Identification of genes and miRNA associated with idiopathic recurrent pregnancy loss: an exploratory data mining study

Abstract

Abstract Background: Recurrent pregnancy loss (RPL) is a significant adverse pregnancy complication, with an incompletely understood pathology. While many entities were proposed to elucidate the pathogenic basis of RPL, only few were significant enough to warrant investigation in all affected couples.. The aim of this study was to provide novel insights into the biological characteristics and related pathways of differentially expressed miRNA (DEMs) and genes (DEGs), in RPL, and construct a molecular miRNAs–mRNAs network. Methods: miRNAs and gene expression data were collected, and a number of DEMs and (DEGs) were obtained, and regulatory co-expression network were constructed. Function and enrichment analyses of DEMs were conducted using DIANA-miRPath. DEGs were screened, and were used in generation of protein-protein interaction (PPI) network, using STRING online database. Modularity analysis, and pathway identification operations were used in identifying graph clusters and associated pathways. DEGs were also used for further gene ontology (GO) analysis, followed by analysis of KEGG pathway. Results: A total of 34 DEMs were identified, and were found to be highly enriched in TGF-β signaling pathway, Fatty acid metabolism and TNF signaling pathway. Hub miRNAs were selected and were found to be involved in several functional pathways including progesterone-mediated oocyte maturation and Thyroid hormone signaling pathway. Five dysregulated feedback loops involving miRNA and TFs were identified and characterized. Most notably, PPI network analysis identified hub-bottleneck protein panel. These appear to offer potential candidate biomarker pattern for RPL diagnosis and treatment. Conclusions: The present study provides novel insights into the molecular mechanisms underlying RPL.

Keywords: Bioinformatics analysis, Gene expression, microRNA, Recurrent pregnancy loss