# Quantification of brain-derived extracellular vesicle microRNAs in blood by a liposome-mediated CRISPR assay for traumatic brain injury detection

> **NIH NIH R21** · TULANE UNIVERSITY OF LOUISIANA · 2022 · $437,348

## Abstract

Abstract
Traumatic brain injury (TBI) affects 10 million people annually, with 10-15% of these individuals suffering chronic
brain disabilities. Diagnosis of TBI remains a clinical challenge because current tests are unable to classify TBI
severity or predict patient recovery due to complex and unique injury states that cannot be analyzed fully using
imaging techniques or single-marker assays. Thus, there is an urgent need for a TBI diagnosis that can rapidly
and accurately characterize TBI and identify patients at risk for long-term brain impairment. Extracellular vesicles
(EVs) in minimally invasive sample types have great potential as biomarkers for TBI since they encapsulate
biomarker signatures specific to TBI, are released by major brain cell-types, and their concentration increases
in the circulation after TBI. However, EV-based tests utilize lengthy and multi-step EV isolation methods that are
impractical for clinical lab use. To overcome these obstacles, we developed a liposome-EV fusion system, which
integrates EV isolation and TBI biomarker detection in a single step, to analyze a panel of TBI-specific miRNA
markers in EVs released from multiple brain cell-types (e.g., neurons, glia, and astrocytes) without prior EV
purification. Specificity is achieved through the interaction of brain cell-type-specific EV surface markers with
matching antibodies on the surface of liposomes loaded with ultrasensitive miRNA exponential amplification
reaction (EXPAR) system reagents to induce liposome-EV fusion. After this fusion event, the EXPAR reagents
mix with the EV miRNA cargo to create rapidly detectable signal. Since EXPAR reactions only occur after
antibody-mediated fusion events, patient samples can be directly analyzed without lysis or miRNA isolation
procedures to minimize handling or equipment requirements. Preliminary plasma and CSF data indicate our
system can distinguish a panel of EV markers among TBI and non-TBI cases. We propose to evaluate the clinical
utility of this EXPAR-FDS liposome-assay by: 1) establishing a one-step assay to directly quantify TBI-associated
markers in brain-specific EVs in unprocessed patient plasma; and 2) developing a predictive model for rapid TBI
classification and to predict future recovery to provide information on injury progression and treatment efficacy,
and to conduct a clinical validation in a longitudinal cohort using paired plasma and CSF samples from TBI and
non-TBI patients. This well-characterized cohort will allow our model to make an initial prediction immediately
after injury and check prediction accuracy using follow-up samples. This study aims to overcome current
diagnostic limitations by analyzing a panel of miRNA markers in EVs released by multiple brain cell-types to
increase clinical specificity and to comprehensively characterize the unique and complex disease state of each
individual after a TBI. We believe that our streamlined assay that analyzes minimally invasive plasma samples
wi...

## Key facts

- **NIH application ID:** 10575436
- **Project number:** 1R21NS130542-01
- **Recipient organization:** TULANE UNIVERSITY OF LOUISIANA
- **Principal Investigator:** Tony Y. Hu
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $437,348
- **Award type:** 1
- **Project period:** 2022-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10575436

## Citation

> US National Institutes of Health, RePORTER application 10575436, Quantification of brain-derived extracellular vesicle microRNAs in blood by a liposome-mediated CRISPR assay for traumatic brain injury detection (1R21NS130542-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10575436. Licensed CC0.

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