Evaluation of the role of vaccination in the COVID-19 pandemic based on the data from the 50 U.S. States.

Vaccination is considered as the ultimate weapon to end the pandemic. However, the role of vaccines in the pandemic remains controversial. To explore the impact of vaccination on the COVID-19 pandemic, we used logistic regression models to predict numbers of population-adjusted confirmed cases, deaths, intensive care unit (ICU) cases, case fatality rates and ICU admission rates of COVID-19 in the 50 U.S. states, based on 17 related variables. The logistic regression analysis showed that percentages of people vaccinated correlated inversely with the numbers of COVID-19 deaths and case fatality rates but showed no significant correlation with numbers of confirmed cases or ICU cases, or ICU admission rates. The Spearman correlation analysis showed that the percentages of people vaccinated correlated inversely with the numbers of COVID-19 deaths, ICU cases, ICU case rates, and case fatality rates but showed no significant correlation with numbers of confirmed cases. The number of deaths and mortality in the group after the vaccine usage were significantly lower than those in the group before the vaccine usage. However, after delta became the dominant strain, there were no longer significant differences in the number of deaths and the mortality rate between before and after delta became the dominant strain, although vaccines were used in both periods. Vaccination can significantly reduce COVID-19 deaths and mortality, while it cannot reduce the risk of COVID-19 infection. In addition to vaccination, other measures, such as social distancing, remain important in containing COVID-19 transmission and lower the risk of COVID-19 severe outcomes.

Comparisons of the immunological landscape of COVID-19 patients based on sex and disease severity by multi-omics analysis.

OBJECTIVE: To determine the differences in the immune response against SARS-CoV-2 infection of patients based on sex and disease severity. METHODS: We used an analytical framework of 382 transcriptional modules and multi-omics analyses to discriminate COVID-19 patients based on sex and disease severity. RESULTS: Male and female patients overexpressed modules related to the innate immune response. The expression of modules related to the adaptive immune response showed lower enrichment levels in males than females. Inflammation modules showed ascending overexpression in male and female patients, while a higher level was observed in severe female patients. Moderate female patients demonstrated significant overexpression to interferon, cytolytic lymphocyte, T & B cells, and erythrocytes modules. Moderate female patients showed a higher adaptive immune response than males matched group. Pathways involved in metabolism dysregulation and Hippo signaling were upregulated in females than in male patients. Females and moderate cases showed higher levels of metabolic dysregulation. CONCLUSIONS: The immune landscape in COVID-19 patients was noticeably different between the sexes, and these differences may highlight disease vulnerability in males. This study suggested that certain treatments that increase or decrease the immune responses to SARS-CoV-2 might be necessary for male and female patients at certain disease stages.

Comparisons of the immunological landscape between COVID-19, influenza, and respiratory syncytial virus patients by clustering analysis.

BACKGROUND: COVID-19 has stronger infectivity and a higher risk for severity than most other contagious respiratory illnesses. The mechanisms underlying this difference remain unclear. METHODS: We compared the immunological landscape between COVID-19 and two other contagious respiratory illnesses (influenza and respiratory syncytial virus (RSV)) by clustering analysis of the three diseases based on 27 immune signatures' scores. RESULTS: We identified three immune subtypes: Immunity-H, Immunity-M, and Immunity-L, which displayed high, medium, and low immune signatures, respectively. We found 20%, 35.5%, and 44.5% of COVID-19 cases included in Immunity-H, Immunity-M, and Immunity-L, respectively; all influenza cases were included in Immunity-H; 66.7% and 33.3% of RSV cases belonged to Immunity-H and Immunity-L, respectively. These data indicate that most COVID-19 patients have weaker immune signatures than influenza and RSV patients, as evidenced by 22 of the 27 immune signatures having lower enrichment scores in COVID-19 than in influenza and/or RSV. The Immunity-M COVID-19 patients had the highest expression levels of ACE2 and IL-6 and lowest viral loads and were the youngest. In contrast, the Immunity-H COVID-19 patients had the lowest expression levels of ACE2 and IL-6 and highest viral loads and were the oldest. Most immune signatures had lower enrichment levels in the intensive care unit (ICU) than in non-ICU patients. Gene ontology analysis showed that the innate and adaptive immune responses were significantly downregulated in COVID-19 versus healthy individuals. CONCLUSIONS: Compared to influenza and RSV, COVID-19 displayed significantly different immunological profiles. Elevated immune signatures are associated with better prognosis in COVID-19 patients.

Evaluation of the Current Therapeutic Approaches for COVID-19: A Systematic Review and a Meta-analysis.

