Structural, Functional, and Molecular Imaging of Autism Spectrum Disorder

Leveraging AI for the diagnosis and treatment of autism spectrum disorder: Current trends and future prospects

The integration of artificial intelligence (AI) into the diagnosis and treatment of autism spectrum disorder (ASD) represents a promising frontier in healthcare. This review explores the current landscape and future prospects of AI technologies in ASD diagnostics and interventions. AI enables early detection and personalized assessment of ASD through the analysis of diverse data sources such as behavioural patterns, neuroimaging, genetics, and electronic health records. Machine learning algorithms exhibit high accuracy in distinguishing ASD from neurotypical development and other developmental disorders, facilitating timely interventions. Furthermore, AI-driven therapeutic interventions, including augmentative communication systems, virtual reality-based training, and robot-assisted therapies, show potential in improving social interactions and communication skills in individuals with ASD. Despite challenges such as data privacy and interpretability, the future of AI in ASD holds promise for refining diagnostic accuracy, deploying telehealth platforms, and tailoring treatment plans. By harnessing AI, clinicians can enhance ASD care delivery, empower patients, and advance our understanding of this complex condition.

Individual cerebellar metabolic connectome in patients with MTLE and NTLE associated with surgical prognosis

PURPOSE

This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes.

METHODS

This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients.

RESULTS

Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis.

CONCLUSION

The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.

Disrupted Human-Dog Interbrain Neural Coupling in Autism-Associated Shank3 Mutant Dogs

Dogs interact with humans effectively and intimately. However, the neural underpinnings for such interspecies social communication are not understood. It is known that interbrain activity coupling, i.e., the synchronization of neural activity between individuals, represents the neural basis of social interactions. Here, previously unknown cross-species interbrain activity coupling in interacting human-dog dyads is reported. By analyzing electroencephalography signals from both dogs and humans, it is found that mutual gaze and petting induce interbrain synchronization in the frontal and parietal regions of the human-dog dyads, respectively. The strength of the synchronization increases with growing familiarity of the human-dog dyad over five days, and the information flow analysis suggests that the human is the leader while the dog is the follower during human-dog interactions. Furthermore, dogs with Shank3 mutations, which represent a promising complementary animal model of autism spectrum disorders (ASD), show a loss of interbrain coupling and reduced attention during human-dog interactions. Such abnormalities are rescued by the psychedelic lysergic acid diethylamide (LSD). The results reveal previously unknown interbrain synchronizations within an interacting human-dog dyad which may underlie the interspecies communication, and suggest a potential of LSD for the amelioration of social impairment in patients with ASD.

The Medial Prefrontal Cortex-Basolateral Amygdala Circuit Mediates Anxiety in Shank3 InsG3680 Knock-in Mice

Anxiety disorder is a major symptom of autism spectrum disorder (ASD) with a comorbidity rate of ~40%. However, the neural mechanisms of the emergence of anxiety in ASD remain unclear. In our study, we found that hyperactivity of basolateral amygdala (BLA) pyramidal neurons (PNs) in Shank3 InsG3680 knock-in (InsG3680+/+) mice is involved in the development of anxiety. Electrophysiological results also showed increased excitatory input and decreased inhibitory input in BLA PNs. Chemogenetic inhibition of the excitability of PNs in the BLA rescued the anxiety phenotype of InsG3680+/+ mice. Further study found that the diminished control of the BLA by medial prefrontal cortex (mPFC) and optogenetic activation of the mPFC-BLA pathway also had a rescue effect, which increased the feedforward inhibition of the BLA. Taken together, our results suggest that hyperactivity of the BLA and alteration of the mPFC-BLA circuitry are involved in anxiety in InsG3680+/+ mice.

Gender and age related brain structural and functional alterations in children with autism spectrum disorder

To explore the effects of age and gender on the brain in children with autism spectrum disorder using magnetic resonance imaging. 185 patients with autism spectrum disorder and 110 typically developing children were enrolled. In terms of gender, boys with autism spectrum disorder had increased gray matter volumes in the insula and superior frontal gyrus and decreased gray matter volumes in the inferior frontal gyrus and thalamus. The brain regions with functional alterations are mainly distributed in the cerebellum, anterior cingulate gyrus, postcentral gyrus, and putamen. Girls with autism spectrum disorder only had increased gray matter volumes in the right cuneus and showed higher amplitude of low-frequency fluctuation in the paracentral lobule, higher regional homogeneity and degree centrality in the calcarine fissure, and greater right frontoparietal network-default mode network connectivity. In terms of age, preschool-aged children with autism spectrum disorder exhibited hypo-connectivity between and within auditory network, somatomotor network, and visual network. School-aged children with autism spectrum disorder showed increased gray matter volumes in the rectus gyrus, superior temporal gyrus, insula, and suboccipital gyrus, as well as increased amplitude of low-frequency fluctuation and regional homogeneity in the calcarine fissure and precentral gyrus and decreased in the cerebellum and anterior cingulate gyrus. The hyper-connectivity between somatomotor network and left frontoparietal network and within visual network was found. It is essential to consider the impact of age and gender on the neurophysiological alterations in autism spectrum disorder children when analyzing changes in brain structure and function.

