No description available.

No description available.

No description available.

Thesis (doctoral)--University of Wisconsin-Madison, 2000. / Includes bibliographical references.

Research Project (M.B.A.) - Simon Fraser University, 2007. / Theses (Faculty of Business Administration) / Simon Fraser University. Senior supervisor: Dr. Aidan Vining -- Faculty of Business Administration. MBA-MOT Program. Also issued in digital format and available on the World Wide Web.

Thesis (doctoral)--University of Wisconsin-Madison, 2000. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Down syndrome, also referred to as trisomy 21, is a chromosomal abnormality in which the 21st human chromosome is partially or entirely duplicated. It is associated with a myriad of characteristics, including distinct facial deformities, intellectual disability, a heart defect, low muscle tone, and development of Alzheimer's disease symptoms with aging. This duplication is associated with increased levels of gene expression relative to what is present in euploid cells and disrupts the structure of some gene products. This study examines current mouse models of trisomy 21, describes a bioinformatics approach to evaluate relationships between genes on chromosome 21, and to determine the role they may play in Down syndrome associated intellectual disability. The Ts1Rhr, Tc1, and Ts65Dn mouse models are compared and contrasted to human trisomy 21. Representation of intellectual disability is determined by how the mice in each model perform on learning and memory tasks. Each model is examined for duplication of Down syndrome associated genes as well as for body weight, cerebral size, cerebellar size, balance, motor coordination, learning and memory, attention, activity, presence or absence of a heart defect, and presence or absence of a craniofacial defect. Next, a bioinformatics approach is proposed as tool with the capacity to examine the individual genes on chromosome 21, the relationships between the genes, group genes together by functional similarity and biological implication, and then establish which of these groups are enriched. The combined evaluation of mouse models and bioinformatics can be used as an innovative way to study the involvement in the intellectual disability associated with Down syndrome. Through the review of current mouse models and the evaluation of individual chromosome 21 genes using bioinformatics resources, the study seeks to determine what insights on intellectually disability can be gained.

Thanks to the affordability of DNA sequencing, hundreds of thousands of individuals with rare disorders are undergoing whole-genome sequencing in an effort to reveal novel disease aetiologies, increase our understanding of biological processes and improve patient care. However, the power to discover the genetic causes of many unexplained rare diseases is hindered by a paucity of cases with a shared molecular aetiology. This thesis presents research into statistical and computational methods for determining the genetic causes of rare diseases. Methods described herein treat important aspects of the nature of rare diseases, including genetic and phenotypic heterogeneity, phenotypes involving multiple organ systems, Mendelian modes of inheritance and the incorporation of complex prior information such as model organism phenotypes and evolutionary conservation. The complex nature of rare disease phenotypes and the need to aggregate patient data across many centres has led to the adoption of the Human Phenotype Ontology (HPO) as a means of coding patient phenotypes. The HPO provides a standardised vocabulary and captures relationships between disease features. I developed a suite of software packages dubbed 'ontologyX' in order to simplify analysis and visualisation of such ontologically encoded data, and enable them to be incorporated into complex analysis methods. An important aspect of the analysis of ontological data is quantifying the semantic similarity between ontologically annotated entities, which is implemented in the ontologyX software. We employed this functionality in a phenotypic similarity regression framework, 'SimReg', which models the relationship between ontologically encoded patient phenotypes of individuals and rare variation in a given genomic locus. It does so by evaluating support for a model under which the probability that a person carries rare alleles in a locus depends on the similarity between the person's ontologically encoded phenotype and a latent characteristic phenotype which can be inferred from data. A probability of association is computed by comparison of the two models, allowing prioritisation of candidate loci for involvement in disease with respect to a heterogeneous collection of disease phenotypes. SimReg includes a sophisticated treatment of HPO-coded phenotypic data but dichotomises the genetic data at a locus. Therefore, we developed an additional method, 'BeviMed', standing for Bayesian Evaluation of Variant Involvement in Mendelian Disease, which evaluates the evidence of association between allele configurations across rare variants within a genomic locus and a case/control label. It is capable of inferring the probability of association, and conditional on association, the probability of each mode of inheritance and probability of involvement of each variant. Inference is performed through a Bayesian comparison of multiple models: under a baseline model disease risk is independent of allele configuration at the given rare variant sites and under an alternate model disease risk depends on the configuration of alleles, a latent partition of variants into pathogenic and non-pathogenic groups and a mode of inheritance. The method can be used to analyse a dataset comprising thousands of individuals genotyped at hundreds of rare variant sites in a fraction of a second, making it much faster than competing methods and facilitating genome-wide application.

