Gastric Emptying and Glycemia in Type 1 Diabetes Mellitus
Approximately 50% of patients with type 1 diabetes mellitus (T1D) have delayed or rapid gastric emptying (GE), which can be measured with scintigraphy or the 13C-Spirulina gastric emptying breath test (GEBT), which is an extensively validated, FDA-approved, office-based test that does not entail radiation. In DM, abnormal GE is usually unrecognized because most patients have limited GI symptoms and GE is not routinely measured. Abnormal GE affects the rate of nutrient absorption; glucagon-like peptide-1 (GLP1) delays GE and improves glycemic control in type 2 DM (T2D), while acceleration of GE increases postprandial glycemia in T1D and T2D. However, the effects of innate (i.e., not pharmacologically mediated) delayed GE on glycemia in T1D are unclear. Our overall long-term objective is to utilize GE to optimize insulin delivery (i.e., dose and timing) with or without artificial pancreas (AP) automated insulin delivery systems and thereby improve glycemic control in DM. Existing models for deconvolving glucose metabolism in DM do not incorporate terms for the rate of GE. Hence, we modified an existing model of oral glucose absorption, added terms for GE to the equations, and incorporated a submodel of insulin diffusion to predict postprandial continuous glucose monitoring (CGM) glucose levels in T1D. Our preliminary findings suggest that subcutaneous glucose values, measured with CGM sensors, for 4 hours after a meal can be accurately predicted with a mathematical model that incorporates fasting glucose, ingested calories, insulin delivery, and GE measured with scintigraphy or a GEBT. The predicted postprandial glucose values approximate closely to actual postprandial CGM glucose values only if the equations use the actual GE values for that patient. This proposal is designed to refine and finalize mathematical models that incorporate GE measured with scintigraphy (Aim 1) and a GEBT (Aim 2) to predict postprandial CGM glucose levels, to assess the closeness of fit between predicted and actual postprandial CGM values, and to establish the importance of GE values to achieving accurate predictions. These models will be developed and validated in existing datasets of T1D patients in whom GE and CGM were simultaneously evaluated. Taken together, we anticipate that these studies will establish that GE, evaluated with scintigraphy or a GEBT, is essential for predicting postprandial glycemia in T1D. If successful, the next steps will be to incorporate GE in insulin hybrid closed loop systems, enabled by our ongoing collaborations with one of the leading AP groups in the world.