In Silico Investigation into Cellular Mechanisms of Cardiac Alternans in Myocardial Ischemia

Myocardial ischemia is associated with pathophysiological conditions such as hyperkalemia, acidosis, and hypoxia. These physiological disorders may lead to changes on the functions of ionic channels, which in turn form the basis for cardiac alternans. In this paper, we investigated the roles of hyperkalemia and calcium handling components played in the genesis of alternans in ischemia at the cellular level by using computational simulations. The results show that hyperkalemic reduced cell excitability and delayed recovery from inactivation of depolarization currents. The inactivation time constant τf of L-type calcium current (ICaL) increased obviously in hyperkalemia. One cycle length was not enough for ICaL to recover completely. Alternans developed as a result of ICaL responding to stimulation every other beat. Sarcoplasmic reticulum calcium-ATPase (SERCA2a) function decreased in ischemia. This change resulted in intracellular Ca (Cai) alternans of small magnitude. A strong Na+-Ca2+ exchange current (INCX) increased the magnitude of Cai alternans, leading to APD alternans through excitation-contraction coupling. Some alternated repolarization currents contributed to this repolarization alternans

Perspective: a dynamics-based classification of ventricular arrhythmias

Despite key advances in the clinical management of life-threatening ventricular arrhythmias, culminating with the development of implantable cardioverter-defibrillators and catheter ablation techniques, pharmacologic/biologic therapeutics have lagged behind. The fundamental issue is that biological targets are molecular factors. Diseases, however, represent emergent properties at the scale of the organism that result from dynamic interactions between multiple constantly changing molecular factors. For a pharmacologic/biologic therapy to be effective, it must target the dynamic processes that underlie the disease. Here we propose a classification of ventricular arrhythmias that is based on our current understanding of the dynamics occurring at the subcellular, cellular, tissue and organism scales, which cause arrhythmias by simultaneously generating arrhythmia triggers and exacerbating tissue vulnerability. The goal is to create a framework that systematically links these key dynamic factors together with fixed factors (structural and electrophysiological heterogeneity) synergistically promoting electrical dispersion and increased arrhythmia risk to molecular factors that can serve as biological targets. We classify ventricular arrhythmias into three primary dynamic categories related generally to unstable Ca cycling, reduced repolarization, and excess repolarization, respectively. The clinical syndromes, arrhythmia mechanisms, dynamic factors and what is known about their molecular counterparts are discussed. Based on this framework, we propose a computational-experimental strategy for exploring the links between molecular factors, fixed factors and dynamic factors that underlie life-threatening ventricular arrhythmias. The ultimate objective is to facilitate drug development by creating an in silico platform to evaluate and predict comprehensively how molecular interventions affect not only a single targeted arrhythmia, but all primary arrhythmia dynamics categories as well as normal cardiac excitation-contraction coupling

Islands of spatially discordant APD alternans underlie arrhythmogenesis by promoting electrotonic dyssynchrony in models of fibrotic rat ventricular myocardium

Fibrosis and altered gap junctional coupling are key features of ventricular remodelling and are associated with abnormal electrical impulse generation and propagation. Such abnormalities predispose to reentrant electrical activity in the heart. In the absence of tissue heterogeneity, high-frequency impulse generation can also induce dynamic electrical instabilities leading to reentrant arrhythmias. However, because of the complexity and stochastic nature of such arrhythmias, the combined effects of tissue heterogeneity and dynamical instabilities in these arrhythmias have not been explored in detail. Here, arrhythmogenesis was studied using in vitro and in silico monolayer models of neonatal rat ventricular tissue with 30% randomly distributed cardiac myofibroblasts and systematically lowered intercellular coupling achieved in vitro through graded knockdown of connexin43 expression. Arrhythmia incidence and complexity increased with decreasing intercellular coupling efficiency. This coincided with the onset of a specialized type of spatially discordant action potential duration alternans characterized by island-like areas of opposite alternans phase, which positively correlated with the degree of connexinx43 knockdown and arrhythmia complexity. At higher myofibroblast densities, more of these islands were formed and reentrant arrhythmias were more easily induced. This is the first study exploring the combinatorial effects of myocardial fibrosis and dynamic electrical instabilities on reentrant arrhythmia initiation and complexity

Developing a novel comprehensive framework for the investigation of cellular and whole heart electrophysiology in the in situ human heart: Historical perspectives, current progress and future prospects

