Adverse events are common while using medications to assist an attempt to quit smoking (Piper et al. 2009). The possibility of assigning optimal smoking cessation medications based on a patient's genetic profile is rapidly becoming a reality: genetic variants associated with nicotine dependence and metabolism have been demonstrated to have an impact on utility of smoking cessation pharmacotherapy (Chen et al. 2012, Bergen et al. 2013, Falcone et al. 2011) and there is preliminary data to support the idea that these variants are also associated with adverse events attributable to smoking cessation pharmacotherapy (King et al. 2012). The goal of this project is to evaluate the utility of genetic variants to predict adverse events while using nicotine replacement therapy or bupropion to help a smoker to quit. To achieve this goal, we will use adverse event, adherence, cessation outcome, and genotype data from the University of Wisconsin Transdisciplinary Tobacco Use Research Center study (UW-TTURC).
The specific aims are (1) to determine associations between genetic variants and adverse events attributable to smoking cessation medications in the UW-TTURC study, focusing on genes previously associated with nicotine dependence (e.g. nicotinic receptor subunit genes CHRNA5 and nicotine metabolism gene CYP2A6), or bupropion metabolism (e.g. CYP2B6), and (2) to determine the extent to which associations between genetic variants and successful smoking cessation are mediated by adverse events and adherence. Results from this study should improve our ability to predict who will experience adverse events due when using particular smoking cessation medications. This knowledge will lead to personalized smoking cessation therapies that will decrease adverse events, improve adherence, and ultimately increase smoking cessation success.
Cigarette smoking is associated with great costs: approximately 443,000 premature deaths and $193 billion in health-care costs and productivity losses in the United States each year. Our study of genetic predictors of side effects from smoking cessation medications may result in improved assignment of treatment plans for smokers, decreasing the number of side effects experienced and possibly shortening the time it will take for a smoker to successfully quit.
| Schwantes-An, Tae-Hwi; Zhang, Juan; Chen, Li-Shiun et al. (2016) Association of the OPRM1 Variant rs1799971 (A118G) with Non-Specific Liability to Substance Dependence in a Collaborative de novo Meta-Analysis of European-Ancestry Cohorts. Behav Genet 46:151-69 |
| Chen, Li-Shiun; Baker, Timothy; Hung, Rayjean J et al. (2016) Genetic Risk Can Be Decreased: Quitting Smoking Decreases and Delays Lung Cancer for Smokers With High and Low CHRNA5 Risk Genotypes - A Meta-Analysis. EBioMedicine 11:219-226 |
