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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

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Key facts

  • Disease

    COVID-19

  • Start & end year

    2020
    2022

  • Known Financial Commitments (USD)

    $548,510.27

  • Funder

    Netherlands Organisation for Health Research and Development (ZonMW)

  • Principal Investigator

    Pending

  • Research Location

    Netherlands

  • Lead Research Institution

    Radboud University Medical Center

  • Research Priority Alignment

    N/A

  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Prognostic factors for disease severity

  • Special Interest Tags

    N/A

  • Study Subject

    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.