Mechanisms Of Autism Spectrum Disorder Research Articles

Microstate Analyses to Study face Processing in Healthy Individuals and Psychiatric Disorders: A Review of ERP Findings.

Microstates represent brief periods of quasi-stable electroencephalography (EEG) scalp topography, offering insights into dynamic fluctuations in event-related potential (ERP) topographies. Despite this, there is a lack of a comprehensive systematic overview of microstate findings concerning cognitive face processing. This review aims to summarize ERP findings on face processing using microstate analyses and assess their effectiveness in characterizing face-related neural representations. A literature search was conducted for microstate ERP studies involving healthy individuals and psychiatric populations, utilizing PubMed, Google Scholar, Web of Science, PsychInfo, and Scopus databases. Twenty-two studies were identified, primarily focusing on healthy individuals (n = 16), with a smaller subset examining psychiatric populations (n = 6). The evidence reviewed in this study suggests that various microstates are consistently associated with distinct ERP stages involved in face processing, encompassing the processing of basic visual facial features to more complex functions such as analytical processing, facial recognition, and semantic representations. Furthermore, these studies shed light on atypical attentional neural mechanisms in Autism Spectrum Disorder (ASD), facial recognition deficits among emotional dysregulation disorders, and encoding and semantic dysfunctions in Post-Traumatic Stress Disorder (PTSD). In conclusion, this review underscores the practical utility of ERP microstate analyses in investigating face processing. Methodologies have evolved towards greater automation and data-driven approaches over time. Future research should aim to forecast clinical outcomes and conduct validation studies to directly demonstrate the efficacy of such analyses in inverse space.

Contrastive machine learning reveals in EEG resting-state network salient features specific to autism spectrum disorder

We explore the potential of the contrastive variational autoencoder to detect latent disorder-specific patterns in the network, analyzing functional brain networks in autistic individuals as the case. Autism spectrum disorder has long troubled medical practitioners, neurologists, and researchers. It is due to its extremely variable nature, both neurologically and behaviorally. Though machine learning has been in use to automate autism diagnosis, little has been done to delve into its intricacies. Here, we attempt to understand the neural mechanisms of autism spectrum disorder using contrastive variational autoencoder in conjunction with feature engineering. Our proposed methodology results in a physiologically interpretable classifier with a remarkable F1-score (up to 95%) and reveals a weak frontal lobe functional connectivity in the alpha band for children with autism spectrum disorder. Our study suggests an increased focus on efficient frontal lobe EEG sampling. Additionally, it highlights the importance of the proposed pipeline for understanding the underlying neural abnormalities in autism over the traditional machine learning pipeline. Thus, the obtained results have proven a contrastive variational autoencoder to be a promising approach for discovering latent patterns and features in complex networks.

The relative usefulness of the identification and analysis of biomarkers for the diagnosis of autism spectrum disorders in early childhood and the implementation of personalized precision medicine

Despite progress towards understanding the etiological mechanisms of autism spectrum disorder (ASD), efficient treatment strategy for the primary clinically presented autistic features remain elusive. Up to the heterogeneity and complex nature of ASD, clinical presentation differ in severity and usually accompanied with multiple comorbidities, including gastrointestinal (GI) problems, sleep disturbances, epilepsy, and attention deficit hyperactivity disorder (ADHD). Discovery of biomarkers of ASD is essential not only for clarifying the clinical features of this disorder but also as an primary diagnostic implement that could help to tailor early interventions. Therefore, this review describes the core areas of ASD biomarker research, including GABAergic/glutamatergic imbalance, mitochondrial dysfunction, hyperserotonemia, and impaired gut microbiota, all of which have demonstrated success in diagnosing ASD and could serve as targets for implementing personalized precision medicine. Additionally, this review includes accomplishment that focus on the importance of precision medicine and the current trials that make use of ASD biomarkers detection.

Morphological Correlates of Behavioral Variation in Autism Spectrum Disorder Groups in A Maternal Immune Activation Model.

