Association of blood glucose level and prognosis of inpatients with coexistent diabetes and COVID-19.

Type 2 diabetes (T2D) increases the risk of coronavirus disease (COVID-19). This study investigates the association between glucose control of COVID-19 patients with T2D in first 7 days after hospital admission and prognosis. A total of 252 infected inpatients with T2D in China were included. Well-controlled blood glucose was defined as stable fasting blood glucose (FBG) levels in the range of 3.9-7.8 mmol/L during first 7 days using indicators of average (FBGA), maximum (FBGM) or first-time (FBG1) FBG levels. The primary endpoint was admission to intensive care unit or death. Hazard ratio (HR) of poorly controlled glucose level group compared with well-controlled group were 4.96 (P = 0.021) for FBGM and 5.55 (P = 0.014) for FBGA. Well-controlled blood glucose levels in first 7 days could improve the prognosis of COVID-19 inpatients with diabetes.

Laboratory Testing Implications of Risk-Stratification and Management of COVID-19 Patients.

Objective: To distinguish COVID-19 patients and non-COVID-19 viral pneumonia patients and classify COVID-19 patients into low-risk and high-risk at admission by laboratory indicators. Materials and methods: In this retrospective cohort, a total of 3,563 COVID-19 patients and 118 non-COVID-19 pneumonia patients were included. There are two cohorts of COVID-19 patients, including 548 patients in the training dataset, and 3,015 patients in the testing dataset. Laboratory indicators were measured during hospitalization for all patients. Based on laboratory indicators, we used the support vector machine and joint random sampling to risk stratification for COVID-19 patients at admission. Based on laboratory indicators detected within the 1st week after admission, we used logistic regression and joint random sampling to develop the survival mode. The laboratory indicators of COVID-10 and non-COVID-19 were also compared. Results: We first identified the significant laboratory indicators related to the severity of COVID-19 in the training dataset. Neutrophils percentage, lymphocytes percentage, creatinine, and blood urea nitrogen with AUC >0.7 were included in the model. These indicators were further used to build a support vector machine model to classify patients into low-risk and high-risk at admission in the testing dataset. Results showed that this model could stratify the patients in the testing dataset effectively (AUC = 0.89). Our model still has good performance at different times (Mean AUC: 0.71, 0.72, 0.72, respectively for 3, 5, and 7 days after admission). Moreover, laboratory indicators detected within the 1st week after admission were able to estimate the probability of death (AUC = 0.95). We identified six indicators with permutation p < 0.05, including eosinophil percentage (p = 0.007), white blood cell count (p = 0.045), albumin (p = 0.041), aspartate transaminase (p = 0.043), lactate dehydrogenase (p = 0.002), and hemoglobin (p = 0.031). We could diagnose COVID-19 and differentiate it from other kinds of viral pneumonia based on these laboratory indicators. Conclusions: Our risk-stratification model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage of COVID-19. In addition, laboratory findings could be used to distinguish COVID-19 and non-COVID-19.

Sex-based clinical and immunological differences in COVID-19.

BACKGROUND: Males and females differ in their immunological responses to foreign pathogens. However, most of the current COVID-19 clinical practices and trials do not take the sex factor into consideration. METHODS: We performed a sex-based comparative analysis for the clinical outcomes, peripheral immune cells, and severe acute respiratory syndrome coronavirus (SARS-CoV-2) specific antibody levels of 1558 males and 1499 females COVID-19 patients from a single center. The lymphocyte subgroups were measured by Flow cytometry. The total antibody, Spike protein (S)-, receptor binding domain (RBD)-, and nucleoprotein (N)- specific IgM and IgG levels were measured by chemiluminescence. RESULTS: We found that male patients had approximately two-fold rates of ICU admission (4.7% vs. 2.7% in males and females, respectively, P = 0.005) and mortality (3% vs. 1.4%, in males and females, respectively, P = 0.004) than female patients. Survival analysis revealed that the male sex is an independent risk factor for death from COVID-19 (adjusted hazard ratio [HR] = 2.22, 95% confidence interval [CI]: 1.3-3.6, P = 0.003). The level of inflammatory cytokines in peripheral blood was higher in males during hospitalization. The renal (102/1588 [6.5%] vs. 63/1499 [4.2%], in males and females, respectively, P = 0.002) and hepatic abnormality (650/1588 [40.9%] vs. 475/1499 [31.7%], P = 0.003) were more common in male patients than in female patients. By analyzing dynamic changes of lymphocyte subsets after symptom onset, we found that the percentage of CD19+ B cells and CD4+ T cells was generally higher in female patients during the disease course of COVID-19. Notably, the protective RBD-specific IgG against SARS-CoV-2 sharply increased and reached a peak in the fourth week after symptom onset in female patients, while gradually increased and reached a peak in the seventh week after symptom onset in male patients. CONCLUSIONS: Males had an unfavorable prognosis, higher inflammation, a lower percentage of lymphocytes, and indolent antibody responses during SARS-CoV-2 infection and recovery. Early medical intervention and close monitoring are important, especially for male COVID-19 patients.

