The IMPC has developed a translational algorithm to find relevant human disease models from the data. The algorithm automatically detects phenotypic similarities between IMPC strains and more than 7,000 rare diseases. The algorithm measures a total of 509 phenotyping parameters that encompasses diverse biological and disease areas including neurological, behavioural, metabolic, cardiovascular, pulmonary, reproductive, respiratory, sensory, musculoskeletal and immunological parameters. The results provide a quantitative measure of how well an adult mouse model recapitulates features of a disease.
So far, it has been found that approximately 889 known rare disease-gene associations have an orthologous mouse strain and display at least one phenotype.
The mission of the IMPC is to generate a comprehensive catalogue of mammalian function and provide the foundations for the functional analysis of human genetic variation. We aim not only to develop insight into the function of every gene by the creation and analysis of null mutations, but also to further explore the relationship between genome and phenome by the generation of putative human pathogenic variants in both coding and non-coding sequences. These models will enable us to confirm pathogenicity, understand disease mechanisms, explore the impact of genomic context on the expressivity of disease phenotypes, and work with like-minded partners to design and undertake preclinical studies. Our aim is to provide transformative insights into the genetic bases of disease that will impact on clinical diagnosis and management, the exploitation of mouse models for therapeutic development, and ultimately support the funders’ goals to prevent, detect, diagnose, and treat disease.
Read more at our Disease Models Help pages
See our paper on Disease model discovery, Nature Genetics 2017