[show abstract][hide abstract] ABSTRACT: The sodium-potassium pump is widely recognized as the principal mechanism for active ion transport across the cellular membrane of cardiac tissue, being responsible for the creation and maintenance of the transarcolemmal sodium and potassium gradients, crucial for cardiac cell electrophysiology. Importantly, sodium-potassium pump activity is impaired in a number of major diseased conditions, including ischemia and heart failure. However, its subtle ways of action on cardiac electrophysiology, both directly through its electrogenic nature and indirectly via the regulation of cell homeostasis, make it hard to predict the electrophysiological consequences of reduced sodium-potassium pump activity in cardiac repolarization. In this review, we discuss how recent studies adopting the systems biology approach, through the integration of experimental and modeling methodologies, have identified the sodium-potassium pump as one of the most important ionic mechanisms in regulating key properties of cardiac repolarization and its rate dependence, from subcellular to whole organ levels. These include the role of the pump in the biphasic modulation of cellular repolarization and refractoriness, the rate control of intracellular sodium and calcium dynamics and therefore of the adaptation of repolarization to changes in heart rate, as well as its importance in regulating pro-arrhythmic substrates through modulation of dispersion of repolarization and restitution. Theoretical findings are consistent across a variety of cell types and species including human, and widely in agreement with experimental findings. The novel insights and hypotheses on the role of the pump in cardiac electrophysiology obtained through this integrative approach could eventually lead to novel therapeutic and diagnostic strategies.
Pflügers Archiv - European Journal of Physiology 02/2014; 466(2):183-193. · 4.87 Impact Factor
[show abstract][hide abstract] ABSTRACT: Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.
PLoS ONE 01/2014; 9(2):e90112. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: Cardiac imaging is routinely used to evaluate cardiac tissue properties prior to therapy. By integrating the structural information with electrophysiological data from e.g. electroanatomical mapping systems, knowledge of the properties of the cardiac tissue can be further refined. However, as in other clinical modalities, electrophysiological data are often sparse and noisy, and this results in high levels of uncertainty in the estimated quantities. In this study, we develop a methodology based on Bayesian inference, coupled with a computationally efficient model of electrical propagation to achieve two main aims: (1) to quantify values and associated uncertainty for different tissue conduction properties inferred from electroanatomical data, and (2) to design strategies to optimize the location and number of measurements required to maximize information and reduce uncertainty. The methodology is validated in an in silico study performed using simulated data obtained from a human image-based ventricular model, including realistic fibre orientation and a transmural scar. We demonstrate that the method provides a simultaneous description of clinically-relevant electrophysiological conduction properties and their associated uncertainty for various levels of noise. By using the developed methodology to investigate how the uncertainty decreases in response to added measurements, we then derive an a priori index for placing electrophysiological measurements in order to optimize the information content of the collected data. Results show that the derived index has a clear benefit in minimizing the uncertainty of inferred conduction properties compared to a random distribution of measurements, reducing the number of required measurements by over 50% in several of the investigated settings. This suggests that the methodology presented in this work provides an important step towards improving the quality of the spatiotemporal information obtained using electroanatomical mapping.
Medical image analysis 10/2013; 18(1):228-240. · 3.09 Impact Factor
[show abstract][hide abstract] ABSTRACT: Both scar and left-to-right ventricular (LV/RV) differ-ences in repolarization properties have been implicated as risk factors for lethal arrhythmias. As a possible mecha-nism for the initiation of re-entry, a recent study has indi-cated that LV/RV heterogeneities in action potential du-ration (APD) adaptation can cause a transient increase in APD dispersion following rate acceleration, promoting unidirectional block of conduction at the LV/RV junction. In the presence of an ischemic region and ectopic stimula-tion, a pathological dispersion in repolarization has been suggested to increase the risk of electrical re-entry. How-ever, the exact location and timing of the ectopic activa-tion play a crucial role in initiation of re-entry, and cer-tain combinations may lead to re-entry even under nor-mal LV/RV dispersion in repolarization. This suggests that the phenomenon needs to be investigated in a quantitative way. In this study we employ a computationally efficient, phenomenological model in order to investigate the pro-arrhythmic properties of a range of combinations of posi-tion and timing of an ectopic activation. This allows us to probabilistically study how increasing interventricular dispersion of repolarization increases arrhythmic risk. Re-sults indicate that a larger LV/RV dispersion in repolariza-tion allows ectopic beats to initiate re-entry during a sig-nificantly larger time window and from a greater number of locations compared to the case of smaller LV/RV disper-sion.
