Contribution of acute-phase reaction proteins to the diagnosis and treatment of 2019 novel coronavirus disease (COVID-19)

Assessment of Humoral Response at SARS-CoV-2 Infection by Multipronged Functional Proteomics Approaches

In the past decade, a major goal in biomedical research has been to understand why individuals differ in disease susceptibility, disease dynamics, and progression. In many pathologies, this variability stems from evolved immune mechanisms that resist inflammatory stress from various diseases that have been encountered throughout life. These may provide advantages against other diseases, reduce comorbidities, and enhance longevity. This study evaluates prior immunity as a prognostic factor in COVID-19 patients, crucial for understanding plasmatic signaling cascades in different disease stages and their impact on disease progression. COVID-19, caused by SARS-CoV-2, primarily affects the respiratory system and presents a wide range of symptoms, posing significant challenges to medicine. This study systematically analyzed prior immunity and inflammation in two independent cohorts of infected patients. A serological profile is determined by protein microarrays, which identify IgM and IgG responses against 37 prevalent microbial pathogens and provide a comprehensive plasma analysis of 21 acute-phase proteins. Our results reveal distinct serological profiles correlating with disease severity, indicating that immune system dysregulation in COVID-19 patients is linked to existing immunity. These findings highlight the relevance of prior immunity for monitoring disease progression, particularly in infections and vaccine failure, and underscore the importance of functional proteomics in determining prognostic biomarkers.

Acute-phase proteins as indicators of disease severity and mortality in COVID-19 patients

The aim of the study was to conduct of relationship of acute-phase proteins (APPs) with the severity of COVID-19 defined by National Institutes of Health and according to the criteria of MEWS scale, with the presence of a cytokine storm, oxygen therapy and patient survival. We enrolled 96 patients with COVID-19 and 30 healthy people. The samples were taken on the day of admission and after 9 days on average. Not only commonly used APPs such as CRP, procalcitonin and ferritin and also rarely assayed proteins such as transferrin, haptoglobin, α1-acid glycoprotein and α1-antitrypsin, were tested in the study. The levels of APPs depends on the severity of COVID-19 disease, on the presence of cytokine storm and used oxygen therapy. The greatest APPs changes occurred in the most advanced form of the disease, with the presence of a cytokine storm and the most intense oxygen therapy. The results obtained from MEWS scale were not consistent with National Institutes of Health scores. Studies in the second samples showed the quenching of the acute phase reactions and the effectiveness of oxygen therapy. Only two of the examined APPs i.e. procalcitonin and transferrin, differed between surviving and non-surviving patients, and these two predispose to the role of prognostic factors in Covid-19. In conclusion, the concentration of not all acute-phase proteins depends on the severity of COVID-19 disease, presence of cytokine storm, the used of oxygen therapy and only some of them (procalcitonin and transferrin) are related to the survival outcomes. Of the newly tested acute-phase proteins, only transferrin shows significance as a marker of disease severity and mortality in COVID-19 disease.

Aging is associated with an insufficient early inflammatory response of lung endothelial cells in SARS-CoV-2 infection

Advanced age is associated with an increased susceptibility to Coronavirus Disease (COVID)-19 and more severe outcomes, although the underlying mechanisms are understudied. The lung endothelium is located next to infected epithelial cells and bystander inflammation may contribute to thromboinflammation and COVID-19-associated coagulopathy. Here, we investigated age-associated SARS-CoV-2 pathogenesis and endothelial inflammatory responses using humanized K18-hACE2 mice. Survival was reduced to 20% in aged mice (85-112 weeks) versus 50% in young mice (12-15 weeks) at 10 days post infection (dpi). Bulk RNA-sequencing of endothelial cells from mock and infected mice at 2dpi of both age groups (aged: 72-85 weeks; young: 15 weeks) showed substantially lower significant differentially regulated genes in infected aged mice than in young mice (712 versus 2294 genes). Viral recognition and anti-viral pathways such as RIG-I-like receptor signaling, NOD-like receptor signaling and interferon signaling were regulated in response to SARS-CoV-2. Young mice showed several fold higher interferon responses (Ifitm3, Ifit1, Isg15, Stat1) and interferon-induced chemokines (Cxcl10 and Cxcl11) than aged mice. Endothelial cells from infected young mice displayed elevated expression of chemokines (Cxcl9, Ccl2) and leukocyte adhesion markers (Icam1) underscoring that inflammation of lung endothelium during infection could facilitate leukocyte adhesion and thromboinflammation. TREM1 and acute phase response signaling were particularly prominent in endothelial cells from infected young mice. Immunohistochemistry was unable to detect viral protein in pulmonary endothelium. In conclusion, our data demonstrate that the early host response of the endothelium to SARS-CoV-2 infection declines with aging, which could be a potential contributor to disease severity.

