FMRI data from 162 ASD and 175 TD adolescents are analyzed to demonstrate statistical associations among altered spatial-functional properties, clinical severity, and transcriptomic profiles related to synaptic signaling, mitochondrial processes, and glial-related functions in ASD, providing a complementary spatial perspective on large-scale functional organization.
Abstract
Autism Spectrum Disorder (ASD) is associated with atypical large-scale brain network organization, yet how spatial-functional dependencies relate to clinical features and molecular reference maps remains incompletely understood. To quantify spatial functional heterogeneity (Sill) and coherence persistence (Range), we analyzed resting-state fMRI data from 162 ASD and 175 TD adolescents, all aged 12–18. Compared with TD, adolescents with ASD exhibited significantly increased Sill within higher-order association networks, including the left Language and right Posterior Multimodal networks, whereas no group differences in Range survived multiple-comparison correction. Within the ASD group, elevated Sill was selectively associated with greater social-affective symptom severity but not restricted and repetitive behaviors. To explore potential biological correlates, we integrated cortical gene expression reference data and identified transcriptomic patterns associated with regional Sill differences. These genes showed enrichment for synaptic signaling, mitochondrial processes, and glial-related functions, highlighting multiscale correspondence between spatial-functional organization and molecular reference maps. Together, these results demonstrate statistical associations among altered spatial-functional properties, clinical severity, and transcriptomic profiles related to synaptic signaling, mitochondrial processes, and glial-related functions in ASD, providing a complementary spatial perspective on large-scale functional organization.
The heterogeneity in both the neurobiological mechanisms and the phenotypic presentations of autism spectrum disorder (ASD) poses a major challenge to clinical and translational research. Alterations in functional connectivity (FC) have been associated with ASD, yet it remains unclear whether and how divergent brain network properties may account for individual differences across ASD-related symptomatology and behaviors. We applied source-level reconstruction to rest-like non-task-related high-density EEG data in a cohort of 104 young children (38 with ASD) to identify global and local alterations of cortical network connectivity. We subsequently used regularized canonical correlation analysis (rCCA) to characterize specific FC patterns linked to variation in cognitive, social and sensory dimensions derived from standard clinical instruments. We found increased low-frequency FC in frontotemporal cross-hemispheric networks and lateral-occipital regions of young ASD children versus healthy peers. RCCA revealed three distinct FC patterns in recurrent ASD-related networks, each contributing to predict individual differences in cognitive, social and sensory features. These linked FC-behavior dimensions may shed light on atypical brain network topology associated with specific phenotypic manifestations of ASD, which might implicate unique underlying neurobiological mechanisms.
B. Rodríguez-Herreros, A. Mheich, J. A. Osório et al.· Autism Research· 0 citations
Autism spectrum disorder (ASD) is classically conceptualized as a dysconnectivity syndrome. However, most studies have examined structural and functional connectivity in isolation, leaving the coupling mechanisms between brain structure and function, particularly the contribution of white matter, poorly understood. To systematically characterize connectome pathology in ASD, we analyzed multimodal imaging data from 580 participants (240 with ASD, 340 typical controls) in the Autism Brain Imaging Data Exchange II dataset. We constructed multilayer brain networks integrating gray and white matter layers and quantified topological alterations using multiplex clustering and participation coefficients. Imaging-transcriptomic analysis was performed using the Allen Human Brain Atlas to link network changes to molecular pathways. The results revealed widespread whole-brain topological reorganization in white matter multiplex networks, involving the corpus callosum and major fiber tracts, with gene expression enriched in immune regulation and cellular metabolism pathways. The gray matter multiplex networks exhibited localized hyper-clustering centered on the cortico-striatum-thalamic-cortical circuit and the default mode network associated with genes implicated in cell adhesion and synaptic transmission. Notably, no significant group differences were observed in the multiplex participation coefficient, which indexes cross-layer integration, suggesting that the overall cross-layer connectivity distribution remains relatively stable. These findings delineate the co-occurring patterns of gray matter hyper-clustering and widespread white matter topological alterations in ASD and establish a multilevel framework bridging macroscopic connectome disruptions to the underlying molecular mechanisms, offering an integrated perspective on ASD heterogeneity.
