Literature DB >> 18676686

Mechanisms of atrial fibrillation termination by rapidly unbinding Na+ channel blockers: insights from mathematical models and experimental correlates.

Philippe Comtois1, Masao Sakabe, Edward J Vigmond, Mauricio Munoz, Anne Texier, Akiko Shiroshita-Takeshita, Stanley Nattel.   

Abstract

Atrial fibrillation (AF) is the most common sustained clinical arrhythmia and is a problem of growing proportions. Recent studies have increased interest in fast-unbinding Na(+) channel blockers like vernakalant (RSD1235) and ranolazine for AF therapy, but the mechanism of efficacy is poorly understood. To study how fast-unbinding I(Na) blockers affect AF, we developed realistic mathematical models of state-dependent Na(+) channel block, using a lidocaine model as a prototype, and studied the effects on simulated cholinergic AF in two- and three-dimensional atrial substrates. We then compared the results with in vivo effects of lidocaine on vagotonic AF in dogs. Lidocaine action was modeled with the Hondeghem-Katzung modulated-receptor theory and maximum affinity for activated Na(+) channels. Lidocaine produced frequency-dependent Na(+) channel blocking and conduction slowing effects and terminated AF in both two- and three-dimensional models with concentration-dependent efficacy (maximum approximately 89% at 60 microM). AF termination was not related to increases in wavelength, which tended to decrease with the drug, but rather to decreased source Na(+) current in the face of large ACh-sensitive K(+) current-related sinks, leading to the destabilization of primary generator rotors and a great reduction in wavebreak, which caused primary rotor annihilations in the absence of secondary rotors to resume generator activity. Lidocaine also reduced the variability and maximum values of the dominant frequency distribution during AF. Qualitatively similar results were obtained in vivo for lidocaine effects on vagal AF in dogs, with an efficacy of 86% at 2 mg/kg iv, as well as with simulations using the guarded-receptor model of lidocaine action. These results provide new insights into the mechanisms by which rapidly unbinding class I antiarrhythmic agents, a class including several novel compounds of considerable promise, terminate AF.

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Year:  2008        PMID: 18676686     DOI: 10.1152/ajpheart.01054.2007

Source DB:  PubMed          Journal:  Am J Physiol Heart Circ Physiol        ISSN: 0363-6135            Impact factor:   4.733


  27 in total

1.  In silico optimization of atrial fibrillation-selective sodium channel blocker pharmacodynamics.

Authors:  Martin Aguilar-Shardonofsky; Edward J Vigmond; Stanley Nattel; Philippe Comtois
Journal:  Biophys J       Date:  2012-03-06       Impact factor: 4.033

Review 2.  New developments in atrial antiarrhythmic drug therapy.

Authors:  Alexander Burashnikov; Charles Antzelevitch
Journal:  Nat Rev Cardiol       Date:  2010-03       Impact factor: 32.419

Review 3.  Novel pharmacological targets for the rhythm control management of atrial fibrillation.

Authors:  Alexander Burashnikov; Charles Antzelevitch
Journal:  Pharmacol Ther       Date:  2011-08-17       Impact factor: 12.310

Review 4.  Role of late sodium channel current block in the management of atrial fibrillation.

Authors:  Alexander Burashnikov; Charles Antzelevitch
Journal:  Cardiovasc Drugs Ther       Date:  2013-02       Impact factor: 3.727

Review 5.  Human atrial fibrillation: insights from computational electrophysiological models.

Authors:  Donald M Bers; Eleonora Grandi
Journal:  Trends Cardiovasc Med       Date:  2011-07       Impact factor: 6.677

Review 6.  Cardiac Delayed Rectifier Potassium Channels in Health and Disease.

Authors:  Lei Chen; Kevin J Sampson; Robert S Kass
Journal:  Card Electrophysiol Clin       Date:  2016-04-01

Review 7.  Early management of atrial fibrillation: from imaging to drugs to ablation.

Authors:  Ashok J Shah; Xingpeng Liu; Amir S Jadidi; Michel Haïssaguerre
Journal:  Nat Rev Cardiol       Date:  2010-04-27       Impact factor: 32.419

Review 8.  Novel approaches for pharmacological management of atrial fibrillation.

Authors:  Joachim R Ehrlich; Stanley Nattel
Journal:  Drugs       Date:  2009       Impact factor: 9.546

Review 9.  Rotors and the dynamics of cardiac fibrillation.

Authors:  Sandeep V Pandit; José Jalife
Journal:  Circ Res       Date:  2013-03-01       Impact factor: 17.367

Review 10.  Anti-arrhythmic strategies for atrial fibrillation: The role of computational modeling in discovery, development, and optimization.

Authors:  Eleonora Grandi; Mary M Maleckar
Journal:  Pharmacol Ther       Date:  2016-09-06       Impact factor: 12.310

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