Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications

Abstract

Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the ANDSystem that provides automatic network reconstruction and analysis based on text mining. The network of GV consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. Cardiovascular system, pancreas, adipose and muscle tissues, gastrointestinal tract, and kidney were recognized as the loci with the highest expression of GV-related genes. According to Gene Ontology enrichment analysis, these genes are associated with insulin secretion, glucose metabolism, glycogen biosynthesis, gluconeogenesis, MAPK and JAK-STAT cascades, protein kinase B signaling, cell proliferation, nitric oxide biosynthesis, etc. GV-related genes were found to occupy central positions in the networks of diabetes complications (cardiovascular disease, diabetic nephropathy, retinopathy, and neuropathy) and were associated with response to hypoxia. Gene prioritization analysis identified new gene candidates (THBS1, FN1, HSP90AA1, EGFR, MAPK1, STAT3, TP53, EGF, GSK3B, and PTEN) potentially involved in GV. The results expand the understanding of the molecular mechanisms of the GV phenomenon in diabetes and provide molecular markers and therapeutic targets for future research.

Glucose Variability: How Does It Work?

“…The network consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. GV-related molecules were involved in glucose metabolism, intracellular signaling, cell proliferation and other biochemical/physiological processes; they were identified in the central positions of the gene networks of diabetic vascular complications [161].…”

Integrated Bioinformatics-Based Identification of Potential Diagnostic Biomarkers Associated with Diabetic Foot Ulcer Development

“…For example, one prior study identified Prenylcysteine oxidase 1 (PCYOX1), beta-ala-his dipeptidase (CNDP1), and extracellular matrix protein 1 (ECM1) as valuable diagnostic biomarkers associated with the incidence of gestational diabetes [17]. Saik et al further found the JAK-STAT, MAPK, and protein kinase B signaling pathway to be closely linked to diabetes complications and hypoxia responses [18]. The GO and KEGG analyses conducted in this study suggested the top DEGs to be enriched in sarcomere organization, muscle filament sliding, and the regulation of cardiac conduction, potentially playing a role in regulating angiogenesis.…”

Integrated analysis reveals the participation of IL4I1, ITGB7, and FUT7 in reshaping the TNBC immune microenvironment by targeting glycolysis

“…Notably, FN1, a gene involved in cell adhesion and migration processes, including embryogenesis, wound healing, blood coagulation, host defense, and metastasis, appears to be the centre of the PPI network. Previous studies suggested that FN1 is a major ECM component secreted by various epithelial or mesenchymal cell types in both physiologic and pathophysiologic situations in response to high glucose stimulations [22][23][24].…”