[show abstract][hide abstract] ABSTRACT: Cardiac alternans is an important risk factor in cardiac physiology, and is related to the initiation of arrhythmia in a number of pathological conditions. However, the mechanisms underlying the generation of alternans remain unclear. In this study, we used a population of computational models of human ventricular electrophysiology based on the O'Hara-Rudy dynamic model to explore the effect of 11 key factors experimentally reported to be related to cardiac alternans. In vivo experimental datasets obtained from patients undergoing cardiac surgery were used in the calibration of an in silico population of models. The calibrated models in the population were divided into two groups (Normal and Alternans) depending on the occurrence of the alternans. Our results showed that there were significant differences in the following 6 ionic currents between the two groups: the fast sodium current, the L-type calcium current, the rapid delayed rectifier potassium current, the sodium calcium exchanger current, the sarcoplasmic reticulum (SR) calcium release flux, and the SR calcium reuptake flux.
[show abstract][hide abstract] ABSTRACT: Intersubject variability in cardiac electrophysiology might determine the patient-specific proneness to suffer and/or sustain arrhythmia episodes, such as atrial fibril-lation (AF). However, its potential influence on arrhyth-mogenesis is not well understood. In this study, we com-pare AF activity in virtual 3D human atria models with notable differences in cellular repolarization dynamics, in order to investigate mechanisms of intersubject variabil-ity. Physiological populations of models representing my-ocytes of patients with chronic AF were obtained and di-vided into sub-populations depending on the action po-tential duration (APD) measured at 90%, 50% and 20% repolarization. Each sub-population was used to build a model of the human atria. Analysis of calculated pseudo-electrograms showed the dominant frequency was in gen-eral higher for the short APD than for the long APD sub-populations. Organisation indices presented similar val-ues for both APD 90 sub-populations, whereas they were higher for the short APD 50 and APD 20 sub-populations, respectively. Regularity indices were lower for the short APD sub-populations. In conclusion, our results indicate that patients with long atrial APD could be associated with slow but very regular fibrillatory patterns, whereas short APDs may entail high frequency reentrant rotors and larger organisation.
[show abstract][hide abstract] ABSTRACT: Rationale: Reduced action potential duration (APD) and lack of APD rate dependent-adaptation are hallmarks of AF-induced electrical remodelling of the atrial myocardium. Understanding the mechanism underlying atrial electrical remodelling in AF is of fundamental importance for the prevention and treatment of AF. We have recently found that nitric oxide synthase (NOS) activity is dramatically reduced in atrial myocytes from goats and patients with AF. Whether loss of NOS activity contributes to the AF-induced atrial electrical remodelling remains to be established. Methodology: The whole cell current patch clamp technique was used to measure the AP in human and murine isolated atrial myocytes (N: number of patients or mice; n: number of myocytes). AF was induced in mice in vivo by using trans-oesophageal electrical stimulation. The protein content of constitutive NOSs (nNOS and eNOS) was assessed by Western blotting in atrial lysates. NOS activity was measured by the L-arginine to citrulline assay. Simulations were performed to evaluate the role of decreased nNOS activity in rotor stability in mouse right/left atrial (RA/LA) tissue models. Results: We found that decreased atrial NOS activity in patients with AF was associated with a significant reduction in nNOS protein expression (by 62%) whereas eNOS was unchanged. To evaluate the role of nNOS on atrial electrical properties, we examined the effects of the nNOS inhibitor, S-methylthiocitrulline (SMTC), or nNOS gene deletion on APD. SMTC induced 38%, 39% and 30% reduction in APD20, APD50 and APD90 respectively in RA myocytes from patients in Sinus Rhythm (SR) (N=8, n=38 control vs. N=8, n=31 cells perfused and dialyzed with SMTC, p<0.001) and suppressed the APD rate dependent-adaptation. In murine RA myocytes, inhibition and gene deletion of nNOS reduced APD by 38% and 22%, respectively (N=9, n=35 from nNOS-/- & N=6, n=11 wild type, WT, cells plus SMTC vs. N=10, n=28 control WT cells, p<0.001). SMTC had no effect on APD in atrial myocytes from nNOS-/- mice. nNOS inhibition and gene deletion also abolished the physiological RA to LA gradient in APD. In silico simulation indicated that lack of atrial APD gradient promotes rotor stability at the RA/LA junction which may contribute to increased AF propensity. In agreement with these findings, nNOS-deficient mice displayed a 2-fold increase in AF inducibility in response to stimulation (p<0.05 vs. WT littermates, N=18 in each group). Conclusions: In mammalian atrial myocytes, nNOS plays an important role in determining APD, its rate-adaptation and the physiological RA/LA electrical gradient. These findings suggest that the marked loss of nNOS protein and activity in the fibrillating atrial myocardium has potentially important implication for AF-induced electrical remodelling.
