Refractoriness in human atria: Time and voltage dependence of sodium channel availability

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.

A detailed mathematical model of the human atrial cardiomyocyte: integration of electrophysiology and cardiomechanics

Mechano-electric regulations (MER) play an important role in the maintenance of cardiac performance. Mechano-calcium and mechano-electric feedback (MCF and MEF) pathways adjust the cardiomyocyte contractile force according to mechanical perturbations and affects electro-mechanical coupling. MER integrates all these regulations in one unit resulting in a complex phenomenon. Computational modelling is a useful tool to accelerate the mechanistic understanding of complex experimental phenomena. We have developed a novel model that integrates the MER loop for human atrial cardiomyocytes with proper consideration of feedforward and feedback pathways. The model couples a modified version of the action potential (AP) Koivumäki model with the contraction model by Quarteroni group. The model simulates iso-sarcometric and isometric twitches and the feedback effects on AP and Ca2+ -handling. The model showed a biphasic response of Ca2+ transient (CaT) peak to increasing pacing rates and highlights the possible mechanisms involved. The model has shown a shift of the threshold for AP and CaT alternans from 4.6 to 4 Hz under post-operative atrial fibrillation, induced by depressed SERCA activity. The alternans incidence was dependent on a chain of mechanisms including RyRs availability time, MCF coupling, CaMKII phosphorylation, and the stretch levels. As a result, the model predicted a 10% slowdown of conduction velocity for a 20% stretch, suggesting a role of stretch in creation of substrate formation for atrial fibrillation. Overall, we conclude that the developed model provides a physiological CaT followed by a physiological twitch. This model can open pathways for the future studies of human atrial electromechanics. KEY POINTS: With the availability of human atrial cellular data, interest in atrial-specific model integration has been enhanced. We have developed a detailed mathematical model of human atrial cardiomyocytes including the mechano-electric regulatory loop. The model has gone through calibration and evaluation phases against a wide collection of available human in-vitro data. The usefulness of the model for analysing clinical problems has been preliminaryly tested by simulating the increased incidence of Ca2+ transient and action potential alternans at high rates in post-operative atrial fibrillation condition. The model determines the possible role of mechano-electric feedback in alternans incidence, which can increase vulnerability to atrial arrhythmias by varying stretch levels. We found that our physiologically accurate description of Ca2+ handling can reproduce many experimental phenomena and can help to gain insights into the underlying pathophysiological mechanisms.

Non-invasive electromechanical assessment during atrial fibrillation identifies underlying atrial myopathy alterations with early prognostic value

Electromechanical characterization during atrial fibrillation (AF) remains a significant gap in the understanding of AF-related atrial myopathy. This study reports mechanistic insights into the electromechanical remodeling process associated with AF progression and further demonstrates its prognostic value in the clinic. In pigs, sequential electromechanical assessment during AF progression shows a progressive decrease in mechanical activity and early dissociation from its electrical counterpart. Atrial tissue samples from animals with AF reveal an abnormal increase in cardiomyocytes death and alterations in calcium handling proteins. High-throughput quantitative proteomics and immunoblotting analyses at different stages of AF progression identify downregulation of contractile proteins and progressive increase in atrial fibrosis. Moreover, advanced optical mapping techniques, applied to whole heart preparations during AF, demonstrate that AF-related remodeling decreases the frequency threshold for dissociation between transmembrane voltage signals and intracellular calcium transients compared to healthy controls. Single cell simulations of human atrial cardiomyocytes also confirm the experimental results. In patients, non-invasive assessment of the atrial electromechanical relationship further demonstrate that atrial electromechanical dissociation is an early prognostic indicator for acute and long-term rhythm control.

Overview of Cardiac Arrhythmias and Treatment Strategies

Maintenance of normal cardiac rhythm requires coordinated activity of ion channels and transporters that allow well-ordered propagation of electrical impulses across the myocardium. Disruptions in this orderly process provoke cardiac arrhythmias that may be lethal in some patients. Risk of common acquired arrhythmias is increased markedly when structural heart disease caused by myocardial infarction (due to fibrotic scar formation) or left ventricular dysfunction is present. Genetic polymorphisms influence structure or excitability of the myocardial substrate, which increases vulnerability or risk of arrhythmias in patients. Similarly, genetic polymorphisms of drug-metabolizing enzymes give rise to distinct subgroups within the population that affect specific drug biotransformation reactions. Nonetheless, identification of triggers involved in initiation or maintenance of cardiac arrhythmias remains a major challenge. Herein, we provide an overview of knowledge regarding physiopathology of inherited and acquired cardiac arrhythmias along with a summary of treatments (pharmacologic or non-pharmacologic) used to limit their effect on morbidity and potential mortality. Improved understanding of molecular and cellular aspects of arrhythmogenesis and more epidemiologic studies (for a more accurate portrait of incidence and prevalence) are crucial for development of novel treatments and for management of cardiac arrhythmias and their consequences in patients, as their incidence is increasing worldwide.

