Identification of novel biomarkers involved in pulmonary arterial hypertension based on multiple-microarray analysis

Biosci Rep. 2020 Sep 30;40(9):BSR20202346. doi: 10.1042/BSR20202346.

Abstract

Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disorder. However, studies providing PAH-related gene expression profiles are scarce. To identify hub genes involved in PAH, we investigate two microarray data sets from gene expression omnibus (GEO). A total of 150 differentially expressed genes (DEGs) were identified by limma package. Enriched Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of DEGs mostly included mitotic nuclear division, ATPase activity, and Herpes simplex virus one infection. Ten hub genes from three significant modules were ascertained by Cytoscape (CytoHubba). Gene set enrichment analysis (GSEA) plots showed that transcription elongation factor complex was the most significantly enriched gene set positively correlated with the PAH group. At the same time, solute proton symporter activity was the most significantly enriched gene set positively correlated with the control group. Correlation analysis between hub genes suggested that SMC4, TOP2A, SMC2, KIF11, KIF23, ANLN, ARHGAP11A, SMC3, SMC6 and RAD50 may involve in the pathogenesis of PAH. Then, the miRNA-target genes regulation network was performed to unveil the underlying complex association among them. Finally, RNA extracted from monocrotaline (MCT)-induced Rat-PAH model lung artery tissues were to conduct quantitative real-time PCR (qRT-PCR) to validate these hub genes. In conclusion, our study offers new evidence for the underlying molecular mechanisms of PAH as well as attractive targets for diagnosis and treatment of PAH.

Keywords: Bioinformatics; Computational biology; Pulmonary Arterial Hypertension; Transcriptomics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biomarkers / analysis
  • Biomarkers / metabolism
  • Computational Biology
  • Datasets as Topic
  • Disease Models, Animal
  • Gene Expression Profiling
  • Gene Regulatory Networks*
  • Humans
  • MicroRNAs / analysis
  • MicroRNAs / metabolism
  • Microarray Analysis
  • Monocrotaline / toxicity
  • Pulmonary Arterial Hypertension / chemically induced
  • Pulmonary Arterial Hypertension / diagnosis
  • Pulmonary Arterial Hypertension / genetics*
  • Pulmonary Arterial Hypertension / pathology
  • Pulmonary Artery / pathology*
  • RNA, Messenger / analysis
  • RNA, Messenger / metabolism
  • Rats

Substances

  • Biomarkers
  • MicroRNAs
  • RNA, Messenger
  • Monocrotaline