Abstract
Interaction analysis of GWAS can detect signal that would be ignored by single variant analysis, yet few robust interactions in humans have been detected. Recent work has highlighted interactions in the MHC region between known HLA risk haplotypes for various autoimmune diseases. To better understand the genetic interactions underlying celiac disease (CD), we have conducted exhaustive genome-wide scans for pairwise interactions in five independent CD case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 14 independent interaction signals within the MHC region that achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD interaction signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for statistical interaction outside the MHC was not observed. Both within and between European populations, we observed striking consistency of two-locus models and model distribution. Within the UK population, models of CD based on both interactions and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. The interactions signal detected across the five cohorts indicates the presence of novel associations in the MHC region that cannot be detected using additive models. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.
Original language | English |
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Article number | e0172826 |
Journal | PLoS ONE |
Volume | 12 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2017 |
Bibliographical note
Publisher Copyright:© 2017 Te et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding
MI was supported by a Career Development Fellowship co-funded by the Australian NHMRC and Heart Foundation (#1061435). GA was supported by an NHMRC Peter Doherty Early Career Fellowship (#1090462). MI and GA were also supported by University of Melbourne funding. BG was supported by IBM Research Australia. BG, EK, QW, DR, FS, IH and AK were supported by National ICT Australia (NICTA).
Funders | Funder number |
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Heart Foundation | 1061435, 1090462 |
National ICT Australia | |
Multiple Sclerosis Research Australia | |
National Health and Medical Research Council | |
University of Melbourne |