Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes

Crohn's disease; Microbiome; Ulcerative colitis

Detalles Bibliográficos
Autores: Liñares Blanco, Jose, Fernandez-Lozano, Carlos, Seoane Fernández, Jose Antonio, Lopez-Campos, Guillermo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Departament de Salut de la Generalitat de Catalunya (DS)
Repositorio:Scientia. Dipòsit d'Informació Digital del Departament de Salut
OAI Identifier:oai:scientiasalut.gencat.cat:11351/8090
Acceso en línea:https://hdl.handle.net/11351/8090
Access Level:acceso abierto
Palabra clave:Aprenentatge automàtic
Intestins - Inflamació - Diagnòstic
Intestins - Microbiologia
PHENOMENA AND PROCESSES::Microbiological Phenomena::Microbiota::Mycobiome
DISEASES::Digestive System Diseases::Gastrointestinal Diseases::Gastroenteritis::Inflammatory Bowel Diseases
Other subheadings::Other subheadings::/diagnosis
INFORMATION SCIENCE::Information Science::Computing Methodologies::Algorithms::Artificial Intelligence::Machine Learning
FENÓMENOS Y PROCESOS::fenómenos microbiológicos::microbiota::micobioma
ENFERMEDADES::enfermedades del sistema digestivo::enfermedades gastrointestinales::gastroenteritis::enfermedad inflamatoria intestinal
Otros calificadores::Otros calificadores::/diagnóstico
CIENCIA DE LA INFORMACIÓN::Ciencias de la información::metodologías computacionales::algoritmos::inteligencia artificial::aprendizaje automático
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network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
title Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
spellingShingle Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
Liñares Blanco, Jose
Aprenentatge automàtic
Intestins - Inflamació - Diagnòstic
Intestins - Microbiologia
PHENOMENA AND PROCESSES::Microbiological Phenomena::Microbiota::Mycobiome
DISEASES::Digestive System Diseases::Gastrointestinal Diseases::Gastroenteritis::Inflammatory Bowel Diseases
Other subheadings::Other subheadings::/diagnosis
INFORMATION SCIENCE::Information Science::Computing Methodologies::Algorithms::Artificial Intelligence::Machine Learning
FENÓMENOS Y PROCESOS::fenómenos microbiológicos::microbiota::micobioma
ENFERMEDADES::enfermedades del sistema digestivo::enfermedades gastrointestinales::gastroenteritis::enfermedad inflamatoria intestinal
Otros calificadores::Otros calificadores::/diagnóstico
CIENCIA DE LA INFORMACIÓN::Ciencias de la información::metodologías computacionales::algoritmos::inteligencia artificial::aprendizaje automático
title_short Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
title_full Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
title_fullStr Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
title_full_unstemmed Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
title_sort Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes
dc.creator.none.fl_str_mv Liñares Blanco, Jose
Fernandez-Lozano, Carlos
Seoane Fernández, Jose Antonio
Lopez-Campos, Guillermo
author Liñares Blanco, Jose
author_facet Liñares Blanco, Jose
Fernandez-Lozano, Carlos
Seoane Fernández, Jose Antonio
Lopez-Campos, Guillermo
author_role author
author2 Fernandez-Lozano, Carlos
Seoane Fernández, Jose Antonio
Lopez-Campos, Guillermo
author2_role author
author
author
dc.contributor.none.fl_str_mv Institut Català de la Salut
[Liñares-Blanco J] Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC, University of A Coruña, A Coruña, Spain. GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government PTS Granada, Granada, Spain. Department of Statistics and Operational Research, University of Granada, Granada, Spain. [Fernandez-Lozano C] Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC, University of A Coruña, A Coruña, Spain. [Seoane JA] Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain. [López-Campos G] Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, United Kingdom
Vall d'Hebron Barcelona Hospital Campus
dc.subject.none.fl_str_mv Aprenentatge automàtic
Intestins - Inflamació - Diagnòstic
Intestins - Microbiologia
PHENOMENA AND PROCESSES::Microbiological Phenomena::Microbiota::Mycobiome
DISEASES::Digestive System Diseases::Gastrointestinal Diseases::Gastroenteritis::Inflammatory Bowel Diseases
Other subheadings::Other subheadings::/diagnosis
INFORMATION SCIENCE::Information Science::Computing Methodologies::Algorithms::Artificial Intelligence::Machine Learning
FENÓMENOS Y PROCESOS::fenómenos microbiológicos::microbiota::micobioma
ENFERMEDADES::enfermedades del sistema digestivo::enfermedades gastrointestinales::gastroenteritis::enfermedad inflamatoria intestinal
Otros calificadores::Otros calificadores::/diagnóstico
CIENCIA DE LA INFORMACIÓN::Ciencias de la información::metodologías computacionales::algoritmos::inteligencia artificial::aprendizaje automático
topic Aprenentatge automàtic
Intestins - Inflamació - Diagnòstic
Intestins - Microbiologia
PHENOMENA AND PROCESSES::Microbiological Phenomena::Microbiota::Mycobiome
DISEASES::Digestive System Diseases::Gastrointestinal Diseases::Gastroenteritis::Inflammatory Bowel Diseases
Other subheadings::Other subheadings::/diagnosis
INFORMATION SCIENCE::Information Science::Computing Methodologies::Algorithms::Artificial Intelligence::Machine Learning
FENÓMENOS Y PROCESOS::fenómenos microbiológicos::microbiota::micobioma
ENFERMEDADES::enfermedades del sistema digestivo::enfermedades gastrointestinales::gastroenteritis::enfermedad inflamatoria intestinal
