Revealing the acute asthma ignorome: Characterization and validation of uninvestigated gene networks

Michela Riba, Jose Manuel Garcia Manteiga, Berislav Bošnjak, Davide Cittaro, Pavol Mikolka, Connie Le, Michelle M. Epstein, Elia Stupka

Research output: Contribution to journalArticlepeer-review


Systems biology provides opportunities to fully understand the genes and pathways in disease pathogenesis. We used literature knowledge and unbiased multiple data meta-analysis paradigms to analyze microarray datasets across different mouse strains and acute allergic asthma models. Our combined gene-driven and pathway-driven strategies generated a stringent signature list totaling 933 genes with 41% (440) asthma-annotated genes and 59% (493) ignorome genes, not previously associated with asthma. Within the list, we identified inflammation, circadian rhythm, lung-specific insult response, stem cell proliferation domains, hubs, peripheral genes, and super-connectors that link the biological domains (Il6, Il1ß, Cd4, Cd44, Stat1, Traf6, Rela, Cadm1, Nr3c1, Prkcd, Vwf, Erbb2). In conclusion, this novel bioinformatics approach will be a powerful strategy for clinical and across species data analysis that allows for the validation of experimental models and might lead to the discovery of novel mechanistic insights in asthma.

Original languageEnglish
Article number24647
JournalScientific Reports
Publication statusPublished - Apr 21 2016

ASJC Scopus subject areas

  • General

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