Dissociations of cerebral cortex, subcortical and cerebral white matter volumes in autistic boys

Review of structural neuroimaging and genetic findings in autism spectrum disorder - a clinical perspective

Autism spectrum disorders (ASDs) are neurodevelopmental conditions characterized by deficits in social relationships and communication and restrictive, repetitive behaviors and interests. ASDs form a heterogeneous group from a clinical and genetic perspective. Currently, ASDs diagnosis is based on the clinical observation of the individual's behavior. The subjective nature of behavioral diagnoses, in the context of ASDs heterogeneity, contributes to significant variation in the age at ASD diagnosis. Early detection has been proved to be critical in ASDs, as early start of appropriate therapeutic interventions greatly improve the outcome for some children. Structural magnetic resonance imaging (MRI) is widely used in the diagnostic work-up of neurodevelopmental conditions, including ASDs, mostly for brain malformations detection. Recently, the focus of brain imaging shifted towards quantitative MRI parameters, aiming to identify subtle changes that may establish early detection biomarkers. ASDs have a strong genetic component; deletions and duplications of several genomic loci have been strongly associated with ASDs risk. Consequently, a multitude of neuroimaging and genetic findings emerged in ASDs in the recent years. The association of gross or subtle changes in brain morphometry and volumes with different genetic defects has the potential to bring new insights regarding normal development and pathomechanisms of various disorders affecting the brain. Still, the clinical implications of these discoveries and the impact of genetic abnormalities on brain structure and function are unclear. Here we review the literature on brain imaging correlated with the most prevalent genomic imbalances in ASD, and discuss the potential clinical impact.

Volumetric alterations in the basal ganglia in autism Spectrum disorder: A systematic review

INTRODUCTION

Recent research indicates that some brain structures show alterations in conditions such as Autism Spectrum Disorder (ASD). Among them, are the basal ganglia that are involved in motor, cognitive and behavioral neural circuits.

OBJECTIVE

Review the literature that describes possible volumetric alterations in the basal ganglia of individuals with ASD and the impacts that these changes have on the severity of the condition.

METHODOLOGY

This systematic review was registered in the design and reported according to the PRISMA Items and registered in PROSPERO (CRD42023394787). The study analyzed data from published clinical, case-contemplate, and cohort trials. The following databases were consulted: PubMed, Embase, Scopus, and Cochrane Central Register of Controlled Trials, using the Medical Subject Titles (MeSH) "Autism Spectrum Disorder" and "Basal Ganglia". The last search was carried out on February 28, 2023.

RESULTS

Thirty-five eligible articles were collected, analyzed, and grouped according to the levels of alterations.

CONCLUSION

The present study showed important volumetric alterations in the basal ganglia in ASD. However, the examined studies have methodological weaknesses that do not allow generalization and correlation with ASD manifestations.

Whole-brain gray matter maturation trajectories associated with autistic traits from adolescence to early adulthood

A growing number of evidence supports a continued distribution of autistic traits in the general population. However, brain maturation trajectories of autistic traits as well as the influence of sex on these trajectories remain largely unknown. We investigated the association of autistic traits in the general population, with longitudinal gray matter (GM) maturation trajectories during the critical period of adolescence. We assessed 709 community-based adolescents (54.7% women) at age 14 and 22. After testing the effect of sex, we used whole-brain voxel-based morphometry to measure longitudinal GM volumes changes associated with autistic traits measured by the Social Responsiveness Scale (SRS) total and sub-scores. In women, we observed that the SRS was associated with slower GM volume decrease globally and in the left parahippocampus and middle temporal gyrus. The social communication sub-score correlated with slower GM volume decrease in the left parahippocampal, superior temporal gyrus, and pallidum; and the social cognition sub-score correlated with slower GM volume decrease in the left middle temporal gyrus, the right ventromedial prefrontal and orbitofrontal cortex. No longitudinal association was found in men. Autistic traits in young women were found to be associated with specific brain trajectories in regions of the social brain and the reward circuit known to be involved in Autism Spectrum Disorder. These findings support both the hypothesis of an earlier GM maturation associated with autistic traits in adolescence and of protective mechanisms in women. They advocate for further studies on brain trajectories associated with autistic traits in women.

Impaired white matter integrity in infants and young children with autism spectrum disorder: What evidence does diffusion tensor imaging provide?

BACKGROUND

Abnormal functional connections are associated with impaired white matter tract integrity in the brain. Diffusion tensor imaging (DTI) is a promising method for evaluating white matter integrity in infants and young children. This work aims to shed light on the location and nature of the decrease in white matter integrity.

METHODS

Here, the results of 19 studies have been presented that investigated white matter integrity in infants and young children (6 months to 12 years) with autism using diffusion tensor imaging.

RESULTS

In most of the reviewed studies, an increase in Fractional Anisotropy (FA) and a decrease in Radial Diffusivity (RD) were reported in Corpus Callosum (CC), Uncinate Fasciculus (UF), Cingulum (Cg), Inferior Longitudinal Fasciculus (ILF), and Superior Longitudinal Fasciculus (SLF), and in the Inferior Fronto-Occipital Fasciculus (IFOF) tract, a decrease in FA and an increase in RD were reported.

CONCLUSION

In the reviewed articles, except for one study, the diffusion indices were different compared to the control group.

Prefrontal Functional Connectivities in Autism Spectrum Disorders: A Connectopathic Disorder Affecting Movement, Interoception, and Cognition

The prefrontal cortex is included in a neuronal system that includes the basal ganglia, the thalamus, and the cerebellum. Most of the higher and more complex motor, cognitive, and emotional behavioral functions are thought to be found primarily in the frontal lobes. Insufficient connectivity between the medial prefrontal cortex (mPFC) and other regions of the brain that are distant from each other involved in top-down information processing rely on the global integration of data from multiple input sources and enhance low level perception processes (bottom-up information processing). The reduced deactivation in mPFC and in the rest of the Default Network during global task processing is consistent with the integrative modulatory role served by the mPFC. We stress the importance of understanding the degree to which sensory and movement anomalies in individuals with autism spectrum disorder (ASD) can contribute to social impairment. Further investigation on the neurobiological basis of sensory symptoms and its relationship to other clinical features found in ASD is required Treatment perhaps should not be first behaviorally based but rather based on facilitating sensory motor development.

Atorvastatin Improves the Propionic Acid-Induced Autism in Rats: The Roles of Sphingosine-1-Phosphate and Anti-inflammatory Action

Purpose The aim of this study is to investigate the benefits of atorvastatin on the propionic acid-induced autism model via increasing sphingosine-1-phosphate and anti-inflammatory actions with imaging and brain tissue investigations. Materials and methods Twenty-five mg/kg/day/rat of propionic acid (PPA) was administered intraperitoneally to 20 male Wistar rats, and 10 male Wistar rats were fed orally. Study groups were designed as follows: Group 1: Control Group (orally fed control, n=10); Group 2 (PPA+saline, n=10); Group 3 (PPA+Atorvastatin, n=10). The brain biochemical and histopathology assessments and magnetic resonance (MR) imaging were conducted across groups in order to compare them. Results The PPA+Atorvastatin group was found to have significantly lower levels of brain malondialdehyde, IL-2 level, IL-17, tumor necrosis factor-alpha (TNF-α), and lactate compared to the PPA+saline group. The PPA+Atorvastatin group had higher levels of nerve growth factor and nuclear factor erythroid 2-related factor 2 (NRF-2) and sphingosine-1-phosphate. In histopathology assessments, the PPA+Atorvastatin group was found to have significantly higher neuronal counts of CA1 and CA2 in the hippocampus, and Purkinje cells in the cerebellum. Conclusions Current findings suggest that atorvastatin increases sphingosine-1-phosphate levels and decreases inflammatory actions which characterize the autism rodent model implemented in this study. These preliminary results have to be confirmed by further experimental and clinical studies.

