Expected Impact:
The action under this topic is expected to achieve the following impacts:
- accelerate the EU’s access to more cost-effective interventions for the most burdensome diseases;
- decrease the risk of developing serious diseases later in life by defining specific prevention strategies;
- contribute to halting the progression of chronic diseases by using biomarkers in early interventions;
- improve the quality of life for healthy individuals and patients by preventing further health decline, avoiding escalating care costs, and properly stratifying individuals and patients earlier in the diagnostic pathway;
- accelerate the adoption of innovative approaches to diagnostic, preventative, and therapeutic strategies, strengthening the EU positioning as an innovator in healthcare.
The action will also support the EU political priority to boost European competitiveness and contribute to a number of European policies/initiatives, which include the European Commission’s European Health Data Space Regulation (EHDS)1 and the EU Artificial Intelligence Act2.
1https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L_202500327
2https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689
Expected Outcome:
The action under this topic must contribute to all of the following outcomes:
1. Accelerated access to interventions: A better understanding of the potential causal links between infections and non-communicable diseases and their accompanying biomarkers could:
- more precisely define a person’s level of risk for long term health complications
- lead to the development of better diagnostic approaches such as early detection and monitoring strategies that will make preventive medicine more effective for the benefit of patients.
2. Development of vaccine strategies:A better understanding of the potential causal links between infections and chronic diseases could lead to the generation of vaccine strategies with the capacity to prevent the development of one or more chronic diseases over the course of a person’s life, significantly reducing the long-term burden of disease.
3. Early intervention strategies:A clear understanding of the mechanisms of action used by infections to cause chronic diseases could more precisely define which cellular processes, metabolic pathways, enzymatic activities, and gene expression changes should be the focus of early intervention strategies. These strategies could halt or potentially reverse the progression of chronic diseases and would aim to replace many current treatments that only manage symptoms.
4. Improved quality of life:A better understanding of the potential causal links between infections and chronic diseases, as well as the biomarkers and mechanisms of action involved, could more precisely define development strategies for prophylactic vaccines, early diagnosis, and early intervention therapeutics that could significantly improve the quality of life of individuals by preventing health decline and avoiding escalating healthcare costs.
5. Adoption of innovative approaches:The establishment of a more systematic collaborative approach to mining existing research cohorts and biobanks to determine potentially causal links between infections and chronic diseases by combining multi-omics, artificial intelligence, and pre-clinical model verification to potentially accelerate the development of prophylactic vaccine, early diagnostic and early intervention strategies.
Scope:
Infectious agent (IA) and non-communicable disease (NCD) interplay has driven effective prevention strategies. However, a growing field of research suggests that there are many unexplored connections between IAs and NCDs that could be utilised to develop better diagnostic, preventative, and therapeutic approaches to burdensome diseases. A cohort analysis identified 96 distinct NCDs correlated to IAs [1]. Other cohort analyses identified neurodegenerative diseases, defined as the progressive loss of neurons resulting in loss of motor function or cognition, with links to viral infection [2], including Alzheimer’s disease, amyotrophic lateral sclerosis, dementia, vascular dementia, Parkinson’s disease and multiple sclerosis. IA links to cardio-metabolic NCDs such as HSV (Herpes simplex viruses) and coronary artery disease [3], CMV (cytomegalovirus), EBV (Epstein-Barr virus), VZV (varicella-zoster virus), influenza and parvovirus B19 have been shown to induce cardiomyopathies [4], and H. pylori infections may drive myocardial infarction [5].
While cancer, autoimmune, neurological, and cardiometabolic NCDs all have significant links to IAs, the scope of this topic is focused on neurodegenerative and cardiometabolic diseases, which carry significant disease burdens, potentially caused by direct, immune-mediated, or microbiota-gut-brain-axis damage/dysregulation, and lack early intervention strategies. Via the action funded under this topic, Europe’s research community could potentially find more infection-based approaches for diagnosing, preventing, and treating NCDs.
The action funded under this topic aims to identify potential causal links and biomarkers leading to mechanism of action (MoA) studies. The literature [6][7][8] demonstrates research cohorts’ utility in exploring the interplay between IAs and NCDs, increasing the likelihood of success. For instance, causative links were determined for oncolytic viruses, EBV [9] and human papillomavirus (HPV) [10], using Hill’s causation criteria. The action funded under this topic should:
- develop methodologies to demonstrate non-carcinogenic IA to NCD causal relationships;
- consolidate data in one repository of IA/NCD causal relationships, biomarkers, and MoA
Applicants are expected to define a strategy to assess non-carcinogenic infection-associated NCD causative links and related biomarkers, incorporating a modelling perspective alongside AI-assisted data mining, appropriate statistical methodologies, and prioritisation approaches for the exploration of mechanisms of action (MoA). Applicants should also detail their methodological approach and data collection procedures, providing preliminary data to show potential for success and strategies for mitigating main methodological risks and limitations.
- As part of the first objective of proposed activities, applicants should work toward generating robust evidence toward proof of causality rather than only strengthening the known associations of IAs and NCDs. Applicants should take advantage of the available research cohorts, biobanks, and exposome data, including microbiota-gut-brain-axis samples from large general population studies, neurodegenerative disease cohorts, or cardiovascular disease cohorts. Association strength, consistency, and specificity should be indicated by similarity of measurement across different cohorts. Insurance data could be used to analyse temporality where infection occurs prior to medically attended disease. Cohorts from patients that have received transplants or immunosuppressive treatments with longitudinal data could demonstrate temporality and biological gradient effects from opportunistic infections, the strength of the immune response to IAs to demonstrate elements of causality driven by immune-mediated damage. Selection of research cohorts should prioritise data sets with populations from diverse ethnicities, socio-economic statuses, and balanced for gender. Applicants should develop/use pre-clinical models for causal link plausibility verification. Applicants are expected to follow and comply with all relevant ethical and data privacy standards for research. Applicants are also expected to conduct their consortium work with full transparency, clearly communicating data provenance, model interpretability, traceability, and limitations, especially when using AI modelling and decision-making.
- The second objective is identifying novel biomarkers, ideally to classify associated IAs, to better stratify individuals (children, adults, the elderly) who are at risk of developing NCDs post infection. This could be done using immune or metabolic markers, host and microbiome metabolomics, sequencing, etc. This pillar can utilise the same cohorts, biobanks, and exposome data used for pillar 1 if sufficient, but should supplement with additional cohorts where needed. To ensure outcomes within the 5-year timeframe of the project, the launch of new prospective cohorts is out of scope but limited recruitment to fill specific data gaps in existing cohorts could be considered.
- The third objective is to define the MoA that IAs use to drive NCD development. MoA identification would require tissue samples from pillars 1 & 2, as well as pre-clinical or in silico experimentation according to the targeted conditions or diseases.
No product development is expected from this action in the proposed timeline.
Applicants are expected to consider the potential regulatory impact of the results and, as relevant, develop a regulatory strategy and interaction plan for generating appropriate evidence as well as engaging with regulators in a timely manner. Additionally, applicants should anticipate engaging regional healthcare systems and authorities to prepare for clinical implementation and outcome acceptance when necessary.
Applicants should include in their proposal a strategy to ensure sustainability of the outputs of the project beyond the funding period.
The funded project should explore synergies with the funded project from IHI Call 11 Topic ‘Towards precision medicine: platform for transdiagnostic stratification of brain dysfunction’ (once the funded projects are awarded) to increase impact. Applicants are also expected to consider synergies with other relevant global, European and national initiatives including projects generated from Cluster Health topic "Relationship between infections and non-communicable diseases (HORIZON-HLTH-2023-DISEASE-03-07).