Differential roles of two delayed rectifier potassium currents in regulation of ventricular action potential duration and arrhythmia susceptibility

Arrhythmias result from disruptions to cardiac electrical activity, although the factors that control cellular action potentials are incompletely understood. We combined mathematical modelling with experiments in heart cells from guinea pigs to determine how cellular electrical activity is regulated. A mismatch between modelling predictions and the experimental results allowed us to construct an improved, more predictive mathematical model. The balance between two particular potassium currents dictates how heart cells respond to perturbations and their susceptibility to arrhythmias.

[1]  Francis A. Ortega,et al.  Dynamic clamp in cardiac and neuronal systems using RTXI. , 2014, Methods in molecular biology.

[2]  Eric A. Sobie,et al.  Parameter sensitivity analysis of stochastic models provides insights into cardiac calcium sparks. , 2013, Biophysical journal.

[3]  E. Marder,et al.  Similar network activity from disparate circuit parameters , 2004, Nature Neuroscience.

[4]  B. Rodríguez,et al.  Experimentally calibrated population of models predicts and explains intersubject variability in cardiac cellular electrophysiology , 2013, Proceedings of the National Academy of Sciences.

[5]  A. V. van Ginneken,et al.  Long‐QT syndrome‐related sodium channel mutations probed by the dynamic action potential clamp technique , 2006, The Journal of physiology.

[6]  Natalia A. Trayanova,et al.  Disrupted Calcium Release as a Mechanism for Atrial Alternans Associated with Human Atrial Fibrillation , 2014, PLoS Comput. Biol..

[7]  Eric A Sobie,et al.  There and back again: Iterating between population-based modeling and experiments reveals surprising regulation of calcium transients in rat cardiac myocytes. , 2016, Journal of molecular and cellular cardiology.

[8]  Kalyanmoy Deb,et al.  Analysing mutation schemes for real-parameter genetic algorithms , 2014, Int. J. Artif. Intell. Soft Comput..

[9]  A. Garfinkel,et al.  Early afterdepolarizations and cardiac arrhythmias. , 2010, Heart rhythm.

[10]  A. Karma Electrical alternans and spiral wave breakup in cardiac tissue. , 1994, Chaos.

[11]  Luke Domanski,et al.  Quantifying the origins of population variability in cardiac electrical activity through sensitivity analysis of the electrocardiogram , 2013, The Journal of physiology.

[12]  E. Marder,et al.  Failure of averaging in the construction of a conductance-based neuron model. , 2002, Journal of neurophysiology.

[13]  P. Taggart,et al.  Early afterdepolarizations promote transmural reentry in ischemic human ventricles with reduced repolarization reserve , 2016, Progress in biophysics and molecular biology.

[14]  Maria Groppi,et al.  How different two almost identical action potentials can be: a model study on cardiac repolarization. , 2010, Mathematical biosciences.

[15]  M. Rocchetti,et al.  Rate dependency of β‐adrenergic modulation of repolarizing currents in the guinea‐pig ventricle , 2006, The Journal of physiology.

[16]  Eric A Sobie,et al.  Quantification of repolarization reserve to understand interpatient variability in the response to proarrhythmic drugs: a computational analysis. , 2011, Heart rhythm.

[17]  N. P. Borgstrom,et al.  Targeting the late component of the cardiac L-type Ca2+ current to suppress early afterdepolarizations , 2015, The Journal of general physiology.

[18]  K. Ono,et al.  Time‐dependent block of the slowly activating delayed rectifier K+ current by chromanol 293B in guinea‐pig ventricular cells , 2000, British journal of pharmacology.

[19]  Eric A Sobie,et al.  Yoga for the sinoatrial node: sarcoplasmic reticulum calcium release confers flexibility. , 2013, Journal of molecular and cellular cardiology.

[20]  D. Bers,et al.  A novel computational model of the human ventricular action potential and Ca transient. , 2010, Journal of Molecular and Cellular Cardiology.

[21]  N. Tohse,et al.  Calcium-sensitive delayed rectifier potassium current in guinea pig ventricular cells. , 1990, The American journal of physiology.

