Jingchun Chen1, Anu Loukola2,3, Nathan A Gillespie4, Roseann Peterson4, Peilin Jia5, Brien Riley4, Hermine Maes4, Daniella M Dick6, Kenneth S Kendler4, M Imad Damaj7, Michael F Miles7, Zhongming Zhao5, Ming D Li8, Jacqueline M Vink9,10, Camelia C Minica9,11,12, Gonneke Willemsen9,11,12, Dorret I Boomsma9,11,12, Beenish Qaiser2,3, Pamela A F Madden13, Tellervo Korhonen2,14, Pekka Jousilahti15, Jenni Hällfors3, Joel Gelernter16, Henry R Kranzler17, Richard Sherva18, Lindsay Farrer18, Brion Maher19, Michael Vanyukov20, Michelle Taylor21, Jenifer J Ware21, Marcus R Munafò21, Sharon M Lutz22, John E Hokanson22, Fangyi Gu23, Maria T Landi23, Neil E Caporaso23, Dana B Hancock24, Nathan C Gaddis25, Timothy B Baker26, Laura J Bierut13, Eric O Johnson24,27, Meghan Chenoweth28, Caryn Lerman29, Rachel Tyndale28, Jaakko Kaprio2,3, Xiangning Chen1,4,30. 1. Nevada Institute of Personalized Medicine, University of Nevada Las Vegas, Las Vegas, NV. 2. Department of Public Health, University of Helsinki, Helsinki, FI, Finland. 3. Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. 4. Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA. 5. School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX. 6. Department of Psychology, Virginia Commonwealth University, Richmond, VA. 7. Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA. 8. State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. 9. Netherlands Twin Register, Department of Biological Psychology, VU University, the Netherlands. 10. Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands. 11. Neuroscience Campus Amsterdam, the Netherlands. 12. EMGO+ Institute for Health and Care Research, VU Medical Center, Amsterdam, the Netherlands. 13. Department of Psychiatry, Washington University, St. Louis, MO. 14. Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Finland. 15. National Institute for Health and Welfare, Helsinki, Finland. 16. Department of Psychiatry, Yale University, New Haven, CT. 17. Department of Psychiatry, University of Pennsylvania, Philadelphia, PA. 18. Section of Biomedical Genetics, Department of Medicine, Boston University School of Medicine, Boston, MA. 19. Department of Mental Health, Johns Hopkins University, Baltimore, MD. 20. Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, PA. 21. MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, BS, UK. 22. Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO. 23. Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, United States Department of Health and Human Services, Bethesda, MD. 24. Behavioral Health and Criminal Justice Division, RTI International, Research Triangle Park, NC. 25. Research Computing Division, RTI International, Research Triangle Park, NC. 26. Center for Tobacco Research and Intervention, University of Wisconsin, Madison, WI. 27. Fellow Program, RTI International, Research Triangle Park, NC. 28. Centre for Addiction and Mental Health, and Departments of Pharmacology and Toxicology, and Psychiatry, University of Toronto, Toronto, Canada. 29. Center for Interdisciplinary Research on Nicotine Addiction, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA. 30. Department of Psychology, University of Nevada Las Vegas, Las Vegas, NV.
Abstract
INTRODUCTION: FTND (Fagerstrӧm test for nicotine dependence) and TTFC (time to smoke first cigarette in the morning) are common measures of nicotine dependence (ND). However, genome-wide meta-analysis for these phenotypes has not been reported. METHODS: Genome-wide meta-analyses for FTND (N = 19,431) and TTFC (N = 18,567) phenotypes were conducted for adult smokers of European ancestry from 14 independent cohorts. RESULTS: We found that SORBS2 on 4q35 (p = 4.05 × 10-8), BG182718 on 11q22 (p = 1.02 × 10-8), and AA333164 on 14q21 (p = 4.11 × 10-9) were associated with TTFC phenotype. We attempted replication of leading candidates with independent samples (FTND, N = 7010 and TTFC, N = 10 061), however, due to limited power of the replication samples, the replication of these new loci did not reach significance. In gene-based analyses, COPB2 was found associated with FTND phenotype, and TFCP2L1, RELN, and INO80C were associated with TTFC phenotype. In pathway and network analyses, we found that the interconnected interactions among the endocytosis, regulation of actin cytoskeleton, axon guidance, MAPK signaling, and chemokine signaling pathways were involved in ND. CONCLUSIONS: Our analyses identified several promising candidates for both FTND and TTFC phenotypes, and further verification of these candidates was necessary. Candidates supported by both FTND and TTFC (CHRNA4, THSD7B, RBFOX1, and ZNF804A) were associated with addiction to alcohol, cocaine, and heroin, and were associated with autism and schizophrenia. We also identified novel pathways involved in cigarette smoking. The pathway interactions highlighted the importance of receptor recycling and internalization in ND. IMPLICATIONS: Understanding the genetic architecture of cigarette smoking and ND is critical to develop effective prevention and treatment. Our study identified novel candidates and biological pathways involved in FTND and TTFC phenotypes, and this will facilitate further investigation of these candidates and pathways.
INTRODUCTION: FTND (Fagerstrӧm test for nicotine dependence) and TTFC (time to smoke first cigarette in the morning) are common measures of nicotine dependence (ND). However, genome-wide meta-analysis for these phenotypes has not been reported. METHODS: Genome-wide meta-analyses for FTND (N = 19,431) and TTFC (N = 18,567) phenotypes were conducted for adult smokers of European ancestry from 14 independent cohorts. RESULTS: We found that SORBS2 on 4q35 (p = 4.05 × 10-8), BG182718 on 11q22 (p = 1.02 × 10-8), and AA333164 on 14q21 (p = 4.11 × 10-9) were associated with TTFC phenotype. We attempted replication of leading candidates with independent samples (FTND, N = 7010 and TTFC, N = 10 061), however, due to limited power of the replication samples, the replication of these new loci did not reach significance. In gene-based analyses, COPB2 was found associated with FTND phenotype, and TFCP2L1, RELN, and INO80C were associated with TTFC phenotype. In pathway and network analyses, we found that the interconnected interactions among the endocytosis, regulation of actin cytoskeleton, axon guidance, MAPK signaling, and chemokine signaling pathways were involved in ND. CONCLUSIONS: Our analyses identified several promising candidates for both FTND and TTFC phenotypes, and further verification of these candidates was necessary. Candidates supported by both FTND and TTFC (CHRNA4, THSD7B, RBFOX1, and ZNF804A) were associated with addiction to alcohol, cocaine, and heroin, and were associated with autism and schizophrenia. We also identified novel pathways involved in cigarette smoking. The pathway interactions highlighted the importance of receptor recycling and internalization in ND. IMPLICATIONS: Understanding the genetic architecture of cigarette smoking and ND is critical to develop effective prevention and treatment. Our study identified novel candidates and biological pathways involved in FTND and TTFC phenotypes, and this will facilitate further investigation of these candidates and pathways.
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