Integrated analysis of human and mouse populations has identified a target, RG1033, that is causally linked to adiposity and diabetes phenotypes (Figure 1). This gene is a key driver of a network in human and mouse liver and adipose that is associated with diabetes, obesity and cardiovascular traits. Validation has been achieved for this target by genetic manipulation in mouse models of obesity (DIO) as well as by the development of an inhibitor and subsequent pharmacological validation. A key lesson from this case study is that this gene has not been identified by public GWAS studies because of the lack of intermediate trait data in these studies that would enable genetic variation to be linked to changes in a molecular trait and ultimately to a clinical outcome like obesity.

Figure 1: Multiple Levels of Data in Human and Mouse Link RG1033 to Metabolic Disease. Key to this Link is the Availability of Population Level Tissue Gene Expression Data.

The pharmaceutical industry has an ever expanding portfolio of compounds that have been shown to be safe in human testing and to effectively modulate particular targets. In some cases these drugs show efficacy and go on to become marketed drugs whilst in other cases they may fail to show efficacy precluding their development for the selected indication. In either case there is a significant value to the industry in finding new indications for drugs with these characteristics (safe & modulate a known target) as a means to realize value on investment. Using network models tied to disease traits it is possible to generate potential new indications for compounds. Figure 2 illustrates how this was done for a compound originally developed for asthma. A molecular signature for the drug was interrogated against disease networks and a significant enrichment of the drug signature was noted for a particular pancreatic islet network linked to obesity and insulin resistance traits in a mouse F2 population. This led to the prediction that this drug may modulate these phenotypes through an effect on the islet module. This was tested in a mouse DIO model in which the compound helped normalize insulin and glucose levels.

Figure 2: Overlap of the Molecular Signature for a Known Drug with a Mouse Pancreatic Islet Module Associated with Diabetes and Obesity Phenotypes Generates a Prediction that can be Validated in vivo.