Autism Spectrum Disorder Brain Research Articles

Embryonic origin of two ASD subtypes of social symptom severity: the larger the brain cortical organoid size, the more severe the social symptoms

BackgroundSocial affective and communication symptoms are central to autism spectrum disorder (ASD), yet their severity differs across toddlers: Some toddlers with ASD display improving abilities across early ages and develop good social and language skills, while others with “profound” autism have persistently low social, language and cognitive skills and require lifelong care. The biological origins of these opposite ASD social severity subtypes and developmental trajectories are not known.MethodsBecause ASD involves early brain overgrowth and excess neurons, we measured size and growth in 4910 embryonic-stage brain cortical organoids (BCOs) from a total of 10 toddlers with ASD and 6 controls (averaging 196 individual BCOs measured/subject). In a 2021 batch, we measured BCOs from 10 ASD and 5 controls. In a 2022 batch, we tested replicability of BCO size and growth effects by generating and measuring an independent batch of BCOs from 6 ASD and 4 control subjects. BCO size was analyzed within the context of our large, one-of-a-kind social symptom, social attention, social brain and social and language psychometric normative datasets ranging from N = 266 to N = 1902 toddlers. BCO growth rates were examined by measuring size changes between 1- and 2-months of organoid development. Neurogenesis markers at 2-months were examined at the cellular level. At the molecular level, we measured activity and expression of Ndel1; Ndel1 is a prime target for cell cycle-activated kinases; known to regulate cell cycle, proliferation, neurogenesis, and growth; and known to be involved in neuropsychiatric conditions.ResultsAt the BCO level, analyses showed BCO size was significantly enlarged by 39% and 41% in ASD in the 2021 and 2022 batches. The larger the embryonic BCO size, the more severe the ASD social symptoms. Correlations between BCO size and social symptoms were r = 0.719 in the 2021 batch and r = 0. 873 in the replication 2022 batch. ASD BCOs grew at an accelerated rate nearly 3 times faster than controls. At the cell level, the two largest ASD BCOs had accelerated neurogenesis. At the molecular level, Ndel1 activity was highly correlated with the growth rate and size of BCOs. Two BCO subtypes were found in ASD toddlers: Those in one subtype had very enlarged BCO size with accelerated rate of growth and neurogenesis; a profound autism clinical phenotype displaying severe social symptoms, reduced social attention, reduced cognitive, very low language and social IQ; and substantially altered growth in specific cortical social, language and sensory regions. Those in a second subtype had milder BCO enlargement and milder social, attention, cognitive, language and cortical differences.LimitationsLarger samples of ASD toddler-derived BCO and clinical phenotypes may reveal additional ASD embryonic subtypes.ConclusionsBy embryogenesis, the biological bases of two subtypes of ASD social and brain development—profound autism and mild autism—are already present and measurable and involve dysregulated cell proliferation and accelerated neurogenesis and growth. The larger the embryonic BCO size in ASD, the more severe the toddler’s social symptoms and the more reduced the social attention, language ability, and IQ, and the more atypical the growth of social and language brain regions.

Personalized repetitive transcranial magnetic stimulation guided by the spectral electroencephalogram may enhance and democratize therapy for autism spectrum disorder

Autism spectrum disorder (ASD) is a genetically heterogeneous group of neurodevelopmental disorders that affect 1 in 36 children (CDC data) and have recognizable core deficits in common, including repetitive stereotyped behaviors and difficulties in social interaction and communication. Pharmacological interventions moderate some ASD comorbidities, but do not alleviate core deficits and have significant side effects. While many behavioral therapies are inadequate, a very intensive form called applied behavioral analysis (ABA) is demonstrably effective. ABA is based on graded progression and immediate feedback. ABA has raised concerns over its intensive nature and has triggered unease about being too harsh. One solution may derive from a widespread hypothesis of ASD pathogenesis, which posits that the brain in ASD is overexcited, i.e., excitation dominates over inhibition, and electroencephalographic (EEG) alpha band oscillatory activity is altered, which degrades sensory input and task management. This may also disrupt the brain mesolimbic dopaminergic reward cascade causing social interactions to be unrewarding, leading to deleterious social behavior and poor communication. We hypothesize that a comprehensive, personalized form of spectral EEG guided repetitive transcranial magnetic stimulation that we term PrTMS, can normalize alpha EEG oscillations, E/I balance, and dopaminergic reward signaling, to facilitate improved psychosocial behavior. The goal is for PrTMS to synergize with behavioral interventions, so that ABA for example, could be less intensive. This may hold the promise of making self-determination more readily attainable for ASD persons, and could also democratize ASD therapy by rendering it more affordable.

