Weighted gene co-expression network analysis reveals the hub genes associated with pulmonary hypertension

Abstract

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.

Network pharmacology and molecular docking: combined computational approaches to explore the antihypertensive potential of Fabaceae species

“…GO analysis recognized 386 biological processes (BP) (Fig. 5 A), which include regulation of transport system, positive regulation of cell communication, positive regulation of signaling pathways, regulation of programmed cell death and blood circulation (Mabhida et al 2021 ; Wei et al 2022 ; Wang et al 2023 ); 56 cellular components (CC) (Fig. 5 B), which include integral component of plasma membrane, neuron projection, axon, cellular surface, secretory vesicle, synapse, membrane raft, perinuclear region of cytoplasm, dendrite and synapse (Ali et al 2022 ; He et al 2023 ; Wang et al 2022a , b , c ); and 110 molecular functions (MF) (Fig.…”

CENPA and BRCA1 are potential biomarkers associated with immune infiltration in heart failure and pan-cancer

“…CALU , PALLD , FOS , DUSP1 have been identified as potential biomarkers of immune cell infiltration in HF [ 26 , 27 ]. Disorders of the immune system and abnormal activation of immune signaling pathway could cause the co-occurrence of HF and lung cancer [ 28 ]. Although the augmented immune response will lead to immune-related HF [ 29 ], transient chimeric antigen receptor (CAR) T cells in vivo reduced myocardial fibrosis and restored cardiac function after injury [ 30 ].…”

Mitochondrial DNA Variations Modulate Alveolar Epithelial Mitochondrial Function and Oxidative Stress in Newborn Mice Exposed to Hyperoxia

“…While hyperoxia-induced changes in lung transcriptome largely produced similar effects on KEGG pathways in C57WT vs. C57MNX and in C3HMNX vs. C3HWT mice (such as downregulation of the Autophagy pathway), we also noted differences such as inhibition of the Mitophagy pathway in C57WT mice but not in C57MNX mice (primarily related to PINK1 inhibition), as well as of inhibition of pathways related to pulmonary vascular remodeling (Nucleocytoplasmic transport) and protein synthesis (Aminoacyl-tRNA synthesis) in C3HMNX but not C3HWT mice lungs. These observations indicate that hyperoxia-induced changes in the lung transcriptome such as upregulation of inflammatory pathways and downregulation of protective/repair mechanisms such as autophagy may vary with differences in mtDNA in newborn mice (Tables 1-4, Figure 7) [31].…”