Inflammation Profiling of Critically Ill Coronavirus Disease 2019 Patients

A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning

BACKGROUND

COVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients' proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19.

METHODS

A case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression.

RESULTS

Machine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems.

CONCLUSIONS

The plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.

Impact of COVID status and blood group on complications in patients in hemorrhagic shock

Objective

Among critically injured patients of various blood groups, we sought to compare survival and complication rates between COVID-19-positive and COVID-19-negative cohorts.

Background

SARS-CoV-2 infections have been shown to cause endothelial injury and dysfunctional coagulation. We hypothesized that, among patients with trauma in hemorrhagic shock, COVID-19-positive status would be associated with increased mortality and inpatient complications. As a secondary hypothesis, we suspected group O patients with COVID-19 would experience fewer complications than non-group O patients with COVID-19.

Methods

We evaluated all trauma patients admitted 4/2020-7/2020. Patients 16 years or older were included if they presented in hemorrhagic shock and received emergency release blood products. Patients were dichotomized by COVID-19 testing and then divided by blood groups.

Results

3281 patients with trauma were evaluated, and 417 met criteria for analysis. Seven percent (29) of patients were COVID-19 positive; 388 were COVID-19 negative. COVID-19-positive patients experienced higher complication rates than the COVID-19-negative cohort, including acute kidney injury, pneumonia, sepsis, venous thromboembolism, and systemic inflammatory response syndrome. Univariate analysis by blood groups demonstrated that survival for COVID-19-positive group O patients was similar to that of COVID-19-negative patients (79 vs 78%). However, COVID-19-positive non-group O patients had a significantly lower survival (38%). Controlling for age, sex and Injury Severity Score, COVID-19-positive patients had a greater than 70% decreased odds of survival (OR 0.28, 95% CI 0.09 to 0.81; p=0.019).

Conclusions

COVID-19 status is associated with increased major complications and 70% decreased odds of survival in this group of patients with trauma. However, among patients with COVID-19, blood group O was associated with twofold increased survival over other blood groups. This survival rate was similar to that of patients without COVID-19.

Comparative effectiveness of dexamethasone in treatment of hospitalized COVID-19 patients in the United States during the first year of the pandemic: Findings from the National COVID Cohort Collaborative (N3C) data repository

BACKGROUND

Dexamethasone was approved for use in hospitalized COVID-19 patients early in the pandemic based on the RECOVERY trial, but evidence is still needed to support its real-world effectiveness in heterogeneous populations of patients with a wide range of comorbidities.

METHODS

COVID-19 inpatients represented within the National COVID Cohort Collaborative (N3C) Data Enclave, prior to vaccine availability, were studied. Primary outcome was in-hospital death; secondary outcome was combined in-hospital death and severe outcome defined by use of ECMO or mechanical ventilation. Missing data were imputed with single imputation. Dexamethasone-treated patients were propensity score (PS) matched to non-dexamethasone-treated controls, stratified by remdesivir treatment and based on demographics, baseline laboratory values, comorbidities, and amount of missing data before imputation. Treatment benefit was quantified using logistic regression. Further sensitivity analyses were performed using clinical adjusters in matched groups and in strata defined by quartiles of PS.

RESULTS

Dexamethasone treatment was associated with reduced risk of in-hospital mortality for n = 1,263 treated, matched 1:3 to untreated, patients not receiving remdesivir (OR = 0.77, 95% CI: 0.62 to 0.95, p = 0.017), and for n = 804 treated, matched 1:1 to untreated, patients receiving remdesivir (OR = 0.74, 95% CI: 0.53 to 1.02, p = 0.054). Treatment showed secondary outcome benefit. In sensitivity analyses, treatment effect generally remained similar with some heterogeneity of benefit across quartiles of PS, possibly reflecting concentration of benefit among the more severely affected.

CONCLUSIONS

We add evidence that dexamethasone provides benefit with respect to mortality and severe outcomes in a diverse, national hospitalized sample, prior to vaccine availability.

Kinome and phosphoproteome reprogramming underlies the aberrant immune responses in critically ill COVID-19 patients

SARS-CoV-2 infection triggers extensive host immune reactions, leading to severe diseases in certain individuals. However, the molecular basis underlying the excessive yet non-productive immune responses in severe COVID-19 remains incompletely understood. In this study, we conducted a comprehensive analysis of the peripheral blood mononuclear cell (PBMC) proteome and phosphoproteome in sepsis patients positive or negative for SARS-CoV-2 infection, as well as healthy subjects, using quantitative mass spectrometry. Our findings demonstrate dynamic changes in the COVID-19 PBMC proteome and phosphoproteome during disease progression, with distinctive protein or phosphoprotein signatures capable of distinguishing longitudinal disease states. Furthermore, SARS-CoV-2 infection induces a global reprogramming of the kinome and phosphoproteome, resulting in defective adaptive immune response mediated by the B and T lymphocytes, compromised innate immune responses involving the SIGLEC and SLAM family of immunoreceptors, and excessive cytokine-JAK-STAT signaling. In addition to uncovering host proteome and phosphoproteome aberrations caused by SARS-CoV-2, our work recapitulates several reported therapeutic targets for COVID-19 and identified numerous new candidates, including the kinases PKG1, CK2, ROCK1/2, GRK2, SYK, JAK2/3, TYK2, DNA-PK, PKCδ, and the cytokine IL-12.

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review

INTRODUCTION

Since the beginning of the COVID-19 pandemic, numerous machine and deep learning (MDL) methods have been proposed in the literature to analyze patient physiological data. The objective of this review is to summarize various aspects of these methods and assess their practical utility for predicting various clinical outcomes.

METHODS

We searched PubMed, Scopus, and Cochrane Library, screened and selected the studies matching the inclusion criteria. The clinical analysis focused on the characteristics of the patient cohorts in the studies included in this review, the specific tasks in the context of the COVID-19 pandemic that machine and deep learning methods were used for, and their practical limitations. The technical analysis focused on the details of specific MDL methods and their performance.

RESULTS

Analysis of the 48 selected studies revealed that the majority (∼54 %) of them examined the application of MDL methods for the prediction of survival/mortality-related patient outcomes, while a smaller fraction (∼13 %) of studies also examined applications to the prediction of patients' physiological outcomes and hospital resource utilization. 21 % of the studies examined the application of MDL methods to multiple clinical tasks. Machine and deep learning methods have been shown to be effective at predicting several outcomes of COVID-19 patients, such as disease severity, complications, intensive care unit (ICU) transfer, and mortality. MDL methods also achieved high accuracy in predicting the required number of ICU beds and ventilators.

CONCLUSION

Machine and deep learning methods have been shown to be valuable tools for predicting disease severity, organ dysfunction and failure, patient outcomes, and hospital resource utilization during the COVID-19 pandemic. The discovered knowledge and our conclusions and recommendations can also be useful to healthcare professionals and artificial intelligence researchers in managing future pandemics.

Plasma proteome of Long-COVID patients indicates HIF-mediated vasculo-proliferative disease with impact on brain and heart function

AIMS

Long-COVID occurs after SARS-CoV-2 infection and results in diverse, prolonged symptoms. The present study aimed to unveil potential mechanisms, and to inform prognosis and treatment.

METHODS

Plasma proteome from Long-COVID outpatients was analyzed in comparison to matched acutely ill COVID-19 (mild and severe) inpatients and healthy control subjects. The expression of 3072 protein biomarkers was determined with proximity extension assays and then deconvoluted with multiple bioinformatics tools into both cell types and signaling mechanisms, as well as organ specificity.

RESULTS

Compared to age- and sex-matched acutely ill COVID-19 inpatients and healthy control subjects, Long-COVID outpatients showed natural killer cell redistribution with a dominant resting phenotype, as opposed to active, and neutrophils that formed extracellular traps. This potential resetting of cell phenotypes was reflected in prospective vascular events mediated by both angiopoietin-1 (ANGPT1) and vascular-endothelial growth factor-A (VEGFA). Several markers (ANGPT1, VEGFA, CCR7, CD56, citrullinated histone 3, elastase) were validated by serological methods in additional patient cohorts. Signaling of transforming growth factor-β1 with probable connections to elevated EP/p300 suggested vascular inflammation and tumor necrosis factor-α driven pathways. In addition, a vascular proliferative state associated with hypoxia inducible factor 1 pathway suggested progression from acute COVID-19 to Long-COVID. The vasculo-proliferative process predicted in Long-COVID might contribute to changes in the organ-specific proteome reflective of neurologic and cardiometabolic dysfunction.

