A network pharmacology integrated molecular docking strategy was used to predict the underlying molecular mechanism of Ermiao san in the treatment of hyperuricemia and gout. Traditional Chinese medicine systems pharmacology (TCMSP) database and analysis platform were used to screen out the active compounds and their targets of Ermiao san. The disease target genes related to hyperuricemia (HUA) and gout were obtained by searching CTD, DisGeNET, DrugBank, GeneCards, OMIM, TTD, and PharmGKB databases with “Hyperuricemia” and “Gout” as keywords, respectively. The potential targets of Ermiao san in the treatment of HUA and gout were screened through a Venn diagram. The protein–protein interaction network was constructed using Cytoscape software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were then conducted. Finally, some compounds and core targets were selected for molecular docking verification by Autodock Vina and Pymol software. Forty-six active compounds, such as quercetin, wogonin and beta-sitosterol, etc were identified. Ermiao san plays a therapeutic role in HUA and gout regulating various biological processes, cellular compounds, and molecular functions. The core targets of Ermiao san for treating HUA and gout are AT1 (namely Protein Kinase Bα), interleukin-1 beta, prostaglandin-endoperoxide synthase 2, JUN, etc. And the key pathways are nuclear factor-κB, interleukin-17 and tumor necrosis factor. The results of molecular docking analyses suggested that active compounds of Ermiao san could bind well to the core protein receptors. Ermiao san has a synergistic mechanism of multiple compounds, multiple targets, and multiple pathways in the treatment of HUA and gout, which provides a good theoretical basis for the clinical application.

Introduction: It has been reported that individuals with type 1 diabetes (T1D) are at a higher risk of concomitant occurrence of other autoimmune diseases (AIDs). Currently, there is a lack of research investigating the causal relationship between T1D and other AIDs. A comprehensive Mendelian randomization (MR) study was conducted using debiased inverse-variance weighted (dIVW) and inverse-variance weighted (IVW) estimators to examine the bidirectional causal relationship between T1D and 12 AIDs.Material and methods: Genome-wide association study (GWAS) summary statistics datasets related to T1D or 12 AIDs were obtained from the FinnGen study or other published cohort studies. Pruned SNPs in linkage disequilibrium (LD)-clumped single-nucleotide polymorphisms (SNPs) were used as instrumental variables. For the dIVW analysis, no genome-wide significance threshold was applied for SNP selection.Results: For each 1-unit increase in the log-transformed odds ratio (OR) of patients with primary biliary cholangitis (PBC) or rheumatoid arthritis (RA), the ORs of T1D were 1.123 (95% CI: 1.094–1.151) and 1.133 (95% CI: 1.100–1.167), respectively. Conversely, for each 1-unit increase in the log-transformed OR of T1D, the OR of RA was 1.383 (95% CI: 1.213–-1.578). No bidirectional associations were found between T1D and other AIDs.Conclusions: Patients with RA or PBC have a higher risk of developing T1D, and those with T1D also have an increased risk of developing RA. These findings highlight the importance of regular screening for individuals with T1D, RA, or PBC.