Identifying miRNA regulatory mechanisms in preeclampsia by systems biology approaches

ABSTRACT

Background: Preeclampsia (PE) is the major cause of maternal and fetal morbidity and mortality, affecting 3–8% of all pregnancies around the globe. miRNAs are small, noncoding RNA molecules, which negatively regulate gene expression. Abnormally expressed miRNAs contribute to pregnancy complications such as PE. The aim of our study was to find possible regulatory mechanisms by system biology approaches, which are connected to the pathogenesis of PE. Methods: We integrated publicly available miRNA and gene expression profiles and created a network from the significant miRNA–mRNA pairs with the help of MAGIA and Cytoscape softwares. Two subnetworks were expanded by adding protein–protein interactions. Differentially expressed miRNAs were identified for the evaluation of their regulatory effect. We analyzed the miRNAs and their targets using different bioinformatics tools and through literature research. Results: Altogether, 52,603 miRNA–mRNA interactions were generated by the MAGIA web tool. The top 250 interactions were visualized and pairs with q < 0.0001 were analyzed, which included 85 nodes and 80 edges signalizing the connections between 52 regulated genes and 33 miRNAs. A total of 11 of the regulated genes are PE related and 9 of them were targeted by multiple miRNAs. A total of 8 miRNAs were associated with PE before, and 13 miRNAs regulated more than 1 mRNA. Hsa-mir-210 was the highest degree node in the network and its role in PE is well established. Conclusions: We identified several miRNA–mRNA regulatory mechanisms which may contribute to the pathogenesis of PE. Further investigations are needed to validate these miRNA–mRNA interactions and to enlighten the possibilities of developing potential therapeutic targets.

KEYWORDS:

• Preeclampsia
• placenta
• miRNA
• systems biology
• network analysis

Funding

The study was supported by The Hungarian Scientific Research Fund (OTKA K113023).

Additional information

Funding

The study was supported by The Hungarian Scientific Research Fund (OTKA K113023).