Respiratory Host-Pathogen Interaction
- Funded by European Commission
- Total publications:8 publications
Grant number: 101057129
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Key facts
Disease
COVID-19Start & end year
20222026Known Financial Commitments (USD)
$7,137,450Funder
European CommissionPrincipal Investigator
Krause TyraResearch Location
DenmarkLead Research Institution
STATENS SERUM INSTITUTResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Pathogen genomics, mutations and adaptations
Special Interest Tags
N/A
Study Type
Clinical
Clinical Trial Details
Not applicable
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Lower respiratory tract infections resulting from seasonal epidemics and pandemics are among the leading causes of death globally. There is a paucity of treatment options for viral respiratory pathogens and patient care remains largely supportive. This underscores a desperate need for identifying novel targets for prophylactic/treatment interventions and early prediction models of disease outcome to personalise treatment. The REACT consortium ? uniting high-level experts in virology, immunology, clinical medicine, epidemiology, and bioinformatics ? will assess genotypic, high-dimensional immunophenotypic, demographic and clinical data in the context of disease course to define host-pathogen interactions of viral respiratory tract infections, focusing on the predominating viruses i.e. influenza, respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In characterised, ethnically diverse clinical cohorts comprising patients with varying disease severities, we will genotype both virus and host, map deep immunological phenotypes spanning cellular, humoral and innate immunity, and characterise host responses in human nasal epithelial organoid models following viral infection. Novel bioinformatics approaches that include knowledge discovery and machine learning will be used to integrate and analyse multidisciplinary datasets to assess the individual and combined impact of factors on disease phenotype. Information on the deep characterisation of the dynamics of the immune responses to the chosen viruses and identified factors critical for viral control and immune protection will be made available on a dedicated project website to clinicians, researchers, health authorities, and public. This will provide direct and immediate access to our findings for further development of personalised treatment, therapeutic targets and vaccines in future trials and clinical practice to improve the wellbeing of the EU population and beyond.
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