Modeling Pathogenesis of Type 2 Diabetes

National Institute Of Diabetes And Digestive And Kidney Diseases

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Abstract

In previous reports we have described our model for T2D pathogenesis. It builds on the foundational model of Topp et al (J. Theor. Biol. 2000; 206(4):605-19), which posited that moderate but persistent increases in blood sugar mediate negative feedback to increase insulin secretion by increasing beta-cell mass, either by increased replication or reduced apoptosis. However, if that increase fails to occur or is inadequate to restore normal glucose homeostasis, further increases in glucose raise it to a level where it becomes toxic to beta cells. Instead of negative feedback (homeostasis), there is then positive feedback (anti-homeostasis), which causes a catastrophic loss of beta-cell mass and T2D. In addition to quantitative refinements to more accurately reflect the measured dynamics of T2D progression in humans and rodents, we included regulation of beta-cell function, in two distinct forms, in addition to mass. Data show that such changes are more rapid and more extensive than changes in mass, especially for humans, for whom beta-cell replication is very slow after adolescence. The model captures many key features of T2D progression, including the sudden deterioration of glucose control after a long period of gradual worsening (threshold behavior) and the fact that prevention is generally much easier than reversal, but drastic interventions, such as bariatric surgery and extreme caloric restriction can reverse established disease. The model has been further extended to track fasting and post-prandial glucose, rather than just average daily glucose, which is important because individuals differ in which aspect of glucose deviates first from normal. In addition, the model can be paused at any point during progression over years to simulate glucose tolerance tests, both oral (OGTT) and intravenous (IVGTT). We also used the model to investigate the hypothesis that high insulin causes insulin resistance rather than the other way around, as we assume in our model. Although there is strong evidence that hyperinsulinemia does contribute to insulin resistance, model simulations suggest that this plays at best a minor role in the development of diabetes. We continued to provide support to the long-term project of Dr. Anne Sumner (NIDDK) to develop methods of screening for T2D and T2D risk in Africa, where there are many challenges to using standard methods. We contributed to a study led by Dr. Sumner of African immigrants living in the US as a group of interest in their own right as well as an accessible proxy for Africans living in Africa. Diabetes in Africa is of great interest because it is growing at the highest rate of world regions and affects both obese populations living in rapidly industrializing cities and lean non-urban populations living. The study was designed to assess whether insulin resistance or beta-cell failure is the predominant impairment leading to type 2 diabetes by examining the prevalence of abnormal glucose tolerance (Abnl-GT), defined as having high fasting or high two-hour glucose during an OGTT with or without insulin resistance, defined as the lowest quartile of the Matsuda index. Abnl-GT in the absence of insulin resistance was assumed to result from beta-cell failure. 38% of the individuals with Abnl-GT were found to have insulin resistance, which suggests that this is the less common pathway among Africans. They also had higher body mass index (BMI) and lipid profiles that predispose to cardiovascular disease, including low HDL cholesterol, high triglycerides, and smaller LDL and HDL particles, which would indicate a greater need for interventions targeted at dyslipdemia. The work has been published in Ref. #1. Although originally designed as longitudinal model for the progression from normal glucose tolerance through pre-diabetes to diabetes, we have found that the model can be applied to assess insulin resistance and beta-cell function at any stage along the process by fitting data from OGTTs. We have found that the estimates correlate and agree reasonably well with those from other widely used, but more invasive and costly approaches. One is the frequently sampled intravenous glucose tolerance test, which requires more than 20 glucose and insulin samples, which are then analyzed using the Bergman-Cobelli Minimal Model (MINMOD). Another is the hyperinsulinemic, euglycemic clamp, in which glucose is infused to maintain glucose at a fixed level in the face of simultaneous insulin infusion. This is technically challenging and takes up to four hours. OGTTs are much easier to implement and more cost-effective for large-scale clinical studies, so our model thus has the potential to enhance the value of such studies. We have also found that the disposition index, defined as the ratio of beta-cell function to insulin resistance, can be calculated from our model without the need to measure insulin, further benefiting large-scale clinical studies. A paper is in preparation. Cardiovascular disease is a major complication of obesity and impaired glucose-insulin regulation. This is a problem at the sub-clinical level already for obese, insulin-resistant youth people with obesity and insulin resistance. Our collaborators Stephanie Chung and Sheela Magge sought to determine the contributions of insulin resistance and hyperglycemia in a cohort of 155 obese youth classified as insulin sensitive, insulin resistant, or abnormal glucose tolerant by assessing the concentrations of good (HDL) and bad (LDL) cholesterol along with the distribution of lipid particle sizes. Profiles linked to atherosclerosis were associated with insulin resistance, as measured by both MINMOD and our model, but not with glucose intolerance. The work has been published in ref. #2.