Whittaker, DG, Ni, H, Benson, AP orcid.org/0000-0003-4679-9842 et al. (2 more authors) (2017) Modelling the effects of disopyramide on short QT syndrome variant 1 in the human ventricles. In: Computing in Cardiology. 2016 Computing in Cardiology Conference (CinC), 11-14 Sep 2016, Vancouver, Canada. Computing in Cardiology ISBN 9781509008964
Abstract
The short QT syndrome (SQTS) is a recently identified genetic disorder associated with ventricular and/or atrial arrhythmias and increased risk of sudden cardiac death. The SQTS variant 1 (SQT1) N588K mutation to the hERG gene causes a gain-of-function to IKr which shortens the ventricular effective refractory period (ERP), as well as reducing the potency of several drugs which block the hERG channel. This study used computational modelling to assess the effects of disopyramide (DISO), a class 1a anti-arrhythmic agent, on human ventricular electro-physiology in SQT1. The O'Hara Rudy dynamic (ORd) model of the human ventricle action potential (AP) was modified to incorporate a Markov chain model of IKr/hERG including formulations for wild type (WT) and SQT1 N588K mutant hERG channels. The blocking effects of DISO on IKr, INa, ICaL, and Ito were modelled using IC50 and Hill coefficient values from the literature. The ability of DISO to prolong the QT interval was evaluated using a 1D model of human ventricular cells with transmural heterogeneities and the corresponding pseudo-ECG. At a clinically-relevant concentration of 10 μM DISO, the action potential duration (APD) at the single cell level was increased significantly through inhibition of mutant SQT1-hERG channels. The corrected QT interval in tissue was prolonged. This study provides further evidence that DISO is a suitable treatment for hERG-mediated SQTS.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, the author(s). This is an open access article licensed under the Creative Commons Attribution License 2.5. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biomedical Sciences (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 May 2017 13:37 |
Last Modified: | 23 Jun 2023 22:29 |
Status: | Published |
Publisher: | Computing in Cardiology |
Identification Number: | 10.22489/CinC.2016.003-435 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116357 |