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. 2025 May 30:12:1488684.
doi: 10.3389/fcvm.2025.1488684. eCollection 2025.

FOS as a biomarker for myocardial infarction treatment with Deng's Yangxin Decoction: a systems biology-based analysis

Affiliations

FOS as a biomarker for myocardial infarction treatment with Deng's Yangxin Decoction: a systems biology-based analysis

Junfeng Fang et al. Front Cardiovasc Med. .

Abstract

Background: Deng's Yangxin Decoction (DYX) is a Chinese herbal formula used in clinical practice to treat patients with myocardial infarction (MI). However, its underlying mechanism remains unclear.

Objective: This study aims to explore potential biomarkers and associated mechanisms of DYX for MI.

Methods: Therapeutic targets for DYX were obtained based on the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Traditional Chinese Medicine Integrated Database, and UniProt databases. Key targets were screened using topological analysis. Differentially expressed genes (DEGs) between MI patients and controls were obtained using open-source datasets. Weighted gene co-expression network analysis (WGCNA) was utilized to screen MI-related genes in the expression array. Hub biomarkers were determined by intersecting DEGs, protein-protein interaction networks, and WGCNA results. Molecular docking validated interactions between DYX components and hub biomarkers. Immune infiltration was assessed via CIBERSORT. Single-cell RNA sequencing analyzed hub biomarker expression in coronary plaques.

Results: FOS was a core biomarker for DYX for MI. Molecular docking confirmed strong binding affinities between quercetin/baicalein and FOS. In addition, high expression of FOS was associated with immune infiltration of neutrophils, activated mast cells, activated dendritic cells, monocytes, and NK cells. FOS was also found to be expressed at high levels in mast and dendritic cells, monocytes, and some T cells in coronary plaques.

Conclusion: FOS is a target of DYX for the treatment of MI, and the mechanism of action may be related to the modulation of immune infiltration.

Keywords: bioinformatic analysis; diagnostic biomarker; immune infiltration; myocardial infarction; network pharmacology; single-cell analysis.

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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
Workflow of the systematic strategies to elucidate the mechanisms of the treatment of DYX on MI. DYX, Deng's Yangxin Decoction; MI, myocardial infarction.
Figure 2
Figure 2
Ingredient–target network of DYX. The network of the relationship between the active ingredients and the targets. PPI, protein–protein interaction; DYX, Deng's Yangxin Decoction.
Figure 3
Figure 3
PPI network of targets. Targets are shown with yellow dots (high degree) and blue dots (low degree). PPI networks of all targets (A), targets with a degree value of >8 (B), and targets with a degree value of >15 (C). (D) PPI network of 15 core targets (degree > 17).
Figure 4
Figure 4
DEGs between healthy people and MI patients and their functional enrichment analysis. (A) Heatmap of DEGs. Red indicates relatively high expression of this gene in the sample, and blue indicates relatively low expression. (B) Volcano plot of DEGs. Red dots represent genes significantly upregulated in MI samples, and green dots represent genes significantly downregulated. (C) GO enrichment analysis of DEGs. Bar length reflects the number of genes associated with each term (count), while color intensity represents statistical significance (q-value, red = more significant). (D) DO analysis of DEGs. Diseases are ranked by significance (q-value, red = most significant), and bar length indicates the number of genes linked to each disease (Count). (E) GSEA comparing gene expression profiles between control and MI samples, highlighting pathways enriched in the control group. (F) GSEA highlighting pathways enriched in MI samples compared with controls. DEGs, differentially expressed genes; MI, myocardial infarction; GO, gene ontology; DO, disease ontology; GSEA, gene set enrichment analysis.
Figure 5
Figure 5
WGCNA. (A,B) Analysis of the scale-free index and the mean connectivity for various soft-thresholding powers. (C) Relationships of consensus modules with samples. Each specified color represents a specific gene module. (D) The gene significance for MI in the green module. WGCNA, weighted gene co-expression network analysis; MI, myocardial infarction.
Figure 6
Figure 6
Identification and validation of hub marker for MI. (A) Venn diagram showing the intersection of DEGs, core targets in the PPI network, and hub genes in WGCNA. (B) The ROC curve of the diagnostic characteristic marker in GSE66360. (C) The ROC curve of the diagnostic characteristic marker in GSE60993. (D) FOS mRNA expression in MI compared with normal groups in the test set. (E) FOS mRNA expression in MI compared with normal groups in the validation set. An AUC value between 0.8 and 0.9 was considered good, and exceptional when the AUC value was >0.9. ROC, receiver operating characteristic; AUC, area under the ROC curve; MI, myocardial infarction; WGCNA, weighted gene co-expression network analysis.
Figure 7
Figure 7
Molecular docking of DYX components and FOS. (A) The action mode of FOS with quercetin. (B) The action mode of FOS with baicalein.
Figure 8
Figure 8
Evaluation of immune cell infiltration. (A) Bar plot of proportions of 22 immune cell types in the control group and MI patients. (B) Heatmap of correlation between the 22 immune cell types. (C) Violin plot of the proportion of 22 immune cell subsets between healthy people and MI patients. MI, myocardial infarction.
Figure 9
Figure 9
The correlation between FOS and immune cells. (A) Forest maps of correlation. (B) Scatterplot of correlation. The orange curve shows the density distribution of FOS expression, and the blue curve shows the density distribution of the corresponding immune cell percentage.
Figure 10
Figure 10
Single-cell analysis of FOS. (A) Feature plot of cell clusters in ACS (left) and SAP (right). (B) Manual annotation of cell clusters. (C) Dot plot of markers. (D) Violin plot of FOS expression in ACS and SAP. ns, not significant. (E) Violin plot of FOS expression in cell clusters. **** p < 0.0001. (F) Feature plot of FOS expression in cell clusters. The yellow-colored cells within the red circle indicate higher FOS expression levels. (G) Circle heatmap of 36 DEGs between high FOS T cells and low FOS T cells. (H) Dot plot illustrating the KEGG enrichment analysis of 36 DEGs. ACS, acute coronary syndrome; SAP, stable angina pectoris; DEGs, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes.

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