The interplay between nutrition, gut microbiota, and its large numberof metabolic and immune mediators plays an essential role in the development of gut immune homeostasis in early life. This interaction needs to be better understood because a disturbed immune function in the neonatal period is harmful for neonatal survival and enhances the risk of chronic inflammatory disease later in life. In particular, preterm infants have an immature gut and an associated intestinal state of dysbiosis, which limits the efficacy of nutritional interventions to 1) support early life nutrition, 2) prevent sepsis and conditions such as necrotizing enterocolitis and intestinal failure, and 3) reduce the risk of chronic inflammatory diseases mediated by the gut. A major barrier to elucidating the critical nutritional-host-microbiome interactions and reducing neonatal mortality is the lack of expertise in this rapidly emerging area of metabolomics. We therefore proposes a multidisciplinary approach making use of a large-scale pre-existing clinical cohort of neonates, and state of the art analytical and bio-informatics tools. GROWTH is an Innovative Training Network focused on European Industrial Doctorates that aims to train young business-oriented researchers in developing pathological insights, biomarker diagnostics and personalized nutritional interventions for intestinal failure in neonates and preterm infants. As a multidisciplinary consortium that will involve the participation of 7 non-academic and 5 academic partners in the life sciences field and will attempt shortening the path from basic research to clinical applications.

Sudden cardiac death (SCD) is a major public health problem accounting for ~20% of all deaths in Europe with an estimated yearly incidence of ~350-700,000, often in patients with previous myocardial infarction (MI). In SCD, the heart suddenly and unexpectedly stops beating. If untreated, the patient dies within minutes, but SCD can be successfully prevented by an implantable cardioverter-defibrillator (ICD). The ICD is highly effective, but is associated with potentially severe complications and high healthcare costs. Based on historical evidence, guidelines recommend prophylactic ICD implantation in post-MI patients with left ventricular ejection fraction (LVEF)≤35% to prevent SCD. However, only a minority of these patients will ever need the device. In addition, in absolute numbers the majority of SCD cases occurs in patients with LVEF>35% who are currently not considered for prophylactic ICD. Due to the inherent risks and considerable health care expenditures, a personalised treatment approach for ICD implantation is urgently required. Using state-of-the-art methods and large clinical datasets from established international cohorts and registries across different European geographies, PROFID will develop a clinical decision support tool (risk score) to predict the individual SCD risk and identify those post-MI patients that will optimally benefit from an ICD. Two parallel randomised clinical trials will validate implementation of the risk score to determine ICD implantation, while health economic analyses will assess its economic impact on health care systems. A software tool for clinical use of the risk score will be implemented, and a pilot run in 3 European regions with participation of insurance companies and authorities. The unique composition of the consortium with key opinion leaders, patient organisations, large hospital chains, payers, policy makers and state authorities across Europe, will ensure implementation into routine clinical practice.

The high and growing global burden of cancer urges the need for effective implementation of primary cancer prevention (PCP) programmes targeting modifiable risk factors. However, evidence-based programmes with proven effectiveness under controlled environments often fail when implemented in the real world due to ineffective adaptation and implementation strategies addressing context-specific barriers, leading to programme failures and public health inequities. The PIECES project will develop, assess, and disseminate a cancer-specific methodological implementation framework, the integrated PCP Implementation Toolkit (PCP-IT). PCP-IT will provide an evidence-informed systematic process for (1) identification, selection, and tailoring of PCP programmes, and (2) developing evidence-informed implementation strategies tailored to local barriers and constraints. The PCP-IT will include a comprehensive repository of PCP programmes, their Theories of Change, and materials for systematically adapting the programmes to local needs and cultural constraints. The project involves 16 consortium members and implementation sites from 10 countries of diverse socio-cultural backgrounds and access to up to 77.7 million inhabitants. PIECES provides an ideal naturalistic laboratory to improve and study the up-scaling and implementation of a wide range of primary PCP programmes targeting major risk factors: tobacco, alcohol, low physical activity, HPV infection, sun exposure, and diet. A multi-site case comparison study will be conducted to assess and optimise implementation outcomes. An in-depth realist evaluation using various sociological theories will be conducted to explain the processes by which the outcomes are achieved. The consortium will employ a high-level external Advisory Board with renowned experts, facilitate continuous engagement with stakeholders, and align with the EU and relevant scientific societies to ensure the future continuity of both the repository and PCP-IT. This action is part of the Cancer Mission cluster of projects on ‘Prevention and early detection’.

The stated goal of RHAPSODY is to define a molecular taxonomy of type 2 diabetes mellitus (T2D) that will support patient segmentation, inform clinical trial design, and the establishment of regulatory paths for the adoption of novel strategies for diabetes prevention and treatment. To address these goals, RHAPSODY will bring together prominent European experts, including the leaders of the diabetes-relevant IMI1 projects to identify, validate and characterize causal biomarkers for T2D subtypes and progression. Our plans are built upon: (a) access to large European cohorts with comprehensive genetic analyses and rich longitudinal clinical and biochemical data and samples; (b) detailed multi-omic maps of key T2D-relevant tissues and organs; (c) large expertise in the development and use of novel genetic, epigenetic, biochemical and physiological experimental approaches; (d) the ability to combine existing and novel data sets through effective data federation and use of these datasets in systems biology approaches towards precision medicine; and (e) expertise in regulatory approval, health economics and patient engagement. These activities will lead to the discovery of novel biomarkers for improved T2D taxonomy, to support development of pharmaceutical activities, and for use in precision medicine to improve health in Europe and worldwide.

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.