3044 Cases reveal important prognosis signatures of COVID-19 patients

Blood-derived product therapies for SARS-CoV-2 infection and long COVID

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is capable of large-scale transmission and has caused the coronavirus disease 2019 (COVID-19) pandemic. Patients with COVID-19 may experience persistent long-term health issues, known as long COVID. Both acute SARS-CoV-2 infection and long COVID have resulted in persistent negative impacts on global public health. The effective application and development of blood-derived products are important strategies to combat the serious damage caused by COVID-19. Since the emergence of COVID-19, various blood-derived products that target or do not target SARS-CoV-2 have been investigated for therapeutic applications. SARS-CoV-2-targeting blood-derived products, including COVID-19 convalescent plasma, COVID-19 hyperimmune globulin, and recombinant anti-SARS-CoV-2 neutralizing immunoglobulin G, are virus-targeting and can provide immediate control of viral infection in the short term. Non-SARS-CoV-2-targeting blood-derived products, including intravenous immunoglobulin and human serum albumin exhibit anti-inflammatory, immunomodulatory, antioxidant, and anticoagulatory properties. Rational use of these products can be beneficial to patients with SARS-CoV-2 infection or long COVID. With evidence accumulated since the pandemic began, we here summarize the progress of blood-derived product therapies for COVID-19, discuss the effective methods and scenarios regarding these therapies, and provide guidance and suggestions for clinical treatment.

Assessment of vaccinations and breakthrough infections after adjustment of the dynamic zero-COVID-19 strategy in China: an online survey

Coronavirus disease 2019 (COVID-19) cases in China has grown rapidly after adjustment of the dynamic zero-COVID-19 strategy. However, how different vaccination states affect symptoms, severity and post COVID conditions was unclear. Here, we used an online questionnaire to investigate the infection status of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among 11,897 participants, with 55.55% positive and 28.42% negative. The common COVID-19 symptoms were fatigue (73.31%), cough (70.02%), fever (65.25%) and overall soreness (58.64%); self-reported asymptomatic infection accounted for 0.7% of participants. The persistent symptoms at 1 month after infection included fatigue (48.7%), drowsiness (34.3%), cough (30.1%), decreased exercise ability (23.1%) and pharyngeal discomfort (19.4%), which was reduced by more than 200% at 2 months. Participants with complications such as chronic obstructive pulmonary disease, respiratory diseases, diabetes, hypertension, etc. have a higher proportion of hospitalization and longer recovery time (p < = 0.01). Multiple vaccination statuses reduced the infection (p < 0.001) and severity rates (p = 0.022) by varying degrees as well as reduced the risk of high fever (>39.1 °C), chills, diarrhea and ageusia/anosmia, respectively (p < 0.05). Vaccination may enhance some upper respiratory symptoms, including sore throat, nasal congestion and runny nose, respectively (p < 0.05). Participants who had been vaccinated within 3 months were better protected by helping reduce their risk of overall soreness, chills and ageusia/anosmia, respectively (p < 0.05). In conclusion, our work has updated the epidemic characteristics of the breakthrough infection (BTI) wave after the dynamic zero-COVID-19 strategy, providing data and insights on how different vaccination statuses affect COVID-19 symptoms and disease prognosis.

The kynurenine pathway of tryptophan metabolism: a neglected therapeutic target of COVID-19 pathophysiology and immunotherapy

SARS-CoV-2 (COVID-19) exerts profound changes in the kynurenine (Kyn) pathway (KP) of tryptophan (Trp) metabolism that may underpin its pathophysiology. The KP is the main source of the vital cellular effector NAD+ and intermediate metabolites that modulate immune and neuronal functions. Trp metabolism is the top pathway influenced by COVID-19. Sixteen studies established virus-induced activation of the KP mediated mainly by induction of indoleamine 2,3-dioxygenase (IDO1) in most affected tissues and of IDO2 in lung by the increased release of proinflammatory cytokines but could additionally involve increased flux of plasma free Trp and induction of Trp 2,3-dioxygenase (TDO) by cortisol. The major Kyn metabolite targeted by COVID-19 is kynurenic acid (KA), the Kyn metabolite with the greatest affinity for the aryl hydrocarbon receptor (AhR), which is also activated by COVID-19. AhR activation initiates two important series of events: a vicious circle involving IDO1 induction, KA accumulation and further AhR activation, and activation of poly (ADP-ribose) polymerase (PARP) leading to NAD+ depletion and cell death. The virus further deprives the host of NAD+ by inhibiting its main biosynthetic pathway from quinolinic acid, while simultaneously acquiring NAD+ by promoting its synthesis from nicotinamide in the salvage pathway. Additionally, the protective effects of sirtuin 1 are minimised by the PARP activation. KP dysfunction may also underpin the mood and neurological disorders acutely and during 'long COVID'. More studies of potential effects of vaccination therapy on the KP are required and exploration of therapeutic strategies involving modulation of the KP changes are proposed.