Clinical heterogeneity is one of the biggest challenges for researchers studying underlying neurobiological mechanisms in Autism Spectrum Disorder (ASD). We aimed to use polyinosinic-polycytidylic acid [Poly (I:C)] induced maternal immune activation mice model to investigate the behavioral variation and the role of brain circuits related to symptom clusters in ASD. For this purpose, behavioral tests were applied to offsprings and regional thickness was measured from histological brain sections in medial prefrontal cortex, hippocampus and striatum. Pups of intraperitoneal Poly (I:C)-applied mothers (n: 14) and phosphate buffered saline-applied mothers (n: 6) were used for this study. We used three chamber socialization test and social memory test to evaluate social behavior deficit in mice. Marble burying test was used for assessing stereotypic behavior and new object recognition test for learning and cognitive flexibility. Three subgroups (n: 4 for each) were determined according to behavioral test parameters. Regional thickness was measured in medial prefrontal cortex, hippocampus and striatum and compared between subgroups. We detected that the behavioral differences were distributed in a spectrum as expected in the clinic and also detected increased hippocampus thickness in the stereotypic behavior dominant Poly (I:C) subgroup. Poly (I:C) induced maternal immune activation model creates the behavioral variation and cortical development differences that are seen in relation with symptom groups in ASD.

Deficiency of Cullin 3, a Protein Encoded by a Schizophrenia and Autism Risk Gene, Impairs Behaviors by Enhancing the Excitability of Ventral Tegmental Area (VTA) DA Neurons.

The dopaminergic neuromodulator system is fundamental to brain functions. Abnormal dopamine (DA) pathway is implicated in psychiatric disorders, including schizophrenia (SZ) and autism spectrum disorder (ASD). Mutations in Cullin 3 (CUL3), a core component of the Cullin-RING ubiquitin E3 ligase complex, have been associated with SZ and ASD. However, little is known about the function and mechanism of CUL3 in the DA system. Here, we show that CUL3 is critical for the function of DA neurons and DA-relevant behaviors in male mice. CUL3-deficient mice exhibited hyperactive locomotion, deficits in working memory and sensorimotor gating, and increased sensitivity to psychostimulants. In addition, enhanced DA signaling and elevated excitability of the VTA DA neurons were observed in CUL3-deficient animals. Behavioral impairments were attenuated by dopamine D2 receptor antagonist haloperidol and chemogenetic inhibition of DA neurons. Furthermore, we identified HCN2, a hyperpolarization-activated and cyclic nucleotide-gated channel, as a potential target of CUL3 in DA neurons. Our study indicates that CUL3 controls DA neuronal activity by maintaining ion channel homeostasis and provides insight into the role of CUL3 in the pathogenesis of psychiatric disorders.SIGNIFICANCE STATEMENT This study provides evidence that Cullin 3 (CUL3), a core component of the Cullin-RING ubiquitin E3 ligase complex that has been associated with autism spectrum disorder and schizophrenia, controls the excitability of dopamine (DA) neurons in mice. Its DA-specific heterozygous deficiency increased spontaneous locomotion, impaired working memory and sensorimotor gating, and elevated response to psychostimulants. We showed that CUL3 deficiency increased the excitability of VTA DA neurons, and inhibiting D2 receptor or DA neuronal activity attenuated behavioral deficits of CUL3-deficient mice. We found HCN2, a hyperpolarization-activated channel, as a target of CUL3 in DA neurons. Our findings reveal CUL3's role in DA neurons and offer insights into the pathogenic mechanisms of autism spectrum disorder and schizophrenia.

Generation of induced pluripotent stem cell lines from three individuals with autism spectrum disorder

Uncovering the molecular mechanisms of autism spectrum disorder (autism) necessitates development of relevant experimental models that are capable of recapitulating features of the clinical phenotype. Using non-integrative episomal vectors, peripheral blood mononuclear cells derived from three unrelated individuals diagnosed with autism were reprogrammed to induced pluripotent stem cells (iPSCs). The resultant lines exhibited the expected cellular morphology, karyotype, and evidence of pluripotency. These iPSCs constitute a valuable resource to support investigations of the underlying aetiology of autism.

