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SBIR Phase I: Using patient specific DNA methylation to predict COVID-19 clinical prognosis

  • Funded by National Science Foundation (NSF)
  • Total publications:2 publications

Grant number: 2034014

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $255,959
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Kristin Brogaard
  • Research Location

    United States of America
  • Lead Research Institution

    INHERENT BIOSCIENCES INC
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Diagnostics

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of an onsite, clinical test to screen incoming patients potentially infected with COVID-19 and prioritize hospital resources and personnel based on a predicted infection severity and treatment response. The benefits of a test that can predict COVID-19 infection severity are enormous. In addition to the millions of infections and hundreds of thousands of dealths, it costs hospitals an average of roughly $2,500 per day per patient for inpatient care. This project will develop a test for COVID-19 screening to accurately identify patients at risk.

This Small Business Innovation Research (SBIR) Phase I project is establishing the use of DNA methylation patterns for personalized screening and treatment for COVID-19. The variation in symptoms and outcomes for COVID-19 progression make it challenging for healthcare workers to triage accurately. The development of a DNA methylation-based test to predict the severity of COVID-19 infection will help manage the pandemic. This project will: 1) generate a comprehensive dataset of white blood cell DNA methylation patterns, health history, and clinical data for patients infected with COVID-19; 2) generate a predictive model for COVID-19 infection severity and treatment response. The anticipated technical results of this project are a testing method and a computer algorithm for predicting infection severity and treatment response based on a patient's unique DNA methylation pattern.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

2 Publications linked via Europe PMC

Epigenetic determinants of reproductive potential augment the predictive ability of the semen analysis.

Tissue-specific DNA methylation variability and its potential clinical value.