The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023
BackgroundNext-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 Patholog...
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Published in: | Human genomics Vol. 17; no. 1; pp. 1 - 15 |
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Abstract | BackgroundNext-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.ResultsFirst, 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.ConclusionsThe 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. |
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AbstractList | Abstract 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. 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.BACKGROUNDNext-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.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.RESULTSFirst, 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.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.CONCLUSIONSThe 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. BackgroundNext-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.ResultsFirst, 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.ConclusionsThe 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. |
ArticleNumber | 102 |
Author | Chazanas, Pedro Lui Nigro Gretschischkin, Michel Chieregato Nakamura, Carolina Naomi Izo de Lima, Larissa Barbosa Perrone, Eduardo Cintra, Vivian Pedigone Moura, Lais Rodrigues do Nascimento, Amanda Thamires Batista do Amaral Virmond, Luiza Quaio, Caio Robledo D’Angioli Costa de Araujo Espolaor, Jessica Grasiela Teixeira, Anne Caroline Barbosa Prota, Joana Rosa Marques Guedes, Rafael Lucas Muniz Chen, Kelin Ceroni, José Ricardo Magliocco Silva, Thiago Yoshinaga Tonholo Cardoso, Milena Andreuzo Moraes, Gabriel Hideki Izuka Moura, Livia Maria Silva Pereira, Michele Araújo Minillo, Renata Moldenhauer de Oliveira Pelegrino, Karla Lage, Fernanda Stussi Duarte de Souza Reis, Rodrigo Moreno, Carolina Araujo de Almeida, Giovanna Bloise Caraciolo, Marcel Pinheiro Cervato, Murilo Castro De França, Marina Biondo, Cheysa Arielly do Nascimento Júnior, José Bandeira de Paula Azevedo, Victor de Oliveira, Gustavo Santos Yamada, Renata Yoshiko Toledo, Carmen Melo de Mello, Mariana Rezende Bandeira de Almeida, Tatiana Ferreira de Oliveira F |
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Cites_doi | 10.1002/ajmg.c.31860 10.1038/gim.2018.42 10.1056/NEJMsr1406261 10.1016/j.cell.2018.12.015 10.1038/s41467-022-28648-3 10.1186/s13073-019-0616-z 10.1038/gim.2015.30 10.1186/s13059-017-1353-5 10.1038/gim.2017.210 10.1016/j.ajhg.2022.10.013 10.1002/humu.23642 10.1038/s41436-019-0686-8 10.1002/humu.24088 10.1093/nar/29.1.308 10.1002/cphg.93 10.1101/2022.03.20.485034 10.1016/j.ajhg.2009.03.010 10.1002/humu.23626 10.1093/nar/gku1206 10.1038/s41598-022-11932-z 10.1093/nar/gkx1153 10.1101/833582 10.1111/j.1399-0004.2011.01818.x 10.1016/j.jmoldx.2016.10.002 10.1016/j.ajhg.2017.04.015 10.1038/nature19057 10.1186/s13073-019-0690-2 10.1101/gr.3577405 10.1038/s41598-019-49224-8 |
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Snippet | BackgroundNext-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it... Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates... Abstract Background Next-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic... |
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Title | The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023 |
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