GenomeDia a personalized medicine tool for diabetes
Diabetes Mellitus affects nearly 600 million people worldwide. It is a major cause of premature death, blindness, end stage kidney disease, and limb amputation. However, it is not a single disease. Most patients are catalogued as...
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Información proyecto GenomeDia
Duración del proyecto: 19 meses
Fecha Inicio: 2024-06-06
Fecha Fin: 2026-01-31
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
Diabetes Mellitus affects nearly 600 million people worldwide. It is a major cause of premature death, blindness, end stage kidney disease, and limb amputation. However, it is not a single disease. Most patients are catalogued as type 2 diabetes, which is itself highly heterogeneous, while others have autoimmune type 1 diabetes. Genetic testing is currently able to define the precise cause of diabetes in a small group of young patients, although the categorization of diabetes subtypes is in most cases largely based on clinical judgement, rather than on specific tests. It is known, however, that the classification of diabetes subtypes has major implications for treatment. The emergence of whole genome sequencing in clinical practice provides new opportunities for classification of diabetes subtypes, but also entails major challenges such as the interpretation of non protein-coding variants. The recently funded ERC project DecodeDiabetes analyzed sequences from nearly 1500 young patients who had typical features of genetic forms of diabetes, but negative genetic tests in specialized genetic diagnostic laboratories. This study revealed different groups of genetic variants that cause diabetes in young patients with diabetes. It also developed approaches that leverage regulatory genomic knowledge to define noncoding genetic defects underlying human disease. The current proposal aims to compile new findings with existing knowledge, and to build a genetic interpretation solution to subcategorize young patients with diabetes. It will then validate this tool in patient cohorts. This proposal can thus translate fundamental knowledge derived from the ERC-funded Decode Diabetes project into applications whose valorization can bridge the gap to market and provide added value for society.