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Clinical Interventions in Aging Volume 16, 2021 - Issue
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Original Research

Identification of Potential Key Genes Involved in the Carotid Atherosclerosis

Youshi Meng1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Chunli Zhang1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Lucong Liang1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Lei Wei1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Hao Wang1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Fengkun Zhou1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Rongjie Li1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of China
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Donghua Zou1 Department of Neurology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of China;2 Department of Neurology, The First People’s Hospital of Nanning, Nanning, Guangxi, 530022, People’s Republic of ChinaORCID Iconhttps://orcid.org/0000-0002-3891-9472
ORCID Icon,
Xiaohua Huang3 Department of Neurology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi, 533000, People’s Republic of ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-6731-5491
ORCID Icon &
Jie Liu4 Department of Cardiology, The Fifth Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530022, People’s Republic of ChinaCorrespondence[email protected]
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Pages 1071-1084 | Published online: 10 Jun 2021

Figures & data

Figure 1 The workflow of this study.

Abbreviation: GEO, gene expression omnibus.
Figure 1 The workflow of this study.

Figure 2 The differentially expressed genes (DEGs) for carotid atherosclerosis and control samples. (A) A volcano plot of the for carotid atherosclerosis and control samples. Red indicated upregulated genes and blue indicated downregulated genes. The gray area showed the gene expression below the threshold criteria. (B) The heatmap of the DEGs.

Abbreviation: DEGs, differentially expressed genes.
Figure 2 The differentially expressed genes (DEGs) for carotid atherosclerosis and control samples. (A) A volcano plot of the for carotid atherosclerosis and control samples. Red indicated upregulated genes and blue indicated downregulated genes. The gray area showed the gene expression below the threshold criteria. (B) The heatmap of the DEGs.

Figure 3 The biological functions of differentially expressed genes (DEGs). (A) Cellular component, (B) biological process, (C) molecular function and (D) KEGG pathway analysis. The gene set enrichment analysis (GSEA) for (E) GO and (F) KEGG for carotid atherosclerosis and control samples.

Abbreviations: GO, gene ontology; KEGG, Kyoto encyclopedia genes and genome.
Figure 3 The biological functions of differentially expressed genes (DEGs). (A) Cellular component, (B) biological process, (C) molecular function and (D) KEGG pathway analysis. The gene set enrichment analysis (GSEA) for (E) GO and (F) KEGG for carotid atherosclerosis and control samples.

Figure 4 The PPI network. A graphic representation of the protein–protein network based on differentially expressed genes of carotid atherosclerosis and control samples. Red nodes indicated upregulated genes and light blue nodes indicated downregulated genes in the carotid atherosclerosis group.

Figure 4 The PPI network. A graphic representation of the protein–protein network based on differentially expressed genes of carotid atherosclerosis and control samples. Red nodes indicated upregulated genes and light blue nodes indicated downregulated genes in the carotid atherosclerosis group.

Figure 5 The selection and analysis of hub genes. Top 50 genes selected based the four ranking methods. (A) Degree, (B) DMNC, (C) MCC and (D) MNC. The darker the color of the node, the higher the score. DMNC, density of maximum neighborhood component; MCC, maximal clique centrality. MNC, maximum neighborhood component. (E) Venn plot. Venn plot of the overlapping genes for the top 50 genes selected based on the four ranking methods. Degree, DMNC, MNC, and MCC. (F) The expression levels for 16 hub genes in carotid atherosclerosis samples compared with control samples.

Figure 5 The selection and analysis of hub genes. Top 50 genes selected based the four ranking methods. (A) Degree, (B) DMNC, (C) MCC and (D) MNC. The darker the color of the node, the higher the score. DMNC, density of maximum neighborhood component; MCC, maximal clique centrality. MNC, maximum neighborhood component. (E) Venn plot. Venn plot of the overlapping genes for the top 50 genes selected based on the four ranking methods. Degree, DMNC, MNC, and MCC. (F) The expression levels for 16 hub genes in carotid atherosclerosis samples compared with control samples.

Figure 6 The GO and KEGG enrichment analysis for the genes in cluster 1 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 1.

Figure 6 The GO and KEGG enrichment analysis for the genes in cluster 1 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 1.

Figure 7 The GO and KEGG enrichment analysis for the genes in cluster 2 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 2.

Figure 7 The GO and KEGG enrichment analysis for the genes in cluster 2 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 2.

Figure 8 The GO and KEGG enrichment analysis for the genes in cluster 3 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 3.

Figure 8 The GO and KEGG enrichment analysis for the genes in cluster 3 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 3.

Figure 9 The GO and KEGG enrichment analysis for the genes in cluster 4 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 4.

Figure 9 The GO and KEGG enrichment analysis for the genes in cluster 4 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 4.

Figure 10 The GO and KEGG enrichment analysis for the genes in cluster 5 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 5.

Figure 10 The GO and KEGG enrichment analysis for the genes in cluster 5 obtained based the MCODE method. (A) The biological processes and (B) KEGG pathways for genes in cluster 5.

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