Type of Document Dissertation Author Kenealy, Shannon URN etd-04042006-040044 Title Investigating the genetic susceptibility to multiple sclerosis: a genomic convergence approach Degree PhD Department Molecular Physiology and Biophysics Advisory Committee
Advisor Name Title Professor Marshall L. Summar Committee Chair Professor Douglas P. Mortlock Committee Member Professor John A. Phillips Committee Member Professor Jonathan L. Haines Committee Member Professor Scott M. Williams Committee Member Professor Subramaniam Sriram Committee Member Keywords
- chromosome 1q
- genetic linkage
- allelic association
- Multiple sclerosis -- Genetic aspects
Date of Defense 2005-08-12 Availability unrestricted AbstractMultiple sclerosis (MS) is a debilitating neuroimmunological and neuro-degenerative disease. Despite substantial evidence for polygenic inheritance, the MHC is the only region that clearly and consistently demonstrates linkage and association in MS studies. The goal of the work presented in this dissertation was to identify additional chromosomal regions harboring MS susceptibility genes. Our studies entailed a new genomic convergence approach incorporating information gained from positional (linkage and association) and functional (comparative sequence) studies. In conjunction with high-throughput genotyping and powerful new statistical analyses methods, this approach identified several regions suggesting the presence of MS loci.
We began our investigation with a genomic linkage screen that identified seven chromosomal regions of interest in a data set of multiplex MS families. To narrow these regions, we developed an approach for more detailed linkage studies that capitalized on new methods for rapid and accurate genotyping of SNPs. In addition to increasing marker coverage in each region, we genotyped an expanded data set and devised covariate analyses schemes to account for genetic effect in the MHC. This method
continued to provide evidence of linkage to several chromosomal regions and was successful in substantially narrowing two regions to only a few Mb.
We then developed a systematic approach to expedite follow-up association studies in the positional candidate regions. In an attempt to increase the likelihood of detecting variants associated with MS, we employed a novel method to select SNPs located in multi-species conserved sequences. Use of this method on chromosome 1q44 resulted in the identification of four subregions demonstrating significant association with MS susceptibility.
The work presented in this dissertation confirmed several regions warranting further investigation for genes conferring susceptibility to MS, including chromosomes 1q44, 2q35, 9q34, and 18p11. It is our hope that these studies will result in the discovery of several genes associated with MS and that our genomic convergence approach will provide researchers with a method for unraveling the genetic heterogeneity of MS and other complex genetic diseases.
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