A diagnostic test to improve surveillance and care of COVID-19 patients

Grant number: 101016072

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2023
  • Known Financial Commitments (USD)

    $4,533,161.49
  • Funder

    European Commission
  • Principal Investigator

    DEVAUX Yvan
  • Research Location

    Luxembourg
  • Lead Research Institution

    LUXEMBOURG INSTITUTE OF HEALTH
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Diagnostics

  • Special Interest Tags

    Innovation

  • Study Type

    Clinical

  • Clinical Trial Details

    Not applicable

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Coronavirus disease 2019 (COVID-19) caused by infection with SARS coronavirus 2 (SARS-CoV-2) has reached pandemic proportions with more than 7 million people infected and 0.4 million people killed worldwide. Death rates are accentuated by cardiovascular comorbidities and arrhythmias leading to unexpected major cardiovascular events. Being able to identify COVID-19 patients at risk of developing cardiovascular events leading to death would allow improving surveillance and care. Currently, there is no accurate method to predict outcome of COVID-19 patients. COVIRNA is a patient-centered Innovation Action aiming to satisfy this urgent and unmet need. COVIRNA will complete and deploy a prognostic system based on cardiovascular biomarkers of COVID-19 clinical outcomes combined with digital tools and artificial intelligence analytics (i.e. prediction model). Complementary expertise of 15 EU partners from the healthcare sector, academia, association and industry will allow conducting a large retrospective study on existing cohorts of COVID-19 patients. By upscaling the already validated and patented research use only FIMICS panel of cardiac-enriched long noncoding RNA biomarkers into an in-vitro diagnostic test (COVIRNA) adapted to COVID-19 patients, the project will quickly deliver a minimally-invasive, simple yet robust and affordable prognosis tool that can be used in the context of the current COVID-19 crisis as well as in further major health issues. By tackling the cardiovascular complications in COVID-19, known to contribute significantly to mortality, the project outputs are expected to have a major impact on the pandemic outcomes. The COVIRNA test will be CE-marked and prepared for commercialization, allowing to risk stratify patients, adapt therapies and to inform drug design.

Publicationslinked via Europe PMC

Prognostic and predictive microRNA panels for heart failure patients with reduced or preserved ejection fraction: a meta-analysis of Kaplan-Meier-based individual patient data.

Blood CD45<sup>+</sup>/CD3<sup>+</sup> lymphocyte-released extracellular vesicles and mortality in hospitalized patients with coronavirus disease 2019.

EDITORIAL for BJP themed issue "noncoding RNA therapeutics".

Prediction of COVID-19 severity using machine learning.

Multiomic biomarkers after cardiac arrest.

CD66b+/CD68+ circulating extracellular vesicles, lactate dehydrogenase and neutrophil-to-lymphocyte ratio can differentiate coronavirus disease 2019 severity during and after infection.

Targeting noncoding RNAs to treat atherosclerosis.

Circular RNA regulatory role in pathological cardiac remodelling.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.