Identification of transcription factor-lipid droplet-related gene biomarkers for the prognosis of post-acute myocardial infarction-induced heart failure

Figures

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  Figure 1. Differential gene expression analysis of peripheral blood samples in patients with and without heart failure after a myocardial infarction.

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  Figure 2. WGCNA analysis of the GSE11947 gene expression matrix. (A) Scale-free network model. (B) Dendrogram constructed based on the correlation of gene expressions. (C) Heatmap of the correlation between modules and prognostic traits (Deeper colors indicate higher correlation, with red representing a positive correlation and blue representing a negative correlation). (D) Venn diagram of genes in the “Indianred” module and differentially expressed genes.

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  Figure 3. Go and KEGG enrichment analyses for both the differentially expressed genes and the genes in the “Indianred” module.

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  Figure 4. ssGSEA enrichment scores for the lipid droplet-associated genes across the samples in GSE11947 (n = 16, each group).

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  Figure 5. Venn diagram of the LDRGs identified by the CART, random forest, support vector machine, and naive Bayes machine-learning algorithms. G0S2, G0/G1 switch 2; VAPA, VAMP-associated protein A; UBE2G2, ubiquitin conjugating enzyme E2 G2; SNAP23, synaptosome-associated protein 23; LPIN1, lipin 1; APOB, apolipoprotein B; OSBPL2, oxysterol-binding protein-like 2; NAPA, NSF attachment protein alpha; BSCL2, Berardinelli-Seip congenital lipodystrophy 2; CAV1, caveolin 1; PNPLA2, patatin-like phospholipase domain-containing 2; CES1, carboxylesterase 1; ADPN, adiponectin; DGAT2, diacylglycerol O-acyltransferase 2; VAMP4, vesicle-associated membrane protein 4; AUP1, ancient ubiquitous protein 1; AGPAT2, 1-acylglycerol-3-phosphate O-acyltransferase 2; ABHD5, abhydrolase domain-containing 5; ACAT1, acetyl-CoA acetyltransferase 1; CAV2, caveolin 2; PEMT, phosphatidylethanolamine N-methyltransferase; APOA4, apolipoprotein A-IV; CIDEC, cell death-inducing DFFA-like effector C; DGAT1, diacylglycerol O-acyltransferase 1; PLD1, phospholipase D1; CIDEB, cell death-inducing DFFA-like effector B; VMP1, vacuole membrane protein 1; VCP, valosin-containing protein; MGLL, monoglyceride lipase; PCYT1A,…

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  Figure 6. The ROC curves of 22 LDRGs for heart failure classification in the GSE11947 microarray data.

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  Figure 7. The transcription factor and lipid droplet-related gene expression network construct. (A) The overall PPI network with 22 transcriptional factors and 409 lipid droplet-related genes. Triangles represent LDRGs. TFs are represented by circles. The lines connecting TFs and LDRGs indicate an LDRG that is predicted to be regulated by a TF. (B) Venn diagram of the predicted transcription factors and differentially expressed genes. (C) PPI network of the transcription factors and lipid droplet-related genes. (D) Correlation heatmap for 35 transcription factors and 22 lipid droplet genes.

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  Figure 8. The ROC curve of the TF-LDRG classification effect in the GSE11947 microarray dataset.

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  Figure 9. The ROC curve of the TF-LDRG classification effect in the GSE55897 microarray dataset for validation.

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  Figure 10. Validation of the TF-LDRG prognostic biomarkers in predicting HF in clinical samples. (A,B) The relative CT values of ABHD5 and ARID3a compared to GAPDH in peripheral blood samples in the non-heart failure and heart failure groups. (C) The ROC curve of ABHD5-ARID3a gene expression in the peripheral blood samples for predicting heart failure. (D) Two-dimensional scatter plots of the relative CT values of the TF-LDRG gene pairs compared to GAPDH in the non-heart failure and heart failure groups.

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  Figure 11. The flow diagram of the whole study.