Nancy L Saccone1, James W Baurley2, Andrew W Bergen2, Sean P David3, Hannah R Elliott4, Marilyn G Foreman5, Jaakko Kaprio6, Thomas M Piasecki7, Caroline L Relton4, Laurie Zawertailo8, Laura J Bierut9, Rachel F Tyndale10, Li-Shiun Chen9. 1. Department of Genetics and Division of Biostatistics, Washington University School of Medicine, St. Louis, MO. 2. BioRealm, Culver City, CA. 3. Department of Medicine, Stanford University, Stanford, CA. 4. MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK. 5. Pulmonary and Critical Care Medicine, Morehouse School of Medicine, Atlanta, GA. 6. Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland. 7. Department of Psychological Sciences, University of Missouri, Columbia, MO. 8. Nicotine Dependence Service, Centre for Addiction and Mental Health, and Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada. 9. Siteman Cancer Center, Institute of Public Health, and Department of Psychiatry, Washington University School of Medicine, St. Louis, MO. 10. Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, and Departments of Pharmacology & Toxicology and Psychiatry, University of Toronto, Toronto, Ontario, Canada.
Abstract
Introduction: Human genetic research has succeeded in definitively identifying multiple genetic variants associated with risk for nicotine dependence and heavy smoking. To build on these advances, and to aid in reducing the prevalence of smoking and its consequent health harms, the next frontier is to identify genetic predictors of successful smoking cessation and also of the efficacy of smoking cessation treatments ("pharmacogenomics"). More broadly, additional biomarkers that can be quantified from biosamples also promise to aid "Precision Medicine" and the personalization of treatment, both pharmacological and behavioral. Aims and Methods: To motivate ongoing and future efforts, here we review several compelling genetic and biomarker findings related to smoking cessation and treatment. Results: These Key results involve genetic variants in the nicotinic receptor subunit gene CHRNA5, variants in the nicotine metabolism gene CYP2A6, and the nicotine metabolite ratio. We also summarize reports of epigenetic changes related to smoking behavior. Conclusions: The results to date demonstrate the value and utility of data generated from biosamples in clinical treatment trial settings. This article cross-references a companion paper in this issue that provides practical guidance on how to incorporate biosample collection into a planned clinical trial and discusses avenues for harmonizing data and fostering consortium-based, collaborative research on the pharmacogenomics of smoking cessation. Implications: Evidence is emerging that certain genotypes and biomarkers are associated with smoking cessation success and efficacy of smoking cessation treatments. We review key findings that open potential avenues for personalizing smoking cessation treatment according to an individual's genetic or metabolic profile. These results provide important incentive for smoking cessation researchers to collect biosamples and perform genotyping in research studies and clinical trials.
Introduction: Human genetic research has succeeded in definitively identifying multiple genetic variants associated with risk for nicotine dependence and heavy smoking. To build on these advances, and to aid in reducing the prevalence of smoking and its consequent health harms, the next frontier is to identify genetic predictors of successful smoking cessation and also of the efficacy of smoking cessation treatments ("pharmacogenomics"). More broadly, additional biomarkers that can be quantified from biosamples also promise to aid "Precision Medicine" and the personalization of treatment, both pharmacological and behavioral. Aims and Methods: To motivate ongoing and future efforts, here we review several compelling genetic and biomarker findings related to smoking cessation and treatment. Results: These Key results involve genetic variants in the nicotinic receptor subunit gene CHRNA5, variants in the nicotine metabolism gene CYP2A6, and the nicotine metabolite ratio. We also summarize reports of epigenetic changes related to smoking behavior. Conclusions: The results to date demonstrate the value and utility of data generated from biosamples in clinical treatment trial settings. This article cross-references a companion paper in this issue that provides practical guidance on how to incorporate biosample collection into a planned clinical trial and discusses avenues for harmonizing data and fostering consortium-based, collaborative research on the pharmacogenomics of smoking cessation. Implications: Evidence is emerging that certain genotypes and biomarkers are associated with smoking cessation success and efficacy of smoking cessation treatments. We review key findings that open potential avenues for personalizing smoking cessation treatment according to an individual's genetic or metabolic profile. These results provide important incentive for smoking cessation researchers to collect biosamples and perform genotyping in research studies and clinical trials.
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