Atrial fibrillation dynamics and ionic block effects in six heterogeneous human 3D virtual atria with distinct repolarization dynamics

Atrial fibrillation (AF) usually manifests as reentrant circuits propagating through the whole atria creating chaotic activation patterns. Little is yet known about how differences in electrophysiological and ionic properties between patients modulate reentrant patterns in AF. The goal of this study is to quantify how variability in action potential duration (APD) at different stages of repolarization determines AF dynamics and their modulation by ionic block using a set of virtual whole-atria human models. Six human whole-atria models are constructed based on the same anatomical structure and fiber orientation, but with different electrophysiological phenotypes. Membrane kinetics for each whole-atria model are selected with distinct APD characteristics at 20, 50, and 90% repolarization, from an experimentally calibrated population of human atrial action potential models, including AF remodeling and acetylcholine parasympathetic effects. Our simulations show that in all whole-atria models, reentrant circuits tend to organize around the pulmonary veins and the right atrial appendage, thus leading to higher dominant frequency (DF) and more organized activation in the left atrium than in the right atrium. Differences in APD in all phases of repolarization (not only APD90) yielded quantitative differences in fibrillation patterns with long APD associated with slower and more regular dynamics. Long APD50 and APD20 were associated with increased interatrial conduction block and interatrial differences in DF and organization index, creating reentry instability and self-termination in some cases. Specific inhibitions of IK1, INaK, or INa reduce DF and organization of the arrhythmia by enlarging wave meandering, reducing the number of secondary wavelets, and promoting interatrial block in all six virtual patients, especially for the phenotypes with short APD at 20, 50, and/or 90% repolarization. This suggests that therapies aiming at prolonging the early phase of repolarization might constitute effective antiarrhythmic strategies for the pharmacological management of AF. In summary, simulations report significant differences in atrial fibrillatory dynamics resulting from differences in APD at all phases of repolarization

High arrhythmic risk in antero-septal acute myocardial ischemia is explained by increased transmural reentry occurrence

Acute myocardial ischemia is a precursor of sudden arrhythmic death. Variability in its manifestation hampers understanding of arrhythmia mechanisms and challenges risk stratification. Our aim is to unravel the mechanisms underlying how size, transmural extent and location of ischemia determine arrhythmia vulnerability and ecG alterations. High performance computing simulations using a human torso/biventricular biophysically-detailed model were conducted to quantify the impact of varying ischemic region properties, including location (LAD/LcX occlusion), transmural/subendocardial ischemia, size, and normal/slow myocardial propagation. ecG biomarkers and vulnerability window for reentry were computed in over 400 simulations for 18 cases evaluated. Two distinct mechanisms explained larger vulnerability to reentry in transmural versus subendocardial ischemia. Macro-reentry around the ischemic region was the primary mechanism increasing arrhythmic risk in transmural versus subendocardial ischemia, for both LAD and LcX occlusion. transmural micro-reentry at the ischemic border zone explained arrhythmic vulnerability in subendocardial ischemia, especially in LAD occlusion, as reentries were favoured by the ischemic region intersecting the septo-apical region. St elevation reflected ischemic extent in transmural ischemia for LCX and LAD occlusion but not in subendocardial ischemia (associated with mild St depression). the technology and results presented can inform safety and efficacy evaluation of anti-arrhythmic therapy in acute myocardial ischemia

Electrocardiogram Analysis Reveals Ionic Current Dysregulation Relevant for Atrial Fibrillation

Antiarrhythmic drug choice for atrial fibrillation (AF) neglects the individual ionic current profile of the patient, even though it determines drug safety and efficacy. We hypothesize that the electrocardiogram (ECG) might contain information critical for pharmacological treatment personalization. Thus, this study aims to identify the extent of atrial ionic information embedded in the ECG, using multi-scale modeling and simulation. A dataset of 1,000 simulated ECGs was computed using a population of human-based whole-atria models with 200 individual ionic profiles and 5 different torso-atria orientations. A regression neural network was built to predict key atrial ionic conductances based on P- and T$_a$ -wave biomarkers. The neural network predicted, with >80% precision, the density of seven ionic currents relevant for AF, namely, ultra-rapid (I$_{Kur}$ ), rapid (I$_{Kr}$ ), outward transient (I$_{to}$ ), inward rectifier K$^+$ (I$_{K1}$ ), L-type Ca$^{2+}$ (I$_{CaL}$ ), Na$^+$ /K$^+$ pump (I$_{NaK}$ ) and fast Na$^+$ (I$_{Na}$) currents. These ionic densities were identified through the P- (i.e., I$_{Na}$), Ta - (i.e., I$_{K1}$ , I$_{NaK}$) or both waves (i.e., I$_{Kur}$ , I$_{Kr}$ , I$_{to}$ , I$_{CaL}$), providing a non- invasive characterization of the atrial electrophysiology. This could improve patient stratification and cardiac safety and the efficacy of AF pharmacological treatment

