ClinPrior

Whole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to t...

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Detalles Bibliográficos
Autores: Schlüter, Agatha|||0000-0001-6732-1528, Vélez-Santamaría, Valentina, Verdura, Edgard|||0000-0003-3856-2060, Rodríguez-Palmero, Agustí|||0000-0002-4141-5515, Ruiz, Montserrat|||0000-0003-0466-2653, Fourcade, Stéphane|||0000-0002-8031-5007, Planas-Serra, Laura|||0000-0002-2586-0897, Launay, Nathalie|||0000-0002-7498-217X, Guilera, Cristina|||0000-0003-0715-9332, Martínez, Juan José, Homedes-Pedret, Christian, Albertí-Aguiló, M. Antonia, Zulaika, Miren, Martí, Itxaso|||0000-0003-0578-9568, Troncoso, Mónica, Tomás Vila, Miguel|||0000-0002-8632-3593, Bullich Vilanova, Gemma|||0000-0002-0737-4422, García-Pérez, M. Asunción, Sobrido-Gómez, María-Jesús, López-Laso, Eduardo, Fons, Carme, Del Toro, Mireia|||0000-0002-8163-1853, Macaya Ruiz, Alfons|||0000-0001-7998-4185, Beltran i Agulló, Sergi|||0000-0002-2810-3445, González Gutiérrez-Solana, Luis|||0000-0003-2890-4565, Pérez-Jurado, Luis Alberto|||0000-0002-1988-3005, Aguilera-Albesa, Sergio|||0000-0003-3540-1448, de Munain, Adolfo López, Casasnovas, Carlos|||0000-0002-7933-4681, Pujol, Aurora|||0000-0002-9606-0600
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:317391
Acceso en línea:https://ddd.uab.cat/record/317391
https://dx.doi.org/urn:doi:10.1186/s13073-023-01214-2
Access Level:acceso abierto
Palabra clave:Algorithm
WES/WGS
HPOs
Variant prioritization
Interactome
Hereditary spastic paraplegia
Cerebellar ataxia
Candidate gene
Descripción
Sumario:Whole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts. We developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA). ClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes. ClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses. The online version contains supplementary material available at 10.1186/s13073-023-01214-2.

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