Sodium current preserves electrical excitability in the heart of hibernating ground squirrel (Citellus undulatus)

Hibernating mammals are capable of maintaining normal cardiac function at low temperatures. Excitability of cardiac myocytes crucially depends on the fast sodium current (I_Na), which is decreased in hypothermia due to both depolarization of resting membrane potential and direct negative effect of low temperature. Therefore, I_Na in hibernating mammals should have specific features allowing to maintain excitability of myocardium at low temperatures. The current-voltage dependence of I_Na, its steady-state inactivation and activation and recovery from inactivation were studied in winter hibernating (WH) and summer active (SA) ground squirrels and in rats using whole-cell patch clamp at 10 °C and 20 °C. I_Na peak amplitude and the parameters of steady-state activation and inactivation curves did not differ between SA and WH ground squirrels at both temperatures. However, at both temperatures strong positive shift of activation and inactivation curves by 5-12 mV was observed in both WH and SA ground squirrels if compared to rats. This peculiarity of cardiac I_Na in ground squirrels helps to maintain excitability in conditions of depolarized resting membrane potential. The time course of I_Na recovery from inactivation at 10 °C was faster in WH than in SA ground squirrels, which could ensure normal activation of myocardium during hibernation.

P-wave durations from automated electrocardiogram analysis to predict atrial fibrillation and mortality in heart failure

BACKGROUND

P-wave indices have been used to predict incident atrial fibrillation (AF), stroke, and mortality. However, such indices derived from automated ECG measurements have not been explored for their predictive values in heart failure (HF). We investigated whether automated P-wave indices can predict adverse outcomes in HF.

METHODS

This study included consecutive Chinese patients admitted to a single tertiary centre, presenting with HF but without prior AF, and with at least one baseline ECG, between 1 January 2010 and 31 December 2016, with last follow-up of 31 December 2019.

RESULTS

A total of 2718 patients were included [median age: 77.4, interquartile range (IQR): (66.9-84.3) years; 47.9 males]. After a median follow-up of 4.8 years (IQR: 1.9-9.0 years), 1150 patients developed AF (8.8/year), 339 developed stroke (2.6/year), 563 developed cardiovascular mortality (4.3/year), and 1972 had all-cause mortality (15.1/year). Compared with 101-120 ms as a reference, maximum P-wave durations predicted new-onset AF at ≤90 ms [HR: 1.17(1.11, 1.50), P < 0.01], 131-140 ms [HR: 1.29(1.09, 1.54), P < 0.001], and ≥141 ms [HR: 1.52(1.32, 1.75), P < 0.001]. Similarly, they predicted cardiovascular mortality at ≤90 ms [HR: 1.50(1.08, 2.06), P < 0.001] or ≥141 ms [HR: 1.18(1.15, 1.45), P < 0.001], and all-cause mortality at ≤90 ms [HR: 1.26(1.04, 1.51), P < 0.001], 131-140 ms [HR: 1.15(1.01, 1.32), P < 0.01], and ≥141 ms [HR: 1.31(1.18, 1.46), P < 0.001]. These remained significant after adjusting for significant demographics, past co-morbidities, P-wave dispersion, and maximum P-wave amplitude.

CONCLUSIONS

Extreme values of maximum P-wave durations (≤90 ms and ≥141 ms) were significant predictors of new-onset AF, cardiovascular mortality, and all-cause mortality.

Steady-state and transient effects of SK channel block and adrenergic stimulation to counteract acetylcholine-induced arrhythmogenic effects in the human atria: A computational study

Hyperactivity of the parasympathetic nervous system has been linked to the development of paroxysmal atrial fibrillation (AF). The parasympathetic neurotransmitter acetylcholine (ACh) causes a reduction in action potential (AP) duration (APD) and an increase in resting membrane potential (RMP), both of which contribute to enhance the risk for reentry. Research suggests that small-conductance calcium activated potassium (SK) channels may be an effective target for treating AF. Therapies targeting the autonomic nervous system, either alone or in combination with other drugs, have been explored and have been shown to decrease the incidence of atrial arrhythmias. This study uses computational modeling and simulation to examine the impact of SK channel block (SKb) and β-adrenergic stimulation through Isoproterenol (Iso) on countering the negative effects of cholinergic activity in human atrial cell and 2D tissue models. The steady-state effects of Iso and/or SKb on AP shape, APD at 90% repolarization (APD₉₀) and RMP were evaluated. The ability to terminate stable rotational activity in cholinergically-stimulated 2D tissue models of AF was also investigated. A range of SKb and Iso application kinetics, which reflect varying drug binding rates, were taken into consideration. The results showed that SKb alone prolonged APD₉₀ and was able to stop sustained rotors in the presence of ACh concentrations up to 0.01 μM. Iso terminated rotors under all tested ACh concentrations, but resulted in highly-variable steady-state outcomes depending on baseline AP morphology. Importantly, the combination of SKb and Iso resulted in greater APD₉₀ prolongation and showed promising anti-arrhythmic potential by stopping stable rotors and preventing re-inducibility.

PITX2 Knockout Induces Key Findings of Electrical Remodeling as Seen in Persistent Atrial Fibrillation

BACKGROUND

Electrical remodeling in human persistent atrial fibrillation is believed to result from rapid electrical activation of the atria, but underlying genetic causes may contribute. Indeed, common gene variants in an enhancer region close to PITX2 (paired-like homeodomain transcription factor 2) are strongly associated with atrial fibrillation, but the mechanism behind this association remains unknown. This study evaluated the consequences of PITX2 deletion (PITX2^-/-) in human induced pluripotent stem cell-derived atrial cardiomyocytes.

METHODS

CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) was used to delete PITX2 in a healthy human iPSC line that served as isogenic control. Human induced pluripotent stem cell-derived atrial cardiomyocytes were differentiated with unfiltered retinoic acid and cultured in atrial engineered heart tissue. Force and action potential were measured in atrial engineered heart tissues. Single human induced pluripotent stem cell-derived atrial cardiomyocytes were isolated from atrial engineered heart tissue for ion current measurements.

