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Diagnostic model and assay for personalized vaccine

Project description

Diagnostic assay for personalised anti-influenza vaccine

Seasonal influenza is a major global health issue, causing hundreds of thousands of deaths annually. While influenza vaccines are vital for prevention, their effectiveness varies, especially in immunocompromised patients who are at greater risk for complications. Previous research has identified key biomarkers linked to vaccine responses. With this in mind, the ERC-funded DiMoVac project will develop a diagnostic assay to measure specific biomarkers and categorise patients based on their responsiveness to the influenza vaccine. The project will use samples from various patient cohorts for validation. After validation, it will integrate these biomarkers into a quick, reliable test to predict vaccine responsiveness. This project could improve influenza vaccine efficacy, reduce disease burden, and save lives.

Objective

Seasonal influenza poses a major global public health challenge, causing 3-5 million cases of severe illness and 290,000-650,000 deaths annually. Influenza vaccines are crucial for preventing illness, reducing severity of infection, and limiting virus transmission; however, their efficacy varies across populations due to factors such as immune status and pre-existing comorbidities. Immunocompromised patients (e.g. rheumatoid arthritis, HIV or organ transplant recipients) are particularly vulnerable to influenza and consequent complications include hospitalization and death, as their immune systems often fail to mount adequate responses to standard vaccines. Leveraging data from our previous ERC-St grant-funded studies, we analyzed the serological and multi-omics profiles of various cohorts across 5 time points over 4 influenza seasons. This analysis, covering multiple virus strains, identified robust molecular biomarkers linked to vaccine responses, which were validated through wet-lab experiments. Machine learning models based on pre-vaccination biomarkers were able to predict vaccine response in independent samples. Building on these findings, we propose to develop a diagnostic assay to measure these biomarkers and apply our established prediction model to stratify patients based on their responsiveness to the influenza vaccine. Samples from various patient cohorts, provided by our collaboration partners, will be used for verification and validation. Once validated, these biomarkers will be integrated into an innovative, fast, and reliable diagnostic test to predict vaccine responsiveness, through collaboration of an experienced industrial partner. Additionally, our team will create a user-interface app to translate biomarker measurements into diagnostic outcome. By enabling personalized vaccine strategies particularly for patients, this project has the potential to significantly improve influenza vaccine efficacy, reduce disease burden and ultimately save lives.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2024-POC

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Host institution

HELMHOLTZ-ZENTRUM FUR INFEKTIONSFORSCHUNG GMBH
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
INHOFFENSTRASSE 7
38124 Braunschweig
Germany

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Region
Niedersachsen Braunschweig Braunschweig, Kreisfreie Stadt
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Beneficiaries (1)

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