2026-04-14T02:09:51Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/589952025-12-12T02:56:34Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Lagorce, David author Lebreton, Emeline author Matalonga, Leslie author Hongnat, Oscar author Chahdil, Maroua author Piscia, Davide author Paramonov, Ida author Ellwanger, Kornelia author Köhler, Sebastian author Robinson, Peter N. author Graessner, Holm author Beltran, Sergi author Lucano, Caterina author Hanauer, Marc author Rath, Ana author 2024-02-08T07:10:10Z 2024-02-08T07:10:10Z 2023 Data de publicació electrònica: 06-11-2023 Rare diseases (RD) have a prevalence of not more than 1/2000 persons in the European population, and are characterised by the difficulty experienced in obtaining a correct and timely diagnosis. According to Orphanet, 72.5% of RD have a genetic origin although 35% of them do not yet have an identified causative gene. A significant proportion of patients suspected to have a genetic RD receive an inconclusive exome/genome sequencing. Working towards the International Rare Diseases Research Consortium (IRDiRC)'s goal for 2027 to ensure that all people living with a RD receive a diagnosis within one year of coming to medical attention, the Solve-RD project aims to identify the molecular causes underlying undiagnosed RD. As part of this strategy, we developed a phenotypic similarity-based variant prioritization methodology comparing submitted cases with other submitted cases and with known RD in Orphanet. Three complementary approaches based on phenotypic similarity calculations using the Human Phenotype Ontology (HPO), the Orphanet Rare Diseases Ontology (ORDO) and the HPO-ORDO Ontological Module (HOOM) were developed; genomic data reanalysis was performed by the RD-Connect Genome-Phenome Analysis Platform (GPAP). The methodology was tested in 4 exemplary cases discussed with experts from European Reference Networks. Variants of interest (pathogenic or likely pathogenic) were detected in 8.8% of the 725 cases clustered by similarity calculations. Diagnostic hypotheses were validated in 42.1% of them and needed further exploration in another 10.9%. Based on the promising results, we are devising an automated standardized phenotypic-based re-analysis pipeline to be applied to the entire unsolved cases cohort. The Solve-RD project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779257. This study makes use of data shared/provided through RD-Connect, which received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 305444. Genome informatics Spinocerebellar ataxia Phenotypic similarity-based approach for variant prioritization for unsolved rare disease: a preliminary methodological report