Increased number of excitatory synapsis and decreased number of inhibitory synapsis in the prefrontal cortex in autism.

Previous studies in autism spectrum disorder demonstrated an increased number of excitatory pyramidal cells and a decreased number of inhibitory parvalbumin+ chandelier interneurons in the prefrontal cortex of postmortem brains. How these changes in cellular composition affect the overall abundance of excitatory and inhibitory synapses in the cortex is not known. Herein, we quantified the number of excitatory and inhibitory synapses in the prefrontal cortex of 10 postmortem autism spectrum disorder brains and 10 control cases. To identify excitatory synapses, we used VGlut1 as a marker of the presynaptic component and postsynaptic density protein-95 as marker of the postsynaptic component. To identify inhibitory synapses, we used the vesicular gamma-aminobutyric acid transporter as a marker of the presynaptic component and gephyrin as a marker of the postsynaptic component. We used Puncta Analyzer to quantify the number of co-localized pre- and postsynaptic synaptic components in each area of interest. We found an increase in the number of excitatory synapses in upper cortical layers and a decrease in inhibitory synapses in all cortical layers in autism spectrum disorder brains compared with control cases. The alteration in the number of excitatory and inhibitory synapses could lead to neuronal dysfunction and disturbed network connectivity in the prefrontal cortex in autism spectrum disorder.

Neuroanatomy of autism: what is the role of the cerebellum?

Autism (or autism spectrum disorder) was initially defined as a psychiatric disorder, with the likely cause maternal behavior (the very destructive "refrigerator mother" theory). It took several decades for research into brain mechanisms to become established. Both neuropathological and imaging studies found differences in the cerebellum in autism spectrum disorder, the most widely documented being a decreased density of Purkinje cells in the cerebellar cortex. The popular interpretation of these results is that cerebellar neuropathology is a critical cause of autism spectrum disorder. We challenge that view by arguing that if fewer Purkinje cells are critical for autism spectrum disorder, then any condition that causes the loss of Purkinje cells should also cause autism spectrum disorder. We will review data on damage to the cerebellum from cerebellar lesions, tumors, and several syndromes (Joubert syndrome, Fragile X, and tuberous sclerosis). Collectively, these studies raise the question of whether the cerebellum really has a role in autism spectrum disorder. Autism spectrum disorder is now recognized as a genetically caused developmental disorder. A better understanding of the genes that underlie the differences in brain development that result in autism spectrum disorder is likely to show that these genes affect the development of the cerebellum in parallel with the development of the structures that do underlie autism spectrum disorder.

Early autism diagnosis based on path signature and Siamese unsupervised feature compressor.

Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and behavioral patterns are unreliable for children younger than 2 years of age. Given evidences of neurodevelopmental abnormalities in autism spectrum disorder infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis. Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features. We also proposed weight constraints to cope with sample heterogeneity by giving different samples different voting weights during validation, and used Path Signature to unravel meaningful developmental features from the two-time point data longitudinally. We further extracted machine learning focused brain regions for autism diagnosis. Extensive experiments have shown that our method performed well under practical scenarios, transcending existing machine learning methods and providing anatomical insights for autism early diagnosis.

Female-specific dysfunction of sensory neocortical circuits in a mouse model of autism mediated by mGluR5 and estrogen receptor α.

Little is known of the brain mechanisms that mediate sex-specific autism symptoms. Here, we demonstrate that deletion of the autism spectrum disorder (ASD)-risk gene, Pten, in neocortical pyramidal neurons (NSEPten knockout [KO]) results in robust cortical circuit hyperexcitability selectively in female mice observed as prolonged spontaneous persistent activity states. Circuit hyperexcitability in females is mediated by metabotropic glutamate receptor 5 (mGluR5) and estrogen receptor α (ERα) signaling to mitogen-activated protein kinases (Erk1/2) and de novo protein synthesis. Pten KO layer 5 neurons have a female-specific increase in mGluR5 and mGluR5-dependent protein synthesis. Furthermore, mGluR5-ERα complexes are generally elevated in female cortices, and genetic reduction of ERα rescues enhanced circuit excitability, protein synthesis, and neuron size selectively in NSEPten KO females. Female NSEPten KO mice display deficits in sensory processing and social behaviors as well as mGluR5-dependent seizures. These results reveal mechanisms by which sex and a high-confidence ASD-risk gene interact to affect brain function and behavior.

