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dc.contributor.advisor Kraus, Virginia Byers en_US
dc.contributor.author Chen, Hsiang-Cheng en_US
dc.date.accessioned 2009-05-01T18:24:35Z
dc.date.available 2011-07-26T04:30:03Z
dc.date.issued 2009 en_US
dc.identifier.uri http://hdl.handle.net/10161/1112
dc.description Dissertation en_US
dc.description.abstract <p>Osteoarthritis (OA) is the most common joint disorder causing chronic disability in the world population. By the year 2030, an estimated one fifth of this population will be affected by OA. Although OA is regarded as a multi-factorial disorder with both environmental and genetic components, the exact pathogenesis remains unknown. </p><p> In this study, we hypothesize that biomarkers associated with OA can be used as quantitative traits of OA, and provide enough power to identify new genes or replicate known gene associations for OA. We established an extensive family called the CARRIAGE (CARolinas Region Interaction of Aging, Genes and Environment) family. Then, we measured and analyzed seven OA-related biomarkers (HA, COMP, PIIANP, CPII, C2C, hs-CRP and GSP) in this extensive family to evaluate their association with OA clinical phenotypes. These findings suggest that OA biomarkers can reflect hand OA in this large multigenerational family. Therefore, we performed nonparametric variance components analysis to evaluate heritability for quantitative traits for those biomarkers. Finally, based upon OA biomarkers with high heritability, we performed a genome-wide linkage scan. Our results provide the first evidence of genetic susceptibility loci identified by OA-related biomarkers, indicating several genetic loci potentially contributing to the genetic diversity of OA. </p><p> Meanwhile, we identified joint hypermobility as a factor which reduces OA risk and has an inverse association with serum COMP levels in this family. The relationship between lower serum COMP and OA have been further validated in another Caucasian GOGO (Genetics of Generalized Osteoarthritis) population. Therefore, we further hypothesize that joint hypermobility, having the characteristic of a decreased OA risk, can serve as a quantitative trait for identifying protective loci for OA. Then, we performed nonparametric variance components analysis to evaluate the heritability of joint hypermobility. The result also shows joint hypermobility has substantial heritable components in this family. Lastly, based on the same genome-wide linkage scan, we identify genetic susceptibility loci for joint hypermobility. </p><p> In conclusion, our work provides the first linkage study to identify genetic loci associated with OA using biological markers. Furthermore, we have also shown genetic susceptibility loci for joint hypermobility, possibly implying protective loci for OA.</p> en_US
dc.format.extent 1892122 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject Biology, Genetics en_US
dc.subject Health Sciences, Epidemiology en_US
dc.subject Biomarkers en_US
dc.subject Cartilage oligomeric matrix protein en_US
dc.subject Genetics en_US
dc.subject Joint Hypermobility en_US
dc.subject Osteoarthritis en_US
dc.subject Quantitative trait linkage analysis en_US
dc.title Genetics and Biomarkers of Osteoarthritis and Joint Hypermobility en_US
dc.type Dissertation en_US
dc.department Pathology en_US
duke.embargo.months 24 en_US

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