Brain structural correlates of autistic traits across the diagnostic divide: A grey matter and white matter microstructure study

Brain functional gradient and structure features in adolescent and adult autism spectrum disorders

Understanding how function and structure are organized and their coupling with clinical traits in individuals with autism spectrum disorder (ASD) is a primary goal in network neuroscience research for ASD. Atypical brain functional networks and structures in individuals with ASD have been reported, but whether these associations show heterogeneous hierarchy modeling in adolescents and adults with ASD remains to be clarified. In this study, 176 adolescent and 74 adult participants with ASD without medication or comorbidities and sex, age matched healthy controls (HCs) from 19 research groups from the openly shared Autism Brain Imaging Data Exchange II database were included. To investigate the relationship between the functional gradient, structural changes, and clinical symptoms of brain networks in adolescents and adults with ASD, functional gradient and voxel-based morphometry (VBM) analyses based on 1000 parcels defined by Schaefer mapped to Yeo's seven-network atlas were performed. Pearson's correlation was calculated between the gradient scores, gray volume and density, and clinical traits. The subsystem-level analysis showed that the second gradient scores of the default mode networks and frontoparietal network in patients with ASD were relatively compressed compared to adolescent HCs. Adult patients with ASD showed an overall compression gradient of 1 in the ventral attention networks. In addition, the gray density and volumes of the subnetworks showed no significant differences between the ASD and HC groups at the adolescent stage. However, adults with ASD showed decreased gray density in the limbic network. Moreover, numerous functional gradient parameters, but not VBM parameters, in adolescents with ASD were considerably correlated with clinical traits in contrast to those in adults with ASD. Our findings proved that the atypical changes in adolescent ASD mainly involve the brain functional network, while in adult ASD, the changes are more related to brain structure, including gray density and volume. These changes in functional gradients or structures are markedly correlated with clinical traits in patients with ASD. Our study provides a novel understanding of the pathophysiology of the structure-function hierarchy in ASD.

Polygenic scores for autism are associated with neurite density in adults and children from the general population

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4,928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.

Peripheral oxytocin levels are linked to hypothalamic gray matter volume in autistic adults: a cross-sectional secondary data analysis

Oxytocin (OXT) is known to modulate social behavior and cognition and has been discussed as pathophysiological and therapeutic factor for autism spectrum disorder (ASD). An accumulating body of evidence indicates the hypothalamus to be of particular importance with regard to the underlying neurobiology. Here we used a region of interest voxel-based morphometry (VBM) approach to investigate hypothalamic gray matter volume (GMV) in autistic (n = 29, age 36.03 ± 11.0) and non-autistic adults (n = 27, age 30.96 ± 11.2). Peripheral plasma OXT levels and the autism spectrum quotient (AQ) were used for correlation analyses. Results showed no differences in hypothalamic GMV in autistic compared to non-autistic adults but suggested a differential association between hypothalamic GMV and OXT levels, such that a positive association was found for the ASD group. In addition, hypothalamic GMV showed a positive association with autistic traits in the ASD group. Bearing in mind the limitations such as a relatively small sample size, a wide age range and a high rate of psychopharmacological treatment in the ASD sample, these results provide new preliminary evidence for a potentially important role of the HTH in ASD and its relationship to the OXT system, but also point towards the importance of interindividual differences.

Alteration of the large-scale white-matter functional networks in autism spectrum disorder

Autism spectrum disorder is a neurodevelopmental disorder whose core deficit is social dysfunction. Previous studies have indicated that structural changes in white matter are associated with autism spectrum disorder. However, few studies have explored the alteration of the large-scale white-matter functional networks in autism spectrum disorder. Here, we identified ten white-matter functional networks on resting-state functional magnetic resonance imaging data using the K-means clustering algorithm. Compared with the white matter and white-matter functional network connectivity of the healthy controls group, we found significantly decreased white matter and white-matter functional network connectivity mainly located within the Occipital network, Middle temporo-frontal network, and Deep network in autism spectrum disorder. Compared with healthy controls, findings from white-matter gray-matter functional network connectivity showed the decreased white-matter gray-matter functional network connectivity mainly distributing in the Occipital network and Deep network. Moreover, we compared the spontaneous activity of white-matter functional networks between the two groups. We found that the spontaneous activity of Middle temporo-frontal and Deep network was significantly decreased in autism spectrum disorder. Finally, the correlation analysis showed that the white matter and white-matter functional network connectivity between the Middle temporo-frontal network and others networks and the spontaneous activity of the Deep network were significantly correlated with the Social Responsiveness Scale scores of autism spectrum disorder. Together, our findings indicate that changes in the white-matter functional networks are associated behavioral deficits in autism spectrum disorder.

IcoConv : Explainable brain cortical surface analysis for ASD classification

In this study, we introduce a novel approach for the analysis and interpretation of 3D shapes, particularly applied in the context of neuroscientific research. Our method captures 2D perspectives from various vantage points of a 3D object. These perspectives are subsequently analyzed using 2D Convolutional Neural Networks (CNNs), uniquely modified with custom pooling mechanisms. We sought to assess the efficacy of our approach through a binary classification task involving subjects at high risk for Autism Spectrum Disorder (ASD). The task entailed differentiating between high-risk positive and high-risk negative ASD cases. To do this, we employed brain attributes like cortical thickness, surface area, and extra-axial cerebral spinal measurements. We then mapped these measurements onto the surface of a sphere and subsequently analyzed them via our bespoke method. One distinguishing feature of our method is the pooling of data from diverse views using our icosahedron convolution operator. This operator facilitates the efficient sharing of information between neighboring views. A significant contribution of our method is the generation of gradient-based explainability maps, which can be visualized on the brain surface. The insights derived from these explainability images align with prior research findings, particularly those detailing the brain regions typically impacted by ASD. Our innovative approach thereby substantiates the known understanding of this disorder while potentially unveiling novel areas of study.

Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.

Corpus callosum organization and its implication to core and co-occurring symptoms of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is characterized by social interaction and communication deficits, repetitive behavior and often by co-occurring conditions such as language and non-verbal IQ development delays. Previous studies reported that those behavioral abnormalities can be associated with corpus callosum organization. However, little is known about the specific differences in white matter structure of the corpus callosum parts in children with ASD and TD peers and their relationships to core and co-occurring symptoms of ASD. The aim of the study was to investigate the volumetric and microstructural characteristics of the corpus callosum parts crucially involved in social, language, and non-verbal IQ behavior in primary-school-aged children with ASD and to assess the relationships between these characteristics and behavioral measures. 38 children (19 with ASD and 19 typically developing (TD) controls) were scanned using diffusion-weighted MRI and assessed with behavioral tests. The tractography of the corpus callosum parts were performed using Quantitative Imaging Toolkit software; diffusivity and volumetric measurements were extracted for the analysis. In the ASD group, fractional anisotropy (FA) was decreased across the supplementary motor area and the ventromedial prefrontal cortex, and axial diffusivity (AD) was reduced across each of the corpus callosum parts in comparison to the TD group. Importantly, the AD decrease was related to worse language skills and more severe autistic traits in individuals with ASD. The microstructure of the corpus callosum parts differs between children with and without ASD. Abnormalities in white matter organization of the corpus callosum parts are associated with core and co-occurring symptoms of ASD.

Relationship between Overweight/Obesity and Social Communication in Autism Spectrum Disorder Children: Mediating Effect of Gray Matter Volume

With advances in medical diagnostic technology, the healthy development of children with autism spectrum disorder (ASD) is receiving more and more attention. In this article, the mediating effect of brain gray matter volume (GMV) between overweight/obesity and social communication (SC) was investigated through the analysis of the relationship between overweight/obesity and SC in autism spectrum disorder children. In total, 101 children with ASD aged 3-12 years were recruited from three special educational centers (Yangzhou, China). Overweight/obesity in children with ASD was indicated by their body mass index (BMI); the Social Responsiveness Scale, Second Edition (SRS-2) was used to assess their social interaction ability, and structural Magnetic Resonance Imaging (sMRI) was used to measure GMV. A mediation model was constructed using the Process plug-in to analyze the mediating effect of GMV between overweight/obesity and SC in children with ASD. The results revealed that: overweight/obesity positively correlated with SRS-2 total points (p = 0.01); gray matter volume in the left dorsolateral superior frontal gyrus (Frontal_Sup_L GMV) negatively correlated with SRS-2 total points (p = 0.001); and overweight/obesity negatively correlated with Frontal_Sup_L GMV (p = 0.001). The Frontal_Sup_L GMV played a partial mediating role in the relationship between overweight/obesity and SC, accounting for 36.6% of total effect values. These findings indicate the significant positive correlation between overweight/obesity and SC; GMV in the left dorsolateral superior frontal gyrus plays a mediating role in the relationship between overweight/obesity and SC. The study may provide new evidence toward comprehensively revealing the overweight/obesity and SC relationship.

Psychopathic and autistic traits differentially influence the neural mechanisms of social cognition from communication signals

Psychopathy is associated with severe deviations in social behavior and cognition. While previous research described such cognitive and neural alterations in the processing of rather specific social information from human expressions, some open questions remain concerning central and differential neurocognitive deficits underlying psychopathic behavior. Here we investigated three rather unexplored factors to explain these deficits, first, by assessing psychopathy subtypes in social cognition, second, by investigating the discrimination of social communication sounds (speech, non-speech) from other non-social sounds, and third, by determining the neural overlap in social cognition impairments with autistic traits, given potential common deficits in the processing of communicative voice signals. The study was exploratory with a focus on how psychopathic and autistic traits differentially influence the function of social cognitive and affective brain networks in response to social voice stimuli. We used a parametric data analysis approach from a sample of 113 participants (47 male, 66 female) with ages ranging between 18 and 40 years (mean 25.59, SD 4.79). Our data revealed four important findings. First, we found a phenotypical overlap between secondary but not primary psychopathy with autistic traits. Second, primary psychopathy showed various neural deficits in neural voice processing nodes (speech, non-speech voices) and in brain systems for social cognition (mirroring, mentalizing, empathy, emotional contagion). Primary psychopathy also showed deficits in the basal ganglia (BG) system that seems specific to the social decoding of communicative voice signals. Third, neural deviations in secondary psychopathy were restricted to social mirroring and mentalizing impairments, but with additional and so far undescribed deficits at the level of auditory sensory processing, potentially concerning deficits in ventral auditory stream mechanisms (auditory object identification). Fourth, high autistic traits also revealed neural deviations in sensory cortices, but rather in the dorsal auditory processing streams (communicative context encoding). Taken together, social cognition of voice signals shows considerable deviations in psychopathy, with differential and newly described deficits in the BG system in primary psychopathy and at the neural level of sensory processing in secondary psychopathy. These deficits seem especially triggered during the social cognition from vocal communication signals.