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Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis
Advances in the molecular characterisation of genetic muscle disease has been rapid, as demonstrated by a recent analysis of these conditions in the north of England by Norwood et al (2009), in which a genetic diagnosis was achieved for 75.7% of patients. However, there remain many patients with sus...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3682761/ https://www.ncbi.nlm.nih.gov/pubmed/23788081 http://dx.doi.org/10.1371/currents.md.37f840ca67f5e722945ecf755f40487e |
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author | Harris, Elizabeth Laval, Steve Hudson, Judith Barresi, Rita De Waele, Liesbeth Straub, Volker Lochmüller, Hanns Bushby, Kate Sarkozy, Anna |
author_facet | Harris, Elizabeth Laval, Steve Hudson, Judith Barresi, Rita De Waele, Liesbeth Straub, Volker Lochmüller, Hanns Bushby, Kate Sarkozy, Anna |
author_sort | Harris, Elizabeth |
collection | PubMed |
description | Advances in the molecular characterisation of genetic muscle disease has been rapid, as demonstrated by a recent analysis of these conditions in the north of England by Norwood et al (2009), in which a genetic diagnosis was achieved for 75.7% of patients. However, there remain many patients with suspected genetic muscle disease in who a diagnosis is not obtained, often despite considerable diagnostic effort, and these patients are now being considered for the application of new technologies such as next generation sequencing. This study aimed to provide an in-depth phenotype analysis of undiagnosed patients referred to the Northern region muscle clinic with suspected genetic muscle disease, with the intention of gaining insight into these conditions, identifing cases with a shared phenotype who may be amenable to collective diagnostic testing or research, and evaluating the strengths and limitations of our current diagnostic strategy. We used two approaches: a review of clinical findings in patients with undiagnosed muscle disease, and a hierarchical cluster analysis to provide an unbiased interpretation of the phenotype data. These joint approaches identified a correlation of phenotypic features according to the age of disease onset and also delineated several interesting groups of patients, as well as highlighting areas of frequent diagnostic difficulty that could benefit from the use of new high-throughput diagnostic techniques. Correspondence to: anna.sarkozy@ncl.ac.uk |
format | Online Article Text |
id | pubmed-3682761 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-36827612013-06-19 Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis Harris, Elizabeth Laval, Steve Hudson, Judith Barresi, Rita De Waele, Liesbeth Straub, Volker Lochmüller, Hanns Bushby, Kate Sarkozy, Anna PLoS Curr Genetics and Genomics Advances in the molecular characterisation of genetic muscle disease has been rapid, as demonstrated by a recent analysis of these conditions in the north of England by Norwood et al (2009), in which a genetic diagnosis was achieved for 75.7% of patients. However, there remain many patients with suspected genetic muscle disease in who a diagnosis is not obtained, often despite considerable diagnostic effort, and these patients are now being considered for the application of new technologies such as next generation sequencing. This study aimed to provide an in-depth phenotype analysis of undiagnosed patients referred to the Northern region muscle clinic with suspected genetic muscle disease, with the intention of gaining insight into these conditions, identifing cases with a shared phenotype who may be amenable to collective diagnostic testing or research, and evaluating the strengths and limitations of our current diagnostic strategy. We used two approaches: a review of clinical findings in patients with undiagnosed muscle disease, and a hierarchical cluster analysis to provide an unbiased interpretation of the phenotype data. These joint approaches identified a correlation of phenotypic features according to the age of disease onset and also delineated several interesting groups of patients, as well as highlighting areas of frequent diagnostic difficulty that could benefit from the use of new high-throughput diagnostic techniques. Correspondence to: anna.sarkozy@ncl.ac.uk Public Library of Science 2013-05-21 /pmc/articles/PMC3682761/ /pubmed/23788081 http://dx.doi.org/10.1371/currents.md.37f840ca67f5e722945ecf755f40487e Text en http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Genetics and Genomics Harris, Elizabeth Laval, Steve Hudson, Judith Barresi, Rita De Waele, Liesbeth Straub, Volker Lochmüller, Hanns Bushby, Kate Sarkozy, Anna Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis |
title | Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis |
title_full | Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis |
title_fullStr | Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis |
title_full_unstemmed | Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis |
title_short | Undiagnosed Genetic Muscle Disease in the North of England: an in Depth Phenotype Analysis |
title_sort | undiagnosed genetic muscle disease in the north of england: an in depth phenotype analysis |
topic | Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3682761/ https://www.ncbi.nlm.nih.gov/pubmed/23788081 http://dx.doi.org/10.1371/currents.md.37f840ca67f5e722945ecf755f40487e |
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