ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic has devastated global health. Identifying key host factors essential for SARS-CoV-2 RNA replication is expected to unravel cellular targets for the development of broad-spectrum antiviral drugs which have been quested for the preparedness of future viral outbreaks. Here, we have identified host proteins that associate with nonstructural protein 12 (nsp12), the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 using a mass spectrometry (MS)-based proteomic approach. Among the candidate factors, CDK2 (Cyclin-dependent kinase 2), a member of cyclin-dependent kinases, interacts with nsp12 and causes its phosphorylation at T20, thus facilitating the assembly of the RdRp complex consisting of nsp12, nsp7 and nsp8 and promoting efficient synthesis of viral RNA. The crucial role of CDK2 in viral RdRp function is further supported by our observation that CDK2 inhibitors potently impair viral RNA synthesis and SARS-CoV-2 infection. Taken together, we have discovered CDK2 as a key host factor of SARS-CoV-2 RdRp complex, thus serving a promising target for the development of SARS-CoV-2 RdRp inhibitors.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , SARS-CoV-2/metabolism , RNA, Viral/genetics , RNA, Viral/metabolism , Cyclin-Dependent Kinase 2/genetics , Proteomics , COVID-19/genetics , Viral Nonstructural Proteins/genetics , RNA-Dependent RNA Polymerase/genetics , RNA-Dependent RNA Polymerase/chemistry , RNA-Dependent RNA Polymerase/metabolismABSTRACT
BACKGROUND: To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This model would assist frontline clinicians in optimizing medical treatment with limited resources. METHODS: 6415 patients from seven hospitals in Wuhan city were assigned to the training and testing cohorts. A total of 6351 patients from another three hospitals in Wuhan, 2169 patients from outside of Wuhan, and 553 patients from Milan, Italy were assigned to three independent validation cohorts. A total of 64 candidate clinical variables at hospital admission were analyzed by random forest and least absolute shrinkage and selection operator (LASSO) analyses. RESULTS: Eight factors, namely, Oxygen saturation, blood Urea nitrogen, Respiratory rate, admission before the date the national Maximum number of daily new cases was reached, Age, Procalcitonin, C-reactive protein (CRP), and absolute Neutrophil counts, were identified as having significant associations with mortality in COVID-19 patients. A composite score based on these eight risk factors, termed the OURMAPCN-score, predicted the risk of mortality among the COVID-19 patients, with a C-statistic of 0.92 (95% confidence interval [CI] 0.90-0.93). The hazard ratio for all-cause mortality between patients with OURMAPCN-score >11 compared with those with scores ≤ 11 was 18.18 (95% CI 13.93-23.71; p < .0001). The predictive performance, specificity, and sensitivity of the score were validated in three independent cohorts. CONCLUSIONS: The OURMAPCN score is a risk assessment tool to determine the mortality rate in COVID-19 patients based on a limited number of baseline parameters. This tool can assist physicians in optimizing the clinical management of COVID-19 patients with limited hospital resources.
Subject(s)
COVID-19 , Risk Assessment/methods , COVID-19/epidemiology , COVID-19/mortality , China , Hospitalization/statistics & numerical data , Humans , Italy , Risk FactorsABSTRACT
Type 2 diabetes (T2D) is a major comorbidity of COVID-19. However, the impact of blood glucose (BG) control on the degree of required medical interventions and on mortality in patients with COVID-19 and T2D remains uncertain. Thus, we performed a retrospective, multi-centered study of 7,337 cases of COVID-19 in Hubei Province, China, among which 952 had pre-existing T2D. We found that subjects with T2D required more medical interventions and had a significantly higher mortality (7.8% versus 2.7%; adjusted hazard ratio [HR], 1.49) and multiple organ injury than the non-diabetic individuals. Further, we found that well-controlled BG (glycemic variability within 3.9 to 10.0 mmol/L) was associated with markedly lower mortality compared to individuals with poorly controlled BG (upper limit of glycemic variability exceeding 10.0 mmol/L) (adjusted HR, 0.14) during hospitalization. These findings provide clinical evidence correlating improved glycemic control with better outcomes in patients with COVID-19 and pre-existing T2D.