Identification and functional analysis of the SARS-COV-2 nucleocapsid protein.

BACKGROUND: A severe form of pneumonia, named coronavirus disease 2019 (COVID-19) by the World Health Organization is widespread on the whole world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was proved to be the main agent of COVID-19. In the present study, we conducted an in depth analysis of the SARS-COV-2 nucleocapsid to identify potential targets that may allow identification of therapeutic targets. METHODS: The SARS-COV-2 N protein subcellular localization and physicochemical property was analyzed by PSORT II Prediction and ProtParam tool. Then SOPMA tool and swiss-model was applied to analyze the structure of N protein. Next, the biological function was explored by mass spectrometry analysis and flow cytometry. At last, its potential phosphorylation sites were analyzed by NetPhos3.1 Server and PROVEAN PROTEIN. RESULTS: SARS-COV-2 N protein composed of 419 aa, is a 45.6 kDa positively charged unstable hydrophobic protein. It has 91 and 49% similarity to SARS-CoV and MERS-CoV and is predicted to be predominantly a nuclear protein. It mainly contains random coil (55.13%) of which the tertiary structure was further determined with high reliability (95.76%). Cells transfected with SARS-COV-2 N protein usually show a G1/S phase block company with an increased expression of TUBA1C, TUBB6. At last, our analysis of SARS-COV-2 N protein predicted a total number of 12 phosphorylated sites and 9 potential protein kinases which would significantly affect SARS-COV-2 N protein function. CONCLUSION: In this study, we report the physicochemical properties, subcellular localization, and biological function of SARS-COV-2 N protein. The 12 phosphorylated sites and 9 potential protein kinase sites in SARS-COV-2 N protein may serve as promising targets for drug discovery and development for of a recombinant virus vaccine.

Implications of liver injury in risk-stratification and management of patients with COVID-19.

BACKGROUND: Infection with SARS-CoV-2 has been associated with liver dysfunction, aggravation of liver burden, and liver injury. This study aimed to assess the effects of liver injuries on the clinical outcomes of patients with COVID-19. METHODS: A total of 1520 patients with severe or critical COVID-19 from Huoshenshan Hospital, Wuhan, were enrolled. Chronic liver disease (CLD) was confirmed by consensus diagnostic criteria. Laboratory test results were compared between different groups. scRNA-seq data and bulk gene expression profiles were used to identify cell types associated with liver injury. RESULTS: A total of 10.98% of patients with severe or critical COVID-19 developed liver injury after admission that was associated with significantly higher rates of mortality (21.74%, p < 0.001) and intensive care unit admission (26.71%, p < 0.001). Pre-existing CLDs were not associated with a higher risk. However, fatty liver disease and cirrhosis were associated with higher risks, supported by evidences from single cell and bulk transcriptome analysis that showed more TMPRSS2+ cells in these tissues. By generating a model, we were able to predict the risk and severity of liver injury during hospitalization. CONCLUSION: We demonstrate that liver injury occurring during therapy as well as pre-existing CLDs like fatty liver disease and cirrhosis in patients with COVID-19 is significantly associated with the severity of disease and mortality, but the presence of other CLD is not associated. We provide a risk-score model that can predict whether patients with COVID-19 will develop liver injury or proceed to higher-risk stages during subsequent hospitalizations.

Dynamic changes in anti-SARS-CoV-2 antibodies during SARS-CoV-2 infection and recovery from COVID-19.

Deciphering the dynamic changes in antibodies against SARS-CoV-2 is essential for understanding the immune response in COVID-19 patients. Here we analyze the laboratory findings of 1,850 patients to describe the dynamic changes of the total antibody, spike protein (S)-, receptor-binding domain (RBD)-, and nucleoprotein (N)-specific immunoglobulin M (IgM) and G (IgG) levels during SARS-CoV-2 infection and recovery. The generation of S-, RBD-, and N-specific IgG occurs one week later in patients with severe/critical COVID-19 compared to patients with mild/moderate disease, while S- and RBD-specific IgG levels are 1.5-fold higher in severe/critical patients during hospitalization. The RBD-specific IgG levels are 4-fold higher in older patients than in younger patients during hospitalization. In addition, the S- and RBD-specific IgG levels are 2-fold higher in the recovered patients who are SARS-CoV-2 RNA negative than those who are RNA positive. Lower S-, RBD-, and N-specific IgG levels are associated with a lower lymphocyte percentage, higher neutrophil percentage, and a longer duration of viral shedding. Patients with low antibody levels on discharge might thereby have a high chance of being tested positive for SARS-CoV-2 RNA after recovery. Our study provides important information for COVID-19 diagnosis, treatment, and vaccine development.