The Association of Serum Profile of Transferrin Isoforms with COVID-19 Disease Severity

Background/Objective: Bearing in mind the relationship of transferrin (TRF) microheterogeneity with the biological activity of its isoforms, we propose, in this study, to determine the association of the profile of TRF isoforms with COVID-19 disease severity and to compare this profile to the profiles of other diseases. Methods: The disease group consisted of 96 patients from whom blood was collected twice, upon admission to the ward and after treatment (on average on the ninth day). TRF isoforms were separated by capillary electrophoresis. The analysis included disease severity, cytokine storm, comorbidities, patient survival, oxygen therapy, and modified early warning scores (MEWSs). Results: The concentration of 5-sialoTRF was higher in patients compared to controls at the beginning and during COVID-19 treatment. The concentration of this isoform varies with the severity of disease and was higher in critical patients than those with a moderate condition. Additionally, the level of 5-sialoTRF was lower and the level of 4-sialoTRF was higher in patients with comorbidities than that in patients without them. The concentration of 5-sialoTRF was lower and the concentration of 4-sialoTRF was higher in surviving patients than in non-surviving patients. There were no statistical changes in TRF isoforms according to presence of cytokine storm, MEWS, and oxygen therapy. Conclusions: We conclude that the profile of TRF isoforms in COVID-19 patients differs from that in other diseases. An increase in the concentration of a sialic acid-rich isoform, 5-sialoTRF, may be a compensatory mechanism, the goal of which is to increase oxygen delivery to tissues and is dependent on the severity of the disease. Additionally, the concentration of 5-sialoTRF may be a prognostic marker of the survival of COVID-19 patients.

Dissociation Phenomenon of Erythrocyte Agglutination and Its Application to Assay of Functional Activity of the Complement System in Clinical Laboratory

OBJECTIVE

The objective of the study was to validate the dissociation phenomenon of erythrocyte agglutination which is based on erythrocyte fragments and to apply it in the functional activity assay of the complement system.

METHODS

The dissociation-agglutination effect of erythrocyte fragments was validated by detecting the number of free erythrocytes after the action of erythrocyte fragments on agglutinated erythrocytes. The number of free erythrocytes produced after hemolysis of agglutinated erythrocytes caused by complements and complement activators(CAs) was detected by auto hematology analyzer and the results were indicated by mean hemoglobin concentration of erythrocytes (MCHC). We optimized the test conditions and validated the inter-batch stability, explored the resolution of the assay method, and assayed for the total complement activity (AC) and the CAs activated complement activity (ACA) in serum from patients and healthy individual groups.

RESULTS

Erythrocyte fragments have a dissociative effect on agglutinated erythrocytes. The auto hematology analyzer was able to detect AC and ACA, where AC showed an inverse correlation with MCHC, and ACA demonstrated a positive correlation with MCHC. The inter-batch CV of AC, ACA, and ACA/AC was found to be 5%, 9%, and 11.7%, respectively, with good stability. The study found that serum samples from acute phase reaction patients showed significant differences in ACA compared with healthy individuals, with a p value of 0.018; serum samples from patients with nephrotic syndrome showed significant differences in AC, ACA, and ACA/AC compared with healthy individuals, with p values of 0.014, 0.002, and 0.041, respectively.

CONCLUSION

Erythrocyte fragments have dissociation-agglutination effect. The complement system immunological functional detection method, based on this effect, has potential clinical application value due to its sensitivity and accuracy.

Differential Transcriptomic Signatures of Small Airway Cell Cultures Derived from IPF and COVID-19-Induced Exacerbation of Interstitial Lung Disease

Idiopathic pulmonary fibrosis (IPF) is a pathological condition wherein lung injury precipitates the deposition of scar tissue, ultimately leading to a decline in pulmonary function. Existing research indicates a notable exacerbation in the clinical prognosis of IPF patients following infection with COVID-19. This investigation employed bulk RNA-sequencing methodologies to describe the transcriptomic profiles of small airway cell cultures derived from IPF and post-COVID fibrosis patients. Differential gene expression analysis unveiled heightened activation of pathways associated with microtubule assembly and interferon signaling in IPF cell cultures. Conversely, post-COVID fibrosis cell cultures exhibited distinctive characteristics, including the upregulation of pathways linked to extracellular matrix remodeling, immune system response, and TGF-β1 signaling. Notably, BMP signaling levels were elevated in cell cultures derived from IPF patients compared to non-IPF control and post-COVID fibrosis samples. These findings underscore the molecular distinctions between IPF and post-COVID fibrosis, particularly in the context of signaling pathways associated with each condition. A better understanding of the underlying molecular mechanisms holds the promise of identifying potential therapeutic targets for future interventions in these diseases.

