Assays of Variant Effect and Automated Patch Clamping Improve KCNH2-LQTS Variant Classification and Cardiac Event Risk Stratification.

BACKGROUND: Long QT syndrome is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by KCNH2. Variant classification is difficult, often because of lack of functional data. Moreover, variant-based risk stratification is also complicated by heterogenous clinical data and incomplete penetrance. Here we sought to test whether variant-specific information, primarily from high-throughput functional assays, could improve both classification and cardiac event risk stratification in a large, harmonized cohort of KCNH2 missense variant heterozygotes. METHODS: We quantified cell-surface trafficking of 18 796 variants in KCNH2 using a multiplexed assay of variant effect (MAVE). We recorded KCNH2 current density for 533 variants by automated patch clamping. We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1458 patients with KCNH2 missense variants, including QTc, cardiac event history, and mortality. We correlated variant functional data and Bayesian long QT syndrome penetrance estimates with cohort phenotypes and assessed hazard ratios for cardiac events. RESULTS: Variant MAVE trafficking scores and automated patch clamping peak tail currents were highly correlated (Spearman rank-order ρ=0.69; n=433). The MAVE data were found to provide up to pathogenic very strong evidence for severe loss-of-function variants. In the cohort, both functional assays and Bayesian long QT syndrome penetrance estimates were significantly predictive of cardiac events when independently modeled with patient sex and adjusted QT interval (QTc); however, MAVE data became nonsignificant when peak tail current and penetrance estimates were also available. The area under the receiver operator characteristic curve for 20-year event outcomes based on patient-specific sex and QTc (area under the curve, 0.80 [0.76-0.83]) was improved with prospectively available penetrance scores conditioned on MAVE (area under the curve, 0.86 [0.83-0.89]) or attainable automated patch clamping peak tail current data (area under the curve, 0.84 [0.81-0.88]). CONCLUSIONS: High-throughput KCNH2 variant MAVE data meaningfully contribute to variant classification at scale, whereas long QT syndrome penetrance estimates and automated patch clamping peak tail current measurements meaningfully contribute to risk stratification of cardiac events in patients with heterozygous KCNH2 missense variants.

Calmodulin variant E140G associated with long QT syndrome impairs CaMKIIδ autophosphorylation and L-type calcium channel inactivation.

Long QT syndrome (LQTS) is a human inherited heart condition that can cause life-threatening arrhythmia including sudden cardiac death. Mutations in the ubiquitous Ca2+-sensing protein calmodulin (CaM) are associated with LQTS, but the molecular mechanism by which these mutations lead to irregular heartbeats is not fully understood. Here, we use a multidisciplinary approach including protein biophysics, structural biology, confocal imaging, and patch-clamp electrophysiology to determine the effect of the disease-associated CaM mutation E140G on CaM structure and function. We present novel data showing that mutant-regulated CaMKIIδ kinase activity is impaired with a significant reduction in enzyme autophosphorylation rate. We report the first high-resolution crystal structure of a LQTS-associated CaM variant in complex with the CaMKIIδ peptide, which shows significant structural differences, compared to the WT complex. Furthermore, we demonstrate that the E140G mutation significantly disrupted Cav1.2 Ca2+/CaM-dependent inactivation, while cardiac ryanodine receptor (RyR2) activity remained unaffected. In addition, we show that the LQTS-associated mutation alters CaM's Ca2+-binding characteristics, secondary structure content, and interaction with key partners involved in excitation-contraction coupling (CaMKIIδ, Cav1.2, RyR2). In conclusion, LQTS-associated CaM mutation E140G severely impacts the structure-function relationship of CaM and its regulation of CaMKIIδ and Cav1.2. This provides a crucial insight into the molecular factors contributing to CaM-mediated arrhythmias with a central role for CaMKIIδ.

Uncovering possible silent acquired long QT syndrome using exercise stress testing in long-term pediatric acute lymphoblastic leukemia survivors.

