Genetic variety of ORF3a shapes SARS-CoV-2 fitness through modulation of lipid droplet.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection leads to the accumulation of lipid droplets (LD), the central hubs of the lipid metabolism, in vitro or in type II pneumocytes and monocytes from coronavirus disease 19 (COVID-19) patients and blockage of LD formation by specific inhibitors impedes SARS-CoV-2 replication. Here, we showed that ORF3a is necessary and sufficient to trigger LD accumulation during SARS-CoV-2 infection, leading to efficient virus replication. Although highly mutated during evolution, ORF3a-mediated LD modulation is conserved in most SARS-CoV-2 variants except the Beta strain and is a major difference between SARS-CoV and SARS-CoV-2 that depends on the genetic variations on the amino acid position 171, 193, and 219 of ORF3a. Importantly, T223I substitution in recent Omicron strains (BA.2-BF.8) impairs ORF3a-Vps39 association and LD accumulation, leading to less efficient replication and potentially contributing to lower pathogenesis of the Omicron strains. Our work characterized how SARS-CoV-2 modulates cellular lipid homeostasis to benefit its replication during virus evolution, making ORF3a-LD axis a promising drug target for the treatment of COVID-19.

Clinical efficacy and safety of high-flow nasal cannula (HFNC) in acute hypoxaemic patients with COVID-19: a protocol for a systematic review and meta-analysis.

INTRODUCTION: When COVID-19 patients develop hypoxaemic respiratory failure, they often undergo early intubation. Such a potentially aerosol-generating approach places caregivers at increased risk of contracting COVID-19. This protocol aims to evaluate the clinical efficacy and safety of a high-flow nasal cannula (HFNC) for the treatment of COVID-19 patients with acute hypoxaemic respiratory failure. METHODS AND ANALYSIS: We intend to search MEDLINE, Embase, Web of Science and Cochrane Library to identify all randomised controlled trials (RCTs) on the use of HFNC in COVID-19 patients with acute respiratory failure. We will screen the RCTs against eligibility criteria for inclusion in our review. Two reviewers will independently undertake RCT selection, data extraction and risk of bias assessment. Primary outcome will be the rate of intubation, and secondary outcomes will be intensive care unit (ICU)/hospital mortality, ICU/hospital length of stay and risks of infection transmission. We will conduct meta-analyses to determine the risk ratio for dichotomous data and the mean difference (MD) or standardised MD for continuous data. Subgroup analyses will be performed based on the different quality of studies, different levels of disease severity, and the age and sex of participants. ETHICS AND DISSEMINATION: Ethical approval is not required for this study considering this is a systematic review protocol that uses only published data. The findings of this study will be disseminated through peer-reviewed publications and conference presentations. PROSPERO REGISTRATION NUMBER: CRD42021236519.

ORF3a-Mediated Incomplete Autophagy Facilitates Severe Acute Respiratory Syndrome Coronavirus-2 Replication.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the causative agent for the coronavirus disease 2019 (COVID-19) pandemic and there is an urgent need to understand the cellular response to SARS-CoV-2 infection. Beclin 1 is an essential scaffold autophagy protein that forms two distinct subcomplexes with modulators Atg14 and UVRAG, responsible for autophagosome formation and maturation, respectively. In the present study, we found that SARS-CoV-2 infection triggers an incomplete autophagy response, elevated autophagosome formation but impaired autophagosome maturation, and declined autophagy by genetic knockout of essential autophagic genes reduces SARS-CoV-2 replication efficiency. By screening 26 viral proteins of SARS-CoV-2, we demonstrated that expression of ORF3a alone is sufficient to induce incomplete autophagy. Mechanistically, SARS-CoV-2 ORF3a interacts with autophagy regulator UVRAG to facilitate PI3KC3-C1 (Beclin-1-Vps34-Atg14) but selectively inhibit PI3KC3-C2 (Beclin-1-Vps34-UVRAG). Interestingly, although SARS-CoV ORF3a shares 72.7% amino acid identity with the SARS-CoV-2 ORF3a, the former had no effect on cellular autophagy response. Thus, our findings provide the mechanistic evidence of possible takeover of host autophagy machinery by ORF3a to facilitate SARS-CoV-2 replication and raise the possibility of targeting the autophagic pathway for the treatment of COVID-19.

Clinical characteristics and a decision tree model to predict death outcome in severe COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death. METHODS: A total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients. RESULTS: Of the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets. CONCLUSION: We performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.

Differences in the Clinical and Hematological Characteristics of COVID-19 Patients with and without Type 2 Diabetes.

