Paediatrics (RCH) - Theses
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ItemInvestigating the DNA methylation profiles of children with oligoarticular juvenile idiopathic arthritis (JIA)( 2019)Juvenile idiopathic arthritis (JIA) is a complex autoimmune disease affecting children aged between 6 months and 16 years. JIA represents a group of 7 subtypes of disease, with the most common being oligoarticular JIA (oJIA). Despite a prevalence of up to 1 in 400, rates similar to those in T1D, JIA research is relatively sparse. Research into disease pathogenesis has largely focussed on genetic risk factors, and has also identified CD4+ T-cells as likely to mediate the autoimmune process. However, research is particularly needed regarding diagnosis and prognosis of disease and its outcomes. Currently, diagnosis is almost entirely dependent on clinical observation and history, with little in the way of biomarkers to classify patients or to guide clinical management. Epigenetics represent biological modifications to DNA and chromatin that control gene expression and chromatin structure. DNA methylation is perhaps the most accessible modification available for study, and is known to modulate immune cell function particularly amongst CD4+ T-cell subsets. A number of autoimmune diseases have reported significant DNAm associations, and have also provided intriguing data on the potential of DNAm to predict clinical outcomes. This study hypothesised that DNAm is important in oJIA pathogenesis, and potentially provides a biological basis for the diagnosis and prognosis of disease. This study utilised CD4+ T-cells and a case-control study design to analyse the associations between DNAm and oJIA, with data generated from the Illumina Infinium HumanMethylation450 BeadChip array. Cases were matched with controls according to age and sex. Further, cases were subtyped according to current diagnostic criteria and had active disease, both of which attempted to ensure all cases were clinically homogeneous. The first aim was to profile DNAm in oJIA cases compared to controls. Processing of data through analysis pipelines resulted in high quality data. Differential methylation analysis suggested that oJIA cases and controls could be segregated in cluster analysis using DNAm data, despite no genome wide significant hits being produced. Immune system pathways analysis suggested the top hits were relevant to disease, being enriched for receptor binding of cytokines such as IL6, IL17 as well as MHC class II. In addition, a number of top ranking probes were enriched within cell death and survival functions. Indeed, gene expression data suggested genes within those pathways were also correlated with DNAm. Technical validation of a selection of probes was highly successful, with all probes validating. A small replication study, however, was not able to reproduce these findings. Of particular note, a wide distribution of DNAm values was observed for many of the validated probes. Since technical validation was so successful, this DNAm heterogeneity potentially derived from sample group heterogeneity, which may well have played a part in difficulties replicating data. Therefore, biological sources of heterogeneity were explored in chapter 5, focussing primarily on the genetic associations with DNAm. Probes utilised for technical validation were analysed for genetic associations associating with either mean or variable DNAm. Both analyses suggested that the most robust associations were for known mQTLs and enhancer SNPs. Indeed, DNAm differences according to genotype were up to 13% and 27% for 2 probes analysed, representing a many-fold difference over case-control differences (typically approximately 5%). Combined with an intermediate level of minor allele frequency for many of these robustly associated SNPs, these mQTLs represent a likely source of biological variation contributing to oJIA DNAm variation. These minor allele frequencies increase the likelihood of inadvertent sampling bias, potentially resulting in difficulties in replicating DNAm data. Deeper analysis provided some initial indication that these mQTLs may also be potential oJIA risk loci, with the most significant associations again coming from known mQTL or enhancer SNPs. This also suggested DNAm data may well identify regions of interest for genetic risk loci discovery. The final chapter hypothesised that sources of potential clinical heterogeneity not captured within current classification criteria may well lead to DNAm heterogeneity, as could recognised subgroups within oJIA. Of primary focus, age of disease diagnosis was assessed for associations with DNAm. This study found that case-control analyses of older diagnosed samples (greater than or equal to 6 years) resulted in case-control clustering using far fewer probes. Indeed, the reduction of probes required for clustering was more pronounced in the analysis of younger diagnosed samples (less than 6 years of age), and also resulted in a genome wide significant hit. These subgroups represented 2 highly divergent populations, since top ranking probes from each subgroup had virtually no overlapping probes. This data suggested that age subgroups in oJIA represent sources of sample heterogeneity, leading to DNAm heterogeneity. Technical validation for a large majority of the select probes from the younger-diagnosed analysis was also successful. However, a small replication study could not reproduce these initial findings. In light of the potential for mQTLs to have pronounced effects on DNAm, as explored in chapter 5, larger replication groups (or, indeed, discovery groups) will likely be needed to mitigate the risk of sampling error to enable reproduction of findings. OJIA heterogeneity was also explored by looking at known subgroups, Persistent vs Extended disease. A number of oJIA cases would go on to develop extended disease, and the possibility existed for DNAm signatures to identify these cases prior to disease extension. This was indeed the case, with an exploratory analysis suggesting a number of probes can cluster persistent cases from extended-to-be cases. Further, these probes were able to produce a highly sensitive and specific test to predict disease extension, thereby providing a proof of principle for a prediction test using DNAm data. This study is the largest case-control analysis of JIA DNAm to date, and provided insights into the potential for DNAm to identify pathogenic pathways, identify sources of oJIA heterogeneity, and opened the possibility for biological markers of disease to be used in clinical management. The findings regarding the pronounced effect of mQTLs on DNAm also suggest that genetics is a large source of DNAm variability, far larger than group differences typically found in a complex diseases (such as oJIA). The identification of subgroup specific differences, even with a clinically homogeneous subtype, warrants further investigation to explore potential differences in pathogenesis between age groups and the use of DNAm as biomarkers for classification or disease management.
