Paediatrics & Child Health - Doctoral Theses
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Item SErENdipITy - study of electrophysiological biomarkers (electroencephalogram and heart rate variability) in neonatal seIzures and encephalopathy(University College Cork, 2023) Pavel, Andreea; Boylan, Geraldine B.; Murray, Deirdre M.; Dempsey, Eugene M.; Health Research Board; Wellcome Trust; Science Foundation IrelandBackground In recent years, the use of conventional electroencephalographic (EEG) monitoring in newborns has increased and it is now recognised worldwide to be the gold standard monitoring for neonatal seizure detection, as well as a reliable biomarker for brain injury and long term prognosis in this population. Similarly, heart rate variability (HRV) is a non-invasive monitoring which provides information regarding the autonomic nervous system function, and has also been explored as a biomarker for brain function and prognosis in newborns. These physiological monitoring have been proven useful, especially in newborns with encephalopathy following hypoxic ischaemic injury. Despite the increased use of therapeutic hypothermia (TH) and the decrease in adverse outcomes following hypoxic ischaemic encephalopathy (HIE), the incidence of HIE is 1.6 per 1000 live births in high-income countries. Early identification of newborns with HIE which might benefit from TH is still challenging in clinical practice. HIE is also the main cause of seizures in newborns. Due to the unique physiological properties of the neonatal brain, this is the age period with the highest risk of seizures, with an incidence of 1-5/1000 live births. Recent evidence showed that seizures themselves might add to the degree of brain injury regardless of the background pathology, and a high seizure burden was associated with worse long-term neurodevelopmental outcome. The majority of neonatal seizures are subclinical (electrographic only) or have very subtle clinical manifestations, thus the importance of early biomarkers to identify newborns which will develop seizures, as well as the importance of prolonged EEG monitoring for seizure detection. Aims The aims of this thesis were to explore the value of physiological biomarkers, such as early clinical parameters, EEG and HRV features for early prediction of neonatal HIE severity and seizures, as well as neonatal seizure detection and evolution. Using early EEG and HRV analysis I aim to develop prediction models for seizure occurrence and HIE severity. In addition, I plan to assess the clinical value of a neonatal seizure detection algorithm (ANSeR algorithm). By analysing newborns with HIE and electrographic seizures, I aim to describe the temporal evolution of seizures during TH and to evaluate if seizure burden and intensity (power) correlates with HIE severity and long-term outcome. Furthermore, I aim to assess if the time to treatment of the first electrographic seizure in newborns with HIE had an impact on subsequent seizure burden and outcome. Methods To achieve my goals, I have analysed infants recruited from two European multicentre cohort studies, across eight European tertiary neonatal intensive care units, between January 2011 and February 2017 (ClinicalTrials.gov Identifier: NCT02160171 and NCT02431780). The studies included infants born at 36 to 44 weeks corrected gestational age, requiring prolonged EEG monitoring for being at high risk of developing seizures or being suspected of having seizures. All infants had continuous EEG monitoring using disposable electrodes according to the 10:20 electrode placement system for neonates (F3, F4, C3, C4, Cz, T3, T4, O1/P3 and O2/P4), with simultaneous electrocardiography (ECG) monitoring. The clinical diagnosis of HIE was established by the teams at each recruiting site based on signs of perinatal asphyxia and encephalopathy on neurological examination (modified Sarnat score within 24 hours of age) and retrospectively corroborated with abnormalities suggestive of HIE on EEG and brain MRI. The clinical grade of HIE was based on the most severe score of modified Sarnat score. The encephalographic grade of HIE was established by visually analysing the EEG background using a system described previously by our group: 0-normal EEG background, 1-mild abnormalities, 2-moderate abnormalities, 3-major abnormalities and 4-inactive EEG background. The quantitative EEG analysis was performed using the NEURAL software package, extracting a set of features for power, discontinuity, spectral distribution and inter-hemispheric connectivity. The HRV analysis was performed using an in-house