Disrupted calcium release as a mechanism for atrial alternans associated with human atrial fibrillation

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Up digital and personal: How heart digital twins can transform heart patient care

Precision medicine is the vision of health care where therapy is tailored to each patient. As part of this vision, digital twinning technology promises to deliver a digital representation of organs or even patients by using tools capable of simulating personal health conditions and predicting patient or disease trajectories on the basis of relationships learned both from data and from biophysics knowledge. Such virtual replicas would update themselves with data from monitoring devices and medical tests and assessments, reflecting dynamically the changes in our health conditions and the responses to treatment. In precision cardiology, the concepts and initial applications of heart digital twins have slowly been gaining popularity and the trust of the clinical community. In this article, we review the advancement in heart digital twinning and its initial translation to the management of heart rhythm disorders.

Targeted Atrial Fibrillation Therapy and Risk Stratification Using Atrial Alternans

Atrial fibrillation (AF) is the most persistent arrhythmia today, with its prevalence increasing exponentially with the rising age of the population. Particularly at elevated heart rates, a functional abnormality known as cardiac alternans can occur prior to the onset of lethal arrhythmias. Cardiac alternans are a beat-to-beat oscillation of electrical activity and the force of cardiac muscle contraction. Extensive evidence has demonstrated that microvolt T-wave alternans can predict ventricular fibrillation vulnerability and the risk of sudden cardiac death. The majority of our knowledge of the mechanisms of alternans stems from studies of ventricular electrophysiology, although recent studies offer promising evidence of the potential of atrial alternans in predicting the risk of AF. Exciting preclinical and clinical studies have demonstrated a link between atrial alternans and the onset of atrial tachyarrhythmias. Here, we provide a comprehensive review of the clinical utility of atrial alternans in identifying the risk and guiding treatment of AF.

Chronic catestatin treatment reduces atrial fibrillation susceptibility via improving calcium handling in post-infarction heart failure rats

BACKGROUND

Abnormal Ca²⁺ handling is a pivotal element of atrial fibrillation (AF) substrates. Catestatin (CST) modulates intracellular Ca²⁺ handling in cardiomyocytes (CMs). We investigated the effects of CST administration on atrial Ca²⁺ handling and AF susceptibility in rats with post-infarction heart failure (HF).

METHODS

Myocardial infarction (MI) was established by ligation of the left anterior descending coronary artery in rats. Two-week later, rats with post-infarction HF were randomly treated with saline (MI group) or CST (MI + CST group) for 4-week. Cellular Ca²⁺ imaging was performed by incubating atrial CMs with Fura-2 AM. An in vitro electrophysiological study was performed to assess the vulnerability to action potential duration (APD) alternans and AF. Ca²⁺ handling proteins expression was determined using western blotting.

RESULTS

In atrial CMs, compared with the sham group, the sarcoplasmic reticulum (SR) Ca²⁺ load, Ca²⁺ transient (CaT) amplitude, and threshold for Ca²⁺ alternans were significantly decreased, but the diastolic intracellular Ca²⁺ level, SR Ca²⁺ leakage, and spontaneous Ca²⁺ events were markedly increased in the MI group. However, CST attenuated these Ca²⁺-handling abnormalities induced by post-infarction HF. Moreover, vulnerability to atrial APD alternans and AF was significantly increased in isolated hearts from the MI group compared to the sham group, whereas all effects were prevented by CST. CST treatment also preserved SR Ca²⁺-ATPase protein expression but decreased the protein levels of phosphorylated-ryanodine receptor 2 and phosphorylated-Ca²⁺/calmodulin-dependent protein kinase II in atria from post-infarction HF rats.

CONCLUSION

Chronic CST treatment reduces AF vulnerability in rats with MI-induced HF by improving Ca²⁺ handling.

Sensitivity Analysis of Cardiac Alternans and Tachyarrhythmia to Ion Channel Conductance Using Population Modeling

Action potential duration (APD) alternans, an alternating phenomenon between action potentials in cardiomyocytes, causes heart arrhythmia when the heart rate is high. However, some of the APD alternans observed in clinical trials occurs under slow heart rate conditions of 100 to 120 bpm, increasing the likelihood of heart arrhythmias such as atrial fibrillation. Advanced studies have identified the occurrence of this type of APD alternans in terms of electrophysiological ion channel currents in cells. However, they only identified physiological phenomena, such as action potential due to random changes in a particular ion channel’s conductivity through ion models specializing in specific ion channel currents. In this study, we performed parameter sensitivity analysis via population modeling using a validated human ventricular physiology model to check the sensitivity of APD alternans to ion channel conductances. Through population modeling, we expressed the changes in alternans onset cycle length (AOCL) and mean APD in AOCL (AO meanAPD) according to the variations in ion channel conductance. Finally, we identified the ion channel that maximally affected the occurrence of APD alternans. AOCL and AO meanAPD were sensitive to changes in the plateau Ca²⁺ current. Accordingly, it was expected that APD alternans would be vulnerable to changes in intracellular calcium concentration.

