Prediction models for neutralization activity against emerging SARS-CoV-2 variants: A cross-sectional study.

Objective: Despite extensive vaccination campaigns to combat the coronavirus disease (COVID-19) pandemic, variants of concern, particularly the Omicron variant (B.1.1.529 or BA.1), may escape the antibodies elicited by vaccination against SARS-CoV-2. Therefore, this study aimed to evaluate 50% neutralizing activity (NT50) against SARS-CoV-2 D614G, Delta, Omicron BA.1, and Omicron BA.2 and to develop prediction models to predict the risk of infection in a general population in Japan. Methods: We used a random 10% of samples from 1,277 participants in a population-based cross-sectional survey conducted in January and February 2022 in Yokohama City, the most populous municipality in Japan. We measured NT50 against D614G as a reference and three variants (Delta, Omicron BA.1, and BA.2) and immunoglobulin G against SARS-CoV-2 spike protein (SP-IgG). Results: Among 123 participants aged 20-74, 93% had received two doses of SARS-CoV-2 vaccine. The geometric means (95% confidence intervals) of NT50 were 65.5 (51.8-82.8) for D614G, 34.3 (27.1-43.4) for Delta, 14.9 (12.2-18.0) for Omicron BA.1, and 12.9 (11.3-14.7) for Omicron BA.2. The prediction model with SP-IgG titers for Omicron BA.1 performed better than the model for Omicron BA.2 (bias-corrected R 2 with bootstrapping: 0.721 vs. 0.588). The models also performed better for BA.1 than for BA.2 (R 2 = 0.850 vs. 0.150) in a validation study with 20 independent samples. Conclusion: In a general Japanese population with 93% of the population vaccinated with two doses of SARS-CoV-2 vaccine, neutralizing activity against Omicron BA.1 and BA.2 were substantially lower than those against D614G or the Delta variant. The prediction models for Omicron BA.1 and BA.2 showed moderate predictive ability and the model for BA.1 performed well in validation data.

Multi-omics characterization of RNA binding proteins reveals disease comorbidities and potential drugs in COVID-19.

The COVID-19 has led to a devastating global health crisis, which emphasizes the urgent need to deepen our understanding of the molecular mechanism and identifying potential antiviral drugs. Here, we comprehensively analyzed the transcriptomic and proteomic profiles of 178 COVID-19 patients, ranging from asymptomatic to critically ill. Our analyses found that the RNA binding proteins (RBPs) were likely to be perturbed in infection. Interactome analysis revealed that RBPs interact with virus proteins and the viral interacting RBPs were likely to locate in central regions of human protein-protein interaction network. Functional enrichment analysis revealed that the viral interacting RBPs were likely to be enriched in RNA transport, apoptosis and viral genome replication-related pathways. Based on network proximity analyses of 299 human complex-disease genes and COVID-19-related RBPs in the human interactome, we revealed the significant associations between complex diseases and COVID-19. Network analysis also implicated potential antiviral drugs for treatment of COVID-19. In summary, our integrative characterization of COVID-19 patients may thus help providing evidence regarding pathophysiology and potential therapeutic strategies for COVID-19.

Lucidenic acid A inhibits the binding of hACE2 receptor with spike protein to prevent SARS-CoV-2 invasion.

High infection caused by mutations of SARS-CoV-2 calls for new prevention strategy. Ganoderma lucidum known as a superior immunoenhancer exhibits various antiviral effects, whether it can resist SARS-CoV-2 remains unclear. Herein, virtual screening combined with in vitro hACE2 inhibition assays were used to investigate its anti SARS-CoV-2 effect. Potential 54 active components, 80 core targets and 20 crucial pathways were identified by the component-target-pathway network. The binding characters of these components to hACE2 and its complexes with spike protein including omicron variant was analyzed by molecular docking. Lucidenic acid A was selected as the top molecule with high affinity to all receptors by forming hydrogen bonds. Molecular dynamics simulation showed it had good binding stability with the receptor proteins. Finally, in vitro FRET test demonstrated it inhibited the hACE2 activity with IC50 2 µmol/mL. Therefore, lucidenic acid A can prevent the virus invasion by blocking hACE2 binding with SARS-CoV-2.

