Multiscale Modeling of Inherited Cardiomyopathies and Therapeutic Interventions

Treatment options for the 5.7 million Americans afflicted with heart failure remain limited, with ~50% of patients dying within 5 years of their diagnosis. Nearly 500,000 Americans are afflicted with familial hypertrophic cardiomyopathy and another 60,000 suffer from familial dilated cardiomyopathy, both of which are caused by genetic mutations that alter sarcomeric proteins, such as myosin. This U01 project seeks to mitigate these dire numbers through innovative research that could ultimately lead to the development of personalized multiscale computer models for optimizing heart failure treatments, including pharmaceutical interventions. To accomplish this goal, the structural scales between single myosin molecules and organ-level ventricular function, as well as the time scales from individual heart beats to long-term ventricular remodeling will need to be bridged. We propose to develop, calibrate, and validate a multiscale computer model that predicts how modulation at the molecular-level, via mutation and/or pharmaceutical alteration of myosin, impacts chronic cardiac performance. Experiments will be conducted to longitudinally measure changes in structure and function at multiple scales. This data will drive the development and validation of multiscale growth and remodeling algorithms that, for the first time, will be able to account for the alterations in both the structure and function of the ventricle. The specific aims of the proposed work are to: (1) Integrate a multi-step myosin kinetic model into an organ-level finite element framework for predicting the effects of mutation and pharmaceutical treatment, (2) Develop growth and remodeling algorithms to model chronic changes in ventricular structure and function resulting from mutation and pharmaceutical treatment, and (3) Calibrate and validate the multiscale model using chronic measurements made at different spatial and temporal scales. The software and techniques developed in this project can be used to help accelerate translational research that focuses on the long-term effects resulting from molecular modulation of cardiac contractile function. In the future, one could envision clinicians testing drug treatments in-silico and selecting the intervention with the greatest long-term benefit for their patient.