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model.

Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challenging. We propose a dual-branch graph neural network that effectively extracts and fuses features from bimodalities, achieving 73.9% diagnostic accuracy. To explain the mechanism distinguishing autism spectrum disorder from healthy controls, we establish a perturbation model for brain imaging markers and perform a neuro-transcriptomic joint analysis using partial least squares regression and enrichment to identify potential genetic biomarkers. The perturbation model identifies brain imaging markers related to structural magnetic resonance imaging in the frontal, temporal, parietal, and occipital lobes, while functional magnetic resonance imaging markers primarily reside in the frontal, temporal, occipital lobes, and cerebellum. The neuro-transcriptomic joint analysis highlights genes associated with biological processes, such as "presynapse," "behavior," and "modulation of chemical synaptic transmission" in autism spectrum disorder's brain development. Different magnetic resonance imaging modalities offer complementary information for autism spectrum disorder diagnosis. Our dual-branch graph neural network achieves high accuracy and identifies abnormal brain regions and the neuro-transcriptomic analysis uncovers important genetic biomarkers. Overall, our study presents an effective approach for assisting in autism spectrum disorder diagnosis and identifying genetic biomarkers, showing potential for enhancing the diagnosis and treatment of this condition.

ASD-GResTM: Deep Learning Framework for ASD classification using Gramian Angular Field.

Autism Spectrum Disorder (ASD) is a heterogeneous disorder in children, and the current clinical diagnosis is accomplished using behavioral, cognitive, developmental, and language metrics. These clinical metrics can be imperfect measures as they are subject to high test-retest variability, and are influenced by assessment factors such as environment, social structure, or comorbid disorders. Advances in neuroimaging coupled with machine-learning provides an opportunity to develop methods that are more quantifiable, and reliable than existing clinical techniques. In this paper, we design and develop a deep-learning model that operates on functional magnetic resonance imaging (fMRI) data, and can classify between ASD and neurotypical brains. We introduce a novel strategy to transform time-series data extracted from fMRI signals into Gramian Angular Field (GAF) while locking in the temporal and spatial patterns in the data. Our motivation is to design and develop a novel framework that could encode the time-series, acquired from fMRI data, into images that can be used by deep-learning architectures that have been successful in computer vision. In our proposed framework called ASD-GResTM, we used a Convolutional Neural Network (CNN) to extract useful features from GAF images. We then used a Long Short-Term Memory (LSTM) layer to learn the activities between the regions. Finally, the output representations of the last LSTM layer are applied to a single-layer perceptron (SPL) to get the final classification. Our extensive experimentation demonstrates high accuracy across 4 centers, and outperforms state-of-the-art models on two centers with an increase in the accuracy of 17.58% and 6.7%, respectively as compared to the state of the art. Our model achieved the maximum accuracy of 81.78% with high degree of sensitivity and specificity. All training, validation, and testing was accomplished using openly available ABIDE-I benchmarking dataset.

Translatome analysis of tuberous sclerosis complex 1 patient-derived neural progenitor cells reveals rapamycin-dependent and independent alterations

