Characterisation of type 2 diabetes progression with regulatory network

Abstract

Type 2 diabetes develops due to beta cell exhaustion with accompanying decrease in insulin secretion, leading to hyperglycemia and eventual damage of nerve, kidney, and eye tissues. It is usually preceded by metabolic alterations related to insulin signaling, inflammatory pathways, or intracellular glucose processing, encompassed as metabolic syndrome. We propose a regulatory network for components of pancreatic-beta cells playing an essential role in the disease. The network interactions are expressed as continuous fuzzy logic propositions. The dynamical modeling of the network allows to portray the disease progression as a transit between steady states associated to health, metabolic syndrome, and diabetes, each state defined by specific expression patterns of the network components. Transitions between equilibrium states are due to altered expression or functional exhaustion associated to modifications of characteristic decay rates of cellular components. This approach let us identify functional modules that may eventually drive the transit from health to diabetes. The analysis reveals that underexpression of protein kinase B and X-box binding protein 1, with concomitant overexpression of lipopolysaccharides and thioredoxin interacting protein are key factors in the transition from health to disease.