Lessons learned from multi-scale modeling of the failing heart

Abstract

Heart failure constitutes a major public health problem worldwide. Affected patients experience a number of changes in the electrical function of the heart that predispose to potentially lethal cardiac arrhythmias. Due to the multitude of electrophysiological changes that may occur during heart failure, the scientific literature is complex and sometimes ambiguous, perhaps because these findings are highly dependent on the etiology, the stage of heart failure, and the experimental model used to study these changes. Nevertheless, a number of common features of failing hearts have been documented. Prolongation of the action potential (AP) involving ion channel remodeling and alterations in calcium handling have been established as the hallmark characteristics of myocytes isolated from failing hearts. Intercellular uncoupling and fibrosis are identified as major arrhythmogen-ic factors. Multi-scale computational simulations are a powerful tool that complements experimental and clinical research. The development of biophysically detailed computer models of single myocytes and cardiac tissues has contributed greatly to our understanding of processes underlying excitation and repolarization in the heart. The electrical , structural, and metabolic remodeling that arises in cardiac tissues during heart failure has been addressed from different computational perspectives to further understand the arrhythmogenic substrate. This review summarizes the contributions from computational modeling and simulation to predict the underlying mechanisms of heart failure phenotypes and their implications for arrhythmogenesis, ranging from the cellular level to whole-heart simulations. The main aspects of heart failure are presented in several related sections. An overview of the main electrophysiological and structural changes that have been observed experimentally in failing hearts is followed by the description and discussion of the simulation work in this field at the cellular level, and then in 2D and 3D cardiac structures. The implications for arrhythmogenesis in heart failure are also discussed including therapeutic measures, such as drug effects and cardiac resynchronization therapy. Finally, the future challenges in heart failure modeling and simulation will be discussed.

Model order reduction for left ventricular mechanics via congruency training

“…Interestingly, the optimization algorithm did not reveal large differences in hemodynamic lumped parameters, but it attributed instead the discrepancies in ejection fraction and cardiac phase duration to the S a and τ 2 parameters, which modulate cardiac contraction efficiency and decay time of calcium transients, respectively. More specifically, our analysis suggested that the HF MRI measurements could be explained by smaller S a values and longer τ 2 times, which is in agreement with experimental findings on heart failure myocyte phenotypes, which are less effective in contracting partially due to dysfunctional calcium handling [39, 40].…”

Contribution of two-pore K+ channels to cardiac ventricular action potential revealed using human iPSC-derived cardiomyocytes

“…6). Downregulation of repolarizing K ϩ currents (with subsequent action potential prolongation) is a common theme in heart failure (17,46), and our data suggest a potential contribution of K 2p 17.1 in the pathogenesis of nonischemic heart failure. Furthermore, we report significant prolongations of APD 90 and APD 50 in siRNA-mediated silencing of K 2p 17.1 in iCells (Fig.…”

Multi-level transcriptome sequencing identifies COL1A1 as a candidate marker in human heart failure progression

“…Thus, understanding the mechanisms contributing to fibrosis will help us identify therapeutic targets. In this study, we identified several genes associated with fibrosis, some of which have been reported in literature, such as ELN and POSTN [47,48]. In addition, we identified several novel fibrosis associated genes for further validation, such as NR4A3, PTGDS, TNC, miR-190a, and miR-708-5p.…”