Elevated frequencies of CD14+HLA-DRlo/neg MDSCs in COVID-19 patients.

BACKGROUND: The immune responses, hyper-inflammation or immunosuppression, may be closely related to COVID-19 progression. We aimed to evaluate the changes of frequency of CD14+HLA-DRlo/neg MDSCs, a population of cells with potent immunosuppressive capacity, in COVID-19 patients. METHODS: The levels of CD14+HLA-DRlo/neg MDSCs were determined by flow cytometry in 27 COVID-19 patients, and their association with clinical characteristics and laboratory data were analyzed. RESULTS: The frequency of CD14+HLA-DRlo/neg MDSCs was elevated in COVID-19 patients, particularly severe patients. A follow-up comparison revealed a decline of CD14+HLA-DRlo/neg MDSCs percentages in most patients 1 day after testing negative for SARS-CoV-2 nucleic acid, but the levels of CD14+HLA-DRlo/neg MDSCs were still greater than 50.0% in 3 ICU patients 4-10 days after negative SARS-CoV-2 results. Elevated frequency of CD14+HLA-DRlo/neg MDSCs was positively correlated with oropharyngeal viral loads and length of hospital stay, while negatively correlated with lymphocyte counts and serum albumin. Moreover, strong correlations were observed between the frequency of CD14+HLA-DRlo/neg MDSCs and T cell subsets, NK cell counts, and B cell percentages. The frequency of CD14+HLA-DRlo/neg MDSCs could be used as a predictor of COVID-19 severity. CONCLUSIONS: A high frequency of CD14+HLA-DRlo/neg MDSCs, especially in severe patients, may indicate an immunoparalysis status and could be a predictor of disease severity and prognosis.

Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19.

BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk of developing serious illness. METHODS: We retrospectively analyzed 114 patients with COVID-19 at the Jinyintan Hospital, Wuhan based on their clinical and laboratory data. Patients were categorized into severe and mild to moderate disease groups. We analyzed the potential of serological inflammation indicators in predicting the severity of COVID-19 in patients using univariate and multivariate logistic regression, receiver operating characteristic curves, and nomogram analysis. The Spearman method was used to understand the correlation between the serological biomarkers and duration of hospital stay. RESULTS: Patients with severe disease had reduced neutrophils and lymphocytes; severe coagulation dysfunction; altered content of biochemical factors (such as urea, lactate dehydrogenase); elevated high sensitivity C-reactive protein levels, neutrophil-lymphocyte, platelet-lymphocyte, and derived neutrophil-lymphocyte ratios, high sensitivity C-reactive protein-prealbumin ratio (HsCPAR), systemic immune-inflammation index, and high sensitivity C-reactive protein-albumin ratio (HsCAR); and low lymphocyte-monocyte ratio, prognostic nutritional index (PNI), and albumin-to-fibrinogen ratio. PNI, HsCAR, and HsCPAR correlated with the risk of severe disease. The nomogram combining the three parameters showed good discrimination with a C-index of 0.873 and reliable calibration. Moreover, HsCAR and HsCPAR correlated with duration of hospital stay. CONCLUSION: Taken together, PNI, HsCAR, and HsCPAR may serve as accurate biomarkers for the prediction of disease severity in patients with COVID-19 upon admission/hospitalization.

Immune characteristics distinguish patients with severe disease associated with SARS-CoV-2.

This single-center, retrospective study aimed to explore the immune characteristics of COVID-19 and biomarkers to predict the severity of this disease. Patients infected with SARS-CoV-2 (n = 215) treated at the First Affiliated Hospital of Nanchang University from January 24 to March 12, 2020, were included in the study and classified into severe and non-severe groups. Peripheral immunocyte count and cytokine statuses were compared. The correlation between immune status, cytokine levels, and disease severity was analyzed. Leukocyte numbers were normal in both groups; however, they were relatively high (7.19 × 109/L) in patients of the severe group. Leukocyte distributions differed between the two groups; the severe group had a higher percentage of neutrophils and lower percentage of lymphocytes compared with the non-severe group, and absolute lymphocyte numbers were below normal in both groups, and particularly deficient in patients in the severe group. Lymphocyte counts have negative correlation with duration of hospital period whereas neutrophil count has no significant correlation with it. Of tested cytokines, IL-6 levels were significantly higher in the severe group (P = 0.0418). Low level of lymphocyte predicts severity of COVID-19. IL-6 levels were significantly higher in the severe group, especially in some extremely severe patients. But we did not detect the significant correlation between severity of COVID-19 with IL-6 level which may be due to limited case numbers. Our observations encourage future research to understand the underlying molecular mechanisms and to improve treatment outcome of COVID-19.

T-Cell Subset Counts in Peripheral Blood Can Be Used as Discriminatory Biomarkers for Diagnosis and Severity Prediction of Coronavirus Disease 2019.

This study evaluated the significance of lymphocyte subset detection in peripheral blood in the diagnosis and prognosis of coronavirus disease 2019 (COVID-19). Our results revealed that CD3+ T cells, CD4+ T cells, CD8+ T cells, and natural killer cells were significantly decreased in patients with COVID-19. These patients had a relatively slight decrease in CD4+ T cells but a severe decrease in CD8+ T cells. The significantly elevated CD4/CD8 ratio was observed in COVID-19 patients. T-cell subset counts were related to the severity and prognosis of COVID-19, suggesting that the counts of CD8+ T and CD4+ T cells can be used as diagnostic markers of COVID-19 and predictors of disease severity.