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复发性流产差异表达基因的综合生物信息学分析。

Comprehensive bioinformation analysis of differentially expressed genes in recurrent pregnancy loss.

机构信息

School of Public Health, North China University of Science and Technology, Tangshan, P.R. China.

Department of Environmental and Chemical Engineering, Tangshan University, Tangshan, P.R. China.

出版信息

Hum Fertil (Camb). 2023 Dec;26(5):1015-1022. doi: 10.1080/14647273.2022.2045636. Epub 2022 Mar 21.

Abstract

Recurrent pregnancy loss (RPL) occurs frequently, and its causes are complex. The aetiology of nearly 50% of RPL cases is still unknown. This study aimed to ascertain differentially expressed genes (DEGs) and pathways by comprehensive bioinformatics analysis. We downloaded the gene expression microarray of GSE165004 from the Gene Expression Omnibus (GEO). Gene ontology (GO) analysis and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were performed on selected genes by using the R Programming Language. A protein-protein interaction (PPI) network was constructed with the Retrieval of Interacting Genes (STRING). Our analysis revealed that 1,869 genes were differentially expressed in RPL and control groups. GO analysis revealed that the interferon type 1 and the glycoprotein-related biological processes played irreplaceable roles, meanwhile KEGG enrichment analysis also revealed that the cAMP signalling pathway and the prolactin signalling pathway played important roles. In the following study, we found that there were many DEGs in the RPL group that were closely related to endometrial decidualization, such as IL17RD, IL16, SOX4, CREBBP, and POFUT1 as well as Notch1 and RBPJ in the Notch signalling pathway family were down-regulated in the RPL group. The results provided valuable information on the pathogenesis of RPL.

摘要

复发性流产(RPL)较为常见,病因复杂。约 50%的 RPL 病例的病因仍不清楚。本研究旨在通过综合生物信息学分析确定差异表达基因(DEGs)和途径。我们从基因表达综合数据库(GEO)中下载了 GSE165004 的基因表达微阵列。使用 R 编程语言对选定基因进行基因本体论(GO)分析和京都基因与基因组百科全书(KEGG)通路富集分析。使用检索互作基因(STRING)构建蛋白质-蛋白质相互作用(PPI)网络。我们的分析表明,RPL 和对照组之间有 1869 个基因差异表达。GO 分析表明,干扰素 1 型和糖蛋白相关的生物学过程发挥了不可替代的作用,同时 KEGG 富集分析也表明 cAMP 信号通路和催乳素信号通路发挥了重要作用。在接下来的研究中,我们发现 RPL 组中有许多 DEGs 与子宫内膜蜕膜化密切相关,如 IL17RD、IL16、SOX4、CREBBP 和 POFUT1,以及 Notch 信号通路家族中的 Notch1 和 RBPJ 在 RPL 组中下调。研究结果为 RPL 的发病机制提供了有价值的信息。

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