From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study

Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions, computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and subcellular ionic densities on Ca2+ transient dynamics. Results showed that 1) variability in APs and ionic densities is large, even within an apparently homogenous patient cohort, and translates into ±100% variation in ionic conductances; 2) experimentally calibrated populations of models with wide variations in ionic densities yield APs overlapping with those obtained experimentally, even if AP characteristics of the original generic model differed significantly from experimental APs; 3) model calibration with AP recordings restricts the variability in ionic densities affecting upstroke and resting potential, but redundancy in repolarization currents admits substantial variability in ionic densities; and 4) model populations constrained with experimental APs and ionic densities exhibit three Ca2+ transient phenotypes, differing in intracellular Ca2+ handling and Na+/Ca2+ membrane extrusion. These findings advance our understanding of the impact of variability in human atrial electrophysiology. NEW & NOTEWORTHY Variability in human atrial electrophysiology is investigated by integrating for the first time cellular-level and ion channel recordings in computational electrophysiological models. Ion channel calibration restricts current densities but not cellular phenotypic variability. Reduced Na+/Ca2+ exchanger is identified as a primary mechanism underlying diastolic Ca2+ fluctuations in human atrial myocytes.

[1]  Sebastian Polak,et al.  Inter-individual Variability in the Pre-clinical Drug Cardiotoxic Safety Assessment—Analysis of the Age–Cardiomyocytes Electric Capacitance Dependence , 2012, Journal of Cardiovascular Translational Research.

[2]  J. Clark,et al.  A model of the action potential and underlying membrane currents in a rabbit atrial cell. , 1996, The American journal of physiology.

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

[4]  Joseph L Greenstein,et al.  K+ current changes account for the rate dependence of the action potential in the human atrial myocyte. , 2009, American journal of physiology. Heart and circulatory physiology.

[5]  U. Schotten,et al.  Up-regulation of miR-31 in human atrial fibrillation begets the arrhythmia by depleting dystrophin and neuronal nitric oxide synthase , 2016, Science Translational Medicine.

[6]  J. Hulot,et al.  Downregulation of the calcium current in human right atrial myocytes from patients in sinus rhythm but with a high risk of atrial fibrillation. , 2008, European heart journal.

[7]  J. Valentin,et al.  Sex differences in ventricular repolarization: from cardiac electrophysiology to Torsades de Pointes , 2004, Fundamental & clinical pharmacology.

[8]  M. Cutler,et al.  Spontaneous calcium oscillations during diastole in the whole heart: the influence of ryanodine reception function and gap junction coupling. , 2011, American journal of physiology. Heart and circulatory physiology.

[9]  Alessio Gizzi,et al.  Role of temperature on nonlinear cardiac dynamics. , 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  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.

[11]  Gary R. Mirams,et al.  mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study , 2013, PloS one.

[12]  E. Segal,et al.  Personalized Nutrition by Prediction of Glycemic Responses , 2015, Cell.

[13]  Amrita X. Sarkar,et al.  Exploiting mathematical models to illuminate electrophysiological variability between individuals , 2012, The Journal of physiology.

[14]  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.

[15]  Xing Liu,et al.  Constructing human atrial electrophysiological models mimicking a patient-specific cell group , 2014, Computing in Cardiology 2014.

[16]  J. Clark,et al.  Mathematical model of an adult human atrial cell: the role of K+ currents in repolarization. , 1998, Circulation research.

[17]  Lei Yuan,et al.  Small-conductance calcium-activated potassium (SK) channels contribute to action potential repolarization in human atria. , 2014, Cardiovascular research.

[18]  E. Carmeliet,et al.  Modulation of transient outward current by extracellular protons and Cd2+ in rat and human ventricular myocytes , 1998, The Journal of physiology.

[19]  Andreu M. Climent,et al.  Balance between sodium and calcium currents underlying chronic atrial fibrillation termination: An in silico intersubject variability study , 2016, Heart rhythm.

[20]  J. Tamargo,et al.  Nitric oxide inhibits Kv4.3 and human cardiac transient outward potassium current (Ito1). , 2008, Cardiovascular research.

[21]  Rebecca A. B. Burton,et al.  Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop , 2015, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[22]  Elizabeth M Cherry,et al.  Dynamics of human atrial cell models: restitution, memory, and intracellular calcium dynamics in single cells. , 2008, Progress in biophysics and molecular biology.

[23]  Alessio Gizzi,et al.  Mechanistic insights into hypothermic ventricular fibrillation: the role of temperature and tissue size. , 2014, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[24]  A. Workman,et al.  Electrophysiological Effects of Prucalopride, a Novel Enterokinetic Agent, on Isolated Atrial Myocytes from Patients Treated with β-Adrenoceptor Antagonists , 2005, Journal of Pharmacology and Experimental Therapeutics.

[25]  Donald M Bers,et al.  A mathematical treatment of integrated Ca dynamics within the ventricular myocyte. , 2004, Biophysical journal.

