Drug-induced Long QT Syndrome Research Articles

The endocannabinoid ARA-S acts as an endogenous rescuing factor of Kv7.1/KCNE1 carrying Long QT syndrome mutations and paves the way for drug development strategies

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union’s Horizon 2020 research and innovation program Long QT Syndrome (LQTS) is a cardiac arrhythmia characterized by delayed ventricular repolarization. LQTS occurs when there are loss-of-function mutations in genes encoding for voltage-gated channels and their beta subunits that contribute to the cardiac action potential. Among them, the most mutated channel is Kv7.1/KCNE1, which encodes for the slowly activating component of the delayed rectifier K+ current (IKs). Families with inherited mutations in the Kv7.1/KCNE1 exhibit inconsistent correlations between genotypes and phenotypes making the clinical management of LQTS challenging. A possible strategy to help guide clinical approaches involves exploring endogenous compounds capable of modulating the Kv7.1/KCNE1 channel function, acting as potential disease modifiers. Using the two-electrode voltage clamp technique, we previously found that the endogenous endocannabinoid-like compound ARA-S, which has an arachidonic acid tail and a serine head group, facilitates activation of the wild-type Kv7.1/KCNE1 channel expressed in Xenopus oocytes. This is seen as a left shift in the voltage dependence of channel opening and an increase in conductance. Moreover, we showed that ARA-S restores a physiological QT interval in isolated guinea pig hearts suffering from drug-induced LQTS. Hence, ARA-S is an interesting endogenous Kv7.1/KCNE1 channel modulator that may influence disease severity. However, it is uncertain whether ARA-S also activates the Kv7.1/KCNE1 when it carries LQTS-associated mutations. Therefore, the current study involves studying the effect of ARA-S on mutated Kv7.1/KCNE1 channels using two-electrode voltage clamp electrophysiology. We find that ARA-S facilitates the activation of all tested LQTS mutants. However, the magnitude of the effect varies among them, suggesting that the compound´s effect is dependent on the genetic background. To understand why ARA-S has different effects, we use computational simulation approaches to study how mutations in the putative ARA-S binding sites change ARA-S efficacy. This understanding aids in developing new substances that can activate different mutations, by, for example, modifying the ARA-S tail to enhance its efficacy. We also try to understand the concentration of ARA-S required to restore a wild-type-like function of each mutant, considering the mutant's intrinsic behavior and the apparent affinity of ARA-S for the specific mutant. Altogether, this work finds ARA-S to be an efficient activator of LQTS-associated mutant Kv7.1/KCNE1 channels and is a first step towards understanding how the genetic background determines the effect of this endogenous modulator.

Genetic characterization of drug-induced long QT syndrome in a large prospective cohort

Abstract Introduction Drug-induced long QT syndrome (DI-LQTS) is a clinical entity with a poorly defined etiopathogenesis. Purpose The objective of the study was to determine the genetic basis of a prospective cohort of patients with DI-LQTS in the setting of a tertiary hospital center. Methods Prospective observational study with consecutive inclusion of patients with the diagnosis of DI-LQTS according to standard criteria, in a tertiary hospital, between 2018 and 2022. A genetic study was performed through massive DNA sequencing to identify variants in known genes associated with cardiopathy, arrhythmogenic and cardiomyopathy. Results 86 patients (age 65±15 years, 59% men) were included. The mean corrected QT interval (QTc) of the entire cohort was 543±56 ms. The drugs associated with QTc interval prolongation were: psychotropics 51%, antiarrhythmics 38%, anesthetics 30%, antibiotics 16%, antineoplastics 5%, others 4%. Twenty-one patients (24%) presented with ventricular arrhythmias at the time of drug-induced QTc prolongation: 10 (12%) ventricular fibrillation, 7 (8%) sustained ventricular tachycardia, 3 (3%) non-sustained ventricular tachycardia, 1 (1%) frequent ventricular premature beats. Genetic information was obtained in 83 (97%) patients. 17 pathogenic mutations associated with heart disease were identified in 15 (18%) patients: 4 (5%) patients with 5 mutations in ion channel genes (KCNE1, KCNE1B, KCNH2, RYR1, RYR2), and 12 (14%) patients with 12 mutations in genes associated with cardiomyopathy (NF1, PKD2, ABCC6, TTN, FHOD3, MYO6, COL11A1, CCDC40, CRELD1, COL4A1). Two patients had 2 pathogenic mutations each, one of them with both mutations associated with channelopathy, and another with a mutation associated with channelopathy and a second mutation related to cardiomyopathy. Only 1 patient carrying a pathogenic mutation related to cardiomyopathy had a clear phenotype, while in 3 carrier patients there was a history of transient systolic dysfunction, 2 due to tachycardiocardiopathy and 1 due to peripartum cardiomyopathy. The identification of a pathogenic mutation was not related to significant differences in QTc interval prolongation (544±63 vs 542±55 ms) or risk of ventricular arrhythmias (26% vs 24%). Conclusions The genetic basis of drug-induced long QT syndrome is essentially different from that of the congenital form of the disease. The identification of pathogenic mutations in genes associated with cardiomyopathy is relatively frequent, while those associated with ion channel genes are uncommon.

Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-Based Classifiers.

The human ether-à-go-go-related gene (hERG) channel plays a crucial role in membrane repolarization. Any disruptions in its function can lead to severe cardiovascular disorders such as long QT syndrome (LQTS), which increases the risk of serious cardiovascular problems such as tachyarrhythmia and sudden cardiac death. Drug-induced LQTS is a significant concern and has resulted in drug withdrawals from the market in the past. The main objective of this study is to pinpoint crucial heteroatoms present in ligands that initiate interactions leading to the effective blocking of the hERG channel. To achieve this aim, ligand-based quantitative structure-activity relationships (QSAR) models were constructed using extensive ligand libraries, considering the heteroatom types and numbers, and their associated hERG channel blockage pIC50 values. Machine learning-assisted QSAR models were developed to analyze the key structural components influencing compound activity. Among the various methods, the KPLS method proved to be the most efficient, allowing the construction of models based on eight distinct fingerprints. The study delved into investigating the influence of heteroatoms on the activity of hERG blockers, revealing their significant role. Furthermore, by quantifying the effect of heteroatom types and numbers on ligand activity at the hERG channel, six compound pairs were selected for molecular docking. Subsequent molecular dynamics simulations and per residue MM/GBSA calculations were performed to comprehensively analyze the interactions of the selected pair compounds.

Rapid changes of mRNA expressions of cardiac ion channels affected by Torsadogenic drugs influence susceptibility of rat hearts to arrhythmias induced by Beta-Adrenergic stimulation.

Drug-induced long QT syndrome (LQTS) and Torsades de Pointes (TdP) are serious concerns in drug development. Although rats are a useful scientific tool, their hearts, unlike larger species, usually do not respond to torsadogenic drugs. Consequently, their resistance to drug-induced arrhythmias is poorly understood. Here, we challenged rats with rapid delayed rectifier current (Ikr)-inhibiting antibiotic clarithromycin (CLA), loop diuretic furosemide (FUR) or their combination (CLA + FUR), and examined functional and molecular abnormalities after stimulation with isoproterenol. Clarithromycin and furosemide were administered orally at 12-h intervals for 7 days. To evaluate electrical instability, electrocardiography (ECG) was recorded either in vivo or ex vivo using the Langendorff-perfused heart method under basal conditions and subsequently under beta-adrenergic stimulation. Gene expression was measured using real-time quantitative PCR in left ventricular tissue. Indeed, FUR and CLA + FUR rats exhibited hypokalemia. CLA and CLA + FUR treatment resulted in drug-induced LQTS and even an episode of TdP in one CLA + FUR rat. The combined treatment dysregulated gene expression of several ion channels subunits, including KCNQ1, calcium channels and Na+/K + -ATPase subunits, while both monotherapies had no impact. The rat with recorded TdP exhibited differences in the expression of ion channel genes compared to the rest of rats within the CLA + FUR group. The ECG changes were not detected in isolated perfused hearts. Hence, we report rapid orchestration of ion channel reprogramming of hearts with QT prolongation induced by simultaneous administration of clarithromycin and furosemide in rats, which may account for their ability to avoid arrhythmias triggered by beta-adrenergic stimulation.

