Dopamine Genes and Nicotine Dependence in Treatment-Seeking and Community Smokers

Center for Health Sciences, SRI International, Menlo Park, CA 94025, USA.
Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology (Impact Factor: 7.05). 06/2009; 34(10):2252-64. DOI: 10.1038/npp.2009.52
Source: PubMed


We utilized a cohort of 828 treatment-seeking self-identified white cigarette smokers (50% female) to rank candidate gene single nucleotide polymorphisms (SNPs) associated with the Fagerström Test for Nicotine Dependence (FTND), a measure of nicotine dependence which assesses quantity of cigarettes smoked and time- and place-dependent characteristics of the respondent's smoking behavior. A total of 1123 SNPs at 55 autosomal candidate genes, nicotinic acetylcholine receptors and genes involved in dopaminergic function, were tested for association to baseline FTND scores adjusted for age, depression, education, sex, and study site. SNP P-values were adjusted for the number of transmission models, the number of SNPs tested per candidate gene, and their intragenic correlation. DRD2, SLC6A3, and NR4A2 SNPs with adjusted P-values <0.10 were considered sufficiently noteworthy to justify further genetic, bioinformatic, and literature analyses. Each independent signal among the top-ranked SNPs accounted for approximately 1% of the FTND variance in this sample. The DRD2 SNP appears to represent a novel association with nicotine dependence. The SLC6A3 SNPs have previously been shown to be associated with SLC6A3 transcription or dopamine transporter density in vitro, in vivo, and ex vivo. Analysis of SLC6A3 and NR4A2 SNPs identified a statistically significant gene-gene interaction (P=0.001), consistent with in vitro evidence that the NR4A2 protein product (NURR1) regulates SLC6A3 transcription. A community cohort of N=175 multiplex ever-smoking pedigrees (N=423 ever smokers) provided nominal evidence for association with the FTND at these top ranked SNPs, uncorrected for multiple comparisons.

