Experimentally-Based Computational Investigation into Beat-To-Beat Variability in Ventricular Repolarization and Its Response to Ionic Current Inhibition

Cell-to-cell heterogeneity in ion channel conductance impacts substrate vulnerability to arrhythmia

Determining whether an ectopic depolarization will lead to a self-perpetuating arrhythmia is of critical importance in determining arrhythmia risk, so it is necessary to understand what factors impact substrate vulnerability. This study sought to explore the impact of cell-to-cell heterogeneity in ion channel conductance on substrate vulnerability to arrhythmia by measuring the duration of the vulnerable window in computational models of one-dimensional cables of ventricular cardiomyocytes. We began by using a population of uniform cable models to determine the mechanisms underlying the vulnerable window phenomenon. We found that in addition to the known importance of GNa, the conductances GCa,L and GKr also play a minor role in determining the vulnerable window duration. We also found that a steeper slope of the repolarizing action potential during the vulnerable window correlated with a shorter vulnerable window duration in uniform cables. We applied our understanding from these initial simulations to an investigation of the vulnerable window in heterogeneous cable models. The heterogeneous cables displayed a great deal of intra-cable variation in vulnerable window duration, highly sensitive to the cardiomyocytes in the local environment of the ectopic stimulus. Coupling strength modulated not only the magnitude of the vulnerable window duration but also the extent of intra-tissue variability in vulnerable window duration.NEW & NOTEWORTHY We investigate the impact of cell-to-cell heterogeneity in ion channel conductance on substrate vulnerability to arrhythmia by measuring the vulnerable window duration in computational cardiomyocyte cable models. We demonstrate a wide range of intra-cable variability in vulnerable window duration (VWD) and show how this is changed by ion channel block and coupling strength perturbations.

Inducing Ito,f and phase 1 repolarization of the cardiac action potential with a Kv4.3/KChIP2.1 bicistronic transgene

The fast transient outward potassium current (I_to,f) plays a key role in phase 1 repolarization of the human cardiac action potential (AP) and its reduction in heart failure (HF) contributes to the loss of contractility. Therefore, restoring I_to,f might be beneficial for treating HF. The coding sequence of a P2A peptide was cloned, in frame, between Kv4.3 and KChIP2.1 genes and ribosomal skipping was confirmed by Western blotting. Typical I_to,f properties with slowed inactivation and accelerated recovery from inactivation due to the association of KChIP2.1 with Kv4.3 was seen in transfected HEK293 cells. Both bicistronic components trafficked to the plasmamembrane and in adenovirus transduced rabbit cardiomyocytes both t-tubular and sarcolemmal construct labelling appeared. The resulting current was similar to I_to,f seen in human ventricular cardiomyocytes and was 50% blocked at ~0.8 mmol/l 4-aminopyridine and increased ~30% by 5 μmol/l NS5806 (an I_to,f agonist). Variation in the density of the expressed I_to,f, in rabbit cardiomyocytes recapitulated typical species-dependent variations in AP morphology. Simultaneous voltage recording and intracellular Ca²⁺ imaging showed that modification of phase 1 to a non-failing human phenotype improved the rate of rise and magnitude of the Ca²⁺ transient. I_to,f expression also reduced AP triangulation but did not affect I_Ca,L and I_Na magnitudes. This raises the possibility for a new gene-based therapeutic approach to HF based on selective phase 1 modification.

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Action potential phase 1 depends on fast transient outward current (I_to,f).

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Construction of a bicistronic transgene for Kv4.3 and KChIP2.1 with P2A separator

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Expressed bicistronic Kv4.3/KChIP2.1 proteins traffic to the cell surface membrane

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Viral transduction with Kv4.3/KChIP2.1 increases I_to,f in cardiomyocytes.

