Abstract
In older (45+ years) populations, sudden cardiac death (SCD) is primarily caused by ischemic heart disease while in younger populations, SCD is often due to genetic causes. Despite recent advances in risk stratification based on clinical evaluation and genetic testing, our ability to predict SCD risk in the younger population remains inadequate. Implantable cardioverter defibrillators (ICDs) have been an essential intervention to reduce the number of out-of-hospital cardiac arrests in patients determined to be at risk of SCD. Nevertheless, one third of patients with an ICD receive inappropriate shocks and are exposed to infection without clear benefit. In addition, some children and young adults receive an ICD that will never deliver a shock even after decades of follow-up. No clear guidelines have been established to detect SCD-predisposing conditions due to cost, sensitivity, and specificity of testing modalities. Human iPSC-derived cardiomyocytes (hiPSC-CMs) are a widely recognized and reliable in vitro platform to study clinical phenotypes but have never been used in the context of SCD risk prediction. We hypothesize that we can establish an hiPSC-CMs cellular model to predict SCD risk. Sixty individuals were recruited and classified in one of five categories, ranging from healthy controls with no known cardiac disease (category 1) to individuals that show the highest SCD risk (category 5). These 5 categories are defined by 3 main parameters: 1) absence or presence of ICD, 2) whether the ICD was placed as primary or secondary prevention and 3) the number of shocks received after ICD implantation. hiPSCs were reprogrammed using blood samples and then differentiated into cardiomyocytes. Molecular and electrophysiology measurements were performed for the different risk categories using high-throughput systems. hiPSC-CMs were assayed by single-cell calcium imaging, microelectrode array and automated action potential and current recordings. In vitro measurements revealed that specific parameters such as field potential duration correlate with the SCD risk and outcome. In conclusion, this study will provide a cellular-based tool to determine patient-specific SCD risk in order to advance medical care for at-risk patients and their family members.
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