Polygenic scores (PGS) summarize the combined effects of common single-nucleotide polymorphisms and contribute to predictions of disease severity, but biological consequences linked to these common variants remain poorly defined. Here, we focused on polygenic liability for a measurable electrophysiologic trait (the QT interval). Prolonged QT interval, measured on patient electrocardiograms, is associated with an increased risk for cardiac arrhythmia. We investigated human induced pluripotent stem cell cardiomyocytes (hiPSC-CMs) from donors with extreme PGS (i.e., high and low) related to QT interval duration. We paired global proteomics with multiplexed affinity purification mass spectrometry (AP-MS) centered on Kv11.1 (hERG), a major determinant of QT-interval repolarization. Global proteomics indicated increased mitochondrial protein abundance in high-PGS cardiomyocytes, but this did not explain the Kv11.1 interactome. In high-PGS cells, Kv11.1 showed increased associations with myosin motor proteins and endosomal recycling machinery, consistent with altered (and potentially increased) recycling/trafficking dynamics rather than trafficking deficiency observed with most pathogenic Kv11.1 variants. This proof-of-concept study underscores a framework for linking polygenic factors to tractable biological consequences by combining patient-specific hiPSCs, proteomics and affinity-purification. Linking polygenic scores to changes in protein networks provides testable mechanisms that can be applied across many diseases.

Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have emerged as a pivotal model for research. Specialized devices can generate Extracellular Field Potential (EFP) measurements from these cells, analogous to the ventricular complex of the electrocardiogram. However, electrophysiological analysis can be complex and requires specialized expertise, posing a barrier to broader adoption in non-specialized labs. We present the EFP-Analyzer (EFPA), a semi-automized analyzer for EFP traces, which identifies and averages beats, identifies landmarks, and calculates intervals. We demonstrate an analysis of 358 EFP traces from 22 patient-derived lines. We analyzed spontaneously beating iPSC-CMs and optically paced iPSC-CMs through channelrhodopsin. We developed stringent quality criteria and measured EFP intervals, including Field Potential Duration (FPD). We further analyzed the usability and data replicability of EFPA through an inter-intra observer analysis. Correlation coefficient for inter-reader tangent and threshold measurements for these FPD ranged between r: 0.93-1.00. Bland-Altman plots comparing inter observer results for spontaneously beating and paced iPSC-CMs showed 95% limits of agreement (- 13.6 to 19.4 ms and - 13.2 to 15.3 ms, respectively). EFPA could accurately detect FPD prolongation due to drug (moxifloxacin) or pathogenic loss of function mutations (CACNA1C N639T). This program and instructions are available for download at https://github.com/kroncke-lab/EFPA .

Long QT syndrome (LQTS), an inherited cardiac arrhythmia syndrome with congenital and drug-induced presentations and known monogenic and polygenic contributions, represents a significant clinical challenge due to its complex genetic underpinning and propensity for fatal arrhythmias. In this study, we generated induced pluripotent stem cells (iPSCs) reprogrammed from peripheral blood mononuclear cells (PBMCs) of six patients with extreme polygenic scores for short and long corrected QT intervals. This patient-specific approach will enable us to better understand variable expressivity and penetrance of LQTS, using rigorously validated iPSC lines serve as a vital resource for elucidating the molecular mechanisms underlying LQTS.

Rationale:Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are an emerging model for determining drug effects and modeling disease. Specialized devices can generate Extracellular Field Potential (EFP) measurements from these cells, analogous to the ventricular complex of the electrocardiogram. Objective:The objective of this study was to develop an easy-to-use, easy-to-teach, reproducible software tool to measure EFPs. Methods-Results:We present the EFP-Analyzer (EFPA), a semi-automized analyzer for EFP traces, which identifies and averages beats, identifies landmarks, and calculates intervals. We evaluated the tool in an analysis of 358 EFP traces from 22 patient-derived lines. We analyzed spontaneously beating iPSC-CMs, as well as optically paced iPSC-CMs through channelrhodopsin. We developed stringent quality criteria and measured EFP intervals, including Field Potential Duration (FPD). FPD from optically paced iPSC-CMs were shorter than those of spontaneously beating iPSC-CMs (283.7.0±54.2 vs. 293.0±47.5, p: 0.32, respectively). We further analyzed the usability and data replicability of EFPA through an inter-intra observer analysis. Correlation coefficient for inter-reader tangent and threshold measurements for these FPD ranged between r: 0.93-1.00. Bland-Altman plots comparing inter observer results for spontaneously beating and paced iPSC-CMs showed 95% limits of agreement (-13.6 to 19.4ms and -13.2 to 15.3ms, respectively). The EFP-analyzer could accurately detect FPD prolongation due to drug (moxifloxacin) or pathogenic loss of function mutations ( CACNA1C N639T). This program is available for download at https://github.com/kroncke-lab/EFPA . The instructions will be available at the same listed website under the README section of the Github main page. Conclusions:The EFP-Analyzer tool is a useful tool that enables the efficient use of iPSC-CMs as a model to study drug effects and disease.

