Chen Min, Yan Jianying
Department of Obstetrics, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, China.
Ginekol Pol. 2024;95(8):627-635. doi: 10.5603/GP.a2023.0017. Epub 2023 Mar 17.
To utilize an integrative strategy to construct functional miRNA-mRNA regulatory networks by combining the reverse expression relationships between miRNAs and targets and computational predictions for gestational diabetes mellitus (GDM).
A total of three microarray or RNA-seq datasets (GSE98043, GSE19649 and GSE92772) of plasma samples comparing GDM pregnant women and healthy control pregnant women were downloaded from the GEO database. The differentially expressed genes (DEmRNAs) and the differentially expressed miRNAs (DEmiRNAs) were analyzed. The target genes of DEmiRNAs were identified using two independent and complementary types of information: computational target predictions and expression relationships. An interaction network was constructed to identify hub genes of GDM. Another dataset (GSE92772) was used to externally verify the predictive ability of the hub genes.
A total of 264 DEmiRNAs and 1217 DEmRNAs were identified with Hsa-miR-146a-3p ranked first of DEmiRNAs. Functions of GDM-related miRNAs were mainly enriched in the glypican pathway, proteoglycan syndecan-mediated signaling events, and syndecan-1-mediated signaling events. A total of 47 target genes, including TRAF6, were shared between the computational target predictions and DEmRNAs and were identified as target genes of hsa-miR-146a-3p. The interaction network analysis identified TRAF6, CASP8, PTPN6, and CHD3 as hub genes involved in the pathophysiological process of GDM. Next, independent external validation was performed using the GSE19649 dataset. The expression of TRAF6, CASP8 and CHD3 in eight pairs of GDM blood samples was confirmed to be higher than that in healthy pregnant women blood samples with a AUC of 0.813, 0.813, and 0.703, respectively.
Our preliminary analysis revealed that miR-146a-3p/TRAF6 might play a central role in the pathogenesis of GDM. Three hub genes, TRAF6, CASP8, and CHD3, were identified and independently externally validated as potential GDM noninvasive serum markers for future biomarkers research.
通过结合微小RNA(miRNA)与其靶标的反向表达关系以及对妊娠期糖尿病(GDM)的计算预测,运用综合策略构建功能性miRNA-信使核糖核酸(mRNA)调控网络。
从基因表达综合数据库(GEO数据库)下载了总共三个比较GDM孕妇和健康对照孕妇血浆样本的微阵列或RNA测序数据集(GSE98043、GSE19649和GSE92772)。分析差异表达基因(DEmRNAs)和差异表达miRNAs(DEmiRNAs)。利用两种独立且互补的信息类型鉴定DEmiRNAs的靶基因:计算靶标预测和表达关系。构建相互作用网络以鉴定GDM的枢纽基因。使用另一个数据集(GSE92772)对外验证枢纽基因的预测能力。
共鉴定出264个DEmiRNAs和1217个DEmRNAs,其中Hsa-miR-146a-3p在DEmiRNAs中排名第一。与GDM相关的miRNAs功能主要富集于硫酸乙酰肝素蛋白聚糖途径、蛋白聚糖syndecan介导的信号事件以及syndecan-1介导的信号事件。在计算靶标预测和DEmRNAs之间共有47个靶基因(包括TRAF6)被共享,并被鉴定为hsa-miR-146a-3p的靶基因。相互作用网络分析确定TRAF6、CASP8、PTPN6和CHD3为参与GDM病理生理过程的枢纽基因。接下来,使用GSE19649数据集进行独立外部验证。证实八对GDM血样中TRAF6、CASP8和CHD3的表达高于健康孕妇血样,其受试者工作特征曲线下面积(AUC)分别为0.813、0.813和0.703。
我们的初步分析表明,miR-146a-3p/TRAF6可能在GDM发病机制中起核心作用。鉴定出三个枢纽基因TRAF6、CASP8和CHD3,并对其进行独立外部验证,作为未来生物标志物研究中潜在的GDM无创血清标志物。