Integrative bioinformatics analysis of Lianmei granules in diabetic nephropathy: Epidemiological and molecular...

Diabetic nephropathy (DN) is a severe complication of diabetes mellitus, leading to end-stage renal disease and significant morbidity. Current therapies are limited by efficacy and side effects, highlighting the need for novel treatments. Lianmei granules (LMG) show potential for treating DN, although their mechanisms remain unclear. This study explored DN epidemiology and investigated the active components, targets, and mechanisms of LMG using a comprehensive bioinformatics approach. We conducted a cross-sectional analysis involving 44,090 participants from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2023. Given the cross-sectional nature of NHANES, our analytical definition of DN was the presence of diagnosed diabetes and UACR≥30 mg/g in both matched adjacent NHANES cycles. This approach reduced potential false positives from single measurements and approximated clinical diagnostic standards without representing longitudinal follow-up. Multivariate logistic regression identified DN risk factors. LMG active compounds were screened using databases such as TCMSP. Overlapping targets with DN-related genes were identified to construct interaction networks, followed by protein-protein interaction networks, gene ontology/Kyoto Encyclopedia of Genes and Genomes enrichment, gene expression, and immune infiltration analyses. Molecular docking and dynamics simulations were performed. Gender (OR: 1.072, 95% CI: 1.015-1.132, P <.01), race (Non-hispanic black: OR=1.536, 95% CI: 1.412-1.671, P < .001; Mexican Americans: OR = 1.284, 95% CI: 1.165-1.415, P < .001) and hypertension (OR = 1.321, 95% CI: 1.235-1.413, P < .001) were identified as independent risk factors for DN. A total of 215 active LMG compounds and 64 potential DN-related targets were identified, with core targets including prostaglandin-endoperoxide synthase 2, EGFR, ESR1, CYP3A4, and matrix metallopeptidase 9. Enrichment analysis indicated that these targets are mainly involved in cellular responses and hormone signaling. Differential expression analysis (GSE96804) revealed 615 differentially expressed genes, and immune infiltration analysis showed significant immune cell distribution differences between DN and control groups. Molecular docking and dynamics simulations predicted strong binding affinities between key compounds (resveratrol, kaempferol) and core targets (matrix metallopeptidase 9, EGFR). However, further in vitro or molecular studies are needed to validate these mechanisms. This integrative approach underscores the complexity of DN pathogenesis and highlights LMG's potential as a multi-target therapeutic strategy, warranting further investigation into its clinical applications.