CONCLUSIONS

Taken together, our findings point to a vasculo-proliferative process in Long-COVID that is likely initiated either prior hypoxia (localized or systemic) and/or stimulatory factors (i.e., cytokines, chemokines, growth factors, angiotensin, etc). Analyses of the plasma proteome, used as a surrogate for cellular signaling, unveiled potential organ-specific prognostic biomarkers and therapeutic targets.

Neurologic Complications of Patients With COVID-19 Requiring Extracorporeal Membrane Oxygenation: A Systematic Review and Meta-Analysis

In COVID-19 patients requiring extracorporeal membrane oxygenation (ECMO), our primary objective was to determine the frequency of intracranial hemorrhage (ICH). Secondary objectives were to estimate the frequency of ischemic stroke, to explore association between higher anticoagulation targets and ICH, and to estimate the association between neurologic complications and in-hospital mortality.

DATA SOURCES

We searched MEDLINE, Embase, PsycINFO, Cochrane, and MedRxiv databases from inception to March 15, 2022.

STUDY SELECTION

We identified studies that described acute neurological complications in adult patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requiring ECMO.

DATA EXTRACTION

Two authors independently performed study selection and data extraction. Studies with 95% or more of its patients on venovenous or venoarterial ECMO were pooled for meta-analysis, which was calculated using a random-effects model.

DATA SYNTHESIS

Fifty-four studies (n = 3,347) were included in the systematic review. Venovenous ECMO was used in 97% of patients. Meta-analysis of ICH and ischemic stroke on venovenous ECMO included 18 and 11 studies, respectively. The frequency of ICH was 11% (95% CI, 8-15%), with intraparenchymal hemorrhage being the most common subtype (73%), while the frequency of ischemic strokes was 2% (95% CI, 1-3%). Higher anticoagulation targets were not associated with increased frequency of ICH (p = 0.06). In-hospital mortality was 37% (95% CI, 34-40%) and neurologic causes ranked as the third most common cause of death. The risk ratio of mortality in COVID-19 patients with neurologic complications on venovenous ECMO compared with patients without neurologic complications was 2.24 (95% CI, 1.46-3.46). There were insufficient studies for meta-analysis of COVID-19 patients on venoarterial ECMO.

CONCLUSIONS

COVID-19 patients requiring venovenous ECMO have a high frequency of ICH, and the development of neurologic complications more than doubled the risk of death. Healthcare providers should be aware of these increased risks and maintain a high index of suspicion for ICH.

Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning

BACKGROUND

Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as "Long-COVID". A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID.

METHODS

A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase.

RESULTS

Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID.

CONCLUSIONS

Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Hyaluronan in the pathogenesis of acute and post-acute COVID-19 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) recently emerged as the cause of a global pandemic. Infection with SARS-CoV-2 can result in COVID-19 with both acute and chronic disease manifestations that continue to impact many patients long after the resolution of viral replication. There is therefore great interest in understanding the host factors that contribute to COVID-19 pathogenesis. In this review, we address the role of hyaluronan (HA), an extracellular matrix polymer with roles in inflammation and cellular metabolism, in COVID-19 and critically evaluate the hypothesis that HA promotes COVID-19 pathogenesis. We first provide a brief overview of COVID-19 infection. Then we briefly summarize the known roles of HA in airway inflammation and immunity. We then address what is known about HA and the pathogenesis of COVID-19 acute respiratory distress syndrome (COVID-19 ARDS). Next, we examine potential roles for HA in post-acute SARS-CoV-2 infection (PASC), also known as "long COVID" as well as in COVID-associated fibrosis. Finally, we discuss the potential therapeutics that target HA as a means to treat COVID-19, including the repurposed drug hymecromone (4-methylumbelliferone). We conclude that HA is a promising potential therapeutic target for the treatment of COVID-19.

Cardiovascular and Renal Comorbidities Included into Neural Networks Predict the Outcome in COVID-19 Patients Admitted to an Intensive Care Unit: Three-Center, Cross-Validation, Age- and Sex-Matched Study

Here, we performed a multicenter, age- and sex-matched study to compare the efficiency of various machine learning algorithms in the prediction of COVID-19 fatal outcomes and to develop sensitive, specific, and robust artificial intelligence tools for the prompt triage of patients with severe COVID-19 in the intensive care unit setting. In a challenge against other established machine learning algorithms (decision trees, random forests, extra trees, neural networks, k-nearest neighbors, and gradient boosting: XGBoost, LightGBM, and CatBoost) and multivariate logistic regression as a reference, neural networks demonstrated the highest sensitivity, sufficient specificity, and excellent robustness. Further, neural networks based on coronary artery disease/chronic heart failure, stage 3-5 chronic kidney disease, blood urea nitrogen, and C-reactive protein as the predictors exceeded 90% sensitivity and 80% specificity, reaching AUROC of 0.866 at primary cross-validation and 0.849 at secondary cross-validation on virtual samples generated by the bootstrapping procedure. These results underscore the impact of cardiovascular and renal comorbidities in the context of thrombotic complications characteristic of severe COVID-19. As aforementioned predictors can be obtained from the case histories or are inexpensive to be measured at admission to the intensive care unit, we suggest this predictor composition is useful for the triage of critically ill COVID-19 patients.

Cross-immunity against SARS-COV-2 variants of concern in naturally infected critically ill COVID-19 patients

Critically ill patients infected with SARS-CoV-2 display adaptive immunity, but it is unknown if they develop cross-reactivity to variants of concern (VOCs). We profiled cross-immunity against SARS-CoV-2 VOCs in naturally infected, non-vaccinated, critically ill COVID-19 patients. Wave-1 patients (wild-type infection) were similar in demographics to Wave-3 patients (wild-type/alpha infection), but Wave-3 patients had higher illness severity. Wave-1 patients developed increasing neutralizing antibodies to all variants, as did patients during Wave-3. Wave-3 patients, when compared to Wave-1, developed more robust antibody responses, particularly for wild-type, alpha, beta and delta variants. Within Wave-3, neutralizing antibodies were significantly less to beta and gamma VOCs, as compared to wild-type, alpha and delta. Patients previously diagnosed with cancer or chronic obstructive pulmonary disease had significantly fewer neutralizing antibodies. Naturally infected ICU patients developed adaptive responses to all VOCs, with greater responses in those patients more likely to be infected with the alpha variant, versus wild-type.

Novel plasma protein biomarkers from critically ill sepsis patients

BACKGROUND

Despite the high morbidity and mortality associated with sepsis, the relationship between the plasma proteome and clinical outcome is poorly understood. In this study, we used targeted plasma proteomics to identify novel biomarkers of sepsis in critically ill patients.

METHODS

Blood was obtained from 15 critically ill patients with suspected/confirmed sepsis (Sepsis-3.0 criteria) on intensive care unit (ICU) Day-1 and Day-3, as well as age- and sex-matched 15 healthy control subjects. A total of 1161 plasma proteins were measured with proximal extension assays. Promising sepsis biomarkers were narrowed with machine learning and then correlated with relevant clinical and laboratory variables.

RESULTS

The median age for critically ill sepsis patients was 56 (IQR 51-61) years. The median MODS and SOFA values were 7 (IQR 5.0-8.0) and 7 (IQR 5.0-9.0) on ICU Day-1, and 4 (IQR 3.5-7.0) and 6 (IQR 3.5-7.0) on ICU Day-3, respectively. Targeted proteomics, together with feature selection, identified the leading proteins that distinguished sepsis patients from healthy control subjects with ≥ 90% classification accuracy; 25 proteins on ICU Day-1 and 26 proteins on ICU Day-3 (6 proteins overlapped both ICU days; PRTN3, UPAR, GDF8, NTRK3, WFDC2 and CXCL13). Only 7 of the leading proteins changed significantly between ICU Day-1 and Day-3 (IL10, CCL23, TGFα1, ST2, VSIG4, CNTN5, and ITGAV; P < 0.01). Significant correlations were observed between a variety of patient clinical/laboratory variables and the expression of 15 proteins on ICU Day-1 and 14 proteins on ICU Day-3 (P < 0.05).

CONCLUSIONS

Targeted proteomics with feature selection identified proteins altered in critically ill sepsis patients relative to healthy control subjects. Correlations between protein expression and clinical/laboratory variables were identified, each providing pathophysiological insight. Our exploratory data provide a rationale for further hypothesis-driven sepsis research.

