Identification of biomarkers, pathways and potential therapeutic agents for white adipocyte insulin resistance using bioinformatics analysis

Abstract

For the better understanding of insulin resistance (IR), the molecular biomarkers in IR white adipocytes and its potential mechanism, we downloaded two mRNA expression profiles from Gene Expression Omnibus (GEO). The white adipocyte samples in two databases were collected from the human omental adipose tissue of IR obese (IRO) subjects and insulin-sensitive obese (ISO) subjects, respectively. We identified 86 differentially expressed genes (DEGs) between the IRO and ISO subjects using limma package in R software. Gene Set Enrichment Analysis (GSEA) provided evidence that the most gene sets enriched in kidney mesenchyme development in the ISO subjects, as compared with the IRO subjects. The Gene Ontology (GO) analysis indicated that the most significantly enriched in cellular response to interferon-gamma. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the DEGs were most significantly enriched in cytokine-cytokine receptor interaction. Protein–Protein Interaction (PPI) network was performed with the STRING, and the top 10 hub genes were identified with the Cytohubba. CMap analysis found several small molecular compounds to reverse the altered DEGs, including dropropizine, aceclofenac, melatonin, and so on. Our outputs could empower the novel potential targets to treat omental white adipocyte insulin resistance, diabetes, and diabetes-related diseases.

Keywords

• insulin resistance
• omental adipocyte
• degs
• hub gene
• bioinformatics