Rule-based definition of muscle bundles in patient-specific models of the left atrium

Atrial fibrillation (AF) is the most common arrhythmia encountered clinically, and as the population ages, its prevalence is increasing. Although the CHA2DS2- VASc score is the most used risk-stratification system for stroke risk in AF, it lacks personalization. Patient-specific computer models of the atria can facilitate personalized risk assessment and treatment planning. However, a challenge faced in creating such models is the complexity of the atrial muscle arrangement and its influence on the atrial fiber architecture. This work proposes a semi-automated rule-based algorithm to generate the local fiber orientation in the left atrium (LA). We use the solutions of several harmonic equations to decompose the LA anatomy into subregions. Solution gradients define a two-layer fiber field in each subregion. The robustness of our approach is demonstrated by recreating the fiber orientation on nine models of the LA obtained from AF patients who underwent WATCHMAN device implantation. This cohort of patients encompasses a variety of morphology variants of the left atrium, both in terms of the left atrial appendages (LAAs) and the number of pulmonary veins (PVs). We test the fiber construction algorithm by performing electrophysiology (EP) simulations. Furthermore, this study is the first to compare its results with other rule-based algorithms for the LA fiber architecture definition available in the literature. This analysis suggests that a multi-layer fiber architecture is important to capture complex electrical activation patterns. A notable advantage of our approach is the ability to reconstruct the main LA fiber bundles in a variety of morphologies while solving for a small number of harmonic fields, leading to a comparatively straightforward and reproducible approach.

Interleukin-6-Mediated-Ca2+ Handling Abnormalities Contributes to Atrial Fibrillation in Sterile Pericarditis Rats

Pre-existing Ca²⁺ handling abnormalities constitute the arrhythmogenic substrate in patients developing postoperative atrial fibrillation (POAF), a common complication after cardiac surgery. Postoperative interleukin (IL)-6 levels are associated with atrial fibrosis in several animal models of POAF, contributing to atrial arrhythmias. Here, we hypothesize that IL-6-mediated-Ca²⁺ handling abnormalities contribute to atrial fibrillation (AF) in sterile pericarditis (SP) rats, an animal model of POAF. SP was induced in rats by dusting atria with sterile talcum powder. Anti-rat-IL-6 antibody (16.7 μg/kg) was administered intraperitoneally at 30 min after the recovery of anesthesia. In vivo electrophysiology, ex vivo optical mapping, western blots, and immunohistochemistry were performed to elucidate mechanisms of AF susceptibility. IL-6 neutralization ameliorated atrial inflammation and fibrosis, as well as AF susceptibility in vivo and the frequency of atrial ectopy and AF with a reentrant pattern in SP rats ex vivo. IL-6 neutralization reversed the prolongation and regional heterogeneity of Ca²⁺ transient duration, relieved alternans, reduced the incidence of discordant alternans, and prevented the reduction and regional heterogeneity of the recovery ratio of Ca²⁺ transient. In agreement, western blots showed that IL-6 neutralization reversed the reduction in the expression of ryanodine receptor 2 (RyR2) and phosphorylated phospholamban. Acute IL-6 administration to isolated rat hearts recapitulated partial Ca²⁺ handling phenotype in SP rats. In addition, intraperitoneal IL-6 administration to rats increased AF susceptibility, independent of fibrosis. Our results reveal that IL-6-mediated-Ca²⁺ handling abnormalities in SP rats, especially RyR2-dysfunction, independent of IL-6-induced-fibrosis, early contribute to the development of POAF by increasing propensity for arrhythmogenic alternans.

Computational models of atrial fibrillation: achievements, challenges, and perspectives for improving clinical care

Despite significant advances in its detection, understanding and management, atrial fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on morbidity and mortality of millions of patients. AF results from complex, dynamic interactions between risk factors and comorbidities that induce diverse atrial remodelling processes. Atrial remodelling increases AF vulnerability and persistence, while promoting disease progression. The variability in presentation and wide range of mechanisms involved in initiation, maintenance and progression of AF, as well as its associated adverse outcomes, make the early identification of causal factors modifiable with therapeutic interventions challenging, likely contributing to suboptimal efficacy of current AF management. Computational modelling facilitates the multilevel integration of multiple datasets and offers new opportunities for mechanistic understanding, risk prediction and personalized therapy. Mathematical simulations of cardiac electrophysiology have been around for 60 years and are being increasingly used to improve our understanding of AF mechanisms and guide AF therapy. This narrative review focuses on the emerging and future applications of computational modelling in AF management. We summarize clinical challenges that may benefit from computational modelling, provide an overview of the different in silico approaches that are available together with their notable achievements, and discuss the major limitations that hinder the routine clinical application of these approaches. Finally, future perspectives are addressed. With the rapid progress in electronic technologies including computing, clinical applications of computational modelling are advancing rapidly. We expect that their application will progressively increase in prominence, especially if their added value can be demonstrated in clinical trials.

