Gene regulatory network reveals oxidative stress as the underlying molecular mechanism of type 2 diabetes and hypertension

Abstract

BackgroundThe prevalence of diabetes is increasing worldwide. It has been long known that increased rates of inflammatory diseases, such as obesity (OBS), hypertension (HT) and cardiovascular diseases (CVD) are highly associated with type 2 diabetes (T2D). T2D and/or OBS can develop independently, due to genetic, behavioral or lifestyle-related variables but both lead to oxidative stress generation. The underlying mechanisms by which theses complications arise and manifest together remain poorly understood. Protein-protein interactions regulate nearly every living process. Availability of high-throughput genomic data has enabled unprecedented views of gene and protein co-expression, co-regulations and interactions in cellular systems.MethodsThe present work, applied a systems biology approach to develop gene interaction network models, comprised of high throughput genomic and PPI data for T2D. The genes differentially regulated through T2D were 'mined' and their 'wirings' were studied to get a more complete understanding of the overall gene network topology and their role in disease progression.ResultsBy analyzing the genes related to T2D, HT and OBS, a highly regulated gene-disease integrated network model has been developed that provides useful functional linkages among groups of genes and thus addressing how different inflammatory diseases are connected and propagated at genetic level. Based on the investigations around the 'hubs' that provided more meaningful insights about the cross-talk within gene-disease networks in terms of disease phenotype association with oxidative stress and inflammation, a hypothetical co-regulation disease mechanism model been proposed. The results from this study revealed that the oxidative stress mediated regulation cascade is the common mechanistic link among the pathogenesis of T2D, HT and other inflammatory diseases such as OBS.ConclusionThe findings provide a novel comprehensive approach for understanding the pathogenesis of various co-associated chronic inflammatory diseases by combining the power of pathway analysis with gene regulatory network evaluation.

Serum Levels of High-sensitivity C-Reactive Protein at Admission Are More Strongly Associated with Poststroke Depression in Acute Ischemic Stroke than Homocysteine Levels

“…Inflammation and oxidative stress are inextricably connected in physiologic as well as disease states. In certain chronic disease states, both of these systems remain activated and may, indeed, form a positive self-sustaining feedback loop or a Bco-activation^state [44]. Over time, such co-activation may lead to a higher risk of depression [5].…”

Understanding Genetic Heterogeneity in Type 2 Diabetes by Delineating Physiological Phenotypes:SIRT1and its Gene Network in Impaired Insulin Secretion

“…In a computational analysis which aimed to evaluate the interaction between these genes, EP300 emerged as a central node connected with 30 other nodes through 135 edges, which included SIRT1, PGC-1α, and TCF7L2. EP300 has been identified as a key regulator in T2D through a generegulatory network cascade, with oxidative stress as the molecular mechanism leading to T2D and hypertension [63]. β-catenin interaction with TCF7L2 and nuclear co-activators such as EP300 is known to result in the stimulation of Wnt or -β-cat/TCF downstream target gene transcription [64,65].…”

“…EP300 emerged as the central node connected with 30 nodes through 135 edges, which included SIRT1, PGC-1α, and TCF7L2 (Figure 1). Recently, EP300 has been identified through a gene regulatory network cascade as a key regulator in T2D; it was linked to oxidative stress as molecular mechanism in the pathogenesis of T2D and hypertension, and generated the co-regulated network of insulin signaling [63]. β-catenin interaction with TCF7L2 and nuclear co-activators, such as EP300, has been known to result in the simulation of Wnt or β-cat/TCF downstream target gene transcription [64,65].…”

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences

“…Other recent applications of systems biology of relevance to the nutritional sciences are network models of human disease (24), human metabolic diseases (25), and other models related to T2D (26,27). Using the Online Mendelian Inheritance in Man database (28) to source disease genes and genetic disorders, Goh et al (24) created both a human disease network where diseases were linked if they shared a gene that had mutations in both disorders and a disease gene network where genes were linked if they associated with the same disorder.…”