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中华眼科医学杂志(电子版) ›› 2022, Vol. 12 ›› Issue (05) : 262 -267. doi: 10.3877/cma.j.issn.2095-2007.2022.05.002

论著

基于文本挖掘数据库干性年龄相关性黄斑变性免疫反应核心基因与关键通路的生物信息学分析
魏航1, 赵明威2, 曲进锋2,†()   
  1. 1. 100044　北京大学第二临床医学院（北京大学人民医院）2018级硕士研究生
    2. 100044　北京大学人民医院眼科、眼视光中心　眼病与视光医学研究所　视网膜脉络膜疾病诊治研究北京市重点实验室　北京大学医学部眼视光学院
  • 收稿日期:2022-04-25 出版日期:2022-10-28
  • 通信作者: 曲进锋
  • 基金资助:
    国家重点研发计划项目(2020YFC2008203)

Text mining-based in bioinformatics analysis of key genes and signal pathways related to immunoreaction in dry age-related macular degeneration

Hang Wei1, Mingwei Zhao2, Jinfeng Qu2,†()   

  1. 1. Master′s degree 2018, Peking University People′s Hospital, Peking University Health Science Center, Beijing 100044, China
    2. Department of Ophthalmology, Peking University People′s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing 100044, China
  • Received:2022-04-25 Published:2022-10-28
  • Corresponding author: Jinfeng Qu
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引用本文：

魏航, 赵明威, 曲进锋. 基于文本挖掘数据库干性年龄相关性黄斑变性免疫反应核心基因与关键通路的生物信息学分析[J]. 中华眼科医学杂志(电子版), 2022, 12(05): 262-267.

Hang Wei, Mingwei Zhao, Jinfeng Qu. Text mining-based in bioinformatics analysis of key genes and signal pathways related to immunoreaction in dry age-related macular degeneration[J]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2022, 12(05): 262-267.

目的

利用生物信息学方法挖掘筛选干性年龄相关性黄斑变性(AMD)免疫反应过程中的核心基因与关键通路。

方法

通过文本挖掘数据库pubmed2ensembl检索dry AMD和immune reaction的基因数据集。利用GeneCodis工具依次进行基因本体数据库(GO)功能富集及京都基因与基因组百科全书(KEGG)信号通路富集。应用基于互联网的STRING数据库构建蛋白质相互作用(PPI)网络关系，并应用Cytoscape软件的CytoHubba及分子复合物检测插件(MCODE)功能分别筛选PPI网络中的枢纽基因及显著基因模块，再通过DAVID数据库平台筛选出相关枢纽基因及基因模块，并进行功能富集分析。

结果

通过文本挖掘，获得了与干性AMD相关的47个基因，与免疫反应相关的2410个基因，其中与两个关键词均相关的基因31个。经GO功能富集及KEGG信号通路富集，得到66个显著富集的信号通路，共包含22个基因。经Cytohubba筛选，分数值排名前10的枢纽基因依次为白细胞介素(IL)10、趋化因子8(CXCL8)、肿瘤坏死因子(TNF)、IL18、IL6、肿瘤蛋白P53(TP53)、血管内皮生长因子(VEGFA)、丝裂原活化蛋白激酶8(MAPK8)、细胞周期蛋白依赖性激酶抑制剂1A(CDKN1A)及丝氨酸－苏氨酸蛋白激酶1(AKT1)。从PPI网络MCODE功能筛选出1个显著基因模块，包含IL10、CXCL8、TNF、IL18及IL6等5个与枢纽基因相重合的基因。GO分析显示显著基因模块的生物过程主要涉及炎症反应、免疫反应、细胞对脂多糖反应及2型免疫反应等；KEGG通路分析显示主要涉及细胞因子－细胞因子受体的相互作用、核苷酸结合寡聚化结构域(NOD)样受体信号通路、炎症性肠病、哮喘、移植物抗宿主病及同种异体移植物排斥反应等信号通路。

结论

文本挖掘结合生物信息分析筛选出与干性AMD免疫反应过程相关的1个核心基因模块和5个关键信号通路，可为其治疗提供潜在靶点。

关键词: 干性年龄相关性黄斑变性, 免疫反应, 核心基因, 信号通路, 生物信息学
Objective

To screen the core genes and key pathways related to immunoreaction in dry age-related macular degeneration (AMD) using text mining and bioinformatics methods.

