特发性肺纤维化中 ceRNA 调控网络的构建与生物信息学分析

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Biochemical Genetics Pub Date : 2024-06-13 DOI:10.1007/s10528-024-10853-y
Menglin Zhang, Xiao Wu, Honglan Zhu, Chenkun Fu, Wenting Yang, Xiaoting Jing, Wenqu Liu, Yiju Cheng
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引用次数: 0

摘要

特发性肺纤维化(IPF)是一种病因不明的慢性进行性肺纤维化。尽管研究仍在继续,但目前还没有治愈这种疾病的方法。最近的研究强调了竞争性内源性 RNA(ceRNA)调控网络在 IPF 发展过程中的重要性。因此,本研究调查了与 IPF 发病机制相关的 ceRNA 网络。我们从基因表达总库(GEO)数据库中获取了基因表达数据集(GSE32538、GSE32537、GSE47460和GSE24206),并使用生物信息学工具对其进行分析,以鉴定差异表达的信使RNA(DEmRNA)、microRNA(DEmiRNA)和长非编码RNA(DElncRNA)。对于 DEmRNA,我们进行了富集分析,构建了蛋白质-蛋白质相互作用网络,并确定了枢纽基因。此外,我们还利用各种数据库预测了差异表达的 mRNA 的靶基因及其相互作用的长非编码 RNA。随后,我们根据筛选结果,在lncACTdb数据库中筛选出了具有ceRNA调控关系的RNA分子。此外,我们还对 ceRNA 网络中的 miRNA 进行了疾病和功能富集分析以及通路预测。我们还通过定量实时逆转录酶聚合酶链反应验证了候选 DEmRNA 的表达水平,并分析了这些候选 DEmRNA 的表达与预测的支气管舒张前用力肺活量百分比[%predicted FVC (pre-bd)]之间的相关性。我们发现,三个 ceRNA 调控轴,特别是 KCNQ1OT1/XIST/NEAT1-miR-20a-5p-ITGB8、XIST-miR-146b-5p/miR-31-5p-MMP16 和 NEAT1-miR-31-5p-MMP16 有可能显著影响 IPF 的进展。对这一网络中潜在调控机制的进一步研究将加深我们对 IPF 发病机制的了解,并有助于确定诊断生物标志物和治疗靶点。
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Construction and Bioinformatics Analysis of ceRNA Regulatory Networks in Idiopathic Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive form of pulmonary fibrosis of unknown etiology. Despite ongoing research, there is currently no cure for this disease. Recent studies have highlighted the significance of competitive endogenous RNA (ceRNA) regulatory networks in IPF development. Therefore, this study investigated the ceRNA network associated with IPF pathogenesis. We obtained gene expression datasets (GSE32538, GSE32537, GSE47460, and GSE24206) from the Gene Expression Omnibus (GEO) database and analyzed them using bioinformatics tools to identify differentially expressed messenger RNAs (DEmRNAs), microRNAs (DEmiRNAs), and long non-coding RNAs (DElncRNA). For DEmRNAs, we conducted an enrichment analysis, constructed protein-protein interaction networks, and identified hub genes. Additionally, we predicted the target genes of differentially expressed mRNAs and their interacting long non-coding RNAs using various databases. Subsequently, we screened RNA molecules with ceRNA regulatory relations in the lncACTdb database based on the screening results. Furthermore, we performed disease and functional enrichment analyses and pathway prediction for miRNAs in the ceRNA network. We also validated the expression levels of candidate DEmRNAs through quantitative real-time reverse transcriptase polymerase chain reaction and analyzed the correlation between the expression of these candidate DEmRNAs and the percent predicted pre-bronchodilator forced vital capacity [%predicted FVC (pre-bd)]. We found that three ceRNA regulatory axes, specifically KCNQ1OT1/XIST/NEAT1-miR-20a-5p-ITGB8, XIST-miR-146b-5p/miR-31-5p- MMP16, and NEAT1-miR-31-5p-MMP16, have the potential to significantly affect IPF progression. Further examination of the underlying regulatory mechanisms within this network enhances our understanding of IPF pathogenesis and may aid in the identification of diagnostic biomarkers and therapeutic targets.

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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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