Complement and COVID-19: Three years on, what we know, what we don't know, and what we ought to know

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus was identified in China in 2019 as the causative agent of COVID-19, and quickly spread throughout the world, causing over 7 million deaths, of which 2 million occurred prior to the introduction of the first vaccine. In the following discussion, while recognising that complement is just one of many players in COVID-19, we focus on the relationship between complement and COVID-19 disease, with limited digression into directly-related areas such as the relationship between complement, kinin release, and coagulation. Prior to the 2019 COVID-19 outbreak, an important role for complement in coronavirus diseases had been established. Subsequently, multiple investigations of patients with COVID-19 confirmed that complement dysregulation is likely to be a major driver of disease pathology, in some, if not all, patients. These data fuelled evaluation of many complement-directed therapeutic agents in small patient cohorts, with claims of significant beneficial effect. As yet, these early results have not been reflected in larger clinical trials, posing questions such as who to treat, appropriate time to treat, duration of treatment, and optimal target for treatment. While significant control of the pandemic has been achieved through a global scientific and medical effort to comprehend the etiology of the disease, through extensive SARS-CoV-2 testing and quarantine measures, through vaccine development, and through improved therapy, possibly aided by attenuation of the dominant strains, it is not yet over. In this review, we summarise complement-relevant literature, emphasise its main conclusions, and formulate a hypothesis for complement involvement in COVID-19. Based on this we make suggestions as to how any future outbreak might be better managed in order to minimise impact on patients.

Serum amyloid A—A potential therapeutic target for hyper-inflammatory syndrome associated with COVID-19

Serum amyloid-A (SAA) is associated with inflammatory disorders such as rheumatoid arthritis, Familial Mediterranean Fever, sarcoidosis, and vasculitis. There is accumulating evidence that SAA is a reliable biomarker for these autoinflammatory and rheumatic diseases and may contribute to their pathophysiology. Hyperinflammatory syndrome associated with COVID-19 is a complex interaction between infection and autoimmunity and elevation of SAA is strongly correlated with severity of the inflammation. In this review we highlight the involvement of SAA in these different inflammatory conditions, consider its potential role and discuss whether it could be a potential target for treatment of the hyperinflammatory state of COVID-19 with many potential advantages and fewer adverse effects. Additional studies linking SAA to the pathophysiology of COVID-19 hyper-inflammation and autoimmunity are needed to establish the causal relationship and the therapeutic potential of inhibitors of SAA activity.

Serum biomarkers for nutritional status as predictors in COVID-19 patients before and after vaccination

The aim of this study was to characterize serum protein biomarkers for nutritional status that may be used as predictors for disease symptomatology in COVID-19 patients before and after vaccination. In pre-vaccine cohorts, proteomics analysis revealed significant differences between groups, with serum proteins alpha-1-acid glycoproteins (AGPs) 1 and 2, C-reactive protein (CRP) and retinol binding protein (RBP) increasing with COVID-19 severity, in contrast with serum albumin, transthyretin (TTR) and serotransferrin (TF) reduction as the symptomatology increased. Immunoassay reproduced and validated proteomics results of serum proteins albumin and RBP. In post-vaccine cohorts, the results showed the same pattern as in pre-vaccine cohorts for serum proteins AGPs, CRP, albumin and TTR. However, TF levels were similar between groups and RBP presented a slight reduction as COVID-19 symptomatology increased. In these cohorts, immunoassay validated proteomics results of serum proteins albumin, TTR and TF. Additionally, immune response to α-Gal in pre-vaccine cohorts varied in predominant immunoglobulin type profile, while post-vaccine groups presented mainly anti-α-Gal protective IgG antibodies. The study identified serum nutritional biomarkers that could potentially predict an accurate prognostic of COVID-19 disease to provide an appropriate nutritional care and guidance in non-vaccinated and vaccinated individuals against SARS-CoV-2. These results highlight the importance of designing personalized nutrition protocols to improve diet along with the application of prebiotics or probiotics for the control of COVID-19 and other infectious diseases.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbour embedding (tSNE) and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.