Stem Cell Secretions as a Potential Therapeutic Agent for Autism Spectrum Disorder: A Narrative Review

Autism spectrum disorder (ASD) is a neurodevelopmental illness characterized by impaired social interaction and restricted repetitive behaviors or interests. The rising prevalence of ASD diagnosis has triggered a surge in research into investigating the underlying neuropathological processes and finding new therapeutic approaches. ASD is characterized by neuroinflammation and dysregulation of neuro-immune cross-talk, which suggests that stem cell treatment might be a potential therapeutic approach. The beneficial and restorative effects of stem cells are mainly due to their paracrine activity, in which stem cells generate and release extracellular vesicles such as exosomes and distinct secreted non-vesicle soluble proteins, including, growth factors, chemokines, cytokines, and immunomodulatory molecules referred to as the Secretome. In this paper, we reviewed the existing research exploring the therapeutic potential of stem cell secretome focusing on their role in addressing ASD pathology. Furthermore, we proposed a comprehensive mechanism of action for stem cell secretions, encompassing the broader secretome as well as the specific contribution of exosomes, in alleviating ASD neuropathology. Across the reviewed studies, exosomes and secreted soluble factors of the transplanted stem cell demonstrate a potential efficacy in ameliorating autistic-like behaviors. The proposed mechanism of action involves the modulation of signaling pathways implicated in neuroinflammation, angiogenesis, cellular apoptosis, and immunomodulation.

SMART (Splitting-Merging Assisted Reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks

Functional networks (FNs) hold significant promise in understanding brain function. Independent component analysis (ICA) has been applied in estimating FNs from functional magnetic resonance imaging (fMRI). However, determining an optimal model order for ICA remains challenging, leading to criticism about the reliability of FN estimation. Here, we propose a SMART (splitting-merging assisted reliable) ICA method that automatically extracts reliable FNs by clustering independent components (ICs) obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model orders. We extend SMART ICA to multi-subject fMRI analysis, validating its effectiveness using simulated and real fMRI data. Based on simulated data, the method accurately estimates both group-common and group-unique components and demonstrates robustness to parameters. Using two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects, the resulting reliable group-level FNs are greatly similar between the two cohorts, and interestingly the subject-specific FNs show progressive changes while age increases. Furthermore, both small-scale and large-scale brain FN templates are provided as benchmarks for future studies. Taken together, SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data, while also providing linkages between different FNs.

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Dysfunction of brain resting-state functional networks has been widely reported in psychiatric disorders. However, the causal relationships between brain resting-state functional networks and psychiatric disorders remain largely unclear. Here we perform bidirectional two-sample Mendelian randomization (MR) analyses to investigate the causalities between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 12 psychiatric disorders (n = 14,307 to 698,672 individuals). Forward MR identified 8 rsfMRI phenotypes causally associated with the risk of psychiatric disorders. For example, the increase in the connectivity of motor, subcortical-cerebellum and limbic network was associated with lower risk of autism spectrum disorder. In adddition, increased connectivity in the default mode and central executive network was associated with lower risk of post-traumatic stress disorder and depression. Reverse MR analysis revealed significant associations between 4 psychiatric disorders and 6 rsfMRI phenotypes. For instance, the risk of attention-deficit/hyperactivity disorder increases the connectivity of the attention, salience, motor and subcortical-cerebellum network. The risk of schizophrenia mainly increases the connectivity of the default mode and central executive network and decreases the connectivity of the attention network. In summary, our findings reveal causal relationships between brain functional networks and psychiatric disorders, providing important interventional and therapeutic targets for psychiatric disorders at the brain functional network level.

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

Introduction

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.

Methods

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.

Results

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.

Conclusion

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.

Quantitative Expression of Latent Disease Factors in Individuals Associated with Psychopathology Dimensions and Treatment Response

Psychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = -0.26-0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18-0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.

Seeing beyond words: Visualizing autism spectrum disorder biomarker insights

Objective

This study employs bibliometric and visual analysis to elucidate global research trends in Autism Spectrum Disorder (ASD) biomarkers, identify critical research focal points, and discuss the potential integration of diverse biomarker modalities for precise ASD assessment.

Methods

A comprehensive bibliometric analysis was conducted using data from the Web of Science Core Collection database until December 31, 2022. Visualization tools, including R, VOSviewer, CiteSpace, and gCLUTO, were utilized to examine collaborative networks, co-citation patterns, and keyword associations among countries, institutions, authors, journals, documents, and keywords.

Results

ASD biomarker research emerged in 2004, accumulating a corpus of 4348 documents by December 31, 2022. The United States, with 1574 publications and an H-index of 213, emerged as the most prolific and influential country. The University of California, Davis, contributed significantly with 346 publications and an H-index of 69, making it the leading institution. Concerning journals, the Journal of Autism and Developmental Disorders, Autism Research, and PLOS ONE were the top three publishers of ASD biomarker-related articles among a total of 1140 academic journals. Co-citation and keyword analyses revealed research hotspots in genetics, imaging, oxidative stress, neuroinflammation, gut microbiota, and eye tracking. Emerging topics included "DNA methylation," "eye tracking," "metabolomics," and "resting-state fMRI."

