Multiplexed Assays of Variant Effect and Automated Patch-clamping ImproveKCNH2-LQTS Variant Classification and Cardiac Event Risk Stratification

Author:

O’Neill Matthew J.ORCID,Ng Chai-AnnORCID,Aizawa Takanori,Sala LucaORCID,Bains Sahej,Winbo Annika,Ullah Rizwan,Shen Qianyi,Tan Chek-Ying,Kozek Krystian,Vanags Loren R.,Mitchell Devyn W.,Shen Alex,Wada Yuko,Kashiwa Asami,Crotti Lia,Dagradi Federica,Musu Giulia,Spazzolini Carla,Neves Raquel,Bos J. Martijn,Giudicessi John R.,Bledsoe Xavier,Gamazon Eric R.,Lancaster Megan,Glazer Andrew M.,Knollmann Bjorn C.,Roden Dan M.ORCID,Weile Jochen,Roth Frederick,Salem Joe-Elie,Earle Nikki,Stiles Rachael,Agee Taylor,Johnson Christopher N.,Horie Minoru,Skinner Jonathan,Ackerman Michael J.,Schwartz Peter J.,Ohno SeikoORCID,Vandenberg Jamie I.ORCID,Kroncke Brett M.ORCID

Abstract

AbstractBackgroundLong QT syndrome (LQTS) is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded byKCNH2. Variant classification is difficult, often owing to 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 ofKCNH2missense variant heterozygotes.MethodsWe quantified cell-surface trafficking of 18,796 variants inKCNH2using a Multiplexed Assay of Variant Effect (MAVE). We recorded KCNH2 current density for 533 variants by automated patch clamping (APC). We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1,458 patients withKCNH2missense variants, including QTc, cardiac event history, and mortality. We correlated variant functional data and Bayesian LQTS penetrance estimates with cohort phenotypes and assessed hazard ratios for cardiac events.ResultsVariant MAVE trafficking scores and APC peak tail currents were highly correlated (Spearman Rank-order ρ = 0.69). The MAVE data were found to provide up topathogenic very strongevidence for severe loss-of-function variants. In the cohort, both functional assays and Bayesian LQTS penetrance estimates were significantly predictive of cardiac events when independently modeled with patient sex and adjusted QT interval (QTc); however, MAVE data became non-significant when peak-tail current and penetrance estimates were also available. The area under the ROC for 20-year event outcomes based on patient-specific sex and QTc (AUC 0.80 [0.76-0.83]) was improved with prospectively available penetrance scores conditioned on MAVE (AUC 0.86 [0.83-0.89]) or attainable APC peak tail current data (AUC 0.84 [0.81-0.88]).ConclusionHigh throughputKCNH2variant MAVE data meaningfully contribute to variant classification at scale while LQTS penetrance estimates and APC peak tail current measurements meaningfully contribute to risk stratification of cardiac events in patients with heterozygousKCNH2missense variants.Clinical PerspectiveWhat is new?A two-order of magnitude increase in the set of calibrated functional data forKCNH2-LQTS is provided by two complementaryKCNH2assaysProactively available variant scores are presented for all possible missense variants by using a LQTS penetrance estimation framework conditioned on high-throughput MAVE dataVariant functional data, in addition to patient features of corrected QT interval and sex, significantly improve modeling of 20-year cardiac event outcomesWhat are the clinical implications?Readily available MAVE scores for thousands of variants may facilitate classification of new variants discovered in individuals with suspected LQTSScores and penetrance estimates are readily searchable atvariantbrowser.orgfor community inquiryBoth automated patch-clamp data and quantitative LQTS penetrance estimates, conditioned on MAVE data, improve prediction of 20-year cardiac event outcomes in a large cohort ofKCNH2heterozygotes

Publisher

Cold Spring Harbor Laboratory

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