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.

Effects of Fmr1 Gene Mutations on Sex Differences in Autism-Like Behavior and Dendritic Spine Development in Mice and Transcriptomic Studies.

Fragile X syndrome (FXS) is the most common single gene disorder contributing to autism spectrum disorder (ASD). Although significant sex differences are observed in FXS, few studies have focused on the phenotypic characteristics as well as the differences in brain pathological changes and gene expression in FXS by sex. Therefore, we analyzed sex differences in autism-like behavior and dendritic spine development in two-month-old male and female Fmr1 KO and C57 mice and evaluated the mechanisms at transcriptome level. Results suggest that Fmr1 KO mice display sex differences in autism-like behavior and dendritic spine density. Compared to females, male had more severe effects on anxiety, repetitive stereotype-like behaviors, and socializing, with higher dendritic spine density. Furthermore, two male-biased and five female-biased expressed genes were screened based on KEGG pathway enrichment and protein-protein interaction (PPI) analyses. In conclusion, our findings show mutations in the Fmr1 gene lead to aberrant expression of related genes and affect the sex-differentiated behavioral phenotypes of Fmr1 KO mice by affecting brain development and functional architecture, and suggest future studies should focus on including female subjects to comprehensively reflect the differentiation of FXS in both sexes and develop more precise and effective therapeutic strategies.

Prenatal SARS-CoV-2 Spike Protein Exposure Induces Autism-Like Neurobehavioral Changes in Male Neonatal Rats.

Recent research on placental, embryo, and brain organoids suggests that the COVID-19 virus may potentially affect embryonic organs, including the brain. Given the established link between SARS-CoV-2 spike protein and neuroinflammation, we sought to investigate the effects of exposure to this protein during pregnancy. We divided pregnant rats into three groups: Group 1 received a 1 ml/kg saline solution, Group 2 received 150 µg/kg adjuvant aluminum hydroxide (AAH), and Group 3 received 40 µg/kg spike protein + 150 µg/kg AAH at 10 and 14 days of gestation. On postnatal day 21 (P21), we randomly separated 60 littermates (10 male-female) into control, AAH-exposed, and spike protein-exposed groups. At P50, we conducted behavioral analyses on these mature animals and performed MR spectroscopy. Subsequently, all animals were sacrificed, and their brains were subject to biochemical and histological analysis. Our findings indicate that male rats exposed to the spike protein displayed a higher rate of impaired performance on behavioral studies, including the three-chamber social test, passive avoidance learning analysis, open field test, rotarod test, and novelty-induced cultivation behavior, indicative of autistic symptoms. Exposure to the spike protein (male) induced gliosis and neuronal cell death in the CA1-CA3 regions of the hippocampus and cerebellum. The spike protein-exposed male rats exhibited significantly greater levels of malondialdehyde (MDA), tumor necrosis factor alpha (TNF-α), interleukin-17 (IL-17), nuclear factor kappa B (NF-κB), and lactate and lower levels of brain-derived neurotrophic factor (BDNF) than the control group. Our study suggests a potential association between prenatal exposure to COVID-19 spike protein and neurodevelopmental problems, such as ASD. These findings highlight the importance of further research into the potential effects of the COVID-19 virus on embryonic and fetal development and the potential long-term consequences for neurodevelopment.

Single-cell brain organoid screening identifies developmental defects in autism.