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 rho=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 corrected 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.

Long QT syndrome (LQTS) is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by KCNH2. Variant-based risk stratification is complicated by heterogenous clinical data, incomplete penetrance, and low-throughput functional data. While variant-specific functional data can assist with variant classification, whether functional data can assist with prediction of outcomes is unknown.

BACKGROUND:Truncating variants in filamin C (FLNC) can cause arrhythmogenic cardiomyopathy (ACM) through haploinsufficiency. Noncanonical splice-altering variants may contribute to this phenotype.OBJECTIVE:The purpose of this study was to investigate the clinical and functional consequences of a recurrent FLNC intronic variant of uncertain significance (VUS), c.970-4A>G.METHODS:Clinical data in 9 variant heterozygotes from 4 kindreds were obtained from 5 tertiary health care centers. We used in silico predictors and functional studies with peripheral blood and patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Isolated RNA was studied by reverse transcription polymerase chain reaction. iPSC-CMs were further characterized at baseline and after nonsense-mediated decay (NMD) inhibition, using quantitative polymerase chain reaction (qPCR), RNA-sequencing, and cellular electrophysiology. American College of Medical Genetics and Genomics (ACMG) criteria were used to adjudicate variant pathogenicity.RESULTS:Variant heterozygotes displayed a spectrum of disease phenotypes, spanning from mild ventricular dysfunction with palpitations to severe ventricular arrhythmias requiring device shocks or progressive cardiomyopathy requiring heart transplantation. Consistent with in silico predictors, the c.970-4A>G FLNC variant activated a cryptic splice acceptor site, introducing a 3-bp insertion containing a premature termination codon. NMD inhibition upregulated aberrantly spliced transcripts by qPCR and RNA-sequencing. Patch clamp studies revealed irregular spontaneous action potentials, increased action potential duration, and increased sodium late current in proband-derived iPSC-CMs. These findings fulfilled multiple ACMG criteria for pathogenicity.CONCLUSION:Clinical, in silico, and functional evidence support the prediction that the intronic c.970-4A>G VUS disrupts splicing and drives ACM, enabling reclassification from VUS to pathogenic.

Introduction: LQTS is a multi-factorial cardiac repolarization disorder characterized by a prolonged corrected QT interval (QTc) that predisposes individuals to sudden death. Variants in KCNH2 account for ~30% of LQTS cases. Variants in a ‘hotspot’ domain of KCNH2 are of concern, as variant location in KCNH2 is strongly associated with increased risk of cardiac events. Here, we determined the trafficking phenotype of all possible variants in the S3 and S4 helices (Voltage sensor) and S5 helix and p-loop (pore domain), both ‘hotspot’ domains, of KCNH2 . Method: We used a HA tagged KCNH2 construct containing mCherry to enable massively parallel characterization of channel trafficking of missense KCNH2 variants. We studied a total of 3315/3381 possible variants for residues 477-637. Results: Our preliminary data revealed a heterogenous distribution of trafficking defects (range: 0-157% of WT). Some regions (e.g. 562-566) were largely intolerant to substitution (trafficking scores ~0% for all variants) whereas other regions (e.g. 509-521) were very permissive of substitution (trafficking ranged from 78-146% of WT). For 51 clinically identified variants, we compared trafficking results with peak tail current density data and found that 4/6 were correctly classified as functionally normal and 42/44 correctly classified as loss of function. Conclusion: Massively parallel trafficking assay can identify KCNH2 defects and illuminate important channel biophysics. Massively parallel trafficking assays will enable prospective and accurate variant assessment for any missense variant in KCNH2 and subsequently other proteins where misfolding is a major loss-of-function mechanism.

