Antibody responses to SARS-CoV-2 in patients with COVID-19.

We report acute antibody responses to SARS-CoV-2 in 285 patients with COVID-19. Within 19 days after symptom onset, 100% of patients tested positive for antiviral immunoglobulin-G (IgG). Seroconversion for IgG and IgM occurred simultaneously or sequentially. Both IgG and IgM titers plateaued within 6 days after seroconversion. Serological testing may be helpful for the diagnosis of suspected patients with negative RT-PCR results and for the identification of asymptomatic infections.

Construction of an autophagy interaction network based on competitive endogenous RNA reveals the key pathways and central genes of SARS-CoV-2 infection in vivo.

As of April 1, 2021, more than 2.8 million people have died of SARS-CoV-2 infection. In addition, the mutation of virus strains that have accompanied the pandemic has brought more severe challenges to pandemic control. Host microRNAs (miRNAs) are widely involved in a variety of biological processes of coronavirus infection, including autophagy in SARS-CoV-2 infection. However, the mechanisms underlying miRNAs involved in autophagy in SARS-CoV-2 infection have not been fully elucidated. In this study, the miRNA and messenger RNA (mRNA) expression profiles of patients with SARS-CoV-2 infection were investigated based on raw data from Gene Expression Omnibus (GEO) datasets, and potential novel biomarkers of autophagy were revealed by bioinformatics analyses. We identified 32 differentially expressed miRNAs and 332 differentially expressed mRNAs in patients with SARS-CoV-2 infection. Cytokine receptor related pathways were the most enriched pathways for differentially expressed miRNAs identified by pathway analysis. Most importantly, an autophagy interaction network, which was associated with the pathological processes of SARS-CoV-2 infection, especially with the cytokine storm, was constructed. In this network, hsa-miR-340-3p, hsa-miR-652-3p, hsa-miR-4772-5p, hsa-miR-192-5p, TP53INP2, and CCR2 may be biomarkers that predict changes in mild SARS-CoV-2 infection. Some molecules, including hsa-miR-1291 and CXCR4, were considered potential targets to predict the emergence of severe symptoms in SARS-CoV-2 infection. To our knowledge, this study provided the first profile analysis of an autophagy interaction network in SARS-CoV-2 infection and revealed several novel autophagy-related biomarkers for understanding the pathogenesis of SARS-CoV-2 infection in vivo.

Safety and efficacy of meplazumab in healthy volunteers and COVID-19 patients: a randomized phase 1 and an exploratory phase 2 trial.

Recent evidence suggests that CD147 serves as a novel receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Blocking CD147 via anti-CD147 antibody could suppress the in vitro SARS-CoV-2 replication. Meplazumab is a humanized anti-CD147 IgG2 monoclonal antibody, which may effectively prevent SARS-CoV-2 infection in coronavirus disease 2019 (COVID-19) patients. Here, we conducted a randomized, double-blinded, placebo-controlled phase 1 trial to evaluate the safety, tolerability, and pharmacokinetics of meplazumab in healthy subjects, and an open-labeled, concurrent controlled add-on exploratory phase 2 study to determine the efficacy in COVID-19 patients. In phase 1 study, 59 subjects were enrolled and assigned to eight cohorts, and no serious treatment-emergent adverse event (TEAE) or TEAE grade ≥3 was observed. The serum and peripheral blood Cmax and area under the curve showed non-linear pharmacokinetic characteristics. No obvious relation between the incidence or titer of positive anti-drug antibody and dosage was observed in each cohort. The biodistribution study indicated that meplazumab reached lung tissue and maintained >14 days stable with the lung tissue/cardiac blood-pool ratio ranging from 0.41 to 0.32. In the exploratory phase 2 study, 17 COVID-19 patients were enrolled, and 11 hospitalized patients were involved as concurrent control. The meplazumab treatment significantly improved the discharged (P = 0.005) and case severity (P = 0.021), and reduced the time to virus negative (P = 0.045) in comparison to the control group. These results show a sound safety and tolerance of meplazumab in healthy volunteers and suggest that meplazumab could accelerate the recovery of patients from COVID-19 pneumonia with a favorable safety profile.

