Abstract：
This study aimed to characterize PANoptosis-related genes with immunoregulatory features in osteoarthritis (OA) and investigate their potential diagnostic and therapeutic implications. Gene expression data from OA patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and functional enrichment analysis were conducted to identify PANoptosis-related genes (PRGs) associated with OA pathogenesis. A diagnostic model was developed using LASSO regression, and the diagnostic value of key PRGs was evaluated using Receiver Operating Characteristic Curve (ROC) analysis. The infiltration of immune cells and potential small molecule agents were also examined. A total of 39 differentially expressed PANoptosis-related genes (DE-PRGs) were identified, with functional enrichment analysis revealing their involvement in inflammatory response regulation and immune modulation pathways. Seven key PRGs, including CDKN1A, EZH2, MEG3, NR4A1, PIK3R2, S100A8, and SYVN1, were selected for diagnostic model construction, demonstrating high predictive performance in both training and validation datasets. The correlation between key PRGs and immune cell infiltration was explored. Additionally, molecular docking analysis identified APHA-compound-8 as a potential therapeutic agent targeting key PRGs. This study identified and analyzed PRGs in OA, uncovering their roles in immune regulation. Seven key PRGs were used to construct a diagnostic model with high predictive performance. The identified PRGs\' correlation with immune cell infiltration was elucidated, and APHA-compound-8 was highlighted as a potential therapeutic agent. These findings offer novel diagnostic markers and therapeutic targets for OA, warranting further in vivo validation and exploration of clinical applications.
摘要：
本研究旨在表征骨关节炎（OA）中具有免疫调节特征的PANoptosis相关基因，并探讨其潜在的诊断和治疗意义。从基因表达综合(GEO)数据库获得来自OA患者和健康对照的基因表达数据。进行差异表达分析和功能富集分析以鉴定与OA发病机制相关的PANoptosis相关基因（PRG）。使用LASSO回归建立了诊断模型，使用受试者工作特征曲线（ROC）分析评估关键PRG的诊断价值。还检查了免疫细胞和潜在的小分子试剂的浸润。共鉴定出39个差异表达的PANoptosis相关基因(DE-PRGs),功能富集分析揭示了它们参与炎症反应调节和免疫调节途径。七个关键的PRG，包括CDKN1A,选择EZH2、MEG3、NR4A1、PIK3R2、S100A8和SYVN1进行诊断模型构建，在训练和验证数据集中都展示了高预测性能。探索关键PRGs与免疫细胞浸润之间的相关性。此外,分子对接分析确定APHA-化合物-8为靶向关键PRG的潜在治疗剂。本研究确定并分析了OA中的PRGs，揭示它们在免疫调节中的作用。使用七个关键PRG来构建具有高预测性能的诊断模型。阐明了已鉴定的PRGs与免疫细胞浸润的相关性，APHA-化合物-8被强调为潜在的治疗剂。这些发现为OA提供了新的诊断标志物和治疗靶点，保证进一步的体内验证和临床应用的探索。