Comparative Effectiveness of Dexamethasone in Treatment of Hospitalized COVID-19 Patients during the First Year of the Pandemic: The N3C Data Repository

Background

Dexamethasone, a widely available glucocorticoid, was approved for use in hospitalized COVID-19 patients early in the pandemic based on the RECOVERY trial; however, evidence is still needed to support its real-world effectiveness in patients with a wide range of comorbidities and in diverse care settings.

Objectives

To conduct a comparative effectiveness analysis of dexamethasone use with and without remdesivir in hospitalized COVID-19 patients using electronic health record data.

Methods

We conducted a retrospective real-world effectiveness analysis using the harmonized, highly granular electronic health record data of the National COVID Cohort Collaborative (N3C) Data Enclave. Analysis was restricted to COVID-19 patients in an inpatient setting, prior to vaccine availability. Primary outcome was in-hospital death; secondary outcome was combined in-hospital death and severe outcome as defined by use of ECMO or mechanical ventilation during stay. Missing data were imputed with single imputation. Matching of dexamethasone-treated patients to non-dexamethasone-treated controls was accomplished using propensity score (PS) matching, stratified by remdesivir treatment and based on demographics, baseline laboratory values, and comorbidities. Treatment benefit was quantified using logistic regression. Further sensitivity analyses were performed using clinical adjusters in matched groups and in strata defined by quartiles of PS.

Results

Regression analysis revealed a statistically significant association between dexamethasone use and reduced risk of in-hospital mortality for those not receiving remdesivir (OR=0.77, 95% CI:0.62 to 0.95, p=0.017), and a borderline statistically significant risk for those receiving remdesivir (OR=0.74, 95% CI: 0.53 to 1.02, p=0.054). Treatment also showed secondary outcome benefit. In sensitivity analyses, treatment effect size generally remained similar with some heterogeneity of benefit across strata of PS.

Conclusions

We add evidence that dexamethasone provides benefit with respect to mortality and severe outcomes in a diverse, national hospitalized sample, prior to vaccine availability.

The intercorrelations between blood levels of ferritin, sCD163, and IL-18 in COVID-19 patients and their association to prognosis

Coronavirus disease 2019 (COVID-19) is associated with immune dysregulation, severe respiratory failure, and multiple organ dysfunction caused by a cytokine storm involving high blood levels of ferritin and IL-18. Furthermore, there is a resemblance between COVID-19 and macrophage activation syndrome (MAS) characterized by high concentrations of soluble CD163 (sCD163) receptor and IL-18. High levels of ferritin, IL-18, and sCD163 receptor are associated with “hyperferritinemic syndrome”, a family of diseases that appears to include COVID-19. In this retrospective cohort study, we tested the association and intercorrelations in the serum levels of ferritin, sCD163, and IL-18 and their impact on the prognosis of COVID-19. We analyzed data of 70 hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The levels of sCD163, ferritin, and IL-18 were measured and the correlation of these parameters with the respiratory deterioration and overall 30-day survival was assessed. Among the 70 patients, 60 survived 30 days from hospitalization. There were substantial differences between the subjects who were alive following 30 days compared to those who expired. The differences were referring to lymphocyte and leukocyte count, CRP, D-dimer, ferritin, sCD163, and IL-18. Results showed high levels of IL-18 (median, 444 pg/mL in the survival group compared with 916 pg/mL in the mortality group, p-value 8.54 × 10–2), a statistically significant rise in levels of ferritin (median, 484 ng/mL in the survival group compared with 1004 ng/mL in the mortality group p-value, 7.94 × 10–3), and an elevated value of in sCD163 (mean, 559 ng/mL in the survival group compared with 840 ng/mL in the mortality group, p-value 1.68 × 10–2). There was no significant correlation between the rise of ferritin and the levels sCD163 or IL-18. Taken together, sCD163, ferritin, and IL-18 were found to correlate with the severity of COVID-19 infection. Although these markers are associated with COVID-19 and might contribute to the cytokine storm, no intercorrelation was found among them. It cannot be excluded though that the results depend on the timing of sampling, assuming that they play distinct roles in different stages of the disease course. The data represented herein may provide clinical benefit in improving our understanding of the pathological course of the disease. Furthermore, measuring these biomarkers during the disease progression may help target them at the right time and refine the decision-making regarding the requirement for hospitalization.

Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism

BACKGROUND

Long-COVID is characterized by prolonged, diffuse symptoms months after acute COVID-19. Accurate diagnosis and targeted therapies for Long-COVID are lacking. We investigated vascular transformation biomarkers in Long-COVID patients.

METHODS

A case-control study utilizing Long-COVID patients, one to six months (median 98.5 days) post-infection, with multiplex immunoassay measurement of sixteen blood biomarkers of vascular transformation, including ANG-1, P-SEL, MMP-1, VE-Cad, Syn-1, Endoglin, PECAM-1, VEGF-A, ICAM-1, VLA-4, E-SEL, thrombomodulin, VEGF-R2, VEGF-R3, VCAM-1 and VEGF-D.

RESULTS

Fourteen vasculature transformation blood biomarkers were significantly elevated in Long-COVID outpatients, versus acutely ill COVID-19 inpatients and healthy controls subjects (P < 0.05). A unique two biomarker profile consisting of ANG-1/P-SEL was developed with machine learning, providing a classification accuracy for Long-COVID status of 96%. Individually, ANG-1 and P-SEL had excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, P < 0.0001; validated in a secondary cohort). Specific to Long-COVID, ANG-1 levels were associated with female sex and a lack of disease interventions at follow-up (P < 0.05).

CONCLUSIONS

Long-COVID patients suffer prolonged, diffuse symptoms and poorer health. Vascular transformation blood biomarkers were significantly elevated in Long-COVID, with angiogenesis markers (ANG-1/P-SEL) providing classification accuracy of 96%. Vascular transformation blood biomarkers hold potential for diagnostics, and modulators of angiogenesis may have therapeutic efficacy.

Therapeutic plasma exchange: A potential therapeutic modality for critically ill adults with severe acute respiratory syndrome coronavirus 2 infection

Background

Severe acute respiratory syndrome coronavirus 2 infection can be severe and fatal due to cytokine storm. Therapeutic plasma exchange (TPE) potentially mitigates the harmful effects of such cytokines. We investigated the use of TPE, as rescue therapy, in patients with severe Coronavirus disease 2019 (COVID‐19) infection.

Study Design and Methods

A retrospective analysis on COVID‐19 patients admitted to the intensive care unit and treated with TPE from April 17, 2020 to July 2, 2020. This group was compared with COVID‐19 patients who received standard therapy without TPE. The following outcomes were analyzed: changes in laboratory parameters, length of hospital stay (LOS), days on mechanical ventilation, mortality at days 14 and overall mortality.

Results

A total of 95 patients were included, among whom 47% (n = 45) received TPE. Patients who received TPE had reductions in C‐reactive protein (P = .002), ferritin (P < .001) and interleukin‐6 (P = .013). After employing entropy‐balancing matching method, those on TPE were also more likely to discontinue inotropes (72% vs 21%; P < .001). However, they were more likely to be associated with longer LOS (23 vs 14 days; P = .002) and longer days on ventilatory support (14 vs 8 days; P < .001). Despite marginal mortality benefit at 14‐days (7.9% vs 24%; P = .071), there was no significant differences in overall mortality (21% vs 31%; P = .315) between the groups.

Conclusions

TPE was effective in reducing inflammatory markers in patients with severe COVID‐19 infection, however, further research is warranted.

Clinical characteristics, multiorgan dysfunction and outcomes of patients with COVID-19: a prospective case series

BACKGROUND

Characterizing the multiorgan manifestations and outcomes of patients hospitalized with COVID-19 will inform resource requirements to address the long-term burden of this disease. We conducted a descriptive analysis using prospectively collected data to describe the clinical characteristics and spectrum of organ dysfunction, and in-hospital and longer-term clinical outcomes of patients hospitalized with COVID-19 during the first wave of the pandemic at a Canadian centre.

METHODS

We conducted a prospective case series involving adult patients (aged ≥ 18 yr) with COVID-19 admitted to 1 of 2 hospitals in London, Ontario, from Mar. 17 to June 18, 2020, during the first wave of the pandemic. We recorded patients' baseline characteristics, physiologic parameters, measures of organ function and therapies administered during hospitalization among patients in the intensive care unit (ICU) and in non-ICU settings, and compared the characteristics of hospital survivors and nonsurvivors. Finally, we recorded follow-up thoracic computed tomography (CT) and echocardiographic findings after hospital discharge.

