Revealing the pathogenic changes of PAH based on multiomics characteristics

Abstract

Background: Pulmonary artery hypertension (PAH), which is characterized by an increase in pulmonary circulation blood pressure, is a fatal disease, and its pathogenesis remains unclear. Methods: In this study, RNA sequencing (RNA-seq), tandem mass tags (TMT) and reduced representation bisulfite sequencing (RRBS) were performed to detect the levels of mRNA, protein, and DNA methylation in pulmonary arteries (PAs), respectively. To screen the possible pathways and proteins related to PAH, pathway enrichment analysis and protein-protein interaction (PPI) network analysis were performed. For selected genes, differential expression levels were confirmed at both the transcriptional and translational levels by real-time PCR and Western blot analyses, respectively. Results: A total of 362 differentially expressed genes (|Fold-change| > 1.5 and p < 0.05), 811 differentially expressed proteins (|Fold-change| > 1.2 and p < 0.05) and 76,562 differentially methylated regions (1000 bp slide windows, 500 bp overlap, p < 0.05, and |Fold-change| > 1.2) were identified when the PAH group (n = 15) was compared with the control group (n = 15). Through an integrated analysis of the characteristics of the three omic analyses, a multiomics table was constructed. Additionally, pathway enrichment analysis showed that the differentially expressed proteins were significantly enriched in five Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathways and ten Gene Ontology (GO) terms for the PAH group compared with the control group. Moreover, protein-protein interaction (PPI) networks were constructed to identify hub genes. Finally, according to the genes identified in the PPI and the protein expression fold-change, nine key genes and their associated proteins were verified by real-time PCR and Western blot analyses, including Col4a1, Itga5, Col2a1, Gstt1, Gstm3, Thbd, Mgst2, Kng1 and Fgg. Conclusions: This study conducted multiomic characteristic profiling to identify genes that contribute to the hypoxia-induced PAH model, identifying new avenues for basic PAH research.