Multifactorial model for prediction of the development of polymorphic ventricular tachycardia in patients with drug-induced QT interval prolongation induced by class III antiarrhythmic drugs

Aim. To develop a multifactorial model for predicting the development of polymorphic ventricular tachycardia (VT) in patients with drug-induced long QT syndrome (LQTS) induced by class III antiarrhythmic drugs (AADs) by identifying electrocardiographic, laboratory and molecular genetic predictors.Methods. The study included 64 patients (37 (57.9%) women and 27 (42.1%) men, mean age 57.2±9.4 years) with ischemic heart disease and/or arterial hypertension. and cardiac arrhythmias, in which drug-induced prolongation of the QTc interval (Bazett) (over 450 ms in men and over 470 ms in women) was noted with the use of class III AADs (amiodarone or sotalol) in a cardiac hospital. Depending on the presence or absence of non-sustained polymorphic VT according to 24-hour ECG Holter monitoring, patients were further divided into two groups: 17 patients with episodes of non-sustained polymorphic VT and 47 patients without such episodes. All patients underwent clinical and laboratory, instrumental and molecular genetic studies, which included taking an anamnesis, recording ECG in 12 leads, biochemical blood test, determining the levels of neuronal NO-synthase (NOS1) and the adapter protein of neuronal NO-synthase (NOS1AP) in blood serum by enzyme immunoassay, determination of nitric oxide synthase gene polymorphisms by polymerase chain reaction. To assess the relationship of the studied parameters with the achievement of the end point, the method of logistic regression with a binary response and the logit function of the connection was used.Results. To assess the risk of developing non-sustained polymorphic VT in patients with drug-induced LQTS while taking class III AADs, a complex binary logistic regression model was developed, including the following indicators: patient gender (p=0.019), relative variance of the QT interval (p=0.002), duration of the Tpeak-Tend interval, (p=0.034), serum magnesium (p=0.004) and NOS1 (p=0.004) levels, as well as the AA genotype of the G84A polymorphism of the NOS1 gene (p=0.049). With the calculated value of the threshold probability p≥0.48, the developed model makes it possible to identify patients at high risk of developing polymorphic VT in patients with drug-induced LQTS with a sensitivity of 94.12%, a specificity of 89.36%, and an area under the ROC curve of 0.977 (0.95-1.0, p<0.001).Conclusion. The developed complex model will allow predicting the risk of proarrhythmic effects in patients with drug-induced LQTS, which will lead to a decrease in the number of cardiovascular events in this category of patients.

The endocannabinoid ARA-S displays variably activating effects on Kv7.1/KCNE1 carrying long QT syndrome mutations.

The cardiac arrhythmia long QT syndrome (LQTS) is characterized by a delayed ventricular repolarization. The most common cause of inherited LQTS is loss-of-function mutations in the KV7.1/KCNE1 channel. Therefore, the KV7.1/KCNE1 channel is an interesting target for developing new antiarrhythmic drugs, which ideally would restore the function of mutated KV7.1/KCNE1 channels. In this study, we evaluate the endogenous endocannabinoid-like compound ARA-S as an activator of the human KV7.1/KCNE1 channel carrying diverse loss-of-function mutations linked to LQTS. Using the two-electrode voltage clamp technique, we have previously found ARA-S to facilitate activation of the wild type KV7.1/KCNE1 channel expressed in Xenopus oocytes, seen as a left-shift in voltage dependence of channel opening and a conductance increase. Moreover, we have previously shown that ARA-S restores a physiological QT interval in isolated guinea pig hearts suffering from drug-induced LQTS. Hence, ARA-S is an interesting endogenous KV7.1/KCNE1 channel modulator which may inspire drug development. Now, using the same technique on LQTS-mutated KV7.1/KCNE1 channels, we find that ARA-S facilitates activation of all tested mutants, but the magnitude of the effect varies among them. For instance, the effect of ARA-S is reduced on the mutant I204F but increased on the mutant A370V, compared to the effect on the wild-type channel. This suggests that the effect of the compound is dependent on the genetic background. To better understand its impact, we group the tested mutants based on their response to ARA-S and factors such as whether they are localized to putative ARA-S binding sites or other interesting sites, such as PIP2 sites. Altogether, this work finds ARA-S as an efficient activator of LQTS-associated mutant KV7.1/KCNE1 channels and is a first step towards understanding how the genetic background determines the effect of this modulator.

Interpretable Machine Learning Prediction of Drug-Induced QT Prolongation: Electronic Health Record Analysis.