RESULTS

We enrolled 100 consecutive patients (47 women) hospitalized with COVID-19, including 32 patients who received ICU care and 68 who received treatment in non-ICU settings. Respiratory sequelae were common: 23.0% received high-flow oxygen by nasal cannula, 9.0% received noninvasive ventilation, 24.0% received invasive mechanical ventilation and 2.0% received venovenous extracorporeal membrane oxygenation. Overall, 9.0% of patients had cerebrovascular events (3.0% ischemic stroke, 6.0% intracranial hemorrhage), and 6.0% had pulmonary embolism. After discharge, 11 of 19 patients had persistent abnormalities on CT thorax, and 6 of 15 had persistent cardiac dysfunction on echocardiography.

INTERPRETATION

This study provides further evidence that COVID-19 is a multisystem disease involving neurologic, cardiac and thrombotic dysfunction, without evidence of hepatic dysfunction. Patients have persistent organ dysfunction after hospital discharge, underscoring the need for research on long-term outcomes of COVID-19 survivors.

The role of IL-1 family of cytokines and receptors in pathogenesis of COVID-19

A global pandemic has erupted as a result of the new brand coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This pandemic has been consociated with widespread mortality worldwide. The antiviral immune response is an imperative factor in confronting the recent coronavirus disease 2019 (COVID-19) infections. Meantime, cytokines recognize as crucial components in guiding the appropriate immune pathways in the restraining and eradication of the virus. Moreover, SARS-CoV-2 can induce uncontrolled inflammatory responses characterized by hyper-inflammatory cytokine production, which causes cytokine storm and acute respiratory distress syndrome (ARDS). As excessive inflammatory responses are contributed to the severe stage of the COVID-19 disease, therefore, the pro-inflammatory cytokines are regarded as the Achilles heel during COVID-19 infection. Among these cytokines, interleukin (IL-) 1 family cytokines (IL-1, IL-18, IL-33, IL-36, IL-37, and IL-38) appear to have a strong inflammatory role in severe COVID-19. Hence, understanding the underlying inflammatory mechanism of these cytokines during infection is critical for reducing the symptoms and severity of the disease. Here, the possible mechanisms and pathways involved in inflammatory immune responses are discussed.

Biochemical, biophysical, and immunological characterization of respiratory secretions in severe SARS-CoV-2 infections

Thick, viscous respiratory secretions are a major pathogenic feature of COVID-19, but the composition and physical properties of these secretions are poorly understood. We characterized the composition and rheological properties (i.e., resistance to flow) of respiratory secretions collected from intubated COVID-19 patients. We found the percentages of solids and protein content were greatly elevated in COVID-19 compared with heathy control samples and closely resembled levels seen in cystic fibrosis, a genetic disease known for thick, tenacious respiratory secretions. DNA and hyaluronan (HA) were major components of respiratory secretions in COVID-19 and were likewise abundant in cadaveric lung tissues from these patients. COVID-19 secretions exhibited heterogeneous rheological behaviors, with thicker samples showing increased sensitivity to DNase and hyaluronidase treatment. In histologic sections from these same patients, we observed increased accumulation of HA and the hyaladherin versican but reduced tumor necrosis factor-stimulated gene-6 staining, consistent with the inflammatory nature of these secretions. Finally, we observed diminished type I interferon and enhanced inflammatory cytokines in these secretions. Overall, our studies indicated that increases in HA and DNA in COVID-19 respiratory secretion samples correlated with enhanced inflammatory burden and suggested that DNA and HA may be viable therapeutic targets in COVID-19 infection.

Biochemical, Biophysical, and Immunological Characterization of Respiratory Secretions in Severe SARS-CoV-2 (COVID-19) Infections.. [PMID: 35411348 PMCID: PMC8996635 DOI: 10.1101/2022.03.28.22272848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Thick, viscous respiratory secretions are a major pathogenic feature of COVID-19 disease, but the composition and physical properties of these secretions are poorly understood. We characterized the composition and rheological properties (i.e. resistance to flow) of respiratory secretions collected from intubated COVID-19 patients. We find the percent solids and protein content are greatly elevated in COVID-19 compared to heathy control samples and closely resemble levels seen in cystic fibrosis, a genetic disease known for thick, tenacious respiratory secretions. DNA and hyaluronan (HA) are major components of respiratory secretions in COVID-19 and are likewise abundant in cadaveric lung tissues from these patients. COVID-19 secretions exhibit heterogeneous rheological behaviors with thicker samples showing increased sensitivity to DNase and hyaluronidase treatment. In histologic sections from these same patients, we observe increased accumulation of HA and the hyaladherin versican but reduced tumor necrosis factor–stimulated gene-6 (TSG6) staining, consistent with the inflammatory nature of these secretions. Finally, we observed diminished type I interferon and enhanced inflammatory cytokines in these secretions. Overall, our studies indicate that increases in HA and DNA in COVID-19 respiratory secretion samples correlate with enhanced inflammatory burden and suggest that DNA and HA may be viable therapeutic targets in COVID-19 infection.

Endothelial glycocalyx degradation in multisystem inflammatory syndrome in children related to COVID-19

Abstract

Multisystem inflammatory syndrome in children (MIS-C) represents a rare but severe complication of severe acute respiratory syndrome coronavirus 2 infection affecting children that can lead to myocardial injury and shock. Vascular endothelial dysfunction has been suggested to be a common complicating factor in patients with coronavirus disease 2019 (COVID-19). This study aims to characterize endothelial glycocalyx degradation in children admitted with MIS-C. We collected blood and urine samples and measured proinflammatory cytokines, myocardial injury markers, and endothelial glycocalyx markers in 17 children admitted with MIS-C, ten of which presented with inflammatory shock requiring intensive care admission and hemodynamic support with vasopressors. All MIS-C patients presented signs of glycocalyx deterioration with elevated levels of syndecan-1 in blood and both heparan sulfate and chondroitin sulfate in the urine. The degree of glycocalyx shedding correlated with tumor necrosis factor-α concentration. Five healthy age-matched children served as controls. Patients with MIS-C presented severe alteration of the endothelial glycocalyx that was associated with disease severity. Future studies should clarify if glycocalyx biomarkers could effectively be predictive indicators for the development of complications in adult patients with severe COVID-19 and children with MIS-C.

Key messages

Children admitted with MIS-C presented signs of endothelial glycocalyx injury with elevated syndecan-1 and heparan sulfate level.

Syndecan-1 levels were associated with MIS-C severity and correlated TNF-α concentration.

Syndecan-1 and heparan sulfate may represent potential biomarkers for patients with severe COVID-19 or MIS-C.

Supplementary information

The online version contains supplementary material available at 10.1007/s00109-022-02190-7.

Cytokine producing ability of peripheral blood cells from COVID-19 patients after unspecific in vitro stimulation

Objective and design

Subjects and methods

Results

Conclusion

Immunothrombosis Biomarkers for Distinguishing Coronavirus Disease 2019 Patients From Noncoronavirus Disease Septic Patients With Pneumonia and for Predicting ICU Mortality

Supplemental Digital Content is available in the text.

IMPORTANCE:

Coronavirus disease 2019 patients have an increased risk of thrombotic complications that may reflect immunothrombosis, a process characterized by blood clotting, endothelial dysfunction, and the release of neutrophil extracellular traps. To date, few studies have investigated longitudinal changes in immunothrombosis biomarkers in these patients. Furthermore, how these longitudinal changes differ between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia are unknown.

OBJECTIVES:

In this pilot observational study, we investigated the utility of immunothrombosis biomarkers for distinguishing between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia. We also evaluated the utility of the biomarkers for predicting ICU mortality in these patients.

DESIGN, SETTING, AND PARTICIPANTS:

The participants were ICU patients with coronavirus disease 2019 (n = 14), noncoronavirus disease septic patients with pneumonia (n = 19), and healthy age-matched controls (n = 14).

MAIN OUTCOMES AND MEASURES:

Nine biomarkers were measured from plasma samples (on days 1, 2, 4, 7, 10, and/or 14). Analysis was based on binomial logit models and receiver operating characteristic analyses.

RESULTS:

Cell-free DNA, d-dimer, soluble endothelial protein C receptor, protein C, soluble thrombomodulin, fibrinogen, citrullinated histones, and thrombin-antithrombin complexes have significant powers for distinguishing coronavirus disease 2019 patients from healthy individuals. In comparison, fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have significant powers for distinguishing coronavirus disease 2019 from pneumonia patients. The predictors of ICU mortality differ between the two patient groups: soluble thrombomodulin and citrullinated histones for coronavirus disease 2019 patients, and protein C and cell-free DNA or fibrinogen for pneumonia patients. In both patient groups, the most recent biomarker values have stronger prognostic value than their ICU day 1 values.

