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

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 reinterpreta...

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Detalles Bibliográficos
Autores: Bullich, Gemma, Matalonga, Leslie, Pujadas, Montserrat, Papakonstantinou, Anastasios, Piscia, Davide, Tonda, Raúl, Artuch, Rafael, Gallano, Pia, Garrabou Tornos, Glòria, González, Juan R., Grinberg Vaisman, Daniel Raúl, Guitart, Míriam, Laurie, Steven, Lázaro García, Conxi, Luengo, Critina, Martí, Ramon, Milà, Montserrat, Ovelleiro, David, Parra, Genís, Pujol, Aurora, 1968-, Tizzano Ferrari, Eduardo, Macaya, Alfonso, Palau, Francesc, Ribes, Antonio, Pérez-Jurado, Luis Alberto, Beltran, Sergi, Undiagnosed Rare Disease Program of Catalonia (URD-Cat) Consortium., Rabionet Janssen, Raquel, Balcells Comas, Susana
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2022
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/194746
Acceso en línea:https://hdl.handle.net/2445/194746
Access Level:acceso abierto
Palabra clave:Malalties rares
Malalties del sistema nerviós
Genòmica
Rare diseases
Nervous system Diseases
Genomics
Descripción
Sumario: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%).

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