Large-Scale Simulation of the Phenotypical Variability Induced by Loss-of-Function Long QT Mutations in Human Induced Pluripotent Stem Cell Cardiomyocytes

Hereditary E200K mutation within the prion protein gene alters human iPSC derived cardiomyocyte function

Cardiomyopathy is a co-morbidity of some prion diseases including genetic disease caused by mutations within the PrP gene (PRNP). Although the cellular prion protein (PrP) has been shown to protect against cardiotoxicity caused by oxidative stress, it is unclear if the cardiomyopathy is directly linked to PrP dysfunction. We differentiated cardiomyocyte cultures from donor human induced pluripotent stem cells and found a direct influence of the PRNP E200K mutation on cellular function. The PRNP E200K cardiomyocytes showed abnormal function evident in the irregularity of the rapid repolarization; a phenotype comparable with the dysfunction reported in Down Syndrome cardiomyocytes. PRNP E200K cardiomyocyte cultures also showed increased mitochondrial superoxide accompanied by increased mitochondrial membrane potential and dysfunction. To confirm that the changes were due to the E200K mutation, CRISPR-Cas9 engineering was used to correct the E200K carrier cells and insert the E200K mutation into control cells. The isotype matched cardiomyocytes showed that the lysine expressing allele does directly influence electrophysiology and mitochondrial function but some differences in severity were apparent between donor lines. Our results demonstrate that cardiomyopathy in hereditary prion disease may be directly linked to PrP dysfunction.

A Novel In Silico Electromechanical Model of Human Ventricular Cardiomyocyte

Contractility has become one of the main readouts in computational and experimental studies on cardiomyocytes. Following this trend, we propose a novel mathematical model of human ventricular cardiomyocytes electromechanics, BPSLand, by coupling a recent human contractile element to the BPS2020 model of electrophysiology. BPSLand is the result of a hybrid optimization process and it reproduces all the electrophysiology experimental indices captured by its predecessor BPS2020, simultaneously enabling the simulation of realistic human active tension and its potential abnormalities. The transmural heterogeneity in both electrophysiology and contractility departments was simulated consistent with previous computational and in vitro studies. Furthermore, our model could capture delayed afterdepolarizations (DADs), early afterdepolarizations (EADs), and contraction abnormalities in terms of aftercontractions triggered by either drug action or special pacing modes. Finally, we further validated the mechanical results of the model against previous experimental and in silico studies, e.g., the contractility dependence on pacing rate. Adding a new level of applicability to the normative models of human cardiomyocytes, BPSLand represents a robust, fully-human in silico model with promising capabilities for translational cardiology.

A mathematical model of hiPSC cardiomyocytes electromechanics

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are becoming instrumental in cardiac research, human-based cell level cardiotoxicity tests, and developing patient-specific care. As one of the principal functional readouts is contractility, we propose a novel electromechanical hiPSC-CM computational model named the hiPSC-CM-CE. This model comprises a reparametrized version of contractile element (CE) by Rice et al., 2008, with a new passive force formulation, integrated into a hiPSC-CM electrophysiology formalism by Paci et al. in 2020. Our simulated results were validated against in vitro data reported for hiPSC-CMs at matching conditions from different labs. Specifically, key action potential (AP) and calcium transient (CaT) biomarkers simulated by the hiPSC-CM-CE model were within the experimental ranges. On the mechanical side, simulated cell shortening, contraction-relaxation kinetic indices (RT50 and RT25 ), and the amplitude of tension fell within the experimental intervals. Markedly, as an inter-scale analysis, correct classification of the inotropic effects due to non-cardiomyocytes in hiPSC-CM tissues was predicted on account of the passive force expression introduced to the CE. Finally, the physiological inotropic effects caused by Verapamil and Bay-K 8644 and the aftercontractions due to the early afterdepolarizations (EADs) were simulated and validated against experimental data. In the future, the presented model can be readily expanded to take in pharmacological trials and genetic mutations, such as those involved in hypertrophic cardiomyopathy, and study arrhythmia trigger mechanisms.

Comparison of the Simulated Response of Three in Silico Human Stem Cell-Derived Cardiomyocytes Models and in Vitro Data Under 15 Drug Actions

Objectives: Improvements in human stem cell-derived cardiomyocyte (hSC-CM) technology have promoted their use for drug testing and disease investigations. Several in silico hSC-CM models have been proposed to augment interpretation of experimental findings through simulations. This work aims to assess the response of three hSC-CM in silico models (Koivumäki2018, Kernik2019, and Paci2020) to simulated drug action, and compare simulation results against in vitro data for 15 drugs.

