Acquired and Inherited Cardiac Arrhythmias

Editorial

21 June 2022

Editorial: Acquired and Inherited Cardiac Arrhythmias

Yael Ben-Haim

Ofer Binah

and

José Jalife

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0 citations

Editors

Ofer Binah

Technion Israel Institute of Technology

Yael Ben-Haim

Research Institute of Molecular and Clinical Sciences, St George's, University of London

José Jalife

Centro Nacional de Investigaciones Cardiovasculares (CNIC)

Impact

(A) Percentage of MEAs that ceased to beat in at least one recording timepoint at different HCQ concentrations. (B) Representative examples of FPs with the associated score that were used to quantify the effect of HCQ on FP quality. (C) Mean FP scores at different HCQ concentrations and different timepoints in all the iPSC lines. The color code indicates the mean FP score.

Brief Research Report

27 January 2022

Use of hiPSC-Derived Cardiomyocytes to Rule Out Proarrhythmic Effects of Drugs: The Case of Hydroxychloroquine in COVID-19

Luca Sala

, 7 more and

Peter J. Schwartz

In the early phases of the COVID-19 pandemic, drug repurposing was widely used to identify compounds that could improve the prognosis of symptomatic patients infected by SARS-CoV-2. Hydroxychloroquine (HCQ) was one of the first drugs used to treat COVID-19 due to its supposed capacity of inhibiting SARS-CoV-2 infection and replication in vitro. While its efficacy is debated, HCQ has been associated with QT interval prolongation and potentially Torsades de Pointes, especially in patients predisposed to developing drug-induced Long QT Syndrome (LQTS) as silent carriers of variants associated with congenital LQTS. If confirmed, these effects represent a limitation to the at-home use of HCQ for COVID-19 infection as adequate ECG monitoring is challenging. We investigated the proarrhythmic profile of HCQ with Multi-Electrode Arrays after exposure of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from two healthy donors, one asymptomatic and two symptomatic LQTS patients. We demonstrated that: I) HCQ induced a concentration-dependent Field Potential Duration (FPD) prolongation and halted the beating at high concentration due to the combined effect of HCQ on multiple ion currents. II) hiPSC-CMs from healthy or asymptomatic carriers tolerated higher concentrations of HCQ and showed lower susceptibility to HCQ-induced electrical abnormalities regardless of baseline FPD. These findings agree with the clinical safety records of HCQ and demonstrated that hiPSC-CMs potentially discriminates symptomatic vs. asymptomatic mutation carriers through pharmacological interventions. Disease-specific cohorts of hiPSC-CMs may be a valid preliminary addition to assess drug safety in vulnerable populations, offering rapid preclinical results with valuable translational relevance for precision medicine.

3,770 views

9 citations

Original Research

16 December 2021

The Linkage Phase of the Polymorphism KCNH2-K897T Influences the Electrophysiological Phenotype in hiPSC Models of LQT2

Lettine van den Brink

, 6 more and

Richard P. Davis

$Genotyping of isogenic human induced pluripotent stem cell (hiPSC) lines with KCNH2 mutations and their differentiation into cardiomyocytes. (A) Schematic outlining the generation of isogenic hiPSC-CMs harboring KCNH2-K897T either in cis or trans orientation with long QT syndrome type 2 (LQT2) missense mutations, p.A561T or p.N996I. (B) Structure of KCNH2-encoded ion channel, hERG, indicating the approximate location of the primary mutations and K897T. (C) Structure of the KCNH2 genomic locus displaying the exons containing the missense mutations and the genomic distance between them. Exon numbers are indicated. (D,E) Sanger sequencing of gene-edited hiPSC lines KCNH2A561T/WT (D) and KCNH2N996I/WT (E) harboring KCNH2-K897T either in cis (top panel) or trans (bottom panel) orientation. Only the p.A561T and p.N996I mutated alleles and their corresponding K897T region of the sequences are shown. (F) Representative flow cytometry plots showing cardiac troponin T (cTnT) and myosin light chain 2v (MLC2v) expression in hiPSC-CMs at differentiation day 21 + 7. Numbers inside the plots are percentage of cells within the gated region. (G) Average percentage of hiPSC-CMs (cTnT+), and the proportion of ventricular-like (MLC2v+) cardiomyocytes within the hiPSC-CM population for the KCNH2A561T/WT (left panel) and KCNH2N996I/WT (right panel) cell lines. Values (n) indicate the number of differentiations analyzed. (H) Quantification of KCNH2 expression specifically from the K897K and K897T alleles in the differentiated hiPSC lines and displayed as fractional abundance, with the shaded area indicating the region close to 0.5 (0.4–0.6). KCNH2A561T/WT cis and KCNH2A561T/WT trans: n = 3 replicates; KCNH2N996I/WT cis and KCNH2N996I/WT trans: n = 6 replicates. Error bars are the Poisson 95% CI.$

