Abstract
Objectives: Idiopathic pulmonary arterial hypertension (IPAH) is a rare but severe lung disorder, which may lead to heart failure and early mortality. However, little is known about the etiology of IPAH. Thus, the present study aimed to establish the differentially expressed genes (DEGs) between IPAH and normal tissues, which may serve as potential prognostic markers in IPAH. Furthermore, we utilized a versatile computational method, CIBERSORT to identify immune cell infiltration characteristics in IPAH.Materials and Methods: The GSE117261 and GSE48149 datasets were obtained from the Gene Expression Omnibus database. The GSE117261 dataset was adopted to screen DEGs between IPAH and the control groups with the criterion of |log2 fold change| ≥ 1, adjusted P < 0.05, and to further explore their potential biological functions via Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes Pathway analysis, and Gene Set Enrichment Analysis. Moreover, the support vector machine (SVM)-recursive feature elimination and the least absolute shrinkage and selection operator regression model were performed jointly to identify the best potential biomarkers. Then we built a regression model based on these selected variables. The GSE48149 dataset was used as a validation cohort to appraise the diagnostic efficacy of the SVM classifier by receiver operating characteristic (ROC) analysis. Finally, immune infiltration was explored by CIBERSORT in IPAH. We further analyzed the correlation between potential biomarkers and immune cells.Results: In total, 75 DEGs were identified; 40 were downregulated, and 35 genes were upregulated. Functional enrichment analysis found a significantly enrichment in heme binding, inflammation, chemokines, cytokine activity, and abnormal glycometabolism. HBB, RNASE2, S100A9, and IL1R2 were identified as the best potential biomarkers with an area under the ROC curve (AUC) of 1 (95%CI = 0.937–1.000, specificity = 100%, sensitivity = 100%) in the discovery cohort and 1(95%CI = 0.805–1.000, specificity = 100%, sensitivity = 100%) in the validation cohort. Moreover, immune infiltration analysis by CIBERSORT showed a higher level of CD8+ T cells, resting memory CD4+ T cells, gamma delta T cells, M1 macrophages, resting mast cells, as well as a lower level of naïve CD4+ T cells, monocytes, M0 macrophages, activated mast cells, and neutrophils in IPAH compared with the control group. In addition, HBB, RNASE2, S100A9, and IL1R2 were correlated with immune cells.Conclusion: HBB, RNASE2, S100A9, and IL1R2 were identified as potential biomarkers to discriminate IPAH from the control. There was an obvious difference in immune infiltration between patient with IPAH and normal groups.
Highlights
Pulmonary arterial hypertension (PAH) is a progressive cardiopulmonary disease in which increased pulmonary arterial pressure leads to right ventricle failure and premature death
We found an obvious difference in immune infiltration between patients with idiopathic PAH (IPAH) and controls by CIBERSORT algorithm
Previous studies have investigated the role of inflammation, chemokine, and cytokines in PAH, but as far as we known, this is the first time potential biomarkers related to immune infiltration in IPAH have been identified
Summary
Pulmonary arterial hypertension (PAH) is a progressive cardiopulmonary disease in which increased pulmonary arterial pressure leads to right ventricle failure and premature death. There are several categories of reasons for patients to develop PAH, but in the absence of any known triggering factor, they are labeled as idiopathic PAH (IPAH) [1] It is progressive and affects the precapillary pulmonary vasculature. IPAH may lead to increased PVR, progressive right ventricular dysfunction, right heart failure, and early mortality. Despite extensive researches and improved diagnosis as well as a broad range of increasing biomarkers, there is currently no specific marker for IPAH. This disorder is still associated with a poor prognosis, especially when complicated with arrhythmia, left ventricular dysfunction, or heart failure. Prompt and specific diagnoses are needed to reduce mortality rates
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