Download full-text


Available from: Hyman Hops,
28 Reads
  • Source
    • "One of them is the CHRNA5-CHRNA3-CHRNB4 gene cluster located on chromosome 15q24-25 [10]–[12]. The contribution of several other candidate genes to the vulnerability to cigarette-smoking has been reported, such as catechol O-methyltransferase [18], dopamine receptor 2 [18]–[21], opioid receptor [22] as well as genes related to nicotine metabolism, such as cytochrome P450 CYP 2A6 [23], [24]. The effects of these genes are often dependent on the ethnicity of the population [18], [25], [26]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Adult cigarette smokers usually become dependent on cigarettes during adolescence. Despite recent advances in addiction genetics, little data delineates the genetic factors that account for the vulnerability of humans to smoke tobacco. We studied the operant nicotine self-administration (SA) behavior of six inbred strains of adolescent male rats (Fisher 344, Brown Norway, Dark Agouti, Spontaneous Hypertensive Rat, Wistar Kyoto and Lewis) and six selected F1 hybrids. All rats were trained to press a lever to obtain food starting on postnatal day (PN) 32, and then nicotine (0.03 mg/kg/infusion, i.v.) reinforcement was made available on PN41-42 (10 consecutive daily 2 h sessions). Of the 12 isogenic strains, Fisher rats self-administered the fewest nicotine infusions (1.45 ± 0.36/d) during the last 3 d, while Lewis rats took the most nicotine (13.0 ± 1.4/d). These strains sorted into high, intermediate and low self-administration groups in 2, 2, and 8 strains, respectively. The influence of heredity on nicotine SA (0.64) is similar to that reported for humans. Therefore, this panel of isogenic rat strains effectively models the overall impact of genetics on the vulnerability to acquire nicotine-reinforced behavior during adolescence. Separate groups of rats responded for food starting on PN41. The correlation between nicotine and food reward was not significant. Hence, the genetic control of the motivation to obtain nicotine is distinctly different from food reward, indicating the specificity of the underlying genetic mechanisms. Lastly, the behavior of F1 hybrids was not predicted from the additive behavior of the parental strains, indicating the impact of significant gene-gene interactions on the susceptibility to nicotine reward. Taken together, the behavioral characteristics of this model indicate its strong potential to identify specific genes mediating the human vulnerability to smoke cigarettes.
    PLoS ONE 08/2012; 7(8):e44234. DOI:10.1371/journal.pone.0044234 · 3.23 Impact Factor
  • Source
    • ") and in other treatment-seeking smoker samples recently investigated (Bergen et al, 2009). We note that the sequencing coverage varied across nAChR subunit genes in this study and that some genes had more common and/or rare SNPs identified than other genes in these analyses. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Common single-nucleotide polymorphisms (SNPs) at nicotinic acetylcholine receptor (nAChR) subunit genes have previously been associated with measures of nicotine dependence. We investigated the contribution of common SNPs and rare single-nucleotide variants (SNVs) in nAChR genes to Fagerström test for nicotine dependence (FTND) scores in treatment-seeking smokers. Exons of 10 genes were resequenced with next-generation sequencing technology in 448 European-American participants of a smoking cessation trial, and CHRNB2 and CHRNA4 were resequenced by Sanger technology to improve sequence coverage. A total of 214 SNP/SNVs were identified, of which 19.2% were excluded from analyses because of reduced completion rate, 73.9% had minor allele frequencies <5%, and 48.1% were novel relative to dbSNP build 129. We tested associations of 173 SNP/SNVs with the FTND score using data obtained from 430 individuals (18 were excluded because of reduced completion rate) using linear regression for common, the cohort allelic sum test and the weighted sum statistic for rare, and the multivariate distance matrix regression method for both common and rare SNP/SNVs. Association testing with common SNPs with adjustment for correlated tests within each gene identified a significant association with two CHRNB2 SNPs, eg, the minor allele of rs2072660 increased the mean FTND score by 0.6 Units (P=0.01). We observed a significant evidence for association with the FTND score of common and rare SNP/SNVs at CHRNA5 and CHRNB2, and of rare SNVs at CHRNA4. Both common and/or rare SNP/SNVs from multiple nAChR subunit genes are associated with the FTND score in this sample of treatment-seeking smokers.
    Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology 11/2010; 35(12):2392-402. DOI:10.1038/npp.2010.120 · 7.05 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Interpreting genome-scale genetic association data, particularly for complex diseases and phenotypes, requires extensive use of prior knowledge across a broad range of potential biological and environmental influences, spanning many scientific subdisciplines. We suggest that known or hypothesized disease risk factors, and causal mechanisms, can be represented using an ontology, a computational specification of a set of concepts and the relations between them. We have integrated the expertise of multiple investigators in nicotine pharmacokinetics and pharmacodynamics, nicotine dependence, and clinical smoking cessation outcomes, and represented this knowledge in an ontology-based network model. Our model spans multiple scales, from molecules, genes and cellular pathways, to complex behavioral phenotypes and even environmental factors. To leverage previous and ongoing work in the field of ontology development, we adopt, expand upon and relate elements from existing ontologies whenever possible. We discuss several applications of our ontology: to support interdisciplinary research by graphically representing a complex scientific theory, to facilitate meta-analysis across different studies, to highlight potential interactions, and to support statistical analysis and causal modeling. We demonstrate that our ontology can focus hypothesis testing on areas supported by current theory. We describe how an ontology-based computational representation can be applied to disease risk factors and mechanisms, enabling the use of prior knowledge in large-scale genetic association studies in general. In specific, we have developed an initial Smoking Behavior Risk Ontology to support studies related to the pharmacogenetics of nicotine addiction and treatment.
    Pharmacogenetics and Genomics 08/2009; 19(7):538-51. DOI:10.1097/FPC.0b013e32832e2ced · 3.48 Impact Factor
Show more