Individualizing nicotine replacement therapy based on genetic and nongenetic factors (UPenn, Lerman).
Lerman C.¹, Shields P.G.¹, Patterson F.¹, Kaufmann V¹, Audrain-McGovern J¹, Rukstalis M¹, Perkins K.², Tyndale, R.³, Benowitz N⁴, & Berrettini WH¹. ¹University of Pennsylvania TTURC in collaboration with Georgetown University, ²University of Pittsburgh, ³University of Toronto, and ⁴University of California at San Francisco.

Despite the well-documented efficacy of nicotine replacement therapy (NRT), there is a lack of sufficient empirical data to guide practitioners in selecting a particular form of treatment for individual patients with tobacco dependence. To fill this gap in knowledge and practice, we conducted a randomized, open-label clinical trial of transdermal nicotine (TN) and nicotine nasal spray (NS), and evaluated predictors of the comparative efficacy. Treatment-seeking smokers participated in 8-weeks of TN or NS, plus behavioral group counseling, and were followed for 6 months following the target quit date. Baseline measurements included demographics, smoking history, depression symptoms, body mass index (BMI), and candidate genetic polymorphisms postulated to modulate the effectiveness of NRT (e.g., genes involved in the regulation of dopamine and endogenous opioids, as well as those influencing nicotine metabolism). Logistic regression analyses of 6-month abstinence rates revealed significant treatment by race, treatment by BMI, and treatment by nicotine dependence interactions. Smokers with low-moderate dependence levels, non-obese smokers, and Caucasian smokers benefited more from TN, while smokers who are highly dependent, obese, or members of minority groups benefited more from NS. Although analyses of genotype data are still in progress at this time, preliminary data support the role of the dopamine D2 receptor gene (DRD2_141 InsC variant) and the mu-opioid receptor (OPRM1 A118G) variant in response to NRT, as well as a differential response to TN v. NS based upon catechol-O-methyl-transferase (COMT) genotype. Models of treatment outcome will be generated to examine the main and interacting effects of these genetic and non-genetic factors, and to explore mediating bio-behavioral mechanisms.