Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus

IF 2.3 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY

Biochemistry and Biophysics Reports Pub Date : 2024-12-16 DOI:10.1016/j.bbrep.2024.101888

Yulan Lu , Chunhong Liu , Xiaoxia Pang , Xinghong Chen , Chunfang Wang , Huatuo Huang

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引用次数: 0

Abstract

Background

Intrauterine exposure to gestational diabetes mellitus (GDM) poses significant risks to fetal development and future metabolic health. Despite its clinical importance, the role of microRNAs (miRNAs) in fetoplacental vascular endothelial cell (VEC) programming in the context of GDM remains elusive. This study aims to identify signature miRNA genes involved in this process using bioinformatics analysis via multiple algorithms.

Methods

The dataset used in this study was acquired from Gene Expression Omnibus (GEO). Firstly, differentially expressed miRNA genes (DEMGs) were evaluated using limma package. Thereafter, an enrichment analysis of DEMGs was performed. Then, the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) were used as the other algorithms for screening candidate signature miRNA genes. Genes from the intersection of limma, LASSO, and SVM genes were used as the final signature miRNA genes. The receiver operator characteristic curve (ROC), the nomogram diagram, gene set enrichment analysis (GSEA), and signature miRNAs-target genes interaction network were implemented further to explore the features and functions of signature genes.

Results

A total of 32 DEMGs, with 21 upregulated and 11 downregulated miRNA genes, were obtained from limma analysis. LASSO and SVM analyses identified 15 and 12 candidate signature miRNA genes, respectively. After the intersection of genes from limma, LASSO, and SVM analyses, MIR34A and MIR186 were found as the final signature genes related to fetoplacental VEC programming. MIR34A and MIR186 were highly expressed and were associated with an increased risk of fetoplacental VEC programming in GDM mothers. The area under the curve (AUC) of ROC for MIR34A and MIR186 were 0.960 and 0.935, respectively. GSEA analysis revealed that these signature genes positively participate in cellular processes related to VEC migration, cell differentiation, angiogenesis, programmed cell death, and inflammatory response. Finally, miRNAs-target genes interaction network analysis provides the interaction of signature miRNAs and their critical target genes, which may help further studies for miR-34a and miR-186 in GDM.

Conclusions

MIR34A and MIR186 are novel signature miRNA genes related to fetoplacental VEC programming that may represent critical genes associated with placental function and fetal programming under GDM conditions.

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与妊娠糖尿病胎儿胎盘血管功能障碍相关的特征mirna的生物信息学鉴定。

背景：宫内暴露于妊娠期糖尿病（GDM）对胎儿发育和未来代谢健康有重大风险。尽管具有重要的临床意义，但在GDM的背景下，microRNAs （miRNAs）在胎胎盘血管内皮细胞（VEC）编程中的作用仍然难以捉摸。本研究旨在通过多种算法利用生物信息学分析鉴定参与该过程的特征miRNA基因。方法：本研究使用的数据集来自Gene Expression Omnibus （GEO）。首先，采用limma包对差异表达的miRNA基因（demg）进行检测。随后，对demg进行富集分析。然后，采用最小绝对收缩和选择算子（LASSO）和支持向量机（SVM）作为筛选候选签名miRNA基因的算法。limma基因、LASSO基因和SVM基因的交集基因被用作最终的签名miRNA基因。进一步通过接受者算子特征曲线（ROC）、诺图图、基因集富集分析（GSEA）、特征mirna -靶基因互作网络等方法探索特征基因的特征和功能。结果：limma分析共获得32个demg，其中miRNA基因上调21个，下调11个。LASSO和SVM分析分别鉴定出15个和12个候选签名miRNA基因。在limma、LASSO和SVM分析的基因交叉后，发现MIR34A和MIR186是与胎胎盘VEC编程相关的最终特征基因。在GDM母亲中，MIR34A和MIR186高表达并与胎胎盘VEC编程风险增加相关。MIR34A和MIR186的ROC曲线下面积（AUC）分别为0.960和0.935。GSEA分析显示，这些特征基因积极参与与VEC迁移、细胞分化、血管生成、程序性细胞死亡和炎症反应相关的细胞过程。最后，mirna -靶基因相互作用网络分析提供了特征mirna与其关键靶基因的相互作用，这可能有助于进一步研究miR-34a和miR-186在GDM中的作用。结论：MIR34A和MIR186是与胎胎盘VEC编程相关的新型标志性miRNA基因，可能是GDM条件下胎盘功能和胎儿编程相关的关键基因。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biochemistry and Biophysics Reports Biochemistry, Genetics and Molecular Biology-Biophysics

CiteScore

4.60

自引率

0.00%

发文量

191

审稿时长

59 days

期刊介绍： Open access, online only, peer-reviewed international journal in the Life Sciences, established in 2014 Biochemistry and Biophysics Reports (BB Reports) publishes original research in all aspects of Biochemistry, Biophysics and related areas like Molecular and Cell Biology. BB Reports welcomes solid though more preliminary, descriptive and small scale results if they have the potential to stimulate and/or contribute to future research, leading to new insights or hypothesis. Primary criteria for acceptance is that the work is original, scientifically and technically sound and provides valuable knowledge to life sciences research. We strongly believe all results deserve to be published and documented for the advancement of science. BB Reports specifically appreciates receiving reports on: Negative results, Replication studies, Reanalysis of previous datasets.