Related Experiment Video

Updated: Aug 18, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

11.1K

Continuous Bayesian variant interpretation accounts for incomplete penetrance among Mendelian cardiac channelopathies

Matthew J O'Neill1, Luca Sala2, Isabelle Denjoy3

  • 1Vanderbilt University School of Medicine, Medical Scientist Training Program, Vanderbilt University, Nashville, TN.

Genetics in Medicine : Official Journal of the American College of Medical Genetics
|December 10, 2022
PubMed

Insights

Bayesian models improve interpretation of genetic variants causing Long QT Syndrome (LQTS) and Brugada Syndrome (BrS). This approach accounts for incomplete penetrance, enhancing clinical management of these inherited cardiac arrhythmia disorders.

Area of Science:

  • Cardiovascular Genetics
  • Computational Biology
  • Medical Genetics

Background:

  • Congenital Long QT Syndrome (LQTS) and Brugada Syndrome (BrS) are life-threatening inherited cardiac arrhythmias.
  • Incomplete penetrance of disease-associated variants complicates clinical management.
  • Key genes involved include KCNQ1, KCNH2, and SCN5A.

Purpose of the Study:

  • To apply and evaluate a Bayesian penetrance estimation strategy for Mendelian autosomal dominant cardiac arrhythmia diseases.
  • To account for incomplete penetrance in heterozygotes harboring variants in KCNQ1, KCNH2, and SCN5A.
  • To provide a more accurate framework for variant interpretation in LQTS and BrS.

Main Methods:

  • Generated Bayesian penetrance models for KCNQ1-LQT1 and SCN5A-LQT3.
  • Utilized variant-specific features and combined clinical data from literature, international centers, and population controls.
  • Analyzed posterior penetrance estimates, compared them with ClinVar annotations, and mapped them onto protein structures.

Main Results:

  • Bayesian penetrance estimates for KCNQ1-LQT1 and SCN5A-LQT3 were empirically equivalent to 10 and 5 phenotype heterozygotes, respectively.
  • Posterior penetrance estimates showed bimodality for KCNQ1-LQT1 and KCNH2-LQT2, with a higher proportion of high-penetrance missense variants in KCNQ1.
  • Significant heterogeneity in variant penetrance estimates was observed across identical ClinVar categories; structural mapping identified specific high-penetrance regions.

Conclusions:

  • Bayesian penetrance estimation offers a continuous and empirically grounded framework for interpreting genetic variants.
  • This method improves the understanding of genotype-phenotype relationships in LQTS and BrS.
  • Enhanced variant interpretation can lead to improved clinical management strategies for affected individuals and families.
Abstract

Keywords:
ChannelopathyIncomplete PenetranceLong QT SyndromePersonalized MedicineStatistical Genetics

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