An example of chemotherapy-induced cardiotoxicity in cancer survivors is acquired long QT syndrome (aLQTS), which may cause serious yet preventable life-threatening consequences. Our objective was to identify and characterize childhood acute lymphoblastic leukemia (ALL) survivors with possible aLQTS using maximal exercise testing. In this cross-sectional study with exploratory analysis, a total of 250 childhood ALL survivors were evaluated for abnormal QT interval prolongation using the McMaster cycle exercise test. A total of 198 survivors (102 males; 96 females), having reached their V ̇ O 2 $$ \dot{\mathrm{V}}{\mathrm{O}}_2 $$ peak (mean 32.1 ± 8.4 mL/kg/min; range 15.5-57.8 mL/kg/min), were included in our analyses. Two survivors were excluded for possible congenital LQTS. QT intervals were corrected for heart rate using the Bazett, Fridericia, and Rautaharju formulas at rest (supine, sitting, and standing positions), at the end of each stage of the CPET, and at 1, 3, and 5 minutes into the recovery period. The corrected QT (QTc) of borderline (n = 37) and long QT survivors (n = 20) was significantly longer than normal survivors (n = 141) at rest, exercise, and recovery. Out of 57 survivors presenting an abnormal QTc prolongation, 40 survivors (70%) showed no QT interval anomalies at rest but developed various anomalies during exercise. No significant differences were found between the groups for any of the measured clinical characteristics or cardiac parameters. The standardization of exercise testing in the regular follow-up of oncology patients is necessary for appropriate cardiac prevention and surveillance to enhance the health and quality of life of the ever-increasing number of cancer survivors.

Molecular genetics in 1991 arrhythmia probands and 2782 relatives in Norway: Results from 17 years of genetic testing in a national laboratory.

The aim of this study was to explore the prevalence of likely pathogenic or pathogenic variants and assess the diagnostic yield from genetic testing for cardiac arrhythmias in Norway since 2003. Data from 1991 probands and 2782 relatives were retrospectively collected from the laboratory information management system at Unit for Cardiac and Cardiovascular Genetics, Oslo University hospital. Of 1991 probands, 57.4% were females, age at genetic testing was 33.1 (±22.7) years, and 32.5% were under the age of 18. A likely pathogenic or pathogenic variant (including 14 novel) was detected in 15.4% in total. Of the 2782 relatives, 53.7% were females, age at genetic testing was 35.6 (±22.5) years, 27.3% were under the age of 18, and 45.3% carried the family variant. Probands and relatives combined, 1/3356 persons in the Norwegian population were heterozygous for an arrhythmia-causing variant. The founder variant p.Q530X (NM_000218.2: c.1588C>T) in KCNQ1 accounted for 34% of all variants in Norway. In conclusion, genetic testing provided a genetic basis of the arrhythmia in 15.4% of the probands. Familial cascade screening identified four times as many variant-positive relatives, allowing early detection and prompt stratification of arrhythmic risk of those variant carriers.

Proceed with caution: Standard protocol exercise stress tests fail to replicate the diagnostic utility of supine-stand tests for long QT syndrome.

BACKGROUND: Long QT syndrome (LQTS) is a sudden death predisposing condition characterized by ECG-derived prolongation of the QT interval. Previous studies have demonstrated that the supine-stand test may aid in the diagnosis of LQTS as patients fail to shorten their QT interval in response to standing up. The aim of this study was to evaluate the diagnostic accuracy of ECG data derived from standard protocol, clinically performed treadmill exercise stress tests (TESTs) in their ability to mimic the formal supine-stand test. METHODS: We performed a retrospective review of 478 TESTs from patients evaluated for LQTS. Patients referred for evaluation of LQTS but who were dismissed as normal served as controls. Heart rate & QT values were obtained from standard protocol TESTs. RESULTS: Overall, 243 patients with LQTS (125 LQT1, 63 LQT2, 55 LQT3; 146 [60%] female, mean age at TEST 30 ± 17 years) and 235 controls (142 [60%] female, mean age 24 ± 15 years) were included. The paired ΔQTc (QTcStand -QTcSupine ) was similar between LQTS (-5 ± 26) and controls (-2 ± 25; p = .2). During position change, the QT interval shortened by ≥20 ms in 33% of LQTS patients, remained unchanged in 62%, and increased in 5% of LQTS patients which was similar to controls (shortened in 40%, unchanged in 54%, and increased in 6% of controls; p = .2). Receiver-operator curve analysis to test the diagnostic ability of supine-stand ΔQT performed poorly in differentiating LQTS from controls with an of AUC 0.52 (p = .4). CONCLUSION: TESTs should be used with caution when trying to interpret supine-stand changes for diagnosis of LQTS.

