Decode the Immunoscience of age-related diseases

Expected Impact:

The action under this topic is expected to achieve the following impacts:

• Accelerate EU access to more cost-effective interventions in an increasingly ageing population by identifying personalised treatment approaches for elderly-onset immune diseases.
• Decrease disease risk later in life by defining specific prevention strategies based on ageing biomarkers and risk factors.
• Halt age-associated disease exacerbation by the identification of predictive and digital biomarkers that can stratify patients for early intervention.
• Improve quality of life for healthy individuals and patients by preventing further health decline, avoiding escalating care costs, and properly stratifying individuals earlier in the diagnostic pathway.
• Accelerate adoption of innovative diagnostic, preventative, and therapeutic strategies, strengthening the EU’s position as a healthcare innovator.
• Evaluate digital biomarker as potential regulatory endpoints in the ultimate goal to develop medicines for ‘healthy ageing’.
• Integrate fragmented research efforts by bringing together health industry sectors and stakeholders to develop clinical and multi-omics data integration capabilities.
• Enable new data-driven research by building AI infrastructure on existing data and cohorts that no single organisation could develop independently

Patients and citizens will benefit from improved medical practice and healthcare solutions, new targeted prevention strategies and ultimately healthier ageing.

The action will support EU policy and priorities including the European Health Data Space Regulation (EHDS) and the EU Artificial Intelligence Act, while contributing to European competitiveness in addressing one of society's major challenges.

Expected Outcome:

The action under this topic must contribute to all of the following outcomes:

1. Researchers will benefit from a better understanding of the potential causal links between chronic inflammatory diseases and biological ageing, and the predictiveness of the accompanying biomarkers could allow for the definition of precise risk profiles for age-associated immune disease onset and exacerbations.
2. Patients will benefit from new early detection strategies as well as new diagnostic approaches to differentiate disease onset in elderly people from onset in younger adults. This will inform a personalised medicine approach to treatment and will in turn help to prevent disease progression.
3. Patients and healthcare professionals will benefit from the repurposing or development of novel therapies for ageing populations with chronic inflammatory diseases and precision medicine approaches that prevent health decline while reducing healthcare costs.
4. Researchers and industry will benefit from the establishment of systematic collaborative approaches for the use of available biobanks across age ranges, immune diseases and comorbidities to adopt innovative approaches (by integration of multi-omics, immunophenotyping, digital biomarkers, ageing clocks, and artificial intelligence (AI) with comprehensive patient information).
5. Patients and healthcare professionals will benefit from deeper insights into treatment response and the evaluation of the impact of ageing on treatment effectiveness.
6. Industry and researchers will benefit from the establishment of regulatory pathways for novel intervention strategies and biomarkers, leading to the faster clinical development of drugs that improve age-associated disease exacerbations, ultimately enabling the translation of research findings into therapeutic solutions for vulnerable patient populations. This includes the field of digital biomarkers and their use in monitoring activity, strength and fatigue as exemplary readouts.

Scope:

The global population is undergoing an unprecedented demographic shift, with the number of individuals aged 65 and older projected to double by 2050, presenting one of the most significant public health challenges of our time. The transition to an ageing society is accompanied by a parallel rise in the prevalence of chronic diseases, multimorbidity, and years lived in poor health, placing immense strain on healthcare systems worldwide [1]. Central to this phenomenon is the progressive decline of immune function with age which not only increases susceptibility to infections and malignancies, but also drives chronic low-grade inflammation, known as "inflammaging" [2].

The profound age-related changes to the immune system are collectively termed immunosenescence. These changes include thymic involution, reduced naive T-cell production, expansion of memory T-cells with limited repertoire diversity, increased inflammatory cytokine production (inflammaging), and broad dysregulation of innate immunity [3] [4]. In parallel, senescent cells accumulate and secrete SASP cytokines—such as IL‑6, IL‑1β, and TNF—which further amplify inflammaging and contribute directly to age‑related immune dysfunction [5] [6]. Concurrently, there is a rising incidence of immune-mediated diseases with initial onset in elderly populations, including late-onset rheumatoid arthritis [7], elderly-onset inflammatory bowel disease (IBD) [8], late-onset systemic lupus erythematosus (SLE) [9] and late-onset respiratory diseases [10] [11].