Conclusion

The field of ASD biomarker research is dynamically evolving. Future endeavors should prioritize individual stratification, methodological standardization, the harmonious integration of biomarker modalities, and longitudinal studies to advance the precision of ASD diagnosis and treatment.

Photoacoustic viscoelasticity assessment of prefrontal cortex and cerebellum in normal and prenatal valproic acid-exposed rats

Mechanical properties of brain tissues are from principal features from different points of view; diagnosis, the performance of the brain and neurological disorders. Particularly viscoelastic properties of the brain tissues are determinative. In this study based on a proposed accurate and non-invasive method, we have measured the viscoelastic properties of prefrontal cortex and cerebellum, two important brain regions involved in motor learning and pathophysiology of autism spectrum disorder (ASD). In this regard, using photoacoustic systems, viscoelastic properties of tissues from the cerebellum and prefrontal cortex of normal and prenatal VPA (Valproic acid)-exposed (i.e. autistic-like) offspring rats are measured. Results of our study show that the cerebellums of normal tissues are stiffer than the tissue obtained from autistic-like rats, while the viscoelasticity of the prefrontal cortex of normal tissues is higher than that of autistic ones. The proposed method for the measurement of viscoelastic properties of the brain tissue has the potential not only for the fundamental studies but as a diagnosis technique.

Developmental Impairments of Synaptic Refinement in the Thalamus of a Mouse Model of Fragile X Syndrome

While somatosensory over-reactivity is a common feature of autism spectrum disorders such as fragile X syndrome (FXS), the thalamic mechanisms underlying this remain unclear. Here, we found that the developmental elimination of synapses formed between the principal nucleus of V (PrV) and the ventral posterior medial nucleus (VPm) of the somatosensory system was delayed in fragile X mental retardation 1 gene knockout (Fmr1 KO) mice, while the developmental strengthening of these synapses was disrupted. Immunohistochemistry showed excessive VGluT2 puncta in mutants at P12-13, but not at P7-8 or P15-16, confirming a delay in somatic pruning of PrV-VPm synapses. Impaired synaptic function was associated with a reduction in the frequency of quantal AMPA events, as well as developmental deficits in presynaptic vesicle size and density. Our results uncovered the developmental impairment of thalamic relay synapses in Fmr1 KO mice and suggest that a thalamic contribution to the somatosensory over-reactivity in FXS should be considered.

Etiologic Evaluation of Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is clinically and etiologically heterogeneous. A causal genetic variant can be identified in approximately 20% to 25% of affected individuals with current clinical genetic testing, and all patients with an ASD diagnosis should be offered genetic etiologic evaluation. We suggest that exome sequencing with copy number variant coverage should be the first-line etiologic evaluation for ASD. Neuroimaging, neurophysiologic, metabolic, and other biochemical evaluations can provide insight into the pathophysiology of ASD but should be recommended in the appropriate clinical circumstances.

The Impact of Microglia on Neurodevelopment and Brain Function in Autism

Microglia, as one of the main types of glial cells in the central nervous system (CNS), are widely distributed throughout the brain and spinal cord. The normal number and function of microglia are very important for maintaining homeostasis in the CNS. In recent years, scientists have paid widespread attention to the role of microglia in the CNS. Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder, and patients with ASD have severe deficits in behavior, social skills, and communication. Most previous studies on ASD have focused on neuronal pathological changes, such as increased cell proliferation, accelerated neuronal differentiation, impaired synaptic development, and reduced neuronal spontaneous and synchronous activity. Currently, more and more research has found that microglia, as immune cells, can promote neurogenesis and synaptic pruning to maintain CNS homeostasis. They can usually reduce unnecessary synaptic connections early in life. Some researchers have proposed that many pathological phenotypes of ASD may be caused by microglial abnormalities. Based on this, we summarize recent research on microglia in ASD, focusing on the function of microglia and neurodevelopmental abnormalities. We aim to clarify the essential factors influenced by microglia in ASD and explore the possibility of microglia-related pathways as potential research targets for ASD.

Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents

Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.

Reduction in Retinal Ganglion Cell Layer, Inner Plexiform Layer, and Choroidal Thickness in Children With Autism Spectrum Disorder

PURPOSES

The aim of this study was to evaluate the retinal nerve fiber layer (RNFL), choroidal layer, inner plexiform layer (IPL), and ganglion cell layer (GCL) in patients with autism spectrum disorder (ASD).

METHODS

In this study, we measured the thickness of the RNFL, GCL, IPL, and choroidal thickness using a spectral optical coherence tomography (OCT) device and we compared the results between the children diagnosed with ASD and healthy controls. Correlation between the Childhood Autism Rating Scale (CARS) and the OCT data was evaluated.

RESULTS

Both ASD and control group consisted of 40 subjects (30 males and 10 females). Of the children in the ASD group, 29 had normal intelligence and 11 had mild intellectual disability (MID). The mean age of patients in the ASD group and control groups were 9.77 ± 3.37 years and 9.85 ± 3.97 years (p = 0.928). There was a statistically significant difference between the ASD group and the control group in the nasal and nasal-superior sectors of the RNFL layers in the left eye when all the lower layers of RNFL were assessed. In both eyes, the children with ASD had considerably lower mean choroidal thicknesses than the controls. When compared to the controls, the GCL and IPL volumes in the individuals with ASD were considerably lower in both eyes. Compared to the MID group, the left GCL volume of the nasal-inferior group was noticeably higher. A significant correlation was found between CARS scores and left GCL left IPL.

