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mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study

Differences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as...

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Autores principales: Walmsley, John, Rodriguez, Jose F., Mirams, Gary R., Burrage, Kevin, Efimov, Igor R., Rodriguez, Blanca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3577832/
https://www.ncbi.nlm.nih.gov/pubmed/23437117
http://dx.doi.org/10.1371/journal.pone.0056359
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author Walmsley, John
Rodriguez, Jose F.
Mirams, Gary R.
Burrage, Kevin
Efimov, Igor R.
Rodriguez, Blanca
author_facet Walmsley, John
Rodriguez, Jose F.
Mirams, Gary R.
Burrage, Kevin
Efimov, Igor R.
Rodriguez, Blanca
author_sort Walmsley, John
collection PubMed
description Differences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as action potential (AP) prolongation, increased AP triangulation, decreased intracellular calcium transient (CaT) magnitude and decreased CaT triangulation. Our goal is to investigate whether the information contained in mRNA measurements can be used to predict cardiac electrophysiological remodeling in heart failure using computational modeling. Using mRNA data recently obtained from failing and non-failing human hearts, we construct failing and non-failing cell populations incorporating natural variability and up/down regulation of channel conductivities. Six biomarkers are calculated for each cell in each population, at cycle lengths between 1500 ms and 300 ms. Regression analysis is performed to determine which ion channels drive biomarker variability in failing versus non-failing cardiomyocytes. Our models suggest that reported mRNA expression changes are consistent with AP prolongation, increased AP triangulation, increased CaT duration, decreased CaT triangulation and amplitude, and increased delay between AP and CaT upstrokes in the failing population. Regression analysis reveals that changes in AP biomarkers are driven primarily by reduction in I[Image: see text], and changes in CaT biomarkers are driven predominantly by reduction in I[Image: see text] and SERCA. In particular, the role of I[Image: see text] is pacing rate dependent. Additionally, alternans developed at fast pacing rates for both failing and non-failing cardiomyocytes, but the underlying mechanisms are different in control and heart failure.
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spelling pubmed-35778322013-02-22 mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study Walmsley, John Rodriguez, Jose F. Mirams, Gary R. Burrage, Kevin Efimov, Igor R. Rodriguez, Blanca PLoS One Research Article Differences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as action potential (AP) prolongation, increased AP triangulation, decreased intracellular calcium transient (CaT) magnitude and decreased CaT triangulation. Our goal is to investigate whether the information contained in mRNA measurements can be used to predict cardiac electrophysiological remodeling in heart failure using computational modeling. Using mRNA data recently obtained from failing and non-failing human hearts, we construct failing and non-failing cell populations incorporating natural variability and up/down regulation of channel conductivities. Six biomarkers are calculated for each cell in each population, at cycle lengths between 1500 ms and 300 ms. Regression analysis is performed to determine which ion channels drive biomarker variability in failing versus non-failing cardiomyocytes. Our models suggest that reported mRNA expression changes are consistent with AP prolongation, increased AP triangulation, increased CaT duration, decreased CaT triangulation and amplitude, and increased delay between AP and CaT upstrokes in the failing population. Regression analysis reveals that changes in AP biomarkers are driven primarily by reduction in I[Image: see text], and changes in CaT biomarkers are driven predominantly by reduction in I[Image: see text] and SERCA. In particular, the role of I[Image: see text] is pacing rate dependent. Additionally, alternans developed at fast pacing rates for both failing and non-failing cardiomyocytes, but the underlying mechanisms are different in control and heart failure. Public Library of Science 2013-02-20 /pmc/articles/PMC3577832/ /pubmed/23437117 http://dx.doi.org/10.1371/journal.pone.0056359 Text en © 2013 Walmsley et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Walmsley, John
Rodriguez, Jose F.
Mirams, Gary R.
Burrage, Kevin
Efimov, Igor R.
Rodriguez, Blanca
mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study
title mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study
title_full mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study
title_fullStr mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study
title_full_unstemmed mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study
title_short mRNA Expression Levels in Failing Human Hearts Predict Cellular Electrophysiological Remodeling: A Population-Based Simulation Study
title_sort mrna expression levels in failing human hearts predict cellular electrophysiological remodeling: a population-based simulation study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3577832/
https://www.ncbi.nlm.nih.gov/pubmed/23437117
http://dx.doi.org/10.1371/journal.pone.0056359
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