The Coexistence of Antibodies to Neuronal Cell and Synaptic Receptor Proteins, Gangliosides and Selected Neurotropic Pathogens in Neurologic Disorders in Children

Various primarily non-autoimmune neurological disorders occur synchronously with autoantibodies against tissues in the nervous system. We aimed to assess serum and cerebrospinal fluid (CSF) autoantibodies in children with neurologic disorders. To find new diagnostic tools, we compared the laboratory and clinical findings between the distinguished groups. Retrospectively, 508 patients were divided into six subgroups: neuroinfections, pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections, neurologic autoimmune and demyelinating diseases, epilepsy, pervasive developmental disorders and other patients. We analysed serum anti-aquaporin-4, antiganglioside, neuronal antinuclear and cytoplasmic antibodies, as well as antibodies against surface neuronal and synaptic antigens in the CSF and serum. We involved available demographic and clinical data. Autoantibodies appeared in 165 (32.3%) children, with 24 showing multiple types of them. The most common were anti-neuroendothelium (anti-NET), anti-N-Methyl-D-Aspartate receptor (anti-NMDAr), anti-glial fibrillary acidic protein and anti-myelin antibodies bothering 46/463 (9.9%), 32/343 (9.4%), 27/463 (5.8%) and 27/463 (5.8%), respectively. Anti-NET and anti-NMDAr antibodies appeared more frequently in children with autoimmunity (p = 0.017; p < 0.001, respectively), increasing the autoimmune disease risk (OR = 2.18, 95% CI 1.13–13.97; OR = 3.91, 95% CI 1.86–8.22, respectively). Similar pathomechanisms appeared in diseases of different aetiology with clinical spectrums mimicking each other, so we proposed the model helping to diagnose autoimmune disease. We proved the influence of age, living place and medical history on the final diagnosis.

Review of Progress in Diagnostic Studies of Autism Spectrum Disorder Using Neuroimaging

This review article summarizes the recent advances in the diagnostic studies of autism spectrum disorders (ASDs) considering some of the most influential research articles from the last two decades. ASD is a heterogeneous neurodevelopmental disorder characterized by abnormalities in social interaction, communication, and behavioral patterns as well as some unique strengths and differences. The current diagnosis systems are based on autism diagnostic observation schedule (ADOS) or autism diagnostic interview-revised (ADI-R), but biological markers are also important for an effective diagnosis of ASDs. The amalgamation of neuroimaging techniques, such as structural and functional magnetic resonance imaging (sMRI and fMRI), with machine-learning and deep-learning approaches helps throw new light on typical biological markers of ASDs at the early stage of life. To assess the performance of a deep neural network, we develop a light-weighted CNN model for ASD classification. The overall accuracy, precision, and F1-score of the proposed model are 99.92%, 99.93% and 99.92%, respectively. All the neuroimaging studies we have reviewed can be divided into 3 categories, viz. thickness, volume and functional connectivity-based studies. We conclude with a discussion of the major findings of considered studies and promising directions for future research in this field.

Circular RNAs: New players involved in the regulation of cognition and cognitive diseases

Circular RNAs (circRNAs), a type of covalently closed endogenous single-stranded RNA, have been regarded as the byproducts of the aberrant splicing of genes without any biological functions. Recently, with the development of high-throughput sequencing and bioinformatics, thousands of circRNAs and their differential biological functions have been identified. Except for the great advances in identifying circRNA roles in tumor progression, diagnosis, and treatment, accumulated evidence shows that circRNAs are enriched in the brain, especially in the synapse, and dynamically change with the development or aging of organisms. Because of the specific roles of synapses in higher-order cognitive functions, circRNAs may not only participate in cognitive functions in normal physiological conditions but also lead to cognition-related diseases after abnormal regulation of their expression or location. Thus, in this review, we summarized the progress of studies looking at the role of circRNA in cognitive function, as well as their involvement in the occurrence, development, prognosis, and treatment of cognitive-related diseases, including autism, depression, and Alzheimer's diseases.

Lopez S, Amodeo DA. Impact of specific serotonin receptor modulation on restricted repetitive behaviors

Restricted, repetitive behaviors (RRBs) are commonly divided into two behavioral categories, lower-order and higher-order RRBs. Individuals displaying lower-order motoric RRBs may express repetitive hand flapping behaviors, body rocking back and forth movements, and continuous body spinning. Higher-order RRBs most commonly cover the behavior inflexibility and cognitive rigidity commonly found in disorders such as autism spectrum disorder and obsessive-compulsive disorder. Various neuropsychiatric disorders are plagued by RRBs yet no FDA-approved treatments have been identified. In rodents, lower-order RRBs are commonly measured through various tasks, such as repetitive self-grooming, marble burying, and stereotypic motor behaviors. This review focuses on the effects that modulation of specific serotonin receptors have on lower-order RRBs. Although there is research examining how changes in 5-HT1A, 5-HT1B, 5-HT2A, 5-HT2B, 5-HT2C, 5-HT3, 5-HT6, and 5-HT7 receptor modulation, more research has focused on the 5-HT1A, 5-HT2A, and 5-HT2C receptors. The accumulating data suggest that increasing 5-HT1A activation decreases RRBs while blocking 5-HT1A activation has no effect on RRBs. While there are mixed findings regarding the impact of 5-HT2A modulation on RRBs, the general trend shows mixed effects of 5-HT2A receptor activation RRB expression, whereas blockade generally decreases RRBs. 5-HT2C receptor activation can modulate RRBs in either direction depending on the 5-HT2C drug used, blocking 5-HT2C activation only seems to show therapeutic properties when 5-HT2C activation is already elevated. The other 5-HT receptors have been explored far less but show promise as potential targets for regulating RRBs. Although it is less clear due to the involvement of 5-HT1D, 5-HT1A activation increases RRBs, and blocking 5-HT1A tends to decrease RRBs. 5-HT2B activation could reduce RRBs, while inhibiting 5-HT2B does not impact RRBs. Increasing 5-HT3 has not been shown to affect RRBs. Yet, increases in RRBs have been observed in Htr3a KO mice. 5-HT6 receptor activation can increase RRBs, while blocking 5-HT6 activity tends to decrease RRBs. Lastly, neither increasing or blocking 5-HT7 activity can reduce RRBs. In sum, there is no uniform pattern in whether all specific 5-HT receptors affect RRBs in either direction, instead, there is evidence suggesting that different 5-HT receptors can modulate RRBs in different directions. Further researching the less explored receptors and aiming to understand why these receptors can differently modulate RRBs, may play a key role in developing therapeutics that treat RRBs.

Translating neuroimaging changes to neuro-endophenotypes of autistic spectrum disorder: a narrative review

Background

Autism-spectrum disorder is a neurodevelopmental disorder with heterogeneity in etiopathogenesis and clinical presentation. Neuroanatomical and neurophysiological abnormalities may represent neural endophenotypes for autism spectrum disorders which may help identify subgroups of patients seemingly similar in clinical presentation yet different in their pathophysiological underpinnings. Furthermore, a thorough understanding of the pathophysiology of disease can pave the way to effective treatments, prevention, and prognostic predictions. The aim of this review is to identify the predominant neural endophenotypes in autism-spectrum disorder. The evidence was researched at the following electronic databases: Pubmed, PsycINFO, Scopus, Web of Science, and EMBASE.

Results

Enlarged brain, especially frontotemporal cortices have been consistently reported by structural neuroimaging, whereas functional neuroimaging has revealed frontotemporal dysconnectivity.

Conclusions

Regrettably, many of these findings have not been consistent. Therefore, translating these findings into neural endophenotype is by far an attempt in its budding stage. The structural and functional neuroimaging changes may represent neural endophenotypes unique to autism-spectrum disorder. Despite inconsistent results, a clinically meaningful finding may require combined efforts of autism-spectrum-disorder researchers focused on different aspects of basic, genetic, neuroimaging, and clinical research.

