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Lookup NU author(s): Professor Jordi Diaz ManeraORCiD, Professor Rita HorvathORCiD, Professor Hanns Lochmuller, Professor Volker StraubORCiD, Dr Christina Trainor, Dr Ana TopfORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© The Author(s) 2025. Genetic diagnosis of rare diseases requires accurate identification and interpretation of genomic variants. Clinical and molecular scientists from 37 expert centers across Europe created the Solve-Rare Diseases Consortium (Solve-RD) resource, encompassing clinical, pedigree and genomic rare-disease data (94.5% exomes, 5.5% genomes), and performed systematic reanalysis for 6,447 individuals (3,592 male, 2,855 female) with previously undiagnosed rare diseases from 6,004 families. We established a collaborative, two-level expert review infrastructure that allowed a genetic diagnosis in 506 (8.4%) families. Of 552 disease-causing variants identified, 464 (84.1%) were single-nucleotide variants or short insertions/deletions. These variants were either located in recently published novel disease genes (n = 67), recently reclassified in ClinVar (n = 187) or reclassified by consensus expert decision within Solve-RD (n = 210). Bespoke bioinformatics analyses identified the remaining 15.9% of causative variants (n = 88). Ad hoc expert review, parallel to the systematic reanalysis, diagnosed 249 (4.1%) additional families for an overall diagnostic yield of 12.6%. The infrastructure and collaborative networks set up by Solve-RD can serve as a blueprint for future further scalable international efforts. The resource is open to the global rare-disease community, allowing phenotype, variant and gene queries, as well as genome-wide discoveries.
Author(s): Laurie S, Steyaert W, de Boer E, Polavarapu K, Schuermans N, Sommer AK, Demidov G, Ellwanger K, Paramonov I, Thomas C, Aretz S, Baets J, Benetti E, Bullich G, Chinnery PF, Clayton-Smith J, Cohen E, Danis D, Denomme-Pichon A-S, Diaz-Manera J, Efthymiou S, Faivre L, Fernandez-Callejo M, Freeberg M, Garcia-Pelaez J, Guillot-Noel L, Haack TB, Hanna M, Hengel H, Horvath R, Houlden H, Jackson A, Johansson L, Johari M, Kamsteeg E-J, Kellner M, Kleefstra T, Lacombe D, Lochmuller H, Lopez-Martin E, Macaya A, Marce-Grau A, Maver A, Morsy H, Muntoni F, Musacchia F, Nelson I, Nigro V, Olimpio C, Oliveira C, Paulasova Schwabova J, Pauly MG, Peterlin B, Peters S, Pfundt R, Piluso G, Piscia D, Posada M, Reich S, Renieri A, Ryba L, Sablauskas K, Savarese M, Schols L, Schutz L, Steinke-Lange V, Stevanin G, Straub V, Sturm M, Swertz MA, Tartaglia M, te Paske IBAW, Thompson R, Torella A, Trainor C, Udd B, Van de Vondel L, van de Warrenburg B, van Reeuwijk J, Vandrovcova J, Vitobello A, Vos J, Vyhnalkova E, Wijngaard R, Wilke C, William D, Xu J, Yaldiz B, Zalatnai L, Zurek B, de Voer RM, de Sainte Agathe J-M, de Sainte Agathe J-M, Vissers LELM, Brookes AJ, Evangelista T, Gilissen C, Graessner H, Hoogerbrugge N, Ossowski S, Riess O, Schule R, Synofzik M, Verloes A, Matalonga L, Brunner HG, Lohmann K, Topf A, Vissers LELM, Beltran S, Hoischen A
Publication type: Article
Publication status: Published
Journal: Nature Medicine
Year: 2025
Volume: 31
Pages: 478-489
Print publication date: 01/02/2025
Online publication date: 17/01/2025
Acceptance date: 14/11/2024
Date deposited: 24/02/2025
ISSN (print): 1078-8956
ISSN (electronic): 1546-170X
Publisher: Springer Nature
URL: https://doi.org/10.1038/s41591-024-03420-w
DOI: 10.1038/s41591-024-03420-w
Data Access Statement: Access to pseudonymized phenotypic information for all individuals and their genetic variants is possible through RD-Connect GPAP (https://platform.rd-connect.eu/), on completion of registration and approval by the independent RD-Connect Data Access Committee (Code of Conduct and registration details can be found at https://platform.rd-connect.eu/userregistration/). All raw and processed data files (FASTQs, BAM/CRAMs, gVCFs, PED and Phenopackets) are available at the European Genome-Phenome Archive (https://ega-archive.org/datasets/; datasets EGAD00001009767, EGAD00001009768, EGAD00001009769 and EGAD00001009770, under the Solve-RD study EGAS00001003851), following approval from the Solve-RD Data Access Committee. Confirmed causative variants were submitted to ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/) under the following accession nos: SCV005091231–SCV005091564, SCV005199960–SCV005200075 and SCV005200692–SCV005200738.
PubMed id: 39825153
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