A Large-scale Extracellular Vesicle RNA-seq Resource for Parkinsons Disease - PROJECT SUMMARY/ABSTRACT Parkinson's disease (PD) is a devastating and progressive neurological disease that impacts 6 million people worldwide. The lack of validated biomarkers of PD has hampered improvements in predicting disease progression, identifying new pathways for therapeutic development, and patient stratification toward rational clinical trial design. Recent advancements in the capture and characterization of extracellular, circulating RNAs (exRNAs) have spurred the identification of disease mechanisms, therapeutic target engagement, and biomarker discovery in neurological diseases. Extracellular vesicles (EVs), which can take pieces of cellular cargo and make their way into circulation, offer a unique opportunity to monitor RNA changes in patients living with PD. Our team has helped to mature the capture and characterization of EVs towards deployment for monitoring disease – using strategies that can look at the cargo from the total EV population as well as EVs derived from specific brain cell types affected by diseases like PD. The longitudinal collection of thousands of samples, with extensive phenotyping from hundreds of patients in the AMP-PD cohorts, offers an unprecedented opportunity to develop a comprehensive resource, that can easily be accessed and utilized by the PD research community. We hypothesize that directly isolating disease-relevant changes in RNA from plasma will provide important biomarker candidates for PD. The purpose of this proposal is to develop a comprehensive, plasma-based, exRNA resource that can easily be accessed and utilized by the PD research community. The resulting data will be deposited in the Accelerated Medical Partnerships for Parkinson's disease (AMP-PD) Knowledge Portal. Our Specific Aims are to 1) isolate and characterize RNA alterations from brain-derived EVs from PD patient plasma and age-matched non-PD controls; 2) measure exRNAs isolated from the total EV population in plasma from PD patients and age-matched, non-PD controls; and 3) uniformly and comprehensively sequence the long RNA from captured EVs for data analysis and deposition in AMP-PD Knowledge Portal. The approach proposed in this study is at the leading edge of the EV field, exRNA detection, and analysis. Successful completion of the work will have employed innovative approaches in EV capture, sequencing, and analyses to develop a comprehensive resource that enables future scientific inquiries with broad applicability in biomarker discovery and validation in PD.