software (HRV Analysis, Beta Version 1.12, ©University College Cork 2008-2012) which automatically identified R-peaks on ECG recording. The RR interval was generated as the time difference between each R peak. HRV was expressed in time, frequency and complexity features. Electrographic seizures were defined as at least one EEG channel with sudden, repetitive and evolving waveforms for minimum 10 seconds. For all infants, electrographic seizures were identified by two neurophysiology experts in neonatal EEG. Seizure characteristics and seizure quantification were calculated based on these expert annotations. Results The two studies included 504 newborns, out of which 266 newborns had a diagnosis of HIE (3 newborns with HIE following postnatal collapse). Machine learning models were developed for early prediction of newborns with seizures in HIE, by analysing a cohort of 164 newborns with EEG monitoring before 12 hours of age. The best predictive models included both clinical parameters and EEG features: clinical and qualitative-EEG model (MCC (95% CI) 0.470 (0.336 to 0.602), AUC (95% CI) 0.721 (0.681 to 0.813)) and clinical and quantitative-EEG model (MCC (95% CI) 0.513 (0.376 to 0.645), AUC (95% CI) 0.746 (0.700 to 0.833)). A randomised controlled trial evaluating the real-time performance of a seizure detection algorithm (ANSeR algorithm) showed a higher detection of seizure hours in the algorithm group compared to the non-algorithm group (absolute difference (95% CI): 20.8% (3.6% to 37.1%)). Seizure hours detection between the two groups was even greater at weekends (Saturday-Sunday vs Monday-Friday), difference (95% CI): 16.6% (0.1% to 32.3%). Another study assessed the impact of the time to treatment of the first electrographic seizure on subsequent seizure burden showed significantly lower seizure burden and less seizures were noted in infants treated with anti-seizure medication (ASM) within 1 hour from seizure onset (p value=0.029 and 0.035, respectively). A similar trend was noted in the subgroup of infants who had a diagnosis of HIE (n=42). Analysis of newborns with HIE requiring TH with EEG monitoring throughout the rewarming phase, showed that newborns with seizures during active cooling and rewarming had a significantly higher seizure burden compared with newborns with seizures during active cooling exclusively (median (IQR) 167(54-275) vs 69(22-104) minutes, p=0.003). Seizure burden peaked at approximately 24 hours in both study groups and had a secondary seizure peak at 85 hours of age for the group of newborns with seizures during active cooling and rewarming. Newborns with seizures during active cooling and rewarming had a significantly higher risk of abnormal outcome compared to infants without seizures (OR(95% CI):4.62(1.40 to 15.24), p=0.012). In another study all electrographic seizures from 64 newborns with HIE and 2-year neurodevelopmental outcome were analysed. Infants in the severe HIE group had a higher seizure period, with more frequent seizures but less intense (lower mean seizure power), compared to infants in the moderate HIE group. Similar characteristics were associated with abnormal outcome at two years. Early HRV analysis was assessed to predict the EEG grade in neonatal HIE within the first 12 hours of life in 120 newborns. Performance of the HRV model was AUROC 0.837 (95% CI: 0.759-0.914), however performance of the HRV and clinical model combined had an AUROC of 0.895 (95% CI: 0.832-0.958). Conclusion Early qualitative and quantitative-EEG features alone and in combination with early clinical information can reliably predict infants that will later develop seizures in HIE, hours before seizure onset. The quantitative-EEG model proved as reliable as the analysis of a neonatal neurophysiologist expert (qualitative-EEG analysis) in predicting the likelihood of seizures, which could be also used to individualise the neurophysiology review frequency of the continuous EEG monitoring. The findings of the neonatal seizure detection algorithm trial validated in real time the performance of the ANSeR seizure detection algorithm by demonstrating its’ usefulness as a support tool for clinicians, especially during weekends when a limited number of health care professionals are available on site. The study of ASM timing for the first electrographic seizure showed that inappropriate treatment remains a concern in clinical practice, and that early anti-seizure treatment was associate with lower total seizure burden. Current findings suggest that treatment of neonatal seizures might be time-critical. The study of seizure evolution in