Novel genes identified in a high-density genome wide association study for nicotine dependence by Bierut Laura Jean, Madden Pamela A F, Breslau Naomi, Johnson Eric O, Hatsukami Dorothy, Pomerleau Ovide F, Swan Gary E, Rutter Joni, Bertelsen Sarah, Fox Louis, Fugman Douglas, Goate Alison M, Hinrichs Anthony L, Konvicka Karel, Martin Nicholas G, Montgomery Grant W, Saccone Nancy L, Saccone Scott F, Wang Jen C, Chase Gary A, Rice John P, Ballinger Dennis G in Human molecular genetics (2007). PubMed

Abstract

Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.

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