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Paul Franks

Paul Franks

Principal investigator

Paul Franks

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Author

  • A.M. Erzurumluoglu
  • Frida Renström
  • Tibor V. Varga
  • Paul Franks
  • D.J. Liu
  • J.M.M. Howson

Summary, in English

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10−8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10−8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10−3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation. © 2019, The Author(s).

Department/s

  • Genetic and Molecular Epidemiology
  • EXODIAB: Excellence in Diabetes Research in Sweden
  • EpiHealth: Epidemiology for Health

Publishing year

2020-10

Language

English

Pages

2392-2409

Publication/Series

Molecular Psychiatry

Volume

25

Issue

10

Document type

Journal article

Publisher

Nature Publishing Group

Topic

  • Medical Genetics

Status

Published

Research group

  • Genetic and Molecular Epidemiology

ISBN/ISSN/Other

  • ISSN: 1359-4184