The Cerebellum and Autism: More than Motor Control

Autism spectrum disorder is a neurodevelopmental disorder characterized by deficits in social cognition at its core. Human and animal studies converge in the existence of a network of key brain structures involved in the perception, integration, and coding of social cues. These structures mainly involve areas traditionally associated with cognitive function, such as the prefrontal cortex; processing of emotions, such as the amygdala; and motivation and reward, such as the nucleus accumbens. The cerebellum, conventionally associated with motor functions, is lately being considered as a key structure within the social circuitry. Cerebellar neuroanatomical alterations are among the most replicated findings in postmortem brain samples of patients with autism. In addition, cerebellar defects have been proposed to affect the functioning of distal brain areas to which the cerebellum projects. In fact, animal studies support the inclusion of the cerebellum as part of the brain network regulating social cognition and provide a mechanistic tool to study its function within the social network. In this chapter, we review current evidence from human and animal studies, opening a new avenue for further research

High-throughput transgenic mouse phenotyping using microscopic-MRI

With the completion of the human genome sequence in 2003, efforts have shifted towards elucidating gene function. Such phenotypic investigations are aided by advances in techniques for genetic modification of mice, with whom we share ~99% of genes. Mice are key models for both examination of basic gene function and translational study of human conditions. Furthering these efforts, ambitious programmes are underway to produce knockout mice for the ~25,000 mouse genes. In the coming years, methods to rapidly phenotype mouse morphology will be in great demand. This thesis demonstrates the development of non-invasive microscopic magnetic resonance imaging (\muMRI) methods for high-resolution ex-vivo phenotyping of mouse embryo and mouse brain morphology. It then goes on to show the application of computational atlasing techniques to these datasets, enabling automated analysis of phenotype. First, the issue of image quality in high-throughput embryo MRI was addressed. After investigating preparation and imaging parameters, substantial gains in signal- and contrast-to-noise were achieved. This protocol was applied to a study of Chd7+/- mice (a model of CHARGE syndrome), identifying cardiac defects. Combining this protocol with automated segmentation-propagation techniques, phenotypic differences were shown between three groups of mice in a volumetric analysis involving a number of organ systems. Focussing on the mouse brain, the optimal preparation and imaging parameters to maximise image quality and structural contrast were investigated, producing a high-resolution in-skull imaging protocol. Enhanced delineation of hippocampal and cerebellar structures was observed, correlating well to detailed histological comparisons. Subsequently this protocol was applied to a phenotypic investigation of the Tc1 model of Down syndrome. Using both visual inspection and automated, tensor based morphometry, novel phenotypic findings were identified in brain and inner ear structures. It is hoped that a combination of \muMRI with computational analysis techniques, as presented in this work, may help ease the burden of current phenotyping efforts

In Vivo 3D Digital Atlas Database of the Adult C57BL/6J Mouse Brain by Magnetic Resonance Microscopy

In this study, a 3D digital atlas of the live mouse brain based on magnetic resonance microscopy (MRM) is presented. C57BL/6J adult mouse brains were imaged in vivo on a 9.4 Tesla MR instrument at an isotropic spatial resolution of 100 μm. With sufficient signal-to-noise (SNR) and contrast-to-noise ratio (CNR), 20 brain regions were identified. Several atlases were constructed including 12 individual brain atlases, an average atlas, a probabilistic atlas and average geometrical deformation maps. We also investigated the feasibility of using lower spatial resolution images to improve time efficiency for future morphological phenotyping. All of the new in vivo data were compared to previous published in vitro C57BL/6J mouse brain atlases and the morphological differences were characterized. Our analyses revealed significant volumetric as well as unexpected geometrical differences between the in vivo and in vitro brain groups which in some instances were predictable (e.g. collapsed and smaller ventricles in vitro) but not in other instances. Based on these findings we conclude that although in vitro datasets, compared to in vivo images, offer higher spatial resolutions, superior SNR and CNR, leading to improved image segmentation, in vivo atlases are likely to be an overall better geometric match for in vivo studies, which are necessary for longitudinal examinations of the same animals and for functional brain activation studies. Thus the new in vivo mouse brain atlas dataset presented here is a valuable complement to the current mouse brain atlas collection and will be accessible to the neuroscience community on our public domain mouse brain atlas website

Neuroanatomical Assessment of the Integrin β3 Mouse Model Related to Autism and the Serotonin System Using High Resolution MRI

