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Innate Immunity Plays a Key Role in Controlling Viral Load in COVID-19: Mechanistic Insights from a Whole-Body Infection Dynamics Model.
Dogra, Prashant; Ruiz-Ramírez, Javier; Sinha, Kavya; Butner, Joseph D; Peláez, Maria J; Rawat, Manmeet; Yellepeddi, Venkata K; Pasqualini, Renata; Arap, Wadih; Sostman, H Dirk; Cristini, Vittorio; Wang, Zhihui.
  • Dogra P; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas 77030, United States.
  • Ruiz-Ramírez J; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas 77030, United States.
  • Sinha K; DeBakey Heart and Vascular Center, Houston Methodist Hospital, Houston, Texas 77030, United States.
  • Butner JD; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas 77030, United States.
  • Peláez MJ; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas 77030, United States.
  • Rawat M; Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico 87131, United States.
  • Yellepeddi VK; Division of Clinical Pharmacology, Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, Utah 84132, United States.
  • Pasqualini R; Department of Pharmaceutics and Pharmaceutical Chemistry, College of Pharmacy, University of Utah, Salt Lake City, Utah 84112, United States.
  • Arap W; Rutgers Cancer Institute of New Jersey, Newark, New Jersey 07101, United States.
  • Sostman HD; Department of Radiation Oncology, Division of Cancer Biology, Rutgers New Jersey Medical School, Newark, New Jersey 07103, United States.
  • Cristini V; Rutgers Cancer Institute of New Jersey, Newark, New Jersey 07101, United States.
  • Wang Z; Department of Medicine, Division of Hematology/Oncology, Rutgers New Jersey Medical School, Newark, New Jersey 07103, United States.
ACS Pharmacol Transl Sci ; 4(1): 248-265, 2021 Feb 12.
Article in English | MEDLINE | ID: covidwho-1062731
Preprint
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ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pathogen of immense public health concern. Efforts to control the disease have only proven mildly successful, and the disease will likely continue to cause excessive fatalities until effective preventative measures (such as a vaccine) are developed. To develop disease management strategies, a better understanding of SARS-CoV-2 pathogenesis and population susceptibility to infection are needed. To this end, mathematical modeling can provide a robust in silico tool to understand COVID-19 pathophysiology and the in vivo dynamics of SARS-CoV-2. Guided by ACE2-tropism (ACE2 receptor dependency for infection) of the virus and by incorporating cellular-scale viral dynamics and innate and adaptive immune responses, we have developed a multiscale mechanistic model for simulating the time-dependent evolution of viral load distribution in susceptible organs of the body (respiratory tract, gut, liver, spleen, heart, kidneys, and brain). Following parameter quantification with in vivo and clinical data, we used the model to simulate viral load progression in a virtual patient with varying degrees of compromised immune status. Further, we ranked model parameters through sensitivity analysis for their significance in governing clearance of viral load to understand the effects of physiological factors and underlying conditions on viral load dynamics. Antiviral drug therapy, interferon therapy, and their combination were simulated to study the effects on viral load kinetics of SARS-CoV-2. The model revealed the dominant role of innate immunity (specifically interferons and resident macrophages) in controlling viral load, and the importance of timing when initiating therapy after infection.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: ACS Pharmacol Transl Sci Year: 2021 Document Type: Article Affiliation country: Acsptsci.0c00183

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Vaccines Language: English Journal: ACS Pharmacol Transl Sci Year: 2021 Document Type: Article Affiliation country: Acsptsci.0c00183