In order to investigate how energy expenditure changes with over and underfeeding the following studies are underway. In one study, after careful calibration of weight maintenance EE, individuals undergo a series of measurements of 24 hour EE in a respiratory chamber in which they are fasting or overfed (by 200% of weight maintenance needs) a series of diets that vary in macronutrient content. This is to further investigate whether low or high protein diets may improve the detection of recruitment of adaptive thermogenesis. In addition, behavioral, metabolic and hormonal tests are performed to examine associated characteristics and to investigate the mechanism of the changes in EE. These individuals are followed up long term (up to 7 years) to investigate whether these energy expenditure phenotypes predict weight change. We have demonstrated that the change in energy expenditure with fasting and with overfeeding is reproducible. We have had 83 participants complete the core portion of this study. We have found a negative association between the percent change in EE with overfeeding with the percent change in EE with fasting indicating the presence of thrifty versus spendthrift energy expenditure phenotypes. We also found that high carbohydrate and high protein overfeeding increased EE the most, while low protein overfeeding increased EE the least. At 6 months, we found that individuals with greater decrease in EE with fasting and less increase in EE with low protein overfeeding gained more weight. These data again indicate the presence of more thrifty phenotypes. However we also found that higher EE change in response to high carbohydrate diet predicted greater weight gain and that those with higher EE after high carbohydrate overfeeding were also hungrier. Thus, high carbohydrate overfeeding may stimulate energy sensing mechanisms that drive food intake. We have also found that the macronutrient composition largely determines fuel preference (carbohydrate versus lipid oxidation rates) and that extrinsic dietary factors account for approximately 20% of the variance in these measurements. However, there is a strong intra-individual component to fuel preference, in particular, with carbohydrate oxidation rates. We have been investigating the mechanisms underlying these energy expenditure changes to fasting and overfeeding. We found that core body temperature correlated with changes in EE in response to fasting, such that individuals with lower core body temperature have a greater decrease in EE with fasting. Urinary epinephrine concentrations increase during fasting, and individuals with higher urinary EE have less decrease in energy expenditure with fasting. Fibroblast growth factor 21 (FGF 21) is secreted by the liver and increases EE in rodent models. In humans FGF 21 increases with low protein diets. We found that FGF21 increased following low protein overfeeding and the greater the change in FGF 21 concentrations the more the %EE increased with low protein overfeeding. Moreover, in change in FGF 21 concentrations with low protein overfeeding was associated with weight change at 6 months, and mediated the association between greater increase in %EE with low protein overfeeding and weight change at 6 months. . We are continuing long term follow-up of those with these energy expenditure measurements and investigating the role, thyroid, gastrointestinal and adipocyte hormones as possible mediators of these EE changes and or weight change. Based on the difference in energy expenditure measured during fasting and overfeeding, the thermic effect of food (TEF) can be calculated. We have found that TEF is inversely associated with adiposity. Thus TEF may predispose to weight gain or be an adaptation to increased bodyweight. As increased adiposity may insulate against trans-abdominal heat loss which may increase TEF, we are investigating the effect of central insulation on the EE and TEF changes associated with overfeeding. Fifteen of the needed 20 participants have completed this part of the study. Because of the recent discovery of the presence of brown fat in humans and its possible role in thermogenesis, we performed positron emission scans with labeled glucose. As brown fat is activated by cold temperatures, we have established that we can visualize brown fat after 2 hours of exposure to 16 degrees Celsius. We then currently investigated whether individuals with visualized brown fat after cold exposure, have visualized brown fat after overfeeding. Following demonstration of visible brown fat after cold exposure individuals were overfed by 200% of their energy needs using a high fat normal protein diet while in our metabolic chamber. The next morning they underwent a PET-CTscan; this was performed in some individuals prior to breakfast (approximately 12 hours after their last overfeeding meals) and in some individuals following a similar overfeeding breakfast (approximately 4 hours after their last meal). We found no evidence of activation of brown fat with overfeeding following a high fat overfeeding, indicating that brown fat does not mediate the increased energy expenditure associated with overfeeding. Based on evidence of brown fat activation with high carbohydrate overfeeding, we have used the same overfeeding paradigm with our high carbohydrate overfeeding diet followed by PET-CT scans. In preliminary analysis, we have found evidence of brown activation with this diet. We are confirming these results and are working on a follow-up study to confirm and investigate the role of overfeeding in brown fat activation. In a related study, after measurement of EE with over and underfeeding, and also after undergoing a series of metabolic and behavioral testing (including biopsies of muscle and fat), individuals are admitted for 6 weeks of an inpatient dietary protocol involving underfeeding (for overweight and obese individuals) or overfeeding (for lean, obesity resistant individuals). During the inpatient study, all aspects of food intake, energy expenditure, and energy loss are carefully measured to determine if differences in weight gain or loss can be attributed to recruitment of adaptive thermogenesis or other factors. We have currently completed 12 individuals who have undergone the weight loss study. In these individuals, we found that the calculated energy deficit (based on measured loss of fat mass and fat free mass) did not significantly differ from the deficit as calculated based on energy intake, measured energy expenditure, and stool and urine losses. We did find that less decrease in 24hEE with fasting was associated with greater weight loss in this controlled inpatient study. Participants with the greatest accumulated measured energy deficit lost the most weight, and greater measured energy deficit was also associated with less 24h EE decrease with fasting. Consistent with our natural history study described above, these results indicate the presence of spendthrift versus thrifty phenotypes even in obese individuals undergoing weight loss, and accounts in part for the variability in dietary weight loss. We collected muscle and adipose tissue biopsies on these participants prior to and following weight loss, and performed RNA sequencing. In muscle we found that expression of uncoupling proteins 2 and 3 showed the greatest change with weight loss. These proteins dissipate proton gradients across mitochondrial membranes and are plausible candidates for regulation of energy expenditure. Individuals with greater decrease in UCP2 loss less weight and had lower 24hEE at the end of the 6 weeks of caloric restriction. This may also be mediated by changes in FGF-21. We are continuing to recruit for the overfeeding and underfeeding studies to confirm and examine the mechanism by which energy expenditure phenotype
