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. 2020 May 26;22(6):900-909.
doi: 10.1093/ntr/ntz099.

Genome-Wide Meta-Analyses of FTND and TTFC Phenotypes

Jingchun Chen  1 , Anu Loukola  2   3 , Nathan A Gillespie  4 , Roseann Peterson  4 , Peilin Jia  5 , Brien Riley  4 , Hermine Maes  4 , Daniella M Dick  6 , Kenneth S Kendler  4 , M Imad Damaj  7 , Michael F Miles  7 , Zhongming Zhao  5 , Ming D Li  8 , Jacqueline M Vink  9   10 , Camelia C Minica  9   11   12 , Gonneke Willemsen  9   11   12 , Dorret I Boomsma  9   11   12 , Beenish Qaiser  2   3 , Pamela A F Madden  13 , Tellervo Korhonen  2   14 , Pekka Jousilahti  15 , Jenni Hällfors  3 , Joel Gelernter  16 , Henry R Kranzler  17 , Richard Sherva  18 , Lindsay Farrer  18 , Brion Maher  19 , Michael Vanyukov  20 , Michelle Taylor  21 , Jenifer J Ware  21 , Marcus R Munafò  21 , Sharon M Lutz  22 , John E Hokanson  22 , Fangyi Gu  23 , Maria T Landi  23 , Neil E Caporaso  23 , Dana B Hancock  24 , Nathan C Gaddis  25 , Timothy B Baker  26 , Laura J Bierut  13 , Eric O Johnson  24   27 , Meghan Chenoweth  28 , Caryn Lerman  29 , Rachel Tyndale  28 , Jaakko Kaprio  2   3 , Xiangning Chen  1   4   30
Affiliations

Genome-Wide Meta-Analyses of FTND and TTFC Phenotypes

Jingchun Chen et al. Nicotine Tob Res. .

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.

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Figures

Figure 1.
Figure 1.
Network interaction based on markers with p values ≤5 × 10−5.
See this image and copyright information in PMC

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