Biomarkers of Reaction To HIIT Exercise (BReaTHE)

November 14, 2023 updated by: VA Office of Research and Development

What Makes a Responder, a Responder? Biomarkers to Help Identify Responders and Resistors to High-intensity Interval Training for Lower Extremity Chronic Stroke

Stroke survivors with lower limb disability can improve their walking speed with high-intensity interval training (HIIT) rehabilitation therapy. However, some individuals may not respond to HIIT even when fully adherent to the program. To address this, the investigators propose to build a predictive model that identifies if a Veteran with chronic subcortical stroke will improve their walking speed with HIIT by incorporating blood lactate as an early predictor of exercise response, and inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and regional cerebral blood flow (CBF) as predictors of the brain's potential to respond, while also taking into consideration other factors such as comorbidities, demographics, and fitness levels.

Study Overview

Detailed Description

Most chronic subcortical stroke survivors have difficulty walking, but few predictors can help identify if a patient will respond to an exercise regimen and improve their function. To enhance precision rehabilitation for chronic subcortical stroke patients, personalized aerobic exercise interventions are crucial. This requires the development of innovative technologies that can identify the essential neurobiological factors to predict intervention response and enable clinicians to determine individualized rehabilitation targets. Lactate is one exciting new target that acts as a molecular messenger between the periphery and the brain. For lactate to have an impact on other organs, including the brain, there must be a substantial increase in its level in the bloodstream from baseline. When the blood lactate threshold is surpassed during exercise, lactate acts on the brain metabolically via the TCA cycle. Embedded within the TCA cycle is the means to increase or decrease neurotransmitter concentrations such as GABA and glutamate. Gamma-aminobutyric acid (GABA), the brain's major inhibitory neurotransmitter, is a new treatment target that promotes neural plasticity during stroke rehabilitation. Drawing from the framework of personalized rehabilitation approaches and our preliminary data, the investigators propose to build a predictive model that can identify if a chronic subcortical stroke patient will respond to exercise training. This model aims to predict improvements in walking speed by incorporating blood lactate as an early predictor of exercise response and GABA and cerebral blood flow (CBF) as predictors of the brain's potential to respond, in addition to other influencing factors such as comorbidities, demographics, and fitness levels. The overarching hypothesis is that robust neurophysiological factors driven by lactate can differentiate responders from resistors and that these factors can be applied clinically as biomarkers to predict functional outcomes after a 12-week HIIT intervention. The investigators will assess improvements in walking speed in 48 Veterans with lower limb disability due to chronic subcortical stroke in response to a 36-session (12-week) HIIT intervention. After the intervention, each adherent participant who improves their walking speed to greater than 0.6 m/s will be categorized as a responder while each adherent participant who does not improve their walking speed will be categorized as a resistor. At baseline and after 12 weeks of HIIT the investigators will evaluate walking speed, balance, leg strength, and endurance to identify resistors and responders to HIIT and collect a) GABA from the primary sensory-motor leg area using single-voxel magnetic resonance spectroscopy, b) CBF from the whole brain using pseudo-Continuous Arterial Spin Labeling MRI and c) VO2 max to evaluate change in CRF. During the intervention, the investigators will collect blood lactate via finger prick during sessions 1, 4, 7, 10, and 28 to assess its potential as an early predictor of exercise response. In aim 1 the investigators determine if surpassing the lactate threshold during the first 4 weeks of HIIT predicts the change in walking speed to ≥ 0.6 m/s, from pre- to post-HIIT. If lactate proves to be a robust early marker of functional response to exercise, the investigators will have an easy-to-deploy predictor of who will best benefit from HIIT. In aim 2 the investigators will determine if (a) baseline GABA and/or CBF predict improvements in walking speed from baseline to after HIIT and (b) if a change in GABA and/or CBF relate to a change in walking speed. The investigators aim to establish neurophysiological correlates of improving function with HIIT to better understand the mechanisms. Finally, in aim 3 the investigators will a predictive machine learning algorithm of who will improve their walking speed with HIIT using factors of blood lactate, baseline GABA and CBF, baseline leg weakness and VO2-max, pre-stroke fitness, age, sex, and comorbidities. The overarching objective is to develop a model to predict which Veteran with chronic stroke will respond to a 12-week exercise program.