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Kv4.3/KChIP2.1 transgene expression increased AP phase 1 and EC coupling

Prediction of arrhythmia susceptibility through mathematical modeling and machine learning

At present, the QT interval on the electrocardiographic (ECG) waveform is the most common metric for assessing an individual's susceptibility to ventricular arrhythmias, with a long QT, or, at the cellular level, a long action potential duration (APD) considered high risk. However, the limitations of this simple approach have long been recognized. Here, we sought to improve prediction of arrhythmia susceptibility by combining mechanistic mathematical modeling with machine learning (ML). Simulations with a model of the ventricular myocyte were performed to develop a large heterogenous population of cardiomyocytes (n = 10,586), and we tested each variant's ability to withstand three arrhythmogenic triggers: 1) block of the rapid delayed rectifier potassium current (I_Kr Block), 2) augmentation of the L-type calcium current (I_CaL Increase), and 3) injection of inward current (Current Injection). Eight ML algorithms were trained to predict, based on simulated AP features in preperturbed cells, whether each cell would develop arrhythmic dynamics in response to each trigger. We found that APD can accurately predict how cells respond to the simple Current Injection trigger but cannot effectively predict the response to I_Kr Block or I_CaL Increase. ML predictive performance could be improved by incorporating additional AP features and simulations of additional experimental protocols. Importantly, we discovered that the most relevant features and experimental protocols were trigger specific, which shed light on the mechanisms that promoted arrhythmia formation in response to the triggers. Overall, our quantitative approach provides a means to understand and predict differences between individuals in arrhythmia susceptibility.

Canine Myocytes Represent a Good Model for Human Ventricular Cells Regarding Their Electrophysiological Properties

Due to the limited availability of healthy human ventricular tissues, the most suitable animal model has to be applied for electrophysiological and pharmacological studies. This can be best identified by studying the properties of ion currents shaping the action potential in the frequently used laboratory animals, such as dogs, rabbits, guinea pigs, or rats, and comparing them to those of human cardiomyocytes. The authors of this article with the experience of three decades of electrophysiological studies, performed in mammalian and human ventricular tissues and isolated cardiomyocytes, summarize their results obtained regarding the major canine and human cardiac ion currents. Accordingly, L-type Ca²⁺ current (I_Ca), late Na⁺ current (I_Na-late), rapid and slow components of the delayed rectifier K⁺ current (I_Kr and I_Ks, respectively), inward rectifier K⁺ current (I_K1), transient outward K⁺ current (I_to1), and Na⁺/Ca²⁺ exchange current (I_NCX) were characterized and compared. Importantly, many of these measurements were performed using the action potential voltage clamp technique allowing for visualization of the actual current profiles flowing during the ventricular action potential. Densities and shapes of these ion currents, as well as the action potential configuration, were similar in human and canine ventricular cells, except for the density of I_K1 and the recovery kinetics of I_to. I_K1 displayed a largely four-fold larger density in canine than human myocytes, and I_to recovery from inactivation displayed a somewhat different time course in the two species. On the basis of these results, it is concluded that canine ventricular cells represent a reasonably good model for human myocytes for electrophysiological studies, however, it must be borne in mind that due to their stronger I_K1, the repolarization reserve is more pronounced in canine cells, and moderate differences in the frequency-dependent repolarization patterns can also be anticipated.

Characterization of Spatio-Temporal Cardiac Action Potential Variability at Baseline and Under β-Adrenergic Stimulation by Combined Unscented Kalman Filter and Double Greedy Dimension Reduction

OBJECTIVE

Elevated spatio-temporal variability of human ventricular repolarization has been related to increased risk for ventricular arrhythmias and sudden cardiac death, particularly under β-adrenergic stimulation ( β-AS). This work presents a methodology for theoretical characterization of temporal and spatial repolarization variability at baseline conditions and in response to β-AS. For any measured voltage trace, the proposed methodology estimates the parameters and state variables of an underlying human ventricular action potential (AP) model by combining Double Greedy Dimension Reduction (DGDR) with automatic selection of biomarkers and the Unscented Kalman Filter (UKF). Such theoretical characterization can facilitate subsequent characterization of underlying variability mechanisms.

