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.

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications.

The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.

The role of lung macrophages in acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS) is an acute and diffuse inflammatory lung injury in a short time, one of the common severe manifestations of the respiratory system that endangers human life and health. As an innate immune cell, macrophages play a key role in the inflammatory response. For a long time, the role of pulmonary macrophages in ARDS has tended to revolve around the polarization of M1/M2. However, with the development of single-cell RNA sequencing, fate mapping, metabolomics, and other new technologies, a deeper understanding of the development process, classification, and function of macrophages in the lung are acquired. Here, we discuss the function of pulmonary macrophages in ARDS from the two dimensions of anatomical location and cell origin and describe the effects of cell metabolism and intercellular interaction on the function of macrophages. Besides, we explore the treatments for targeting macrophages, such as enhancing macrophage phagocytosis, regulating macrophage recruitment, and macrophage death. Considering the differences in responsiveness of different research groups to these treatments and the tremendous dynamic changes in the gene expression of monocyte/macrophage, we discussed the possibility of characterizing the gene expression of monocyte/macrophage as the biomarkers. We hope that this review will provide new insight into pulmonary macrophage function and therapeutic targets of ARDS.

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.

The trans-omics landscape of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) is a global health emergency. Various omics results have been reported for COVID-19, but the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here we collect blood samples from 231 COVID-19 patients, prefiltered to exclude those with selected comorbidities, yet with symptoms ranging from asymptomatic to critically ill. Using integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles, we report a trans-omics landscape for COVID-19. Our analyses find neutrophils heterogeneity between asymptomatic and critically ill patients. Meanwhile, neutrophils over-activation, arginine depletion and tryptophan metabolites accumulation correlate with T cell dysfunction in critical patients. Our multi-omics data and characterization of peripheral blood from COVID-19 patients may thus help provide clues regarding pathophysiology of and potential therapeutic strategies for COVID-19.

Identification and Prediction of Novel Clinical Phenotypes for Intensive Care Patients With SARS-CoV-2 Pneumonia: An Observational Cohort Study.

Background: Phenotypes have been identified within heterogeneous disease, such as acute respiratory distress syndrome and sepsis, which are associated with important prognostic and therapeutic implications. The present study sought to assess whether phenotypes can be derived from intensive care patients with coronavirus disease 2019 (COVID-19), to assess the correlation with prognosis, and to develop a parsimonious model for phenotype identification. Methods: Adult patients with COVID-19 from Tongji hospital between January 2020 and March 2020 were included. The consensus k means clustering and latent class analysis (LCA) were applied to identify phenotypes using 26 clinical variables. We then employed machine learning algorithms to select a maximum of five important classifier variables, which were further used to establish a nested logistic regression model for phenotype identification. Results: Both consensus k means clustering and LCA showed that a two-phenotype model was the best fit for the present cohort (N = 504). A total of 182 patients (36.1%) were classified as hyperactive phenotype, who exhibited a higher 28-day mortality and higher rates of organ dysfunction than did those in hypoactive phenotype. The top five variables used to assign phenotypes were neutrophil-to-lymphocyte ratio (NLR), ratio of pulse oxygen saturation to the fractional concentration of oxygen in inspired air (Spo2/Fio2) ratio, lactate dehydrogenase (LDH), tumor necrosis factor α (TNF-α), and urea nitrogen. From the nested logistic models, three-variable (NLR, Spo2/Fio2 ratio, and LDH) and four-variable (three-variable plus TNF-α) models were adjudicated to be the best performing, with the area under the curve of 0.95 [95% confidence interval (CI) = 0.94-0.97] and 0.97 (95% CI = 0.96-0.98), respectively. Conclusion: We identified two phenotypes within COVID-19, with different host responses and outcomes. The phenotypes can be accurately identified with parsimonious classifier models using three or four variables.

Specific cytokines in the inflammatory cytokine storm of patients with COVID-19-associated acute respiratory distress syndrome and extrapulmonary multiple-organ dysfunction.

