Acronym: GEDI
Study coordinator: Julien THEVENON, Emmanuel BARBIER
The implementation of genomic medicine on a population scale represents one of the major public health challenges of the coming years. The France Genomic Medicine 2025 Plan provides an unprecedented framework for patients with rare diseases or cancer.
The pilot project DEFIDIAG is designed to evaluate the technical and methodological feasibility of genome sequencing for the diagnosis of a group of rare diseases associated with intellectual disability. The clinical and genetic records of 1,277 individuals will be interpreted by a network of experts in the field, resulting in the creation of a unique dataset in both France and internationally.
The GEDI study is an ancillary project to DEFIDIAG that reuses data collected as part of a research initiative. GEDI is part of the work of the Artificial Intelligence for Health chair based in Grenoble, and aims to overcome methodological barriers specific to large-scale genomic medicine through efficient machine learning solutions and the development of medical decision-support tools.
Preliminary work has already been conducted within the chair by two PhD students involved in the project since 2019. This early research supports the objectives of GEDI and includes three ongoing publications on original algorithms for the reanalysis of genomic data, phenotype-based variant prioritization, and magnetic resonance imaging (MRI) signal processing.
The transfer of DEFIDIAG data to the CAD (Data Collector and Analyzer) will enable GEDI to apply these algorithms to a large dataset. The project will be rolled out gradually to align with the scale-up of the CAD between 2022 and 2023. GEDI ultimately aims to help define a standard for automated WGS analysis by evaluating a clinical decision-support tool for diagnosing rare diseases, using intellectual disability as a model case.