Familial clustering of diabetic kidney disease (DKD) suggests the existence of a genetic predisposition towards the development of the disease. DKD continues to be the leading cause of end-stage renal disease (ESRD) worldwide. The identification of factors associated with a higher risk of DKD is an important scientific goal. Novel biomarkers associated with DKD may prove useful for the clinical prediction of DKD. At the beginning of this project the key research theme was to explore the genome-wide association study (GWAS) data generated by the GEnetics of Nephropathy, an International Effort (GENIE) consortium. The GWAS dataset was derived from -2.4 million single nucleotide polymorphisms (SNPs) genotyped in a large case-control collection with multi-centre replication (n>12,OOO individuals). This initial project was promising, stimulating several additional projects assessing both mitochondrial and telomere-related genes and their associations with DKD. Genetic variation in the form of SNPs does not explain all of the inherited component of DKD so DNA methylation, was considered using data from an epigenome-wide association study (EWAS). This too was conducted on mitochondrial and telomere-related genes. The final stage of research within this thesis was to comprehensively evaluate genetic polymorph isms within the mitochondrial genome using next generation technology employing the Ion Torrent Personal Genome Machine (PGM) and Illumina TruSeq Genome Analyser (GAll).
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:696325 |
| Date | January 2015 |
| Creators | Swan, Elizabeth Joy |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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