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A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation
Variants of unknown significance in cardiomyopathic disease should be analyzed systematically based on the prevalence of the variant in the population compared to prevalence of disease, evidence that other variants in the gene are pathologic, consistency of prediction software on pathogenicity, and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332775/ https://www.ncbi.nlm.nih.gov/pubmed/30656044 http://dx.doi.org/10.1002/ccr3.1920 |
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author | Connell, Patrick S. Jeewa, Aamir Kearney, Debra L. Tunuguntla, Hari Denfield, Susan W. Allen, Hugh D. Landstrom, Andrew P. |
author_facet | Connell, Patrick S. Jeewa, Aamir Kearney, Debra L. Tunuguntla, Hari Denfield, Susan W. Allen, Hugh D. Landstrom, Andrew P. |
author_sort | Connell, Patrick S. |
collection | PubMed |
description | Variants of unknown significance in cardiomyopathic disease should be analyzed systematically based on the prevalence of the variant in the population compared to prevalence of disease, evidence that other variants in the gene are pathologic, consistency of prediction software on pathogenicity, and the current clinical consensus. |
format | Online Article Text |
id | pubmed-6332775 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63327752019-01-17 A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation Connell, Patrick S. Jeewa, Aamir Kearney, Debra L. Tunuguntla, Hari Denfield, Susan W. Allen, Hugh D. Landstrom, Andrew P. Clin Case Rep Case Reports Variants of unknown significance in cardiomyopathic disease should be analyzed systematically based on the prevalence of the variant in the population compared to prevalence of disease, evidence that other variants in the gene are pathologic, consistency of prediction software on pathogenicity, and the current clinical consensus. John Wiley and Sons Inc. 2018-12-14 /pmc/articles/PMC6332775/ /pubmed/30656044 http://dx.doi.org/10.1002/ccr3.1920 Text en © 2018 The Authors. Clinical Case Reports published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Case Reports Connell, Patrick S. Jeewa, Aamir Kearney, Debra L. Tunuguntla, Hari Denfield, Susan W. Allen, Hugh D. Landstrom, Andrew P. A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
title | A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
title_full | A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
title_fullStr | A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
title_full_unstemmed | A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
title_short | A 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
title_sort | 14‐year‐old in heart failure with multiple cardiomyopathy variants illustrates a role for signal‐to‐noise analysis in gene test re‐interpretation |
topic | Case Reports |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332775/ https://www.ncbi.nlm.nih.gov/pubmed/30656044 http://dx.doi.org/10.1002/ccr3.1920 |
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