Epistatic Analysis of Clarkson Disease

Abstract Genome Wide Association Studies (GWAS) have predominantly focused on the association between single SNPs and disease. It is probable, however, that complex diseases are due to combined effects of multiple genetic variations, as opposed to single variations. Multi-SNP interactions, known as epistatic interactions, can potentially provide information about causes of complex diseases, and build on previous GWAS looking at associations between single SNPs and phenotypes. By applying epistatic analysis methods to GWAS datasets, it is possible to identify significant epistatic interactions, and map SNPs identified to genes allowing the construction of a gene network. A large number of studies have applied graph theory techniques to analyse gene networks from microarray data sets, using graph theory metrics to identify important hub genes in these networks. In this work, we present a graph theory study of SNP and gene interaction networks constructed for a Clarkson disease GWAS, as a result of applying epistatic interaction methods to identify significant epistatic interactions. This study identifies a number of genes and SNPs with potential roles for Clarkson disease that could not be found using traditional single SNP analysis, including a number located on chromosome 5q previously identified as being of interest for capillary malformation.