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基于GEO强直性脊柱炎外周血芯片数据的生物信息学分析寻找新型诊断标志物
引用本文:王晨峰,卢旭华.基于GEO强直性脊柱炎外周血芯片数据的生物信息学分析寻找新型诊断标志物[J].第二军医大学学报,2022,43(8).
作者姓名:王晨峰  卢旭华
作者单位:海军军医大学第二附属医院骨科,海军军医大学第二附属医院骨科
基金项目:国家自然科学基金资助项目(81572201). Supported by National Natural Science Foundation of China (81572201).
摘    要:目的:通过生物信息学策略探索强直性脊柱炎相关的差异基因,寻找疾病的新型诊断标志物。方法:通过美国国立生物中心的基因表达汇总(GEO)数据库下载强直性脊柱炎疾病相关的芯片GSE25101,分析筛选出强直性脊柱炎患者组和正常组之间的差异表达基因,使用在线数据库DAVID对差异基因展开功能注释和信号通路分析,后利用在线数据库STRING和Cytoscape软件构建蛋白互作网络并获取关键基因。最后评估疾病标记物的诊断效能。结果:通过分析共筛选出187个差异基因,其中包含96个上调基因和91个下调基因。GO功能富集和KEGG分析发现差异基因主要参与氧化磷酸化和代谢等生物过程与信号通路。基于蛋白互作网络分析结果筛选出5个关键基因,且ATP5J (AUC=0.859), NDUFB3 (AUC=0.852), UQCRB (AUC=0.840)、COX7A2 (AUC=0.820) 和UQCRH (AUC=0.805)在强直性脊柱炎疾病外周血样本诊断效能显著,可作为该病的新型诊断标记物。结论:ATP5J、NDUFB3、UQCRB、COX7A2和UQCRH或可成为外周血强直性脊柱炎疾病相关的新型诊断标记物,为该病进一步的功能研究提供理论依据。

关 键 词:强直性脊柱炎  GEO  生物信息学  差异基因  标记物
收稿时间:2021/12/20 0:00:00
修稿时间:2022/7/2 0:00:00

Bioinformatics analysis of blood-based diagnostic biomarkers for ankylosing spondylitis by GEO database
WANG Chen-feng and LU Xu-hua.Bioinformatics analysis of blood-based diagnostic biomarkers for ankylosing spondylitis by GEO database[J].Academic Journal of Second Military Medical University,2022,43(8).
Authors:WANG Chen-feng and LU Xu-hua
Institution:Department of Orthopedics,Changzheng Hospital,Navy Medical University,Department of Orthopedics,Changzheng Hospital,Navy Medical University
Abstract:Objective: To explore the differential expression genes (DEGs) related to ankylosing spondylitis (AS) through bioinformatics analysis methods, further identifying the signaling pathways and key molecules involved in the disease. Methods: The GSE25101 was downloaded from the Gene Expression Omnibus (GEO) database of the National Center of Biotechnology Information, and the DEGs were identified between the AS patients and the normal. The online database DAVID was utilized to complete the functional annotation and signaling pathway analysis, and the database STRING and Cytoscape software were applied to construct a protein-protein interaction (PPI) network, finally obtaining hub genes. Results: 187 DEGs were screened out, including 96 up-regulated genes and 91 down-regulated genes. GO enrichment and KEGG analysis demonstrated that the DEGs were mainly involved in biological processes and signaling pathways such as oxidative phosphorylation and metabolism. 5 key genes were screened out based on the PPI network analysis, and ATP5J (AUC=0.859), NDUFB3 (AUC=0.852), UQCRB (AUC=0.840), COX7A2 (AUC=0.820) and UQCRH (AUC=0.805) played a significant role in the diagnosis of spinal disease in peripheral blood samples which were recognized as the novel diagnostic biomarkers for AS. Conclusion: ATP5J, NDUFB3, UQCRB, COX7A2 and UQCRH may be new diagnostic markers related to AS in peripheral blood species, which provides a theoretical basis for further functional studies of the disease.
Keywords:Ankylosing spondylitis  GEO  Bioinformatics  Differential expression genes  Biomarkers
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