MATERIAL AND METHODS

Given an AP trace, initial estimates for the ionic conductances in a stochastic version of the baseline human ventricular O'Hara et al. model were obtained by DGDR. Those estimates served to initialize and update model parameter estimates by the UKF method based on formulation of an associated nonlinear state-space representation and joint estimation of model parameters and state variables. Similarly, β-AS-induced phosphorylation levels of cellular substrates were estimated by the DGDR-UKF methodology. Performance was tested by building an experimentally-calibrated population of virtual cells, from which synthetic AP traces were generated for baseline and β-AS conditions.

RESULTS

The combined DGDR-UKF methodology led to 25% reduction in the error associated with estimation of ionic current conductances at baseline conditions and phosphorylation levels under β-AS with respect to individual DGDR and UKF methods. This improvement was not at the expense of higher computational load, which was diminished by 90% with respect to the individual UKF method. Both temporal and spatial AP variability of repolarization were accurately characterized by the DGDR-UKF methodology.

CONCLUSIONS

A combined DGDR-UKF methodology is proposed for parameter and state variable estimation of human ventricular cell models from available AP traces at baseline and under β-AS. This methodology improves the estimation performance and reduces the convergence time with respect to individual DGDR and UKF methods and renders a suitable approach for computational characterization of spatio-temporal repolarization variability to be used for ascertainment of variability mechanisms and its relation to arrhythmogenesis.

Cardiac transmembrane ion channels and action potentials: cellular physiology and arrhythmogenic behavior

Cardiac arrhythmias are among the leading causes of mortality. They often arise from alterations in the electrophysiological properties of cardiac cells and their underlying ionic mechanisms. It is therefore critical to further unravel the pathophysiology of the ionic basis of human cardiac electrophysiology in health and disease. In the first part of this review, current knowledge on the differences in ion channel expression and properties of the ionic processes that determine the morphology and properties of cardiac action potentials and calcium dynamics from cardiomyocytes in different regions of the heart are described. Then the cellular mechanisms promoting arrhythmias in congenital or acquired conditions of ion channel function (electrical remodeling) are discussed. The focus is on human-relevant findings obtained with clinical, experimental, and computational studies, given that interspecies differences make the extrapolation from animal experiments to human clinical settings difficult. Deepening the understanding of the diverse pathophysiology of human cellular electrophysiology will help in developing novel and effective antiarrhythmic strategies for specific subpopulations and disease conditions.

Cardiac computational modelling

Cardiovascular diseases currently have a major social and economic impact, constituting one of the leading causes of mortality and morbidity. Personalized computational models of the heart are demonstrating their usefulness both to help understand the mechanisms underlying cardiac disease, and to optimize their treatment and predict the patient's response. Within this framework, the Spanish Research Network for Cardiac Computational Modelling (VHeart-SN) has been launched. The general objective of the VHeart-SN network is the development of an integrated, modular and multiscale multiphysical computational model of the heart. This general objective is addressed through the following specific objectives: a) to integrate the different numerical methods and models taking into account the specificity of patients; b) to assist in advancing knowledge of the mechanisms associated with cardiac and vascular diseases; and c) to support the application of different personalized therapies. This article presents the current state of cardiac computational modelling and different scientific works conducted by the members of the network to gain greater understanding of the characteristics and usefulness of these models.

Complex Interaction Between Low-Frequency APD Oscillations and Beat-to-Beat APD Variability in Humans Is Governed by the Sympathetic Nervous System

BACKGROUND

Recent clinical, experimental and modeling studies link oscillations of ventricular repolarization in the low frequency (LF) (approx. 0.1 Hz) to arrhythmogenesis. Sympathetic provocation has been shown to enhance both LF oscillations of action potential duration (APD) and beat-to-beat variability (BVR) in humans. We hypothesized that beta-adrenergic blockade would reduce LF oscillations of APD and BVR of APD in humans and that the two processes might be linked.

