Modeling Duchenne Muscular Dystrophy to Unravel the Complex Mechanisms of Disease Progression: from Biomechanics to Cell Physiology
Virgilio, Kelley, Biomedical Engineering - School of Engineering and Applied Science, University of Virginia
Blemker, Silvia, En-Biomed Engr Dept, University of Virginia
Duchenne muscular dystrophy is a devastating muscle wasting disease affecting 1 in 3500 boys. It is caused by the lack of the dystrophin protein, which serves as a structural link to the muscle fiber membrane. Boys are typically diagnosed around age three to five. As the disease progresses they often exhibit changes in walking patterns around age six to eight, use a wheel-chair in their teens, and die due to respiratory or cardiac malfunction in their third decade of life. Despite extensive experimental research, there remains no cure for DMD. We hypothesize that one of the reasons DMD is so difficult to treat is that multiple mechanisms contribute to disease progression, including an increased susceptibility to damage, chronic inflammation, fibrosis, and altered satellite stem cell dynamics.
We believe this is an ideal opportunity to use computational models to help unravel the complex, multifaceted nature of DMD. My dissertation developed two computational models to investigate disease mechanisms in DMD. First, we developed micromechanical models to analyze the mechanical effects of pathological changes associated with disease progression. Then we developed an agent-based model of injury and regeneration to investigate the cellular dynamics driving impaired regeneration in dystrophic muscle. These models predicted that the fibrotic microenvironment was a key regulator of function, damage susceptibility, and muscle regeneration in dystrophic muscle. Then we used these models to design an experiment to evaluate our model parameters and test our model-derived hypothesis of the effect of fibrosis on regeneration. Ultimately, the models in this thesis revealed new hypotheses about the role of the microenvironment, and provided insight into our experimental results. These models can serve as the foundation for in silico therapeutic testing, and to predict long-term chronic changes in dystrophic muscle. We believe that computational models can help us unravel the complexity of DMD to provide insight into the best therapies to treat boys living with DMD today.
PHD (Doctor of Philosophy)
skeletal muscle, Duchenne muscular dystrophy, computational modeling