RESULTS

PITX2^-/- atrial engineered heart tissue beats slightly slower than isogenic control without irregularity. Force was lower in PITX2^-/- than in isogenic control (0.053±0.015 versus 0.131±0.017 mN, n=28/3 versus n=28/4, PITX2^-/- versus isogenic control; P<0.0001), accompanied by lower expression of CACNA1C and lower L-type Ca²⁺ current density. Early repolarization was weaker (action potential duration at 20% repolarization; 45.5±13.2 versus 8.6±5.3 ms, n=18/3 versus n=12/4, PITX2^-/- versus isogenic control; P<0.0001), and maximum diastolic potential was more negative (-78.3±3.1 versus -69.7±0.6 mV, n=18/3 versus n=12/4, PITX2^-/- versus isogenic control; P=0.001), despite normal inward rectifier currents (both I_K1 and I_K,ACh) and carbachol-induced shortening of action potential duration.

CONCLUSIONS

Complete PITX2 deficiency in human induced pluripotent stem cell-derived atrial cardiomyocytes recapitulates some findings of electrical remodeling of atrial fibrillation in the absence of fast beating, indicating that these abnormalities could be primary consequences of lower PITX2 levels.

Adenosine and Adenosine Receptors: Advances in Atrial Fibrillation

Atrial fibrillation (AF) is the most common arrhythmia in the world. Because the key to developing innovative therapies that limit the onset and the progression of AF is to fully understand the underlying molecular mechanisms of AF, the aim of the present narrative review is to report the most recent advances in the potential role of the adenosinergic system in the pathophysiology of AF. After a comprehensive approach describing adenosinergic system signaling and the mechanisms of the initiation and maintenance of AF, we address the interactions of the adenosinergic system's signaling with AF. Indeed, adenosine release can activate four G-coupled membrane receptors, named A₁, A_2A, A_2B and A₃. Activation of the A_2A receptors can promote the occurrence of delayed depolarization, while activation of the A₁ receptors can shorten the action potential's duration and induce the resting membrane's potential hyperpolarization, which promote pulmonary vein firing, stabilize the AF rotors and allow for functional reentry. Moreover, the A_2B receptors have been associated with atrial fibrosis homeostasis. Finally, the adenosinergic system can modulate the autonomous nervous system and is associated with AF risk factors. A question remains regarding adenosine release and the adenosine receptors' activation and whether this would be a cause or consequence of AF.

Artificial intelligence analysis of the impact of fibrosis in arrhythmogenesis and drug response

Background: Cardiac fibrosis has been identified as a major factor in conduction alterations leading to atrial arrhythmias and modification of drug treatment response. Objective: To perform an in silico proof-of-concept study of Artificial Intelligence (AI) ability to identify susceptibility for conduction blocks in simulations on a population of models with diffused fibrotic atrial tissue and anti-arrhythmic drugs. Methods: Activity in 2D cardiac tissue planes were simulated on a population of variable electrophysiological and anatomical profiles using the Koivumaki model for the atrial cardiomyocytes and the Maleckar model for the diffused fibroblasts (0%, 5% and 10% fibrosis area). Tissue sheets were of 2 cm side and the effect of amiodarone, dofetilide and sotalol was simulated to assess the conduction of the electrical impulse across the planes. Four different AI algorithms (Quadratic Support Vector Machine, QSVM, Cubic Support Vector Machine, CSVM, decision trees, DT, and K-Nearest Neighbors, KNN) were evaluated in predicting conduction of a stimulated electrical impulse. Results: Overall, fibrosis implementation lowered conduction velocity (CV) for the conducting profiles (0% fibrosis: 67.52 ± 7.3 cm/s; 5%: 58.81 ± 14.04 cm/s; 10%: 57.56 ± 14.78 cm/s; p < 0.001) in combination with a reduced 90% action potential duration (0% fibrosis: 187.77 ± 37.62 ms; 5%: 93.29 ± 82.69 ms; 10%: 106.37 ± 85.15 ms; p < 0.001) and peak membrane potential (0% fibrosis: 89.16 ± 16.01 mV; 5%: 70.06 ± 17.08 mV; 10%: 82.21 ± 19.90 mV; p < 0.001). When the antiarrhythmic drugs were present, a total block was observed in most of the profiles. In those profiles in which electrical conduction was preserved, a decrease in CV was observed when simulations were performed in the 0% fibrosis tissue patch (Amiodarone ΔCV: -3.59 ± 1.52 cm/s; Dofetilide ΔCV: -13.43 ± 4.07 cm/s; Sotalol ΔCV: -0.023 ± 0.24 cm/s). This effect was preserved for amiodarone in the 5% fibrosis patch (Amiodarone ΔCV: -4.96 ± 2.15 cm/s; Dofetilide ΔCV: 0.14 ± 1.87 cm/s; Sotalol ΔCV: 0.30 ± 4.69 cm/s). 10% fibrosis simulations showed that part of the profiles increased CV while others showed a decrease in this variable (Amiodarone ΔCV: 0.62 ± 9.56 cm/s; Dofetilide ΔCV: 0.05 ± 1.16 cm/s; Sotalol ΔCV: 0.22 ± 1.39 cm/s). Finally, when the AI algorithms were tested for predicting conduction on input of variables from the population of modelled, Cubic SVM showed the best performance with AUC = 0.95. Conclusion: In silico proof-of-concept study demonstrates that fibrosis can alter the expected behavior of antiarrhythmic drugs in a minority of atrial population models and AI can assist in revealing the profiles that will respond differently.