Critically, advanced age is associated with the increased incidence of autoimmune and inflammatory diseases [12]. Moreover, older adults exhibit heightened vulnerability to immune-mediated pathologies ranging from late-onset autoimmune disorders to vaccine hyporesponsiveness and impaired tissue repair [13] [14]. Despite the clear clinical burden, the mechanistic underpinnings of how ageing reshapes immune homeostasis and disease susceptibility, and concomitantly, of how diseases reshape the ageing-process and the immune system, remain incompletely understood. A comprehensive understanding of the bidirectional relationship between immune system dysfunction and the ageing process is therefore imperative to develop targeted interventions that can prevent, delay, or reverse age-associated immune diseases and ultimately extend health span.

Despite their clinical significance, elderly-onset immune diseases remain poorly understood compared to their younger adult-onset counterparts. Evidence suggests that they may represent distinct disease entities with unique pathogenic mechanisms, clinical presentations, and treatment responses [15] [16]. The intersection of immunosenescence with pathological immune dysregulation presents both challenges and opportunities for targeted interventions.

Industry, regulators, researchers, and other stakeholders should address the critical gap in our understanding of how ageing-related immune changes contribute to disease pathogenesis in the elderly. New evidence-based findings should help to elucidate the molecular drivers of both elderly-onset immune diseases as well as immune disease exacerbations during ageing. In addition, these findings should help to identify predictive biomarkers, leading to age-appropriate therapeutic and prevention strategies accounting for the unique immunological context of older patients, and ultimately reducing the socio-economic burden for society.

The action funded under this topic therefore aims to elucidate the key biological determinants that drive healthy ageing and immune‑mediated disease, with a particular focus on how age‑associated immune system remodelling shapes these outcomes.

Applicants are expected to address all of the following objectives of the topic in their proposal:

Understanding molecular and clinical differences between younger adult-onset and elderly-onset diseases: The focus of the action should be on immune-mediated diseases with a peak of onset in elderly patients, such as inflammatory bowel disease and respiratory diseases, and specifically directed to diseases with mainly elderly onset.

Therefore, in summary the proposal should cover the following immune-mediated diseases:

• gastroenterological diseases: IBD like Crohn’s disease, ulcerative colitis;
• respiratory diseases: like asthma, chronic obstructive pulmonary disease, immune-mediated interstitial lung disease;
• rheumatoid diseases: like rheumatoid arthritis, giant cell arteritis, polymyalgia rheumatica, Sjögren’s disease, SLE.

The focus and the combination of these disease types would limit the risk of dispersion but still reflect different organ systems and enable crucial cross-disease comparisons.

Identify drivers of elderly-onset immune diseases: Determine the specific cellular and molecular mechanisms that trigger immune dysregulation uniquely in elderly populations.

Characterise factors driving disease exacerbations with ageing: Investigate how age-related physiological changes influence disease progression and flare frequency/severity.

Evaluate biological age as a driver of disease: Distinguish chronological from biological ageing in disease pathogenesis and identify predictive biomarkers for onset and exacerbations, including the influence of comorbidities.

Discriminate the molecular phenotypes and associated patient characteristics between chronologically aged versus biologically aged adults and elderly-onset disease patients. Understand patient heterogeneity in elderly-onset disease, both in regard to treatment response and molecular signatures.

Define the relevance of immunosenescence on biological and chronological ageing and whether there is a causal link between age, senescence and chronic inflammatory diseases including treatment response.

Identify common immunosenescence signatures across elderly-onset immune diseases: Elucidate shared pathways that might represent universal therapeutic targets.

