Journal article
A Bayesian method to estimate variant-induced disease penetrance
PLoS genetics, Vol.16(6), p.e1008862
06/22/2020
DOI: 10.1371/journal.pgen.1008862
PMCID: PMC7347235
PMID: 32569262
Abstract
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.
Details
- Title: Subtitle
- A Bayesian method to estimate variant-induced disease penetrance
- Creators
- Brett M Kroncke - Vanderbilt UniversityDerek K Smith - Vanderbilt UniversityYi Zuo - Vanderbilt UniversityAndrew M Glazer - Vanderbilt University Medical CenterDan M Roden - Vanderbilt University Medical CenterJeffrey D Blume - Vanderbilt University
- Resource Type
- Journal article
- Publication Details
- PLoS genetics, Vol.16(6), p.e1008862
- DOI
- 10.1371/journal.pgen.1008862
- PMID
- 32569262
- PMCID
- PMC7347235
- NLM abbreviation
- PLoS Genet
- ISSN
- 1553-7404
- eISSN
- 1553-7404
- Grant note
- P50 GM115305 / NIGMS NIH HHS K99 HG010904 / NHGRI NIH HHS R00 HL135442 / NHLBI NIH HHS F32 HL137385 / NHLBI NIH HHS R01 HL149826 / NHLBI NIH HHS
- Language
- English
- Date published
- 06/22/2020
- Academic Unit
- Preventive and Community Dentistry; Dental Research
- Record Identifier
- 9984966852302771
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