COVID-19: Multi-Omics Approach to Identify Molecular Mechanisms Responsible for Risk and Resilience to Adverse Outcomes

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 1I01BX005442-01

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2021
    2023
  • Known Financial Commitments (USD)

    $0
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    Charles D Searles
  • Research Location

    United States of America
  • Lead Research Institution

    Veterans Health Administration
  • Research Priority Alignment

    N/A
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Prognostic factors for disease severity

  • Special Interest Tags

    N/A

  • Study Type

    Unspecified

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Objective: Emerging data from the COVID-19 pandemic indicate that men and African Americans have higher mortality, and cardiometabolic risk factors, including obesity, diabetes, and hypertension, cluster in patients who develop adverse outcomes to SARS-CoV-2 infection. The Veteran population is particularly vulnerable to COVID-19 because of the very high prevalence of cardiometabolic risk factors. However, not all Veterans with COVID-19 experience severe disease, and there is an urgent need to identify novel molecular pathways underlying risk and resilience to COVID-19. Previous work and preliminary studies from our team have demonstrated that targeted proteomics, metabolomics, and miRNA-omics can identify novel biomarkers and molecular pathways associated with cardiovascular health and disease. In this project, we will use a multi-omics to elucidate novel biomarkers and pathways associated with risk and resilience to severe COVID-19. Research Plan: In Aim 1, we will compare expression of pathway-specific biomarkers in hospitalized patients with severe COVID-19 with expression of these biomarkers in patients who do not develop severe COVID-19. Pathway-specific biomarkers reflecting activation of the renin-angiotensin-aldosterone system, systemic inflammation, oxidative stress, immune activation, thrombogenesis, and myocardial injury and stretch will be assessed. The primary endpoints for severe disease will be pathologic elevation of IL-6 levels or troponin I levels. Secondary endpoints will be requirement for mechanical ventilation, congestive heart failure, change in SOFA score, and death. In Aim 2, we will assess the extracellular miRNA and metabolomic profiles of the same two groups of hospitalized COVID-19 patients and determine miRNAs and metabolites differentially expressed between the two groups. Subsequently, we will examine connectivity between miRNA-metabolome networks and clinical endpoints in COVID-19 patients by performing an integrative analysis of differentially expressed miRNAs and metabolites, which will identify metabolic pathways associated with severe infection. Methods: The proposed studies will analyze de-identified blood samples and clinical data from COVID-19 patients hospitalized at the Atlanta VAMC and Emory University Hospital. The samples will be obtained from a bio repository that is currently banking residual plasma and serum from routine laboratory testing of COVID-19 patients. In Aim 1, we will measure levels of aminothiol (oxidative stress), suPAR (thrombogenesis/immune dysregulation), hsCRP (inflammation), hsTnI (myocardial injury), BNP (myocardial stretch), D-dimers (thrombogenesis), angiotensin II, angiotensin-(1-7) and plasma renin activity. Logistic regression modeling will be performed to identify biomarkers predictive of clinical endpoints. In Aim 2, we will use next generation sequencing, RT-qPCR, and high-throughput metabolomics profiling to assess expression of extracellular miRNAs and metabolites. A metabolome wide association study (MWAS) and ensemble feature selection (EFS) will be used to identify robust biomarkers and develop predictive models for severe COVID-19. Data from EFS analysis will input to the program xMWAS, which will determine connectivity between miRNA-metabolome networks and clinical outcomes. Clinical Relevance: Veterans with cardiovascular conditions are at higher risk for SARS-CoV-2 infection and severe disease progression. Our team has the infrastructure and methods in place to conduct in-depth, multi- omics studies to address predictors of adverse outcomes in Veterans with COVID-19 and identify epigenetic and cardiometabolic pathways that determine susceptibility to adverse outcomes. Furthermore, because 50% of the Veteran population at the Atlanta VA Medical Center Veteran is African American, we are in a unique position to address the role of race in susceptibility to severe COVID-19. Discovery of novel biomarkers and pathways associated with severe COVID-19 has broad implications for screening, therapeutics, and implementation of earlier personalized interventional strategies for attenuating adverse outcomes.