A big-data approach to understanding metabolic rate and response to obesity in laboratory mice [preprint]
UMass Chan Affiliations
Division of Endocrinology, Metabolism, and Diabetes, Department of MedicineProgram in Molecular Medicine
Document Type
PreprintPublication Date
2019-11-12Keywords
Physiologyobesity
body weight
energy balance experiments
metabolism
laboratory mice
Biochemical Phenomena, Metabolism, and Nutrition
Endocrinology, Diabetes, and Metabolism
Investigative Techniques
Nutritional and Metabolic DiseasesPathological Conditions, Signs and SymptomsPhysiology
Metadata
Show full item recordAbstract
Maintaining a healthy body weight requires an exquisite balance between energy intake and energy expenditure. In humans and in laboratory mice these factors are experimentally measured by powerful and sensitive indirect calorimetry devices. To understand the genetic and environmental factors that contribute to the regulation of body weight, an important first step is to establish the normal range of metabolic values and primary sources contributing to variability in results. Here we examine indirect calorimetry results from two experimental mouse projects, the Mouse Metabolic Phenotyping Centers and International Mouse Phenotyping Consortium to develop insights into large-scale trends in mammalian metabolism. Analysis of nearly 10,000 wildtype mice revealed that the largest experimental variances are consequences of institutional site. This institutional effect on variation eclipsed those of housing temperature, body mass, locomotor activity, sex, or season. We do not find support for the claim that female mice have greater metabolic variation than male mice. An analysis of these factors shows a normal distribution for energy expenditure in the phenotypic analysis of 2,246 knockout strains and establishes a reference for the magnitude of metabolic changes. Using this framework, we examine knockout strains with known metabolic phenotypes. We compare these effects with common environmental challenges including age, and exercise. We further examine the distribution of metabolic phenotypes exhibited by knockout strains of genes corresponding to GWAS obesity susceptibility loci. Based on these findings, we provide suggestions for how best to design and conduct energy balance experiments in rodents, as well as how to analyze and report data from these studies. These recommendations will move us closer to the goal of a centralized physiological repository to foster transparency, rigor and reproducibility in metabolic physiology experimentation.Source
bioRxiv 839076; doi: https://doi.org/10.1101/839076. Link to preprint on bioRxiv service.
DOI
10.1101/839076Permanent Link to this Item
http://hdl.handle.net/20.500.14038/29419Rights
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-ND 4.0 International license.Distribution License
http://creativecommons.org/licenses/by-nd/4.0/Scopus Count
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Except where otherwise noted, this item's license is described as The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-ND 4.0 International license.
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