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Cytochrome P450 2A6 (CYP2A6) encodes the enzyme responsible for the majority of nicotine metabolism. Previous studies support that slow metabolizers smoke fewer cigarettes once nicotine dependent but provide conflicting results on the role of CYP2A6 in the development of dependence. By focusing on the critical period of young adulthood, this study examines the relationship of CYP2A6 variation and smoking milestones. A total of 1209 European American young adults enrolled in the Collaborative Study on the Genetics of Alcoholism were genotyped for CYP2A6 variants to calculate a previously well-validated metric that estimates nicotine metabolism. This metric was not associated with the transition from never smoking to smoking initiation nor with the transition from initiation to daily smoking (P > 0.4). But among young adults who had become daily smokers (n = 506), decreased metabolism was associated with increased risk of nicotine dependence (P = 0.03) (defined as Fagerstrom Test for Nicotine Dependence score ≥4). This finding was replicated in the Collaborative Genetic Study of Nicotine Dependence with 335 young adult daily smokers (P = 0.02). Secondary meta-analysis indicated that slow metabolizers had a 53 percent increased odds (OR = 1.53, 95 percent CI 1.11-2.11, P = 0.009) of developing nicotine dependence compared with normal metabolizers. Furthermore, secondary analyses examining four-level response of time to first cigarette after waking (>60, 31-60, 6-30, ≤5 minutes) demonstrated a robust effect of the metabolism metric in Collaborative Study on the Genetics of Alcoholism (P = 0.03) and Collaborative Genetic Study of Nicotine Dependence (P = 0.004), illustrating the important role of this measure of dependence. These findings highlight the complex role of CYP2A6 variation across different developmental stages of smoking behaviors.

Nicotine dependence is moderately heritable, but identified genetic associations explain only modest portions of this heritability. We analyzed 3,369 SNPs from 349 candidate genes, and investigated whether incorporation of SNP-by-environment interaction into association analyses might bolster gene discovery efforts and prediction of nicotine dependence. Specifically, we incorporated the interaction between allele count and age-at-onset of regular smoking (AOS) into association analyses of nicotine dependence. Subjects were from the Collaborative Genetic Study of Nicotine Dependence, and included 797 cases ascertained for Fagerstrom nicotine dependence, and 811 non-nicotine dependent smokers as controls, all of European descent. Compared with main-effect models, SNP x AOS interaction models resulted in higher numbers of nominally significant tests, increased predictive utility at individual SNPs, and higher predictive utility in a multi-locus model. Some SNPs previously documented in main-effect analyses exhibited improved fits in the joint-analysis, including rs16969968 from CHRNA5 and rs2314379 from MAP3K4. CHRNA5 exhibited larger effects in later-onset smokers, in contrast with a previous report that suggested the opposite interaction (Weiss et al, PLOS Genetics, 4: e1000125, 2008). However, a number of SNPs that did not emerge in main-effect analyses were among the strongest findings in the interaction analyses. These include SNPs located in GRIN2B (p=1.5 × 10−5), which encodes a subunit of the NMDA receptor channel, a key molecule in mediating age-dependent synaptic plasticity. Incorporation of logically chosen interaction parameters, such as AOS, into genetic models of substance-use disorders may increase the degree of explained phenotypic variation, and constitutes a promising avenue for gene-discovery.

Nicotine dependence is moderately heritable, but identified genetic associations explain only modest portions of this heritability. We analyzed 3,369 SNPs from 349 candidate genes, and investigated whether incorporation of SNP-by-environment interaction into association analyses might bolster gene discovery efforts and prediction of nicotine dependence. Specifically, we incorporated the interaction between allele count and age-at-onset of regular smoking (AOS) into association analyses of nicotine dependence. Subjects were from the Collaborative Genetic Study of Nicotine Dependence, and included 797 cases ascertained for Fagerström nicotine dependence, and 811 non-nicotine dependent smokers as controls, all of European descent. Compared with main-effect models, SNP x AOS interaction models resulted in higher numbers of nominally significant tests, increased predictive utility at individual SNPs, and higher predictive utility in a multi-locus model. Some SNPs previously documented in main-effect analyses exhibited improved fits in the joint-analysis, including rs16969968 from CHRNA5 and rs2314379 from MAP3K4. CHRNA5 exhibited larger effects in later-onset smokers, in contrast with a previous report that suggested the opposite interaction (Weiss et al, PLOS Genetics, 4: e1000125, 2008). However, a number of SNPs that did not emerge in main-effect analyses were among the strongest findings in the interaction analyses. These include SNPs located in GRIN2B (p=1.5 × 10−5), which encodes a subunit of the NMDA receptor channel, a key molecule in mediating age-dependent synaptic plasticity. Incorporation of logically chosen interaction parameters, such as AOS, into genetic models of substance-use disorders may increase the degree of explained phenotypic variation, and constitutes a promising avenue for gene-discovery.