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Functional Characterisation of Rheumatoid Arthritis Risk Loci
[Thesis]. Manchester, UK: The University of Manchester; 2016.
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Abstract
The University of ManchesterAbstract of thesis submitted by Amanda Jane McGovern for the degree of Doctor of Philosophy entitled Functional Characterisation of Rheumatoid Arthritis Risk Loci in June 2016.Rheumatoid arthritis (RA) is a complex autoimmune disease affecting approximately 1% of the population. Multiple factors contribute to the development of RA, with genetic factors accounting for around 60% of the disease risk. Over the last few years, genome-wide association studies (GWAS) have successfully been used to identify regions of the genome predisposing to complex disease. There are now 101 confirmed RA risk loci, but for the vast majority of these loci the causal gene and causal variant remain unidentified and therefore, their function in disease is unexplored. The majority of genetic variants, or single nucleotide polymorphisms (SNPs), associated with disease map to non-coding enhancer regions, which may regulate transcription through long-range interactions with their target genes. The aims of this project were to identify the causal genes within an RA locus, pinpoint the causal variants and elucidate the mechanisms by which the variants modify gene function. Capture Hi-C (CHi-C) was carried out with the aim of identifying long range interactions between disease-associated SNPs and genes in four related autoimmune diseases. Many long-range interactions were identified which implicated novel candidate genes, interactions involving multiple genetic loci which had a common target, and interactions with loci which had previously been implicated in disease. Complex interaction patterns were observed in many of the disease associated loci, particularly in the 6q23 locus which is associated with a number of autoimmune diseases and is the focus of the present thesis. Within the 6q23 locus, associated SNPs lie a large distance from any gene (>180kb) making it difficult to pinpoint the exact causal gene. Results from CHi-C and chromosome conformation capture (3C-qPCR) experiments indicated that restriction fragments containing disease associated intergenic SNPs could display genotype-specific interactions with genes associated with autoimmunity (IL20RA and IFNGR1). Interactions could also be detected with long non-coding RNAs (lncRNAs), The lead SNP in the 6q23 region is in tight LD with eight other SNPs which are equally likely to be causal. Bioinformatics analysis suggested that the most plausible causal SNP in the 6q23 intergenic region was rs6927172, as it maps to an enhancer in both B-cells and T-cells, is in a DNaseI hypersensitivity cluster, shows transcription factor binding and is in a conserved region. Chromatin immunoprecipitation (ChIP) demonstrated binding of chromatin marks of active enhancers (H3K4me1 and H3K27ac) and the transcription factors BCL3 and NF-κB to the rs6927172 SNP target site in Jurkat T-cells and GM12878 B-cells, suggesting the risk allele could be associated with increased regulatory activity.In conclusion, these results show that CHi-C can help identify novel GWAS causal genes with the potential to suggest novel therapeutic targets. For example IL20RA is already a target for a monoclonal antibody which has been shown to be effective in treating RA in clinical trials. This project has also provided compelling evidence that the autoimmune risk variant in the 6q23 locus, rs6927172, is within a complex gene regulatory region, involving multiple immune genes and regulatory elements, such as lncRNAs.