Essential Genes and MiRNA-mRNA Network Contributing to the Pathogenesis of Idiopathic Pulmonary Arterial Hypertension

Abstract

Background: Idiopathic pulmonary arterial hypertension (IPAH) is a life-threatening disease. Owing to its high fatality rate and narrow therapeutic options, identification of the pathogenic mechanisms of IPAH is becoming increasingly important. Methods: In our research, we utilized the robust rank aggregation (RRA) method to integrate four eligible pulmonary arterial hypertension (PAH) microarray datasets and identified the significant differentially expressed genes (DEGs) between IPAH and normal samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed to analyze their functions. The interaction network of protein-protein interaction (PPI) was constructed to explore the correlation between these DEGs. The functional modules and hub genes were further identified by the weighted gene coexpression network analysis (WGCNA). Moreover, a miRNA microarray dataset was involved and analyzed to filter differentially expressed miRNAs (DE-miRNAs). Potential target genes of screened DE-miRNAs were predicted and merged with DEGs to explore a miRNA-mRNA network in IPAH. Some hub genes were selected and validated by RT-PCR in lung tissues from the PAH animal model. Results: A total of 260 DEGs, consisting of 183 upregulated and 77 downregulated significant DEGs, were identified, and some of those genes were novel. Their molecular roles in the etiology of IPAH remained vague. The most crucial functional module involved in IPAH is mainly enriched in biological processes, including leukocyte migration, cell chemotaxis, and myeloid leukocyte migration. Construction and analysis of the PPI network showed that CXCL10, CXCL9, CCR1, CX3CR1, CX3CL1, CXCR2, CXCR1, PF4, CCL4L1, and ADORA3 were recognized as top 10 hub genes with high connectivity degrees. WGCNA further identified five main functional modules involved in the pathogenesis of IPAH. Twelve upregulated DE-miRNAs and nine downregulated DE-miRNAs were identified. Among them, four downregulated DEGs and eight upregulated DEGs were supposed to be negatively regulated by three upregulated DE-miRNAs and three downregulated DE-miRNAs, respectively. Conclusions: This study identifies some key and functional coexpression modules involved in IPAH, as well as a potential IPAH-related miRNA-mRNA regulated network. It provides deepening insights into the molecular mechanisms and provides vital clues in seeking novel therapeutic targets for IPAH.

Keywords: GEO; hub genes; idiopathic pulmonary arterial hypertension; lung tissues; microRNA.

Figure 1

Flowchart of the bioinformatics analysis. MiRNA, microRNA; RRA, robust rank aggregation; IPAH, idiopathic pulmonary arterial hypertension; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; WGCNA, the weighted gene coexpression network analysis.

Figure 2

Robust DEGs identified by RRA analysis. Heatmap of the four datasets showing the top 30 upregulated and 30 downregulated DEGs. The horizontal axis indicates the gene name, and the vertical axis represents a dataset. Red indicates that the gene is upregulated in the IPAH patients compared with the controls, and the green represents downregulation. The number in a cell indicates the logFC of each gene in a dataset. DEG, differentially expressed gene; RRA, robust rank aggregation.

Figure 3

GO and KEGG pathway enrichment of the robust DEGs in IPAH. (A) Top 10 biological processes. (B) Top 10 molecular functions. (C) Top 10 cellular components. (D) Top 10 of the KEGG pathway. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEG, differentially expressed gene; IPAH, idiopathic pulmonary arterial hypertension.

Figure 4

The PPI network of the robust DEGs. (A) PPI network of upregulated and downregulated significant genes. (B–D) The most significant modules identified through MCODE in Cytoscape software. PPI, protein–protein interaction; DEG, differentially expressed gene.

Figure 5

Identification of crucial modules associated with IPAH by WGCNA. (A) Clustering dendrograms of genes from bath-normalized four datasets. In the column of clinical status, red indicates IPAH, and white means the control. (B) The scale-free fit index (left) and the mean connectivity (right) for various soft-thresholding powers. (C) Clustering of module eigengenes. The cut height (red line) was 0.25. (D) Dendrogram of the DEGs clustered based on a dissimilarity measure (1—TOM). (E) Heatmap showing the relationship between module eigengenes and clinical status. The numbers in each cell means the correlation coefficient and p-value. (F) Cluster analysis and heatmap of the genes in different modules. Red means a positive correlation, and blue indicates a negative correlation. (G) Scatter plot of module eigengenes in the midnight-blue module. (H) Venn diagram. The overlap of top 20 genes in the midnight-blue module of WGCNA and top 20 hub genes of PPI analysis. IPAH, idiopathic pulmonary arterial hypertension; WGCNA, weighted gene coexpression network analysis; DEG, differentially expressed gene; TOM, topological overlap matrix; PPI, protein–protein interaction.

Figure 6

Potential target genes of DE-miRNAs predicted by miRNet database. (A) The network of downregulated DE-miRNAs and predicted target genes. (B) Predicted target gene count for each downregulated DE-miRNAs. (C) The Venn gram of predicted upregulated target genes and upregulated DEGs from RRA analysis. (D) The network of upregulated DE-miRNAs and predicted target genes. (E) Predicted target gene count for each upregulated DE-miRNAs. (F) The Venn gram of predicted downregulated target genes and downregulated DEGs from RRA analysis. DE-miRNAs, differentially expressed miRNAs; DEG, differentially expressed gene; RRA, robust rank aggregation.

Figure 7

An interactive network of overlapped genes and the upstream miRNAs.

Figure 8

PAH mice model. (A) Representative tracing of RVSP in mice after CH+SU or Nor treatment (left) and the mean values of RVSP in the two groups. (B) Fulton index (RV/LV+S) in mice after CH+SU or Nor treatment. (C) Representative Masson stain images of the hearts from CH+SU or Nor mice. (D) Representative α-SMA immunostaining images of lung sections from CH+SU or Nor mice. Bar, 25 μm. (E) Representative images of H&E staining of lung sections from CH+SU or Nor mice. Bar, 25 μm. (F) The ratio of pulmonary arterial medial thickness to total vessel size for the CH+SU or Nor mice. n = 6 in each group. **p < 0.01, ***p < 0.001 vs. Nor group. All graphs are shown as mean ± SEM. PAH, pulmonary arterial hypertension; RVSP, right ventricular systolic pressure.

Figure 9

Validation of seven differently expressed key genes through RT-PCR in the lungs from CH+SU or Nor mice. Expression of PKP2 (A), ADORA3 (B), PROK2 (C), IL-13 (D), CXCL10 (E), SFN (F), and SFRP2 (G) in CH+SU mice compared with Nor controls. PKP2, plakophilin-2; ADORA3, adenosine A3 receptor; PROK2, prokineticin 2; IL-13, interleukin-13; SFN, stratifin; SFRP2, secreted frizzled-related proteins. n = 6 in each group. *p < 0.05, **p < 0.01 vs. Nor group. All graphs are shown as mean ± SEM.