Why the study?
Induced pluripotent stem cell-derived cardiomyocytes are an emerging model for studying drug effects and disease, but an easy-to-use, easy-to-teach, and reproducible software tool to measure extracellular field potentials was needed.
The EFP-Analyzer is a highly reproducible, semi-automated software tool for measuring extracellular field potentials in iPSC-derived cardiomyocytes, accurately detecting drug- and mutation-induced changes.
Rationale Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are an emerging model for determining drug effects and modeling disease. Specialized devices can generate Extracellular Field Potential (EFP) measurements from these cells, analogous to the ventricular complex of the electrocardiogram. Objective The objective of this study was to develop an easy-to-use, easy-to-teach, reproducible software tool to measure EFPs. Methods-Results We present the EFP-Analyzer (EFPA), a semi-automized analyzer for EFP traces, which identifies and averages beats, identifies landmarks, and calculates intervals. We evaluated the tool in an analysis of 358 EFP traces from 22 patient-derived lines. We analyzed spontaneously beating iPSC-CMs, as well as optically paced iPSC-CMs through channelrhodopsin. We developed stringent quality criteria and measured EFP intervals, including Field Potential Duration (FPD). FPD from optically paced iPSC-CMs were shorter than those of spontaneously beating iPSC-CMs (283.7.0±54.2 vs. 293.0±47.5, p: 0.32, respectively). We further analyzed the usability and data replicability of EFPA through an inter-intra observer analysis. Correlation coefficient for inter-reader tangent and threshold measurements for these FPD ranged between r: 0.93-1.00. Bland-Altman plots comparing inter observer results for spontaneously beating and paced iPSC-CMs showed 95% limits of agreement (−13.6 to 19.4ms and −13.2 to 15.3ms, respectively). The EFP-analyzer could accurately detect FPD prolongation due to drug (moxifloxacin) or pathogenic loss of function mutations ( CACNA1C N639T). This program is available for download at https://github.com/kroncke-lab/EFPA . The instructions will be available at the same listed website under the README section of the Github main page. Conclusions The EFP-Analyzer tool is a useful tool that enables the efficient use of iPSC-CMs as a model to study drug effects and disease.
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Patel et al. (2024) studied this question.
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