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The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023
BACKGROUND: Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates can be challenging. To address this, the American College of Medical Genetics and Genomics and the Association for Molecular Pathol...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10652504/ https://www.ncbi.nlm.nih.gov/pubmed/37968704 http://dx.doi.org/10.1186/s40246-023-00549-6 |
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author | Quaio, Caio Robledo D’Angioli Costa Ceroni, José Ricardo Magliocco Pereira, Michele Araújo Teixeira, Anne Caroline Barbosa Yamada, Renata Yoshiko Cintra, Vivian Pedigone Perrone, Eduardo De França, Marina Chen, Kelin Minillo, Renata Moldenhauer Biondo, Cheysa Arielly de Mello, Mariana Rezende Bandeira Moura, Lais Rodrigues do Nascimento, Amanda Thamires Batista de Oliveira Pelegrino, Karla de Lima, Larissa Barbosa do Amaral Virmond, Luiza Moreno, Carolina Araujo Prota, Joana Rosa Marques de Araujo Espolaor, Jessica Grasiela Silva, Thiago Yoshinaga Tonholo Moraes, Gabriel Hideki Izuka de Oliveira, Gustavo Santos Moura, Livia Maria Silva Caraciolo, Marcel Pinheiro Guedes, Rafael Lucas Muniz Gretschischkin, Michel Chieregato Chazanas, Pedro Lui Nigro Nakamura, Carolina Naomi Izo de Souza Reis, Rodrigo Toledo, Carmen Melo Lage, Fernanda Stussi Duarte de Almeida, Giovanna Bloise do Nascimento Júnior, José Bandeira Cardoso, Milena Andreuzo de Paula Azevedo, Victor de Almeida, Tatiana Ferreira Cervato, Murilo Castro de Oliveira Filho, Joao Bosco |
author_facet | Quaio, Caio Robledo D’Angioli Costa Ceroni, José Ricardo Magliocco Pereira, Michele Araújo Teixeira, Anne Caroline Barbosa Yamada, Renata Yoshiko Cintra, Vivian Pedigone Perrone, Eduardo De França, Marina Chen, Kelin Minillo, Renata Moldenhauer Biondo, Cheysa Arielly de Mello, Mariana Rezende Bandeira Moura, Lais Rodrigues do Nascimento, Amanda Thamires Batista de Oliveira Pelegrino, Karla de Lima, Larissa Barbosa do Amaral Virmond, Luiza Moreno, Carolina Araujo Prota, Joana Rosa Marques de Araujo Espolaor, Jessica Grasiela Silva, Thiago Yoshinaga Tonholo Moraes, Gabriel Hideki Izuka de Oliveira, Gustavo Santos Moura, Livia Maria Silva Caraciolo, Marcel Pinheiro Guedes, Rafael Lucas Muniz Gretschischkin, Michel Chieregato Chazanas, Pedro Lui Nigro Nakamura, Carolina Naomi Izo de Souza Reis, Rodrigo Toledo, Carmen Melo Lage, Fernanda Stussi Duarte de Almeida, Giovanna Bloise do Nascimento Júnior, José Bandeira Cardoso, Milena Andreuzo de Paula Azevedo, Victor de Almeida, Tatiana Ferreira Cervato, Murilo Castro de Oliveira Filho, Joao Bosco |
author_sort | Quaio, Caio Robledo D’Angioli Costa |
collection | PubMed |
description | BACKGROUND: Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates can be challenging. To address this, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology have established guidelines for standardized variant interpretation. In this manuscript, we present the updated Hospital Israelita Albert Einstein Standards for Constitutional Sequence Variants Classification, incorporating modifications from leading genetics societies and the ClinGen initiative. RESULTS: First, we standardized the scientific publications, documents, and other reliable sources for this document to ensure an evidence-based approach. Next, we defined the databases that would provide variant information for the classification process, established the terminology for molecular findings, set standards for disease-gene associations, and determined the nomenclature for classification criteria. Subsequently, we defined the general rules for variant classification and the Bayesian statistical reasoning principles to enhance this process. We also defined bioinformatics standards for automated classification. Our workgroup adhered to gene-specific rules and workflows curated by the ClinGen Variant Curation Expert Panels whenever available. Additionally, a distinct set of specifications for criteria modulation was created for cancer genes, recognizing their unique characteristics. CONCLUSIONS: The development of an internal consensus and standards for constitutional sequence variant classification, specifically adapted to the Brazilian population, further contributes to the continuous refinement of variant classification practices. The aim of these efforts from the workgroup is to enhance the reliability and uniformity of variant classification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00549-6. |
format | Online Article Text |