Arrhythmogenic influence of mutations in a myocyte-based computational model of the pulmonary vein sleeve

In the heart, electrophysiological dysregulation arises from defects at many biological levels (from point mutations in ion channel proteins to gross structural abnormalities). These defects disrupt the normal pattern of electrical activation, producing ectopic activity and reentrant arrhythmia. To interrogate mechanisms that link these primary biological defects to macroscopic electrophysiologic dysregulation most prior computational studies have utilized either (i) detailed models of myocyte ion channel dynamics at limited spatial scales, or (ii) homogenized models of action potential conduction that reproduce arrhythmic activity at tissue and organ levels. Here we apply our recent model (EMI), which integrates electrical activation and propagation across these scales, to study human atrial arrhythmias originating in the pulmonary vein (PV) sleeves. These small structures initiate most supraventricular arrhythmias and include pronounced myocyte-to-myocyte heterogeneities in ion channel expression and intercellular coupling. To test EMI's cell-based architecture in this physiological context we asked whether ion channel mutations known to underlie atrial fibrillation are capable of initiating arrhythmogenic behavior via increased excitability or reentry in a schematic PV sleeve geometry. Our results illustrate that EMI's improved spatial resolution can directly interrogate how electrophysiological changes at the individual myocyte level manifest in tissue and as arrhythmia in the PV sleeve.

Artificial Intelligence-Driven Algorithm for Drug Effect Prediction on Atrial Fibrillation: An in silico Population of Models Approach

Background: Antiarrhythmic drugs are the first-line treatment for atrial fibrillation (AF), but their effect is highly dependent on the characteristics of the patient. Moreover, anatomical variability, and specifically atrial size, have also a strong influence on AF recurrence. Objective: We performed a proof-of-concept study using artificial intelligence (AI) that enabled us to identify proarrhythmic profiles based on pattern identification from in silico simulations. Methods: A population of models consisting of 127 electrophysiological profiles with a variation of nine electrophysiological variables (G _Na , I _NaK , G _K1, G _CaL , G _Kur , I _KCa , [Na] _ext , and [K] _ext and diffusion) was simulated using the Koivumaki atrial model on square planes corresponding to a normal (16 cm²) and dilated (22.5 cm²) atrium. The simple pore channel equation was used for drug implementation including three drugs (isoproterenol, flecainide, and verapamil). We analyzed the effect of every ionic channel combination to evaluate arrhythmia induction. A Random Forest algorithm was trained using the population of models and AF inducibility as input and output, respectively. The algorithm was trained with 80% of the data (N = 832) and 20% of the data was used for testing with a k-fold cross-validation (k = 5). Results: We found two electrophysiological patterns derived from the AI algorithm that was associated with proarrhythmic behavior in most of the profiles, where G _K1 was identified as the most important current for classifying the proarrhythmicity of a given profile. Additionally, we found different effects of the drugs depending on the electrophysiological profile and a higher tendency of the dilated tissue to fibrillate (Small tissue: 80 profiles vs Dilated tissue: 87 profiles). Conclusion: Artificial intelligence algorithms appear as a novel tool for electrophysiological pattern identification and analysis of the effect of antiarrhythmic drugs on a heterogeneous population of patients with AF.

Fibrotic Remodeling during Persistent Atrial Fibrillation: In Silico Investigation of the Role of Calcium for Human Atrial Myofibroblast Electrophysiology

During atrial fibrillation, cardiac tissue undergoes different remodeling processes at different scales from the molecular level to the tissue level. One central player that contributes to both electrical and structural remodeling is the myofibroblast. Based on recent experimental evidence on myofibroblasts' ability to contract, we extended a biophysical myofibroblast model with Ca²⁺ handling components and studied the effect on cellular and tissue electrophysiology. Using genetic algorithms, we fitted the myofibroblast model parameters to the existing in vitro data. In silico experiments showed that Ca²⁺ currents can explain the experimentally observed variability regarding the myofibroblast resting membrane potential. The presence of an L-type Ca²⁺ current can trigger automaticity in the myofibroblast with a cycle length of 799.9 ms. Myocyte action potentials were prolonged when coupled to myofibroblasts with Ca²⁺ handling machinery. Different spatial myofibroblast distribution patterns increased the vulnerable window to induce arrhythmia from 12 ms in non-fibrotic tissue to 22 ± 2.5 ms and altered the reentry dynamics. Our findings suggest that Ca²⁺ handling can considerably affect myofibroblast electrophysiology and alter the electrical propagation in atrial tissue composed of myocytes coupled with myofibroblasts. These findings can inform experimental validation experiments to further elucidate the role of myofibroblast Ca²⁺ handling in atrial arrhythmogenesis.

Personalized Evaluation of Atrial Complexity of Patients Undergoing Atrial Fibrillation Ablation: A Clinical Computational Study

Simple Summary

Atrial fibrillation is a type of arrhythmia that occurs when the electrical activity of the heart in the atrium is not coordinated, and its consequences can be lethal. The driving source that initiates this chaotic activity can be located anywhere in the atrium, but most frequently appears in certain areas such as the pulmonary veins. In this study, we developed a new estimation method to evaluate possible source location and complexity of the arrhythmia using computer simulations. This method represents mathematical descriptions of natural processes that can be used to mimic a real scenario, including specific information such as the atrial anatomy. Here, we identified a specific biomarker the enabled obtaining a foci distribution map and found that elimination of pulmonary vein drivers was associated with a successful long-term ablation outcome. This study could, therefore, help to identify and characterize patients in order to better plan the ablation procedure.

