Interplay of genetic risk factors (CHRNA 5-CHRNA 3-CHRNB4) and cessation treatments in smoking cessation success

Johns Hopkins University, Baltimore, Maryland, United States
American Journal of Psychiatry (Impact Factor: 12.3). 05/2012; 169(7):735-42. DOI: 10.1176/appi.ajp.2012.11101545
Source: PubMed


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 development of treatment algorithms. This study tested whether variants in the nicotinic receptor gene cluster CHRNA5-CHRNA3-CHRNB4 predict age at smoking cessation and relapse after an attempt to quit smoking. Method: In a community-based, crosssectional study (N=5,216) and a randomized comparative effectiveness smoking cessation trial (N=1,073), the authors used Cox proportional hazard models and logistic regression to model the relationships of smoking cessation (self-reported quit age in the community study and point-prevalence abstinence at the end of treatment in the clinical trial) to three common haplotypes in the CHRNA5-CHRNA3-CHRNB4 region defined by rs16969968 and rs680244.
The genetic variants in the CHRNA5-CHRNA3-CHRNB4 region that predict nicotine dependence also predicted a later age at smoking cessation in the community sample. In the smoking cessation trial, haplotype predicted abstinence at end of treatment in individuals receiving placebo but not among individuals receiving active medication. Haplotype interacted with treatment in affecting cessation success.
Smokers with the high-risk haplotype were three times as likely to respond to pharmacologic cessation treatments as were smokers with the low-risk haplotype. The high-risk haplotype increased the risk of cessation failure, and this increased risk was 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.

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    • " of smoking milestones , by peer ( Johnson et al . , 2010 ) and partner ( Chen et al . , 2014 ) smoking and parental monitoring ( Chen et al . , 2009 ) . Of impor - tance , emerging evidence suggests that carriers of the risk - conferring allele ( and a related high - risk haplo - type ) might delay their smoking cessation by 2 median quit years ( Chen et al . , 2012 ) . However , these individuals are also ideal targets for cessation phar - macotherapy as its efficacy appears considerably enhanced in those who carry the high - risk haplotype ( Chen & Bierut , 2013 ) . In this instance , a single series of GWAS studies revolutionized our understanding of an addictive behavior . Yet , what often goes"

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    • "Individuals with missing data were considered to be smoking. This sample was previously examined by Chen et al. (2012) who reported the interaction of CHRNA5 and medication on smoking abstinence (Chen et al., 2012). This paper presents new analyses targeting the effect of CHRNA5 rs16969968 in the cNRT and placebo arms. "
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    ABSTRACT: Recent evidence suggests that the efficacy of smoking cessation pharmacotherapy can vary across patients based on their genotypes. This study tests whether the coding variant rs16969968 in the CHRNA5 nicotinic receptor gene predicts the effects of combination nicotine replacement therapy (cNRT) and varenicline on treatment outcomes. In two randomized smoking cessation trials comparing cNRT vs. placebo, and varenicline vs. placebo, we used logistic regression to model associations between CHRNA5 rs16969968 and abstinence at end of treatment. For abstinence at end of treatment, there was an interaction between cNRT and rs16969968 (X(2)=8.15, df=2, omnibus-p=0.017 for the interaction); individuals with the high-risk AA genotype were more likely to benefit from cNRT. In contrast, varenicline increased abstinence, but its effect did not vary with CHRNA5. However, the genetic effects differed between the placebo control groups across two trials (wald=3.94, df=1, p=0.047), this non-replication can alter the interpretation of pharmacogenetic findings. Results from two complementary smoking cessation trials demonstrate inconsistent genetic results in the placebo arms. This evidence highlights the need to compare the most effective pharmacotherapies with the same placebo control to establish pharmacogenetic evidence to aid decisions on medication choice for patients trying to quit smoking. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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    • "And although observational studies of naturally occurring adversities dominate G × E research on mental disorders and other problematic behaviors, intervention studies and studies of health-promoting behaviors more commonly illustrate vantage sensitivity. As an example, nicotinic receptor gene variations associated with frequency of smoking in a community sample were recently found to predict successful abstinence among individuals assigned to active treatment arms of a smoking cessation trial, relative to placebo-treated controls (Chen et al. 2012). Similarly, several developmental studies have found benefits of favorable environmental exposures moderated by variation in DRD4. "
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    ABSTRACT: With the advent of increasingly accessible technologies for typing genetic variation, studies of gene-environment (G×E) interactions have proliferated in psychological research. Among the aims of such studies are testing developmental hypotheses and models of the etiology of behavioral disorders, defining boundaries of genetic and environmental influences, and identifying individuals most susceptible to risk exposures or most amenable to preventive and therapeutic interventions. This research also coincides with the emergence of unanticipated difficulties in detecting genetic variants of direct association with behavioral traits and disorders, which may be obscured if genetic effects are expressed only in predisposing environments. In this essay we consider these and other rationales for positing G×E interactions, review conceptual models meant to inform G×E interpretations from a psychological perspective, discuss points of common critique to which G×E research is vulnerable, and address the role of the environment in G×E interactions.
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