Prognostic Value of Multiplexed Assays of Variant Effect and Automated Patch-clamping for<i>KCNH2</i>-LQTS Risk Stratification
Abstract Background Long QT syndrome (LQTS) is a lethal arrhythmia condition, frequently caused by rare loss-of-function variants in the cardiac potassium channel encoded byKCNH2. Variant-based risk stratification is complicated by heterogenous clinical data, incomplete penetrance, and low-throughput functional data.Objective To test the utility of variant-specific features, including high-throughput functional data, to predict cardiac events amongKCNH2variant heterozygotes.Methods We quantified cell-surface trafficking of 18,323 variants inKCNH2and recorded potassium current densities for 506KCNH2variants. Next, we deeply phenotyped 1150KCNH2missense variant patients, including ECG features, cardiac event history (528 total cardiac events), and mortality. We then assessed variant functional,in silico, structural, and LQTS penetrance data to stratify event-free survival for cardiac events in the study cohort.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.Graphical Abstract Implementation ofKCNH2variant functional studies, deep clinical phenotyping, and cardiac event risk stratification.<jats:fig id="ufig1" position="float" fig-type="figure" orientation="portrait"><jats:graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="24301443v1_ufig1" position="float" orientation="portrait" /></jats:fig>.
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 08. Feb. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
O’Neill, Matthew J. [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2024.02.01.24301443 |
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| PPN (Katalog-ID): |
XBI042404207 |
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| 100 | 1 | |a O’Neill, Matthew J. |e verfasserin |0 (orcid)0000-0003-2014-7950 |4 aut | |
| 245 | 1 | 0 | |a Prognostic Value of Multiplexed Assays of Variant Effect and Automated Patch-clamping for<i>KCNH2</i>-LQTS Risk Stratification |
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| 520 | |a Abstract Background Long QT syndrome (LQTS) is a lethal arrhythmia condition, frequently caused by rare loss-of-function variants in the cardiac potassium channel encoded byKCNH2. Variant-based risk stratification is complicated by heterogenous clinical data, incomplete penetrance, and low-throughput functional data.Objective To test the utility of variant-specific features, including high-throughput functional data, to predict cardiac events amongKCNH2variant heterozygotes.Methods We quantified cell-surface trafficking of 18,323 variants inKCNH2and recorded potassium current densities for 506KCNH2variants. Next, we deeply phenotyped 1150KCNH2missense variant patients, including ECG features, cardiac event history (528 total cardiac events), and mortality. We then assessed variant functional,in silico, structural, and LQTS penetrance data to stratify event-free survival for cardiac events in the study cohort.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.Graphical Abstract Implementation ofKCNH2variant functional studies, deep clinical phenotyping, and cardiac event risk stratification.<jats:fig id="ufig1" position="float" fig-type="figure" orientation="portrait"><jats:graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="24301443v1_ufig1" position="float" orientation="portrait" /></jats:fig> | ||
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