Neurodegenerative pathologies, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), are major public health issues. A major barrier to the development and testing of new treatments is the difficulty to appropriately select the patient populations to include in clinical trials. Specifically, it is crucial to be able to identify patients that are:
- at the earliest disease stage (ideally presymptomatic);
- at high risk of rapid progression;
- possess homogeneous disease characteristics.
Brain imaging and “omics” technologies (genomics, transcriptomics…) can provide biomarkers of progression and allow to identify disease risk factors. However, the analysis of such complex multimodal data is a hampered by the lack of appropriate methodologies.
The Inria Project Lab Neuromarkers aims
- to develop new statistical and computational approaches to integrate multimodal imaging and “omics” data;
- to demonstrate their potential to identify early alterations and predict progression of neurodegenerative diseases.
To tackle this challenge, the project brings together multidisciplinary expertise from Inria (www.inria.fr) and ICM (Brain and Spine Institute, www.icm-institute.org) in the fields of statistical learning, brain imaging, bioinformatics, knowledge modeling, genomics and neurodegenerative diseases.