HIE showed that one third of infants with HIE undergoing TH continued to have seizures after the completion of active cooling, increasing the overall seizure burden which might have an impact on long-term outcomes. Supporting the current guidelines recommendations, there is a clear need for continuous EEG monitoring during active cooling, rewarming and beyond when seizures persist. The seizure analysis in HIE showed that seizures were more frequent and were less intense in severe HIE compared to moderate HIE, and in newborns with adverse outcome compared to newborns with normal outcome at two years. This may have implications for seizure identification as low power seizures are usually harder to detect, especially using aEEG monitoring, which might have an impact on anti-seizure treatment and subsequently on long-term outcome. The study of early HRV analysis showed that HRV and clinical model had a good prediction of encephalopathy HIE severity in the early newborn period and may be a very useful additional tool for neonatologists who are often faced with challenging decisions about TH, especially where EEG monitoring is not available or feasible.Item Sleep and developmental outcome of the moderate to late preterm infant(University College Cork, 2023) Ryan, Mary Anne; Boylan, Geraldine B.; Mathieson, Sean; Dempsey, Eugene M.Background Sleep is the primary activity during early brain development and an essential part of healthy cognitive, physical and psychosocial development. Electroencephalography (EEG) provides detailed information about brainwave activity during sleep which changes in different sleep states and advancing gestational age (GA). The moderate to late preterm (MLP) infant is defined as an infant born between 32-36 +6 weeks GA. MLP’s are under-researched in terms of developmental outcome. We hypothesise that: • The sleep architecture of healthy MLP infants at 36 weeks may differ according to birth GA, birth weight, sex, mode of feeding or location (cot/incubator) at time of monitoring. • The developmental outcome of healthy MLP infants may be different to that of a term control group at 4 months and 18 months PMA. Aims • To describe the sleep architecture of healthy MLP infants in the neonatal unit at 36 weeks and the frequency of sleep interruptions using continuous EEG monitoring with video. • To describe parameters for the main EEG feature of quiet sleep i.e. inter-burst intervals (IBI) of MLP group with a normal developmental outcome at 18 months • To compare neurodevelopmental outcome of the MLP infant group to that of a term control (TC) infant group at 4 months and 18 months. Methods MLP infants recruited in the neonatal unit had overnight continuous EEG monitoring (12 hours) with video at 36 weeks post menstrual age (PMA). Post-acquisition, sleep states and sleep interruptions were annotated and quantified based on visual analysis of EEG, behavioural observation and cardiorespiratory parameters. Using an inter-burst interval (IBI) detection algorithm five IBI features of QS were extracted from MLP infants with a normal developmental outcome at 18 months. Outcome of MLP infant group was compared to a healthy term control (TC) group based on scores achieved in the Griffiths lll mental development scales at 4 and 18 months PMA. In comparing outcome of MLP and TC infant groups, the Mann–Whitney U test was used for continuous variables and the Chi-squared test or Fisher’s exact test was used for categorical variables. A p-value <0.05 is considered to be statistically significant. Cohens d (the standardized mean difference between the MLP and TC groups) was used as the measure of effect size. Results Ninety-eight infants had overnight EEG’s included in this study. In the neonatal unit 23.3% of sleep cycles were interrupted primarily for feeding. The total overnight sleep time (TST) was 7.09(6.61-7.76) hrs including 4.58(3.69-5.09) hrs in active sleep (AS), 2.02(1.76-2.36) hrs in quiet sleep (QS) and 0.65(0.48-0.89) hrs in indeterminate sleep (IS). The total duration of AS was significantly lower in infants born at lower GA (p= 0.007) whilst the duration of individual QS periods was significantly higher (p=0.001).Sixty infants had a normal outcome at 18 months and were included in the QS analysis study using the IBI detection algorithm. Normative data for five IBI features was extracted from QS. All IBI features were significantly longer for infants cared for in incubators although these infants were chronologically younger ( p<0.001). When neurodevelopmental outcome of the MLP and TC groups were compared at 4 and 18 months PMA, the MLP