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

NIH RePORTER · NIH · R41 · $110,405 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY / ABSTRACT Alzheimer'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.

Key facts

NIH application ID
10604194
Project number
3R41AG076098-01S1
Recipient
WELLSIM BIOMEDICAL TECHNOLOGIES, INC.
Principal Investigator
Yuchao Chen
Activity code
R41
Funding institute
NIH
Fiscal year
2022
Award amount
$110,405
Award type
3
Project period
2021-09-30 → 2023-09-29