Convergence of models of human ventricular myocyte electrophysiology after global optimization to recapitulate clinical long QT phenotypes.
In-silico models of human cardiac electrophysiology are now being considered for prediction of cardiotoxicity as part of the preclinical assessment phase of all new drugs. We ask the question whether any of the available models are actually fit for this purpose. We tested three models of the human ventricular action potential, the O'hara-Rudy (ORD11), the Grandi-Bers (GB10) and the Ten Tusscher (TT06) models. We extracted clinical QT data for LQTS1 and LQTS2 patients with nonsense mutations that would be predicted to cause 50% loss of function in IKsand IKrrespectively. We also obtained clinical QT data for LQTS3 patients. We then used a global optimization approach to improve the existing in silico models so that they reproduced all three clinical data sets more closely. We also examined the effects of adrenergic stimulation in the different LQTS subsets. All models, in their original form, produce markedly different and unrealistic predictions of QT prolongation for LQTS1, 2 and 3. After global optimization of the maximum conductances for membrane channels, all models have similar current densities during the action potential, despite differences in kinetic properties of the channels in the different models, and more closely reproduce the prolongation of repolarization seen in all LQTS subtypes. In-silico models of cardiac electrophysiology have the potential to be tremendously useful in complementing traditional preclinical drug testing studies. However, our results demonstrate they should be carefully validated and optimized to clinical data before they can be used for this purpose.
Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW 2010, Australia; St Vincent's Clinical School, University of New South Wales, Australia.
Stefan A
SA
Mann
Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW 2010, Australia.
Mohammad
M
Imtiaz
Department of Clinical Sciences, Pediatrics, Umeå University, 90185 Umeå, Sweden.
Annika
A
Winbo
Department of Clinical Sciences, Pediatrics, Umeå University, 90185 Umeå, Sweden.
Annika
A
Rydberg
Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW 2010, Australia; St Vincent's Clinical School, University of New South Wales, Australia.
Matthew D
MD
Perry
Division of Cardiology, University of Rochester, School of Medicine, Rochester, NY, USA.
Jean-Philippe
JP
Couderc
Division of Cardiology, University of Rochester, School of Medicine, Rochester, NY, USA.
Bronislava
B
Polonsky
Division of Cardiology, University of Rochester, School of Medicine, Rochester, NY, USA.
Scott
S
McNitt
Division of Cardiology, University of Rochester, School of Medicine, Rochester, NY, USA.
Wojciech
W
Zareba
Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW 2010, Australia; St Vincent's Clinical School, University of New South Wales, Australia. Electronic address: a.hill@victorchang.edu.au.
Adam P
AP
Hill
Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW 2010, Australia; St Vincent's Clinical School, University of New South Wales, Australia. Electronic address: j.vandenberg@victorchang.edu.au.
Jamie I
JI
Vandenberg
D016022:Case-Control Studies; D003198:Computer Simulation; D016208:Databases, Factual; D004562:Electrocardiography; D055724:Electrophysiological Phenomena; D006329:Heart Conduction System; D006352:Heart Ventricles / Q000503:physiopathology*; D006801:Humans; D008133:Long QT Syndrome / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology*; D008954:Models, Biological; D032383:Myocytes, Cardiac / Q000187:drug effects / Q000378:metabolism*; D010641:Phenotype
Adrenergic regulation; Global optimization, computational cardiology; In-silico models; Long QT syndrome; Repolarization