Human Metabolic Flexibility: Its Role in Energy Regulation and Obesity
Condition: Metabolic Flexibility
MeSH terms: Obesity
Study type: Interventional

Summary: 
      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 hypothesize that the measure of an
      individual's fraction of energy mobilized or deposited as protein (P-ratio), contributes
      towards an obese morphology and may essentially form a novel approach in understanding the
      etiology, management and treatment of obesity. In addition, there is a general perception
      that the consumption of sugar sweetened foods and beverages are one of the major causes of
      obesity. This study aims to understand metabolic flexibility and the glycemic index of diets
      in the etiology of obesity. Individual metabolic flexibility may be the key factor that
      predisposes an individual to obesity. This study is carried out to determine the P-ratio in
      human subjects.
    

Detailed description: 
      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.
    

Intervention name(s): Low Protein
Intervention type(s): Other
Intervention description(s): Low protein/protein-free diet for 3 days (Day 1, 2 and Day 3) in order to deplete the label protein pool. The diet provided will meet the daily energy requirements of all the subjects.
Intervention model: Single Group Assignment
Masking: None (Open Label)
Primary purpose: Other
Keywords: BMR; P-ratio; Tissue partitioning