Computational and experimental study of Hypertrophic Cardiomyopathy modelled in iPSC-CMs

Hypertrophic Cardiomyopathy (HCM) is one of the most common cardiac disorders characterized by a thickening of the ventricular wall and mutations in sarcomeric genes. Since the understanding of HCM mechanisms and treatments to reverse its phenotype are still lacking, the study of the disease with induced pluripotent stem cells-derived cardiomyocytes (iPSC-CMs) could improve HCM knowledge. Based on promising iPSC-CM results, new cardiomyocytes computational models have been built to model cardiac diseases and test new drugs. This thesis aims to fit parameters of iPCS-CM AP models to recapitulate data acquired from HCM-derived cells. In particular a genetic algorithm is used to find a profile of conductances that could represent HCM features. Experiments on HCM and healthy cells have been conducted to compare real and computational data. The Paci iPSC-CMs model is found to better replicate HCM mechanisms, such as AP prolongation, ICaL increase and higher predisposition to develop arrhythmias compared to healthy cells. This study demonstrates the potential of cardiac computational models to describe HCM in iPSC-CMs, to highlight differences in disease mechanism between adult CMs and iPSC-CMs, and to improve the understanding of HCM.