IgA nephropathy (IgAN) and celiac disease (CeD) are autoimmune disorders characterized by dysregulated immune responses; however, the molecular mechanisms underlying their comorbidity remain incompletely understood. Here, we integrated transcriptomic datasets from IgAN and CeD to perform differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, and machine learning-based hub gene identification. The expression profiles and diagnostic performance of the identified hub genes were validated across multiple independent cohorts using receiver operating characteristic analysis, and their cellular localization was further explored using single-cell RNA sequencing data. In addition, we conducted clinical correlation analysis, immune infiltration profiling, therapeutic drug prediction, and constructed transcription factor-miRNA-mRNA regulatory networks. We identified ITGB2, CD74, and KLK1 as shared biomarkers with robust diagnostic performance (AUC > 0.7, with an AUC > 0.9 in the combined model). These genes were closely associated with immune dysregulation and disease progression, and four candidate therapeutic agents were predicted. Collectively, our findings provide novel insights into the shared pathogenic mechanisms and potential therapeutic strategies for IgAN and CeD.
Tao et al. (Thu,) studied this question.