Cigarette smoking is a major contributor to cancer, heartdisease, stroke, and lung disease and is the leading cause of preventable mortality in the United States and worldwide. Genome-wide association studies (GWAS) of nicotine dependence (ND) and other smoking phenotypes have unequivocally identified associations with single nucleotide polymorphisms (SNPs) spanning the nicotinic acetylcholine receptor (nAChR) genes on chromosome 15q25 (CHRNA5-CHRNA3-CHRNB4) and on chromosome 8p11 (CHRNB3- CHRNA6). The functional variants alter cessation treatment response and are independently associated with health consequences of smoking. However, they explain <10% of the phenotypic variability for smoking. In this study, we will move beyond standard GWAS, conducting the first study to apply the joint 2 degree-of- freedom (2df) statistical method using gene-gene interaction. It will be the largest genome-wide study of ND. The newly developed joint 2df method simultaneously considers SNP main and interactive effects but does not focus on detecting interaction per se. Instead, the method leverages interaction to increase power of the SNP association test. It has been used to successfully identify SNP associations missed in standard GWAS for other complex traits when accounting for gene-environment interactions. Here, we will apply the joint 2df method to simultaneously consider SNP main associations and their interactions with the established nAChR variants. We capitalize on existing GWAS data from our Collaborative Genetic Study of ND (COGEND), deCODE Genetics, and other studies available via the Database of Genotypes and Phenotypes (dbGaP) with Fagerstrom Test for Nicotine Dependence (FTND) data: collective size of >23,000 participants.
In Aim1, we will obtain genome-wide SNP genotype data from 14 study samples and harmonize their FTND phenotype data. Using COGEND and deCODE Genetics (total N=10,319 Caucasians), we will conduct genome-wide joint 2df meta-analyses of ND, in parallel, accounting for an interaction with either CHRNA5- CHRNA3-CHRNB4 (in Aim 2) or CHRNB3-CHRNA6 (in Aim 3). The top-ranking SNPs from the joint 2df meta-analyses will be prioritized using bioinformatics analyses to evaluate their annotation, functionality, and regulatory potential.
In Aim 4 a, we will select up to 100 top-ranking SNPs for replication testing in seven independent Caucasian samples from dbGaP (total N=8,913). Replicated SNPs from Aim 4a will be further tested for association with ND in Aim 4b using two of our African American samples and three dbGaP samples (total N=4,145). Our prior GWAS of smoking and others have identified robust, functionally important variants that also contribute to cessation treatment response and smoking-related diseases (e.g., lung cancer). This study leverages these early findings and a new statistical method to discover novel variants contributing to ND, which may similarly add to our understanding of smoking cessation and smoking's health consequences.

Public Health Relevance

This study will identify new genes associated with nicotine dependence, which is one of the strongest predictors of failing to quit cigarette smoking. The new genes will be identified by using a statistical method that will leverage interactions with wel-established nicotinic acetylcholine receptor genes. Results of this study may be used to better understand the genetic risk factors for nicotine dependence and smoking cessation and ultimately reduce the burden of smoking health consequences.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA035825-02
Application #
8692550
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Pollock, Jonathan D
Project Start
2013-07-01
Project End
2016-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Research Triangle Institute
Department
Type
DUNS #
City
Research Triangle
State
NC
Country
United States
Zip Code
27709
Saccone, Nancy L; Emery, Leslie S; Sofer, Tamar et al. (2017) Genome-wide association study of heavy smoking and daily/nondaily smoking in the Hispanic Community Health Study / Study of Latinos (HCHS/SOL). Nicotine Tob Res :
McKay, James D; Hung, Rayjean J; Han, Younghun et al. (2017) Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nat Genet 49:1126-1132
Chen, Li-Shiun; Baker, Timothy; Brownson, Ross C et al. (2017) Smoking Cessation and Electronic Cigarettes in Community Mental Health Centers: Patient and Provider Perspectives. Community Ment Health J 53:695-702
Hartz, Sarah M; Horton, Amy C; Hancock, Dana B et al. (2017) Genetic correlation between smoking behaviors and schizophrenia. Schizophr Res :
Hancock, D B; Guo, Y; Reginsson, G W et al. (2017) Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence. Mol Psychiatry :
Markunas, Christina A; Johnson, Eric O; Hancock, Dana B (2017) Comprehensive evaluation of disease- and trait-specific enrichment for eight functional elements among GWAS-identified variants. Hum Genet 136:911-919
Hartz, Sarah M; Horton, Amy C; Oehlert, Mary et al. (2017) Association Between Substance Use Disorder and Polygenic Liability to Schizophrenia. Biol Psychiatry 82:709-715
Hancock, D B; Reginsson, G W; Gaddis, N C et al. (2015) Genome-wide meta-analysis reveals common splice site acceptor variant in CHRNA4 associated with nicotine dependence. Transl Psychiatry 5:e651
Ramnarine, Shelina; Zhang, Juan; Chen, Li-Shiun et al. (2015) When Does Choice of Accuracy Measure Alter Imputation Accuracy Assessments? PLoS One 10:e0137601
Hancock, Dana B; Wang, Jen-Chyong; Gaddis, Nathan C et al. (2015) A multiancestry study identifies novel genetic associations with CHRNA5 methylation in human brain and risk of nicotine dependence. Hum Mol Genet 24:5940-54