CONCLUSIONS AND RELEVANCE:

Fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have utility for distinguishing coronavirus disease 2019 patients from noncoronavirus disease septic patients with pneumonia. The most important predictors of ICU mortality are soluble thrombomodulin/citrullinated histones for coronavirus disease 2019 patients, and protein C/cell-free DNA for noncoronavirus disease pneumonia patients. This hypothesis-generating study suggests that the pathophysiology of immunothrombosis differs between the two patient groups.

Syndecan-1, an indicator of endothelial glycocalyx degradation, predicts outcome of patients admitted to an ICU with COVID-19

Background

We investigated the feasibility of two biomarkers of endothelial damage (Syndecan-1 and thrombomodulin) in coronavirus disease 2019 (COVID-19), and their association with inflammation, coagulopathy, and mortality.

Methods

The records of 49 COVID-19 patients who were admitted to an intensive care unit (ICU) in Wuhan, China between February and April 2020 were examined. Demographic, clinical, and laboratory data, and outcomes were compared between survivors and non-survivors COVID-19 patients, and between patients with high and low serum Syndecan-1 levels. The dynamics of serum Syndecan-1 levels were also analyzed.

Results

The levels of Syndecan-1 were significantly higher in non-survivor group compared with survivor group (median 1031.4 versus 504.0 ng/mL, P = 0.002), and the levels of thrombomodulin were not significantly different between these two groups (median 4534.0 versus 3780.0 ng/mL, P = 0.070). Kaplan–Meier survival analysis showed that the group with high Syndecan-1 levels had worse overall survival (log-rank test: P = 0.023). Patients with high Syndecan-1 levels also had significantly higher levels of thrombomodulin, interleukin-6, and tumor necrosis factor-α. Data on the dynamics of Syndecan-1 levels indicated much greater variations in non-survivors than survivors.

Conclusions

COVID-19 patients with high levels of Syndecan-1 develop more serious endothelial damage and inflammatory reactions, and have increased mortality. Syndecan-1 has potential for use as a marker for progression or severity of COVID-19. Protecting the glycocalyx from destruction is a potential treatment for COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00412-1.

Discovery Proteomics for COVID-19: Where We Are Now

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus responsible for the pandemic coronavirus disease 2019 (COVID-19), which has had a devastating impact on society. Here, we summarize proteomic research that has helped elucidate hallmark proteins associated with the disease with respect to both short- and long-term diagnosis and prognosis. Additionally, we review the highly variable humoral response associated with COVID-19 and the increased risk of autoimmunity.

Therapeutic Potential of Annexins in Sepsis and COVID-19

Sepsis is a continuing problem in modern healthcare, with a relatively high prevalence, and a significant mortality rate worldwide. Currently, no specific anti-sepsis treatment exists despite decades of research on developing potential therapies. Annexins are molecules that show efficacy in preclinical models of sepsis but have not been investigated as a potential therapy in patients with sepsis. Human annexins play important roles in cell membrane dynamics, as well as mediation of systemic effects. Most notably, annexins are highly involved in anti-inflammatory processes, adaptive immunity, modulation of coagulation and fibrinolysis, as well as protective shielding of cells from phagocytosis. These discoveries led to the development of analogous peptides which mimic their physiological function, and investigation into the potential of using the annexins and their analogous peptides as therapeutic agents in conditions where inflammation and coagulation play a large role in the pathophysiology. In numerous studies, treatment with recombinant human annexins and annexin analogue peptides have consistently found positive outcomes in animal models of sepsis, myocardial infarction, and ischemia reperfusion injury. Annexins A1 and A5 improve organ function and reduce mortality in animal sepsis models, inhibit inflammatory processes, reduce inflammatory mediator release, and protect against ischemic injury. The mechanisms of action and demonstrated efficacy of annexins in animal models support development of annexins and their analogues for the treatment of sepsis. The effects of annexin A5 on inflammation and platelet activation may be particularly beneficial in disease caused by SARS-CoV-2 infection. Safety and efficacy of recombinant human annexin A5 are currently being studied in clinical trials in sepsis and severe COVID-19 patients.

A possible pathogenic correlation between neutrophil elastase (NE) enzyme and inflammation in the pathogenesis of coronavirus disease 2019 (COVID-19)

A growing body of evidence indicates that neutrophil elastase (NE) is involved in the pathogenesis of respiratory infectious diseases, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to analyze the dynamic changes in serum levels of NE associated with inflammation, disease activity, and mortality rate in patients with COVID-19. We measured the serum concentrations of NE, C-Reactive protein (CRP), interleukin (IL)- 4, IL-6, IL-8, IL-10, and vitamin D levels in 83 ICU and 69 non-ICU patients compared with 82 healthy subjects (HS) in three-time points (T1-T3). Serum levels of NE, IL-6, IL-8, and CRP in ICU and non-ICU patients were significantly higher than HS (P < 0.001) in three-time points. Also, serum levels of NE, IL-6, IL-8, and CRP in ICU patients were significantly higher than in non-ICU patients (P < 0.05). On the day of admission (T1), the levels of NE, CRP, IL-6, IL-8 were gradually decreased from T1 to T3. At the same time, IL-4 and IL-10 were gradually increased from T1 to T2 and then reduced to T3. Further analyses demonstrated that the levels of NE, IL-6, and IL-8 in deceased patients were significantly higher than in recovered patients (P < 0.05). The ROC curve analysis demonstrated that markers, including NE, IL-6, and IL-8, were valuable indicators in evaluating the activity of COVID-19. Overall, our results signify the critical role of NE in the pathogenesis of COVID-19, and also, further support that NE has a potential therapeutic target for the attenuation of COVID-19 severity.

Biomarkers of Post-COVID Depression

The COVID-19 pandemic is spreading around the world and 187 million people have already been affected. One of its after-effects is post-COVID depression, which, according to the latest data, affects up to 40% of people who have had SARS-CoV-2 infection. A very important issue for the mental health of the general population is to look for the causes of this complication and its biomarkers. This will help in faster diagnosis and effective treatment of the affected patients. In our work, we focused on the search for major depressive disorder (MDD) biomarkers, which are also present in COVID-19 patients and may influence the development of post-COVID depression. For this purpose, we searched PubMed, Scopus and Google Scholar scientific literature databases using keywords such as 'COVID-19', 'SARS-CoV-2', 'depression', 'post-COVID', 'biomarkers' and others. Among the biomarkers found, the most important that were frequently described are increased levels of interleukin 6 (IL-6), soluble interleukin 6 receptor (sIL-6R), interleukin 1 β (IL-1β), tumor necrosis factor α (TNF-α), interferon gamma (IFN-γ), interleukin 10 (IL-10), interleukin 2 (IL-2), soluble interleukin 2 receptor (sIL-2R), C-reactive protein (CRP), Monocyte Chemoattractant Protein-1 (MCP-1), serum amyloid a (SAA1) and metabolites of the kynurenine pathway, as well as decreased brain derived neurotrophic factor (BDNF) and tryptophan (TRP). The biomarkers identified by us indicate the etiopathogenesis of post-COVID depression analogous to the leading inflammatory hypothesis of MDD.

Routine Hematological Parameters May Be Predictors of COVID-19 Severity

To date, coronavirus disease 2019 (COVID-19) has affected over 100 million people globally. COVID-19 can present with a variety of different symptoms leading to manifestation of disease ranging from mild cases to a life-threatening condition requiring critical care-level support. At present, a rapid prediction of disease severity and critical care requirement in COVID-19 patients, in early stages of disease, remains an unmet challenge. Therefore, we assessed whether parameters from a routine clinical hematology workup, at the time of hospital admission, can be valuable predictors of COVID-19 severity and the requirement for critical care. Hematological data from the day of hospital admission (day of positive COVID-19 test) for patients with severe COVID-19 disease (requiring critical care during illness) and patients with non-severe disease (not requiring critical care) were acquired. The data were amalgamated and cleaned and modeling was performed. Using a decision tree model, we demonstrated that routine clinical hematology parameters are important predictors of COVID-19 severity. This proof-of-concept study shows that a combination of activated partial thromboplastin time, white cell count-to-neutrophil ratio, and platelet count can predict subsequent severity of COVID-19 with high sensitivity and specificity (area under ROC 0.9956) at the time of the patient's hospital admission. These data, pending further validation, indicate that a decision tree model with hematological parameters could potentially form the basis for a rapid risk stratification tool that predicts COVID-19 severity in hospitalized patients.

