Identification of Key Biomarkers in Pulmonary Arterial Hypertension Based on Weighted Gene Co-expression Network Analysis

Pulmonary arterial hypertension (PAH) is a complex and devastating disease that the underlying cellular and molecular mechanisms are largely remains unknown. This study aimed to elucidate the key hub genes and pathways in PAH by bioinformatics analysis. In the current study, we performed WGCNA analysis to systematically identify the hub genes for PAH using transcriptome microarray data. From the Gene Expression Omnibus (GEO) database, one microarray dataset (GSE113439) was downloaded for this study. There were 26 samples in this data set, including 15 PHA samples and 11 normal controls. Based on weighted correlation network analysis, 11 modules were identified and the MEgreenyellow module showed a significantly positive correlation with PAH (r = 0.93, P = 1e−06). The genes in greenyellow module were mainly significantly enriched in mitophagy related pathways by KEGG analyses. Combined with the protein–protein interaction (PPI) and co-expression networks, ten hub genes were identified as candidate biomarkers for PAH in the greenyellow module, including CTNNB1, NIPBL, ROCK2, ROCK1, SCAF11, JAK1, BIRC6, KIF5B, PPP1R12A and XRN1. These hub genes might be potential targets for clinical therapy against PAH. The molecular mechanisms involved in these genes that affected the prognosis of PAH should be further validated through biological and basic studies.