Co-infecting pathogens can contribute to inflammatory responses and severe symptoms in COVID-19.

Background: The current COVID-19 pandemic is posing a major challenge to public health on a global scale. While it is generally believed that severe COVID-19 results from over-expression of inflammatory mediators (i.e., a "cytokine storm"), it is still unclear whether and how co-infecting pathogens contribute to disease pathogenesis. To address this, we followed the entire course of the disease in cases with severe or critical COVID-19 to determine the presence and abundance of all potential pathogens present-the total "infectome"-and how they interact with the host immune system in the context of severe COVID-19. Methods: We examined one severe and three critical cases of COVID-19, as well as a set of healthy controls, with longitudinal samples (throat swab, whole blood, and serum) collected from each case. Total RNA sequencing (meta-transcriptomics) was performed to simultaneously investigate pathogen diversity and abundance, as well as host immune responses, in each sample. A Bio-Plex method was used to measure serum cytokine and chemokine levels. Results: Eight pathogens, SARS-CoV-2, Aspergillus fumigatus (A. fumigatus), Mycoplasma orale (M. orale), Myroides odoratus (M. odoratus), Acinetobacter baumannii (A. baumannii), Candida tropicalis, herpes simplex virus (HSV) and human cytomegalovirus (CMV), identified in patients with COVID-19 appeared at different stages of the disease. The dynamics of inflammatory mediators in serum and the respiratory tract were more strongly associated with the dynamics of the infectome compared with SARS-CoV-2 alone. Correlation analysis revealed that pulmonary injury was directly associated with cytokine levels, which in turn were associated with the proliferation of SARS-CoV-2 and co-infecting pathogens. Conclusions: For each patient, the cytokine storm that resulted in acute lung injury and death involved a dynamic and highly complex infectome, of which SARS-CoV-2 was a component. These results indicate the need for a precision medicine approach to investigate both the infection and host response as a standard means of infectious disease characterization.

Adverse Outcomes Associated With Corticosteroid Use in Critical COVID-19: A Retrospective Multicenter Cohort Study.

Corticosteroid is commonly used to reduce damage from inflammatory reactions in coronavirus disease 2019 (COVID-19). We aim to determine the outcomes of corticosteroid use in critically ill COVID-19 patients. Ninety six critically ill patients, hospitalized in 14 hospitals outside Wuhan from January 16 to March 30, 2020 were enrolled in this study. Among 96 critical patients, 68 were treated with corticosteroid (CS group), while 28 were not treated with corticosteroids (non-CS group). Multivariable logistic regression were performed to determine the possible correlation between corticosteroid use and the treatment outcomes. Forty-six (68%) patients in the CS group died compared to six (21%) of the non-CS group. Corticosteroid use was also associated with the development of ARDS, exacerbation of pulmonary fibrosis, longer hospital stay and virus clearance time. On admission, no difference in laboratory findings between the CS and the non-CS group was observed. After corticosteroid treatment, patients treated with corticosteroids were associated with higher counts of white blood cells, neutrophils, neutrophil-to-lymphocyte ratio, alanine aminotransferase level and Sequential Organ Failure Assessment score. In conclusion, corticosteroid use in critically ill COVID-19 patients was associated with a much higher case fatality rate. Frequent incidence of liver injury and multi-organ failure in corticosteroid treated patients may have contributed to the adverse outcomes. The multi-organ failure is likely caused by more persistent SARS-CoV-2 infection and higher viral load, due to the inhibition of immune surveillance by corticosteroid.

Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study.

BACKGROUND: Prior studies reported that 5 ~ 32% COVID-19 patients were critically ill, a situation that poses great challenge for the management of the patients and ICU resources. We aim to identify independent risk factors to serve as prediction markers for critical illness of SARS-CoV-2 infection. METHODS: Fifty-two critical and 200 non-critical SARS-CoV-2 nucleic acid positive patients hospitalized in 15 hospitals outside Wuhan from January 19 to March 6, 2020 were enrolled in this study. Multivariable logistic regression and LASSO logistic regression were performed to identify independent risk factors for critical illness. RESULTS: Age older than 60 years, dyspnea, respiratory rate > 24 breaths per min, leukocytosis > 9.5 × 109/L, neutrophilia > 6.3 × 109/L, lymphopenia < 1.1 × 109/L, neutrophil-to-lymphocyte ratio > 3.53, fibrinogen > 4 g/L, d-dimer > 0.55 µg/mL, blood urea nitrogen > 7.1 mM, elevated aspartate transaminase, elevated alanine aminotransferase, total bilirubin > 21 µM, and Sequential Organ Failure Assessment (SOFA) score ≥ 2 were identified as risk factors for critical illness. LASSO logistic regression identified the best combination of risk factors as SOFA score, age, dyspnea, and leukocytosis. The Area Under the Receiver-Operator Curve values for the risk factors in predicting critical illness were 0.921 for SOFA score, 0.776 for age, 0.764 for dyspnea, 0.658 for leukocytosis, and 0.960 for the combination of the four risk factors. CONCLUSIONS: Our findings advocate the use of risk factors SOFA score ≥ 2, age > 60, dyspnea and leukocytosis > 9.5 × 109/L on admission, alone or in combination, to determine the optimal management of the patients and health care resources.

Human post-infection serological response to the spike and nucleocapsid proteins of SARS-CoV-2.

To inform seroepidemiological studies, we characterized the IgG- responses in COVID-19 patients against the two major SARS-CoV-2 viral proteins, spike (S) and nucleocapsid (N). We tested 70 COVID-19 sera collected up to 85 days post-symptom onset and 230 non-COVID-19 sera, including 27 SARS sera from 2003. Although the average SARS-CoV-2 S and N-IgG titers were comparable, N-responses were more variable among individuals. S- and N-assay specificity tested with non-COVID-19 sera were comparable at 97.5% and 97.0%, respectively. Therefore, S will make a better target due to its lower cross-reactive potential and its' more consistent frequency of detection compared to N.