Yingzhuo Wan, Hairong Xiao, Hanrui Chen et al.· Progress in Neuro-psychophar...· 0 citations
Atypical brain connectivity is considered a key neurobiological feature underlying the heterogeneous clinical manifestations of autism spectrum disorder (ASD). However, findings on brain networks in ASD are inconsistent, likely owing to the effects of developmental factors. In addition, how large-scale brain networks in ASD differ across developmental stages remains unclear. We aimed to elucidate the atypical developmental patterns of white matter (WM) structural networks in children and adolescents with ASD using a graph-theoretical approach.
Diffusion/T1-weighted brain imaging data were acquired from 69 individuals with ASD (age: 6–17 years) and 71 age- and sex-matched typically developing controls. Global and nodal topological properties of WM structural networks were computed, and 28 social-related regions were examined through subnetwork and nodal analyses. Case–control comparisons of global and nodal graph metrics were conducted separately for children and adolescents.
The children with ASD exhibited reduced integration of the whole-brain network, reflected by increased characteristic path length and decreased global efficiency. In contrast, the adolescents with ASD showed enhanced segregation within the social-brain subnetwork, indicated by increased clustering coefficient and local efficiency. Nodal analyses revealed reduced nodal efficiency across several social-related regions (e.g., the left inferior frontal gyrus, insula, amygdala, supramarginal gyrus, bilateral superior temporal poles) in children with ASD.
Topological disorganization in the autistic brain network varies across developmental stages, shifting from reduced global integration in childhood to enhanced segregation of social-brain circuits in adolescence. Such atypical WM structural organization may underlie the persistent social cognitive deficits observed in ASD.
Min Li, Kohei Kurita, Takashi Yamada et al.· Frontiers in Neuroscience· 0 citations
Autism is a heterogeneous neurodevelopmental condition, often accompanied by challenges in language and cognitive development. Although atypical functional connectivity (FC) has been reported in autism, the timing of when it first emerges and its relevance for later behavior remain poorly understood. In this study, we examined developmental trajectories of alpha-band FC and network organization across the first three years of life. We computed global alpha-band measures, including peak alpha connectivity frequency (PACF), mean FC, clustering coefficient, and modularity, to characterize nonlinear developmental trajectories from longitudinal EEGs collected from 238 children (3-to-36-month-olds) with (Autism; n=58) and without (LL-noAutism; n=180) autism. Network-based statistics (NBS-Predict) identified subnetworks contributing to group differences at each age. Exploratory graph analyses (EGA) examined associations among FC, network measures, and language outcomes. We observed that PACF increased linearly with age in both groups. Global alpha-band connectivity measures showed a similar developmental pattern, with mean global FC, clustering coefficient, and modularity all increasing rapidly during the first year in both groups. Thereafter, these measures declined in the Autism group but continued to gradually increase in the LL-noAutism group. Compared to LL-noAutism, NBS-Predict identified both hyper- and hypo-connectivity subnetworks in Autism at 3 months, followed by a hypo-connectivity subnetwork at 24 and 36 months. EGA indicated that early hyperconnectivity predicted later hypoconnectivity and was associated with subsequent network organization and language outcomes. These findings indicate that altered alpha-band connectivity trajectories are detectable in infancy in children later diagnosed with autism and may contribute to later differences in developmental outcomes.
Haerin Chung, W. W. An, C. Wilkinson et al.· medRxiv· 0 citations
Children and adolescents with ASD exhibited lower empathy capabilities than control subjects, which may be attributed to dysfunctions in the salience and social brain networks.
Yonglu Wang, Zhangliang Ma, Zhiyi Wang et al.· Frontiers in Psychiatry· 0 citations
An exploratory association between right precuneus GMV and ADOS social-domain scores suggests a possible link between localized structural variation and social symptom severity, although this finding requires replication in longitudinal and clinically richer datasets given their sensitivity to the harmonization strategy.
Gang Xiao, Xiaoshi Li, Yue Qin et al.· Frontiers in Neuroscience· 0 citations
