title: Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility.
abstract: Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicity library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation.
authors.affiliation: Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827, USA.
authors.forename: R Jason
authors.initials: RJ
authors.lastname: Kirby
authors.affiliation: Sanford Burnham Prebys Medical Discovery Institute, Applied Bioinformatics Facility, 6400 Sanger Rd, Orlando, FL 32827, USA.
authors.forename: Feng
authors.initials: F
authors.lastname: Qi
authors.affiliation: Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827, USA.
authors.forename: Sharangdhar
authors.initials: S
authors.lastname: Phatak
authors.affiliation: Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827, USA.
authors.forename: Layton H
authors.initials: LH
authors.lastname: Smith
authors.affiliation: Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827, USA. Electronic address: smalany@sbpdiscovery.org.
authors.forename: Siobhan
authors.initials: S
authors.lastname: Malany
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000139:chemically induced*; D002478:Cells, Cultured; D019295:Computational Biology; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D006801:Humans; D057026:Induced Pluripotent Stem Cells / Q000502:physiology*; D009200:Myocardial Contraction / Q000187:drug effects; D032383:Myocytes, Cardiac / Q000502:physiology*; D012306:Risk; D012984:Software
keywords: Arrhythmia; Autocorrelation; Human induced pluripotent stem cell cardiomyocytes (hiPSC-CMs); Label-free impedance; Limit cycle; Python v2.7 software