Optimization of a Cardiomyocyte Model Illuminates Role of Increased INaL in Repolarization Reserve. Academic Article uri icon

Overview

abstract

  • Cardiac ion currents may compensate for each other when one is compromised by a congenital or drug-induced defect. Such redundancy contributes to a robust repolarization reserve that can prevent the development of lethal arrhythmias. Most efforts made to describe this phenomenon have quantified contributions by individual ion currents. However, it is important to understand the interplay between all major ion channel conductances, as repolarization reserve is dependent on the balance between all ion currents in a cardiomyocyte. Here, a genetic algorithm was designed to derive profiles of nine ion-channel conductances that optimize repolarization reserve in a mathematical cardiomyocyte model. Repolarization reserve was quantified using a previously defined metric, repolarization reserve current, i.e., the minimum constant current to prevent normal action potential repolarization in a cell. The optimization improved repolarization reserve current up to 84 \% compared to baseline in a human adult ventricular myocyte model and increased resistance to arrhythmogenic insult.The optimized conductance profiles were characterized by increased repolarizing current conductances, but also uncovered a previously unreported behavior by the late sodium current. Simulations demonstrated that upregulated late sodium increased action potential duration, without compromising repolarization reserve current. The finding was generalized to multiple models. Ultimately, this computational approach in which multiple currents were studied simultaneously illuminated mechanistic insights into how the metric's magnitude could be increased, and allowed for the unexpected role of late sodium to be elucidated.

publication date

  • December 1, 2023

Research

keywords

  • Arrhythmias, Cardiac
  • Myocytes, Cardiac

Identity

Digital Object Identifier (DOI)

  • 10.1152/ajpheart.00553.2023

PubMed ID

  • 38038718