Cargando…

MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations

We have developed MAGI-ACMG, a classification algorithm that allows the classification of sequencing variants (single nucleotide or small indels) according to the recommendations of the American College of Medical Genetics (ACMG) and the Association for Clinical Genomic Science (ACGS). The MAGI-ACMG...

Descripción completa

Detalles Bibliográficos
Autores principales: Cristofoli, Francesca, Daja, Muharrem, Maltese, Paolo Enrico, Guerri, Giulia, Tanzi, Benedetta, Miotto, Roberta, Bonetti, Gabriele, Miertus, Jan, Chiurazzi, Pietro, Stuppia, Liborio, Gatta, Valentina, Cecchin, Stefano, Bertelli, Matteo, Marceddu, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10454715/
https://www.ncbi.nlm.nih.gov/pubmed/37628650
http://dx.doi.org/10.3390/genes14081600
_version_ 1785096262838648832
author Cristofoli, Francesca
Daja, Muharrem
Maltese, Paolo Enrico
Guerri, Giulia
Tanzi, Benedetta
Miotto, Roberta
Bonetti, Gabriele
Miertus, Jan
Chiurazzi, Pietro
Stuppia, Liborio
Gatta, Valentina
Cecchin, Stefano
Bertelli, Matteo
Marceddu, Giuseppe
author_facet Cristofoli, Francesca
Daja, Muharrem
Maltese, Paolo Enrico
Guerri, Giulia
Tanzi, Benedetta
Miotto, Roberta
Bonetti, Gabriele
Miertus, Jan
Chiurazzi, Pietro
Stuppia, Liborio
Gatta, Valentina
Cecchin, Stefano
Bertelli, Matteo
Marceddu, Giuseppe
author_sort Cristofoli, Francesca
collection PubMed
description We have developed MAGI-ACMG, a classification algorithm that allows the classification of sequencing variants (single nucleotide or small indels) according to the recommendations of the American College of Medical Genetics (ACMG) and the Association for Clinical Genomic Science (ACGS). The MAGI-ACMG classification algorithm uses information retrieved through the VarSome Application Programming Interface (API), integrates the AutoPVS1 tool in order to evaluate more precisely the attribution of the PVS1 criterion, and performs the customized assignment of specific criteria. In addition, we propose a sub-classification scheme for variants of uncertain significance (VUS) according to their proximity either towards the “likely pathogenic” or “likely benign” classes. We also conceived a pathogenicity potential criterion (P_POT) as a proxy for segregation criteria that might be added to a VUS after posterior testing, thus allowing it to upgrade its clinical significance in a diagnostic reporting setting. Finally, we have developed a user-friendly web application based on the MAGI-ACMG algorithm, available to geneticists for variant interpretation.
format Online
Article
Text
id pubmed-10454715
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-104547152023-08-26 MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations Cristofoli, Francesca Daja, Muharrem Maltese, Paolo Enrico Guerri, Giulia Tanzi, Benedetta Miotto, Roberta Bonetti, Gabriele Miertus, Jan Chiurazzi, Pietro Stuppia, Liborio Gatta, Valentina Cecchin, Stefano Bertelli, Matteo Marceddu, Giuseppe Genes (Basel) Article We have developed MAGI-ACMG, a classification algorithm that allows the classification of sequencing variants (single nucleotide or small indels) according to the recommendations of the American College of Medical Genetics (ACMG) and the Association for Clinical Genomic Science (ACGS). The MAGI-ACMG classification algorithm uses information retrieved through the VarSome Application Programming Interface (API), integrates the AutoPVS1 tool in order to evaluate more precisely the attribution of the PVS1 criterion, and performs the customized assignment of specific criteria. In addition, we propose a sub-classification scheme for variants of uncertain significance (VUS) according to their proximity either towards the “likely pathogenic” or “likely benign” classes. We also conceived a pathogenicity potential criterion (P_POT) as a proxy for segregation criteria that might be added to a VUS after posterior testing, thus allowing it to upgrade its clinical significance in a diagnostic reporting setting. Finally, we have developed a user-friendly web application based on the MAGI-ACMG algorithm, available to geneticists for variant interpretation. MDPI 2023-08-08 /pmc/articles/PMC10454715/ /pubmed/37628650 http://dx.doi.org/10.3390/genes14081600 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cristofoli, Francesca
Daja, Muharrem
Maltese, Paolo Enrico
Guerri, Giulia
Tanzi, Benedetta
Miotto, Roberta
Bonetti, Gabriele
Miertus, Jan
Chiurazzi, Pietro
Stuppia, Liborio
Gatta, Valentina
Cecchin, Stefano
Bertelli, Matteo
Marceddu, Giuseppe
MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations
title MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations
title_full MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations
title_fullStr MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations
title_full_unstemmed MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations
title_short MAGI-ACMG: Algorithm for the Classification of Variants According to ACMG and ACGS Recommendations
title_sort magi-acmg: algorithm for the classification of variants according to acmg and acgs recommendations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10454715/
https://www.ncbi.nlm.nih.gov/pubmed/37628650
http://dx.doi.org/10.3390/genes14081600
work_keys_str_mv AT cristofolifrancesca magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT dajamuharrem magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT maltesepaoloenrico magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT guerrigiulia magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT tanzibenedetta magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT miottoroberta magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT bonettigabriele magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT miertusjan magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT chiurazzipietro magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT stuppialiborio magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT gattavalentina magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT cecchinstefano magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT bertellimatteo magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations
AT marceddugiuseppe magiacmgalgorithmfortheclassificationofvariantsaccordingtoacmgandacgsrecommendations