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The kidney is a primary target organ in systemic lupus erythematosus (SLE) and ANCA-associated vasculitis (AAV), which frequently manifest as lupus nephritis (LN) and renal AAV, respectively. A severe acute presentation of both diseases is rapidly progressive glomerulonephritis (RPGN), leading to rapid loss of renal function. However, the shared molecular mechanisms underlying this aggressive phenotype remain poorly defined. This study aimed to identify key biomarkers and pathological processes in acute autoimmune-related glomerulonephritis, with a focus on LN and AAV presenting as RPGN. Through comparative transcriptomic analysis of glomerular samples from patients with LN, AAV, and RPGN against healthy controls, we identified a total of 180 common differentially expressed genes, comprising 33 upregulated and 147 downregulated genes. Pathway analysis revealed enhanced immune and inflammatory responses, including neutrophil extracellular trap (NET) formation, accompanied by significant impairments in amino acid and fatty acid metabolism. A core set of 12 hub genes was identified, and network analysis suggested specific transcriptional and post-transcriptional regulatory axes. Immune infiltration analysis demonstrated a common pattern characterized by decreased resting immune cells and increased activated cells—including memory CD4 ⁺ T cells, NK cells, and mast cells—along with elevated monocyte levels, particularly in LN. Notably, epidermal growth factor (EGF) was significantly downregulated and strongly correlated with impaired renal function, demonstrating good diagnostic performance. These findings suggest that EGF may serve as a potential biomarker for LN and RPGN. This study provides the first systematic transcriptomic analysis of LN and AAV presenting as RPGN, highlighting enhanced inflammation (including NETosis) and dysregulated amino acid/fatty acid metabolism as key glomerular pathological features. Targeting EGF signaling and monocyte differentiation may offer novel therapeutic strategy for LN and AAV presenting as RPGN.
Xu et al. (Fri,) studied this question.