Excessive Matrix Metalloproteinase-1 and Hyperactivation of Endothelial Cells Occurred in COVID-19 Patients and Were Associated With the Severity of COVID-19

BACKGROUND

Systemic vascular injury occurs in coronavirus disease 2019 (COVID-19) patients; however, the underlying mechanisms remain unknown.

METHODS

To clarify the role of inflammatory factors in COVID-19 vascular injury, we used a multiplex immunoassay to profile 65 inflammatory cytokines/chemokines/growth factors in plasma samples from 24 hospitalized (severe/critical) COVID-19 patients, 14 mild/moderate cases, and 13 healthy controls (HCs).

RESULTS

COVID-19 patients had significantly higher plasma levels of 20 analytes than HCs. Surprisingly, only 1 cytokine, macrophage migration inhibitory factor (MIF), was among these altered analytes, while the rest were chemokines/growth factors. Additionally, only matrix metalloproteinase-1 (MMP-1) and vascular endothelial growth factor A (VEGF-A) were significantly elevated in hospitalized COVID-19 patients when compared to mild/moderate cases. We further studied MMP-1 enzymatic activity and multiple endothelial cell (EC) activation markers (soluble forms of CD146, intercellular adhesion molecule 1 [ICAM-1], and vascular cell adhesion molecule 1 [VCAM-1]) and found that they were highly dysregulated in COVID-19 patients.

CONCLUSIONS

COVID-19 patients have a unique inflammatory profile, and excessive MMP-1 and hyperactivation of ECs are associated with the severity of COVID-19.

Biomarkers of coagulation, endothelial function, and fibrinolysis in critically ill patients with COVID-19: A single-center prospective longitudinal study

BACKGROUND

Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID-19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential.

METHODS

We performed a single-center prospective study of 14 adult COVID-19(+) intensive care unit patients who were age- and sex-matched to 14 COVID-19(-) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher's linear discriminant function. Linear repeated-measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts.

RESULTS

Elevated D-dimer was the strongest contributor in distinguishing COVID-19 status; however, D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels.

CONCLUSIONS

Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19.

Key Determinants of Cell-Mediated Immune Responses: A Randomized Trial of High Dose Vs. Standard Dose Split-Virus Influenza Vaccine in Older Adults

Background: Efforts to improve influenza vaccine effectiveness in older adults have resulted in some successes, such as the introduction of high-dose split-virus influenza vaccine (HD-SVV), yet studies of cell-mediated immune responses to these vaccines remain limited. We have shown that granzyme B (GrB) activity in influenza A/H3N2 challenged peripheral blood mononuclear cells (PBMC) correlates with protection against influenza following standard dose vaccination (SD-SVV) in older adults. Further, the interferon-γ (IFNγ) to interleukin-10 (IL-10) ratio can be a correlate of protection.

Methods: In a double-blind trial (ClinicalTrials.gov NCT02297542) older adults (≥65 years, n = 582) were randomized to receive SD-SVV or HD-SVV (Fluzone®) from 2014/15 to 2017/18. Young adults (20–40 years, n = 79) received SD-SVV. At 0, 4, 10, and 20 weeks post-vaccination, serum antibody titers, IFNγ, IL-10, and inducible GrB (iGrB) were measured in ex vivo influenza-challenged PBMC. iGrB is defined as the fold change in GrB activity from baseline levels (bGrB) in circulating T cells. Responses of older adults were compared to younger controls, and in older adults, we analyzed effects of age, sex, cytomegalovirus (CMV) serostatus, frailty, and vaccine dose.

Results: Prior to vaccination, younger compared to older adults produced significantly higher IFNγ, IL-10, and iGrB levels. Relative to SD-SVV recipients, older HD-SVV recipients exhibited significantly lower IFNγ:IL-10 ratios at 4 weeks post-vaccination. In contrast, IFNγ and iGrB levels were higher in younger SD vs. older SD or HD recipients; only the HD group showed a significant IFNγ response to vaccination compared to the SD groups; all three groups showed a significant iGrB response to vaccination. In a regression analysis, frailty was associated with lower IFNγ levels, whereas female sex and HD-SVV with higher IL-10 levels. Age and SD-SVV were associated with lower iGrB levels. The effect of prior season influenza vaccination was decreased iGrB levels, and increased IFNγ and IL-10 levels, which correlated with influenza A/H3N2 hemagglutination inhibition antibody titers.

Conclusion: Overall, HD-SVV amplified the IL-10 response consistent with enhanced antibody responses, with little effect on the iGrB response relative to SD-SVV in either younger or older adults. These results suggest that enhanced protection with HD-SVV is largely antibody-mediated.

Clinical Trial Registration: ClinicalTrials.gov (NCT02297542).

Critically Ill COVID-19 Patients Exhibit Anti-SARS-CoV-2 Serological Responses

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is a global health care emergency. Anti-SARS-CoV-2 serological profiling of critically ill COVID-19 patients was performed to determine their humoral response. Blood was collected from critically ill ICU patients, either COVID-19 positive (+) or COVID-19 negative (-), to measure anti-SARS-CoV-2 immunoglobulins: IgM; IgA; IgG; and Total Ig (combined IgM/IgA/IgG). Cohorts were similar, with the exception that COVID-19+ patients had a greater body mass indexes, developed bilateral pneumonias more frequently and suffered increased hypoxia when compared to COVID-19- patients (p < 0.05). The mortality rate for COVID-19+ patients was 50%. COVID-19 status could be determined by anti-SARS-CoV-2 serological responses with excellent classification accuracies on ICU day 1 (89%); ICU day 3 (96%); and ICU days 7 and 10 (100%). The importance of each Ig isotype for determining COVID-19 status on combined ICU days 1 and 3 was: Total Ig, 43%; IgM, 27%; IgA, 24% and IgG, 6%. Peak serological responses for each Ig isotype occurred on different ICU days (IgM day 13 > IgA day 17 > IgG persistently increased), with the Total Ig peaking at approximately ICU day 18. Those COVID-19+ patients who died had earlier or similar peaks in IgA and Total Ig in their ICU stay when compared to patients who survived (p < 0.005). Critically ill COVID-19 patients exhibit anti-SARS-CoV-2 serological responses, including those COVID-19 patients who ultimately died, suggesting that blunted serological responses did not contribute to mortality. Serological profiling of critically ill COVID-19 patients may aid disease surveillance, patient cohorting and help guide antibody therapies such as convalescent plasma.

Artificial Intelligence Applications for COVID-19 in Intensive Care and Emergency Settings: A Systematic Review

Background: Little is known about the role of artificial intelligence (AI) as a decisive technology in the clinical management of COVID-19 patients. We aimed to systematically review and critically appraise the current evidence on AI applications for COVID-19 in intensive care and emergency settings. Methods: We systematically searched PubMed, Embase, Scopus, CINAHL, IEEE Xplore, and ACM Digital Library databases from inception to 1 October 2020, without language restrictions. We included peer-reviewed original studies that applied AI for COVID-19 patients, healthcare workers, or health systems in intensive care, emergency, or prehospital settings. We assessed predictive modelling studies and critically appraised the methodology and key findings of all other studies. Results: Of fourteen eligible studies, eleven developed prognostic or diagnostic AI predictive models, all of which were assessed to be at high risk of bias. Common pitfalls included inadequate sample sizes, poor handling of missing data, failure to account for censored participants, and weak validation of models. Conclusions: Current AI applications for COVID-19 are not ready for deployment in acute care settings, given their limited scope and poor quality. Our findings underscore the need for improvements to facilitate safe and effective clinical adoption of AI applications, for and beyond the COVID-19 pandemic.

A possible pathogenic role of Syndecan-1 in the pathogenesis of coronavirus disease 2019 (COVID-19)

A cell-surface heparan proteoglycan called Syndecan-1 (SDC-1) has multiple roles in healthy and pathogenic conditions, including respiratory viral infection. In this study, we explore the dynamic alternation in the levels of SDC-1 in cases with COVID-19. A total of 120 cases definitely diagnosed with COVID-19 were admitted to the Firoozgar Hospital, Tehran, Iran, from December 1, 2020, to January 29, 2021, and included in our study. Also, 58 healthy subjects (HS) were chosen as the control group. Patients were classified into two groups: 1) ICU patients and (63 cases) 2) non-ICU patients (57 cases). The dynamic changes of serum SCD-1, CRP, IL-6, IL-10, IL-18, and Vit D levels a well as the disease activity were investigated in three-time points (T1-T3). Our results indicated that the COVID-19 patients had significantly increased SCD-1, CRP, IL-6, IL-10, and IL-18 levels than in HS, while the Vit D levels in COVID-19 patients were significantly lower than HS. Further analysis demonstrated that the SCD-1, CRP, IL-6, IL-10, and IL-18 levels in ICU patients were significantly higher than in non-ICU patients. Tracking dynamic changes in the above markers indicated that on the day of admission, the SCD-1, CRP, IL-6, IL-10, and IL-18 levels were gradually increased on day 5 (T2) and then gradually decreased on day 10 (T3). ROC curve analysis suggests that markers mentioned above, SDC-1, IL-6, and IL-18 are valuable indicators in evaluating the activity of COVID-19. All in all, it seems that the serum SDC-1 levels alone or combined with other markers might be a good candidate for disease activity monitoring.