Novel insight into the underlying dysregulation mechanisms of immune cell-to-cell communication by analyzing multitissue single-cell atlas of two COVID-19 patients

How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell's activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

Exploration of Molecular Targets and Mechanisms of Curcumin in the Treatment of COVID-19 with Depression by an Integrative Pharmacology Strategy

BACKGROUND

Coronavirus disease 2019 (COVID-19) not only causes a range of respiratory symptoms but also has a great impact on individual mental health. With the global pandemic of SARS-CoV-2, the incidence of COVID-19 comorbid with depression has increased significantly. Curcumin, a natural polyphenol compound, has been shown to have antidepressant and anti-coronavirus activities.

METHODS

This study aimed to explore the molecular targets and underlying biological mechanisms of curcumin in the treatment of COVID-19 with depression through an integrative pharmacology strategy, including target prediction, network analysis, PPI analysis, GO and KEGG enrichment analyses, and molecular docking.

RESULTS

After a comprehensive search and thorough analysis, 8 core targets (ALB, AKT1, CASP3, STAT3, EGFR, PTGS2, FOS, and SERPINE1) were identified. GO and KEGG enrichment analysis results revealed that the pathways related to viral infection, immune regulation, neuronal reorganization, apoptosis, and secretion of inflammatory cytokines were involved in the pathological process. Furthermore, molecular docking showed that curcumin could spontaneously bind to the SARS-CoV-2-related receptor proteins and the core targets with a strong binding force.

CONCLUSION

The potential pharmacological mechanisms of curcumin in COVID-19 comorbid depression were evaluated. Curcumin can be used as a therapeutic agent for COVID-19 comorbid depression. One of the potential mechanisms may be to reduce the inflammatory response and suppress the cytokine storm by regulating the JAK-STAT signaling pathway and MAPK signaling pathway. These findings may help to overcome the impact of the COVID-19 pandemic on psychological health.

Review: Roles of human serum albumin in prediction, diagnoses and treatment of COVID-19

The severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) keeps on destroying normal social integrity worldwide, bringing about extraordinary medical services, cultural and financial interruption. Individuals with diabetes have been demonstrated to be at higher risk of complications and even death when exposed to SARS-CoV-2. Regardless of pandemic scale infection, there is presently limited comprehension on the potential impact of SARS-CoV-2 on individuals with diabetes. Human serum albumin (HSA) is the most abundant circulating plasma protein in human serum and attracted more interest from researchers because most susceptible to non-enzymatic glycation reactions. Albumin down-regulates the expression of ACE2 that is the target receptor of COVID-19. Hypoalbuminemia, coagulopathy, and vascular disease have been connected in COVID-19 and appear to predict outcomes independent of age and morbidity. This review discusses the most recent evidence that the ACE/ACE2 ratio could influence by human serum albumin both the susceptibility of individuals to SARS-CoV-2 infection and the outcome of the COVID-19 disease.

Serum hydroxybutyrate dehydrogenase and COVID-19 severity and mortality: a systematic review and meta-analysis with meta-regression

Alterations in cardiac and renal biomarkers have been reported in coronavirus disease 19 (COVID-19). We conducted a systematic review and meta-analysis to investigate serum concentrations of hydroxybutyrate dehydrogenase (HBDH), a combined marker of myocardial and renal injury, in hospitalized COVID-19 patients with different disease severity and survival status. We searched PubMed, Web of Science and Scopus, between December 2019 and April 2021, for studies reporting HBDH in COVID-19. Risk of bias was assessed using the Newcastle–Ottawa scale, publication bias was assessed with the Begg’s and Egger’s tests, and certainty of evidence was assessed using GRADE. In 22 studies in 15,019 COVID-19 patients, serum HBDH concentrations on admission were significantly higher in patients with high disease severity or non-survivor status when compared to patients with low severity or survivor status (standardized mean difference, SMD = 0.90, 95% CI 0.74 to 1.07, p < 0.001; moderate certainty of evidence). Extreme between-study heterogeneity was observed (I² = 93.5%, p < 0.001). Sensitivity analysis, performed by sequentially removing each study and re-assessing the pooled estimates, showed that the magnitude and the direction of the effect size were not substantially modified. A significant publication bias was observed. In meta-regression, the SMD of HBDH concentrations was significantly associated with markers of inflammation, sepsis, liver damage, non-specific tissue damage, myocardial injury, and renal function. Higher HBDH concentrations were significantly associated with higher COVID-19 severity and mortality. This biomarker of cardiac and renal injury might be useful for risk stratification in COVID-19. (PROSPERO registration number: CRD42021258123).

