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Latent MicroRNA Networks in Asthma Endotypes [NS_H_miR_v3a]

ABSTRACT: Transcriptome analysis of whole blood from subjects with asthma and controls The presence or absence of type 2 inflammation (T2) biomarkers is used to identify T2-high and T2-low endotypes in the clinic. Despite the clinical relevance of these endotypes, the molecular mechanisms of T2-low asthma remain poorly understood. Specific microRNAs may regulate transcriptomic networks associated with asthma endotypes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE287880 | GEO | 2025/12/01

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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Latent MicroRNA Networks in Asthma Endotypes [NS_H_miR_v3a]

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