Low-Level Tragus Stimulation Modulates Atrial Alternans and Fibrillation Burden in Patients With Paroxysmal Atrial Fibrillation

Background

Low‐level tragus stimulation (LLTS) has been shown to significantly reduce atrial fibrillation (AF) burden in patients with paroxysmal AF. P‐wave alternans (PWA) is believed to be generated by the same substrate responsible for AF. Hence, PWA may serve as a marker in guiding LLTS therapy. We investigated the utility of PWA in guiding LLTS therapy in patients with AF.

Methods and Results

Twenty‐eight patients with AF were randomized to either active LLTS or sham (earlobe stimulation). LLTS was delivered through a transcutaneous electrical nerve stimulation device (pulse width 200 μs, frequency 20 Hz, amplitude 10–50 mA), for 1 hour daily over a 6‐month period. AF burden over 2‐week periods was assessed by noninvasive continuous ECG monitoring at baseline, 3 months, and 6 months. A 5‐minute control ECG for PWA analysis was recorded during all 3 follow‐up visits. Following the control ECG, an additional 5‐minute ECG was recorded during active LLTS in all patients. At baseline, acute LLTS led to a significant rise in PWA burden. However, active patients receiving chronic LLTS demonstrated a significant reduction in both PWA and AF burden after 6 months (P<0.05). Active patients who demonstrated an increase in PWA burden with acute LLTS showed a significant drop in AF burden after 6 months of chronic LLTS.

Conclusions

Chronic, intermittent LLTS resulted in lower PWA and AF burden than did sham control stimulation. Our results support the use of PWA as a potential marker for guiding LLTS treatment of paroxysmal AF.

Altered calcium handling produces reentry-promoting action potential alternans in atrial fibrillation-remodeled hearts

Atrial fibrillation (AF) alters atrial cardiomyocyte (ACM) Ca2+ handling, promoting ectopic beat formation. We examined the effects of AF-associated remodeling on Ca2+-related action potential dynamics and consequences for AF susceptibility. AF was maintained electrically in dogs by right atrial (RA) tachypacing. ACMs isolated from AF dogs showed increased Ca2+ release refractoriness, spontaneous Ca2+ spark frequency, and cycle length (CL) threshold for Ca2+ and action potential duration (APD) alternans versus controls. AF increased the in situ CL threshold for Ca2+/APD alternans and spatial dispersion in Ca2+ release recovery kinetics, leading to spatially discordant alternans associated with reentrant rotor formation and susceptibility to AF induction/maintenance. The clinically available agent dantrolene reduced Ca2+ leak and CL threshold for Ca2+/APD alternans in ACMs and AF dog right atrium, while suppressing AF susceptibility; caffeine increased Ca2+ leak and CL threshold for Ca2+/APD alternans in control dog ACMs and RA tissues. In vivo, the atrial repolarization alternans CL threshold was increased in AF versus control, as was AF vulnerability. Intravenous dantrolene restored repolarization alternans threshold and reduced AF vulnerability. Immunoblots showed reduced expression of total and phosphorylated ryanodine receptors and calsequestrin in AF and unchanged phospholamban/SERCA expression. Thus, along with promoting spontaneous ectopy, AF-induced Ca2+ handling abnormalities favor AF by enhancing vulnerability to repolarization alternans, promoting initiation and maintenance of reentrant activity; dantrolene provides a lead molecule to target this mechanism.

Computational models in cardiology

The treatment of individual patients in cardiology practice increasingly relies on advanced imaging, genetic screening and devices. As the amount of imaging and other diagnostic data increases, paralleled by the greater capacity to personalize treatment, the difficulty of using the full array of measurements of a patient to determine an optimal treatment seems also to be paradoxically increasing. Computational models are progressively addressing this issue by providing a common framework for integrating multiple data sets from individual patients. These models, which are based on physiology and physics rather than on population statistics, enable computational simulations to reveal diagnostic information that would have otherwise remained concealed and to predict treatment outcomes for individual patients. The inherent need for patient-specific models in cardiology is clear and is driving the rapid development of tools and techniques for creating personalized methods to guide pharmaceutical therapy, deployment of devices and surgical interventions.

Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment

Multiscale computational models of the heart are being extensively investigated for improved assessment of drug-induced torsades de pointes (TdP) risk, a fatal side effect of many drugs. Model-derived metrics such as action potential duration and net charge carried by ionic currents (qNet) have been proposed as potential candidates for TdP risk stratification after being tested on small datasets. Unlike purely statistical approaches, model-derived metrics are thought to provide mechanism-based classification. In particular, qNet has been recently proposed as a surrogate metric for early afterdepolarizations (EADs), which are known to be cellular triggers of TdP. Analysis of critical model components and of the ion channels that have major impact on model-derived metrics can lead to improvements in the confidence of the prediction. In this paper, we analyze large populations of virtual drugs to systematically examine the influence of different ion channels on model-derived metrics that have been proposed for proarrhythmic risk assessment. We demonstrate via global sensitivity analysis (GSA) that model-derived metrics are most sensitive to different sets of input parameters. Similarly, important differences in sensitivity to specific channel blocks are highlighted when classifying drugs into different risk categories by either qNet or a metric directly based on simulated EADs. In particular, the higher sensitivity of qNet to the block of the late sodium channel might explain why its classification accuracy is better than that of the EAD-based metric, as shown for a small set of known drugs. Our results highlight the need for a better mechanistic interpretation of promising metrics like qNet based on a formal analysis of models. GSA should, therefore, constitute an essential component of the in silico workflow for proarrhythmic risk assessment, as an improved understanding of the structure of model-derived metrics could increase confidence in model-predicted risk.

