Another factor that has been shown to be associated with cigarettes per day (CPD) is the rate of nicotine metabolism as measured by the nicotine metabolite ratio (NMR; Benowitz, Pomerleau, Pomerleau, & Jacob, 2003; Johnstone et al., 2006). The NMR is the ratio of 3′-hydroxycotinine to cotinine and is a measure of the rate of nicotine clearance (Dempsey et al., 2004). Nicotine is metabolized to cotinine primarily by the liver enzyme CYP2A6. Cotinine is in turn metabolized to 3′-hydroxycotinine exclusively or nearly exclusively by the same enzyme. As a ratio of metabolite to parent drug, the NMR is a measure of enzymatic activity through that pathway (i.e., CYP2A6 activity). The activity of CYP2A6 is determined in part by genetics. The CYP2A6 gene is polymorphic, and various alleles are associated with reduced activity; however, known CYP2A6 genotypes account for only a modest proportion of the heritability of nicotine clearance rates (Swan et al., 2005). The NMR is significantly associated with CYP2A6 genotype (Malaiyandi et al., 2006) and has the additional advantage of reflecting environmental influences on CYP2A6 activity (Benowitz, Hukkanen, & Jacob, 2009). Therefore, the NMR may better reflect individual variation in nicotine metabolism as it affects smoking behavior (Ray, Tyndale, & Lerman, 2009).

Although both 15q25 genetic variants and NMR have been associated independently with CPD, to our knowledge, no studies have examined them in combination. Classic pharmacogenetic studies have shown that both variation in drug metabolism and drug targets are important to consider (Evans & Johnson, 2001). In this study, we examined potential interactions between the NMR and three of the SNPs in the CHRNA5-CHRNA3-CHRNB4 gene region that have been previously associated with CPD: CHRNA5 rs16969968, CHRNA5 rs578776, and CHRNA3 rs1051730 (Saccone et al., 2010; TAG Consortium, 2010; Thorgeirsson et al., 2010). Although rs16969968 and rs1051730 are in strong LD and may mark the same genetic locus, some studies have reported rs1051730 as a stronger signal (TAG Consortium, 2010; Thorgeirsson et al., 2010); we therefore decided to include both in our analysis.

In the overall sample, 47.6% of participants were female, 40.9% were college graduates, and the mean age was 44.98 (SD = 11.01). At baseline, the mean CPD was 22.63 (SD = 9.32), mean nicotine dependence (FTND) score was 5.38 (SD = 2.20), and mean NMR was 0.416 (SD = 0.217).

Genotyping for SNPs rs16969968, rs578776, and rs1051730 was performed using the TaqMan SNP Genotyping Assays in a 384-well microplate format along with SNP-specific control samples (Applied Biosystems). The genotype distribution for the three SNPs was as follows: For rs16969968, 97 participants (14.3%) were of the A/A genotype, 325 (48.0%) were A/G, and 255 (37.7%) were G/G; for rs578776, 49 (4.8%) were A/A, 367 (35.6%) were A/G, and 614 (59.6%) were G/G; and for rs1051730, 152 (14.8%) were A/A, 491 (47.7%) were A/G, and 387 (37.6%) were G/G.

Pairwise LD (|D′| and r²) was determined using Haploview (Barrett, Fry, Maller, & Daly, 2005) from the subset of 677 participants who had data for all three SNPs. For rs16969968 and rs578776, |D′| = 1.0 and r² = .182; for rs578776 and rs1051730, |D′| = 0.99 and r² = .182; and for rs16969968 and rs1051730, |D′| = 0.98 and r² = .957 (Supplementary Figure S1), which are consistent with previous studies (Bierut et al., 2008; N. L. Saccone et al., 2009). Genotype frequencies were in Hardy–Weinberg equilibrium.

NMR data were determined by liquid chromatography—tandem mass spectrometry (Dempsey et al., 2004) using blood samples collected at the pretreatment visit in each of the three studies. Participants were not given specific instructions regarding smoking behavior prior to collection; however, all participants reported smoking at least 10 CPD. The range of NMR values in this dataset was 0.01–2.08, consistent with previous studies (Johnstone et al., 2006; Swan et al., 2009). Previous studies at our center observed significant differences in smoking cessation between smokers in the lowest quartile of NMR and smokers in all other quartiles (Lerman et al., 2010; Schnoll et al., 2009). Based on those studies, we defined slow metabolizers as those in the lowest quartile (NMR < 0.27) and normal metabolizers as those in the top three quartiles (NMR > 0.27).

