PROJECT SUMMARY The rising number of Americans currently living with Alzheimer’s disease (AD) demands pressing therapeutic and diagnostic solutions. The consensus is that early detection is critical to delay and better manage the disease. The recent discovery of extracellular vesicles (EVs) and their potentially important cellular functions in neuronal-glial communication, synaptic plasticity, or as endocannabinoid carriers has presented them as intriguing sources for neuronal disease diagnosis and therapeutics. The growing body of functional studies have provided strong evidence that EV-based disease markers, such as active miRNAs and signaling molecules, can be identified well before the onset of symptoms or physiological detection of diseases, making them a promising source for early-stage AD detection. However, multiple technical challenges related to EV-based biomarker discovery have greatly limited its applications in clinical studies. In this STTR study that focuses on innovative EV research and detection for AD, we will apply a novel strategy for EV isolation and analysis, rigorously characterize disease-relevant EV surface proteins, and then focus on developing EV surface proteins as biosignatures for AD. EV surface proteins, consisting of receptors, transporters, channels, and enzymes, are a source of potential diagnostic biomarkers of disease and therapeutic targets. More importantly, the detection of EV surface proteins can be achieved in situ without long sample preparation procedure such as lysis, protein extraction, digestion, enrichment and so on. The proposed strategy introduces a novel platform technology for EV isolation and on-bead detection of EV surface proteins specific to AD. Accordingly, the following aims will be completed: Aim #1: Implementation of an integrated strategy for fast and effective EV isolation and cargo extraction; Aim #2: Characterization of EV surface proteins linked to AD; Aim #3: Development of on-bead detection of EV surface proteins as biosignatures for AD. By the completion of this exploratory project, we expect to establish a platform technology to detect EV surface proteins as promising AD biomarkers for further validation.