nicotine addiction. Genetic variants in DRD2, DRD4, ANKK1, DAT1, COMT and DBH genes show some promise in informing personalized prescribing of smoking cessation pharmacotherapies. However, many trials studying these variants had small samples, used retrospective design or were composed of mainly self-identified Caucasian individuals. Furthermore, many of these studies lacked a comprehensive measurement of nicotine metabolism rate, did not assess the roles of sex or the menstrual cycle, and did not investigate the role of rare variants and/or epigenetic factors. Future work should be conducted addressing these limitations to more effectively utilize DA genetic information to unlock the potential of smoking cessation pharmacogenetics.

Pharmacogenetics of nicotine and associated smoking behaviors

This chapter summarizes genetic factors that contribute to variation in nicotine pharmacokinetics and nicotine's pharmacological action in the central nervous system (CNS), and how this in turn influences smoking behaviors. Nicotine, the major psychoactive compound in cigarette smoke, is metabolized by a number of enzymes, including CYP2A6, CYP2B6, FMOs, and UGTs, among others. Variation in the genes encoding these enzymes, in particular CYP2A6, can alter the rate of nicotine metabolism and smoking behaviors. Faster nicotine metabolism is associated with higher cigarette consumption and nicotine dependence, as well as lower quit rates. Variation in nicotine's CNS targets and downstream signaling pathways can also contribute to interindividual differences in smoking patterns. Binding of nicotine to neuronal nicotinic acetylcholine receptors (nAChRs) mediates the release of several neurotransmitters including dopamine and serotonin. Genetic variation in nAChRs, and in transporter and enzyme systems that leads to altered CNS levels of dopamine and serotonin, is associated with a number of smoking behaviors. To date, the precise mechanism underpinning many of these findings remains unknown. Considering the complex etiology of nicotine addiction, a more comprehensive approach that assesses the contribution of multiple gene variants, and their interaction with environmental factors, will likely improve personalized therapeutic approaches and increase smoking cessation rates.

Nicotine dependence as a moderator of genetic influences on smoking cessation treatment outcome

BACKGROUND

Genetic influences on smoking cessation treatment outcome may be affected by pretreatment patient characteristics. Nicotine dependence is arguably the most salient clinical factor in smoking cessation.

METHODS

In this secondary analysis of clinical trial data (N=793), we examined nicotine dependence severity as a moderator of the effects of 1198 single nucleotide polymorphisms (SNPs) in 53 biologically-relevant gene regions on smoking cessation outcomes. P-values were adjusted to account for multiple correlated SNPs within a gene region; corrected system-wide significance was 5 × 10(-4).

RESULTS

SNP × nicotine dependence interactions reached region-wide significance for several SNPs in the Dopamine Beta Hydroxylase (DBH) locus (0.0005<Adjusted-P<0.05), including rs1541333, which reached system-wide significance for predicting end of treatment (EOT) abstinence (Adjusted-P=0.0004). A haplotype including 6 DBH SNPs predicted abstinence at EOT (OR=1.7, P=0.001) and 6-month follow-up (OR=1.6, P=0.008) in those with high nicotine dependence (n=526) but not in those with low dependence (n=227). The DBH signal observed here may be distinct from a previously reported genome-wide significant signal for former smoking status and from the principal haplotype associated with plasma dopamine beta-hydroxylase activity. A haplotype within the Chromosome 15 Nicotinic Acetylcholine Receptor gene region predicted abstinence at EOT in those with high (OR=2.0, P=0.0004) but not low (P=0.6) dependence in post hoc analyses.

CONCLUSIONS

Considering pre-treatment nicotine dependence level may optimize the prediction of genetic influences on cessation outcomes. If replicated, results like these may inform prognosticative genomic screening panels designed to identify smokers at high risk of relapse when coupled with severe nicotine dependence.

Effects of nicotine deprivation and replacement on BOLD-fMRI response to smoking cues as a function of DRD4 VNTR genotype

INTRODUCTION

Reactivity to smoking cues is an important factor in the motivation to smoke and has been associated with the dopamine receptor 4 variable number tandem repeat (DRD4 exon III VNTR) polymorphism. However, little is known about the associated neural mechanisms.

