Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings

Background and AimsHuman induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have become an essential tool to study arrhythmia mechanisms. Much of the foundational work on these cells, and the computational models built from the resultant data, has overlooked the contribution of seal-leak current on the immature and heterogeneous phenotype that has come to define these cells. The aim of this study is to understand the effect of seal-leak current on recordings of action potential (AP) morphology.MethodsAPs were recorded in human iPSC-CMs using patch clamp and simulated using previously published mathematical models.ResultsOur in silico and in vitro studies demonstrate how seal-leak current depolarises APs, substantially affecting their morphology, even with seal resistances (Rseal) above 1 GΩ. We show that compensation of this leak current is difficult due to challenges with obtaining accurate measures of Rseal during an experiment. Using simulation, we show that Rseal measures: 1) change during an experiment, invalidating the use of pre-rupture values, and 2) are polluted by the presence of transmembrane currents at every voltage. Finally, we posit that the background sodium current in baseline iPSC-CM models imitates the effects of seal-leak current and is increased to a level that masks the effects of seal-leak current on iPSC-CMs.ConclusionBased on these findings, we make recommendations to improve iPSC-CM AP data acquisition, interpretation, and model-building. Taking these recommendations into account will improve our understanding of iPSC-CM physiology and the descriptive ability of models built from such data

Pituitary–gonadal hormones associated with respiratory failure in men and women hospitalized with COVID-19: an observational cohort study

Aim: To explore pituitary–gonadal hormone concentrations and assess their association with inflammation, severe respiratory failure, and mortality in hospitalized men and women with COVID-19, and compare these to hormone concentration s in hospitalized patients with bacterial community-acquired pneumonia (CAP) and influenza virus CAP and to concentrations in a reference group of healthy individuals. Methods: Serum concentrations of testosterone, estrone sulfate, luteini zing hormone (LH), follicle-stimulating hormone (FSH), and interleukin-6 (IL-6) were measured within 4 days of admission. Associations were assessed by logistic regression analysis in patients with COVID-19, and results were reported as odds ratio with 95% CI per two-fold reduction after adjustment for age, comorbidities, days to sample collection, and IL-6 concentrations. Results: In total, 278 patients with COVID-19, 21 with influenza virus CA P, and 76 with bacterial CAP were included. Testosterone concentrations were suppressed in men hospitalized with COVID-19, bacterial and influenza virus CA P, and moderately suppressed in women. Reductions in testosterone (OR: 3.43 (1.14–10.30), P = 0.028) and LH (OR: 2.51 (1.28–4.92), P = 0.008) were associated with higher odds of mehanical ventilation (MV) in men with COVID-19. In women with COVID-19, reductions in LH (OR: 3.34 (1.02–10-90), P = 0.046) and FSH (OR: 2.52 (1.01–6.27), P = 0.047) were associated with higher odds of MV. Conclusion: Low testosterone and LH concentrations were predictive of severe respiratory failure in men with COVID-19, whereas low concentrations of LH and FSH were predictive of severe respiratory failure in women with COVID-19

Effects of Electrical and Structural Remodeling on Atrial Fibrillation Maintenance: A Simulation Study

Atrial fibrillation, a common cardiac arrhythmia, often progresses unfavourably: in patients with long-term atrial fibrillation, fibrillatory episodes are typically of increased duration and frequency of occurrence relative to healthy controls. This is due to electrical, structural, and contractile remodeling processes. We investigated mechanisms of how electrical and structural remodeling contribute to perpetuation of simulated atrial fibrillation, using a mathematical model of the human atrial action potential incorporated into an anatomically realistic three-dimensional structural model of the human atria. Electrical and structural remodeling both shortened the atrial wavelength - electrical remodeling primarily through a decrease in action potential duration, while structural remodeling primarily slowed conduction. The decrease in wavelength correlates with an increase in the average duration of atrial fibrillation/flutter episodes. The dependence of reentry duration on wavelength was the same for electrical vs. structural remodeling. However, the dynamics during atrial reentry varied between electrical, structural, and combined electrical and structural remodeling in several ways, including: (i) with structural remodeling there were more occurrences of fragmented wavefronts and hence more filaments than during electrical remodeling; (ii) dominant waves anchored around different anatomical obstacles in electrical vs. structural remodeling; (iii) dominant waves were often not anchored in combined electrical and structural remodeling. We conclude that, in simulated atrial fibrillation, the wavelength dependence of reentry duration is similar for electrical and structural remodeling, despite major differences in overall dynamics, including maximal number of filaments, wave fragmentation, restitution properties, and whether dominant waves are anchored to anatomical obstacles or spiralling freely

Effects of single-channel noise on spontaneous beating and the phase-resetting response of cardiac oscillators

