Computational assessment of the functional role of sinoatrial node exit pathways in the human heart

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.

Mechanistic insight into the functional role of human sinoatrial node conduction pathways and pacemaker compartments heterogeneity: A computer model analysis

The sinoatrial node (SAN), the primary pacemaker of the heart, is responsible for the initiation and robust regulation of sinus rhythm. 3D mapping studies of the ex-vivo human heart suggested that the robust regulation of sinus rhythm relies on specialized fibrotically-insulated pacemaker compartments (head, center and tail) with heterogeneous expressions of key ion channels and receptors. They also revealed up to five sinoatrial conduction pathways (SACPs), which electrically connect the SAN with neighboring right atrium (RA). To elucidate the role of these structural-molecular factors in the functional robustness of human SAN, we developed comprehensive biophysical computer models of the SAN based on 3D structural, functional and molecular mapping of ex-vivo human hearts. Our key finding is that the electrical insulation of the SAN except SACPs, the heterogeneous expression of If, INa currents and adenosine A1 receptors (A1R) across SAN pacemaker-conduction compartments are required to experimentally reproduce observed SAN activation patterns and important phenomena such as shifts of the leading pacemaker and preferential SACP. In particular, we found that the insulating border between the SAN and RA, is required for robust SAN function and protection from SAN arrest during adenosine challenge. The heterogeneity in the expression of A1R within the human SAN compartments underlies the direction of pacemaker shift and preferential SACPs in the presence of adenosine. Alterations of INa current and fibrotic remodelling in SACPs can significantly modulate SAN conduction and shift the preferential SACP/exit from SAN. Finally, we show that disease-induced fibrotic remodeling, INa suppression or increased adenosine make the human SAN vulnerable to pacing-induced exit blocks and reentrant arrhythmia. In summary, our computer model recapitulates the structural and functional features of the human SAN and can be a valuable tool for investigating mechanisms of SAN automaticity and conduction as well as SAN arrhythmia mechanisms under different pathophysiological conditions.

The virtual sinoatrial node: What did computational models tell us about cardiac pacemaking?

Since its discovery, the sinoatrial node (SAN) has represented a fascinating and complex matter of research. Despite over a century of discoveries, a full comprehension of pacemaking has still to be achieved. Experiments often produced conflicting evidence that was used either in support or against alternative theories, originating intense debates. In this context, mathematical descriptions of the phenomena underlying the heartbeat have grown in importance in the last decades since they helped in gaining insights where experimental evaluation could not reach. This review presents the most updated SAN computational models and discusses their contribution to our understanding of cardiac pacemaking. Electrophysiological, structural and pathological aspects - as well as the autonomic control over the SAN - are taken into consideration to reach a holistic view of SAN activity.

Characterization of the pace-and-drive capacity of the human sinoatrial node: A 3D in silico study

The sinoatrial node (SAN) is a complex structure that spontaneously depolarizes rhythmically ("pacing") and excites the surrounding non-automatic cardiac cells ("drive") to initiate each heart beat. However, the mechanisms by which the SAN cells can activate the large and hyperpolarized surrounding cardiac tissue are incompletely understood. Experimental studies demonstrated the presence of an insulating border that separates the SAN from the hyperpolarizing influence of the surrounding myocardium, except at a discrete number of sinoatrial exit pathways (SEPs). We propose a highly detailed 3D model of the human SAN, including 3D SEPs to study the requirements for successful electrical activation of the primary pacemaking structure of the human heart. A total of 788 simulations investigate the ability of the SAN to pace and drive with different heterogeneous characteristics of the nodal tissue (gradient and mosaic models) and myocyte orientation. A sigmoidal distribution of the tissue conductivity combined with a mosaic model of SAN and atrial cells in the SEP was able to drive the right atrium (RA) at varying rates induced by gradual If block. Additionally, we investigated the influence of the SEPs by varying their number, length, and width. SEPs created a transition zone of transmembrane voltage and ionic currents to enable successful pace and drive. Unsuccessful simulations showed a hyperpolarized transmembrane voltage (-66 mV), which blocked the L-type channels and attenuated the sodium-calcium exchanger. The fiber direction influenced the SEPs that preferentially activated the crista terminalis (CT). The location of the leading pacemaker site (LPS) shifted toward the SEP-free areas. LPSs were located closer to the SEP-free areas (3.46 ± 1.42 mm), where the hyperpolarizing influence of the CT was reduced, compared with a larger distance from the LPS to the areas where SEPs were located (7.17± 0.98 mm). This study identified the geometrical and electrophysiological aspects of the 3D SAN-SEP-CT structure required for successful pace and drive in silico.

