Key result
Type 2 diabetes mellitus is associated with 238 differentially expressed genes in epicardial adipose tissue compared to non-diabetic controls, primarily enriched in inflammatory response and cytokine activity.
Why the study?
Peri-organ fat has emerged as a diagnostic and therapeutic target in metabolic diseases, motivating an exploration of epicardial adipose tissue transcriptome differences between diabetic and non-diabetic individuals.
Observational (n=19)
p-value: p=<0.01
EAT transcriptomic signatures in diabetes are hypothesis-generating; leaves open mechanistic validation and therapeutic targeting.
Background: In recent years, peri-organ fat has emerged as a diagnostic and therapeutic target in metabolic diseases, including diabetes mellitus. Here, we performed a comprehensive analysis of epicardial adipose tissue (EAT) transcriptome expression differences between diabetic and non-diabetic participants and explored the possible mechanisms using various bioinformatic tools. Methods: RNA-seq datasets GSE108971 and GSE179455 for EAT between diabetic and non-diabetic patients were obtained from the public functional genomics database Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were identified using the R package DESeq2, then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed. Next, a PPI (protein-protein interaction) network was constructed, and hub genes were mined using STRING and Cytoscape. Additionally, CIBERSORT was used to analyze the immune cell infiltration, and key transcription factors were predicted based on ChEA3. Results: By comparing EAT samples between diabetic and non-diabetic patients, a total of 238 DEGs were identified, including 161 upregulated genes and 77 downregulated genes. A total of 10 genes (IL-1β, CD274, PDCD1, ITGAX, PRDM1, LAG3, TNFRSF18, CCL20, IL1RN, and SPP1) were selected as hub genes. GO and KEGG analysis showed that DEGs were mainly enriched in the inflammatory response and cytokine activity. Immune cell infiltration analysis indicated that macrophage M2 and T cells CD4 memory resting accounted for the largest proportion of these immune cells. CSRNP1, RELB, NFKB2, SNAI1, and FOSB were detected as potential transcription factors. Conclusion: Comprehensive bioinformatic analysis was used to compare the difference in EAT between diabetic and non-diabetic patients. Several hub genes, transcription factors, and immune cell infiltration were identified. Diabetic EAT is significantly different in the inflammatory response and cytokine activity. These findings may provide new targets for the diagnosis and treatment of diabetes, as well as reduce potential cardiovascular complications in diabetic patients through EAT modification.
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Yang et al. (2022) conducted an observational in Type 2 diabetes mellitus (n=19). Type 2 diabetes mellitus vs. Non-diabetic patients was evaluated on Differentially expressed genes (DEGs) (p=<0.01). Type 2 diabetes mellitus is associated with 238 differentially expressed genes in epicardial adipose tissue compared to non-diabetic controls, primarily enriched in inflammatory response and cytokine activity.
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