Integration Of Gene Expression With Gwas To Identify Risk Genes For Nicotine Dependence

Background Cigarette smoking is addictive and persistent smoking leads to nicotine dependence. Both family and twin studies have indicated that it is influenced by genetic factors. In recent years, several risk genes for nicotine dependence have been identified. However, these genes account for only a small proportion of observed heritability. It is a challenge to discover those remaining genetic factors. FTND score is a common measure for nicotine dependence, and the time to smoke the first cigarette in the morning (TFC) can be considered as a measure of nicotine withdrawal since the half-life of nicotine in human blood is about 2 hours. Methods To identify genes involved in these phenotypes, we performed a gene-based genome-wide meta-analysis of FTND score and TFC using several African American samples from dbGaP. We also conducted transcriptome sequencing for samples isolated from nucleus accumbens of chronic nicotine treated and withdrawal mice. Results By integrating differentially expressed genes in nicotine treated and withdrawal mice with GWAS meta-analyses, we discover some novel genes associated with nicotine dependence and withdrawal. These include TEAD3, ORC3, TCTN3, and SERPINE2. These genes are reported associated with schizophrenia, neuronal maturation, orofaciodigital syndromes and cancers. Discussion Our results indicate that integration of functional data with GWAS analyses could significantly improve power to discover new risk genes.