Methods

The gene datasets related to dry AMD and immune reactionwere retrieved through the text mining database pubmed2ensembl. The gene ontology (GO) function enrichment and Kyoto Encyclopedia of genes and genomes (KEGG) were carried out successively by using the GeneCodis tool signal pathway enrichment. The protein-protein interaction (PPI) network relationship was constructed by using the STRING database based on the Internet, and the hub genes and significant gene modules in the PPI network were screened by using the CytoHubba and mcode plug-ins of Cytoscape software. The function enrichment analysis of the screened hub genes and gene modules was carried out through the DAVID platform.

Results

Based on text mining and enrichment analysis, 47 genes related to dry AMD and 2410 genes related to immune response were obtained. Among of them, there were 31 genes related to both.GO functional enrichment and KEGG signal pathway enrichment analysis obtained 66 significantly enriched signal pathways, including 22 genes. The top 10 hub genes screened by Cytohub plug-in were interleukin (IL)10, C-X-C motif chemokine ligand 8 (CXCL8), tumor necrosis factor (TNF), IL18, IL6, tumor Protein P53 (TP53), vascular endothelial growth factor A (VEGFA), mitogen-activated protein kinase 8 (MAPK8), cyclin dependent kinase inhibitor 1A (CDKN1A) and AKT serine-threonine kinase 1 (AKT1). The significant gene module from PPI network screened by MCODE plug-in included IL10, CXCL8, TNF, IL18 and IL6 genes, which coincided with the hub gene. The GO analysis showed that significant gene modules were mainly involved in the inflammatory response, immune response, cell response to lipopolysaccharide and type 2 immune response in the biological processes. KEGG pathway analysis found that they were mainly involved in the interaction of cytokine-cytokine receptor, nucleotide-binding oligomerization domain (NOD)-like receptor signal pathway, inflammatory bowel disease, asthma, graft-versus-host disease and allograft rejection.

Conclusions

The one core gene modules and five key signal pathways related to the immunoreaction process of dry AMD are screened out through text mining and biological information analysis, which provides a potential target for the treatment of dry AMD.