OBJECTIVE: To examine whether comorbidity with type 2 diabetes (T2D) affects the clinical and hematological parameters of coronavirus disease 2019 (COVID-19) patients. METHODS: We retrospectively investigated the clinical, imaging, and laboratory characteristics of patients with confirmed COVID-19 who were hospitalized from January 30, 2020 to March 17, 2020, at the Renmin Hospital of Wuhan University. A detailed clinical record was kept for each subject, including the medical history of COVID-19 and physical and laboratory examinations. A total of 164 subjects were eligible for the study, among which 40 patients were comorbid with T2D. Further analysis was conducted in two subcohorts of sex- and age-matched patients with and without T2D to identify hematological and biochemical differences. The laboratory tests, including routine blood tests, serum biochemistry, and coagulation function, were performed upon admission. RESULTS: The two groups showed no significant differences in baseline parameters, including age, sex, chest X-ray, or computed tomography (CT) findings, upon admission. However, patients with T2D showed an increased incidence of diarrhea. T2D patients required more recovery time from pneumonia, as shown by follow-up CT findings, which might contribute to the prolonged hospitalization. Comorbidity with T2D also increased risk of secondary bacterial infection during COVID-19. The T2D group had significantly higher white blood cell and neutrophil counts compared with the nondiabetic group, but T2D patients suffered from more severe lymphocytopenia and inflammation (P < 0.05). Most biochemical parameters showed no significant differences between the two groups (P > 0.05). However, patients with T2D seemed to have a significantly higher risk of developing hyperlactatemia, hyponatremia, and hypocalcemia. CONCLUSIONS: COVID-19 patients comorbid with T2D demonstrated distinguishing clinical features and hematological parameters during the infection. It is necessary to develop a different clinical severity scoring system for COVID-19 patients with T2D. This study may provide helpful clues for the assessment and management of COVID-19 in T2D patients.

Distinguishable Immunologic Characteristics of COVID-19 Patients with Comorbid Type 2 Diabetes Compared with Nondiabetic Individuals.

BACKGROUND: COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has threatened every civilian as a global pandemic. The immune system poses the critical interactive chain between the human body and the virus. Here, we make efforts to examine whether comorbidity with type 2 diabetes (T2D) affects the immunological response in COVID-19 patients. METHODS: We conducted a retrospective pilot study investigating immunological characteristics of confirmed cases of COVID-19 with or without comorbid T2D. Two subcohorts of sex- and age-matched participants were eligible for data analysis, of which 33 participants were with T2D and the remaining 37 were nondiabetic (NDM). Cellular immunity was assessed by flow cytometric determination of surface markers including CD3, CD4, CD8, CD19, CD16, and CD56 in peripheral blood. Levels of C reactive protein, immunoglobulin (IgG, IgM, IgA, and IgE), and complements (C3, C4) were detected by rate nephelometry immunoassay. And Th1/Th2 cytokines (IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ) were detected by Cytometric Bead Array. RESULTS: Neutrophil counts were found to be significantly higher in the T2D group than in the NDM group and had a significant relevance with clinical severity. Lymphocyte frequencies showed no significant differences in the two groups. However, the proportions and absolute counts of T, Tc, Th, and NK cells decreased in both groups to different degrees. An abnormal increase in neutrophil count and a decrease in lymphocyte subpopulations may represent risk factors of COVID-19 severity. The level of IgG, IgM, IgA, C3, and C4 showed no significant difference between the two groups, while the IgE levels were higher in the T2D group than in the NDM group (p < 0.05). Th1 cytokines including IFN-γ, TNF-α, and IL-6, as well as CRP, appeared significantly higher in the T2D group. CONCLUSIONS: The COVID-19 patients comorbid with T2D demonstrated distinguishable immunological parameters, which represented clinical relevancies with the predisposed disease severity in T2D.

Clinical features and potential risk factors for discerning the critical cases and predicting the outcome of patients with COVID-19.

OBJECTIVE: To investigate the clinical features and risk factors for discerning the critical and predicting the outcome of patients with COVID-19. METHODS: Patients who were admitted to the intensive care unit (ICU) department and general infection department of TaiKang Tongji (Wuhan) Hospital from February 10 to March 27, 2020, were included. Data on clinical features, complications, laboratory parameters, chest CT, nutrient requirement, and electrolyte imbalance were analyzed retrospectively. RESULTS: A total of 123 (50 critical and 73 non-critical) patients were enrolled. 65% of patients with comorbidities, hypertension (45.5%), diabetes (21.9%), 36.5% of patients had more than one comorbidity. The proportion of lymphocytes in critical patients was significantly lower than that of non-critical patients. The proportion of patients with increased NLR, PLR, IL-6, CRP levels, and chest CT score was significantly higher in the critical than that of non-critical patients. The logistic regression analysis identified low lymphocyte count, high NLR, PLR, IL-6, CRP levels, and CT score as independent factors for discerning critical cases and high NLR, PLR, IL-6, and CT score could predict poor clinical outcome. Furthermore, we identified patients who needed nutrition support (HR 16.99) and with correction of electrolyte imbalance (HR 18.24) via intravenous injection were more likely to have a poor outcome. CONCLUSIONS: The potential risk factors of lower lymphocyte count, high levels of NLR, PLR, IL-6, CRP, chest CT score, and the statue of nutrient requirement or electrolyte imbalance could assist clinicians in discerning critical cases and predict the poor outcome in patients with COVID-19.