Cellular and ionic causes of variability in the electrophysiological activity of hearts from individuals of the same species are unknown. However, improved understanding of this variability is key to enable prediction of the response of specific hearts to disease and therapies. Limitations of current mathematical modeling and experimental techniques hamper our ability to provide insight into variability. Here, we describe a methodology to unravel the ionic determinants of intersubject variability exhibited in experimental recordings, based on the construction and calibration of populations of models. We illustrate the methodology through its application to rabbit Purkinje preparations, because of their importance in arrhythmias and safety pharmacology assessment. We consider a set of equations describing the biophysical processes underlying rabbit Purkinje electrophysiology, and we construct a population of over 10,000 models by randomly assigning specific parameter values corresponding to ionic current conductances and kinetics. We calibrate the model population by closely comparing simulation output and experimental recordings at three pacing frequencies. We show that 213 of the 10,000 candidate models are fully consistent with the experimental dataset. Ionic properties in the 213 models cover a wide range of values, including differences up to ±100% in several conductances. Partial correlation analysis shows that particular combinations of ionic properties determine the precise shape, amplitude, and rate dependence of specific action potentials. Finally, we demonstrate that the population of models calibrated using data obtained under physiological conditions quantitatively predicts the action potential duration prolongation caused by exposure to four concentrations of the potassium channel blocker dofetilide.
|Original language||English (US)|
|Number of pages||1|
|Journal||PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA|
|State||Published - 2013|
Bibliographical noteKAUST Repository Item: Exported on 2021-09-21
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: This study was supported by a Medical Research Council Industry Partnership award and Research Grant from Janssen Pharmaceutica NV. O.J.B. is supported by an Engineering and Physical Sciences Research Council-funded Systems Biology Doctoral Training Centre studentship, B.R. holds a Medical Research Council Career Development Award, and the contribution to this work by A.B.-O. was supported by Award KUK-C1-013-04 from the King Abdullah University of Science and Technology.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
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