Glycemic Index and Brain Function

Overview

The investigators propose examine the effects of the dietary factor glycemic index (GI) on brain areas that control food intake and hunger. This knowledge could help design dietary approaches that decrease hunger, and thus promote new weight loss strategies.

Most individuals have great difficulty following reduced calorie diets because they experience increased hunger. This process is regulated by specific brain areas. Though many psychological and environmental factors are involved, physiological effects of diet may have a significant impact. The postprandial rise in blood glucose, quantified by the glycemic index (GI), is of particular interest. High GI meals elicit hormonal events that limit availability of metabolic fuels, causing hunger and overeating, especially in people with high insulin secretion. Our aim is to examine how postprandial changes after high versus low GI meals affect hunger and brain function in areas of intake control. Specifically, we speculate that obese individuals will demonstrate functional changes in brain areas of intake control and increased hunger after a high versus low GI meal. We will recruit obese, young adults and quantify their insulin secretion during a 2-hour oral glucose tolerance test. A brief practice MRI session will serve to familiarize the subjects with the scanning process. During the two test sessions, standardized test meals with high versus low GI will be given in a randomized, blinded cross-over design. Serial blood levels of hormones, metabolic fuels, and metabolites will be correlated with perceived hunger, and a perfusion MRI scan will be performed to assess brain activation during the late postprandial phase, at the nadir of blood sugar and insulin levels (4 hours postprandial). This work will inform an integrated physiological model relating peripheral postprandial changes to brain function and hunger. In addition, findings may provide evidence of a novel diet-phenotype, in which baseline clinical characteristics can be used to predict which weight loss diet will work best for a specific individual. Metabolite profiling might shed light on the mechanisms linking diet composition to brain function, and provide feasible clinical markers of the identified phenotype to facilitate translation into practice.

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