A Bayesian method to estimate variant-induced disease penetrance

Autoři: Brett M. Kroncke aff001;  Derek K. Smith aff004;  Yi Zuo aff004;  Andrew M. Glazer aff001;  Dan M. Roden aff001;  Jeffrey D. Blume aff004
Působiště autorů: Department of Medicine Vanderbilt University Medical Center, Nashville, Tennessee, United States of America aff001;  Vanderbilt Center for Arrhythmia Research and Therapeutics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America aff002;  Department of Pharmacology Vanderbilt University, Nashville, Tennessee, United States of America aff003;  Department of Biostatistics Vanderbilt University, Nashville, Tennessee, United States of America aff004;  Department of Biomedical Informatics Vanderbilt University Medical Center, Nashville, Tennessee, United States of America aff005
Vyšlo v časopise: A Bayesian method to estimate variant-induced disease penetrance. PLoS Genet 16(6): e32767. doi:10.1371/journal.pgen.1008862
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008862


A major challenge emerging in genomic medicine is how to assess best disease risk from rare or novel variants found in disease-related genes. The expanding volume of data generated by very large phenotyping efforts coupled to DNA sequence data presents an opportunity to reinterpret genetic liability of disease risk. Here we propose a framework to estimate the probability of disease given the presence of a genetic variant conditioned on features of that variant. We refer to this as the penetrance, the fraction of all variant heterozygotes that will present with disease. We demonstrate this methodology using a well-established disease-gene pair, the cardiac sodium channel gene SCN5A and the heart arrhythmia Brugada syndrome. From a review of 756 publications, we developed a pattern mixture algorithm, based on a Bayesian Beta-Binomial model, to generate SCN5A penetrance probabilities for the Brugada syndrome conditioned on variant-specific attributes. These probabilities are determined from variant-specific features (e.g. function, structural context, and sequence conservation) and from observations of affected and unaffected heterozygotes. Variant functional perturbation and structural context prove most predictive of Brugada syndrome penetrance.

Klíčová slova:

Arrhythmia – Forecasting – Genetics of disease – Genomic medicine – Pathogenesis – Phenotypes – Probability distribution – Sodium channels


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Článek vyšel v časopise

PLOS Genetics

2020 Číslo 6

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