Metabolic subgroups of Diversity Outbred mice show distinct phenotypic and transcriptomic signatures of obesity and insulin resistance

Clinicians and researchers are turning towards precision medicine to treat and prevent obesity and diabetes, given the known contributions of genetics to these metabolic diseases and the wide variability reported in response to treatments. Animal models that incorporate the genetic diversity present in the human population may help discover novel genetic contributors to metabolic disease and test potential treatments. We characterized the Diversity Outbred (DO) mouse population as a model in which to study interindividual variability in metabolic disease and investigated the presence of metabolic subgroups within the population. Glucose metabolism was assessed in male Diversity Outbred (DO) mice after consumption of a high-fat diet for 14 weeks and profiled transcriptomic changes in liver, adipose, and muscle—key tissues involved in glucose homeostasis. To identify metabolic subgroups, we applied classification and regression tree analyses to metabolic phenotype measures as well as transcriptomic data. These findings suggest that DO mice exhibit a diversity of metabolic phenotypes that can be segmented into subgroups using a machine learning approach. The metabolic subgroups observed in the DO may be a useful for probing the phenotypic variability in metabolic disease observed in humans. Male DO mice received either control or high-fat diet (HFD) for 14 weeks. At study start animals were randomized and half of the mice (N=75) were placed on the High Fat diet (60 kcal %, D12492/D12492N; Research Diets, New Brunswick, NJ) while the other half (N=75) continued receiving control diet ad libitum. Animals were examined for morbidity and clinical observation twice daily on weekdays and once daily on weekends and holidays. Body weight was measured prior to blood collection on week 1 and then weekly for the remainder of the study. Feed consumption was monitored weekly. During Week 1, 5, 9, and 14, mice were fasted for a period of 4-5 hours and resting-state glucose levels were measured. After 12 weeks, an oral glucose tolerance test was also conducted after mice were fasted overnight (approximately 16-18 hours). Serum insulin and leptin content as well as routine clinical chemistry were also measured. After 14 weeks animals were necropsied and tissues collected. Samples of liver, muscle, and adipose (abdominal) tissue were frozen in liquid nitrogen and stored at or below -70 degrees C. Total RNA was extracted from small sub-samples of these three tissues and gene expression was measured to investigate potential molecular changes driving variability among mice to allow subgroupings. Metabolic subgroups were identified using a machine-learning algorithm.