Evaluation of brain structure abnormalities in children with autism spectrum disorder (ASD) using structural magnetic resonance imaging

Background

Autism spectrum disorder (ASD) is a group of developmental disorders of the nervous system. Since the core cause of many of the symptoms of autism spectrum disorder is due to changes in the structure of the brain, the importance of examining the structural abnormalities of the brain in these disorder becomes apparent. The aim of this study is evaluation of brain structure abnormalities in children with autism spectrum disorder (ASD) using structural magnetic resonance imaging (sMRI). sMRI images of 26 autistic and 26 Healthy control subjects in the range of 5–10 years are selected from the ABIDE database. For a better assessment of structural abnormalities, the surface and volume features are extracted together from this images. Then, the extracted features from both groups were compared with the sample t test and the features with significant differences between the two groups were identified.

Results

The results of volume-based features indicate an increase in total brain volume and white matter and a change in white and gray matter volume in brain regions of Hammers atlas in the autism group. In addition, the results of surface-based features indicate an increase in mean and standard deviation of cerebral cortex thickness and changes in cerebral cortex thickness, sulcus depth, surface complexity and gyrification index in the brain regions of the Desikan–Killany cortical atlas.

Conclusions

Identifying structurally abnormal areas of the brain and examining their relationship to the clinical features of Autism Spectrum Disorder can pave the way for the correct and early detection of this disorder using structural magnetic resonance imaging. It is also possible to design treatment for autistic people based on the abnormal areas of the brain, and to see the effectiveness of the treatment using imaging.

HOA2.0-ComPaRe: A next generation Harvard-Oxford Atlas comparative parcellation reasoning method for human and macaque individual brain parcellation and atlases of the cerebral cortex

Comparative structural neuroanatomy is a cornerstone for understanding human brain structure and function. A parcellation framework that relates systematically to fundamental principles of histological organization is an essential step in generating structural comparisons between species. In the present investigation, we developed a comparative parcellation reasoning system (ComPaRe), which is a formal ontological system in human and non-human primate brains based on the cortical cytoarchitectonic mapping used for both species as detailed by Brodmann. ComPaRe provides a theoretical foundation for mapping neural systems in humans and other species using neuroimaging. Based on this approach, we revised the methodology of the original Harvard-Oxford Atlas (HOA) system of brain parcellation to produce a comparative framework for the human (hHOA) and the rhesus monkey (mHOA) brains, which we refer to as HOA2.0-ComPaRe. In addition, we used dedicated segmentation software in the publicly available 3D Slicer platform to parcellate an individual human and rhesus monkey brain. This method produces quantitative morphometric parcellations in the individual brains. Based on these parcellations we created a representative template and 3D brain atlas for the two species, each based on a single subject. Thus, HOA2.0-ComPaRe provides a theoretical foundation for mapping neural systems in humans and other species using neuroimaging, while also representing a significant revision of the original human and macaque monkey HOA parcellation schemas. The methodology and atlases presented here can be used in basic and clinical neuroimaging for morphometric (volumetric) analysis, further generation of atlases, as well as localization of function and structural lesions.

Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach

Magnetic resonance imaging (MRI)-based brain segmentation has recently been revolutionized by deep learning methods. These methods use large numbers of annotated segmentations to train algorithms that have the potential to perform brain segmentations reliably and quickly. However, training data for these algorithms are frequently obtained from automated brain segmentation systems, which may contain inaccurate neuroanatomy. Thus, the neuroimaging community would benefit from an open source database of high quality, neuroanatomically curated and manually edited MRI brain images, as well as the publicly available tools and detailed procedures for generating these curated data. Manual segmentation approaches are regarded as the gold standard for brain segmentation and parcellation. These approaches underpin the construction of neuroanatomically accurate human brain atlases. In addition, neuroanatomically precise definitions of MRI-based regions of interest (ROIs) derived from manual brain segmentation are essential for accuracy in structural connectivity studies and in surgical planning for procedures such as deep brain stimulation. However, manual segmentation procedures are time and labor intensive, and not practical in studies utilizing very large datasets, large cohorts, or multimodal imaging. Automated segmentation methods were developed to overcome these issues, and provide high data throughput, increased reliability, and multimodal imaging capability. These methods utilize manually labeled brain atlases to automatically parcellate the brain into different ROIs, but do not have the anatomical accuracy of skilled manual segmentation approaches. In the present study, we developed a custom software module for manual editing of brain structures in the freely available 3D Slicer software platform that employs principles and tools based on pioneering work from the Center for Morphometric Analysis (CMA) at Massachusetts General Hospital. We used these novel 3D Slicer segmentation tools and techniques in conjunction with well-established neuroanatomical definitions of subcortical brain structures to manually segment 50 high resolution T1w MRI brains from the Human Connectome Project (HCP) Young Adult database. The structural definitions used herein are associated with specific neuroanatomical ontologies to systematically interrelate histological and MRI-based morphometric definitions. The resulting brain datasets are publicly available and will provide the basis for a larger database of anatomically curated brains as an open science resource.

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence

BACKGROUND

Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14-15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16-17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = -0.181, r = -0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = -0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = -0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic-striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals.

Regional homogeneity of adolescents with high-functioning autism spectrum disorder and its association with symptom severity

BACKGROUND AND PURPOSE

Previous studies have revealed abnormal regional homogeneity (ReHo) in individuals with autism spectrum disorder (ASD); however, there is little consistency across the findings within these studies, partly due to small sample size and great heterogeneity among participants between studies. Additionally, few studies have explored the association between ReHo aberrance and clinical symptoms in individuals with ASD.

METHODS

Forty-eight adolescents with high-functioning ASD and 63 group-matched typically developing (TD) controls received functional magnetic resonance imaging at rest. Group-level analysis was performed to detect differences in ReHo between ASD and TD. Evaluation of symptom severity in individuals with ASD was based on the Autism Behavior Checklist (ABC). Voxel-wise correlation analysis was undergone to examine the correlations between the symptom severity and ReHo map in individuals with ASD within brain areas with ReHo abnormalities.

RESULTS

Compared with the TD controls, individuals with ASD exhibited increased ReHo in the bilateral anterior cingulate cortex, left caudate, right posterior cerebellum (cerebellar tonsil), and bilateral brainstem and decreased ReHo in the left precentral gyrus, left inferior parietal lobule, bilateral postcentral gyrus, and right anterior cerebellum (culmen). The correlation analysis indicated that the ReHo value in the brainstem was negatively associated with the ABC total scores and the scores of Relating factor, respectively.

CONCLUSIONS

Our findings indicated that widespread ReHo abnormalities occurred in ASD, shedding light on the underlying neurobiology of pathogenesis and symptomatology of ASD.

Two neuroanatomical subtypes of males with autism spectrum disorder revealed using semi-supervised machine learning

Background

Clinical and etiological varieties remain major obstacles to decompose heterogeneity in autism spectrum disorders (ASD). Recently, neuroimaging raised new hope to identify neurosubtypes of ASD for further understanding the biological mechanisms behind the disorder.

Methods

In this study, brain structural MRI data and clinical measures of 221 male subjects with ASD and 257 healthy controls were selected from 7 independent sites from the Autism Brain Image Data Exchange database (ABIDE). Heterogeneity through discriminative analysis (HYDRA), a recently-proposed semi-supervised clustering method was utilized to divide individuals with ASD into several neurosubtypes by regional volumetric measures of gray matter, white matter, and cerebrospinal fluid. Voxel-wise volume, clinical measures, dynamic resting-state functional magnetic resonance imaging (R-fMRI) measures among different neurosubtypes of ASD were explored. In addition, support vector machine (SVM) model was applied to test whether the neurosubtyping of ASD could improve diagnostic accuracy of ASD.

