O'Neill Matthew J, Ng Chai-Ann, Aizawa Takanori, Sala Luca, 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, 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 Seiko, Vandenberg Jamie I, Kroncke Brett M
Vanderbilt University School of Medicine, Medical Scientist Training Program, Nashville, TN, USA.
These authors contributed equally.
medRxiv. 2024 Jun 18:2024.02.01.24301443. doi: 10.1101/2024.02.01.24301443.
Long QT syndrome (LQTS) is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by . 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 missense variant heterozygotes.
We quantified cell-surface trafficking of 18,796 variants in 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 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.
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 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]).
High throughput 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 missense variants.
长QT综合征（LQTS）是一种致死性心律失常综合征，通常由编码钾通道的罕见功能丧失变异引起。变异分类困难，这通常是由于缺乏功能数据。此外，基于变异的风险分层也因临床数据的异质性和不完全外显率而变得复杂。在这里，我们试图测试主要来自高通量功能分析的变异特异性信息是否能改善一个大型、统一队列中错义变异杂合子的分类和心脏事件风险分层。
我们使用变异效应多重分析（MAVE）对18796个变异在细胞表面的转运进行了量化。我们通过自动膜片钳（APC）记录了533个变异的KCNH2电流密度。我们根据临床基因组学指南校准了MAVE数据的证据强度。我们对1458例有错义变异的患者进行了深入的表型分析，包括QTc、心脏事件史和死亡率。我们将变异功能数据和贝叶斯LQTS外显率估计值与队列表型相关联，并评估心脏事件的风险比。
变异MAVE转运评分与APC峰尾电流高度相关（斯皮尔曼等级相关系数ρ = 0.69）。发现MAVE数据为严重功能丧失变异提供了高达 的证据。在该队列中，当与患者性别和校正QT间期（QTc）独立建模时，功能分析和贝叶斯LQTS外显率估计值均能显著预测心脏事件；然而，当也有峰尾电流和外显率估计值时，MAVE数据变得不显著。基于患者特异性性别和QTc的20年事件结局的ROC曲线下面积（AUC 0.80 [0.76 - 0.83]），在根据MAVE调整的前瞻性可用外显率评分（AUC 0.86 [0.83 - 0.89]）或可获得的APC峰尾电流数据（AUC 0.84 [0.81 - 0.88]）条件下得到了改善。
高通量变异MAVE数据对大规模变异分类有重要贡献，而LQTS外显率估计值和APC峰尾电流测量值对杂合错义变异患者的心脏事件风险分层有重要贡献。