infant group achieved lower scores than in overall general development. The greatest differences were in the area of gross motor development (p <0.001, with a Cohen’s d effect size of -0.665), eye-hand coordination (p<0.001, with a Cohen’s d effect size of -0.648). Using the reported Griffith’s cut off of < 90 for delayed development, 7% (5/75) of the MLP group had delayed development at 18mths compared to 2% (2/92) of the TC group. Conclusion EEG provides an objective insight into sleep organisation and may be considered a biomarker of brain development. This thesis provides detailed analysis of the sleep EEG of a cohort of healthy MLP infant at 36 weeks PMA and provides useful reference criteria for studies that may assess brain maturation in the future, particularly for those infants in neonatal intensive care units.Item PiRAMiD: predicting early onset autism through maternal immune activation and proteomic discovery(University College Cork, 2023) Carter, Michael; Murray, Deirdre M.; Gibson, Louise; O'Keeffe, Gerard W.; English, Jane; National Children's Research CentreAutism spectrum disorder (ASD) is a heterogeneous developmental disorder arising early in life. ASD is composed of a wide variety of clinical characteristics, neuropsychological impairments and complex phenotypes. The classical triad of ASD symptoms includes disrupted social function, atypical verbal and non-verbal communication skills, and restricted interests with repetitive behaviours. These core symptoms often coexist with other psychiatric and neurological comorbidities. Attention Deficit Hyperactivity Disorder (ADHD), epilepsy, migraine, and anxiety are much commoner in children with ASD. Children and adults with ASD often encounter difficulties with emotional and behavioural problems (EBPs) such as emotional reactivity, aggression, and depression. Up to 50% of those affected can have intellectual disability (ID) and limited verbal communication. Social, emotional and behavioural deficits in children with ASD are also important modifiers of outcome and are linked to elevated stress, mental and physical health problems, and lower overall family and caregiver well-being. We know that early intervention can be effective, and may be parent or therapist delivered. Pharmacological treatment of ASD can be successful insofar as it is useful for symptomatic management of some ASD comorbidities such as ADHD, and depression. Although genetic susceptibilities are increasingly recognised, the mechanism of disease development in ASD remains unknown. We are aware of both common and rare genetic risk factors with more than four hundred diverse high confidence genes now linked to ASD (https://www.sfari.org/resource/sfari-gene/). Singly, these genetic factors each convey only a modest increase in ASD risk (~1%), however collectively they can contribute to a far greater risk. Both de novo and inherited genetic defects are recognised but ASD risk in progeny does not follow a clear pattern of inheritance. Estimates of heritability of ASD in twin pairs vary widely between 50 – 90%. The apparent male preponderance in ASD persists with a clear bias towards males. Rates of ASD among males exceed those of females by three or fourfold hinting at a possible sex differential genetic foundation. Up to 20% of individuals with ASD may possess copy number variants (CNV) and de novo loss of function single nucleotide variants (SNV) that are individually rare but in combination, increase an individual’s overall ASD risk. While newer methods of genetic analysis (such as whole genome sequencing) are uncovering new candidate genes with regularity, the heterogeneity of the clinical and phenotypic groups within ASD strongly suggest that in those with a genetic predisposition, environmental factors may act in concert to bring about a multisystem dysfunction leading to ASD. Despite recent advances in gene analysis, we are yet to discover a single gene determinant that can account for more than a small percent of ASD cases. The current ASD literature suggests that mutations occurring in genes involved in synapse formation, cell adhesion molecule production (Cadherin), scaffolding proteins (SHANK proteins), ion channels (sodium, calcium, and potassium channels), and signaling molecules can disrupt regulatory or coding regions and affect synapse formation, plasticity and synaptic transmission. All this suggests that we cannot explain many cases of ASD by genetic factors alone, or at least we cannot explain them using our current understanding of ASD genetics or our current techniques of genetic analysis. The flawed picture