Understanding the mechanisms of fatal ventricular arrhythmias is of great importance. In view of the many electrophysiological differences that exist between animal species and humans, the acquisition of basic electrophysiological data in the intact human heart is essential to drive and complement experimental work in animal and in-silico models. Over the years techniques have been developed to obtain basic electrophysiological signals directly from the patients by incorporating these measurements into routine clinical procedures which access the heart such as cardiac catheterisation and cardiac surgery. Early recordings with monophasic action potentials provided valuable information including normal values for the in vivo human heart, cycle length dependent properties, the effect of ischaemia, autonomic nervous system activity, and mechano-electric interaction. Transmural recordings addressed the controversial issue of the mid myocardial “M” cell. More recently, the technique of multielectrode mapping (256 electrodes) developed in animal models has been extended to humans, enabling mapping of activation and repolarisation on the entire left and right ventricular epicardium in patients during cardiac surgery. Studies have examined the issue of whether ventricular fibrillation was driven by a “mother” rotor with inhomogeneous and fragmented conduction as in some animal models, or by multiple wavelets as in other animal studies; results showed that both mechanisms are operative in humans. The simpler spatial organisation of human VF has important implications for treatment and prevention. To link in-vivo human electrophysiological mapping with cellular biophysics, multielectrode mapping is now being combined with myocardial biopsies. This technique enables region-specific electrophysiology changes to be related to underlying cellular biology, for example: APD alternans, which is a precursor of VF and sudden death. The mechanism is incompletely understood but related to calcium cycling and APD restitution. Multielectrode sock mapping during incremental pacing enables epicardial sites to be identified which exhibit marked APD alternans and sites where APD alternans is absent. Whole heart electrophysiology is assessed by activation repolarisation mapping and analysis is performed immediately on-site in order to guide biopsies to specific myocardial sites. Samples are analysed for ion channel expression, Ca2+-handling proteins, gap junctions and extracellular matrix. This new comprehensive approach to bridge cellular and whole heart electrophysiology allowed to identify 20 significant changes in mRNA for ion channels Ca2+-handling proteins, a gap junction channel, a Na+–K+ pump subunit and receptors (particularly Kir 2.1) between the positive and negative alternans sites

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop.

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting

Cardiac dynamics: Alternans and arrhythmogenesis

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New Methodologies for the Development and Validation of Electrophysiological Models

