Connecting Subcellular Electrophysiology to Patient Arrhythmia: A Case Study of Amiodarone

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PROJECT SUMMARY Abnormalities in cardiac rhythm, or arrhythmia, affect more than 2% of individuals and are responsible for the majority of cases of sudden cardiac death. Understanding human cardiac electrophysiology is crucial to our ability to prevent and treat arrhythmias. A critical obstacle to this is that cardiac rhythm involves both spatial and temporal coordination of ion channel activity in heart muscle cells. However, while robust temporal characterization at the single-cell level is feasible, linking this with emergent organ-level spatial manifestations of cardiac arrhythmia is far more difficult. Despite a significant disease burden, current antiarrhythmic drug therapies often lack therapeutic efficacy and are hampered by significant side effects. Amiodarone is a commonly prescribed antiarrhythmic drug, with multiple clinical indications. While effective, amiodarone exhibits significant extracardiac toxicity and affects multiple currents and ion channels, making it difficult to characterize. Further constraining this effort is the limited availability of clinical samples of healthy human cardiac cells and tissues for experimentation, necessitating the use of suboptimal animal model surrogates. Here, I propose a high- throughput integrated platform of single-cell and tissue analyses in human-derived induced pluripotent stem cell cardiomyocytes (hiPSC-CMs) to robustly characterize the electrophysiology, calcium handling, and biomechanics of human-derived cells treated with antiarrhythmic molecules. I will use a computational model of hiPSC-CMs to link these data. I will then complete the same analyses in isolated patient ventricular myocytes, an innovative approach. I will then use this data to train a computational ventricular myocyte model and link these via established methods. Here, I take a bottom-up approach to understand mechanisms of success and failure of the most commonly prescribed antiarrhythmic drug, amiodarone. My goal is to build a framework to gain insight into rational design of the next generation of therapeutics that are safe and effective.