EXODUS-enabled High-throughput Multi-omics Profiling of Extracellular Vesicles for Diagnosis of Preclinical Alzheimer's Disease

PROJECT SUMMARY / ABSTRACT Alzheimerandapos;s disease (AD) is the most widespread neurodegenerative disorder and has caused a major global health concern with the aging population. Early diagnosis of AD before irreversible brain damage or mental decline is critical for timely intervention, symptomatic treatment, and improved patient function. Accumulating studies indicate that neuron-derived extracellular vesicles (EVs) are important biomarkers for AD. However, researchers face significant challenges in the efficient isolation and accurate analysis of EVs, limiting the broad study and application of EVs in early diagnosis or targeted therapy of AD. WellSIM proposes to develop and validate a high-throughput platform and workflow based on our revolutionary EXODUS technique for reliable and reproducible isolation and analysis of EVs from plasma and CSF with unparalleled throughput, purity, yield, and sensitivity. Based on hi-EXODUS-NGS and hi-EXODUS-MS integrative analysis, transcriptomic and proteomic profiling of EVs will be developed to discover and detect EV-derived multi-class biomarkers for AD diagnosis.PROJECT NARRATIVE One of the significant challenges for clinical validation and application of circulating EVs in AD diagnosis is the difficulties in efficiently isolating EVs from complicated biofluids with sufficient yield and purity for accurate interpretation. Our technique could address the unmet needs for EV isolation in AD studies, which will facilitate early diagnosis and targeted therapy of AD as well as accelerate our understanding of AD pathogenesis and propagation. Moreover, our study will develop and validate a new methodology and workflow for purification, profiling, and integrative analysis of EV-derived biomolecules, providing substantial benefits to the EV research community.