METHODS AND RESULTS

Twelve patients with normal ventricles were studied during routine electrophysiological procedures. Activation-recovery intervals (ARI) as a conventional surrogate for APD were recorded from 10 left and 10 right ventricular endocardial sites before and after acute beta-adrenergic adrenergic blockade. Cycle length was maintained constant with right ventricular pacing. Oscillatory behavior of ARI was quantified by spectral analysis and BVR as the short-term variability. Beta-adrenergic blockade reduced LF ARI oscillations (8.6 ± 4.5 ms2 vs. 5.5 ± 3.5 ms2, p = 0.027). A significant correlation was present between the initial control values and reduction seen following beta-adrenergic blockade in LF ARI (r s = 0.62, p = 0.037) such that when initial values are high the effect is greater. A similar relationship was also seen in the beat-to beat variability of ARI (r s = 0.74, p = 0.008). There was a significant correlation between the beta-adrenergic blockade induced reduction in LF power of ARI and the witnessed reduction of beat-to-beat variability of ARI (r s = 0.74, p = 0.01). These clinical results accord with recent computational modeling studies which provide mechanistic insight into the interactions of LF oscillations and beat-to-beat variability of APD at the cellular level.

CONCLUSION

Beta-adrenergic blockade reduces LF oscillatory behavior of APD (ARI) in humans in vivo. Our results support the importance of LF oscillations in modulating the response of BVR to beta-adrenergic blockers, suggesting that LF oscillations may play role in modulating beta-adrenergic mechanisms underlying BVR.

Mechanisms Underlying Interactions Between Low-Frequency Oscillations and Beat-to-Beat Variability of Celullar Ventricular Repolarization in Response to Sympathetic Stimulation: Implications for Arrhythmogenesis

Background and Objectives: Enhanced beat-to-beat variability of ventricular repolarization (BVR) has been linked to arrhythmias and sudden cardiac death. Recent experimental studies on human left ventricular epicardial electrograms have shown that BVR closely interacts with low-frequency (LF) oscillations of activation recovery interval during sympathetic provocation. In this work human ventricular computational cell models are developed to reproduce the experimentally observed interactions between BVR and its LF oscillations, to assess underlying mechanisms and to establish a relationship with arrhythmic risk.

Materials and Methods: A set of human ventricular action potential (AP) models covering a range of experimental electrophysiological characteristics was constructed. These models incorporated stochasticity in major ionic currents as well as descriptions of β-adrenergic stimulation and mechanical effects to investigate the AP response to enhanced sympathetic activity. Statistical methods based on Automatic Relevance Determination and Canonical Correlation Analysis were developed to unravel individual and common factors contributing to BVR and LF patterning of APD in response to sympathetic provocation.

Results: Simulated results reproduced experimental evidences on the interactions between BVR and LF oscillations of AP duration (APD), with replication of the high inter-individual variability observed in both phenomena. I_CaL, I_Kr and I_K1 currents were identified as common ionic modulators of the inter-individual differences in BVR and LF oscillatory behavior and were shown to be crucial in determining susceptibility to arrhythmogenic events.

Conclusions: The calibrated family of human ventricular cell models proposed in this study allows reproducing experimentally reported interactions between BVR and LF oscillations of APD. Ionic factors involving I_CaL, I_Kr and I_K1 currents are found to underlie correlated increments in both phenomena in response to sympathetic provocation. A link to arrhythmogenesis is established for concomitantly elevated levels of BVR and its LF oscillations.

Data-Driven Identification of Stochastic Model Parameters and State Variables: Application to the Study of Cardiac Beat-to-Beat Variability

OBJECTIVE

Enhanced spatiotemporal ventricular repolarization variability has been associated with ventricular arrhythmias and sudden cardiac death, but the involved mechanisms remain elusive. In this paper, a methodology for estimation of parameters and state variables of stochastic human ventricular cell models from input voltage data is proposed for investigation of repolarization variability.

METHODS

The proposed methodology formulates state-space representations based on developed stochastic cell models and uses the unscented Kalman filter to perform joint parameter and state estimation. Evaluation over synthetic and experimental data is presented.