BACKGROUND: To date, specific cytokines associated with development of acute respiratory distress syndrome (ARDS) and extrapulmonary multiple organ dysfunction (MOD) in COVID-19 patients have not been systematically described. We determined the levels of inflammatory cytokines in patients with COVID-19 and their relationships with ARDS and extrapulmonary MOD. METHODS: The clinical and laboratory data of 94 COVID-19 patients with and without ARDS were analyzed. The levels of inflammatory cytokines (interleukin 6 [IL-6], IL-8, IL-10, and tumor necrosis factor α [TNF-α]) were measured on days 1, 3, and 5 following admission. Seventeen healthy volunteers were recruited as controls. Correlations in the levels of inflammatory cytokines with clinical and laboratory variables were analyzed, furthermore, we also explored the relationships of different cytokines with ARDS and extrapulmonary MOD. RESULTS: The ARDS group had higher serum levels of all 4 inflammatory cytokines than the controls, and these levels steadily increased after admission. The ARDS group also had higher levels of IL-6, IL-8, and IL-10 than the non-ARDS group, and the levels of these cytokines correlated significantly with coagulation parameters and disseminated intravascular coagulation (DIC). The levels of IL-6 and TNF-α correlated with the levels of creatinine and urea nitrogen, and were also higher in ARDS patients with acute kidney injury (AKI). All 4 inflammatory cytokines had negative correlations with PaO2/FiO2. IL-6, IL-8, and TNF-α had positive correlations with the APACHE-II score. Relative to survivors, non-survivors had higher levels of IL-6 and IL-10 at admission, and increasing levels over time. CONCLUSIONS: The cytokine storm apparently contributed to the development of ARDS and extrapulmonary MOD in COVID-19 patients. The levels of IL-6, IL-8, and IL-10 correlated with DIC, and the levels of IL-6 and TNF-α were associated with AKI. Relative to survivors, patients who died within 28 days had increased levels of IL-6 and IL-10.

Early risk factors for extrapulmonary organ injury in adult COVID-19 patients.

BACKGROUND: The novel 2019 coronavirus (COVID-19) has caused a global pandemic, and often leads to extrapulmonary organ injury. However, the risk factors for extrapulmonary organ injury are still unclear. We aim to explore the risk factors for extrapulmonary organ injury and the association between extrapulmonary organ injury and the prognosis in COVID-19 patients. METHODS: We implemented a single-center, retrospective, observational study, in which a total of 349 confirmed COVID-19 patients admitted to Tongji Hospital from January 25, 2020, to February 25, 2020, were enrolled. We collected demographic, clinical, laboratory, and treatment data from electronic medical records. Potential risk factors for extrapulmonary organ injury of COVID-19 patients were analyzed by a multivariable binary logistic model, and multivariable Cox proportional hazards regression model was used for survival analysis in the patients with extrapulmonary organ injury. RESULTS: The average age of the included patients was 61.73±14.64 years. In the final logistic model, variables including aged 60 or older [odds ratio (OR) 1.826, 95% confidence interval (CI): 1.060-3.142], acute respiratory distress syndrome (ARDS) (OR 2.748, 95% CI: 1.051-7.185), lymphocytes count lower than 1.1×109/L (OR 0.478, 95% CI: 0.240-0.949), level of interleukin-6 (IL-6) greater than 7 pg/mL (OR 1.664, 95% CI: 1.005-2.751) and D-Dimer greater than 0.5 µg/mL (OR 2.190, 95% CI: 1.176-4.084) were significantly associated with the extrapulmonary organ injury. Kaplan-Meier curve and log-rank test showed that the probabilities of survival for patients with extrapulmonary organ injury were significantly lower than those without extrapulmonary organ injury. Multivariate Cox proportional hazards model showed that only myocardial injury (P=0.000, HR: 5.068, 95% CI: 2.728-9.417) and circulatory system injury (P=0.000, HR: 4.076, 95% CI: 2.216-7.498) were the independent factors associated with COVID-19 patients' poor prognosis. CONCLUSIONS: Older age, lymphocytopenia, high level of D-Dimer and IL-6, and the severity of lung injury were the high-risk factors of extrapulmonary organ injury in COVID-19 patients. Myocardial and circulatory system injury were the most important risk factors related to poor outcomes of COVID-19 patients. It may help clinicians to identify extrapulmonary organ injury early and initiate appropriate treatment.

