Abstract
Pulmonary arterial hypertension (PAH) comprises a heterogeneous group of diseases with diverse aetiologies. It is characterized by increased pulmonary arterial pressure and right ventricular (RV) failure without specific drugs for treatment. Emerging evidence suggests that inflammation and autoimmune disorders are common features across all PAH phenotypes. This provides a novel idea to explore the characteristics of immunological disorders in PAH and identify immune-related genes or biomarkers for specific anti-remodelling regimens. In this study, we integrated three gene expression profiles and performed Gene Ontology (GO) and KEGG pathway analysis. CIBERSORT was utilized to estimate the abundance of tissue-infiltrating immune cells in PAH. The PPI network and machine learning were constructed to identify immune-related hub genes and then evaluate the relationship between hub genes and differential immune cells using ImmucellAI. Additionally, we implemented molecular docking to screen potential small-molecule compounds based on the obtained genes. Our findings demonstrated the density and distribution of infiltrating CD4 T cells in PAH and identified four immune-related genes (ROCK2, ATHL1, HSP90AA1 and ACTR2) as potential targets. We also listed 20 promising molecules, including TDI01953, pemetrexed acid and radotinib, for PAH treatment. These results provide a promising avenue for further research into immunological disorders in PAH and potential novel therapeutic targets.