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Thesis (MAppSc) -- Auckland University of Technology, 2003. / Also held in print (102 leaves, 30cm.) in Wellesley Theses Collection. (T 616.9515 PER)

Identifying a group of individuals that share a common set of characteristics is a conceptually simple task, which is often difficult in practice. Such phenotyping problems emerge in various settings, including the analysis of clinical data. In this setting, phenotyping is often stymied by persistent data quality issues. These include a lack of reliable labels to indicate the presence of absence of characteristics of interest, and significant missingness in observed variables. This dissertation introduces methods for learning phenotypes when the data contain missing values (partially observed) and labels are scarce (partially labeled). Aim 1 utilizes an unsupervised probabilistic graphical model to learn phenotypes from partially observed data. Aim 2 introduces a related semi-supervised probabilistic graphical model for learning phenotypes from partially labeled clinical data. Finally, Aim 3 describes a method for training deep generative models when the training data contain missing values. The algorithm is then applied in a semi-supervised setting where it accounts for partially labeled data as well.

Sickle cell disease is a monogenic blood disorder in which the clinical course and disease severity vary widely among patients. In order for physicians to make more informed decisions regarding the treatment and management of disease, it would be useful to be able to predict disease severity. We focus on two primary modulators of disease severity in sickle cell patients, hemolysis and fetal hemoglobin (HbF). This dissertation evaluates methodology to identify genetic variants associated with severity of sickle cell disease and develops new methodology of genetic risk prediction to predict disease severity in sickle cell patients based on levels of HbF. Hemolysis is a trait that is influenced by multiple correlated phenotypes (lactate dehydrogenase, reticulocytes, bilirubin and aspartate transaminase). There are several approaches to statistical analyses of multiple correlated phenotypes. The first part of this dissertation evaluates the use of principal component analysis (PCA) and compares it to the alternative approach of examining the results of multiple univariate phenotypes individually. We will focus on the question of if and under what conditions we gain more power using a summarized phenotype from PCA in a genome wide association study (GWAS) rather than conducting multiple individual GWAS. We find that the there is more power gained from the PCA approach when there is a strong intercorrelation between the phenotypes. The second part of this dissertation proposes a novel method of genetic risk prediction for continuous traits using an ensemble of genetic models. We aim to show through a simulation and prediction of HbF that the proposed method is more robust to the inclusion of false positives and yields more stable predictions than computing a GRS and 10 fold cross validation. The third part of this dissertation introduces a Bayesian-based clustering approach to produce clusters of sickle cell anemia patients based on their "predicted genetic profiles" of HbF. We then examine the genetic profiles of individuals in the extreme clusters to determine which genes contribute more prominently to the genetic profile so that we may potentially identify genes that are highly influential in the regulation of extremely high and low values of HbF.

published_or_final_version / Pathology / Master / Master of Medical Sciences

No description available.

Phase variation is mechanism of phenotypic switching used by many pathogenic bacterial species. This thesis describes work on three aspects of phase variation. Mathematical models are described which can be used to determine the rate of phase variation and subsequently the influence of variation rate and fitness differences associated with the altered phenotype on population structure. An approach to whole genome analysis has been developed which has been used to identify putative phase variable contingency genes in H. pylori, T. pallidum and N. meningitidis. This has identified many new contingency genes likely to be involved in host - bacterium and bacterium population interactions. Finally, a detailed molecular investigation of the promoter of the phase variable opc gene of N. meningitidis is presented. In this it is shown that the promoter located homopolymeric tract controls transcription by affecting the relative spacing and facing of promoter components, that this determines RNA polymerase binding to the promoter, and that this interaction involves direct contact of the a-subunit of RNA polymerase with the promoter. In addition it is shown that transcription is dependent upon an IHF consensus sequence in the opc promoter.

