Luke M Evans1,2, Emma C Johnson3, Whitney E Melroy-Greif1, John K Hewitt1,4, Charles A Hoeffer1,5, Matthew C Keller1,4, Laura M Saba6, Jerry A Stitzel1,5, Marissa A Ehringer1,5. 1. Institute for Behavioral Genetics, University of Colorado, Boulder, CO. 2. Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO. 3. Department of Psychiatry, Washington University School of Medicine, St. Louis, MO. 4. Department of Psychology and Neuroscience, University of Colorado, Boulder, CO. 5. Department of Integrative Physiology, University of Colorado, Boulder, CO. 6. Department of Pharmaceutical Sciences, University of Colorado, Anschutz Medical Campus, Aurora, CO.
Abstract
INTRODUCTION: Smoking is a leading cause of death, and genetic variation contributes to smoking behaviors. Identifying genes and sets of genes that contribute to risk for addiction is necessary to prioritize targets for functional characterization and for personalized medicine. METHODS: We performed a gene set-based association and heritable enrichment study of two addiction-related gene sets, those on the Smokescreen Genotyping Array and the nicotinic acetylcholine receptors, using the largest available GWAS summary statistics. We assessed smoking initiation, cigarettes per day, smoking cessation, and age of smoking initiation. RESULTS: Individual genes within each gene set were significantly associated with smoking behaviors. Both sets of genes were significantly associated with cigarettes per day, smoking initiation, and smoking cessation. Age of initiation was only associated with the Smokescreen gene set. Although both sets of genes were enriched for trait heritability, each accounts for only a small proportion of the single nucleotide polymorphism-based heritability (2%-12%). CONCLUSIONS: These two gene sets are associated with smoking behaviors, but collectively account for a limited amount of the genetic and phenotypic variation of these complex traits, consistent with high polygenicity. IMPLICATIONS: We evaluated evidence for the association and heritable contribution of expert-curated and bioinformatically identified sets of genes related to smoking. Although they impact smoking behaviors, these specifically targeted genes do not account for much of the heritability in smoking and will be of limited use for predictive purposes. Advanced genome-wide approaches and integration of other 'omics data will be needed to fully account for the genetic variation in smoking phenotypes.
INTRODUCTION: Smoking is a leading cause of death, and genetic variation contributes to smoking behaviors. Identifying genes and sets of genes that contribute to risk for addiction is necessary to prioritize targets for functional characterization and for personalized medicine. METHODS: We performed a gene set-based association and heritable enrichment study of two addiction-related gene sets, those on the Smokescreen Genotyping Array and the nicotinic acetylcholine receptors, using the largest available GWAS summary statistics. We assessed smoking initiation, cigarettes per day, smoking cessation, and age of smoking initiation. RESULTS: Individual genes within each gene set were significantly associated with smoking behaviors. Both sets of genes were significantly associated with cigarettes per day, smoking initiation, and smoking cessation. Age of initiation was only associated with the Smokescreen gene set. Although both sets of genes were enriched for trait heritability, each accounts for only a small proportion of the single nucleotide polymorphism-based heritability (2%-12%). CONCLUSIONS: These two gene sets are associated with smoking behaviors, but collectively account for a limited amount of the genetic and phenotypic variation of these complex traits, consistent with high polygenicity. IMPLICATIONS: We evaluated evidence for the association and heritable contribution of expert-curated and bioinformatically identified sets of genes related to smoking. Although they impact smoking behaviors, these specifically targeted genes do not account for much of the heritability in smoking and will be of limited use for predictive purposes. Advanced genome-wide approaches and integration of other 'omics data will be needed to fully account for the genetic variation in smoking phenotypes.
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