RESULTS

Results on synthetically generated data show the ability of the methodology to: first, filter out measurement noise from action potential (AP) traces; second, identify model parameters and state variables from each of those individual AP traces, thus allowing robust characterization of cell-to-cell variability; and, third, replicate statistical population's distributions of input AP-based markers, including dynamic markers quantifying beat-to-beat variability. Application onto experimental data demonstrates the ability of the methodology to match input AP traces while concomitantly inferring the characteristics of underlying stochastic cell models.

CONCLUSION

A novel methodology is presented for estimation of parameters and hidden variables of stochastic cardiac computational models, with the advantage of providing a one-to-one match between each individual AP trace and a corresponding set of model characteristics.

SIGNIFICANCE

The proposed methodology can greatly help in the characterization of temporal (beat-to-beat) and spatial (cell-to-cell) variability in human ventricular repolarization and in ascertaining the corresponding underlying mechanisms, particularly in scenarios with limited available experimental data.

Modelling variability in cardiac electrophysiology: a moment-matching approach

The variability observed in action potential (AP) cardiomyocyte measurements is the consequence of many different sources of randomness. Often ignored, this variability may be studied to gain insight into the cell ionic properties. In this paper, we focus on the study of ionic channel conductances and describe a methodology to estimate their probability density function (PDF) from AP recordings. The method relies on the matching of observable statistical moments and on the maximum entropy principle. We present four case studies using synthetic and sets of experimental AP measurements from human and canine cardiomyocytes. In each case, the proposed methodology is applied to infer the PDF of key conductances from the exhibited variability. The estimated PDFs are discussed and, when possible, compared to the true distributions. We conclude that it is possible to extract relevant information from the variability in AP measurements and discuss the limitations and possible implications of the proposed approach.

Beat-to-Beat Variability of Ventricular Action Potential Duration Oscillates at Low Frequency During Sympathetic Provocation in Humans

Background: The temporal pattern of ventricular repolarization is of critical importance in arrhythmogenesis. Enhanced beat-to-beat variability (BBV) of ventricular action potential duration (APD) is pro-arrhythmic and is increased during sympathetic provocation. Since sympathetic nerve activity characteristically exhibits burst patterning in the low frequency range, we hypothesized that physiologically enhanced sympathetic activity may not only increase BBV of left ventricular APD but also impose a low frequency oscillation which further increases repolarization instability in humans. Methods and Results: Heart failure patients with cardiac resynchronization therapy defibrillator devices (n = 11) had activation recovery intervals (ARI, surrogate for APD) recorded from left ventricular epicardial electrodes alongside simultaneous non-invasive blood pressure and respiratory recordings. Fixed cycle length was achieved by right ventricular pacing. Recordings took place during resting conditions and following an autonomic stimulus (Valsalva). The variability of ARI and the normalized variability of ARI showed significant increases post Valsalva when compared to control (p = 0.019 and p = 0.032, respectively). The oscillatory behavior was quantified by spectral analysis. Significant increases in low frequency (LF) power (p = 0.002) and normalized LF power (p = 0.019) of ARI were seen following Valsalva. The Valsalva did not induce changes in conduction variability nor the LF oscillatory behavior of conduction. However, increases in the LF power of ARI were accompanied by increases in the LF power of systolic blood pressure (SBP) and the rate of systolic pressure increase (dP/dtmax). Positive correlations were found between LF-SBP and LF-dP/dtmax (rs = 0.933, p < 0.001), LF-ARI and LF-SBP (rs = 0.681, p = 0.001) and between LF-ARI and LF-dP/dtmax (rs = 0.623, p = 0.004). There was a strong positive correlation between the variability of ARI and LF power of ARI (rs = 0.679, p < 0.001). Conclusions: In heart failure patients, physiological sympathetic provocation induced low frequency oscillation (~0.1 Hz) of left ventricular APD with a strong positive correlation between the LF power of APD and the BBV of APD. These findings may be of importance in mechanisms underlying stability/instability of repolarization and arrhythmogenesis in humans.

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.

