<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE186267" accession="SRP342403">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP342403</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA773094</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE186267</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Transcriptional reprogramming of infiltrating neutrophils drives lung disease in severe COVID-19 despite low viral load</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the ensuing COVID-19 pandemic have caused ~40 million cases and over 648,000 deaths in the United States alone. Troubling disparities in COVID-19-associated mortality emerged early, with nearly 70% of deaths confined to Black/African-American (AA) patients in some areas, yet targeted studies within this demographic are scant. Multi-omics single-cell analyses of immune profiles from airways and matching blood samples of Black/AA patients revealed low viral load, yet pronounced and persistent pulmonary neutrophilia with advanced features of cytokine release syndrome and acute respiratory distress syndrome (ARDS), including exacerbated production of IL-8, IL-1ß, IL-6, and CCL3/4 along with elevated levels of neutrophil elastase and myeloperoxidase. Circulating S100A12+/IFITM2+ mature neutrophils are recruited via the IL-8/CXCR2 axis, which emerges as a potential therapeutic target to reduce pathogenic neutrophilia and constrain ARDS in severe COVID-19. Overall design: Cells from blood and endotracheal aspirates (ETA) from 4 individual COVID-19 patients along with blood from 6 individual healthy participants for a total of 14 individual samples (10 blood, 4 ETA).</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE186267</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>36399523</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
  </STUDY>
</STUDY_SET>
