Influence of a Dopamine Pathway Additive Genetic Efficacy Score on Smoking Cessation: Results from Two Randomized Clinical Trials of Bupropion.
Alpert Medical School of Brown University: Department of Family Medicine, Pawtucket, RI, USA. Addiction
(Impact Factor: 4.74).
08/2013; 108(12). DOI: 10.1111/add.12325
To evaluate associations of treatment and an 'additive genetic efficacy score' (AGES) based on dopamine functional polymorphisms with time to first smoking lapse and point prevalence abstinence at end of treatment among participants enrolled in two randomized clinical trials of smoking cessation therapies.
Double-blind pharmacogenetic efficacy trials randomizing participants to active or placebo bupropion. Study 1 also randomized participants to cognitive-behavioral smoking cessation treatment (CBT) or this treatment with CBT for depression. Study 2 provided standardized behavioural support.
Two Hospital-affiliated clinics (Study 1), and two University-affiliated clinics (Study 2).
N=792 self-identified white treatment-seeking smokers aged ≥18 years smoking ≥10 cigarettes per day over the last year.
Age, gender, Fagerström Test for Nicotine Dependence, dopamine pathway genotypes (rs1800497 [ANKK1 E713K], rs4680 [COMT V158M], DRD4 exon 3 Variable Number of Tandem Repeats polymorphism [DRD4 VNTR], SLC6A3 3' VNTR) analyzed both separately and as part of an AGES, time to first lapse, and point prevalence abstinence at end of treatment.
Significant associations of the AGES (hazard ratio = 1.10, 95% Confidence Interval [CI] = 1.06-1.14], p=0.0099) and of the DRD4 VNTR (HR = 1.29, 95%CI 1.17-1.41, p=0.0073) were observed with time to first lapse. A significant AGES by pharmacotherapy interaction was observed (β [SE]=-0.18 [0.07], p=0.016), such that AGES predicted risk for time to first lapse only for individuals randomized to placebo.
A score based on functional polymorphisms relating to dopamine pathways appears to predict lapse to smoking following a quit attempt, and the association is mitigated in smokers using bupropion.
Figures in this publication
Available from: Daniel W Belsky
- "" The hypothesis-driven approach can furnish genetic variants that measure individual differences in difficult-to-observe biological processes. For example, a recent study of smoking cessation used a hypothesis-driven approach to construct a genetic measure of dopamine signaling in the brain (David et al. 2013). The authors then used that genetic measure to test the hypothesis that dopamine signaling capacity would predict smoking cessation therapy outcome. "
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ABSTRACT: The sequencing of the human genome and the advent of low-cost genome-wide assays that generate millions of observations of individual genomes in a matter of hours constitute a disruptive innovation for social science. Many public use social science datasets have or will soon add genome-wide genetic data. With these new data come technical challenges, but also new possibilities. Among these, the lowest-hanging fruit and the most potentially disruptive to existing research programs is the ability to measure previously invisible contours of health and disease risk within populations. In this article, we outline why now is the time for social scientists to bring genetics into their research programs. We discuss how to select genetic variants to study. We explain how the polygenic architecture of complex traits and the low penetrance of individual genetic loci pose challenges to research integrating genetics and social science. We introduce genetic risk scores as a method of addressing these challenges and provide guidance on how genetic risk scores can be constructed. We conclude by outlining research questions that are ripe for social science inquiry.
Biodemography and Social Biology 10/2014; 60(2):137-55. DOI:10.1080/19485565.2014.946591 · 1.37 Impact Factor
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In smoking cessation trials, placebo response rates are reported to be rather low, and they are lowest when compared to the placebo response rates of treatment of other addictions. We hypothesized that high placebo response rates in trials outside of cessation treatment may predict low participation of smokers, and that non-smoking may be a behavioral marker of the placebo response.
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Non-smoking behavior may be association with higher placebo response rates and may indicate a biomarker for reward sensitivity of the nicotine-dopamine pathway. Common genotypes may underlie both behaviors.
Medical Hypotheses 06/2014; 83(3). DOI:10.1016/j.mehy.2014.06.012 · 1.07 Impact Factor
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Current Topics in Behavioral Neurosciences 02/2015; 23:37-86. DOI:10.1007/978-3-319-13665-3_3
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