Integrative analysis of multi-omics longitudinal data to identify effective strategies for the prediction and treatment of COVID-19
- Funded by Netherlands Organisation for Health Research and Development (ZonMW)
- Total publications:0 publications
Grant number: 1.043E+13
Grant search
Key facts
Disease
COVID-19Start & end year
20202022Known Financial Commitments (USD)
$548,510.27Funder
Netherlands Organisation for Health Research and Development (ZonMW)Principal Investigator
PendingResearch Location
NetherlandsLead Research Institution
Radboud University Medical CenterResearch Priority Alignment
N/A
Research Category
Clinical characterisation and management
Research Subcategory
Prognostic factors for disease severity
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
Project description Some of the COVID-19 patients develop very severe respiratory symptoms, while others experience mild flu-like symptoms. While it is clear that genetic and non-genetic factors influence the severity of the disease course, the underlying molecular mechanisms are unknown. As a result, disease progression cannot be predicted for an individual at this time. Research and expected outcomes This project aims to gain more insight into the disease and to predict its course by using long-term measurements of multi-omics data. The ultimate goal is to develop a treatment strategy for individual patients.