目的 研究银杏二萜内酯葡胺注射液（Diterpene Ginkgolides Meglumine Injection，DGMI）及其银杏二萜内酯成分抗人脐静脉内皮细胞（human umbilical vein endothelial cells-T1，HUVEC-T1）氧糖剥夺（oxygen-glucose deprivation，OGD）损伤的潜在作用通路。方法 采用CCK-8法分别测定不同浓度银杏内酯A（ginkgolide A，GA）、银杏内酯B（ginkgolide B，GB）、银杏内酯K（ginkgolide K，GK）和DGMI对HUVEC-T1细胞的毒性，明确药物处理细胞浓度；采用转录组测序技术对溶剂对照组（二甲基亚砜）、模型组（OGD/R 4 h/24 h）及给药组（造模＋不同剂量DGMI、GA、GB、GK处理）的细胞样本分别进行转录组测序；通过生物信息学分析方法，以GEO数据库中缺血性脑卒中患者转录组数据为参考，采用基因集富集分析（gene set enrichment analysis，GSEA）、差异基因富集等分析方法完成对HUVEC-T1 OGD模型及不同浓度药物抗OGD损伤能力的评价，阐明DGMI及其功效成分的潜在作用机制。结果 GSEA分析显示，临床缺血性脑卒中患者血液转录组数据分析获得的疾病富集通路与本实验细胞模型测序结果获得的富集通路相似度为55.6%；DGMI、GA、GB、GK处理组与模型组相比，显著富集的主要信号通路包括FcεRI、NOD样受体、有丝分裂原激活蛋白激酶（mitogen-activated protein kinase，MAPK）、血管内皮生长因子（vascular endothelial growth factor，VEGF）等。差异基因分析显示，与对照组相比，模型组共筛选出439个差异基因，差异基因的基因本体（gene ontology，GO）分析主要富集在应激反应过程，京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）分析主要富集在磷脂酶D、FcεRI、NOD样受体和血小板活化等信号通路；与模型组相比，给药组差异基因的GO分析主要富集在造血和代谢过程，KEGG分析主要富集在血小板活化、磷脂酶D等信号通路。结论 HUVEC-T1 OGD模型模拟了部分缺血性脑卒中的病理特征；DGMI、GA、GB、GK均具有抗OGD损伤作用，发挥抗OGD损伤作用的关键基因及信号通路主要集中在抗炎、抗凋亡、调控血小板活化等生物学过程，可能通过下调FcεRI、NOD样受体、MAPK和VEGF信号通路，干预血小板活化、磷脂酶D等信号通路发挥作用。

Objective To study the potential pathway of Diterpene Ginkgolides Meglumine Injection (银杏二萜内酯葡胺注射液, DGMI) and its ginkgo diterpene lactone components against oxygen-glucose deprivation (OGD) injury in human umbilical vein endothelial cells-T1 (HUVEC-T1). Methods CCK-8 method was used to determine the toxicity of ginkgolide A (GA), ginkgolide B (GB), ginkgolide K (GK) and DGMI at different concentrations on HUVEC-T1 cells, and determine the drug treatment cell concentration. Transcriptomic sequencing was performed on the cell samples of solvent control group (DMSO), model group (OGD/R 4 h/24 h) and the drug administration group (modeling + different doses of GA, GB, GK, DGMI treatment), respectively. Through bioinformatics analysis, the transcriptomic data of ischemic stroke patients in GEO database was used as reference, gene set enrichment analysis (GSEA) and differential genes enrichment analysis methods were used to evaluate the HUVEC-T1 OGD model and the anti-OGD ability of different concentrations of drugs, and to clarify the potential mechanism of action of DGMI and its functional components. Results GSEA analysis showed that the similarity between the disease enrichment pathway obtained from the analysis of blood transcriptome data of clinical ischemic stroke patients and the enrichment pathway obtained from the cell model sequencing results in this experiment was 55.6%. Compared with model group, the main signaling pathways in DGMI, GA, GB, GK treatment group were significantly enriched, including FcεRI, NOD like receptors, mitogen-activated protein kinase (MAPK), vascular endothelial growth factor (VEGF), etc. Differential genes analysis showed that 439 differential genes were detected in model group compared with control group. Gene ontology (GO) analysis of differential genes was mainly enriched in the stress response process, while Kyoto encyclopedia of genes and genomes (KEGG) analysis was mainly enriched in phospholipase D, FcεRI, Nod-like receptor and platelet activation signaling pathways. Compared with model group, GO analysis of differential genes in administration group was mainly enriched in hematopoietic and metabolic processes, while KEGG analysis was mainly enriched in signal pathways such as platelet activation and phospholipase D, etc.Conclusion The HUVEC-T1OGD model simulated the pathological features of partial ischemic stroke. DGMI, GA, GB, GK have anti-OGD damage effects. The key genes and signaling pathways of DGMI, GA, GB, GK in anti-OGD injury mainly focus on anti-inflammatory, anti-apoptosis, regulation of platelet activation and other biological processes, which may down-regulate FcεRI, Nod-like receptor, MAPK and VEGF signaling pathways, and intervene in platelet activation and phospholipase D and other signaling pathways.

R285.5

江苏省自然科学青年基金资助项目（BK20210139）