微创医学

目的基于生物信息学分析红景天苷（SAL）影响脊髓损伤（SCI）预后的关键基因，为治疗SCI提供新的靶点。方法通过SwissTargetPrediction、CTD、HERB数据库检索SAL靶点，利用R软件分析大鼠SCI基因芯片数据集GSE45006中的差异表达基因，利用Venny 2.1分析得到SAL与GSE45006数据集差异基因中共有的基因。基于STRING数据库和Cytoscape软件筛选核心基因。运用Metascape数据库进行GO富集分析和KEGG分析，预测SAL治疗SCI的机制。最后制备SCI大鼠模型，通过实时荧光定量聚合酶链反应（qRT-PCR）验证核心基因。结果数据库筛选得到SAL与SCI交集靶基因共25个。GO富集分析发现交集靶基因主要参与缺氧反应、营养响应、细胞发育的正向调控、神经元细胞体、细胞顶端部分、细胞因子受体结合等生物学过程。KEGG主要富集在糖尿病并发症中的AGE-RAGE信号通路、脂质与动脉粥样硬化、阿尔茨海默病、MAPK信号通路和癌症中的微小RNA等信号通路。qRT-PCR实验发现，与假手术组相比，SCI模型组中AKT1、SPP1 表达显著下调，FN1、TGFB1、CASP1、IL-18、HMOX1、MAPT、CYBB及RELA表达显著升高。与SCI组相比，SAL组中AKT1、FN1、TGFB1、IL-18、HMOX1、MAPT、CYBB、TUBB3、RELA mRNA表达水平下降，CASP1和CASP3 mRNA表达水平上升，SPP1 表达无明显变化。结论 FN1、TGFB1、IL-18、HMOX1、CYBB、RELA基因可能是SAL治疗SCI新的生物标志物。

Objective To analyze the key genes influencing the progonosis of SCI by salidroside(SAL) based on bioinformatics, and to a new targets for the treatement of SCI. Methods The targets of SAL were searched through SwissTargetPrediction, CTD, and HERB database. The differentially expressed genes in the rat SCI gene chip dataset GSE45006 were analyzed by R software. Venny 2.1 analysis was carried out to find shared genes between the SAL targets and differentially expressed genes in the GSE45006 dataset. The STRING database and Cytoscape software were utilized to identify core targets. GO functional and KEGG analyses were performed using the Metascape database to clarify the mechanisms by which SAL acts on SCI. Finally, a rat model of SCI was constructed, and the core genes were validate using real-time fluorescence quantititative polymerase chain reaction (qRT-PCR) technique. Results A total of 25 common target genes of SAL and SCI were obtained by database screening. GO enrichment analysis indicated that the intersection target genes were mainly involved in biological processes such as hypoxia response, nutrient response, positive regulation of cell development, neuronal cell body, apical part of cell, cytokine receptor binding and so on. KEGG highlighted several critical pathways, including AGE-RAGE signaling pathway in diabetic complications, lipid and atherosclerosis, Alzheimer disease, MAPK signaling pathway and MicroRNAs in cancer. The qRT-PCR experiment revealed that, compared to the Sham operation group, the SCI model group showed a significant downregulation of AKT1 and SPP1 expression, while the expression of FN1, TGFB1, CASP1, IL-18, HMOX1, MAPT, CYBB and RELA was significantly upregulated. Compared with the SCI group, the mRNA expression levels of AKT1, FN1, TGFB1, IL-18, HMOX1, MAPT, CYBB, TUBB3, and RELA decreased in the SAL group. Conversely, the mRNA expression levels of CASP1 and CASP3 increased, while the expression of SPP1 remained unchanged with no significant difference. Conclusion The FN1, TGFB1, IL-18, HMOX1, CYBB, and RELA genes are potential biomarkers for the treatment of SCI with SAL.