[22]  E. Sobie Parameter sensitivity analysis in electrophysiological models using multivariable regression. , 2009, Biophysical journal.

[23]  Kevin Burrage,et al.  Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm , 2016, Progress in biophysics and molecular biology.

[24]  Peter J. Hunter,et al.  Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models , 2011, BMC Systems Biology.

[25]  Trine Krogh-Madsen,et al.  Improving cardiomyocyte model fidelity and utility via dynamic electrophysiology protocols and optimization algorithms , 2016, The Journal of physiology.

[26]  Prashanthan Sanders,et al.  Epistatic effects of potassium channel variation on cardiac repolarization and atrial fibrillation risk. , 2012, Journal of the American College of Cardiology.

[27]  L. Izu,et al.  Beta-adrenergic stimulation reverses the IKr–IKs dominant pattern during cardiac action potential , 2014, Pflügers Archiv - European Journal of Physiology.

[28]  Trine Krogh-Madsen,et al.  Cell-Specific Cardiac Electrophysiology Models , 2015, PLoS Comput. Biol..

[29]  Antonio Zaza,et al.  Reverse rate dependency is an intrinsic property of canine cardiac preparations. , 2009, Cardiovascular research.

[30]  Trine Krogh-Madsen,et al.  Rapid Genetic Algorithm Optimization of a Mouse Computational Model: Benefits for Anthropomorphization of Neonatal Mouse Cardiomyocytes , 2012, Front. Physio..

[31]  Edward J. Vigmond,et al.  Atrial cell action potential parameter fitting using genetic algorithms , 2005, Medical and Biological Engineering and Computing.

[32]  Ronald Wilders,et al.  UvA-DARE ( Digital Academic Repository ) HERG channel ( dys ) function revealed by dynamic action potential clamp technique , 2004 .

[33]  S Nattel,et al.  Effects of the chromanol 293B, a selective blocker of the slow, component of the delayed rectifier K+ current, on repolarization in human and guinea pig ventricular myocytes. , 1998, Cardiovascular research.

[34]  Kevin Burrage,et al.  In Vivo and In Silico Investigation Into Mechanisms of Frequency Dependence of Repolarization Alternans in Human Ventricular Cardiomyocytes , 2016, Circulation research.

[35]  Erik De Schutter,et al.  Complex Parameter Landscape for a Complex Neuron Model , 2006, PLoS Comput. Biol..

[36]  A. Garfinkel,et al.  Mechanisms of Discordant Alternans and Induction of Reentry in Simulated Cardiac Tissue , 2000, Circulation.

[37]  Edward J. Vigmond,et al.  Fitting Membrane Resistance along with Action Potential Shape in Cardiac Myocytes Improves Convergence: Application of a Multi-Objective Parallel Genetic Algorithm , 2014, PloS one.

[38]  E. Marder Variability, compensation, and modulation in neurons and circuits , 2011, Proceedings of the National Academy of Sciences.

[39]  Socrates Dokos,et al.  Parameter estimation in cardiac ionic models. , 2004, Progress in biophysics and molecular biology.

[40]  Alan Garfinkel,et al.  Perspective: a dynamics-based classification of ventricular arrhythmias. , 2015, Journal of molecular and cellular cardiology.

[41]  Antonio Zaza,et al.  Rate dependency of delayed rectifier currents during the guinea‐pig ventricular action potential , 2001, The Journal of physiology.

[42]  Ronald Wilders,et al.  Dynamic clamp: a powerful tool in cardiac electrophysiology , 2006, The Journal of physiology.

[43]  David J. Christini,et al.  Real-Time Linux Dynamic Clamp: A Fast and Flexible Way to Construct Virtual Ion Channels in Living Cells , 2001, Annals of Biomedical Engineering.

[44]  D. Christini,et al.  Anthropomorphizing the mouse cardiac action potential via a novel dynamic clamp method. , 2009, Biophysical journal.

[45]  László Virág,et al.  Restricting Excessive Cardiac Action Potential and QT Prolongation: A Vital Role for IKs in Human Ventricular Muscle , 2005, Circulation.

[46]  Zhong Jian,et al.  Sequential dissection of multiple ionic currents in single cardiac myocytes under action potential-clamp. , 2011, Journal of molecular and cellular cardiology.

