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Impairment of T cells' antiviral and anti-inflammation immunities dominates the death from COVID-19
Zhen-su She; Gregory Scholes; Luhao Zhang; Rong Li; Gang Song.
Affiliation
  • Zhen-su She; Peking University
  • Gregory Scholes; Princeton University
  • Luhao Zhang; Princeton University
  • Rong Li; Peking University
  • Gang Song; Beijing Hospital
Preprint in English | medRxiv | ID: ppmedrxiv-21256093
Journal article
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ABSTRACT
Clarifying dominant factors determining the immune heterogeneity from non-survivors to survivors is crucial for developing therapeutics and vaccines against COVID-19. The main difficulty is quantitatively analyzing the multi-level clinical data, including viral dynamics, immune response, and tissue damages. Here, we adopt a top-down modelling approach to quantify key functional aspects and their dynamical interplay in the battle between the virus and the immune system, yielding an accurate description of real-time clinical data involving hundreds of patients for the first time. The quantification of antiviral responses demonstrates that, compared to antibodies, T cells play a more dominant role in virus clearance, especially for mild patients (96.5%). Moreover, the anti-inflammatory responses, namely the cytokine inhibition and tissue repair rates, also positively correlate with T cell number and are significantly suppressed in non-survivors. Simulations show that the lack of T cells leads to more significant inflammation, proposing an explanation for the monotonous increase of COVID-19 mortality with age and higher mortality for males. We conclude that T cells play a crucial role in the immunity against COVID-19, which reveals a new direction----improvement of T cell number for advancing current prevention and treatment.
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Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2021 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2021 Document type: Preprint
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