Human Genetics of Cardiac Arrhythmias.

Inherited forms of cardiac arrhythmias mostly are rare diseases (prevalence <1:2000) and considered to be either "primary electrical heart disorders" due to the absence of structural heart abnormalities or "cardiac ion channel disorders" due to the myocellular structures involved. Precise knowledge of the electrocardiographic features of these diseases and their genetic classification will enable early disease recognition and prevention of cardiac events including sudden cardiac death.The genetic background of these diseases is complex and heterogeneous. In addition to the predominant "private character" of a mutation in each family, locus heterogeneity involving many ion channel genes for the same familial arrhythmia syndrome is typical. Founder pathogenic variants or mutational hot spots are uncommon. Moreover, phenotypes may vary and overlap even within the same family and mutation carriers. For the majority of arrhythmias, the clinical phenotype of an ion channel mutation is restricted to cardiac tissue, and therefore, the disease is nonsyndromic.Recent and innovative methods of parallel DNA analysis (so-called next-generation sequencing, NGS) will enhance further mutation and other variant detection as well as arrhythmia gene identification.

Molecular Pathways and Animal Models of Arrhythmias.

Arrhythmias account for over 300,000 annual deaths in the United States, and approximately half of all deaths are associated with heart disease. Mechanisms underlying arrhythmia risk are complex; however, work in humans and animal models over the past 25 years has identified a host of molecular pathways linked with both arrhythmia substrates and triggers. This chapter will focus on select arrhythmia pathways solved by linking human clinical and genetic data with animal models.

Conformation-sensitive antibody reveals an altered cytosolic PAS/CNBh assembly during hERG channel gating.

The human ERG (hERG) K+ channel has a crucial function in cardiac repolarization, and mutations or channel block can give rise to long QT syndrome and catastrophic ventricular arrhythmias. The cytosolic assembly formed by the Per-Arnt-Sim (PAS) and cyclic nucleotide binding homology (CNBh) domains is the defining structural feature of hERG and related KCNH channels. However, the molecular role of these two domains in channel gating remains unclear. We have previously shown that single-chain variable fragment (scFv) antibodies can modulate hERG function by binding to the PAS domain. Here, we mapped the scFv2.12 epitope to a site overlapping with the PAS/CNBh domain interface using NMR spectroscopy and mutagenesis and show that scFv binding in vitro and in the cell is incompatible with the PAS interaction with CNBh. By generating a fluorescently labeled scFv2.12, we demonstrate that association with the full-length hERG channel is state dependent. We detect Förster resonance energy transfer (FRET) with scFv2.12 when the channel gate is open but not when it is closed. In addition, state dependence of scFv2.12 FRET signal disappears when the R56Q mutation, known to destabilize the PAS-CNBh interaction, is introduced in the channel. Altogether, these data are consistent with an extensive structural alteration of the PAS/CNBh assembly when the cytosolic gate opens, likely favoring PAS domain dissociation from the CNBh domain.

Calmodulin mutation in long QT syndrome 15 associated with congenital heart defects further complicated by a functional 2:1 atrioventricular block: Management from foetal life to postpartum.

