Brett M. Kroncke

BACKGROUND: Variants in the ion channel gene KCNQ1 are the leading cause of congenital long QT syndrome (LQTS), a disorder characterized by QT prolongation and risk of fatal arrhythmias. The expanding use of genetic testing has led to the identification of numerous variants of uncertain significance, complicating clinical interpretation and risk stratification. Functional characterization of KCNQ1 variants is essential to define their role in long QT syndrome and advance precision medicine in cardiovascular care. METHODS: We generated a nearly comprehensive variant library of 13 403 protein-coding variants in KCNQ1 . Using 4 pooled assays followed by high-throughput sequencing, we characterized the variants’ effects on cell surface abundance and channel function in both the variant-only and heterozygous states. Case–control analyses and data from large-scale biobanks were used to assess the clinical impact of loss-of-function variants on QT prolongation and long QT syndrome. Heterozygous assay results were used to determine dominant-negative effects, which were also evaluated for association with arrhythmia risk. Protein structural clustering of distinct classes of deleterious variants was analyzed. RESULTS: Across the 4 assays, we generated 49 305 functional measurements of KCNQ1 variants. Of the 13 403 KCNQ1 studied variants, 1757 demonstrated strong pathogenic evidence, and 6660 showed moderate benign evidence. Loss-of-function variants were significantly associated with QT prolongation and long QT syndrome in case–control and biobank analyses. Deleterious variants clustered within distinct structural domains based on their functional classification. A majority of pathogenic variants exhibited dominant-negative effects; these variants were linked to a higher risk of arrhythmia diagnoses than were haploinsufficient variants. CONCLUSIONS: This comprehensive KCNQ1 functional atlas provides novel functional evidence for most KCNQ1 variants of uncertain significance. It also reveals mechanistic principles linking genetic variation to ion channel biology and arrhythmia susceptibility, advancing cardiovascular precision medicine.

The promise of precision therapeutics in genetic cardiomyopathies relies on linking specific therapies to variant mechanisms. Missense variants in the cardiac splice regulator RBM20 cause a highly penetrant and arrhythmogenic dilated cardiomyopathy. Disease-causing variants in RBM20’s arginine-serine rich (RS) domain act via formation of toxic gain of function cytoplasmic granules, but this is not true for a small number of clinically adjudicated pathogenic variants in its glutamate(E)-rich domain. To better define the effects of E-rich domain variants, we developed a scalable screen based on induced pluripotent stem cell (iPSC) cardiomyocyte differentiation that identified several additional damaging variants. Several of these reduced RBM20 protein abundance and stability. We therefore hypothesized that, unlike RS domain variants, these E-rich variants might be rescued by RBM20 overexpression. To test this hypothesis, we generated induced pluripotent stem cells (iPSCs) from a patient with a pathogenic E-rich domain variant (p.E913K), and confirmed reduced RBM20 protein expression in these RBM20 ^+/p.E913K cells after differentiation to iPSC-derived cardiomyocytes (iPSC-CM, vs. engineered isogenic RBM20 ^+/+ ). These iPSC-CMs also displayed aberrant transcriptional splicing, reduced contractility, increased calcium-induced calcium release, and nuclear localization of RBM20 protein, often with more than the two expected RBM20- centric splice factories. AAV-based overexpression of RBM20 reversed some, but not all of the mis-splicing events identified in RBM20 ^+/p.E913K iPSC-CMs, and did not improve their abnormal contractility, calcium handling or supernumerary RBM20 nuclear granules. In summary, our data indicate that pathogenic E-rich domain variants reduce RBM20 protein abundance, but that their mechanism is unlikely to be explained by haploinsufficiency alone.

BACKGROUND: Catecholaminergic polymorphic ventricular tachycardia (CPVT) is strongly associated with rare missense variants in RYR2 , the gene encoding the intracellular calcium release channel RyR2. METHODS: We curated 179 articles reviewed by 3 individuals to extrapolate RYR2 -CPVT missense variant genotype-phenotype relationships. Purportedly neutral control variants were ascertained from RYR2 missense variants observed in gnomAD and ClinVar. We performed an RYR2 -CPVT Bayesian penetrance analysis by conditioning a CPVT penetrance prior (hereafter called Bayesian CPVT-prior) on variant-specific features (in silico and structural) calibrated by heterozygote phenotypes. We evaluated various features, including the Bayesian CPVT-prior, ClinVar, REVEL, and AlphaMissense against our observed CPVT penetrance, using Spearman rank-order correlations and Brier Scores. Penetrance estimates were superimposed on a cryo-EM structure of RyR2 to investigate hot-spot heterogeneity. RESULTS: From the literature, we identified 1014 affected missense RYR2 heterozygotes (468 unique variants), and further supplemented by purpuroted unaffected heterozygotes in GnomAD to a total of 622 575 heterozygotes (5181 unique variants). Among the predictors, the Bayesian CPVT-prior score had the highest Spearman rank-order and lowest Brier scores, respectively (0.19; 0.0090), compared with ClinVar (0.083; 0.019), REVEL (0.16; 0.018), or AlphaMissense (0.18; 0.018). Penetrance estimates for all RYR2 missense variants are prospectively hosted at the Variant Browser website. CONCLUSIONS: Traditional categorical variant annotations limit accurate disease risk assessment, especially in populations unascertained for disease. A probabilistic, population-calibrated penetrance framework enables more meaningful prospective variant interpretation. Our Bayesian CPVT-prior outperforms current tools in evaluating RYR2 variant penetrance. We provide prospective Bayesian CPVT penetrance values for 29 242 RYR2 missense variants at our online variant browser.

