Differentially expressed genes analysis in expression profile data of pulmonary fibrosis with pulmonary hypertension

Abstract

Objective: To analyze the differential gene expression of patients with idiopathic pulmonary fibrosis and pulmonary hypertension (IPF-PH). Methods: The expression profile data of GSE15197 was downloaded from the Gene Expression Omnibus (GEO) database. Bonferroni algorithm was used to identify the differentially expressed genes of pulmonary tissues from IPF-PH, idiopathic pulmonary arterial hypertension (IPAH) and Normal groups. Principal component analysis was used to extract the principal components of three types of samples and differentially expressed genes were obtained. Gene annotation and gene association analysis were used to analyze gene function and related signaling pathways. Results: Gene expression profiles of pulmonary tissues from IPF-PH, IPAH and Normal groups were compared and analyzed, and 160 differentially expressed genes were found (P<0.05). Nine principal component were found with the cumulative contribution rate of >0.85, and there were 44 significant differences genes with the loading coefficient >80% in principal component one, which was mainly related to the expression of cilium, gamma-glutamyltransferase, and phospholipase. The signaling pathway of differential expression genes were mainly involved in the biosynthesis of leukotriene biosynthetic process and gamma-glutamyltransferase activity. Conclusion: The differential gene expression and their functional annotation can provide important clues for the pathogenic genes of IPF-PH, and may provide a theoretical basis for exploring potential biomarkers and drug targets.