Reduced grey matter volume of amygdala and hippocampus is associated with the severity of autistic symptoms and language abilities in school-aged children with Autism Spectrum Disorder: an exploratory study

Identification of high-functioning autism spectrum disorders based on gray-white matter functional network connectivity

In the field of autism spectrum disorder (ASD), research on functional connectivity between gray matter and white matter remains under-researched. To address this gap, this study innovatively introduced a nested cross-validation method that integrates gray-white matter functional connectivity with an F-Score algorithm. This method calculates the correlation based on signals extracted from functional magnetic resonance imaging data using gray matter and white matter brain region templates. After applying the method to a New York University Langone Medical Center dataset consisting of 55 individuals with high-functioning ASD and 52 healthy subjects, we achieved a classification accuracy of 72.94%. This study found abnormal functional connectivity, primarily involving the left anterior prefrontal cortex and right superior corona radiata, left retrosplenial cortex and left superior corona radiata, as well as the left ventral anterior cingulate cortex and body of corpus callosum. Besides, we discovered that these abnormal connections are closely related to social impairment and restrictive and repetitive behaviors in ASD. In conclusion, this study provides a gray-white matter functional connectivity perspective for the diagnosis and understanding of ASD.

Understanding Depression in Autism: The Role of Subjective Perception and Anterior Cingulate Cortex Volume

Background

The prevalence of depression is elevated in individuals with autism spectrum disorder (ASD) compared to the general population, yet the reasons for this disparity remain unclear. While social deficits central to ASD may contribute to depression, it is uncertain whether social interaction behavior themselves or individuals' introspection about their social behaviors are more impactful. Although the anterior cingulate cortex (ACC) and amygdala are frequently implicated in ASD, depression, and social functioning, it is unknown if these regions explain differences between ASD adults with and without co-occurring depression.

Methods

The present study contrasted observed vs. subjective perception of autism symptoms and social performances assessed with both standardized measures and a lab task, in 65 sex-balanced (52.24% male) autistic young adults. We also quantified ACC and amygdala volume with 7-Tesla structural neuroimaging to examine correlations with depression and social functioning.

Results

We found that ASD individuals with depression exhibited differences in subjective evaluations including heightened self-awareness of ASD symptoms, lower subjective satisfaction with social relations, and less perceived affiliation during the social interaction task, yet no differences in corresponding observed measures, compared to those without depression. Larger ACC volume was related to depression, greater self-awareness of ASD symptoms, and worse subjective satisfaction with social interactions. In contrast, amygdala volume, despite its association with clinician-rated ASD symptoms, was not related to depression.

Limitations

Due to the cross-sectional nature of our study, we cannot determine the directionality of the observed relationships. Additionally, we included only individuals with an IQ over 60 to ensure participants could complete the social task, which excluded many on the autism spectrum. We also utilized self-reported depression indices instead of clinically diagnosed depression, which may limit the comprehensiveness of the findings.

Conclusions

Our approach highlights the unique role of subjective perception of autism symptoms and social interactions, beyond the observable manifestation of social interaction in ASD, in contributing to depression, with the ACC playing a crucial role. These findings imply possible heterogeneity of ASD concerning co-occurring depression. Using neuroimaging, we were able to demarcate depressive phenotypes co-occurring alongside autistic phenotypes.

T1w/T2w ratio maps identify children with autism spectrum disorder and the relationships between myelin-related changes and symptoms

BACKGROUND

Modern neuroimaging methods have revealed that autistic symptoms are associated with abnormalities in brain morphology, connectivity, and activity patterns. However, the changes in brain microstructure underlying the neurobiological and behavioral deficits of autism remain largely unknown.

METHODS

we characterized the associated abnormalities in intracortical myelination pattern by constructing cortical T1-weighted/T2-weighted ratio maps. Voxel-wise comparisons of cortical myelination were conducted between 150 children with autism spectrum disorder (ASD) and 139 typically developing (TD) children. Group differences in cortical T1-weighted/T2-weighted ratio and gray matter volume were then examined for associations with autistic symptoms. A convolutional neural network (CNN) model was also constructed to examine the utility of these regional abnormalities in cortical myelination for ASD diagnosis.

