Duchenne muscular dystrophy (DMD), a genetic mutation in the dystrophin gene that affects 1 in 3500 male births, causes rapid progressive muscle degeneration. Boys with DMD gradually lose ambulation, often in their teens, and die of respiratory and cardiac complications by their twenties or thirties. Currently, there are no definitive effective cures for DMD. While potential treatments are in trial phases, priorities of care and exercise management for patients with DMD are to prolong ambulation, maintain quality of life and improve longevity. However, there is currently a paucity of scientifically base guidelines for prescribing safe exercise management for boys with DMD. A better understanding of how physical activity leads to muscle degeneration in DMD is critical for establishing evidence-based practices for maintaining ambulation as long as possible. It remains unclear why some lower limb muscles degenerate more quickly than others in DMD (selective degeneration), despite the fact that dystrophin is deficient in all lower limb muscles. Although multiple factors could affect the pace of degeneration, our central hypothesis is that specifically for lower limb muscles in DMD, differing degree of eccentric contraction during walking across muscles significantly contributes to the selective degeneration. The goal of our work is to develop computer models to predict the impact of various activities on the progression of muscle degeneration in DMD, thereby providing scientific guidelines for DMD care and exercise management. Since walking is the most frequent and essential activity for lower limb muscles, this exploratory project will test the hypothesis that eccentric contractions estimated from musculoskeletal simulations of walking predict the patterns of muscle degeneration in the lower limb of children with DMD. This work will lead to a more scientific basis for determining exercise and designing assistive devices that promote muscle health and mobility while minimizing damage in children with DMD. We propose to integrate computer simulations, gait experiments and magnetic resonance imaging (MRI) to achieve this goal with two specific aims.
In aim 1, we will determine if muscle loads during gait - determined from computer simulations - predict selective degeneration of lower limb muscles in DMD.
In aim 2, we will determine if impaired DMD gait leads to increased muscle loads during gait. This project will provide a new innovative framework for developing rehabilitation regimens that optimize gait and prolong ambulation. The experiment-simulation framework developed in this project can be further applied to understand the influences of various other activities on the progression of DMD, and potentially on the progression of other types of muscular dystrophy, such as Becker or Limb-Girdle. The research proposed here will be crucial to develop quantitative guidelines for care and exercise management as well as in designing assistive devices that would alleviate muscle degeneration, prolonging ambulation, maintaining quality of life and improving longevity.

Public Health Relevance

Duchenne muscular dystrophy (DMD) affects 1 in 3,500 male births in the US. Boys with DMD loose ambulation in their teens and ultimately die of respiratory and/or cardiac failure in their 20's and 30's. This proposal combines medical imaging and computer modeling to determine how and why certain lower limb muscles are more prone to damage than others in DMD. Leveraging these results will lead to better and more informed strategies for prescribing safe, but healthy, exercise regimens that prolong the ambulation and improve the quality of life for boys with DMD.

Agency
National Institute of Health (NIH)
Institute
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AR068562-01A1
Application #
9112515
Study Section
Skeletal Muscle Biology and Exercise Physiology Study Section (SMEP)
Program Officer
Cheever, Thomas
Project Start
2016-03-01
Project End
2018-02-28
Budget Start
2016-03-01
Budget End
2017-02-28
Support Year
1
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Virginia
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904