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Computational analysis of multimorbidity between asthma, eczema and rhinitis

(2017) PLOS ONE. 12(6).
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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.
Keywords
GENOME-WIDE ASSOCIATION, IMMUNE-RELATED DISEASES, INNATE LYMPHOID-CELLS, ATOPIC-DERMATITIS, ALLERGIC RHINITIS, NETWORK MEDICINE, COMORBIDITY, INFLAMMATION, MEDALL, METAANALYSIS

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Chicago
Aguilar, Daniel, Mariona Pinart, Gerard H Koppelman, Yvan Saeys, Martijn C Nawijn, Dirkje S Postma, Mübeccel Akdis, et al. 2017. “Computational Analysis of Multimorbidity Between Asthma, Eczema and Rhinitis.” Plos One 12 (6).
APA
Aguilar, D., Pinart, M., Koppelman, G. H., Saeys, Y., Nawijn, M. C., Postma, D. S., Akdis, M., et al. (2017). Computational analysis of multimorbidity between asthma, eczema and rhinitis. PLOS ONE, 12(6).
Vancouver
1.
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;12(6).
MLA
Aguilar, Daniel, Mariona Pinart, Gerard H Koppelman, et al. “Computational Analysis of Multimorbidity Between Asthma, Eczema and Rhinitis.” PLOS ONE 12.6 (2017): n. pag. Print.
@article{8525806,
  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.},
  articleno    = {e0179125},
  author       = {Aguilar, Daniel and Pinart, Mariona and Koppelman, Gerard H and Saeys, Yvan and Nawijn, Martijn C and Postma, Dirkje S and Akdis, M{\"u}beccel and Auffray, Charles and Ballereau, St{\'e}phane and Benet, Marta and Garc{\'i}a-Aymerich, Judith and Ramon Gonz{\'a}lez, Juan and Guerra, Stefano and Keil, Thomas and Kogevinas, Manolis and Lambrecht, Bart and Lemonnier, Nathanael and Melen, Erik and Sunyer, Jordi and Valenta, Rudolf and Valverde, Sergi and Wickman, Magnus and Bousquet, Jean and Oliva, Baldo and Ant{\'o}, Josep M},
  issn         = {1932-6203},
  journal      = {PLOS ONE},
  keyword      = {GENOME-WIDE ASSOCIATION,IMMUNE-RELATED DISEASES,INNATE LYMPHOID-CELLS,ATOPIC-DERMATITIS,ALLERGIC RHINITIS,NETWORK MEDICINE,COMORBIDITY,INFLAMMATION,MEDALL,METAANALYSIS},
  language     = {eng},
  number       = {6},
  pages        = {26},
  title        = {Computational analysis of multimorbidity between asthma, eczema and rhinitis},
  url          = {http://dx.doi.org/10.1371/journal.pone.0179125},
  volume       = {12},
  year         = {2017},
}

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