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Research Article

Experimentally calibrated population of models predicts and explains intersubject variability in cardiac cellular electrophysiology

Oliver J. Britton, Alfonso Bueno-Orovio, Karel Van Ammel, Hua Rong Lu, Rob Towart, David J. Gallacher, and Blanca Rodriguez
  1. aDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom;
  2. bOxford Centre for Collaborative Applied Mathematics, Mathematical Institute, University of Oxford, Oxford OX1 3LB, United Kingdom; and
  3. cTranslational Sciences, Safety Pharmacology Research, Janssen Research and Development, Janssen Pharmaceutica NV, B-2340 Beerse, Belgium

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PNAS June 4, 2013 110 (23) E2098-E2105; https://doi.org/10.1073/pnas.1304382110
Oliver J. Britton
aDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom;
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Alfonso Bueno-Orovio
bOxford Centre for Collaborative Applied Mathematics, Mathematical Institute, University of Oxford, Oxford OX1 3LB, United Kingdom; and
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Karel Van Ammel
cTranslational Sciences, Safety Pharmacology Research, Janssen Research and Development, Janssen Pharmaceutica NV, B-2340 Beerse, Belgium
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Hua Rong Lu
cTranslational Sciences, Safety Pharmacology Research, Janssen Research and Development, Janssen Pharmaceutica NV, B-2340 Beerse, Belgium
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Rob Towart
cTranslational Sciences, Safety Pharmacology Research, Janssen Research and Development, Janssen Pharmaceutica NV, B-2340 Beerse, Belgium
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David J. Gallacher
cTranslational Sciences, Safety Pharmacology Research, Janssen Research and Development, Janssen Pharmaceutica NV, B-2340 Beerse, Belgium
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Blanca Rodriguez
aDepartment of Computer Science, University of Oxford, Oxford OX1 3QD, United Kingdom;
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  • For correspondence: Blanca.Rodriguez@cs.ox.ac.uk
  1. Edited by Eve Marder, Brandeis University, Waltham, MA, and approved April 18, 2013 (received for review March 12, 2013)

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Significance

Causes of intersubject variability in electrophysiological activity are unknown. We describe a methodology to unravel the ionic determinants of variability exhibited in experimental cardiac action potential recordings, based on the construction and calibration of populations of models. We show that 213 of 10,000 candidate models are consistent with the control experimental dataset. Ionic properties across the model population cover a wide range of values, and particular combinations of ionic properties determine shape, amplitude, and rate dependence of specific action potentials. Finally, we demonstrate that the calibrated model population quantitatively predicts effects caused by four concentrations of a potassium channel blocker.

Abstract

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.

  • cardiac electrophysiology
  • computational biology
  • mathematical modeling
  • systems biology
  • drug

Footnotes

  • ↵1To whom correspondence should be addressed. E-mail: Blanca.Rodriguez{at}cs.ox.ac.uk.
  • Author contributions: O.J.B., A.B.-O., and B.R. designed research; O.J.B. performed research; O.J.B., K.V.A., H.R.L., R.T., and D.J.G. contributed new reagents/analytic tools; O.J.B., A.B.-O., and B.R. analyzed data; and O.J.B., A.B.-O., and B.R. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

Freely available online through the PNAS open access option.

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Predictive model of intersubject variability
Oliver J. Britton, Alfonso Bueno-Orovio, Karel Van Ammel, Hua Rong Lu, Rob Towart, David J. Gallacher, Blanca Rodriguez
Proceedings of the National Academy of Sciences Jun 2013, 110 (23) E2098-E2105; DOI: 10.1073/pnas.1304382110

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Predictive model of intersubject variability
Oliver J. Britton, Alfonso Bueno-Orovio, Karel Van Ammel, Hua Rong Lu, Rob Towart, David J. Gallacher, Blanca Rodriguez
Proceedings of the National Academy of Sciences Jun 2013, 110 (23) E2098-E2105; DOI: 10.1073/pnas.1304382110
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Proceedings of the National Academy of Sciences: 110 (23)
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