Methods: First, simulations were conducted considering 15 drugs, using a simple pore-block model and experimental data for seven ion channels. Similarities and differences were analyzed in the in silico responses of the three models to drugs, in terms of Ca²⁺ transient duration (CTD₉₀) and occurrence of arrhythmic events. Then, the sensitivity of each model to different degrees of blockage of Na⁺ (I_Na), L-type Ca²⁺ (I_CaL), and rapid delayed rectifying K⁺ (I_Kr) currents was quantified. Finally, we compared the drug-induced effects on CTD₉₀ against the corresponding in vitro experiments.

Results: The observed CTD₉₀ changes were overall consistent among the in silico models, all three showing changes of smaller magnitudes compared to the ones measured in vitro. For example, sparfloxacin 10 µM induced +42% CTD₉₀ prolongation in vitro, and +17% (Koivumäki2018), +6% (Kernik2019), and +9% (Paci2020) in silico. Different arrhythmic events were observed following drug application, mainly for drugs affecting I_Kr. Paci2020 and Kernik2019 showed only repolarization failure, while Koivumäki2018 also displayed early and delayed afterdepolarizations. The spontaneous activity was suppressed by Na⁺ blockers and by drugs with similar effects on I_CaL and I_Kr in Koivumäki2018 and Paci2020, while only by strong I_CaL blockers, e.g. nisoldipine, in Kernik2019. These results were confirmed by the sensitivity analysis.

Conclusion: To conclude, The CTD₉₀ changes observed in silico are qualitatively consistent with our in vitro data, although our simulations show differences in drug responses across the hSC-CM models, which could stem from variability in the experimental data used in their construction.

Evolution of mathematical models of cardiomyocyte electrophysiology

Advanced computational techniques and mathematical modeling have become more and more important to the study of cardiac electrophysiology. In this review, we provide a brief history of the evolution of cardiomyocyte electrophysiology models and highlight some of the most important ones that had a major impact on our understanding of the electrical activity of the myocardium and associated transmembrane ion fluxes in normal and pathological states. We also present the use of these models in the study of various arrhythmogenesis mechanisms, particularly the integration of experimental pharmacology data into advanced humanized models for in silico proarrhythmogenic risk prediction as an essential component of the Comprehensive in vitro Proarrhythmia Assay (CiPA) drug safety paradigm.

In Silico Assessment of Class I Antiarrhythmic Drug Effects on Pitx2-Induced Atrial Fibrillation: Insights from Populations of Electrophysiological Models of Human Atrial Cells and Tissues

Electrical remodelling as a result of homeodomain transcription factor 2 (Pitx2)-dependent gene regulation was linked to atrial fibrillation (AF) and AF patients with single nucleotide polymorphisms at chromosome 4q25 responded favorably to class I antiarrhythmic drugs (AADs). The possible reasons behind this remain elusive. The purpose of this study was to assess the efficacy of the AADs disopyramide, quinidine, and propafenone on human atrial arrhythmias mediated by Pitx2-induced remodelling, from a single cell to the tissue level, using drug binding models with multi-channel pharmacology. Experimentally calibrated populations of human atrial action po-tential (AP) models in both sinus rhythm (SR) and Pitx2-induced AF conditions were constructed by using two distinct models to represent morphological subtypes of AP. Multi-channel pharmaco-logical effects of disopyramide, quinidine, and propafenone on ionic currents were considered. Simulated results showed that Pitx2-induced remodelling increased maximum upstroke velocity (dVdtmax), and decreased AP duration (APD), conduction velocity (CV), and wavelength (WL). At the concentrations tested in this study, these AADs decreased dVdtmax and CV and prolonged APD in the setting of Pitx2-induced AF. Our findings of alterations in WL indicated that disopyramide may be more effective against Pitx2-induced AF than propafenone and quinidine by prolonging WL.

