Non-Invasive Quantification of White and Brown Adipose Tissues and Liver Fat Content by Computed Tomography in Mice

OBJECTIVES: Obesity and its distribution pattern are important factors for the prediction of the onset of diabetes in humans. Since several mouse models are suitable to study the pathophysiology of type 2 diabetes the aim was to validate a novel computed tomograph model (Aloka-Hitachi LCT-200) for the quantification of visceral, subcutaneous, brown and intrahepatic fat depots in mice. METHODS: Different lean and obese mouse models (C57BL/6, B6.V-Lep(ob), NZO) were used to determine the most adequate scanning parameters for the detection of the different fat depots. The data were compared with those obtained after preparation and weighing the fat depots. Liver fat content was determined by biochemical analysis. RESULTS: The correlations between weights of fat tissues on scale and weights determined by CT were significant for subcutaneous (r(2) = 0.995), visceral (r(2) = 0.990) and total white adipose tissue (r(2) = 0.992). Moreover, scans in the abdominal region, between lumbar vertebrae L4 to L5 correlated with whole-body fat distribution allowing experimenters to reduce scanning time and animal exposure to radiation and anesthesia. Test-retest reliability and measurements conducted by different experimenters showed a high reproducibility in the obtained results. Intrahepatic fat content estimated by CT was linearly related to biochemical analysis (r(2) = 0.915). Furthermore, brown fat mass correlated well with weighted brown fat depots (r(2) = 0.952). In addition, short-term cold-expose (4 °C, 4 hours) led to alterations in brown adipose tissue attributed to a reduction in triglyceride content that can be visualized as an increase in Hounsfield units by CT imaging. CONCLUSION: The 3D imaging of fat by CT provides reliable results in the quantification of total, visceral, subcutaneous, brown and intrahepatic fat in mice. This non-invasive method allows the conduction of longitudinal studies of obesity in mice and therefore enables experimenters to investigate the onset of complex diseases such as diabetes and obesity

The Number of X Chromosomes Causes Sex Differences in Adiposity in Mice

Sexual dimorphism in body weight, fat distribution, and metabolic disease has been attributed largely to differential effects of male and female gonadal hormones. Here, we report that the number of X chromosomes within cells also contributes to these sex differences. We employed a unique mouse model, known as the “four core genotypes,” to distinguish between effects of gonadal sex (testes or ovaries) and sex chromosomes (XX or XY). With this model, we produced gonadal male and female mice carrying XX or XY sex chromosome complements. Mice were gonadectomized to remove the acute effects of gonadal hormones and to uncover effects of sex chromosome complement on obesity. Mice with XX sex chromosomes (relative to XY), regardless of their type of gonad, had up to 2-fold increased adiposity and greater food intake during daylight hours, when mice are normally inactive. Mice with two X chromosomes also had accelerated weight gain on a high fat diet and developed fatty liver and elevated lipid and insulin levels. Further genetic studies with mice carrying XO and XXY chromosome complements revealed that the differences between XX and XY mice are attributable to dosage of the X chromosome, rather than effects of the Y chromosome. A subset of genes that escape X chromosome inactivation exhibited higher expression levels in adipose tissue and liver of XX compared to XY mice, and may contribute to the sex differences in obesity. Overall, our study is the first to identify sex chromosome complement, a factor distinguishing all male and female cells, as a cause of sex differences in obesity and metabolism