The main aim of this project was to identify likely candidate genes in ischaemic stroke from a population in North-East Scotland. SNP allele frequencies were investigated for significant differences between case and control pools to identify chromosomal regions likely to contain relevant genes. In this way, 43 candidate genes for ischaemic stroke were identified. Two had previously been found by other studies (ALOX5AP and PDE4D), and several interact with each other in a particular biochemical pathway. Moreover, the majority of genes identified could be grouped into four main disease processes – lipid metabolism, atherosclerosis, inflammation and apoptosis. These are all either known risk factors for, or characteristic of, Stroke and therefore strengthen our confidence in these results. In a separate study, polymorphisms in two candidate genes (PPP1R3, implicated in type II diabetes, and PLAT, involved in the development of stroke) were selected for individual grouping genotyping in available samples on the basis of previous studies and literature searches. Results were conflicting: no association with stroke sub-type was found for any polymorphism in the PLAT gene, while only one PPP1R3 SNP was significantly reduced in small and large vessel disease (but not cardio-embolic) stroke cases compared to controls. On the other hand, a common ATTTA deletion was associated with cardio-embolic strokes. Haplotype analysis in PPP1R3 showed one combination to be more frequent in cases overall than controls. These experiments highlighted the complex nature of stroke genetics, and also emphasised the usefulness of studying intermediate phenotypes to identify the genetic basis of common, complex disorders. In addition, DNA pools combined with microarrays are a powerful, efficient means by which to identify novel candidate genes relatively quickly.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:439913 |
| Date | January 2006 |
| Creators | Ross-Adams, Helen |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU222719 |
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