Pulmonary hypertension (PH) is a cardiopulmonary vascular disease that acutely endangers human health and can be fatal. It progresses rapidly and has a high mortality rate. Its pathophysiology is complicated and still not completely elucidated; therefore, achieving treatment breakthroughs are difficult. In this study, data from 58 normal controls and 135 patients with PH were extracted from the GSE24988, GSE113439, and GSE117261 datasets in the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs). In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Weighted gene co-expression network analysis (WGCNA) was used to identify the key modules and hub genes associated with PH. Eight PH-associated hub genes were identified. Furthermore, correlation analysis between immune cell infiltration and hub genes was performed, and the receiver operating characteristic (ROC) curves showed that TARDBP had the best diagnostic efficacy. Moreover, a rat hypoxic pulmonary hypertension (HPH) model was generated, and the expression of hub genes in the lungs and pulmonary arteries of HPH rats was verified using western blotting assays. Our results showed that mTOR, PSMD2, RBM8A, SMARCA4, TARDBP, and UBXN7 were highly expressed in the lungs. In addition, EFTUD2, mTOR, RBM8A, SMARCA4, TARDBP, and UBXN7 were significantly upregulated, whereas DDB1 was significantly downregulated in the pulmonary arteries of HPH rats compared with those of controls. In conclusion, we identified PH hub genes with diagnostic and predictive value by performing WGCNA on data from the GEO database. Furthermore, we provided novel insights of PH that might be utilized to evaluate potential biomarker genes and therapeutic targets.
Keywords: Pulmonary hypertension; hub genes; integrated bioinformatics analysis; weighted gene co-expression network analysis.