Hypoalbuminemia - An Indicator of the Severity and Prognosis of COVID-19 Patients: A Multicentre Retrospective Analysis

Background

Hypoalbuminemia has been reported in COVID-19 patients. Exploring the influencing factors and possible adverse consequences of albumin reduction may provide some guidance for the treatment of COVID-19 patients.

Methods

In this multicentre retrospective study, we collected information including demographics, comorbidities, clinical symptoms, complications, laboratory tests, treatment, and outcomes of patients diagnosed with COVID-19 from three hospitals in Wuhan, China. We compared the indexes between patients with hypoalbuminemia and normal albumin. Regression model was used to evaluate various influencing factors of patients with hypoalbuminemia and their relationship with clinical outcomes. We also compared the changes of particular laboratory indexes in patients with hypoalbuminemia before and after enteral nutrition therapy.

Results

A total of 482 patients were enrolled in the study. About 53.7% patients developed hypoalbuminemia during admission. Patients with hypoalbuminemia were older, had a higher proportion of combined diabetes mellitus, fever, dyspnea, and natriuresis, and had a relatively poorer prognosis than patients with normal albumin. Patients with hypoalbuminemia had higher levels of CRP, leukocytes, ALT, AST, total bilirubin, ALP, GGT, LDH, creatine kinase, D-dimer, globulin, and lower levels of lymphocytes and eosinophils. Severe, older, anorexia, elevated CRP, and decreased lymphocytes were the independent predictors for decreased albumin in COVID-19 patients. In addition, decreased albumin is correlated with adverse outcomes. Nutritional support therapy to correct serum albumin may improve patient outcomes.

Conclusion

COVID-19 patients with hypoalbuminemia tend to have more severe clinical manifestations and more abnormal biochemical tests, which may result in poorer clinical outcomes. Nutritional support therapy may improve the clinical outcome of these patients.

Broad Severe Acute Respiratory Syndrome Coronavirus 2 Cell Tropism and Immunopathology in Lung Tissues From Fatal Coronavirus Disease 2019

BACKGROUND

Coronavirus disease 2019 (COVID-19) patients manifest with pulmonary symptoms reflected by diffuse alveolar damage (DAD), excessive inflammation, and thromboembolism. The mechanisms mediating these processes remain unclear.

METHODS

We performed multicolor staining for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins and lineage markers to define viral tropism and lung pathobiology in 5 autopsy cases.

RESULTS

Lung parenchyma showed severe DAD with thromboemboli. Viral infection was found in an extensive range of cells including pneumocyte type II, ciliated, goblet, club-like, and endothelial cells. More than 90% of infiltrating immune cells were positive for viral proteins including macrophages, monocytes, neutrophils, natural killer (NK) cells, B cells, and T cells. Most but not all infected cells were angiotensin-converting enzyme 2 (ACE2) positive. The numbers of infected and ACE2-positive cells are associated with extensive tissue damage. Infected tissues exhibited high levels of inflammatory cells including macrophages, monocytes, neutrophils, and NK cells, and low levels of B cells but abundant T cells consisting of mainly T helper cells, few cytotoxic T cells, and no regulatory T cells. Robust interleukin-6 expression was present in most cells, with or without infection.

CONCLUSIONS

In fatal COVID-19 lungs, there are broad SARS-CoV-2 cell tropisms, extensive infiltrated innate immune cells, and activation and depletion of adaptive immune cells, contributing to severe tissue damage, thromboemboli, excess inflammation, and compromised immune responses.

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE

To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease.

DESIGN

Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group.

DATA SOURCES

PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020.

STUDY SELECTION

Studies that developed or validated a multivariable covid-19 related prediction model.

DATA EXTRACTION

At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool).

RESULTS

37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models.

CONCLUSION

Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline.

SYSTEMATIC REVIEW REGISTRATION

Protocol https://osf.io/ehc47/, registration https://osf.io/wy245.

READERS' NOTE

This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.