Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension.

Despite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH. In this research, we aimed to examine the mechanisms underlying PAH and identify key genes with potential usefulness as clinical biomarkers of PAH and thereby establish therapeutic targets for PAH. The datasets GSE117261, GSE113439, and GSE53408 were downloaded from the Gene Expression Omnibus (GEOs) database. We used weighted gene coexpression network analysis (WGCNA) to identify networks and the most relevant modules in PAH. Functional enrichment analysis was performed for the selected clinically relevant modules. The least absolute shrinkage and selection operator (LASSO) was applied to identify key genes in lung samples from patients with PAH. The genes were validated in a monocrotaline-induced PAH rat model. Three clinically relevant modules were identified through average linkage hierarchical clustering. The genes in the clinically relevant modules were related to endothelial cell differentiation, inflammation, and autoimmunity. Seven genes were screened as key genes significantly associated with PAH. Interferon-induced protein 44-like (IFI44L) and signal transducer and activator of transcription 1 (STAT1) were expressed at higher levels in the lung tissues of the PAH rat model than in those of the controls. Our findings reveal the novel pathological mechanisms underlying PAH and indicate that STAT1 and IFI44L may represent potential therapeutic targets in PAH.