Functional Heterogeneity of Cell Populations Increases Robustness of Pacemaker Function in a Numerical Model of the Sinoatrial Node Tissue

Each heartbeat is initiated by specialized pacemaker cells operating within the sinoatrial node (SAN). While individual cells within SAN tissue exhibit substantial heterogeneity of their electrophysiological parameters and Ca cycling, the role of this heterogeneity for cardiac pacemaker function remains mainly unknown. Here we investigated the problem numerically in a 25 × 25 square grid of connected coupled-clock Maltsev-Lakatta cell models. The tissue models were populated by cells with different degree of heterogeneity of the two key model parameters, maximum L-type Ca current conductance (g_CaL) and sarcoplasmic reticulum Ca pumping rate (P_up). Our simulations showed that in the areas of P_up-g_CaL parametric space at the edge of the system stability, where action potential (AP) firing is absent or dysrhythmic in SAN tissue models populated with identical cells, rhythmic AP firing can be rescued by populating the tissues with heterogeneous cells. This robust SAN function is synergistic with respect to heterogeneity in g_CaL and P_up and can be further strengthened by clustering of cells with similar properties. The effect of cell heterogeneity is not due to a simple summation of activity of intrinsically firing cells naturally present in heterogeneous SAN; rather AP firing cells locally and critically interact with non-firing/dormant cells. When firing cells prevail, they recruit many dormant cells to fire, strongly enhancing overall SAN function; and vice versa, prevailing dormant cells suppress AP firing in cells with intrinsic automaticity and halt SAN function. The transitions between firing and non-firing states of the system are sharp, resembling phase transitions in statistical physics. Furthermore, robust function of heterogeneous SAN tissue requires weak cell coupling, a known property of the central area of SAN where cardiac impulse emerges; stronger cell coupling reduces AP firing rate and ultimately halts SAN automaticity at the edge of stability.

Pacemaking function of two simplified cell models

Simplified nonlinear models of biological cells are widely used in computational electrophysiology. The models reproduce qualitatively many of the characteristics of various organs, such as the heart, brain, and intestine. In contrast to complex cellular ion-channel models, the simplified models usually contain a small number of variables and parameters, which facilitates nonlinear analysis and reduces computational load. In this paper, we consider pacemaking variants of the Aliev-Panfilov and Corrado two-variable excitable cell models. We conducted a numerical simulation study of these models and investigated the main nonlinear dynamic features of both isolated cells and 1D coupled pacemaker-excitable systems. Simulations of the 2D sinoatrial node and 3D intestine tissue as application examples of combined pacemaker-excitable systems demonstrated results similar to obtained previously. The uniform formulation for the conventional excitable cell models and proposed pacemaker models allows a convenient and easy implementation for the construction of personalized physiological models, inverse tissue modeling, and development of real-time simulation systems for various organs that contain both pacemaker and excitable cells.

Further insights into the molecular complexity of the human sinus node - The role of 'novel' transcription factors and microRNAs

RESEARCH PURPOSE

The sinus node (SN) is the heart's primary pacemaker. Key ion channels (mainly the funny channel, HCN4) and Ca2+-handling proteins in the SN are responsible for its function. Transcription factors (TFs) regulate gene expression through inhibition or activation and microRNAs (miRs) do this through inhibition. There is high expression of macrophages and mast cells within the SN connective tissue. 'Novel'/unexplored TFs and miRs in the regulation of ion channels and immune cells in the SN are not well understood. Using RNAseq and bioinformatics, the expression profile and predicted interaction of key TFs and cell markers with key miRs in the adult human SN vs. right atrial tissue (RA) were determined.

PRINCIPAL RESULTS

68 and 60 TFs significantly more or less expressed in the SN vs. RA respectively. Among those more expressed were ISL1 and TBX3 (involved in embryonic development of the SN) and 'novel' RUNX1-2, CEBPA, GLI1-2 and SOX2. These TFs were predicted to regulate HCN4 expression in the SN. Markers for different cells: fibroblasts (COL1A1), fat (FABP4), macrophages (CSF1R and CD209), natural killer (GZMA) and mast (TPSAB1) were significantly more expressed in the SN vs. RA. Interestingly, RUNX1-3, CEBPA and GLI1 also regulate expression of these cells. MiR-486-3p inhibits HCN4 and markers involved in immune response.

