Quantification of repolarization reserve to understand interpatient variability in the response to proarrhythmic drugs: A computational analysis

Amrita X. Sarkar, Eric A. Sobie

Research output: Contribution to journalArticlepeer-review

91 Scopus citations

Abstract

Background: "Repolarization reserve" is frequently invoked to explain why potentially proarrhythmic drugs cause, across a population, a range of changes to cardiac action potentials (APs). However, the mechanisms underlying this interindividual variability are not understood quantitatively. Objective: The purpose of this study was to perform a novel analysis of mathematical models of ventricular myocytes to quantify repolarization reserve and gain insight into the factors responsible for variability in the response to proarrhythmic drugs. Methods/Results: In several models of human or canine ventricular myocytes, variability was simulated by randomizing model parameters and running repeated simulations. With each randomly generated set of parameters, APs before and after simulated 75% block of the rapid delayed rectifier current (I Kr) were calculated. Multivariable regression was performed to determine how much each model parameter attenuated or exacerbated the AP prolongation caused by the I Kr-blocking drug. Simulations with a human ventricular myocyte model suggest that drug response is influenced most strongly by (1) the density of I Kr, (2) the density of slow delayed rectifier current I Ks, (3) the voltage dependence of I Kr inactivation, (4) the density of L-type Ca 2+ current, and (5) the kinetics of I Ks activation. The analysis also identified mechanisms underlying nonintuitive behavior, such as ionic currents that prolong baseline APs but decrease drug-induced AP prolongation. Finally, the simulations provided quantitative insight into conditions that aggravate the drug response, such as silent ion channel mutations and heart failure. Conclusion: These modeling results provide the first thorough quantification of repolarization reserve and improve our understanding of interindividual variability in adverse drug reactions.

Original languageEnglish
Pages (from-to)1749-1755
Number of pages7
JournalHeart Rhythm
Volume8
Issue number11
DOIs
StatePublished - Nov 2011

Keywords

  • Arrhythmia
  • Long QT syndrome
  • Modeling
  • Systems biology
  • Ventricular tachycardia

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