BackgroundTuberous sclerosis complex (TSC) is an inherited neurocutaneous disorder caused by mutations in the TSC1 or TSC2 genes, with patients often exhibiting neurodevelopmental (ND) manifestations termed TSC-associated neuropsychiatric disorders (TAND) including autism spectrum disorder (ASD) and intellectual disability. Hamartin (TSC1) and tuberin (TSC2) proteins form a complex inhibiting mechanistic target of rapamycin complex 1 (mTORC1) signaling. Loss of TSC1 or TSC2 activates mTORC1 that, among several targets, controls protein synthesis by inhibiting translational repressor eIF4E-binding proteins. Using TSC1 patient-derived neural progenitor cells (NPCs), we recently reported early ND phenotypic changes, including increased cell proliferation and altered neurite outgrowth in TSC1-null NPCs, which were unaffected by the mTORC1 inhibitor rapamycin.MethodsHere, we used polysome profiling, which quantifies changes in mRNA abundance and translational efficiencies at a transcriptome-wide level, to compare CRISPR-edited TSC1-null with CRISPR-corrected TSC1-WT NPCs generated from one TSC donor (one clone/genotype). To assess the relevance of identified gene expression alterations, we performed polysome profiling in postmortem brains from ASD donors and age-matched controls. We further compared effects on translation of a subset of transcripts and rescue of early ND phenotypes in NPCs following inhibition of mTORC1 using the allosteric inhibitor rapamycin versus a third-generation bi-steric, mTORC1-selective inhibitor RMC-6272.ResultsPolysome profiling of NPCs revealed numerous TSC1-associated alterations in mRNA translation that were largely recapitulated in human ASD brains. Moreover, although rapamycin treatment partially reversed the TSC1-associated alterations in mRNA translation, most genes related to neural activity/synaptic regulation or ASD were rapamycin-insensitive. In contrast, treatment with RMC-6272 inhibited rapamycin-insensitive translation and reversed TSC1-associated early ND phenotypes including proliferation and neurite outgrowth that were unaffected by rapamycin.ConclusionsOur work reveals ample mRNA translation alterations in TSC1 patient-derived NPCs that recapitulate mRNA translation in ASD brain samples. Further, suppression of TSC1-associated but rapamycin-insensitive translation and ND phenotypes by RMC-6272 unveils potential implications for more efficient targeting of mTORC1 as a superior treatment strategy for TAND.

A Framework to Diagnose Autism Spectrum Disorder Using Morphological Connectivity of sMRI and XGBoost.

In this study, we automated the diagnostic procedure of autism spectrum disorder (ASD) with the help of anatomical alterations found in structural magnetic resonance imaging (sMRI) data of the ASD brain and machine learning tools. Initially, the sMRI data was preprocessed using the FreeSurfer toolbox. Further, the brain regions were segmented into 148 regions of interest using the Destrieux atlas. Features such as volume, thickness, surface area, and mean curvature were extracted for each brain region, and the morphological connectivity was computed using Pearson correlation. These morphological connections were fed to XGBoost for feature reduction and to build the diagnostic model. The results showed an average accuracy of 94.16% for the top 18 features. The frontal and limbic regions contributed more features to the classification model. Our proposed method is thus effective for the classification of ASD and can also be useful for the screening of other similar neurological disorders.

APPlications of amyloid-β precursor protein metabolites in macrocephaly and autism spectrum disorder.

Metabolites of the Amyloid-β precursor protein (APP) proteolysis may underlie brain overgrowth in Autism Spectrum Disorder (ASD). We have found elevated APP metabolites (total APP, secreted (s) APPα, and α-secretase adamalysins in the plasma and brain tissue of children with ASD). In this review, we highlight several lines of evidence supporting APP metabolites' potential contribution to macrocephaly in ASD. First, APP appears early in corticogenesis, placing APP in a prime position to accelerate growth in neurons and glia. APP metabolites are upregulated in neuroinflammation, another potential contributor to excessive brain growth in ASD. APP metabolites appear to directly affect translational signaling pathways, which have been linked to single gene forms of syndromic ASD (Fragile X Syndrome, PTEN, Tuberous Sclerosis Complex). Finally, APP metabolites, and microRNA, which regulates APP expression, may contribute to ASD brain overgrowth, particularly increased white matter, through ERK receptor activation on the PI3K/Akt/mTOR/Rho GTPase pathway, favoring myelination.

LAMP1 as a novel molecular biomarker to predict the prognosis of the children with autism spectrum disorder using bioinformatics approaches

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that usually manifests in childhood and is thought to be caused by a complex interaction of genetic, environmental, and immune factors. The majority of current ASD diagnostic methods rely on subjective behavioral observation and scale assessment, making early detection difficult. In this study, we confirmed that lysosomal-associated membrane protein 1 (LAMP1), a functional marker of immune cell activation and cytotoxic degranulation, was upregulated in ASD blood, brain cortex, and various genetic animal models or cells using bioinformatics approaches. The prognostic value of LAMP1 was investigated by correlating its expression with clinical ASD rating scales, and the receiver operating characteristic (ROC) curve analysis in ASD also revealed that it has a favorable diagnostic ability in distinguishing ASD from control cohort. According to gene set enrichment analysis (GSEA) results, LAMP1 correlated with genes that were enriched in natural kill and T cell immune function. Taking all of the evidence into account, we discovered that abnormal elevations of LAMP1 mRNA and protein in the blood of ASD children, may influence the development of ASD through its involvement in immune cell activity regulation. This report highlights a novel marker for ASD early detection as well as potential therapeutic targets.