MAJOR CONCLUSIONS

In conclusion, RUNX1-2, CSF1R, TPSAB1, COL1A1 and HCN4 are highly expressed in the SN but not miR-486-3p. Their complex interactions can be used to treat SN dysfunction such as bradycardia. Interestingly, another research group recently reported miR-486-3p is upregulated in blood samples from severe COVID-19 patients who suffer from bradycardia.

The openCARP simulation environment for cardiac electrophysiology

BACKGROUND AND OBJECTIVE

Cardiac electrophysiology is a medical specialty with a long and rich tradition of computational modeling. Nevertheless, no community standard for cardiac electrophysiology simulation software has evolved yet. Here, we present the openCARP simulation environment as one solution that could foster the needs of large parts of this community.

METHODS AND RESULTS

openCARP and the Python-based carputils framework allow developing and sharing simulation pipelines which automate in silico experiments including all modeling and simulation steps to increase reproducibility and productivity. The continuously expanding openCARP user community is supported by tailored infrastructure. Documentation and training material facilitate access to this complementary research tool for new users. After a brief historic review, this paper summarizes requirements for a high-usability electrophysiology simulator and describes how openCARP fulfills them. We introduce the openCARP modeling workflow in a multi-scale example of atrial fibrillation simulations on single cell, tissue, organ and body level and finally outline future development potential.

CONCLUSION

As an open simulator, openCARP can advance the computational cardiac electrophysiology field by making state-of-the-art simulations accessible. In combination with the carputils framework, it offers a tailored software solution for the scientific community and contributes towards increasing use, transparency, standardization and reproducibility of in silico experiments.

Assembly of the Cardiac Pacemaking Complex: Electrogenic Principles of Sinoatrial Node Morphogenesis

Cardiac pacemaker cells located in the sinoatrial node initiate the electrical impulses that drive rhythmic contraction of the heart. The sinoatrial node accounts for only a small proportion of the total mass of the heart yet must produce a stimulus of sufficient strength to stimulate the entire volume of downstream cardiac tissue. This requires balancing a delicate set of electrical interactions both within the sinoatrial node and with the downstream working myocardium. Understanding the fundamental features of these interactions is critical for defining vulnerabilities that arise in human arrhythmic disease and may provide insight towards the design and implementation of the next generation of potential cellular-based cardiac therapeutics. Here, we discuss physiological conditions that influence electrical impulse generation and propagation in the sinoatrial node and describe developmental events that construct the tissue-level architecture that appears necessary for sinoatrial node function.

Proarrhythmic Effects of Electrolyte Imbalance in Virtual Human Atrial and Ventricular Cardiomyocytes

Dialysis is prescribed to renal failure patients as a long-term chronic treatment. Whereas dialysis therapeutically normalizes serum electrolytes and removes small toxin molecules, it fails to alleviate fibroblast induced structural fibrosis, and unresponsive uremia. The simultaneous presence of altered electrolytes and fibrosis or uremia is thought to be pro-arrhythmogenic. This study explored potential arrhythmogenesis under pre-dialysis (high electrolyte levels) and post-dialysis (low physiological electrolyte levels) in the presence of fibrosis and uremia in human atrial and ventricular model cardiomyocytes.Two validated human cardiomyocyte models were used in this study that permitted simulation of cardiac atrial and ventricular detailed electrophysiology. Pathological conditions simulating active fibrosis and uremia were implemented in both models. Pre- and post-dialysis conditions were simulated using high and low electrolyte levels respectively. Arrythmogenesis was quantified by computing restitution curves that permitted identification of action potential duration and calcium transient alternans instabilities.In comparison to control conditions, fibrosis abbreviated action potential durations while uremia prolonged the same. Under pre-dialysis conditions, an elevation of serum electrolyte levels caused action potential durations to be abbreviated under both fibrosis and uremia. Alternans instability was observed in the ventricular cardiomyocyte model. Under post-dialysis conditions, lower levels of serum electrolytes promoted an abbreviated action potential duration under fibrosis but caused a large increase of the control and uremic action potential durations. Alternans instabilities were observed in the atrial cardiomyocyte model under post-dialysis conditions at physiological heart rates. The calcium transient restitution showed similar alternans instabilities.Co-existing conditions such as fibrosis and uremia in the presence of unphysiological electrolyte levels promote arrhythmogenesis and may require additional treatment to improve dialysis outcomes.Clinical Relevance. Knowledge of model response to clinically relevant conditions permits use of in silico modeling to better understand and dissect underlying arrhythmia mechanisms.

