ABSTRACT
SARS-CoV-2-induced cytokine storms constitute the primary cause of COVID-19 progression, severity, criticality, and death. Glucocorticoid and anti-cytokine therapies have been frequently administered to treat COVID-19 but have had limited clinical efficacy in severe and critical cases. Nevertheless, the weaknesses of these treatment modalities have prompted the development of anti-inflammatory therapy against this infection. We found that the broad-spectrum anti-inflammatory agent inosine downregulated proinflammatory IL-6, upregulated anti-inflammatory IL-10, and ameliorated acute inflammatory lung injury caused by multiple infectious agents. Inosine significantly improved survival in mice infected with SARS-CoV-2. It indirectly impeded TANK-binding kinase 1 (TBK1) phosphorylation by binding stimulator of interferon genes (STING) and glycogen synthase kinase-3ß (GSK3ß), inhibited the activation and nuclear translocation of the downstream transcription factors IRF3 and NF-κB, and downregulated IL-6 in the sera and lung tissues of mice infected with lipopolysaccharide (LPS), H1N1, or SARS-CoV-2. Thus, inosine administration is feasible for clinical anti-inflammatory therapy against severe and critical COVID-19. Moreover, targeting TBK1 is a promising strategy for inhibiting cytokine storms and mitigating acute inflammatory lung injury induced by SARS-CoV-2 and other infectious agents.
ABSTRACT
New emerging severe acute respiratory syndrome 2 (SARS-CoV-2) has caused a worldwide pandemic. Several animal models of coronavirus disease 2019 (COVID-19) have been developed and applied to antiviral research. In this study, two lethal mouse-adapted SARS-CoV-2 variants (BMA8 and C57MA14) with different virulence were generated from different hosts, which are characterized by high viral replication titers in the upper and lower respiratory tract, pulmonary pathology, cytokine storm, cellular tropism, lymphopenia, and neutrophilia. Two variants exhibit host genetics-related and age-dependent morbidity and mortality in mice, exquisitely reflecting the clinical manifestation of asymptomatic, moderate, and severe COVID-19 patients. Notably, both variants equally weaken the neutralization capacity of the serum derived from COVID-19 convalescent, but the C57MA14 variant showed a much higher virulence than the BMA8 variant in vitro. Q489H substitution in the receptor-binding domain (RBD) of BMA8 and C57MA14 variants results in the receptors of SARS-CoV-2 switching from human angiotensin-converting enzyme 2 (hACE2) to murine angiotensin-converting enzyme 2 (mACE2). Additionally, A22D and A36V mutation in E protein were first reported in our study, which potentially contributed to the virulence difference between the two variants. Of note, the protective efficacy of the novel bacterium-like particle (BLP) vaccine candidate was validated using the BMA8- or C57MA14-infected aged mouse model. The BMA8 variant- and C57MA14 variant-infected models provide a relatively inexpensive and accessible evaluation platform for assessing the efficacy of vaccines and novel therapeutic approaches. This will promote further research in the transmissibility and pathogenicity mechanisms of SARS-CoV-2.
ABSTRACT
COVID-19 has spread globally with over 90,000,000 incidences and 1,930,000 deaths by Jan 11, 2021, which poses a big threat to public health. It is urgent to distinguish COVID-19 from common pneumonia. In this study, we reported multiple clinical feature analyses on COVID-19 in Inner Mongolia for the first time. We dynamically monitored multiple clinical features of all 75 confirmed COVID-19 patients, 219 pneumonia patients, and 68 matched healthy people in Inner Mongolia. Then, we studied the association between COVID-19 and clinical characteristics, based on which to construct a novel logistic regression model for predicting COVID-19. As a result, among the tested clinical characteristics, WBC, hemoglobin, C-reactive protein (CRP), ALT, and Cr were significantly different between COVID-19 patients and patients in other groups. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.869 for the logistic regression model using multiple factors associated with COVID-19. Furthermore, the CRP reaction showed five different time-series patterns with one-peak and double-peak modes. In conclusion, our study identified a few clinical characteristics significantly different between COVID-19 patients and others in Inner Mongolia. The features can be used to establish a reliable logistic regression model for predicting COVID-19.