Pharmacogenetic Optimization of Smoking Cessation Treatment

Abstract

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.

Keywords: metabolism; nicotine; pharmacogenetics; smoking cessation; tobacco; treatment.

Figure 1

Role of CYP2A6 in the metabolic pathway of nicotine. Up to 80% of a nicotine dose inhaled from cigarette smoke undergoes metabolic inactivation to cotinine. CYP2A6 is responsible for approximately 90% of nicotine’s inactivation to cotinine. The majority of cotinine is then further metabolized to 3′hydroxycotinine, in a reaction mediated wholly by CYP2A6. The ratio of these two metabolites, 3′hydroxycotinine/cotinine, known as the nicotine metabolite ratio or NMR, serves as a biomarker of CYP2A6 activity. Faster CYP2A6 activity is reflected by a higher NMR.

Figure 2

Key Figure. The nicotine metabolite ratio influences smoking cessation outcomes on varenicline and the nicotine patch. In smokers prospectively randomized to varenicline, nicotine patch, or placebo based on the nicotine metabolite ratio or NMR, end-of-treatment quit rates and odds ratios (OR) with 95% confidence intervals (CI) comparing the efficacy of varenicline versus the nicotine patch as a function of NMR group (faster vs. slower nicotine metabolizers) are shown in (a). There was a significant NMR-by-treatment interaction on end-of-treatment quit rates: ratio of odds ratios (ORR) = 1.89 (95% CI = 1.02, 3.45; P=0.04) (a). In a longitudinal model including end-of-treatment as well as 6-month and 12-month quit rates, the NMR-by-treatment interaction was also significant: ORR = 1.96 (95% CI = 1.11, 3.46; P=0.02). Number needed to treat analyses comparing the effectiveness of varenicline versus placebo, and nicotine patch versus placebo, as a function of NMR group (faster vs. slower nicotine metabolizers) are shown in (b). For example, 26 faster metabolizers would need to be treated with the nicotine patch to have one smoker quit. The full results from this clinical trial (NCT01314001) are found in a publication by Lerman et al., 2015 [22]. Abbreviation: CI, confidence interval

Figure 3

The rs1051730–rs16969968 genetic variant in the nicotinic receptor does not influence smoking cessation outcomes on NRT. Effect sizes (odds ratios) from four clinical studies [, –81] comprising NRT treatment arms show the likelihood of successful smoking cessation at end-of-treatment for smokers with the rs1051730-rs16969968 risk allele (rs1051730 T allele or rs16969968 A allele) relative to smokers with the rs1051730-rs16969968 reference allele (rs1051730 C or rs16969968 G allele). This figure is adapted from a meta-analysis performed by Leung et al, 2015 [7]. The overall effect size from the meta-analyzed data is also depicted. Results were generated from additive genetic models adjusting for age and sex. No significant heterogeneity was present in the meta-analysis (I²=50.6%; P=0.07). The dashed vertical line represents the overall effect size, which was 0.97. Abbreviations: PiP, Patch in Practice study; CI, confidence interval