No abstract

This study confirms that at least two independent variants in this nicotinic receptor gene cluster contribute to the development of habitual smoking in some populations, and it underscores the importance of multiple genetic variants contributing to the development of common diseases in various populations.

Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.

The purpose of this study was to assess the test-retest stability of the Fagerstrom Tolerance Questionnaire (FTQ) in two samples: (a) paid subjects in an American laboratory; data were collected via telephone screen and subsequently via questions embedded in a written history; and (b) smokers hospitalized for depression in Paris; data were collected via a written questionnaire upon admission and again after 3 weeks of treatment for depression. Reliability data are also presented for a recently revised version of the FTQ, the Fagerstrom Test for Nicotine Dependence (FTND), and compared with FTQ data collected in a subsample of subjects in the American database who received both versions of the questionnaire. Both the FTQ (in both samples) and the FTND proved to be highly reliable. The validity of the scales, using cotinine, number of years smoked, and the "addictive" factor on the Classification of Smoking by Motives questionnaire as criterion variables, was also supported. No relationship between FTQ score and severity of depression was detected in either sample. Internal consistency was somewhat higher for the FTND than for the FTQ, replicating previous findings in the literature.

Background Web-based programs for health promotion, disease prevention, and disease management often experience high rates of attrition. There are 3 questions which are particularly relevant to this issue. First, does engagement with program content predict long-term outcomes? Second, which users are most likely to drop out or disengage from the program? Third, do particular intervention strategies enhance engagement?Objective To determine: (1) whether engagement (defined by the number of Web sections opened) in a Web-based smoking cessation intervention predicts 6-month abstinence, (2) whether particular sociodemographic and psychographic groups are more likely to have lower engagement, and (3) whether particular components of a Web-based smoking cessation program influence engagement.Methods A randomized trial of 1866 smokers was used to examine the efficacy of 5 different treatment components of a Web-based smoking cessation intervention. The components were: high- versus low-personalized message source, high- versus low-tailored outcome expectation, efficacy expectation, and success story messages. Moreover, the timing of exposure to these sections was manipulated, with participants randomized to either a single unified Web program with all sections available at once, or sequential exposure to each section over a 5-week period of time. Participants from 2 large health plans enrolled to receive the online behavioral smoking cessation program and a free course of nicotine replacement therapy (patch). The program included: an introduction section, a section focusing on outcome expectations, 2 sections focusing on efficacy expectations, and a section with a narrative success story (5 sections altogether, each with multiple screens). Most of the analyses were conducted with a stratification of the 2 exposure types. Measures included: sociodemographic and psychosocial characteristics, Web sections opened, perceived message relevance, and smoking cessation 6-months following quit date.Results The total number of Web sections opened was related to subsequent smoking cessation. Participants who were younger, were male, or had less formal education were more likely to disengage from the Web-based cessation program, particularly when the program sections were delivered sequentially over time. More personalized source and high-depth tailored self-efficacy components were related to a greater number of Web sections opened. A path analysis model suggested that the impact of high-depth message tailoring on engagement in the sequentially delivered Web program was mediated by perceived message relevance.Conclusions Results of this study suggest that one of the mechanisms underlying the impact of Web-based smoking cessation interventions is engagement with the program. The source of the message, the degree of message tailoring, and the timing of exposure appear to influence Web-based program engagement.