Paediatrics (RCH) - Theses
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ItemEpigenetic Markers As A Predictor Of Lung Disease Severity In Cystic Fibrosis( 2020)Cystic fibrosis (CF) is a multisystem disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Lung disease which is the major source of morbidity and mortality in CF, begins in infancy and persists and progresses in the first years of life. The most sensitive measure of CF lung disease is computed tomography (CT) and the majority of children show evidence of bronchiectasis, which represents irreversible structural lung disease, by five years of age. The rate with which lung disease develops and progresses varies greatly between people with CF. Accurate prediction of future lung disease severity in people with CF would facilitate significant improvements in clinical care, as well as provide helpful information to people with CF and their families, health authorities and CF researchers. It has been demonstrated that CF lung disease severity is determined by a combination of non-CFTR genetic and environmental factors. However, no robust predictive biomarkers have been developed. Epigenetic mechanisms are those which regulate gene expression but do not alter the DNA sequence itself. DNA methylation is the most widely studied epigenetic mechanism, and an individual’s DNA methylation profile is determined by their underlying genotype and environmental exposures (including in utero). DNA methylation has been studied as a predictive biomarker in other childhood diseases, and given it is determined by the same factors which determine CF lung disease severity, is well positioned to act as a biomarker in CF. Despite this, DNA methylation based biomarkers of future lung disease severity have not been explored in CF. The thesis presents a series of projects which aimed to identify DNA methylation based biomarkers of future CF lung disease severity. The projects in this thesis utilised biospecimens and clinical data from the world leading Australian Respiratory Early Surveillance Team for Cystic Fibrosis (AREST CF) cohort. In order to better understand previous attempts at identifying predictive biomarkers, Chapter Two and Three describe reviews of the evidence regarding non-CFTR genetic modifiers of CF lung disease and DNA methylation based biomarkers of future health outcomes in children. The reviews highlight the importance of appropriate study design when trying to identify predictive biomarkers, which then informed design of the subsequent epigenome wide association study (EWAS). Chapters Four and Five describe the development of methods that were necessary for subsequent EWAS. In Chapter Four protocols for cryopreservation, and flow cytometry based phenotyping and sorting of specific cell populations were developed and validated for use with paediatric bronchoalveolar lavage (BAL). These methods were then used in Chapter Five to obtain purified populations of the common cell types in BAL, which were then used to develop reference epigenomes for these cell types. These reference epigenomes allowed adjustment for cell composition in the subsequent EWAS, which is a crucial step in DNA methylation studies involving samples with multiple cell types. Chapters Six and Seven describe the EWAS studies that attempted to identify predictive biomarkers. Chapter Six involved genome wide DNA methylation profiling of BAL collected at six years of age, and assessed the ability to predict the presence or absence of bronchiectasis at nine years of age. No predictive biomarkers were identified. Chapter Seven involved genome wide DNA methylation profiling of BAL collected at one year of age, and assessed the ability to predict the presence or absence of bronchiectasis at five years of age. Seven predictive biomarkers were identified, which when assessed using area under the receiver operator curve analysis had extremely good performance as predictive biomarkers. Several of the predictive biomarkers were related to genes that are relevant to CF lung disease pathophysiology and hence may represent therapeutic targets. By following best practice for EWAS, and in particular using tissue specific samples, adjusting for cell composition and assessing outcome using the gold standard measure, this thesis succeeded in identifying DNA methylation based biomarkers of future lung disease severity in CF. If these biomarkers are validated in external cohorts they could dramatically improve the care of children with CF around the world. N.B. There are two files that have been submitted separate to this thesis document as supplementary files. They have been highlighted as appropriate in the thesis. In addition, the code used for statistical analysis is available at: https://atlassian.petermac.org.au/bitbucket/pages/OS/paed-cf- methylation/master/browse/docs/index.html