Abstract
Purpose
The congenital Long QT Syndrome (LQTS) and Brugada Syndrome (BrS) are Mendelian autosomal
dominant diseases that frequently precipitate fatal cardiac arrhythmias. Incomplete penetrance is a barrier to clinical management of heterozygotes harboring
variants in the major implicated disease genes KCNQ1, KCNH2, and SCN5A. We apply and evaluate a Bayesian penetrance estimation strategy that accounts for
this phenomenon.
Methods
We generated Bayesian penetrance models for KCNQ1-LQT1 and SCN5A-LQT3 using variant-specific features and clinical data from the literature, international
arrhythmia genetic centers, and population controls. We analyzed the distribution
of posterior penetrance estimates across 4 genotype-phenotype relationships and compared
continuous estimates with ClinVar annotations. Posterior estimates were mapped onto
protein structure.
Results
Bayesian penetrance estimates of KCNQ1-LQT1 and SCN5A-LQT3 are empirically equivalent to 10 and 5 clinically phenotype heterozygotes, respectively.
Posterior penetrance estimates were bimodal for KCNQ1-LQT1 and KCNH2-LQT2, with a higher fraction of missense variants with high penetrance among KCNQ1 variants. There was a wide distribution of variant penetrance estimates among identical
ClinVar categories. Structural mapping revealed heterogeneity among “hot spot” regions
and featured high penetrance estimates for KCNQ1 variants in contact with calmodulin and the S6 domain.
Conclusions
Bayesian penetrance estimates provide a continuous framework for variant interpretation.
Keywords
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Article info
Publication history
Published online: December 06, 2022
Accepted:
December 5,
2022
Received in revised form:
December 5,
2022
Received:
August 11,
2022
Identification
Copyright
© 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.