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ItemCombined genetic and epigenetic analysis to identify early life determinants of complex phenotype( 2019)There is now considerable evidence indicating that risk of many complex diseases in adulthood may be influenced by exposure to environmental exposures in utero. A growing number of studies suggest epigenetic markers, including DNA methylation, are involved in this process. Understanding how DNA methylation is impacted by pregnancy exposures, and related to later health, may both contribute to unravelling the aetiology of complex disease risk in later life and provide a potential early-life biomarker for risk prediction. However, current evidence is limited. There has been a predominance of small, poorly powered studies, failure to consider the effects of genetic variation, and limited replication of previous findings. In addition, previous studies investigating the relationship between DNA methylation and offspring health have been primarily cross-sectional. For these reasons, I investigated the associations between pregnancy exposures (in particular, maternal smoking, nutrition and metabolic health, psychosocial stress, and adverse pregnancy conditions), birth outcomes, and offspring blood DNA methylation of the insulin-like growth factor 2 (IGF2) and H19, hypoxia-inducible factor 3A (HIF3A), leptin (LEP) genes. I also considered how genetic variation impacted on these associations. I then investigated the longitudinal relationship between early life methylation and anthropometry, as well as the association between early life methylation and later childhood measures of weight, adiposity, and cardiovascular health. To do this, the large, population-based longitudinal Barwon Infant Study pre-birth cohort (n=1,074) was used, with clinical and questionnaire measures from 28 weeks pregnancy, birth, 12 months post-birth and 4 years post-birth time points. DNA methylation of candidate regions was measured using the Sequenom EpiTyper mass-spectrometry platform in cord (birth) and peripheral (12-month) blood. Infant genetic variation in and near the candidate genes was considered. Infant adiposity was assessed as sum of triceps and subscapular skinfold thicknesses in infancy, and with DEXA scanning at 4 years of age. We found evidence that exposure to maternal psychosocial stress, gestational diabetes, and pre-eclampsia was associated with differences in offspring methylation at the candidate regions, as was infant sex. Genetic variation showed strong effects on DNA methylation levels, with some evidence for the associations of pre-eclampsia and infant adiposity with LEP methylation differing by infant genotype. Early life methylation of HIF3A and LEP showed modest associations with four-year blood pressure and BMI, respectively. While these associations persisted with adjustment for potential confounding factors, they explained relatively little variance in the four-year phenotypes compared to traditional predictors, such as weight. These findings suggest that offspring DNA methylation of these candidate genes involved in regulation of growth and metabolism are sensitive to several environmental exposures and genetic factors. While there is modest evidence for methylation in infant blood associating with later phenotypes, methylation of these genes appears unlikely to have useful predictive utility in isolation. This study is the first to perform early life longitudinal analysis to investigate the association between anthropometry and methylation in infancy. It is also the first to report evidence of earlier methylation associating with later cardiovascular phenotypes. However, as gene expression data was not available, the functional consequences of the altered methylation observed in blood is unclear. Further work is required to replicate these findings in independent cohorts, to determine the nature of expression of these genes in blood, and to investigate if the relationship between early life methylation and later health persists into adulthood.