Acute kidney injury associated to COVID-19 leads to a strong unbalance of circulant immune mediators

BACKGROUND

Severe cases of coronavirus disease 2019 (COVID-19) have increased risk for acute kidney injury (AKI). The exacerbation of the immune response seems to contribute to AKI development, but the immunopathological process is not completely understood.

OBJECTIVES

To analyze levels of circulant immune mediators in COVID-19 patients evolving with or without AKI. We have also investigated possible associations of these mediators with viral load and clinical outcomes.

METHODS

This is a longitudinal study performed with hospitalized patients with moderate to severe COVID-19. Serum levels of 27 immune mediators were measured by a multiplex immunoassay. Data were analyzed at two timepoints during the follow-up: within the first 13 days of the disease onset (early sample) and from the 14th day to death or hospital discharge (follow-up sample).

RESULTS

We studied 82 COVID-19 patients (59.5 ± 17.5 years, 54.9% male). Of these, 34 (41.5%) developed AKI. These patients presented higher SARS-CoV-2 viral load (P = 0.03), higher frequency of diabetes (P = 0.01) and death (P = 0.0004). Overall, AKI patients presented significantly higher and sustained levels (P < 0.05) of CCL-2, CCL-3, CCL-4, CXCL-8, CXCL-10, IFN-γ, IL-2, IL-6, TNF-α, IL-1Ra, IL-10 and VEGF. Importantly, higher levels of CCL-2, CXCL-10, IL-2, TNF-α, IL-10, FGFb, and VEGF were observed in AKI patients independently of death. ROC curves demonstrated that early alterations in CCL-2, CXCL-8, CXCL-10, IFN-γ, IL-6, IL-1Ra and IL-10 show a good predictive value regarding AKI development. Lastly, immune mediators were significantly associated with each other and with SARS-CoV-2 viral load in AKI patients.

CONCLUSIONS

COVID-19 associated AKI is accompanied by substantial alterations in circulant levels of immune mediators, which could significantly contribute to the establishment of kidney injury.

Decision support analysis for risk identification and control of patients affected by COVID-19 based on Bayesian Networks

In the context of the outbreak of coronavirus disease (COVID-19), this paper proposes an innovative and systematic decision support model based on Bayesian networks (BNs) to identify and control the risk of COVID-19 patients spreading the virus, which requires the following three steps. First, by consulting the related literature and combining this with expert knowledge, we identify and classify the characteristics (risk factors) of COVID-19 and obtain a conceptual framework for COVID-19 Risk Assessment Bayesian Networks (CRABNs). Second, data on COVID-19 patients with expert scoring results on patient risk levels were collected from hospitals in Hubei Province of China and are used as the training set, and the structure and parameters of the CRABNs model are obtained through machine learning. Finally, we propose two indicators, namely, Model Bias and Model Accuracy, and use the remaining data to verify the feasibility and effectiveness of the CRABNs model to ensure that there are no significant differences between the predicted results of the model and the actual results provided by experts who have relevant experience in treating COVID-19. At the same time, we compared the CRABNs model with the support vector machine (SVM), random forest (RF), and k-nearest neighbour (KNN) models through four indicators: accuracy, sensitivity, specificity, and F-score. The results suggest the reliability of the model and show that it has promising application potential. The proposed model can be used globally by doctors in hospitals as a decision support tool to improve the accuracy of assessing the severity of COVID-19 symptoms in patients. Furthermore, with the further improvement of the model in the future, it can be used for risk assessments in the field of epidemics.

Prognostic value of serum amyloid A in COVID-19: A meta-analysis

BACKGROUND

There is still a lack of large-scale clinical studies and evidence-based evidence to prove the relationship between serum amyloid A (SAA) and the severity and prognosis of patients with new coronavirus pneumonia (COVID-19).

METHODS

We searched PubMed, Cochrane Library, Excerpta Medica Database, and Web of Science for original articles from December 1, 2019 to December 19, 2020. Search criteria include free text search, explosive MESH/EMTREE terms, and all synonyms for SAA and COVID-19. There are no language restrictions on the searched documents. Statistical methods were performed using Stata 14.0 software, and RevMan 5.4 software provided by the Cochrane Collaboration for meta-analysis. The 10 included studies in the literature were classified according to the severity of the novel coronavirus treatment guidelines, with mild/moderate categorized as nonsevere and severe/critical as severe, and the data were meta-analyzed using multiple subgroup standard deviations combined. Severe and nonsevere were finally divided into 2 groups, and the combined data were meta-analyzed according to the standardized mean difference.

