Adipocyte size, adipose tissue calories, and circulating adipokines, before and after diet-induced weight loss in humans.

OBJECTIVE: Adipose tissue (AT) contains a bimodal population of large and small adipocytes. Changes in fat cell size (FCS) distribution and AT caloric density (kcal/g) with weight loss are unclear. We aimed to evaluate changes in FCS and AT calories in weight loss and determine associations with anthropometrics. MATERIALS AND METHODS: Healthy adults (6 men/4 women; age 33 ± 11 years; BMI 35 ± 6 kg/m2) underwent DXA and subcutaneous abdominal/thigh fat biopsies, before and after 6 weeks of caloric restriction. AT calories (bomb calorimetry) and hormones (adiponectin, leptin, FGF21) were measured. RESULTS: Abdominal large cell diameter (LCD; Δ = -13.2 µm, p = 0.01) and nadir (Δ = -7.3 µm, p = 0.03) decreased. In repeated measures correlations (rrm), abdominal and thigh LCD and nadir were associated with fat mass (FM) loss (rrm = 0.68; rrm = 0.63; rrm = 0.66; rrm = 0.62, p's < 0.05, respectively) and waist circumference decrease (rrm = 0.70; rrm = 0.60, p's ≤ 0.05). Small cell percentage did not change and was not associated with FM changes. Abdominal AT calories were unchanged with weight loss. Change in leptin was associated with change in abdominal LCD (rrm = 0.77, p = 0.01). CONCLUSIONS: Caloric restriction reduces adipocyte LCD and nadir. These changes are associated with FM loss. Larger fat cells should be considered as phenotypic targets for weight loss. CLINICAL TRIALS REGISTRATION: clinicaltrials.gov identifier: NCT00687115, May 29, 2008.

Chemical Oxygen Demand Can Be Converted to Gross Energy for Food Items Using a Linear Regression Model.

BACKGROUND: Human and microbial metabolism are distinct disciplines. Terminology, metrics, and methodologies have been developed separately. Therefore, combining the 2 fields to study energetic processes simultaneously is difficult. OBJECTIVES: When developing a mechanistic framework describing gut microbiome and human metabolism interactions, energy values of food and digestive materials that use consistent and compatible metrics are required. As an initial step toward this goal, we developed and validated a model to convert between chemical oxygen demand (COD) and gross energy (${E_g}$) for >100 food items and ingredients. METHODS: We developed linear regression models to relate (and be able to convert between) theoretical gross energy (${E_g}^{\prime}$) and chemical oxygen demand (COD'); the latter is a measure of electron equivalents in the food's carbon. We developed an overall regression model for the food items as a whole and separate regression models for the carbohydrate, protein, and fat components. The models were validated using a sample set of computed ${E_g}^{\prime}$ and COD' values, an experimental sample set using measured ${E_g}$ and COD values, and robust statistical methods. RESULTS: The overall linear regression model and the carbohydrate, protein, and fat regression models accurately converted between COD and ${E_g}$, and the component models had smaller error. Because the ratios of COD per gram dry weight were greatest for fats and smallest for carbohydrates, foods with a high fat content also had higher ${E_g}$ values in terms of kcal · g dry weight-1. CONCLUSION: Our models make it possible to analyze human and microbial energetic processes in concert using a single unit of measure, which fills an important need in the food-nutrition-metabolism-microbiome field. In addition, measuring COD and using the regressions to calculate ${E_g}$ can be used instead of measuring ${E_g}$ directly using bomb calorimetry, which saves time and money.

Procedures for Measuring Excreted and Ingested Calories to Assess Nutrient Absorption Using Bomb Calorimetry.

OBJECTIVE: With the upsurge in interest in the gut microbiome, complete and accurate measurement of ingested calories and calories lost through excreted stool is crucial for assessing the effect of the microbiota on nutrient absorption. METHODS: Measurement of ingested and excreted calories was conducted over 3 days. Meals were made in duplicate: one was given to the participant, and one was used for the measurement of calories. Stool was marked by nonabsorbable dye ingested prior to and at the end of each 3-day diet period and was collected for caloric assessment from the appearance of the first dye marker until the appearance of the second dye marker. RESULTS: Stool calories per gram for pellets were 4.91 ± 0.06 kcal/g. The mean stool calorie loss as a percentage of ingested calories was 7.3% ± 1.6% (range, 6.6%-8.5%). The stool measurement of kilocalories per gram was not associated with the total measured stool calories or with stool weight (P = 0.2 and P = 0.2, respectively) over the 3-day period. However, the weight of stool samples during each dietary intervention was positively associated with the calorie loss in stool (r = 0.58, P < 0.0001). CONCLUSIONS: Our methods provide a direct measure of ingested calories and stool calories needed to accurately assess relative stool calorie loss as a measure of nutrient absorption. The weight of stool samples across the marked diet period is crucial to determining total stool calories.

