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Linkage and association mapping for quantitative phenotypes in isolated populations

Many complex diseases are known to have a substantial genetically heritable component. Elucidation of these genetic risk factors provides increased knowledge of the biological mechanisms that result in the diseases while also presenting new potential targets for therapy. This thesis explores the methodology of mapping genetic loci using isolated populations in the context of quantitative trait analysis. Chapter 1 explores the rational for the project, discussing the benefits of using quantitative traits rather than binary disease status and the pros and cons of using isolated populations. This is followed by a brief history of genetic mapping with reference to type 2 diabetes mellitus (T2D) and related quantitative traits. Chapter 2 introduces the methods used in this thesis. This includes strategies to deal with medication, methods to determine kinship between individuals, linkage analysis, association analysis and meta‐analysis of multiple studies. Chapter 3 presents linkage analysis of T2D related traits carried out in 2 – 4 populations depending on availability of the traits and appropriate marker data. Chapter 4 presents the results of association analysis for T2D related traits in 3 – 5 populations using genome‐wide SNP data. The results using the alternate methods described in chapter 2 are compared using fasting glucose as this was the most widely measured phenotype. Chapter 5 introduces additional traits derived by pulse wave analysis and discusses their relevance to metabolic disease before presenting association analysis using the preferred method from chapter 4. An overall discussion of the strengths and weaknesses of the analysis is given in chapter 6.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:563235
Date January 2011
CreatorsFranklin, Christopher Steven
ContributorsWilson, Jim. ; Wild, Sarah. ; Knott, Sara
PublisherUniversity of Edinburgh
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://hdl.handle.net/1842/5913

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