of ASD genetics has led some to investigate the role of environmental exposures in the aetiology of ASD. Researchers have identified many environmental risks in ASD. Advanced parental age, foetal environmental exposures, perinatal and obstetric events, maternal medication use, smoking and alcohol use, psychosocial hardship, nutrition and toxic exposures have all been implicated as risks in the pathogenesis of ASD. While authors attribute between 17 - 41% of ASD risk to non-genetic or environmental exposures, the exact balance between genetic and environmental determinants and their roles in aetiology remains disputed. Multiple mechanisms have been proposed through which each of these exposures may exert an influence on genetic and epigenetic risk in ASD , but there are only a handful that are likely to effect abnormal neurodevelopment. Animal models of inflammation and maternal immune activation are particularly well characterised, and have successfully modelled ASD type behaviours and social difficulties in mice, rats and non-human primates. Maternal immune activation (MIA) is defined as an increase in measured levels of inflammatory markers in mothers during pregnancy. Through this process, a cytokine cascade transmits to the foetus, resulting in adverse neurodevelopmental phenotypes and even remodelling of the immature foetal brain. Many studies have profiled cytokine, chemokine, immune cell and inflammatory signatures in ASD affected individuals. Only a much smaller number have characterised cytokine profiles in expectant mothers who progressed to birth children who develop ASD. The few previous studies, which have examined gestational serum, have indicated mid-gestational upregulation in specific pro-inflammatory cytokines or indeed down-regulation in anti-inflammatory cytokines. Metabolomic analysis refers to the systematic identification and quantitation of all metabolites in a given biological sample. This collection of metabolites, known as the metabolome, is thought to directly reflect the biochemical activity of the studied system at a specific point in time. The metabolome has become an area of interest, as some inborn errors of metabolism (IEM) are clearly linked to ASD phenotypes. Phenylketonuria (PKU) and Smith-Lemli-Opitz syndrome (SLOS) are disorders of amino acid and cholesterol metabolism respectively. Untreated PKU is associated with strongly autistic phenotypes, while SLOS is phenotypically heterogeneous, but autism remains a common feature in these children. Similarly, proteomics is defined as the study of the complete protein profile in a given tissue, cell or biological sample. Proteomic studies of human sera have so far noted altered levels of proteins involved in inflammation or immune system regulation, including acute phase reactants and interleukins. Abnormalities of the complement system have also been found in ASD and other psychopathologies such as schizophrenia. Recent works demonstrate that the complement pathway can affect synaptic remodelling and has roles in neurodevelopmental processes. The initial focus of ASD research on genomics has largely failed to result in the much-hoped-for silver bullet of ASD aetiology, i.e. a common genetic cause. Instead, the genetic landscape has proven to be exceedingly complex and interdependent on a multitude of factors, including environmental exposures and other modifiers of genetic risk. Research examining the aetiology of ASD has shifted focus from genetics to a multimodal approach. In recent years, funding has become available for a far wider variety of ASD aligned research topics, beyond those with a focus on genetics. Opportunities now exist to adopt a multifaceted approach to ASD aetiology, shifting the focus from a narrow genetic base, to a broader multimodal approach to examine other potential mechanistic players. While this adds further complexity to what is already a complicated picture, the strived for parsimonious answer is simply never likely to materialise. Newer fields and modalities such as proteomics, metabolomics and machine learning will help to further refine and untangle the complicated web of ASD, and this variety of granular detail is what is likely to result in a practicable biomarker or effective therapy in the future. In this thesis using a multimodal approach (ELISA, metabolome and proteome analysis) we aim to explore further the role of MIA and alterations of the proteome and metabolome in the pathophysiology of ASD. We hope that our findings may ultimately help to identify a potential gestational biomarker of ASD, which will improve access to early