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<p>Diabetic nephropathy (DN) is characterized by nephron degeneration induced by hyperglycemia, driven by complex interactions between glucose metabolism dysregulation and immune microenvironment dynamics. This study employed machine learning and bioinformatics techniques to investigate the role of finerenone, a novel nonsteroidal mineralocorticoid receptor antagonist, in modulating immune dysregulation associated with DN through targeted intervention in PANoptosis-related networks. Using machine learning algorithms, five key PANoptosis-associated genes (CASP3, FLT3, KDR, HIF1A, and MMP2) were identified, and a diagnostic model incorporating these biomarkers demonstrated high efficacy in distinguishing patients with DN from controls. These genes were strongly correlated with immune cell infiltration, particularly mast cells, M2 macrophages, and B lymphocytes. KEGG and GSVA enrichment analyses highlighted significant pathway enrichment in PI3K-Akt signaling and glycosphingolipid biosynthesis (lacto and neolacto series). These results suggest that finerenone mitigates DN-related immune disruptions by modulating PANoptosis-linked gene expression, thereby influencing PI3K-Akt signaling and glycosphingolipid biosynthesis in mast cells, M2 macrophages, and B cells. This study provides new insights into potential therapeutic targets and pharmacological evidence for precision immunomodulation in DN treatment.</p>

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Finerenone Modulates PANoptosis to Improve Immune Microenvironment in Diabetic Nephropathy: A Machine Learning–Based Mechanistic Analysis

  • 期刊论文

  • 发表日期：

    2025年8月7日

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  • Aihua Chen,
  • Fenghua Wang

摘要

Diabetic nephropathy (DN) is characterized by nephron degeneration induced by hyperglycemia, driven by complex interactions between glucose metabolism dysregulation and immune microenvironment dynamics. This study employed machine learning and bioinformatics techniques to investigate the role of finerenone, a novel nonsteroidal mineralocorticoid receptor antagonist, in modulating immune dysregulation associated with DN through targeted intervention in PANoptosis-related networks. Using machine learning algorithms, five key PANoptosis-associated genes (CASP3, FLT3, KDR, HIF1A, and MMP2) were identified, and a diagnostic model incorporating these biomarkers demonstrated high efficacy in distinguishing patients with DN from controls. These genes were strongly correlated with immune cell infiltration, particularly mast cells, M2 macrophages, and B lymphocytes. KEGG and GSVA enrichment analyses highlighted significant pathway enrichment in PI3K-Akt signaling and glycosphingolipid biosynthesis (lacto and neolacto series). These results suggest that finerenone mitigates DN-related immune disruptions by modulating PANoptosis-linked gene expression, thereby influencing PI3K-Akt signaling and glycosphingolipid biosynthesis in mast cells, M2 macrophages, and B cells. This study provides new insights into potential therapeutic targets and pharmacological evidence for precision immunomodulation in DN treatment.