title: Abdominal fat analyzed by DEXA scan reflects visceral body fat and improves the phenotype description and the assessment of metabolic risk in mice.
abstract: Clinical studies have demonstrated a strong relationship between visceral fat content and metabolic diseases, such as type 2 diabetes and liver steatosis. Obese mouse models are an excellent tool to study metabolic diseases; however, there are limited methods for the noninvasive measurement of fat distribution in mice. Although micromagnetic resonance imaging and microcomputed tomography are the "gold standards" in the measurement of fat distribution, more economical and accessible methods are required. Dual energy X-ray absorptiometry (DEXA) is an effective method in characterizing fat content; however, it cannot discriminate between visceral and subcutaneous fat depots. We demonstrate that an evaluation of abdominal fat content measured by DEXA through the selection of one localized abdominal area strongly correlates with visceral fat content in C57BL/6J mice. We found that DEXA is able to measure fat pad volume ex vivo with high accuracy; however, the measurement of visceral fat in vivo shows an overestimation caused by subcutaneous tissue interference. The overestimation is almost constant for a wide range of values, and thus it is possible to correct the data for a more accurate estimation of visceral fat content. We demonstrate the utility of this technique in characterizing phenotypes of several obese mouse models (ob/ob, db/db, MC4R-KO, and DIO) and evaluating the effect of treatments on visceral fat content in longitudinal studies. Additionally, we also establish abdominal obesity as a potential biomarker for metabolic abnormalities (liver fat accumulation, insulin resistance/diabetes) in mice, similar to that described in humans.
authors: Department of Physiology, Faculty of Medicine, Monash University, Melbourne, Victoria, Australia.
authors: Weiyi
authors: W
authors: Chen
authors: Jenny L
authors: JL
authors: Wilson
authors: Mohammad
authors: M
authors: Khaksari
authors: Michael A
authors: MA
authors: Cowley
authors: Pablo J
authors: PJ
authors: Enriori
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods*; D050154:Adiposity; D000818:Animals; D004195:Disease Models, Animal; D005260:Female; D007333:Insulin Resistance; D050152:Intra-Abdominal Fat / Q000000981:diagnostic imaging*; D050356:Lipid Metabolism; D008099:Liver / Q000378:metabolism; D008297:Male; D008659:Metabolic Diseases / Q000000981:diagnostic imaging* / Q000378:metabolism; D051379:Mice; D008815:Mice, Inbred Strains; D018345:Mice, Knockout; D008820:Mice, Obese; D056128:Obesity, Abdominal / Q000000981:diagnostic imaging / Q000378:metabolism; D015203:Reproducibility of Results; D012727:Sex Characteristics; D050507:Subcutaneous Fat, Abdominal / Q000000981:diagnostic imaging; D051598:Whole Body Imaging