Glutaminase 1 deficiency confined in forebrain neurons causes autism spectrum disorder-like behaviors

An abnormal glutamate signaling pathway has been proposed in the mechanisms of autism spectrum disorder (ASD). However, less is known about the involvement of alterations of glutaminase 1 (GLS1) in the pathophysiology of ASD. We show that the transcript level of GLS1 is significantly decreased in the postmortem frontal cortex and peripheral blood of ASD subjects. Mice lacking Gls1 in CamKIIα-positive neurons display a series of ASD-like behaviors, synaptic excitatory and inhibitory (E/I) imbalance, higher spine density, and glutamate receptor expression in the prefrontal cortex, as well as a compromised expression pattern of genes involved in synapse pruning and less engulfed synaptic puncta in microglia. A low dose of lipopolysaccharide treatment restores microglial synapse pruning, corrects synaptic neurotransmission, and rescues behavioral deficits in these mice. In summary, these findings provide mechanistic insights into Gls1 loss in ASD symptoms and identify Gls1 as a target for the treatment of ASD.

Increased risk of alopecia areata in patients with autism spectrum disorders: A Korean nationwide population-based study

To the Editor: Autism spectrum disorder (ASD) is a major neurobehavioral disorder in children. 1 Lord C. Elsabbagh M. Baird G. Veenstra-Vanderweele J. Autism spectrum disorder. Lancet. 2018; 392: 508-520 Abstract Full Text Full Text PDF PubMed Google Scholar Some studies have shown an association between ASD and immune-mediated 2 Hughes H.K. Mills Ko E. Rose D. et al. Immune dysfunction and autoimmunity as pathological mechanisms in autism spectrum disorders. Front Cell Neurosci. 2018; 12: 405 Crossref PubMed Scopus (116) Google Scholar and cutaneous diseases 3 Accordino R.E. Lucarelli J. Yan A.C. Cutaneous disease in autism spectrum disorder: a review. Pediatr Dermatol. 2015; 32: 455-460 Crossref PubMed Scopus (5) Google Scholar ; however, an association with alopecia areata (AA) has not yet been established. This study investigated whether patients with ASD have an increased risk of AA.

Cortical thickness abnormalities in autism spectrum disorder.

The pathological mechanism of autism spectrum disorder (ASD) remains unclear. Nowadays, surface-based morphometry (SBM) based on structural magnetic resonance imaging (sMRI) techniques have reported cortical thickness (CT) variations in ASD. However, the findings were inconsistent and heterogeneous. This current meta-analysis conducted a whole-brain vertex-wise coordinate-based meta-analysis (CBMA) on CT studies to explore the most noticeable and robust CT changes in ASD individuals by applying the seed-based d mapping (SDM) program. A total of 26 investigations comprised 27 datasets were included, containing 1,635 subjects with ASD and 1470 HC, along with 94 coordinates. Individuals with ASD exhibited significantly altered CT in several regions compared to HC, including four clusters with thicker CT in the right superior temporal gyrus (STG.R), the left middle temporal gyrus (MTG.L), the left anterior cingulate/paracingulate gyri, the right superior frontal gyrus (SFG.R, medial orbital parts), as well as three clusters with cortical thinning including the left parahippocampal gyrus (PHG.L), the right precentral gyrus (PCG.R) and the left middle frontal gyrus (MFG.L). Adults with ASD only demonstrated CT thinning in the right parahippocampal gyrus (PHG.R), revealed by subgroup meta-analyses. Meta-regression analyses found that CT in STG.R was positively correlated with age. Meanwhile, CT in MFG.L and PHG.L had negative correlations with the age of ASD individuals. These results suggested a complicated and atypical cortical development trajectory in ASD, and would provide a deeper understanding of the neural mechanism underlying the cortical morphology in ASD.

Aberrant causal inference and presence of a compensatory mechanism in autism spectrum disorder.

Autism spectrum disorder (ASD) is characterized by a panoply of social, communicative, and sensory anomalies. As such, a central goal of computational psychiatry is to ascribe the heterogenous phenotypes observed in ASD to a limited set of canonical computations that may have gone awry in the disorder. Here, we posit causal inference - the process of inferring a causal structure linking sensory signals to hidden world causes - as one such computation. We show that audio-visual integration is intact in ASD and in line with optimal models of cue combination, yet multisensory behavior is anomalous in ASD because this group operates under an internal model favoring integration (vs. segregation). Paradoxically, during explicit reports of common cause across spatial or temporal disparities, individuals with ASD were less and not more likely to report common cause, particularly at small cue disparities. Formal model fitting revealed differences in both the prior probability for common cause (p-common) and choice biases, which are dissociable in implicit but not explicit causal inference tasks. Together, this pattern of results suggests (i) different internal models in attributing world causes to sensory signals in ASD relative to neurotypical individuals given identical sensory cues, and (ii) the presence of an explicit compensatory mechanism in ASD, with these individuals putatively having learned to compensate for their bias to integrate in explicit reports.

