Structural Evaluation of <i>RYR2</i> -CPVT Missense Variants and Continuous Bayesian Estimates of Their Penetrance

Traditional categorical variant annotations limit accurate disease risk assessment, especially in populations unascertained for disease. A probabilistic, population-calibrated penetrance framework enables more meaningful prospective variant interpretation. Our Bayesian CPVT-prior outperforms current tools in evaluating RYR2 variant penetrance. We provide prospective Bayesian CPVT penetrance values for 29 242 RYR2 missense variants at our online variant browser.

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Publication Details

Journal
Circulation Genomic and Precision Medicine
Published
2026-03-27
DOI
https://doi.org/10.1161/circgen.125.005457
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00
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article

Structural Evaluation of RYR2 -CPVT Missense Variants and Continuous Bayesian Estimates of Their Penetrance

Bjorn K Knollmann, Brett M. Kroncke, Jeffrey Schmeckpeper, Loren Vanags et al.
Circulation Genomic and Precision Medicine
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Structural Evaluation of RYR2 -CPVT Missense Variants and Continuous Bayesian Estimates of Their Penetrance

Bjorn K Knollmann, Brett M. Kroncke, Jeffrey Schmeckpeper, Loren Vanags, Matthew J. O’Neill, Kohei Yamauchi, Kundivy Dauda, Devyn W. Mitchell, Alex Shen, Prince J. Kannankeril, Matthew Ku
article en

Abstract

Traditional categorical variant annotations limit accurate disease risk assessment, especially in populations unascertained for disease. A probabilistic, population-calibrated penetrance framework enables more meaningful prospective variant interpretation. Our Bayesian CPVT-prior outperforms current tools in evaluating RYR2 variant penetrance. We provide prospective Bayesian CPVT penetrance values for 29 242 RYR2 missense variants at our online variant browser.

Circulation Genomic and Precision Medicine
Brigham and Women's Hospital (US), Harvard University (US), Shiga University of Medical Science (JP), Monroe Carell Jr. Children's Hospital (US)
Openalex Percentile: Top 6%
Genomics and Rare Diseases
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