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Cross-omics integration to identify modulators for improving vaccine efficacy

Project description

Predicting variation in influenza vaccination response

Vaccination against influenza shows great variability in efficacy among individuals, but the underlying aetiology remains poorly understood. The scope of the EU-funded ModVaccine project is to shed light on the genetic, host and environmental determinants of vaccination response. Scientists will study vaccinated individuals and integrate omics data sets with immune phenotypes. The identified cell types, molecules and pathways involved in vaccine-induced immune responses will be fed into mathematical models capable of predicting individual variation in vaccination response. The ModVaccine prediction model has the potential to improve the future design of influenza vaccines.

Objective

Influenza is a significant public health threat and vaccines are crucial for preventing infections at population-level. The efficacy of vaccination per individual, however, is highly variable. The causes for this broad variability in vaccine response between individuals remain poorly understood. In this proposal, I hypothesize that genetic variants and their downstream pathways underlie the heterogeneity in vaccine response between individuals. This ERC project aims to for the first time, systematically investigate the interactions between genetic, non-genetic host and environmental factors, and the response to vaccination in order to build reliable models for predicting vaccine efficacy. The outcomes of this research will pinpoint key deterministic factors and identify modulators that can be used to improve vaccination strategies. This project is based on the expertise that my research group has built up for identifying the downstream consequences of genetic variants, and for predictive modelling through integration of large cross-omics datasets. Given the rapid evolution of influenza virus, I will use seasonal trivalent inactivated influenza vaccines as prototype responses within two cohorts of 500 individuals from the Netherlands and 200 individuals from Germany. I will systematically generate, analyse, and integrate the cross-omics data (six layers of information from genome, epigenome, transcriptome, proteome, metabolome, and microbiome) with immune phenotypes (e.g. antibody titers, an important indicator of protection) using novel computational methods. This research will reveal the previously unknown cell-types, molecules, and pathways involved in vaccine-induced immune response and provide mathematical models for predicting individual variation in immune response, a crucial first step towards personalized prevention. The key molecules I identify will provide leads for pharmacological modulators for improving vaccine efficacy.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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ERC-STG - Starting Grant

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Call for proposal

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(opens in new window) ERC-2020-STG

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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.

€ 1 499 871,00
Address
INHOFFENSTRASSE 7
38124 Braunschweig
Germany

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Region
Niedersachsen Braunschweig Braunschweig, Kreisfreie Stadt
Activity type
Research Organisations
Links
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.

€ 1 499 871,00

Beneficiaries (1)

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