A recurrent SHANK1 mutation implicated in autism spectrum disorder causes autistic-like core behaviors in mice via downregulation of mGluR1-IP3R1-calcium signaling

The genetic etiology and underlying mechanism of autism spectrum disorder (ASD) remain elusive. SHANK family genes (SHANK1/2/3) are well known ASD-related genes. However, little is known about how SHANK missense mutations contribute to ASD. Here, we aimed to clarify the molecular mechanism of and the multilevel neuropathological features induced by Shank1 mutations in knock-in (KI) mice. In this study, by sequencing the SHANK1 gene in a cohort of 615 ASD patients and 503 controls, we identified an ASD-specific recurrent missense mutation, c.2621 G > A (p.R874H). This mutation demonstrated strong pathogenic potential in in vitro experiments, and we generated the corresponding Shank1 R882H-KI mice. Shank1 R882H-KI mice displayed core symptoms of ASD, namely, social disability and repetitive behaviors, without confounding comorbidities of abnormal motor function and heightened anxiety. Brain structural changes in the frontal cortex, hippocampus and cerebellar cortex were observed in Shank1 R882H-KI mice via structural magnetic resonance imaging. These key brain regions also showed severe and consistent downregulation of mGluR1-IP3R1-calcium signaling, which subsequently affected the release of intracellular calcium. Corresponding cellular structural and functional changes were present in Shank1 R882H-KI mice, including decreased spine size, reduced spine density, abnormal morphology of postsynaptic densities, and impaired hippocampal long-term potentiation and basal excitatory transmission. These findings demonstrate the causative role of SHANK1 in ASD and elucidate the underlying biological mechanism of core symptoms of ASD. We also provide a reliable model of ASD with core symptoms for future studies, such as biomarker identification and therapeutic intervention studies.

Astrocytes derived from ASD individuals alter behavior and destabilize neuronal activity through aberrant Ca2+ signaling

The cellular mechanisms of autism spectrum disorder (ASD) are poorly understood. Cumulative evidence suggests that abnormal synapse function underlies many features of this disease. Astrocytes regulate several key neuronal processes, including the formation of synapses and the modulation of synaptic plasticity. Astrocyte abnormalities have also been identified in the postmortem brain tissue of ASD individuals. However, it remains unclear whether astrocyte pathology plays a mechanistic role in ASD, as opposed to a compensatory response. To address this, we combined stem cell culturing with transplantation techniques to determine disease-specific properties inherent to ASD astrocytes. We demonstrate that ASD astrocytes induce repetitive behavior as well as impair memory and long-term potentiation when transplanted into the healthy mouse brain. These in vivo phenotypes were accompanied by reduced neuronal network activity and spine density caused by ASD astrocytes in hippocampal neurons in vitro. Transplanted ASD astrocytes also exhibit exaggerated Ca2+ fluctuations in chimeric brains. Genetic modulation of evoked Ca2+ responses in ASD astrocytes modulates behavior and neuronal activity deficits. Thus, this study determines that astrocytes derived from ASD iPSCs are sufficient to induce repetitive behavior as well as cognitive deficit, suggesting a previously unrecognized primary role for astrocytes in ASD.

DSCAM Deficiency Leads to Premature Spine Maturation and Autism-like Behaviors.

