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. 2022 Apr 6:9:831605.
doi: 10.3389/fcvm.2022.831605. eCollection 2022.

Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction

Yanze Wu  1   2 , Ting Jiang  3 , Jinghai Hua  1 , Zhiping Xiong  1 , Hui Chen  1 , Lei Li  1 , Jingtian Peng  1 , Wenjun Xiong  1
Affiliations

Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction

Yanze Wu et al. Front Cardiovasc Med. .

Abstract

Background: Acute myocardial infarction (AMI) is a fatal disease that causes high morbidity and mortality. It has been reported that AMI is associated with immune cell infiltration. Now, we aimed to identify the potential diagnostic biomarkers of AMI and uncover the immune cell infiltration profile of AMI.

Methods: From the Gene Expression Omnibus (GEO) data set, three data sets (GSE48060, GSE60993, and GSE66360) were downloaded. Differentially expressed genes (DEGs) from AMI and healthy control samples were screened. Furthermore, DEGs were performed via gene ontology (GO) functional and kyoto encyclopedia of genes and genome (KEGG) pathway analyses. The Gene set enrichment analysis (GSEA) was used to analyze GO terms and KEGG pathways. Utilizing the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database, a protein-protein interaction (PPI) network was constructed, and the hub genes were identified. Then, the receiver operating characteristic (ROC) curves were constructed to analyze the diagnostic value of hub genes. And, the diagnostic value of hub genes was further validated in an independent data set GSE61144. Finally, CIBERSORT was used to represent the compositional patterns of the 22 types of immune cell fractions in AMI.

Results: A total of 71 DEGs were identified. These DEGs were mainly enriched in immune response and immune-related pathways. Toll-like receptor 2 (TLR2), interleukin-1B (IL1B), leukocyte immunoglobulin-like receptor subfamily B2 (LILRB2), Fc fragment of IgE receptor Ig (FCER1G), formyl peptide receptor 1 (FPR1), and matrix metalloproteinase 9 (MMP9) were identified as diagnostic markers with the value of p < 0.05. Also, the immune cell infiltration analysis indicated that TLR2, IL1B, LILRB2, FCER1G, FPR1, and MMP9 were correlated with neutrophils, monocytes, resting natural killer (NK) cells, gamma delta T cells, and CD4 memory resting T cells. The fractions of monocytes and neutrophils were significantly higher in AMI tissues than in control tissues.

Conclusion: TLR2, IL1B, LILRB2, FCER1G, FPR1, and MMP9 are involved in the process of AMI, which can be used as molecular biomarkers for the screening and diagnosis of AMI. In addition, the immune system plays a vital role in the occurrence and progression of AMI.

Keywords: CIBERSORT; acute myocardial infarction; bioinformatics; hub gene; immune cell infiltration.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Differentially expressed genes (DEGs) between acute myocardial infarction samples and control ones. The red dots represent upregulated differential genes, the green dots represent differential downregulated genes, and the black dots represent genes without significant differences.
FIGURE 2
FIGURE 2
Heatmap showing the expression changes in acute myocardial infarction and control samples. Red represents upregulated DEGs, blue represents downregulated DEGS, and the gradation of color represents the value of | log FC| (FC: fold change).
FIGURE 3
FIGURE 3
Gene ontology (GO) enrichment analyses of DEGs in acute myocardial infarction (AMI).
FIGURE 4
FIGURE 4
Kyoto encyclopedia of genes and genome (KEGG) pathway enrichment analysis of DEGs in AMI.
FIGURE 5
FIGURE 5
Enrichment analyses via gene set enrichment analysis (GSEA). (A) Five representative enriched immune-related GO gene sets and (B) five representative enriched immune-related KEGG pathways.
FIGURE 6
FIGURE 6
Protein–protein interaction (PPI) network construction. Circles and lines represent genes and the interaction of proteins between genes, respectively. The red represents the upregulated genes. The green represents the downregulated genes.
FIGURE 7
FIGURE 7
The number of adjacent nodes.
FIGURE 8
FIGURE 8
Diagnostic value of top six hub genes with receiver operating characteristic (ROC) curves. (A) Analysis with ROC curves. (B) Specific value of diagnosis efficiency.
FIGURE 9
FIGURE 9
Validation of the diagnostic value of hub genes in the GSE61144 data set. (A) Fc fragment of IgE receptor Ig (FCER1G), (B) formyl peptide receptor 1 (FPR1), (C) interleukin-1B (IL1B), (D) leukocyte immunoglobulin-like receptor subfamily B2 (LILRB2), (E) matrix metalloproteinase 9 (MMP9), and (F) Toll-like receptor 2 (TLR2).
FIGURE 10
FIGURE 10
Distribution and visualization of immune cell infiltration. (A) The fraction of 22 subsets of immune cells in AMI and control samples. (B) The violin graph shows the difference of immune infiltration between AMI and control samples. The control samples are shown in blue and AMI samples are shown in red. The value of value p < 0.05.
FIGURE 11
FIGURE 11
Correlation matrix among fractions of 22 immune cell subtype. Red: positive correlation; white: the same correlation levels; and blue: negative correlation.
FIGURE 12
FIGURE 12
Analysis of correlation between hub genes and immune cells. (A) FCER1G, (B) FPR1, (C) IL1B, (D) LILRB2, (E) MMP9, and (F) TLR2.
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