CONCLUSIONS

In contrast to RNFL in the ASD group, significant reductions in IPL, GCL, and choroidal thickness were observed in both eyes. It is thought that GCL may be a much more important biomarker than RNFL in terms of representing the structural deterioration in the brain. In addition, these results may form the basis for a new perspective on the use of OCT for the diagnosis and clinical course of autism.

Genetic Ablation of GIGYF1, Associated With Autism, Causes Behavioral and Neurodevelopmental Defects in Zebrafish and Mice

BACKGROUND

Autism spectrum disorder is characterized by deficits in social communication and restricted or repetitive behaviors. Due to the extremely high genetic and phenotypic heterogeneity, it is critical to pinpoint the genetic factors for understanding the pathology of these disorders.

METHODS

We analyzed the exomes generated by the SPARK (Simons Powering Autism Research) project and performed a meta-analysis with previous data. We then generated 1 zebrafish knockout model and 3 mouse knockout models to examine the function of GIGYF1 in neurodevelopment and behavior. Finally, we performed whole tissue and single-nucleus transcriptome analysis to explore the molecular and cellular function of GIGYF1.

RESULTS

GIGYF1 variants are significantly associated with various neurodevelopmental disorder phenotypes, including autism, global developmental delay, intellectual disability, and sleep disturbance. Loss of GIGYF1 causes similar behavioral effects in zebrafish and mice, including elevated levels of anxiety and reduced social engagement, which is reminiscent of the behavioral deficits in human patients carrying GIGYF1 variants. Moreover, excitatory neuron-specific Gigyf1 knockout mice recapitulate the increased repetitive behaviors and impaired social memory, suggesting a crucial role of Gigyf1 in excitatory neurons, which correlates with the observations in single-nucleus RNA sequencing. We also identified a series of downstream target genes of GIGYF1 that affect many aspects of the nervous system, especially synaptic transmission.

CONCLUSIONS

De novo variants of GIGYF1 are associated with neurodevelopmental disorders, including autism spectrum disorder. GIGYF1 is involved in neurodevelopment and animal behavior, potentially through regulating hippocampal CA2 neuronal numbers and disturbing synaptic transmission.

Understanding Sensory-Motor Disorders in Autism Spectrum Disorders by Extending Hebbian Theory: Formation of a Rigid-Autonomous Phase Sequence

Autism spectrum disorder is a neuropsychiatric disorder characterized by persistent deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. The symptoms invariably appear in early childhood and cause significant impairment in social, occupational, and other important functions. Various abnormalities in the genetic, neurological, and endocrine systems of patients with autism spectrum disorder have been reported as the etiology; however, no clear factor leading to the onset of the disease has been identified. Additionally, higher order cognitive dysfunctions, which are represented by a lack of theory of mind, sensorimotor disorders, and memory-related disorders (e.g., flashbacks), have been reported in recent years, but no theoretical framework has been proposed to explain these behavioral abnormalities. In this study, we extended Hebb's biopsychology theory to provide a theoretical framework that comprehensively explains the various behavioral abnormalities observed in autism spectrum disorder. Specifically, we propose that a wide range of symptoms in autism spectrum disorder may be caused by the formation of a rigid-autonomous phase sequence (RAPS) in the brain. Using the RAPS formation theory, we propose a biopsychological mechanism that could be a target for the treatment of autism spectrum disorders.

Oxytocin Receptor in Cerebellar Purkinje Cells Does Not Engage in Autism-Related Behaviors

The classical motor center cerebellum is one of the most consistent structures of abnormality in autism spectrum disorders (ASD), and neuropeptide oxytocin is increasingly explored as a potential pharmacotherapy for ASD. However, whether oxytocin targets the cerebellum for therapeutic effects remains unclear. Here, we report a localization of oxytocin receptor (OXTR) in Purkinje cells (PCs) of cerebellar lobule Crus I, which is functionally connected with ASD-implicated circuits. OXTR activation neither affects firing activities, intrinsic excitability, and synaptic transmission of normal PCs nor improves abnormal intrinsic excitability and synaptic transmission of PCs in maternal immune activation (MIA) mouse model of autism. Furthermore, blockage of OXTR in Crus I in wild-type mice does not induce autistic-like social, stereotypic, cognitive, and anxiety-like behaviors. These results suggest that oxytocin signaling in Crus I PCs seems to be uninvolved in ASD pathophysiology, and contribute to understanding of targets and mechanisms of oxytocin in ASD treatment.

Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.

