Systematic collaborative reanalysis of genomic data improves diagnostic yield in neurologic rare diseases

Bullich, Gemma; Matalonga, Leslie; Pujadas, Montserrat; Papakonstantinou Ntalis, Anastasios; Piscia, Davide; Tonda, Raúl; González, Juan Ramón; Laurie, Steven, 1973-; Luengo, Cristina; Ovelleiro, David; Parra Farré, Genís; Pérez Jurado, Luis Alberto; Beltran, Sergi; Undiagnosed Rare Disease Program of Catalonia (URD-Cat) Consortium

Systematic collaborative reanalysis of genomic data improves diagnostic yield in neurologic rare diseases

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dc.contributor.author Bullich, Gemma
dc.contributor.author Matalonga, Leslie
dc.contributor.author Pujadas, Montserrat
dc.contributor.author Papakonstantinou Ntalis, Anastasios
dc.contributor.author Piscia, Davide
dc.contributor.author Tonda, Raúl
dc.contributor.author González, Juan Ramón
dc.contributor.author Laurie, Steven, 1973-
dc.contributor.author Luengo, Cristina
dc.contributor.author Ovelleiro, David
dc.contributor.author Parra Farré, Genís
dc.contributor.author Pérez Jurado, Luis Alberto
dc.contributor.author Beltran, Sergi
dc.contributor.author Undiagnosed Rare Disease Program of Catalonia (URD-Cat) Consortium
dc.date.accessioned 2022-06-22T08:08:21Z
dc.date.available 2022-06-22T08:08:21Z
dc.date.issued 2022
dc.description.abstract Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%).
dc.description.sponsorship Supported by Generalitat de Catalunya through Departament de Salut (SLT002/16/00174 to URD-Cat consortium) and Departament d’Empresa i Coneixement and the CERCA Program; FP7 and H2020 EU projects RD-Connect, Solve-RD, and EJP-RD grants FP7 305444, H2020 779257, and H2020 825575 for CNAG-CRG; Spanish Ministry of Science and Innovation to the EMBL partnership and through the Instituto de Salud Carlos III grants PT13/0001/0044 and PT17/0009/0019 for CNAG-CRG and grants PI16/01048, PI19/01310, PI18/00451, PI18/00498, and PI21/00935 for IDIBAPS (Instituto Nacional de Bioinformática); ELIXIR Implementation Studies (CNAG-CRG); Centro de Investigaciones Biomédicas en Red de Enfermedades Raras; Centro de Excelencia Severo Ochoa grant SEV-2016-0571 (CNAG-CRG) and grant CEX 2018-000806-S (ISGLOBAL); and cofinancing with funds from the European Regional Development Fund by the Spanish Ministry of Science and Innovation corresponding to the Programa Operativo FEDER Plurirregional de España (POPE) 2014 to 2020 and by the Secretaria d’Universitats i Recerca, Departament d’Empresa i Coneixement of the Generalitat de Catalunya corresponding to the Programa Operatiu FEDER de Catalunya 2014 to 2020.
dc.format.mimetype application/pdf
dc.identifier.citation Bullich G, Matalonga L, Pujadas M, Papakonstantinou A, Piscia D, Tonda R et al. Systematic collaborative reanalysis of genomic data improves diagnostic yield in neurologic rare diseases. J Mol Diagn. 2022 May;24(5):529-42. DOI: 10.1016/j.jmoldx.2022.02.003
dc.identifier.doi http://dx.doi.org/10.1016/j.jmoldx.2022.02.003
dc.identifier.issn 1525-1578
dc.identifier.uri http://hdl.handle.net/10230/53563
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof J Mol Diagn. 2022 May;24(5):529-42
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/305444
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/779257
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825575
dc.rights © 2022 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0).
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0
dc.title Systematic collaborative reanalysis of genomic data improves diagnostic yield in neurologic rare diseases
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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Articles (Departament de Medicina i Ciències de la Vida)
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