Obesity negatively affects the entire body – no organ system is left untouched. It increases a person’s risk of type 2 diabetes, high blood pressure, depression, certain cancers and many other conditions. If the current trend of expanding waistlines continues, the U.S. Centers for Disease Control and Prevention estimates that at least one in five Americans will be diabetic by the year 2050.

The goal of the Translational Research Institute for Metabolism and Diabetes (TRI), a collaboration between Florida Hospital and Sanford-Burnham, is to alter this course by translating basic scientific discoveries in the laboratory to usable information and products that improve the diagnosis and treatment of human diseases – especially obesity and diabetes.

“At the moment, there is a big gap between what we know and what we want to know about human metabolism, obesity and diabetes. Our ultimate goal in translational research is to bridge that gap,” says Dr. Steven R. Smith, TRI’s scientific director and professor at Sanford-Burnham. “As basic researchers continue to unravel the molecular underpinnings of these diseases, TRI will be conducting proof-of-concept experiments to validate new drug targets and test new therapies for safety and efficacy.”

When it opens in January 2012, the TRI’s new three-story facility in Orlando, Florida will contain a research clinic, imaging technology, a biorepository for sample collection and storage, and several other resources for metabolic studies. But the facility’s highlight will be the calorimeter rooms – small dormitory-style rooms outfitted with a bed, treadmill and toilet. These whole-room calorimeters will allow the TRI staff to measure fat and carbohydrate oxidation and energy expenditure as a person goes about his or her normal life – sleeping, eating, walking, etc. As the patient exercises on the treadmill, scientists will be able to measure his or her oxygen consumption and calories burned without using invasive tubing or sensors. This approach will provide superior comfort – and therefore generate more accurate data – during exercise.

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