The Metabolism, Energy Balance, and Obesity program supports basic and clinical studies related to energy balance and physiological mechanisms modulating weight gain, loss, and maintenance. Specific areas of interest include factors that affect energy regulation such as food choices, diet composition, food intake, eating behavior, appetite, satiety, body composition, nutrient partitioning, sedentary behavior, and physical activity. Other supported research topics include, but are not limited to, hormonal regulation of body composition, such as interactions between nutrition, exercise, and appetite-regulating hormones; circulating factors and their receptors involved in regulatory pathways controlling feeding behavior, satiety, and energy expenditure; interactions between the gut-brain axis and peripheral secretory metabolic signals (e.g., insulin, leptin, glucocorticoids, ghrelin, and other small bioactive peptides); integration of appetite-regulating and metabolic signals in the regulation of food intake and energy balance; the impact of circadian rhythms on nutrient sensing and food intake; and the impact of gustatory signals on food consumption and energy balance. Studies investigating the mechanism by which interventions, including drugs, devices, and surgery, affect food consumption or food preferences, physical activity, body composition, or other aspects of energy regulation are also supported by this program.
Also of interest are studies that use improved methods to assess body composition, examine health-risk factors with specific degrees of obesity or body composition, and determine the effects of exercise on body composition.
This program also supports studies that explore mathematical models contributing to the understanding of whole-body energy balance and metabolism as well as the metabolic pathways in cells, tissues, and organs. A particular focus of interest is on models that allow the integration of data gained from a variety of technical approaches, such as tracer studies, calorimetry, plasma hormone/cytokines, metabolomics, genomics, epigenomics, and proteomics, and on those models that would be of clinical utility, including prediction of plasma glucose levels in diabetes, nutritional partitioning, and weight management.