Inferring the genetic relationship between brain imaging-derived phenotypes and risk of complex diseases by Mendelian randomization and genome-wide colocalization

Observational studies consistently disclose brain imaging-derived phenotypes (IDPs) as critical markers for early diagnosis of both brain disorders and cardiovascular diseases. However, it remains unclear about the shared genetic landscape between brain IDPs and the risk of brain disorders and cardiovascular diseases, restricting the applications of potential diagnostic techniques through brain IDPs. Here, we reported genetic correlations and putative causal relationships between 921 brain IDPs, 20 brain disorders and six cardiovascular diseases by leveraging their large-scale genome-wide association study (GWAS) summary statistics. Applications of Mendelian randomization (MR) identified significant putative causal effects of multiple region-specific brain IDPs in relation to the increased risks for amyotrophic lateral sclerosis (ALS), major depressive disorder (MDD), autism spectrum disorder (ASD) and schizophrenia (SCZ). We also found brain IDPs specifically from temporal lobe as a putatively causal consequence of hypertension. The genome-wide colocalization analysis identified three genomic regions in which MDD, ASD and SCZ colocalized with the brain IDPs, and two novel SNPs to be associated with ASD, SCZ, and multiple brain IDPs. Furthermore, we identified a list of candidate genes involved in the shared genetics underlying pairs of brain IDPs and MDD, ASD, SCZ, ALS and hypertension. Our results provide novel insights into the genetic relationships between brain disorders and cardiovascular diseases and brain IDP, which may server as clues for using brain IDPs to predict risks of diseases.

Microtubule Cytoskeletal Network Alterations in a Transgenic Model of Tuberous Sclerosis Complex: Relevance to Autism Spectrum Disorders.

Tuberous sclerosis complex (TSC) is a rare genetic multisystem disorder caused by loss-of-function mutations in the tumour suppressors TSC1/TSC2, both of which are negative regulators of the mammalian target of rapamycin (mTOR) kinase. Importantly, mTOR hyperactivity seems to be linked with the pathobiology of autism spectrum disorders (ASD). Recent studies suggest the potential involvement of microtubule (MT) network dysfunction in the neuropathology of "mTORopathies", including ASD. Cytoskeletal reorganization could be responsible for neuroplasticity disturbances in ASD individuals. Thus, the aim of this work was to study the effect of Tsc2 haploinsufficiency on the cytoskeletal pathology and disturbances in the proteostasis of the key cytoskeletal proteins in the brain of a TSC mouse model of ASD. Western-blot analysis indicated significant brain-structure-dependent abnormalities in the microtubule-associated protein Tau (MAP-Tau), and reduced MAP1B and neurofilament light (NF-L) protein level in 2-month-old male B6;129S4-Tsc2tm1Djk/J mice. Alongside, pathological irregularities in the ultrastructure of both MT and neurofilament (NFL) networks as well as swelling of the nerve endings were demonstrated. These changes in the level of key cytoskeletal proteins in the brain of the autistic-like TSC mice suggest the possible molecular mechanisms responsible for neuroplasticity alterations in the ASD brain.

Heterozygous Cc2d1a mice show sex-dependent changes in the Beclin-1/p62 ratio with impaired prefrontal cortex and hippocampal autophagy

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders characterized by repetitive behaviors, lack of social interaction and communication. CC2D1A is identified in patients as an autism risk gene. Recently, we suggested that heterozygous Cc2d1a mice exhibit impaired autophagy in the hippocampus. We now report the analysis of autophagy markers (Lc3, Beclin and p62) in different regions hippocampus, prefrontal cortex, hypothalamus and cerebellum, with an overall decrease in autophagy and changes in Beclin-1/p62 ratio in the hippocampus. We observed sex-dependent variations in transcripts and protein expression levels. Moreover, our analyses suggest that alterations in autophagy initiated in Cc2d1a heterozygous parents are variably transmitted to offspring, even when the offspring's genotype is wild type. Aberration in the autophagy mechanism may indirectly contribute to induce synapse alteration in the ASD brain.

