Despite evidence of strong genetic contributions to the etiology of smoking initiation (SI) and nicotine dependence (ND), we are far from identifying the specific genetic basis of individual susceptibility to ND. This project - to deepen our understanding of how genes contribute to risk for nicotine dependence (ND) - has arisen as an effort to utilize maximally the relatively unique and complementary set of skill of this group of investigators in complex human genetics, animal genetics and nicotine pharmacology. We will validate these putative risk genes using a two-step approach: replication in other human samples and the demonstration in animal models of ND that variants in these genes contribute to neurobiological pathways likely involved in ND. We will first identify promising candidate genes for smoking initiation (SI) and ND by data-mining GWA datasets and the selected candidates will be replicated. Using a mouse model of nicotine withdrawal, we will characterize behavioral QTLs relevant for ND using a recently developed expanded BXD RI mouse strain panel, focusing on strains informative for already identified areas of provisional QTLs. This approach allows us to both validate and refine our mapping of the nicotine behavioral QTL. Furthermore, we will identify candidate genes for ND by combining expression and behavioral genetics analyses in these BXD RI mouse strains. Candidate genes/pathways identified and prioritized from human and mouse studies will be validated by pharmacological or genetic manipulations to alter expression or function of candidate genes in mouse brain and determine effects on behavioral responses to in models of nicotine reward and withdrawal.
Tobacco smoking results in millions of deaths worldwide each year even when using the most efficacious smoking cessation agents available. Indeed, approximately 75 to 80% of smokers attempting to quit will relapse within one year, highlighting the need to develop more effective smoking cessation agents. Here, using human and animal models we will deepen our understanding of how genes contribute to risk for nicotine dependence. If successful, this application promises to have a significant positive impact on human health.
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