RESULTS

Compared to TD children, the ASD group exhibited widespread reductions in cortical myelination within regions related to default mode, salience, and executive control networks such as the inferior frontal gyrus, bilateral insula, left fusiform gyrus, bilateral hippocampus, right calcarine sulcus, bilateral precentral, and left posterior cingulate gyrus. Moreover, greater myelination deficits in most of these regions were associated with more severe autistic symptoms. In addition, children with ASD exhibited reduced myelination in regions with greater gray matter volume, including left insula, left cerebellum_4_5, left posterior cingulate gyrus, and right calcarine sulcus. Notably, the CNN model based on brain regions with abnormal myelination demonstrated high diagnostic efficacy for ASD.

CONCLUSIONS

Our findings suggest that microstructural abnormalities in myelination contribute to autistic symptoms and so are potentially promising therapeutic targets as well as biomarkers for ASD diagnosis.

Gut-brain barrier dysfunction bridge autistic-like behavior in mouse model of maternal separation stress: A behavioral, histopathological, and molecular study

Autism spectrum disorder (ASD) is a fast-growing neurodevelopmental disorder throughout the world. Experiencing early life stresses (ELS) like maternal separation (MS) is associated with autistic-like behaviors. It has been proposed that disturbance in the gut-brain axis-mediated psychiatric disorders following MS. The role of disruption in the integrity of gut-brain barrier in ASD remains unclear. Addressing this knowledge gap, in this study we aimed to investigate role of the gut-brain barrier integrity in mediating autistic-like behaviors in mouse models of MS stress. To do this, mice neonates are separated daily from their mothers from postnatal day (PND) 2 to PND 14 for 3 hours. During PND58-60, behavioral tests related to autistic-like behaviors including three-chamber sociability, shuttle box, and resident-intruder tests were performed. Then, prefrontal cortex (PFC), hippocampus, and colon samples were dissected out for histopathological and molecular evaluations. Results showed that MS is associated with impaired sociability and social preference indexes, aggressive behaviors, and impaired passive avoidance memory. The gene expression of CLDN1 decreased in the colon, and the gene expression of CLDN5, CLDN12, and MMP9 increased in the PFC of the MS mice. MS is associated with decrease in the diameter of CA1 and CA3 areas of the hippocampus. In addition, MS led to histopathological changes in the colon. We concluded that, probably, disturbance in the gut-brain barrier integrities mediated the autistic-like behavior in MS stress in mice.

Neuroplasticity of children in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that encompasses a range of symptoms including difficulties in verbal communication, social interaction, limited interests, and repetitive behaviors. Neuroplasticity refers to the structural and functional changes that occur in the nervous system to adapt and respond to changes in the external environment. In simpler terms, it is the brain's ability to learn and adapt to new environments. However, individuals with ASD exhibit abnormal neuroplasticity, which impacts information processing, sensory processing, and social cognition, leading to the manifestation of corresponding symptoms. This paper aims to review the current research progress on ASD neuroplasticity, focusing on genetics, environment, neural pathways, neuroinflammation, and immunity. The findings will provide a theoretical foundation and insights for intervention and treatment in pediatric fields related to ASD.

Autism Spectrum Disorder: Brain Areas Involved, Neurobiological Mechanisms, Diagnoses and Therapies

Autism spectrum disorder (ASD), affecting over 2% of the pre-school children population, includes an important fraction of the conditions accounting for the heterogeneity of autism. The disease was discovered 75 years ago, and the present review, based on critical evaluations of the recognized ASD studies from the beginning of 1990, has been further developed by the comparative analyses of the research and clinical reports, which have grown progressively in recent years up to late 2023. The tools necessary for the identification of the ASD disease and its related clinical pathologies are genetic and epigenetic mutations affected by the specific interaction with transcription factors and chromatin remodeling processes occurring within specific complexes of brain neurons. Most often, the ensuing effects induce the inhibition/excitation of synaptic structures sustained primarily, at dendritic fibers, by alterations of flat and spine response sites. These effects are relevant because synapses, established by specific interactions of neurons with glial cells, operate as early and key targets of ASD. The pathology of children is often suspected by parents and communities and then confirmed by ensuing experiences. The final diagnoses of children and mature patients are then completed by the combination of neuropsychological (cognitive) tests and electro-/magneto-encephalography studies developed in specialized centers. ASD comorbidities, induced by processes such as anxieties, depressions, hyperactivities, and sleep defects, interact with and reinforce other brain diseases, especially schizophrenia. Advanced therapies, prescribed to children and adult patients for the control of ASD symptoms and disease, are based on the combination of well-known brain drugs with classical tools of neurologic and psychiatric practice. Overall, this review reports and discusses the advanced knowledge about the biological and medical properties of ASD.

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

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