37th Congress of IUPS (Birmingham, UK) (2013), Birmingham, UK; 07/2013
[show abstract][hide abstract] ABSTRACT: Cellular and ionic causes of variability in the electrophysiological activity of hearts from individuals of the same species are unknown. However, improved understanding of this variability is key to enable prediction of the response of specific hearts to disease and therapies. Limitations of current mathematical modeling and experimental techniques hamper our ability to provide insight into variability. Here, we describe a methodology to unravel the ionic determinants of intersubject variability exhibited in experimental recordings, based on the construction and calibration of populations of models. We illustrate the methodology through its application to rabbit Purkinje preparations, because of their importance in arrhythmias and safety pharmacology assessment. We consider a set of equations describing the biophysical processes underlying rabbit Purkinje electrophysiology, and we construct a population of over 10,000 models by randomly assigning specific parameter values corresponding to ionic current conductances and kinetics. We calibrate the model population by closely comparing simulation output and experimental recordings at three pacing frequencies. We show that 213 of the 10,000 candidate models are fully consistent with the experimental dataset. Ionic properties in the 213 models cover a wide range of values, including differences up to ±100% in several conductances. Partial correlation analysis shows that particular combinations of ionic properties determine the precise shape, amplitude, and rate dependence of specific action potentials. Finally, we demonstrate that the population of models calibrated using data obtained under physiological conditions quantitatively predicts the action potential duration prolongation caused by exposure to four concentrations of the potassium channel blocker dofetilide.
Proceedings of the National Academy of Sciences 05/2013; · 9.74 Impact Factor
[show abstract][hide abstract] ABSTRACT: Differences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as action potential (AP) prolongation, increased AP triangulation, decreased intracellular calcium transient (CaT) magnitude and decreased CaT triangulation. Our goal is to investigate whether the information contained in mRNA measurements can be used to predict cardiac electrophysiological remodeling in heart failure using computational modeling. Using mRNA data recently obtained from failing and non-failing human hearts, we construct failing and non-failing cell populations incorporating natural variability and up/down regulation of channel conductivities. Six biomarkers are calculated for each cell in each population, at cycle lengths between 1500 ms and 300 ms. Regression analysis is performed to determine which ion channels drive biomarker variability in failing versus non-failing cardiomyocytes. Our models suggest that reported mRNA expression changes are consistent with AP prolongation, increased AP triangulation, increased CaT duration, decreased CaT triangulation and amplitude, and increased delay between AP and CaT upstrokes in the failing population. Regression analysis reveals that changes in AP biomarkers are driven primarily by reduction in I[Formula: see text], and changes in CaT biomarkers are driven predominantly by reduction in I[Formula: see text] and SERCA. In particular, the role of I[Formula: see text] is pacing rate dependent. Additionally, alternans developed at fast pacing rates for both failing and non-failing cardiomyocytes, but the underlying mechanisms are different in control and heart failure.
PLoS ONE 01/2013; 8(2):e56359. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: "The paper considers the question ‘what is the model?’ in a specific example of the use of computational modelling and simulation in systems biology, multi-scale models of cardiac electrophysiology. A detailed account of the construction of the computational models and simulations in these contexts shows that the modelling and simulating process is itself better understood as a hybrid and dynamic system of interacting models (in equation form), simulations and experiments, or what we have called the MSE system. That is, the MSE system is a system both as model source and with respect to the biological systems that they target.
