Understanding allergic multimorbidity within the non-eosinophilic interactome.

Background: The mechanisms explaining multimorbidity between asthma, dermatitis and rhinitis (allergic multimorbidity) are not well known. We investigated these mechanisms and their specificity in distinct cell types by means of an interactome-based analysis of expression data.
Methods: Genes associated to the diseases were identified using data mining approaches, and their multimorbidity mechanisms in distinct cell types were characterized by means of an in silico analysis of the topology of the human interactome.
Results: We characterized specific pathomechanisms for multimorbidities between asthma, dermatitis and rhinitis for distinct emergent non-eosinophilic cell types. We observed differential roles for cytokine signaling, TLR-mediated signaling and metabolic pathways for multimorbidities across distinct cell types. Furthermore, we also identified individual genes potentially associated to multimorbidity mechanisms.
Conclusions: Our results support the existence of differentiated multimorbidity mechanisms between asthma, dermatitis and rhinitis at cell type level, as well as mechanisms common to distinct cell types. These results will help understanding the biology underlying allergic multimorbidity, assisting in the design of new clinical studies.
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: DA worked for 6AM Data Mining data science company as a bioinformatics consultant at the time of the study. This commercial affiliation does not alter our adherence PLOS ONE policies on sharing data and materials. The authors have declared that no competing interests exist.