Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology

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 curren...

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Main Authors: Britton, O, Bueno-Orovio, A, van Ammel, K, Lu, H, Towart, R, Gallacher, D, Rodriguez, B
Format: Journal article
Published: 2013
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author Britton, O
Bueno-Orovio, A
van Ammel, K
Lu, H
Towart, R
Gallacher, D
Rodriguez, B
author_facet Britton, O
Bueno-Orovio, A
van Ammel, K
Lu, H
Towart, R
Gallacher, D
Rodriguez, B
author_sort Britton, O
collection OXFORD
description 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 inter-subject 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, due to 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.
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spelling oxford-uuid:d3289513-bba3-4673-841e-8dd5341155042022-03-27T08:09:19ZExperimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiologyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d3289513-bba3-4673-841e-8dd534115504Mathematical Institute - ePrints2013Britton, OBueno-Orovio, Avan Ammel, KLu, HTowart, RGallacher, DRodriguez, BCellular 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 inter-subject 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, due to 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.
spellingShingle Britton, O
Bueno-Orovio, A
van Ammel, K
Lu, H
Towart, R
Gallacher, D
Rodriguez, B
Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology
title Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology
title_full Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology
title_fullStr Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology
title_full_unstemmed Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology
title_short Experimentally-calibrated population of models predicts and explains inter-subject variability in cardiac cellular electrophysiology
title_sort experimentally calibrated population of models predicts and explains inter subject variability in cardiac cellular electrophysiology
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