Evaluate how vaccination history can contribute to reducing disease onset and/or exacerbation in older populations. Moreover, assess the translatability of system serology or other immunological endpoints as senescence markers.

Pathway identification and validation: AI / machine learning (ML)-assisted identification of underlying biological pathways and biomarkers from the gathered datasets. Evaluation of the impact of ageing on treatment effectiveness. Assessment of the predictiveness of identified biomarkers in ageing populations independent of underlying chronic inflammatory diseases.

Applicants should envisage the following activities as part of the action funded under this topic:

1. Applicants are expected to define a strategy to assess age-related disease phenotypes 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).

2. Applicants should detail their methodological approach, including verification strategies and data collection procedures, providing preliminary data to show potential for success and strategies for mitigating the main methodological risks and limitations.

The action should leverage both the wealth of existing cohorts, as well as the data from a new targeted observational cohort, which is expected to be set up by the consortium, and to include appropriate age-ranges and disease onset groups. New and existing observational cohorts should be used to evaluate the impact of standard of care treatments on the chosen diseases to define a path forward towards precision medicine and understanding age-dependent impacts of therapy response.

The analysis of existing and new bio-specimens (peripheral blood mononuclear cells, white blood cells, stool, saliva, urine, diseased tissues and exhaled breath condensate) should allow for the conduct of deep molecular profiling of the targeted chronic inflammatory diseases across various age ranges with appropriate age-matched control groups.

The wealth of data (both existing as well as newly created via the observational cohort), including participants’ clinical characteristics and health records (e.g. disease, comorbidities, frailty assessment, vaccination and infection history) gathered through state-of-the-art methodologies and technologies will enable the comprehensive analysis of chronological ageing, biological ageing markers, and immune signatures through:

• Immunological profiling: systems serology, immunophenotyping, T/B cell repertoire analysis, immunopeptidome.
• Molecular profiling (systemic and organ-specific) including RNASeq, scRNASeq, spatial transcriptomics, proteomics, metabolomics, epigenome.
• Evaluating and comparing multiple ageing clocks e.g. IMM-AGE, iAge, proteomic, somatic DNA mutations e.g. CHIP associated mutations, epigenetic (DNAm), RNA, and metabolic clocks.
• Metagenomic: Microbiome/Virome. The gut, lung and tissue-resident microbiomes are key modulators of immunosenescence and inflammaging and influence the onset and exacerbation of elderly-onset immune diseases. Integrated metagenomic and metabolomic profiling will be combined with immunophenotyping, ageing clocks and digital biomarkers to identify microbiome-driven signatures of biological ageing and disease risk. Incorporating host–microbiome interaction modelling will enable identification of modifiable pathways to support targeted prevention and early intervention strategies in ageing populations.
• Leveraging population-wide electronic health records with comorbidities, but also vaccination history, viral/bacterial infection data, and immunogenicity profiles as functional metrics to define immunosenescence.
• Applying AI-driven computational approaches to integrate multi-omics data with electronic health records and population-based disease registries to identify potential disease-agnostic senescence pathways and reveal both disease-agnostic as well as disease-specific mechanisms by which immunosenescence may drive the onset and progression of autoimmune diseases in elderly populations. The action should link identified changes with patient characteristics including disease severity, treatment response, comorbidities, age, and age at onset of disease. Appropriate verification strategies to bridge the gap between computational and biological outcomes should be developed whenever possible.
• Applying digital health technologies (e.g. wearables, in-soles, hand grip, sleep monitoring) and related digital biomarkers to assess physical function, track sleep and to correlate with molecular markers.

3. 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.

4. Applicants should include in their proposal a strategy to ensure sustainability of the outputs of the project, including data and samples collected, beyond the funding period.

5. Applicants should leverage experience from the European research infrastructures (ERICs) already working on the areas mentioned in this call topic to avoid overlaps and increase the impact of results.

The action funded under this topic is expected to consider potential synergies with projects that work on the area of interest of this topic.

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