We report a long QT syndrome 15 whose diagnosis was suspected during foetal life and confirmed at birth and was associated with congenital heart disease. Genetic testing revealed a rare mutation associated with the CALM2 gene. At 23 weeks of gestation, severe foetal sinus bradycardia (∼100 bpm) was detected. In the third trimester, the foetus developed severe right ventricular hypertrophy. At birth, the electrocardiogram showed a long QT interval of 640 ms, and after 1 hour, the newborn showed functional 2:1 atrioventricular block at ventricular rate of 50 bpm. After further pharmacological therapies, epicardial wires were surgically implanted for transient pacing in VVI mode at 90 bpm. Echocardiogram showed aneurysmatic left atrial appendage, dilated right segments, hypertrophied right ventricle, ostium secundum type atrial septal defect, and muscular ventricular septal defect. At two weeks of postpartum, a permanent dual-chamber pacemaker was implanted in the DDD mode and the patient was discharged with a prescription of beta-blockers and calcium therapy.

Prediction of Kv11.1 potassium channel PAS-domain variants trafficking via machine learning.

Congenital long QT syndrome (LQTS) is characterized by a prolonged QT-interval on an electrocardiogram (ECG). An abnormal prolongation in the QT-interval increases the risk for fatal arrhythmias. Genetic variants in several different cardiac ion channel genes, including KCNH2, are known to cause LQTS. Here, we evaluated whether structure-based molecular dynamics (MD) simulations and machine learning (ML) could improve the identification of missense variants in LQTS-linked genes. To do this, we investigated KCNH2 missense variants in the Kv11.1 channel protein shown to have wild type (WT) like or class II (trafficking-deficient) phenotypes in vitro. We focused on KCNH2 missense variants that disrupt normal Kv11.1 channel protein trafficking, as it is the most common phenotype for LQTS-associated variants. Specifically, we used computational techniques to correlate structural and dynamic changes in the Kv11.1 channel protein PAS domain (PASD) with Kv11.1 channel protein trafficking phenotypes. These simulations unveiled several molecular features, including the numbers of hydrating waters and hydrogen bonding pairs, as well as folding free energy scores, that are predictive of trafficking. We then used statistical and machine learning (ML) (Decision tree (DT), Random forest (RF), and Support vector machine (SVM)) techniques to classify variants using these simulation-derived features. Together with bioinformatics data, such as sequence conservation and folding energies, we were able to predict with reasonable accuracy (≈75%) which KCNH2 variants do not traffic normally. We conclude that structure-based simulations of KCNH2 variants localized to the Kv11.1 channel PASD led to an improvement in classification accuracy. Therefore, this approach should be considered to complement the classification of variant of unknown significance (VUS) in the Kv11.1 channel PASD.

Long QT syndrome-associated calmodulin variants disrupt the activity of the slowly activating delayed rectifier potassium channel.

Calmodulin (CaM) is a highly conserved mediator of calcium (Ca2+ )-dependent signalling and modulates various cardiac ion channels. Genotyping has revealed several CaM mutations associated with long QT syndrome (LQTS). LQTS patients display prolonged ventricular recovery times (QT interval), increasing their risk of incurring life-threatening arrhythmic events. Loss-of-function mutations to Kv7.1 (which drives the slow delayed rectifier potassium current, IKs, a key ventricular repolarising current) are the largest contributor to congenital LQTS (>50% of cases). CaM modulates Kv7.1 to produce a Ca2+ -sensitive IKs, but little is known about the consequences of LQTS-associated CaM mutations on Kv7.1 function. Here, we present novel data characterising the biophysical and modulatory properties of three LQTS-associated CaM variants (D95V, N97I and D131H). We showed that mutations induced structural alterations in CaM and reduced affinity for Kv7.1, when compared with wild-type (WT). Using HEK293T cells expressing Kv7.1 channel subunits (KCNQ1/KCNE1) and patch-clamp electrophysiology, we demonstrated that LQTS-associated CaM variants reduced current density at systolic Ca2+ concentrations (1 µm), revealing a direct QT-prolonging modulatory effect. Our data highlight for the first time that LQTS-associated perturbations to CaM's structure impede complex formation with Kv7.1 and subsequently result in reduced IKs. This provides a novel mechanistic insight into how the perturbed structure-function relationship of CaM variants contributes to the LQTS phenotype. KEY POINTS: Calmodulin (CaM) is a ubiquitous, highly conserved calcium (Ca2+ ) sensor playing a key role in cardiac muscle contraction. Genotyping has revealed several CaM mutations associated with long QT syndrome (LQTS), a life-threatening cardiac arrhythmia syndrome. LQTS-associated CaM variants (D95V, N97I and D131H) induced structural alterations, altered binding to Kv7.1 and reduced IKs. Our data provide a novel mechanistic insight into how the perturbed structure-function relationship of CaM variants contributes to the LQTS phenotype.

