Investigation of the shared molecular mechanisms and hub genes between myocardial infarction and depression

Figures

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  Figure 1. The flowchart of this study.

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  Figure 2. Identification and functional analysis of M-DEGs and D-DEGs. (A) The heatmap of M-DEGs. (B) The volcano plot of M-DEGs. (C) The heatmap of D-DEGs. (D) The volcano plot of D-DEGs. (E) The bubble chart of GO analysis of M-DEGs. (F) The circle diagram of GO analysis of M-DEGs. (G) The bubble chart of KEGG analysis of M-DEGs. (H) The circle diagram of KEGG analysis of M-DEGs. (I) The bubble chart of GO analysis of D-DEGs. (J) The circle diagram of GO analysis of D-DEGs. (K) The bubble chart of KEGG analysis of D-DEGs. (L) The circle diagram of KEGG analysis of D-DEGs.

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  Figure 3. Identification and functional analysis of S-DEGs. (A) The S-DEGs were identified by Venn diagram. (B) The bubble chart of GO analysis of S-DEGs. (C) The circle diagram of GO analysis of S-DEGs. (D) The bubble chart of KEGG analysis of S-DEGs. (E) The circle diagram of KEGG analysis of S-DEGs.

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  Figure 4. Differential function analysis between control group and myocardial infarction group or depression group. (A) The results of GSVA analysis showing the differences in biological functions between myocardial infarction group and control group (red bars represent activation of these biological functions in the myocardial infarction group, blue bars represent inhibition of these biological functions in the myocardial infarction group). (B) The results of GSVA analysis showing the differences in signaling pathways between myocardial infarction group and control group (red bars represent activation of these signal pathways in the myocardial infarction group, blue bars represent inhibition of these signal pathways in the myocardial infarction group). (C) The results of GSVA analysis showing the differences in biological functions between depression group and control group. (D) The results of GSVA analysis showing the differences in signaling pathways between depression group and control group. (E) The box plot showing the differences in infiltrated immune cells between myocardial infarction group and control group. (F) The bar plot showing relative proportion of 22 infiltrated immune…

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  Figure 5. Evaluation of the diagnostic value of S-DEGs. (A) The LASSO coefficient of 13 S-DEGs of the diagnostic value. (B) The optimal lambda value was selected by LASSO regression based on cross-validation. (C) Evaluation of the diagnostic value of 6 hub S-DEGs individually by ROC analysis. (D) The residual boxplots of 3 machine learning models. (E) The cumulative residual distribution curves of 3 machine learning models. (F) The ROC curves of 3 machine learning models. (G) The nomogram for predicting the risk of depression based on 6 hub S-DEGs. (H) The calibration curves of the nomogram. (I) The DCA of the nomogram.

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  Figure 6. Single-gene GSEA analysis of 6 hub S-DEGs. (A) Single-gene GSEA GO analysis of CD24. (B) Single-gene GSEA GO analysis of CSTA. (C) Single-gene GSEA GO analysis of EXTL3. (D) Single-gene GSEA GO analysis of RPS7. (E) Single-gene GSEA GO analysis of SLC25A5. (F) Single-gene GSEA GO analysis of ZMAT3. (G) Single-gene GSEA KEGG analysis of CD24. (H) Single-gene GSEA KEGG analysis of CSTA. (I) Single-gene GSEA KEGG analysis of EXTL3. (J) Single-gene GSEA KEGG analysis of RPS7. (K) Single-gene GSEA KEGG analysis of SLC25A5. (L) Single-gene GSEA KEGG analysis of ZMAT3.

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  Figure 7. Functional analysis of 6 hub S-DEGs. (A,B) The correlation analysis of 6 hub S-DEGs. (C) The correlation analysis of infiltrated immune cells and 6 hub S-DEGs. (D) The position of 6 hub S-DEGs on the chromosome.

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  Figure 8. Identification of myocardial infarction molecular subtypes clusters and evaluation of the molecular subtype identification value of 6 hub S-DEGs. (A) The consensus clustering matrix when k = 2. (B) The CDF curves. (C) The CDF delta area curves. (D) The PCA analysis of the 2 molecular subtypes clusters. (E) The results of GSVA analysis showing the differences in biological functions between cluster 1 and cluster 2 (red bars represent activation of these biological functions in the cluster 2, blue bars represent inhibition of these biological functions in the cluster 2). (F) The results of GSVA analysis showing the differences in signaling pathways between cluster 1 and cluster 2 (red bars represent activation of these signal pathways in the cluster 2, blue bars represent inhibition of these signal pathways in the cluster 2). (G) The box plot showing the differences in infiltrated immune cells between cluster 1 and cluster 2. (H) The bar plot showing relative proportion of 22 infiltrated immune cells in cluster 1 and cluster 2. (I) Evaluation of the molecular subtype identification value of 6 hub S-DEGs individually by ROC analysis. (J) The residual boxplots of 3 machine learning…

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  Figure 9. Evaluation of the expression levels and diagnostic value of 6 hub S-DEGs in the depression validation set (GSE98793). (A–F) Differences in expression levels of 6 hub S-DEGs between depression group and control group in the validation set. (G) Evaluation of the diagnostic value of 6 hub S-DEGs individually by ROC analysis in the validation set. (H) The residual boxplots of 3 machine learning models in the validation set. (I) The cumulative residual distribution curves of 3 machine learning models in the validation set. (J) The ROC curves of 3 machine learning models in the validation set.

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  Figure 10. Evaluation of the molecular subtype identification value of 6 hub S-DEGs in the myocardial infarction validation set (GSE48060). (A) The consensus clustering matrix when k = 2 in the validation set. (B) The CDF curves in the validation set. (C) The CDF delta area curves in the validation set. (D) The PCA analysis of the 2 molecular subtypes clusters in the validation set. (E) The results of GSVA analysis showing the differences in biological functions between cluster 1 and cluster 2 in the validation set. (F) The results of GSVA analysis showing the differences in signaling pathways between cluster 1 and cluster 2 in the validation set. (G) The box plot showing the differences in infiltrated immune cells between cluster 1 and cluster 2 in the validation set. (H) The bar plot showing relative proportion of 22 infiltrated immune cells in cluster 1 and cluster 2 in the validation set. (I) Evaluation of the molecular subtypes identification value of 3 M-CRGs individually by ROC analysis in the validation set. (J) The residual boxplots of 3 machine learning models in the validation set. (K) The cumulative residual distribution curves of 3 machine learning models in the validation set.…

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  Figure 11. The RT-qPCR results of blood samples of 40 patients. (A) The mRNA expression levels of CD24. (B) The mRNA expression levels of CSTA. (C) The mRNA expression levels of EXTL3. (D) The mRNA expression levels of RPS4. (E) The mRNA expression levels of SLC25A5. (F) The mRNA expression levels of ZMAT3. (*P < 0.05, **P < 0.01).

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  Figure 12. Prediction of ceRNA regulatory network of hub S-DEGs (165 nodes and 186 edges).