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基于生物信息学分析溃疡性结肠炎的差异表达基因和相关微小RNA

Differentially expressed genes of ulcerative colitis and associated microRNAs based on bioinformatics analysis

    摘要
  • 摘要:
    目的 基于生物信息学分析溃疡性结肠炎(UC)中具有诊断和治疗潜力的差异表达基因以及潜在的微小RNA(miRNA)。
    方法 采用加权基因共表达网络分析法对GEO数据库中的芯片原始数据进行筛选。获取UC相关差异表达基因进行富集分析。根据关键基因, 预测与差异表达基因相关的潜在miRNA, 并构建基因-miRNA调控网络。
    结果 共筛选出277个差异表达基因，其中有200个基因上调, 77个基因下调。基因集富集分析(GSEA)显示，主要富集通路是神经活性配体受体相互作用、利什曼原虫感染、朊病毒病害以及心电图受体相互作用等通路。基因本体论(GO)分析结果显示，主要参与趋化因子活性、肝素结合、趋化因子受体结合等条目。京都基因与基因组百科全书(KEGG)分析结果显示，主要富集通路为细胞因子受体相互作用通路、磷脂酰肌醇-3激酶/蛋白激酶B(PI3K-AKT)信号通路、趋化因子信号通路、核转录因子kappa B(NF-κB)信号通路富集通路等。筛选出10个枢纽基因，分别是C-X-C趋化因子配体8(CXCL8)、Toll样受体2(TLR2)、细胞间黏附分子1(ICAM1)、选择素L(SELL)、趋化因子受体4(CXCR4)、细胞毒性T淋巴细胞相关抗原(CTLA4)、细胞分化抗原69(CD69)、双糖链蛋白多糖(BGN)、C-X-C趋化因子配体13(CXCL13)、金属蛋白酶抑制剂1(TIMP1)。鉴定出12个潜在的关键miRNAs, 分别为hsa-mir-335-5p、hsa-mir-146a-5p、hsa-mir-92a-3p、hsa-mir-155-5p、hsa-mir-26b-5p、hsa-mir-4426、hsa-mir-4462b、hsa-mir-4647、hsa-mir-32-5p、hsa-mir-92b-3p、hsa-mir-98-5p和hsa-mir-93-5p。
    结论 本研究共筛选出277个差异表达基因可能参与UC的发生发展，鉴定出10个枢纽基因和12个miRNAs或可作为UC的生物标志物。

     

    Abstract:
    Objective To analyze differentially expressed genes and potential microRNA (miRNAs) with diagnostic and therapeutic potential in ulcerative colitis (UC) based on bioinformatics.
    Methods The chip raw data in GEO database was screened by weighted gene coexpression network analysis. UC related differentially expressed genes were obtained for enrichment analysis. Potential miRNAs associated with differentially expressed genes were predicted based on key genes, and gene-miRNA regulatory networks were constructed.
    Results A total of 277 differentially expressed genes were screened, of which 200 genes were up-regulated and 77 genes were down-regulated. Gene set enrichment analysis (GSEA) showed that the main enrichment pathways were neuroactive ligand-receptor interaction, leishmania infection, prion disease and electrocardiogram receptor interaction. The results of gene ontology (GO) analysis showed that it was mainly involved in chemokine activity, heparin binding as well as chemokine receptor binding and other items. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the main enrichment pathways were cytokine receptor interaction pathway, phosphatidylinositol-3 kinase/protein kinase B(PI3K-AKT) signaling pathway, chemokine signaling pathway as well as nuclear transcription factor kappa B(NF-κB) signaling pathway and other pathway. A total of 10 hub genes were screened: C-X-C chemokine ligand 8 (CXCL8), Toll-like receptor 2 (TLR2), intercellular adhesion molecule-1 (ICAM-1), selectin L (SELL), C-X-C chemokine receptor type 4 (CXCR4), cytotoxic T lymphocyte associated antigen 4 (CTLA4), cluster of differentiation 69 (CD69), and Biglycan (BGN), C-X-C chemokine ligand 13 (CXCL13), tissue inhibitor of metalloproteinases 1(TIMP1). A total of 12 potentially key miRNAs were identified, they were respectively hsa-mir-335-5p, hsa-mir-146a-5p, hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-26b-5p, hsa-mir-4426, hsa-mir-4462b, hsa-mir-4647, hsa-mir-32-5p, hsa-mir-92b-3p, hsa-mir-98-5p and hsa-mir-93-5p, respectively.
    Conclusion In this study, a total of 277 differentially expressed genes are screened for possible involvement in the development of UC, and 10 hub genes and 12 miRNAs are identified as possible biomarkers for UC.

     

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