Abstract
Pulmonary arterial hypertension (PAH) is a life-threatening condition characterized by elevated pulmonary vascular resistance. Despite recent advances, early diagnosis remains challenging due to nonspecific symptoms. By utilizing RNA sequencing (RNA-seq) data from the GEO database, we conducted bioinformatics analyses to identify potential diagnostic biomarkers. Differentially expressed genes (DEGs) were screened in blood from PAH patients, followed by functional enrichment and protein-protein interaction (PPI) network analyses. Thirteen overlapping DEGs were identified, which were enriched in erythrocyte development, heme biosynthesis, and chloride transport. Five hub genes (SLC4A1, AHSP, ALAS2, FECH, and CA1), exhibited strong diagnostic potential, with an area under the curve (AUC) ≥ 0.7 in training datasets (GSE38267, GSE22356). External validation using datasets GSE33463 and GSE117261 confirmed their efficacy in blood samples, although AHSP showed reduced performance in lung tissue. Experimental validation in hypoxic human pulmonary artery smooth muscle cells (hPASMCs) supported the bioinformatics findings. These results underscore SLC4A1, AHSP, ALAS2, FECH, and CA1 as promising noninvasive diagnostic biomarkers for PAH, linking transcriptional dysregulation to clinical application.