Results

Two neurosubtypes of ASD with different voxel-wise volumetric patterns were revealed. The full-scale intelligence quotient (IQ), verbal IQ, Autism Diagnostic Observation Schedule (ADOS) total scores and ADOS severity scores were significantly different between the two neurosubtypes, the total intracranial volume was correlated with performance IQ in Subtype 1 and was correlated with ADOS communication score and ADOS social score in Subtype 2. Compared with Subtype 2, Subtype 1 showed lower dynamic R-fMRI measures, lower dynamic functional architecture stability, higher mean and lower standard deviation (SD) of concordance among dynamic R-fMRI measures in cerebellum. In addition, classification accuracies between ASD neurosubtypes and healthy controls were significantly improved compared with classification accuracy between entire ASD group and healthy controls.

Limitations

The present study excluded female subjects and left-handed subjects, which limited the ability to investigate the associations between these factors and the heterogeneity of ASD.

Conclusions

The two distinct neuroanatomical subtypes of ASD validated by other data modalities not only adds reliability of the result, but also bridges from brain phenomenology to clinical behavior. The current neurosubtypes of ASD could facilitate understanding the neuropathology of this disorder and could be potentially used to improve clinical decision-making process and optimize treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00489-3.

Developmental brain structural atypicalities in autism: a voxel-based morphometry analysis

BACKGROUND

Structural magnetic resonance imaging (sMRI) studies have shown atypicalities in structural brain changes in individuals with autism spectrum disorder (ASD), while a noticeable discrepancy in their results indicates the necessity of conducting further researches.

METHODS

The current study investigated the atypical structural brain features of autistic individuals who aged 6-30 years old. A total of 52 autistic individuals and 50 age-, gender-, and intelligence quotient (IQ)-matched typically developing (TD) individuals were included in this study, and were assigned into three based cohorts: childhood (6-12 years old), adolescence (13-18 years old), and adulthood (19-30 years old). Analyses of whole-brain volume and voxel-based morphometry (VBM) on the sMRI data were conducted.

RESULTS

No significant difference was found in the volumes of whole-brain, gray matter, and white matter between the autism and TD groups in the three age-based cohorts. For VBM analyses, the volumes of gray matter in the right superior temporal gyrus and right inferior parietal lobule in the autism group (6-12 years old) were smaller than those in the TD group; the gray matter volume in the left inferior parietal lobule in the autism group (13-18 years old) was larger than that in the TD group; the gray matter volume in the right middle occipital gyrus in the autism group (19-30 years old) was larger than that in the TD group, and the gray matter volume in the left posterior cingulate gyrus in the autism group was smaller than that in the TD group.

CONCLUSION

Autistic individuals showed different atypical regional gray matter volumetric changes in childhood, adolescence, and adulthood compared to their TD peers, indicating that it is essential to consider developmental stages of the brain when exploring brain structural atypicalities in autism.

Atypically high influence of subcortical activity on primary sensory regions in autism

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The age-dependent decrease of subcortico-cortical connectivity is attenuated in ASD.

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Primary sensory regions remain less segregated from subcortical activity in ASD.

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This could underlie an excessive amount of sensory input relayed to the cortex.

Background

Hypersensitivity, stereotyped behaviors and attentional problems in autism spectrum disorder (ASD) are compatible with inefficient filtering of undesired or irrelevant sensory information at early stages of neural processing. This could stem from the persistent overconnectivity between primary sensory regions and deep brain nuclei in both children and adults with ASD – as reported by several previous studies – which could reflect a decreased or arrested maturation of brain connectivity. However, it has not yet been investigated whether this overconnectivity can be modelled as an excessive directional influence of subcortical brain activity on primary sensory cortical regions in ASD, with respect to age-matched typically developing (TD) individuals.

Methods

To this aim, we used dynamic causal modelling to estimate (1) the directional influence of subcortical activity on cortical processing and (2) the functional segregation of primary sensory cortical regions from subcortical activity in 166 participants with ASD and 193 TD participants from the Autism Brain Imaging Data Exchange (ABIDE). We then specifically tested the hypothesis that the age-related changes of these indicators of brain connectivity would differ between the two groups.

Results

We found that in TD participants age was significantly associated with decreased influence of subcortical activity on cortical processing, paralleled by an increased functional segregation of cortical sensory processing from subcortical activity. Instead these effects were highly reduced and mostly absent in ASD participants, suggesting a delayed or arrested development of the segregation between subcortical and cortical sensory processing in ASD.

Conclusion

This atypical configuration of subcortico-cortical connectivity in ASD can result in an excessive amount of unprocessed sensory input relayed to the cortex, which is likely to impact cognitive functioning in everyday situations where it is beneficial to limit the influence of basic sensory information on cognitive processing, such as activities requiring focused attention or social interactions.

Pten haploinsufficiency causes desynchronized growth of brain areas involved in sensory processing

How changes in brain scaling relate to altered behavior is an important question in neurodevelopmental disorder research. Mice with germline Pten haploinsufficiency (Pten ^+/-) closely mirror the abnormal brain scaling and behavioral deficits seen in humans with macrocephaly/autism syndrome, which is caused by PTEN mutations. We explored whether deviation from normal patterns of growth can predict behavioral abnormalities. Brain regions associated with sensory processing (e.g., pons and inferior colliculus) had the biggest deviations from expected volume. While Pten ^+/- mice showed little or no abnormal behavior on most assays, both sexes showed sensory deficits, including impaired sensorimotor gating and hyporeactivity to high-intensity stimuli. Developmental analysis of this phenotype showed sexual dimorphism for hyporeactivity. Mapping behavioral phenotypes of Pten ^+/- mice onto relevant brain regions suggested abnormal behavior is likely when associated with relatively enlarged brain regions, while unchanged or relatively decreased brain regions have little predictive value.

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

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

Cerebellar Transcranial Direct Current Stimulation in Children with Autism Spectrum Disorder: A Pilot Study on Efficacy, Feasibility, Safety, and Unexpected Outcomes in Tic Disorder and Epilepsy

Patients with autism spectrum disorder (ASD) display distinctive neurophysiological characteristics associated with significant cognitive, emotional, and behavioral symptoms. Transcranial direct current stimulation (tDCS) applied to the frontal or temporoparietal lobes has demonstrated potential to reduce the severity of ASD-related symptoms. Recently, the cerebellum has been identified as a brain area involved in ASD pathophysiology. In this open-label pilot study, seven ASD patients aged between 9 and 13 years underwent 20 daily sessions of 20 min cathodal stimulation of the right cerebellar lobe. At the end of the treatment, the Aberrant Behavior Checklist (ABC) scores showed a 25% mean reduction in global severity of symptoms, with a more pronounced reduction in the “social withdrawal and lethargy” (−35%), “hyperactivity and noncompliance” (−26%), and “irritability, agitation, and crying” (−25%) subscales. Minor and no improvement were observed in the “stereotypic behavior” (−18%) and “inappropriate speech” (−0%) subscales, respectively. Improvements were not detected in the two patients who were taking psychotropic drugs during the study. Clinical response showed a symptom-specific time course. Quality of sleep and mood improved earlier than hyperactivity and social withdrawal. The treatment was generally accepted by patients and well tolerated. No serious adverse events were reported. Stimulation also appeared to markedly reduce the severity of tics in a patient with comorbid tic disorder and led to the disappearance of a frontal epileptogenic focus in another patient with a history of seizures. In conclusion, cerebellar tDCS is safe, feasible, and potentially effective in the treatment of ASD symptoms among children. Strategies to improve recruitment and retention are discussed.