In silico models for evaluating proarrhythmic risk of drugs

Safety evaluation of drugs requires examination of the risk of generating Torsade de Pointes (TdP) because it can lead to sudden cardiac death. Until recently, the QT interval in the electrocardiogram (ECG) has been used in the evaluation of TdP risk because the QT interval is known to be associated with the development of TdP. Although TdP risk evaluation based on QT interval has been successful in removing drugs with TdP risk from the market, some safe drugs may have also been affected due to the low specificity of QT interval-based evaluation. For more accurate evaluation of drug safety, the comprehensive in vitro proarrhythmia assay (CiPA) has been proposed by regulatory agencies, industry, and academia. Although the CiPA initiative includes in silico evaluation of cellular action potential as a component, attempts to utilize in silico simulation in drug safety evaluation are expanding, even to simulating human ECG using biophysical three-dimensional models of the heart and torso under the effects of drugs. Here, we review recent developments in the use of in silico models for the evaluation of the proarrhythmic risk of drugs. We review the single cell, one-dimensional, two-dimensional, and three-dimensional models and their applications reported in the literature and discuss the possibility of utilizing ECG simulation in drug safety evaluation.

Cardiac Pacemaker Activity and Aging

A progressive decline in maximum heart rate (mHR) is a fundamental aspect of aging in humans and other mammals. This decrease in mHR is independent of gender, fitness, and lifestyle, affecting in equal measure women and men, athletes and couch potatoes, spinach eaters and fast food enthusiasts. Importantly, the decline in mHR is the major determinant of the age-dependent decline in aerobic capacity that ultimately limits functional independence for many older individuals. The gradual reduction in mHR with age reflects a slowing of the intrinsic pacemaker activity of the sinoatrial node of the heart, which results from electrical remodeling of individual pacemaker cells along with structural remodeling and a blunted β-adrenergic response. In this review, we summarize current evidence about the tissue, cellular, and molecular mechanisms that underlie the reduction in pacemaker activity with age and highlight key areas for future work.

Arterial Hypertension and Unusual Ascending Aortic Dilatation in a Neonate With Acute Kidney Injury: Mechanistic Computer Modeling

Background

Neonatal asphyxia caused kidney injury and severe hypertension in a newborn. An unusually dilatated ascending aorta developed. Dialysis and pharmacological treatment led to partial recovery of the ascending aortic diameters. It was hypothesized that the aortic dilatation may be associated with aortic stiffening, peripheral resistance, and cardiovascular changes. Mathematical modeling was used to better understand the potential causes of the hypertension, and to confirm our clinical treatment within the confines of the model's capabilities.

Methods

The patient's systolic arterial blood pressure showed hypertension. Echocardiographic exams showed ascending aorta dilatation during hypertension, which partially normalized upon antihypertensive treatment. To explore the underlying mechanisms of the aortic dilatation and hypertension, an existing lumped parameter hemodynamics model was deployed. Hypertension was simulated using realistic literature informed parameter values. It was also simulated using large parameter perturbations to demonstrate effects. Simulations were designed to permit examination of causal mechanisms. The hypertension inducing effects of aortic stiffnesses, vascular resistances, and cardiac hypertrophy on blood flow and pressure were simulated. Sensitivity analysis was used to stratify causes.

Results

In agreement with our clinical diagnosis, the model showed that an increase of aortic stiffness followed by augmentation of peripheral resistance are the prime causes of realistic hypertension. Increased left ventricular elastance may also cause hypertension. Ascending aortic pressure and flow increased in the simultaneous presence of left ventricle hypertrophy and augmented small vessel resistance, which indicate a plausible condition for ascending aorta dilatation. In case of realistic hypertension, sensitivity analysis showed that the treatment of both the large vessel stiffness and small vessel resistance are more important in comparison to cardiac hypertrophy.

Conclusion and Discussion

Large vessel stiffness was found to be the prime factor in arterial hypertension, which confirmed the clinical treatment. Treatment of cardiac hypertrophy appears to provide significant benefit but may be secondary to treatment of large vessel stiffness. The quantitative grading of pathophysiological mechanisms provided by the modeling may contribute to treatment recommendations. The model was limited due to a lack of data suitable to permit model identification.

