Integrated bioinformatics analysis for identifying fibroblast-associated biomarkers and molecular subtypes in human membranous nephropathy

Membranous nephropathy (MN) is characterized by immune complex deposition in the glomerular basement membrane, leading to proteinuria and potentially progressive renal dysfunction. Fibroblasts have been implicated in the pathogenesis of MN through their involvement in tissue remodeling and immune modulation. We employed integrated bioinformatics analyses to identify fibroblast-associated biomarkers and molecular subtypes in MN. The xCell algorithm was used to assess fibroblast infiltration, and weighted gene co-expression network analysis (WGCNA) identified fibroblast-related gene modules. Differentially expressed fibroblast-associated genes (DEFAGs) were screened between MN and healthy controls (HC) using differential expression analysis and protein-protein interaction (PPI) network construction. Consensus clustering categorized MN patients into distinct subtypes based on DEFAG expression profiles. Fibroblast scores were a significant elevation in MN compared to HC, indicating increased fibroblast involvement in MN pathogenesis. WGCNA identified 13 fibroblast-related gene modules, with the brown and turquoise modules showing strong correlation with fibroblast scores (correlation coefficient = 0.79 and 0.75, respectively, p