Background Rare protein-altering variants in SCN5A, KCNQ1 , and KCNH2 are major causes of Brugada Syndrome (BrS) and the congenital Long QT Syndrome (LQTS). While splice-altering variants lying outside 2-bp canonical splice sites can cause these diseases, their role remains poorly described. Objective We implemented two functional assays to assess 12 recently reported putative splice-altering variants of uncertain significance (VUS) and 1 likely pathogenic (LP) variant without functional data observed in BrS and LQTS probands. Methods We deployed minigene assays to assess the splicing consequences of 10 variants. Three variants incompatible with the minigene approach were introduced into control induced pluripotent stem cells (iPSCs) by CRISPR genome editing. We differentiated cells into iPSC-derived cardiomyocytes (iPSC-CMs) and studied splicing outcomes by reverse transcription-polymerase chain reaction (RT-PCR). We used the American College of Medical Genetics and Genomics functional assay criteria (PS3/BS3) to reclassify variants. Results We identified aberrant splicing, with presumed disruption of protein sequence, in 8/10 variants studied using the minigene assay and 1/3 studied in iPSC-CMs. We reclassified 9 VUS to LP, 1 VUS to Likely Benign, and 1 LP variant to pathogenic. Conclusions Functional assays reclassified splice-altering variants outside canonical splice sites in BrS- and LQTS-associated genes.

Many genes, including KCNH2, contain "hotspot" domains associated with a high density of variants associated with disease. This has led to the suggestion that variant location can be used as evidence supporting classification of clinical variants. However, it is not known what proportion of all potential variants in hotspot domains cause loss of function. Here, we have used a massively parallel trafficking assay to characterize all single-nucleotide variants in exon 2 of KCNH2, a known hotspot for variants that cause long QT syndrome type 2 and an increased risk of sudden cardiac death. Forty-two percent of KCNH2 exon 2 variants caused at least 50% reduction in protein trafficking, and 65% of these trafficking-defective variants exerted a dominant-negative effect when co-expressed with a WT KCNH2 allele as assessed using a calibrated patch-clamp electrophysiology assay. The massively parallel trafficking assay was more accurate (AUC of 0.94) than bioinformatic prediction tools (REVEL and CardioBoost, AUC of 0.81) in discriminating between functionally normal and abnormal variants. Interestingly, over half of variants in exon 2 were found to be functionally normal, suggesting a nuanced interpretation of variants in this "hotspot" domain is necessary. Our massively parallel trafficking assay can provide this information prospectively.

Introduction: Individuals with congenital long QT syndrome (LQTS) are at high risk for the life-threatening arrhythmia torsades de pointes . Loss-of-function KCNH2 (aka hERG ) variants that reduce repolarizing current, I Kr , are responsible for >30% of LQTS cases with ~6% of sudden death in the young and ~1% in infants. Most KCNH2 variants are observed in some individual(s) making it difficult to obtain clinical evidence to assign pathogenicity; >80% of KCNH2 missense variants in ClinVar are listed as variants of uncertain significance. To help adjudicate variants lacking in compelling clinical data, we demonstrate a method to characterize KCNH2 variant dysfunctions. Methods: We combined deep mutational scanning with a HA tagged KCNH2 construct to enable massively parallel characterization of channel trafficking of missense variants in KCNH2 . We have applied this method to the first 160 residues of KCNH2 ; 3,123 missense variants in total, a known hotspot for disease causing variants. For a subset of 458 non-redundant single nucleotide missense variants, we compared trafficking data, and in silico classifiers, with patch clamp data collected on the SyncroPatch platform. Results: Trafficking data is better than in silico features at predicting peak tail I Kr values, with an area under the receiver operating characteristic curve of > 0.9 for trafficking data versus 0.8 for in silico feature. The Spearman correlation coefficients were 0.73 [0.67-0.78] compared to 0.51 [0.44-0.58] for trafficking and in silico predictions respectively. Our assay identified substitution sensitive regions, surrounded by more permissive residues. We also found substitution intolerant sites involved in networked hydrogen-bonding. Conclusion: A massively parallel trafficking assay can recapitulate most KCNH2 defects more effectively than in silico methods. Extended application of our method will enable the assessment of all missense variants in KCNH2 and other cardiac ion channels.

Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. Methods: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record–derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier; NCT03394859.

High throughput genomics has greatly facilitated identification of genetic variants. However, determining which variants contribute to disease causation is challenging with more than half of all missense variants now classified as variants of uncertain significance (VUS). A VUS leaves patients and their clinicians unable to utilize the variant information in clinical decision-making. In long QT syndrome type 2, KCNH2 channel function is directly associated with disease presentation. Therefore, functional phenotyping of KCNH2 variants can provide direct evidence to aid variant classification. Here, we investigated the expression of all codon variants in exon 2 of KCNH2 using a massively parallel trafficking assay and for a subset of 458 single nucleotide variants compared the results with peak tail current density and gating using automated patch clamp electrophysiology. Trafficking could correctly classify loss of peak tail current density variants with an AUC reaching 0.94 compared to AUCs of 0.75 to 0.8 for in silico variant classifiers. We suggest massively parallel trafficking assays can provide prospective and accurate functional assessment for all missense variants in KCNH2 and most likely many other ion channels and membrane proteins.

Background KCHN2 encodes the KV11.1 potassium channel responsible for IKr , a major repolarization current during the cardiomyocyte action potential. Variants in KCNH2 that decrease IKr can cause Type 2 Long QT syndrome, usually due to mistrafficking to the cell surface. Accurately discriminating between variants with normal and abnormal trafficking would help clinicians identify and treat individuals at risk of a major cardiac event. The volume of reported non-synonymous KCNH2 variants preclude the use of conventional electrophysiologic methods for functional study. Objective To report a high-throughput, multiplexed screening method for KCNH2 genetic variants capable of measuring the cell surface abundance of hundreds of missense variants in KCNH2 . Methods We develop a method to quantitate KCNH2 variant trafficking on a pilot region of 11 residues in the S5 helix, and generate trafficking scores for 220/231 missense variants in this region. Results For 5/5 variants, high-throughput trafficking scores validated when tested in single variant flow cytometry and confocal microscopy experiments. We additionally compare our results with planar patch electrophysiology and find that loss-of-trafficking variants do not produce IKr , but that some variants which traffic normally may still be functionally compromised. Conclusions Here, we describe a new method for detecting trafficking-deficient variants in KCNH2 in a multiplexed assay. This new method accurately generates trafficking data for variants in KCNH2 and can be readily extended to all residues in Kv11.1 and to other cell surface proteins. CLINICAL IMPLICATIONS Hundreds of KCNH2 variants have been observed to date, and thousands more will be found as clinical and population sequencing efforts become increasingly widespread. The major mechanism of KV11.1 loss of function is misfolding and failure to traffic to the cell surface. Deep mutational scanning of KCNH2 trafficking is a scalable, high-throughput method that can help identify new loss of function variants and decipher the large number of KCNH2 variants being found in the population.

BACKGROUND KCHN2 encodes the K(V)11.1 potassium channel responsible for IKr, a major repolarization current during the cardiomyocyte action potential. Variants in KCNH2 that lead to decreased IKr have been associated with long QT syndrome type 2 (LQT2). The mechanism of LQT2 is most often induced loss of K(V)11.1 trafficking to the cell surface. Accurately discriminating between variants with normal and abnormal trafficking would aid in understanding the deleterious nature of these variants; however, the volume of reported nonsynonymous KCNH2 variants precludes the use of conventional methods for functional study. OBJECTIVE The purpose of this study was to report a high-throughput, multiplexed screening method for KCNH2 genetic variants capable of measuring the cell surface abundance of hundreds of missense variants in the resulting K(V)11.1 channel. METHODS We developed a method to quantitate K(V)11.1 variant trafficking on a pilot region of 11 residues in the S5 helix. RESULTS We generated trafficking scores for 220 of 231 missense variants in the pilot region. For 5 of 5 variants, high-throughput trafficking scores validated when tested in single variant flow cytometry and confocal microscopy experiments. We further explored these results with planar patch electrophysiology and found that loss-of-trafficking variants do not produce I-Kr. Conversely, but expectedly, some variants that traffic normally were still functionally compromised. CONCLUSION We describe a new method for detecting K(V)11.1 trafficking-deficient variants in a multiplexed assay. This new method accurately generated trafficking data for variants in K(V)11.1 and is extendable both to all residues in K(V)11.1 and to other cell surface proteins.