The development of the human brain involves unique processes (not observed in many other species) that can contribute to neurodevelopmental disorders1-4. Cerebral organoids enable the study of neurodevelopmental disorders in a human context. We have developed the CRISPR-human organoids-single-cell RNA sequencing (CHOOSE) system, which uses verified pairs of guide RNAs, inducible CRISPR-Cas9-based genetic disruption and single-cell transcriptomics for pooled loss-of-function screening in mosaic organoids. Here we show that perturbation of 36 high-risk autism spectrum disorder genes related to transcriptional regulation uncovers their effects on cell fate determination. We find that dorsal intermediate progenitors, ventral progenitors and upper-layer excitatory neurons are among the most vulnerable cell types. We construct a developmental gene regulatory network of cerebral organoids from single-cell transcriptomes and chromatin modalities and identify autism spectrum disorder-associated and perturbation-enriched regulatory modules. Perturbing members of the BRG1/BRM-associated factor (BAF) chromatin remodelling complex leads to enrichment of ventral telencephalon progenitors. Specifically, mutating the BAF subunit ARID1B affects the fate transition of progenitors to oligodendrocyte and interneuron precursor cells, a phenotype that we confirmed in patient-specific induced pluripotent stem cell-derived organoids. Our study paves the way for high-throughput phenotypic characterization of disease susceptibility genes in organoid models with cell state, molecular pathway and gene regulatory network readouts.

Amelioration of cognition impairments in the valproic acid-induced animal model of autism by ciproxifan, a histamine H3-receptor antagonist.

Autism spectrum disorder is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behavior. Many studies show that the number of cognitive impairmentscan be reduced by antagonists of the histamine H3 receptor (H3R). In this study, the effects of ciproxifan (CPX) (1 and 3 mg/kg, intraperitoneally) on cognitive impairments in rat pups exposed to valproic acid (VPA) (600 mg/kg, intraperitoneally) wereexamined on postnatal day 48-50 (PND 48-50) using marble-burying task (MBT), open field, novel object recognition (NOR), and Passive avoidance tasks. Famotidine (FAM) (10, 20, and 40 mg/kg, intraperitoneally) was also used to determine whether histaminergic neurotransmission exerts its procognitive effects via H2 receptors (H2Rs). Furthermore, a histological investigation was conducted to assess the degree of degeneration of hippocampal neurons. The results revealed that repetitive behaviors increased in VPA-exposed rat offspring in the MBT. In addition, VPA-exposed rat offspring exhibited more anxiety-like behaviors in the open field than saline-treated rats. It was found that VPA-exposed rat offspring showed memory deficits in NOR and Passive avoidance tasks. Our results indicated that 3 mg/kg CPX improved cognitive impairments induced by VPA, while 20 mg/kg FAM attenuated them. We concluded that 3 mg/kg CPX improved VPA-induced cognitive impairments through H3Rs. The histological assessment showed that the number of CA1 neurons decreased in the VPA-exposed rat offspring compared to the saline-exposed rat offspring, but this decrease was not significant. The histological assessment also revealed no significant differences in CA1 neurons in VPA-exposed rat offspring compared to saline-exposed rat offspring. However, CPX3 increased the number of CA1 neurons in the VPA + CPX3 group compared to the VPA + Saline group, but this increase was not significant. This study showed that rats prenatally exposed to VPA exhibit cognitive impairments in the MBT, open field, NOR, and Passive avoidance tests, which are ameliorated by CPX treatment on PND 48-50. In addition, morphological investigations showed that VPA treatment did not lead to neuronal degeneration in the CA1 subfield of the hippocampus in rat pups.