METHODS

Non-treatment-seeking Caucasian smokers completed overnight abstinence and viewed smoking and neutral cues during 2 separate functional magnetic resonance imaging scans while wearing either a nicotine or placebo patch (order randomized) and were genotyped for the DRD4 VNTR. We conducted mixed-effects repeated-measures analyses of variance (within-subject factor: nicotine or placebo patch; between-subject factor: DRD4 long [L: ≥ 1 copy of ≥ 7 repeats] or short [S: 2 copies ≤ 6 repeats] genotype) of 6 a priori regions of interest.

RESULTS

Relative to neutral cues, smoking cues elicited greater activity in bilateral ventral striatum and left amygdala during nicotine replacement and deactivation in these regions during nicotine deprivation. A patch × DRD4 interaction was observed in the left amygdala, an area associated with appetitive reinforcement and relapse risk, such that S allele carriers demonstrated greater activation on active patch than on placebo patch.

CONCLUSIONS

Brain systems associated with reward salience may become primed and overreactive at nicotine replacement doses intended for the first step of smoking cessation and may become inhibited during nicotine withdrawal in DRD4 S but not in DRD4 L carriers. These findings are consistent with the role of these regions in drug reinforcement and suggest a differential influence of nicotine replacement on amygdala activation in the association of incentive salience with smoking stimuli across DRD4 genotypes.

Antidepressants for smoking cessation

BACKGROUND

There are at least three reasons to believe antidepressants might help in smoking cessation. Firstly, nicotine withdrawal may produce depressive symptoms or precipitate a major depressive episode and antidepressants may relieve these. Secondly, nicotine may have antidepressant effects that maintain smoking, and antidepressants may substitute for this effect. Finally, some antidepressants may have a specific effect on neural pathways (e.g. inhibiting monoamine oxidase) or receptors (e.g. blockade of nicotinic-cholinergic receptors) underlying nicotine addiction.

OBJECTIVES

The aim of this review is to assess the effect and safety of antidepressant medications to aid long-term smoking cessation. The medications include bupropion; doxepin; fluoxetine; imipramine; lazabemide; moclobemide; nortriptyline; paroxetine; S-Adenosyl-L-Methionine (SAMe); selegiline; sertraline; St. John's wort; tryptophan; venlafaxine; and zimeledine.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register which includes reports of trials indexed in the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, and PsycINFO, and other reviews and meeting abstracts, in July 2013.

SELECTION CRITERIA

We considered randomized trials comparing antidepressant medications to placebo or an alternative pharmacotherapy for smoking cessation. We also included trials comparing different doses, using pharmacotherapy to prevent relapse or re-initiate smoking cessation or to help smokers reduce cigarette consumption. We excluded trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

We extracted data and assessed risk of bias using standard methodological procedures expected by the Cochrane Collaboration.The main outcome measure was abstinence from smoking after at least six months follow-up in patients smoking at baseline, expressed as a risk ratio (RR). We used the most rigorous definition of abstinence available in each trial, and biochemically validated rates if available. Where appropriate, we performed meta-analysis using a fixed-effect model.