De acuerdo a los datos de la Organización Mundial de la Salud, se estima que 17,7 millones de personas murieron de enfermedades cardiacas en 2015, lo que supone el 31% de las muertes, haciendo de estas patologías la primera causa de muerte en el mundo. El corazón es un sistema complejo que trabaja gracias a la interacción de un gran número de elementos en diferentes escalas espaciales y temporales. La función principal del corazón es bombear sangre en todo el cuerpo, siendo esta acción mecánica activada por la estimulación eléctrica. La aparición de problemas en el funcionamiento eléctrico o mecánico del corazón en cualquiera de las escalas involucradas, temporal o espacial, puede dar lugar a un mal funcionamiento cardiaco. El modelado matemático y la simulación de la actividad eléctrica del corazón (denominada electrofisiología cardiaca) y el procesado de señales bioeléctricas proporcionan un marco ideal para unir la información clínica y los estudios experimentales con la comprensión de los mecanismos que subyacen a estos problemas. Debido al gran número de factores que se deben tener en cuenta a la hora de desarrollar y validar un modelo computacional de electrofisiología cardiaca, asi como las complejas interacciones que existen entre ellos, hacen que nuevas metodologías que facilitan la concepción, la actualización y la validación de nuevos modelos sean de gran valor. Estas metodologías pueden enfocarse sea en la definición de las compuertas iónicas de los modelos, como en la propagación del impulso eléctrico en modelos multiescala. Esta tesis pretende mejorar el conocimiento existente sobre electrofisiología cardiaca proponiendo nuevas técnicas para desarrollar y validar modelos computacionales cardiacos, a través de la evaluación de los efectos de los eventos modelados mediante la consideración de las interacciones entre los diferentes componentes del modelo y la simulación de un rango de escalas espacio-temporales.En el capítulo 2, se introdujo un nuevo paradigma para desarrollar un nuevo modelo de potencial de acción de cardiomiocito humano, el modelo CRLP, partiendo de un modelo previamente publicado e incorporando nuevas mediciones experimentales de corrientes de potasio y reformulando la corriente de calcio tipo L. El paradigma introducido se basó en el análisis de la capacidad del modelo para replicar un conjunto de marcadores electrofisiológicos bien establecidos y en un análisis de sensibilidad de esos marcadores a las variaciones en los parámetros del modelo. Una de las ventajas del paradigma propuesto fue la posibilidad de identificar parámetros del modelo que no dependen directamente de las mediciones individuales de corrientes o concentraciones y que comúnmente se establecen ad hoc. El modelo CRLP se validó y se midió su rendimiento en la capacidad para predecir marcadores relacionados con la arritmia ventricular en comparación con el modelo cellular en el que se había basado.En el capítulo 3, se actualizó el modelo CRLP desarrollado en el capítulo 2 para introducir la formulación de la dinámica de potasio intracelular ([K+]i). Esta es una característica importante para la investigación de arritmias ventriculares que surgen en condiciones de hiperpotasemia, uno de los componentes de la isquemia de miocardio. La introducción directa de la dinámica de [K+]i en el modelo generó un desequilibrio en las corrientes de potasio que condugeron a una deriva en [K+]i. Para corregir tal desequilibrio, se propuso un algoritmo de optimización que permitía estimar las conductancias de las corrientes iónicas del modelo CRLP al tiempo que garantizaba valores fisiológicamente plausibles de una selección de propiedades electrofisiológicas, algunas de ellas muy relevantes en el estudio de arritmias ventriculares.Como se mencionó anteriormente, al proponer un nuevo modelo o al actualizar un modelo existente, la coherencia entre los datos simulados y experimentales debe verificarse considerando todos los efectos y escalas involucradas. Cuanto mejor se reproduzcan las condiciones experimentales en las simulaciones, más robusto será el proceso de desarrollo y validación del modelo. En el capítulo 4, se propuso la simulación de protocolos experimentales in silico para analizar cómo las interacciones entre los componentes del modelo afectan el desarrollo y la validación de los modelos matemáticos de canales iónicos; y cómo la propagación afecta los marcadores basados en el potencial de acción cuando son simulados en células aisladas o en preparaciones tisulares, identificando cómo contribuye cada corriente iónica en cada caso. y con los modelos de células ventriculares humanas más recientes publicados en laliteratura.El capítulo 7 resume las principales conclusiones de la tesis y presenta nuevas líneas de investigación que podrían emprenderse en futuros estudios. En conclusión, diferentes técnicas para mejorar el desarrollo y la validación de modelos electrofisiológicos cardíacos han sido propuestos y analizados en esta tesis. Basándose en el aumento de potencia computacional, se han considerado nuevas estrategias para reducir el número de hipótesis y/o supuestos al construir un modelo de potencial de acción de cardiomiocito ventricular. La aplicación de un algoritmo de optimización junto con la simulación in silico de los protocolos experimentales han ayudado a encontrar un modelo que represente mejor los resultados experimentales de los marcadores electrofisiológicos de riesgo arrítmico.El modelo CRLP, desarrollado en el capítulo 2 y actualizado en el capítulo 3, presentaba una forma más bien atípica al final de la fase de despolarización del potencial de acción (fase 1). La simulación in silico de los protocolos experimentales descritos en el capítulo 4 y la metodología de optimización presentada en el capítulo 3 se utilizaron para mejorar la forma del potencial de acción al tiempo que validaba el modelo ajustado a escalas iónicas, celulares y de tejido.En el capítulo 6 se integraron todas las formulaciones iniciales y actualizaciones subsiguientes del modelo CRLP propuestas en los capítulos anteriores y se reajustaron las conductancias iónicas del modelo para mejorar el comportamiento del modelo con respecto a medidas electrofisiológicas experimentales. Todas las metodologías introducidas a lo largo de la tesis se utilizaron para obtener un nuevo modelo de potencial de acción ventricular humano. Para la validación del modelo, se consideró un rango de datos experimentales disponibles a diferentes escalas y destinados a evaluar diferentes propiedades electrofisiológicas. Las condiciones subyacentes a cada uno de los estudios experimentales se replicaron tan fielmente como fue posible. Los resultados simulados con la versión final del modelo CRLP se compararon en todos los casos con todas las evidencias experimentales disponiblesAccording to data from the World Health Organization (WHO), 17.7 million people were estimated to have died of cardiovascular diseases (CVDs) in 2015. This represents 31 of all global deaths, making CVDs the leading cause of death worldwide. The heart is a complex system that works due to the interaction of a large number of elements at different temporal and spatial scales. The main function of the heart is to pump blood throughout the body, with this mechanical action being triggered by electrical impulses. Issues arising in the electrical or mechanical actions of the heart at any of the involved temporal and spatial scales can lead to cardiac malfunctioning. Mathematical modeling and simulation of the heart's electrical activity (so-called cardiac electrophysiology) combined with signal processing of bioelectrical signals provide an ideal framework to join the information from clinical and experimental studies with the understanding of the mechanisms underlying them. Due to the high number of factors involved in the development and validation of cardiac computational electrophysiological models and the intricate interrelationships between them, novel methodologies that help to control the design, update and validation of new models become of great advantage. These methodologies can target from the definition of ionic gating in the simulated cells to the propagation of the electrical impulse in multi-scale models. This thesis aims to improve the existing knowledge on heart's electrophysiology by proposing novel techniques to develop and validate cardiac computational models while accounting for the interactions between model components and including simulations of a range of spatio-temporal scales. In chapter 2, a new paradigm was introduced to develop a novel human ventricular cell model, the CRLP model, by departing from a previously published model, the Grandi-Pasqualini-Bers model (Grandi et al., 2009). Novel experimental measurements of potassium currents were incorporated and the L-type calcium current was reformulated. The introduced paradigm was based on the analysis of the model's ability to replicate a set of well-established electrophysiological markers and on a sensitivity analysis of those markers to variations in model parameters (Romero et al., 2008). A major advantage of the proposed paradigm was the possibility to identify model parameter values that do not directly depend on individual current measurements or concentrations, which are commonly set in an ad hoc manner. The developed CRLP model was validated and its improved capacity to investigate arrhythmia-related properties, as compared to the cell model it was based on, was corroborated. In chapter 3, the CRLP model developed in chapter 2 was updated to introduce the formulation of intracellular potassium ([K+]i) dynamics. This is an important characteristic for investigation of ventricular arrhythmias arising under conditions of hyperkalemia, one of the components of myocardial ischemia (Coronel et al. 1988). Direct introduction of [K+]i dynamics into the model generated an imbalance in the potassium currents leading to a drift in [K+]i. To correct for such an imbalance, an optimization framework was proposed that allowed estimating the ionic current conductances of the CRLP model while guaranteeing physiologically plausible values of selected electrophysiological properties, many of them highly relevant for investigation of ventricular arrhythmias. As mentioned above, when proposing a new model, or when updating an existing model, consistency between simulated and experimental data should be verified by considering all involved effects and scales. The closer the experimental conditions are reproduced in the computer simulations, the more robust the process of model development and validation can be. In chapter 4, in silico simulation of experimental protocols was proposed to analyze: how interactions between model components affect the development and validation of mathematical ion channel models; and how propagation affects action potential (AP)-based markers simulated in isolated cells and in tissue preparations, with identification of the ionic contributors in each case. The CRLP model, developed in chapter 2 and updated in chapter 3, presented a rather atypical shape at the end of the depolarization phase of the AP (phase 1). In chapter 5, the in silico simulations of experimental protocols described in chapter and the optimization methodology introduced in chapter 3 were used to improve the AP shape, while validating the adjusted model at ionic, cell and tissue scales. In chapter 6, all the initial formulations and subsequent updates of the CRLP model proposed in previous chapters were integrated and the ionic conductances of the integrated model were readjusted to improve replication of experimental electrophysiological measures. All the methodologies introduced throughout the thesis were thus used to build a novel human ventricular AP model. For model validation, a range of available experimental data at different scales targetting different electrophysiological properties was considered. Conditions underlying each of the experimental studies were replicated as faithfully as possible. Results simulated with the final version of the CRLP model were in all cases compared with all available experimental evidences and with the most recent human ventricular cell models published in the literature. Chapter 7, summarizes the main conclusions of the thesis and presents new lines of research that could be undertaken in future studies. <br /

