International Journal of Infectious Diseases (Dec 2020)

Patients with Covid-19 exhibit different immunological profiles according to their clinical presentation

  • M. Vassallo,
  • S. Manni,
  • P. Pini,
  • E. Blanchouin,
  • M. Ticchioni,
  • B. Seitz-Polski,
  • A. Puchois,
  • A. Sindt,
  • L. Lotte,
  • P. Fauque,
  • J. Durant

Journal volume & issue
Vol. 101
pp. 174 – 179

Abstract

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Objectives: A novel beta coronavirus has been identified as responsible for the 2019 coronavirus infection (Covid-19). Clinical presentations range from asymptomatic cases to acute respiratory distress syndrome with fatal outcome. Such a broad spectrum of disease expression calls for an investigation of immune response characteristics. Methods: We identified subjects admitted for Covid-19 in whom a large panel of immunological markers were measured, including B- and T- and NK-lymphocyte phenotypes, T-lymphocyte subpopulation cells and plasma cytokines. Patients were divided according to symptom severity during hospitalisation, in those with uncomplicated and complicated infection. Differences between groups were analyzed. Results: Seventeen patients were included (mean age: 83 years; 9 women; mean delay of symptoms onset: 4 days). Six had uncomplicated infection, while 11 developed complicated forms during hospitalization. CD10 + B lymphocyte levels were inversely correlated with clinical severity (5.8% vs 2.0%, p = 0.04) and CD10+ levels above 3% were independently associated with uncomplicated forms [Odds Ratio 0.04 (CI 0.002-0.795, p = 0.034)]. TNF-alpha, IL-1, Il-6 and Il-8 measurements upon admission differed between patients who died and those who survived (p < 0.01 for all comparisons). Conclusions: In a population of elderly patients recently infected with Covid-19, CD10 + B cell levels were inversely correlated with clinical severity. Cytokine values upon admission were highly predictive of fatal outcome during hospitalisation. These findings could explain differences in the clinical presentation and allow rapid identification of patients at risk for complications.

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