Investigation of PAS and CNBH domain interactions in hERG channels and effects of long-QT syndrome-causing mutations with surface plasmon resonance.

Human ether-á-go-go-related gene (hERG) channels are key regulators of cardiac repolarization, neuronal excitability, and tumorigenesis. hERG channels contain N-terminal Per-Arnt-Sim (PAS) and C-terminal cyclic nucleotide-binding homology (CNBH) domains with many long-QT syndrome (LQTS)-causing mutations located at the interface between these domains. Despite the importance of PAS/CNBH domain interactions, little is known about their affinity. Here, we used the surface plasmon resonance (SPR) technique to investigate interactions between isolated PAS and CNBH domains and the effects of LQTS-causing mutations R20G, N33T, and E58D, located at the PAS/CNBH domain interface, on these interactions. We determined that the affinity of the PAS/CNBH domain interactions was ∼1.4 µM. R20G and E58D mutations had little effect on the domain interaction affinity, while N33T abolished the domain interactions. Interestingly, mutations in the intrinsic ligand, a conserved stretch of amino acids occupying the beta-roll cavity in the CNBH domain, had little effect on the affinity of PAS/CNBH domain interactions. Additionally, we determined that the isolated PAS domains formed oligomers with an interaction affinity of ∼1.6 µM. Coexpression of the isolated PAS domains with the full-length hERG channels or addition of the purified PAS protein inhibited hERG currents. These PAS/PAS interactions can have important implications for hERG function in normal and pathological conditions associated with increased surface density of channels or interaction with other PAS-domain-containing proteins. Taken together, our study provides the first account of the binding affinities for wild-type and mutant hERG PAS and CNBH domains and highlights the potential functional significance of PAS/PAS domain interactions.

Precision medicine for long QT syndrome: patient-specific iPSCs take the lead.

Long QT syndrome (LQTS) is a detrimental arrhythmia syndrome mainly caused by dysregulated expression or aberrant function of ion channels. The major clinical symptoms of ventricular arrhythmia, palpitations and syncope vary among LQTS subtypes. Susceptibility to malignant arrhythmia is a result of delayed repolarisation of the cardiomyocyte action potential (AP). There are 17 distinct subtypes of LQTS linked to 15 autosomal dominant genes with monogenic mutations. However, due to the presence of modifier genes, the identical mutation may result in completely different clinical manifestations in different carriers. In this review, we describe the roles of various ion channels in orchestrating APs and discuss molecular aetiologies of various types of LQTS. We highlight the usage of patient-specific induced pluripotent stem cell (iPSC) models in characterising fundamental mechanisms associated with LQTS. To mitigate the outcomes of LQTS, treatment strategies are initially focused on small molecules targeting ion channel activities. Next-generation treatments will reap the benefits from development of LQTS patient-specific iPSC platform, which is bolstered by the state-of-the-art technologies including whole-genome sequencing, CRISPR genome editing and machine learning. Deep phenotyping and high-throughput drug testing using LQTS patient-specific cardiomyocytes herald the upcoming precision medicine in LQTS.

Computational Study on Effect of KCNQ1 P535T Mutation in a Cardiac Ventricular Tissue.

