4.6 Article

Profiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression

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LIFE SCIENCE ALLIANCE
卷 4, 期 2, 页码 -

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LIFE SCIENCE ALLIANCE LLC
DOI: 10.26508/lsa.202000955

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  1. Translational Pathology Research Covid-19 grant
  2. National Center for Advancing Translational Science of the National Institute of Health [UL1TR002384]
  3. National Cancer Institute [T32CA203702]
  4. National Institutes of Health (NIH) [K08 AI132739]
  5. Clinical and Translational Science Center at Weill Cornell Medical College [KL2TR002385]
  6. NIH [T32 AI07613-19, K08 AI139360]
  7. Kellen Foundation
  8. Leukemia and Lymphoma Society (LLS), a startup grant from the Dept. of Radiation Oncology at Weill Cornell Medicine
  9. Functional Genomics Initiative (New York, US)

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A study on COVID-19 patients found dynamic changes in innate and adaptive immune cells during disease progression, with significant absolute changes in lymphocyte and myeloid cells in severe cases. Intubation and death were associated with selected natural killer cell KIR receptor usage and IgM+ B cells, along with profound CD4 and CD8 T-cell exhaustion.
With a rising incidence of COVID-19-associated morbidity and mortality worldwide, it is critical to elucidate the innate and adaptive immune responses that drive disease severity. We performed longitudinal immune profiling of peripheral blood mononuclear cells from 45 patients and healthy donors. We observed a dynamic immune landscape of innate and adaptive immune cells in disease progression and absolute changes of lymphocyte and myeloid cells in severe versus mild cases or healthy controls. Intubation and death were coupled with selected natural killer cell KIR receptor usage and IgM+ B cells and associated with profound CD4 and CD8 T-cell exhaustion. Pseudo-temporal reconstruction of the hierarchy of disease progression revealed dynamic time changes in the global population recapitulating individual patients and the development of an eight-marker classifier of disease severity. Estimating the effect of clinical progression on the immune response and early assessment of disease progression risks may allow implementation of tailored therapies.

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