MAIN RESULTS

Twenty-four new trials were identified since the 2009 update, bringing the total number of included trials to 90. There were 65 trials of bupropion and ten trials of nortriptyline, with the majority at low or unclear risk of bias. There was high quality evidence that, when used as the sole pharmacotherapy, bupropion significantly increased long-term cessation (44 trials, N = 13,728, risk ratio [RR] 1.62, 95% confidence interval [CI] 1.49 to 1.76). There was moderate quality evidence, limited by a relatively small number of trials and participants, that nortriptyline also significantly increased long-term cessation when used as the sole pharmacotherapy (six trials, N = 975, RR 2.03, 95% CI 1.48 to 2.78). There is insufficient evidence that adding bupropion (12 trials, N = 3487, RR 1.9, 95% CI 0.94 to 1.51) or nortriptyline (4 trials, N = 1644, RR 1.21, 95% CI 0.94 to 1.55) to nicotine replacement therapy (NRT) provides an additional long-term benefit. Based on a limited amount of data from direct comparisons, bupropion and nortriptyline appear to be equally effective and of similar efficacy to NRT (bupropion versus nortriptyline 3 trials, N = 417, RR 1.30, 95% CI 0.93 to 1.82; bupropion versus NRT 8 trials, N = 4096, RR 0.96, 95% CI 0.85 to 1.09; no direct comparisons between nortriptyline and NRT). Pooled results from four trials comparing bupropion to varenicline showed significantly lower quitting with bupropion than with varenicline (N = 1810, RR 0.68, 95% CI 0.56 to 0.83). Meta-analyses did not detect a significant increase in the rate of serious adverse events amongst participants taking bupropion, though the confidence interval only narrowly missed statistical significance (33 trials, N = 9631, RR 1.30, 95% CI 1.00 to 1.69). There is a risk of about 1 in 1000 of seizures associated with bupropion use. Bupropion has been associated with suicide risk, but whether this is causal is unclear. Nortriptyline has the potential for serious side-effects, but none have been seen in the few small trials for smoking cessation.There was no evidence of a significant effect for selective serotonin reuptake inhibitors on their own (RR 0.93, 95% CI 0.71 to 1.22, N = 1594; 2 trials fluoxetine, 1 paroxetine, 1 sertraline) or as an adjunct to NRT (3 trials of fluoxetine, N = 466, RR 0.70, 95% CI 0.64 to 1.82). Significant effects were also not detected for monoamine oxidase inhibitors (RR 1.29, 95% CI 0.93 to 1.79, N = 827; 1 trial moclobemide, 5 selegiline), the atypical antidepressant venlafaxine (1 trial, N = 147, RR 1.22, 95% CI 0.64 to 2.32), the herbal therapy St John's wort (hypericum) (2 trials, N = 261, RR 0.81, 95% CI 0.26 to 2.53), or the dietary supplement SAMe (1 trial, N = 120, RR 0.70, 95% CI 0.24 to 2.07).

AUTHORS' CONCLUSIONS

The antidepressants bupropion and nortriptyline aid long-term smoking cessation. Adverse events with either medication appear to rarely be serious or lead to stopping medication. Evidence suggests that the mode of action of bupropion and nortriptyline is independent of their antidepressant effect and that they are of similar efficacy to nicotine replacement. Evidence also suggests that bupropion is less effective than varenicline, but further research is needed to confirm this finding. Evidence suggests that neither selective serotonin reuptake inhibitors (e.g. fluoxetine) nor monoamine oxidase inhibitors aid cessation.

Influence of a dopamine pathway additive genetic efficacy score on smoking cessation: results from two randomized clinical trials of bupropion

AIMS

To evaluate the associations of treatment and an additive genetic efficacy score (AGES) based on dopamine functional polymorphisms with time to first smoking lapse and point prevalence abstinence at end of treatment among participants enrolled into two randomized clinical trials of smoking cessation therapies.

DESIGN

Double-blind pharmacogenetic efficacy trials randomizing participants to active or placebo bupropion. Study 1 also randomized participants to cognitive-behavioral smoking cessation treatment (CBT) or this treatment with CBT for depression. Study 2 provided standardized behavioural support.

SETTING

Two hospital-affiliated clinics (study 1), and two university-affiliated clinics (study 2).

PARTICIPANTS

A total of 792 self-identified white treatment-seeking smokers aged ≥18 years smoking ≥10 cigarettes per day over the last year.

MEASUREMENTS

Age, gender, Fagerström Test for Nicotine Dependence, dopamine pathway genotypes (rs1800497 [ANKK1 E713K], rs4680 [COMT V158M], DRD4 exon 3 variable number of tandem repeats polymorphism [DRD4 VNTR], SLC6A3,3' VNTR) analyzed both separately and as part of an AGES, time to first lapse and point prevalence abstinence at end of treatment.

FINDINGS

Significant associations of the AGES (hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.06-1.14, P = 0.009) and of the DRD4 VNTR (HR = 1.29, 95% CI = 1.17-1.41, P = 0.0073) were observed with time to first lapse. A significant AGES by pharmacotherapy interaction was observed (β standard error = -0.18 [0.07], P = 0.016), such that AGES predicted risk for time to first lapse only for individuals randomized to placebo.

