Diabetes and obesity research

Bridging between humans and model organisms to boost research on diabetes and obesity

Diabetes and obesity are complex diseases that represent a major international public health threat. To date, the genetic factors underlying these complex conditions have not been identified. Understanding these factors better would greatly help the diagnosis, treatment, and prevention of diabetes and obesity.

In recent years, a large number of new genetically modified animal models including transgenic, generalized and/or tissue-specific knockout mice have been engineered for the study of diabetes and obesity. However, researchers working on mouse disease models and those working with human patients use different terms to describe the same type of data, resulting in a major challenge in translating information from one to the other or even identifying a suitable mouse model to answer specific research questions. Working with experts from the different communities involved, BioMedBridges employs large-scale datasets provided by INFRAFRONTIER, BBMRI and ELIXIR to develop infrastructure that enables “crossing the species bridge” between mouse models and human to enable research into the genetic factors underlying diabetes and obesity.

The infrastructure being constructed consists of a number of components. First, a comprehensive ontology - an online representation which shows the relationship between different concepts - was developed to describe Type 2 diabetes and obesity phenotypes in mouse and human. Using this ontology, mouse and human datasets from a number of sources were annotated with specific terms used to describe Type 2 diabetes progression, enabling “translation” between mouse model and human data. Second, an online tool is being developed to assist researchers in the identification of suitable mouse models based on diabetes and obesity-related phenotypes. Finally, a set of scripts is being developed that integrate data from a number of sources to support the validation and prioritization of genes that could contribute to diabetes and obesity.

Tools and resources