Assigning function to genome wide association study variants associated with complex gastrointestinal disease

Abstract

The genome‐wide association study era has identified numerous loci associated with many common polygenic diseases. The next challenge is to identify the functional consequences of these variants and elicit how they impact on disease risk. Using a combination of protein based assays, large scale microarrays and high‐throughput generation sequencing platforms this thesis aims to identify the functional effects of disease loci, with particular focus on Crohn’s disease and coeliac disease, two common complex gastrointestinal diseases. Variants located within the Interleukin 23 receptor are associated with both susceptibility and protection from Crohn’s disease, a debilitating chronic inflammatory disease of the bowel. A study was undertaken to investigate the effect of these variants, at the mRNA as well as the protein level, on both cytokine and receptor levels. Coeliac disease is a dietary intolerance to the gluten component of wheat, barley and rye and has an estimated prevalence of approximately 1%. Genome‐wide association studies have identified eight genomic different loci as associated with coeliac disease but none have been functionally characterised. To investigate the effect that genotype has on gene transcript levels, a genetical genomics study was undertaken in patients with coeliac disease generating results with relevance to a range of autoimmune disorders. Before disease based effects can be identified, it is first important to fully characterise the normal human transcriptome and methylome. To this end CD4 + T cells were studied using novel high‐throughput sequencing techniques, with the aim of providing some insight into novel genomic properties that may illuminate current and future disease associated loci. Given the base pair resolution approach of high‐throughput sequencing, a novel method of assaying for SNP effects on gene expression was developed. This allele specific method, using whole transcriptome sequencing, is capable of identifying alterations in transcript expression on a genome‐wide scale.