Factors which predict variance in weight change

National Institute Of Diabetes And Digestive And Kidney Diseases

Investigators

Linked publications, trials & patents

Abstract

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 96 participants complete the core portion of this study. Consumption of high carbohydrate and high protein overfeeding diets increased EE the most, while low protein overfeeding increased EE the least. Individuals with a greater increase in EE with overfeeding have less decline in EE with fasting indicating the presence of thrifty versus spendthrift energy expenditure phenotypes. After 6 months, we found that several EE phenotypes predicted weight gain: 1. Individuals with greater decrease in EE with fasting 2. Individuals with less increase in EE with low protein overfeeding 3. Individuals with greater increase in EE with high carbohydrate overfeeding. Increased EE after high carbohydrate overfeeding was also associated with greater hunger. Our data also demonstrates that 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 with carbohydrate oxidation rates. In addition, greater metabolic flexibility (those who decreased their 24hRQ and lipid oxidation rates more) determined during 24 hours of high fat overfeeding was associated with less weight gain, gained less (or even lost) weight. In further examining the thrifty versus spendthrift phenotypes, we have found that the greater drop in 24hEE with fasting, is due to a higher energy balance 24hEE rather than a lower fasting 24hEE. Thus, thrifty subjects have a higher energy balance 24hEE compared to spendthrift. Spendthrift subjects increase their EE during sleep. Furthermore, during protein imbalance overfeeding, thrifty individuals have blunted increase in 24hEE. These analyses fundamentally recharacterizes the prevailing model of the thrifty vs. spendthrift phenotype as we have defined it. We have been investigating the mechanisms underlying these energy expenditure changes to fasting and overfeeding. One measure of the ability to dissipate heat is changes in core body temperature. 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. Core body temperature increases with overfeeding, and in the setting of a high fat diet, this increase is associated with an increase in EE. Activation of the sympathetic nervous system may also explain EE changes. We found that 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 FGF-21 increased substantially (by 300%) following two different low protein overfeeding diets and that increased change in FGF 21 concentrations correlated with greater %EE increased with low protein overfeeding. Moreover, the greater increase in FGF-21 concentrations were associated with less weight gain at 6 months. Most significantly, this increase in FGF-21 mediated the association between greater increase in %EE with low protein overfeeding and weight change at 6 months indicating that FGF-21 is a good target for weight loss treatment. We have also found that urinary dopamine concentrations also increase during fasting and low protein overfeeding and are associated with changes in pancreatic polypeptide indicating a shift in sympathetic/parasympathetic tone with protein deprivation. In examining the growth hormone (GH) axis role in EE changes, we found that fasting induces GH hypersecretion independent of changes in ghrelin and without changes in its downstream mediator insulin-like growth factor-1. We did find that individuals who increase ghrelin more with fasting had greater decrease in 24hEE. We have found that while thyroid hormones do change with fasting and with low protein and high protein overfeeding diets, these changes are not related to changes in energy expenditure. Thus, diet induced thermogenesis does not appear to be mediated by the thyroid hormone axis. We are continuing long term follow-up of those with these energy expenditure measurements and investigating the role of gastrointestinal, inflammatory and adipocyte hormones as possible mediators of these EE changes and or weight change. As increased adiposity may insulate against trans-abdominal heat loss which may increase TEF, we investigated the effect of central insulation on the EE and TEF changes associated with overfeeding. However, despite earlier evidence of an important role of abdominal heat dissipation in determining DIT and TEF, we did not find any changes in EE during overfeeding with additional abdominal insulation. 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-CT scan; 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. We have found evidence of brown activation with this diet. As high carbohydrate diets induced sympathetic nervous system (SNS) activation, we examined whether our measures of SNS were associated with presence of brown fat. We found that those with both lower levels of urinary epinephrine and free T4 measured during thermoneutrality had increased brown fat activation indicating lower SNS and thyroid tone define individuals with a greater capacity to activate brown fat. In a re-examination of total body brown fat activation in all participants who underwent cold inducted BAT measures, we did find an association between greater peak cold induced BAT and less decrease in EE with fasting (spendthrift phenotype)