RESULTS

The results of the meta-analysis given by random effects showed that SAA levels were significantly higher in severe vs nonsevere (standardized mean difference 1.20 [95% confidence interval 0.91-1.48]), which was statistically significant (P < .001). The 3 literatures studied (random effect size 0.11 [95% confidence interval 0.05-0.19]; I2 = 56.68%) and were statistically significant, z = 5.46 P < .01, suggesting that the risk of death occurs at higher levels with increasing SAA values, with the risk of death in the severe group being 11% higher than in the nonsevere group.

CONCLUSION

SAA can be considered as a biomarker for predicting the severity and prognosis of COVID-19. SAA can be used for early warning of the poor prognosis of COVID-19 and for monitoring the recovery process, which has important clinical value.

SARS-CoV-2 Infection Triggers Auto-Immune Response in ARDS

Acute respiratory distress syndrome (ARDS) is a severe pulmonary disease, which is one of the major complications in COVID-19 patients. Dysregulation of the immune system and imbalances in cytokine release and immune cell activation are involved in SARS-CoV-2 infection. Here, the inflammatory, antigen, and auto-immune profile of patients presenting COVID-19-associated severe ARDS has been analyzed using functional proteomics approaches. Both, innate and humoral responses have been characterized through acute-phase protein network and auto-antibody signature. Severity and sepsis by SARS-CoV-2 emerged to be correlated with auto-immune profiles of patients and define their clinical progression, which could provide novel perspectives in therapeutics development and biomarkers of COVID-19 patients. Humoral response in COVID-19 patients’ profile separates with significant differences patients with or without ARDS. Furthermore, we found that this profile can be correlated with COVID-19 severity and results more common in elderly patients.

A high neutrophil to lymphocyte ratio at ICU admission is associated with nutritional risk in COVID-19 patients

Background

Inflammation plays a crucial role in nutrition status and can be useful in early nutrition risk screening of patients during the coronavirus disease 2019 (COVID‐19) pandemic. Thus, this study aimed to assess the association between systemic inflammatory markers and nutrition risk tools in intensive care unit (ICU) patients with COVID‐19.

Methods

Patients with confirmed COVID‐19 and ICU admission were enrolled in a retrospective, observational, cross‐sectional study. The medians of C‐reactive protein (CRP; ≥13.8 mg/dl) and the neutrophil‐to‐lymphocyte ratio (NLR; ≥12.6) upon admission were used to dichotomize patients.

Results

Of the 73 patients, 63% were men; the average age was 56 years, and the median length of hospital stay was 10 (25th: 4; 75th: 17) days. When nutrition risk screening tools were used, 85% were at risk according to Nutritional Risk Screening (≥3 points), whereas 42% had high risk according to the Modified Nutrition Risk in the Critically Ill (mNUTRIC; ≥5 points), and 57% were moderately or severely malnourished according to the Subjective Global Assessment (B or C). Mortality was higher in the group with NLR ≥12.6 than in the group with NLR <12.6, with no difference between CRP groups. A significant association was found only between NLR and mNUTRIC, even when adjusted by sex, age, and body mass index (odds ratio, 1.36; 95% CI, 1.06–1.76; P = 0.016), but not between CRP and nutrition risk.

Conclusion

Although the inflammatory marker CRP is the most used in hospital clinical practice, we found that only NLR was associated with nutrition risk (NUTRIC score).

Complement inhibition: A possible therapeutic approach in the fight against Covid-19

The complement system, as a vital part of innate immunity, has an important role in the clearance of pathogens; however, unregulated activation of this system probably has a key role in the pathogenesis of acute lung injury, which is induced by highly pathogenic viruses (i.e. influenza A viruses and severe acute respiratory syndrome [SARS] coronavirus). The novel coronavirus SARS-CoV-2, which is the causal agent for the ongoing global pandemic of the coronavirus disease 2019 (Covid-19), has recently been spread to almost all countries around the world. Although most people are immunocompetent to SARS-CoV-2, a small group develops hyper-inflammation that leads to complications like acute respiratory distress syndrome, disseminated intravascular coagulation, and multi-organ failure. Emerging evidence demonstrates that the complement system exerts a crucial role in this inflammatory reaction. Additionally, patients with the severe form of Covid-19 show over-activation of the complement in their skin, sera, and lungs. This study aims to summarise current knowledge concerning the interaction of SARS-CoV-2 with the complement system and to critically appraise complement inhibition as a potential new approach for Covid-19 treatment.

