Functional evaluation of gene mutations in Long QT Syndrome: strength of evidence from in vitro assays for deciphering variants of uncertain significance

Evaluating pro-arrhythmogenic effects of the T634S-hERG mutation: insights from a simulation study

A mutation to serine of a conserved threonine (T634S) in the hERG K+ channel S6 pore region has been identified as a variant of uncertain significance, showing a loss-of-function effect. However, its potential consequences for ventricular excitation and arrhythmogenesis have not been reported. This study evaluated possible functional effects of the T634S-hERG mutation on ventricular excitation and arrhythmogenesis by using multi-scale computer models of the human ventricle. A Markov chain model of the rapid delayed rectifier potassium current (IKr) was reconstructed for wild-type and T634S-hERG mutant conditions and incorporated into the ten Tusscher et al. models of human ventricles at cell and tissue (1D, 2D and 3D) levels. Possible functional impacts of the T634S-hERG mutation were evaluated by its effects on action potential durations (APDs) and their rate-dependence (APDr) at the cell level; and on the QT interval of pseudo-ECGs, tissue vulnerability to unidirectional conduction block (VW), spiral wave dynamics and repolarization dispersion at the tissue level. It was found that the T634S-hERG mutation prolonged cellular APDs, steepened APDr, prolonged the QT interval, increased VW, destablized re-entry and augmented repolarization dispersion across the ventricle. Collectively, these results imply potential pro-arrhythmic effects of the T634S-hERG mutation, consistent with LQT2.

Automated Patch-Clamp and Induced Pluripotent Stem Cell-Derived Cardiomyocytes: A Synergistic Approach in the Study of Brugada Syndrome

The development of high-throughput automated patch-clamp technology is a recent breakthrough in the field of Brugada syndrome research. Brugada syndrome is a heart disorder marked by abnormal electrocardiographic readings and an elevated risk of sudden cardiac death due to arrhythmias. Various experimental models, developed either in animals, cell lines, human tissue or computational simulation, play a crucial role in advancing our understanding of this condition, and developing effective treatments. In the perspective of the pathophysiological role of ion channels and their pharmacology, automated patch-clamp involves a robotic system that enables the simultaneous recording of electrical activity from multiple single cells at once, greatly improving the speed and efficiency of data collection. By combining this approach with the use of patient-derived cardiomyocytes, researchers are gaining a more comprehensive view of the underlying mechanisms of heart disease. This has led to the development of more effective treatments for those affected by cardiovascular conditions.

Modeling long QT syndrome type 2 on-a-chip via in-depth assessment of isogenic gene-edited 3D cardiac tissues

Long QT syndrome (LQTS) is a cardiovascular disease characterized by QT interval prolongation that can lead to sudden cardiac death. Many mutations with heterogeneous mechanisms have been identified in KCNH2, the gene that encodes for hERG (Kv11.1), which lead to onset of LQTS type 2 (LQTS2). In this work, we developed a LQTS2-diseased tissue-on-a-chip model, using 3D coculture of isogenic stem cell-derived cardiomyocytes (CMs) and cardiac fibroblasts (CFs) within an organotypic microfluidic chip technology. Primarily, we created a hiPSC line with R531W mutation in KCNH2 using CRISPR-Cas9 gene-editing technique and characterized the resultant differentiated CMs and CFs. A deficiency in hERG trafficking was identified in KCNH2-edited hiPSC-CMs, revealing a possible mechanism of R531W mutation in LQTS2 pathophysiology. Following creation of a 3D LQTS2 tissue-on-a-chip, the tissues were extensively characterized, through analysis of calcium handling and response to β-agonist. Furthermore, attempted phenotypic rescue via pharmacological intervention of LQTS2 on a chip was investigated.

Evolutionary coupling analysis guides identification of mistrafficking-sensitive variants in cardiac K+ channels: Validation with hERG

Loss of function (LOF) mutations of voltage sensitive K+ channel proteins hERG (Kv11.1) and KCNQ1 (Kv7.1) account for the majority of instances of congenital Long QT Syndrome (cLQTS) with the dominant molecular phenotype being a mistrafficking one resulting from protein misfolding. We explored the use of Evolutionary Coupling (EC) analysis, which identifies evolutionarily conserved pairwise amino acid interactions that may contribute to protein structural stability, to identify regions of the channels susceptible to misfolding mutations. Comparison with published experimental trafficking data for hERG and KCNQ1 showed that the method strongly predicts "scaffolding" regions of the channel membrane domains and has useful predictive power for trafficking phenotypes of individual variants. We identified a region in and around the cytoplasmic S2-S3 loop of the hERG Voltage Sensor Domain (VSD) as susceptible to destabilising mutation, and this was confirmed using a quantitative LI-COR ® based trafficking assay that showed severely attenuated trafficking in eight out of 10 natural hERG VSD variants selected using EC analysis. Our analysis highlights an equivalence in the scaffolding structures of the hERG and KCNQ1 membrane domains. Pathogenic variants of ion channels with an underlying mistrafficking phenotype are likely to be located within similar scaffolding structures that are identifiable by EC analysis.

How Functional Genomics Can Keep Pace With VUS Identification

Over the last two decades, an exponentially expanding number of genetic variants have been identified associated with inherited cardiac conditions. These tremendous gains also present challenges in deciphering the clinical relevance of unclassified variants or variants of uncertain significance (VUS). This review provides an overview of the advancements (and challenges) in functional and computational approaches to characterize variants and help keep pace with VUS identification related to inherited heart diseases.