Early prediction and identification for severe patients during the pandemic of COVID-19: A severe COVID-19 risk model constructed by multivariate logistic regression analysis.

BACKGROUND: As an emergent and fulminant infectious disease, Corona Virus Disease 2019 (COVID-19) has caused a worldwide pandemic. The early identification and timely treatment of severe patients are crucial to reducing the mortality of COVID-19. This study aimed to investigate the clinical characteristics and early predictors for severe COVID-19, and to establish a prediction model for the identification and triage of severe patients. METHODS: All confirmed patients with COVID-19 admitted by the Second Affiliated Hospital of Air Force Medical University were enrolled in this retrospective non-interventional study. The patients were divided into a mild group and a severe group, and the clinical data were compared between the two groups. Univariate and multivariate analysis were used to identify the independent early predictors for severe COVID-19, and the prediction model was constructed by multivariate logistic regression analysis. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the prediction model and each early predictor. RESULTS: A total of 40 patients were enrolled in this study, of whom 19 were mild and 21 were severe. The proportions of patients with venerable age (≥60 years old), comorbidities, and hypertension in severe patients were higher than that of the mild (P < 0.05). The duration of fever and respiratory symptoms, and the interval from illness onset to viral clearance were longer in severe patients (P < 0.05). Most patients received at least one form of oxygen treatments, while severe patients required more mechanical ventilation (P < 0.05). Univariate and multivariate analysis showed that venerable age, hypertension, lymphopenia, hypoalbuminemia and elevated neutrophil lymphocyte ratio (NLR) were the independent high-risk factors for severe COVID-19. ROC curves demonstrated significant predictive value of age, lymphocyte count, albumin and NLR for severe COVID-19. The sensitivity and specificity of the newly constructed prediction model for predicting severe COVID-19 was 90.5% and 84.2%, respectively, and whose positive predictive value, negative predictive value and crude agreement were all over 85%. CONCLUSIONS: The severe COVID-19 risk model might help clinicians quickly identify severe patients at an early stage and timely take optimal therapeutic schedule for them.

A Peptide-Based Magnetic Chemiluminescence Enzyme Immunoassay for Serological Diagnosis of Coronavirus Disease 2019.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel ß-coronavirus, causes severe pneumonia and has spread throughout the globe rapidly. The disease associated with SARS-CoV-2 infection is named coronavirus disease 2019 (COVID-19). To date, real-time reverse-transcription polymerase chain reaction (RT-PCR) is the only test able to confirm this infection. However, the accuracy of RT-PCR depends on several factors; variations in these factors might significantly lower the sensitivity of detection. METHODS: In this study, we developed a peptide-based luminescent immunoassay that detected immunoglobulin (Ig)G and IgM. The assay cutoff value was determined by evaluating the sera from healthy and infected patients for pathogens other than SARS-CoV-2. RESULTS: To evaluate assay performance, we detected IgG and IgM in the sera from confirmed patients. The positive rate of IgG and IgM was 71.4% and 57.2%, respectively. CONCLUSIONS: Therefore, combining our immunoassay with real-time RT-PCR might enhance the diagnostic accuracy of COVID-19.

Traditional Chinese Medicine: an effective treatment for 2019 novel coronavirus pneumonia (NCP).

The novel coronavirus pneumonia broke out in 2019 and spread rapidly. In 30 different countries, there are over seventy thousand patients have been diagnosed in total. Therefore, it is urgent to develop the effective program to prevent and treat for the novel coronavirus pneumonia. In view of Traditional Chinese Medicine has accumulated a solid theoretical foundation of plague in ancient and recent decades. Meanwhile, Traditional Chinese Medicine can provide the more effective and personalized treatment via adjusting the specific medicine for each patient based on the different syndromes. In addition, TCM often has different effect on the distinct stages of diseases, contributing to the prevention, treatment and rehabilitation. Nowadays, TCM has exhibited decent effect in the in the fight against NCP. Therefore, it is convinced that Traditional Chinese Medicine is an effective treatment for 2019 novel coronavirus pneumonia.