Abstract
<p>Length-dependent axonal degeneration, sometimes referred to as the "dying-back" of a nerve, results in axonal degeneration at the most distal extent of the axon. Degeneration of extended axons in the peripheral (PNS) and central nervous systems (CNS) is the pathological basis for a number of neurological disorders, including the axonal peripheral neuropathies known as Charcot-Marie-Tooth disease type 2 (CMT2) and the axonal degeneration of the corticospinal tract in the CNS known as hereditary spastic paraplegias (HSP). CMT2 and HSP are inherited neurodegenerative disorders characterized by progressive axonal degeneration, which can cause severe disabilities and have no clinically available treatment options. While length-dependent axonal degeneration in CMT2 occurs in the periphery and in HSP in the central nervous system, it is becoming more evident that there is significant biological and genetic overlap between these disorders. In addition, the known genes only explain ~60% of HSP cases and ~30% of CMT2 cases, which suggests many more disease genes are still left to be identified. New technologies, such as exome and genome sequencing, allow us to rapidly increase our knowledge on genes involved in these diseases. Therefore, the overall goal of this project was to use exome sequencing to build upon and extend the existing knowledge of genetic factors and biological pathways involved in axonopathies. I analyzed >1,000 whole exome datasets from patients with CMT2 and HSP. This analysis has lead to the identification of the novel disease genes MARS and DDHD2, which cause CMT2 and HSP, respectively. However, while producing this large cohort of exome data, it became evident that novel strategies for analyzing genomic-scale data would be needed. To this end, I developed GEnomes Management Application (GEM.app) to address the computational challenges brought forth by genomic ‘big data’. This platform has lead to numerous gene identifications (BICD2, GBA2, DDHD1, DDHD2, FBXO38, REEP2, etc). Due to the scalability of the GEM.app platform, I was able to analyze large collections of exome datasets. These analyses lead to the findings that redefined the phenotypic spectrum of two disease genes PNPLA6 and VCP. Given that much of our knowledge of the pathophysiology of these diseases has initially been identified via genetic studies, the value of the present work cannot be underestimated. Further characterization of molecular pathways involved in axonal degeneration will lead to better understanding of biological mechanisms and eventually lead to new therapeutic options for disorders characterized by axon degeneration.</p>