The AETIONOMY project
- recruited more than 400 PD patients and generated a unique biobank with clinical data and bio samples for further analyses;
- developed the first version of a mechanism-based taxonomy for Alzheimerism and Parkinsonism;
- generated 8 biomarkers;
- successfully developed strategies and new algorithms to associate mechanisms with biomarkers (and progression) in patient-level data;
- generated a publicly accessible resource, the AETIONOMY Knowledge Base (AKB), that contains high-quality, curated data, and computable models of disease;
- created the largest inventory of computable disease mechanisms underlying neurodegeneration worldwide, NeuroMMSig, (Alzheimerism=126, Parkinsonism=76, Epilepsy=31);
- worked on the concept of Virtual Dementia Cohorts for effective data sharing.
Dementia affects 44 million people globally, and that figure is set to rise to 135 million by 2050, mostly due to ageing of the population. Alzheimer’s disease is the most common form of dementia, accounting for between 60% and 80% of all cases. Meanwhile an estimated 4-6 million people globally suffer from Parkinson’s disease. There is no cure for these devastating diseases, and caring for patients as their disease progresses represents an immense burden for family members, carers, and health and social care systems.
Developing new treatments for brain disorders takes longer and costs more than for other disease areas. When it comes to Alzheimer’s and Parkinson’s diseases, the way these diseases are classified is hampering efforts to develop effective, targeted treatments.
Currently, diseases are defined largely on the basis of the patient’s symptoms and where they occur in the body. Many are classified based simply on the name of the doctor or researcher who first discovered or described the disease – this is the case for both (Alois) Alzheimer’s and (James) Parkinson’s diseases.
Rethinking classification: from effect to cause
There is growing evidence that while two patients may be classified as having the same disease, the genetic or molecular causes of their symptoms may be very different. This means that a treatment that works in one patient will prove ineffective in another. In other cases, diseases that are currently defined as separate conditions may share a common molecular basis. There is therefore now broad recognition that the way diseases are classified needs to change, and the field of neurodegenerative diseases in particular is considered to be ripe for a rethink.
AETIONOMY was an ambitious project: there are few meaningful correlations or causal links between disease features at the molecular level (e.g. genetic mutations or gene activity), features at the tissue / organ level (e.g. changes in the brain), and features at the clinical level (including symptoms and the results of imaging scans). Even in cases where the disease runs in families, it is not uncommon to find family members who share the same genetic mutation but have different clinical symptoms. For most patients, the disease is simply described as ‘idiopathic’, meaning the cause is unknown.
Nevertheless, the literature, public databases, and private companies have vast amounts of data that could be used to pave the way for a better classification of patients, based on underlying causes instead of symptoms. However, we lack an efficient way to generate new knowledge from these resources, and that is where the AETIONOMY project comes in.
The AETIONOMY team tackled the problem of how to dynamically organise and structure different types of data (ranging from molecular data to information on symptoms) and how to apply this knowledge to construct a new classification of patient groups based on the underlying causes of their disease. Achieving this is far beyond the scope of any single company or university; the key to AETIONOMY’s success is the broad nature of the project consortium, which brought together pharmaceutical companies, universities, and two patient groups, and boasts expertise in neurodegenerative diseases, molecular biology, clinical research, research ethics, data modelling and simulation, data standards, and patient involvement in research.
The new project delivered data, tools and recommendations that can be used by the biomedical community and regulators to develop and approve new treatments and diagnostic tests.
An urgent need for new treatments
There are currently no drugs capable of curing Alzheimer’s or Parkinson’s diseases, and the few treatments designed to alleviate symptoms are not effective in all patients. By identifying sub-groups of patients based on the underlying, molecular cause of their disease, AETIONOMY will usher in a new era of personalised medicine, in which patients’ treatments will be determined on the basis of the cause of their disease, not its effects.