We argue that the process of constructing the MSE system as a model system is a process of constructing the grounds for comparability between the MSE system and the target domain. The ‘systems’ nature of the MSE system is foregrounded by validation experiments, which demand consideration of the whole system in order to be interpreted. We propose that validation is a process rather than a result, and that it consists in seeking maximal coherence and consistency within the MSE system, and across it and validation experimental outputs. In addition, these models invert the relationship between theory and model that holds on traditional views of models in science, according to which models are derived from theory, and seek to derive theory from models.
[show abstract][hide abstract] ABSTRACT: Left-to-right ventricular (LV/RV) differences in repolarization have been implicated in lethal arrhythmias in animal models. Our goal is to quantify LV/RV differences in action potential duration (APD) and APD rate adaptation and their contribution to arrhythmogenic substrates in the in vivo human heart using combined in vivo and in silico studies. Electrograms were acquired from 10 LV and 10 RV endocardial sites in 15 patients with normal ventricles. APD and APD adaptation were measured during an increase in heart rate. Analysis of in vivo electrograms revealed longer APD in LV than RV (207.8±21.5 vs 196.7±20.1 ms; P<0.05), and slower APD adaptation in LV than RV (time constant τ(s) = 47.0±14.3 vs 35.6±6.5 s; P<0.05). Following rate acceleration, LV/RV APD dispersion experienced an increase of up to 91% in 12 patients, showing a strong correlation (r(2) = 0.90) with both initial dispersion and LV/RV difference in slow adaptation. Pro-arrhythmic implications of measured LV/RV functional differences were studied using in silico simulations. Results show that LV/RV APD and APD adaptation heterogeneities promote unidirectional block following rate acceleration, albeit being insufficient for establishment of reentry in normal hearts. However, in the presence of an ischemic region at the LV/RV junction, LV/RV heterogeneity in APD and APD rate adaptation promotes reentrant activity and its degeneration into fibrillatory activity. Our results suggest that LV/RV heterogeneities in APD adaptation cause a transient increase in APD dispersion in the human ventricles following rate acceleration, which promotes unidirectional block and wave-break at the LV/RV junction, and may potentiate the arrhythmogenic substrate, particularly in patients with ischemic heart disease.
PLoS ONE 12/2012; 7(12):e52234. · 3.73 Impact Factor
[show abstract][hide abstract] ABSTRACT: Background
Alterations in mRNA expression levels are reported in human heart failure (HF). However, their potential causative link to changes in action potential (AP) and calcium transient (CaiT) measured in human HF is still unclear. Our aim is to investigate consequences of HF-related mRNA changes on cellular electrophysiology taking into account interindividual variability and uncertainty in membrane-level effect of changed mRNA expression of channel subunits.
HF and non-HF human cell model populations were constructed using Monte-Carlo sampling and recent mRNA expression data from HF and nondiseased human hearts. Six AP and CaiT biomarkers were calculated for each cell at cycle lengths between 1500 and 300 ms. Regression analysis was used to determine key ionic properties underlying biomarker changes.
Simulations show that HF-related mRNA changes result in increase in AP duration, AP triangulation, CaiT duration, delay between AP and CaiT upstroke as well as decrease in CaiT triangulation and amplitude in HF cells. Changes in AP biomarkers in HF are correlated with reduction in IKr, whereas changes in CaiT biomarkers are correlated with reduction in ICaL and SERCA. The role of ICaL is pacing rate dependent. At fast pacing rates, both HF and non-HF cells develop alternans, but the underlying mechanisms differed.
A population-based simulation study reveals the functional consequences of HR-related mRNA changes on cellular electrophysiology, consistent with experimental measurements in human HF. Remodeling in IKr, ICaL, and SERCA are identified as main determinants of AP and CaiT changes in HF.
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Sample AP traces at 1500ms BCL
[show abstract][hide abstract] ABSTRACT: Atrial fibrillation (AF) is the most common cardiac ar-rhythmia, and is mainly sustained by reentrant circuits and rapid ectopic activity. In the present study, we performed computer simulations using a 3D human atrial model including fibre orientation, electrophysiological hetero-geneities and tissue anisotropy. Membrane kinetics were described as in the human atrial action potential model by Maleckar et al., including AF-induced ionic remodel-ing. The impact of ionic changes on reentrant activity was investigated by characterizing arrhythmia stability, rotor dynamics and dominant frequency (DF). Our simulations show that reentrant circuits tend to organize around the pulmonary veins and the right atrial appendage. Simu-lated I K1 and I N a blocks lead to slower DF in the whole atria, expanded wave meandering and reduction of sec-ondary wavelets. I N aK block slightly reduces DF and does not notably change the propagation pattern. Reg-ularity and coupling indices of electrograms are usually higher in the right atrium than in the left atrium, entailing a higher likelihood of arrhythmia generation in the latter, as occurs in AF patients.