Pathogenic Mis-splicing of CPEB4 in Schizophrenia

BackgroundSchizophrenia (SCZ) is caused by an interplay of polygenic risk and environmental factors, which may alter regulators of gene expression leading to pathogenic misexpression of SCZ risk genes. The CPEB family of RNA-binding proteins (CPEB1–4) regulates translation of target RNAs (approximately 40% of overall genes). We previously identified CPEB4 as a key dysregulated translational regulator in autism spectrum disorder (ASD) because its neuronal-specific microexon (exon 4) is mis-spliced in ASD brains, causing underexpression of numerous ASD risk genes. The genetic factors and pathogenic mechanisms shared between SCZ and ASD led us to hypothesize CPEB4 mis-splicing in SCZ leading to underexpression of multiple SCZ-related genes. MethodsWe performed MAGMA-enrichment analysis on Psychiatric Genomics Consortium genome-wide association study data and analyzed RNA sequencing data from the PsychENCODE Consortium. Reverse transcriptase polymerase chain reaction and Western blot were performed on postmortem brain tissue, and the presence/absence of antipsychotics was assessed through toxicological analysis. Finally, mice with mild overexpression of exon 4–lacking CPEB4 (CPEB4Δ4) were generated and analyzed biochemically and behaviorally. ResultsFirst, we found enrichment of SCZ-associated genes for CPEB4-binder transcripts. We also found decreased usage of CPEB4 microexon in SCZ probands, which was correlated with decreased protein levels of CPEB4-target SCZ-associated genes only in antipsychotic-free individuals. Interestingly, differentially expressed genes fit those reported for SCZ, specifically in the SCZ probands with decreased CPEB4-microexon inclusion. Finally, we demonstrated that mice with mild overexpression of CPEB4Δ4 showed decreased protein levels of CPEB4-target SCZ genes and SCZ-linked behaviors. ConclusionsWe identified aberrant CPEB4 splicing and downstream misexpression of SCZ risk genes as a novel etiological mechanism in SCZ.

Convergent coexpression of autism-associated genes suggests some novel risk genes may not be detectable in large-scale genetic studies

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder characterized by deficits in social interactions and communication. Protein-altering variants in many genes have been shown to contribute to ASD; however, understanding the convergence across many genes remains a challenge. We demonstrate that coexpression patterns from 993 human postmortem brains are significantly correlated with the transcriptional consequences of CRISPR perturbations in human neurons. Across 71 ASD risk genes, there was significant tissue-specific convergence implicating synaptic pathways. Tissue-specific convergence was further demonstrated across schizophrenia and atrial fibrillation risk genes. The degree of ASD convergence was significantly correlated with ASD association from rare variation and differential expression in ASD brains. Positively convergent genes showed intolerance to functional mutations and had shorter coding lengths than known risk genes even after removing association with ASD. These results indicate that convergent coexpression can identify potentially novel genes that are unlikely to be discovered by sequencing studies.

Effects of spatially filtered fearful faces and awareness on amygdala activity in adults with autism spectrum disorder: A magnetoencephalography study

BackgroundThe amygdala is pivotal in emotional face processing. Spatial frequencies (SFs) of visual images are divided and processed via two visual pathways: low spatial frequency (LSF) information is conveyed by the magnocellular pathway, while the parvocellular pathway carries high spatial frequency information. We hypothesized that altered amygdala activity might underlie atypical social communication caused by changes in both conscious and non-conscious emotional face processing in the brain in individuals with autism spectrum disorder (ASD). MethodEighteen adults with ASD and 18 typically developing (TD) peers participated in this study. Spatially filtered fearful- and neutral-expression faces and object stimuli were presented under supraliminal or subliminal conditions, and neuromagnetic responses in the amygdala were measured using 306-channel whole-head magnetoencephalography. ResultsThe latency of the evoked responses at approximately 200 ms to unfiltered neutral face stimuli and object stimuli in the ASD group was shorter than that in the TD group in the unaware condition. Regarding emotional face processing, the evoked responses in the ASD group were larger than those in the TD group under the aware condition. The later positive shift during 200–500 ms (ARV) was larger than that in the TD group, regardless of awareness. Moreover, ARV to HSF face stimuli was larger than that to the other spatial filtered face stimuli in the aware condition. ConclusionRegardless of awareness, ARV might reflect atypical face information processing in the ASD brain.

