Application of acute myocardial infarction-related key genes in noninvasive diagnosis: a comprehensive analysis based on transcriptome and single-cell transcriptome

Figures

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  FIGURE 1. Identification of core genes in AMI peripheral blood. (A,B) Volcano plots of AMI-associated differentially expressed genes (DEGs) in the GSE62646 (A) and GSE141512 (B) datasets. (C) Analysis of scale-free topology fit for WGCNA, illustrating the distribution of network connectivity. (D) Gene co-expression module clustering dendrogram. Modules were determined via dynamic tree cutting and merging (mergeCutHeight = 0.4). (E) Heatmap displaying the correlation of co-expression modules with AMI. The MEpink module showed a significant positive correlation. (F) Venn diagram identifying the three core genes through the intersection of the MEpink module genes and DEGs from GSE62646 and GSE141512. (G) Comparison of ADAP2, FAM20C, and PLA2G15 expression levels in peripheral blood between STEMI and CAD patients.

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  FIGURE 2. Evaluation of the diagnostic value of core genes and construction of the diagnostic model. (A) ROC curves for individual core genes PLA2G15 in the GSE62646 training set. (B) ROC curve of the multivariable logistic regression combined diagnostic model based on ADAP2, FAM20C, and PLA2G15 in the GSE62646 training set. (C) Nomogram for predicting the risk probability of AMI using the core genes. (D) Calibration curve of the nomogram. (E) ROC curve of the combined diagnostic model in the GSE59867 validation set.

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  FIGURE 3. Immune Cell Atlas of AMI Peripheral Blood and Expression Characteristics of Core Genes. (A) UMAP plot showing dimensionality reduction and visualization of all immune cells based on scRNA-seq data. (B) Expression levels of canonical marker genes across the identified cell subsets. (C) Distribution of sample origins within the UMAP space, illustrating the cellular composition from different samples. (D) Bar plot showing the proportional distribution of different cell types within each sample. (E) UMAP plots displaying the expression distribution of the core genes ADAP2, FAM20C, and PLA2G15 across all immune cells.

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  FIGURE 4. The roles of ADAP2 and FAM20C in myeloid cells. (A) UMAP plot showing the sub-clustering of myeloid cell subsets. (B) Expression distribution of characteristic marker genes across the myeloid cell subsets. (C) Results of GO biological process enrichment analysis for each myeloid cell subset. (D) Distribution of myeloid cell states along the differentiation trajectory. (E) Trajectory path of cells based on pseudotime. (F) Trajectory illustrating cell differentiation towards terminal states, corresponding to specific myeloid cell subtypes. (G,H) Expression patterns of the core genes ADAP2 (G) and FAM20C (H) along the myeloid cell differentiation trajectory.

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  FIGURE 5. ADAP2 exacerbates OGD/R-induced cardiomyocyte injury. (A) mRNA expression level of ADAP2 in AC16 cells after OGD/R treatment. (B) Successful construction of the ADAP2-knockdown cell model under OGD/R conditions. (C) Effect of ADAP2 knockdown on cell proliferation under OGD/R conditions, as detected by the CCK-8 assay. (D,E) Effects of ADAP2 knockdown on cell apoptosis under OGD/R conditions, assessed by Annexin V-FITC/PI flow cytometry (D) and TUNEL staining (E). (F) Effect of ADAP2 knockdown on the mRNA expression of inflammatory factors TNF-α, IL-6, and IL-1β under OGD/R conditions, as detected by qRT-PCR.

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  FIGURE 6. ADAP2 mediates OGD/R-induced cardiomyocyte injury by regulating the IL-17 signaling pathway. (A) KEGG pathway enrichment analysis of ADAP2. (B) Western blot analysis of the protein expression levels of key IL-17 signaling pathway molecules (IL-17A, IL-17RA, and ACT1) after ADAP2 knockdown. (C) Changes in cell proliferation viability under OGD/R conditions across different treatment groups, as measured by the CCK-8 assay. (D,E) Changes in the apoptosis rate under OGD/R conditions across different treatment groups, detected by flow cytometry (D) and TUNEL staining (E). (F) mRNA expression levels of the inflammatory factors TNF-α, IL-6, and IL-1β in different treatment groups under OGD/R conditions, as detected by qRT-PCR.