Untargeted metabolomics reveals hepatic metabolic disorder in the BTBR mouse model of autism and the significant role of liver in autism.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, and the etiology is unknown. Metabolic dysfunction is present in patients with ASD. In the current study, untargeted metabolomics was employed to screen the differential metabolites in the liver of BTBR mouse model of autism, and MetaboAnalyst 4.0 was used for metabolic pathway analysis. Mice were killed, and liver samples were collected for untargeted metabolomics analysis and examination of histopathology. Finally, 12 differential metabolites were identified. The intensities of phenylethylamine, 4-Guanidinobutanoic acid, leukotrieneD4, and SM(d18:1/24:1(15Z)) were significantly upregulated (p < .01), and the intensities of estradiol, CMP-N-glycoloylneuraminate, retinoyl ß-glucuronide,4-phosphopantothenoylcysteine, aldophosphamide, taurochenodesoxycholic acid, taurocholic acid, and dephospho-CoA were significantly downregulated (p < .01) in the BTBR group compared with C57 control group, indicating that differences between BTBR and C57 groups were observed in metabolic patterns. Disturbed pathways of the BTBR mice involved lipid metabolism, retinol metabolism, and amino acid and energy metabolism, revealing that bile acid-mediated activation of LXRα might contribute to metabolic dysfunction of lipid and leukotriene D4 produced by the activation of 5-LOX led to hepatic inflammation. Pathological changes in the liver tissue, such as hepatocyte vacuolization, and small amounts of inflammatory and cell necrosis, further supported metabolomic results. Moreover, Spearman's rank correlation revealed that there is a strong relationship between metabolites across liver and cortex, suggesting liver may exert action by connecting peripheral and neural systems. These findings were likely to be of pathological importance or a cause/consequence of autism, and may provide insight into key metabolic dysfunction to target potential therapeutic strategies relating to ASD.

Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism.

Fiber tract segmentation is a prerequisite for tract-based statistical analysis. Brain fiber streamlines obtained by diffusion magnetic resonance imaging and tractography technology are usually difficult to be leveraged directly, thus need to be segmented into fiber tracts. Previous research mainly consists of two steps: defining and computing the similarity features of fiber streamlines, then adopting machine learning algorithms for fiber clustering or classification. Defining the similarity feature is the basic premise and determines its potential reliability and application. In this study, we adopt geometric features for fiber tract segmentation and develop a novel descriptor (FiberGeoMap) for the corresponding representation, which can effectively depict fiber streamlines' shapes and positions. FiberGeoMap can differentiate fiber tracts within the same subject, meanwhile preserving the shape and position consistency across subjects, thus can identify common fiber tracts across brains. We also proposed a Transformer-based encoder network called FiberGeoMap Learner, to perform segmentation based on the geometric features. Experimental results showed that the proposed method can differentiate the 103 various fiber tracts, which outperformed the existing methods in both the number of categories and segmentation accuracy. Furthermore, the proposed method identified some fiber tracts that were statistically different on fractional anisotropy (FA), mean diffusion (MD), and fiber number ration in autism.

Pyramidal neurons form active, transient, multilayered circuits perturbed by autism-associated mutations at the inception of neocortex.

Cortical circuits are composed predominantly of pyramidal-to-pyramidal neuron connections, yet their assembly during embryonic development is not well understood. We show that mouse embryonic Rbp4-Cre cortical neurons, transcriptomically closest to layer 5 pyramidal neurons, display two phases of circuit assembly in vivo. At E14.5, they form a multi-layered circuit motif, composed of only embryonic near-projecting-type neurons. By E17.5, this transitions to a second motif involving all three embryonic types, analogous to the three adult layer 5 types. In vivo patch clamp recordings and two-photon calcium imaging of embryonic Rbp4-Cre neurons reveal active somas and neurites, tetrodotoxin-sensitive voltage-gated conductances, and functional glutamatergic synapses, from E14.5 onwards. Embryonic Rbp4-Cre neurons strongly express autism-associated genes and perturbing these genes interferes with the switch between the two motifs. Hence, pyramidal neurons form active, transient, multi-layered pyramidal-to-pyramidal circuits at the inception of neocortex, and studying these circuits could yield insights into the etiology of autism.

Exploring the Clinical Feasibility of Alternative Word-Understanding Measures for Autistic Children With Minimal Spoken Language.

