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dc.contributor.authorSánchez, Jon
dc.contributor.authorTejero, Héctor
dc.contributor.authorFernández, José María
dc.contributor.authorJuan, David
dc.contributor.authorUrda García, Beatriz
dc.contributor.authorCapella Gutiérrez, Salvador
dc.contributor.authorAl-Shahrour, Fátima
dc.contributor.authorTabarés Seisdedos, Rafael
dc.contributor.authorBaudot, Anais
dc.contributor.authorPancaldi, Vera
dc.contributor.authorValencia, Alfonso
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2020-06-12T13:49:11Z
dc.date.available2020-06-12T13:49:11Z
dc.date.issued2020
dc.identifier.citationSánchez, J. [et al.]. Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships. "Nature Communications", 2020, vol. 11, núm. 2854.
dc.identifier.issn2041-1723
dc.identifier.urihttp://hdl.handle.net/2117/190646
dc.description.abstractComorbidity is a medical condition attracting increasing attention in healthcare and biomedical research. Little is known about the involvement of potential molecular factors leading to the emergence of a specific disease in patients affected by other conditions. We present here a disease interaction network inferred from similarities between patients’ molecular profiles, which significantly recapitulates epidemiologically documented comorbidities. Furthermore, we identify disease patient-subgroups that present different molecular similarities with other diseases, some of them opposing the general tendencies observed at the disease level. Analyzing the generated patient-subgroup network, we identify genes involved in such relations, together with drugs whose effects are potentially associated with the observed comorbidities. All the obtained associations are available at the disease PERCEPTION portal (http://disease-perception.bsc.es).
dc.description.sponsorshipThis work was supported by a Ph.D. Fellowship (BES-2016-077403) and funded by the Spanish Ministry of Economics and Competitiveness (BFU2015-71241-R, RTI2018-096653-B-I00). The Coordination Node led by A.V. at the Barcelona Supercomputing Center (BSC) is a member of the Spanish National Bioinformatics Institute (INB), ISCIII-Bioinformatics platform and is supported by grant PT17/0009/0001 of the Acción Estratégica en Salud 2013-2016 of the Programa Estatal de Investigación Orientada a los Retos de la Sociedad, funded by the Instituto de Salud Carlos III (ISCIII) and European Regional Development Fund (ERDF). V.P. is supported by INSERM, the Fondation Toulouse Cancer Santé and Pierre Fabre Research Institute as part of the Chair of Bioinformatics in Oncology of the CRCT. A.B. has received funding from the Excellence Initiative of Aix-Marseille University—A*Midex, a French “Investissements d’Avenir” program. D.J. was supported by Juan de la Cierva fellowship (FJCI-2016-29558) from the Ministerio de Ciencia, Innovación y Universidades. H.T. and F.A.-S. were supported by the Instituto de Salud Carlos III (ISCIII), Spanish National Bioinformatics Institute (INB) Grant (PT17/0009/0011—ISCIII-SGEFI/ERDF) and Marie-Curie Career Integration Grant (CIG334361). J.M.F. and S.C.-G. were supported by the Instituto de Salud Carlos III (ISCIII), Spanish National Bioinformatics Institute (INB) Grant (PT17/0009/0001—ISCIII-SGEFI/ERDF). R.T.-S. was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER.
dc.format.extent13 p.
dc.language.isoeng
dc.publisherSpringer Nature
dc.rightsAttribution 3.0 Spain
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subject.lcshBiomedical engineering
dc.subject.lcshDiseases
dc.subject.lcshMolecular genetics
dc.subject.lcshComorbidity
dc.subject.lcshMedical care.
dc.subject.otherComorbidity
dc.subject.otherMolecular similarity
dc.subject.otherBiomedical research
dc.subject.otherDisease PERCEPTION portal
dc.subject.otherGene expression profiles
dc.subject.otherProtein−protein interaction
dc.subject.otherPhenotypes
dc.subject.otherHealthcare
dc.titleInterpreting molecular similarity between patients as a determinant of disease comorbidity relationships
dc.typeArticle
dc.subject.lemacEnginyeria biomèdica
dc.subject.lemacMalalties
dc.subject.lemacGenètica molecular
dc.identifier.doi10.1038/s41467-020-16540-x
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.nature.com/articles/s41467-020-16540-x
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/BES-2016-077403
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096653-B-I00/ES/EXTRACCION DE PERFILES DE COMORBILIDAD PERSONALIZADOS Y DE TRAYECTORIAS BASADAS EN DATOS MULTI-OMICOS/
local.citation.publicationNameNature Communications
local.citation.volume11
local.citation.number2854
dc.relation.datasethttp://disease-perception.bsc.es
dc.relation.datasethttps://www.ebi.ac.uk/arrayexpress/) and GEO (http://www.ncbi.nlm.nih.gov/geo
dc.relation.datasethttps://github.com/jonsv89/Disease_PERCEPTION


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