Chi-square tests and one-way ANOVAs were used to check for differences by genotype group on sex, education, and age. These variables did not differ by genotype on any of the three SNPs (p values > .05). Three linear regression models of CPD were then estimated. In each model, the predictors were sex, age, education (college graduate vs. other), NMR, and a set of two indicator variables denoting genotype on one of the three SNPs of interest. For each SNP, the reference category was the genotype with the lowest projected risk (i.e., associated with lower CPD) based on previous association studies (S. F. Saccone et al., 2007; Stevens et al., 2008). For rs16969968 and rs1051730, the indicator variables denoted genotypes of A/G and A/A, with G/G the reference category; for rs578776, the indicator variables denoted genotypes of A/G and G/G, with A/A the reference category. In each model, a set of two indicator variables representing the potential interaction of NMR by genotype was also included. All predictors were entered as a block after which the interaction terms were allowed to drop out if nonsignificant (p > .05). To obtain effect sizes for NMR within genotype, regressions of CPD on sex, age, education, and NMR were performed separately within each of the three genotype groups for each of the three SNPs.

Although the precise functional consequences of SNPs at rs16969968, rs578776, and rs1051730 have not yet been established, all three SNPs have documented associations with heaviness of smoking in nontreatment-seeking smokers (Berrettini et al., 2008; TAG Consortium, 2010; Thorgeirsson et al., 2010). As demonstrated in prior published studies, rs16969968 has been associated with reduced receptor response to an agonist (Bierut et al., 2008) and rs578776 with reduced mRNA levels (Wang et al., 2009). It is also possible, due to the high LD across the CHRNA5-CHRNA3-CHRNB4 region, that these SNPs could serve as markers of yet undiscovered functional variants.

Contrary to our hypothesis, we did not observe an interaction between the NMR and CHRNA5-A3 SNPs on CPD. Positron emission tomography imaging has demonstrated that low levels of nicotine (i.e., smoking one cigarette after extended abstinence) can desensitize most of the available α4β2 nAChRs in a smoker's brain (Brody et al., 2006). Therefore, it is possible that the higher nicotine levels in the slower metabolizers might cause prolonged α4β2 desensitization, which in turn might minimize the importance of receptor sensitivity, explaining the lack of interaction between the NMR and CHRNA5-A3 variants. Another possible explanation may be that our study population is restricted to treatment-seeking smokers who report smoking at least 10 CPD. Because slower nicotine metabolism has been associated with smoking fewer CPD (Benowitz et al., 2003), by excluding individuals who smoke fewer than 10 CPD, our sample may not represent the full variation in CPD among slow metabolizers in the general smoking population.

In addition, differences in nicotine content between cigarette brands and individual differences in smoking topography may affect an individual's exposure to nicotine in ways that are not reflected in a measure of CPD (Pérez-Stable, Benowitz, & Marin, 1995). Slow nicotine metabolizers have been shown to take smaller cigarette puffs but not differ in the number of puffs taken compared with intermediate and normal metabolizers (Strasser, Malaiyandi, Hoffman, Tyndale, & Lerman, 2007; Strasser et al., in press). Cotinine, the primary metabolite of nicotine, has a half-life of 15–20 hr and may be a more precise measure of total nicotine exposure (Pérez-Stable et al., 1995). A recent investigation by Keskitalo et al. (2009) found an association between rs1051730 and cotinine level; the effect size of rs1051730 on cotinine level was 2.3 times greater than that on CPD in their study. An exploratory analysis of pretreatment cotinine level in our sample revealed a significant (p = .03) interaction between rs1051730 genotype and NMR (results not shown). The risk allele at rs1051730 (i.e., less-sensitive receptors) was associated with greater baseline cotinine levels in both the slow and normal metabolizers; however, this association was more pronounced among slow metabolizers [one-way analysis of variance, F(2 df) = 10.76, p = .00003] as compared with normal metabolizers [F(2 df) = 5.49, p = .004]. However,although rs1051730 is in tight LD with rs16969968 (which alters receptor function), no functional consequences have been noted with this SNP. Cotinine levels are dependent upon time from last cigarette and gradually rise throughout the day (Hukkanen, Jacob, & Benowitz, 2005), and the time of day of cotinine collection was not standardized among the participants in our sample. Additionally, since the NMR is calculated as the ratio of 3′-hydroxycotinine to cotinine, this may be a confounding factor in a statistical model that uses cotinine as an outcome. For these reasons, these cotinine results should be interpreted with caution.

In the recent meta-analysis by Saccone et al. (2010) a third genetic locus (marked by CHRNA5 rs588765) was found to be significantly associated with smoking rate after controlling for rs16969968. It is a limitation of our study that data for rs588765 were not collected for our sample. Another potential limitation is due to the high LD observed between rs16969968 and rs1051730; we might only be assessing two independent signals from the SNPs assessed in our sample. Our sample of 1,030 individuals gave us adequate power to detect an R² change in an interactive model (SNP × NMR) of .006, which would correspond to effect sizes ranging from onefold to threefold larger than we observed. Thus, it is possible that we were unable to identify smaller interaction effects that may exist. Additionally, our sample is restricted to treatment-seeking smokers who reported smoking at least 10 CPD at pretreatment.