Role of WNK4 and FKBP5 in asthma: Insights from bioinformatics analysis, machine learning, and preliminary validation

The complex and heterogeneous molecular mechanisms of asthma are currently unclear, and treatment outcomes are dismal in some patients. This study aimed to identify biomarkers with diagnostic and therapeutic potential.

Gene Expression Omnibus was used to obtain asthma-related gene expression data for identifying differentially expressed genes. They were subjected to functional and pathway enrichment analyses using the Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Disease Ontology. Gene Set Enrichment Analysis and Gene Set Variation Analysis were used to explore potential asthma-related mechanisms. Candidate biomarkers were identified using two machine learning algorithms and evaluated via ROC curve analysis. Immune cell fractions were assessed using CIBERSORT, and biomarker expression was validated in external database, in vivo, and in vitro studies.

The 168 differentially expressed genes (96 upregulated and 72 downregulated) were enriched for xenobiotic stimuli, glutathione transferase activity, negative regulation of proteolysis, and endopeptidase inhibitor activity; the pathways for glutathione metabolism, xenobiotic metabolism via cytochrome P450, and chemical carcinogenesis involving DNA adducts; and for periodontitis and asthma. WNK4 and FKBP5 were identified as critical genes and were validated using ROC assays. Correlations were found between WNK4 and M2-macrophages, and between FKBP5 expression and mast cells, resting NK cells, and T cells. Our findings demonstrated increased FKBP5 expression and decreased WNK4 expression in the asthmatic cohort, aligning with the results from dataset analyses. This concordance reinforces the reliability and validity of the bioinformatics assessments.

This study identified WNK4 and FKBP5 as candidate biomarkers of asthma warranting further clinical validation, thus contributing to a deeper understanding of asthma pathogenesis and offering a theoretical basis for future treatment strategies.