Insights into Innate Immune Response Against SARS-CoV-2 Infection

The innate immune system is mandatory for the activation of antiviral host defense and eradication of the infection. In this regard, dendritic cells, natural killer cells, macrophages, neutrophils representing the cellular component, and cytokines, interferons, complement or Toll-Like Receptors, representing the mediators of unspecific response act together for both activation of the adaptive immune response and viral clearance. Of great importance is the proper functioning of the innate immune response from the very beginning. For instance, in the early stages of viral infection, the defective interferon response leads to uncontrolled viral replication and pathogen evasion, while hypersecretion during the later stages of infection generates hyperinflammation. This cascade activation of systemic inflammation culminates with cytokine storm syndrome and hypercoagulability state, due to a close interconnection between them. Thus an unbalanced reaction, either under- or over- stimulation of the innate immune system will lead to an uncoordinated response and unfavorable disease outcomes. Since both cellular and humoral factors are involved in the time-course of the innate immune response, in this review we aimed to address their gradual involvement in the antiviral response with emphasis on key steps in SARS-CoV-2 infection.

Corticosteroids for COVID-19

Coronavirus disease 19 (COVID-19) is placing a major burden on healthcare, economy and social systems worldwide owing to its fast spread and unacceptably high death toll. The unprecedented research effort has established the role of a deregulated immune response to the severe acute respiratory syndrome coronavirus 2, resulting in systemic inflammation. After that, the immunomodulatory approach has been placed in the top list of the research agenda for COVID-19. Corticosteroids have been used for more than 70 years to modulate the immune response in a broad variety of diseases. These drugs have been shown to prevent and attenuate inflammation both in tissues and in circulation via non-genomic and genomic effects. At the bedside, numerous observational cohorts have been published in the past months and have been inconclusive. Randomized controlled trials with subsequent high quality meta-analyses have provided moderate to strong certainty for an increased chance of survival and relief from life supportive therapy with corticosteroids given at a dose of 6 mg per day dexamethasone or equivalent doses of hydrocortisone or methylprednisolone. The corticotherapy was not associated with an increased risk of bacterial infection or of delayed viral clearance. In daily practice, physicians may be encouraged to use corticosteroids when managing patients with COVID-19 requiring oxygen supplementation.

Coagulation and wound repair during COVID-19

While COVID-19 is best known as a respiratory infection, SARS-CoV-2 causes systemic disease manifestations including coagulopathies. Both dysregulated extracellular matrix remodeling pathways and circulating coagulation proteins are hallmarks of severe COVID-19 and often continue after the resolution of acute infection. Coagulation proteins have proven effective as biomarkers for severe disease and anticoagulants are a mainstay of COVID-19 therapeutics in hospitalized patients. While much knowledge has been gained about the role of clotting pathway activation in COVID-19, much remains to be elucidated in this complex network of signaling pathways.

Serum Complement C3 and C4 and COVID-19 Severity and Mortality: A Systematic Review and Meta-Analysis With Meta-Regression

Activation of the complement system has been observed in coronavirus disease 19 (COVID-19). We conducted a systematic review and meta-analysis with meta-regression to investigate possible differences in the serum concentrations of two routinely measured complement components, C3 and C4, in COVID-19 patients with different severity and survival status. We searched PubMed, Web of Science and Scopus, between January 2020 and February 2021, for studies reporting serum complement C3 and C4, measures of COVID-19 severity, and survival. Eligibility criteria were a) reporting continuous data on serum C3 and C4 concentrations in COVID-19 patients, -b) investigating COVID-19 patients with different disease severity and/or survival status, c) adult patients, d) English language, e) ≥10 patients, and f) full-text available. Using a random-effects model, standardized mean differences (SMD) with 95% confidence intervals (CIs) were calculated to evaluate differences in serum C3 and C4 concentrations between COVID-19 patients with low vs. high severity or survivor vs. non-survivor status. Risk of bias was assessed using the Newcastle-Ottawa scale whereas publication bias was assessed with the Begg’s and Egger’s tests. Certainty of evidence was assessed using GRADE. Nineteen studies in 3,764 COVID-19 patients were included in the meta-analysis. Both C3 and C4 concentrations were significantly lower in patients with high disease severity or non-survivor status than patients with low severity or survivor status (C3 SMD=-0.40, 95% CI -0.60 to -0.21, p<0.001; C4 SMD=-0.29, 95% CI -0.49 to -0.09, p=0.005; moderate certainty of evidence). Extreme between-study heterogeneity was observed (C3, I² = 82.1%; C4, I² = 84.4%). Sensitivity analysis, performed by sequentially removing each study and re-assessing the pooled estimates, showed that the magnitude and direction of the effect size was not modified. There was no publication bias. In meta-regression, the SMD of C3 was significantly associated with white blood cell count, C-reactive protein (CRP), and pro-thrombin time, whereas the SMD of C4 was significantly associated with CRP, pro-thrombin time, D-dimer, and albumin. In conclusion, lower concentrations of C3 and C4, indicating complement activation, were significantly associated with higher COVID-19 severity and mortality. C3 and C4 might be useful to predict adverse clinical consequences in these patients.

