PT  - JOURNAL ARTICLE
AU  - June K. Corrigan
AU  - Deepti Ramachandran
AU  - Yuchen He
AU  - Colin Palmer
AU  - Michael J. Jurczak
AU  - Bingshan Li
AU  - Randall H. Friedline
AU  - Jason K. Kim
AU  - Jon J. Ramsey
AU  - Louise Lantier
AU  - Owen P. McGuinness
AU  - Alexander S. Banks
AU  - Mouse Metabolic Phenotyping Center Energy Balance Working Group
TI  - A big-data approach to understanding metabolic rate and response to obesity in laboratory mice
AID  - 10.1101/839076
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 839076
4099  - http://biorxiv.org/content/early/2019/11/12/839076.short
4100  - http://biorxiv.org/content/early/2019/11/12/839076.full
AB  - 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.EEenergy expenditureLFDlow-fat dietHFDhigh-fat dietWTwild typeKOknockoutRERrespiratory exchange ratioMMPCMouse Metabolic Phenotyping CentersIMPCInternational Mouse Phenotyping ConsortiumSDstandard deviation