PURPOSE: The primary aim of this study was to explore the clinical feasibility of using alternate word-understanding assessment modalities for autistic children who have minimal verbal skills. Specifically, assessment duration, occurrence of disruptive behavior, and no-response trials were examined across three word-understanding assessment conditions: a low-tech condition, a touchscreen condition, and a condition that used real-object stimuli. A secondary aim was to examine the relationship between disruptive behavior and assessment outcomes. METHOD: Twenty-seven autistic children between the ages of 3 and 12 years who had minimal verbal skills completed 12 test items on the three assessment conditions. Repeated-measures analyses of variance with post hoc Bonferroni procedures were used to describe and compare assessment duration, occurrence of disruptive behavior, and no-response trials across conditions. A Spearman rank-order correlation coefficient was used to examine the relationship between disruptive behavior and assessment outcomes. RESULTS: The real-object assessment condition took significantly longer than the low-tech and touchscreen conditions. Participants engaged in disruptive behavior most frequently during the low-tech condition; however, differences among conditions were not significant. There were significantly more no-response trials in the low-tech condition than in the touchscreen condition. There was a significant, weak negative correlation between disruptive behavior and experimental assessment outcomes. CONCLUSION: Results show there is promise in using real objects and touchscreen devices to assess word understanding in autistic children who have minimal verbal skills.

Oxidative stress and neuroimmune proteins in a mouse model of autism.

Oxidative stress including decreased antioxidant enzyme activities, elevated lipid peroxidation, and accumulation of advanced glycation end products in the blood from children with autism spectrum disorders (ASD) has been reported. The mechanisms affecting the development of ASD remain unclear; however, toxic environmental exposures leading to oxidative stress have been proposed to play a significant role. The BTBRT+Itpr3tf/J (BTBR) strain provides a model to investigate the markers of oxidation in a mouse strain exhibiting ASD-like behavioral phenotypes. In the present study, we investigated the level of oxidative stress and its effects on immune cell populations, specifically oxidative stress affecting surface thiols (R-SH), intracellular glutathione (iGSH), and expression of brain biomarkers that may contribute to the development of the ASD-like phenotypes that have been observed and reported in BTBR mice. Lower levels of cell surface R-SH were detected on multiple immune cell subpopulations from blood, spleens, and lymph nodes and for sera R-SH levels of BTBR mice compared to C57BL/6 J (B6) mice. The iGSH levels of immune cell populations were also lower in the BTBR mice. Elevated protein expression of GATA3, TGM2, AhR, EPHX2, TSLP, PTEN, IRE1α, GDF15, and metallothionein in BTBR mice is supportive of an increased level of oxidative stress in BTBR mice and may underpin the pro-inflammatory immune state that has been reported in the BTBR strain. Results of a decreased antioxidant system suggest an important oxidative stress role in the development of the BTBR ASD-like phenotype.

Autism detection based on multiple time scale model.

Objective.Current autism clinical detection relies on doctor observation and filling of clinical scales, which is subjective and prone to misdetection. Existing autism research of functional magnetic resonance imaging (fMRI) over-compresses the time-scale information and has poor generalization ability. This study extracts multiple time scale brain features of fMRI, providing objective detection.Approach. We first use least absolute shrinkage and selection operator to build a sparse network and extract features with a time scale of 1. Then, we use hidden markov model to extract features that describe the dynamic changes of the brain, with a time scale of 2. Additionally, to analyze the features of the potential network activity of autism from a higher time scale, we use long short-term memory to construct an auto-encoder to re-encode the original data and extract the features at a higher time scale, with a time scale ofT, andTis the time length of fMRI. We use recursive feature elimination for feature selection for three different time scale features, merge them into multiple time scale features, and finally use one-dimensional convolution neural network for classification.Main results. Compared with well-established models, our method has achieved better results. The accuracy of our method is 76.0%, and the area under the roc curve is 0.83, tested on completely independent data, so our method has better generalization ability.Significance. This research analyzes fMRI sequences from multiple time scale to detect autism, and it also provides a new framework and research ideas for subsequent fMRI analysis.

SARM1 deletion in parvalbumin neurons is associated with autism-like behaviors in mice.

