Using biological networks to search for interacting loci in genomewide association studies

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  • Bioinformatics Research Centre (BiRC)
  • Interdisciplinary Nanoscience Center
  • Department of Computer Science
  • Department of Biological Sciences, Genetics and Ecology
Genome-wide association studies have identified a large number of single-nucleotide polymorphisms (SNPs) that individually predispose to diseases. However, many genetic risk factors remain unaccounted for. Proteins coded by genes interact in the cell, and it is most likely that certain variants mainly affect the phenotype in combination with other variants, termed epistasis. An exhaustive search for epistatic effects is computationally demanding, as several billions of SNP pairs exist for typical genotyping chips. In this study, the experimental knowledge on biological networks is used to narrow the search for two-locus epistasis. We provide evidence that this approach is computationally feasible and statistically powerful. By applying this method to the Wellcome Trust Case-Control Consortium data sets, we report four significant cases of epistasis between unlinked loci, in susceptibility to Crohn's disease, bipolar disorder, hypertension and rheumatoid arthritis.
Original languageEnglish
JournalEuropean Journal of Human Genetics
Number of pages10
Publication statusPublished - 2009

    Research areas

  • association studies, genome-wide scan, epistasis, biological network

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