While rare mutations in ion channel genes are primarily responsible for inherited cardiac arrhythmias, common genetic variants are also an important contributor to the clinical heterogeneity observed among mutation carriers. The common single nucleotide polymorphism (SNP) KCNH2-K897T is associated with QT interval duration, but its influence on the disease phenotype in patients with long QT syndrome type 2 (LQT2) remains unclear. Human induced pluripotent stem cells (hiPSCs), coupled with advances in gene editing technologies, are proving an invaluable tool for modeling cardiac genetic diseases and identifying variants responsible for variability in disease expressivity. In this study, we have used isogenic hiPSC-derived cardiomyocytes (hiPSC-CMs) to establish the functional consequences of having the KCNH2-K897T SNP in cis- or trans-orientation with LQT2-causing missense variants either within the pore-loop domain (KCNH2^A561T/WT) or tail region (KCNH2^N996I/WT) of the potassium ion channel, human ether-a-go-go-related gene (hERG). When KCNH2-K897T was on the same allele (cis) as the primary mutation, the hERG channel in hiPSC-CMs exhibited faster activation and deactivation kinetics compared to their trans-oriented counterparts. Consistent with this, hiPSC-CMs with KCNH2-K897T in cis orientation had longer action and field potential durations. Furthermore, there was an increased occurrence of arrhythmic events upon pharmacological blocking of hERG. Collectively, these results indicate that the common polymorphism KCNH2-K897T differs in its influence on LQT2-causing KCNH2 mutations depending on whether it is present in cis or trans. This study corroborates hiPSC-CMs as a powerful platform to investigate the modifying effects of common genetic variants on inherited cardiac arrhythmias and aids in unraveling their contribution to the variable expressivity of these diseases.

3,299 views

6 citations

Original Research

06 December 2021

Artificial Intelligence-Driven Algorithm for Drug Effect Prediction on Atrial Fibrillation: An in silico Population of Models Approach

Ana Maria Sanchez de la Nava

, 2 more and

Felipe Atienza

Background: Antiarrhythmic drugs are the first-line treatment for atrial fibrillation (AF), but their effect is highly dependent on the characteristics of the patient. Moreover, anatomical variability, and specifically atrial size, have also a strong influence on AF recurrence.

Objective: We performed a proof-of-concept study using artificial intelligence (AI) that enabled us to identify proarrhythmic profiles based on pattern identification from in silico simulations.

Methods: A population of models consisting of 127 electrophysiological profiles with a variation of nine electrophysiological variables (G_Na, I_NaK, G_K1, G_CaL, G_Kur, I_KCa, [Na]_ext, and [K]_ext and diffusion) was simulated using the Koivumaki atrial model on square planes corresponding to a normal (16 cm²) and dilated (22.5 cm²) atrium. The simple pore channel equation was used for drug implementation including three drugs (isoproterenol, flecainide, and verapamil). We analyzed the effect of every ionic channel combination to evaluate arrhythmia induction. A Random Forest algorithm was trained using the population of models and AF inducibility as input and output, respectively. The algorithm was trained with 80% of the data (N = 832) and 20% of the data was used for testing with a k-fold cross-validation (k = 5).

Results: We found two electrophysiological patterns derived from the AI algorithm that was associated with proarrhythmic behavior in most of the profiles, where G_K1 was identified as the most important current for classifying the proarrhythmicity of a given profile. Additionally, we found different effects of the drugs depending on the electrophysiological profile and a higher tendency of the dilated tissue to fibrillate (Small tissue: 80 profiles vs Dilated tissue: 87 profiles).

Conclusion: Artificial intelligence algorithms appear as a novel tool for electrophysiological pattern identification and analysis of the effect of antiarrhythmic drugs on a heterogeneous population of patients with AF.

3,235 views

10 citations