[show abstract][hide abstract] ABSTRACT: BACKGROUND AND PURPOSE: This work is based on the computational models describing the physiology of the electrical wave propagation in the heart. The goal is to show the ability of computational models to reproduce the effect drugs on the electrical activity of the heart at the cell, the organ (heart) and the ECG body surface potential levels. EXPERIMENTAL APPROACH: We use the state-of-the-art mathematical models governing the heart electrical activity. The drug model is introduced using an ion channel conductance block for both hERG and sodium depending on the IC50 value and the drug dose. We measure the ECG at the surface and compare the different biomarkers. KEY RESULTS: Introducing a 50% hERG block results in 7.8% prolongation of the APD(90) and 5.7% QT interval prolongation, whereas the hERG block does not affect the QRS interval. Introducing 50% of sodium block prolongs the QRS and the QT intervals respectively by 12% and 5% and delays the activation times, whereas the sodium block does not affect the APD(90) . CONCLUSIONS AND IMPLICATIONS: Both potassium and sodium blocks prolong the QT interval, but the reason behind is different: For the first it is due to APD prolongation, while for the second it is due to a reduction of the electrical wave velocity. This example of study shows the usability of the in silco models in the investigation of drugs mechanism and the assessment of drug side effects.
British Journal of Pharmacology 09/2012; · 5.07 Impact Factor
[show abstract][hide abstract] ABSTRACT: Adaptation of the QT-interval to changes in heart rate reflects on the body-surface ECG the adaptation of action potential duration (APD) at the cellular level. The initial fast phase of APD adaptation has been shown to modulate the arrhythmia substrate, but whether the slow phase is potentially proarrhythmic remains unclear. In this paper, we analyze in-vivo human data and use computer simulations to examine the effects of the slow phase of APD adaptation on repolarization dispersion in the human ventricle. Spatial heterogeneity of rate adaptation was observed in all patients. Computer simulations showed that altering local slow time constants of adaptation was sufficient to convert partial wavefront block with no reentry to block with successful reentry, highlighting heterogeneity in the slow phase of APD adaptation to changes in heart rate as a potentially important component of arrhythmogenesis.
7th International Workshop on Biosignal Interpretation; 07/2012
[show abstract][hide abstract] ABSTRACT: Computational models in physiology often integrate functional and structural information from a large range of spatiotemporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and skepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace, and refine animal experiments. A fundamental requirement to fulfill these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations among experiments, models, and simulations in cardiac electrophysiology. We describe the processes, data, and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. We argue that validation is part of the whole MSE system and is contingent upon 1) understanding and coping with sources of biovariability; 2) testing and developing robust techniques and tools as a prerequisite to conducting physiological investigations; 3) defining and adopting standards to facilitate the interoperability of experiments, models, and simulations; 4) and understanding physiological validation as an iterative process that contributes to defining the specific aspects of cardiac electrophysiology the MSE system targets, rather than being only an external test, and that this is driven by advances in experimental and computational methods and the combination of both.
[show abstract][hide abstract] ABSTRACT: The bidomain and monodomain equations are well established as the standard set of equations for the simulation of cardiac electrophysiological behavior. However, the computational cost of detailed bidomain/monodomain simulations limits their applicability in scenarios where a large number of simulations needs to be performed (e.g., parameter estimation). In this study, we present a graph-based method, which relies on point-to-point path finding to estimate activation times for single points in cardiac tissue with minimal computational costs. To validate our approach, activation times are compared to monodomain simulation results for an anatomically based rabbit ventricular model, incorporating realistic fiber orientation and conduction heterogeneities. Differences in activation times between the graph-based method and monodomain results are less than 10% of the total activation time, and computational performance is orders of magnitude faster with the proposed method when calculating activation times at single points. These results suggest that the graph-based method is well suited for estimating activation times when the need for fast performance justifies a limited loss of accuracy.