Otros calificadores::Otros calificadores::/diagnóstico
CIENCIA DE LA INFORMACIÓN::Ciencias de la información::metodologías computacionales::algoritmos::inteligencia artificial::aprendizaje automático
description Crohn's disease; Microbiome; Ulcerative colitis
publishDate 2022
dc.date.none.fl_str_mv 2022
2022
2022
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 https://hdl.handle.net/11351/8090
url https://hdl.handle.net/11351/8090
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Frontiers in Microbiology;13
https://doi.org/10.3389/fmicb.2022.872671
info:eu-repo/grantAgreement/ES/PE2017-2020/RYC2019-026576-I
dc.rights.none.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv Scientia
reponame:Scientia. Dipòsit d'Informació Digital del Departament de Salut
instname:Departament de Salut de la Generalitat de Catalunya (DS)
instname_str Departament de Salut de la Generalitat de Catalunya (DS)
reponame_str Scientia. Dipòsit d'Informació Digital del Departament de Salut
collection Scientia. Dipòsit d'Informació Digital del Departament de Salut
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869412713017376768
spelling Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease SubtypesLiñares Blanco, JoseFernandez-Lozano, CarlosSeoane Fernández, Jose AntonioLopez-Campos, GuillermoAprenentatge automàticIntestins - Inflamació - DiagnòsticIntestins - MicrobiologiaPHENOMENA AND PROCESSES::Microbiological Phenomena::Microbiota::MycobiomeDISEASES::Digestive System Diseases::Gastrointestinal Diseases::Gastroenteritis::Inflammatory Bowel DiseasesOther subheadings::Other subheadings::/diagnosisINFORMATION SCIENCE::Information Science::Computing Methodologies::Algorithms::Artificial Intelligence::Machine LearningFENÓMENOS Y PROCESOS::fenómenos microbiológicos::microbiota::micobiomaENFERMEDADES::enfermedades del sistema digestivo::enfermedades gastrointestinales::gastroenteritis::enfermedad inflamatoria intestinalOtros calificadores::Otros calificadores::/diagnósticoCIENCIA DE LA INFORMACIÓN::Ciencias de la información::metodologías computacionales::algoritmos::inteligencia artificial::aprendizaje automáticoCrohn's disease; Microbiome; Ulcerative colitisEnfermedad de Crohn; Microbioma; Colitis ulcerosaMalaltia de Crohn; Microbioma; Colitis ulcerosaInflammatory bowel disease (IBD) is a chronic disease with unknown pathophysiological mechanisms. There is evidence of the role of microorganims in this disease development. Thanks to the open access to multiple omics data, it is possible to develop predictive models that are able to prognosticate the course and development of the disease. The interpretability of these models, and the study of the variables used, allows the identification of biological aspects of great importance in the development of the disease. In this work we generated a metagenomic signature with predictive capacity to identify IBD from fecal samples. Different Machine Learning models were trained, obtaining high performance measures. The predictive capacity of the identified signature was validated in two external cohorts. More precisely a cohort containing samples from patients suffering Ulcerative Colitis and another from patients suffering Crohn's Disease, the two major subtypes of IBD. The results obtained in this validation (AUC 0.74 and AUC = 0.76, respectively) show that our signature presents a generalization capacity in both subtypes. The study of the variables within the model, and a correlation study based on text mining, identified different genera that play an important and common role in the development of these two subtypes.CF-L's work was supported by the Collaborative Project in Genomic Data Integration (CICLOGEN) PI17/01826 funded by the Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation 2013-2016 and the European Regional Development Funds (FEDER)–A way to build Europe. JS's work was funded by the Ramón y Cajal grant (RYC2019-026576-I) funded by Ministry of Science and Innovation of the Spanish government. GL-C's work was supported by a grant from the Biotechnology and Biological Sciences Research Council (BBSRC grant BB/S006281/1) and open access publication fees were supported by Queen's University of Belfast UKRI block grant.Frontiers MediaInstitut Català de la Salut[Liñares-Blanco J] Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC, University of A Coruña, A Coruña, Spain. GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government PTS Granada, Granada, Spain. Department of Statistics and Operational Research, University of Granada, Granada, Spain. [Fernandez-Lozano C] Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC, University of A Coruña, A Coruña, Spain. [Seoane JA] Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain. [López-Campos G] Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, United KingdomVall d'Hebron Barcelona Hospital Campus202220222022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/11351/8090Scientiareponame:Scientia. Dipòsit d'Informació Digital del Departament de Salutinstname:Departament de Salut de la Generalitat de Catalunya (DS)InglésFrontiers in Microbiology;13https://doi.org/10.3389/fmicb.2022.872671info:eu-repo/grantAgreement/ES/PE2017-2020/RYC2019-026576-IAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:scientiasalut.gencat.cat:11351/80902026-06-12T09:38:37Z
score 15,811543

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