CONCLUSIONS

A score based on functional polymorphisms relating to dopamine pathways appears to predict lapse to smoking following a quit attempt, and the association is mitigated in smokers using bupropion.

Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?

Substantial genetic contributions to addiction vulnerability are supported by data from twin studies, linkage studies, candidate gene association studies and, more recently, Genome Wide Association Studies (GWAS). Parallel to this work, animal studies have attempted to identify the genes that may contribute to responses to addictive drugs and addiction liability, initially focusing upon genes for the targets of the major drugs of abuse. These studies identified genes/proteins that affect responses to drugs of abuse; however, this does not necessarily mean that variation in these genes contributes to the genetic component of addiction liability. One of the major problems with initial linkage and candidate gene studies was an a priori focus on the genes thought to be involved in addiction based upon the known contributions of those proteins to drug actions, making the identification of novel genes unlikely. The GWAS approach is systematic and agnostic to such a priori assumptions. From the numerous GWAS now completed several conclusions may be drawn: (1) addiction is highly polygenic; each allelic variant contributing in a small, additive fashion to addiction vulnerability; (2) unexpected, compared to our a priori assumptions, classes of genes are most important in explaining addiction vulnerability; (3) although substantial genetic heterogeneity exists, there is substantial convergence of GWAS signals on particular genes. This review traces the history of this research; from initial transgenic mouse models based upon candidate gene and linkage studies, through the progression of GWAS for addiction and nicotine cessation, to the current human and transgenic mouse studies post-GWAS.

A prospective study of the effects of the DRD2/ANKK1 TaqIA polymorphism and impulsivity on smoking initiation

This study tested whether DRD2/ANKK1 TaqIA genotype predicted smoking initiation and subsequent use, and effects were mediated by sensation seeking and negative urgency. Between 2009 and 2012, college never smokers (n = 387) completed six assessments over 15 months; those who reported smoking were classified as initiators. Logistic regression indicated that the A1 allele was associated with initiation (p = .003). This effect was partially mediated by sensation seeking and negative urgency. Effects were stronger in Asian Americans. Findings have implications for improving prevention by including elements focused on urges to seek positive or negative reinforcement. Limitations and future directions are discussed.

An Association between Emotional Responsiveness and Smoking Behavior

Introduction. Emotional responsiveness (ER) has been theorized to play a protective role in pathways to tobacco initiation, regular use, and dependence, yet a possible association between ER and smoking behavior has not been studied. Our aim was to test whether measuring ER to a neutral stimulus was associated with decreased odds of current smoking. Methods. We measured ER and smoking status (current, former, and never) in two datasets: a cross-sectional dataset of persons with diabetes (n = 127) and a prospective dataset of depressed patients (n = 107) from an urban primary care system. Because there were few former smokers in the datasets, smoking status was dichotomized (current versus former/never) and measured at baseline (cross-sectional dataset) or at 36 weeks after-baseline (prospective dataset). ER was ascertained with response to a neutral facial expression (any ER versus none). Results. Compared to their nonresponsive counterparts, adjusted odds of current smoking were lower among participants endorsing emotional responsiveness in both the cross-sectional and prospective datasets (ORs = .29 and .32, P's <.02, resp.). Discussion. ER may be protective against current smoking behavior. Further research investigating the association between ER and decreased smoking may hold potential to inform treatment approaches to improve smoking prevalence.

The DRD4 exon III VNTR, bupropion, and associations with prospective abstinence

INTRODUCTION

DRD4 Exon III Variable Number of Tandem Repeat (VNTR) variation was found to interact with bupropion to influence prospective smoking abstinence, in a recently published longitudinal analyses of N = 331 individuals from a randomized double-blind placebo-controlled trial of bupropion and intensive cognitive-behavioral mood management therapy.