Understanding AF Mechanisms Through Computational Modelling and Simulations

AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF.

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

The remarkable advances in high-performance computing and the resulting increase of the computational power have the potential to leverage computational cardiology toward improving our understanding of the pathophysiological mechanisms of arrhythmias, such as Atrial Fibrillation (AF). In AF, a complex interaction between various triggers and the atrial substrate is considered to be the leading cause of AF initiation and perpetuation. In electrocardiography (ECG), P-wave is supposed to reflect atrial depolarization. It has been found that even during sinus rhythm (SR), multiple P-wave morphologies are present in AF patients with a history of AF, suggesting a higher dispersion of the conduction route in this population. In this scoping review, we focused on the mechanisms which modify the electrical substrate of the atria in AF patients, while investigating the existence of computational models that simulate the propagation of the electrical signal through different routes. The adopted review methodology is based on a structured analytical framework which includes the extraction of the keywords based on an initial limited bibliographic search, the extensive literature search and finally the identification of relevant articles based on the reference list of the studies. The leading mechanisms identified were classified according to their scale, spanning from mechanisms in the cell, tissue or organ level, and the produced outputs. The computational modeling approaches for each of the factors that influence the initiation and the perpetuation of AF are presented here to provide a clear overview of the existing literature. Several levels of categorization were adopted while the studies which aim to translate their findings to ECG phenotyping are highlighted. The results denote the availability of multiple models, which are appropriate under specific conditions. However, the consideration of complex scenarios taking into account multiple spatiotemporal scales, personalization of electrophysiological and anatomical models and the reproducibility in terms of ECG phenotyping has only partially been tackled so far.

The role of personalized atrial modeling in understanding atrial fibrillation mechanisms and improving treatment

Atrial fibrillation is the most common arrhythmia in humans and is associated with high morbidity, mortality and health-related expenses. Computational approaches have been increasingly utilized in atrial electrophysiology. In this review we summarize the recent advancements in atrial fibrillation modeling at the organ scale. Multi-scale atrial models now incorporate high level detail of atrial anatomy, tissue ultrastructure and fibrosis distribution. We provide the state-of-the art methodologies in developing personalized atrial fibrillation models with realistic geometry and tissue properties. We then focus on the use of multi-scale atrial models to gain mechanistic insights in AF. Simulations using atrial models have provided important insight in the mechanisms underlying AF, showing the importance of the atrial fibrotic substrate and altered atrial electrophysiology in initiation and maintenance of AF. Last, we summarize the translational evidence that supports incorporation of computational modeling in clinical practice for development of personalized treatment strategies for patients with AF. In early-stages clinical studies, AF models successfully identify patients where pulmonary vein isolation alone is not adequate for treatment of AF and suggest novel targets for ablation. We conclude with a summary of the future developments envisioned for the field of atrial computational electrophysiology.

Increased thin filament activation enhances alternans in human chronic atrial fibrillation

Action potential duration (APD) alternans (APD-ALT), defined as beat-to-beat oscillations in APD, has been proposed as an important clinical marker for chronic atrial fibrillation (cAF) risk when it occurs at pacing rates of 120-200 beats/min. Although the ionic mechanisms for occurrence of APD-ALT in human cAF at these clinically relevant rates have been investigated, little is known about the effects of myofilament protein kinetics on APD-ALT. Therefore, we used computer simulations of single cell function to explore whether remodeling in myofilament protein kinetics in human cAF alters the occurrence of APD-ALT and to uncover how these mechanisms are affected by sarcomere length and the degree of cAF-induced myofilament remodeling. Mechanistically based, bidirectionally coupled electromechanical models of human right and left atrial myocytes were constructed, incorporating both ionic and myofilament remodeling associated with cAF. By comparing results from our electromechanical model with those from the uncoupled ionic model, we found that intracellular Ca2+ concentration buffering of troponin C has a dampening effect on the magnitude of APD-ALT (APD-ANM) at slower rates (150 beats/min) due to the cooperativity between strongly bound cross-bridges and Ca2+-troponin C binding affinity. We also discovered that cAF-induced enhanced thin filament activation enhanced APD-ANM at these clinically relevant heart rates (150 beats/min). In addition, longer sarcomere lengths increased APD-ANM, suggesting that atrial stretch is an important modulator of APD-ALT. Together, these findings demonstrate that myofilament kinetics mechanisms play an important role in altering APD-ALT in human cAF. NEW & NOTEWORTHY Using a single cell simulation approach, we explored how myofilament protein kinetics alter the formation of alternans in action potential duration (APD) in human myocytes with chronic atrial fibrillation remodeling. We discovered that enhanced thin filament activation and longer sarcomere lengths increased the magnitude of APD alternans at clinically important pacing rates of 120-200 beats/min. Furthermore, we found that altered intracellular Ca2+ concentration buffering of troponin C has a dampening effect on the magnitude of APD alternans.

