TY - JOUR
T1 - ClinPrior :
T2 - an algorithm for diagnosis and novel gene discovery by network-based prioritization
AU - Schlüter, Agatha
AU - Vélez-Santamaría, Valentina
AU - Verdura, Edgard
AU - Rodríguez-Palmero, Agustí
AU - Ruiz, Montserrat
AU - Fourcade, Stéphane
AU - Planas-Serra, Laura
AU - Launay, Nathalie
AU - Guilera, Cristina
AU - Martínez, Juan José
AU - Homedes-Pedret, Christian
AU - Albertí-Aguiló, M. Antonia
AU - Zulaika, Miren
AU - Martí, Itxaso
AU - Troncoso, Mónica
AU - Tomás-Vila, Miguel
AU - Bullich Vilanova, Gemma
AU - García-Pérez, M. Asunción
AU - Sobrido-Gómez, María-Jesús
AU - López-Laso, Eduardo
AU - Fons, Carme
AU - Del Toro, Mireia
AU - Macaya Ruiz, Alfons
AU - Beltran i Agulló, Sergi
AU - Gutiérrez-Solana, Luis G.
AU - Pérez-Jurado, Luis A.
AU - Aguilera-Albesa, Sergio
AU - de Munain, Adolfo López
AU - Casasnovas, Carlos
AU - Pujol, Aurora
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Algorithm
KW - WES/WGS
KW - HPOs
KW - Variant prioritization
KW - Interactome
KW - Hereditary spastic paraplegia
KW - Cerebellar ataxia
KW - Candidate gene
UR - https://www.scopus.com/pages/publications/85170168560
U2 - 10.1186/s13073-023-01214-2
DO - 10.1186/s13073-023-01214-2
M3 - Article
C2 - 37679823
SN - 1756-994X
VL - 15
JO - Genome Medicine
JF - Genome Medicine
ER -