Identification of nitric oxide-related key genes in pulmonary hypertension via bioinformatics and in vitro validation for therapeutic target discovery.

Abstract

This study aims to uncover key genes and associated pathways related to nitric oxide (NO) in pulmonary hypertension (PH). By analyzing datasets GSE131793 and GSE703 from the Gene Expression Omnibus (GEO), differentially expressed genes (DEGs) associated with PH were identified. NO-related genes were selected from the GeneCards database and intersected with the DEGs. Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were conducted to evaluate pathway enrichment, and key genes were selected using the random forest and least absolute shrinkage and selection operator (LASSO) regression algorithms. Immune cell infiltration was analyzed using the CIBERSORT algorithm, and Gene Set Enrichment Analysis (GSEA) was performed to explore potential mechanisms. The transcriptional regulatory networks of key genes were constructed using Cytoscape software. The expression levels of the key genes were validated in peripheral blood samples from PH patients using quantitative real-time PCR (RT-qPCR). A total of 97 DEGs were identified, of which 20 were NO-related genes. Three key genes, HBG2, PRKAB1, and THBD, were further selected. RT-qPCR results revealed significant upregulation of HBG2 and THBD, and downregulation of PRKAB1 in PH patients. CIBERSORT analysis indicated the significant role of immune cells in the pathology of PH. GSEA and transcriptional network analyses further suggested that key genes may participate in the pathogenesis of PH through immune regulation and metabolic pathways. Through bioinformatics analysis and clinical sample validation, this study systematically elucidates the potential mechanisms of NO-related key genes in PH, providing new molecular targets for early diagnosis and targeted therapy of PH.