Superaligned Carbon Nanotubes Guide Oriented Cell Growth and Promote Electrophysiological Homogeneity for Synthetic Cardiac Tissues

Cardiac engineering of patches and tissues is a promising option to restore infarcted hearts, by seeding cardiac cells onto scaffolds and nurturing their growth in vitro. However, current patches fail to fully imitate the hierarchically aligned structure in the natural myocardium, the fast electrotonic propagation, and the subsequent synchronized contractions. Here, superaligned carbon-nanotube sheets (SA-CNTs) are explored to culture cardiomyocytes, mimicking the aligned structure and electrical-impulse transmission behavior of the natural myocardium. The SA-CNTs not only induce an elongated and aligned cell morphology of cultured cardiomyocytes, but also provide efficient extracellular signal-transmission pathways required for regular and synchronous cell contractions. Furthermore, the SA-CNTs can reduce the beat-to-beat and cell-to-cell dispersion in repolarization of cultured cells, which is essential for a normal beating rhythm, and potentially reduce the occurrence of arrhythmias. Finally, SA-CNT-based flexible one-piece electrodes demonstrate a multipoint pacing function. These combined high properties make SA-CNTs promising in applications in cardiac resynchronization therapy in patients with heart failure and following myocardial infarctions.

Integrating cardiomyocytes from human pluripotent stem cells in safety pharmacology: has the time come?

Cardiotoxicity is a severe side effect of drugs that induce structural or electrophysiological changes in heart muscle cells. As a result, the heart undergoes failure and potentially lethal arrhythmias. It is still a major reason for drug failure in preclinical and clinical phases of drug discovery. Current methods for predicting cardiotoxicity are based on guidelines that combine electrophysiological analysis of cell lines expressing ion channels ectopically in vitro with animal models and clinical trials. Although no new cases of drugs linked to lethal arrhythmias have been reported since the introduction of these guidelines in 2005, their limited predictive power likely means that potentially valuable drugs may not reach clinical practice. Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are now emerging as potentially more predictive alternatives, particularly for the early phases of preclinical research. However, these cells are phenotypically immature and culture and assay methods not standardized, which could be a hurdle to the development of predictive computational models and their implementation into the drug discovery pipeline, in contrast to the ambitions of the comprehensive pro-arrhythmia in vitro assay (CiPA) initiative. Here, we review present and future preclinical cardiotoxicity screening and suggest possible hPSC-CM-based strategies that may help to move the field forward. Coordinated efforts by basic scientists, companies and hPSC banks to standardize experimental conditions for generating reliable and reproducible safety indices will be helpful not only for cardiotoxicity prediction but also for precision medicine.

LINKED ARTICLES

This article is part of a themed section on New Insights into Cardiotoxicity Caused by Chemotherapeutic Agents. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.21/issuetoc.

Humans Vary, So Cardiac Models Should Account for That Too!

The utilization of mathematical modeling and simulation in drug development encompasses multiple mathematical techniques and the location of a drug candidate in the development pipeline. Historically speaking they have been used to analyze experimental data (i.e., Hill equation) and clarify the involved physical and chemical processes (i.e., Fick laws and drug molecule diffusion). In recent years the advanced utilization of mathematical modeling has been an important part of the regulatory review process. Physiologically based pharmacokinetic (PBPK) models identify the need to conduct specific clinical studies, suggest specific study designs and propose appropriate labeling language. Their application allows the evaluation of the influence of intrinsic (e.g., age, gender, genetics, disease) and extrinsic [e.g., dosing schedule, drug-drug interactions (DDIs)] factors, alone or in combinations, on drug exposure and therefore provides accurate population assessment. A similar pathway has been taken for the assessment of drug safety with cardiac safety being one the most advanced examples. Mechanistic mathematical model-informed safety evaluation, with a focus on drug potential for causing arrhythmias, is now discussed as an element of the Comprehensive in vitro Proarrhythmia Assay. One of the pillars of this paradigm is the use of an in silico model of the adult human ventricular cardiomyocyte to integrate in vitro measured data. Existing examples (in vitro—in vivo extrapolation with the use of PBPK models) suggest that deterministic, epidemiological and clinical data based variability models can be merged with the mechanistic models describing human physiology. There are other methods available, based on the stochastic approach and on population of models generated by randomly assigning specific parameter values (ionic current conductance and kinetic) and further pruning. Both approaches are briefly characterized in this manuscript, in parallel with the drug-specific variability.

