دورية أكاديمية
أعرض في EDS

COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes.

التفاصيل البيبلوغرافية
العنوان: COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes.
المؤلفون: Jenner AL; Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.; Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada., Aogo RA; Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America., Alfonso S; Department of Physiology, McGill University, Montréal, Québec, Canada., Crowe V; Department of Mathematics and Statistics, Concordia University, Montréal, Québec, Canada., Deng X; Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.; Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada., Smith AP; Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America., Morel PA; Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America., Davis CL; Natural Science Division, Pepperdine University, Malibu, California, United States of America., Smith AM; Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America., Craig M; Sainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.; Department of Mathematics and Statistics, Université de Montréal, Montréal, Québec, Canada.; Department of Physiology, McGill University, Montréal, Québec, Canada.
المصدر: PLoS pathogens [PLoS Pathog] 2021 Jul 14; Vol. 17 (7), pp. e1009753. Date of Electronic Publication: 2021 Jul 14 (Print Publication: 2021).
نوع المنشور: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238921 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7374 (Electronic) Linking ISSN: 15537366 NLM ISO Abbreviation: PLoS Pathog Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science, c2005-
مواضيع طبية MeSH: Models, Immunological* , SARS-CoV-2*/immunology, COVID-19/*immunology, Biomarkers/metabolism ; CD8-Positive T-Lymphocytes/immunology ; COVID-19/virology ; Cohort Studies ; Computational Biology ; Computer Simulation ; Disease Susceptibility/immunology ; Host Microbial Interactions/immunology ; Humans ; Immunity, Innate ; Immunosuppression Therapy ; Interferons/metabolism ; Interleukin-6/metabolism ; Macrophages/immunology ; Pandemics ; Severity of Illness Index ; User-Computer Interface
مستخلص: To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.
Competing Interests: The authors have declared that no competing interests exist.
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معلومات مُعتمدة: R01 AI139088 United States AI NIAID NIH HHS
المشرفين على المادة: 0 (Biomarkers)
0 (IL6 protein, human)
0 (Interleukin-6)
9008-11-1 (Interferons)
تواريخ الأحداث: Date Created: 20210714 Date Completed: 20210805 Latest Revision: 20231102
رمز التحديث: 20231102
مُعرف محوري في PubMed: PMC8312984
DOI: 10.1371/journal.ppat.1009753
PMID: 34260666
قاعدة البيانات: MEDLINE
الوصف
تدمد:1553-7374
DOI:10.1371/journal.ppat.1009753