The PPARy ligand rosiglitazone influences triacylglycerol metabolism in non-obese males, without increasing the transcriptional activity of PPARy in the subcutaneous adipose tissue

PPAR¿ is obligatory for fat mass generation and is thought to determine the amount of TAG stored per fat cell. We investigated whether ligand availability for PPAR¿ is rate limiting in fat mass generation and substrate metabolism. Twenty healthy men (20¿29 years) were randomly assigned to receive the PPAR¿ ligand rosiglitazone (RSG) (8 mg/d) (n 10) or a placebo (n 10) during a stay of 7 d in a respiration chamber. Food intake was ad libitum, resulting in positive energy balances of 32·2 MJ (placebo) and 44·7 MJ (RSG). Fat cell size and expression of PPAR¿, adipocyte fatty acid-binding protein (aP2), adipsin, adiponectin and fasting-induced adipose factor (FIAF) were determined in subcutaneous abdominal fat biopsies. The total amount of fat stored and the amount of TAG per fat cell were not different between groups. For the entire group, fat cell size was decreased after overeating (P = 0·02). FIAF mRNA levels were decreased after overeating in the RSG group (P = 0·01), with a trend towards a decrease in the placebo group. Unexpectedly, RSG treatment did not influence the expression levels of PPAR¿ and of the PPAR¿ responsive genes aP2, adiponectin and adipsin. In addition, RSG resulted in a larger increase in plasma TAG during overeating than placebo treatment. These results suggest that in healthy, non-obese males the PPAR¿ ligand RSG influences TAG metabolism, independent of its PPAR¿ transcriptional activity in the subcutaneous adipose tissue

The effect of the PPARgamma ligand rosiglitazone on energy balance regulation

BACKGROUND AND AIM: Fat mass generation requires an energy surplus and the activity of the peroxisome proliferator-activated receptor gamma (PPARgamma). We investigated if the PPARgamma ligand rosiglitazone influences substrate usage, energy expenditure (EE) and energy intake (EI) and, thereby, how PPARgamma activity contributes to susceptibility to obesity. METHODS: Twenty healthy males (20-29 years) were randomly assigned to receive a placebo (n = 10) or rosiglitazone (8 mg/d) (n = 10) for seven consecutive days, while staying in a respiration chamber. Food intake was ad libitum. Body composition was determined by underwater weighing (day 1) and deuterium dilution (day 1 and 8). RESULTS: Mean (+/-SE) EI was 15.9 +/- 0.9 MJ/d in the placebo group and 18.9 +/- 1.2 MJ/d in the rosiglitazone group. Mean EE was 11.3 +/- 0.3 MJ/d and 12.5 +/- 0.5 MJ/d for the placebo and rosiglitazone groups respectively. This resulted in a cumulative positive energy balance (EB) of 32.3 +/- 5.1 MJ for placebo and 44.7 +/- 6.9 MJ for rosiglitazone. There were no significant differences in EI, EE, and EB between treatments. Both groups did not adjust their fat oxidation to the increased fat intake, but fat oxidation decreased faster in the rosiglitazone group (significantly lower on days 6 and 7). During treatment with rosiglitazone, significantly more fat storage was seen in overweight subjects while this was not the case in the placebo group. CONCLUSIONS: Our results suggest a shift in substrate usage during PPARgamma stimulation leading to a preference for fat storage, especially in subjects with a higher BMI. Copyright (c) 2005 John Wiley & Sons, Ltd

Metabolic efficiency and energy expenditure during short-term overfeeding

OBJECTIVE: To investigate whether efficiency of weight gain during a short period of overfeeding is related to adaptive differences in basal metabolic rate (BMR) and physical activity. SUBJECTS: Fourteen healthy females (age 25+/-4 years, BMI 22.1+/-2.3 kg/m2). DESIGN AND MEASUREMENTS: Subjects were overfed with a diet supplying 50% more energy than baseline energy requirements for 14 days. Overfeeding diets provided 7% of energy from protein, 40% from fat and 53% from carbohydrates. Body composition was determined using hydrodensitometry and isotope dilution, total energy expenditure (TEE) with doubly labeled water and basal metabolic rate (BMR) with indirect calorimetry. Physical activity (PA) was recorded with a tri-axial accelerometer. RESULTS: Body weight increased by 1.45+/-0.86 kg (mean+/-S.D.) (P<0.0001), fat mass increased by 1.05+/-0.75 kg. Energy storage was 57.0+/-17.9 MJ, which is the difference between energy intake (207.2 MJ) and energy expenditure (150.2 MJ) during overfeeding. There was no difference between metabolically efficient and metabolically inefficient subjects in changes in BMR and PA. CONCLUSION: These results indicate that the metabolic efficiency of weight gain was not related to adaptive changes in energy expenditure

Measuring free-living energy expenditure and physical activity with triaxial accelerometry

OBJECTIVE: To investigate the ability of a newly developed triaxial accelerometer to predict total energy expenditure (EE) (TEE) and activity-related EE (AEE) in free-living conditions. RESEARCH METHODS AND PROCEDURES: Subjects were 29 healthy subjects between the ages of 18 and 40. The Triaxial Accelerometer for Movement Registration (Tracmor) was worn for 15 consecutive days. Tracmor output was defined as activity counts per day (ACD) for the sum of all three axes or each axis separately (ACD-X, ACD-Y, ACD-Z). TEE was measured with the doubly labeled water technique. Sleeping metabolic rate (SMR) was measured during an overnight stay in a respiration chamber. The physical activity level was calculated as TEE x SMR(-1), and AEE was calculated as [(0.9 x TEE) - SMR]. Body composition was calculated from body weight, body volume, and total body water using Siri's three-compartment model. RESULTS: Age, height, body mass, and ACD explained 83% of the variation in TEE [standard error of estimate (SEE) = 1.00 MJ/d] and 81% of the variation in AEE (SEE = 0.70 MJ/d). The partial correlations for ACD were 0.73 (p < 0.001) and 0.79 (p < 0.001) with TEE and AEE, respectively. When data on SMR or body composition were used with ACD, the explained variation in TEE was 90% (SEE = 0.74 and 0.77 MJ/d, respectively). The increase in the explained variation using three axes instead of one axis (vertical) was 5% (p < 0.05). DISCUSSION: The correlations between Tracmor output and EE measures are the highest reported so far. To measure daily life activities, the use of triaxial accelerometry seems beneficial to uniaxial