diagnosis and treatment. We also aim to characterise co-morbid emotional and behavioural problems, which arise early in children with ASD and are pervasive throughout all spheres of life. Early recognition and intervention with these co-morbidities can improve treatment outcomes, patient, and family wellbeing.Item Multi-modal assessment of newborns at risk of neonatal hypoxic ischaemic encephalopathy – the MONItOr study(University College Cork, 2022) Garvey, Aisling A.; Dempsey, Eugene M.; Murray, Deirdre M.; Boylan, Geraldine B.; National Children’s Research Centre, Crumlin, IrelandBackground: Hypoxic ischaemic encephalopathy (HIE) is the leading cause of acquired brain injury in term infants. At present, therapeutic hypothermia (TH) is the only approved therapy for infants with moderate-severe HIE. However, it must be commenced before 6 hours of age resulting in a clinical challenge to resuscitate, stabilize, identify and stratify infants in this narrow timeframe. Furthermore, a significant proportion of infants with mild HIE will have neurodevelopmental impairment. Improved, timely identification of infants at risk of brain injury is required. The aim of this study was to improve our knowledge of the early physiology of infants with HIE by describing the evolution of electroencephalography (EEG), near-infrared spectroscopy (NIRS) and non-invasive cardiac output monitoring (NICOM) in infants with all grades of HIE and to determine whether these markers may be helpful in the identification of infants at risk of brain injury. Methods: This prospective observational study was set in a tertiary neonatal unit (November 2017-March 2020). Infants with all grades of HIE had multi-modal monitoring, including EEG, NIRS and NICOM, commenced after delivery and continued for up to 84 hours. All infants had an MRI performed in the first week of life. Healthy term controls were recruited after delivery and had NICOM monitoring at 6 and 24 hours of age. In this thesis, I also included infants recruited previously as part of four historic prospective cohorts that had early EEG monitoring. These infants were combined with infants with mild HIE from the current prospective cohort to examine the difference in EEG features between infants with mild HIE and healthy term controls. Results: Eighty-two infants were recruited in the prospective cohort (30 mild HIE, 25 moderate, 6 severe, 21 controls) and 60 infants were included from the historic cohorts. This study identified significant differences between EEG features of infants with mild HIE and controls in the first 6 hours after birth. Seventy-two percent of infants with mild HIE had some abnormal features on their continuous EEG and quantitative analysis revealed significant differences in spectral shape between the groups. In our cohort, cSO2 increased and FTOE decreased over the first 24 hours in all grades of HIE regardless of TH status. Compared to the moderate group, infants with mild HIE had significantly higher cSO2 at 6 hours (p=0.003), 9 hours (p=0.009) and 12 hours (p=0.032) and lower FTOE at 6 hours (p=0.016) and 9 hours (0.029). Beyond 18 hours, no differences were seen between the groups. NICOM was assessed in infants with HIE and compared with controls. Infants with mild HIE have a significantly higher heart rate at 6 hours of age compared with controls (p=0.034). Infants with moderate HIE undergoing TH have a significantly lower cardiac output compared with mild HIE (p=0.046) and control groups (p=0.040). Heart rate is significantly reduced (p<0.001) but stroke volume is maintained and gradually increases from 6-72 hours despite TH. Finally, we assessed the ability of EEG, NIRS and NICOM to predict short-term outcome (abnormal MRI +/- death in the first week of life). At 6 hours, none of the EEG, NIRS or NICOM measures predicted short-term outcome. At 12 hours of age, both qualitative and quantitative EEG features significantly predicted abnormal short-term outcome. Conclusion: Identification of infants at risk of brain injury immediately after birth is challenging. Objective, early biomarkers are required. This is the first study to combine EEG, NIRS and NICOM in infants with all grades of HIE. Multi-modal monitoring is feasible and this thesis provides novel insights into the underlying physiology and evolution of injury in infants with HIE. Furthermore, it reaffirms the importance of early continuous EEG in HIE.Item Inflammation driven molecular alterations in disorders of the perinatal brain(University College Cork, 2021-03) Casey, Sophie; Murray, Deirdre M.; O'Keeffe, Gerard W.; Boylan, Geraldine