Molecular genetics of successful smoking cessation: Convergent genome-wide association study results

George R. Uhl, Qing Rong Liu, Tomas Drgon, Catherine Johnson, Donna Walther, Jed E. Rose, Sean P. David, Ray Niaura, Caryn Lerman

Research output: Contribution to journalArticlepeer-review

196 Scopus citations

Abstract

Context: Smoking remains a major public health problem. Twin studies indicate that the ability to quit smoking is substantially heritable, with genetics that overlap modestly with the genetics of vulnerability to dependence on addictive substances. Objectives: To identify replicated genes that facilitate smokers' abilities to achieve and sustain abstinence from smoking (hereinafter referred to as quit-success genes) found in more than 2 genome-wide association (GWA) studies of successful vs unsuccessful abstainers, and, secondarily, to nominate genes for selective involvement in smoking cessation success with bupropion hydrochloride vs nicotine replacement therapy (NRT). Design: The GWA results in subjects from 3 centers, with secondary analyses of NRT vs bupropion responders. Setting: Outpatient smoking cessation trial participants from 3 centers. Participants: European American smokers who successfully vs unsuccessfully abstain from smoking with biochemical confirmation in a smoking cessation trial using NRT, bupropion, or placebo (N=550). Main Outcome Measures: Quit-success genes, reproducibly identified by clustered nominally positive single-nucleotide polymorphisms (SNPs) in more than 2 independent samples with significant P values based on Monte Carlo simulation trials. The NRT-selective genes were nominated by clustered SNPs that display much larger t values for NRT vs placebo comparisons. The bupropion-selective genes were nominated by bupropion-selective results. Results: Variants in quit-success genes are likely to alter cell adhesion, enzymatic, transcriptional, structural, and DNA, RNA, and/or protein-handling functions. Quit-success genes are identified by clustered nominally positive SNPs from more than 2 samples and are unlikely to represent chance observations (Monte Carlo P

Original languageEnglish (US)
Pages (from-to)683-693
Number of pages11
JournalArchives of General Psychiatry
Volume65
Issue number6
DOIs
StatePublished - Jun 2008

ASJC Scopus subject areas

  • Psychiatry and Mental health

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