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.

EarlyCause will identify and demonstrate causative mechanisms and molecular pathways linking early life stress (ELS) to depression and two of its main physical comorbidities, namely coronary heart disease and diabetes. The consortium will disentangle the complex biological contributions from four key interconnected domains linked to ELS, namely epigenetics, inflammation, neuroendocrine system, and microbiome. Furthermore, modifying effects of environmental factors such as sex/gender, socioeconomics, lifestyle and behavior will be quantified, thus uncovering potential intervention targets that may reverse the causative mechanisms and reduce the impact of ELS on multi-morbidity development in high-risk individuals. To achieve the goals of the project, this highly multi-disciplinary and experienced consortium will combine state-of-the-art and novel approaches from basic, pre-clinical and clinical research, including causal inference methods such as Mendelian randomisation, animal models of prenatal and postnatal stress, cellular models in various tissues, and integrative bioinformatics and machine learning methods. The consortium members will also enable access and exploitation of the largest set of European cohorts, comprising rich information on early stressors, biological and omics data, as well as depressive, cardiovascular and metabolic phenotypes. Generated data, tissue samples, experimental protocols and cell lines, as well as best practices, will be compiled and integrated into a new open-access research platform within ELIXIR to support future researchers in the emerging topics of ELS and multi-morbidity. Finally, the project will ensure the research, clinical and socioeconomic impacts are adequately quantified and translated to allow full exploitation of the identified biomarkers and innovation outputs, in particular in relation to new integrated care pathways taking into account ELS-induced multi-morbidity in clinical practice.

Alzheimer's disease (AD), the main cause of dementia, is one of the major global health challenges of our time. This disabling disorder affects 55 million people worldwide, with costs above $1.3 trillion. With 67 million people at risk for AD dementia (prodromal and preclinical AD) in Europe alone, it is a major unmet public health need, with increasing burden for European economies, healthcare and social care systems and a concern for the future. Yet, prevention and early detection strategies have been lacking. Recent advances in disease-modifying therapies and the huge potential benefits of preventive multidomain interventions based on modifiable lifestyle and vascular factors (prevention potential ~ 40%) provide new opportunities. New developments in blood-based biomarkers (BBMs) and digital cognitive tests enable broader, cost-effective testing. The AD-RIDDLE platform is envisioned to revolutionize how AD is detected and diagnosed, prevented and treated across healthcare settings (HCS). AD-RIDDLE centres around a toolbox platform concept, providing a series of validated tools at each key step to enable HCS and practitioners to deploy enhanced AD management across diverse patient populations. The AD-RIDDLE toolbox platform will include a) community outreach tools to increase awareness/activation on AD prevention; b) combination of easily available, clinically validated biomarkers: digital cognitive tools and BBMs, for early detection of AD dementia risk; c) validated algorithms supporting clinical decisions, to identify people who can benefit from specific preventive therapies (pharma and/or non-pharma) using precision prevention approach. The toolbox usability and efficacy with be tested in real-world settings. We expect that the AD-RIDDLE modular and flexible design can facilitate broad uptake from different healthcare systems, and its tools can advance research to develop cost-effective preventive therapies for AD, with scalability for other dementias