Autism spectrum disorder (ASD), a group of neurodevelopmental disorder diseases, is characterized by social deficits, communication difficulties, and repetitive behaviors. Sterile alpha and TIR motif-containing 1 protein (SARM1) is known as an autism-associated protein and is enriched in brain tissue. Moreover, SARM1 knockdown mice exhibit autism-like behaviors. However, its specific mechanism in ASD pathogenesis remains unclear. Here we generated parvalbumin-positive interneurons (PVI)-specific conditional SARM1 knockout (SARM1PV-CKO) mice. SARM1PV-CKO male mice showed autism-like behaviors, such as mild social interaction deficits and repetitive behaviors. Moreover, we found that the expression level of parvalbumin was reduced in SARM1PV-CKO male mice, together with upregulated apoptosis-related proteins and more cleaved-caspase-3-positive PVIs, suggesting that knocking out SARM1 may cause a reduction in the number of PVIs due to apoptosis. Furthermore, the expression of c-fos was shown to increase in SARM1PV-CKO male mice, in combination with upregulation of excitatory postsynaptic proteins such as PSD-95 or neuroligin-1, indicating enhanced excitatory synaptic input in mutant mice. This notion was further supported by the partial rescue of autism-like behavior deficits by the administration of GABA receptor agonists in SARM1PV-CKO male mice. In conclusion, our findings suggest that SARM1 deficiency in PVIs may be involved in the pathogenesis of ASD.

White matter microstructural and morphometric alterations in autism: implications for intellectual capabilities.

BACKGROUND: Neuroimage literature of autism spectrum disorder (ASD) has a moderate-to-high risk of bias, partially because those combined with intellectual impairment (II) and/or minimally verbal (MV) status are generally ignored. We aimed to provide more comprehensive insights into white matter alterations of ASD, inclusive of individuals with II (ASD-II-Only) or MV expression (ASD-MV). METHODS: Sixty-five participants with ASD (ASD-Whole; 16.6 ± 5.9 years; comprising 34 intellectually able youth, ASD-IA, and 31 intellectually impaired youth, ASD-II, including 24 ASD-II-Only plus 7 ASD-MV) and 38 demographic-matched typically developing controls (TDC; 17.3 ± 5.6 years) were scanned in accelerated diffusion-weighted MRI. Fixel-based analysis was undertaken to investigate the categorical differences in fiber density (FD), fiber cross section (FC), and a combined index (FDC), and brain symptom/cognition associations. RESULTS: ASD-Whole had reduced FD in the anterior and posterior corpus callosum and left cerebellum Crus I, and smaller FDC in right cerebellum Crus II, compared to TDC. ASD-IA, relative to TDC, had no significant discrepancies, while ASD-II showed almost identical alterations to those from ASD-Whole vs. TDC. ASD-II-Only had greater FD/FDC in the isthmus splenium of callosum than ASD-MV. Autistic severity negatively correlated with FC in right Crus I. Nonverbal full-scale IQ positively correlated with FC/FDC in cerebellum VI. FD/FDC of the right dorsolateral prefrontal cortex showed a diagnosis-by-executive function interaction. LIMITATIONS: We could not preclude the potential effects of age and sex from the ASD cohort, although statistical tests suggested that these factors were not influential. Our results could be confounded by variable psychiatric comorbidities and psychotropic medication uses in our ASD participants recruited from outpatient clinics, which is nevertheless closer to a real-world presentation of ASD. The outcomes related to ASD-MV were considered preliminaries due to the small sample size within this subgroup. Finally, our study design did not include intellectual impairment-only participants without ASD to disentangle the mixture of autistic and intellectual symptoms. CONCLUSIONS: ASD-associated white matter alterations appear driven by individuals with II and potentially further by MV. Results suggest that changes in the corpus callosum and cerebellum are key for psychopathology and cognition associated with ASD. Our work highlights an essential to include understudied subpopulations on the spectrum in research.

Frontotemporal neurofibrillary tangles and cerebrovascular lesions are associated with autism spectrum behaviors in late-life dementia.

