Clinical trial NCT06059872: Biomarkers of Reaction To HIIT Exercise
Official title: What Makes a Responder, a Responder? Biomarkers to Help Identify Responders and Resistors to High-intensity Interval Training for Lower Extremity Chronic Stroke
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Stroke
Stroke Rehabilitation
Lower Extremity Weakness, Spastic
Walking, Difficulty
Keywords: Predictors of Stroke Rehabilitation
Biomarkers of Stroke Rehabilitation
Exercise Intervention
Neuroimaging
Lead sponsor: VA Office of Research and Development
Sponsor class: FED
Collaborators: name: Atlanta VA Medical Center
First posted: 2023-09-29
Enrollment: 55
Sex: ALL
Minimum age (years): 18
Maximum age (years): 89
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: 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 overall study protocol with pre-, during-, and post-intervention measurements. The 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.
Primary purpose: TREATMENT

Brief summary: 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.

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.

Eligibility criteria: 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

Primary outcomes:
measure: 10 m walk test on a GAITRite mat
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
measure: Timed-Up-and-Go (TUG) test
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
measure: 6-minute walk test
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
Secondary outcomes:
measure: Blood lactate change during HIIT session
timeFrame: On exercise day 1, 4, 7, 10, and 28. The total number of exercise days is 36 (3 times per week for 12 weeks).
measure: MEGA-PRESS Magnetic Resonance Spectroscopy
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
measure: pseudo Continuous Arterial Spin Labeling MRI
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
measure: Graded treadmill or bike testing
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
Other outcomes:
measure: Repetition max strength test
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
measure: Global physical activity questionnaire (GPAQ)
timeFrame: baseline (week 1)
measure: Self-administered Comorbidity Questionnaire (SCQ)
timeFrame: baseline (week 1) and after the completion of 12 weeks of exercise (week 14)
Locations:
city: Decatur
country: United States
facility: Atlanta VA Medical and Rehab Center, Decatur, GA
state: Georgia
Study officials:
affiliation: Atlanta VA Medical and Rehab Center, Decatur, GA
name: Lisa C Krishnamurthy, PhD
role: PRINCIPAL_INVESTIGATOR
References: