Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation.

ABSTRACT:

Background

Asthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease.

Methods

The gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used

SUBMITTER: Yan K 

PROVIDER: S-EPMC10858610 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature