Arrhythpy: An Automated Tool to Quantify and Classify Arrhythmias in Ca2+ Transients of iPSC-Cardiomyocytes

Arrhythmias constitute an intricate and clinically significant phenomenon of great importance in various research areas. Ca2+ homeostasis plays a pivotal role in forming rhythmic contractions in the heart, and its dysregulation has emerged as a critical component in developing arrhythmias. Until now, however, the quantification of arrhythmias has been limited to indirect measurements via Ca2+ sparks, electrophysiological parameters, or manual classification, which can lead to human bias. We aimed to develop an analysis platform that directly and automatically analyzes arrhythmias in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Here, we present Arrhythpy, a robust and automated open-source program to quantify and classify confocal microscopy-based Fluo-4 Ca2+ transients to generate a measure of arrhythmia. In contrast to other automated and semi-automated analysis tools, that measure established parameters such as time-to-peak, Arrhythpy directly analyzes the degree of arrhythmia in a Ca2+ transient. We demonstrate its utility in monitoring Ca2+ transient-based arrhythmias in atrial and ventricular iPSC-CMs of healthy individual and cardiac disease patients, including dilated cardiomyopathy (DCM) and Takotsubo syndrome (TTS). Arrhythpy was validated by analyzing drug-treated iPSC-CMs, confirming the beating frequency effects of compounds that directly activate (Isoprenaline) or inhibit (Metoprolol) beta-adrenergic signaling. Arrhythpy analysis of iPSC-CMs of TTS patients recapitulated TTS phenotypes, including atrial arrhythmia that could be normalized with beta-blocker treatment. The programs adaptable framework enables arrhythmic pattern analysis in various cell types using periodic dye-based line scan measurement techniques, applicable to single cells or layered cultures.