Extracellular Vesicle miRNAs as Biomarkers of Asthma Severity

Asthma is a chronic lung disease with various clinical phenotypes, complicating its diagnosis and treatment. The micro-RNA (miRNA) profile of plasma-derived extracellular vesicles (EVs) may serve as potential circulating biomarkers for differentiating asthma phenotypes/endotypes. This study aims to characterize and compare the miRNA profiles in plasma-derived EVs across healthy controls (HC), non-severe asthmatics (NS), and severe asthmatics (SA). EVs were isolated from plasma samples of HC, NS, and SA, followed by physiochemical characterization and RNA isolation. Small RNA sequencing was performed, and differentially expressed (DE) miRNAs were identified through DESeq2 analysis. DE miRNAs and their predicted mRNA targets were identified using Ingenuity Pathway Analysis (IPA), and pathway enrichment was conducted using STRING DB and Enrichr. EVs from all groups were predominantly ~150-200 nm in size, with significantly higher EV counts in SA compared to HC and NS. miRNA expression analysis revealed unique and shared DE miRNAs across the three comparisons (HC vs. NS; HC vs. SA; NS vs. SA). A total of 16 unique DE miRNAs among these comparisons, between which in the NS vs. SA comparison, miR-515-3p positively correlates with lung function, and exacerbation and miR-133a-3p and miR-9-5p with ACT score. Target and pathway analyses from the NS vs. SA comparison indicated the enrichment of key pathways, including IL-4/IL-13, Th1, Th2, and Th17 cell differentiation, MAPK, PI3K-Akt, and receptor tyrosine kinase signaling. This study identified distinct miRNAs in plasma-derived EVs from NS vs. SA which could serve as potential circulating biomarkers for differentiating asthma severity. Overall design: EVs were isolated from plasma samples of HC, NS, and SA, followed by physiochemical characterization and RNA isolation. Small RNA sequencing was performed, and differentially expressed (DE) miRNAs were identified through DESeq2 analysis. DE miRNAs and their predicted mRNA targets were identified using Ingenuity Pathway Analysis (IPA), and pathway enrichment was conducted using STRING DB and Enrichr.