AETIONOMY results presented to Innovative Medicines Initative leadership

AETIONOMY was started more than five years ago to explore the idea that conventional disease definition (that is, the expert clinical assessment of groups of symptoms leading to an eventual diagnosis) is an increasingly outdated concept in the current medical environment. AETIONOMY sought to explore the factors that define or drive Alzheimer’s and Parkinsonian syndromes and their outcomes. To this end, there was a critical focus on integrating data from a range of external studies, as well as studies conceived and managed within the project, into a central database. This investigation has been performed by a broad group of scientists from clinical, research and data-science institutions and organisations across Europe.

The project has now ended and has been reported here and in other publications. The results were presented to IMI leadership in Brussels on 15 November. The key outcomes of AETIONOMY offer the community interesting insights into the potential to differentiate subtypes of neurodegenerative disorders. The project has delivered several computational models to link molecular features to different clinical presentations or outcomes, such as the speed of disease progression. The hope now is for ongoing research and clinical trials to utilise insights like these to understand options for differential treatment paths – indeed some members of the AETIONOMY consortium are already leading or participating in such initiatives.

It is too early to speak about treatment or diagnostic advances, but the team has demonstrated the power of data to identify valuable insights. Researchers will continue to build on the legacy of the project, as they leverage the AETIONOMY database and methods to further refine these findings.

You can access two key project tools here:

  • The AETIONOMY Knowledge Base, a unification point of the knowledge and data management on neurodegeneration with a main focus on Alzheimer’s and Parkinson’s diseases.
  • NeuroMMSig, a mechanistic interpretation of multiscale, multimodal clinical data, representing essential pathophysiology mechanisms of neurodegenerative diseases. Researchers can explore the biology that underpins disease development through this user interface.