Comprehensive characterization of human-virus protein-protein interactions reveals disease comorbidities and potential antiviral drugs.

The protein-protein interactions (PPIs) between human and viruses play important roles in viral infection and host immune responses. Rapid accumulation of experimentally validated human-virus PPIs provides an unprecedented opportunity to investigate the regulatory pattern of viral infection. However, we are still lack of knowledge about the regulatory patterns of human-virus interactions. We collected 27,293 experimentally validated human-virus PPIs, covering 8 virus families, 140 viral proteins and 6059 human proteins. Functional enrichment analysis revealed that the viral interacting proteins were likely to be enriched in cell cycle and immune-related pathways. Moreover, we analysed the topological features of the viral interacting proteins and found that they were likely to locate in central regions of human PPI network. Based on network proximity analyses of diseases genes and human-virus interactions in the human interactome, we revealed the associations between complex diseases and viral infections. Network analysis also implicated potential antiviral drugs that were further validated by text mining. Finally, we presented the Human-Virus Protein-Protein Interaction database (HVPPI, http://bio-bigdata.hrbmu.edu.cn/HVPPI), that provides experimentally validated human-virus PPIs as well as seamlessly integrates online functional analysis tools. In summary, comprehensive understanding the regulatory pattern of human-virus interactome will provide novel insights into fundamental infectious mechanism discovery and new antiviral therapy development.

Safety and immunogenicity of SARS-CoV-2 vaccines in Chinese patients with cirrhosis: a prospective multicenter study.

BACKGROUND: Data on safety and immunogenicity of coronavirus disease 2019 (COVID-19) vaccination in patients with compensated (C-cirrhosis) and decompensated cirrhosis (D-cirrhosis) are limited. METHODS: In this prospective multicenter study, adult participants with C-cirrhosis and D-cirrhosis were enrolled and received two doses of inactivated whole-virion COVID-19 vaccines. Adverse events were recorded within 14 days after any dose of vaccination, and serum samples of enrolled patients were collected and tested for SARS-CoV-2 neutralizing antibodies at least 14 days after the second dose. Risk factors for negative neutralizing antibody were analyzed. RESULTS: In total, 553 patients were enrolled from 15 centers in China, including 388 and 165 patients with C-cirrhosis and D-cirrhosis. The vaccines were well tolerated, most adverse reactions were mild and transient, and injection site pain (23/388 [5.9%] vs 9/165 [5.5%]) and fatigue (5/388 [1.3%] vs 3/165 [1.8%]) were the most frequently local and systemic adverse events in both the C-cirrhosis and D-cirrhosis groups. Overall, 4.4% (16/363) and 0.3% (1/363) of patients were reported Grades 2 and 3 alanine aminotransferase (ALT) elevations (defined as ALT > 2 upper limit of normal [ULN] but ≤ 5 ULN, and ALT > 5 ULN, respectively). The positive rates of COVID-19 neutralizing antibodies were 71.6% (278/388) and 66.1% (109/165) in C-cirrhosis and D-cirrhosis groups. Notably, Child-Pugh score of B and C levels was an independent risk factor of negative neutralizing antibody. CONCLUSIONS: Inactivated COVID-19 vaccinations are safe with acceptable immunogenicity in cirrhotic patients, and Child-Pugh score of B and C levels is associated with hyporesponsive to COVID-19 vaccination.

Association between Thyroid Disease and Severe Coronavirus Disease 2019 (COVID-19) Infection: A Meta-Analysis.