Arrhythmia Mechanisms in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

ABSTRACT

Despite major efforts by clinicians and researchers, cardiac arrhythmia remains a leading cause of morbidity and mortality in the world. Experimental work has relied on combining high-throughput strategies with standard molecular and electrophysiological studies, which are, to a great extent, based on the use of animal models. Because this poses major challenges for translation, the progress in the development of novel antiarrhythmic agents and clinical care has been mostly disappointing. Recently, the advent of human induced pluripotent stem cell-derived cardiomyocytes has opened new avenues for both basic cardiac research and drug discovery; now, there is an unlimited source of cardiomyocytes of human origin, both from healthy individuals and patients with cardiac diseases. Understanding arrhythmic mechanisms is one of the main use cases of human induced pluripotent stem cell-derived cardiomyocytes, in addition to pharmacological cardiotoxicity and efficacy testing, in vitro disease modeling, developing patient-specific models and personalized drugs, and regenerative medicine. Here, we review the advances that the human induced pluripotent stem cell-derived-based modeling systems have brought so far regarding the understanding of both arrhythmogenic triggers and substrates, while also briefly speculating about the possibilities in the future.

All-Optical Electrophysiology Refines Populations of In Silico Human iPSC-CMs for Drug Evaluation

High-throughput in vitro drug assays have been impacted by recent advances in human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) technology and by contact-free all-optical systems simultaneously measuring action potentials (APs) and Ca2+ transients (CaTrs). Parallel computational advances have shown that in silico simulations can predict drug effects with high accuracy. We combine these in vitro and in silico technologies and demonstrate the utility of high-throughput experimental data to refine in silico hiPSC-CM populations and to predict and explain drug action mechanisms. Optically obtained hiPSC-CM APs and CaTrs were used from spontaneous activity and under optical pacing in control and drug conditions at multiple doses. An updated version of the Paci2018 model was developed to refine the description of hiPSC-CM spontaneous electrical activity; a population of in silico hiPSC-CMs was constructed and calibrated using simultaneously recorded APs and CaTrs. We tested in silico five drugs (astemizole, dofetilide, ibutilide, bepridil, and diltiazem) and compared the outcomes to in vitro optical recordings. Our simulations showed that physiologically accurate population of models can be obtained by integrating AP and CaTr control records. Thus, constructed population of models correctly predicted the drug effects and occurrence of adverse episodes, even though the population was optimized only based on control data and in vitro drug testing data were not deployed during its calibration. Furthermore, the in silico investigation yielded mechanistic insights; e.g., through simulations, bepridil's more proarrhythmic action in adult cardiomyocytes compared to hiPSC-CMs could be traced to the different expression of ion currents in the two. Therefore, our work 1) supports the utility of all-optical electrophysiology in providing high-content data to refine experimentally calibrated populations of in silico hiPSC-CMs, 2) offers insights into certain limitations when translating results obtained in hiPSC-CMs to humans, and 3) shows the strength of combining high-throughput in vitro and population in silico approaches.

Simulation of the Effects of Extracellular Calcium Changes Leads to a Novel Computational Model of Human Ventricular Action Potential With a Revised Calcium Handling

The importance of electrolyte concentrations for cardiac function is well established. Electrolyte variations can lead to arrhythmias onset, due to their important role in the action potential (AP) genesis and in maintaining cell homeostasis. However, most of the human AP computer models available in literature were developed with constant electrolyte concentrations, and fail to simulate physiological changes induced by electrolyte variations. This is especially true for Ca2+, even in the O'Hara-Rudy model (ORd), one of the most widely used models in cardiac electrophysiology. Therefore, the present work develops a new human ventricular model (BPS2020), based on ORd, able to simulate the inverse dependence of AP duration (APD) on extracellular Ca2+ concentration ([Ca2+]o), and APD rate dependence at 4 mM extracellular K+. The main changes needed with respect to ORd are: (i) an increased sensitivity of L-type Ca2+ current inactivation to [Ca2+]o; (ii) a single compartment description of the sarcoplasmic reticulum; iii) the replacement of Ca2+ release. BPS2020 is able to simulate the physiological APD-[Ca2+]o relationship, while also retaining the well-reproduced properties of ORd (APD rate dependence, restitution, accommodation and current block effects). We also used BPS2020 to generate an experimentally-calibrated population of models to investigate: (i) the occurrence of repolarization abnormalities in response to hERG current block; (ii) the rate adaptation variability; (iii) the occurrence of alternans and delayed after-depolarizations at fast pacing. Our results indicate that we successfully developed an improved version of ORd, which can be used to investigate electrophysiological changes and pro-arrhythmic abnormalities induced by electrolyte variations and current block at multiple rates and at the population level.

