What implications do biomarkers have for the prediction and treatment of Type 2 diabetes?

Abstract

Type 2 diabetes (T2D) is an escalating health problem of enormous proportions. Current treatment is insuff icient, as evidenced by the devastating complications that many patients encounter. In this editorial, I present my views on how we may obtain a more integrated view of the disease to facilitate more effective interventions using a combination of biomarkers. This article begins with a background about what is currently known about the pathophysiology. T2D is characterized by chronic hyper­ glycemia. Despite extensive research, the molecular causes and the sequence of patho­ physiological events leading to the disease are largely unknown. Reduced insulin sensitivity in target tissues is a key feature; however, only 20% of insulin­resistant individuals develop T2D [1], as the b­cells manage to compensate for the increased insulin demands in the majority of individuals. Consequently, a key issue is to elucidate why the b­cells fail to compensate and increase the insulin output. Several hypotheses have been proposed, involving both a reduction in b­cell mass and functional failure [2–4]. Whether there is a specific tipping point, in analogy to the Starling curve for heart failure, leading to incompensation of the insulin secretion capacity is not known. An equally interesting topic would perhaps be to study why some individuals in fact manage to compensate for severe insulin resistance with adequate insulin output. In addition to b­cell failure, the most commonly studied components in the pathophysiology of T2D include but are not limited to: low­grade inf lammation in metabolically active tissues; ER stress; impaired glucose uptake in muscle and fat; elevated hepatic glucose production; increased lipolysis; impaired response to the incretin hormones GLP­1 and Anders Rosengren* Editorial