Key words: Dry age-related macular degeneration, Immunoreaction, Core genes, Signaling pathway, Bioinformatics
图1 干性AMD免疫反应关键基因及信号通路筛选流程图　注：AMD，年龄相关性黄斑变性；GO，基因本体数据库；KEGG，京都基因与基因组百科全书；PPI，蛋白质相互作用网络
表1 KEGG富集分析中富集基因数排名前10位的生物过程和信号通路
项目 参与过程(或通路) 富集基因数(个) 基因组总基因数(个) 矫正超几何P值 富集基因
生物过程 基因表达的负调控 13 305 1.93e－19 SERPINF1、KDR、AKT1、ESR1、TNF、BMP4、APOE、TP53、CDKN1A、IL8、PPARG、ACE及VEGFA
细胞因子相关信号通路 12 313 1.89e－17 HMOX1、PTGS2、AKT1、TNF、IL18、TP53、CDKN1A、KIT、IL6、IL8、IL10及VEGFA
基因表达的正调控 12 508 4.32e－15 AKT1、TNF、BMP4、IL18、TP53、KIT、IL6、MAPK8、IL8、PPARG、CRP及VEGFA
凋亡过程的负调控 11 526 3.51e－13 PTGS2、KDR、AKT1、BMP4、TP53、CDKN1A、ALB、IL6、MAPK8、IL10及VEGFA
平滑肌细胞增殖的正调控 7 63 5.25e－13 HMOX1、PTGS2、AKT1、TNF、BMP4、IL18及IL6
正调控DNA结合转录因子的活性 7 117 3.85e－11 AKT1、ESR1、TNF、KIT、IL6、PPARG及IL10
氧化应激反应 7 125 5.29e－11 HMOX1、PTGS2、AKT1、APOE、TP53、MBL2及MAPK8
MAPK级联正调控 7 164 3.18e－10 KDR、TNF、BMP4、KIT、IL6、ADRA1D及VEGFA
对有机物的反应 6 82 4.52e－10 PTGS2、TIMP3、AKT1、TNF、CDKN1A及IL10
凋亡过程的正调控 8 375 1.50e－9 HMOX1、PTGS2、AKT1、TNF、BMP4、TP53、IL6及MAPK8
信号通路 癌症相关通路 13 369 9.01e－21 HMOX1、PTGS2、AKT1、ESR1、BMP4、TP53、CDKN1A、KIT、IL6、MAPK8、IL8、PPARG及VEGFA
流体剪切应力与动脉粥样硬化 8 97 2.68e－15 HMOX1、KDR、AKT1、TNF、BMP4、TP53、MAPK8及VEGFA
卡波西肉瘤相关疱疹病毒感染 8 134 2.55e－14 PTGS2、AKT1、TP53、CDKN1A、IL6、MAPK8、IL8及VEGFA
癌症相关蛋白聚糖 8 142 3.07e－14 TIMP3、KDR、AKT1、ESR1、TNF、TP53、CDKN1A及VEGFA
人类巨细胞病毒感染 8 160 4.65e－14 PTGS2、AKT1、TNF、TP53、CDKN1A、IL6、IL8及VEGFA
脂质和动脉粥样硬化 8 159 5.15e－14 AKT1、TNF、IL18、TP53、IL6、MAPK8、IL8及PPARG
恰加斯病 7 77 6.13e－14 AKT1、TNF、IL6、MAPK8、IL8、ACE及IL10
鼠疫感染 7 102 2.92e－13 AKT1、TNF、IL18、IL6、MAPK8、IL8及IL10
乙型肝炎 7 129 1.40e－12 AKT1、TNF、TP53、CDKN1A、IL6、MAPK8及IL8
非酒精性脂肪性肝病 6 65 3.43e－12 AKT1、TNF、IL6、MAPK8、IL8及PPARG
图3 干性AMD相关免疫反应的显著基因模块和枢纽基因　图3A示Cytoscape可视化下的PPI网络，黄色的为显著基因模块；图3B示经MCODE分析得到的显著基因模块，红色为模块核心基因；图3C示经Cytohubb分析PPI网络中的枢纽基因代表　注：AMD，年龄相关性黄斑变性；PPI，蛋白质相互作用；IL，白细胞介素；CXCL8，趋化因子8；TNF，肿瘤坏死因子；TP53，肿瘤蛋白P53；VEGFA，血管内皮生长因子A；MAPK8，丝裂原活化蛋白激酶8；CDKN1A，细胞周期蛋白依赖性激酶抑制剂1A；AKT1，丝氨酸－苏氨酸蛋白激酶1；KDR，血管内皮细胞生长因子受体2；BMP4，人骨形态发生蛋白4；TIMP3，组织金属蛋白酶抑制因子3；PPARG，过氧化物酶体增生激活受体γ；ESR1，雌激素受体1；PTGS2，前列腺素内过氧化物合酶2；KIT，Ⅲ型跨膜受体酪氨酸激酶编码基因
图4 枢纽基因和显著基因模块的功能富集分析　图4A和4C分别示10个枢纽基因和显著基因模块的基因本体数据库富集分析；图4B和4D分别示10个枢纽基因和显著基因模块的京都基因与基因组百科全书富集分析　注：RNA，核糖核酸；DNA，脱氧核糖核酸
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