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ItemIntragenic DNA methylation and neurodevelopmental outcomes in children with fragile X-related disorders( 2019)The type and severity of clinical involvement in children with fragile X syndrome (FXS) and disorders related to premutations (PM) of the fragile X mental retardation 1 gene (FMR1), herein collectively denoted as fragile X-related disorders (FXDs), is highly variable. Multiple molecular factors contribute to the heterogeneity of neurodevelopmental outcomes. Increased intragenic DNA methylation (DNAm) in blood of the fragile X-related epigenetic element 2 (FREE2) region, located at the FMR1 exon 1/intron 1 boundary, was associated with lower intellectual functioning in a cohort of female children and adults with FXS and with neuro-cognitive and psychiatric phenotypes in women with PM. Nevertheless, FREE2 DNAm has not yet been investigated in exclusively paediatric male and female FXDs cohorts. The overarching aim of this thesis was to explore FREE2 DNAm and neurodevelopmental outcomes of Australian male and female children with FXDs. Matrix assisted laser desorption/ionization time-of-flight mass spectrometry and methylation specific-quantitative melt analysis were used to analyse FREE2 DNAm in venous blood, buccal epithelial cells (BEC) and retrieved newborn blood spots (NBS). In addition, FMR1 mRNA levels in blood were assessed using real-time polymerase chain reaction (PCR) relative standard curve method. The evaluation of the neurodevelopmental outcomes concentrated on direct clinical assessment of intellectual functioning and autism spectrum disorder (ASD) symptom severity. Intelligence Quotient (IQ) scores were corrected for floor effect using the Whitaker and Gordon (WG) extrapolation method. The findings highlighted the variability of the clinical presentation of children with PM. Results also showed that compared to sex-matched paediatric controls, children with FXS had significantly higher levels of FREE2 DNAm levels in blood and BEC and, within the FXS group, higher FREE2 DNAm levels in blood correlated with lower FMR1 mRNA levels. In children with FXS, the application of the WG method effectively addressed the floor effect inherent in standardised intelligence scales, unmasked inter-individual variability in IQ scores and uncovered significant associations between intragenic DNAm and neurodevelopmental outcomes. Strength and statistical significance of these epigenotype-phenotype relationships varied based on sex, position of the differentially methylated sites, tissue analysed, assay used and neurodevelopmental domain investigated. The most significant finding was in males with FXS, for whom higher levels of BEC FREE2 DNAm were associated with lower WG-corrected Full Scale IQ (cFSIQ) and Performance IQ (cPIQ) scores. Finally, findings showed that the best-performing FREE2 biomarker had sensitivity, specificity, negative and positive predictive values of 100% for detection of full mutation alleles in NBS of males and females with FXS. Additionally, this study revealed that for males with FXS, FREE2 DNAm in NBS was significantly associated with lower cFSIQ and cPIQ scores obtained in childhood and adolescence. This is the first study in any monogenic neurodevelopmental disorder associated with intellectual disability, showing that a perinatal epigenetic biomarker is significantly associated with paediatric neuropsychological outcomes. In conclusion, the results of this thesis contribute to the characterisation of the neurodevelopmental outcomes in children with FXDs, provide evidence that FREE2 DNAm is a sensitive epigenetic biomarker significantly associated with the variability of intellectual functioning in male children with FXS, and may have implications for the development of new methylation specific tests for earlier diagnosis with potential prognostic applications.
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ItemInvestigating genomic and environmental risk factors and their interactions in juvenile idiopathic arthritis( 2017)Juvenile idiopathic arthritis (JIA) is a paediatric autoimmune disease arising from an abnormal immune response to self. It is the most common childhood rheumatic disease, with a prevalence of around 1 in 1000 Caucasian children. Disease prevalence is biased towards females, with around 2–3 females affected for every male. Due to the young age of onset, JIA can have a severe effect on a child’s growing skeleton and cause serious functional disability. And though onset is in childhood, the morbidity associated with JIA can be life-long as currently there is no cure for the disease, treatments are imperfect and preventative measures aren’t available – largely due to the limited understanding of disease pathogenesis. We hypothesised that genetic and environmental risk factors contribute individually and through interaction to cause JIA, and contribute to the sex bias in disease prevalence. The first aim of this study was to replicate the association of genetic variants that had previously been associated with JIA, in our independent sample. We confirmed the association of seven risk loci in our sample, six replicated for the first time. Our findings significantly strengthen the evidence that these loci harbour true JIA risk variants. The second aim of this study was to investigate whether autosomal genetic variants confer sex-specific risk for JIA. We established that of the 68 JIA risk loci tested, eight conferred sex-specific risk for JIA. Of these, three had statistically significant evidence of sex modifying the effect of that SNP on JIA. Of note, we replicated the femalespecific association of PTPN22 rs2476601 across two independent samples. Our findings illustrate that the genetic architecture of JIA differs between the sexes. Our third aim was to investigate whether the Y chromosome contributes to JIA risk in males. We determined that genetic variation captured by Y chromosome haplogroup I was associated with JIA risk, in males over the age of 6. We also demonstrated that there was an increased risk of JIA for males that had a father with autoimmune disease. Our findings are the first to suggest that the Y chromosome may play a role in JIA risk and provide further evidence that JIA has sex-specific genetic architecture. Next we considered the role of the environment in JIA risk. The fourth aim of this study was to assess the association between factors that impact vitamin D status and JIA. We identified a protective association between increasing UVR exposure over the life course and at 12 weeks of pregnancy, and JIA. Our findings are the first to implicate insufficient UVR exposure in the development of JIA. We then considered mechanisms through which genetic and environmental risk may be mediated, such as DNA methylation and gene expression. Our fifth aim was to identify sex-specific DNA methylation differences in CD4+ T cells between oligoarticular JIA cases and healthy controls. Oligoarticular JIA cases did not have substantial sex-specific DNA methylation differences when compared to controls, but there was evidence of modest case–control differences and these were more prominent in males than females. Our findings suggest that DNA methylation is not a significant driver of the sex bias in JIA. The final aim of this study was to investigate whether CD4+ T cell gene expression profiles differed between oligoarticular JIA cases and healthy controls. Oligoarticular JIA cases had aberrant gene expression relative to controls, suggesting that disease processes are in part driven by gene regulatory differences in CD4+ T cells. In conclusion, the cumulative findings of this study improve our understanding of the aetiology of JIA by revealing sex-specific genetic architecture for the disease, establishing UVR exposure as an environmental risk factor for JIA, and characterising the DNA methylation and gene expression signatures of the active disease state.