A Systematic Review of Brainstem Contributions to Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects one in 66 children in Canada. The contributions of changes in the cortex and cerebellum to autism have been studied for decades. However, our understanding of brainstem contributions has only started to emerge more recently. Disruptions of sensory processing, startle response, sensory filtering, sensorimotor gating, multisensory integration and sleep are all features of ASD and are processes in which the brainstem is involved. In addition, preliminary research into brainstem contribution emphasizes the importance of the developmental timeline rather than just the mature brainstem. Therefore, the purpose of this systematic review is to compile histological, behavioral, neuroimaging, and electrophysiological evidence from human and animal studies about brainstem contributions and their functional implications in autism. Moreover, due to the developmental nature of autism, the review pays attention to the atypical brainstem development and compares findings based on age. Overall, there is evidence of an important role of brainstem disruptions in ASD, but there is still the need to examine the brainstem across the life span, from infancy to adulthood which could lead the way for early diagnosis and possibly treatment of ASD.

Brain MRI in Autism Spectrum Disorder: Narrative Review and Recent Advances

Autism spectrum disorder (ASD) is neuropsychiatric continuum of disorders characterized by persistent deficits in social communication and restricted repetitive patterns of behavior which impede optimal functioning. Early detection and intervention in ASD children can mitigate the deficits in social interaction and result in a better outcome. Various non-invasive imaging methods and molecular techniques have been developed for the early identification of ASD characteristics. There is no general consensus on specific neuroimaging features of autism; however, quantitative magnetic resonance techniques have provided valuable structural and functional information in understanding the neuropathophysiology of ASD and how the autistic brain changes during childhood, adolescence, and adulthood. In this review of decades of ASD neuroimaging research, we identify the structural, functional, and molecular imaging clues that most accurately point to the diagnosis of ASD vs. typically developing children. These studies highlight the 1) exaggerated synaptic pruning, 2) anomalous gyrification, 3) interhemispheric under- and overconnectivity, and 4) excitatory glutamate and inhibitory GABA imbalance theories of ASD. The application of these various theories to the analysis of a patient with ASD is mitigated often by superimposed comorbid neuropsychological disorders, evolving brain maturation processes, and pharmacologic and behavioral interventions that may affect the structure and function of the brain. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

Longitudinal Evaluation of Cerebral Growth Across Childhood in Boys and Girls With Autism Spectrum Disorder

BACKGROUND

Cerebral overgrowth is frequently reported in children but not in adults with autism spectrum disorder (ASD). This suggests that early cerebral overgrowth is followed by normalization of cerebral volumes. However, this notion is predicated on cross-sectional research that is vulnerable to sampling bias. For example, autistic individuals with disproportionate megalencephaly, a subgroup with higher rates of intellectual disability and larger cerebral volumes, may be underrepresented in studies of adolescents and adults. Furthermore, extant studies have cohorts that are predominately male, thus limiting knowledge of cerebral growth in females with ASD.

METHODS

Growth of total cerebral volume, gray matter (GM) volume, and white matter volume as well as proportion of GM to total cerebral volume were examined in a longitudinal sample comprising 273 boys (199 with ASD) scanned at up to four time points (mean ages = 38, 50, 64, and 137 months, respectively) and 156 girls (95 with ASD) scanned at up to three time points (mean ages = 39, 53, and 65 months, respectively) using mixed-effects modeling.

RESULTS

In boys with ASD, cerebral overgrowth in the ASD with disproportionate megalencephaly subgroup was predominately driven by increases in GM and persisted throughout childhood without evidence of volumetric regression or normalization. In girls with ASD, cerebral volumes were similar to those in typically developing girls, but growth trajectories of GM and white matter were slower throughout early childhood. The proportion of GM to total cerebral volume declined with age at a slower rate in autistic boys and girls relative to typically developing control subjects.

CONCLUSIONS

Longitudinal evidence does not support the notion that early brain overgrowth is followed by volumetric regression, at least from early to late childhood.

Brain, behavioral, affective, and sex correlates of recovery from alcohol use disorders

BACKGROUND

Recovery from alcohol use disorders (AUDs) consists of salutary changes in behavior and affect. While evidence suggests that recovery-related behavioral changes, such as abstinence, emerge in tandem with both neural and affective changes, the precise relationships among these changes are unknown. To understand these relationships, we examined associations between the duration of abstinence (DOA), affective states, and neuroimaging-based structural measures of the brain reward system (BRS) in AUD men (AUD_M ) and AUD women (AUD_W ).

METHODS

Participants were community respondents from the Boston area comprising right-handed abstinent individuals with AUD (n = 60; 30 men) and controls without AUD (NC; n = 60; 29 men). Multivariate linear regressions compared short-/mid-term abstainers (≤5 years), long-term abstainers (>5 years), and the NC group on measures of BRS volume (3T magnetic resonance imaging scans) and measures of affect (Profile of Mood States [POMS]; Multiple Affect Adjective Check List [MAACL]; Hamilton Rating Scale for Depression [HRSD]). Analyses contrasted sex differences and accounted for age, education, drinking severity, and verbal IQ.

RESULTS

Compared to the NC group, short-/mid-term abstainers exhibited larger posterior insular volume (total (β = 0.019, 95% CI: 0.004, 0.034)), higher negative affect (POMS Mood Disturbance (β = 27.8, 95% CI: 11.56, 44.04), and lower positive affect (POMS Vigor (β = -4.89, 95% CI: -9.06, -0.72)). Compared to the NC group, Long-term abstainers exhibited significantly smaller volumes of aggregate anterior cingulate cortex (β = -0.06, 95% CI: -0.113, -0.008) and higher HRSD scores (β = 1.56, 95% CI: 0.14, 2.98). Relative to AUD_M , AUD_W exhibited significantly larger right anterior insular volumes (β = 0.03, 95% CI: 0.01, 0.06) and significantly greater MAACL Positive Affect scores (β = 7.56, 95% CI: 0.59, 11.55) in association with DOA.

CONCLUSIONS

We found that differences in abstinence from alcohol were correlated with differences in both neural recovery and affective dimensions of recovery from AUDs. The observed sex differences extend evidence of dimorphic effects of AUDs and recovery on brain structure and function. Future longitudinal research will test inferences concerning the directionality of these relationships.

A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI

Autism spectrum disorder (ASD) is a complex and degenerative neuro-developmental disorder. Most of the existing methods utilize functional magnetic resonance imaging (fMRI) to detect ASD with a very limited dataset which provides high accuracy but results in poor generalization. To overcome this limitation and to enhance the performance of the automated autism diagnosis model, in this paper, we propose an ASD detection model using functional connectivity features of resting-state fMRI data. Our proposed model utilizes two commonly used brain atlases, Craddock 200 (CC200) and Automated Anatomical Labelling (AAL), and two rarely used atlases Bootstrap Analysis of Stable Clusters (BASC) and Power. A deep neural network (DNN) classifier is used to perform the classification task. Simulation results indicate that the proposed model outperforms state-of-the-art methods in terms of accuracy. The mean accuracy of the proposed model was 88%, whereas the mean accuracy of the state-of-the-art methods ranged from 67% to 85%. The sensitivity, F1-score, and area under receiver operating characteristic curve (AUC) score of the proposed model were 90%, 87%, and 96%, respectively. Comparative analysis on various scoring strategies show the superiority of BASC atlas over other aforementioned atlases in classifying ASD and control.

A 16-year study of longitudinal volumetric brain development in males with autism

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with unknown brain etiology. Our knowledge to date about structural brain development across the lifespan in ASD comes mainly from cross-sectional studies, thereby limiting our understanding of true age effects within individuals with the disorder that can only be gained through longitudinal research. The present study describes FreeSurfer-derived volumetric findings from a longitudinal dataset consisting of 607 T1-weighted magnetic resonance imaging (MRI) scans collected from 105 male individuals with ASD (349 MRIs) and 125 typically developing male controls (258 MRIs). Participants were six to forty-five years of age at their first scan, and were scanned up to 5 times over a period of 16 years (average inter-scan interval of 3.7 years). Atypical age-related volumetric trajectories in ASD included enlarged gray matter volume in early childhood that approached levels of the control group by late childhood, an age-related increase in ventricle volume resulting in enlarged ventricles by early adulthood and reduced corpus callosum age-related volumetric increase resulting in smaller corpus callosum volume in adulthood. Larger corpus callosum volume was related to a lower (better) ADOS score at the most recent study visit for the participants with ASD. These longitudinal findings expand our knowledge of volumetric brain-based abnormalities in males with ASD, and highlight the need to continue to examine brain structure across the lifespan and well into adulthood.

