Dataset Information

Identification of body fat mass as a major determinant of metabolic rate in mice.

ABSTRACT: Analysis of energy expenditure (EE) in mice is essential to obesity research. Since EE varies with body mass, comparisons between lean and obese mice are confounded unless EE is normalized to account for body mass differences. We 1) assessed the validity of ratio-based EE normalization involving division of EE by either total body mass (TBM) or lean body mass (LBM), 2) compared the independent contributions of LBM and fat mass (FM) to EE, and 3) investigated whether leptin contributes to the link between FM and EE.We used regression modeling of calorimetry and body composition data in 137 mice to estimate the independent contributions of LBM and FM to EE. Subcutaneous administration of leptin or vehicle to 28 obese ob/ob mice and 32 fasting wild-type mice was used to determine if FM affects EE via a leptin-dependent mechanism.Division of EE by either TBM or LBM is confounded by body mass variation. The contribution of FM to EE is comparable to that of LBM in normal mice (expressed per gram of tissue) but is absent in leptin-deficient ob/ob mice. When leptin is administered at physiological doses, the plasma leptin concentration supplants FM as an independent determinant of EE in both ob/ob mice and normal mice rendered leptin-deficient by fasting.The contribution of FM to EE is substantially greater than predicted from the metabolic cost of adipose tissue per se, and the mechanism underlying this effect is leptin dependent. Regression-based approaches that account for variation in both FM and LBM are recommended for normalization of EE in mice.

SUBMITTER: Kaiyala KJ

PROVIDER: S-EPMC2889765 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Identification of body fat mass as a major determinant of metabolic rate in mice.

Kaiyala Karl J KJ Morton Gregory J GJ Leroux Brian G BG Ogimoto Kayoko K Wisse Brent B Schwartz Michael W MW

Diabetes 20100422 7

<h4>Objective</h4>Analysis of energy expenditure (EE) in mice is essential to obesity research. Since EE varies with body mass, comparisons between lean and obese mice are confounded unless EE is normalized to account for body mass differences. We 1) assessed the validity of ratio-based EE normalization involving division of EE by either total body mass (TBM) or lean body mass (LBM), 2) compared the independent contributions of LBM and fat mass (FM) to EE, and 3) investigated whether leptin cont ...[more]

PMID: 20413511

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Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.

Project description:1. The power-law dependence of metabolic rate on body mass has major implications at every level of ecological organization. However, the overwhelming majority of studies examining this relationship have used basal or resting metabolic rates, and/or have used data consisting of species-averaged masses and metabolic rates. Field metabolic rates are more ecologically relevant and are probably more directly subject to natural selection than basal rates. Individual rates might be more important than species-average rates in determining the outcome of ecological interactions, and hence selection. 2. We here provide the first comprehensive database of published field metabolic rates and body masses of individual birds and mammals, containing measurements of 1498 animals of 133 species in 28 orders. We used linear mixed-effects models to answer questions about the body mass scaling of metabolic rate and its taxonomic universality/heterogeneity that have become classic areas of controversy. Our statistical approach allows mean scaling exponents and taxonomic heterogeneity in scaling to be analysed in a unified way while simultaneously accounting for nonindependence in the data due to shared evolutionary history of related species. 3. The mean power-law scaling exponents of metabolic rate vs. body mass relationships were 0.71 [95% confidence intervals (CI) 0.625-0.795] for birds and 0.64 (95% CI 0.564-0.716) for mammals. However, these central tendencies obscured meaningful taxonomic heterogeneity in scaling exponents. The primary taxonomic level at which heterogeneity occurred was the order level. Substantial heterogeneity also occurred at the species level, a fact that cannot be revealed by species-averaged data sets used in prior work. Variability in scaling exponents at both order and species levels was comparable to or exceeded the differences 3/4-2/3 = 1/12 and 0.71-0.64. 4. Results are interpreted in the light of a variety of existing theories. In particular, results are consistent with the heat dissipation theory of Speakman & Król (2010) and provided some support for the metabolic levels boundary hypothesis of Glazier (2010). 5. Our analysis provides the first comprehensive empirical analysis of the scaling relationship between field metabolic rate and body mass in individual birds and mammals. Our data set is a valuable contribution to those interested in theories of the allometry of metabolic rates.

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Identification of body fat mass as a major determinant of metabolic rate in mice.

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Identification of body fat mass as a major determinant of metabolic rate in mice.

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