Adipocytokine Pathway Dysregulation Characterizes Immune-Related Molecular Subtypes and Candidate Biomarkers in Myocardial Infarction

Figures

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  Figure 1. Integration and batch effect removal of MI datasets. (A) UMAP plot of the combined datasets before batch effect removal, showing distinct clustering of GSE48060 (red) and GSE66360 (blue). (B) UMAP plot after batch effect correction using the ComBat function.

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  Figure 2. Adipocytokine pathway analysis in control and MI Groups. (A) Box plot of ssGSEA scores for the adipocytokine pathway in the MI group compared to the control group (***p < 0.001). (B) Box plots of gene expression levels for adipocytokine pathway-related genes, indicating significant upregulation in MI patients across multiple genes (**p < 0.01, ***p < 0.001). (C) Heatmap illustrating the differential expression patterns of adipocytokine pathway-related genes. (D) Correlation pie chart of differentially expressed adipocytokine pathway genes, highlighting strong positive correlations among multiple genes.

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  Figure 3. Identification and validation of diagnostic genes associated with the adipocytokine signaling pathway in MI. (A) Variable importance plot from the XGBoost algorithm, ranking the top 4 genes based on their contribution to the classification model. (B) Venn diagram illustrating the intersection of genes identified by the XGBoost algorithm and multivariate logistic regression analysis. (C) Validation of the expression levels of the two overlapping genes, IRS2 and SOCS3, in clinical blood samples from MI patients and controls using qPCR (***p < 0.001).

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  Figure 4. Identification of MI subtypes. (A) Consensus matrix heatmap from the clustering analysis, showing two distinct MI patient subtypes (C1 and C2) with high consensus values within each subtype. (B) Volcano plot illustrating the differential expression analysis between subtypes C1 and C2. (C) Heatmap of the top differentially expressed genes between C1 and C2.

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  Figure 5. Enrichment analysis of adipocytokine pathway-related MI subtypes. (A) Chord diagram of Gene Ontology (GO) enrichment analysis. The color scale represents the -log10(p-value), indicating the significance of each term. (B) Dot plot of KEGG pathway enrichment analysis. The size of the dots corresponds to the number of genes involved, and the color gradient indicates the -log10(p-value), showing the significance of the pathways.

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  Figure 6. Comparative analysis of adipocytokine pathway-related gene expression and pathway activity. (A) Box plot of ssGSEA scores representing adipocytokine pathway activity between subtypes C1 and C2 (*** p < 0.001). (B) Box plots depicting significant differences in the expression levels of adipocytokine pathway-related genes between subtypes C1 and C2 (** p < 0.01, *** p < 0.001). (C) Heatmap showing the expression levels of adipocytokine pathway-related genes, with subtype C2 (red) exhibiting higher gene expression compared to subtype C1 (blue).

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  Figure 7. Comparison of immune cell infiltration and immune pathway activity. (A) The levels of immune cell infiltration between subtypes C1 (blue) and C2 (red). (B) The activity levels of immune-related pathways between subtypes C1 and C2. * p < 0.05, ** p < 0.01, *** p < 0.001.

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  Figure 8. Differential pathway activities between adipocytokine-related MI subtypes. Box plot showing the GSVA scores for hallmark gene sets, comparing pathway activity between subtypes C1 (blue) and C2 (red). * p < 0.05, ** p < 0.01, *** p < 0.001.