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Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology
Advances in genome sequencing technologies have unlocked new possibilities in identifying disease-associated and causative genetic markers, which may in turn enhance disease diagnosis and improve prognostication and management strategies. With the capability of examining genetic variations ranging f...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331588/ https://www.ncbi.nlm.nih.gov/pubmed/37435434 http://dx.doi.org/10.1212/NXG.0000000000200005 |
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author | Lin, Xin Yang, Yuanhao Melton, Phillip E. Singh, Vikrant Simpson-Yap, Steve Burdon, Kathryn P. Taylor, Bruce V. Zhou, Yuan |
author_facet | Lin, Xin Yang, Yuanhao Melton, Phillip E. Singh, Vikrant Simpson-Yap, Steve Burdon, Kathryn P. Taylor, Bruce V. Zhou, Yuan |
author_sort | Lin, Xin |
collection | PubMed |
description | Advances in genome sequencing technologies have unlocked new possibilities in identifying disease-associated and causative genetic markers, which may in turn enhance disease diagnosis and improve prognostication and management strategies. With the capability of examining genetic variations ranging from single-nucleotide mutations to large structural variants, whole-genome sequencing (WGS) is an increasingly adopted approach to dissect the complex genetic architecture of neurologic diseases. There is emerging evidence for different structural variants and their roles in major neurologic and neurodevelopmental diseases. This review first describes different structural variants and their implicated roles in major neurologic and neurodevelopmental diseases, and then discusses the clinical relevance of WGS applications in neurology. Notably, WGS-based detection of structural variants has shown promising potential in enhancing diagnostic power of genetic tests in clinical settings. Ongoing WGS-based research in structural variations and quantifying mutational constraints can also yield clinical benefits by improving variant interpretation and disease diagnosis, while supporting biomarker discovery and therapeutic development. As a result, wider integration of WGS technologies into health care will likely increase diagnostic yields in difficult-to-diagnose conditions and define potential therapeutic targets or intervention points for genome-editing strategies. |
format | Online Article Text |
id | pubmed-10331588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Wolters Kluwer |
record_format | MEDLINE/PubMed |
spelling | pubmed-103315882023-07-11 Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology Lin, Xin Yang, Yuanhao Melton, Phillip E. Singh, Vikrant Simpson-Yap, Steve Burdon, Kathryn P. Taylor, Bruce V. Zhou, Yuan Neurol Genet Review Advances in genome sequencing technologies have unlocked new possibilities in identifying disease-associated and causative genetic markers, which may in turn enhance disease diagnosis and improve prognostication and management strategies. With the capability of examining genetic variations ranging from single-nucleotide mutations to large structural variants, whole-genome sequencing (WGS) is an increasingly adopted approach to dissect the complex genetic architecture of neurologic diseases. There is emerging evidence for different structural variants and their roles in major neurologic and neurodevelopmental diseases. This review first describes different structural variants and their implicated roles in major neurologic and neurodevelopmental diseases, and then discusses the clinical relevance of WGS applications in neurology. Notably, WGS-based detection of structural variants has shown promising potential in enhancing diagnostic power of genetic tests in clinical settings. Ongoing WGS-based research in structural variations and quantifying mutational constraints can also yield clinical benefits by improving variant interpretation and disease diagnosis, while supporting biomarker discovery and therapeutic development. As a result, wider integration of WGS technologies into health care will likely increase diagnostic yields in difficult-to-diagnose conditions and define potential therapeutic targets or intervention points for genome-editing strategies. Wolters Kluwer 2022-05-27 /pmc/articles/PMC10331588/ /pubmed/37435434 http://dx.doi.org/10.1212/NXG.0000000000200005 Text en Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Review Lin, Xin Yang, Yuanhao Melton, Phillip E. Singh, Vikrant Simpson-Yap, Steve Burdon, Kathryn P. Taylor, Bruce V. Zhou, Yuan Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology |
title | Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology |
title_full | Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology |
title_fullStr | Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology |
title_full_unstemmed | Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology |
title_short | Integrating Genetic Structural Variations and Whole-Genome Sequencing Into Clinical Neurology |
title_sort | integrating genetic structural variations and whole-genome sequencing into clinical neurology |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331588/ https://www.ncbi.nlm.nih.gov/pubmed/37435434 http://dx.doi.org/10.1212/NXG.0000000000200005 |
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