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Cell specific peripheral immune responses predict survival in critical COVID-19 patients.
Amrute, Junedh M; Perry, Alexandra M; Anand, Gautam; Cruchaga, Carlos; Hock, Karl G; Farnsworth, Christopher W; Randolph, Gwendalyn J; Lavine, Kory J; Steed, Ashley L.
  • Amrute JM; Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Perry AM; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Anand G; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Cruchaga C; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Hock KG; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Farnsworth CW; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Randolph GJ; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Lavine KJ; Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63110, USA.
  • Steed AL; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, 63110, USA. steeda@wustl.edu.
Nat Commun ; 13(1): 882, 2022 02 15.
Article in English | MEDLINE | ID: covidwho-1692614
ABSTRACT
SARS-CoV-2 triggers a complex systemic immune response in circulating blood mononuclear cells. The relationship between immune cell activation of the peripheral compartment and survival in critical COVID-19 remains to be established. Here we use single-cell RNA sequencing and Cellular Indexing of Transcriptomes and Epitomes by sequence mapping to elucidate cell type specific transcriptional signatures that associate with and predict survival in critical COVID-19. Patients who survive infection display activation of antibody processing, early activation response, and cell cycle regulation pathways most prominent within B-, T-, and NK-cell subsets. We further leverage cell specific differential gene expression and machine learning to predict mortality using single cell transcriptomes. We identify interferon signaling and antigen presentation pathways within cDC2 cells, CD14 monocytes, and CD16 monocytes as predictors of mortality with 90% accuracy. Finally, we validate our findings in an independent transcriptomics dataset and provide a framework to elucidate mechanisms that promote survival in critically ill COVID-19 patients. Identifying prognostic indicators among critical COVID-19 patients holds tremendous value in risk stratification and clinical management.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Immunity, Cellular Type of study: Cohort study / Observational study / Prognostic study Limits: Aged / Female / Humans / Male / Middle aged Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-022-28505-3

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 / Immunity, Cellular Type of study: Cohort study / Observational study / Prognostic study Limits: Aged / Female / Humans / Male / Middle aged Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2022 Document Type: Article Affiliation country: S41467-022-28505-3