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. Significance Statement: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low-PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found mechanisms that are influenced by common genetic traits in patients. Our work connects polygenic scores to pathway-level molecular mechanisms in human cells and provides a general framework for uncovering how complex genetic architecture drives disease-relevant biology. Classification: Biological Sciences; Medical Sciences

Loss-of-function variants in KCNQ1 are the primary cause of congenital Long QT Syndrome (LQTS), characterized by QT prolongation and increased risk of fatal arrhythmias. The surge in genetic testing continues to uncover vast numbers of variants of uncertain significance in Mendelian disease genes, including KCNQ1. Using four multiplexed assays, we mapped the functional landscape of KCNQ1, identifying trafficking, gating, and dominant negative variants. We provide functional evidence for 13,403 variants, including 1,757 with strong pathogenic and 6,660 with moderate benign evidence. Structure-function analyses revealed variant enrichment in regions regulating trafficking, multimerization, ubiquitylation, and channel gating. Loss-of-function variants showed a risk ratio of 263 (95% CI 241-286) in an LQTS cohort and were significantly associated with QTc prolongation and LQTS diagnoses in biobank participants. By characterizing the functional impact of nearly all KCNQ1 variants, we provide critical insights into arrhythmia mechanisms and open new avenues for precision medicine in LQTS.

Genetic diseases such as ion channelopathies substantially burden human health. Existing treatments are limited and not genotype specific. Here, we report a 2-step high-throughput approach to rapidly identify drug candidates for repurposing as genotype-specific therapy. We first screened 1,680 medicines using a thallium-flux trafficking assay against Kv11.1 gene variants causing long QT syndrome (LQTS), an ion channelopathy associated with fatal cardiac arrhythmia. We identified evacetrapib as a suitable drug candidate that improves membrane trafficking and activates channels. We then used deep mutational scanning to prospectively identify all Kv11.1 missense variants in an LQTS hotspot region responsive to treatment with evacetrapib. Combining high-throughput drug screens with deep mutational scanning establishes a paradigm for mutation-specific drug discovery translatable to personalized treatment of carriers with rare genetic disorders.

Polygenic scores (PGS) have emerged as important modifiers of disease risk, drug response, and rare variant penetrance, but the biological mechanisms underlying these associations remain poorly understood. To experimentally investigate these relationships, we derived induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from individuals at the 1st, 50th, and 99th percentiles of a genome-wide QT interval polygenic score (QT-PGS). We examined baseline repolarization, drug response to the hERG inhibitor E4031, and penetrance of two KCNH2 variants (p.Arg148Trp and p.Arg823Trp) in these cellular models. While baseline field potential durations (FPDs) did not differ across PGS levels, high-PGS iPSC-CMs showed exaggerated prolongation in response to E4031 and increased phenotypic expression of both KCNH2 variants. These findings provide the first experimental demonstration that polygenic background can shape cardiac electrophysiologic phenotypes and modulate the functional impact of both pharmacologic and genetic perturbations. This work establishes a scalable platform for mechanistic studies of polygenic risk.

Background: Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) is strongly associated with rare missense variants in RYR2 , the gene encoding the intracellular calcium release channel RyR2. Precision medicine is complicated by incomplete penetrance, particularly in the case of RYR2 -CPVT variants Objective: To improve structural understanding and clinical actionability of RYR2- CPVT incomplete penetrance. Methods: We curated 179 manuscripts reviewed by three individuals to extrapolate RYR2 -CPVT missense variant genotype-phenotype relationships. Purportedly neutral control variants were ascertained from RYR2 missense variants observed in gnomAD and ClinVar. We performed an RYR2 -CPVT Bayesian penetrance analysis by conditioning a CPVT penetrance prior on variant-specific features ( in silico and structural) calibrated by heterozygote phenotypes. We compared the calibration of our Bayesian penetrance estimates and our previous described structural density metric with in silico predictors REVEL, AlphaMissense and ClinVar annotations, using Spearman rank-order correlations, and Brier Scores. Penetrance estimates were superimposed upon a cryo-EM structure of RyR2 to investigate ‘hot-spot’ heterogeneity. Results: From the literature and gnomAD, we identified 1,014 affected missense RYR2 heterozygotes (468 unique variants) among a total of 622,575 heterozygotes (5,181 unique variants). Among the predictors, our Bayesian prior score had the highest Spearman rank-order and lowest Brier scores, respectively (0.19; 0.0090), compared to ClinVar (0.083; 0.019), REVEL (0.16; 0.018), or AlphaMissense (0.18; 0.018). Penetrance estimates for all RYR2 missense variants are prospectively hosted at our Variant Browser website. Conclusions: Bayesian penetrance scores outperform current tools in evaluating variant penetrance. We provide prospective CPVT penetrance values for 29,242 RYR2 missense variants at our online Variant Browser.