id | pubmed-10652504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106525042023-11-16 The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 Quaio, Caio Robledo D’Angioli Costa Ceroni, José Ricardo Magliocco Pereira, Michele Araújo Teixeira, Anne Caroline Barbosa Yamada, Renata Yoshiko Cintra, Vivian Pedigone Perrone, Eduardo De França, Marina Chen, Kelin Minillo, Renata Moldenhauer Biondo, Cheysa Arielly de Mello, Mariana Rezende Bandeira Moura, Lais Rodrigues do Nascimento, Amanda Thamires Batista de Oliveira Pelegrino, Karla de Lima, Larissa Barbosa do Amaral Virmond, Luiza Moreno, Carolina Araujo Prota, Joana Rosa Marques de Araujo Espolaor, Jessica Grasiela Silva, Thiago Yoshinaga Tonholo Moraes, Gabriel Hideki Izuka de Oliveira, Gustavo Santos Moura, Livia Maria Silva Caraciolo, Marcel Pinheiro Guedes, Rafael Lucas Muniz Gretschischkin, Michel Chieregato Chazanas, Pedro Lui Nigro Nakamura, Carolina Naomi Izo de Souza Reis, Rodrigo Toledo, Carmen Melo Lage, Fernanda Stussi Duarte de Almeida, Giovanna Bloise do Nascimento Júnior, José Bandeira Cardoso, Milena Andreuzo de Paula Azevedo, Victor de Almeida, Tatiana Ferreira Cervato, Murilo Castro de Oliveira Filho, Joao Bosco Hum Genomics Research BACKGROUND: Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates can be challenging. To address this, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology have established guidelines for standardized variant interpretation. In this manuscript, we present the updated Hospital Israelita Albert Einstein Standards for Constitutional Sequence Variants Classification, incorporating modifications from leading genetics societies and the ClinGen initiative. RESULTS: First, we standardized the scientific publications, documents, and other reliable sources for this document to ensure an evidence-based approach. Next, we defined the databases that would provide variant information for the classification process, established the terminology for molecular findings, set standards for disease-gene associations, and determined the nomenclature for classification criteria. Subsequently, we defined the general rules for variant classification and the Bayesian statistical reasoning principles to enhance this process. We also defined bioinformatics standards for automated classification. Our workgroup adhered to gene-specific rules and workflows curated by the ClinGen Variant Curation Expert Panels whenever available. Additionally, a distinct set of specifications for criteria modulation was created for cancer genes, recognizing their unique characteristics. CONCLUSIONS: The development of an internal consensus and standards for constitutional sequence variant classification, specifically adapted to the Brazilian population, further contributes to the continuous refinement of variant classification practices. The aim of these efforts from the workgroup is to enhance the reliability and uniformity of variant classification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00549-6. BioMed Central 2023-11-16 /pmc/articles/PMC10652504/ /pubmed/37968704 http://dx.doi.org/10.1186/s40246-023-00549-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Quaio, Caio Robledo D’Angioli Costa Ceroni, José Ricardo Magliocco Pereira, Michele Araújo Teixeira, Anne Caroline Barbosa Yamada, Renata Yoshiko Cintra, Vivian Pedigone Perrone, Eduardo De França, Marina Chen, Kelin Minillo, Renata Moldenhauer Biondo, Cheysa Arielly de Mello, Mariana Rezende Bandeira Moura, Lais Rodrigues do Nascimento, Amanda Thamires Batista de Oliveira Pelegrino, Karla de Lima, Larissa Barbosa do Amaral Virmond, Luiza Moreno, Carolina Araujo Prota, Joana Rosa Marques de Araujo Espolaor, Jessica Grasiela Silva, Thiago Yoshinaga Tonholo Moraes, Gabriel Hideki Izuka de Oliveira, Gustavo Santos Moura, Livia Maria Silva Caraciolo, Marcel Pinheiro Guedes, Rafael Lucas Muniz Gretschischkin, Michel Chieregato Chazanas, Pedro Lui Nigro Nakamura, Carolina Naomi Izo de Souza Reis, Rodrigo Toledo, Carmen Melo Lage, Fernanda Stussi Duarte de Almeida, Giovanna Bloise do Nascimento Júnior, José Bandeira Cardoso, Milena Andreuzo de Paula Azevedo, Victor de Almeida, Tatiana Ferreira Cervato, Murilo Castro de Oliveira Filho, Joao Bosco The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
title | The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
title_full | The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
title_fullStr | The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
title_full_unstemmed | The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
title_short | The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
title_sort | hospital israelita albert einstein standards for constitutional sequence variants classification: version 2023 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10652504/ https://www.ncbi.nlm.nih.gov/pubmed/37968704 http://dx.doi.org/10.1186/s40246-023-00549-6 |
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