Lai Ching Ha. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 225-243). / Title --- p.1 / Abstract --- p.2 / Acknowledgments --- p.4 / Contents --- p.5 / Abbreviations --- p.10 / List of Figures --- p.12 / List of Tables --- p.15 / Chapter Chapter 1 --- Review on Inherited Metabolic Diseases --- p.18 / Chapter 1.1 --- Development of the concept of inherited metabolic diseases (IMD) --- p.18 / Chapter 1.2 --- Frequency of inherited metabolic diseases --- p.20 / Chapter 1.3 --- Molecular basis of mutations in inherited metabolic diseases --- p.22 / Chapter 1.3.1 --- Point mutations --- p.22 / Chapter 1.3.2 --- Small deletions and insertions --- p.25 / Chapter 1.3.3 --- large deletions or duplications --- p.26 / Chapter 1.4 --- Pathological consequences of protein defect resultingin IMD --- p.27 / Chapter 1.4.1 --- End product --- p.28 / Chapter 1.4.2 --- Precursor accumulation --- p.28 / Chapter 1.4.3 --- Unusual metabolites --- p.29 / Chapter 1.5 --- Heterogeneity of inherited metabolic diseases --- p.29 / Chapter 1.5.1 --- Genetic heterogeneity --- p.29 / Chapter 1.5.2 --- Variations of expression in different cells --- p.31 / Chapter 1.6 --- Diagnosis of inherited metabolic diseases --- p.32 / Chapter 1.6.1. --- Biochemical investigations --- p.32 / Chapter 1.6.2 --- Identification of accumulated or missing metabolites --- p.33 / Chapter 1.6.3 --- Direct analysis of enzymes and proteins --- p.34 / Chapter 1.6.4 --- Molecular investigations --- p.34 / Chapter 1.7 --- Treatment of inherited metabolic diseases --- p.40 / Chapter 1.7.1 --- Treatment at the clinical phenotype level --- p.41 / Chapter 1.7.2 --- Treatment at the metabolite level --- p.41 / Chapter 1.7.3 --- Treatment at the dysfunctional protein level --- p.43 / Chapter 1.7.4 --- Transplantation --- p.44 / Chapter 1.7.5 --- Gene therapy --- p.45 / Chapter 1.8 --- Inherited metabolic diseases in Hong Kong --- p.47 / Chapter 1.9 --- General Aim --- p.48 / Chapter Chapter 2 --- Study of Inherited Metabolic Diseases in Mentally Retarded Patients --- p.49 / Chapter 2.1 --- Introduction --- p.49 / Chapter 2.2 --- Aim --- p.52 / Chapter 2.3 --- Materials --- p.53 / Chapter 2.3.1 --- Standards --- p.53 / Chapter 2.3.2 --- Chemical reagents --- p.53 / Chapter 2.3.3 --- Derivatization reagents --- p.54 / Chapter 2.3.4 --- Major equipment --- p.54 / Chapter 2.4 --- Clinical materials --- p.56 / Chapter 2.4.1 --- Subjects --- p.55 / Chapter 2.4.2 --- Blood and urine samples --- p.56 / Chapter 2.5 --- Methods --- p.57 / Chapter 2.5.1 --- General biochemistry tests --- p.57 / Chapter 2.5.2 --- Metabolic screening tests --- p.57 / Chapter 2.5.3 --- Two-dimensional thin layer chromatography --- p.53 / Chapter 2.5.4 --- Identification of urinary organic acids by gas chromatography mass spectroscopy --- p.59 / Chapter 2.5.5 --- Amino acid analysis by high performance liquid chromatography --- p.66 / Chapter 2.6 --- Results --- p.71 / Chapter (A) --- Methodological Aspects / Chapter 2.6.1 --- Identification of urinary organic acids by gas chromatography-mass spectroscopy (GC-MS) --- p.71 / Chapter 2.6.2 --- Amino acid analysis by high performance liquid chromatography (HPLC) --- p.86 / Chapter (B) --- Patient Investigations / Chapter 2.6.3 --- General biochemistry tests --- p.107 / Chapter 2.6.4 --- Serum amino acid profiles --- p.113 / Chapter 2.6.5 --- Urinary organic acid analysis --- p.115 / Chapter 2.6.6 --- Case reports --- p.119 / Chapter 2.7 --- Discussion --- p.123 / Chapter 2.7.1 --- Identification of urinary organic acids by gas chromatography-mass spectroscopy (GC-MS) --- p.123 / Chapter 2.7.2. --- Amino acid analysis by high performance liquid chromatography (HPLC) --- p.130 / Chapter 2.7.3 --- Identification of inherited metabolic diseases (IMD)in an institutionalized mentally retarded patients --- p.136 / Chapter Chapter 3 --- Molecular Investigation of Maple Syrup Urine Disease --- p.140 / Chapter 3.1 --- Introduction --- p.140 / Chapter 3.1.1 --- Branched chain amino acids (BCAA) --- p.140 / Chapter 3.1.2 --- Metabolism of branched chain amino acids --- p.142 / Chapter 3.1.3 --- Maple syrup urine disease (MSUD) --- p.144 / Chapter 3.1.4 --- Classification of maple syrup urine disease --- p.146 / Chapter 3.1.5 --- Screening and diagnosis of maple syrup urine disease --- p.148 / Chapter 3.1.6 --- Treatment of maple syrup urine disease --- p.150 / Chapter 3.1.7. --- Branched chain a-ketoacid dehydrogenase complex (BCKDH) --- p.151 / Chapter 3.1.8 --- "Gene features of human E1α,E1β and E2 subunitsin branched chain α-ketoacid dehydrogenase complex" --- p.153 / Chapter 3.1.9 --- Molecular defects of the BCKDH gene complex --- p.156 / Chapter 3.1.10 --- MSUD in Hong Kong --- p.161 / Chapter 3.2 --- Aim --- p.163 / Chapter 3.3 --- Materials --- p.164 / Chapter 3.3.1 --- Source of skin fibroblasts --- p.164 / Chapter 3.3.2 --- Enzymes --- p.164 / Chapter 3.3.3 --- DNA markers --- p.164 / Chapter 3.3.4 --- Reagent Kits --- p.165 / Chapter 3.3.5 --- Primers --- p.165 / Chapter 3.3.6 --- Chemical reagents --- p.165 / Chapter 3.3.7 --- Nitrocellulose membrane --- p.166 / Chapter 3.3.8 --- Antiserum for Western blotting --- p.166 / Chapter 3.3.9 --- Radioisotopes --- p.166 / Chapter 3.4 --- Methods --- p.168 / Chapter 3.4.1 --- Preparation of buffers and solutions --- p.168 / Chapter 3.4.2 --- Agarose gel electrophoresis --- p.170 / Chapter 3.4.3 --- Preparation of native polyacrylamide gel --- p.171 / Chapter 3.4.4 --- Preparation of sodium dodecyl sulfate (SDS) polyacrylamide gel --- p.172 / Chapter 3.4.5 --- Preparation of denaturing polyacrylamide gel --- p.173 / Chapter 3.4.6 --- Branched chain α-ketoacid dehydrogenase complex enzyme assay --- p.173 / Chapter 3.4.7. --- Identification of the affected subunits in BCKDH complex of MSUD patient and her family members --- p.176 / Chapter 3.4.8 --- Screening of mutation in the BCKDH subunits by RT-PCR-SSCP --- p.178 / Chapter 3.4.9 --- Mutation analysis of whole cDNA fragments of Elα， Elβ and E2 subunits by ds DNA cycle sequencing --- p.184 / Chapter 3.5 --- Results --- p.188 / Chapter 3.5.1 --- Branched chain α-ketoacid dehydrogenase complex enzyme assay --- p.188 / Chapter 3.5.2 --- Identification of the affected subunits in BCKDH complex ofMSUD patient and her family members --- p.188 / Chapter 3.5.3 --- Screening of mutation in the BCKDH subunits by RT-PCR-SSCP --- p.192 / Chapter 3.5.4 --- "Mutation analysis of whole cDNA fragments of Ela, Elβ and E2 subunits by ds DNA cycle sequencing" --- p.204 / Chapter 3.6 --- Discussion --- p.210 / Chapter 3.6.1 --- BCKDH activity in the MSUD patient and her family members --- p.210 / Chapter 3.6.2 --- Investigation of the mutation sites --- p.212 / General Conclusion --- p.222 / Appendix --- p.224 / References --- p.225

