PHAGO project to explore a new approach for patients with Alzheimer’s disease

On 1st November 2016 the Innovative Medicines Initiative (IMI) together with an association of industrial partners came together to support PHAGO, an innovative research project devoted to the development of immunomodulatory therapies for Alzheimer’s disease (AD).

Alzheimer’s disease (AD) is an age-related chronic neurodegenerative disease with progressive loss of nerve cells and their connectivity in the brain. Today, over 46 million people live with dementia worldwide and this number is estimated to increase to 131.5 million by 2050. Affected patients have memory loss and progressive dementia. Although current treatments can slightly delay some mental symptoms, there is currently no cure. The burden on caregivers who are often family members is huge. With an estimated 160 billion Euros of costs of care annually in Europe alone, this translates into a high socio-economic burden.

It has been known for many years that specialized types of immune cells accumulate around amyloid plaques (one of the pathological hallmarks of Alzheimer’s disease) in the brains of patients and show a dysfunctional activation profile. Recent systems biology approaches based on genome-wide association studies and brain gene expression profiling identified the innate immune receptor genes TREM2 and CD33/SIGLEC3 as disease relevant players in Alzheimer’s disease. These findings present novel and attractive targets for treatment. However a complete understanding of their exact role and underlying cellular mechanisms is still unclear. PHAGO aims to fill this knowledge gap and provide tools and assays for targeting these immune receptors to pave the way for the development of drugs that delay the progression of Alzheimer’s disease.

Prof. Harald Neumann, University Hospital of Bonn and PHAGO project coordinator, commented: "We are seeking to understand the immune response in Alzheimer’s disease. To this aim, we will analyse the function of both immune receptors in more detail and will set up tools and assay systems to establish pharmaceutical interventions".

The ambition of PHAGO is to improve patient outcomes through better understanding of the biology of TREM2 and CD33/SIGLEC3 and their biological networks and pathways, and develop therapies aimed at modulating the immune dysfunction in Alzheimer’s disease. To achieve this, PHAGO brings together experts from industry and academia in a powerful collaboration.

Dr. Andreas Ebneth, project leader at Janssen Pharmaceutica NV, stated: "The research project's value is its interdisciplinary approach focused on two relevant immune cell receptors suspected to be involved in Alzheimer’s disease. By bringing together scientific knowledge of leading European experts from different technical areas on TREM2 and CD33, we will be able to establish and exploit innovative tools on TREM2/CD33 suitable for pharmaceutical and industrial application. Over time, our ambition is that these contribute to the development of drugs for the treatment of Alzheimer’s disease."

Dr. Laurent Pradier, project co-leader at Sanofi added: "I see great potential for this project to develop a way to intervene pharmacologically in the TREM2 and CD33 pathways for the treatment of this devastating disease”.

Christian Ebeling, one of the main developers of the knowledge base implemented for IMI-project AETIONOMY, is taking care of the data- and knowledge management infrastructure in PHAGO. "The challenge of data- and knowledge management in PHAGO is substantial", says Martin Hofmann-Apitius, who is the academic work package leader for all informatics aspects in PHAGO, "the data produced in the course of the project come from a wide spectrum of biological test systems and range from genome and transcriptome data to cell-based assay data and proteomics data. Christian´s task is not only, to enable easy and secure exchange of data and knowledge, but rather to enable integrative modeling and mining in these data".

REHACARE.com; Source: Fraunhofer Institute for Algorithms and Scientific Computing SCAI