We at the MSA utilize the CGAP infrastructure in order to develop a database jointly created and shared by MSA Coalition researchers that amalgamates their genetic data, in such a way that each researcher can access information across the database for specific genetic changes (variants) of interest but without the ability to download the entire database.
Gene-environment interactions are thought to underlie the vast majority of MSA. Such interactions will not be tractable in the laboratory without identifying the genetic component. Thus, a critical impediment to understanding the biology of MSA, and thus developing therapies, is the absence of well-defined genetic causes for the disease. For rare diseases, “strength in numbers” is critical for genetic analysis, in addition to the development of creative strategies to better analyze the data. Genetic datasets are growing in size, but currently they are isolated from each other in different centers. There is considerable interest among groups to collaborate, but poor collective knowledge among of what is available and how to collaborate. Advocacy groups like the MSA Coalition (USA) and MSA Trust (UK) and their researcher networks could be pivotal to fostering this collaboration and meeting a significant unmet need in the MSA community. The Clinical Genomic Analysis Platform (CGAP) is a centralized, cloud-based software ecosystem for genome data analysis and visualization that is being used for this collaborative effort.