Drug-induced long-QT syndrome (diLQTS) is a major concern among patients who are hospitalized, for whom prediction models capable of identifying individualized risk could be useful to guide monitoring. We have previously demonstrated the feasibility of machine learning to predict the risk of diLQTS, in which deep learning models provided superior accuracy for risk prediction, although these models were limited by a lack of interpretability. In this investigation, we sought to examine the potential trade-off between interpretability and predictive accuracy with the use of more complex models to identify patients at risk for diLQTS. We planned to compare a deep learning algorithm to predict diLQTS with a more interpretable algorithm based on cluster analysis that would allow medication- and subpopulation-specific evaluation of risk. We examined the risk of diLQTS among 35,639 inpatients treated between 2003 and 2018 with at least 1 of 39 medications associated with risk of diLQTS and who had an electrocardiogram in the system performed within 24 hours of medication administration. Predictors included over 22,000 diagnoses and medications at the time of medication administration, with cases of diLQTS defined as a corrected QT interval over 500 milliseconds after treatment with a culprit medication. The interpretable model was developed using cluster analysis (K=4 clusters), and risk was assessed for specific medications and classes of medications. The deep learning model was created using all predictors within a 6-layer neural network, based on previously identified hyperparameters. Among the medications, we found that class III antiarrhythmic medications were associated with increased risk across all clusters, and that in patients who are noncritically ill without cardiovascular disease, propofol was associated with increased risk, whereas ondansetron was associated with decreased risk. Compared with deep learning, the interpretable approach was less accurate (area under the receiver operating characteristic curve: 0.65 vs 0.78), with comparable calibration. In summary, we found that an interpretable modeling approach was less accurate, but more clinically applicable, than deep learning for the prediction of diLQTS. Future investigations should consider this trade-off in the development of methods for clinical prediction.

Oxytocin exerts harmful cardiac repolarization prolonging effects in drug-induced LQTS.

BackgroundOxytocin is used therapeutically in psychiatric patients. Many of these also receive anti-depressant or anti-psychotic drugs causing acquired long-QT-syndrome (LQTS) by blocking HERG/IKr. We previously identified an oxytocin-induced QT-prolongation in LQT2 rabbits, indicating potential harmful effects of combined therapy. We thus aimed to analyze the effects of dual therapy with oxytocin and fluoxetine/risperidone on cardiac repolarization.MethodsEffects of risperidone, fluoxetine and oxytocin on QT/QTc, short-term variability (STV) of QT, and APD were assessed in rabbits using in vivo ECG and ex vivo monophasic AP recordings in Langendorff-perfused hearts. Underlying mechanisms were assessed using patch clamp in isolated cardiomyocytes.ResultsOxytocin, fluoxetine and risperidone prolonged QTc and APD in whole hearts. The combination of fluoxetine + oxytocin resulted in further QTc- and APD-prolongation, risperidone + oxytocin tended to increase QTc and APD compared to monotherapy. Temporal QT instability, STVQTc was increased by oxytocin, fluoxetine / fluoxetine + oxytocin and risperidone / risperidone + oxytocin. Similar APD-prolonging effects were confirmed in isolated cardiomyocytes due to differential effects of the compounds on repolarizing ion currents: Oxytocin reduced IKs, fluoxetine and risperidone reduced IKr, resulting in additive effects on IKtotal-tail. In addition, oxytocin reduced IK1, further reducing the repolarization reserve.ConclusionOxytocin, risperidone and fluoxetine prolong QTc / APD. Combined treatment further prolongs QTc/APD due to differential effects on IKs and IK1 (block by oxytocin) and IKr (block by risperidone and fluoxetine), leading to pronounced impairment of repolarization reserve. Oxytocin should be used with caution in patients in the context of acquired LQTS.

Drug-Induced QT Interval Prolongation

The correct measurement of the QT interval (using the QT correction formulas, preferably Fridericia and Framingham) as well as a correct interpretation of the causes and of the clinical consequences of a QT prolongation is very important in clinical practice. Drug-induced long QT syndrome (DILQTS) is one of the most common causes of LQTS. In the diagnosis and management of the DILQTS, it can be useful to follow the three-step rule presented in this article: detailed pharmacological anamnesis and correct ECG interpretation; database search and clinical interpretation; confirmatory test.