Abstract

Current clinical guidelines establish Pulmonary Vein (PV) isolation as the indicated treatment for Atrial Fibrillation (AF). However, AF can also be triggered or sustained due to atrial drivers located elsewhere in the atria. We designed a new simulation workflow based on personalized computer simulations to characterize AF complexity of patients undergoing PV ablation, validated with non-invasive electrocardiographic imaging and evaluated at one year after ablation. We included 30 patients using atrial anatomies segmented from MRI and simulated an automata model for the electrical modelling, consisting of three states (resting, excited and refractory). In total, 100 different scenarios were simulated per anatomy varying rotor number and location. The 3 states were calibrated with Koivumaki action potential, entropy maps were obtained from the electrograms and compared with ECGi for each patient to analyze PV isolation outcome. The completion of the workflow indicated that successful AF ablation occurred in patients with rotors mainly located at the PV antrum, while unsuccessful procedures presented greater number of driving sites outside the PV area. The number of rotors attached to the PV was significantly higher in patients with favorable long-term ablation outcome (1-year freedom from AF: 1.61 ± 0.21 vs. AF recurrence: 1.40 ± 0.20; p-value = 0.018). The presented workflow could improve patient stratification for PV ablation by screening the complexity of the atria.

Using Machine Learning to Characterize Atrial Fibrotic Substrate From Intracardiac Signals With a Hybrid in silico and in vivo Dataset

In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. However, it remains an open challenge to find fibrotic areas and to differentiate their density and transmurality. This study aims to identify the volume fraction and transmurality of fibrosis in the atrial substrate. Simulated cardiac electrograms, combined with a generalized model of clinical noise, reproduce clinically measured signals. Our hybrid dataset approach combines in silico and clinical electrograms to train a decision tree classifier to characterize the fibrotic atrial substrate. This approach captures different in vivo dynamics of the electrical propagation reflected on healthy electrogram morphology and synergistically combines it with synthetic fibrotic electrograms from in silico experiments. The machine learning algorithm was tested on five patients and compared against clinical voltage maps as a proof of concept, distinguishing non-fibrotic from fibrotic tissue and characterizing the patient's fibrotic tissue in terms of density and transmurality. The proposed approach can be used to overcome a single voltage cut-off value to identify fibrotic tissue and guide ablation targeting fibrotic areas.

Statistical Approach to Incorporating Experimental Variability into a Mathematical Model of the Voltage-Gated Na+ Channel and Human Atrial Action Potential

The voltage-gated Na⁺ channel Na_v1.5 is critical for normal cardiac myocyte excitability. Mathematical models have been widely used to study Na_v1.5 function and link to a range of cardiac arrhythmias. There is growing appreciation for the importance of incorporating physiological heterogeneity observed even in a healthy population into mathematical models of the cardiac action potential. Here, we apply methods from Bayesian statistics to capture the variability in experimental measurements on human atrial Na_v1.5 across experimental protocols and labs. This variability was used to define a physiological distribution for model parameters in a novel model formulation of Na_v1.5, which was then incorporated into an existing human atrial action potential model. Model validation was performed by comparing the simulated distribution of action potential upstroke velocity measurements to experimental measurements from several different sources. Going forward, we hope to apply this approach to other major atrial ion channels to create a comprehensive model of the human atrial AP. We anticipate that such a model will be useful for understanding excitability at the population level, including variable drug response and penetrance of variants linked to inherited cardiac arrhythmia syndromes.

Immediate and Delayed Response of Simulated Human Atrial Myocytes to Clinically-Relevant Hypokalemia

Although plasma electrolyte levels are quickly and precisely regulated in the mammalian cardiovascular system, even small transient changes in K⁺, Na⁺, Ca²⁺, and/or Mg²⁺ can significantly alter physiological responses in the heart, blood vessels, and intrinsic (intracardiac) autonomic nervous system. We have used mathematical models of the human atrial action potential (AP) to explore the electrophysiological mechanisms that underlie changes in resting potential (V_r) and the AP following decreases in plasma K⁺, [K⁺]_o, that were selected to mimic clinical hypokalemia. Such changes may be associated with arrhythmias and are commonly encountered in patients (i) in therapy for hypertension and heart failure; (ii) undergoing renal dialysis; (iii) with any disease with acid-base imbalance; or (iv) post-operatively. Our study emphasizes clinically-relevant hypokalemic conditions, corresponding to [K⁺]_o reductions of approximately 1.5 mM from the normal value of 4 to 4.5 mM. We show how the resulting electrophysiological responses in human atrial myocytes progress within two distinct time frames: (i) Immediately after [K⁺]_o is reduced, the K⁺-sensing mechanism of the background inward rectifier current (I_K1) responds. Specifically, its highly non-linear current-voltage relationship changes significantly as judged by the voltage dependence of its region of outward current. This rapidly alters, and sometimes even depolarizes, V_r and can also markedly prolong the final repolarization phase of the AP, thus modulating excitability and refractoriness. (ii) A second much slower electrophysiological response (developing 5-10 minutes after [K⁺]_o is reduced) results from alterations in the intracellular electrolyte balance. A progressive shift in intracellular [Na⁺]_i causes a change in the outward electrogenic current generated by the Na⁺/K⁺ pump, thereby modifying V_r and AP repolarization and changing the human atrial electrophysiological substrate. In this study, these two effects were investigated quantitatively, using seven published models of the human atrial AP. This highlighted the important role of I_K1 rectification when analyzing both the mechanisms by which [K⁺]_o regulates V_r and how the AP waveform may contribute to "trigger" mechanisms within the proarrhythmic substrate. Our simulations complement and extend previous studies aimed at understanding key factors by which decreases in [K⁺]_o can produce effects that are known to promote atrial arrhythmias in human hearts.