Heart diseases such as arrhythmia are the main causes of sudden death. Arrhythmias are typically caused by mutations in specific genes, damage in the cardiac tissue, or due to some chemical exposure. Arrhythmias caused due to mutation is called inherited arrhythmia. Induced arrhythmias are caused due to tissue damage or chemical exposure. Mutations in genes that encode ion channels of the cardiac cells usually result in (dysfunction) improper functioning of the channel. Improper functioning of the ion channel may lead to major changes in the action potential (AP) of the cardiac cells. This further leads to distorted electrical activity of the heart. Distorted electrical activity will affect the ECG that results in arrhythmia. KCNQ1 P535T mutation is one such gene mutation that encodes the potassium ion channel (KV7.1) of the cardiac ventricular tissue. Its clinical significance is not known. This study aims to perform a simulation study on P535T mutation in the KCNQ1 gene that encodes the potassium ion channel KV7.1 in the ventricular tissue grid. The effect of P535T mutation on transmural tissue grids for three genotypes (wild type, heterozygous, and homozygous) of cells are studied and the generated pseudo-ECGs are compared. Results show the delayed repolarization in the cells of ventricular tissue grid. Slower propagation of action potential in the transmural tissue grid is observed in the mutated (heterozygous and homozygous) genotypes. Longer QT interval is also observed in the pseudo-ECG of heterozygous and homozygous genotype tissue grids. From the pseudo-ECGs, it is observed that KCNQ1 P535T mutation leads to Long QT Syndrome (LQTS) which may result in life-threatening arrhythmias, such as Torsade de Pointes (TdP), Jervell and Lange-Nielsen syndrome (JLNS), and Romano-Ward syndrome (RWS).

Gene- and variant-specific efficacy of serum/glucocorticoid-regulated kinase 1 inhibition in long QT syndrome types 1 and 2.

AIMS: Current long QT syndrome (LQTS) therapy, largely based on beta-blockade, does not prevent arrhythmias in all patients; therefore, novel therapies are warranted. Pharmacological inhibition of the serum/glucocorticoid-regulated kinase 1 (SGK1-Inh) has been shown to shorten action potential duration (APD) in LQTS type 3. We aimed to investigate whether SGK1-Inh could similarly shorten APD in LQTS types 1 and 2. METHODS AND RESULTS: Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and hiPSC-cardiac cell sheets (CCS) were obtained from LQT1 and LQT2 patients; CMs were isolated from transgenic LQT1, LQT2, and wild-type (WT) rabbits. Serum/glucocorticoid-regulated kinase 1 inhibition effects (300 nM-10 µM) on field potential durations (FPD) were investigated in hiPSC-CMs with multielectrode arrays; optical mapping was performed in LQT2 CCS. Whole-cell and perforated patch clamp recordings were performed in isolated LQT1, LQT2, and WT rabbit CMs to investigate SGK1-Inh (3 µM) effects on APD. In all LQT2 models across different species (hiPSC-CMs, hiPSC-CCS, and rabbit CMs) and independent of the disease-causing variant (KCNH2-p.A561V/p.A614V/p.G628S/IVS9-28A/G), SGK1-Inh dose-dependently shortened FPD/APD at 0.3-10 µM (by 20-32%/25-30%/44-45%). Importantly, in LQT2 rabbit CMs, 3 µM SGK1-Inh normalized APD to its WT value. A significant FPD shortening was observed in KCNQ1-p.R594Q hiPSC-CMs at 1/3/10 µM (by 19/26/35%) and in KCNQ1-p.A341V hiPSC-CMs at 10 µM (by 29%). No SGK1-Inh-induced FPD/APD shortening effect was observed in LQT1 KCNQ1-p.A341V hiPSC-CMs or KCNQ1-p.Y315S rabbit CMs at 0.3-3 µM. CONCLUSION: A robust SGK1-Inh-induced APD shortening was observed across different LQT2 models, species, and genetic variants but less consistently in LQT1 models. This suggests a genotype- and variant-specific beneficial effect of this novel therapeutic approach in LQTS.

The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review.

