Quantifying the Brain Developmental Trajectory of Autism-Associated Brain Overgrowth Using 3D Cellular Resolution Imaging

2019 Award: $39,069

Need/Problem: Alterations in brain development are associated with a variety of neuropsychiatric disorders, including autism spectrum disorder (ASD). Many studies demonstrate that mouse models re-capitulate a core human phenotype, brain overgrowth, associated with an increase in the neural progenitor pool and that this brain overgrowth shows a regionally specific pattern. However, we do not know the cell-types that are driving the effect. And due to the limited temporal resolution of previous immunohistochemistry, we do not know the full developmental trajectory of cell-types leading to brain overgrowth.

Grant Summary: We aim to develop high throughput computational tools for 3D light-sheet microscopy images to quantify the brain developmental trajectory of autism-associated brain overgrowth. The computational tools developed in this project will be used to study cortical development in the mouse brain, including how typical development is altered by an autism-associated genetic mutation.

Goals and Projected Outcomes: We expect that the tools developed in this proposal will be widely used in the field, as many mouse models of neuropsychiatric diseases exhibit pathology during neural development, but limited tools exist to comprehensively analyze these large datasets. We additionally hope to leverage the tools developed as part of this pilot award for further projects studying the differences in brain development among genetically diverse mice (collaborative cross) and genotyped human tissue samples.

Guorong Wu, PhD

Grant Details:  To achieve these goals, we will pursue the following three specific aims. (1) Acquire whole brain cellular resolution images of neural progenitor and neuronal cell-types across critical time-periods of neocortical neurogenesis in wild-type and Chd8+/- mice. (2) Develop longitudinal image registration algorithms to map the developmental trajectories of neocortical development. Specifically, we will develop a novel groupwise longitudinal image registration method for mouse brain microscopy image sequences. (3) Quantify cell-type distributions within annotated areas of the developing neocortex. After we quantify the developmental trajectory of specific cell-types, we will perform statistical test to determine significance in trajectories between wild type and Chd8+/- mice.