METHODS

We used univariate, multivariate, and longitudinal logistic regression to evaluate gene, treatment, time, and interaction effects on point prevalence and continuous abstinence at end of treatment, 6 months, and 12 months, respectively, in N = 416 European ancestry participants in a double-blind pharmacogenetic efficacy trial randomizing participants to active or placebo bupropion. Participants received 10 weeks of pharmacotherapy and 7 sessions of behavioral therapy, with a target quit date 2 weeks after initiating both therapies. VNTR genotypes were coded with the long allele dominant resulting in 4 analysis categories. Covariates included demographics, dependence measures, depressive symptoms, and genetic ancestry. We also performed genotype-stratified secondary analyses.

RESULTS

We observed significant effects of time in longitudinal analyses of both abstinence outcomes, of treatment in individuals with VNTR long allele genotypes for both abstinence outcomes, and of covariates in some analyses. We observed non-significantly larger differences in active versus placebo effect sizes in individuals with VNTR long allele genotypes than in individuals without the VNTR long allele, in the directions previously reported.

CONCLUSIONS

VNTR by treatment interaction differences between these and previous analyses may be attributable to insufficient size of the replication sample. Analyses of multiple randomized clinical trials will enable identification and validation of factors mediating treatment response.

Predictors of relapse in a bupropion trial for smoking cessation in recently-abstinent alcoholics: preliminary results using an aggregate genetic risk score

Introduction

Rates of smoking in the US population have decreased overall, but rates in some groups, including alcoholic smokers, remain high. Many newly sober alcoholics are concerned about their smoking and some attempt to quit. However, quit rates in this population are low. Prior studies suggest risk for relapse in this population may be genetically influenced and that genetic factors may moderate response to treatment.

Methods

In this exploratory study, we had two specific aims: (1) to investigate associations between genetic risk and outcome; (2) to investigate whether genetic risk moderates the efficacy of a medication intervention. Data are from a subsample of 90 participants from a clinical trial of smoking cessation treatment for smokers with between 2 and 12 months of alcohol abstinence. Subjects were randomly assigned to bupropion or placebo. All subjects received counseling and nicotine patches. To examine the possibility that bupropion may have been efficacious in participants with a specific genetic profile (ie, a pharmacogenetic approach), an aggregate genetic risk score was created by combining risk genotypes previously identified in bupropion treatment studies.

Results

Although medication efficacy was not moderated by the aggregate genetic risk score, there was an interaction between nicotine dependence and genetic risk in predicting smoking abstinence rates at the end of treatment (10 weeks).

Conclusions

Results suggest an aggregate genetic risk score approach may have utility in treatment trials of alcoholics who smoke. Additionally, these findings suggest a strategy for understanding and interpreting conflicting results for single genetic markers examined as moderators of smoking cessation treatment.

Mouse models for studying genetic influences on factors determining smoking cessation success in humans

Humans differ in their ability to quit using addictive substances, including nicotine, the major psychoactive ingredient in tobacco. For tobacco smoking, a substantial body of evidence, largely derived from twin studies, indicates that approximately half of these individual differences in ability to quit are heritable genetic influences that likely overlap with those for other addictive substances. Both twin and molecular genetic studies support overlapping influences on nicotine addiction vulnerability and smoking cessation success, although there is little formal analysis of the twin data that support this important point. None of the current datasets provides clarity concerning which heritable factors might provide robust dimensions around which individuals differ in ability to quit smoking. One approach to this problem is to test mice with genetic variations in genes that contain human variants that alter quit success. This review considers which features of quit success should be included in a comprehensive approach to elucidate the genetics of quit success, and how those features may be modeled in mice.

Biomarkers to optimize the treatment of nicotine dependence

The application of genomic medicine to the treatment of nicotine dependence holds great promise for revitalizing the steady decline in smoking rates witnessed in the USA over the past several decades. This paper examines the current knowledge base concerning the use of biomarkers to guide the selection of nicotine dependence treatments. First, we review the neurobiology of nicotine dependence and present evidence that supports its heritability. We then discuss the various studies of pharmacokinetic and pharmacodynamic genes related to therapeutic response. Current evidence suggests that biomarkers of genetic variability in both nicotine metabolism, referred to as the nicotine metabolite ratio, and dopamine genotypes may be useful for guiding treatment selection for nicotine dependence. Barriers to the translation of this research to clinical practice are discussed, as are directions for future research.