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.
"" 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. "
[Show abstract][Hide abstract] 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
[Show abstract][Hide abstract] ABSTRACT: Background:
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.
We re-analyzed raw data from a randomized controlled drug trial in functional dyspepsia (n=315) for the number of smokers and non-smokers in both treatment arms (drug, placebo) and varied the responder definition in a sensitivity analysis.
An equal number of smokers and non-smokers were assigned to drug and placebo. With the pre-defined responder definition (40% symptom improvement of a patient-reported outcome scale), 3% of placebo responders were smokers, but around 20% of patients among the placebo non-responder, and the drug responders and non-responders. With a more restrictive response definition (50% improvement) none of the placebo responders (n=29) was a smoker while the percentage of smokers remained similar in all other groups (p<.001). Age and gender did not affect this distribution.
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
[Show abstract][Hide abstract] ABSTRACT: This chapter summarizes genetic factors that contribute to variation in nicotineNicotine pharmacokinetics and nicotine's pharmacological action in the central nervous system (CNS), and how this in turn influences smokingSmoking behaviors. NicotineNicotine , the major psychoactive compound in cigarette smoke, is metabolized by a number of enzymes, including CYP2A6CYP2A6 , CYP2B6, FMOs, and UGTs, among others. Variation in the genes encoding these enzymes, in particular CYP2A6 CYP2A6 , can alter the rate of nicotineNicotine metabolism and smokingSmoking behaviors. Faster nicotineNicotine metabolism is associated with higher cigarette consumption and nicotine dependence, as well as lower quit rates. Variation in nicotine's CNS targets and downstream signaling pathways can also contribute to interindividual differences in smokingSmoking patterns. Binding of nicotineNicotine to neuronal nicotinic acetylcholine receptors (nAChRsnAChRs ) mediates the release of several neurotransmitters including dopamineDopamine and serotoninSerotonin . Genetic variationGenetic variation in nAChRsnAChRs , and in transporter and enzyme systems that leads to altered CNS levels of dopamineDopamine and serotoninSerotonin , is associated with a number of smokingSmoking behaviors. To date, the precise mechanism underpinning many of these findings remains unknown. Considering the complex etiology of nicotineNicotine addiction, a more comprehensive approach that assesses the contribution of multiple gene variants, and their interaction with environmental factors, will likely improve personalized therapeutic approaches and increase smokingSmoking cessation rates.
Current Topics in Behavioral Neurosciences 02/2015; 23:37-86. DOI:10.1007/978-3-319-13665-3_3
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