Short P-Wave Duration is a Marker of Higher Rate of Atrial Fibrillation Recurrences after Pulmonary Vein Isolation: New Insights into the Pathophysiological Mechanisms Through Computer Simulations

Background Short ECG P-wave duration has recently been demonstrated to be associated with higher risk of atrial fibrillation (AF). The aim of this study was to assess the rate of AF recurrence after pulmonary vein isolation in patients with a short P wave, and to mechanistically elucidate the observation by computer modeling. Methods and Results A total of 282 consecutive patients undergoing a first single-pulmonary vein isolation procedure for paroxysmal or persistent AF were included. Computational models studied the effect of adenosine and sodium conductance on action potential duration and P-wave duration (PWD). About 16% of the patients had a PWD of 110 ms or shorter (median PWD 126 ms, interquartile range, 115 ms-138 ms; range, 71 ms-180 ms). At Cox regression, PWD was significantly associated with AF recurrence (P=0.012). Patients with a PWD <110 ms (hazard ratio [HR], 2.20; 95% CI, 1.24-3.88; P=0.007) and patients with a PWD ≥140 (HR, 1.87, 95% CI, 1.06-3.30; P=0.031) had a nearly 2-fold increase in risk with respect to the other group. In the computational model, adenosine yielded a significant reduction of action potential duration 90 (52%) and PWD (7%). An increased sodium conductance (up to 200%) was robustly accompanied by an increase in conduction velocity (26%), a reduction in action potential duration 90 (28%), and PWD (22%). Conclusions One out of 5 patients referred for pulmonary vein isolation has a short PWD which was associated with a higher rate of AF after the index procedure. Computer simulations suggest that shortening of atrial action potential duration leading to a faster atrial conduction may be the cause of this clinical observation.

Intermittent Optogenetic Tachypacing of Atrial Engineered Heart Tissue Induces Only Limited Electrical Remodelling

ABSTRACT

Atrial tachypacing is an accepted model for atrial fibrillation (AF) in large animals and in cellular models. Human induced pluripotent stem cells-derived cardiomyocytes (hiPSC-CM) provide a novel human source to model cardiovascular diseases. Here, we investigated whether optogenetic tachypacing of atrial-like hiPSC-CMs grown into engineered heart tissue (aEHT) can induce AF-remodeling. After differentiation of atrial-like cardiomyocytes from hiPSCs using retinoic acid, aEHTs were generated from ∼1 million atrial-like hiPSC-CMs per aEHT. AEHTs were transduced with lentivirus expressing channelrhodopsin-2 to enable optogenetic stimulation by blue light pulses. AEHTs underwent optical tachypacing at 5 Hz for 15 seconds twice a minute over 3 weeks and compared with transduced spontaneously beating isogenic aEHTs (1.95 ± 0.07 Hz). Force and action potential duration did not differ between spontaneously beating and tachypaced aEHTs. Action potentials in tachypaced aEHTs showed higher upstroke velocity (138 ± 15 vs. 87 ± 11 V/s, n = 15-13/3; P = 0.018), possibly corresponding to a tendency for more negative diastolic potentials (73.0 ± 1.8 vs. 68.0 ± 1.9 mV; P = 0.07). Tachypaced aEHTs exhibited a more irregular spontaneous beating pattern (beat-to-beat scatter: 0.07 ± 0.01 vs. 0.03 ± 0.004 seconds, n = 15-13/3; P = 0.008). Targeted expression analysis showed higher RNA levels of KCNJ12 [Kir2.2, inward rectifier (IK1); 69 ± 7 vs. 44 ± 4, P = 0.014] and NPPB (NT-proBNP; 39,690 ± 4834 vs. 23,671 ± 3691; P = 0.024). Intermittent tachypacing in aEHTs induces some electrical alterations found in AF and induces an arrhythmic spontaneous beating pattern, but does not affect resting force. Further studies using longer, continuous, or more aggressive stimulation may clarify the contribution of different rate patterns on the changes in aEHT mimicking the remodeling process from paroxysmal to persistent atrial fibrillation.

SK Channel Block and Adrenergic Stimulation Counteract Acetylcholine-Induced Arrhythmogenic Effects in Human Atria