Deep learning analysis of electrocardiogram for risk prediction of drug-induced arrhythmias and diagnosis of long QT syndrome.

Congenital long-QT syndromes (cLQTS) or drug-induced long-QT syndromes (diLQTS) can cause torsade de pointes (TdP), a life-threatening ventricular arrhythmia. The current strategy for the identification of drugs at the high risk of TdP relies on measuring the QT interval corrected for heart rate (QTc) on the electrocardiogram (ECG). However, QTc has a low positive predictive value. We used convolutional neural network (CNN) models to quantify ECG alterations induced by sotalol, an IKr blocker associated with TdP, aiming to provide new tools (CNN models) to enhance the prediction of drug-induced TdP (diTdP) and diagnosis of cLQTS. Tested CNN models used single or multiple 10-s recordings/patient using 8 leads or single leads in various cohorts: 1029 healthy subjects before and after sotalol intake (n = 14 135 ECGs); 487 cLQTS patients (n = 1083 ECGs: 560 type 1, 456 type 2, 67 type 3); and 48 patients with diTdP (n = 1105 ECGs, with 147 obtained within 48 h of a diTdP episode). CNN models outperformed models using QTc to identify exposure to sotalol [area under the receiver operating characteristic curve (ROC-AUC) = 0.98 vs. 0.72, P ≤ 0.001]. CNN models had higher ROC-AUC using multiple vs. single 10-s ECG (P ≤ 0.001). Performances were comparable for 8-lead vs. single-lead models. CNN models predicting sotalol exposure also accurately detected the presence and type of cLQTS vs. healthy controls, particularly for cLQT2 (AUC-ROC = 0.9) and were greatest shortly after a diTdP event and declining over time (P ≤ 0.001), after controlling for QTc and intake of culprit drugs. ECG segment analysis identified the J-Tpeak interval as the best discriminator of sotalol intake. CNN models applied to ECGs outperform QTc measurements to identify exposure to drugs altering the QT interval, congenital LQTS, and are greatest shortly after a diTdP episode.

Adverse drug event risk assessment by the virtual addition of COVID-19 repurposed drugs to Medicare and commercially insured patients' drug regimens: A drug safety simulation study.

Drug safety is generally established from clinical trials, by pharmacovigilance programs and during observational phase IV safety studies according to drug intended or approved indications. The objective of this study was to estimate the risk of potential adverse drug events (ADEs) associated with drugs repurposed for coronavirus disease 2019 (COVID‐19) treatment in a large‐scale population. Drug claims were used to calculate a baseline medication risk score (MRS) indicative of ADE risk level. Fictitious claims of repurposed drugs were added, one at a time, to patients’ drug regimens to calculate a new MRS and compute a level of risk. Drug claims data from enrollees with Regence health insurance were used and sub‐payer analyses were performed with Medicare and commercial insured groups. Simulated interventions were conducted with hydroxychloroquine and chloroquine, alone or combined with azithromycin, and lopinavir/ritonavir, along with terfenadine and fexofenadine as positive and negative controls for drug‐induced Long QT Syndrome (LQTS). There were 527,471 subjects (56.6% women; mean [SD] age, 47 years [21]) were studied. The simulated addition of each repurposed drug caused an increased risk of ADEs (median MRS increased by two‐to‐seven points, p < 0.001). The increase in ADE risk was mainly driven by an increase in CYP450 drug interaction risk score and by drug‐induced LQTS risk score. The Medicare group presented a greater risk overall compared to the commercial group. All repurposed drugs were associated with an increased risk of ADEs. Our simulation strategy could be used as a blueprint to preemptively assess safety associated with future repurposed or new drugs.