Description of the Human Atrial Action Potential Derived From a Single, Congruent Data Source: Novel Computational Models for Integrated Experimental-Numerical Study of Atrial Arrhythmia Mechanisms

Introduction: The development of improved diagnosis, management, and treatment strategies for human atrial fibrillation (AF) is a significant and important challenge in order to improve quality of life for millions and reduce the substantial social-economic costs of the condition. As a complex condition demonstrating high variability and relation to other cardiac conditions, the study of AF requires approaches from multiple disciplines including single-cell experimental electrophysiology and computational modeling. Models of human atrial cells are less well parameterized than those of the human ventricle or other mammal species, largely due to the inherent challenges in patch clamping human atrial cells. Such challenges include, frequently, unphysiologically depolarized resting potentials and thus injection of a compensatory hyperpolarizing current, as well as detecting certain ion currents which may be disrupted by the cell isolation process. The aim of this study was to develop a laboratory specific model of human atrial electrophysiology which reproduces exactly the conditions of isolated-cell experiments, including testing of multiple experimental interventions. Methods: Formulations for the primary ion currents characterized by isolated-cell experiments in the Workman laboratory were fit directly to voltage-clamp data; the fast sodium-current was parameterized based on experiments relating resting membrane potential to maximal action potential upstroke velocity; compensatory hyperpolarizing current was included as a constant applied current. These formulations were integrated with three independent human atrial cell models to provide a family of novel models. Extrapolated intact-cell models were developed through removal of the hyperpolarizing current and introduction of terminal repolarization potassium currents. Results: The isolated-cell models quantitatively reproduced experimentally measured properties of excitation in both control and pharmacological and dynamic-clamp interventions. Comparison of isolated and intact-cell models highlighted the importance of reproducing this cellular environment when comparing experimental and simulation data. Conclusion: We have developed a laboratory specific model of the human atrial cell which directly reproduces the experimental isolated-cell conditions and captures human atrial excitation properties. The model may be particularly useful for directly relating model to experiment, and offers a complementary tool to the available set of human atrial cell models with specific advantages resulting from the congruent input data source.

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.

Mechanisms and Drug Development in Atrial Fibrillation

Atrial fibrillation is a highly prevalent cardiac arrhythmia and the most important cause of embolic stroke. Although genetic studies have identified an increasing assembly of AF-related genes, the impact of these genetic discoveries is yet to be realized. In addition, despite more than a century of research and speculation, the molecular and cellular mechanisms underlying AF have not been established, and therapy for AF, particularly persistent AF, remains suboptimal. Current antiarrhythmic drugs are associated with a significant rate of adverse events, particularly proarrhythmia, which may explain why many highly symptomatic AF patients are not receiving any rhythm control therapy. This review focuses on recent advances in AF research, including its epidemiology, genetics, and pathophysiological mechanisms. We then discuss the status of antiarrhythmic drug therapy for AF today, reviewing molecular mechanisms, and the possible clinical use of some of the new atrial-selective antifibrillatory agents, as well as drugs that target atrial remodeling, inflammation and fibrosis, which are being tested as upstream therapies to prevent AF perpetuation. Altogether, the objective is to highlight the magnitude and endemic dimension of AF, which requires a significant effort to develop new and effective antiarrhythmic drugs, but also improve AF prevention and treatment of risk factors that are associated with AF complications.

Slow [Na+]i dynamics impacts arrhythmogenesis and spiral wave reentry in cardiac myocyte ionic model

Accumulation of intracellular Na⁺ is gaining recognition as an important regulator of cardiac myocyte electrophysiology. The intracellular Na⁺ concentration can be an important determinant of the cardiac action potential duration, can modulate the tissue-level conduction of excitation waves, and can alter vulnerability to arrhythmias. Mathematical models of cardiac electrophysiology often incorporate a dynamic intracellular Na⁺ concentration, which changes much more slowly than the remaining variables. We investigated the dependence of several arrhythmogenesis-related factors on [Na⁺]_i in a mathematical model of the human atrial action potential. In cell simulations, we found that [Na⁺]_i accumulation stabilizes the action potential duration to variations in several conductances and that the slow dynamics of [Na⁺]_i impacts bifurcations to pro-arrhythmic afterdepolarizations, causing intermittency between different rhythms. In long-lasting tissue simulations of spiral wave reentry, [Na⁺]_i becomes spatially heterogeneous with a decreased area around the spiral wave rotation center. This heterogeneous region forms a functional anchor, resulting in diminished meandering of the spiral wave. Our findings suggest that slow, physiological, rate-dependent variations in [Na⁺]_i may play complex roles in cellular and tissue-level cardiac dynamics.

