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ABSTRACT: Background
Asthma is a heterogeneous chronic inflammatory disease of the airway, and its development is the result of genetic factors, environmental factors, immune dysfunction, and other factors. This study aimed to identify biomarkers of asthma.Methods
A differential gene expression (DGE) analysis and a weighted gene co-expression network analysis (WGCNA) were conducted to identify the asthma-related genes in the GSE67472 dataset, and these genes were intersected with immune genes from the Immuport database to identify the asthma-associated immune genes. Least absolute shrinkage and selection operator (LASSO) regression was used to identify the key asthma-associated immune genes, and receiver operating characteristic (ROC) curves were used to assess the diagnostic potenti
SUBMITTER: Zhang H
PROVIDER: S-EPMC12268608 | biostudies-literature | 2025 Jun
REPOSITORIES: biostudies-literature