Pathways to smoking behaviours: biological insights from the Tobacco and Genetics Consortium meta-analysis

Mol Psychiatry. 2017 Jan;22(1):82-88. doi: 10.1038/mp.2016.20. Epub 2016 Mar 29.

Abstract

By running gene and pathway analyses for several smoking behaviours in the Tobacco and Genetics Consortium (TAG) sample of 74 053 individuals, 21 genes and several chains of biological pathways were implicated. Analyses were carried out using the HYbrid Set-based Test (HYST) as implemented in the Knowledge-based mining system for Genome-wide Genetic studies software. Fifteen genes are novel and were not detected with the single nucleotide polymorphism-based approach in the original TAG analysis. For quantity smoked, 14 genes passed the false discovery rate of 0.05 (corrected for multiple testing), with the top association signal located at the IREB2 gene (P=1.57E-37). Three genomic loci were significantly associated with ever smoked. The top signal is located at the noncoding antisense RNA transcript BDNF-AS (P=6.25E-07) on 11p14. The SLC25A21 gene (P=2.09E-08) yielded the top association signal in the analysis of smoking cessation. The 19q13 noncoding RNA locus exceeded the genome-wide significance in the analysis of age at initiation (P=1.33E-06). Pathways belonging to the Neuronal system pathways, harbouring the nicotinic acetylcholine receptor genes expressing the α (CHRNA 1-9), β (CHRNB 1-4), γ, δ and ɛ subunits, yielded the smallest P-values in the pathway analysis of the quantity smoked (lowest P=4.90E-42). Additionally, pathways belonging to 'a subway map of cancer pathways' regulating the cell cycle, mitotic DNA replication, axon growth and synaptic plasticity were found significantly enriched for genetic variants in ever smokers relative to never smokers (lowest P=1.61E-07). In addition, these pathways were also significantly associated with the quantity smoked (lowest P=4.28E-17). Our results shed light on one of the world's leading causes of preventable death and open a path to potential therapeutic targets. These results are informative in decoding the biological bases of other disease traits, such as depression and cancers, with which smoking shares genetic vulnerabilities.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Female
  • Genetic Predisposition to Disease / genetics
  • Genetic Variation / genetics
  • Genome
  • Genome-Wide Association Study / methods
  • Genotype
  • Humans
  • Iron Regulatory Protein 2 / genetics
  • Male
  • Mitochondrial Membrane Transport Proteins / genetics
  • Nicotiana
  • Polymorphism, Single Nucleotide / genetics
  • Receptors, Nicotinic / genetics
  • Smoking / genetics*
  • Smoking / psychology
  • Smoking Cessation
  • Tobacco Use / genetics*
  • Tobacco Use Disorder / genetics

Substances

  • Mitochondrial Membrane Transport Proteins
  • Receptors, Nicotinic
  • SLC25A22 protein, human
  • Iron Regulatory Protein 2