PLoS ONE (Jan 2020)

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

  • Peitao Wu,
  • Denis Rybin,
  • Lawrence F Bielak,
  • Mary F Feitosa,
  • Nora Franceschini,
  • Yize Li,
  • Yingchang Lu,
  • Jonathan Marten,
  • Solomon K Musani,
  • Raymond Noordam,
  • Sridharan Raghavan,
  • Lynda M Rose,
  • Karen Schwander,
  • Albert V Smith,
  • Salman M Tajuddin,
  • Dina Vojinovic,
  • Najaf Amin,
  • Donna K Arnett,
  • Erwin P Bottinger,
  • Ayse Demirkan,
  • Jose C Florez,
  • Mohsen Ghanbari,
  • Tamara B Harris,
  • Lenore J Launer,
  • Jingmin Liu,
  • Jun Liu,
  • Dennis O Mook-Kanamori,
  • Alison D Murray,
  • Mike A Nalls,
  • Patricia A Peyser,
  • André G Uitterlinden,
  • Trudy Voortman,
  • Claude Bouchard,
  • Daniel Chasman,
  • Adolfo Correa,
  • Renée de Mutsert,
  • Michele K Evans,
  • Vilmundur Gudnason,
  • Caroline Hayward,
  • Linda Kao,
  • Sharon L R Kardia,
  • Charles Kooperberg,
  • Ruth J F Loos,
  • Michael M Province,
  • Tuomo Rankinen,
  • Susan Redline,
  • Paul M Ridker,
  • Jerome I Rotter,
  • David Siscovick,
  • Blair H Smith,
  • Cornelia van Duijn,
  • Alan B Zonderman,
  • D C Rao,
  • James G Wilson,
  • Josée Dupuis,
  • James B Meigs,
  • Ching-Ti Liu,
  • Jason L Vassy

DOI
https://doi.org/10.1371/journal.pone.0230815
Journal volume & issue
Vol. 15, no. 5
p. e0230815

Abstract

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Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.