Computational analysis of multimorbidity between asthma, eczema and rhinitis

Daniel Aguilar, Mariona Pinart, Gerard H. Koppelman, Yvan Saeys, Martijn C. Nawijn, Dirkje S. Postma, Mubeccel Akdis, Charles Auffray, Stephane Ballereau, Marta Benet, Judith Garcõa-Aymerich, Juan Ramon Gonzalez, Stefano Guerra, Thomas Keil, Manolis Kogevinas, Bart Lambrecht, Nathanael Lemonnier, Erik Melen, Jordi Sunyer, Rudolf ValentaSergi Valverde, Magnus Wickman, Jean Bousquet, Baldo Oliva, Josep M. Anto

Research output: Contribution to journalArticle

14 Scopus citations

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.

Original languageEnglish (US)
Article number0179125
JournalPloS one
Volume12
Issue number6
DOIs
StatePublished - Jun 2017

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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    Aguilar, D., Pinart, M., Koppelman, G. H., Saeys, Y., Nawijn, M. C., Postma, D. S., Akdis, M., Auffray, C., Ballereau, S., Benet, M., Garcõa-Aymerich, J., Ramon Gonzalez, J., Guerra, S., Keil, T., Kogevinas, M., Lambrecht, B., Lemonnier, N., Melen, E., Sunyer, J., ... Anto, J. M. (2017). Computational analysis of multimorbidity between asthma, eczema and rhinitis. PloS one, 12(6), [0179125]. https://doi.org/10.1371/journal.pone.0179125