Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.

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Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity

10.1101/027516 ◽

2015 ◽

Author(s):

Manjari Narayan ◽

Genevera I. Allen

Keyword(s):

Autism Spectrum Disorders ◽

Functional Connectivity ◽

Network Structure ◽

Symptom Severity ◽

Statistical Power ◽

Autism Spectrum ◽

Covariate Effects ◽

Activity Measurements ◽

Wide Range ◽

Spectrum Disorders

AbstractMany complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is impaired in such conditions, functional connectivity studies seek to understand individual differences in brain network structure in terms of covariates that measure symptom severity. In practice, however, functional connectivity is not observed but estimated from complex and noisy neural activity measurements. Imperfect subject network estimates can compromise subsequent efforts to detect covariate effects on network structure. We address this problem in the case of Gaussian graphical models of functional connectivity, by proposing novel two-level models that treat both subject level networks and population level covariate effects as unknown parameters. To account for imperfectly estimated subject level networks when fitting these models, we propose two related approaches — R2 based on resampling and random effects test statistics, and R3 that additionally employs random adaptive penalization. Simulation studies using realistic graph structures reveal that R2 and R3 have superior statistical power to detect covariate effects compared to existing approaches, particularly when the number of within subject observations is comparable to the size of subject networks. Using our novel models and methods to study parts of the ABIDE dataset, we find evidence of hypoconnectivity associated with symptom severity in autism spectrum disorders, in frontoparietal and limbic systems as well as in anterior and posterior cingulate cortices.

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FC05-05 - Fronto-temporal disconnectivity and symptom severity in autism spectrum disorders

European Psychiatry ◽

10.1016/s0924-9338(11)73542-8 ◽

2011 ◽

Vol 26 (S2) ◽

pp. 1838-1838

Author(s):

L. Poustka ◽

C. Jennen-Steinmetz ◽

R. Henze ◽

B. Stieltjes ◽

Keyword(s):

Autism Spectrum Disorders ◽

White Matter ◽

Symptom Severity ◽

Diffusion Tensor ◽

Autism Spectrum ◽

Diagnostic Interview ◽

Embedded Figures Test ◽

Fiber Tracts ◽

Spectrum Disorders ◽

The Right

BackgroundThere is increasing evidence that many of the core behavioral impairments in autism spectrum disorders (ASD) emerge from disconnectivity of networks that are important for social communication. It is less clear, which specific fiber tracts are involved and how possible alterations of white matter are associated with clinical symptomatology and neuropsychololgical characteristics in ASD.Methods18 children with ASD and 18 carefully matched typically developing controls aged 6–12 years were examined using diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). Fractional anisotropy (FA) values were correlated with symptom severity as indexed by the children's scores on the Autisms Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R) and results from the Childrens Embedded Figures Test (CEFT).ResultsDecreased FA values were identified for the fornix (FO), the superior longitudinal fasciculus (SLF) the corpus callosum and the uncinate fasciculus (UF) in the ASD group compared to controls, with most prominent differences in the UF bilaterally and the right SLF. FA values of affected fiber tracts were negatively associated with clinical measures of autistic smypotmatology and response time of the CEFT. Additionally, we observed decreased grey matter concentration in the left supramarginal gyrus.ConclusionOur findings support the hypothesis of abnormal white matter microstructure of fronto-temporal cortical networks in ASD, which are associated with core symptoms of the disorder.

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Alterations of Regional Homogeneity in Preschool Boys With Autism Spectrum Disorders

Frontiers in Neuroscience ◽

10.3389/fnins.2021.644543 ◽

2021 ◽

Vol 15 ◽

Author(s):

Zhihong Lan ◽

Shoujun Xu ◽

Yunfan Wu ◽

Likun Xia ◽

Kelei Hua ◽

...

Keyword(s):

Autism Spectrum Disorders ◽

Rating Scale ◽

Brain Activity ◽

Brain Regions ◽

Autism Spectrum ◽

Regional Homogeneity ◽

Angular Gyrus ◽

Spectrum Disorders ◽

Preschool Boys ◽

The Right

ObjectivesThe study was aimed at investigating the alterations of local spontaneous brain activity in preschool boys with autism spectrum disorders (ASD).MethodsBased on regional homogeneity (ReHo), the acquired resting state functional magnetic resonance imaging (fMRI) data sets, which included 86 boys with ASD and 54 typically developing (TD) boys, were used to detect regional brain activity. Pearson correlation analysis was used to study the relationship between abnormal ReHo value and the Childhood Autism Rating Scale (CARS), Autism Behavior Checklist (ABC), developmental quotient, and age.ResultsIn the ASD group, we found increased ReHo in the right calcarine as well as decreased ReHo in the opercular part of the left inferior frontal gyrus, the left middle temporal gyrus, the left angular gyrus, and the right medial orbital frontal cortex (p < 0.05, false discovery rate correction). We did not find a correlation between the results of brain regions and the CARS, ABC, and age.ConclusionsOur study found spontaneous activity changes in multiple brain regions, especially the visual and language-related areas of ASD, that may help to further understand the clinical characteristics of boys with ASD.

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Improving Synchronization and Functional Connectivity in Autism Spectrum Disorders through Plasticity-Induced Rehabilitation Training

10.21236/ada555805 ◽

2011 ◽

Author(s):

Jaime A. Pineda ◽

Ralph-Axel Mueller

Keyword(s):

Autism Spectrum Disorders ◽

Functional Connectivity ◽

Autism Spectrum ◽

Rehabilitation Training ◽

Spectrum Disorders

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Individual Differences in Intrinsic Brain Networks Predict Symptom Severity in Autism Spectrum Disorders

Cerebral Cortex ◽

10.1093/cercor/bhaa252 ◽

2020 ◽

Vol 31 (1) ◽

pp. 681-693 ◽

Cited By ~ 1

Author(s):

Emmanuel Peng Kiat Pua ◽

Phoebe Thomson ◽

Joseph Yuan-Mou Yang ◽

Jeffrey M Craig ◽

Gareth Ball ◽

...

Keyword(s):

Autism Spectrum Disorders ◽

Individual Differences ◽

Face Perception ◽

Symptom Severity ◽

Brain Networks ◽

Monozygotic Twins ◽

Autism Spectrum ◽

Social Impairment ◽

Individual Level ◽

Spectrum Disorders

Abstract The neurobiology of heterogeneous neurodevelopmental disorders such as Autism Spectrum Disorders (ASD) is still unknown. We hypothesized that differences in subject-level properties of intrinsic brain networks were important features that could predict individual variation in ASD symptom severity. We matched cases and controls from a large multicohort ASD dataset (ABIDE-II) on age, sex, IQ, and image acquisition site. Subjects were matched at the individual level (rather than at group level) to improve homogeneity within matched case–control pairs (ASD: n = 100, mean age = 11.43 years, IQ = 110.58; controls: n = 100, mean age = 11.43 years, IQ = 110.70). Using task-free functional magnetic resonance imaging, we extracted intrinsic functional brain networks using projective non-negative matrix factorization. Intrapair differences in strength in subnetworks related to the salience network (SN) and the occipital-temporal face perception network were robustly associated with individual differences in social impairment severity (T = 2.206, P = 0.0301). Findings were further replicated and validated in an independent validation cohort of monozygotic twins (n = 12; 3 pairs concordant and 3 pairs discordant for ASD). Individual differences in the SN and face-perception network are centrally implicated in the neural mechanisms of social deficits related to ASD.

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