Identification of extracellular vesicle microRNA signatures specifically linked to inflammatory and metabolic mechanisms in obesity-associated low type-2 asthma

Abstract

Rationale and objective: Plasma extracellular vesicles (EVs) represent a vital source of molecular information about health and disease states. Due to their heterogenous cellular sources, EVs and their cargo may predict specific pathomechanisms behind disease phenotypes. Here we aimed to utilize EV microRNA (miRNA) signatures to gain new insights into underlying molecular mechanisms of obesity-associated low type-2 asthma.

Methods: Obese low type-2 asthma (OA) and non-obese low type-2 asthma (NOA) patients were selected from an asthma cohort conjointly with healthy controls. Plasma EVs were isolated and characterised by nanoparticle tracking analysis. EV-associated small RNAs were extracted, sequenced and bioinformatically analysed.

Results: Based on EV miRNA expression profiles, a clear distinction between the three study groups could be established using a principal component analysis. Integrative pathway analysis of potential target genes of the differentially expressed miRNAs revealed inflammatory cytokines (e.g., interleukin-6, transforming growth factor-beta, interferons) and metabolic factors (e.g., insulin, leptin) signalling pathways to be specifically associated with OA. The miR-17-92 and miR-106a-363 clusters were significantly enriched only in OA. These miRNA clusters exhibited discrete bivariate correlations with several key laboratory (e.g., C-reactive protein) and lung function parameters. Plasma EV miRNA signatures mirrored blood-derived CD4⁺ T-cell transcriptome data, but achieved an even higher sensitivity in identifying specifically affected biological pathways.

Conclusion: The identified plasma EV miRNA signatures and particularly the miR-17-92 and -106a-363 clusters were capable to disentangle specific mechanisms of the obesity-associated low type-2 asthma phenotype, which may serve as basis for stratified treatment development.

Keywords: asthma endotypes; asthma phenotypes; extracellular vesicles; microRNA clusters; obesity-associated asthma.