Published in

Nature Research, Scientific Reports, 1(6), 2016

DOI: 10.1038/srep35371

Links

Tools

Export citation

Search in Google Scholar

Gene-gene Interaction Analyses for Atrial Fibrillation

Journal article published in 2016 by Honghuang Lin, Martina Mueller-Nurasyid, Albert V. (Albert Vernon) Smith, Dan E. (Dan) Arking, John Barnard, Traci M. (Traci M.) Bartz, Kathryn L. (Kathryn) Lunetta ORCID, Kurt Lohman, Marcus E. (Marcus) Kleber, Steven A. (Steven) Lubitz, Bastiaan Geelhoed, Stella Trompet, Maartje N. (Maartje) Niemeijer, Tim Kacprowski, Daniel I. (Daniel) Chasman and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Upload
Red circle
Postprint: archiving forbidden
Green circle
Published version: archiving allowed
Upload
Policy details
Data provided by SHERPA/RoMEO

Abstract

AbstractAtrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27–1.65, P = 4.3 × 10–8). Eight additional gene-gene interactions were also marginally significant (P < 5 × 10–7). However, none of the top interactions were replicated. In summary, we did not find significant interactions that were associated with AF susceptibility. Future increases in sample size and denser genotyping might facilitate the identification of gene-gene interactions associated with AF.