, Volume 41, Issue 5, pp 680-690
Date: 12 Jul 2011

A Twin Association Study of Nicotine Dependence with Markers in the CHRNA3 and CHRNA5 Genes

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Twin and family studies have provided overwhelming evidence for the genetic basis of individual differences in tobacco initiation (TI), regular smoking (RS) and nicotine dependence (ND). However, only a few genes have been reliably associated with ND. We used a finite mixture distribution model to examine the significance and effect size of the association of previously identified and replicated specific variants in the CHRNA5 and CHRNA3 receptor genes with ND, against the background of genetic and environmental risk factors for ND. We hypothesize that additional phenotypic information in relatives who have not been genotyped can be used to increase the power of detecting the genetic variant. The nicotine measures were assessed by personal interview in female, male and opposite sex twin pairs (N = 4,153) from the population-based Virginia Twin Registry. Three SNPs in the CHRNA5 and CHRNA3 receptor genes, previously shown to be significantly associated with ND in this sample, were replicated in the augmented analyses; they accounted for less than one percent of the genetic variance in liability to ND, which is estimated to be over 50% of the phenotypic variance. The significance of these effects was increased by adding twins with phenotype but without genotype data, but gains are limited and variable. The SNPs associated with ND did not show a significant association with either TI or RS and appear to be specific to the addictive stage of ND, characterized by current smoking and smoking a large amount of cigarettes per day. Furthermore, these SNPs did not appear to be associated with the remaining items comprising the FTND scale. This study confirmed a significant contribution of the CHRNA receptor on different forms of tobacco dependence. However, the genetic variant only accounted for little of the total genetic variance for liability to ND. Including phenotypic data on ungenotyped relatives can improve the statistical power to detect the effects of genetic variants when they contribute to individual differences in the phenotype.