INTRODUCTION: QTc prolongation is key in diagnosing long QT syndrome (LQTS), however 25%-50% with congenital LQTS (cLQTS) demonstrate a normal resting QTc. T wave morphology (TWM) can distinguish cLQTS subtypes but its role in acquired LQTS (aLQTS) is unclear. METHODS: Electronic databases were searched using the terms "LQTS," "long QT syndrome," "QTc prolongation," "prolonged QT," and "T wave," "T wave morphology," "T wave pattern," "T wave biomarkers." Whole text articles assessing TWM, independent of QTc, were included. RESULTS: Seventeen studies met criteria. TWM measurements included T-wave amplitude, duration, magnitude, Tpeak-Tend, QTpeak, left and right slope, center of gravity (COG), sigmoidal and polynomial classifiers, repolarizing integral, morphology combination score (MCS) and principal component analysis (PCA); and vectorcardiographic biomarkers. cLQTS were distinguished from controls by sigmoidal and polynomial classifiers, MCS, QTpeak, Tpeak-Tend, left slope; and COG x axis. MCS detected aLQTS more significantly than QTc. Flatness, asymmetry and notching, J-Tpeak; and Tpeak-Tend correlated with QTc in aLQTS. Multichannel block in aLQTS was identified by early repolarization (ERD30% ) and late repolarization (LRD30% ), with ERD reflecting hERG-specific blockade. Cardiac events were predicted in cLQTS by T wave flatness, notching, and inversion in leads II and V5 , left slope in lead V6 ; and COG last 25% in lead I. T wave right slope in lead I and T-roundness achieved this in aLQTS. CONCLUSION: Numerous TWM biomarkers which supplement QTc assessment were identified. Their diagnostic capabilities include differentiation of genotypes, identification of concealed LQTS, differentiating aLQTS from cLQTS; and determining multichannel versus hERG channel blockade.

Genome Editing and Inherited Cardiac Arrhythmias.

Inherited arrhythmic disorders are a group of heterogeneous diseases predisposing to life-threatening arrhythmias and sudden cardiac death. Their diagnosis is not always simple due to incomplete penetrance and genetic heterogeneity. Furthermore, the available treatments are usually invasive and merely preventive. Genome editing and especially CRISPR/Cas9 technologies have the potential to correct the genetic arrhythmogenic substrate, thereby offering a cure for these fatal diseases. To date, genome editing has allowed reproducing cardiac arrhythmias in vitro, providing a robust platform for variant pathogenicity, mechanistic, and drug-testing studies. However, in vivo approaches still need profound research regarding safety, specificity, and efficiency of the methods.

Personalized, intuitive & visual QT-prolongation monitoring using patient-specific QTc threshold with pseudo-coloring and explainable AI.

BACKGROUND: Drug-induced QT-prolongation increases the risk of TdP arrhythmia attacks and sudden cardiac death. However, measuring the QT-interval and determining a precise cut-off QT/QTc value that could put a patient at risk of TdP is challenging and influenced by many factors including female sex, drug-free baseline, age, genetic predisposition, and bradycardia. OBJECTIVES: This paper presents a novel approach for intuitively and visually monitoring QT-prolongation showing a potential risk of TdP, which can be adjusted according to patient-specific risk factors, using a pseudo-coloring technique and explainable artificial intelligence (AI). METHODS: We extended the development and evaluation of an explainable AI-based technique- visualized using pseudo-color on the ECG signal, thus intuitively 'explaining' how its decision was made -to detect QT-prolongation showing a potential risk of TdP according to a cut-off personalized QTc value (using Bazett's ∆QTc > 60 ms relative to drug-free baseline and Bazett's QTc > 500 ms as examples), and validated its performance using a large number of ECGs (n = 5050), acquired from a clinical trial assessing the effects of four known QT-prolonging drugs versus placebo on healthy subjects. We compared this new personalized approach to our previous study that used a more general approach using the QT-nomogram. RESULTS AND CONCLUSIONS: The explainable AI-based algorithm can accurately detect QT-prolongation when adjusted to a personalized patient-specific cut-off QTc value showing a potential risk of TdP. Using ∆QTc > 60 ms relative to drug-free baseline and QTc > 500 ms as examples, the algorithm yielded a sensitivity of 0.95 and 0.79, and a specificity of 0.95 and 0.98, respectively. We found that adjusting pseudo-coloring according to Bazett's ∆QTc > 60 ms relative to a drug-free baseline personalized to each patient provides better sensitivity than using Bazett's QTc > 500 ms, which could underestimate a potentially clinically significant QT-prolongation with bradycardia.

