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Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications

Ascertaining a diagnosis through exome sequencing can provide potential benefits to patients, insurance companies, and the healthcare system. Yet, as diagnostic sequencing is increasingly employed, vast amounts of human genetic data are produced that need careful curation. We discuss methods for acc...

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Autores principales: Smith, Erica D., Radtke, Kelly, Rossi, Mari, Shinde, Deepali N., Darabi, Sourat, El‐Khechen, Dima, Powis, Zöe, Helbig, Katherine, Waller, Kendra, Grange, Dorothy K., Tang, Sha, Farwell Hagman, Kelly D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655771/
https://www.ncbi.nlm.nih.gov/pubmed/28106320
http://dx.doi.org/10.1002/humu.23183
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author Smith, Erica D.
Radtke, Kelly
Rossi, Mari
Shinde, Deepali N.
Darabi, Sourat
El‐Khechen, Dima
Powis, Zöe
Helbig, Katherine
Waller, Kendra
Grange, Dorothy K.
Tang, Sha
Farwell Hagman, Kelly D.
author_facet Smith, Erica D.
Radtke, Kelly
Rossi, Mari
Shinde, Deepali N.
Darabi, Sourat
El‐Khechen, Dima
Powis, Zöe
Helbig, Katherine
Waller, Kendra
Grange, Dorothy K.
Tang, Sha
Farwell Hagman, Kelly D.
author_sort Smith, Erica D.
collection PubMed
description Ascertaining a diagnosis through exome sequencing can provide potential benefits to patients, insurance companies, and the healthcare system. Yet, as diagnostic sequencing is increasingly employed, vast amounts of human genetic data are produced that need careful curation. We discuss methods for accurately assessing the clinical validity of gene–disease relationships to interpret new research findings in a clinical context and increase the diagnostic rate. The specifics of a gene–disease scoring system adapted for use in a clinical laboratory are described. In turn, clinical validity scoring of gene–disease relationships can inform exome reporting for the identification of new or the upgrade of previous, clinically relevant gene findings. Our retrospective analysis of all reclassification reports from the first 4 years of diagnostic exome sequencing showed that 78% were due to new gene–disease discoveries published in the literature. Among all exome positive/likely positive findings in characterized genes, 32% were in genetic etiologies that were discovered after 2010. Our data underscore the importance and benefits of active and up‐to‐date curation of a gene–disease database combined with critical clinical validity scoring and proactive reanalysis in the clinical genomics era.
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spelling pubmed-56557712017-11-01 Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications Smith, Erica D. Radtke, Kelly Rossi, Mari Shinde, Deepali N. Darabi, Sourat El‐Khechen, Dima Powis, Zöe Helbig, Katherine Waller, Kendra Grange, Dorothy K. Tang, Sha Farwell Hagman, Kelly D. Hum Mutat Methods Ascertaining a diagnosis through exome sequencing can provide potential benefits to patients, insurance companies, and the healthcare system. Yet, as diagnostic sequencing is increasingly employed, vast amounts of human genetic data are produced that need careful curation. We discuss methods for accurately assessing the clinical validity of gene–disease relationships to interpret new research findings in a clinical context and increase the diagnostic rate. The specifics of a gene–disease scoring system adapted for use in a clinical laboratory are described. In turn, clinical validity scoring of gene–disease relationships can inform exome reporting for the identification of new or the upgrade of previous, clinically relevant gene findings. Our retrospective analysis of all reclassification reports from the first 4 years of diagnostic exome sequencing showed that 78% were due to new gene–disease discoveries published in the literature. Among all exome positive/likely positive findings in characterized genes, 32% were in genetic etiologies that were discovered after 2010. Our data underscore the importance and benefits of active and up‐to‐date curation of a gene–disease database combined with critical clinical validity scoring and proactive reanalysis in the clinical genomics era. John Wiley and Sons Inc. 2017-02-13 2017-05 /pmc/articles/PMC5655771/ /pubmed/28106320 http://dx.doi.org/10.1002/humu.23183 Text en © 2017 The Authors. **Human Mutation published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution (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 Methods
Smith, Erica D.
Radtke, Kelly
Rossi, Mari
Shinde, Deepali N.
Darabi, Sourat
El‐Khechen, Dima
Powis, Zöe
Helbig, Katherine
Waller, Kendra
Grange, Dorothy K.
Tang, Sha
Farwell Hagman, Kelly D.
Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications
title Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications
title_full Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications
title_fullStr Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications
title_full_unstemmed Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications
title_short Classification of Genes: Standardized Clinical Validity Assessment of Gene–Disease Associations Aids Diagnostic Exome Analysis and Reclassifications
title_sort classification of genes: standardized clinical validity assessment of gene–disease associations aids diagnostic exome analysis and reclassifications
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655771/
https://www.ncbi.nlm.nih.gov/pubmed/28106320
http://dx.doi.org/10.1002/humu.23183
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