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Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios

PURPOSE: Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating...

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Autores principales: Zhu, Xiaolin, Petrovski, Slavé, Xie, Pingxing, Ruzzo, Elizabeth K., Lu, Yi-Fan, McSweeney, K. Melodi, Ben-Zeev, Bruria, Nissenkorn, Andreea, Anikster, Yair, Oz-Levi, Danit, Dhindsa, Ryan S., Hitomi, Yuki, Schoch, Kelly, Spillmann, Rebecca C., Heimer, Gali, Marek-Yagel, Dina, Tzadok, Michal, Han, Yujun, Worley, Gordon, Goldstein, Jennifer, Jiang, Yong-Hui, Lancet, Doron, Pras, Elon, Shashi, Vandana, McHale, Duncan, Need, Anna C., Goldstein, David B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4791490/
https://www.ncbi.nlm.nih.gov/pubmed/25590979
http://dx.doi.org/10.1038/gim.2014.191
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author Zhu, Xiaolin
Petrovski, Slavé
Xie, Pingxing
Ruzzo, Elizabeth K.
Lu, Yi-Fan
McSweeney, K. Melodi
Ben-Zeev, Bruria
Nissenkorn, Andreea
Anikster, Yair
Oz-Levi, Danit
Dhindsa, Ryan S.
Hitomi, Yuki
Schoch, Kelly
Spillmann, Rebecca C.
Heimer, Gali
Marek-Yagel, Dina
Tzadok, Michal
Han, Yujun
Worley, Gordon
Goldstein, Jennifer
Jiang, Yong-Hui
Lancet, Doron
Pras, Elon
Shashi, Vandana
McHale, Duncan
Need, Anna C.
Goldstein, David B.
author_facet Zhu, Xiaolin
Petrovski, Slavé
Xie, Pingxing
Ruzzo, Elizabeth K.
Lu, Yi-Fan
McSweeney, K. Melodi
Ben-Zeev, Bruria
Nissenkorn, Andreea
Anikster, Yair
Oz-Levi, Danit
Dhindsa, Ryan S.
Hitomi, Yuki
Schoch, Kelly
Spillmann, Rebecca C.
Heimer, Gali
Marek-Yagel, Dina
Tzadok, Michal
Han, Yujun
Worley, Gordon
Goldstein, Jennifer
Jiang, Yong-Hui
Lancet, Doron
Pras, Elon
Shashi, Vandana
McHale, Duncan
Need, Anna C.
Goldstein, David B.
author_sort Zhu, Xiaolin
collection PubMed
description PURPOSE: Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene–disease associations. Genet Med 17 10, 774–781. METHODS: We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients. Genet Med 17 10, 774–781. RESULTS: We obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10(−8)). This enrichment is only partially explained by mutations found in known disease-causing genes. Genet Med 17 10, 774–781. CONCLUSION: This work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications. Genet Med 17 10, 774–781.
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spelling pubmed-47914902016-03-21 Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios Zhu, Xiaolin Petrovski, Slavé Xie, Pingxing Ruzzo, Elizabeth K. Lu, Yi-Fan McSweeney, K. Melodi Ben-Zeev, Bruria Nissenkorn, Andreea Anikster, Yair Oz-Levi, Danit Dhindsa, Ryan S. Hitomi, Yuki Schoch, Kelly Spillmann, Rebecca C. Heimer, Gali Marek-Yagel, Dina Tzadok, Michal Han, Yujun Worley, Gordon Goldstein, Jennifer Jiang, Yong-Hui Lancet, Doron Pras, Elon Shashi, Vandana McHale, Duncan Need, Anna C. Goldstein, David B. Genet Med Original Research Article PURPOSE: Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene–disease associations. Genet Med 17 10, 774–781. METHODS: We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients. Genet Med 17 10, 774–781. RESULTS: We obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10(−8)). This enrichment is only partially explained by mutations found in known disease-causing genes. Genet Med 17 10, 774–781. CONCLUSION: This work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications. Genet Med 17 10, 774–781. Nature Publishing Group 2015-10 2015-01-15 /pmc/articles/PMC4791490/ /pubmed/25590979 http://dx.doi.org/10.1038/gim.2014.191 Text en Copyright © 2015 American College of Medical Genetics and Genomics http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Original Research Article
Zhu, Xiaolin
Petrovski, Slavé
Xie, Pingxing
Ruzzo, Elizabeth K.
Lu, Yi-Fan
McSweeney, K. Melodi
Ben-Zeev, Bruria
Nissenkorn, Andreea
Anikster, Yair
Oz-Levi, Danit
Dhindsa, Ryan S.
Hitomi, Yuki
Schoch, Kelly
Spillmann, Rebecca C.
Heimer, Gali
Marek-Yagel, Dina
Tzadok, Michal
Han, Yujun
Worley, Gordon
Goldstein, Jennifer
Jiang, Yong-Hui
Lancet, Doron
Pras, Elon
Shashi, Vandana
McHale, Duncan
Need, Anna C.
Goldstein, David B.
Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
title Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
title_full Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
title_fullStr Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
title_full_unstemmed Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
title_short Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
title_sort whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4791490/
https://www.ncbi.nlm.nih.gov/pubmed/25590979
http://dx.doi.org/10.1038/gim.2014.191
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