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Divergent COVID-19 Disease Trajectories Predicted by a DAMP-Centered Immune Network Model.
Day, Judy D; Park, Soojin; Ranard, Benjamin L; Singh, Harinder; Chow, Carson C; Vodovotz, Yoram.
  • Day JD; Department of Mathematics, University of Tennessee, Knoxville, TN, United States.
  • Park S; Department of Electrical Engineering & Computer Science, University of Tennessee, Knoxville, TN, United States.
  • Ranard BL; Department of Neurology & Division of Critical Care and Hospital Neurology, Columbia University College of Physicians and Surgeons, New York Presbyterian Hospital - Columbia University Irving Medical Center, New York, NY, United States.
  • Singh H; Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University College of Physicians and Surgeons, New York, NY, United States.
  • Chow CC; Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University College of Physicians and Surgeons, New York, NY, United States.
  • Vodovotz Y; Division of Pulmonary, Allergy & Critical Care Medicine, Department of Medicine, Columbia University College of Physicians and Surgeons, New York Presbyterian Hospital - Columbia University Irving Medical Center, New York, NY, United States.
Front Immunol ; 12: 754127, 2021.
Article in English | MEDLINE | ID: covidwho-1518487
ABSTRACT
COVID-19 presentations range from mild to moderate through severe disease but also manifest with persistent illness or viral recrudescence. We hypothesized that the spectrum of COVID-19 disease manifestations was a consequence of SARS-CoV-2-mediated delay in the pathogen-associated molecular pattern (PAMP) response, including dampened type I interferon signaling, thereby shifting the balance of the immune response to be dominated by damage-associated molecular pattern (DAMP) signaling. To test the hypothesis, we constructed a parsimonious mechanistic mathematical model. After calibration of the model for initial viral load and then by varying a few key parameters, we show that the core model generates four distinct viral load, immune response and associated disease trajectories termed "patient archetypes", whose temporal dynamics are reflected in clinical data from hospitalized COVID-19 patients. The model also accounts for responses to corticosteroid therapy and predicts that vaccine-induced neutralizing antibodies and cellular memory will be protective, including from severe COVID-19 disease. This generalizable modeling framework could be used to analyze protective and pathogenic immune responses to diverse viral infections.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Alarmins / SARS-CoV-2 / COVID-19 / COVID-19 Drug Treatment / Models, Biological Type of study: Diagnostic study / Prognostic study Topics: Long Covid / Vaccines Limits: Adult / Aged / Humans / Middle aged Language: English Journal: Front Immunol Year: 2021 Document Type: Article Affiliation country: Fimmu.2021.754127

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Alarmins / SARS-CoV-2 / COVID-19 / COVID-19 Drug Treatment / Models, Biological Type of study: Diagnostic study / Prognostic study Topics: Long Covid / Vaccines Limits: Adult / Aged / Humans / Middle aged Language: English Journal: Front Immunol Year: 2021 Document Type: Article Affiliation country: Fimmu.2021.754127