PiRAMiD: predicting early onset autism through maternal immune activation and proteomic discovery

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Carter, Michael
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University College Cork
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Autism 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.
ASD , Autism , Developmental disorders , Early intervention , Emotional and behavioural problems , Maternal immune activation , Cytokine , Proteomics , Machine learning , Metabolomics
Carter, M. J. 2023. PiRAMiD: predicting early onset autism through maternal immune activation and proteomic discovery. PhD Thesis, University College Cork.
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