Bioinformatics analysis identifies key secretory protein-encoding differentially expressed genes in adipose tissue of metabolic syndrome
收藏Taylor & Francis Group2025-12-12 更新2026-04-16 收录
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https://tandf.figshare.com/articles/dataset/Bioinformatics_analysis_identifies_key_secretory_protein-encoding_differentially_expressed_genes_in_adipose_tissue_of_metabolic_syndrome/28227194/1
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The objective of this study was to identify key secretory protein-encoding differentially expressed genes (SP-DEGs) in adipose tissue in female metabolic syndrome, thus detecting potential targets in treatment. We examined gene expression profiles in 8 women with metabolic syndrome and 7 healthy, normal body weight women. A total of 143 SP-DEGs were screened, including 83 upregulated genes and 60 downregulated genes. GO analyses of these SP-DEGs included proteolysis, angiogenesis, positive regulation of endothelial cell proliferation, immune response, protein processing, positive regulation of neuroblast proliferation, cell adhesion and ER to Golgi vesicle-mediated transport. KEGG pathway analysis of the SP-DEGs were involved in the TGF-beta signalling pathway, cytokine‒cytokine receptor interactions, the hippo signalling pathway, Malaria. Two modules were identified from the PPI network, namely, Module 1 (DNMT1, KDM1A, NCoR1, and E2F1) and Module 2 (IL-7 R, IL-12A, and CSF3). The gene DNMT1 was shared between the network modules and the WGCNA brown module. According to the single-gene GSEA results, DNMT1 was significantly positively correlated with histidine metabolism and phenylalanine metabolism. This study identified 7 key SP-DEGs in adipose tissue. DNMT1 was selected as the central gene in the development of metabolic syndrome and might be a potential therapeutic target.
提供机构:
Liu, Xuan; Yuan, Weijie; Guo, Yunshan; Zhou, Jiandong
创建时间:
2025-01-17



