Why the study?
KCNH2 variant classification and risk stratification are hindered by a lack of functional data, heterogeneous clinical data, and incomplete penetrance.
Does variant-specific functional data improve risk stratification for cardiac events in patients with KCNH2 missense variants?
Does variant-specific functional data improve risk stratification for cardiac events in patients with KCNH2 missense variants?
High-throughput functional assay data and Bayesian penetrance estimates significantly improve the prediction of 20-year cardiac events in patients with KCNH2 missense variants compared to traditional clinical features alone.
Answers are grounded in this paper and cite their sources.
Variant-specific functional data may refine LQTS classification; leaves open impact on risk stratification and practice.
Background 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 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 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 (APC). We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1,458 patients with KCNH2 missense 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. Results Variant 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 to pathogenic very strong evidence 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]). Conclusion High throughput KCNH2 variant 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 heterozygous KCNH2 missense variants. Clinical Perspective What is new? A two-order of magnitude increase in the set of calibrated functional data for KCNH2 -LQTS is provided by two complementary KCNH2 assays Proactively available variant scores are presented for all possible missense variants by using a LQTS penetrance estimation framework conditioned on high-throughput MAVE data Variant functional data, in addition to patient features of corrected QT interval and sex, significantly improve modeling of 20-year cardiac event outcomes What are the clinical implications? Readily available MAVE scores for thousands of variants may facilitate classification of new variants discovered in individuals with suspected LQTS Scores and penetrance estimates are readily searchable at variantbrowser.org for community inquiry Both 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 of KCNH2 heterozygotes
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O’Neill et al. (2024) studied this question.
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