Background: Limited data on the efficacy and safety of currently applied COVID-19 therapeutics and their impact on COVID-19 outcomes have raised additional concern. Objective and Methods: To estimate the efficacy and safety of COVID-19 therapeutics, we performed meta-analyses of the studies reporting clinical features and treatments of COVID-19 published from January 21 to September 6, 2020. Results: We included 136 studies that involved 102,345 COVID-19 patients. The most prevalent treatments were antibiotics (proportion: 0.59, 95% CI: [0.51, 0.67]) and antivirals (proportion: 0.52, 95% CI: [0.44, 0.60]). The combination of lopinavir/ritonavir and Arbidol was the most effective in treating COVID-19 (standardized mean difference (SMD) = 0.68, 95% CI: [0.15, 1.21]). The use of corticosteroids was associated with a small clinical improvement (SMD = -0.40, 95% CI: [-0.85, -0.23]), but with a higher risk of disease progression and death (mortality: RR = 9.26, 95% CI: [4.81, 17.80]; hospitalization length: RR = 1.54, 95% CI: [1.39, 1.72]; severe adverse events: RR = 2.65, 95% CI: [2.09, 3.37]). The use of hydroxychloroquine was associated with a higher risk of death (RR = 1.68, 95% CI: [1.18, 2.38]). The combination of lopinavir/ritonavir, ribavirin, and interferon-ß (RR = 0.34, 95% CI: [0.22, 0.54]); hydroxychloroquine (RR = 0.58, 95% CI: [0.39, 0.58]); and lopinavir/ritonavir (RR = 0.72, 95% CI: [0.56, 0.91]) was associated with reduced hospitalization length. Hydrocortisone (RR = 0.05, 95% CI: [0.03, 0.10]) and remdesivir (RR = 0.74, 95% CI: [0.62, 0.90]) were associated with lower incidence of severe adverse events. Dexamethasone was not significant in reducing disease progression (RR = 0.45, 95% CI: [0.16, 1.25]) and mortality (RR = 0.90, 95% CI: [0.70, 1.16]). The estimated combination of corticosteroids with antivirals was associated with a better clinical improvement than antivirals alone (SMD = -1.09, 95% CI: [-1.64, -0.53]). Conclusion: Antivirals are safe and effective in COVID-19 treatment. Remdesivir cannot significantly reduce COVID-19 mortality and hospitalization length, while it is associated with a lower incidence of severe adverse events. Corticosteroids could increase COVID-19 severity, but it could be beneficial when combined with antivirals. Our data are potentially valuable for the clinical treatment and management of COVID-19 patients.

Expression of SARS-COV-2 cell receptor gene ACE2 is associated with immunosuppression and metabolic reprogramming in lung adenocarcinoma based on bioinformatics analyses of gene expression profiles.

The aberrant expression level of SARS-CoV-2 cell receptor gene ACE2 was reported in lung adenocarcinoma (LUAD) comorbidity of COVID-19. However, the association of ACE2 expression levels with immunosuppression and metabolic reprogramming in LUAD remains lacking. We investigated the expression level of ACE2, an association of ACE2 expression level with various types of immune signatures, immune ratios, and pathways. We employed a weighted gene co-expression network analysis (WGCNA) R package to identify the gene modules and investigated prognostic roles of hub genes in LUAD. Overexpression of ACE2 level was found in LUAD and ACE2 expression was negatively associated with various types of immune signatures including CD8+ T cells, CD4+ regulatory T cells, NK cells, and T cell activation. Besides, ACE2 upregulation was not only associated with CD8+ T cell/CD4+ regulatory T cell ratios but also linked with downregulation of immune-markers including CD8A, KLRC1, GZMA, GZMB, NKG7, CCL4, and IFNG. Moreover, the ACE2 expression level was found to be associated with the enrichment level of various metabolic pathways and it was also found that the metabolic pathways are directly positively correlated with the increased expression levels of ACE2, indicating that the overexpression of ACE2 is associated with metabolic reprogramming in LUAD. Furthermore, WGCNA based analysis revealed the gene modules in the high-ACE2-expression-level group of LUAD and identified GCLC and SLC7A11 hub genes which are not only highly expressed in lung adenocarcinoma but also correlated with the poor survival prognosis. Our analysis of ACE2 in LUAD tissues suggests that ACE2 is not only a receptor but is also associated with immunosuppression and metabolic reprogramming. This study underlines the clue for understanding the clinical significance of ACE2 in COVID-19 patients with LUAD comorbidity.

Comparative Review of SARS-CoV-2, SARS-CoV, MERS-CoV, and Influenza A Respiratory Viruses.

The 2019 novel coronavirus (SARS-CoV-2) pandemic has caused a global health emergency. The outbreak of this virus has raised a number of questions: What is SARS-CoV-2? How transmissible is SARS-CoV-2? How severely affected are patients infected with SARS-CoV-2? What are the risk factors for viral infection? What are the differences between this novel coronavirus and other coronaviruses? To answer these questions, we performed a comparative study of four pathogenic viruses that primarily attack the respiratory system and may cause death, namely, SARS-CoV-2, severe acute respiratory syndrome (SARS-CoV), Middle East respiratory syndrome (MERS-CoV), and influenza A viruses (H1N1 and H3N2 strains). This comparative study provides a critical evaluation of the origin, genomic features, transmission, and pathogenicity of these viruses. Because the coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 is ongoing, this evaluation may inform public health administrators and medical experts to aid in curbing the pandemic's progression.