Weighted gene co‑expression network analysis identifies key genes from extracellular vesicles as potential prognostic biomarkers for congenital pulmonary stenosis

Pulmonary stenosis (PS) is a congenital heart disease characterized by a dynamic or fixed anatomic obstruction of blood flow from the right ventricle to the pulmonary arterial vasculature. In the present study, extracellular vesicle long RNAs (EVLRs) from pregnant females who had healthy infants or PS infants were analyzed by RNA sequencing, and their diagnostic potential for PS during pregnancy was evaluated. A method for the selection of genes that could be considered as informative for the prediction PS based on extracellular vesicles (EVs) from pregnant females using long‑read RNA sequencing was developed. Blood samples were collected from females carrying fetuses with PS and females carrying unaffected fetuses (n=6 in each group). Physical characterization of EVs was performed using nanoparticle tracking analysis, transmission electron microscopy and western blotting. EVLRs from plasma were profiled by RNA sequencing and mRNA co‑expression modules were constructed by weighted gene co‑expression network analysis (WGCNA). Gene Ontology (GO) enrichment analysis was used to predict the function of the genes in each module. Hub genes were filtered out based on WGCNA and visualized using Cytoscape. EVLRs consisted of mRNAs, microRNAs and long non‑coding RNA. Overall, 26 modules were identified containing 16,394 genes. All modules were independent of each other. One particular module, referred to as the blue module, was markedly different between the two groups. A total of 735 hub genes in the blue module were identified, of which 33 were visualized, demonstrating the connection between these hub genes. GO enrichment analysis demonstrated that the analyzed hub genes were enriched in 'glucose transport', 'ATP‑dependent chromatin remodeling', 'histone deacetylation', 'histone H3‑K4 methylation', 'DNA methylation', 'apoptotic signaling pathway' and 'glucocorticoid receptor signaling pathway'. The hub genes identified in this module may provide a genetic framework for prenatal PS diagnosis. Furthermore, functional analysis of these associated genes may provide a theoretical basis for further research on PS pathogenesis.