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    Genetics of Plasminogen Activator Inhibitor – 1: a potent biological effector of cardiovascular disease risk

    White, Marquitta Jonisse
    : https://etd.library.vanderbilt.edu/etd-08272014-211036
    http://hdl.handle.net/1803/14029
    : 2014-08-28

    Abstract

    Cardiovascular disease (CVD) is an inclusive term encompassing several disorders of the circulatory system that together account for the majority of global non-communicable disease (NCD) mortality. Major thrombotic events, due in part to impaired fibrinolysis, are a unifying characteristic of several CVDs. Plasminogen activator inhibitor-1 (PAI-1) is a major regulator of fibrinolysis, and PAI-1 levels associate with CVD susceptibility and severity in several populations. The main objectives of this dissertation were to evaluate the genetic impact of common single nucleotide polymorphisms (SNPs) on inter-individual variation in PAI-1 levels in a Ghanaian population, and present a novel method to identify candidate genes for prioritization in future studies. We discovered novel associations between single variants in the arylsulfatase b (ARSB), carboxypeptidase A2 (CPA2), and leukocyte receptor cluster member 9 (LENG9) and median PAI-1 levels. Quantile regression analyses directed at the upper quartile of the PAI-1 distribution was performed to uncover novel variants with significant impact on this clinically relevant portion of the PAI-1 distribution. Upper quartile regression analyses revealed significant associations between single variants in period circadian clock 3 (PER3), a discovery that supports previous evidence of the involvement of the circadian pathway in regulation of PAI-1 levels in Caucasian populations as well as model organisms. This finding suggests that the significance of the circadian pathway as a whole may be generalizable across populations, even though gene effects may be population specific. We present a novel approach; Multi-lOcus based selection of Candidate genes (MOCA), which incorporates multi-variant association signals into the prioritization of genes for further evaluation. MOCA identified four significantly associated loci; these loci included 28 novel candidate genes for PAI-1 levels. Each MOCA identified locus was located within previously identified CVD and/or PAI-1 related quantitative trait loci (QTL).
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