Elisa Passini

Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm.

Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm.

Mechanisms of pro-arrhythmic abnormalities in ventricular repolarisation and anti-arrhythmic therapies in human hypertrophic cardiomyopathy

Introduction Hypertrophic cardiomyopathy (HCM) is a cause of sudden arrhythmic death, but the understanding of its pro-arrhythmic mechanisms and an effective pharmacological treatment are lacking. HCM electrophysiological remodelling includes both increased inward and reduced outward currents, but their role in promoting repolarisation abnormalities remains unknown. The goal of this study is to identify key ionic mechanisms driving repolarisation abnormalities in human HCM, and to evaluate anti-arrhythmic effects of single and multichannel inward current blocks. Methods Experimental ionic current, action potential (AP) and Ca2 +-transient (CaT) recordings were used to construct populations of human non-diseased and HCM AP models (n = 9118), accounting for inter-subject variability. Simulations were conducted for several degrees of selective and combined inward current block. Results Simulated HCM cardiomyocytes exhibited prolonged AP and CaT, diastolic Ca2 + overload and decreased CaT amplitude, in agreement with experiments. Repolarisation abnormalities in HCM models were consistently driven by L-type Ca2 + current (ICaL) re-activation, and ICaL block was the most effective intervention to normalise repolarisation and diastolic Ca2 +, but compromised CaT amplitude. Late Na+ current (INaL) block partially abolished repolarisation abnormalities, with small impact on CaT. Na+/Ca2 + exchanger (INCX) block effectively restored repolarisation and CaT amplitude, but increased Ca2 + overload. Multichannel block increased efficacy in normalising repolarisation, AP biomarkers and CaT amplitude compared to selective block. Conclusions Experimentally-calibrated populations of human AP models identify ICaL re-activation as the key mechanism for repolarisation abnormalities in HCM, and combined INCX, INaL and ICaL block as effective anti-arrhythmic therapies also able to partially reverse the HCM electrophysiological phenotype.

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na+ and Ca2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca2+-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting.

Recurrent intradialytic paroxysmal atrial fibrillation: hypotheses on onset mechanisms based on clinical data and computational analysis

Atrial fibrillation (AF) incidence is high in end-stage renal disease (ESRD) patients, and haemodialysis (HD) session may induce paroxysmal AF episodes. Structural atrium remodelling is common in ESRD patients, moreover, HD session induces rapid plasma electrolytes and blood volume changes, possibly favouring arrhythmia onset. Therefore, HD session represents a unique model to study in vivo the mechanisms potentially inducing paroxysmal AF episodes. Here, we present the case report of a patient in which HD regularly induced paroxysmal AF. In four consecutive sessions, heart rate variability analysis showed a progressive reduction of low/high frequency ratio before the AF onset, suggesting a relative increase in vagal activity. Moreover, all AF episodes were preceded by a great increase of supraventricular ectopic beats. We applied computational modelling of cardiac cellular electrophysiology to these clinical findings, using plasma electrolyte concentrations and heart rate to simulate patient conditions at the beginning of HD session (pre-HD) and right before the AF onset (pre-AF), in a human atrial action potential model. Simulation results provided evidence of a slower depolarization and a shortened refractory period in pre-AF vs. pre-HD, and these effects were enhanced when adding acetylcholine effect. Paroxysmal AF episodes are induced by the presence of a trigger that acts upon a favourable substrate on the background of autonomic nervous system changes and in the described case report all these three elements were present. Starting from these findings, here we review the possible mechanisms leading to intradialytic AF onset.

Phenotypic variability in LQT3 human induced pluripotent stem cell−derived cardiomyocytes and their response to antiarrhythmic pharmacologic therapy: An in silico approach

Background Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are in vitro models with the clear advantages of their human origin and suitability for human disease investigations. However, limitations include their incomplete characterization and variability reported in different cell lines and laboratories. Objective The purpose of this study was to investigate in silico ionic mechanisms potentially explaining the phenotypic variability of hiPSC-CMs in long QT syndrome type 3 (LQT3) and their response to antiarrhythmic drugs. Methods Populations of in silico hiPSC-CM models were constructed and calibrated for control (n = 1,463 models) and LQT3 caused by INaL channelopathy (n = 1,401 models), using experimental recordings for late sodium current (INaL) and action potentials (APs). Antiarrhythmic drug therapy was evaluated by simulating mexiletine and ranolazine multichannel effects. Results As in experiments, LQT3 hiPSC-CMs yield prolonged action potential duration at 90% repolarization (APD90) (+34.3% than controls) and large electrophysiological variability. LQT3 hiPSC-CMs with symptomatic APs showed overexpression of ICaL, IK1, and INaL, underexpression of IKr, and increased sensitivity to both drugs compared to asymptomatic LQT3 models. Simulations showed that both mexiletine and ranolazine corrected APD prolongation in the LQT3 population but also highlighted differences in drug response. Mexiletine stops spontaneous APs in more LQT3 hiPSC-CMs models than ranolazine (784/1,401 vs 53/1,401) due to its stronger action on INa. Conclusion In silico simulations demonstrate our ability to recapitulate variability in LQT3 and control hiPSC-CM phenotypes, and the ability of mexiletine and ranolazine to reduce APD prolongation, in agreement with experiments. The in silico models also identify potential ionic mechanisms of phenotypic variability in LQT3 hiPSC-CMs, explaining APD prolongation in symptomatic vs asymptomatic LQT3 hiPSC-CMs.

Human Atrial Cell Models to Analyse Haemodialysis-Related Effects on Cardiac Electrophysiology: Work in Progress

During haemodialysis (HD) sessions, patients undergo alterations in the extracellular environment, mostly concerning plasma electrolyte concentrations, pH, and volume, together with a modification of sympathovagal balance. All these changes affect cardiac electrophysiology, possibly leading to an increased arrhythmic risk. Computational modeling may help to investigate the impact of HD-related changes on atrial electrophysiology. However, many different human atrial action potential (AP) models are currently available, all validated only with the standard electrolyte concentrations used in experiments. Therefore, they may respond in different ways to the same environmental changes. After an overview on how the computational approach has been used in the past to investigate the effect of HD therapy on cardiac electrophysiology, the aim of this work has been to assess the current state of the art in human atrial AP models, with respect to the HD context. All the published human atrial AP models have been considered and tested for electrolytes, volume changes, and different acetylcholine concentrations. Most of them proved to be reliable for single modifications, but all of them showed some drawbacks. Therefore, there is room for a new human atrial AP model, hopefully able to physiologically reproduce all the HD-related effects. At the moment, work is still in progress in this specific field.