Management of COVID-19-associated multisystem inflammatory syndrome in children: A comprehensive literature review

Background

The prevalence and severity of COVID-19 are greatly reduced in children, yet some pediatric patients develop a syndrome resembling Kawasaki Disease (KD), termed Multisystem Inflammatory Syndrome in Children (MIS-C). With an estimated incidence of 2/100,000 children, MIS-C is relatively rare but can be fatal. Clinical features can include fever, hyperinflammatory state, gastrointestinal symptoms, myocardial dysfunction, and shock. The pathogenesis of MIS-C, although yet to be completely elucidated, appears to be distinct from KD in terms of epidemiology, severity, and biochemical signature.

Aim of Review

Although efficacy of treatments for MIS-C have largely not yet been investigated, we aim to conduct a comprehensive literature search of numerous medical databases (AMED, EBM Reviews, Embase, Healthstar, MEDLINE, ERIC, and Cochrane) to highlight treatments used around the world, their rationale, and outcomes to better inform guidelines in the future. Using the findings, an approach to MIS-C management will be outlined.

Key Scientific Concepts of Review

•

MIS-C appears to be a SARS-CoV-2 related post-infection phenomenon that is distinct from Kawasaki disease.

•

Although outcomes are largely favorable, there is significant variation in MIS-C treatment. Most management regimens reported to date mirror that of KD; however, targeted therapy based on specific MIS-C phenotypes may have the potential to improve outcomes.

•

We recommend close monitoring by a multidisciplinary team, symptomatic treatment (e.g., intravenous immunoglobulin for KD-like symptoms, steroids/immunotherapy for multisystem inflammation), and long-term follow-up.

•

Further research is required to evaluate the effectiveness of current MIS-C treatments and to determine more refined therapies.

Detection and Profiling of Human Coronavirus Immunoglobulins in Critically Ill Coronavirus Disease 2019 Patients

OBJECTIVES

Coronavirus disease 2019 continues to spread worldwide with high levels of morbidity and mortality. We performed anticoronavirus immunoglobulin G profiling of critically ill coronavirus disease 2019 patients to better define their underlying humoral response.

DESIGN

Blood was collected at predetermined ICU days to measure immunoglobulin G with a research multiplex assay against four severe acute respiratory syndrome coronavirus 2 proteins/subunits and against all six additionally known human coronaviruses.

SETTING

Tertiary care ICU and academic laboratory.

SUBJECTS

ICU patients suspected of being infected with severe acute respiratory syndrome coronavirus 2 had blood collected until either polymerase chain reaction testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative) or until death or discharge if the patient tested polymerase chain reaction positive (coronavirus disease 2019 positive).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Age- and sex-matched healthy controls and ICU patients who were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients had greater body mass indexes, presented with bilateral pneumonias more frequently, and suffered lower Pao2:Fio2 ratios, when compared with coronavirus disease 2019 negative patients (p < 0.05). Mortality rate for coronavirus disease 2019 positive patients was 50%. On ICU days 1-3, anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G was significantly elevated in coronavirus disease 2019 positive patients, as compared to both healthy control subjects and coronavirus disease 2019 negative patients (p < 0.001). Weak severe acute respiratory syndrome coronavirus immunoglobulin G serologic responses were also detected, but not other coronavirus subtypes. The four anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G were maximal by ICU day 3, with all four anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G providing excellent diagnostic potential (severe acute respiratory syndrome coronavirus 2 Spike 1 protein immunoglobulin G, area under the curve 1.0, p < 0.0005; severe acute respiratory syndrome coronavirus receptor binding domain immunoglobulin G, area under the curve, 0.93-1.0; p ≤ 0.0001; severe acute respiratory syndrome coronavirus 2 Spike proteins immunoglobulin G, area under the curve, 1.0; p < 0.0001; severe acute respiratory syndrome coronavirus 2 Nucleocapsid protein immunoglobulin G area under the curve, 0.90-0.95; p ≤ 0.0003). Anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G increased and/or plateaued over 10 ICU days.

CONCLUSIONS

Critically ill coronavirus disease 2019 patients exhibited anti-severe acute respiratory syndrome coronavirus 2 immunoglobulin G, whereas serologic responses to non-severe acute respiratory syndrome coronavirus 2 antigens were weak or absent. Detection of human coronavirus immunoglobulin G against the different immunogenic structural proteins/subunits with multiplex assays may be useful for pathogen identification, patient cohorting, and guiding convalescent plasma therapy.

Unique inflammatory profile is associated with higher SARS-CoV-2 acute respiratory distress syndrome (ARDS) mortality

The COVID19 pandemic has caused more than a million of deaths worldwide, primarily due to complications from COVID19-associated acute respiratory distress syndrome (ARDS). Controversy surrounds the circulating cytokine/chemokine profile of COVID19-associated ARDS, with some groups suggesting that it is similar to patients without COVID19 ARDS and others observing substantial differences. Moreover, although a hyperinflammatory phenotype associates with higher mortality in non-COVID19 ARDS, there is little information on the inflammatory landscape's association with mortality in patients with COVID19 ARDS. Even though the circulating leukocytes' transcriptomic signature has been associated with distinct phenotypes and outcomes in critical illness including ARDS, it is unclear whether the mortality-associated inflammatory mediators from patients with COVID19 are transcriptionally regulated in the leukocyte compartment. Here, we conducted a prospective cohort study of 41 mechanically ventilated patients with COVID19 infection using highly calibrated methods to define the levels of plasma cytokines/chemokines and their gene expressions in circulating leukocytes. Plasma IL1RA and IL8 were found positively associated with mortality, whereas RANTES and EGF negatively associated with that outcome. However, the leukocyte gene expression of these proteins had no statistically significant correlation with mortality. These data suggest a unique inflammatory signature associated with severe COVID19.

First and Second Waves of Coronavirus Disease 2019 in Madrid, Spain: Clinical Characteristics and Hematological Risk Factors Associated With Critical/Fatal Illness

Supplemental Digital Content is available in the text.

Objectives:

This study aims to determine similarities and differences in clinical characteristics between the patients from two waves of severe acute respiratory syndrome coronavirus-2 infection at the time of hospital admission, as well as to identify risk biomarkers of coronavirus disease 2019 severity.

Design:

Retrospective observational study.

Setting:

A single tertiary-care center in Madrid.

Patients:

Coronavirus disease 2019 adult patients admitted to hospital from March 4, 2020, to March 25, 2020 (first infection wave), and during July 18, 2020, and August 20, 2020 (second infection wave).

Interventions:

Treatment with a hospital-approved drug cocktail during hospitalization.

Measurements and Main Results:

Demographic, clinical, and laboratory data were compared between the patients with moderate and critical/fatal illness across both infection waves. The median age of patients with critical/fatal coronavirus disease 2019 was 67.5 years (interquartile range, 56.75–78.25 yr; 64.5% male) in the first wave and 59.0 years (interquartile range, 48.25–80.50 yr; 70.8% male) in the second wave. Hypertension and dyslipidemia were major comorbidities in both waves. Body mass index over 25 and presence of bilateral pneumonia were common findings. Univariate logistic regression analyses revealed an association of a number of blood parameters with the subsequent illness progression and severity in both waves. However, some remarkable differences were detected between both waves that prevented an accurate extrapolation of prediction models from the first wave into the second wave. Interleukin-6 and d-dimer concentrations at the time of hospital admission were remarkably higher in patients who developed a critical/fatal condition only during the first wave (p < 0.001), although both parameters significantly increased with disease worsening in follow-up studies from both waves. Multivariate analyses from wave 1 rendered a predictive signature for critical/fatal illness upon hospital admission that comprised six blood biomarkers: neutrophil-to-lymphocyte ratio (≥ 5; odds ratio, 2.684 [95% CI, 1.143–6.308]), C-reactive protein (≥ 15.2 mg/dL; odds ratio, 2.412 [95% CI, 1.006–5.786]), lactate dehydrogenase (≥ 411.96 U/L; odds ratio, 2.875 [95% CI, 1.229–6.726]), interleukin-6 (≥ 78.8 pg/mL; odds ratio, 5.737 [95% CI, 2.432–13.535]), urea (≥ 40 mg/dL; odds ratio, 1.701 [95% CI, 0.737–3.928]), and d-dimer (≥ 713 ng/mL; odds ratio, 1.903 [95% CI, 0.832–4.356]). The predictive accuracy of the signature was 84% and the area under the receiver operating characteristic curve was 0.886. When the signature was validated with data from wave 2, the accuracy was 81% and the area under the receiver operating characteristic curve value was 0.874, albeit most biomarkers lost their independent significance. Follow-up studies reassured the importance of monitoring the biomarkers included in the signature, since dramatic increases in the levels of such biomarkers occurred in critical/fatal patients over disease progression.

