Regulatory Action of Plasma from Patients with Obesity and Diabetes towards Muscle Cells Differentiation and Bioenergetics Revealed by the C2C12 Cell Model and MicroRNA Analysis

Hub genes, key miRNAs and interaction analyses in type 2 diabetes mellitus: an integrative in silico approach

Diabetes is a rising global metabolic disorder and leads to long-term consequences. As a multifactorial disease, the gene-associated mechanisms are important to know. This study applied a bioinformatics approach to explore the molecular underpinning of type 2 diabetes mellitus through differential gene expression analysis. We used microarray datasets GSE16415 and GSE29226 to identify differentially expressed genes between type 2 diabetes and normal samples using R software. Following that, using the STRING database, the protein-protein interaction network was constructed and further analyzed by Cytoscape software. The EnrichR database was used for Gene Ontology and pathway enrichment analysis to explore key pathways and functional annotations of hub genes. We also used miRTarBase and TargetScan databases to predict miRNAs targeting hub genes. We identified 21 hub genes in type 2 diabetes, some showing more significant changes in the PPI network. Our results revealed that GLUL, SLC32A1, PC, MAPK10, MAPT, and POSTN genes are more important in the PPI network and can be experimentally investigated as therapeutic targets. Hsa-miR-492 and hsa-miR-16-5p are suggested for diagnosis and prognosis by targeting GLUL, SLC32A1, PC, MAPK10, and MAPT genes involved in the insulin signaling pathway. Insight: Type 2 diabetes, as a rising global and multifactorial disorder, is important to know the gene-associated mechanisms. In an integrative bioinformatics analysis, we integrated different finding datasets to put together and find valuable diagnostic and prognostic hub genes and miRNAs. In contrast, genes, RNAs, and enzymes interact systematically in pathways. Using multiple databases and software, we identified differential expression between hub genes of diabetes and normal samples. We explored different protein-protein interaction networks, gene ontology, key pathway analysis, and predicted miRNAs that target hub genes. This study reported 21 significant hub genes and some miRNAs in the insulin signaling pathway for innovative and potential diagnostic and therapeutic purposes.

Role of MicroRNAs in Dietary Interventions for Obesity and Obesity-Related Diseases

Obesity and related metabolic syndromes pose a serious threat to human health and quality of life. A proper diet is a safe and effective strategy to prevent and control obesity, thus maintaining overall health. However, no consensus exists on the connotations of proper diet, and it is attributed to various factors, including "nutritional dark matter" and the "matrix effect" of food. Accumulating evidence confirms that obesity is associated with the in vivo levels of miRNAs, which serve as potential markers and regulatory targets for obesity onset and progression; food-derived miRNAs can regulate host obesity by targeting the related genes or gut microbiota across the animal kingdom. Host miRNAs mediate food nutrient-gut microbiota-obesity interactions. Thus, miRNAs are important correlates of diet and obesity onset. This review outlines the recent findings on miRNA-mediated food interventions for obesity, thereby elucidating their potential applications. Overall, we provide new perspectives and views on the evaluation of dietary nutrition, which may bear important implications for dietary control and obesity prevention.