Exploring Impaired SERCA Pump-Caused Alternation Occurrence in Ischemia

Impaired sarcoplasmic reticulum (SR) calcium transport ATPase (SERCA) gives rise to Ca(2+) alternans and changes of the Ca2+release amount. These changes in Ca(2+) release amount can reveal the mechanism underlying how the interaction between Ca(2+) release and Ca(2+) uptake induces Ca(2+) alternans. This study of alternans by calculating the values of Ca(2+) release properties with impaired SERCA has not been explored before. Here, we induced Ca(2+) alternans by using an impaired SERCA pump under ischemic conditions. The results showed that the recruitment and refractoriness of the Ca(2+) release increased as Ca(2+) alternans occurred. This indicates triggering Ca waves. As the propagation of Ca waves is linked to the occurrence of Ca(2+) alternans, the "threshold" for Ca waves reflects the key factor in Ca(2+) alternans development, and it is still controversial nowadays. We proposed the ratio between the diastolic network SR (NSR) Ca content (Cansr) and the cytoplasmic Ca content (Ca i ) (Cansr/Ca i ) as the "threshold" of Ca waves and Ca(2+) alternans. Diastolic Cansr, Ca i , and their ratio were recorded at the onset of Ca(2+) alternans. Compared with certain Cansr and Ca i , the "threshold" of the ratio can better explain the comprehensive effects of the Ca(2+) release and the Ca(2+) uptake on Ca(2+) alternans onset. In addition, these ratios are related with the function of SERCA pumps, which vary with different ischemic conditions. Thus, values of these ratios could be used to differentiate Ca(2+) alternans from different ischemic cases. This agrees with some experimental results. Therefore, the certain value of diastolic Cansr/Ca i can be the better "threshold" for Ca waves and Ca(2+) alternans

Multiscale Modeling of Cardiac Electrophysiology: Adaptation to Atrial and Ventricular Rhythm Disorders and Pharmacological Treatment

Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface