INFANT Research Centre - Doctoral Theses
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Item Developing a patient-reported outcome measure (PROM) for postpartum care in Ireland(University College Cork, 2024) O'Byrne, Laura; Maher, Gillian; Khashan, Ali; Greene, Richard; Browne, John P.; McCarthy, Fergus; Health Research Board; National Perinatal Epidemiology CentreBackground and Aims: Patient-reported outcome measures (PROMs) are validated tools completed by patients to assess the impact of an intervention or therapy on them. In recent years, PROMs have gained attention for their patient-centred focus. However, there is no gold standard for assessing maternity care quality through PROM. The aim of this thesis was to examine the construction, feasibility, and validity of a comprehensive postnatal PROM, created as a combination of existing validated PROMs. This was achieved by systematically reviewing existing literature and conducting a range of analyses using recruited patient data from a postnatal population. Methods: This thesis includes an introductory chapter and a comprehensive methods section detailing the study designs, methodological choices, and statistical analyses. Chapters Three and Four present the systematic review and meta-analysis of existing postnatal PROMs. Chapter Five explores the feasibility of using a combination PROM based on the recommended findings from the systematic review. Chapters Six and Seven assess the content validity and construct validity of this approach. Chapter Eight discusses the overall findings, evaluates the strengths and limitations of the thesis, and offers recommendations for future studies. Results: The systematic review identified 10,324 records and 41 eligible studies evaluating 29 individual tools. Their psychometric properties were assessed according to the COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN). Twenty-one postnatal PROMs were recommended with 17 covering mental health, 4 addressing health-related quality of life, 4 focusing on breastfeeding and 3 on role transition. Gaps were found in postpartum urinary incontinence and pain with sexual intercourse coverage. The feasibility study assessed combining the identified psychometric tools with two bespoke sexual health inquiries to create a comprehensive postpartum PROM. Using the International Consortium for Health Outcomes Measurement (ICHOM) domains as a framework, the study tested the Postpartum Quality of Life (PQoL) and International Consultation on Incontinence Questionnaire–Urinary Incontinence Short Form (ICIQ-UI SF) questionnaires with additional sexual health questions on 86 women within the first week postpartum (T1), at 6 weeks after delivery (T2) and at 12 weeks post-partum (T3). High participation and favourable response rates were achieved: 69% (n=59) at T1, 67% (n=57) at T2, and 48% (n=41) at T3. There was high concordance between self-reported and clinician-reported delivery complications, providing a foundation for further validity studies. The content validity section examined the ability of the combination PROM in addressing ICHOM’s framework for postpartum care. 534 women agreed to participate, with observed response rates of 63% (n=334) at T1, 53% (n=283) at T2, and 45% (n=240) at T3. This analysis highlighted gaps in the coverage of mental health, early postpartum trauma related to childbirth, feeding challenges beyond breastfeeding, and evolving comprehensive physical health concerns throughout the postpartum period. The construct validity assessed how well the comprehensive PROM aligned with theoretical hypotheses regarding postpartum health. There were longitudinal changes in scores over time, with significant changes observed in PQoL and ICIQ-UI SF scores but not in pelvic pain scores. PQoL T1: 128 [±9.67], T2: 125 [±8.47], and T3: 126 [±8.51] p= 0.002. The ICIQ-UI SF had a median score and interquartile ranges of T1: 7.7 (IQR=6), T2: 9 (IQR=7), and T3: 9 (IQR=7), p = <0.001. No significant differences in scores were found between women with and without maternal morbidity, or across different morbidity types, neonatal unit admissions, or delivery types. Conclusion: This thesis evaluated the use of a comprehensive postpartum PROM, created as a combination of the best available instruments. The data suggests that current tools, including our comprehensive PROM, despite good psychometric properties, do not adequately cover postpartum health and wellbeing or discern between clinically distinct groups and outcomes.Item Evaluation of biomarkers for the diagnosis, management and follow-up of women with gestational trophoblastic disease(University College Cork, 2024) Joyce, Caroline Martha; O'Donoghue, Keelin; McCarthy, Tommie V.; Coulter, John; Irish Research CouncilGestational Trophoblastic Disease (GTD) describes a spectrum of disorders arising from the abnormal proliferation of trophoblastic tissue. Human chorionic gonadotrophin (hCG) is an excellent biomarker for most forms of this disease as its concentration accurately reflects trophoblastic activity. Hydatidiform mole (HM) or molar pregnancy is the most common form of GTD which may be suspected on ultrasound but requires pathological confirmation for diagnosis. Prognosis is generally excellent however close surveillance with hCG monitoring is imperative to detect cases progressing to malignant disease, referred to as gestational trophoblastic neoplasia (GTN). Clinical management and treatment of women with GTN in specialist centres achieves cure rates approaching 100%, emphasising the importance of accurate hCG monitoring for early detection of disease persistence to ensure optimal outcome. This thesis aims to evaluate pathological, genetic, and biochemical biomarkers used in the diagnosis, monitoring, and follow-up of women with GTD. In this thesis, a scoping review was performed to generate evidence and identify gaps in the GTD knowledge base to inform areas for future research. Key findings were the need to standardise hCG immunoassays for effective GTD surveillance, to improve diagnostic reporting pathways and to establish more accurate incidence rates. In order to identify patient priorities and inform initiatives to enhance the quality of care, a service evaluation was performed with women enrolled in the National GTD Registry invited to participate. Feedback revealed a knowledge gap regarding GTD amongst healthcare professionals outside GTD centres. This study also revealed shortcomings in psychological support and bereavement counselling offered to women after a molar pregnancy. To enhance the diagnostic accuracy of HM reporting, an in-situ hybridisation ploidy assay was developed with a customised scoring system to aid partial hydatidiform mole (PHM) diagnosis. This innovative technique provides a reliable adjunct to morphological assessment for PHM classification. The accuracy of this ploidy technique was confirmed by evaluation with molecular short tandem repeat genotyping. A national pathology questionnaire was performed to gather information on GTD diagnostic rates. Data collected was cross-referenced with cases documented in the National GTD Registry. This revealed a concerning under-enrolment of women with GTD (42%) onto the National GTD Registry by their clinicians. An audit of HM diagnostic rates over a 3-year period was performed following the Implementation of the new ploidy technique to aid diagnosis . This revealed a higher local PHM incidence rate (1 in 296 births) than reported nationally in the pathology audit (1 in 484 births). An electronic questionnaire was distributed to all European laboratories offering hCG for GTD management to gather insights on 5 key areas: hCG methodology, quality parameters, reporting and operational procedures, and use of hCG for non-GTD testing. This revealed considerable inter- and intra-laboratory variability in practice, emphasising the need to promote standardisation and harmonisation of immunoassays for GTD-derived hCG. A review of five challenging cases managed at the Irish GTD centre was conducted to evaluate the role of serum hCG and molecular genotyping in guiding management decisions, treatment strategies, and risk stratification for women with molar pregnancy, GTN and GTD mimics. These complex cases confirmed the pivotal role of serum hCG and molecular genotyping in monitoring disease persistence, prognostic stratification, and clinical management Novel strategies to measure hCG were pursued to address the lack of centralised hCG testing for GTD in Ireland. A proof-of-concept study for remote capillary blood collection was performed to evaluate the clinical efficacy and user acceptability of this method of collection for hCG monitoring in early pregnancy. The study confirmed the equivalence of capillary and venous blood hCG testing, demonstrated complete clinical concordance, thereby offering an alternative to venepuncture for hCG measurement. To explore the accessibility of hCG testing in the community, a point-of-care testing (POCT) device was evaluated for its suitability to triage women with pregnancy of unknown location (PUL) in the early pregnancy unit. The Abbott iSTAT®1 POCT instrument was chosen for this purpose and was clinically concordant with central laboratory hCG results facilitating the use of clinical decision thresholds for PUL. The research presented in this thesis provides valuable clinical insights through a series of nine research studies and has broadened the knowledge base in GTD. The findings offer an opportunity to positively impact diagnostic practices. The knowledge gap regarding GTD amongst healthcare professionals revealed in the patient survey points to a need for targeted educational initiatives in this area. Widespread integration of the HER2 ploidy technique to support morphology and standardise HM reporting could improve diagnostic accuracy, addressing a suspected underdiagnosis of PHM nationally and possibly internationally. It also suggests the need to re-evaluate incidence rates following the introduction of advanced diagnostic techniques such as ploidy assessment and molecular genotyping. This thesis identified an under-registration of women with GTD in Ireland supporting the need for initiatives such as mandatory registration or advocacy by professional organisations to increase registration rates. The inter and intra-laboratory variation in hCG immunoassays revealed in the European laboratory survey merits renewed harmonisation efforts through pilot external quality assurance and sample exchange programmes. The use of novel methods to enhance the accessibility of hCG monitoring for GTD in the community, through capillary blood collection or use of point-of-care analysis, warrants further study. The positive patient feedback indicated a preference for this approach, suggesting better compliance with serial test monitoring, a priority for GTD management.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.