A big-data approach to understanding metabolic rate and A big-data approach to understanding metabolic rate and response to obesity in laboratory mice [preprint] response to obesity in laboratory mice [preprint]

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. phenotype consistent phenotypic Cdkal1 -/- , where EE values similar to WT values for mice at all 3 locations tested. Unidirectional phenotypes were observed for 3 strains. Significantly increased EE was observed Ap4e1 -/- and Dbn1 +/- mice at 3 of 9 sites and 3 of 7 sites, respectively. Nxn +/- mice had significantly lower EE at 3 of 8 sites. Bidirectional changes were observed for the remaining 3 strains. Dnase1l2 -/- mice were similar to WT controls at 6 sites, with 2 sites showing significantly altered EE, with one higher and one lower. Prkab1 -/- mice were similar to controls at 5 sites, consistent with results from an independently generated strain of AMPK b 1 deficiency which found no significant EE phenotype (Dzamko et al., 2010). Yet at two sites Prkab1 -/- mice were statistically different, higher and lower than controls at 1 site each. Lastly, Rnf10 -/- mice had the greatest variability. Variants in RNF10 are associated with obesity in a population of Pima Indians et al., 2014). For Rnf10 -/- mice, EE was significantly increased at 2 sites, unchanged at 2 sites, and decreased at 1 site. Consistently the largest residual values were from sites that did not report precise temperature values or locomotor activity, pointing towards incomplete modeling from these locations. These results illustrate the large phenotypic variability among mice with identical genetic perturbations observed at different locations.