Prognostic Value of Multiplexed Assays of Variant Effect and Automated Patch-clamping for

Background

Long QT syndrome (LQTS) is a lethal arrhythmia condition, frequently caused by rare loss-of-function variants in the cardiac potassium channel encoded by

Objective

To test the utility of variant-specific features, including high-throughput functional data, to predict cardiac events among

Methods

We quantified cell-surface trafficking of 18,323 variants in

Results

Variant-specific current density (HR 0.28 [0.13-0.60]) and estimates of LQTS penetrance incorporating MAVE data (HR 3.16 [1.59-6.27]) were independently predictive of severe cardiac events when controlling for patient-specific features. Risk prediction models incorporating these data significantly improved prediction of 20 year cardiac events (AUC 0.79 [0.75-0.82]) over patient-only covariates (QTc and sex) (AUC 0.73 [0.70-0.77]).

Conclusion

We show that high-throughput functional data, and other variant-specific features, meaningfully contribute to both diagnosis and prognosis of a clinically actionable monogenic disease.