Identification of immune-associated biomarkers in diagnosing allergic rhinitis.

ABSTRACT:

Background

Allergic rhinitis (AR), as a prevailing disease worldwide, is a common chronic inflammatory disease of the upper airway; however, its prognosis did not meet expectations of the general public. Regarding the importance of treatment for AR, biomarkers with high sensitivity and precision are in urgent need.

Methods

To detect the potential mechanisms associated with the AR pathology, the differentially expressed gene data from the clinical dataset GSE19187 and GSE46171 were used for weighted gene co-expression network analysis. Additionally, 5 machine-learning algorithms were integrated to screen for novel diagnostic biomarkers for AR.

Results

This analysis identified 133 genes enriched in the black and purple module pathways from weighted gene co-expression ne

SUBMITTER: Cheng Q 

PROVIDER: S-EPMC12320532 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature