Association Between Risk of VTE and Mortality in Patients with COVID-19 (preprint)

Background: Hospitalized patients with COVID-19 appeared high risk of venous thromboembolism (VTE), which exhibited the predictor of mortality in non-COVID-19 patients. Objectives: We aimed to investigate the association between risk of VTE with 30-day mortality in COVID-19 patients.Methods: In this retrospective cohort study, 1030 consecutive hospitalized patients with COVID-19 were recruited in two hospitals of Wuhan, China. We collected baseline data on demographics, SOFA parameters, and VTE risk assessment models (RAMs) including Padua Prediction Score (PPS), IMPROVE and Caprini RAM. The primary outcome of the study was 30-day mortality. Results: Thirty-day mortality increased progressively from 2% in patients at low risk of VTE to 63% in those at high risk defined by PPS. Similar findings were also observed for risk of VTE defined by IMPROVE and Caprini score. Progressive increases in VTE risk also were associated with higher SOFA score. Our findings showed that the presence of high risk of VTE was independently associated with 30-day mortality regardless of adjusted gender, smoking status and some comorbidities with hazard ratios of 29.19, 37.37, 20.60 for PPS, IMPROVE and Caprini RAM, respectively (P< 0.001 for all comparisons). Predictive accuracy of PPS (AUC, 0.900), IMPROVE (AUC, 0.917) or Caprini RAM (AUC, 0.861) as the risk of 30-day mortality was markedly well.Conclusions: The presence of high risk of VTE identifies a group of patients with COVID-19 at higher risk for 30-day mortality. Furthermore, there is higher accuracy of VTE RAMs to predict 30-day mortality in these patients.

Association between Risk of Venous Thromboembolism and Mortality in Patients with COVID-19 (preprint)

Background: Hospitalized patients with COVID-19 appeared high risk of venous thromboembolism (VTE) defined by some risk assessment models (RAMs), which exhibited the predictor of mortality in patients with non-COVID-19. We aimed to investigate the association between risk of VTE with 30-day mortality in COVID-19 patients.Methods: In this retrospective cohort study, 1030 consecutive hospitalized patients, between January 26, 2020 and March 29, 2020, aged 14–98 years with a confirmed diagnosis of COVID-19-related pneumonia were recruited from Jinyintan Hospital and Union Hosptial, Wuhan, China. We collected baseline data on demographics, SOFA parameters, and VTE RAMs including Padua Prediction Score (PPS), IMPROVE RAM and Caprini RAM. The primary outcome of the study was 30-day mortality. The secondary outcome was the length of stay in hospital. Findings: Thirty-day mortality increased progressively from 2% in patients at low risk of VTE to 63% in those at high risk of VTE defined by PPS ≥ 4. Similar findings were also observed for risk of VTE defined by IMPROVE score ³ 2 and Caprini score ³ 5. Progressive increases in VTE risk also were associated with higher SOFA score. Our findings showed that the presence of high risk of VTE was independently associated with 30-day mortality regardless of adjusted gender, smoking status and some comorbidities with hazard ratios of 29.19 (95% CI 15.76 - 54.05), 37.37 (95% CI 18.43 - 75.78), 20.60 (95% CI 11.41 - 37.19) for PPS, IMPROVE RAM and Caprini RAM, respectively (P < 0.001 for all comparisons). Predictive accuracy of PPS (AUC, 0.900; 95% CI 0.881 - 0.919), IMPROVE RAM (AUC, 0.917; 95% CI 0.898 - 0.936) or Caprini RAM (AUC, 0.861; 95% CI 0.840 - 0.882) as the risk of 30-day mortality was markedly well.Interpretation: The presence of high risk of VTE identifies a group of patients with COVID-19 at higher risk for 30-day mortality. Furthermore, there is higher accuracy of VTE RAMs to predict 30-day mortality in COVID-19 hospitalized patients.Funding Statement: This study is funded by the National Nature Science Foundation of China (81870062 to Jinjun Jiang, 81900038 to Shujing Chen).Declaration of Interests: The authors have no conflict of interest to disclose.Ethics Approval Statement: The study was approved by Jinyintan Hospital Ethics Committee (KY2020-06.01) and Union Hospital Ethics Committee (2020-0039). Written informed consent was waived by the Ethics Commission.