BACKGROUND: COVID-19 has resulted in an emerging respiratory infection with a pandemical diffusion since December 2019. We aimed to elucidate whether the presence of thyroid disease might increase the risk of severe COVID-19 infection. METHODS: Studies reporting seriously ill in COVID-19 patients with and without thyroid disease combined were searched and 11 relevant studies were subjected to our analysis, and pooled odds ratios (ORs) together with 95% confidence intervals (CIs) were calculated by using STATA and Review Manager Software. RESULTS: In total, 2,995 COVID-19 patients were included in this study. The pooled ORs were calculated using a fixed-effects model according to the heterogeneity. The pooled results revealed that thyroid disease was associated with severe COVID-19 infection in patients (OR = 2.14, 95 % CI: 1.23-3.72, P = 0.007). In the subgroup analysis by type of thyroid disease, hypothyroidism was positively associated with risks of severe COVID-19 infection (OR = 4.78, 95 % CI: 1.59-14.36, P = 0.005), however, no obvious difference was found in the risk regarding the severe COVID-19 infection amongst hyperthyroidism or unclassified thyroid disease. In addition, subgroup analysis stratified by ethnic groups demonstrated that thyroid disease was linked to the risks of severe COVID-19 infection in Asian patients (OR = 2.41, 95 % CI: 1.30-4.48, P = 0.005) rather than non-Asian (OR = 1.31, 95 % CI: 0.35-4.87, P = 0.684). CONCLUSION: This study indicates a correlation between thyroid disease and severe COVID-19 infection.

Collaborative governance in emergencies: community food supply in COVID-19 in Wuhan, China

Country governments and the WHO advocated that the "whole-of-government" and the "whole-of-society" approaches are necessary to fight against the pandemic. However, it is unclear what it means in practice and its implication in the of context of food security and in emergencies. This article examines in the “whole-of-government and whole-of-society approach” (WOG-WOS), how the government and non-government stakeholders’ has quickly engaged in collaborative governance to address the community food supply challenges. This research analysed government policies and reports, scanned grey literature and conduced in-depth interviews with key stakeholders in Wuhan working on the frontline of food supply during the first wave of COVID-19 lockdowns. The findings contribute to the literature on collaborative governance in emergency management. The case of Wuhan tells the point that the government and society are interdependent in emergencies. For the whole society to achieve its full potential, the government need to focus on the goals, function as an open-minded coordinator and adopt a flexible governing structure.

Risk Factors for Death Among the First 80 543 Coronavirus Disease 2019 (COVID-19) Cases in China: Relationships Between Age, Underlying Disease, Case Severity, and Region.

BACKGROUND: Knowledge of COVID-19 epidemiology remains incomplete and crucial questions persist. We aimed to examine risk factors for COVID-19 death. METHODS: A total of 80 543 COVID-19 cases reported in China, nationwide, through 8 April 2020 were included. Risk factors for death were investigated by Cox proportional hazards regression and stratified analyses. RESULTS: Overall national case-fatality ratio (CFR) was 5.64%. Risk factors for death were older age (≥80: adjusted hazard ratio, 12.58; 95% confidence interval, 6.78-23.33), presence of underlying disease (1.33; 1.19-1.49), worse case severity (severe: 3.86; 3.15-4.73; critical: 11.34; 9.22-13.95), and near-epicenter region (Hubei: 2.64; 2.11-3.30; Wuhan: 6.35; 5.04-8.00). CFR increased from 0.35% (30-39 years) to 18.21% (≥70 years) without underlying disease. Regardless of age, CFR increased from 2.50% for no underlying disease to 7.72% for 1, 13.99% for 2, and 21.99% for ≥3 underlying diseases. CFR increased with worse case severity from 2.80% (mild) to 12.51% (severe) and 48.60% (critical), regardless of region. Compared with other regions, CFR was much higher in Wuhan regardless of case severity (mild: 3.83% vs 0.14% in Hubei and 0.03% elsewhere; moderate: 4.60% vs 0.21% and 0.06%; severe: 15.92% vs 5.84% and 1.86%; and critical: 58.57% vs 49.80% and 18.39%). CONCLUSIONS: Older patients regardless of underlying disease and patients with underlying disease regardless of age were at elevated risk of death. Higher death rates near the outbreak epicenter and during the surge of cases reflect the deleterious effects of allowing health systems to become overwhelmed.