The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis

Eur J Med Res. 2022 Oct 27;27(1):212. doi: 10.1186/s40001-022-00840-7.

Abstract

Aim: The study aimed to identify the underlying differentially expressed genes (DEGs) and mechanism of unstable atherosclerotic plaque using bioinformatics methods.

Methods: GSE120521, which includes four unstable samples and four stable atherosclerotic samples, was downloaded from the GEO database. DEGs were identified using LIMMA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed using the Database for metascape Visualization online tool. Based on the STRING database, protein-protein interactions (PPIs) network among DEGs were constructed. Regulatory networks were visualized using Cytoscape. We use the xCell to analyze the different immune cell subtypes.

Results: A total of 1626 DEGs (1034 up-regulated and 592 down-regulated DEGs) were identified between unstable and stable samples. I pulled 62 transcription factors (34 up-regulated TFs and 28 down-regulated TFs) from the Trust database. The up-regulated TFs were mainly enrichment in positive regulation of myeloid leukocyte differentiation, and the down-regulated TFs were mainly enrichment in connective tissue development. In the PPI network, RB1, CEBPA, PPARG, BATF was the most significantly up-regulated gene in ruptured atherosclerotic samples. The immune cell composition enriched in CD cells and macrophages in the unstable carotid plaque.

Conclusions: Upregulated RB1, CEBPA, PPARG, BATF and down-regulated SRF, MYOCD, HEY2, GATA6 might perform critical promotional roles in atherosclerotic plaque rupture, furthermore, number and polarization of macrophages may play an important role in vulnerable plaques.

Keywords: Atherosclerosis; Differentially expressed genes; Macrophages; Transcription factors; Unstable atherosclerotic plaque.

MeSH terms

  • Atherosclerosis* / genetics
  • Biomarkers
  • Computational Biology / methods
  • Gene Expression Profiling / methods
  • Gene Regulatory Networks / genetics
  • Humans
  • PPAR gamma / genetics
  • Plaque, Atherosclerotic* / genetics
  • Protein Interaction Maps / genetics
  • Transcriptome

Substances

  • PPAR gamma
  • Biomarkers