SARS-CoV-2 ORF9c Is a Membrane-Associated Protein that Suppresses Antiviral Responses in Cells (preprint)

Disrupted antiviral immune responses are associated with severe COVID-19, the disease caused by SAR-CoV-2. Here, we show that the 73-amino-acid protein encoded by ORF9c of the viral genome contains a putative transmembrane domain, interacts with membrane proteins in multiple cellular compartments, and impairs antiviral processes in a lung epithelial cell line. Proteomic, interactome, and transcriptomic analyses, combined with bioinformatic analysis, revealed that expression of only this highly unstable small viral protein impaired interferon signaling, antigen presentation, and complement signaling, while inducing IL-6 signaling. Furthermore, we showed that interfering with ORF9c degradation by either proteasome inhibition or inhibition of the ATPase VCP blunted the effects of ORF9c. Our study indicated that ORF9c enables immune evasion and coordinates cellular changes essential for the SARS-CoV-2 life cycle. One-sentence summarySARS-CoV-2 ORF9c is the first human coronavirus protein localized to membrane, suppressing antiviral response, resembling full viral infection.

Identification of potential key genes for SARS-CoV-2 infected human bronchial organoids based on bioinformatics analysis (preprint)

There is an urgent need to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) that leads to COVID-19 and respiratory failure. Our study is to discover differentially expressed genes (DEGs) and biological signaling pathways by using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profiles of the GSE150819 datasets were originally produced using an Illumina NextSeq 500 (Homo sapiens). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) were utilized to identify functional categories and significant pathways. KEGG and GO results suggested that the Cytokine-cytokine receptor interaction, P53 signaling pathway, and Apoptosis are the main signaling pathways in SARS-CoV-2 infected human bronchial organoids (hBOs). Furthermore, NFKBIA, C3, and CCL20 may be key genes in SARS-CoV-2 infected hBOs. Therefore, our study provides further insights into the therapy of COVID-19.

Multi-organ Proteomic Landscape of COVID-19 Autopsies (preprint)

The molecular pathology of multi-organ injuries in COVID-19 patients remains unclear, preventing effective therapeutics development. Here, we report an in-depth multi-organ proteomic landscape of COVID-19 patient autopsy samples. By integrative analysis of proteomes of seven organs, namely lung, spleen, liver, heart, kidney, thyroid and testis, we characterized 11,394 proteins, in which 5336 were perturbed in COVID-19 patients compared to controls. Our data showed that CTSL, rather than ACE2, was significantly upregulated in the lung from COVID-19 patients. Dysregulation of protein translation, glucose metabolism, fatty acid metabolism was detected in multiple organs. Our data suggested upon SARS-CoV-2 infection, hyperinflammation might be triggered which in turn induces damage of gas exchange barrier in the lung, leading to hypoxia, angiogenesis, coagulation and fibrosis in the lung, kidney, spleen, liver, heart and thyroid. Evidence for testicular injuries included reduced Leydig cells, suppressed cholesterol biosynthesis and sperm mobility. In summary, this study depicts the multi-organ proteomic landscape of COVID-19 autopsies, and uncovered dysregulated proteins and biological processes, offering novel therapeutic clues. HIGHLIGHTSO_LICharacterization of 5336 regulated proteins out of 11,394 quantified proteins in the lung, spleen, liver, kidney, heart, thyroid and testis autopsies from 19 patients died from COVID-19. C_LIO_LICTSL, rather than ACE2, was significantly upregulated in the lung from COVID-19 patients. C_LIO_LIEvidence for suppression of glucose metabolism in the spleen, liver and kidney; suppression of fatty acid metabolism in the kidney; enhanced fatty acid metabolism in the lung, spleen, liver, heart and thyroid from COVID-19 patients; enhanced protein translation initiation in the lung, liver, renal medulla and thyroid. C_LIO_LITentative model for multi-organ injuries in patients died from COVID-19: SARS-CoV-2 infection triggers hyperinflammatory which in turn induces damage of gas exchange barrier in the lung, leading to hypoxia, angiogenesis, coagulation and fibrosis in the lung, kidney, spleen, liver, heart, kidney and thyroid. C_LIO_LITesticular injuries in COVID-19 patients included reduced Leydig cells, suppressed cholesterol biosynthesis and sperm mobility. C_LI

