Identification and functional characterization of novel inflammation-associated genes differentially expressed by pulmonary arterial hypertension patients:Method (Preprint)

Abstract

BACKGROUND Pulmonary arterial hypertension (PAH) is a severe disease with high mortality. The characteristics of PAH pathology include pulmonary arterial vasoconstriction and vascular remodeling, subsequently leading to right ventricular dysfunction and right heart failure. Recent advancement in clinical and experimental studies have documented that multiple types of immune cells are recruited to and accumulated in the PAH lungs, and high levels of inflammatory mediators have been observed in both vascular remodeling environment and circulation of PAH patients, demonstrating that inflammation plays an important role in vascular remodeling in PAH. How the immune cells crosstalk with other cells involved in the process of vascular remodeling is unclear. METHODS Single cell sequencing and bulk transcriptome database associated with PAH were obtained from Gene Expression Omnibus (GEO). GSE154959 was used for single cell sequencing analysis, data set of GPL6244 was used for target cell annotation. For model construction and Hub gene identification, PAH patient databese GSE117261 was used as the training set, and GSE113439 as the verification set. STRING was used for protein-protein interaction analysis, and CIBERSORT algorism was used for immune cell and inflammatory mediator analysis. The hub genes identified were further characterized by gene set enrichment analysis (GSEA) to illustrate their signal pathways, and by Cistrome DB for their transcription factor network. The receiver operating characteristic (ROC) curves were analyzed for evaluating and validating the diagnostic values of the hub genes. RESULTS Four Hub genes differentially expressed by PAH immune cells were identified. The correlation of these genes with immune cell infiltration and inflammatory mediator secretion in PAH were established. The diagnostic value of these genes was evaluated and validated with PAH patient data, and the signaling pathways of the hub genes potentially associated with inflammation of the pathology process of PAH were defined. CONCLUSIONS In this study, we have identified four Hub genes associated with PAH through machine learning algorisms coupled with bioinformatics methods. These genes were differentially expressed by immune cells of PAH lungs, and highly correlated with immune cell infiltration and inflammatory mediator secretion. The genes were enriched in multiple signal pathways characteristic of inflammation and fibrosis and have diagnostic values of high confidence as validated using PAH patient data from GSE113439 database. CLINICALTRIAL None