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Rhinovirus-induced gene expression patterns that distinguish between neutrophilic asthma and other asthma inflammatory phenotypes in human peripheral blood mononuclear cells

ABSTRACT: Objective: The aim of the current study was to use circulating immune cells to define gene expression patterns that best distinguish between different asthma phenotypes. We hypothesised that analysing gene expression patterns in unstimulated cells would be of limited value, and that variations in gene expression patterns would be most apparent in the setting of RV stimulation. Methods: Peripheral blood mononuclear cells samples from adults with persistent asthma of different inflammatory subtypes were stimulated with RV in vitro with RNA sequencing and bioinformatics used to define gene expression patterns. Results: RV-induced changes in gene expression differed markedly between neutrophilic asthma (NA) and other asthma phenotypes. Expression of many anti-viral immune pathways and their regulators genes was down regulated in NA compared to the other phenotypes, accompanied by enhanced expression of chemokine genes, proinflammatory cytokines and Y chromosome linked genes. These changes were detected in circulating, bone marrow-derived immune cells and were most apparent in RV-stimulated rather than resting cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE202216 | GEO | 2025/05/04

REPOSITORIES: GEO

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Project description:BACKGROUND: Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. METHODS: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation. RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). Subjects in TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. CONCLUSIONS: Patterns of gene expression in the sputum and blood reveal TEA clusters that are associated with severe asthma phenotypes in children and adults. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.

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Rhinovirus-induced gene expression patterns that distinguish between neutrophilic asthma and other asthma inflammatory phenotypes in human peripheral blood mononuclear cells

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