Impact of the Olig Family on Neurodevelopmental Disorders

The Olig genes encode members of the basic helix-loop-helix (bHLH) family of transcription factors. Olig1, Olig2, and Olig3 are expressed in both the developing and mature central nervous system (CNS) and strictly regulate cellular specification and differentiation. Extensive studies have established functional roles of Olig1 and Olig2 in directing neuronal and glial formation during different stages in development. Recently, Olig2 overexpression was implicated in neurodevelopmental disorders down syndrome (DS) and autism spectrum disorder (ASD) but its influence on cognitive and intellectual defects remains unknown. In this review, we summarize the biological functions of the Olig family and how it uniquely promotes cellular diversity in the CNS. This is followed up with a discussion on how abnormal Olig2 expression impacts brain development and function in DS and ASD. Collectively, the studies described here emphasize vital features of the Olig members and their distinctive potential roles in neurodevelopmental disease states.

Emerging mechanisms of valproic acid-induced neurotoxic events in autism and its implications for pharmacological treatment

Autism spectrum disorder (ASD) is a sort of mental disorder marked by deficits in cognitive and communication abilities. To date no effective cure for this pernicious disease has been available. Valproic acid (VPA) is a broad-spectrum, antiepileptic drug, and it is also a potent teratogen. Epidemiological studies have shown that children exposed to VPA are at higher risk for ASD during the first trimester of their gestational development. Several animal and human studies have demonstrated important behavioral impairments and morphological changes in the brain following VPA treatment. However, the mechanism of VPA exposure-induced ASD remains unclear. Several factors are involved in the pathological phase of ASD, including aberrant excitation/inhibition of synaptic transmission, neuroinflammation, diminished neurogenesis, oxidative stress, etc. In this review, we aim to outline the current knowledge of the critical pathophysiological mechanisms underlying VPA exposure-induced ASD. This review will give insight toward understanding the complex nature of VPA-induced neuronal toxicity and exploring a new path toward the development of novel pharmacological treatment against ASD.

Morphological study of embryonic Chd8+/- mouse brains using light-sheet microscopy

Objective

Autism spectrum disorder (ASD) encompasses a group of neurodevelopmental conditions that remain poorly understood due to their genetic complexity. CHD8 is a risk allele strongly associated with ASD, and heterozygous Chd8 loss-of-function mice have been reported to exhibit macrocephaly in early postnatal stages. In this work, we sought to identify measurable brain alterations in early embryonic development.

Results

We performed light-sheet fluorescence microscopy imaging of N-cadherin stained and optically cleared Chd8^+/− and wild-type mouse brains at embryonic day 12.5 (E12.5). We report a detailed morphometric characterization of embryonic brain shapes and cortical neuroepithelial apical architecture. While Chd8^+/− characteristic expansion of the forebrain and midbrain was not observed this early in embryogenesis, a tendency for a decreased lateral ventricular sphericity and an increased intraocular distance in Chd8^+/− brains was found compared to controls. This study advocates the use of high-resolution microscopy technologies and multi-scale morphometric analyses of target brain regions to explore the etiology and cellular basis of Chd8 haploinsufficiency.

Role of Oligodendrocytes and Myelin in the Pathophysiology of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is an early neurodevelopmental disorder that involves deficits in interpersonal communication, social interaction, and repetitive behaviors. Although ASD pathophysiology is still uncertain, alterations in the abnormal development of the frontal lobe, limbic areas, and putamen generate an imbalance between inhibition and excitation of neuronal activity. Interestingly, recent findings suggest that a disruption in neuronal connectivity is associated with neural alterations in white matter production and myelination in diverse brain regions of patients with ASD. This review is aimed to summarize the most recent evidence that supports the notion that abnormalities in the oligodendrocyte generation and axonal myelination in specific brain regions are involved in the pathophysiology of ASD. Fundamental molecular mediators of these pathological processes are also examined. Determining the role of alterations in oligodendrogenesis and myelination is a fundamental step to understand the pathophysiology of ASD and identify possible therapeutic targets.

Genetic and environmental influences on structural brain measures in twins with autism spectrum disorder

Atypical growth patterns of the brain have been previously reported in autism spectrum disorder (ASD) but these alterations are heterogeneous across individuals, which may be associated with the variable effects of genetic and environmental influences on brain development. Monozygotic (MZ) and dizygotic (DZ) twin pairs with and without ASD (aged 6-15 years) were recruited to participate in this study. T1-weighted MRIs (n = 164) were processed with FreeSurfer to evaluate structural brain measures. Intra-class correlations were examined within twin pairs and compared across diagnostic groups. ACE modeling was also completed. Structural brain measures, including cerebral and cerebellar gray matter (GM) and white matter (WM) volume, surface area, and cortical thickness, were primarily influenced by genetic factors in TD twins; however, mean curvature appeared to be primarily influenced by environmental factors. Similarly, genetic factors accounted for the majority of variation in brain size in twins with ASD, potentially to a larger extent regarding curvature and subcortical GM; however, there were also more environmental contributions in twins with ASD on some structural brain measures, such that cortical thickness and cerebellar WM volume were primarily influenced by environmental factors. These findings indicate potential neurobiological outcomes of the genetic and environmental risk factors that have been previously associated with ASD and, although preliminary, may help account for some of the previously outlined neurobiological heterogeneity across affected individuals. This is especially relevant regarding the role of genetic and environmental factors in the development of ASD, in which certain brain structures may be more sensitive to specific influences.

Maternal-Autoantibody-Related (MAR) Autism: Identifying Neuronal Antigens and Approaching Prospects for Intervention

Recent studies indicate the existence of a maternal-autoantibody-related subtype of autism spectrum disorder (ASD). To date, a large number of studies have focused on describing patterns of brain-reactive serum antibodies in maternal-autoantibody-related (MAR) autism and some have described attempts to define the antigenic targets. This article describes evidence on MAR autism and the various autoantibodies that have been implicated. Among other possibilities, antibodies to neuronal surface protein Contactin Associated Protein 2 (CASPR2) have been found more frequently in mothers of children with neurodevelopmental disorders or autism, and two independent experimental studies have shown pathogenicity in mice. The N-methyl-D-aspartate receptor (NMDAR) is another possible target for maternal antibodies as demonstrated in mice. Here, we discuss the growing evidence, discuss issues regarding biomarker definition, and summarise the therapeutic approaches that might be used to reduce or prevent the transfer of pathogenic maternal antibodies.

Poly(I:C) Challenge Alters Brain Expression of Oligodendroglia-Related Genes of Adult Progeny in a Mouse Model of Maternal Immune Activation

Background: Altered white matter connectivity, as evidenced by pervasive microstructural changes in myelination and axonal integrity in neuroimaging studies, has been implicated in the development of autism spectrum disorder (ASD) and related neurodevelopmental conditions such as schizophrenia. Despite an increasing appreciation that such white matter disconnectivity is linked to social behavior deficits, virtually no etiologically meaningful myelin-related genes have been identified in oligodendrocytes, the key myelinating cells in the CNS, to furnish an account on the causes. The impact of neurodevelopmental perturbations during pregnancy such as maternal immune activation (MIA) on these genes in memory-related neural networks has not been experimentally scrutinized.

Methods: In this study, a mouse model of MIA by the viral dsRNA analog poly(I:C) was employed to mimic the effects of inflammation during pregnancy. Transcriptional expression levels of selected myelin- or oligodendroglia-related genes implicated in schizophrenia or ASD development were analyzed by in situ hybridization (ISH) and quantitative real-time PCR (qRT-PCR) with brain samples from MIA and control groups. The analysis focused on SOX-10 (SRY-related HMG-box 10), MAG (myelin-associated glycoprotein), and Tf (transferrin) expression in the hippocampus and the surrounding memory-related cortical regions in either hemisphere.