BACKGROUND AND OBJECTIVES: The pathologic substrates or neuroanatomic regions responsible for similarities in behavioral features seen in autism spectrum disorder and late-life dementia remain unknown. The present study examined the neuropathologic features of late-life dementia in research volunteers with and without antemortem behaviors characteristic of autism spectrum disorders. METHODS: Antemortem cross-sectional assessment of autistic spectrum behaviors proximal to death in persons with diagnosis of mild cognitive impairment or dementia was completed using the Gilliam Autism Rating Scale, 2nd edition (GARS-2), followed by postmortem quantitative and semiquantitative neuropathologic assessment. All individuals who completed the GARS-2 prior to autopsy were included (n = 56) and we note that no participants had known diagnosis of autism spectrum disorder. The GARS-2 was used as an antemortem screening tool to stratify participants into two groups: "Autism Possible/Very Likely" or "Autism Unlikely." Data were analyzed using nonparametric statistics comparing location and scale to evaluate between-group differences in pathologic features. RESULTS: Neurofibrillary tangles (NFT; p = 0.028) density and tau burden (p = 0.032) in the frontal region, the NFT density (p = 0.048) and neuritic plaque burden (p = 0.042), and the tau burden (p = 0.032) of the temporal region, were significantly different in scale between groups. For measures with significant group differences, the medians of the Autism Possible/Very Likely group were roughly equal to the 75th percentile of the Autism Unlikely group (i.e., the distributions were shifted to the right). DISCUSSION: This study links behaviors characteristic of autism to increased pathologic tau burden in the frontal and temporal lobes in persons with late-life dementia. Additional studies are needed to determine causal factors and treatment options for behaviors characteristic of autism behaviors in late-life dementias.

Postnatal baicalin ameliorates behavioral and neurochemical alterations in valproic acid-induced rodent model of autism: The possible implication of sirtuin-1/mitofusin-2/ Bcl-2 pathway.

Autism spectrum disorder (ASD) is characterized by pervasive impairments in social communication along with repetitive or stereotyped behaviors. Although its distinctive etiology isn`t completely understood, genetic and environmental risk factors were incriminated. Being a flavonoid of high biomedical value, baicalin was recently verified as an emerging medicinal herb with numerous pharmacological activities. The objective of this study was to investigate the feasible effects of baicalin on valproic acid (VPA)-induced autism regarding its potential mitochondrial modulatory, antioxidant, and antiapoptotic effects. The present study was performed using a rodent model of autism by exposing rat fetuses to VPA on the 12.5th day of gestation. Ten male Wistar rats that were born from control pregnant females were considered as group I (control group). Twenty male Wistar rats that were born from prenatal VPA- treated females were further divided into two groups: Group II (VPA- induced ASD) and group III (VPA + Baicalin). Postnatal baicalin promoted postnatal growth and maturation. In addition, it improved motor development and ameliorated repetitive behavior as well as social deficits in prenatally exposed VPA rats. Moreover, baicalin enhanced neuronal mitochondrial functions as evidenced by elevation of mitochondrial adenosine triphosphate (ATP) level and promotion of mitofusin-2 expression. Furthermore, baicalin elevated sirtuin-1 (SIRT1) level in VPA rats' brain tissues and restored the antioxidant defense mechanisms. Besides, it abrogated the neuronal histopathological changes in the brain tissues. Based on the data herein, baicalin may provide a promising pre-clinical therapeutic line in ASD as a mitochondrial function modulator, antioxidant and anti-apoptotic agent.

Differences in functional brain organization during gesture recognition between autistic and neurotypical individuals.

Persons with and without autism process sensory information differently. Differences in sensory processing are directly relevant to social functioning and communicative abilities, which are known to be hampered in persons with autism. We collected functional magnetic resonance imaging data from 25 autistic individuals and 25 neurotypical individuals while they performed a silent gesture recognition task. We exploited brain network topology, a holistic quantification of how networks within the brain are organized to provide new insights into how visual communicative signals are processed in autistic and neurotypical individuals. Performing graph theoretical analysis, we calculated two network properties of the action observation network: 'local efficiency', as a measure of network segregation, and 'global efficiency', as a measure of network integration. We found that persons with autism and neurotypical persons differ in how the action observation network is organized. Persons with autism utilize a more clustered, local-processing-oriented network configuration (i.e. higher local efficiency) rather than the more integrative network organization seen in neurotypicals (i.e. higher global efficiency). These results shed new light on the complex interplay between social and sensory processing in autism.