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Computational analysis of multimorbidity between asthma, eczema and rhinitis

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dc.contributor.author Aguilar, Daniel
dc.contributor.author Pinart, Mariona
dc.contributor.author Benet, Marta
dc.contributor.author García Aymerich, Judith
dc.contributor.author González Ruiz, Juan Ramón
dc.contributor.author Guerra, Stefano
dc.contributor.author Kogevinas, Manolis
dc.contributor.author Sunyer Deu, Jordi
dc.contributor.author Valverde, Sergi
dc.contributor.author Oliva Miguel, Baldomero
dc.contributor.author Antó i Boqué, Josep Maria
dc.date.accessioned 2017-11-08T16:42:52Z
dc.date.available 2017-11-08T16:42:52Z
dc.date.issued 2017
dc.identifier.citation Aguilar D, Pinart M, Koppelman GH, Saeys Y, Nawijn MC, Postma DS et al. Computational analysis of multimorbidity between asthma, eczema and rhinitis. PLoS One. 2017 Jun 9;12(6):e0179125. DOI: 10.1371/journal.pone.0179125
dc.identifier.issn 1932-6203
dc.identifier.uri http://hdl.handle.net/10230/33179
dc.description.abstract Background: The mechanisms explaining the co-existence of asthma, eczema and rhinitis (allergic multimorbidity) are largely unknown. We investigated the mechanisms underlying multimorbidity between three main allergic diseases at a molecular level by identifying the proteins and cellular processes that are common to them. Methods: An in silico study based on computational analysis of the topology of the protein interaction network was performed in order to characterize the molecular mechanisms of multimorbidity of asthma, eczema and rhinitis. As a first step, proteins associated to either disease were identified using data mining approaches, and their overlap was calculated. Secondly, a functional interaction network was built, allowing to identify cellular pathways involved in allergic multimorbidity. Finally, a network-based algorithm generated a ranked list of newly predicted multimorbidity-associated proteins. Results: Asthma, eczema and rhinitis shared a larger number of associated proteins than expected by chance, and their associated proteins exhibited a significant degree of interconnectedness in the interaction network. There were 15 pathways involved in the multimorbidity of asthma, eczema and rhinitis, including IL4 signaling and GATA3-related pathways. A number of proteins potentially associated to these multimorbidity processes were also obtained. Conclusions: These results strongly support the existence of an allergic multimorbidity cluster between asthma, eczema and rhinitis, and suggest that type 2 signaling pathways represent a relevant multimorbidity mechanism of allergic diseases. Furthermore, we identified new candidates contributing to multimorbidity that may assist in identifying new targets for multimorbid allergic diseases.
dc.description.sponsorship This work was supported by the Spanish Ministry of Science and Innovation (MICINN) grant BIO2011-22568, and by Mechanisms of the Development of ALLergy (MeDALL), a collaborative project done within the EU under the Health Cooperation Work Programme of the Seventh Framework programme (grant agreement number 261357).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Public Library of Science (PLoS)
dc.relation.ispartof PLoS One. 2017 Jun 9;12(6):e0179125
dc.rights © 2017 Aguilar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Computational analysis of multimorbidity between asthma, eczema and rhinitis
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0179125
dc.subject.keyword Asthma/epidemiology
dc.subject.keyword Asthma/etiology
dc.subject.keyword Asthma/metabolism
dc.subject.keyword Biomarkers
dc.subject.keyword Comorbidity
dc.subject.keyword Computer Simulation
dc.subject.keyword Databases, Factual
dc.subject.keyword Gene Expression Regulation
dc.subject.keyword Models, Statistical
dc.subject.keyword Models, Theoretical
dc.subject.keyword Proteomics/methods
dc.subject.keyword Rhinitis/epidemiology
dc.subject.keyword Rhinitis/etiology
dc.subject.keyword Rhinitis/metabolism
dc.subject.keyword Proteome
dc.subject.keyword Rhinitis, Allergic/epidemiology
dc.subject.keyword Rhinitis, Allergic/etiology
dc.subject.keyword Rhinitis, Allergic/metabolism
dc.subject.keyword Signal Transduction
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/261357
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BIO2011-22568
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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