Integrated Omics Insights into Dapagliflozin Effects in Sepsis-Induced Cardiomyopathy

Figures

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  Figure 1. SIC patient selection and survival analysis with COX model. (A) Flowchart of SIC patient selection. From 79 patients, 22 were excluded (chronic liver/kidney failure, heart disease, coagulopathy, age limits, incomplete data), leaving 57 patients: 24 with DAPA and 33 without; (B) Kaplan–Meier survival curves comparing the two treatment groups (treatment 1: pre-hospital use of DAPA vs. treatment 0: no pre-hospital use of DAPA). The log-rank test is shown, with HR (95% CI) values indicated; (C,D) COX proportional hazards regression models were used to evaluate the impact of treatment and other variables on survival outcomes: (C) univariate and (D) multivariate analyses. Hazard ratios (HRs), 95% confidence intervals (CIs), and p-values are reported for key clinical parameters. HR: hazard ratio, CI: confidence interval; (E) dapagliflozin intervention on 7-day survival in mice with sepsis (n = 10).

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  Figure 2. Dapagliflozin alleviates myocardial dysfunction in SIC mice. (A) Representative images of M-mode echocardiography (n = 4); (B) quantitative analysis of LVESV, LVEDV, LVEF, and LVFS in each group of mice (n = 4); (C) measurements of myocardial injury markers: cTnT and BNP levels were assessed from myocardial tissue supernatants, while CK-MB and LDH levels were measured from serum samples (n = 4); (D) representative images of HE staining; (E) representative images of MASSON staining; (F) histopathological score of the heart (n = 4); (G) quantitative analysis of collagen deposition: the percentage of collagen-positive area was calculated as the ratio of blue-stained regions to the total tissue area, reflecting the degree of fibrosis. * Indicates a statistically significant p < 0.05. ** Indicates a statistically significant p < 0.01; *** Indicates a statistically significant p < 0.001; **** indicates a statistically significant p < 0.0001.

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  Figure 3. Transcriptomic analysis of dapagliflozin’s regulatory effects on gene expression in SIC mice (n = 4). (A) Volcano plot of differential gene expression: The x-axis shows log2FoldChange values, and the y-axis displays −log10padj or −log10pvalue. The blue dashed line indicates the differential gene screening threshold; (B) Venn diagram of differential genes: different colors represent various comparison groups; (C) Clustering heat map of differentially expressed genes; In the figure, the abscissa is the sample name, and the ordinate is the normalized value of the differential gene FPKM. The redder the color, the higher the expression level, and the greener the expression level, the lower the expression level. The chromosome to which each gene belongs, the length of the gene and the biological type of the gene are also added to the heat map; (D) GO enrichment analysis upward and downward histogram; In the figure, the abscissa is the GO Term, and the ordinate is the number of up-and down-regulated differential genes annotated on the GO Term; (E) KEGG enrichment distribution plot; In the figure, the abscissa is the ratio of the number of differential genes annotated to the KEGG pathway…

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  Figure 4. Impact of dapagliflozin on metabolic alterations (n = 7). (A) Volcano plot of differential gene expression: The x-axis represents log2FoldChange, and the y-axis is −log10padj or −log10pvalue. The blue dashed line shows the differential gene screening threshold; (B) Stick/bar plot of differential metabolites: The top 20 upregulated (red) and downregulated (blue) metabolites, sorted by log2(Fold Change), are displayed. Dot color indicates regulation direction (red: upregulated; blue: downregulated). Stick length corresponds to the magnitude of log2(Fold Change), and dot size represents VIP (Variable Importance in Projection) values; (C) Hierarchical clustering analysis of differential metabolites: Vertical dendrograms represent sample clustering, and horizontal dendrograms represent metabolite clustering. Shorter dendrogram branches indicate higher similarity. (D) Venn diagram of differential genes: various colors correspond to distinct comparison groups.

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  Figure 5. Comprehensive visualization of dapagliflozin’s effects on differential metabolites and pathway enrichment. (A) Correlation diagram of differential metabolites: Correlation ranges from 1 (complete positive, red) to −1 (complete negative, blue). Uncolored areas indicate p-value > 0.05. The top 20 metabolites are ordered by p-value; (B) chord chart of differential metabolites: Line thickness shows correlation strength; red lines denote positive correlations; and blue lines denote negative correlations. Only correlations with an absolute value > 0.7 are displayed; (C) Z-score plot: The x-axis is the Z-score value, and the y-axis lists differential metabolites. Each circle represents a sample. Only the top 30 metabolites (sorted by p-value) are shown; (D) KEGG enrichment bubble chart: The x-axis represents the ratio of differential metabolites in each pathway. Point size reflects the number of metabolites, and color indicates p-value significance, with smaller values showing greater statistical reliability; (E) GSEA enrichment analysis: depicts enrichment profiles for pathways affected by metabolites; (F) The x-axis represents the average decline (MeanDecreaseAccuracy) in model…

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  Figure 6. Integrated analysis of synergistic regulation of genes and metabolites by dapagliflozin. (A) Nine-image plot of differential metabolites and transcripts: The x-axis shows log2 fold change of transcripts (log2FC_Tran), and the y-axis shows log2 fold change of metabolites (log2FC_Met). Different groups are marked in red and green; (B) KEGG enrichment bubble chart: The x-axis is the ratio of metabolites or genes enriched in a pathway to the total annotated in the pathway. The y-axis lists KEGG pathways enriched by both metabolome and transcriptome. Dot size represents the number of enriched features, and color indicates p-value, with brighter colors signifying greater significance; (C) correlation network diagram: Yellow boxes represent metabolites, and blue boxes represent genes. Lines indicate correlations: red for positive and blue for negative. Darker colors correspond to higher correlation coefficients; (D) correlation heat map: Displays the relationship between differential metabolites and genes (positive ion mode). The y-axis represents metabolites, and the x-axis represents genes. Red indicates positive correlation; blue indicates negative correlation. The plot shows the top…

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  Figure 7. Schematic diagram of the protective mechanism of dapagliflozin in sepsis-induced cardiomyopathy: The SIC model was established by animal experiments. After one week of pretreatment with dapagliflozin (10 mg/kg), mice underwent CLP surgery to induce SIC, and cardiac function, pathological changes, and overall mechanism changes were evaluated 24 h after surgery. Treatment with dapagliflozin significantly improved cardiac function, reduced levels of myocardial injury markers, and attenuated histopathological damage in SIC mice. Mechanistically, dapagliflozin enhances autophagy, reduces oxidative stress and inflammatory response, and restores the balance of energy metabolism by regulating key genes (such as Prdm10, Rac2, Myc, Stat3, Mapk3) and activating the AMPK signaling pathway. Overall, dapagliflozin exerted cardioprotective effects through multiple regulations, ultimately improving myocardial function and reducing tissue damage in SIC mice.