目的 应用生物信息学技术，从免疫炎症角度探索严重急性呼吸综合征冠状病毒-2（severe acute respiratory syndrome coronavirus-2，SARS-CoV-2）感染诱导动脉粥样硬化（atherosclerosis，AS）进展的核心靶点及重要通路，进而预测潜在防治中药。方法 从基因表达数据库（Gene Expression Omnibus，GEO）中获取新型冠状病毒肺炎患者和动脉粥样硬化患者芯片数据，利用“limmar”包及“Venn”包筛选2种疾病的共同差异表达基因（differentially expressed genes，DEGs），对共同DEGs进行基因本体论（gene ontology，GO）和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）分析，注释其功能及重要通路。对2组基因集进行免疫细胞和免疫功能打分，评估免疫细胞浸润水平。利用STRING数据库，构建蛋白-蛋白互作（protein-protein interaction，PPI）网络；通过Cytoscape的CytoHubba插件识别中枢（hub）基因，引入另外2组数据集对hub基因进行外部验证得到核心基因，并对核心基因分别进行免疫浸润分析及基因集富集分析（gene set enrichment analysis，GSEA），最后通过Coremine Medical数据库预测调控核心基因的潜在中药。结果 得到新型冠状病毒肺炎相关基因7898个，AS进展相关基因471个；共同DEGs 51个，其中高表达基因32个，低表达基因19个。GO与KEGG分析结果显示，共同DEGs主要定位在氯氰菊酯-包膜内吞囊、血小板α颗粒、吞噬泡膜与小泡，经由Toll样受体信号通路、中性粒细胞胞外陷阱形成、补体和凝血级联反应等信号通路，参与髓样分化因子（myeloid differentiation factor 88，MyD88）依赖性Toll样受体信号通路转导、白细胞介素-8（interleukin-8，IL-8）生成与正向调节、IL-6生成与正向调节等生物途径，发挥调节烟酰胺腺嘌呤二核苷磷酸氧化酶活性、Toll样受体结合、脂肽及糖胺聚糖结合等功能。免疫浸润分析结果展现了新型冠状病毒肺炎与AS免疫微环境状态。经筛选共获得5个hub基因，Toll样受体2（Toll-like receptor 2，TLR2）、分化抗原簇163（cluster of differentiation 163，CD163）及补体C1q亚组分亚单位B（complement C1q subcomponent subunit B，C1QB）基因通过了外部验证，成为核心基因。核心基因在免疫浸润分析及GSEA富集分析中均显示出与免疫过程和炎症反应具有较强相关性。川芎、桃仁、当归、黄芩、蒲公英、太子参、黄精等35味中药可作为潜在防治药物。结论 TLR2、CD163及C1QB是SARS-CoV-2介导免疫炎症反应促进AS进展的核心分子，靶向预测的中药是延缓SARS-CoV-2感染后AS进展的潜在药物。

Objective To explore the core targets and important pathways of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced atherosclerosis (AS) progression from the perspective of immune inflammation, so as to predict the potential prevention and treatment of traditional Chinese medicine (TCM). Methods Microarray data were obtained from the Gene Expression Omnibus (GEO) database for coronavirus disease 2019 (COVID-19) patients and AS patients, and the “limmar” and “Venn” packages were used to screen out the common differentially expressed genes (DEGs) genes in both diseases. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed on the common DEGs to annotate their functions and important pathways. The two gene sets were scored for immune cells and immune function to assess the level of immune cell infiltration. The protein-protein interaction (PPI) network was constructed by STRING database, and the CytoHubba plug-in of Cytoscape was used to identify the hub genes. Two external validation datasets were introduced to validate the hub genes and obtain the core genes. Immuno-infiltration analysis and gene set enrichment analysis (GSEA) were performed on the core genes respectively. Finally the potential TCM regulating the core genes were predicted by Coremine Medical database. Results A total of 7898 genes related to COVID-19, 471 genes related to AS progression; And 51 common DEGs, including 32 highly expressed genes and 19 low expressed genes were obtained. GO and KEGG analysis showed that common DEGs, which were mainly localized in cypermethrin-encapsulated vesicles, platelet alpha particles, phagocytic vesicle membranes and vesicles, were involved in many biological processes such as myeloid differentiation factor 88 (MyD88)-dependent Toll-like receptor signaling pathway transduction, interleukin-8 (IL-8) production and positive regulation, IL-6 production and positive regulation to play a role in regulating nicotinamide adenine dinucleotide phosphate oxidase activity, Toll-like receptor binding and lipopeptide and glycosaminoglycan binding through many biological pathways, including Toll-like receptor signaling pathways, neutrophil extracellular trap formation, complement and coagulation cascade reactions. The results of immune infiltration analysis demonstrated the state of immune microenvironment of COVID-19 and AS. A total of 5 hub genes were obtained after screening, among which Toll-like receptor 2 (TLR2), cluster of differentiation 163 (CD163) and complement C1q subcomponent subunit B (C1QB) genes passed external validation as core genes. The core genes showed strong correlation with immune process and inflammatory response in both immune infiltration analysis and GSEA enrichment analysis. A total of 35 TCMs, including Chuanxiong (Chuanxiong Rhizoma), Taoren (Persicae Semen), Danggui (Angelicae Sinensis Radix), Huangqin (Scutellariae Radix), Pugongying (Taraxaci Herba), Taizishen (Pseudostellariae Radix), Huangjing (Polygonati Rhizoma), could be used as potential therapeutic agents. Conclusion TLR2, CD163 and C1QB were the core molecules of SARS-CoV-2-mediated immune inflammatory response promoting AS progression, and targeting predicted herbs were potential drugs to slow down AS progression in COVID-19 patients.

国家重点研发计划“中医药现代化研究”（2021YFC1712900）；国家自然科学基金项目（81873149）；国家“重大新药创制”科技重大专项资助项目（2018ZX09734002）