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中华危重症医学杂志(电子版) ›› 2022, Vol. 15 ›› Issue (05) : 360 -366. doi: 10.3877/cma.j.issn.1674-6880.2022.05.002

论著

基于生物信息学分析筛选脓毒症诱导急性肺损伤的关键基因
梁哲浩1, 方明笋2, 胡弘毅3, 陶涛3, 徐孝平2, 孙华琴3,()   
  1. 1. 310006 杭州,浙江中医药大学附属第一医院超声诊断科
    2. 310053 杭州,浙江中医药大学动物实验研究中心
    3. 310006 杭州,浙江中医药大学附属第一医院麻醉科
  • 收稿日期:2022-05-25 出版日期:2022-10-31
  • 通信作者: 孙华琴
  • 基金资助:
    浙江省自然科学基金项目(LY20H150002); 浙江省医药卫生科技计划项目(2014KYA159)

Bioinformatics analysis to screen key genes in septic-induced acute lung injury

Zhehao Liang1, Mingsun Fang2, Hongyi Hu3, Tao Tao3, Xiaoping Xu2, Huaqin Sun3,()   

  1. 1. Department of Ultrasound Diagnosis, the First Affiliated Hospital of Zhejiang Chinese Medicine University, Hangzhou 310006, China
    2. Animal Experimental Research Center, Zhejiang Chinese Medicine University, Hangzhou 310053, China
    3. Department of Anesthesiology, the First Affiliated Hospital of Zhejiang Chinese Medicine University, Hangzhou 310006, China
  • Received:2022-05-25 Published:2022-10-31
  • Corresponding author: Huaqin Sun
引用本文:

梁哲浩, 方明笋, 胡弘毅, 陶涛, 徐孝平, 孙华琴. 基于生物信息学分析筛选脓毒症诱导急性肺损伤的关键基因[J]. 中华危重症医学杂志(电子版), 2022, 15(05): 360-366.

Zhehao Liang, Mingsun Fang, Hongyi Hu, Tao Tao, Xiaoping Xu, Huaqin Sun. Bioinformatics analysis to screen key genes in septic-induced acute lung injury[J]. Chinese Journal of Critical Care Medicine(Electronic Edition), 2022, 15(05): 360-366.

目的

通过生物信息学分析筛选脓毒症诱导急性肺损伤(ALI)的关键基因。

方法

从基因表达谱(GEO)数据库中下载GSE10474数据集,该数据集包含13例脓毒症ALI患者样本(ALI组)和21例脓毒症患者样本(脓毒症组)基因数据。使用limma包筛选两组样本的差异表达基因,并对筛选出的差异表达基因进行基因本体论(GO)功能分析及京都基因与基因组百科全书(KEGG)富集分析。通过STRING数据库构建蛋白质相互作用(PPI)网络并确定前10位hub基因。

结果

从GSE10474数据集中共筛选出115个差异表达基因,其中65个上调基因,50个下调基因。GO分析显示,生物过程的基因主要富集在金属离子稳态、氧化应激、电离辐射等;细胞组分主要富集在液泡膜、高尔基体膜、内质网膜、溶酶体膜等生物膜;这些基因主要与生物跨膜、泛素结合酶活性、蛋白络氨酸、丝氨酸和苏氨酸激酶结合蛋白活性以及蛋白激酶抑制活性等分子功能相关。KEGG富集分析显示,差异表达基因主要富集在磷脂酶信号通路、胰岛素信号通路、T细胞介导的免疫反应以及免疫相关的信号通路。PPI网络图筛选出了前10位hub基因,分别为CD4、CD74、髓细胞核分化抗原(MNDA)、髓细胞触发受体1(TREM1)、人白细胞抗原DRA(HLA-DRA)、细胞附着蛋白1相互作用蛋白(CYTIP)、凝血因子XⅢA链(F13A1)、血清胱抑素F(CST7)、丝裂原激活蛋白激酶1(MAPK1)、细胞周期蛋白依赖性激酶抑制剂1A(CDKN1A)。

结论

CD4、CD74、MNDA、TREM1、HLA-DRA、CYTIP、F13A1、CST7、MAPK1及CDKN1A是脓毒症诱导ALI的关键基因,可作为临床治疗和新药开发的新靶点。

Objective

To screen key genes in sepsis-induced acute lung injury (ALI) by bioinformatics analysis.

Methods

The GSE10474 dataset was downloaded from the gene expression omnibus (GEO). The dataset included gene data of 13 patients with sepsis-induced ALI (ALI group) and 21 patients with sepsis (sepsis group). The limma package was used to screen differentially expressed genes between the two groups. Then gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEEG) enrichment analysis were performed on these differentially expressed genes. The protein-protein interaction (PPI) network was established using the STRING database to identify the top 10 hub genes.

Results

A total of 115 differentially expressed genes were identified from the GSE10474 dataset, including 65 up-regulated genes and 50 down-regulated genes. GO analysis showed that the differentially expressed genes of biological processes were mainly enriched in metal ion homeostasis, oxidative stress, and ionizing radiation. The cellular components were mainly concentrated in biofilms such as vacuolar membrane, Golgi apparatus, endoplasmic reticulum membrane, and lysosomal membrane. These genes were mainly associated with molecular functions such as biological transmembrane, ubiquitin-conjugating enzyme activity, protein tyrosine, serine and threonine kinases binding protein activity, and protein kinase inhibitory activity. KEGG enrichment analysis showed that the differentially expressed genes were mainly concentrated in the phospholipase signaling pathway, insulin signaling pathway, and T cell-mediated immune response and immune-related signaling pathways. The PPI network screened out the top 10 hub genes, including CD4, CD74, myeloid cell nuclear differentiation antigen (MNDA), triggering receptor expressed on myeloid cells 1 (TREM1), human leukocyte antigen DRA (HLA-DRA), cytohesin 1 interacting protein (CYTIP), coagulation factor XⅢA chain (F13A1), cystatin F (CST7), mitogen-activated protein kinase 1 (MAPK1), and cyclin dependent kinase inhibitor 1A (CDKN1A).

Conclusion

CD4, CD74, MNDA, TREM1, HLA-DRA, CYTIP, F13A1, CST7, MAPK1, and CDKN1A are key genes for sepsis-induced ALI, which can be used as new targets for clinical treatment and drug development.

图1 GSE10474数据集中ALI组与脓毒症组样本差异表达基因的分析图注:ALI.急性肺损伤;FC.差异倍数;a图为差异表达基因热图,横坐标代表样品(橙色为ALI组,蓝色为脓毒症组),纵坐标代表基因,红色为上调,绿色为下调;b图为差异表达基因火山图,蓝色为下调基因,红色为上调基因,灰色为非显著差异基因。图中每一个点代表一个基因
图2 GSE10474数据集中ALI组与脓毒症组样本差异表达基因的GO/KEGG分析注:ALI.急性肺损伤;GO.基因本体;KEGG.京都基因与基因组百科全书;BP.生物学过程;CC.细胞组分;MF.分子功能;a~c图分别为差异表达基因的GO-BP气泡图、GO-CC气泡图、GO-MF气泡图;d图为差异表达基因的KEGG分析气泡图
图3 PPI网络分析图注:PPI.蛋白质相互作用;a图为赋予参数的PPI网络分析图,圆点越大节点度越大,颜色由红至蓝为上调至下调,结合分数越高,连线越粗,线的颜色越红;b图为hub-Gene关系图,颜色越深,最大团中心性得分越高
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