DOPA decarboxylase gene is associated with nicotine dependence. (December 2006)

• Record Type: Journal Article
• Authors: Zhang, Heping; Ye, Yuanqing; Wang, Xueqing; Gelernter, Joel; Ma, Jennie Z; Li, Ming D
• Is Part Of: Pharmacogenomics. Volume 7:Number 8(2006)
• Page Start: 1159
• Page End: 1166
• Publication Date: 2006-12
• Subjects: haplotypes -- nicotine dependence -- ordinal traits -- smoking -- single nucleotide polymorphism; Pharmacogenomics -- Periodicals; 615.1
• DOI: 10.2217/14622416.7.8.1159
• Languages: English
• ISSNs: 1462-2416

Abstract

Introduction: Cigarette smoking is a prevalent and harmful behavior. Although the heritability of nicotine dependence (ND) is well documented and many candidate genetic regions have been identified, few of them were confirmed. This may be, in part, due to analytic methods that sacrifice power.Methods: Using a recently developed, more powerful method for testing association between a genetic marker and an ordinal trait, we analyzed data from 1879 smokers and nonsmokers from 600 nuclear families of African–– or European––American (AA or EA) ancestry. This method increases power principally by accounting for differences in severity between affected subjects.Results: To demonstrate the more powerful method, we re-analyzed an existing dataset, which confirmed the association of the DOPA decarboxylase ( DDC ) gene on chromosome 7p11 with measures of nicotine dependence. Although none of the eight single nucleotide polymorphisms (SNPs) studied were found to be significantly associated with nicotine dependence (unadjusted p-value > 0.01), we identified haplotypes from those SNPs that were significantly associated with nicotine dependence in both AA and EA samples.Conclusion: The associated haplotypes differed in the AA and EA samples. The strongest association (p-value = 0.003) was identified between the ''heaviness of smoking index'' and haplotype C-A-T-G in SNPs rs921451––rs3735273––rs1451371––rs2060762. However, this association was not found significant in a previous report (p-value = 0.19) that used the same sample, underscoring the importance of using the statistical methods that use more of the available phenotypic information, and thereby better reflect the distribution of the phenotypes.