Systematic Review Registration: PROSPERO, Registration number: CRD42021239634.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.

Serum amyloid A concentrations, COVID-19 severity and mortality: An updated systematic review and meta-analysis

BACKGROUND AND OBJECTIVES

An excessive inflammatory response in patients with coronavirus disease 2019 (COVID-19) is associated with high disease severity and mortality. Specific acute phase reactants might be useful for risk stratification. A systematic review and meta-analysis was conducted of studies on serum amyloid A (SAA) in patients with COVID-19.

METHODS

The PubMed, Web of Science, and Scopus databases were searched, covering the period January 2020 to December 2020, for studies reporting SAA concentrations, COVID-19 severity, and survival status.

RESULTS

Nineteen studies involving 5617 COVID-19 patients were included in the meta-analysis. Pooled results showed that SAA concentrations were significantly higher in patients with severe disease and non-survivors (standard mean difference (SMD) 1.20, 95% confidence interval 0.91-1.49, P < 0.001). Extreme between-study heterogeneity was observed (I² = 92.4%, P < 0.001). In the sensitivity analysis, the effect size was not significantly affected when each study was removed in turn (range 1.10-1.29). The Begg test (P = 0.030), but not the Egger test (P = 0.385), revealed the presence of publication bias. Pooled SMD values were significantly and positively associated with sex (t = 2.20, P = 0.047) and aspartate aminotransferase (t = 3.44, P = 0.014).

CONCLUSIONS

SAA concentrations were significantly and positively associated with higher COVID-19 severity and mortality. This acute phase reactant might assist with risk stratification and monitoring in this group.

Circulating Exosomes Are Strongly Involved in SARS-CoV-2 Infection

Knowledge of the host response to the novel coronavirus SARS-CoV-2 remains limited, hindering the understanding of COVID-19 pathogenesis and the development of therapeutic strategies. During the course of a viral infection, host cells release exosomes and other extracellular vesicles carrying viral and host components that can modulate the immune response. The present study used a shotgun proteomic approach to map the host circulating exosomes’ response to SARS-CoV-2 infection. We investigated how SARS-CoV-2 infection modulates exosome content, exosomes’ involvement in disease progression, and the potential use of plasma exosomes as biomarkers of disease severity. A proteomic analysis of patient-derived exosomes identified several molecules involved in the immune response, inflammation, and activation of the coagulation and complement pathways, which are the main mechanisms of COVID-19–associated tissue damage and multiple organ dysfunctions. In addition, several potential biomarkers—such as fibrinogen, fibronectin, complement C1r subcomponent and serum amyloid P-component—were shown to have a diagnostic feature presenting an area under the curve (AUC) of almost 1. Proteins correlating with disease severity were also detected. Moreover, for the first time, we identified the presence of SARS-CoV-2 RNA in the exosomal cargo, which suggests that the virus might use the endocytosis route to spread infection. Our findings indicate circulating exosomes’ significant contribution to several processes—such as inflammation, coagulation, and immunomodulation—during SARS-CoV-2 infection. The study’s data are available via ProteomeXchange with the identifier PXD021144.

