Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm – ScienceOpen
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      Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm

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          Abstract

          Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm.

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          Similar network activity from disparate circuit parameters.

          It is often assumed that cellular and synaptic properties need to be regulated to specific values to allow a neuronal network to function properly. To determine how tightly neuronal properties and synaptic strengths need to be tuned to produce a given network output, we simulated more than 20 million versions of a three-cell model of the pyloric network of the crustacean stomatogastric ganglion using different combinations of synapse strengths and neuron properties. We found that virtually indistinguishable network activity can arise from widely disparate sets of underlying mechanisms, suggesting that there could be considerable animal-to-animal variability in many of the parameters that control network activity, and that many different combinations of synaptic strengths and intrinsic membrane properties can be consistent with appropriate network performance.
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            Variable channel expression in identified single and electrically coupled neurons in different animals.

            It is often assumed that all neurons of the same cell type have identical intrinsic properties, both within an animal and between animals. We exploited the large size and small number of unambiguously identifiable neurons in the crab stomatogastric ganglion to test this assumption at the level of channel mRNA expression and membrane currents (measured in voltage-clamp experiments). In lateral pyloric (LP) neurons, we saw strong correlations between measured current and the abundance of Shal and BK-KCa mRNAs (encoding the Shal-family voltage-gated potassium channel and large-conductance calcium-activated potassium channel, respectively). We also saw two- to fourfold interanimal variability for three potassium currents and their mRNA expression. Measurements of channel expression in the two electrically coupled pyloric dilator (PD) neurons showed significant interanimal variability, but copy numbers for IH (encoding the hyperpolarization-activated, inward-current channel) and Shal mRNA in the two PD neurons from the same crab were similar, suggesting that the regulation of some currents may be shared in electrically coupled neurons.
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              Gender-related differences in ion-channel and transporter subunit expression in non-diseased human hearts.

              Gender-related differences in ventricular electrophysiology are known to be important determinants of human arrhythmic risk, but the underlying molecular basis is poorly understood. The present work aims to provide the first detailed analysis of gender-related cardiac ion-channel gene-distribution, based on samples from non-diseased human hearts. By using a high-throughput quantitative approach, we investigated at a genome-scale the expression of 79 genes encoding ion-channel and transporter subunits in epicardial and endocardial tissue samples from non-diseased transplant donors (10 males, 10 females). Gender-related expression differences involved key genes implicated in conduction and repolarization. Female hearts showed reduced expression for a variety of K(+)-channel subunits with potentially important roles in cardiac repolarization, including HERG, minK, Kir2.3, Kv1.4, KChIP2, SUR2 and Kir6.2, as well as lower expression of connexin43 and phospholamban. In addition, they demonstrated an isoform switch in Na(+)/K(+)-ATPase, expressing more of the alpha1 and less of the alpha3 subunit than male hearts, along with increased expression of calmodulin-3. Iroquois transcription factors (IRX3, IRX5) were more strongly expressed in female than male epicardium, but the transmural gradient remained. Protein-expression paralleled transcript patterns for all subunits examined: HERG, minK, Kv1.4, KChIP2, IRX5, Nav1.5 and connexin43. Our results indicate that male and female human hearts have significant differences in ion-channel subunit composition, with female hearts showing decreased expression for a number of repolarizing ion-channels. These findings are important for understanding sex-related differences in the susceptibility to ventricular arrhythmias, particularly for conditions associated with repolarization abnormalities like Brugada and Long QT syndrome. Copyright 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Prog Biophys Mol Biol
                Prog. Biophys. Mol. Biol
                Progress in Biophysics and Molecular Biology
                Pergamon Press
                0079-6107
                1873-1732
                1 January 2016
                January 2016
                : 120
                : 1-3
                : 115-127
                Affiliations
                [a ]Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, United Kingdom
                [b ]Clyde Biosciences Ltd, West Medical Building, University of Glasgow, Glasgow G12 8QQ, United Kingdom
                [c ]Center for Computational Medicine in Cardiology (CCMC), Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland
                [d ]Medical Humanities, University of Sheffield, United Kingdom
                [e ]Department of Physiology and Biophysics, Dalhousie University, Halifax, Nova Scotia, Canada
                [f ]Mathematical Sciences, Queensland University of Technology, Queensland 4072, Australia
                [g ]ACEMS, ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Queensland 4072, Australia
                Author notes
                []Corresponding author. blanca.rodriguez@ 123456cs.ox.ac.uk
                Article
                S0079-6107(15)00242-4
                10.1016/j.pbiomolbio.2015.12.002
                4821179
                26701222
                e6348a9a-f6e6-4849-a3e2-b4c633d60e2b
                © 2015 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 September 2015
                : 24 November 2015
                : 2 December 2015
                Categories
                Article

                Biophysics
                physiological variability,cardiac electrophysiology,populations of models,action potential,in silico high-throughput screening,arrhythmias

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