Current Pharmaceutical DesignCurrent Pharmaceutical DesignCurrent Pharmaceutical Design1381-61281873-4286Bentham Science64599210.2174/0113816128331463240816145054Immunology, Inflammation & AllergyResearch ArticleIntegrating Network Pharmacology, Bioinformatics, and Mendelian Randomization Analysis to Identify Hub Targets and Mechanisms of Kunkui Baoshen Decoction in Treating Diabetic Kidney DiseaseSongSiyuaninfo@benthamscience.netYuJiangyiinfo@benthamscience.netDepartment of Endocrinology, Nanjing University of Chinese MedicineDepartment of Endocrinology, Nanjing University of Chinese Medicine,1011202430423367339311012025Copyright ©; 2024, Bentham Science Publishers2024Bentham Science Publishershttps://journals.eco-vector.com/1381-6128/article/view/645992

Objective:To uncover the potential hub targets of Kunkui Baoshen Decoction (KKBS) in alleviating Diabetic Kidney Disease (DKD).

Methods:Targets associated with KKBS and DKD were curated from TCMSP, GeneCards, OMIM, and Dis- GeNET databases. Common targets were identified through intersection analysis using a Venn diagram. Employing the \"Drug-component-target\" approach and constructing a Protein-protein Interaction (PPI) network, pivotal components and hub targets involved in KKBS's therapeutic action against DKD were identified. Functional enrichment and Gene Set Enrichment Analysis (GSEA) elucidated the potential mechanisms of these hub targets. Molecular docking simulations validated binding interactions. Subsequently, hub targets were validated using independent cohorts and clinical datasets. Immune cell infiltration in DKD samples was assessed using ESTIMATE, CIBERSORT, and IPS algorithms. A nomogram was developed to predict DKD prevalence. Finally, causal relationships between hub targets and DKD were explored through Mendelian randomization (MR) analysis at the genetic level.

Results:Jaranol, isorhamnetin, nobiletin, calycosin, and quercetin emerged as principal effective components in KKBS, with predicted modulation of the PI3K/Akt, MAPK, HIF-1, NF-kB, and IL-17 signaling pathways. The hub targets in the PPI network include proteins involved in regulating podocyte autophagy and apoptosis, managing antioxidant stress, contributing to insulin resistance, and participating in extracellular matrix deposition in DKD. Molecular docking affirmed favorable binding interactions between principal components and hub targets. Validation efforts across cohorts and databases underscored the potential of hub targets as DKD biomarkers. Among 20 model algorithms, the Extra Tree model yielded the largest Area Under the Curve (AUC) in receiver operating characteristic (ROC) analysis. MR analysis elucidated that the targets related to antioxidant stress had a positive impact on DKD, while the target associated with renal tubular basement membrane degradation had a negative impact.

Conclusion:Integration of Network Pharmacology, Bioinformatics, and MR analysis unveiled the capacity of KKBS to modulate pivotal targets in the treatment of DKD.

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