A transcriptomics-based approach to identify quantitative biomarkers for multiple system atrophy - PROJECT SUMMARY Multiple system atrophy (MSA), an invariably fatal neurodegenerative disorder with no disease- modifying therapeutics or biomarkers, is characterized by the presence of pathogenic α-synuclein (α-syn) in the brain. Whether the onset of clinical signs is due to gain-of-function (GOF) deficits arising from toxic protein aggregation or from the loss-of-function (LOF) consequences due to α-syn sequestration remains a subject of debate. My objective is to identify MSA-driven changes in neuronal gene expression that may serve as novel biomarkers. Rather than an either-or scenario, I hypothesize that in MSA patients, a combination of the gain of toxic function of α-syn with the loss of normal function contributes to disease pathogenesis. My approach will draw from the expertise of both my sponsor (Dr. Woerman) and co-sponsor (Dr. Regan) to use an unbiased approach to interrogate the GOF vs LOF debate while also identifying potential quantitative biomarkers for MSA. Specific Aim 1 will identify and interrogate distinct changes in gene expression in response to MSA. I will investigate the effect of MSA-induced changes on neuronal gene expression using RNA sequencing (RNA- Seq) on human iPSC-derived dopaminergic neurons infected with MSA α-syn. I will validate hits via ELISA or Western blot using frozen brain tissue from MSA and control patients. Additional time course studies in a mouse model of MSA will be paired with qRT-PCR to identify genes with altered expression throughout disease, which will determine differentially expressed genes that may be used as quantifiable biomarkers for MSA. Specific Aim 2 will determine the effect of MSA on RNA stability. In light of recent findings demonstrating that α-syn interacts with P-bodies, I hypothesize that α-syn accumulation in MSA affects mRNA stability, leading to LOF deficits through altered gene expression. I will test this hypothesis by infecting human iPSC- derived dopaminergic neurons with MSA α-syn and then performing an ActinomycinD pulse time-course assay to measure the decay rate for mRNA. RNA-Seq will then be used to determine differentially expressed genes due to altered mRNA stability. Together, these studies will provide critical knowledge about the consequences of α-syn sequestration on mRNA stability and neuronal gene expression. Given the lack of biomarkers, diagnostics, or disease-modifying therapeutics for MSA, this work will enable future studies focused on MSA patient stratification and the development of a quantitative biomarker that can be used to determine therapeutic efficacy in clinical trials.