Dynamics and Correlation Among Viral Positivity, Seroconversion, and Disease Severity in COVID-19 : A Retrospective Study.

BACKGROUND: The understanding of viral positivity and seroconversion during the course of coronavirus disease 2019 (COVID-19) is limited. OBJECTIVE: To describe patterns of viral polymerase chain reaction (PCR) positivity and evaluate their correlations with seroconversion and disease severity. DESIGN: Retrospective cohort study. SETTING: 3 designated specialty care centers for COVID-19 in Wuhan, China. PARTICIPANTS: 3192 adult patients with COVID-19. MEASUREMENTS: Demographic, clinical, and laboratory data. RESULTS: Among 12 780 reverse transcriptase PCR tests for severe acute respiratory syndrome coronavirus 2 that were done, 24.0% had positive results. In 2142 patients with laboratory-confirmed COVID-19, the viral positivity rate peaked within the first 3 days. The median duration of viral positivity was 24.0 days (95% CI, 18.9 to 29.1 days) in critically ill patients and 18.0 days (CI, 16.8 to 19.1 days) in noncritically ill patients. Being critically ill was an independent risk factor for longer viral positivity (hazard ratio, 0.700 [CI, 0.595 to 0.824]; P < 0.001). In patients with laboratory-confirmed COVID-19, the IgM-positive rate was 19.3% in the first week, peaked in the fifth week (81.5%), and then decreased steadily to around 55% within 9 to 10 weeks. The IgG-positive rate was 44.6% in the first week, reached 93.3% in the fourth week, and then remained high. Similar antibody responses were seen in clinically diagnosed cases. Serum inflammatory markers remained higher in critically ill patients. Among noncritically ill patients, a higher proportion of those with persistent viral positivity had low IgM titers (<100 AU/mL) during the entire course compared with those with short viral positivity. LIMITATION: Retrospective study and irregular viral and serology testing. CONCLUSION: The rate of viral PCR positivity peaked within the initial few days. Seroconversion rates peaked within 4 to 5 weeks. Dynamic laboratory index changes corresponded well to clinical signs, the recovery process, and disease severity. Low IgM titers (<100 AU/mL) are an independent risk factor for persistent viral positivity. PRIMARY FUNDING SOURCE: None.

RNase T2 in Inflammation and Cancer: Immunological and Biological Views.

The RNase T2 family consists of evolutionarily conserved endonucleases that express in many different species, including animals, plants, protozoans, bacteria, and viruses. The main biological roles of these ribonucleases are cleaving or degrading RNA substrates. They preferentially cleave single-stranded RNA molecules between purine and uridine residues to generate two nucleotide fragments with 2'3'-cyclic phosphate adenosine/guanosine terminus and uridine residue, respectively. Accumulating studies have revealed that RNase T2 is critical for the pathophysiology of inflammation and cancer. In this review, we introduce the distribution, structure, and functions of RNase T2, its differential roles in inflammation and cancer, and the perspective for its research and related applications in medicine.