Community pharmacist use of mobile ECG to inform drug therapy decision making for patients receiving QTc prolonging medications

AbstractIntroductionFor patients using QTc prolonging medications, the health care system is challenged to mitigate the risk of drug‐induced long‐QT syndrome (DiLQTS) and sudden cardiac death (SCD). Community pharmacists (CPs) receive QTc alerts when dispensing but intervene infrequently. Personal electrocardiogram (ECG) monitors are a new, inexpensive technology that could provide additional patient risk information to identify individuals with a prolonged QTc interval in real time.Objectives(1) Describe QTc interval‐prolonging medications, QTc interval calculations, and associated interventions and prescriber responses for a CP‐delivered QTc interval assessment program, and (2) Describe patient satisfaction with the service.MethodsA prospective study of 9‐month duration in three community pharmacies in Iowa. CPs were trained to measure QTc interval using the KardiaMobile ECG monitor. English‐speaking patients aged ≥18 years were recruited to have a 30 seconds ECG tracing if the CP received a computer QTc‐related alert or had concern about QTc effect/interaction. CPs used professional judgment regarding prescriber contact but were required to contact the prescriber if the QTc interval was prolonged (&gt;470 ms males, &gt;480 ms females).ResultsThere were 53 patients who met study criteria and participated in the service. Mean age was 55.1 years, 38 (72%) were female, and 19 (36%) received newly prescribed QTc interval‐prolonging medications. A computer‐generated QTc alert was present for 36 (68%) of participants. CPs contacted a prescriber for 6 (11%) patients regarding concern for DiLQTS (mean QTc 495 ms). Of these six instances, three had QTc prolongation requiring mandatory prescriber contact (mean QTc 529 ms). Prescriber contact resulted in medication changes for 3 (50%) patients.ConclusionCPs were able to measure QTc interval, identify patients at risk for DiLQTS, and make accepted medication therapy recommendations related to QTc prolongation. CP assessment of QTc interval may be a useful approach to improve risk stratification of individuals at risk of DiLQTS and SCD.Trial registration: Clinical Trials.gov Identifier: NCT04000542.

Risk Assessment of Drug-Induced Long QT Syndrome for Some COVID-19 Repurposed Drugs.

The risk‐benefit ratio associated with the use of repurposed drugs to treat severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2)‐related infectious coronavirus disease 2019 (COVID‐19) is complicated because benefits are awaited, not proven. A thorough literature search was conducted to source information on the pharmacological properties of 5 drugs and 1 combination (azithromycin, chloroquine, favipiravir, hydroxychloroquine, remdesivir, and lopinavir/ritonavir) repurposed to treat COVID‐19. A risk assessment of drug‐induced long QT syndrome (LQTS) associated with COVID‐19 repurposed drugs was performed and compared with 23 well‐known torsadogenic and 10 low torsadogenic risk compounds. Computer calculations were performed using pharmacokinetic and pharmacodynamic data, including affinity to block the rapid component of the delayed rectifier cardiac potassium current (IKr) encoded by the human ether‐a‐go‐go gene (hERG), propensity to prolong cardiac repolarization (QT interval) and cause torsade de pointes (TdP). Seven different LQTS indices were calculated and compared. The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database was queried with specific key words relating to arrhythmogenic events. Estimators of LQTS risk levels indicated a very high or moderate risk for all COVID‐19 repurposed drugs with the exception for azithromycin, although cases of TdP have been reported with this drug. There was excellent agreement among the various indices used to assess risk of drug‐induced LQTS for the 6 repurposed medications and 23 torsadogenic compounds. Based on our results, monitoring of the QT interval shall be performed when some COVID‐19 repurposed drugs are used, as such monitoring is possible for hospitalized patients or with the use of biodevices for outpatients.

Functional Impact of BeKm-1, a High-Affinity hERG Blocker, on Cardiomyocytes Derived from Human-Induced Pluripotent Stem Cells.

IKr current, a major component of cardiac repolarization, is mediated by human Ether-à-go-go-Related Gene (hERG, Kv11.1) potassium channels. The blockage of these channels by pharmacological compounds is associated to drug-induced long QT syndrome (LQTS), which is a life-threatening disorder characterized by ventricular arrhythmias and defects in cardiac repolarization that can be illustrated using cardiomyocytes derived from human-induced pluripotent stem cells (hiPS-CMs). This study was meant to assess the modification in hiPS-CMs excitability and contractile properties by BeKm-1, a natural scorpion venom peptide that selectively interacts with the extracellular face of hERG, by opposition to reference compounds that act onto the intracellular face. Using an automated patch-clamp system, we compared the affinity of BeKm-1 for hERG channels with some reference compounds. We fully assessed its effects on the electrophysiological, calcium handling, and beating properties of hiPS-CMs. By delaying cardiomyocyte repolarization, the peptide induces early afterdepolarizations and reduces spontaneous action potentials, calcium transients, and contraction frequencies, therefore recapitulating several of the critical phenotype features associated with arrhythmic risk in drug-induced LQTS. BeKm-1 exemplifies an interesting reference compound in the integrated hiPS-CMs cell model for all drugs that may block the hERG channel from the outer face. Being a peptide that is easily modifiable, it will serve as an ideal molecular platform for the design of new hERG modulators displaying additional functionalities.

