Circulating MicroRNAs as Biomarkers of Insulin Resistance

Background: Insulin resistance (IR) is a common and complicated metabolic disorder. Objective: The purpose of this study was to select several novel circulating microRNA biomarkers for IR by high-throughput sequencing and integrated bioinformatics analysis. Methods: The plasma microRNA expression profiles in plasma of 5 patients with IR and 5 healthy controls were compared through high-throughput sequencing technology. Target genes of the identified differentially expressed microRNAs (DEMs) were predicted using TargetScan and miRDB database. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to conduct pathway and function enrichment analysis. A protein-protein interaction network was constructed based on STRING database and the module analyze was performed using Cytoscape. Least Absolute Shrinkage and Selectionator Operator (LASSO) regression was conducted to achieve to further microRNA screening. Results: 2 up-regulated and 36 down- regulated DEMs were identified in the plasma samples of IR patients as compared with the healthy control. Functional enrichment analyses in the GO and KEGG databases indicated these DEMs are significantly enriched in biological processes like regulation of mitogen-activated protein kinase activity, cellular response to steroid hormone stimulus and so on. Finally, 6 hub microRNA (hsa-miR-526b-5p, hsa-miR-487a-3p, hsa-miR-409-3p, hsa-miR-1343-3p, hsa-miR-6809-5p and hsa- miR-6810-5p) were identified to be associated with IR. Conclusion: Our findings identified several novel circulating miRNAs highly associated with IR which may serve as the potential early diagnosis biomarkers and therapeutic intervention targets.