Yield of brain MRI in children with autism spectrum disorder

Autism spectrum disorder (ASD) is a common neurodevelopmental condition. The American Academy of Paediatrics and American Academy of Neurology do not recommend routine brain magnetic resonance imaging (MRI) in the assessment of ASD. The need for a brain MRI should be decided on atypical features in the clinical history and examination. However, many physicians continue to use brain MRI routinely in the assessment process. We performed a retrospective review of indications for requesting brain MRI in our institution over a 5-year period. The aim was to identify the yield of MRI in children with ASD and calculate the prevalence of significant neuroimaging abnormalities in children with ASD and identify clinical indications for neuroimaging. One hundred eighty-one participants were analysed. An abnormal brain MRI was identified in 7.2% (13/181). Abnormal brain MRI was more likely with an abnormal neurological examination (OR 33.1, p = 0.001) or genetic/metabolic abnormality (OR 20, p = 0.02). In contrast, abnormal MRI was not shown to be more likely in children with a variety of other indications such as behavioural issues and developmental delay.      Conclusion: Thus, our findings support that MRI should not be a routine investigation in ASD, without additional findings. The decision to arrange brain MRI should be made on a case-by-case basis following careful evaluation of potential risks and benefits. The impact of any findings on the management course of the child should be considered prior to arranging imaging. What is Known: • Incidental brain MRI findings are common in children with and without ASD. • Many children with ASD undergo brain MRI in the absence of neurological comorbidities. What is New: • Brain MRI abnormalities in ASD are more likely with an abnormal neurological examination and genetic or metabolic conditions. • Prevalence of significant brain MRI abnormalities in ASD alone is low.

Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders

Neuroimaging has revolutionized our understanding of brain function and has become an essential tool for researchers studying neurological disorders. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two widely used neuroimaging techniques to review changes in brain activity. fMRI is a noninvasive technique that uses magnetic fields and radio waves to produce detailed brain images. An EEG is a noninvasive technique that records the brain's electrical activity through electrodes placed on the scalp. This review overviews recent developments in noninvasive functional neuroimaging methods, including fMRI and EEG. Recent advances in fMRI technology, its application to studying brain function, and the impact of neuroimaging techniques on neuroscience research are discussed. Advances in EEG technology and its applications to analyzing brain function and neural oscillations are also highlighted. In addition, advanced courses in neuroimaging, such as diffusion tensor imaging (DTI) and transcranial electrical stimulation (TES), are described, along with their role in studying brain connectivity, white matter tracts, and potential treatments for schizophrenia and chronic pain. Application. The review concludes by examining neuroimaging studies of neurodevelopmental and neurological disorders such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer's disease (AD), and Parkinson's disease (PD). We also described the role of transcranial direct current stimulation (tDCS) in ASD, ADHD, AD, and PD. Neuroimaging techniques have significantly advanced our understanding of brain function and provided essential insights into neurological disorders. However, further research into noninvasive treatments such as EEG, MRI, and TES is necessary to continue to develop new diagnostic and therapeutic strategies for neurological disorders.

Classification of autism based on short-term spontaneous hemodynamic fluctuations using an adaptive graph neural network

BACKGROUND

Short-term spontaneous hemodynamic fluctuations were collected by the functional near-infrared spectroscopy (fNIRS) system to classify children with autism spectrum disorder (ASD) and typical development (TD), and to explore abnormalities in the left inferior frontal gyrus in ASD.

METHODS

Using the fNIRS data of 25 children with ASD and 22 children with TD, a graph neural network combined with the temporal convolution module and the graph convolution module was used, to extract the spatio-temporal features of the data and achieve accurate classification of ASD.

RESULTS

The graph neural network was used to obtain a good classification result in the left inferior frontal gyrus, with an accuracy of 97.1%, precision of 95.1%, and specificity of 93.4%. It was found that the 5th channel (which is located in BA 10) and the 8th channel (which is located in BA 47) in the left inferior frontal gyrus were closely correlated with ASD.

COMPARISON WITH PREVIOUSLY USED METHOD(S)

Compared with the previous deep learning model using the same input, the accuracy of our model has increased by up to 13%, and the correlation between channels in the left inferior frontal gyrus area with the best classification effect was explored through the graph neural network.

CONCLUSION

The adaptive graph neural network (AGNN) model may be able to mine more valuable information to distinguish ASD from TD and in addition, the left inferior frontal gyrus may have greater investigative value.

A Molecular Toolbox of Positron Emission Tomography Tracers for General Anesthesia Mechanism Research

With appropriate radiotracers, positron emission tomography (PET) allows direct or indirect monitoring of the spatial and temporal distribution of anesthetics, neurotransmitters, and biomarkers, making it an indispensable tool for studying the general anesthesia mechanism. In this Perspective, PET tracers that have been recruited in general anesthesia research are introduced in the following order: 1) ¹¹C/¹⁸F-labeled anesthetics, i.e., PET tracers made from inhaled and intravenous anesthetics; 2) PET tracers targeting anesthesia-related receptors, e.g., neurotransmitters and voltage-gated ion channels; and 3) PET tracers for studying anesthesia-related neurophysiological effects and neurotoxicity. The radiosynthesis, pharmacodynamics, and pharmacokinetics of the above PET tracers are mainly discussed to provide a practical molecular toolbox for radiochemists, anesthesiologists, and those who are interested in general anesthesia.

