Systematic analysis of myocardial immune progression in septic cardiomyopathy: Immune-related mechanisms in septic cardiomyopathy

Figures

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  FIGURE 1. Workflow used for bioinformatics analyses.

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  FIGURE 2. Overview of WGCNA network construction of all genes (A) Gene modules’ dendrogram plots of all genes; (B) module-trait relationships of four groups in 18 modules. (C–E) Module membership vs. gene significance between three significant modules, including blue module (Pearson cor = 0.9, p < 1e-200), dark green module (cor = 0.9, p = 3.3e-34), and orange module (Pearson cor = 0.79, p < 1e-200); (F) the bubble diagram showing the GO (biological process, BP) function enrichment of genes in sub-modules. The size represents the gene counts, and node colors show the gene expression negative Log10_FDR (false discovery rate).

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  FIGURE 3. Analysis of gene ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) network of genes in septic cardiomyopathy (SC)-related modules. (A–C) The bubble map showing the GO function (cellular component, CC, and molecular function, MF) and KEGG pathways were constructed by the STRING database. The sizes represent negative Log10 (FDR). (D) The gene PPI network was also constructed based on the STRING database. (E) The plots showing the top 10 higher degree hub genes for SC.

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  FIGURE 4. Immunocyte infiltration analysis and potential immunocyte subtype detection. (A) This diagram shows the immune-related pathways by gene set enrichment analysis (GSEA) analysis. (B) This heatmap shows the immunocyte infiltration difference between SC and control heart samples. (C,D) Box plots presenting significantly infiltrated immunocyte subtypes, neutrophils, and M2 macrophages. (E) This correlated heatmap shows the relationship between immunocytes and hub genes. (F) Intersection between DEGs and hub genes, identifying the key genes, LCN2, and PTX3.