Results: Specifically, ISH reveals that in the brain of prenatal poly(I:C)-exposed mouse offspring in the MIA model (gestation day 9), mRNA expression of the genes SOX10, MAG and Tf were generally reduced in the limbic system including the hippocampus, retrosplenial cortex and parahippocampal gyrus on either side of the hemispheres. qRT-PCR further confirms the reduction of SOX10, MAG, and Tf expression in the medial prefrontal cortex, sensory cortex, amygdala, and hippocampus.

Conclusions: Our present results provide direct evidence that prenatal exposure to poly(I:C) elicits profound and long-term changes in transcript level and spatial distribution of myelin-related genes in multiple neocortical and limbic regions, notably the hippocampus and its surrounding memory-related neural networks. Our work demonstrates the potential utility of oligodendroglia-related genes as biomarkers for modeling neurodevelopmental disorders, in agreement with the hypothesis that MIA during pregnancy could lead to compromised white matter connectivity in ASD.

Age-related differences in white matter diffusion measures in autism spectrum condition

BACKGROUND

Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions.

METHODS

Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7-17 years of age.

RESULTS

We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls.

LIMITATIONS

The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group.

CONCLUSIONS

Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.

Improving the detection of autism spectrum disorder by combining structural and functional MRI information

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We present an approach for autism classification based on neuroimaging MRI.

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The pipeline relies on connectivity matrices and machine learning techniques.

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Accuracy is 85.06  ±  3.52% evaluated in more than 800 cases of the ABIDE I dataset.

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The most important correlations for autism classification are highlighted.

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Merging functional and structural information outperforms the monomodal pipelines.

Autism Spectrum Disorder (ASD) is a brain disorder that is typically characterized by deficits in social communication and interaction, as well as restrictive and repetitive behaviors and interests. During the last years, there has been an increase in the use of magnetic resonance imaging (MRI) to help in the detection of common patterns in autism subjects versus typical controls for classification purposes. In this work, we propose a method for the classification of ASD patients versus control subjects using both functional and structural MRI information. Functional connectivity patterns among brain regions, together with volumetric correspondences of gray matter volumes among cortical parcels are used as features for functional and structural processing pipelines, respectively. The classification network is a combination of stacked autoencoders trained in an unsupervised manner and multilayer perceptrons trained in a supervised manner. Quantitative analysis is performed on 817 cases from the multisite international Autism Brain Imaging Data Exchange I (ABIDE I) dataset, consisting of 368 ASD patients and 449 control subjects and obtaining a classification accuracy of 85.06 ± 3.52% when using an ensemble of classifiers. Merging information from functional and structural sources significantly outperforms the implemented individual pipelines.

Pten haploinsufficiency disrupts scaling across brain areas during development in mice

Haploinsufficiency for PTEN is a cause of autism spectrum disorder and brain overgrowth; however, it is not known if PTEN mutations disrupt scaling across brain areas during development. To address this question, we used magnetic resonance imaging to analyze brains of male Pten haploinsufficient (Pten^+/-) mice and wild-type littermates during early postnatal development and adulthood. Adult Pten^+/- mice display a consistent pattern of abnormal scaling across brain areas, with white matter (WM) areas being particularly affected. This regional and WM enlargement recapitulates structural abnormalities found in individuals with PTEN haploinsufficiency and autism. Early postnatal Pten^+/- mice do not display the same pattern, instead exhibiting greater variability across mice and brain regions than controls. This suggests that Pten haploinsufficiency may desynchronize growth across brain regions during early development before stabilizing by maturity. Pten^+/- cortical cultures display increased proliferation of glial cell populations, indicating a potential substrate of WM enlargement, and provide a platform for testing candidate therapeutics. Pten haploinsufficiency dysregulates coordinated growth across brain regions during development. This results in abnormally scaled brain areas and associated behavioral deficits, potentially explaining the relationship between PTEN mutations and neurodevelopmental disorders.

Modulation of hippocampal neuronal resilience during aging by the Hsp70/Hsp90 co-chaperone STI1

Chaperone networks are dysregulated with aging, but whether compromised Hsp70/Hsp90 chaperone function disturbs neuronal resilience is unknown. Stress-inducible phosphoprotein 1 (STI1; STIP1; HOP) is a co-chaperone that simultaneously interacts with Hsp70 and Hsp90, but whose function in vivo remains poorly understood. We combined in-depth analysis of chaperone genes in human datasets, analysis of a neuronal cell line lacking STI1 and of a mouse line with a hypomorphic Stip1 allele to investigate the requirement for STI1 in aging. Our experiments revealed that dysfunctional STI1 activity compromised Hsp70/Hsp90 chaperone network and neuronal resilience. The levels of a set of Hsp90 co-chaperones and client proteins were selectively affected by reduced levels of STI1, suggesting that their stability depends on functional Hsp70/Hsp90 machinery. Analysis of human databases revealed a subset of co-chaperones, including STI1, whose loss of function is incompatible with life in mammals, albeit they are not essential in yeast. Importantly, mice expressing a hypomorphic STI1 allele presented spontaneous age-dependent hippocampal neurodegeneration and reduced hippocampal volume, with consequent spatial memory deficit. We suggest that impaired STI1 function compromises Hsp70/Hsp90 chaperone activity in mammals and can by itself cause age-dependent hippocampal neurodegeneration in mice. Cover Image for this issue: doi: 10.1111/jnc.14749.

Purkinje cell-specific Grip1/2 knockout mice show increased repetitive self-grooming and enhanced mGluR5 signaling in cerebellum

Cerebellar Purkinje cell (PC) loss is a consistent pathological finding in autism. However, neural mechanisms of PC-dysfunction in autism remain poorly characterized. Glutamate receptor interacting proteins 1/2 (Grip1/2) regulate AMPA receptor (AMPAR) trafficking and synaptic strength. To evaluate role of PC-AMPAR signaling in autism, we produced PC-specific Grip1/2 knockout mice by crossing Grip2 conventional and Grip1 conditional KO with L7-Cre driver mice. PCs in the mutant mice showed normal morphology and number, and a lack of Grip1/2 expression. Rodent behavioral testing identified normal ambulation, anxiety, social interaction, and an increase in repetitive self-grooming. Electrophysiology studies revealed normal mEPSCs but an impaired mGluR-LTD at the Parallel Fiber-PC synapses. Immunoblots showed increased expression of mGluR5 and Arc, and enhanced phosphorylation of P38 and AKT in cerebellum of PC-specific Grip1/2 knockout mice. Results indicate that loss of Grip1/2 in PCs contributes to increased repetitive self-grooming, a core autism behavior in mice. Results support a role of AMPAR trafficking defects in PCs and disturbances of mGluR5 signaling in cerebellum in the pathogenesis of repetitive behaviors.

Motor Memory Deficits Contribute to Motor Impairments in Autism Spectrum Disorder

Sensorimotor abnormalities are common in individuals with autism spectrum disorder (ASD); however, the processes underlying these deficits remain unclear. This study examined force production with and without visual feedback to determine if individuals with ASD can utilize internal representations to guide sustained force. Individuals with ASD showed a faster rate of force decay in the absence of visual feedback. Comparison of force output and tests of social and verbal abilities demonstrated a link between motor memory impairment and social and verbal deficits in individuals with ASD. This finding suggests that deficits in storage or retrieval of motor memories contribute to sensorimotor deficits and implicates frontoparietal networks involved in short-term consolidation of action dynamics used to optimize ongoing motor output.

