Interplay of Genetic Risk Factors (CHRNA5-CHRNA3-CHRNB4) and Cessation Treatments in Smoking Cessation Success

Abstract

Objective Smoking is highly intractable and the genetic influences on cessation are unclear. Identifying the genetic factors affecting smoking cessation could elucidate the nature of tobacco dependence, enhance risk assessment, and support treatment algorithm development. This study tests whether variants in the nicotinic receptor gene cluster (CHRNA5-CHRNA3-CHRNB4) predict age of smoking cessation and relapse to smoking after a quit attempt. Method In a community-based, cross-sectional study (N=5,216) and a randomized comparative effectiveness smoking cessation trial (N=1,073), we used survival analyses and logistic regression to model relations between smoking cessation (self-reported quit age in a community study and point-prevalence abstinence at end-of-treatment in a clinical trial) and three common haplotypes in the CHRNA5-CHRNA3-CHRNB4 region defined by rs16969968 and rs680244. Results The genetic variants in the CHRNA5-CHRNA3-CHRNB4 region that predict nicotine dependence also predict a later age of smoking cessation in a community-based sample (X2=8.46, df=2, p=0.015). In the smoking cessation trial, these variants predict abstinence at end-of-treatment in individuals receiving placebo medication, but not amongst individuals receiving active medication. Genetic variants interact with treatment in affecting cessation success (X2=8.97, df=2, p=0.011). Conclusions Smokers with the high risk genetic variants have a three-fold increased likelihood of responding to pharmacologic cessation treatments, compared to smokers with the low risk genetic variants. The high-risk variants increase the risk of cessation failure, and this increased risk can be ameliorated by cessation pharmacotherapy. By identifying a high-risk genetic group with heightened response to smoking cessation pharmacotherapy, this work may support the development of personalized cessation treatments.

Organic Cation Transporter Variation and Response to Smoking Cessation Therapies

“…For example, plasma concentrations of varenicline could be measured in individuals prescribed this medication 34 to test for the effect of functional OCT2 alleles on medication plasma levels, to test association between medication plasma levels and prospective abstinence, and on the influence of the functional OCT2 alleles on prospective abstinence, as has been reported for the bupropion metabolite hydoxybupropion and CYP2B6 variation. 81 Effects of the functional OCT2 allele on brain structure and function may be observable, given prior studies that have identified effects on brain structure 82 and function 83 of cholinergic 47,84 and dopaminergic 40,85 alleles that influence smoking cessation.…”

The Value of Control Conditions for Evaluating Pharmacogenetic Effects

“…The genetic effect of CHRNA5 on smoking cessation has been demonstrated in some research studies [3,7,[9][10][11][12][13][14][15], but not in several other important studies [16][17][18][19]. We believe that such variability reflects the actions of important moderators related to treatment and sample characteristics.…”

“…For example, multiple genes can predict coronary artery disease outcomes, but examination of only individuals treated with statins will not reveal some of the genetic associations because these medications modify the genetic effect [2]. Similarly, the CHRNA5 effect on smoking cessation may be moderated by nicotine replacement therapy [3], suggesting that meta-analyses of pharmacogenetic effects should include both placebo and active treatment arms. Indeed, many authors have urged that pharmacogenetic research such as the Leung et al study analyze both placebo and active medication arms to fully understand genetic modifiers of treatment [4][5][6].…”

“…It is likely that some of the variability in genetic relations across studies and analyses reflects the complex moderation of genetic effects by environmental factors such as treatment, comorbidities and environmental events such as stressors and social contexts [3,[7][8]. The genetic effect of CHRNA5 on smoking cessation has been demonstrated in some research studies [3,7,[9][10][11][12][13][14][15], but not in several other important studies [16][17][18][19].…”

UGMDR: a unified conceptual framework for detection of multifactor interactions underlying complex traits

“…To demonstrate the increased power, the UGMDR method was applied to detect interactions among single-nucleotide polymorphisms in three genes that were revealed responsible for smoking-related phenotypes in the literature (Li et al, 2010;Chen et al, 2012): 8 in CHRNA5, 12 in CHRNA3, and 20 in CHRNB4, for nicotine dependence in the cohort for Study of Addiction: Genetics and Environment (SAGE) composed of three subsamples: the Collaborative Study on the Genetics of Alcoholism (COGA), the Collaborative Study on the Genetics of Nicotine Dependence (COGEND), and the Family Study of Cocaine Dependence (FSCD). A majority of the SAGE are unrelated samples plus a few families.…”