P-selectin Facilitates SARS-CoV-2 Spike 1 Subunit Attachment to Vesicular Endothelium and Platelets.

SARS-CoV-2 infection starts from the association of its spike 1 (S1) subunit with sensitive cells. Vesicular endothelial cells and platelets are among the cell types that bind SARS-CoV-2, but the effectors that mediate viral attachment on the cell membrane have not been fully elucidated. Herein, we show that P-selectin (SELP), a biomarker for endothelial dysfunction and platelet activation, can facilitate the attachment of SARS-CoV-2 S1. Since we observe colocalization of SELP with S1 in the lung tissues of COVID-19 patients, we perform molecular biology experiments on human umbilical vein endothelial cells (HUVECs) to confirm the intermolecular interaction between SELP and S1. SELP overexpression increases S1 recruitment to HUVECs and enhances SARS-CoV-2 spike pseudovirion infection. The opposite results are determined after SELP downregulation. As S1 causes endothelial inflammatory responses in a dose-dependent manner, by activating the interleukin (IL)-17 signaling pathway, SELP-induced S1 recruitment may contribute to the development of a "cytokine storm" after viral infection. Furthermore, SELP also promotes the attachment of S1 to the platelet membrane. Employment of PSI-697, a small inhibitor of SELP, markedly decreases S1 adhesion to both HUVECs and platelets. In addition to the role of membrane SELP in facilitating S1 attachment, we also discover that soluble SELP is a prognostic factor for severe COVID-19 through a meta-analysis. In this study, we identify SELP as an adhesive site for the SARS-CoV-2 S1, thus providing a potential drug target for COVID-19 treatment.

Novel inflammatory biomarkers in the prognosis of COVID-19.

BACKGROUND: The central role of inflammatory progression in the development of Coronavirus disease 2019 (COVID-19), especially in severe cases, is indisputable. However, the role of some novel inflammatory biomarkers in the prognosis of COVID-19 remains controversial. OBJECTIVE: To assess the effect of some novel inflammatory biomarkers in the occurrence and prognosis of COVID-19. METHODS: We systematically retrieved the studies related to COVID-19 and the inflammatory biomarkers of interest. The data of each biomarker in different groups were extracted, then were categorized and pooled. The standardized mean difference was chosen as an effect size measure to compare the difference between groups. RESULTS: A total of 90 studies with 12,059 participants were included in this study. We found higher levels of endocan, PTX3, suPAR, sRAGE, galectin-3, and monocyte distribution width (MDW) in the COVID-19 positive groups compared to the COVID-19 negative groups. No significant differences for suPAR and galectin-3 were detected between the severe group and mild/moderate group of COVID-19. In addition, the deaths usually had higher levels of PTX3, sCD14-ST, suPAR, and MDW at admission compared to the survivors. Furthermore, patients with higher levels of endocan, galectin-3, sCD14-ST, suPAR, and MDW usually developed poorer comprehensive clinical prognoses. CONCLUSIONS: In summary, this meta-analysis provides the most up-to-date and comprehensive evidence for the role of the mentioned novel inflammatory biomarkers in the prognosis of COVID-19, especially in evaluating death and other poor prognoses, with most biomarkers showing a better discriminatory ability.

Effect of Antidiabetic Therapy on Clinical Outcomes of COVID-19 Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis.

BACKGROUND: No study has yet systematically evaluated the effect of antidiabetic therapy on clinical outcomes of COVID-19 patients with type 2 diabetes (T2D). OBJECTIVE: We aimed to evaluate the effect of different antidiabetic therapy on clinical outcomes of COVID-19 patients with T2D. METHODS: We comprehensively retrieved the published research which examined the effect of antidiabetic therapy on clinical outcomes of COVID-19 patients with T2D. The odds ratio (OR) and its 95% confidence interval (95% CI) for clinical outcomes were calculated using the random-effects model, and meta-regression was adopted to evaluate the potential sources of heterogeneity between studies. RESULTS: A total of 54 studies were included in this study. We found that the use of metformin (OR = 0.66, 95% CI: 0.58-0.75), SGLT-2i (OR = 0.80, 95% CI: 0.73-0.88), and GLP-1ra (OR = 0.83, 95% CI: 0.70-0.98) were significantly associated with lower mortality risk in COVID-19 patients with T2D, while insulin use might unexpectedly increase the ICU admission rate (OR = 2.32, 95% CI: 1.34-4.01) and risk of death (OR = 1.52, 95% CI: 1.32-1.75). No statistically significant associations were identified for DPP-4i, SUs, AGIs, and TZDs. CONCLUSION AND RELEVANCE: We demonstrated that the usage of metformin, SGLT-2i, and GLP-1ra could significantly decrease mortality in COVID-19 patients with T2D. The heterogeneity across the studies, baseline characteristics of the included patients, shortage of dosage and the duration of antidiabetic drugs and autonomy of drug selection might limit the objectivity and accuracy of results. Further adequately powered and high-quality randomized controlled trials are warranted for conclusive findings.

Post-sequelae one year after hospital discharge among older COVID-19 patients: A multi-center prospective cohort study.

BACKGROUND: To systematically evaluate the prevalence of post-sequelae and chronic obstructive pulmonary disease assessment test (CAT) scoring one year after hospital discharge among older COVID-19 patients, as well as potential risk factors. METHODS: A multi-center prospective cohort study involving 1,233 eligible older COVID-19 patients was conducted. All patients were followed-up between Mar 1, 2021 and Mar 20, 2021. CAT scoring was adopted to measure symptom burden in COVID-19 patients. RESULTS: Of the 1233 eligible cases, 630 (51.1%) reported at least one sequelae. The top six post-sequelae included fatigue (32.4%), sweating (20.0%), chest tightness (15.8%), anxiety (11.4%), myalgia (9.0%), and cough (5.8%). Severe patients had significantly higher percentage of fatigue, sweating, chest tightness, myalgia, and cough (P<0.05), while anxiety was universal in all subjects. Sweating, anxiety, palpitation, edema of lower limbs, smell reduction, and taste change were emerging sequelae. Disease severity during hospitalization (OR: 1.46, 95% CI: 1.15-1.84, P = 0.002), and follow-up time (OR: 0.71, 95% CI: 0.50-0.99, P = 0.043) were independently associated with risk of post-sequelae, while disease severity during hospitalization was significantly associated with increased risk of emerging sequelae (OR: 1.33, 95% CI: 1.03-1.71, P = 0.029). The median of CAT score was 2 (0-5) in all patients, and a total of 120 patients (9.7%) had CAT scores ≥10. Disease severity during hospitalization (OR: 1.81, 95% CI: 1.23-2.67, P = 0.003) and age (OR: 1.07, 95% CI: 1.04-1.09, P<0.001) were significantly associated with increased risk of CAT scores ≥10. CONCLUSIONS: While the dramatic decline in the prevalence rate of persistent symptoms is reassuring, new sequelae among older COVID-19 patients cannot be ignored. Disease severity during hospitalization, age, and follow-up time contributed to the risk of post-sequelae and CAT scoring one year after hospital discharge among older COVID-19 patients. Our study provides valuable clues for long-term post-sequelae of the older COVID-19 patients, as well as their risk factors.