SEP 10, 2025 11:00 AM EDT

Unlocking the Proteomic Landscape of CSF-Derived EVs: A New Pathway for Neurology Biomarker Discovery

Sponsored by: Olink Proteomics
Speakers
  • David R. Walt, PhD

    Hansjörg Wyss Professor of Biologically Inspired Engineering, Harvard Medical School, Brigham and Women's Hospital, Wyss Institute at Harvard University
    BIOGRAPHY
  • Ryan Lamers, PhD

    Product Management, Olink, part of Thermo Fisher Scientific

Event Date & Time
Date: September 10, 2025
Time: 8:00 AM (PT), 11:00 AM (ET), 5:00 PM (CET)
Abstract

Brain-derived extracellular vesicle (EV) biomarkers represent a promising frontier for liquid biopsy development targeting the nervous system. They offer strong potential for enabling minimally invasive diagnostics for neurological and psychiatric diseases. However, analyzing the proteomic content of EVs is technically challenging due to the low abundance of proteins in EV fractions.

In this webinar, Dr. David Walt—renowned scientist and co-founder of multiple biotechnology companies—will present a large-scale, unbiased study that addresses these challenges using the highly specific and sensitive Olink® Explore HT platform. By profiling over 5,400 proteins in cerebrospinal fluid (CSF) fractions separated by size exclusion chromatography, Dr. Walt and his team created a first-of-its-kind reference dataset to help distinguish EV-associated proteins from soluble or cleaved counterparts. This work lays the foundation for building a robust, bioinformatics-driven resource to support future biomarker discovery in neurology.

The session will also feature commentary from Olink’s Ryan Lamers, who will share additional details highlighting the unique capabilities of Olink technology in EV research.

Learning Objectives:

  • Learn how the highly sensitive and specific Olink® Explore HT platform overcomes key challenges in proteomic profiling of extracellular vesicles (EVs).
  • Explore how protein biomarkers can be used to distinguish EV-associated proteins from soluble or cleaved counterparts.
  • Understand how this study supports the development of a robust reference dataset to advance bioinformatics-driven biomarker discovery and enable the development of minimally invasive diagnostic tools in neurology.

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