# Validation of a Point of Care Diagnostic Test for Sports Related Concussion

> **NIH NIH R01** · UNIVERSITY OF KENTUCKY · 2020 · $328,450

## Abstract

Abstract
Mild traumatic brain injury (mTBI) resulting from sports related concussion (SRC) is a substantial public health
concern with ~ 1.6 – 3.8 million injuries per year in the United States. Although extremes of head injury are
recognizable, mTBI associated with SRC is more difficult to diagnose and is complicated by subtle physical,
cognitive, and emotional symptoms that may manifest up to 48 h following a concussive blow. In preliminary
studies using a rat model of mTBI and in a small clinical trial of patients with mTBI due to motor vehicle
accidents or unintentional falls we identified a novel post translationally modified marker of neuronal injury,
ubiquitinated visinin like protein 1 (ubVILIP-1), that is released into blood rapidly after injury. To facilitate rapid
measurement of circulating ubVILIP-1 we developed a lateral flow device (LFD) that provides detection of the
biomarker in less than 20 min. The aim of the current proposal is determine if ubVILIP-1 levels can be used to
identify athletes with SRC by establishing baseline levels of the marker and then quantifying changes that
occur following SRC and to correlate ubVILIP-1 levels with clinical metrics including SCAT3 measures.

## Key facts

- **NIH application ID:** 9828116
- **Project number:** 5R01NS104289-03
- **Recipient organization:** UNIVERSITY OF KENTUCKY
- **Principal Investigator:** MARK Anthony LOVELL
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $328,450
- **Award type:** 5
- **Project period:** 2017-12-01 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9828116

## Citation

> US National Institutes of Health, RePORTER application 9828116, Validation of a Point of Care Diagnostic Test for Sports Related Concussion (5R01NS104289-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9828116. Licensed CC0.

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