Atrial Fibrillation Dynamics and Ionic Block Effects in Six Heterogeneous Human 3D Virtual Atria with Distinct Repolarization Dynamics

Atrial fibrillation (AF) usually manifests as reentrant circuits propagating through the whole atria creating chaotic activation patterns. Little is yet known about how differences in electrophysiological and ionic properties between patients modulate reentrant patterns in AF. The goal of this study is to quantify how variability in action potential duration (APD) at different stages of repolarization determines AF dynamics and their modulation by ionic block using a set of virtual whole-atria human models. Six human whole-atria models are constructed based on the same anatomical structure and fiber orientation, but with different electrophysiological phenotypes. Membrane kinetics for each whole-atria model are selected with distinct APD characteristics at 20, 50, and 90% repolarization, from an experimentally calibrated population of human atrial action potential models, including AF remodeling and acetylcholine parasympathetic effects. Our simulations show that in all whole-atria models, reentrant circuits tend to organize around the pulmonary veins and the right atrial appendage, thus leading to higher dominant frequency (DF) and more organized activation in the left atrium than in the right atrium. Differences in APD in all phases of repolarization (not only APD90) yielded quantitative differences in fibrillation patterns with long APD associated with slower and more regular dynamics. Long APD50 and APD20 were associated with increased interatrial conduction block and interatrial differences in DF and organization index, creating reentry instability and self-termination in some cases. Specific inhibitions of IK1, INaK, or INa reduce DF and organization of the arrhythmia by enlarging wave meandering, reducing the number of secondary wavelets, and promoting interatrial block in all six virtual patients, especially for the phenotypes with short APD at 20, 50, and/or 90% repolarization. This suggests that therapies aiming at prolonging the early phase of repolarization might constitute effective antiarrhythmic strategies for the pharmacological management of AF. In summary, simulations report significant differences in atrial fibrillatory dynamics resulting from differences in APD at all phases of repolarization

Mechanism based therapies enable personalised treatment of hypertrophic cardiomyopathy

Cardiomyopathies have unresolved genotype–phenotype relationships and lack disease-specific treatments. Here we provide a framework to identify genotype-specific pathomechanisms and therapeutic targets to accelerate the development of precision medicine. We use human cardiac electromechanical in-silico modelling and simulation which we validate with experimental hiPSC-CM data and modelling in combination with clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7R403Q/+) and thin filaments (TNNT2R92Q/+, TNNI3R21C/+) of the cardiac sarcomere. Using in-silico techniques we show that the destabilisation of myosin super relaxation observed in hiPSC-CMs drives disease in virtual cells and ventricles carrying the MYH7R403Q/+ variant, and that secondary effects on thin filament activation are necessary to precipitate slowed relaxation of the cell and diastolic insufficiency in the chamber. In-silico modelling shows that Mavacamten corrects the MYH7R403Q/+ phenotype in agreement with hiPSC-CM experiments. Our in-silico model predicts that the thin filament variants TNNT2R92Q/+ and TNNI3R21C/+ display altered calcium regulation as central pathomechanism, for which Mavacamten provides incomplete salvage, which we have corroborated in TNNT2R92Q/+ and TNNI3R21C/+ hiPSC-CMs. We define the ideal characteristics of a novel thin filament-targeting compound and show its efficacy in-silico. We demonstrate that hybrid human-based hiPSC-CM and in-silico studies accelerate pathomechanism discovery and classification testing, improving clinical interpretation of genetic variants, and directing rational therapeutic targeting and design