Our overarching goal is to determine whether genetic markers can be used to optimize smoking cessation pharmacotherapy to enhance efficacy, medication adherence, and reduce side effects. Smoking is a leading cause of preventable death and disability, and smoking cessation reverses the risk of mortality. However, cessation failure is common despite available cessation medications, which are associated with different efficacy, side effects, adherence, use constraints, and costs. This challenge can be addressed by improving current treatments via personalized medicine based on individual genetic markers to maximize efficacy and minimize side effects. Our recent work suggesting that the nicotinic receptor gene CHRNA5 alters response to nicotine replacement therapy (NRT) has been replicated in a meta-analysis. Our new preliminary data suggest that CHRNA5 may be a useful marker for medication choice, because patients with CHRNA5 variant rs16969968 AA/GA genotypes may benefit from NRT and those with GG genotypes (conferring poor response to NRT) may benefit from varenicline, a medication with higher cost and use restrictions. Similarly, other genetic variation such as the nicotine metabolism gene CYP2A6 also alters response to NRT. Currently there is insufficient evidence to support the clinical use of genotype based smoking cessation treatment, because these findings are based on retrospective pharmacogenetic analyses of different trials with markedly different placebo and counseling effect sizes and dissimilar designs. For clinical translation, we need head to head comparison of state-of-the-art interventions, use of key genotypes implicated by current research, and valid assessments of side effects/ adherence. We propose a first, prospective, genotype-based stratified randomization trial to compare the two most effective smoking cessation medications (combination NRT [patch and lozenge], varenicline vs. placebo for 3 months) in 720 smokers with known genotypes. Leveraging the Principal Investigator's observational genetic follow-up study of smoking cessation with existing genotypes, this study uses a stratified randomization trial design based on a subject's pertinent genotype for smoking cessation. Specifically, in Aim 1, we will determine if CHRNA5 genotype moderates the effect of medication (combination NRT, varenicline, vs. placebo) on abstinence.
In Aim 2, we will determine if CHRNA5 genotype predicts medication adherence and side effects.
In Aim 3, we will incorporate multiple genotypes and other predictors in order to develop a clinical treatment assignment algorithm for cessation success. This proposal is an innovative smoking cessation trial leveraging existing genotyped smokers and a genotype-based randomization design to build the evidence base to support a genotype based algorithm that can optimize smoking cessation pharmacotherapy in terms of efficacy, side effects, adherence, and improve overall smoking cessation success. This work can result in improved physician care of patients who smoke, overall smoking cessation success, and prevention of cancer, heart, and lung disease.

Public Health Relevance

Smoking is a leading modifiable risk factor for disability and death and a major national health problem. We will identify the most effective and safe cessation treatment based on personal genetic markers and other predictors to help people who want to quit smoking succeed. Our study will help clinicians to personalize treatments to produce the strongest smoking cessation outcomes at reduced health risks.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
1R01DA038076-01A1
Application #
8835537
Study Section
Behavioral Genetics and Epidemiology Study Section (BGES)
Program Officer
Walton, Kevin
Project Start
2014-09-30
Project End
2019-07-31
Budget Start
2014-09-30
Budget End
2015-07-31
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Washington University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Chiu, Ami; Hartz, Sarah; Smock, Nina et al. (2018) Most Current Smokers Desire Genetic Susceptibility Testing and Genetically-Efficacious Medication. J Neuroimmune Pharmacol 13:430-437
Chen, Li-Shiun; Baker, Timothy B; Korpecki, Jeanette M et al. (2018) Low-Burden Strategies to Promote Smoking Cessation Treatment Among Patients With Serious Mental Illness. Psychiatr Serv 69:849-851
Salloum, Naji C; Buchalter, Erica Lf; Chanani, Swati et al. (2018) From genes to treatments: a systematic review of the pharmacogenetics in smoking cessation. Pharmacogenomics 19:861-871
Chen, Li-Shiun; Horton, Amy; Bierut, Laura (2018) Pathways to precision medicine in smoking cessation treatments. Neurosci Lett 669:83-92
Saccone, Nancy L; Baurley, James W; Bergen, Andrew W et al. (2018) The Value of Biosamples in Smoking Cessation Trials: A Review of Genetic, Metabolomic, and Epigenetic Findings. Nicotine Tob Res 20:403-413
Jenkins, Wiley D; Gilbert, David; Chen, Li-Shiun et al. (2018) Finding paths with the greatest chance of success: enabling and focusing lung cancer screening and cessation in resource-constrained areas. Transl Lung Cancer Res 7:S261-S264
Chen, Li-Shiun; Zawertailo, Laurie; Piasecki, Thomas M et al. (2018) Leveraging Genomic Data in Smoking Cessation Trials in the Era of Precision Medicine: Why and How. Nicotine Tob Res 20:414-424
Chen, Li-Shiun; Baker, Timothy; Brownson, Ross C et al. (2017) Smoking Cessation and Electronic Cigarettes in Community Mental Health Centers: Patient and Provider Perspectives. Community Ment Health J 53:695-702
Olfson, E; Saccone, N L; Johnson, E O et al. (2016) Rare, low frequency and common coding variants in CHRNA5 and their contribution to nicotine dependence in European and African Americans. Mol Psychiatry 21:601-7
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

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