子痫前期相关Siglec-6核心基因的预测及生物信息学分析

doi:10.6040/j.issn.1671-7554.0.2023.0799

摘要/Abstract

摘要： 目的探讨子痫前期高通量生物信息学分析与核心发病基因。方法选取基因表达综合数据库(Gene Expression Omnibus, GEO)2个关于子痫前期编码基因芯片数据进行生物信息学分析。通过R语言对2组数据进行均一化矫正,其后找到共同上调和下调表达的差异基因。对上调和下调表达的差异基因进行基因本体富集分析、京都百科全书信号通路富集分析、蛋白互作网络分析以及核心基因计算分析,找到与子痫前期最相关的发病基因及信号通路。随机选取河北大学附属医院产科5例子痫前期患者和正常产妇的胎盘组织进行实时定量聚合酶链反应对核心基因进行验证实验。结果融合子痫编码基因芯片GSE43942和GSE66273筛选出38个共同上调和20个共同下调表达的基因。全部数据经均一化处理后基因本体分析显示,生物功能富集于促卵泡激素分泌的正向调节,分子组成富集于细胞外区,细胞组分富集于激素活性,信号通路富集于肽激素代谢通路。蛋白质互作网络结果显示,全部差异基因间共58个点,30条线,cytohubba对全部点和线分析计算后锁定Siglec-6为子痫前期发病的核心基因。实时定量聚合酶链反应验证子痫前期孕妇胎盘组织内Siglec-6表达是正常孕妇体内的2.85倍,与生物信息学分析结果一致。结论 Siglec-6可作为子痫前期血清学诊断的潜在诊疗标志物,并有希望成为此疾病新的治疗靶点。

关键词: 子痫前期, 高通量生物信息学分析, 基因本体富集分析, 京都百科全书信号通路富集分析, 蛋白互作网络分析, 实时定量聚合酶链反应

Abstract: Objective To investigate the core pathogenesis genes of preeclampsia through high throughput bioinformatics analysis. Methods Two microarray datasets of preeclampsia coding genes from Gene Expression Omnibus(GEO)were selected for bioinformatics analysis. The datasets were homogenized and corrected with R language, and then the up-regulated and down-regulated differentially expressed genes were selected, which were then analyzed with gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes(KEGG)signal pathway enrichment, protein interaction network analysis and core gene calculation analysis to identify the most relevant pathogenesis genes and signal pathways of preeclampsia. Five placentas of preeclampsia patients and normal pregnant women were randomly selected for real-time quantitative PCR to verify the core genes. Results A total of 38 up-regulated and 20 down-regulated genes were screened from the microarray GSE43942 and GSE66273. After homogenization of all data, gene ontology analysis showed that biological function was enriched in positive regulation of follicle-stimulating hormone secretion, molecular composition was enriched in extracellular region, and cell component was enriched in hormone activity. KEGG signaling pathway was enriched in the Peptide hormone metabolism pathway. The protein interaction network showed that there were 58 points and 30 lines among all differentially expressed genes. The cytohubba analysis identified Siglec-6 as the core gene of preeclampsia. The real-time quantitative PCR showed that the expression of Siglec-6 in the placental tissue of preeclampsia pregnant women was 2.85 times that of normal pregnant women, which was consistent with the results of bioinformatics analysis. Conclusion Siglec-6 could be used as a potential diagnostic and therapeutic marker for preeclampsia.

Key words: Preeclampsia, High throughput bioinformatics analysis, Gene ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes signal pathway enrichment analysis, Protein interaction network analysis, Real-time quantitative PCR

中图分类号:

R714.244

秦金金,曹辰媛,邢杰杰,安燕,黄煜湘. 子痫前期相关Siglec-6核心基因的预测及生物信息学分析[J]. 山东大学学报 (医学版), 2024, 62(1): 31-37.

QIN Jinjin, CAO Chenyuan, XING Jiejie, AN Yan, HUANG Yuxiang. Predication and bioinformatics analysis of preeclampsia-related Siglec-6 core genes[J]. Journal of Shandong University (Health Sciences), 2024, 62(1): 31-37.

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