Liver injury after antiviral treatment of critically ill patients with COVID-19: a single-centered retrospective cohort study.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is the causative agent of coronavirus disease 2019 (COVID-19). Lung lesions are considered to be the main damage caused by SARSCoV-2 infection. In addition, liver injury has also been reported to occur during the course of the disease in severe cases. However, the effect of antiviral treatment on liver injury in critically ill patients is not yet clear. METHODS: We retrospectively evaluated the effect of antiviral treatment and antiviral drug arbidol on liver injury in COVID-19 critically ill patients. Baseline characteristics were collected from patients who were admitted to intensive care units of Tongji Hospital in Wuhan, China, and confounders were balanced by propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses. RESULTS: Both the PSM (OR=2.77; 95% CI: 1.03, 7.48; P=0.045) and the IPTW-adjusted (OR=2.33; 95% CI: 1.02, 5.34; P=0.047) results showed that COVID-19 critically ill patients receiving antiviral treatment had a significantly higher risk of liver injury. However, arbidol treatment did not have a significant effect on liver injury (IPTW: OR=2.11; 95% CI: 0.79, 5.67; P=0.14). CONCLUSIONS: Our results show that although arbidol treatment does not seem to be significantly associated with liver injury complications, the overall use of antiviral drugs increases the risk of liver injury for critically ill patients with COVID-19. Antiviral drugs are widely used to treat COVID-19, but we recommend that for critically ill patients, antiviral treatment should be used with caution considering both effectiveness and potential adverse effects.

Validation of Predictors of Disease Severity and Outcomes in COVID-19 Patients: A Descriptive and Retrospective Study.

BACKGROUND: The severity and outcome of COVID-19 cases has been associated with the percentage of circulating lymphocytes (LYM%), levels of C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT), lactic acid (LA), and viral load (ORF1ab Ct). However, the predictive power of each of these indicators in disease classification and prognosis remains largely unclear. METHODS: We retrospectively collected information on the above parameters in 142 patients with COVID-19, stratifying them by survival or disease severity. FINDINGS: CRP, PCT, IL-6, LYM%, and ORF1ab Ct were significantly altered between survivors and non-survivors. LYM%, CRP, and IL-6 were the most sensitive and reliable factors in distinguishing between survivors and non-survivors. These indicators were significantly different between critically ill and severe/moderate patients. Only LYM% levels were significantly different between severe and moderate types. Among all the investigated indicators, LYM% was the most sensitive and reliable in discriminating between critically ill, severe, and moderate types and between survivors and non-survivors. CONCLUSIONS: CRP, PCT, IL-6, LYM%, and ORF1ab Ct, but not LA, could predict prognosis and guide classification of COVID-19 patients. LYM% was the most sensitive and reliable predictor for disease typing and prognosis. We recommend that LYM% be further investigated in the management of COVID-19. FUNDING: This study was supported in part by awards from the National Natural Science Foundation of China, the Foundation and Frontier Research Project of Chongqing, and the Chongqing Youth Top Talent Project.

Acute Kidney Injury Is Associated With In-hospital Mortality in Older Patients With COVID-19.

BACKGROUND: The epidemic of COVID-19 presents a special threat to older adults. However, information on kidney damage in older patients with COVID-19 is limited. Acute kidney injury (AKI) is common in hospitalized adults and associated with poor prognosis. We sought to explore the association between AKI and mortality in older patients with COVID-19. METHODS: We conducted a retrospective, observational cohort study in a large tertiary care university hospital in Wuhan, China. All consecutive inpatients older than 65 years with COVID-19 were enrolled in this cohort. Demographic data, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between patients with AKI and without AKI. The association between AKI and mortality was analyzed. RESULTS: Of 1764 in-hospital patients, 882 older adult cases were included in this cohort. The median age was 71 years (interquartile range: 68-77), 440 (49.9%) were men. The most presented comorbidity was cardiovascular diseases (58.2%), followed by diabetes (31.4%). Of 882 older patients, 115 (13%) developed AKI and 128 (14.5%) died. Patients with AKI had higher mortality than those without AKI (68 [59.1%] vs 60 [7.8%]; p < .001). Multivariable Cox regression analysis showed that increasing odds of in-hospital mortality are associated with higher interleukin-6 on admission, myocardial injury, and AKI. CONCLUSIONS: Acute kidney injury is not an uncommon complication in older patients with COVID-19 but is associated with a high risk of death. Physicians should be aware of the risk of AKI in older patients with COVID-19.