Regularity of beating of small clusters of embryonic chick ventricular heart-cells: experiment vs. stochastic single-channel population model

The transmembrane potential is recorded from small isopotential clusters of 2-4 embryonic chick ventricular cells spontaneously generating action potentials. We analyze the cycle-to-cycle fluctuations in the time between successive action potentials (the interbeat interval or IBI). We also convert an existing model of electrical activity in the cluster, which is formulated as a Hodgkin-Huxley-like deterministic system of nonlinear ordinary differential equations describing five individual ionic currents, into a stochastic model consisting of a population of ∼20 000 independently and randomly gating ionic channels, with the randomness being set by a real physical stochastic process (radio static). This stochastic model, implemented using the Clay-DeFelice algorithm, reproduces the fluctuations seen experimentally: e.g., the coefficient of variation (standard deviation/mean) of IBI is 4.3% in the model vs. the 3.9% average value of the 17 clusters studied. The model also replicates all but one of several other quantitative measures of the experimental results, including the power spectrum and correlation integral of the voltage, as well as the histogram, Poincaré plot, serial correlation coefficients, power spectrum, detrended fluctuation analysis, approximate entropy, and sample entropy of IBI. The channel noise from one particular ionic current (I_Ks), which has channel kinetics that are relatively slow compared to that of the other currents, makes the major contribution to the fluctuations in IBI. Reproduction of the experimental coefficient of variation of IBI by adding a Gaussian white noise-current into the deterministic model necessitates using an unrealistically high noise-current amplitude. Indeed, a major implication of the modelling results is that, given the wide range of time-scales over which the various species of channels open and close, only a cell-specific stochastic model that is formulated taking into consideration the widely different ranges in the frequency content of the channel-noise produced by the opening and closing of several different types of channels will be able to reproduce precisely the various effects due to membrane noise seen in a particular electrophysiological preparation.

Autonomic Modulation in Patients with Heart Failure Increases Beat-to-Beat Variability of Ventricular Action Potential Duration

Background: Exaggerated beat-to-beat variability of ventricular action potential duration (APD) is linked to arrhythmogenesis. Sympathetic stimulation has been shown to increase QT interval variability, but its effect on ventricular APD in humans has not been determined.

Methods and Results: Eleven heart failure patients with implanted bi-ventricular pacing devices had activation–recovery intervals (ARI, surrogate for APD) recorded from LV epicardial electrodes under constant RV pacing. Sympathetic activity was increased using a standard autonomic challenge (Valsalva) and baroreceptor indices were applied to determine changes in sympathetic stimulation. Two Valsalvas were performed for each study and were repeated, both off and on bisoprolol. In addition sympathetic nerve activity (SNA) was measured from skin electrodes on the thorax using a novel validated method. Autonomic modulation significantly increased mean short-term variability in ARI; off bisoprolol mean STV increased from 3.73 ± 1.3 to 5.27 ± 1.04 ms (p = 0.01), on bisoprolol mean STV of ARI increased from 4.15 ± 1.14 to 4.62 ± 1 ms (p = 0.14). Adrenergic indices of the Valsalva demonstrated significantly reduced beta-adrenergic function when on bisoprolol (Δ pressure recovery time, p = 0.04; Δ systolic overshoot in Phase IV, p = 0.05). Corresponding increases in SNA from rest both off (1.4 uV, p < 0.01) and on (0.7 uV, p < 0.01) bisoprolol were also seen.

Conclusions: Beat-to-beat variability of ventricular APD increases during brief periods of increased sympathetic activity in patients with heart failure. Bisoprolol reduces, but does not eliminate, these effects. This may be important in the genesis of ventricular arrhythmias in heart failure patients.

