ASMAPORT - Connect to conquer: integrating clinical and Omics data to characterize asthma in Portugal

Asthma is a heterogeneous syndrome currently affecting 695,000 children and adults in Portugal. It encompasses multiple disease phenotypes of clinically observable characteristics, and different disease subtypes or endotypes, driven by distinct functional and pathophysiological mechanisms. Moreover, emerging evidence shows that the airway microbiome also impacts both clinical features and asthma pathogenesis. However, no study so far has been able to untangle the biological interactions between all these variants of asthma. This major gap in knowledge hinders efforts to unravel the causes of asthma and improve its treatment and classification. Our previous analyses indicate that the nasopharynx contains unique microbial profiles and host transcripts that contribute to clinical variation in asthma and will allow the identification of underlying mechanisms in asthma. Moreover, dual transcriptomic analyses performed by our group detected 11 bacteria (including 6 potential pathogens) and 27 mediators involved in IL-6 and NFKB signaling overrepresented in asthmatics and differentially expressed across asthma phenotypes. In the current application, we apply state-of-the art Omic and analytical approaches to integrate microbiome diversity (bacteria, fungi and viruses) and host phenotypic and pathophysiological information (immune and inflammatory responses modulated via IL-6 and NFKB signaling) to better characterize asthma in Portugal. Towards that goal, we will use nasal and oral specimens from 200 asthmatics and 50 healthy controls from the Porto area. In Aim 1 we will identify airway microbial taxonomic (DNA) and functional (RNA) profiles associated with asthma phenotypes. In Aim 2 we will identify host airway transcripts (mRNAs and microRNAs) inducing IL-6 and NFKB signaling associated with asthma phenotypes. Lastly, using a systems biology approach, in Aim 3 we will define inclusive and consistent (temporally stable) asthma endotypes by integrating clinical phenotypes and above Omics data (DNA, RNA and signaling mediators) from both microbiomes and host. In this natural experiment, we will have a unique opportunity to identify airway microbes and host RNAs associated with asthma phenotypes. Furthermore, we will investigate underlying mechanisms linking clinical variation to asthma (e.g., enhanced IL-6 and NFKB signaling), and identify phenotypes/endotypes of asthma that are likely to respond differently to different interventions. This study will provide new criteria for classifying, preventing and treating asthma (e.g., mRNA-targeting therapy or anti-IL-6 and NFKB therapies) in adults and children.