Sinus node-like pacemaker mechanisms regulate ectopic pacemaker activity in the adult rat atrioventricular ring

In adult mammalian hearts, atrioventricular rings (AVRs) surround the atrial orifices of atrioventricular valves and are hotbed of ectopic activity in patients with focal atrial tachycardia. Experimental data offering mechanistic insights into initiation and maintenance of ectopic foci is lacking. We aimed to characterise AVRs in structurally normal rat hearts, identify arrhythmia predisposition and investigate mechanisms underlying arrhythmogenicity. Extracellular potential mapping and intracellular action potential recording techniques were used for electrophysiology, qPCR for gene and, Western blot and immunohistochemistry for protein expression. Conditions favouring ectopic foci were assessed by simulations. In right atrial preparations, sinus node (SN) was dominant and AVRs displayed 1:1 impulse conduction. Detaching SN unmasked ectopic pacemaking in AVRs and pacemaker action potentials were SN-like. Blocking pacemaker current I_f, and disrupting intracellular Ca²⁺ release, prolonged spontaneous cycle length in AVRs, indicating a role for SN-like pacemaker mechanisms. AVRs labelled positive for HCN4, and SERCA2a was comparable to SN. Pacemaking was potentiated by isoproterenol and abolished with carbachol and AVRs had abundant sympathetic nerve endings. β₂-adrenergic and M₂-muscarinic receptor mRNA and β₂-receptor protein were comparable to SN. In computer simulations of a sick SN, ectopic foci in AVR were unmasked, causing transient suppression of SN pacemaking.

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.

Heart Rhythm Insights Into Structural Remodeling in Atrial Tissue: Timed Automata Approach

The heart rhythm of a person following heart transplantation (HTX) is assumed to display an intrinsic cardiac rhythm because it is significantly less influenced by the autonomic nervous system-the main source of heart rate variability in healthy people. Therefore, such a rhythm provides evidence for arrhythmogenic processes developing, usually silently, in the cardiac tissue. A model is proposed to simulate alterations in the cardiac tissue and to observe the effects of these changes on the resulting heart rhythm. The hybrid automata framework used makes it possible to represent reliably and simulate efficiently both the electrophysiology of a cardiac cell and the tissue organization. The curve fitting method used in the design of the hybrid automaton cycle follows the well-recognized physiological phases of the atrial myocyte membrane excitation. Moreover, knowledge of the complex architecture of the right atrium, the ability of the almost free design of intercellular connections makes the automata approach the only one possible. Two particular aspects are investigated: impairment of the impulse transmission between cells and structural changes in intercellular connections. The first aspect models the observed fatigue of cells due to specific cardiac tissue diseases. The second aspect simulates the increase in collagen deposition with aging. Finally, heart rhythms arising from the model are validated with the sinus heart rhythms recorded in HTX patients. The modulation in the impairment of the impulse transmission between cells reveals qualitatively the abnormally high heart rate variability observed in patients living long after HTX.

3D ultrastructural organisation of calcium release units in the avian sarcoplasmic reticulum

Excitation-contraction coupling in vertebrate hearts is underpinned by calcium (Ca2+) release from Ca2+ release units (CRUs). CRUs are formed by clusters of channels called ryanodine receptors on the sarcoplasmic reticulum (SR) within the cardiomyocyte. Distances between CRUs influence the diffusion of Ca2+, thus influencing the rate and strength of excitation-contraction coupling. Avian myocytes lack T-tubules, thus Ca2+ from surface CRUs (peripheral couplings, PCs), must diffuse to internal CRU sites of the corbular SR (cSR) during centripetal propagation. Despite this, avian hearts achieve higher contractile rates and develop greater contractile strength than many mammalian hearts, which have T-tubules to provide simultaneous activation of the Ca2+ signal through the myocyte. We used 3D electron tomography to test the hypothesis that the intracellular distribution of CRUs in the avian heart permits faster and stronger contractions despite the absence T-tubules. Nearest edge-edge distances between PCs and cSR, and geometric information including surface area and volumes of individual cSR, were obtained for each cardiac chamber of the White Leghorn chicken. Computational modelling was then used to establish a relationship between CRUs distances and cell activation time in the avian heart. Our data suggest that cSR clustered close together along the Z-line is vital for rapid propagation of the Ca2+ signal from the cell periphery to the cell centre which would aid in the strong and fast contractions of the avian heart.