[26]  S Nattel,et al.  Sustained depolarization-induced outward current in human atrial myocytes. Evidence for a novel delayed rectifier K+ current similar to Kv1.5 cloned channel currents. , 1993, Circulation research.

[27]  Gui-Rong Li,et al.  Intravenous Anesthetic Propofol Inhibits Multiple Human Cardiac Potassium Channels , 2015, Anesthesiology.

[28]  M. Courtemanche,et al.  Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. , 1998, The American journal of physiology.

[29]  W. Crumb,et al.  L-Type Calcium Current in Pediatric and Adult Human Atrial Myocytes: Evidence for Developmental Changes in Channel Inactivation , 1996, Pediatric Research.

[30]  E. Ashley,et al.  Cardiac Neuronal Nitric Oxide Synthase Isoform Regulates Myocardial Contraction and Calcium Handling , 2003, Circulation research.

[31]  Kevin Burrage,et al.  Rabbit-specific computational modelling of ventricular cell electrophysiology: Using populations of models to explore variability in the response to ischemia , 2016, Progress in biophysics and molecular biology.

[32]  S. Nattel,et al.  Sex differences in cardiac electrophysiology and clinical arrhythmias: epidemiology, therapeutics, and mechanisms. , 2014, The Canadian journal of cardiology.

[33]  C. Luo,et al.  A dynamic model of the cardiac ventricular action potential. I. Simulations of ionic currents and concentration changes. , 1994, Circulation research.

[34]  Kevin Burrage,et al.  Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology. , 2012, American journal of physiology. Heart and circulatory physiology.

[35]  J. Nerbonne,et al.  Atrial L-type Ca2+ currents and human atrial fibrillation. , 1999, Circulation research.

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

[37]  Denis Noble,et al.  Successes and failures in modeling heart cell electrophysiology. , 2011, Heart rhythm.

[38]  M. Borggrefe,et al.  Upregulation of K2P3.1 K+ Current Causes Action Potential Shortening in Patients With Chronic Atrial Fibrillation , 2015, Circulation.

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

[40]  Carlos Sánchez,et al.  Inter-Subject Variability in Human Atrial Action Potential in Sinus Rhythm versus Chronic Atrial Fibrillation , 2014, PloS one.

[41]  Niels Voigt,et al.  Left-to-Right Atrial Inward Rectifier Potassium Current Gradients in Patients With Paroxysmal Versus Chronic Atrial Fibrillation , 2010, Circulation. Arrhythmia and electrophysiology.

[42]  J. Nerbonne,et al.  Outward K+ current densities and Kv1.5 expression are reduced in chronic human atrial fibrillation. , 1997, Circulation research.

[43]  B. Small,et al.  Gender differences in the slow delayed (IKs) but not in inward (IK1) rectifier K+ currents of canine Purkinje fibre cardiac action potential: key roles for IKs, β‐adrenoceptor stimulation, pacing rate and gender , 2006, British journal of pharmacology.

[44]  David S. Rosenbaum,et al.  Circadian rhythms govern cardiac repolarization and arrhythmogenesis , 2012, Nature.

[45]  Christopher R. Myers,et al.  Universally Sloppy Parameter Sensitivities in Systems Biology Models , 2007, PLoS Comput. Biol..

[46]  Alexander G. Fletcher,et al.  Chaste: A test-driven approach to software development for biological modelling , 2009, Comput. Phys. Commun..

[47]  C C Drovandi,et al.  Sampling methods for exploring between-subject variability in cardiac electrophysiology experiments , 2016, Journal of The Royal Society Interface.

[48]  Stefano Severi,et al.  Mechanisms of pro-arrhythmic abnormalities in ventricular repolarisation and anti-arrhythmic therapies in human hypertrophic cardiomyopathy , 2016, Journal of molecular and cellular cardiology.

[49]  E. Pueyo,et al.  Experimentally-Based Computational Investigation into Beat-To-Beat Variability in Ventricular Repolarization and Its Response to Ionic Current Inhibition , 2016, PloS one.

[50]  S. Severi,et al.  Recurrent intradialytic paroxysmal atrial fibrillation: hypotheses on onset mechanisms based on clinical data and computational analysis. , 2014, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[51]  F. Atienza,et al.  Nitric Oxide Increases Cardiac IK1 by Nitrosylation of Cysteine 76 of Kir2.1 Channels , 2009, Circulation research.

[52]  R F Bosch,et al.  Ionic mechanisms of electrical remodeling in human atrial fibrillation. , 1999, Cardiovascular research.

[53]  Stanley Nattel,et al.  Differential Distribution of Cardiac Ion Channel Expression as a Basis for Regional Specialization in Electrical Function , 2002, Circulation research.

[54]  A. Workman,et al.  The contribution of ionic currents to changes in refractoriness of human atrial myocytes associated with chronic atrial fibrillation. , 2001, Cardiovascular research.