General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy

This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration-sponsored Think Tank Meeting on May 22, 2018. The meeting was convened to evaluate the progress in the development of a new cardiac safety paradigm, the Comprehensive in Vitro Proarrhythmia Assay (CiPA). The opinions regarding these principles reflect the collective views of those who participated in the discussion of this topic both at and after the breakout session. Although primarily discussed in the context of in silico models, these principles describe the interface between experimental input and model-based interpretation and are intended to be general enough to be applied to other types of nonclinical models for proarrhythmia assessment. This document was developed with the intention of providing a foundation for more consistency and harmonization in developing and validating different models for proarrhythmia risk prediction using the example of the CiPA paradigm.

hiPSCs Derived Cardiac Cells for Drug and Toxicity Screening and Disease Modeling: What Micro- Electrode-Array Analyses Can Tell Us

Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (CM) have been intensively used in drug development and disease modeling. Since iPSC-cardiomyocyte (CM) was first generated, their characterization has become a major focus of research. Multi-/micro-electrode array (MEA) systems provide a non-invasive user-friendly platform for detailed electrophysiological analysis of iPSC cardiomyocytes including drug testing to identify potential targets and the assessment of proarrhythmic risk. Here, we provide a systematical overview about the physiological and technical background of micro-electrode array measurements of iPSC-CM. We introduce the similarities and differences between action- and field potential and the advantages and drawbacks of MEA technology. In addition, we present current studies focusing on proarrhythmic side effects of novel and established compounds combining MEA systems and iPSC-CM. MEA technology will help to open a new gateway for novel therapies in cardiovascular diseases while reducing animal experiments at the same time.

A computational model of induced pluripotent stem-cell derived cardiomyocytes incorporating experimental variability from multiple data sources

Key points

Induced pluripotent stem cell‐derived cardiomyocytes (iPSC‐CMs) capture patient‐specific genotype–phenotype relationships, as well as cell‐to‐cell variability of cardiac electrical activity

Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes

We have developed a whole‐cell model of iPSC‐CMs, composed of single exponential voltage‐dependent gating variable rate constants, parameterized to fit experimental iPSC‐CM outputs

We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC‐CMs

This framework links molecular mechanisms to cellular‐level outputs by revealing unique subsets of model parameters linked to known iPSC‐CM phenotypes

Abstract

There is a profound need to develop a strategy for predicting patient‐to‐patient vulnerability in the emergence of cardiac arrhythmia. A promising in vitro method to address patient‐specific proclivity to cardiac disease utilizes induced pluripotent stem cell‐derived cardiomyocytes (iPSC‐CMs). A major strength of this approach is that iPSC‐CMs contain donor genetic information and therefore capture patient‐specific genotype–phenotype relationships. A cited detriment of iPSC‐CMs is the cell‐to‐cell variability observed in electrical activity. We postulated, however, that cell‐to‐cell variability may constitute a strength when appropriately utilized in a computational framework to build cell populations that can be employed to identify phenotypic mechanisms and pinpoint key sensitive parameters. Thus, we have exploited variation in experimental data across multiple laboratories to develop a computational framework for investigating subcellular phenotypic mechanisms. We have developed a whole‐cell model of iPSC‐CMs composed of simple model components comprising ion channel models with single exponential voltage‐dependent gating variable rate constants, parameterized to fit experimental iPSC‐CM data for all major ionic currents. By optimizing ionic current model parameters to multiple experimental datasets, we incorporate experimentally‐observed variability in the ionic currents. The resulting population of cellular models predicts robust inter‐subject variability in iPSC‐CMs. This approach links molecular mechanisms to known cellular‐level iPSC‐CM phenotypes, as shown by comparing immature and mature subpopulations of models to analyse the contributing factors underlying each phenotype. In the future, the presented models can be readily expanded to include genetic mutations and pharmacological interventions for studying the mechanisms of rare events, such as arrhythmia triggers.

Induced pluripotent stem cell‐derived cardiomyocytes (iPSC‐CMs) capture patient‐specific genotype–phenotype relationships, as well as cell‐to‐cell variability of cardiac electrical activity

Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes

We have developed a whole‐cell model of iPSC‐CMs, composed of single exponential voltage‐dependent gating variable rate constants, parameterized to fit experimental iPSC‐CM outputs

We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC‐CMs

This framework links molecular mechanisms to cellular‐level outputs by revealing unique subsets of model parameters linked to known iPSC‐CM phenotypes