Efficacy of copeptin in distinguishing COVID-19 pneumonia from community-acquired pneumonia

The clinical symptoms of community‐acquired pneumonia (CAP) and coronavirus disease 2019 (COVID‐19)‐associated pneumonia are similar. Effective predictive markers are needed to differentiate COVID‐19 pneumonia from CAP in the current pandemic conditions. Copeptin, a 39‐aminoacid glycopeptide, is a C‐terminal part of the precursor pre‐provasopressin (pre‐proAVP). The activation of the AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aims to determine serum copeptin levels in patients with CAP and COVID‐19 pneumonia and to analyze the power of copeptin in predicting COVID‐19 pneumonia. The study consists of 98 patients with COVID‐19 and 44 patients with CAP. The basic demographic and clinical data of all patients were recorded, and blood samples were collected. The receiver operating characteristic (ROC) curve was generated and the area under the ROC curve (AUC) was measured to evaluate the discriminative ability. Serum copeptin levels were significantly higher in COVID‐19 patients compared to CAP patients (10.2 ± 4.4 ng/ml and 7.1 ± 3.1 ng/ml; p < .001). Serum copeptin levels were positively correlated with leukocyte, neutrophil, and platelet count (r = −.21, p = .012; r = −.21, p = .013; r = −.20, p = .018; respectively). The multivariable logistic regression analysis revealed that increased copeptin (odds ratio [OR] = 1.183, 95% confidence interval [CI], 1.033–1.354; p = .015) and CK‐MB (OR = 1.052, 95% CI, 1.013–1.092; p = .008) levels and decreased leukocyte count (OR = 0.829, 95% CI, 0.730–0.940; p = .004) were independent predictors of COVID‐19 pneumonia. A cut‐off value of 6.83 ng/ml for copeptin predicted COVID‐19 with a sensitivity of 78% and a specificity of 73% (AUC: 0.764% 95 Cl: 0.671–0.856, p < .001). Copeptin could be a promising and useful biomarker to be used to distinguish COVID‐19 patients from CAP patients.

Serum Prealbumin Concentrations, COVID-19 Severity, and Mortality: A Systematic Review and Meta-Analysis

Excessive inflammation and malnutrition are associated with coronavirus disease 2019 (COVID-19) severity and mortality. Combined biomarkers of malnutrition and inflammation, such as serum prealbumin, might be particularly attractive for early risk stratification. We conducted a systematic review and meta-analysis of studies reporting serum prealbumin in patients with COVID-19. We searched PubMed, Web of Science and Scopus, between January and November 2020, for studies reporting data on serum prealbumin, COVID-19 severity, defined as severe illness, prolonged viral load, receiving mechanical ventilation or admitted to intensive care unit (ICU), and mortality. Nineteen studies in 4,616 COVID-19 patients were included in the meta-analysis. Pooled results showed that serum prealbumin concentrations were significantly lower in patients with severe disease and non-survivors (standard mean difference, SMD, −0.92, 95% CI, −1.10 to −0.74, P < 0.001). Extreme heterogeneity was observed (I² = 77.9%; P < 0.001). In sensitivity analysis, the effect size was not significantly affected when each study was in turn removed (range between −0.86 and −0.95). The Begg's (P = 0.06) and Egger's t-tests (P = 0.26) did not show publication bias. Pooled SMD values were significantly and negatively associated with age (t = −2.18, P = 0.045) and C-reactive protein (t = −3.85, P = 0.002). In our meta-analysis, lower serum prealbumin concentrations were significantly associated with COVID-19 severity and mortality. This combined marker of malnutrition and inflammation might assist with early risk stratification and management in this group.

Complement Factors in COVID-19 Therapeutics and Vaccines

Complement is integral to a healthy functioning immune system and orchestrates various innate and adaptive responses against viruses and other pathogens. Despite its importance, the potential beneficial role of complement in immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been overshadowed by reports of extensive complement activation in severe coronavirus disease 2019 (COVID-19) patients. Here, we hypothesize that complement may also have a protective role and could function to enhance virus neutralization by antibodies, promote virus phagocytosis by immune cells, and lysis of virus. These functions might be exploited in the development of effective therapeutics and vaccines against SARS-CoV-2.

Complement has been implicated in playing some role in severe COVID-19 pathogenesis. However, the evidence to support this is largely inferred from case–control studies.

The potential protective role of complement has been largely ignored, which might contribute to innate and adaptive immunity against SARS-CoV-2 infection.

Immunity to many pathogens relies on complement to enhance antibody-mediated neutralization and mediate phagocytosis and lysis. These mechanisms might also contribute to immunity against SARS-CoV-2 infection, and complement might be potentially exploited in antibody-based therapeutics and vaccines.

Careful selection of vaccine adjuvants and epitopes included in vaccine constructs can influence whether vaccine-induced antibodies activate complement.

Mutations in monoclonal antibodies can be used to promote hexamer formation between antibodies, which can significantly improve complement binding and activation.