29585
Disrupted Cerebellar - Cerebrocortical Circuits in ASD Models and in ASD

Panel Presentation
Thursday, May 2, 2019: 10:55 AM
Room: 516ABC (Palais des congres de Montreal)
J. P. Lerch1, J. Ellegood1, C. Hammill2, P. Tsai3, M. J. Taylor2 and E. Anagnostou4, (1)Mouse Imaging Centre, Hospital for Sick Children, Toronto, ON, Canada, (2)The Hospital for Sick Children, Toronto, ON, Canada, (3)University of Texas Southwestern Medical Center, Dallas, TX, (4)Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
Background: There is increasing evidence for cerebellar involvement in autism. It is unclear, however, to what extent different mutations implicated in autism contribute to cerebellar phenotypes, or whether cerebellar involvement is universal to all autism cases.

Objectives: To understand the extent to which cerebellar circuits are implicated in autism and to dissect which mutations might drive those results.

Methods: Anatomical MRIs combined with automated cerebellar segmentation protocols were used in both large human and mouse datasets. In the human sample, T1-weighted images from 582 subjects (328 controls, 254 ASD) collected at a single site in Toronto, Ontario, combining data from the Province of Ontario Neurodevelopmental Disorders Programme and studies from the Taylor lab, were used. All subjects were between 5-21 years of age. For the mouse data, >60 individual mouse models (>1300 individual animals) with high-resolution ex-vivo T2-weighted MRIs were used.

Results: Significant differences in volumes between those with autism and controls were identified in multiple cerebellar regions, strongest in lobules IV, crus I and II, and X. Similar results were identified in the mouse models, where the strongest effects were in the cerebellar nuclei (which were not separately segmented in the human dataset). Not all mouse models showed the same pattern of cerebellar volume change; instead, these effects were driven by a few key, highly affected mutations.

Conclusions: The cerebellum is one of the most affected brain areas in both humans and mice. The mouse data showed that this effect is driven by a few key mutations rather than a broad effect across all models.