The metabolic fate of an individual exposed to a Western diet is determined by genetic background. Although the interaction between genetic and environmental factors is central to the development of metabolic disease, few studies have prioritised identification of mechanisms to explain altered disease susceptibility. Studies in mice benefit from strict environmental control and easy access to deep tissues. Few studies, however, can identify drivers of disease susceptibility. Most are conducted using a single inbred strain (C57BL/6J) and those that do use multiple strains often examine genetic diversity only in the context of a single environment.
To address this, we interrogated the susceptibility of 11 genetically divergent mouse strains to diet-induced insulin resistance in multiple tissues using an in vivo method which quantifies both basal and insulin-stimulated glucose uptake in individual animals. In parallel, we performed a deep proteomic analysis of 4 metabolically important tissues: skeletal and cardiac muscle and white and brown adipose tissues, enabling us to integrate both within tissue and whole-body effects of diet. Strikingly, the largest proteomic differences existed between strains at baseline (before exposure to a Western diet). The ability of diet to induce proteomic remodelling was highly tissue-specific, and diet-induced changes were overwhelmingly confined to a small number of strains; even in white adipose tissue where widespread increases in adiposity would be expected to be accompanied by common proteomic adaptation. To make sense of the immense complexity within these datasets, we developed a sophisticated analysis strategy to prioritise candidates with the strongest molecular evidence linking them to disease. This identified strong relationships between the heart and hyperglycaemia, and brown adipose tissue and obesity; revealing powerful insights into the contributions of individual organs to the pathogenesis of metabolic disease, potential interactions between them and the underlying molecular drivers.