Glycolysis mediates neuron specific histone acetylation in valproic acid-induced human excitatory neuron differentiation

Pregnancy exposure of valproic acid (VPA) is widely adopted as a model of environmental factor induced autism spectrum disorder (ASD). Increase of excitatory/inhibitory synaptic transmission ratio has been proposed as the mechanism of VPA induced ASD. How this happened, particularly at the level of excitatory neuron differentiation in human neural progenitor cells (NPCs) remains largely unclear. Here, we report that VPA exposure remarkably inhibited human NPC proliferation and induced excitatory neuronal differentiation without affecting inhibitory neurons. Following VPA treatment, mitochondrial dysfunction was observed before neuronal differentiation, as showed by ultrastructural changes, respiratory complex activity, mitochondrial membrane potential and oxidation levels. Meanwhile, extracellular acidification assay revealed an elevation of glycolysis by VPA stimulation. Interestingly, inhibiting glycolysis by 2-deoxy-d-glucose-6-phosphate (2-DG) efficiently blocked the excitatory neuronal differentiation of human NPCs induced by VPA. Furthermore, 2-DG treatment significantly compromised the VPA-induced expression of H3ac and H3K9ac, and the VPA-induced binding of H3K9ac on the promoter of Ngn2 and Mash1, two key transcription factors of excitatory neuron fate determination. These data, for the first time, demonstrated that VPA biased excitatory neuron differentiation by glycolysis-mediated histone acetylation of neuron specific transcription factors.

Altered rich-club organization of brain functional network in autism spectrum disorder

Despite numerous research showing the association between brain network abnormalities and autism spectrum disorder (ASD), contrasting findings have been reported from broad functional underconnectivity to broad overconnectivity. Thus, the significance of rich-hub organizations in the brain functional connectome of individuals with ASD remains largely unknown. High-quality data subset of ASD (n = 45) and healthy controls (HC; n = 47) children (7-15 years old) were retrieved from the ABIDE data set, and rich-club organization and network-based statistic (NBS) were assessed from resting-state functional magnetic resonance imaging (rs-fMRI). The rich-club organization functional network (normalized rich-club coefficients >1) was observed in all subjects under a range of thresholds. Compared with HC, ASD patients had higher degree of feeder connections and lower degree of local connections (degree of feeder connections: ASD = 259.20 ± 32.97, HC = 244.98 ± 30.09, p = 0.041; degree of local connections: ASD = 664.02 ± 39.19, HC = 679.89 ± 34.05, p = 0.033) but had similar in rich-club connections. Further, nonparametric NBS analysis showed the presence of abnormal connectivity in the functional network of ASD individuals. Our findings indicated that local connection might be more vulnerable, and feeder connection may compensate for its disruption in ASD, enhancing our understanding on the mechanism of functional connectome dysfunction in ASD.

Dendritic Spine in Autism Genetics: Whole-Exome Sequencing Identifying De Novo Variant of CTTNBP2 in a Quad Family Affected by Autism Spectrum Disorder

Autism spectrum disorder (ASD) affects around 1% of children with no effective blood test or cure. Recent studies have suggested that these are neurological disorders with a strong genetic basis and that they are associated with the abnormal formation of dendritic spines. Chromosome microarray (CMA) together with high-throughput sequencing technology has been used as a powerful tool to identify new candidate genes for ASD. In the present study, CMA was first used to scan for genome-wide copy number variants in a proband, and no clinically significant copy number variants were found. Whole-exome sequencing (WES) was used further for genetic testing of the whole quad family affected by ASD, including the proband, his non-autistic sister, and his parents. Sanger sequencing and MassARRAY-based validation were used to identify and confirm variants associated with ASD. WES yielded a 151-fold coverage depth for each sample. A total of 98.65% of the targeted whole-exome region was covered at >20-fold depth. A de novo variant in CTTNBP2, p.M115T, was identified. The CTTNBP2 gene belongs to a family of ankyrin repeat domain-containing proteins associated with dendritic spine formation. Although CTTNBP2 has been associated with ASD, limited studies have been developed to identify clinically relevant de novo mutations of CTTNBP2 in children with ASD; family-based WES successfully identified a clinically relevant mutation in the CTTNBP2 gene in a quad family affected by ASD. Considering the neuron-specific expression of CTTNBP2 and its role in dendritic spine formation, our results suggest a correlation between the CTTNBP2 mutation and ASD, providing genetic evidence for ASD spine pathology. Although the present study is currently insufficient to support the assertion that the de novo mutation M115T in CTTNBP2 directly causes the autism phenotype, our study provides support for the assertion that this mutation is a candidate clinically relevant variant in autism.

Inductively coupled plasma mass spectrometry based urine metallome to construct clinical decision models for autism spectrum disorder

BACKGROUND

The global prevalence of autism spectrum disorder (ASD) is on the rise, and high levels of exposure to toxic heavy metals may be associated with this increase. Urine analysis is a noninvasive method for investigating the accumulation and excretion of heavy metals. The aim of this study was to identify ASD-associated urinary metal markers.

METHODS

Overall, 70 children with ASD and 71 children with typical development (TD) were enrolled in this retrospective case-control study. In this metallomics investigation, inductively coupled plasma mass spectrometry was performed to obtain the urine profile of 27 metals.

