Multiscale cardiac modelling reveals the origins of notched T waves in long QT syndrome type 2

dc.contributor.authorSadrieh, Arash
dc.contributor.authorDomanski, Luke
dc.contributor.authorPitt-Francis, Joe
dc.contributor.authorMann, Stefan A.
dc.contributor.authorHodkinson, Emily C.
dc.contributor.authorNg, Chai Ann
dc.contributor.authorPerry, Matthew D.
dc.contributor.authorTaylor, John
dc.contributor.authorGavaghan, David
dc.contributor.authorSubbiah, Rajesh N.
dc.contributor.authorVandenberg, Jamie I.
dc.contributor.authorHill, Adam P
dc.date.accessioned2018-11-29T22:56:28Z
dc.date.available2018-11-29T22:56:28Z
dc.date.issued2014
dc.date.updated2018-11-29T08:12:36Z
dc.description.abstractThe heart rhythm disorder long QT syndrome (LQTS) can result in sudden death in the young or remain asymptomatic into adulthood. The features of the surface electrocardiogram (ECG), a measure of the electrical activity of the heart, can be equally variable in LQTS patients, posing well-described diagnostic dilemmas. Here we report a correlation between QT interval prolongation and T-wave notching in LQTS2 patients and use a novel computational framework to investigate how individual ionic currents, as well as cellular and tissue level factors, contribute to notched T waves. Furthermore, we show that variable expressivity of ECG features observed in LQTS2 patients can be explained by as little as 20% variation in the levels of ionic conductances that contribute to repolarization reserve. This has significant implications for interpretation of whole-genome sequencing data and underlies the importance of interpreting the entire molecular signature of disease in any given individual
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2041-1723
dc.identifier.urihttp://hdl.handle.net/1885/153533
dc.publisherMacmillan Publishers Ltd
dc.sourceNature Communications
dc.titleMultiscale cardiac modelling reveals the origins of notched T waves in long QT syndrome type 2
dc.typeJournal article
dcterms.accessRightsOpen Accessen_AU
local.contributor.affiliationSadrieh, Arash , Victor Chang Cardiac Research Institute
local.contributor.affiliationDomanski, Luke , CSIRO eResearch, and Computational and Simulation Sciences
local.contributor.affiliationPitt-Francis, Joe, University of Oxford
local.contributor.affiliationMann, Stefan A., CytoBioScience GmbH
local.contributor.affiliationHodkinson, Emily C., Victor Chang Cardiac Research Institute
local.contributor.affiliationNg, Chai Ann, Victor Chang Cardiac Research Institute
local.contributor.affiliationPerry, Matthew D., Victor Chang Cardiac Research Institute
local.contributor.affiliationTaylor, John, College of Engineering and Computer Science, ANU
local.contributor.affiliationGavaghan, David, University of Oxford
local.contributor.affiliationSubbiah, Rajesh N., Victor Chang Cardiac Research Institute
local.contributor.affiliationVandenberg, Jamie I., Victor Chang Cardiac Research Institute
local.contributor.affiliationHill, Adam P, Victor Chang Cardiac Research Institute
local.contributor.authoruidTaylor, John, u1486570
local.description.notesImported from ARIES
local.identifier.absfor110000 - MEDICAL AND HEALTH SCIENCES
local.identifier.ariespublicationa383154xPUB7921
local.identifier.citationvolume5
local.identifier.doi10.1038/ncomms6069
local.identifier.scopusID2-s2.0-84922432370
local.identifier.thomsonID000343029500001
local.type.statusPublished Version

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