Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

Matalonga, Leslie; Hernández Ferrer, Carles; Piscia, Davide; Tonda, Raúl; Laurie, Steven, 1973-; Fernández Callejo, Marcos; Picó, Daniel; Garcia-Linares, Carles; Papakonstantinou Ntalis, Anastasios; Corvò, Alberto; Joshi, Ricky S.; Diez, Hector; Gut, Ivo Glynne; Beltran, Sergi; Solve-RD Consortium

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

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dc.contributor.author Matalonga, Leslie
dc.contributor.author Hernández Ferrer, Carles
dc.contributor.author Piscia, Davide
dc.contributor.author Tonda, Raúl
dc.contributor.author Laurie, Steven, 1973-
dc.contributor.author Fernández Callejo, Marcos
dc.contributor.author Picó, Daniel
dc.contributor.author Garcia-Linares, Carles
dc.contributor.author Papakonstantinou Ntalis, Anastasios
dc.contributor.author Corvò, Alberto
dc.contributor.author Joshi, Ricky S.
dc.contributor.author Diez, Hector
dc.contributor.author Gut, Ivo Glynne
dc.contributor.author Beltran, Sergi
dc.contributor.author Solve-RD Consortium
dc.date.accessioned 2021-11-19T07:04:59Z
dc.date.available 2021-11-19T07:04:59Z
dc.date.issued 2021
dc.description.abstract Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.
dc.description.sponsorship The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257. Data were analysed using the RD‐Connect Genome‐Phenome Analysis Platform, which received funding from EU projects RD‐Connect, Solve-RD and EJP-RD (grant numbers FP7 305444, H2020 779257, H2020 825575), Instituto de Salud Carlos III (grant numbers PT13/0001/0044, PT17/0009/0019; Instituto Nacional de Bioinformática, INB) and ELIXIR Implementation Studies.
dc.format.mimetype application/pdf
dc.identifier.citation Matalonga L, Hernández-Ferrer C, Piscia D; Solve-RD SNV-indel working group, Schüle R, Synofzik M et al. Solving patients with rare diseases through programmatic reanalysis of genome-phenome data. Eur J Hum Genet. 2021;29(9):1337-47. DOI: 10.1038/s41431-021-00852-7
dc.identifier.doi http://dx.doi.org/10.1038/s41431-021-00852-7
dc.identifier.issn 1018-4813
dc.identifier.uri http://hdl.handle.net/10230/49023
dc.language.iso eng
dc.publisher Nature Research
dc.relation.ispartof Eur J Hum Genet. 2021;29(9):1337-47
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/779257
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/305444
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825575
dc.rights © The Author(s) 2021. 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.keyword Diseases
dc.subject.keyword Genetic testing
dc.subject.keyword Genome informatics
dc.subject.keyword Genomic analysis
dc.title Solving patients with rare diseases through programmatic reanalysis of genome-phenome data
dc.type info:eu-repo/semantics/article
dc.type.version info:eu-repo/semantics/publishedVersion

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