From our everyday life, we know that our hearts beat with a rhythm which is not perfectly periodic. Even an isolated spontaneously beating cardiac cell, devoid of neural, hormonal, and intracardiac regulatory input, does not beat perfectly regularly. I investigate the hypothesis that the beat-to-beat fluctuations in transmembrane potential of spontaneously beating cardiac cells are due to stochastic gating of the ionic channels in the cell membrane.Recordings of transmembrane potential from small clusters of spontaneously beating 7-day-old embryonic chick ventricular cells were analyzed to characterize the voltage waveform and the regularity of beating. I constructed a deterministic Hodgkin-Huxley-type ionic model which reproduces spontaneous activity in our experimental recordings, as well as the experimental results of applying various ion channel blockers (D-600, almokalant, and Ba2+). The model consists of six currents: a calcium current (ICa), three potassium currents (IKs, I Kr, IK1), a background current ( Ib), and a seal-leak current (I seal).The deterministic Hodgkin-Huxley-type model was then reformulated into a stochastic single-channel model. The single-channel model reproduces the irregularity of beating seen experimentally: e.g. the coefficient of variation of interbeat interval was 4.4% vs. 3.9% in the clusters. In the model, IKs is the current giving the major contributions to fluctuations in interbeat interval.Phase resetting of the spontaneous activity of cardiac pacemaker cells by a brief stimulus pulse was simulated in Hodgkin-Huxley-type models and single-channel models of slow-upstroke (central) and fast-upstroke (peripheral) rabbit sinoatrial node cells. In the Hodgkin-Huxley-type models the phase-resetting response is continuous, but can be extremely delicate in the fast-upstroke model, in that a tiny difference in the stimulus timing can change the stimulus response from a delayed action potential to an advanced one. Therefore, the noise in the fast-upstroke single-channel model can cause a stimulus with fixed amplitude and fixed timing to have widely different effects: sometimes it will induce an action potential but in other cases it will delay an action potential, as seen previously in experiments on cardiac preparations

Krogh-Madsen - Global optimization of ventricular myocyte model to multi-variable objective improves predictions of drug-induced Torsades de Pointes

A talk given by Trine Krogh-Madsen at the Cardiac Physiome Workshop satellite meeting on CiPA in-silico modelling, November 2017, Toronto.<br

Global Optimization of Ventricular Myocyte Model to Multi-Variable Objective Improves Predictions of Drug-Induced Torsades de Pointes

In silico cardiac myocyte models present powerful tools for drug safety testing and for predicting phenotypical consequences of ion channel mutations, but their accuracy is sometimes limited. For example, several models describing human ventricular electrophysiology perform poorly when simulating effects of long QT mutations. Model optimization represents one way of obtaining models with stronger predictive power. Using a recent human ventricular myocyte model, we demonstrate that model optimization to clinical long QT data, in conjunction with physiologically-based bounds on intracellular calcium and sodium concentrations, better constrains model parameters. To determine if the model optimized to congenital long QT data better predicts risk of drug-induced long QT arrhythmogenesis, in particular Torsades de Pointes risk, we tested the optimized model against a database of known arrhythmogenic and non-arrhythmogenic ion channel blockers. When doing so, the optimized model provided an improved risk assessment. In particular, we demonstrate an elimination of false-positive outcomes generated by the baseline model, in which simulations of non-torsadogenic drugs, in particular verapamil, predict action potential prolongation. Our results underscore the importance of currents beyond those directly impacted by a drug block in determining torsadogenic risk. Our study also highlights the need for rich data in cardiac myocyte model optimization and substantiates such optimization as a method to generate models with higher accuracy of predictions of drug-induced cardiotoxicity

Computational Approaches to Understanding the Role of Fibroblast-Myocyte Interactions in Cardiac Arrhythmogenesis

The adult heart is composed of a dense network of cardiomyocytes surrounded by nonmyocytes, the most abundant of which are cardiac fibroblasts. Several cardiac diseases, such as myocardial infarction or dilated cardiomyopathy, are associated with an increased density of fibroblasts, that is, fibrosis. Fibroblasts play a significant role in the development of electrical and mechanical dysfunction of the heart; however the underlying mechanisms are only partially understood. One widely studied mechanism suggests that fibroblasts produce excess extracellular matrix, resulting in collagenous septa. These collagenous septa slow propagation, cause zig-zag conduction paths, and decouple cardiomyocytes resulting in a substrate for arrhythmia. Another emerging mechanism suggests that fibroblasts promote arrhythmogenesis through direct electrical interactions with cardiomyocytes via gap junctions. Due to the challenges of investigating fibroblast-myocyte coupling in native cardiac tissue, computational modeling and in vitro experiments have facilitated the investigation into the mechanisms underlying fibroblast-mediated changes in cardiomyocyte action potential morphology, conduction velocity, spontaneous excitability, and vulnerability to reentry. In this paper, we summarize the major findings of the existing computational studies investigating the implications of fibroblast-myocyte interactions in the normal and diseased heart. We then present investigations from our group into the potential role of voltage-dependent gap junctions in fibroblast-myocyte interactions