Human Metabolic Flexibility: Its Role in Energy Regulation and Obesity

Obesity is commonly described as a consequence of excess calorie intake. Conventionally, the physiological variables that have been of extensive interest are food intake and energy expenditure. Despite decades of research on factors influencing intake and expenditure, to date, no compelling theory has been promulgated to explain why certain humans are more susceptible to weight gain than others. The investigators believe that a measure of an individual's metabolic flexibility towards an obese morphology is essential and forms a novel approach in understanding the etiology, management and treatment of obesity. Payne and Dugdale developed a simple model of energy balance, based on dividing the human body into four compartments, namely "fast" lean tissue (protein), "slow" lean tissue (protein), structural fat, and tissue fat. Notionally, these are considered to act as four separate compartments which interconnect with each other. Body weight is thus simply the sum of the four weights, and metabolic rate is the sum of the separate compartment rates. Any energy deficit in the "balancing compartment" is met by withdrawing tissues from the neighboring fat and lean (muscle) compartments in a proportion which is fixed for any individual. The observed human variability in both the susceptibility to gain weight or to lose weight efficiently on a calorie surplus or restricted diet is thus afforded by using the model developed by Payne and Dugdale for energy balance. P-ratio is calculated on the assumption that body protein is 16% nitrogen and has a metabolizable energy value of 16.7 kJ/g. Thus P-ratio can be calculated as: P- ratio= urinary nitrogen excretion x 6.25 x 16.7 / total energy expenditure. The regulatory control of energy-partitioning between protein and fat is highly variable between individuals, but constant within the same subject. It is this variability in tissue partitioning between lean (protein) and fat that is central to the regulation of body weight. This implies that for a given individual, there is a fixed partitioning of energy between lean (protein) and fat tissue when excess calories are consumed. Using the results of the classical study of human semi-starvation by Keys et al, Dugdale and Payne calculated the individual pattern of tissue mobilization (P-ratio) in these subjects. The P-ratio ranged from 0.03 to 0.60. On the basis of these data, they classified individuals into "metabolically lean" and "metabolically fat". A P-ratio of 0.03 means approximately 3% of the energy loss from this subject's body tissues was derived from protein catabolism and 97% from fat. Thus during excess calorie consumption, 3% of the calories will be deposited as protein and 97% as fat ("metabolically fat"). Similarly a subject with a P-ratio of 0.60 will deposit 60% calories as protein and only 40% as fat ("metabolically lean"). This stratification of "metabolic type" is a novel approach in obesity research, treatment and its management. The current method for the determination of P-ratio is based on subjects undergoing total starvation/fasting, e.g. complete food restriction, ad libitum water intake. This is a highly impractical approach. The investigator's proposal is to develop a more convenient and practical methodology to determine the P-ratio. An individual's Basal Metabolic Rate after a 10 hour overnight fast will approximate the denominator of the P-ratio. Henry et al reported a quantitative relationship between a fasting urine nitrogen loss (FUNL) and obligatory urinary nitrogen loss (OUNL), the ratio FUNL: OUNL remained close to 1.5. OUNL can be measured in urine when a subject is fed a protein free diet. With these two measures, the P-ratio of an individual can be estimated. OUNL is the protein lost in the urine when fed a zero or non-protein diet and fasting urinary loss is the nitrogen lost during starvation/ fasting (FUNL). The investigator's proposed study will be the first real-time study that will utilize the obligatory urine nitrogen loss and BMR to quantitate human P-ratio.