Desmosomes are macromolecular, dynamic and adaptable complexes that connect intermediate filaments of neighboring cells in a variety of tissues, generating a large mechanically resilient structure. The importance of maintaining desmosome homeostasis for tissue integrity and optimal organ function has been revealed through the identification of desmosome-associated disorders and mechanistic studies into desmosome regulation. This thesis focuses on inherited skin and heart conditions linked to mutations in desmosomal genes or in genes believed to be implicated in desmosome regulation. Part of this thesis is focused on the molecular analysis and identification of novel desmosomal mutations in patients clinically diagnosed with Arrhythmogenic Right Ventricular Cardiomyopathy, and the genetic diagnosis of patients with hypotrichosis, hypotrichosis and PPK or acral peeling skin syndrome. Patients were analysed using a number of different genetic techniques including custom capture array, HaloPlex targeted resequencing, exome capture and Sanger sequencing. Both novel and previously reported mutations were identified in DSP, DSC2, DSG2, PKP2, DSG4 or CSTA in patients diagnosed with these disorders. The molecular mechanisms behind mutations in the protease inhibitors cystatin A and calpastatin, leading to the skin disorders exfoliative ichthyosis and PLACK syndrome, were also investigated. In vitro analysis, using siRNA-mediated knockdown in the immortalised keratinocyte cell line HaCaT, demonstrated that these mutations, affecting the structure and function of the protease inhibitors, lead to deficient intercellular adhesion, possibly through the indirect regulation of desmosomal complexes through their target proteases.