Genome-wide association studies (GWAS) have made substantial progress in implicating genomic regions in type 2 diabetes (T2D) susceptibility. Whilst attributing causal mechanisms to loci has proved non trivial, these studies have provided insights into the genetic architecture underlying the disease. GWAS findings indicate a causal role for gene regulatory processes, and suggest that pancreatic beta-cells play a pivotal role in mediating common T2D association. Work presented in this thesis therefore sought to generate novel regulatory annotations from human islets, and to assess whether T2D-associated loci can be accurately fine-mapped using statistical approaches, with the aim of improving understanding of causal mechanisms underlying these associations through integration of the two approaches. Using small RNA sequencing in human islets and enriched beta-cell populations (both n=3) and mRNA sequencing in a large number of human islets (n=130), I increased the number of available human islet annotations. These studies identified high or islet-specific expression in many micro RNAs (miRNAs) without previously known roles in human islets. It also provided the largest study of quantitative trait loci (eQTLs) and allele-specific expression (ASE) in human islets to date, identifying significant eQTLs for 1,636 genes and significant ASE at 8,754 genes. There was enrichment of active islet chromatin, compared to other tissues, at the best eQTL variant for each gene, but also substantial sharing of significant eQTLs between islets and other tissues. Simulations were used to assess the utility of fine-mapping approaches for refining common disease-associated loci to smaller intervals or sets of variants likely to include the causal variant. The results demonstrated that fine-mapping can indeed refine these loci to sets or intervals of a size more amenable to functional follow-up or focussed intersection with high quality annotations. Furthermore, using an approximated Bayesian approach, I was able to refine twenty-one of the known common T2D-associated loci. Finally, using the newly generated annotations, I demonstrated enrichment of T2D association signal for regulatory RNA annotations (islet lncRNAs and miRNA target gene sets). I also identified examples in which these types of annotation overlap common and rare variation suggestive of a role in T2D pathogenesis. Using further islet annotations, I also uncovered potential causal mechanisms at four of the twentyone fine-mapped common T2D loci. These data therefore provide many novel islet regulatory annotations that can be intersected with T2D genetics, and provide a first example of how such an approach can lead to novel potential causal mechanisms underlying association loci.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:639982 |
| Date | January 2014 |
| Creators | van de Bunt, Gerrit Martinus |
| Contributors | McCarthy, Mark I.; Gloyn, Anna L. |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:384baf0e-25b7-4ae4-a9c3-fee649d45368 |
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