RESULTS

Children with ASD could be distinguished from children with TD based on the urine metal profile, with ASD children showing an increased urine metal Shannon diversity. A metallome-wide association analysis was used to identify seven ASD-related metals in urine, with cobalt, aluminum, selenium, and lithium significantly higher, and manganese, mercury, and titanium significantly lower in the urine of children with ASD than in children with TD. The least absolute shrinkage and selection operator (LASSO) machine learning method was used to rank the seven urine metals in terms of their effect on ASD. On the basis of these seven urine metals, we constructed a LASSO regression model for ASD classification and found an area under the receiver operating characteristic curve of 0.913. We also constructed a clinical prediction model for ASD based on the seven metals that were different in the urine of children with ASD and found that the model would be useful for the clinical prediction of ASD risk.

CONCLUSIONS

The study findings suggest that altered urine metal concentrations may be an important risk factor for ASD, and we recommend further exploration of the mechanisms and clinical treatment measures for such alterations.

Brain white matter microstructure abnormalities in children with optimal outcome from autism: a four-year follow-up study

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder, with only a small proportion of people obtaining optimal outcomes. We do not know if children with ASD exhibit abnormalities in the white matter (WM) microstructure or if this pattern would predict ASD prognosis in a longitudinal study. 182 children with ASD were recruited for MRI and clinical assessment; 111 completed a four-year follow-up visit (30 with optimal outcomes, ASD-; 81 with persistent diagnosis, ASD+). Additionally, 72 typically developing controls (TDC) were recruited. The microstructural integrity of WM fiber tracts was revealed using tract-based spatial statistics (TBSS) and probabilistic tractography analyses. We examined the neuroimaging abnormality associated with ASD and its relationship to ASD with optimal outcome. The ASD+ and TDC groups were propensity score matched to the ASD- group in terms of age, gender, and IQ. TBSS indicated that children with ASD exhibited abnormalities in the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and extending to the anterior thalamic radiation (ATR) and cingulum; whereas the ASD+ group showed more severe abnormalities than the ASD- group. Probabilistic tractography analysis revealed that ASD+ group exhibited lower Fractional Anisotropy (FA) of the left superior thalamic radiation (STR L) than ASD- group, and that FA value of the STR L was a significant predictor of optimal outcome (EX(B), 6.25; 95% CI 2.50-15.63; p < 0.001). Children with ASD showed significant variations in SLF_L and STR_L, and STR_L was a predictor of 'ASD with optimal outcome'. Our findings may aid in comprehension of the mechanisms of 'ASD with optimal outcome'.

Deficiency of the ywhaz gene, involved in neurodevelopmental disorders, alters brain activity and behaviour in zebrafish

Genetic variants in YWHAZ contribute to psychiatric disorders such as autism spectrum disorder and schizophrenia, and have been related to an impaired neurodevelopment in humans and mice. Here, we have used zebrafish to investigate the mechanisms by which YWHAZ contributes to neurodevelopmental disorders. We observed that ywhaz expression was pan-neuronal during developmental stages and restricted to Purkinje cells in the adult cerebellum, cells that are described to be reduced in number and size in autistic patients. We then performed whole-brain imaging in wild-type and ywhaz CRISPR/Cas9 knockout (KO) larvae and found altered neuronal activity and connectivity in the hindbrain. Adult ywhaz KO fish display decreased levels of monoamines in the hindbrain and freeze when exposed to novel stimuli, a phenotype that can be reversed with drugs that target monoamine neurotransmission. These findings suggest an important role for ywhaz in establishing neuronal connectivity during development and modulating both neurotransmission and behaviour in adults.

In-depth characterization of neuroradiological findings in a large sample of individuals with autism spectrum disorder and controls

BACKGROUND

Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions associated with quantitative differences in cortical and subcortical brain morphometry. Qualitative assessment of brain morphology provides complementary information on the possible underlying neurobiology. Studies of neuroradiological findings in ASD have rendered mixed results, and await robust replication in a sizable and independent sample.

METHODS

We systematically and comprehensively assessed neuroradiological findings in a large cohort of participants with ASD and age-matched controls (total N = 620, 348 ASD and 272 controls), including 70 participants with intellectual disability (47 ASD, 23 controls). We developed a comprehensive scoring system, augmented by standardized biometric measures.

RESULTS

There was a higher incidence of neuroradiological findings in individuals with ASD (89.4 %) compared to controls (83.8 %, p = .042). Certain findings were also more common in ASD, in particular opercular abnormalities (OR 1.9, 95 % CI 1.3-3.6) and mega cisterna magna (OR 2.4, 95 % CI 1.4-4.0) reached significance when using FDR, whereas increases in macrocephaly (OR 2.0, 95 % CI 1.2-3.2), cranial deformities (OR 2.4, 95 % CI: 1.0-5.8), calvarian / dural thickening (OR 1.5, 95 % CI 1.0-2.3), ventriculomegaly (OR 3.4, 95 % CI 1.3-9.2), and hypoplasia of the corpus callosum (OR 2.7, 95 % CI 1.1-6.3) did not survive this correction. Furthermore, neuroradiological findings were more likely to occur in isolation in controls, whereas they clustered more frequently in ASD. The incidence of neuroradiological findings was higher in individuals with mild intellectual disability (95.7 %), irrespective of ASD diagnosis.

