
This study identified diagnostic markers and potential therapeutic options for psoriatic arthritis (PSA) using bioinformatics analysis. Differentially expressed genes (DEGs) were identified from the GSE61281 dataset, and WGCNA analysis revealed PSA-related modules and prognostic biomarkers. The diagnostic marker CLEC2B was identified, showing significant upregulation in blood samples of PSA patients. The CMap database was used to identify the drug candidate celastrol for PSA treatment. Network pharmacology analysis predicted four core targets (IL6, TNF, GAPDH, and AKT1) for celastrol, suggesting its modulation of inflammatory pathways. Molecular docking confirmed stable binding of celastrol to the core targets. This study provides insights into potential diagnostic markers and therapeutic options for PSA.
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