Neuroinflammation, Energy and Sphingolipid Metabolism Biomarkers Are Revealed by Metabolic Modeling of Autistic Brains

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental disorders generally characterized by repetitive behaviors and difficulties in communication and social behavior. Despite its heterogeneous nature, several metabolic dysregulations are prevalent in individuals with ASD. This work aims to understand ASD brain metabolism by constructing an ASD-specific prefrontal cortex genome-scale metabolic model (GEM) using transcriptomics data to decipher novel neuroinflammatory biomarkers. The healthy and ASD-specific models are compared via uniform sampling to identify ASD-exclusive metabolic features. Noticeably, the results of our simulations and those found in the literature are comparable, supporting the accuracy of our reconstructed ASD model. We identified that several oxidative stress, mitochondrial dysfunction, and inflammatory markers are elevated in ASD. While oxidative phosphorylation fluxes were similar for healthy and ASD-specific models, and the fluxes through the pathway were nearly undisturbed, the tricarboxylic acid (TCA) fluxes indicated disruptions in the pathway. Similarly, the secretions of mitochondrial dysfunction markers such as pyruvate are found to be higher, as well as the activities of oxidative stress marker enzymes like alanine and aspartate aminotransferases (ALT and AST) and glutathione-disulfide reductase (GSR). We also detected abnormalities in the sphingolipid metabolism, which has been implicated in many inflammatory and immune processes, but its relationship with ASD has not been thoroughly explored in the existing literature. We suggest that important sphingolipid metabolites, such as sphingosine-1-phosphate (S1P), ceramide, and glucosylceramide, may be promising biomarkers for the diagnosis of ASD and provide an opportunity for the adoption of early intervention for young children.

Characteristics of the Brain in ASD and Effective Ways of Teaching

Autism Spectrum Disorder (ASD) is a sort of neurodiversity that is characterized by repetitive behavior, limited interests, struggling in social interaction, expressing feelings, and many more. It is an innate disorder and combines several previously used definitions of mental syndromes and diseases into one diagnostic unit. Its signs can be noticed in infancy or early childhood, at two years old, or a little later. For instance, the child practices non-verbal communication speaks very little, and repeatedly makes the same movement with his fingers, arms, or legs. Such a person may have intact intelligence and the ability to live in society, but ASD is often associated with cognitive impairments of varying severity. A single cause of the appearance of ASD has not yet been found. Scientists identify only factors that can affect the likelihood of its occurrence, for instance, mutations, problems with pregnancy, or difficult ecological situations.

Fmr1 Mutation Alters the Early Development of Sensory Coding and Hunting and Social Behaviors in Larval Zebrafish.

Autism spectrum disorders (ASDs) are developmental in origin; however, little is known about how they affect the early development of behavior and sensory coding. The most common inherited form of autism is Fragile X syndrome (FXS), caused by a mutation in FMR1 Mutation of fmr1 in zebrafish causes anxiety-like behavior, hyperactivity, and hypersensitivity in auditory and visual processing. Here, we show that zebrafish fmr1-/- mutant larvae of either sex also display changes in hunting behavior, tectal coding, and social interaction. During hunting, they were less successful at catching prey and displayed altered behavioral sequences. In the tectum, representations of prey-like stimuli were more diffuse and had higher dimensionality. In a social behavioral assay, they spent more time observing a conspecific but responded more slowly to social cues. However, when given a choice of rearing environment fmr1-/- larvae preferred one with reduced visual stimulation, and rearing them in this environment reduced genotype-specific effects on tectal excitability. Together, these results shed new light on how fmr1-/- changes the early development of neural systems and behavior in a vertebrate.SIGNIFICANCE STATEMENT Autism spectrum disorders (ASDs) are caused by changes in early neural development. Animal models of ASDs offer the opportunity to study these developmental processes in greater detail than in humans. Here, we found that a zebrafish mutant for a gene which in humans causes one type of ASD showed early alterations in hunting behavior, social behavior, and how visual stimuli are represented in the brain. However, we also found that mutant fish preferred reduced visual stimulation, and rearing them in this environment reduced alterations in neural activity patterns. These results suggest interesting new directions for using zebrafish as a model to study the development of brain and behavior in ASDs, and how the impact of ASDs could potentially be reduced.

