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Observational Study
. 2021 Sep:110:83-92.
doi: 10.1016/j.ijid.2021.06.056. Epub 2021 Jul 1.

Immunological predictors of disease severity in patients with COVID-19

Asma Al Balushi  1 , Jalila AlShekaili  2 , Mahmood Al Kindi  3 , Zainab Ansari  4 , Murtadha Al-Khabori  5 , Faryal Khamis  6 , Zaiyana Ambusaidi  7 , Afra Al Balushi  8 , Aisha Al Huraizi  9 , Sumaiya Al Sulaimi  10 , Fatma Al Fahdi  11 , Iman Al Balushi  12 , Nenad Pandak  13 , Tom Fletcher  14 , Iman Nasr  15
Affiliations
Observational Study

Immunological predictors of disease severity in patients with COVID-19

Asma Al Balushi et al. Int J Infect Dis. 2021 Sep.

Abstract

Background: Identifying the immune cells involved in coronavirus disease 2019 (COVID-19) disease progression and the predictors of poor outcomes is important to manage patients adequately.

Methods: This prospective observational cohort study enrolled 48 patients with COVID-19 hospitalized in a tertiary hospital in Oman and 53 non-hospitalized patients with confirmed mild COVID-19.

Results: Hospitalized patients were older (58 years vs 36 years, P < 0.001) and had more comorbid conditions such as diabetes (65% vs 21% P < 0.001). Hospitalized patients had significantly higher inflammatory markers (P < 0.001): C-reactive protein (114 vs 4 mg/l), interleukin 6 (IL-6) (33 vs 3.71 pg/ml), lactate dehydrogenase (417 vs 214 U/l), ferritin (760 vs 196 ng/ml), fibrinogen (6 vs 3 g/l), D-dimer (1.0 vs 0.3 μg/ml), disseminated intravascular coagulopathy score (2 vs 0), and neutrophil/lymphocyte ratio (4 vs 1.1) (P < 0.001). On multivariate regression analysis, statistically significant independent early predictors of intensive care unit admission or death were higher levels of IL-6 (odds ratio 1.03, P = 0.03), frequency of large inflammatory monocytes (CD14+CD16+) (odds ratio 1.117, P = 0.010), and frequency of circulating naïve CD4+ T cells (CD27+CD28+CD45RA+CCR7+) (odds ratio 0.476, P = 0.03).

Conclusion: IL-6, the frequency of large inflammatory monocytes, and the frequency of circulating naïve CD4 T cells can be used as independent immunological predictors of poor outcomes in COVID-19 patients to prioritize critical care and resources.

Keywords: COVID-19; Immunological predictors; Inflammatory markers; Lymphocyte subsets; Mortality predictors.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no financial interests or personal relationships that might influence the work presented in this paper.

Figures

Figure 1
Figure 1
Distribution of CD4 and CD8 T cell subsets in the blood. (A) Representative flow cytometry analysis of the gating strategy, leukocytes (CD45+), T cell (CD3+), and CD4 and CD8 T cells. (B) Based on CD45RA and CCR7 expression, CD4 and CD8 have four main subsets: naïve (CD45RA+CCR7+), central memory (TCM, CD45RA−CCR7+), effector memory (TEM, CD45RA−CCR7−), and revertant effector memory TEMRA (CD45RA+CCR7−); CD4+ subset in the upper panel and CD8+ subsets in the lower panel. (C) The four main subsets, naïve (dark blue), TCM (green), TEM (light blue), and TEMRA (orange), are further divided into a different subset based on surface expression of CD27 and CD28. (D) CD4 is separated into T follicular helper cells (PD-1+CD45RA−). CD4 and CD8 are divided into cytotoxic (PD-1+CD57+) and senescence cells (PD-1−CD57+); CD4+ subset in the left panel and CD8+ subsets in the right panel.
Figure 2
Figure 2
Distribution of lymphocytes and monocytes. (A) Representative flow cytometry analysis of the gating strategy, leukocytes (CD45+), T cell (CD3+), B cell (CD19), NK cell (CD56), and CD4 and CD8 T cells. (B) Gating on CD3− followed by gating on CD19− and then CD14+ (upper two rows). Based on the size of CD14+ monocytes (small (orange) and large (green)), followed by expression of CD14 and CD16 (lower row).
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