Microglia are the resident macrophages of the central nervous system (CNS) and, as key immune effector cells, form the first line of defence. Microglial cells also provide support for maintaining neuronal homeostasis and more generally normal brain physiology and cognitive function. It has been speculated that in order to support homeostasis, microglia adapt to a variety of brain microenvironments leading to regional phenotypic heterogeneity. To date this hypothesis lacks convincing empirical evidence, yet is critical to better understand microglial function in health and age-related neurodegenerative disease. In 2010 it was estimated that in the UK approximately 10 million people are over the age of 65, which is expected to double by 2050. Ageing is one of the strongest risk factors for neurodegenerative diseases such as Alzheimer’s and Parkinson‘s disease and growing evidence implicates neuroinflammatory mechansims that may involve microglial dysfunction in disease aetiology. The majority of age-related neurodegenerative diseases develop in a region-specific manner but the reasons are poorly understood. Accordingly, the work described in this thesis sought to determine the extent and nature of regional transcriptional heterogeneity of microglia and how this is affected by ageing. To examine the function and phenotype of these cells a technique for isolating pure microglia from the adult mouse brain was established. Microglia were consistently extracted by density-gradient and immunomagnetic cell separation. In vitro assays showed purified microglia retained key functional properties including phagocytosis, polarisation and production of pro-inflammatory cytokines in response to exogenous stimulation. Thus, freshly isolated microglia are not altered or dysfunctional during the extraction process and are likely to adequately represent the 'real' in vivo state. Genome-wide transcriptional network analysis of young adult mouse microglia from four discrete regions of the brain (cerebellum, cerebral cortex, hippocampus and striatum) uncovered regional heterogeneity in the microglial transcriptome driven particularly by bioenergetic and immunoregulatory functions. Transcriptional profiles of cerebellar and hippocampal microglia suggest a higher immune vigilance and alertness, which was supported by functional differences in the capability of microglia to phagocytose and control replication of bacteria. Region-dependent heterogeneity of microglia was largely consistent throughout the ageing process; however the region-specific phenotypes were more pronounced as age increased indicating region-dependent kinetics of microglial ageing. Collectively, the outcome of this study implies that microglia adapt to region-specific demands of brain tissue under steady-state conditions and are susceptible to ageing. Region was found to have a greater impact on microglial diversity than age. Overall, these findings will generate a substantial advance in our understanding of microglial function in the healthy brain and in age-related neurodegeneration.

Ecosystem engineers can govern ecosystem dynamics, yet ecosystem consequences of trait variation within engineering species are often overlooked. Combining field and greenhouse experiments with mathematical modelling, this study aimed to assess the relative importance of heritable and non-heritable trait variation within the engineer species Spartina alterniflora in controlling salt marsh erosion. In the field experiment, plots along a devegetated shoreline were restored with wild and cultivated sources to test whether populations exerted different control on erosion. The greenhouse experiment investigated whether genotypic trait differences were conserved when genotypes were exposed to elevated nutrients. A modelling approach was used to extrapolate empirical findings to temporal and spatial scales involved in landform evolution, considering spatial patterns in trait variation. The field experiment revealed that erosion rates were higher in plots planted with a wild, non-local source population as compared to plots planted with cultivars or local genotypes. Differential erosion could not be explained by differences in biomass, suggesting that other traits and resource use are stronger determinants of erosion. In the greenhouse experiment, cultivars and wild genotypes exhibited trait-specific differences in phenotypic plasticity under changing nutrient availability. Nutrient regime and heritable trait differences explained 70% of observed variation in soil shear strength. Soil shear strength increased when plants received more nutrients, but plant genotype had an equal or larger influence on soil characteristics. Model simulations suggested that older marshes (with large clones) and genetically diverse marshes (with high spatial variance in soil shear strength) may experience higher mean erosion rates. However, simulations also showed that average erosion rates are easily underestimated if the observation period is short, as variability of annual erosion rates and the probability of mass failure events were also mediated by clone size and composition. These findings illustrate that heritable and non-heritable trait variation interact with environmental conditions and landform history, together driving geomorphological processes crucial to the persistence of coastal marshes. Consideration of these interacting factors is needed when deploying ecosystem engineers for habitat restoration. / 1 / Brittany Marie Bernik

Previous studies of association of ABO phenotypes with gonorrhoea have shown contradictory results. Despite the interdependencies, none have examined the combined effect of ABO, Lewis and Secretor phenotypes. Furthermore, none have used genotyping to confirm phenotyping. This study is ground-breaking in this regard, and illustrates how such an association study should be performed. STUDY DESIGNS AND METHODS: The study examined 175 individuals who tested positive for gonorrhoea, and 211 individuals who tested negative for gonorrhoea. Strain typing was not performed. The following blood grouping methods were performed on the study participants: ABO phenotyping Lewis phenotyping, and genotyping of selected samples Secretor genotyping Chi-square and p values were used to examine whether or not there is an association of ABO, Lewis and Secretor blood group related molecules with gonorrhoea infection. RESULTS: Neither random statistical analysis of data sets, nor statistical analysis of data sets arranged by blood group, yielded a statistically significant association of ABO, Lewis and Secretor phenotypes and genotypes with Neisseria gonorrhoeae that could not be refuted when the data was disaggregated for ethnicity. The study did show a statistically significant difference in the incidence of the partial secretor phenotype (26.7%) in the gonorrhoea positive population and the incidence of the partial secretor phenotype (15.4%) in the gonorrhoea negative population, when all ethnic groups were analysed together. However, when the data was disaggregated for ethnicity, the p values were no longer statistically significant. CONCLUSION: There is no association of ABO, Lewis and Secretor phenotypes and genotypes with Neisseria gonorrhoeae. Nevertheless, this study still has merit, because, to the author's knowledge, it is the first time a study of these human blood groups with a disease has been performed correctly.