Functional Characterization of a Spectrum of Novel Romano-Ward Syndrome KCNQ1 Variants.

The KCNQ1 gene encodes the α-subunit of the cardiac voltage-gated potassium (Kv) channel KCNQ1, also denoted as Kv7.1 or KvLQT1. The channel assembles with the ß-subunit KCNE1, also known as minK, to generate the slowly activating cardiac delayed rectifier current IKs, a key regulator of the heart rate dependent adaptation of the cardiac action potential duration (APD). Loss-of-function variants in KCNQ1 cause the congenital Long QT1 (LQT1) syndrome, characterized by delayed cardiac repolarization and a QT interval prolongation in the surface electrocardiogram (ECG). Autosomal dominant loss-of-function variants in KCNQ1 result in the LQT syndrome called Romano-Ward syndrome (RWS), while autosomal recessive variants affecting function, lead to Jervell and Lange-Nielsen syndrome (JLNS), associated with deafness. The aim of this study was the characterization of novel KCNQ1 variants identified in patients with RWS to widen the spectrum of known LQT1 variants, and improve the interpretation of the clinical relevance of variants in the KCNQ1 gene. We functionally characterized nine human KCNQ1 variants using the voltage-clamp technique in Xenopus laevis oocytes, from which we report seven novel variants. The functional data was taken as input to model surface ECGs, to subsequently compare the functional changes with the clinically observed QTc times, allowing a further interpretation of the severity of the different LQTS variants. We found that the electrophysiological properties of the variants correlate with the severity of the clinically diagnosed phenotype in most cases, however, not in all. Electrophysiological studies combined with in silico modelling approaches are valuable components for the interpretation of the pathogenicity of KCNQ1 variants, but assessing the clinical severity demands the consideration of other factors that are included, for example in the Schwartz score.

A deep learning approach identifies new ECG features in congenital long QT syndrome.

BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying mutations. Most general cardiologists do not routinely see patients with congenital LQTS and may not always recognize the accompanying ECG features. In addition, a proportion of disease carriers do not display obvious abnormalities on their ECG. Combined, this can cause underdiagnosing of this potentially life-threatening disease. METHODS: This study presents 1D convolutional neural network models trained to identify genotype positive LQTS patients from electrocardiogram as input. The deep learning (DL) models were trained with a large 10-s 12-lead ECGs dataset provided by Amsterdam UMC and externally validated with a dataset provided by University Hospital Leuven. The Amsterdam dataset included ECGs from 10000 controls, 172 LQTS1, 214 LQTS2, and 72 LQTS3 patients. The Leuven dataset included ECGs from 2200 controls, 32 LQTS1, and 80 LQTS2 patients. The performance of the DL models was compared with conventional QTc measurement and with that of an international expert in congenital LQTS (A.A.M.W). Lastly, an explainable artificial intelligence (AI) technique was used to better understand the prediction models. RESULTS: Overall, the best performing DL models, across 5-fold cross-validation, achieved on average a sensitivity of 84 ± 2%, 90 ± 2% and 87 ± 6%, specificity of 96 ± 2%, 95 ± 1%, and 92 ± 4%, and AUC of 0.90 ± 0.01, 0.92 ± 0.02, and 0.89 ± 0.03, for LQTS 1, 2, and 3 respectively. The DL models were also shown to perform better than conventional QTc measurements in detecting LQTS patients. Furthermore, the performances held up when the DL models were validated on a novel external cohort and outperformed the expert cardiologist in terms of specificity, while in terms of sensitivity, the DL models and the expert cardiologist in LQTS performed the same. Finally, the explainable AI technique identified the onset of the QRS complex as the most informative region to classify LQTS from non-LQTS patients, a feature previously not associated with this disease. CONCLUSIONS: This study suggests that DL models can potentially be used to aid cardiologists in diagnosing LQTS. Furthermore, explainable DL models can be used to possibly identify new features for LQTS on the ECG, thus increasing our understanding of this syndrome.