Dysregulated phosphate metabolism in autism spectrum disorder: associations and insights for future research.

Studies of autism spectrum disorder (ASD) related to exposure to toxic levels of dietary phosphate are lacking. Phosphate toxicity from dysregulated phosphate metabolism can negatively impact almost every major organ system of the body, including the central nervous system. The present paper used a grounded theory-literature review method to synthesise associations of dysregulated phosphate metabolism with the aetiology of ASD. Cell signalling in autism has been linked to an altered balance between phosphoinositide kinases, which phosphorylate proteins, and the counteracting effect of phosphatases in neuronal membranes. Glial cell overgrowth in the developing ASD brain can lead to disturbances in neuro-circuitry, neuroinflammation and immune responses which are potentially related to excessive inorganic phosphate. The rise in ASD prevalence has been suggested to originate in changes to the gut microbiome from increasing consumption of additives in processed food, including phosphate additives. Ketogenic diets and dietary patterns that eliminate casein also reduce phosphate intake, which may account for many of the suggested benefits of these diets in children with ASD. Dysregulated phosphate metabolism is causatively linked to comorbid conditions associated with ASD such as cancer, tuberous sclerosis, mitochondrial dysfunction, diabetes, epilepsy, obesity, chronic kidney disease, tauopathy, cardiovascular disease and bone mineral disorders. Associations and proposals presented in this paper offer novel insights and directions for future research linking the aetiology of ASD with dysregulated phosphate metabolism and phosphate toxicity from excessive dietary phosphorus intake.

The interaction between intestinal bacterial metabolites and phosphatase and tensin homolog in autism spectrum disorder

Intestinal bacteria-associated para-cresyl sulfate (pCS) and 4-ethylphenyl sulfate (4EPS) are elevated in autism spectrum disorder (ASD). Both metabolites can induce ASD-like behaviors in mice, but the molecular mechanisms are not known. Phosphatase and tensin homolog (PTEN) is a susceptibility gene for ASD. The present study investigated the relation between pCS and 4EPS and PTEN in ASD in a valproic acid (VPA)-induced murine ASD model and an in vitro LPS-activated microglial model. The VPA-induced intestinal inflammation and compromised permeability in the distal ileum was not associated with changes of PTEN expression and phosphorylation. In contrast, VPA reduced PTEN expression in the hippocampus of mice. In vitro results show that pCS and 4EPS reduced PTEN expression and derailed innate immune response of BV2 microglial cells. The PTEN inhibitor VO-OHpic did not affect innate immune response of microglial cells. In conclusion, PTEN does not play a role in intestinal inflammation and compromised permeability in VPA-induced murine model for ASD. Although pCS and 4EPS reduced PTEN expression in microglial cells, PTEN is not involved in the pCS and 4EPS-induced derailed innate immune response of microglial cells. Further studies are needed to investigate the possible involvement of reduced PTEN expression in the ASD brain regarding synapse function and neuronal connectivity.

Common targetable inflammatory pathways in brain transcriptome of autism spectrum disorders and Tourette syndrome.

Neurodevelopmental disorders (NDDs), including autism-spectrum disorders (ASD) and Tourette syndrome (TS) are common brain conditions which often co-exist, and have no approved treatments targeting disease mechanisms. Accumulating literature implicates the immune system in NDDs, and transcriptomics of post-mortem brain tissue has revealed an inflammatory signal. We interrogated two RNA-sequencing datasets of ASD and TS and identified differentially expressed genes, to explore commonly enriched pathways through GO, KEGG, and Reactome. The DEGs [False Discovery Rate (FDR) <0.05] in the ASD dataset (n = 248) and the TS dataset (n = 156) enriched pathways involving inflammation, cytokines, signal transduction and cell signalling. Of the DEGs from the ASD and TS analyses, 23 were shared, all of which were up-regulated: interaction networks of the common protein-coding genes using STRING revealed 5 central up-regulated hub genes: CCL2, ICAM1, HMOX1, MYC, and SOCS3. Applying KEGG and Reactome analysis to the 23 common genes identified pathways involving the innate immune response such as interleukin and interferon signalling pathways. These findings bring new evidence of shared immune signalling in ASD and TS brain transcriptome, to support the overlapping symptoms that individuals with these complex disorders experience.