Poster de conférence
Résumé : The study of genetic variation associated with disease has shown the inadequacy of the “one gene - one disease phenotype” paradigm for many cases, leading to the notion of a conceptual continuum starting from monogenic disorders to oligogenic and polygenic diseases. An important step towards understanding non-Mendelian disorders was the creation of the Digenic Diseases Database (DIDA), collecting curated scientific information on digenic variant combinations involved in digenic diseases. Different machine learning methods aiming to tackle the cause of digenic diseases have successfully used DIDA as a benchmark dataset and have been in turn used in scientific studies analysing novel oligogenic cases. While this marked a new age of predictive tools and underlined the importance of DIDA, these advances also demonstrated the need to expand further in the genetic disease continuum, beyond digenic diseases, in a continuous and more careful manner. Moreover, a structured re-evaluation of the inclusion of oligogenic combinations in such a database and their pathogenic link to diseases has become essential, in order to aid researchers in using high-quality and properly curated information when assessing their medical cases. We present OLIDA (https://olida.ibsquare.be/), the Oligogenic Diseases Database, which reinvents DIDA, containing newly and fully re-curated data and freely accessible information on oligogenic variant combinations, i.e. combinations of variants in multiple genes involved in an oligogenic disease, published in the scientific literature until February 2020. The database includes 916 oligogenic variant combinations, 192 of them involving more than two genes, linked to 159 genetic diseases. OLIDA provides, for the first time in the field, a structured protocol for the evaluation of the pathogenicity of each oligogenic combination, based on the genetic and functional evidence supporting it, paying special attention to their joint variant effect. The evidence is derived from a combination of the results presented in the scientific papers and information from knowledge databases, and is depicted with a confidence score. OLIDA further follows the FAIR principles on data management. To conclude, OLIDA is the first database containing oligogenic variant combinations and, for each, a confidence score of its pathogenic involvement in the associated disease. With this work, we are initiating the important discussion on how the evidence of pathogenicity related to oligogenic diseases should be reported and evaluated in the scientific literature, a concept that becomes increasingly important with the growing amount of data in the field.

Documents en relation

DI-fusion