Research Paper Volume 13, Issue 2 pp 3080—3100
Constructing a ceRNA-immunoregulatory network associated with the development and prognosis of human atherosclerosis through weighted gene co-expression network analysis
- 1 Department of Cardiovascular Medicine, Second Xiangya Hospital, Central South University, Changsha, Hunan Province, China
Received: October 1, 2020 Accepted: November 13, 2020 Published: January 17, 2021https://doi.org/10.18632/aging.202486
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Copyright: © 2021 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
There is now overwhelming experimental and clinical evidence that atherosclerosis (AS) is a chronic inflammatory disease. The recent discovery of a new group of mediators known as competing endogenous RNA (ceRNA) offers a unique opportunity for investigating immunoregulation in AS. In this study, we used gene expression profiles from GEO database to construct a lncRNA-miRNA-mRNA ceRNA network during AS plaque development through weighted gene co-expression network analysis (WGCNA). GO annotation and pathway enrichment analysis suggested that the ceRNA network was mainly involved in the immune response. CIBERSORT and GSVA were used to calculate the immune cell infiltration score and identified macrophage as hub immunocyte in plaque development. A macrophage related ceRNA subnetwork was constructed through correlation analysis. Samples from Biobank of Karolinska Endarterectomy (BiKE) were used to identify prognostic factors from the subnetwork and yielded 7 hub factors that can predict ischemic events including macrophage GSVA score and expression value of AL138756.1, CTSB, MAFB, LYN, GRK3, and BID. A nomogram based on the key factors was established. GSEA identified that the PD1 signaling pathway was negatively associated with these prognostic factors which may explain the cardiovascular side effect of immune checkpoint therapy in anti-tumor treatment.
AS: atherosclerosis; MI: myocardial infarction; LDL: low-density lipoprotein; EC: endothelial cell; SMC: smooth muscle cells; lncRNA: long noncoding RNA; miRNA: microRNAs; mRNA: messenger RNA; ceRNA: competing endogenous RNA; WGCNA: weighted gene co-expression network analysis; MM: module membership; GS: gene significance; GO: gene ontology; BP: biological process; CC: cellular component; MF: molecular function; DEG: differentially expressed gene; ox-LDL: oxidized low-density lipoprotein; GEO: Gene Expression Omnibus; PBMC: peripheral blood mononuclear cells; BiKE: Biobank of Karolinska Endarterectomy; CAD: coronary arterial disease; MEs: module eigengenes; STRING: Search Tool for the Retrieval of Interacting Genes; PPI: protein-protein interaction; GSVA: gene set variation analysis; GSEA: gene set enrichment analysis; KEGG: Kyoto Encyclopedia of Genes and Genomes; NES: normalized enrichment score.