[47]  Alan Garfinkel,et al.  Arrhythmogenic consequences of myofibroblast-myocyte coupling. , 2012, Cardiovascular research.

[48]  Alan Garfinkel,et al.  Shaping a new Ca2+ conductance to suppress early afterdepolarizations in cardiac myocytes , 2011, The Journal of physiology.

[49]  Eleazar Eskin,et al.  "Good enough solutions" and the genetics of complex diseases. , 2012, Circulation research.

[50]  C. January,et al.  Cellular Mechanisms of Early Afterdepolarizations a , 1992, Annals of the New York Academy of Sciences.

[51]  A. Garfinkel,et al.  Early afterdepolarizations in cardiac myocytes: beyond reduced repolarization reserve. , 2013, Cardiovascular research.

[52]  Qinlian Zhou,et al.  Electronic "expression" of the inward rectifier in cardiocytes derived from human-induced pluripotent stem cells. , 2013, Heart rhythm.

[53]  E. Lakatta,et al.  Numerical models based on a minimal set of sarcolemmal electrogenic proteins and an intracellular Ca(2+) clock generate robust, flexible, and energy-efficient cardiac pacemaking. , 2013, Journal of molecular and cellular cardiology.

[54]  L. Izu,et al.  From Action Potential-Clamp to "Onion-Peeling" Technique – Recording of Ionic Currents Under Physiological Conditions , 2012 .

[55]  Ralf L. M. Peeters,et al.  Digital Commons@Becker , 2022 .

[56]  J. Weiss,et al.  Repolarization Reserve Evolves Dynamically During the Cardiac Action Potential: Effects of Transient Outward Currents on Early Afterdepolarizations , 2015, Circulation. Arrhythmia and electrophysiology.

[57]  Stefano Severi,et al.  Comprehensive Analyses of Ventricular Myocyte Models Identify Targets Exhibiting Favorable Rate Dependence , 2014, PLoS Comput. Biol..

[58]  J. Stockman Genetic Testing in the Long QT Syndrome: Development and Validation of an Efficient Approach to Genotyping in Clinical Practice , 2007 .

[59]  M. Lehmann,et al.  The long QT syndrome family of cardiac ion channelopathies: A HuGE review* , 2006, Genetics in Medicine.

[60]  Eric A. Sobie,et al.  Regression Analysis for Constraining Free Parameters in Electrophysiological Models of Cardiac Cells , 2009, PLoS Comput. Biol..

[61]  Antonio Zaza,et al.  Control of the cardiac action potential: The role of repolarization dynamics. , 2010, Journal of molecular and cellular cardiology.

[62]  S. Priori,et al.  Genetic testing in the long QT syndrome: development and validation of an efficient approach to genotyping in clinical practice. , 2005, JAMA.

[63]  David J. Christini,et al.  Practical Real-Time Computing System for Biomedical Experiment Interface , 1999, Annals of Biomedical Engineering.

[64]  K. T. ten Tusscher,et al.  Alternans and spiral breakup in a human ventricular tissue model. , 2006, American journal of physiology. Heart and circulatory physiology.

[65]  Itsuo Kodama,et al.  Density and Kinetics of IKr and IKs in Guinea Pig and Rabbit Ventricular Myocytes Explain Different Efficacy of IKs Blockade at High Heart Rate in Guinea Pig and Rabbit: Implications for Arrhythmogenesis in Humans , 2001, Circulation.

[66]  Kevin H Hobbs,et al.  Using complicated, wide dynamic range driving to develop models of single neurons in single recording sessions. , 2008, Journal of neurophysiology.

[67]  David Gavaghan,et al.  Multiscale cardiac modelling reveals the origins of notched T waves in long QT syndrome type 2 , 2014, Nature Communications.

[68]  R. Harvey,et al.  Autonomic regulation of delayed rectifier K+ current in mammalian heart involves G proteins. , 1989, The American journal of physiology.

[69]  Yoram Rudy,et al.  Uniqueness and stability of action potential models during rest, pacing, and conduction using problem-solving environment. , 2009, Biophysical journal.