Minimal model for calcium alternans due to SR release refractoriness

In the heart, rapid pacing rates may induce alternations in the strength of cardiac contraction, termed pulsus alternans. Often, this is due to an instability in the dynamics of the intracellular calcium concentration, whose transients become larger and smaller at consecutive beats. This alternation has been linked experimentally and theoretically to two different mechanisms: an instability due to (1) a strong dependence of calcium release on sarcoplasmic reticulum (SR) load, together with a slow calcium reuptake into the SR or (2) to SR release refractoriness, due to a slow recovery of the ryanodine receptors (RyR2) from inactivation. The relationship between calcium alternans and refractoriness of the RyR2 has been more elusive than the corresponding SR Ca load mechanism. To study the former, we reduce a general calcium model, which mimics the deterministic evolution of a calcium release unit, to its most basic elements. We show that calcium alternans can be understood using a simple nonlinear equation for calcium concentration at the dyadic space, coupled to a relaxation equation for the number of recovered RyR2s. Depending on the number of RyR2s that are recovered at the beginning of a stimulation, the increase in calcium concentration may pass, or not, over an excitability threshold that limits the occurrence of a large calcium transient. When the recovery of the RyR2 is slow, this produces naturally a period doubling bifurcation, resulting in calcium alternans. We then study the effects of inactivation, calcium diffusion, and release conductance for the onset of alternans. We find that the development of alternans requires a well-defined value of diffusion while it is less sensitive to the values of inactivation or release conductance.

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Atrial arrhythmogenicity of KCNJ2 mutations in short QT syndrome: Insights from virtual human atria

Gain-of-function mutations in KCNJ2-encoded Kir2.1 channels underlie variant 3 (SQT3) of the short QT syndrome, which is associated with atrial fibrillation (AF). Using biophysically-detailed human atria computer models, this study investigated the mechanistic link between SQT3 mutations and atrial arrhythmogenesis, and potential ion channel targets for treatment of SQT3. A contemporary model of the human atrial action potential (AP) was modified to recapitulate functional changes in I_K1 due to heterozygous and homozygous forms of the D172N and E299V Kir2.1 mutations. Wild-type (WT) and mutant formulations were incorporated into multi-scale homogeneous and heterogeneous tissue models. Effects of mutations on AP duration (APD), conduction velocity (CV), effective refractory period (ERP), tissue excitation threshold and their rate-dependence, as well as the wavelength of re-entry (WL) were quantified. The D172N and E299V Kir2.1 mutations produced distinct effects on I_K1 and APD shortening. Both mutations decreased WL for re-entry through a reduction in ERP and CV. Stability of re-entrant excitation waves in 2D and 3D tissue models was mediated by changes to tissue excitability and dispersion of APD in mutation conditions. Combined block of I_K1 and I_Kr was effective in terminating re-entry associated with heterozygous D172N conditions, whereas I_Kr block alone may be a safer alternative for the E299V mutation. Combined inhibition of I_Kr and I_Kur produced a synergistic anti-arrhythmic effect in both forms of SQT3. In conclusion, this study provides mechanistic insights into atrial proarrhythmia with SQT3 Kir2.1 mutations and highlights possible pharmacological strategies for management of SQT3-linked AF.

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and is characterised by complex and irregular electrical activation of the upper chambers of the heart. One rare, genetic condition associated with increased risk of AF is the short QT syndrome (SQTS), which is caused by mutations in genes involved in normal electrical function of the heart. Underlying mechanisms by which SQTS-related gene mutations facilitate development of arrhythmias in the human atria are not well understood. In this study, sophisticated computer models representing ‘virtual’ human atria, incorporating detailed electrophysiological data at the ‘ion channel’ protein level into both idealised and realistic multi-scale tissue geometries, were used to dissect mechanisms by which two mutations in the KCNJ2 gene responsible for SQTS variant 3 (SQT3) promote initiation and sustenance of arrhythmias. It was found that the D172N and E299V mutations to KCNJ2 accelerated the repolarisation process at the cellular level through distinct mechanisms. This, along with the way the mutations affected heterogeneity in electrical behaviour at the organ level, mediated stability of arrhythmias and response to simulated ion channel block. This study improves understanding of mechanisms underlying increased AF risk associated with D172N and E299V KCNJ2 mutations, and outlines potential therapeutic strategies.

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/.

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

KEY POINTS

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.

