Nidhi Patel, Alex Shen, Yuko Wada, Marcia Blair, Devyn Mitchell, Loren Vanags, Suah Woo, Matthew Ku, Kundivy Dauda, William Morris, Minjoo Yang, Björn C Knollmann, Joe-Elie Salem, Andrew M Glazer, Brett M Kroncke
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引用次数: 0
Abstract
Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have emerged as a pivotal model for research. Specialized devices can generate Extracellular Field Potential (EFP) measurements from these cells, analogous to the ventricular complex of the electrocardiogram. However, electrophysiological analysis can be complex and requires specialized expertise, posing a barrier to broader adoption in non-specialized labs. We present the EFP-Analyzer (EFPA), a semi-automized analyzer for EFP traces, which identifies and averages beats, identifies landmarks, and calculates intervals. We demonstrate an analysis of 358 EFP traces from 22 patient-derived lines. We analyzed spontaneously beating iPSC-CMs and optically paced iPSC-CMs through channelrhodopsin. We developed stringent quality criteria and measured EFP intervals, including Field Potential Duration (FPD). 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 19.4 ms and - 13.2 to 15.3 ms, respectively). EFPA could accurately detect FPD prolongation due to drug (moxifloxacin) or pathogenic loss of function mutations (CACNA1C N639T). This program and instructions are available for download at https://github.com/kroncke-lab/EFPA .
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