Abstract Details

Title scMRI Reveals Large-Scale Brain Network Abnormalities in Autism

Topic Child Neurology/Developmental Neurobiology

Presentation(s) P03 - (-)

Poster/Presentation
Number 013

Objective

Background BACKGROUND: Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. It has long been known that autistic children show gross anatomic differences versus normal children, particularly in brain size and compartmental volumes. However, recent studies investigating morphological differences in gray and white matter structure, as well as functional MRI connectivity, have yielded divergent and seemingly contradictory results. How these regional abnormalities relate to phenotype remains unclear.

Design/Methods DESIGN/METHODS: We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. We used structural covariance MRI to interrogate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls.

Results RESULTS: We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and topology of the salience network, involved in social-emotional regulation of environmental stimuli, is markedly underdeveloped in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a 'posteriorization' of this network.

Conclusions CONCLUSIONS: Specific abnormalities in brain network architecture may underlie autism. Network-level anatomic abnormalities in autism have not previously been described. Our findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Network-level abnormalities in autism are quantifiable using standard clinical MRI.

Authors/Disclosures
Brandon A. Zielinski, MD, PhD (University of Utah Medical Center) PRESENTER	Dr. Zielinski has nothing to disclose.
	No disclosure on file
	No disclosure on file
Nazem Atassi, MD	Dr. Atassi has received personal compensation for serving as an employee of Sanofi. Dr. Atassi has stock in Sanofi.
Erin D. Bigler, PhD (Erin D. Bigler, Ph.D.)	Dr. Bigler has received personal compensation in the range of $50,000-$99,999 for serving as an Expert Witness for Erin D. Bigler, Ph.D., Private Consulting Practice. Dr. Bigler has received publishing royalties from a publication relating to health care.
	No disclosure on file

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