Risk of Adverse Drug Events Following the Virtual Addition of COVID-19 Repurposed Drugs to Drug Regimens of Frail Older Adults with Polypharmacy.

Determination of the risk–benefit ratio associated with the use of novel coronavirus disease 2019 (COVID-19) repurposed drugs in older adults with polypharmacy is mandatory. Our objective was to develop and validate a strategy to assess risk for adverse drug events (ADE) associated with COVID-19 repurposed drugs using hydroxychloroquine (HCQ) and chloroquine (CQ), alone or in combination with azithromycin (AZ), and the combination lopinavir/ritonavir (LPV/r). These medications were virtually added, one at a time, to drug regimens of 12,383 participants of the Program of All-Inclusive Care for the Elderly. The MedWise Risk Score (MRSTM) was determined from 198,323 drug claims. Results demonstrated that the addition of each repurposed drug caused a rightward shift in the frequency distribution of MRSTM values (p < 0.05); the increase was due to an increase in the drug-induced Long QT Syndrome (LQTS) or CYP450 drug interaction burden risk scores. Increases in LQTS risk observed with HCQ + AZ and CQ + AZ were of the same magnitude as those estimated when terfenadine or terfenadine + AZ, used as positive controls for drug-induced LQTS, were added to drug regimens. The simulation-based strategy performed offers a way to assess risk of ADE for drugs to be used in people with underlying medical comorbidities and polypharmacy at risk of COVID-19 infection without exposing them to these drugs.

Proarrhythmic proclivity of left-stellate ganglion stimulation in a canine model of drug-induced long-QT syndrome type 1

BackgroundLeft-stellate ganglion stimulation (LSGS) can modify regional dispersion of ventricular refractoriness, promote triggered activity, and reduce the threshold for ventricular fibrillation (VF). Sympathetic hyperactivity precipitates torsades de pointes (TdP) and VF in susceptible patients with long-QT syndrome type 1 (LQT1). We investigated the electromechanical effects of LSGS in a canine model of drug-induced LQT1, gaining novel arrhythmogenic insights. MethodsIn nine mongrel dogs, the left and right stellate ganglia were exposed for electrical stimulation. ECG, left- and right-ventricular endocardial monophasic action potentials (MAPs) and pressures (LVP, RVP) were recorded. The electromechanical window (EMW; Q to LVP at 90% relaxation minus QT interval) was calculated. LQT1 was mimicked by infusion of the KCNQ1/IKs blocker HMR1556. ResultsAt baseline, LSGS and right-stellate ganglion stimulation (RSGS) caused similar heart-rate acceleration and QT shortening. Positive inotropic and lusitropic effects were more pronounced under LSGS than RSGS. IKs blockade prolonged QTc, triggered MAP-early afterdepolarizations (EADs) and rendered the EMW negative, but no ventricular tachyarrhythmias occurred. Superimposed LSGS exaggerated EMW negativity and evoked TdP in 5/9 dogs within 30 s. Preceding extrasystoles originated mostly from the outflow-tracts region. TdP deteriorated into therapy-refractory VF in 4/5 animals. RSGS did not provoke TdP/VF. ConclusionsIn this model of drug-induced LQT1, LSGS readily induced TdP and VF during repolarization prolongation and MAP-EAD generation, but only if EMW turned from positive to very negative. We postulate that altered mechano-electric coupling can exaggerate regional dispersion of refractoriness and facilitates ventricular ectopy.

