Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients

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Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients

1. View ORCID ProfileJérôme Hadjadj1,2,*,
2. View ORCID ProfileNader Yatim2,3,*,
3. Laura Barnabei1,
4. Aurélien Corneau4,
5. View ORCID ProfileJeremy Boussier3,
6. View ORCID ProfileNikaïa Smith3,
7. Hélène Péré5,6,
8. View ORCID ProfileBruno Charbit7,
9. View ORCID ProfileVincent Bondet3,
10. Camille Chenevier-Gobeaux8,
11. View ORCID ProfilePaul Breillat2,
12. View ORCID ProfileNicolas Carlier9,
13. Rémy Gauzit10,
14. Caroline Morbieu2,
15. View ORCID ProfileFrédéric Pène11,
16. Nathalie Marin11,
17. View ORCID ProfileNicolas Roche9,
18. View ORCID ProfileTali-Anne Szwebel2,
19. View ORCID ProfileSarah H Merkling12,
20. Jean-Marc Treluyer13,
21. David Veyer5,
22. View ORCID ProfileLuc Mouthon2,
23. Catherine Blanc4,
24. View ORCID ProfilePierre-Louis Tharaux6,
25. Flore Rozenberg14,
26. Alain Fischer1,15,16,
27. View ORCID ProfileDarragh Duffy3,7,†,
28. View ORCID ProfileFrédéric Rieux-Laucat1,†,
29. View ORCID ProfileSolen Kernéis10,17,†,
30. Benjamin Terrier2,6,†,‡

See all authors and affiliations

Science 13 Jul 2020:
eabc6027
DOI: 10.1126/science.abc6027

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Abstract
Coronavirus disease 2019 (COVID-19) is characterized by distinct patterns of disease progression suggesting diverse host immune responses. We performed an integrated immune analysis on a cohort of 50 COVID-19 patients with various disease severity. A unique phenotype was observed in severe and critical patients, consisting of a highly impaired interferon (IFN) type I response (characterized by no IFN-β and low IFN-α production and activity), associated with a persistent blood viral load and an exacerbated inflammatory response. Inflammation was partially driven by the transcriptional factor NF-κB and characterized by increased tumor necrosis factor (TNF)-α and interleukin (IL)-6 production and signaling. These data suggest that type-I IFN deficiency in the blood could be a hallmark of severe COVID-19 and provide a rationale for combined therapeutic approaches.

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Early clinical descriptions of the first SARS-CoV-2 coronavirus disease (COVID-19) cases at the end of 2019 rapidly highlighted distinct patterns of disease progression (1). Although most patients experience mild-to-moderate disease, 5-10% progress to severe or critical disease, including pneumonia and acute respiratory failure (2, 3). Based on data from patients with laboratory-confirmed COVID-19 from mainland China, admission to intensive care unit (ICU), invasive mechanical ventilation or death occurred in 6.1% of cases (1), and the death rate from recent current French data was 0.70% (3). This proportion of critical cases is higher than that estimated for seasonal Influenza (4). Additionally, relatively high rates of respiratory failure were reported in young adults (aged 50 years and lower) with previously mild comorbidities (e.g., hypertension, diabetes mellitus, overweight) (5). Severe cases can occur early in the disease course but clinical observations typically describe a two-step disease progression, starting with a mild-to-moderate presentation, followed by a secondary respiratory worsening 9-12 days after the first onset of symptoms (2, 6, 7). Respiratory deterioration is concomitant with extension of ground-glass lung opacities on chest computed tomography (CT) scans, lymphocytopenia, high prothrombin time and D-dimer levels (2). This biphasic evolution marked by a dramatic increase of acute phase reactants in the blood suggests a dysregulated inflammatory host response resulting in an imbalance between pro- and anti-inflammatory mediators. This leads to the subsequent recruitment and accumulation of leukocytes in tissues causing acute respiratory distress syndrome (ARDS) (8). However, little is known about the immunological features and the molecular mechanisms involved in COVID-19 severity.

To test the hypothesis of a virally-driven hyperinflammation leading to severe disease, we employed an integrative approach based on clinical and biological data, in-depth phenotypical analysis of immune cells, standardized whole-blood transcriptomic analysis and cytokine measurements on a group of fifty COVID-19 patients with variable severity from mild to critical.

COVID-19 patients (n = 50) and healthy controls (n = 18) were included. Patients’ characteristics are detailed in the supplementary materials and depicted in table S1 and fig. S1. Patients were analyzed after a median duration of 10 days (interquartile range, 9 -11 days) after disease onset. On admission, the degree of severity of COVID-19 was categorized as mild-to-moderate (n = 15 patients), severe (n = 17 patients) and critical (n = 18 patients).

As reported in previous studies (1, 2, 8), lymphocytopenia correlates with disease severity (Fig. 1A). To further characterize this, we used mass cytometry and performed Visualization of t-Distributed Stochastic Neighbor Embedding (viSNE) (9) to compare cell population densities according to disease severity (Fig. 1B). viSNE representation and differentiated cell counts showed a decrease in the density of NK cells and CD3+ T cells, including all T cell subsets, that was more pronounced for CD8+ T cells. This phenotype was more prominent in severe and critical patients, contrasting with an increase in the density of B cells and monocytes (Fig. 1, C to F). No major imbalance in CD4+ and CD8+ T cell naïve/memory subsets was observed (fig. S2). Data on T cell polarization and other minor T cell subsets are shown in fig. S3. Plasmablasts were enriched in all infected patients (Fig. 1F), as supported by the increase in genes associated with B cell activation and plasmablast differentiation, such as IL4R, TNFSF13B and XBP1 (fig. S4) but without any significant increase of serum immunoglobulin levels (fig. S5).

Fig. 1 Phenotyping of peripheral blood leukocytes in patients with SARS-CoV-2 infection.
(A) Lymphocyte counts in whole blood from COVID-19 patients were analyzed between days 8 and 12 after onset of first symptoms, according to disease severity. (B) viSNE map of blood leukocytes after exclusion of granulocytes, stained with 30 markers and measured with mass cytometry. Cells are automatically separated into spatially distinct subsets based on the combination of markers that they express. (C) viSNE map colored by cell density across disease severity (classified as healthy controls, mild-to-moderate, severe and critical). Red represents the highest density of cells. (D) Absolute number of CD3+ T cells, CD8+ T cells and CD3- CD56+ natural killer (NK) cells in peripheral blood from COVID-19 patients, according to disease severity. (E and F) Proportions (frequencies) of lymphocyte subsets from COVID-19 patients. Shown are (E) proportions of CD3+ T cells among lymphocytes, CD8+ T cells among CD3+ T cells and NK cells among lymphocytes; (F) proportions of CD19+ B cells among lymphocytes and CD38hi CD27hi plasmablasts among CD19+ B cells. (G) Analysis of the functional status of specific T cell subsets and NK cells based on the expression of activation (CD38, HLA-DR) and exhaustion (PD-1, Tim-3) markers. In (D) to (G), data indicate median. Each dot represents a single patient. P values were determined by the Kruskal-Wallis test, followed by Dunn’s post-test for multiple group comparisons with median reported; *P < 0.05; **P < 0.01; ***P < 0.001.


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Fig. 1 Phenotyping of peripheral blood leukocytes in patients with SARS-CoV-2 infection.