Correlation analysis of key genes and immune infiltration in visceral adipose tissue and subcutaneous adipose tissue of patients with type 2 diabetes in women

Figures

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  Figure 1.. To analyze the DEGs in SAT or VAT gene expression profiles of women with T2DM. (a) The volcanic plot illustrates the distribution of DEGs derived from comparing the gene expression profiles of VAT in women with T2DM (n = 12) versus those without T2DM (n = 12) (GSE 29231). (b) The volcanic plot illustrates the distribution of DEGs derived from comparing the gene expression profiles of women SAT in women with T2DM (n = 12) versus those without T2DM (n = 12) (GSE 29226). (c) The histogram presents the distribution and quantity of DEGs in VAT and SAT, with red indicating upregulated genes and blue indicating downregulated genes; (d) In the Venn diagram, the red circles represent DEGs specific to VAT, the blue rectangles represent DEGs specific to SAT, the overlapping areas indicate shared DEGs (n = 55), while the non-overlapping sections denote VAT-specific DEGs (n = 741) and SAT-specific DEGs (n = 273), respectively.

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  Figure 2.. Perform GO enrichment analysis of shared DEGs, VATspecific DEGs, and SAT-specific DEGs in women VAT and SAT gene expression profiles using metascape. Five GO enrichment results were displayed in each term for biological processes (BP), cellular components (CC), and molecular functions (MF) (if enough), with p < 0.01. (a) GO enrichment results of shared DEGs with the same expression trends in VAT and SAT(n = 37). (b) GO enrichment results of shared DEGs with the different expression trends (upregulated in one type and downregulated in the other at type) in VAT and SAT (n = 18). (c, d) GO enrichment analysis of DEGs with VAT-specific DEGs upregulation (n = 642) or downregulation (n = 99). (e, f) GO enrichment analysis of DEGs with SAT-specific DEGs upregulation (n = 78) or downregulation (n = 195).

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  Figure 3.. Perform KEGG enrichment analysis of shared DEGs, VAT-specific DEGs, and SAT-specific DEGs in women VAT and SAT gene expression profiles usingMetascape. Each term displays 10 enriched KEGG pathways, with p < 0.01 as the selection criterion. (a) KEGG analysis of shared DEGs(n = 55). (b) KEGG analysis of VAT-specific DEGs (n = 741). (c) KEGG analysis of SAT-specific DEGs (n = 273).

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  Figure 4.. Use STRING to analyze the shared DEGs, VAT-specific DEGs, and SAT-specific DEGs in the women VAT and SAT gene expression profiles, and visualize them using Cytoscape, displaying the top 10 hub genes in each term. (a)The top 10 hub genes in shared DEGs. (b) The top 10 hub genes in VAT-specific DEGs. (c) The top 10 hub genes in SAT-specific DEGs.

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  Figure 5.. Immunoinfiltration analysis of DEGs in 22 immune cell subtypes in women VAT and SAT using CIBERSORTx. (a, b) block diagram and cumulative histogram show the difference in immune cell infiltration in VAT between diabetes patients (n = 12) and non-diabetes patients (n = 12). (c, d) block diagram and cumulative histogram show the difference in immune cell infiltration in SAT between diabetes patients (n = 12) and non-diabetes patients (n = 12). *p < 0.05 **p < 0.01.

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  Figure 6.. Correlation matrix of infiltration degree of 22 immune cells and hub DEGs in women VAT and SAT using Sangerbox. Red represents a positive correlation, blue represents a negative correlation, and darker colors represent a stronger correlation. (a) Select the top 10 hub genes in shared DEGs and the top 10 hub genes in VAT-specific DEGs to generate a heatmap of their correlation with the degree of immune cell infiltration. (b) Select the top 10 hub genes in shared DEGs and the top 10 hub genes in SAT-specific DEGs to generate a heatmap of their correlation with the degree of immune cell infiltration.