ABSTRACT

Imbalances of ionic currents can destabilize the cardiac action potential and potentially trigger lethal cardiac arrhythmias. In the present study, we combined mathematical modelling with information-rich dynamic clamp experiments to determine the regulation of action potential morphology in guinea pig ventricular myocytes. Parameter sensitivity analysis was used to predict how changes in ionic currents alter action potential duration, and these were tested experimentally using dynamic clamp, a technique that allows for multiple perturbations to be tested in each cell. Surprisingly, we found that a leading mathematical model, developed with traditional approaches, systematically underestimated experimental responses to dynamic clamp perturbations. We then re-parameterized the model using a genetic algorithm, which allowed us to estimate ionic current levels in each of the cells studied. This unbiased model adjustment consistently predicted an increase in the rapid delayed rectifier K⁺ current and a drastic decrease in the slow delayed rectifier K⁺ current, and this prediction was validated experimentally. Subsequent simulations with the adjusted model generated the clinically relevant prediction that the slow delayed rectifier is better able to stabilize the action potential and suppress pro-arrhythmic events than the rapid delayed rectifier. In summary, iterative coupling of simulations and experiments enabled novel insight into how the balance between cardiac K⁺ currents influences ventricular arrhythmia susceptibility.

Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation

The occurrence of atrial fibrillation (AF) is associated with progressive changes in the calcium handling system of atrial myocytes. Calcium cycling instability has been implicated as an underlying mechanism of electrical alternans observed in patients who experience AF. However, the extent to which calcium-induced alternation of electrical activity in the atria contributes to arrhythmogenesis is unknown. In this study, we investigated the effects of calcium-driven alternans (CDA) on arrhythmia susceptibility in a biophysically detailed, 3D computer model of the human atria representing electrical and structural remodeling secondary to chronic AF. We found that elevated propensity to CDA rendered the atria vulnerable to ectopy-induced arrhythmia. It also increased the complexity and persistence of arrhythmias induced by fast pacing, with unstable scroll waves meandering and frequently breaking up to produce multiple wavelets. Our results suggest that calcium-induced electrical instability may increase arrhythmia vulnerability and promote increasing disorganization of arrhythmias in the chronic AF-remodeled atria, thus playing an important role in the progression of the disease.

Cardiac dynamics: Alternans and arrhythmogenesis

Pre-existing heterogeneities present in cardiac tissue are essential for maintaining the normal electrical and mechanical functions of the heart. Exacerbation of such heterogeneities or the emergence of dynamic factors can produce repolarization alternans, which are beat-to-beat alternations in the action potential time course. Traditionally, this was explained by restitution, but additional factors, such as cardiac memory, calcium handling dynamics, refractory period restitution, and mechano-electric feedback, are increasingly recognized as the underlying causes. The aim of this article is to review the mechanisms that generate cardiac repolarization alternans and convert spatially concordant alternans to the more arrhythmogenic spatially discordant alternans. This is followed by a discussion on how alternans generate arrhythmias in a number of clinical scenarios, and concluded by an outline of future therapeutic targets for anti-arrhythmic therapy.

The Contribution of Ionic Currents to Rate-Dependent Action Potential Duration and Pattern of Reentry in a Mathematical Model of Human Atrial Fibrillation

Persistent atrial fibrillation (PeAF) in humans is characterized by shortening of action potential duration (APD) and attenuation of APD rate-adaptation. However, the quantitative influences of particular ionic current alterations on rate-dependent APD changes, and effects on patterns of reentry in atrial tissue, have not been systematically investigated. Using mathematical models of human atrial cells and tissue and performing parameter sensitivity analysis, we evaluated the quantitative contributions to action potential (AP) shortening and APD rate-adaptation of ionic current remodeling seen with PeAF. Ionic remodeling in PeAF was simulated by reducing L-type Ca²⁺ channel current (I_CaL), increasing inward rectifier K⁺ current (I_K1) and modulating five other ionic currents. Parameter sensitivity analysis, which quantified how each ionic current influenced APD in control and PeAF conditions, identified interesting results, including a negative effect of Na⁺/Ca²⁺ exchange on APD only in the PeAF condition. At high pacing rate (2 Hz), electrical remodeling in I_K1 alone accounts for the APD reduction of PeAF, but at slow pacing rate (0.5 Hz) both electrical remodeling in I_CaL alone (-70%) and I_K1 alone (+100%) contribute equally to the APD reduction. Furthermore, AP rate-adaptation was affected by I_Kur in control and by I_NaCa in the PeAF condition. In a 2D tissue model, a large reduction (-70%) of I_CaL becomes a dominant factor leading to a stable spiral wave in PeAF. Our study provides a quantitative and unifying understanding of the roles of ionic current remodeling in determining rate-dependent APD changes at the cellular level and spatial reentry patterns in tissue.

How computer simulations of the human heart can improve anti-arrhythmia therapy

Over the last decade, the state-of-the-art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation-guided approaches to anti-arrhythmic drug development and patient-specific therapeutic interventions. In this review, we outline the basic methodology for cardiac modelling, which has been developed and validated over decades of research. In addition, we present several recent examples of how computational models of the human heart have been used to address current clinical problems in cardiac electrophysiology. We will explore the use of simulations to improve anti-arrhythmic pacing and defibrillation interventions; to predict optimal sites for clinical ablation procedures; and to aid in the understanding and selection of arrhythmia risk markers. Together, these studies illustrate how the tremendous advances in cardiac modelling are poised to revolutionize medical treatment and prevention of arrhythmia.

