Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8841733 | Neuroscience Letters | 2018 | 32 Pages |
Abstract
Cigarette smoking is highly addictive and modern genetic research has identified robust genetic influences on nicotine dependence. An important step in translating these genetic findings to clinical practice is identifying the genetic factors affecting smoking cessation in order to enhance current smoking cessation treatments. We reviewed the significant genetic variants that predict nicotine dependence, smoking cessation, and response to cessation pharmacotherapy. These data suggest that genetic risks can predict smoking cessation outcomes and moderate the effect of pharmacological treatments. Some pharmacogenetic findings have been replicated in meta-analyses or in multiple smoking cessation trials. The variation in efficacy between smokers with different genetic markers supports the notion that personalized smoking cessation intervention based upon genotype could maximize the efficiency of such treatment while minimizing side effects, thus influencing the number needed to treat (NNT) and the number needed to harm. In summary, as precision medicine is revolutionizing healthcare, smoking cessation may be one of the first areas where genetic variants may identify individuals at increased risk. Current evidence strongly suggests that genetic variants predict cessation failure and that cessation pharmacotherapy effectiveness is modulated by biomarkers such as nicotinic cholinergic receptor α5 subunit (CHRNA5) genotypes or nicotine metabolism ratio (NMR). These findings strengthen the case for the development and rigorous testing of treatments that target patients with different biological risk profiles.
Keywords
nAChRsCytochrome P450 2A6Cytochrome P450 2B6CYP2A6CYP2B6CHRNB4CHRNA5CHRNA3NNTNRTcpdMyocardial infarctioncoronary artery diseaseCOPDChronic obstructive pulmonary diseaseSmoking cessationNMRNicotine replacement therapycigarettes per dayCADPharmacogeneticsgenome wide association studyGWASPrecision medicineSingle nucleotide polymorphismSNP
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Authors
Li-Shiun Chen, Amy Horton, Laura Bierut,