基于综合生物信息学分析识别神经病理性疼痛中NLRP3炎性小体相关生物标志物

推荐 为解决神经病理性疼痛（NP）中NLRP3炎性小体机制研究不足的问题，研究人员通过公共数据库分析NP与正常样本的差异基因，结合加权基因共表达网络分析（WGCNA）和机器学习筛选出Lyz2、Fcgr4等六个关键标志物，并验证其与NLRP3的关联性。该研究为NP治疗提供了潜在靶点。

　　

翻译
Neuropathic pain (NP) is a chronic disorder caused by nerve injury, viral infections, and other factors. Inflammatory mediators play a crucial role in its pathogenesis, with the NLRP3 inflammasome being extensively studied in other diseases but less explored in NP. This study analyzed differentially expressed genes between NP and normal samples using public databases. Six key biomarkers—Lyz2, Fcgr4, Gm2a, Sumf1, Zbtb7a, and Treml2—were identified through weighted gene co-expression network analysis (WGCNA) and machine learning approaches. The research value of these biomarkers was further validated through correlation analysis, expression validation, regulatory network construction, and molecular docking. Results indicated that Lyz2 might serve as a pivotal NLRP3-associated marker with significant potential in NP. This study offers novel targets for NP research.