Study Type

Interventional

Enrollment (Estimated)

55

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Georgia
      • Decatur, Georgia, United States, 30033-4004
        • Atlanta VA Medical and Rehab Center, Decatur, GA
        • Contact:
        • Principal Investigator:
          • Lisa C Krishnamurthy, PhD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • chronic left or right subcortical stroke as defined by 6 months or more after a cardiovascular accident
  • lower extremity motor impairment due to stroke that causes a walking speed of less than 0.6 m/s during a 10m walk
  • Veteran status

Exclusion Criteria:

  • MRI contraindications, including implanted cardiac pacemakers and severe claustrophobia
  • any neurodegenerative condition other than stroke that may lead to lower extremity impairment
  • a visual or auditory impairment that may hinder study procedures
  • any medical condition that would preclude participation in a physical exercise intervention program

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Chronic Stroke with lower limb disability
The investigators will enroll 55 Veterans with chronic subcortical stroke in the 12-week HIIT intervention, with the expectation that 48 participants (85%) will complete the entire program. In our experience, 65% of participants will respond to the HIIT intervention, resulting in an estimated 31 responders and 17 resistors. Each chronic subcortical stroke participant will be asked to participate in the HIIT study protocol. Classification of resistor or responder: A responder to the 12-week HIIT intervention will be defined as a participant who increases their walking speed to greater than 0.6 m/s. A resistor to the intervention will be defined as a participant who does not increase their walking speed to greater than 0.6 m/s.
HIIT consists of three weekly 25-60 minute cycling sessions for 12 weeks at the Atlanta VA, administered by a trained exercise physiologist, for a total of 36 HIIT sessions.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
10 m walk test on a GAITRite mat
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess short-distance walking speed and gait characteristics.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
Timed-Up-and-Go (TUG) test
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess short-distance walking and postural control.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
6-minute walk test
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess endurance.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Blood lactate change during HIIT session
Time Frame: On exercise day 1, 4, 7, 10, and 28. The total number of exercise days is 36 (3 times per week for 12 weeks).
To assess if the participant increases their blood lactate during the HIIT session.
On exercise day 1, 4, 7, 10, and 28. The total number of exercise days is 36 (3 times per week for 12 weeks).
MEGA-PRESS Magnetic Resonance Spectroscopy
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess GABA from the ipsilesional and contralesional leg areas of the brain.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
pseudo Continuous Arterial Spin Labeling MRI
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess whole brain regional cerebral blood flow.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
Graded treadmill or bike testing
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To estimate VO2-max.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Repetition max strength test
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess the leg strength of the affected and less affected leg.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
Global physical activity questionnaire (GPAQ)
Time Frame: baseline (week 1)
To assess pre-stroke fitness levels.
baseline (week 1)
Self-administered Comorbidity Questionnaire (SCQ)
Time Frame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
To assess the presence and burden of comorbidities.
baseline (week 1) and after the completion of 12 weeks of exercise (week 14)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Lisa C Krishnamurthy, PhD, Atlanta VA Medical and Rehab Center, Decatur, GA

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

January 1, 2024

Primary Completion (Estimated)

June 1, 2027

Study Completion (Estimated)

December 1, 2027

Study Registration Dates

First Submitted

September 18, 2023

First Submitted That Met QC Criteria

September 22, 2023

First Posted (Actual)

September 29, 2023

Study Record Updates

Last Update Posted (Estimated)

November 17, 2023

Last Update Submitted That Met QC Criteria

November 14, 2023

Last Verified

November 1, 2023

More Information

Terms related to this study

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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