Thigh Adipocyte Size is Inversely Related to Energy Intake and Respiratory Quotient in Healthy Women.

OBJECTIVE: The relationship between adipocyte size and ad libitum energy intake has not been previously examined. This study hypothesized an inverse relationship between adipocyte size and daily energy intake (DEI). METHODS: Seventy healthy adults (39 men and 31 women; BMI 30.0 [SD 6.3]) underwent dual-energy x-ray absorptiometry and subcutaneous fat biopsies from the abdomen and thigh. Osmium-fixed adipocytes were sized with a Coulter counter. Volunteers self-selected food from a vending machine paradigm as the only source of energy intake over 3 days as inpatients. Volunteers also had 24-hour respiratory quotient (RQ) measured in a whole-room indirect calorimeter. RESULTS: In women, the large cell peak diameter of the thigh depot was greater than that of the abdominal depot (Δ = +15.8 µm; P < 0.0001). In women, thigh peak diameter was inversely associated with DEI (ß = -264.7 kcal/d per 10-µm difference; P = 0.03) after adjusting for demographics and body composition. The thigh peak diameter in women was associated with 24-hour RQ (r = -0.47, P = 0.04) after adjusting for demographics, body composition, and 24-hour energy balance. These associations did not extend to men or the abdominal depot. CONCLUSIONS: In women, thigh adipocyte size was associated with reduced DEI and 24-hour RQ, indicating a special role for thigh fat in women. This depot-specific sexual dimorphism indicates common regulation of energy intake and adipocyte size in the thigh region of women.

Effects of underfeeding and oral vancomycin on gut microbiome and nutrient absorption in humans.

Direct evidence in humans for the impact of the microbiome on nutrient absorption is lacking. We conducted an extended inpatient study using two interventions that we hypothesized would alter the gut microbiome and nutrient absorption. In each, stool calorie loss, a direct proxy of nutrient absorption, was measured. The first phase was a randomized cross-over dietary intervention in which all participants underwent in random order 3 d of over- and underfeeding. The second was a randomized, double-blind, placebo-controlled pharmacologic intervention using oral vancomycin or matching placebo (NCT02037295). Twenty-seven volunteers (17 men and 10 women, age 35.1 ± 7.3, BMI 32.3 ± 8.0), who were healthy other than having impaired glucose tolerance and obesity, were enrolled and 25 completed the entire trial. The primary endpoints were the effects of dietary and pharmacological intervention on stool calorie loss. We hypothesized that stool calories expressed as percentage of caloric intake would increase with underfeeding compared with overfeeding and increase during oral vancomycin treatment. Both primary endpoints were met. Greater stool calorie loss was observed during underfeeding relative to overfeeding and during vancomycin treatment compared with placebo. Key secondary endpoints were to evaluate the changes in gut microbial community structure as evidenced by amplicon sequencing and metagenomics. We observed only a modest perturbation of gut microbial community structure with under- versus overfeeding but a more widespread change in community structure with reduced diversity with oral vancomycin. Increase in Akkermansia muciniphila was common to both interventions that resulted in greater stool calorie loss. These results indicate that nutrient absorption is sensitive to environmental perturbations and support the translational relevance of preclinical models demonstrating a possible causal role for the gut microbiome in dietary energy harvest.

Food label accuracy of common snack foods.

UNLABELLED: Nutrition labels have raised awareness of the energetic value of foods, and represent for many a pivotal guideline to regulate food intake. However, recent data have created doubts on label accuracy. OBJECTIVE: We tested label accuracy for energy and macronutrient content of prepackaged energy-dense snack food products. We measured "true" caloric content of 24 popular snack food products in the U.S. and determined macronutrient content in 10 selected items. DESIGN AND METHODS: Bomb calorimetry and food factors were used to estimate energy content. Macronutrient content was determined according to Official Methods of Analysis. Calorimetric measurements were performed in our metabolic laboratory between April 20th and May 18th and macronutrient content was measured between September 28th and October 7th of 2010. RESULTS AND CONCLUSION: Serving size, by weight, exceeded label statements by 1.2% [median] (25th percentile -1.4, 75th percentile 4.3, P = 0.10). When differences in serving size were accounted for, metabolizable calories were 6.8 kcal (0.5, 23.5, P = 0.0003) or 4.3% (0.2, 13.7, P = 0.001) higher than the label statement. In a small convenience sample of the tested snack foods, carbohydrate content exceeded label statements by 7.7% (0.8, 16.7, P = 0.01); however fat and protein content were not significantly different from label statements (-12.8% [-38.6, 9.6], P = 0.23; 6.1% [-6.1, 17.5], P = 0.32). Carbohydrate content explained 40% and serving size an additional 55% of the excess calories. Among a convenience sample of energy-dense snack foods, caloric content is higher than stated on the nutrition labels, but overall well within FDA limits. This discrepancy may be explained by inaccurate carbohydrate content and serving size.