Frontotemporal dementia (FTD) has a debilitating effect on patients and their caregivers and leads to substantial economic costs. 15-30% of patients have familial FTD caused by known pathogenetic mutations. For the other 70-85% of patients, termed sporadic FTD, diagnosis is slow (~3.6 years) with frequent misdiagnosis due to clinical, genetic and molecular heterogeneity. Thus, there is great need for biomarkers for early diagnosis of sporadic FTD and its pathological subtypes. In PREDICTFTD, we will validate a set of biomarkers and create a diagnostic tool for early diagnosis of familial and sporadic FTD, which will facilitate tailored support and symptomatic treatments and care. We will apply several new approaches to achieve this: 1) we combine 11 geographically diverse cohorts of sporadic and familial FTD with retrospective and prospective longitudinal liquid biopsy samples and extensive clinical and behavioural data; 2) we are the first to use multimodal clinical and liquid biomarker data to train an AI-algorithm as a diagnostic tool for quick and early clinical FTD diagnosis; and 3) we implement a novel robust two-stage strategy for biomarker and AI algorithm validation, where phase I validates biomarkers and algorithms on a cohort of genetic and autopsied cases and phase II assesses biomarker value for diagnosis of sporadic FTD and at-risk pre-symptomatic mutation carriers. We will apply this two-stage validation strategy to address three critical clinical challenges: i) To distinguish sporadic FTD from (non-) neurodegenerative disorders that show significant clinical/symptomatic overlap, ii) To robustly detect FTD pathological subtypes in sporadic FTD and iii) pre-symptomatic identification of FTD onset. Thus, PREDICTFTD will transform FTD diagnosis, offering potential for early disease confirmation, guiding treatment decisions, facilitating patient recruitment for clinical trials, guidance of patients and caregivers, and enabling preventive measures.

Neurodegenerative diseases are one of the most important contributors to morbidity and mortality in the elderly. In Europe, over 14 million people are currently living with dementia, at a cost of over 400 billion EUR annually. Comorbidities with these conditions are frequent and a major obstacle to optimal diagnosis and management. Recent advances in diagnostic technologies and the advent of disease-modifying therapies (DMT) for Alzheimer’s disease (AD), the most common aetiology of dementia, heralds the beginning of precision medicine in this disease area. PROMINENT will develop a digital platform for precision medicine that will remove barriers that currently exists for leveraging these technological advancements in the routine care of patients with neurodegenerative disorders and co-morbidities. The platform gives clinicians access to prediction models leveraging multimodal diagnostic data automatically derived from multiple sources (imaging repositories, medical records, mobile devices), helping them choose optimal care pathways and improving diagnostic precision. It will provide personalized, relevant and meaningful information on diagnosis and prognosis in a format understandable by patients and care partners. Further, it will support the introduction of new health technologies such as DMT for AD, by ensuring adherence to appropriate use guidelines and facilitating the prospective collection of data on real-world usage, safety and effectiveness. The expected impact of the project is to increase diagnostic accuracy and optimized use of existing and new treatment options. It will empower patients and caregivers by engaging them in more person-centric health care decisions, leading to improved adherence and patient experience. Ultimately this is expected to lead to cost-effective care, improved health outcomes and quality of life.

The annual worldwide cost of Alzheimer’s dementia was 777.81 billion Euro in 2015. This number will rise to 7.41 trillion Euro in 2050. Early diagnosis would save up to $7.9 trillion in medical and care costs by 2050 in the US alone. However, the emergent pathology is highly variable across people, necehighly variable across people, necessitating individualized diagnostics and interventions. The VirtualBrainCloud addresses this by bridging the gap between computational neuroscience and subcellular systems biology, integrating both research streams into a unifying computational model that supports personalized diagnostics and treatments in NDD. TheVirtualBrainCloud not only integrates existing software tools, it also merges the efforts of two big EU initiatives, namely The Virtual Brain large scale simulation platform of the EU Flagship Human Brain Project and IMI-EPAD initiative (European prevention of Alzheimer’s dementia consortium). VirtualBrainCloud will develop and validate a decision support system that provides access to high quality multi-disciplinary data for clinical practice. The result will be a cloud-based brain simulation platform to support personalized diagnostics and treatments in NDD. The EU PRACE (Partnership for Advanced Computing in Europe) initiative, will provide the required computing infrastructure. The VirtualBrainCloud will develop robust solutions for legal and ethical matters by interacting with EU projects such as European Open Science Cloud (EOSC), ‘cloud4health’, Alzheimer’s Europe patient organizations and ELIXIR, an organization that manages and safeguards EU research data. Our software developers have already produced highly successful brain simulation and clinical decision support tools. The resulting software will be a cloud based computational modeling system that is tailored to the individual, and bridges multiple scales to identify key mechanisms that predict NDD progression and serves as Precision Decision Support System.

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are common neurodegenerative conditions, posing a major societal burden. There is a lack of treatments to slow disease progression, and therapeutic development has been impeded by a lack of biomarkers that can detect individuals early in the disease, measure treatment effects, and stratify patients. European cohorts recruited for research on aging and neurodegeneration provide a huge potential for biomarker discovery and validation by providing bio-samples along with deep clinical and imaging phenotypes. However, these cohorts are difficult to access. An overview of the availability of data and samples is lacking, and protocols and regulations for data and sample collection, storage, and sharing vary. The European Platform for Neurodegenerative Diseases (EPND) will tackle the above issues by developing a self-sustaining European-based platform to facilitate discovery and access of relevant bio-samples and data. EPND will be built on an existing informatics infrastructure, the AD Workbench, which EPND will adapt to support resource- and participant-level discovery, data harmonisation, central and federated data and sample storage, and data analysis. The sample and data discovery tools will be connected to a network of over 60 cohorts on AD, PD, and related disorders. Together, these cohorts will facilitate access to data and samples of over 120,000 research participants including CSF (n=30,000), plasma (n=120,000), stools (n=6,000), urine (n=27,000), saliva (n=17,000) and digital biomarkers (n=2,000). Prospective data collection will also occur during the project. This approach provides the community with a new and powerful environment for collaborative cross study analysis of harmonised biomarkers, datasets and samples. EPND will provide visibility into the quality and standardization of the data and samples available in the platform from the cohorts available and will also provide protocols for ongoing data and sample collection. This will guarantee quality of samples available, an important factor for validation and regulatory approval for biomarkers. EPND will be guided by ethical, legal and regulatory experts, patients, and other stakeholders to ensure responsible practices and processes underpin all discovery, sharing and access of data and samples, whilst simultaneously ensuring the platform is self-sustainable by the end of the project. Thereby, EPND will provide the community with a long-term, powerful environment to aid biomarker research for neurodegenerative disorders, enabling critical advances in the development of treatments for AD and PD.