Title:Integrating Network Pharmacology, Bioinformatics, and Mendelian Randomization Analysis to Identify Hub Targets and Mechanisms of Kunkui Baoshen Decoction in Treating Diabetic Kidney Disease
Volume: 30
Issue: 42
Author(s): Siyuan Song and Jiangyi Yu*
Affiliation:
- Department of Endocrinology, Nanjing University of Chinese Medicine, Nanjing 210029, Jiangsu Province, China
- Department of
Endocrinology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine,
Nanjing, China
Keywords:
Kunkui Baoshen decoction, diabetic kidney disease, network pharmacology, molecular docking, bioinformatics, MR analysis.
Abstract:
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.
