ADRC Developmental Projects

2023-2024 ADRC Developmental Project Announcement

Application Deadline: February 6, 2023
ADRC Developmental Projects RFA

ADRC Developmental Projects

Each year, the University of Pennsylvania (Penn) Alzheimer’s Disease Research Center (ADRC) will fund up to two developmental projects, pending availability of funds, to support basic, translational or clinical research within the theme of heterogeneity in the Alzheimer’s Disease (AD) continuum.

Special emphasis will be given to projects that address the theme of AD heterogeneity, but consideration will also be given for projects that are more novel, offer an area of research underrepresented in the ADRC or at Penn, and are transdisciplinary, expanding the breadth of collaborations.

Funded Projects

PI: Jina Ko, PhD

Alzheimer’s disease (AD) is the most common cause of major neurocognitive disorders that affects more than 50 million people worldwide. The ability to diagnose AD at an early stage can open up opportunities to benefit patients and their carers and develop new treatment options. Recent studies have shown that a subset of extracellular vesicles (EV) carries important molecular information, which can detect cognitive declines of AD patients in the preclinical stage. However, it has been difficult to isolate these EV subtypes (e.g., brain-derived EV, mitovesicles) due to their rarity and heterogeneity. To solve these challenges, we aim to develop an ultra-high sensitive single EV BEAMing (beads, emulsion, amplification, magnetics) method that can profile EV at a single particle level, and apply it to diagnose AD before the onset of the disease. The technology combines emulsion PCR and flow cytometry to achieve high multiplexing (>20), high throughput (~106 EV/hr), and single vesicle sensitivity. We will apply this platform to i) resolve EV heterogeneity and discover rare EV subtypes for disease biomarkers, ii) clearly distinguish AD from other neurodegenerative diseases, and iii) identify AD at an early stage to provide the best possible clinical outcome.