β-Adrenergic receptor stimulation inhibits proarrhythmic alternans in postinfarction border zone cardiomyocytes: a computational analysis

We integrated, for the first time, postmyocardial infarction electrical and autonomic remodeling in a detailed, validated computer model of β-adrenergic stimulation in ventricular cardiomyocytes. Here, we show that β-adrenergic stimulation inhibits alternans and provide novel insights into underlying mechanisms, adding to a recent controversy about pro-/antiarrhythmic effects of postmyocardial infarction hyperinnervation.

The border zone (BZ) of the viable myocardium adjacent to an infarct undergoes extensive autonomic and electrical remodeling and is prone to repolarization alternans-induced cardiac arrhythmias. BZ remodeling processes may promote or inhibit Ca²⁺ and/or repolarization alternans and may differentially affect ventricular arrhythmogenesis. Here, we used a detailed computational model of the canine ventricular cardiomyocyte to study the determinants of alternans in the BZ and their regulation by β-adrenergic receptor (β-AR) stimulation. The BZ model developed Ca²⁺ transient alternans at slower pacing cycle lengths than the control model, suggesting that the BZ may promote spatially heterogeneous alternans formation in an infarcted heart. β-AR stimulation abolished alternans. By evaluating all combinations of downstream β-AR stimulation targets, we identified both direct (via ryanodine receptor channels) and indirect [via sarcoplasmic reticulum (SR) Ca²⁺ load] modulation of SR Ca²⁺ release as critical determinants of Ca²⁺ transient alternans. These findings were confirmed in a human ventricular cardiomyocyte model. Cell-to-cell coupling indirectly modulated the likelihood of alternans by affecting the action potential upstroke, reducing the trigger for SR Ca²⁺ release in one-dimensional strand simulations. However, β-AR stimulation inhibited alternans in both single and multicellular simulations. Taken together, these data highlight a potential antiarrhythmic role of sympathetic hyperinnervation in the BZ by reducing the likelihood of alternans and provide new insights into the underlying mechanisms controlling Ca²⁺ transient and repolarization alternans.

NEW & NOTEWORTHY We integrated, for the first time, postmyocardial infarction electrical and autonomic remodeling in a detailed, validated computer model of β-adrenergic stimulation in ventricular cardiomyocytes. Here, we show that β-adrenergic stimulation inhibits alternans and provide novel insights into underlying mechanisms, adding to a recent controversy about pro-/antiarrhythmic effects of postmyocardial infarction hyperinnervation.

Listen to this article’s corresponding podcast at http://ajpheart.podbean.com/e/%CE%B2-ar-stimulation-and-alternans-in-border-zone-cardiomyocytes/.

A new hERG allosteric modulator rescues genetic and drug-induced long-QT syndrome phenotypes in cardiomyocytes from isogenic pairs of patient induced pluripotent stem cells

Long-QT syndrome (LQTS) is an arrhythmogenic disorder characterised by prolongation of the QT interval in the electrocardiogram, which can lead to sudden cardiac death. Pharmacological treatments are far from optimal for congenital forms of LQTS, while the acquired form, often triggered by drugs that (sometimes inadvertently) target the cardiac hERG channel, is still a challenge in drug development because of cardiotoxicity. Current experimental models in vitro fall short in predicting proarrhythmic properties of new drugs in humans. Here, we leveraged a series of isogenically matched, diseased and genetically engineered, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients to test a novel hERG allosteric modulator for treating congenital LQTS, drug-induced LQTS or a combination of the two. By slowing IK r deactivation and positively shifting IK r inactivation, the small molecule LUF7346 effectively rescued all of these conditions, demonstrating in a human system that allosteric modulation of hERG may be useful as an approach to treat inherited and drug-induced LQTS Furthermore, our study provides experimental support of the value of isogenic pairs of patient hiPSC-CMs as platforms for testing drug sensitivities and performing safety pharmacology.