NVX-CoV2373 vaccine protects cynomolgus macaque upper and lower airways against SARS-CoV-2 challenge (preprint)

There is an urgent need for a safe and protective vaccine to control the global spread of SARS-CoV-2 and prevent COVID-19. Here, we report the immunogenicity and protective efficacy of a SARS-CoV-2 subunit vaccine (NVX-CoV2373) produced from the full-length SARS-CoV-2 spike (S) glycoprotein stabilized in the prefusion conformation. Cynomolgus macaques (Macaca fascicularis) immunized with NVX-CoV2373 and the saponin-based Matrix-M adjuvant induced anti-S antibody that was neutralizing and blocked binding to the human angiotensin-converting enzyme 2 (hACE2) receptor. Following intranasal and intratracheal challenge with SARS-CoV-2, immunized macaques were protected against upper and lower infection and pulmonary disease. These results support ongoing phase 1/2 clinical studies of the safety and immunogenicity of NVX-CoV2327 vaccine (NCT04368988). HighlightsO_LIFull-length SARS-CoV-2 prefusion spike with Matrix-M1 (NVX-CoV2373) vaccine. C_LIO_LIInduced hACE2 receptor blocking and neutralizing antibodies in macaques. C_LIO_LIVaccine protected against SARS-CoV-2 replication in the nose and lungs. C_LIO_LIAbsence of pulmonary pathology in NVX-CoV2373 vaccinated macaques. C_LI

Derivation and validation of a prognostic model for predicting in-hospital mortality in patients admitted with COVID-19 in Wuhan, China: the PLANS (Platelet Lymphocyte Age Neutrophil Sex) model (preprint)

OBJECTIVETo develop and validate a prognostic model for in-hospital mortality in COVID-19 patients using routinely collected demographic and clinical characteristics. DESIGNMulticenter, retrospective cohort study. SETTINGJinyintan Hospital, Union Hospital, and Tongji Hosptial in Wuhan, China. PARTICIPANTSA pooled derivation cohort of 1008 COVID-19 patients from Jinyintan Hospital, Union Hospital in Wuhan and an external validation cohort of 1031 patients from Tongji Hospital in Wuhan, China. MAIN OUTCOME MEASURESOutcome of interest was in-hospital mortality, treating discharged alive from hospital as the competing event. Fine-Gray models, using backward elimination for inclusion of predictor variables and allowing non-linear effects of continuous variables, were used to derive a prognostic model for predicting in-hospital mortality among COVID-19 patients. Internal validation was implemented to check model overfitting using bootstrap approach. External validation to a separate hospital was implemented to evaluate the generalizability of the model. RESULTSThe derivation cohort was a case-mix of mild-to-severe hospitalized COVID-19 patients (n=1008, 43.6% females, median age 55). The final model (PLANS), including five predictor variables of platelet count, lymphocyte count, age, neutrophil count, and sex, had an excellent predictive performance (optimism-adjusted C-index: 0.85, 95% CI: 0.83 to 0.87; averaged calibration slope: 0.95, 95% CI: 0.82 to 1.08). Internal validation showed little overfitting. External validation using an independent cohort (n=1031, 47.8% female, median age 63) demonstrated excellent predictive performance (C-index: 0.87, 95% CI: 0.85 to 0.89; calibration slope: 1.02, 95% CI: 0.92 to 1.12). The averaged predicted survival curves were close to the observed survival curves across patients with different risk profiles. CONCLUSIONSThe PLANS model based on the five routinely collected demographic and clinical characteristics (platelet count, lymphocyte count, age, neutrophil count, and sex) showed excellent discriminative and calibration accuracy in predicting in-hospital mortality in COVID-19 patients. This prognostic model would assist clinicians in better triaging patients and allocating healthcare resources to reduce COVID-19 fatality.