Mutations in some cell adhesion molecules (CAMs) cause abnormal synapse formation and maturation, and serve as one of the potential mechanisms of autism spectrum disorders (ASDs). Recently, DSCAM (Down syndrome cell adhesion molecule) was found to be a high-risk gene for autism. However, it is still unclear how DSCAM contributes to ASD. Here, we show that DSCAM expression was downregulated following synapse maturation, and that DSCAM deficiency caused accelerated dendritic spine maturation during early postnatal development. Mechanistically, the extracellular domain of DSCAM interacts with neuroligin1 (NLGN1) to block the NLGN1-neurexin1β (NRXN1β) interaction. DSCAM extracellular domain was able to rescue spine overmaturation in DSCAM knockdown neurons. Precocious spines in DSCAM-deficient mice showed increased glutamatergic transmission in the developing cortex and induced autism-like behaviors, such as social novelty deficits and repetitive behaviors. Thus, DSCAM might be a repressor that prevents premature spine maturation and excessive glutamatergic transmission, and its deficiency could lead to autism-like behaviors. Our study provides new insight into the potential pathophysiological mechanisms of ASDs.SIGNIFICANCE STATEMENT DSCAM is not only associated with Down syndrome but is also a strong autism risk gene based on large-scale sequencing analysis. However, it remains unknown exactly how DSCAM contributes to autism. In mice, either neuron- and astrocyte-specific or pyramidal neuron-specific DSCAM deficiencies resulted in autism-like behaviors and enhanced spatial memory. In addition, DSCAM knockout or knockdown in pyramidal neurons led to increased dendritic spine maturation. Mechanistically, the extracellular domain of DSCAM binds to NLGN1 and inhibits NLGN1-NRXN1β interaction, which can rescue abnormal spine maturation induced by DSCAM deficiency. Our research demonstrates that DSCAM negatively modulates spine maturation, and that DSCAM deficiency leads to excessive spine maturation and autism-like behaviors, thus providing new insight into a potential pathophysiological mechanism of autism.

Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder.

Autism spectrum disorder has long been conceptualized as a disorder of "atypical development of functional brain connectivity (which refers to correlations in activity levels of distant brain regions)." However, most of the research has focused on the connectivity between cortical regions, and much remains unknown about the developmental changes of functional connectivity between subcortical and cortical areas in autism spectrum disorder. We used the technique of resting-state functional magnetic resonance imaging to explore the developmental characteristics of intrinsic functional connectivity (functional brain connectivity when people are asked not to do anything) between subcortical and cortical regions in individuals with and without autism spectrum disorder aged 6-30 years. We focused on one important subcortical structure called striatum, which has roles in motor, cognitive, and affective processes. We found that cortico-striatal intrinsic functional connectivities showed opposite developmental trajectories in autism spectrum disorder and typically developing individuals, with connectivity increasing with age in autism spectrum disorder and decreasing or constant in typically developing individuals. We also found significant negative behavioral correlations between those atypical cortico-striatal intrinsic functional connectivities and autistic symptoms, such as social-communication deficits, and restricted/repetitive behaviors and interests. Taken together, this work highlights that the atypical development of cortico-subcortical functional connectivity might be largely involved in the neuropathological mechanisms of autism spectrum disorder.

Altered complexity in resting-state fNIRS signal in autism: a multiscale entropy approach

Objective. Feature extraction and recognition in brain signal processing is of great significance for understanding the neurological mechanism of autism spectrum disorder (ASD). Resting-state (RS) functional near-infrared spectroscopy measurement provides a way to investigate the possible alteration in ASD-related complexity of resting-state (RS) functional near-infrared spectroscopy (fNIRS) signals and to explore the relationship between brain functional connectivity and complexity. Approach. Using the multiscale entropy (MSE) of fNIRS signals recorded from the bilateral temporal lobes (TLs) on 25 children with ASD and 22 typical development (TD) children, the pattern of brain complexity was assessed for both the ASD and TD groups. Main results. The quantitative analysis of MSE revealed the increased complexity in RS-fNIRS in children with ASD, particularly in the left temporal lobe. The complexity in the RS signal and resting state functional connectivity (RSFC) were also observed to exhibit negative correlation in the medium magnitude. Significance. These results indicated that the MSE might serve as a novel measure for RS-fNIRS signals in characterizing and understanding ASD.

Screening methods for autism spectrum disorders in the study of neuropsychological development of preschool children

