Paediatrics (RCH) - Theses
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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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ItemEnvironment versus genetics in the development of health-related problems in childhood obesity( 2017)Introduction: Childhood obesity is a major health concern affecting a quarter of all Australian youth. Obese youth are at risk of multi-systemic obesity-related comorbidities (ORC), such as Prediabetes and Type 2 Diabetes Mellitus (T2DM), Hypertension, Hyperlipidaemia, Non-alcoholic fatty liver disease (NAFLD), Polycystic ovarian syndrome (PCOS), Obstructive sleep apnoea (OSA), mental health and orthopaedic issues. However, within the obese population, the severity of obesity is a poor predictor of these comorbidities. As such, current guidelines advise screening obese youth for all comorbidities, which is both time consuming and costly. ORC, as with obesity itself, are complex polygenic disorders involving interaction between genetic and environmental risk factors. Furthermore, many of these interactions are likely mediated by epigenetic variation, linking environmental exposures with genetic predisposition. Therefore, clarification of the role of environmental exposures, genetic risk factors and epigenetic profile in obese youth may provide valuable insight into determining which obese youth are at risk of developing ORC. The aim of this study was to characterise and investigate the associations between environmental, genetic and epigenetic factors with obesity-related comorbidities in obese youth. This information obtained will allow clinicians to better predict and profile the comorbidity burden in obese youth for targeting interventions to those most likely to benefit. Materials and Methods: The Childhood Overweight BioRepository of Australia collected comprehensive clinical and anthropometric data, as well as blood samples for genetic, metabolic and hormonal profile testing from patients (age 1 to 18 years) attending the Weight Management Clinic at the Royal Children’s Hospital, Melbourne. Anthropometric measures included standard measurements of weight, height and waist circumference (converted into BMI z-score (BMI-Z) and waist-height ratio for analyses) as well as total percentage body fat (%FM) and percentage truncal body fat (%truncal) using bioimpedance. Dietary intake was assessed using the Australian Child and Adolescent Eating Survey and physical activity was measured objectively using accelerometry. Genetic typing and epigenetic profiling of single nucleotide polymorphisms (SNP) and measures of DNA methylation were performed using the SEQUENOM MassARRAY platform. Results: 349 participants were included in the study. Both metabolic and non-metabolic ORC are common in obese youth. The most commonly used measure of adiposity, BMI-Z, was the anthropometric marker least associated with ORC, while important ORCs such as T2DM and hyperlipidaemia were not significantly associated with any of the anthropometric measures. The presence of two or more significantly elevated anthropometric markers was associated with the presence of a higher number of ORCs. Almost all obese youth reported poor vegetable intake and high sedentary behaviour (TV-watching and total media) time. Although initial analyses observed associations between sedentary behaviour (TV-watching and total media use time) with prediabetes and hyperlipidaemia, unhealthy food options with mental health issues, and high fruit intake with NAFLD, these associations lost significance after correction for multiple testing by false discovery procedure (FDR). However, low vitamin D levels were significantly associated with hypertension, independent of adiposity and season. The Fat Mass and Obesity (FTO) gene has the largest influence on adiposity amongst obesity-risk genes to date and has been associated with ORCs. In our cohort, the FTO risk allele was associated with poorer longitudinal weight outcomes in pre-pubertal children, but not pubertal adolescents. The FTO SNP however was not associated with any ORCs. We also examined the association between the top 22 T2DM risk SNPs identified from previous studies and Prediabetes or T2DM status. The SLC30A8 rs13266634 SNP appeared to be protective of prediabetes/T2DM status in unadjusted analysis but lost significant on FDR testing. The addition of T2DM SNPs profile to TV-watching time improved the predictive model for Prediabetes/T2DM status. We were not able to replicate the previously reported association of FTO CpG hypomethylation with prediabetes/T2DM in obese children and adolescents. However FTO hypomethylation was seen in obese youth with NAFLD, independent of age, sex and total body adiposity. FTO methylation was independent of FTO expression, which was not associated with any ORC. Conclusion: Anthropometry is not associated with comorbidities in childhood obesity. Environmental factors do not appear to be associated with comorbidities. Low vitamin D level is associated with hypertension. Genetic factors impact on weight gain but not comorbidities, and epigenetic factors may contribute to NAFLD. Combining these environmental and genetic elements with established clinical risk factors in the assessment of each individual ORC may assist in enhancing current clinical models of care for obese children and adolescents.