B.; Irish Research CouncilIntroduction: Inflammatory insults during the perinatal period are known to disrupt normal neurodevelopmental processes. Neonatal hypoxic ischemic encephalopathy (HIE) may occur with or without infection and is characterised by a significant immunoinflammatory response. Infection sensitises the neonatal brain to further hypoxic-ischemic injury. HIE with and without infection affects approximately 3 per thousand of all live births in the developed world. Despite the advent of therapeutic hypothermia (TH), almost half of affected neonates die or are left with lifelong disabilities or disorders. Autism Spectrum Disorder (ASD) is one such disorder and affects approximately 1.5% of the population in the developed world. Epidemiological and animal studies suggest that maternal immune dysregulation may contribute to the development of ASD. Rapid identification of neonates and infants at risk of HIE and ASD is vital, but many miss the critical therapeutic windows due to subjective and suboptimal diagnostic techniques. Circulating inflammation-associated markers such as microRNA (miRNA) and cytokines may hold the key to rapid diagnosis, providing an insight into maternal, foetal and neonatal injury cascades. Blood represents a non-invasive, and rapidly accessible medium in which to examine aberrant expression of these inflammation-driven molecular markers. In addition, miRNAs and cytokines are stably expressed in the blood, so may represent robust biomarker candidates. Furthermore, while many studies of miRNA expression have been performed in clinical cases of HIE, their functional role is still largely unknown. The primary hypothesis of this thesis is that examination of temporal inflammatory profiles may improve our understanding of the pathophysiology of early-life neuronal injury and subsequent development of long-term disabilities, and may provide novel biomarkers, therapeutic targets, or candidates capable of improving long-term outcomes. The current thesis aims to identify early molecular biomarkers of HIE and ASD in clinical and preclinical models and investigate the functional role of altered miRNAs in vitro. To investigate this, we aimed to examine temporal profiles of miRNA and cytokine alterations in a large animal model of HIE, with and without inflammatory sensitisation. Following this, we aimed to identify rapidly detectable miRNA and cytokine biomarkers of HIE, with and without inflammatory sensitisation. Lastly, we aimed to investigate the role of altered miRNA biomarkers through identification and examination of their functional targets, and to examine the mid-gestational cytokine profiles of mothers who give birth to offspring with ASD in a large clinical cohort. Methods: The current thesis utilised a large cohort of HIE neonates recruited to the Validation of Biomarkers in Hypoxic Ischemic Encephalopathy (BiHIVE) 1 & 2 studies (NCT02019147) and a clinically relevant large animal model of HIE with and without inflammation-sensitisation – the neonatal porcine model. To achieve a moderate-severe level of hypoxia-ischemia (HI) in piglets, inspired oxygen was reduced to 4% for approximately 30 minutes and titrated to achieve the desired level of neuronal injury. To achieve inflammation-sensitisation, piglets received an infusion of lipopolysaccharide (LPS) prior to HI. Blood was drawn from piglets at regular intervals for 48-72h following injury. Whole blood was used for analysis of miRNA content, while serum was preferable for analysis of cytokines. The multi-national Screening for Pregnancy Endpoints (SCOPE) cohort was utilised for the examination of circulating midgestational cytokine markers of ASD following diagnosis at neurodevelopmental follow-up. Cohorts from Cork, Ireland and Auckland, New Zealand were examined. Techniques employed throughout the current thesis are state-of-the-art, and were performed by both the PhD candidate and collaborating co-authors. Neurodevelopmental outcomes for neonatal study subjects were measured using Apgar/Sarnat staging, clinical signs (Chapter 3), early intervention services teams and child psychiatrists (Chapter 6). Outcomes for animal subjects were measured using clinical signs and Haemotoxylin & Eosin (H&E)/Terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL) staining of porcine brain tissues (Chapters 3 and 4). Further techniques featured in Chapter 3 include ribonucleic acid (RNA) Sequencing (RNA-Seq), Haemotoxylin & Eosin (H&E) staining of porcine brain tissues, magnetic resonance spectroscopy (MRS), RNA isolation from whole blood, complementary deoxyribonucleic acid (cDNA) synthesis, quantitative real-time polymerase chain reaction (qRT-PCR), in silico analysis, cell culture of SH-SY5Y cells and primary cultures of embryonic day (E) 14 rat midbrain, in vitro transfection of miRNA inhibitors, immunocytochemistry and fluorescent microscopy. Techniques used throughout the remainder of the thesis were performed solely by the PhD candidate. Techniques employed in Chapters 4 and 6 include electrochemiluminescent Mesoscale Discovery sandwich enzyme-linked immunosorbent (ELISA) immunoassays for analysis of serum cytokines. Finally, Chapter 5 used cell cultures of SH-SY5Y cells, in vitro transfection of miRNA inhibitors, green fluorescent protein (GFP) based reporter assays, immunocytochemistry, and fluorescent microscopy. All statistical analyses were conducted using IBM SPSS Statistics 24/26 and GraphPad Prism 7/8. Graphical representations of data were generated using GraphPad Prism 8. Results: miRNA Dysfunction in the Porcine Model of HIE Eleven candidate miRNAs were determined from a combination of results generated from microarray and RNA-Seq from a clinical cohort of hypoxic-ischemic neonates. These were then examined in the porcine model over 72h. Six miRNAs - miR-128, miR-148a, miR-151a, miR-181a, miR-181b and miR-374a, were upregulated in whole blood 1h after HI. Three - miR-374a, miR-181a and miR-181b, were specifically upregulated in moderate-severely injured piglets. miRNA levels at 1h correlated with histopathological and MRS-measured Lactate/Creatine (Lac/Cr) neuropathological outcomes. Inhibition of miR-181a in vitro resulted in increased neurite growth and increased expression of one member of the target bone morphogenetic protein (BMP) signalling pathway - BMPR2. Cytokine Dysfunction in the Porcine Model of Inflammation-Sensitised HIE Eight candidate cytokines were examined in serum samples from the inflammation-sensitised porcine model over 48h. Interleukin (IL) 6, tumor necrosis factor (TNF) α and Tau displayed a sustained inflammatory response following LPS exposure with and without hypoxia. Neuron-specific enolase (NSE) increased slowly following HI. LPS + Hypoxia-ischemia (LPS-HI) piglets displayed late increases in both NSE and C-reactive protein (CRP). TNFα and IL-6 allowed discrimination between animals who were exposed to inflammation-sensitised HI and those who were exposed to HI alone 6h following a moderate-severe HIE-like insult. miRNA Function In Vitro We previously identified the BMP signalling pathway as a predicted downstream target of miR-374a and miR-181a. The effect of miR-374a and miR-181a manipulation on the BMP-small mothers against decapentaplegic (SMAD) signalling pathway was investigated in vitro. miR-374a inhibition increased expression of BMP2 and BMPR2 but did not alter transcription of SMAD. Likewise, miR-181a inhibition was previously found to increase BMPR2 expression and did not alter SMAD transcription in vitro. Midgestational Cytokine Dysfunction in ASD Eight candidate cytokines were examined in serum samples retrieved at 15 and 20 weeks’ gestation in mothers of children affected by ASD. IL-17A concentrations were downregulated at 20 weeks’ gestation in mothers of children who progressed to develop ASD. IL-16, eotaxin, monocyte chemoattractant protein (MCP) 1, interferon (IFN) γ, IL-1β, IL-6 and IL-8 were unchanged in both groups at both 15 and 20 weeks. Conclusions: The current thesis has identified dysregulated expression of inflammation-driven molecular markers of the perinatal brain disorders HIE and ASD. Circulating levels of miRNAs (miR-128 miR-148a, miR-151a, miR-181a, miR-181b and miR-374a) and cytokines (IL-6, TNFα) were rapidly raised in response to HIE with and without inflammation-sensitisation in the porcine model. IL-17A was also dysregulated at 20 weeks’ gestation in mothers of ASD-affected children. These molecular markers may aid in rapid diagnosis, prognosis, and therapeutic decision-making for these time-sensitive disorders. Moreover, they may allow for discrimination of complex inflammation-sensitised HIE from classic HIE. Furthermore, evidence is beginning to suggest that HIE-associated miRNAs may play a functional role in the regulation of essential BMP-SMAD signalling. The current thesis puts forward novel information regarding the temporal profiles of these circulating molecular markers and begins to explore the functional roles of HIE-associated miRNAs. We hope this work will aid in the development of early blood-based biomarkers of disorders with an inflammatory milieu like HIE and ASD, and pave the way for more functional analysis of these markers.