Molecular characterization of allergic constitution based on network pharmacology and multi-omics analysis methods

The objective of this study was to identify critical pathways associated with allergic constitution. Shared genes among allergic rhinitis (AR), asthma (AA), and atopic dermatitis (AD) were extracted from the GWAS catalog. RNA-seq data of AR, AA, and AD from gene expression omnibus (GEO) database were preprocessed and subjected to differential gene expression analysis. The differentially expressed genes (DEGs) were merged using the Robust Rank Aggregation (RRA) algorithm. Weighted gene co-expression network analysis (WGCNA) was performed to identify modules associated with allergies. Components of Guominkang (GMK) were obtained from 6 databases and activate components were identified by SwissADME website. Utilizing the SwissTarget Prediction, PharmMapper, SymMap, and HERB, the targets of GMK were predicted and subsequently validated using gene chip data from our team previous study. Differentially expressed proteins (DEPs) related to the allergic constitution were also extracted based on a previous study. Pathway enrichment analysis was performed using KOBAS-i on the GWAS, RRA, WGCNA modules, DEPs, and GMK targets. P values from multi-omics datasets were combined by meta-analysis, and Bonferroni correction was applied. The significant pathways were further validated using Gene Set Enrichment Analysis (GSEA) with intervention data of GMK. The GWAS results yielded 172 genes. Four datasets AR1, AA1, AD1, and AD2 were acquired from GSE75011, GSE125916, and GSE184237. The RRA algorithm identified 19 upregulated and 20 downregulated genes. WGCNA identified 5 significant modules, with the blue and turquoise modules displaying a moderate correlation with allergies. By performing network pharmacology analysis, we identified 127 active ingredients of GMK and predicted 618 targets. Validation using gene chip data confirmed 107 GMK targets. Single-omics pathway analysis was conducted using KOBAS-i, and 39 significant pathways were identified across multiple omics datasets. GSEA analysis using GMK intervention data identified 11 of 39 significant pathways as the final key pathways associated with the allergic constitution. Through multi-omics integrated pathway analysis, we identified 11 critical pathways of allergic constitution, including TH1 and TH2 cell differentiation, TLR cascade, and TH17 cell differentiation. Identifying these pathways suggests that the observed alterations at the pathway level may play significant roles in the molecular characteristics of the allergic constitution.