Aim. To assess the effectiveness of screening methods for diagnosing autism spectrum disorders available to the pediatric service; to prove in practice impossibilities to identify signs of autism spectrum disorders by using the existed pediatric methods.
 Methods. The neuropsychological development of 187 preschool children (56 years old) was investigated. The neurological status, anxiety according to A.M. Parishioners, level of intelligence using Raven's Progressive Matrices, the presence of hyperactivity according to the method of V.R. Kuchma, mental performance according to V.Ya. Anfimov, screening diagnostics of autism spectrum disorders were studied.
 Results. Assessment of the neurological status showed an increase in tendon reflexes in 10.22.2% of children, a decrease in 12.32.4%. The study of the intelligence levels in the Ravenna test showed that the average intelligence level was in 47.13.7% of the studied children, the intelligence was below the average in 52.93.7% of children. Screening diagnostics of autism spectrum disorders did not reveal abnormalities, however, 5.31.6% of children had signs of predisposition to the autism spectrum disorder (decreased adaptation to changes, nervousness and fears, verbal and non-verbal communication, level of activity and consistency of intellectual response). The indicator of the productivity of mental performance of preschool children was 5.40.5. Attention deficit was detected in 5.91.7% of children (according to the parent's questionnaire) and 8.62.0% children (according to the teachers' questionnaire). The level of anxiety was 9.60.3 points.
 Conclusion. The currently known screening methods for detecting autism spectrum disorders, available to the pediatric service, in our opinion, are uninformative; the search for the most sensitive markers of autism should be based on an understanding of the epigenetic mechanisms of autism spectrum disorders.

The relationships between the topological properties of the whole-brain white matter network and the severity of autism spectrum disorder: A study from monozygotic twins

Twins provide a valuable perspective for exploring the pathological mechanism of autism spectrum disorder (ASD). We aim to analyze differences in the topological properties of the white matter (WM) network between monozygotic twins with ASD (MZCo-ASD) and children with typical development (TD). We enrolled 67 subjects aged 2–9 years. Twenty-three pairs of MZCo-ASD and 21 singleton children with TD completed clinical assessments and diffusion tensor imaging (DTI). Graph theory was used to compare the topological properties of the WM network between the two groups, and analyzed their correlations with the severity of clinical symptoms. We found that the global efficiency (Eg) of MZCo-ASD is weaker than that of TD children, while the shortest path length (Lp) of MZCo-ASD is longer than that of TD children, and MZCo-ASD have three unique hubs (the bilateral dorsolateral superior frontal gyrus and right insula). Eg and Lp were both correlated with the repetitive behavior scores of the Autism Diagnostic Interview-Revised (ADI-R) in the MZCo-ASD group, and the nodal efficiency of the dorsal superior frontal gyrus (SFGdor) was correlated with the ADI-R scores of repetitive behaviors. Left SFGdor nodal efficiency was correlated with Repetitive Behavior and Communication, two core symptoms of autism. The results implicated that MZCo-ASD had atypical brain structural network attributes and node distributions. Using MZCo-ASD, we found that the WM topological properties that correlate with the severity of ASD core symptoms were Eg, Lp, and the nodal efficiency of the SFGdor.

Molecular Mechanisms of Aberrant Neuroplasticity in Autism Spectrum Disorders (Review).

This review presents the analysis and systematization of modern data on the molecular mechanisms of autism spectrum disorders (ASD) development. Polyetiology and the multifactorial nature of ASD have been proved. The attempt has been made to jointly review and systematize current hypotheses of ASD pathogenesis at the molecular level from the standpoint of aberrant brain plasticity. The mechanism of glutamate excitotoxicity formation, the effect of imbalance of neuroactive amino acids and their derivatives, neurotransmitters, and hormones on the ASD formation have been considered in detail. The strengths and weaknesses of the proposed hypotheses have been analyzed from the standpoint of evidence-based medicine. The conclusion has been drawn on the leading role of glutamate excitotoxicity as a biochemical mechanism of aberrant neuroplasticity accompanied by oxidative stress and mitochondrial dysfunction. The mechanism of aberrant neuroplasticity has also been traced at the critical moments of the nervous system development taking into account the influence of various factors of the internal and external environment. New approaches to searching for ASD molecular markers have been considered.

