Neurodegenerative diseases impose a substantial medical and public health burden on populations throughout the world. The prevalence of this kind of diseases increases drastically with age. The early detection and identification of these diseases would permit the design of therapies oriented to modify the evolution of them. For this reason, the early diagnosis of neurodegenerative diseases has captured the attention of a number of researchers, not only in clinical practice but also in other areas of knowledge such as engineering. In the last decades, researchers have achieved big advances in the knowledge of the development of this kind of diseases in earlier stages. However, there is still a long way to go towards the integration of this knowledge between the clinic and these areas of expertise, with the purpose of anticipating and improving both diagnosis and treatment of these diseases.


The purpose of this project is to integrate methods, tools and heterogeneous data sources which are used in studying the development of neurodegenerative diseases. Individually, the former only provide partial knowledge for most of the cases diagnosed. In this context, there already exist initiatives addressing this challenge from a multi-disciplinary point of view (see enigma.ini.usc.edu). In our case, we take as staring point three heterogeneous data sources:

Bioinformatic data. Analysis of existing genetic studies in three directions: pathogenic mutations, increased or decreased risk of disease associated to different haplogroups, and relationship of a higher mutation rate with disease progression.

Clinical image data. Design of medical image registration procedures which allow for estimating large deformations. These have been proved to be keystone features for the characterization of neurodegenerative diseases.

Cognitive test data. Design of models and techniques for analyzing data about sensorimotor disturbances and language deficits which can be addressed in cognitive tasks analyzed for patients suffering this kind of diseases.

This proposal is ambitious, built on the sound work team contributions to the state of the art in the methods that will be used to develop the project, and the previous expertise in other clinical applications, some of them in Neurology.