There is increasing evidence on the role of the autonomic nervous system in the pathogenesis of atrial fibrillation. Interventions targeting autonomic modulation of atrial electrical activity have been shown to reduce the incidence of atrial arrhythmias. Additionally, recent investigations have proved that pharmacological therapies inhibiting small-conductance calcium-activated potassium (SK) channels are able to lessen cholinergic effects in the atria.In this study we use computational modeling and simulation to test individual and combined effects of SK channel block and adrenergic stimulation in counteracting detrimental effects induced by the parasympathetic neurotransmitter acetylcholine (ACh) on human atrial electrophysiology. Cell and tissue models are built that incorporate descriptions of SK channels as well as of isoproterenol (Iso)- and ACh-mediated regulation of the atrial action potential (AP). Three different cellular AP models, representing a range of physiological AP shapes, are considered and both homogeneous and heterogeneous ACh distributions in atrial tissue are simulated.At the cellular level, SK channel block is demonstrated to partially revert shortening of AP duration (APD) mediated by ACh at various doses, whereas 1 µM Iso has a variable response depending on the AP shape. The combination of SK block and Iso is in all cases able to take APD back to baseline levels, recovering between 82% and 120% of the APD shortening induced by 0.1 µM ACh. At the tissue level, SK block and Iso alone or in combination do not exert remarkable effects on conduction velocity, but the combination of the two is able to notably prolong the ACh-mediated APD shortening, thus increasing the wavelength for reentry.In conclusion, the results from this study support the combination of SK channel block and adrenergic stimulation as a potential option to counteract parasympathetically-mediated proarrhythmic effects in the human atria.

Populations of in silico myocytes and tissues reveal synergy of multiatrial-predominant K+ -current block in atrial fibrillation

BACKGROUND AND PURPOSE

Pharmacotherapy of atrial fibrillation (AF), the most common cardiac arrhythmia, remains unsatisfactory due to low efficacy and safety concerns. New therapeutic strategies target atrial-predominant ion-channels and involve multichannel block (poly)therapy. As AF is characterized by rapid and irregular atrial activations, compounds displaying potent antiarrhythmic effects at fast and minimal effects at slow rates are desirable. We present a novel systems pharmacology framework to quantitatively evaluate synergistic anti-AF effects of combined block of multiple atrial-predominant K⁺ currents (ultra-rapid delayed rectifier K⁺ current, I_Kur , small conductance Ca²⁺ -activated K⁺ current, I_KCa , K_2P 3.1 2-pore-domain K⁺ current, I_K2P ) in AF.

EXPERIMENTAL APPROACH

We constructed experimentally calibrated populations of virtual atrial myocyte models in normal sinus rhythm and AF-remodelled conditions using two distinct, well-established atrial models. Sensitivity analyses on our atrial populations was used to investigate the rate dependence of action potential duration (APD) changes due to blocking I_Kur , I_K2P or I_KCa and interactions caused by blocking of these currents in modulating APD. Block was simulated in both single myocytes and one-dimensional tissue strands to confirm insights from the sensitivity analyses and examine anti-arrhythmic effects of multi-atrial-predominant K⁺ current block in single cells and coupled tissue.

KEY RESULTS

In both virtual atrial myocytes and tissues, multiple atrial-predominant K⁺ -current block promoted favourable positive rate-dependent APD prolongation and displayed positive rate-dependent synergy, that is, increasing synergistic antiarrhythmic effects at fast pacing versus slow rates.

CONCLUSION AND IMPLICATIONS

Simultaneous block of multiple atrial-predominant K⁺ currents may be a valuable antiarrhythmic pharmacotherapeutic strategy for AF.

PITX2 upregulation increases the risk of chronic atrial fibrillation in a dose-dependent manner by modulating IKs and ICaL -insights from human atrial modelling

Background

Functional analysis has shown that the paired-like homeodomain transcription factor 2 (PITX2) overexpression associated with atrial fibrillation (AF) leads to the slow delayed rectifier K⁺ current (I_Ks) increase and the L-type Ca²⁺ current (I_CaL) reduction observed in isolated right atrial myocytes from chronic AF (CAF) patients. Through multiscale computational models, this study aimed to investigate the functional impact of the PITX2 overexpression on atrial electrical activity.

Methods

The well-known Courtemanche-Ramirez-Nattel (CRN) model of human atrial action potentials (APs) was updated to incorporate experimental data on alterations in I_Ks and I_CaL due to the PITX2 overexpression. These cell models for sinus rhythm (SR) and CAF were then incorporated into homogeneous multicellular one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) tissue models. The proarrhythmic effects of the PITX2 overexpression were quantified with ion current profiles, AP morphology, AP duration (APD) restitution, conduction velocity restitution (CVR), wavelength (WL), vulnerable window (VW) for unidirectional conduction block, and minimal substrate size required to induce re-entry. Dynamic behaviors of spiral waves were characterized by measuring lifespan (LS), tip patterns and dominant frequencies.

Results

The I_Ks increase and the I_CaL decrease arising from the PITX2 overexpression abbreviated APD and flattened APD restitution (APDR) curves in single cells. It reduced WL and increased CV at high excitation rates at the 1D tissue level. Although it had no effects on VW for initiating spiral waves, it decreased the minimal substrate size necessary to sustain re-entry. It also stabilized and accelerated spiral waves in 2D and 3D tissue models.

Conclusions

Electrical remodeling (I_Ks and I_CaL) due to the PITX2 overexpression increases susceptibility to AF due to increased tissue vulnerability, abbreviated APD, shortened WL and altered CV, which, in combination, facilitate initiation and maintenance of spiral waves.

