ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization

Background: 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...

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Autores: Schlüter, Agatha, Bullich, Gemma, Beltran, Sergi, Pérez Jurado, Luis Alberto, Pujol, Aurora, 1968-
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/58563
Acesso em linha:http://hdl.handle.net/10230/58563
http://dx.doi.org/10.1186/s13073-023-01214-2
Access Level:acceso abierto
Palavra-chave:Algorithm
Candidate gene
Cerebellar ataxia
HPOs
Hereditary spastic paraplegia
Interactome
Variant prioritization
WES/WGS
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spelling ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritizationSchlüter, AgathaBullich, GemmaBeltran, SergiPérez Jurado, Luis AlbertoPujol, Aurora, 1968-AlgorithmCandidate geneCerebellar ataxiaHPOsHereditary spastic paraplegiaInteractomeVariant prioritizationWES/WGSBackground: 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. Methods: 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). Results: 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. Conclusions: 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.BioMed Central202320232023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/58563http://dx.doi.org/10.1186/s13073-023-01214-2reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésGenome Med. 2023 Sep 7;15(1):68© The Author(s) 2023. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/585632026-05-29T05:05:01Z
dc.title.none.fl_str_mv ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
title ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
spellingShingle ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
Schlüter, Agatha
Algorithm
Candidate gene
Cerebellar ataxia
HPOs
Hereditary spastic paraplegia
Interactome
Variant prioritization
WES/WGS
title_short ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
title_full ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
title_fullStr ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
title_full_unstemmed ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
title_sort ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization
dc.creator.none.fl_str_mv Schlüter, Agatha
Bullich, Gemma
Beltran, Sergi
Pérez Jurado, Luis Alberto
Pujol, Aurora, 1968-
author Schlüter, Agatha
author_facet Schlüter, Agatha
Bullich, Gemma
Beltran, Sergi
Pérez Jurado, Luis Alberto
Pujol, Aurora, 1968-
author_role author
author2 Bullich, Gemma
Beltran, Sergi
Pérez Jurado, Luis Alberto
Pujol, Aurora, 1968-
author2_role author
author
author
author
dc.subject.none.fl_str_mv Algorithm
Candidate gene
Cerebellar ataxia
HPOs
Hereditary spastic paraplegia
Interactome
Variant prioritization
WES/WGS
topic Algorithm
Candidate gene
Cerebellar ataxia
HPOs
Hereditary spastic paraplegia
Interactome
Variant prioritization
WES/WGS
description Background: 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. Methods: 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). Results: 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. Conclusions: 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.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/58563
http://dx.doi.org/10.1186/s13073-023-01214-2
url http://hdl.handle.net/10230/58563
http://dx.doi.org/10.1186/s13073-023-01214-2
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Genome Med. 2023 Sep 7;15(1):68
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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