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Recent advances in understanding the molecular genetic basis of mitochondrial disease

Mitochondrial disease is hugely diverse with respect to associated clinical presentations and underlying genetic causes, with pathogenic variants in over 300 disease genes currently described. Approximately half of these have been discovered in the last decade due to the increasingly widespread appl...

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Autores principales: Thompson, Kyle, Collier, Jack J., Glasgow, Ruth I. C., Robertson, Fiona M., Pyle, Angela, Blakely, Emma L., Alston, Charlotte L., Oláhová, Monika, McFarland, Robert, Taylor, Robert W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041634/
https://www.ncbi.nlm.nih.gov/pubmed/31021000
http://dx.doi.org/10.1002/jimd.12104
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author Thompson, Kyle
Collier, Jack J.
Glasgow, Ruth I. C.
Robertson, Fiona M.
Pyle, Angela
Blakely, Emma L.
Alston, Charlotte L.
Oláhová, Monika
McFarland, Robert
Taylor, Robert W.
author_facet Thompson, Kyle
Collier, Jack J.
Glasgow, Ruth I. C.
Robertson, Fiona M.
Pyle, Angela
Blakely, Emma L.
Alston, Charlotte L.
Oláhová, Monika
McFarland, Robert
Taylor, Robert W.
author_sort Thompson, Kyle
collection PubMed
description Mitochondrial disease is hugely diverse with respect to associated clinical presentations and underlying genetic causes, with pathogenic variants in over 300 disease genes currently described. Approximately half of these have been discovered in the last decade due to the increasingly widespread application of next generation sequencing technologies, in particular unbiased, whole exome—and latterly, whole genome sequencing. These technologies allow more genetic data to be collected from patients with mitochondrial disorders, continually improving the diagnostic success rate in a clinical setting. Despite these significant advances, some patients still remain without a definitive genetic diagnosis. Large datasets containing many variants of unknown significance have become a major challenge with next generation sequencing strategies and these require significant functional validation to confirm pathogenicity. This interface between diagnostics and research is critical in continuing to expand the list of known pathogenic variants and concomitantly enhance our knowledge of mitochondrial biology. The increasing use of whole exome sequencing, whole genome sequencing and other “omics” techniques such as transcriptomics and proteomics will generate even more data and allow further interrogation and validation of genetic causes, including those outside of coding regions. This will improve diagnostic yields still further and emphasizes the integral role that functional assessment of variant causality plays in this process—the overarching focus of this review.
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spelling pubmed-70416342020-03-03 Recent advances in understanding the molecular genetic basis of mitochondrial disease Thompson, Kyle Collier, Jack J. Glasgow, Ruth I. C. Robertson, Fiona M. Pyle, Angela Blakely, Emma L. Alston, Charlotte L. Oláhová, Monika McFarland, Robert Taylor, Robert W. J Inherit Metab Dis Review Articles Mitochondrial disease is hugely diverse with respect to associated clinical presentations and underlying genetic causes, with pathogenic variants in over 300 disease genes currently described. Approximately half of these have been discovered in the last decade due to the increasingly widespread application of next generation sequencing technologies, in particular unbiased, whole exome—and latterly, whole genome sequencing. These technologies allow more genetic data to be collected from patients with mitochondrial disorders, continually improving the diagnostic success rate in a clinical setting. Despite these significant advances, some patients still remain without a definitive genetic diagnosis. Large datasets containing many variants of unknown significance have become a major challenge with next generation sequencing strategies and these require significant functional validation to confirm pathogenicity. This interface between diagnostics and research is critical in continuing to expand the list of known pathogenic variants and concomitantly enhance our knowledge of mitochondrial biology. The increasing use of whole exome sequencing, whole genome sequencing and other “omics” techniques such as transcriptomics and proteomics will generate even more data and allow further interrogation and validation of genetic causes, including those outside of coding regions. This will improve diagnostic yields still further and emphasizes the integral role that functional assessment of variant causality plays in this process—the overarching focus of this review. John Wiley & Sons, Inc. 2019-05-10 2020-01 /pmc/articles/PMC7041634/ /pubmed/31021000 http://dx.doi.org/10.1002/jimd.12104 Text en © 2019 The Authors. Journal of Inherited Metabolic Disease published by John Wiley & Sons Ltd on behalf of SSIEM 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 Review Articles
Thompson, Kyle
Collier, Jack J.
Glasgow, Ruth I. C.
Robertson, Fiona M.
Pyle, Angela
Blakely, Emma L.
Alston, Charlotte L.
Oláhová, Monika
McFarland, Robert
Taylor, Robert W.
Recent advances in understanding the molecular genetic basis of mitochondrial disease
title Recent advances in understanding the molecular genetic basis of mitochondrial disease
title_full Recent advances in understanding the molecular genetic basis of mitochondrial disease
title_fullStr Recent advances in understanding the molecular genetic basis of mitochondrial disease
title_full_unstemmed Recent advances in understanding the molecular genetic basis of mitochondrial disease
title_short Recent advances in understanding the molecular genetic basis of mitochondrial disease
title_sort recent advances in understanding the molecular genetic basis of mitochondrial disease
topic Review Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041634/
https://www.ncbi.nlm.nih.gov/pubmed/31021000
http://dx.doi.org/10.1002/jimd.12104
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