In the United States, 2.8 million people every year seek medical attention for traumatic brain injury (TBI), of which 80% are considered to have a mild TBI (i.e. concussion). Even in those with mild injuries, 10-20% of individuals will suffer long-term disability including seizures and emotional and behavioral issues. One of the primary challenges in TBI care is appropriately classifying this heterogeneous injury and identifying patients at risk for these chronic impairments. Conventional imaging studies, including magnetic resonance imaging (MRI) and computed tomography (CT), are commonly used to classify TBI, but do not reliably capture the full extent of the injury, particularly in those patients with mild injuries. Currently, there are few molecular markers to assist in the assessment of an individual's unique injury and subsequent recovery and biomarkers are desperately needed in the field that correlate with these varied endophenotypes, track the progress of the disease, and predict clinical outcomes. To address this challenge, we propose to develop a microchip-based platform that can be used to characterize TBI and its recovery using the RNA cargo found in brain-derived circulating extracellular vesicles (EVs), including exosomes. Unlike prior work that has mainly focused on single biomarkers, our approach measures a panel of circulating EV miRNA markers processed with machine learning algorithms, to more comprehensively capture the state of the injured and recovering brain. Our proposal combines surface marker-specific nanomagnetic isolation of brain-derived EVs from a variety of cell types, biomarker discovery using RNA sequencing, and machine learning processing of EV miRNA cargo to measure the state of injury and recovery in TBI.

Public Health Relevance

Nanoscale exosomes are known to shed from brain cells into the blood stream, carrying with them the molecular signatures that can be used to better diagnose and treat injuries, such as traumatic brain injury. We propose an innovative, clinically practical approach to probe the RNA contained within these nanoscale vesicles to better understand a patient's injury and recovery to better guide treatment. Our rapid and easily multiplexed platform has great potential for non-invasive diagnostics and monitoring of both secondary injury progression and drug efficacy, offers tremendous benefits for patients.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
4R33MH118170-03
Application #
10019696
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Meinecke, Douglas L
Project Start
2018-09-19
Project End
2023-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104