Mechanism of Autism Spectrum Disorder and The Involvement of microRNA

Autism Spectrum Disorder or ASD refers to a broad range of neurodevelopmental disorder characterised by persistent deficits in social abilities, repetitive behavioural pattern and restricted interest propensity that usually developed throughout childhood. It is referred as spectrum disorder due to its wide variation of subsets that includes several conditions. Autism is referred as spectrum of disorders with wide range of subtypes due to its aetiologically diverse nature. Even each person with ASD within the same subsets may experience a distinct set of strengths and challenges in terms of learning, thoughts and problem-solving ranging from highly skilled to being severely affected. The genesis of it is incompletely comprehensible despite numerous studies have been done to elucidate the pathogenic mechanisms beneath this whole range of impaired neurodevelopmental condition. In this review, literature search was performed with primary focus was given to known mechanism of ASD and specific involvement of microRNA. Given the complexity of ASD with diversity of clinical manifestations, it can be considered as multifactorial aetiopathogenesis disorder that is associated with diverse genetic factors that may also be predisposed by environmental exposures and prenatal factors. Environmental risk factor that may modulate the genetic factors predisposing towards ASD includes advanced parental age, prenatal and perinatal factors, medications and toxic materials exposure. This is supported by epigenetic theory which in other words, the environmental risk factors may increase the tendency for the abnormal genes to be expressed at much earlier stage without changing the primary DNA sequence. Meanwhile, spontaneous de novo mutation and neurobiological factors have been proposed to be the factors contributing to ASD. Currently, there are a lot of studies pivoting on identifying the microRNA involved in dysregulation of gene expression in autistic individuals by microRNA expression profiling. These approaches were able to elucidate the specific microRNAs that involves in regulating gene expression at post-transcriptional level. Subsequent pathway analysis had enabled the understanding of potential mechanisms that lead to ASD. As ASD is a heterogenous disorder in nature, the quest to reveal its definite mechanism is challenging. Genetic, neurobiological and environmental factors were regarded as its main causes. A growing number of reports have supported the involvement of microRNA in the mechanism of ASD. Detection of microRNA in extracellular fluids such as serum, saliva and plasma are the key to identify pathways and processes involved in ASD pathophysiology. Further preclinical validation of these microRNAs target transcripts may be beneficial to support its clinical application. Validated microRNAs may potentially use as non-invasive biomarker in early detection and later on opening up opportunities for future potential therapies for ASD.

Mechanism of Autism Spectrum Disorder and The Involvement of microRNA

Autism Spectrum Disorder or ASD refers to a broad range of neurodevelopmental disorder characterised by persistent deficits in social abilities, repetitive behavioural pattern and restricted interest propensity that usually developed throughout childhood. It is referred as spectrum disorder due to its wide variation of subsets that includes several conditions. Autism is referred as spectrum of disorders with wide range of subtypes due to its aetiologically diverse nature. Even each person with ASD within the same subsets may experience a distinct set of strengths and challenges in terms of learning, thoughts and problem-solving ranging from highly skilled to being severely affected. The genesis of it is incompletely comprehensible despite numerous studies have been done to elucidate the pathogenic mechanisms beneath this whole range of impaired neurodevelopmental condition. In this review, literature search was performed with primary focus was given to known mechanism of ASD and specific involvement of microRNA. Given the complexity of ASD with diversity of clinical manifestations, it can be considered as multifactorial aetiopathogenesis disorder that is associated with diverse genetic factors that may also be predisposed by environmental exposures and prenatal factors. Environmental risk factor that may modulate the genetic factors predisposing towards ASD includes advanced parental age, prenatal and perinatal factors, medications and toxic materials exposure. This is supported by epigenetic theory which in other words, the environmental risk factors may increase the tendency for the abnormal genes to be expressed at much earlier stage without changing the primary DNA sequence. Meanwhile, spontaneous de novo mutation and neurobiological factors have been proposed to be the factors contributing to ASD. Currently, there are a lot of studies pivoting on identifying the microRNA involved in dysregulation of gene expression in autistic individuals by microRNA expression profiling. These approaches were able to elucidate the specific microRNAs that involves in regulating gene expression at post-transcriptional level. Subsequent pathway analysis had enabled the understanding of potential mechanisms that lead to ASD. As ASD is a heterogenous disorder in nature, the quest to reveal its definite mechanism is challenging. Genetic, neurobiological and environmental factors were regarded as its main causes. A growing number of reports have supported the involvement of microRNA in the mechanism of ASD. Detection of microRNA in extracellular fluids such as serum, saliva and plasma are the key to identify pathways and processes involved in ASD pathophysiology. Further preclinical validation of these microRNAs target transcripts may be beneficial to support its clinical application. Validated microRNAs may potentially use as non-invasive biomarker in early detection and later on opening up opportunities for future potential therapies for ASD.