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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Format: | Journal article |
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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. |
first_indexed | 2024-03-07T04:45:38Z |
format | Journal article |
id | oxford-uuid:d3289513-bba3-4673-841e-8dd534115504 |
institution | University of Oxford |
last_indexed | 2024-03-07T04:45:38Z |
publishDate | 2013 |
record_format | dspace |
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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