The integrinβ3 (ITGβ3) gene has been associated with both autism and the serotonin system. The purpose of this study was to examine the volumetric differences in the brain of an ITGβ3 homozygous knockout mouse model compared with a corresponding wild-type mouse using high resolution magnetic resonance imaging and detailed statistical analyses. The most striking difference found was an 11% reduction in total brain volume. Moreover, 32 different regions were found to have significantly different relative volumes (percentage total brain volume) in the ITGβ3 mouse. A number of interesting differences relevant to autism were discovered including a smaller corpus callosum volume and bilateral decreases in the hippocampus, striatum, and cerebellum. Relative volume increases were also found in the frontal and parieto-temporal lobes as well as in the amygdala. Particularly intriguing were the changes in the lateral wings of the dorsal raphe nuclei since that nucleus is so integral to the development of many different brain regions and the serotonin system in general

Autism genetics: searching for specificity and convergence.

Advances in genetics and genomics have improved our understanding of autism spectrum disorders. As many genes have been implicated, we look to points of convergence among these genes across biological systems to better understand and treat these disorders

Translational outcomes in a full gene deletion of ubiquitin protein ligase E3A rat model of Angelman syndrome.

Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by developmental delay, impaired communication, motor deficits and ataxia, intellectual disabilities, microcephaly, and seizures. The genetic cause of AS is the loss of expression of UBE3A (ubiquitin protein ligase E6-AP) in the brain, typically due to a deletion of the maternal 15q11-q13 region. Previous studies have been performed using a mouse model with a deletion of a single exon of Ube3a. Since three splice variants of Ube3a exist, this has led to a lack of consistent reports and the theory that perhaps not all mouse studies were assessing the effects of an absence of all functional UBE3A. Herein, we report the generation and functional characterization of a novel model of Angelman syndrome by deleting the entire Ube3a gene in the rat. We validated that this resulted in the first comprehensive gene deletion rodent model. Ultrasonic vocalizations from newborn Ube3am-/p+ were reduced in the maternal inherited deletion group with no observable change in the Ube3am+/p- paternal transmission cohort. We also discovered Ube3am-/p+ exhibited delayed reflex development, motor deficits in rearing and fine motor skills, aberrant social communication, and impaired touchscreen learning and memory in young adults. These behavioral deficits were large in effect size and easily apparent in the larger rodent species. Low social communication was detected using a playback task that is unique to rats. Structural imaging illustrated decreased brain volume in Ube3am-/p+ and a variety of intriguing neuroanatomical phenotypes while Ube3am+/p- did not exhibit altered neuroanatomy. Our report identifies, for the first time, unique AS relevant functional phenotypes and anatomical markers as preclinical outcomes to test various strategies for gene and molecular therapies in AS

Automated morphometric analysis and phenotyping of mouse brains from structural µMR images

In light of the utility and increasing ubiquity of mouse models of genetic and neurological disease, I describefully automated pipelines for the investigation of structural microscopic magnetic resonance images of mouse brains – for both high-throughput phenotyping, and monitoring disease. Mouse models offer unparalleled insight into genetic function and brain plasticity, in phenotyping studies; and neurodegenerative disease onset and progression, in therapeutic trials. I developed two cohesive, automatic software tools, for Voxel- and Tensor-Based Morphometry (V/TBM) and the Boundary Shift Integral (BSI), in the mouse brain. V/TBM are advantageous for their ability to highlight morphological differences between groups, without laboriously delineating regions of interest. The BSI is a powerful and sensitive imaging biomarker for the detection of atrophy. The resulting pipelines are described in detail. I show the translation and application of open-source software developed for clinical MRI analysis to mouse brain data: for tissue segmentation into high-quality, subject-specific maps, using contemporary multi-atlas techniques; and for symmetric, inverse-consistent registration. I describe atlases and parameters suitable for the preclinical paradigm, and illustrate and discuss image processing challenges encountered and overcome during development. As proof of principle and to illustrate robustness, I used both pipelines with in and ex vivo mouse brain datasets to identify differences between groups, representing the morphological influence of genes, and subtle, longitudinal changes over time, in particular relation to Down syndrome and Alzheimer’s disease. I also discuss the merits of transitioning preclinical analysis from predominately ex vivo MRI to in vivo, where morphometry is still viable and fewer mice are necessary. This thesis conveys the cross-disciplinary translation of up-to-date image analysis techniques to the preclinical paradigm; the development of novel methods and adaptations to robustly process large cohorts of data; and the sensitive detection of phenotypic differences and neurodegenerative changes in the mouse brai