A Comparative Study of the Metabolic and Skeletal Response of C57BL-6J and C57BL-6N Mice in a Diet-Induced Model of Type 2 DiabetesReportar como inadecuado

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Journal of Nutrition and Metabolism - Volume 2015 2015, Article ID 758080, 13 pages -

Research Article

Department of Nutritional Sciences, Oklahoma State University, Stillwater, OK 74078, USA

Center for Cancer Prevention and Drug Development, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA

Received 4 December 2014; Revised 8 May 2015; Accepted 12 May 2015

Academic Editor: H. K. Biesalski

Copyright © 2015 Elizabeth Rendina-Ruedy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Type 2 diabetes mellitus T2DM represents a complex clinical scenario of altered energy metabolism and increased fracture incidence. The C57BL-6 mouse model of diet-induced obesity has been used to study the mechanisms by which altered glucose homeostasis affects bone mass and quality, but genetic variations in substrains of C57BL-6 may have confounded data interpretation. This study investigated the long-term metabolic and skeletal consequences of two commonly used C57BL-6 substrains to a high fat HF diet. Male C57BL-6J, C57BL-6N, and the negative control strain, C3H-HeJ, mice were fed a control or HF diet for 24 wks. C57BL-6N mice on a HF diet demonstrated an increase in plasma insulin and blood glucose as early as 4 wk, whereas these responses were delayed in the C57BL-6J mice. The C57BL-6N mice exhibited more severe hepatic steatosis and inflammation. Only the C57BL-6N mice lost significant trabecular bone in response to the high fat diet. The C3H-HeJ mice were protected from bone loss. The data show that C57BL-6J and C57BL-6N mice differ in their metabolic and skeletal response when fed a HF diet. These substrain differences should be considered when designing experiments and are likely to have implications on data interpretation and reproducibility.

Autor: Elizabeth Rendina-Ruedy, Kelsey D. Hembree, Angela Sasaki, McKale R. Davis, Stan A. Lightfoot, Stephen L. Clarke, Edralin A.

Fuente: https://www.hindawi.com/


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