A wearable remote monitoring system for the identification of subjects with a prolonged QT interval or at risk for drug-induced long QT syndrome

BackgroundA correct measurement of the QT interval in the out-of-hospital setting is important whenever the long QT syndrome (LQTS) is suspected or a therapy might lead to drug-induced LQTS (diLQTS) because QT interval monitoring in the initial days of therapy could alert to dangerous QT prolongation. We explored whether automated QTc measurements (BGM) by BodyGuardian™ (BG), a wearable remote monitoring system, are sufficiently reliable compared to our own manual measurements (MM) performed on the same beats during 12‑lead Holter recordings in LQTS patients (pts) and in healthy controls. MethodsWe performed 351 measurements in 20 LQTS pts and 16 controls. MM and BGM were compared by a Bland-Altman plot (BAp). High values of BAp indicate large differences between measurements. ResultsIn all 36 subjects QTc was 446 ± 41 and 445 ± 47 ms in MM and BGM, respectively. The mean ± SE BAp was −1.4 ± 1.8 ms for QTc in all subjects, 8.3 ± 2.3 and −7.2 ± 2.5 ms respectively in controls and LQTS. The disagreement between BGM and MM <15 ms in all, in controls, and in LQTS was respectively 57%, 63% and 54%. Among controls, there were only 3/132 false positive measurements (BGM QTc >470 ms when MM QTc <440 ms) in 3 different subjects. Among LQTS, there were 10/219 false negative measurements (BGM QTc <440 ms when MM QTc >470 ms) in 6 pts, but only two had multiple false negative values. ConclusionsThis wearable monitoring system reliably identifies a prolonged QT interval and probably also subjects at risk for diLQTS.

Cardiovascular Safety of Psychiatric Agents: A Cautionary Tale.

Psychiatric agents are among the most commonly prescribed medications. Despite the advent of newer generation agents, patients receiving them still experience cardiovascular (CV) side effects. However, these agents may have heterogeneous properties, calling for an individualized approach based on efficacy and also on the particular side effect profile of each specific agent. Proarrhythmic effects arising from drug-induced long-QT syndrome and consequent potentially life-threatening polymorphic ventricular arrhythmias in the form of torsade de pointes, the metabolic syndrome contributing to atherosclerosis and acute coronary syndromes, and drug-induced orthostatic hypotension raise major concerns. Of course, it is also crucial that fear of potential CV adverse effects does not deprive psychiatric patients of appropriate drug therapy. Modification of CV risk factors in psychiatric patients together with optimal management of their CV diseases and appropriate selection of psychotropic agents with greater efficacy and least CV toxicity are of paramount importance in mitigating CV risks and enhancing safety. Identifying patients at high risk of CV complications and close monitoring of all patients receiving these agents are crucial steps to prevent and manage such complications. All these issues are herein reviewed, relevant guidelines are discussed, and schemas are depicted that illustrate the interrelated connections among the psychotropic agents and their CV effects.

Acquired long QT syndrome and torsade de pointes.

Since its initial description by Jervell and Lange-Nielsen in 1957, the congenital long QT syndrome (LQTS) has been the most investigated cardiac ion channelopathy. Although congenital LQTS continues to remain the domain of cardiologists, cardiac electrophysiologists, and specialized centers, the by far more frequent acquired drug-induced LQTS is the domain of all physicians and other members of the health care team who are required to make therapeutic decisions. This report will review the electrophysiological mechanisms of LQTS and torsade de pointes, electrocardiographic characteristics of acquired LQTS, its clinical presentation, management, and future directions in the field.

F463L increases the potential of dofetilide on human ether-a-go-go-related gene (hERG) channels.

Mutations in genes related to long QT syndrome (LQTS) is recognized as an independent risk of drug-induced LQTS. We previously screened a mutation F463L in a Chinese patient with LQT2, syncope, and epilepsy. Here, we planned to illustrate how F463L influences the action of dofetilide on hERG channels. F463L-hERG plasmids were transfected into the stable Human Embryonic Kidney 293 (HEK293) cells expressing WT-hERG to generate heterozygous mutant (WT + F463L-hERG). Whole-cell patch clamp and laser confocal scanning microscopy were used to evaluate electrophysiological consequences and the membrane distribution of hERG protein. In comparison of WT-hERG channels exposed to dofetilide, heterozygous F463L-hERG channels showed a reduction in the density of tail currents when exposed amidarone. F463L-hERG also altered the action of dofetilide on the gating properties of hERG channels. Images of dofetilide-treated cells expressing heterozygous F463L showed a severe retention and reduction of protein expression on the membrane compared to WT. In conclusion, dofetilide displays a powerful inhibitory effect on the currents from cells expressing heterozygous F463L, thus showing an additive suppression of currents by F463L with dofetilide.