β-Cell dysfunction is an important factor in the development of hyperglycemia of type-2 diabetes mellitus, and pancreatic islet amyloidosis (IA) has been postulated to be one of the main contributors to impaired insulin secretion. The aim of this study was to evaluate the correlation of IA with metabolic parameters and its effect on islets of Langerhans remodeling and relative endocrine-cell volume in baboons. We sequenced the amylin peptide, determined the fibrillogenic propensities, and evaluated pancreatic histology, clinical and biochemical characteristics, and endocrine cell proliferation and apoptosis in 150 baboons with different metabolic status. Amylin sequence in the baboon was 92% similar to humans and showed superimposable fibrillogenic propensities. IA severity correlated with fasting plasma glucose (FPG) ( r = 0.662, P < 0.001) and HbA1c ( r = 0.726, P < 0.001), as well as with free fatty acid, glucagon values, decreased homeostasis model assessment (HOMA) insulin resistance, and HOMA-B. IA severity was associated with a decreased relative β-cell volume, and increased relative α-cell volume and hyperglucagonemia. These results strongly support the concept that IA and β-cell apoptosis in concert with α-cell proliferation and hypertrophy are key determinants of islets of Langerhans “dysfunctional remodeling” and hyperglycemia in the baboon, a nonhuman primate model of type-2 diabetes mellitus. The most important determinants of IA were age and FPG ( R ² = 0.519, P < 0.0001), and different FPG levels were sensitive and specific to predict IA severity. Finally, a predictive model for islet amyloid severity was generated with age and FPG as required variables.

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases worldwide, presenting a great challenge to the public health systems due to high morbidity and mortality, because of frequent micro-/macro-vascular complications. Many treatment options are now available, with different...

The association between the physio-pathological variables of type 2 diabetes (T2D) and gut microbiota composition suggests a new avenue to track the disease and improve the outcomes of pharmacological and non-pharmacological treatments. This enterprise requires new strategies to elucidate the metabolic disturbances occurring in the gut microbiome as the disease progresses. To this end, physiological knowledge and systems biology pave the way for characterizing microbiota and identifying strategies in a move toward healthy compositions. Here, we dissect the recent associations between gut microbiota and T2D. In addition, we discuss recent advances in how drugs, diet, and exercise modulate the microbiome to favor healthy stages. Finally, we present computational approaches for disentangling the metabolic activity underlying host-microbiota codependence. Altogether, we envision that the combination of physiology and computational modeling of microbiota metabolism will drive us to optimize the diagnosis and treatment of T2D patients in a personalized way.