ORCID Profile
0000-0002-3718-6027
Current Organisations
Children's Medical Research Institute
,
National University of Singapore
,
Institute of High Performance Computing
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Publisher: Elsevier BV
Date: 04-2021
Publisher: Oxford University Press (OUP)
Date: 10-2021
DOI: 10.1093/CVR/CVAA280
Abstract: Cardiac electrical activity is extraordinarily robust. However, when it goes wrong it can have fatal consequences. Electrical activity in the heart is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. While there is considerable variability in cardiac ion channel expression levels between in iduals, studies in rodents have indicated that there are modules of ion channels whose expression co-vary. The aim of this study was to investigate whether meta-analytic co-expression analysis of large-scale gene expression datasets could identify modules of co-expressed cardiac ion channel genes in human hearts that are of functional importance. Meta-analysis of 3653 public human RNA-seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was also observed in human adult heart tissue s les. In silico modelling suggested that co-expression of CACNA1C and KCNH2 would limit the variability in action potential duration seen with variations in expression of ion channel genes and reduce susceptibility to early afterdepolarizations, a surrogate marker for proarrhythmia. We also found that levels of KCNH2 and CACNA1C expression are correlated in human-induced pluripotent stem cell-derived cardiac myocytes and the levels of CACNA1C and KCNH2 expression were inversely correlated with the magnitude of changes in repolarization duration following inhibition of IKr. Meta-analytic approaches of multiple independent human gene expression datasets can be used to identify gene modules that are important for regulating heart function. Specifically, we have verified that there is co-expression of CACNA1C and KCNH2 ion channel genes in human heart tissue, and in silico analyses suggest that CACNA1C–KCNH2 co-expression increases the robustness of cardiac electrical activity.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 07-2023
DOI: 10.1161/CIRCEP.122.011574
Abstract: Drug-induced or acquired long QT syndrome occurs as a result of the unintended disruption of cardiac repolarization due to drugs that block cardiac ion channels. These side effects have been responsible for the withdrawal of a range of drugs from market and are a common reason for termination of the development of new drugs in the preclinical stage. Existing approaches to risk prediction are expensive and overly sensitive meaning that recently there have been renewed efforts, largely driven by the comprehensive proarrhythmic assay initiative, to develop more accurate methods for allocation of proarrhythmic risk. In this study, we aimed to quantify changes in the morphology of the repolarization phase of the cardiac action potential as an indicator of proarrhythmia, supposing that these shape changes might precede the emergence of ectopic depolarizations that trigger arrhythmia. To do this, we describe a new method of quantifying action potential morphology by measuring the radius of curvature of the repolarization phase both in simulated action potentials, as well as in action potentials measured from induced pluripotent stem cell-derived cardiomyocytes. Features derived from the curvature signal were used as inputs for logistic regressions to predict proarrhythmic risk. Optimal risk classifiers based on morphology were able to correctly classify risk to drugs in the comprehensive proarrhythmic assay initiative panels with very high accuracy (0.9375) and outperformed conventional metrics based on action potential duration at 90% repolarization, triangulation, and charge movement (qNet). Analysis of action potential morphology in response to proarrhythmic drugs improves prediction of torsadogenic risk. Furthermore, morphology metrics can be measured directly from the action potential, potentially eliminating the burden of undertaking complex screens of potency and drug-binding kinetics against multiple cardiac ion channels. As such, this method has the potential to improve and streamline regulatory assessment of proarrhythmia in preclinical drug development.
No related grants have been discovered for Zhi Gen YU.