The Antimalarial Chloroquine Reduces the Burden of Persistent Atrial Fibrillation

In clinical practice, reducing the burden of persistent atrial fibrillation by pharmacological means is challenging. We explored if blocking the background and the acetylcholine-activated inward rectifier potassium currents (I_K1 and I_KACh) could be antiarrhythmic in persistent atrial fibrillation. We thus tested the hypothesis that blocking I_K1 and I_KACh with chloroquine decreases the burden of persistent atrial fibrillation. We used patch clamp to determine the IC₅₀ of I_K1 and I_KACh block by chloroquine and molecular modeling to simulate the interaction between chloroquine and Kir2.1 and Kir3.1, the molecular correlates of I_K1 and I_KACh. We then tested, as a proof of concept, if oral chloroquine administration to a patient with persistent atrial fibrillation can decrease the arrhythmia burden. We also simulated the effects of chloroquine in a 3D model of human atria with persistent atrial fibrillation. In patch clamp the IC₅₀ of I_K1 block by chloroquine was similar to that of I_KACh. A 14-day regimen of oral chloroquine significantly decreased the burden of persistent atrial fibrillation in a patient. Mathematical simulations of persistent atrial fibrillation in a 3D model of human atria suggested that chloroquine prolonged the action potential duration, leading to failure of reentrant excitation, and the subsequent termination of the arrhythmia. The combined block of I_K1 and I_KACh can be a targeted therapeutic strategy for persistent atrial fibrillation.

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.

Atrial-like Engineered Heart Tissue: An In Vitro Model of the Human Atrium

Cardiomyocytes (CMs) generated from human induced pluripotent stem cells (hiPSCs) are under investigation for their suitability as human models in preclinical drug development. Antiarrhythmic drug development focuses on atrial biology for the treatment of atrial fibrillation. Here we used recent retinoic acid-based protocols to generate atrial CMs from hiPSCs and establish right atrial engineered heart tissue (RA-EHT) as a 3D model of human atrium. EHT from standard protocol-derived hiPSC-CMs (Ctrl-EHT) and intact human muscle strips served as comparators. RA-EHT exhibited higher mRNA and protein concentrations of atrial-selective markers, faster contraction kinetics, lower force generation, shorter action potential duration, and higher repolarization fraction than Ctrl-EHTs. In addition, RA-EHTs but not Ctrl-EHTs responded to pharmacological manipulation of atrial-selective potassium currents. RA- and Ctrl-EHTs’ behavior reflected differences between human atrial and ventricular muscle preparations. Taken together, RA-EHT is a model of human atrium that may be useful in preclinical drug screening.

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Retinoic acid induced differentiation of hiPSCs into atrial-like myocytes

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3D engineered heart tissue format favored atrial specificity compared with 2D culture

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Atrial-like engineered heart tissue can be used as a model of human atrium

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.

A Heart for Diversity: Simulating Variability in Cardiac Arrhythmia Research

In cardiac electrophysiology, there exist many sources of inter- and intra-personal variability. These include variability in conditions and environment, and genotypic and molecular diversity, including differences in expression and behavior of ion channels and transporters, which lead to phenotypic diversity (e.g., variable integrated responses at the cell, tissue, and organ levels). These variabilities play an important role in progression of heart disease and arrhythmia syndromes and outcomes of therapeutic interventions. Yet, the traditional in silico framework for investigating cardiac arrhythmias is built upon a parameter/property-averaging approach that typically overlooks the physiological diversity. Inspired by work done in genetics and neuroscience, new modeling frameworks of cardiac electrophysiology have been recently developed that take advantage of modern computational capabilities and approaches, and account for the variance in the biological data they are intended to illuminate. In this review, we outline the recent advances in statistical and computational techniques that take into account physiological variability, and move beyond the traditional cardiac model-building scheme that involves averaging over samples from many individuals in the construction of a highly tuned composite model. We discuss how these advanced methods have harnessed the power of big (simulated) data to study the mechanisms of cardiac arrhythmias, with a special emphasis on atrial fibrillation, and improve the assessment of proarrhythmic risk and drug response. The challenges of using in silico approaches with variability are also addressed and future directions are proposed.

Structural Immaturity of Human iPSC-Derived Cardiomyocytes: In Silico Investigation of Effects on Function and Disease Modeling

Background: Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a promising experimental tool for translational heart research and drug development. However, their usability as a human adult cardiomyocyte model is limited by their functional immaturity. Our aim is to analyse quantitatively those characteristics and how they differ from adult CMs.

Methods and Results: We have developed a novel in silico model with all essential functional electrophysiology and calcium handling features of hiPSC-CMs. Importantly, the virtual cell recapitulates the immature intracellular ion dynamics that are characteristic for hiPSC-CMs, as quantified based our in vitro imaging data. The strong “calcium clock” is a source for a dual function of excitation-contraction coupling in hiPSC-CMs: action potential and calcium transient morphology vary substantially depending on the activation sequence of underlying ionic currents and fluxes that is altered in spontaneous vs. paced mode. Furthermore, parallel simulations with hiPSC-CM and adult cardiomyocyte models demonstrate the central differences. Results indicate that hiPSC-CMs translate poorly the disease specific phenotypes of Brugada syndrome, long QT Syndrome and catecholaminergic polymorphic ventricular tachycardia, showing less robustness and greater tendency for arrhythmic events than adult CMs. Based on a comparative sensitivity analysis, hiPSC-CMs share some features with adult CMs, but are still functionally closer to prenatal CMs than adult CMs. A database analysis of 3000 hiPSC-CM model variants suggests that hiPSC-CMs recapitulate poorly fundamental physiological properties of adult CMs. Single modifications do not appear to solve this problem, which is mostly contributed by the immaturity of intracellular calcium handling.

Conclusion: Our data indicates that translation of findings from hiPSC-CMs to human disease should be made with great caution. Furthermore, we established a mathematical platform that can be used to improve the translation from hiPSC-CMs to human, and to quantitatively evaluate hiPSC-CMs development toward more general and valuable model for human cardiac diseases.

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.