Network construction revealed that gestational diabetes mellitus may lead to congenital heart disease via potential lncRNAs-miRNAs regulating PPARγ

Abstract

Backgroundcongenital heart disease (CHD) is the most common birth defect. Gestational diabetes mellitus (GDM) induces a pro-inflammatory environment in the uterus which makes it difficult for the placenta, fetus, and embryo to develop properly. Despite the progress in underlying physiological knowledge, the knowledge of molecular mechanisms of potential connection of metabolic conditions to CHD is limited. This study aimed to mine potential regulatory missing links between GDM and CHD. MethodsWe constructed a network based on 914 differentially expressed mRNAs obtained from public GEO datasets analysis of cardiac differentiation and their regulatory miRNAs, predicted via complementarity algorithms and lncRNAs acquired from disease-associated databases. Furthermore, we compared the revealed gene set with reported RNA-seq results regarding Heart failure and Diabetes. Also, protein-protein interactions, particularly with PPARγ, were obtained from String database and visualized in Cytoscape v3.6.1. We finally mined the literature according to the applications of the revealed data. ResultsThe final resulted ncRNAs network consisted of 55 mRNAs, 13 miRNAs, and 7 lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed two conserved miRNAs in this network comprising miR-27a-3p and miR-130b-3p, primarily enriched in insulin resistance, AGE-RAGE signaling, and adrenergic signaling pathways. In addition, the screened key lncRNAs Jpx, Meg3, Xist, H19, and Mir17hg were potential regulators of diabetes-associated genes involved in Glycolysis/Gluconeogenesis and insulin signaling pathways. Retrospective literature mining showed the potential of AGE-RAGE manipulation in the nutrigenomics area according to PPARγ application. Besides, RNA-seq reports confirmed that some of our identified genes and mechanisms were involved in Heart failure and Diabetes biomarkers. ConclusionOur findings are some of the first to show a potential axis through which GDM could lead to CHD via metabolism-associated noncoding networks. PPARγ may mediate the effects of this noncoding network on cardiac differentiation and shed light on the road of nutrigenomics consultations for GDM patients.