Computational models of atrial cellular electrophysiology and calcium handling, and their role in atrial fibrillation

The complexity of the heart makes an intuitive understanding of the relative contribution of ion channels, transporters and signalling pathways to cardiac electrophysiology challenging. Computational modelling of cardiac cellular electrophysiology has proven useful to integrate experimental findings, extrapolate results obtained in expression systems or animal models to other systems, test quantitatively ideas based on experimental data and provide novel hypotheses that are experimentally testable. While the bulk of computational modelling has traditionally been directed towards ventricular bioelectricity, increasing recognition of the clinical importance of atrial arrhythmias, particularly atrial fibrillation, has led to widespread efforts to apply computational approaches to understanding atrial electrical function. The increasing availability of detailed, atrial-specific experimental data has stimulated the development of novel computational models of atrial-cellular electrophysiology and Ca(2+) handling. To date, more than 300 studies have employed mathematical simulations to enhance our understanding of atrial electrophysiology, arrhythmogenesis and therapeutic responses. Future modelling studies are likely to move beyond current whole-cell models by incorporating new data on subcellular architecture, macromolecular protein complexes, and localized ion-channel regulation by signalling pathways. At the same time, more integrative multicellular models that take into account regional electrophysiological and Ca(2+) handling properties, mechano-electrical feedback and/or autonomic regulation will be needed to investigate the mechanisms governing atrial arrhythmias. A combined experimental and computational approach is expected to provide the more comprehensive understanding of atrial arrhythmogenesis that is required to develop improved diagnostic and therapeutic options. Here, we review this rapidly expanding area, with a particular focus on Ca(2+) handling, and provide ideas about potential future directions.

Prevention of adenosine A2A receptor activation diminishes beat-to-beat alternation in human atrial myocytes

Atrial fibrillation (AF) has been associated with increased spontaneous calcium release from the sarcoplasmic reticulum and linked to increased adenosine A2A receptor (A2AR) expression and activation. Here we tested whether this may favor atrial arrhythmogenesis by promoting beat-to-beat alternation and irregularity. Patch-clamp and confocal calcium imaging was used to measure the beat-to-beat response of the calcium current and transient in human atrial myocytes. Responses were classified as uniform, alternating or irregular and stimulation of Gs-protein coupled receptors decreased the frequency where a uniform response could be maintained from 1.0 ± 0.1 to 0.6 ± 0.1 Hz; p < 0.01 for beta-adrenergic receptors and from 1.4 ± 0.1 to 0.5 ± 0.1 Hz; p < 0.05 for A2ARs. The latter was linked to increased spontaneous calcium release and after-depolarizations. Moreover, A2AR activation increased the fraction of non-uniformly responding cells in HL-1 myocyte cultures from 19 ± 3 to 51 ± 9 %; p < 0.02, and electrical mapping in perfused porcine atria revealed that adenosine induced electrical alternans at longer cycle lengths, doubled the fraction of electrodes showing alternation, and increased the amplitude of alternations. Importantly, protein kinase A inhibition increased the highest frequency where uniform responses could be maintained from 0.84 ± 0.12 to 1.86 ± 0.11 Hz; p < 0.001 and prevention of A2AR-activation with exogenous adenosine deaminase selectively increased the threshold from 0.8 ± 0.1 to 1.2 ± 0.1 Hz; p = 0.001 in myocytes from patients with AF. In conclusion, A2AR-activation promotes beat-to-beat irregularities in the calcium transient in human atrial myocytes, and prevention of A2AR activation may be a novel means to maintain uniform beat-to-beat responses at higher beating frequencies in patients with atrial fibrillation.

Computational modeling of cardiac optogenetics: Methodology overview & review of findings from simulations

Cardiac optogenetics is emerging as an exciting new potential avenue to enable spatiotemporally precise control of excitable cells and tissue in the heart with low-energy optical stimuli. This approach involves the expression of exogenous light-sensitive proteins (opsins) in target heart tissue via viral gene or cell delivery. Preliminary experiments in optogenetically-modified cells, tissue, and organisms have made great strides towards demonstrating the feasibility of basic applications, including the use of light stimuli to pace or disrupt reentrant activity. However, it remains unknown whether techniques based on this intriguing technology could be scaled up and used in humans for novel clinical applications, such as pain-free optical defibrillation or dynamic modulation of action potential shape. A key step towards answering such questions is to explore potential optogenetics-based therapies using sophisticated computer simulation tools capable of realistically representing opsin delivery and light stimulation in biophysically detailed, patient-specific models of the human heart. This review provides (1) a detailed overview of the methodological developments necessary to represent optogenetics-based solutions in existing virtual heart platforms and (2) a survey of findings that have been derived from such simulations and a critical assessment of their significance with respect to the progress of the field.