CONCLUSION

There was a subtly higher prevalence of neuroradiological findings in ASD, which did not appear to be specific to the condition. Individual findings or clusters of findings may point towards the neurodevelopmental mechanisms involved in individual cases. As such, clinical MRI assessments may be useful to guide further etiopathological (genetic) investigations, and are potentially valuable to fundamental ASD research.

Positron Emission Tomography in the Neuroimaging of Autism Spectrum Disorder: A Review

Autism spectrum disorder (ASD) is a basket term for neurodevelopmental disorders characterized by marked impairments in social interactions, repetitive and stereotypical behaviors, and restricted interests and activities. Subtypes include (A) disorders with known genetic abnormalities including fragile X syndrome, Rett syndrome, and tuberous sclerosis and (B) idiopathic ASD, conditions with unknown etiologies. Positron emission tomography (PET) is a molecular imaging technology that can be utilized in vivo for dynamic and quantitative research, and is a valuable tool for exploring pathophysiological mechanisms, evaluating therapeutic efficacy, and accelerating drug development in ASD. Recently, several imaging studies on ASD have been published and physiological changes during ASD progression was disclosed by PET. This paper reviews the specific radioligands for PET imaging of critical biomarkers in ASD, and summarizes and discusses the similar and different discoveries in outcomes of previous studies. It is of great importance to identify general physiological changes in cerebral glucose metabolism, cerebral blood flow perfusion, abnormalities in neurotransmitter systems, and inflammation in the central nervous system in ASD, which may provide excellent points for further ASD research.

Novel treatments in autism spectrum disorder

PURPOSE OF REVIEW

There are currently no approved medications for the core symptoms of autism spectrum disorder (ASD), and only limited data on the management of co-occurring mental health and behavioural symptoms. The purpose of this review is to synthesize recent trials on novel treatments in ASD, with a focus on research trends in the past 2 years.

RECENT FINDINGS

No new pharmacologic agents received regulatory approval for use in ASD. Several large randomized controlled trials (RCTs) had negative or ambiguous results (e.g. fluoxetine, oxytocin). A cross-over RCT of an oral cannabinoid suggested possible benefits for disruptive behaviours. Two large-scale multicentre trials of bumetanide were terminated early for lack of efficacy. Multicenter trials using repetitive transcranial magnetic stimulation are underway. Recent meta-analyses indicate that specific behavioural and psychological interventions can support social communication and treat anxiety. Numerous novel treatment targets informed by biological mechanisms are under investigation.

SUMMARY

Recent data support the use of behavioural and psychological interventions for social communication and anxiety in ASD; data are more limited regarding pharmacotherapy for core and associated symptoms. Next steps include replication of early findings, trials of new molecular targets, and the identification of novel biomarkers, including genetic predictors, of treatment response.

Comorbidity of Attention-Deficit Hyperactivity Disorder and Autism Spectrum Disorders: Current Status and Promising Directions

High rates of co-occurring Attention-Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) suggest common causal pathways, which await elucidation. What is well-established, however, is the negative impact of comorbid ADHD and ASD on outcomes for everyday living, particularly in social interaction and communication and on broader psychopathology. Neurocognitive approaches suggest correlates of comorbidity are rooted in functional connectivity networks associated with executive control. There is support for familial origins, with molecular-genetic studies suggesting a causal role of pleiotropic genes. Further investigation is needed to elucidate fully how genetic risk for ADHD and ASD affects neurodevelopment and to identify structural and functional neural correlates and their behavioral sequelae. Identification of intermediate phenotypes is necessary to advance understanding, which requires studies that include the full spectrum of ASD and ADHD symptom severity, use longitudinal designs and multivariate methods to probe broad constructs, such as executive and social function, and consider other sources of heterogeneity, such as age, sex, and other psychopathology. Randomized efficacy trials targeting comorbid symptomatology are needed to mitigate negative developmental outcomes.

Association of CDH11 with Autism Spectrum Disorder Revealed by Matched-gene Co-expression Analysis and Mouse Behavioral Studies

A large number of putative risk genes for autism spectrum disorder (ASD) have been reported. The functions of most of these susceptibility genes in developing brains remain unknown, and causal relationships between their variation and autism traits have not been established. The aim of this study was to predict putative risk genes at the whole-genome level based on the analysis of gene co-expression with a group of high-confidence ASD risk genes (hcASDs). The results showed that three gene features - gene size, mRNA abundance, and guanine-cytosine content - affect the genome-wide co-expression profiles of hcASDs. To circumvent the interference of these features in gene co-expression analysis, we developed a method to determine whether a gene is significantly co-expressed with hcASDs by statistically comparing the co-expression profile of this gene with hcASDs to that of this gene with permuted gene sets of feature-matched genes. This method is referred to as "matched-gene co-expression analysis" (MGCA). With MGCA, we demonstrated the convergence in developmental expression profiles of hcASDs and improved the efficacy of risk gene prediction. The results of analysis of two recently-reported ASD candidate genes, CDH11 and CDH9, suggested the involvement of CDH11, but not CDH9, in ASD. Consistent with this prediction, behavioral studies showed that Cdh11-null mice, but not Cdh9-null mice, have multiple autism-like behavioral alterations. This study highlights the power of MGCA in revealing ASD-associated genes and the potential role of CDH11 in ASD.