# Plasma MicroRNA Biomarkers to Guide Rehabilitation Therapy After Stroke

> **NIH NIH R61** · GEORGETOWN UNIVERSITY · 2020 · $969,858

## Abstract

Abstract
Following a stroke, each patient has a specific capacity to recover function that likely hinges on their ability to
mount a neural repair response. Knowing this capacity early on would provide opportunities for personalized
medicine in stroke rehabilitation. Physicians and therapists currently have few methods to predict recovery,
and therefore have little data to guide decisions on treatment approach and length of stay. This has led to
suboptimal therapy delivery. There is, however, emerging evidence to suggest that biomarkers can accurately
predict recovery potential in order to guide therapy. Early attempts to improve motor recovery prediction used
clinical, neurophysiologic (TMS), and MRI biomarkers to develop algorithms with up to 80% accuracy. While
these are helpful, they tell us little about the biology of stroke recovery and are difficult to implement in most
rehabilitation facilities. We recently identified a panel of 5 microRNAs (miRNAs) collected from plasma on
rehab admission that can predict motor recovery with 95% accuracy. These 5 miRNAs converge on axonal
guidance and developmental biology pathways. We therefore suspect that they capture the potential to mount
a neural repair response after stroke. The overall goal of the proposal is to refine this miRNA predictive panel
using a larger number of samples from 3 studies, test it’s predictive / analytic qualities, and validate the
predictive panel in a large prospective study. R61 Phase Specific Aims: Aim #1a. Analyze stroke samples
from 3 independent studies and matched controls using discovery-based qRT-PCR. Aim #1b. Use machine
learning to develop a miRNA panel with ≥ 80% predictive ability across the 3 studies to identify patients who
achieve excellent, moderate, and poor motor recovery by 3-12 months, controlling for covariates. Aim #1c.
Develop custom qRT-PCR cards that include ~10 miRNAs in the refined panel in triplicate along with
endogenous controls. Perform analytic validation to gauge precision, accuracy, and ideal handling / storage.
R33 Phase Specific Aims: Aim #2a. Prospectively validate the miRNA panel by collecting samples from
patients with upper limb impairment admitted to 2 inpatient rehab facilities, testing sensitivity, specificity, and
positive/negative predictive value for classifying excellent, moderate, and poor motor recovery at 6 months.
Aim #2b Give the predicted recovery potential score to the treatment team upon patient discharge from the
inpatient rehabilitation facility. Use regression and chi-squared tests to assess how having this information on
the day of admission would have changed percent of time delivering specific therapies and recommended
length of stay. Tailoring rehabilitation treatment to the individual’s biological capacity to recover may lead to
greater independence and lower costs. Specifically, evidence suggests that delivering more restorative-type
therapy to the subset of patients most likely to respond improves motor outco...

## Key facts

- **NIH application ID:** 10008023
- **Project number:** 1R61NS117196-01
- **Recipient organization:** GEORGETOWN UNIVERSITY
- **Principal Investigator:** Matthew A Edwardson
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $969,858
- **Award type:** 1
- **Project period:** 2020-05-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10008023

## Citation

> US National Institutes of Health, RePORTER application 10008023, Plasma MicroRNA Biomarkers to Guide Rehabilitation Therapy After Stroke (1R61NS117196-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10008023. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*