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Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data
PURPOSE: McArdle disease is one of the most common glycogen storage disorders. Although the exact prevalence is not known, it has been estimated to be 1 in 100,000 patients in the United States. More than 100 mutations in PYGM have been associated with this disorder. McArdle disease has significant...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561039/ https://www.ncbi.nlm.nih.gov/pubmed/25741863 http://dx.doi.org/10.1038/gim.2015.9 |
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author | De Castro, Mauricio Johnston, Jennifer Biesecker, Leslie |
author_facet | De Castro, Mauricio Johnston, Jennifer Biesecker, Leslie |
author_sort | De Castro, Mauricio |
collection | PubMed |
description | PURPOSE: McArdle disease is one of the most common glycogen storage disorders. Although the exact prevalence is not known, it has been estimated to be 1 in 100,000 patients in the United States. More than 100 mutations in PYGM have been associated with this disorder. McArdle disease has significant clinical variability with some patients presenting with severe muscle pain and weakness while others have only mild, exercise-related symptoms. METHODS: Next-Generation sequencing data allow estimation of disease prevalence with minimal ascertainment bias. We analyzed gene frequencies in two cohorts of patients from exome sequencing results. We categorized variants into three groups: a curated set of published mutations, variants of uncertain significance, and likely benign variants. RESULTS: An initial estimate based on the frequency of six common mutations predicts a disease prevalence of 1/7,650 (95% CI 1/5,362 to 1/11,108), which greatly deviates from published estimates. A second method using the two most common mutations predicts a prevalence of 1/42,355 (95% CI 1/24,536 - 1/76,310) in Caucasians. CONCLUSIONS: These results suggest that the currently accepted prevalence of McArdle disease is an underestimate and that some of the currently considered pathogenic variants are likely benign. |
format | Online Article Text |
id | pubmed-4561039 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
record_format | MEDLINE/PubMed |
spelling | pubmed-45610392016-05-18 Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data De Castro, Mauricio Johnston, Jennifer Biesecker, Leslie Genet Med Article PURPOSE: McArdle disease is one of the most common glycogen storage disorders. Although the exact prevalence is not known, it has been estimated to be 1 in 100,000 patients in the United States. More than 100 mutations in PYGM have been associated with this disorder. McArdle disease has significant clinical variability with some patients presenting with severe muscle pain and weakness while others have only mild, exercise-related symptoms. METHODS: Next-Generation sequencing data allow estimation of disease prevalence with minimal ascertainment bias. We analyzed gene frequencies in two cohorts of patients from exome sequencing results. We categorized variants into three groups: a curated set of published mutations, variants of uncertain significance, and likely benign variants. RESULTS: An initial estimate based on the frequency of six common mutations predicts a disease prevalence of 1/7,650 (95% CI 1/5,362 to 1/11,108), which greatly deviates from published estimates. A second method using the two most common mutations predicts a prevalence of 1/42,355 (95% CI 1/24,536 - 1/76,310) in Caucasians. CONCLUSIONS: These results suggest that the currently accepted prevalence of McArdle disease is an underestimate and that some of the currently considered pathogenic variants are likely benign. 2015-03-05 2015-12 /pmc/articles/PMC4561039/ /pubmed/25741863 http://dx.doi.org/10.1038/gim.2015.9 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article De Castro, Mauricio Johnston, Jennifer Biesecker, Leslie Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data |
title | Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data |
title_full | Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data |
title_fullStr | Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data |
title_full_unstemmed | Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data |
title_short | Determining the prevalence of McArdle disease from gene frequency by analysis of next generation sequencing data: McArdle prevalence by NGS data |
title_sort | determining the prevalence of mcardle disease from gene frequency by analysis of next generation sequencing data: mcardle prevalence by ngs data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4561039/ https://www.ncbi.nlm.nih.gov/pubmed/25741863 http://dx.doi.org/10.1038/gim.2015.9 |
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