Familial risk of autism alters subcortical and cerebellar brain anatomy in infants and predicts the emergence of repetitive behaviors in early childhood

Autism spectrum disorder (ASD) is a common neurodevelopmental condition, and infant siblings of children with ASD are at a higher risk of developing autistic traits or an ASD diagnosis, when compared to those with typically developing siblings. Reports of differences in brain anatomy and function in high-risk infants which predict later autistic behaviors are emerging, but although cerebellar and subcortical brain regions have been frequently implicated in ASD, no high-risk study has examined these regions. Therefore, in this study, we compared regional MRI volumes across the whole brain in 4-6-month-old infants with (high-risk, n = 24) and without (low-risk, n = 26) a sibling with ASD. Within the high-risk group, we also examined whether any regional differences observed were associated with autistic behaviors at 36 months. We found that high-risk infants had significantly larger cerebellar and subcortical volumes at 4-6-months of age, relative to low-risk infants; and that larger volumes in high-risk infants were linked to more repetitive behaviors at 36 months. Our preliminary observations require replication in longitudinal studies of larger samples. If correct, they suggest that the early subcortex and cerebellum volumes may be predictive biomarkers for childhood repetitive behaviors. Autism Res 2019, 12: 614-627. © 2019 The Authors. Autism Research published by International Society for Autism Research published byWiley Periodicals, Inc. LAY SUMMARY: Individuals with a family history of autism spectrum disorder (ASD) are at risk of ASD and related developmental difficulties. This study revealed that 4-6-month-old infants at high-risk of ASD have larger cerebellum and subcortical volumes than low-risk infants, and that larger volumes in high-risk infants are associated with more repetitive behaviors in childhood.

Auditory Brainstem Pathology in Autism Spectrum Disorder: A Review

Atypical responses to sound are common in individuals with autism spectrum disorder (ASD), and growing evidence suggests an underlying auditory brainstem pathology. This review of the literature provides a comprehensive account of the structural and functional evidence for auditory brainstem abnormalities in ASD. The studies reviewed were published between 1975 and 2016 and were sourced from multiple online databases. Indices of both the quantity and quality of the studies reviewed are considered. Findings show converging evidence for auditory brainstem pathology in ASD, although the specific functions and anatomical structures involved remain equivocal. Two main trends emerge from the literature: (1) abnormalities occur mainly at higher levels of the auditory brainstem, according to structural imaging and electrophysiology studies; and (2) brainstem abnormalities appear to be more common in younger than older children with ASD. These findings suggest delayed maturation of neural transmission pathways between lower and higher levels of the brainstem and are consistent with the auditory disorders commonly observed in ASD, including atypical sound sensitivity, poor sound localization, and difficulty listening in background noise. Limitations of existing studies are discussed, and recommendations for future research are offered.

Using Pupillometry to Assess the Atypical Pupillary Light Reflex and LC-NE System in ASD

With recent advances in technology, there has been growing interest in use of eye-tracking and pupillometry to assess the visual pathway in autism spectrum disorder (ASD). Within emerging literature, an atypical pupillary light reflex (PLR) has been documented, holding potential for use as a clinical screening biomarker for ASD. This review outlines dominant theories of neuropathology associated with ASD and integrates underlying neuroscience associated with the atypical PLR through a reciprocal model of brainstem involvement and cortical underconnectivity. This review draws from animal models of ASD demonstrating disruption of cranial motor nuclei and brain imaging studies examining arousal and the influence of the locus coeruleus norepinephrine (LC-NE) system on the pupillary response. Pupillometry methods are explained in relation to existing data examining the PLR in ASD and pupillary parameters of constriction latency and tonic pupil diameter as key parameters for investigation. This focused review provides preliminary data toward future work developing pupillometry metrics and offers direction for studies aimed at rigorous study replication using pupillometry with the ASD population. Experimental conditions and testing protocol for capturing pupil parameters with this clinical population are discussed to promote clinical research and translational application.

Brainstem enlargement in preschool children with autism: Results from an intermethod agreement study of segmentation algorithms

The intermethod agreement between automated algorithms for brainstem segmentation is investigated, focusing on the potential involvement of this structure in Autism Spectrum Disorders (ASD). Inconsistencies highlighted in previous studies on brainstem in the population with ASD may in part be a result of poor agreement in the extraction of structural features between different methods. A sample of 76 children with ASD and 76 age-, gender-, and intelligence-matched controls was considered. Volumetric analyses were performed using common tools for brain structures segmentation, namely FSL-FIRST, FreeSurfer (FS), and Advanced Normalization Tools (ANTs). For shape analysis SPHARM-MAT was employed. Intermethod agreement was quantified in terms of Pearson correlations between pairs of volumes obtained by the different methods. The degree of overlap between segmented masks was quantified in terms of the Dice index. Both Pearson correlations and Dice indices, showed poor agreement between FSL-FIRST and the other methods (ANTs and FS), which by contrast, yielded Pearson correlations greater than 0.93 and average Dice indices greater than 0.76 when compared with each other. As with volume, shape analyses exhibited discrepancies between segmentation methods, with particular differences noted between FSL-FIRST and the others (ANT and FS), with under- and over-segmentation in specific brainstem regions. These data suggest that research on brain structure alterations should cross-validate findings across multiple methods. We consistently detected an enlargement of brainstem volume in the whole sample and in the male cohort across multiple segmentation methods, a feature particularly driven by the subgroup of children with idiopathic intellectual disability associated with ASD.

Differences in Cortical Structure and Functional MRI Connectivity in High Functioning Autism

Autism spectrum disorders (ASD) represent a complex group of neurodevelopmental conditions characterized by deficits in communication and social behaviors. We examined the functional connectivity (FC) of the default mode network (DMN) and its relation to multimodal morphometry to investigate superregional, system-level alterations in a group of 22 adolescents and young adults with high-functioning autism compared to age-, and intelligence quotient-matched 29 healthy controls. The main findings were that ASD patients had gray matter (GM) reduction, decreased cortical thickness and larger cortical surface areas in several brain regions, including the cingulate, temporal lobes, and amygdala, as well as increased gyrification in regions associated with encoding visual memories and areas of the sensorimotor component of the DMN, more pronounced in the left hemisphere. Moreover, patients with ASD had decreased connectivity between the posterior cingulate cortex, and areas of the executive control component of the DMN and increased FC between the anteromedial prefrontal cortex and areas of the sensorimotor component of the DMN. Reduced cortical thickness in the right inferior frontal lobe correlated with higher social impairment according to the scores of the Autism Diagnostic Interview-Revised (ADI-R). Reduced cortical thickness in left frontal regions, as well as an increased cortical thickness in the right temporal pole and posterior cingulate, were associated with worse scores on the communication domain of the ADI-R. We found no association between scores on the restrictive and repetitive behaviors domain of ADI-R with structural measures or FC. The combination of these structural and connectivity abnormalities may help to explain some of the core behaviors in high-functioning ASD and need to be investigated further.

Cerebellar Volume in Autism: Literature Meta-analysis and Analysis of the Autism Brain Imaging Data Exchange Cohort

BACKGROUND

The neuroanatomical bases of autism spectrum disorder remain largely unknown. Among the most widely discussed candidate endophenotypes, differences in cerebellar volume have been often reported as statistically significant.

METHODS

We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature and an analysis of the ABIDE (Autism Brain Imaging Data Exchange) cohort. Our meta-analysis sought to determine a combined effect size of autism spectrum disorder diagnosis on different measures of the cerebellar anatomy as well as the effect of possible factors of variability across studies. We then analyzed the cerebellar volume of 328 patients and 353 control subjects from the ABIDE project.

RESULTS

The meta-analysis of the literature suggested a weak but significant association between autism spectrum disorder diagnosis and increased cerebellar volume (p = .049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies meta-analyzed were generally underpowered; however, the number of statistically significant findings was larger than expected.

CONCLUSIONS

Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex, and IQ were important sources of cerebellar volume variability, although independent of autism diagnosis.