Conclusions:

Most parameters analyzed behaved similarly in the two waves of coronavirus disease 2019. However, univariate logistic regression conducted in both waves revealed differences in some parameters associated with poor prognosis in wave 1 that were not found in wave 2, which may reflect a different disease stage of patients on arrival to hospital. The six-biomarker predictive signature reported here constitutes a helpful tool to classify patient’s prognosis on arrival to hospital.

Human Dental Pulp Stem Cells Modulate Cytokine Production in vitro by Peripheral Blood Mononuclear Cells From Coronavirus Disease 2019 Patients

A subset of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) developed a condition of hyper-inflammation, which can cause multi-organ damage and the more severe forms of coronavirus disease 2019 (COVID-19). Mesenchymal stem cells (MSCs) can promote tissue regeneration and modulate immune responses and, thus, have the rational requirements to be used to counteract SARS-CoV-2-induced pneumonia and hyper-inflammation. The aim of the present study was to gain insight into possible mechanisms of action of MSCs obtained from human dental pulp [dental pulp stem cells (DPSCs)] in COVID-19 patients. We investigated the concentrations of 18 cytokines in supernatants of peripheral blood mononuclear cells (PBMCs) obtained from COVID-19 patients cultured in vitro alone and in contact with DPSCs. The modulation of cytokines in PBMCs was confirmed by real-time PCR. IL-6 was the sole cytokine detected in supernatants of DPSCs. In resting conditions, co-culture increased IL-1β, IL-2, IL-5, IL-6, IL-10, IL-18, TNFα, and granulocyte macrophage colony-stimulating factor (GM-CSF) levels. When PBMCs were activated with anti-CD3/CD28 antibody-coated beads, co-culture increased IL-6 and GM-CSF, whereas it decreased IFNγ, TNFα, IL-2, IL-5, IL-9, IL-10, IL-12 (p70), IL-17A, IL-18, IL-21, IL-23, and IL-27 levels. Concentrations of IL-1β, IL-4, IL-13, and IL-22 were not affected. The comparison of cytokine concentrations in supernatants of PBMCs from COVID-19 patients vs. healthy subjects revealed lower concentrations of IL-10 and higher concentrations of IL-18 in supernatants of CD3/CD28-activated PBMCs from COVID-19 patients. Results are explorative but indicate that DPSCs can modulate the production of cytokines deregulated in COVID-19 patients, supporting their potential use in COVID-19.

Pathophysiology of acute respiratory syndrome coronavirus 2 infection: a systematic literature review to inform EULAR points to consider

BACKGROUND

The SARS-CoV-2 pandemic is a global health problem. Beside the specific pathogenic effect of SARS-CoV-2, incompletely understood deleterious and aberrant host immune responses play critical roles in severe disease. Our objective was to summarise the available information on the pathophysiology of COVID-19.

METHODS

Two reviewers independently identified eligible studies according to the following PICO framework: P (population): patients with SARS-CoV-2 infection; I (intervention): any intervention/no intervention; C (comparator): any comparator; O (outcome) any clinical or serological outcome including but not limited to immune cell phenotype and function and serum cytokine concentration.

RESULTS

Of the 55 496 records yielded, 84 articles were eligible for inclusion according to question-specific research criteria. Proinflammatory cytokine expression, including interleukin-6 (IL-6), was increased, especially in severe COVID-19, although not as high as other states with severe systemic inflammation. The myeloid and lymphoid compartments were differentially affected by SARS-CoV-2 infection depending on disease phenotype. Failure to maintain high interferon (IFN) levels was characteristic of severe forms of COVID-19 and could be related to loss-of-function mutations in the IFN pathway and/or the presence of anti-IFN antibodies. Antibody response to SARS-CoV-2 infection showed a high variability across individuals and disease spectrum. Multiparametric algorithms showed variable diagnostic performances in predicting survival, hospitalisation, disease progression or severity, and mortality.

CONCLUSIONS

SARS-CoV-2 infection affects both humoral and cellular immunity depending on both disease severity and individual parameters. This systematic literature review informed the EULAR 'points to consider' on COVID-19 pathophysiology and immunomodulatory therapies.

Possible involvement of Syndecan-1 in the state of COVID-19 related to endothelial injury

BACKGROUND

The coronavirus infection 2019 (COVID-19) is associated with microvascular endothelial injury. Here, we report that syndecan-1, a component of endothelial glycocalyx, may reflect the disease state of COVID-19 related to endothelial injury.

CASE PRESENTATION

A patient with COVID-19 was transferred to the intensive care unit of our hospital. Computed tomography of the chest showed bilateral ground glass opacities, which was diagnosed as acute respiratory syndrome. The PaO₂/F_IO₂ ratio gradually increased from 158 on hospitalization to 300 on Day 11, on which day the ventilator was withdrawn. However, serum syndecan-1 (SDC-1) level gradually decreased from 400.5 ng/ml at hospitalization to 165.1 ng/ml on Day 5. On Day 6, serum SDC-1 level increased to 612.9 ng/ml owing to a systemic thrombosis with an increase in D-dimer. Serum SDC-1 level then decreased until 206.0 ng/ml on Day 11 after a decrease in D-dimer. The patient was transferred to another hospital on Day 21 after hospitalization.

CONCLUSIONS

In this case report, changes in serum SDC-1 level closely reflected the change in disease condition in a patient with COVID-19. Serum SDC-1 may be a useful biomarker for monitoring the disease state of critically ill patients with COVID-19.

Inflammatory Response and Phenotyping in Severe Acute Respiratory Infection From the Middle East Respiratory Syndrome Coronavirus and Other Etiologies

OBJECTIVES

In this study, we evaluated the inflammatory response in patients with severe acute respiratory infection due to the Middle East respiratory syndrome and non-Middle East respiratory syndrome and assessed the presence of distinct inflammatory subphenotypes using latent class analysis.

DESIGN

Prospective cohort study.

SETTING

A tertiary care ICU in Riyadh, Saudi Arabia.

PATIENTS

Consecutive critically ill patients with laboratory-confirmed Middle East respiratory syndrome severe acute respiratory infection and non-Middle East respiratory syndrome severe acute respiratory infection.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

We measured cytokines on days 1, 3, 7, and 14 of ICU stay. We included 116 patients (40 with Middle East respiratory syndrome severe acute respiratory infection and 76 with non-Middle East respiratory syndrome severe acute respiratory infection). On ICU day 1, both patients with Middle East respiratory syndrome severe acute respiratory infection and non-Middle East respiratory syndrome severe acute respiratory infection had higher levels of interleukin-3, interleukin-4, interleukin-6, interleukin-8, interleukin-17A, eotaxin, and epidermal growth factor compared with healthy controls. There were no differences in cytokines over time between patients with Middle East respiratory syndrome severe acute respiratory infection and non-Middle East respiratory syndrome severe acute respiratory infection. Using day 1 cytokine levels, latent class analysis categorized patients into two subphenotypes: subphenotype 1 (n = 74 [64%]) and subphenotype 2 (n = 42 [36%]); the latter had significantly higher levels of interleukin-1β, interleukin-1ra, interleukin-2, interleukin-6, interleukin-7, interleukin-8, interleukin-10, interleukin-12p70, interleukin-15, interleukin-17A, inducible protein-10, monocyte chemoattractant protein-1, macrophage inflammatory protein-1α, macrophage inflammatory protein-1β, tumor necrosis factor-α, granulocyte-macrophage colony-stimulating factor, granulocyte-colony stimulating factor, interferon-α, and interferon-γ. Although baseline characteristics were not different between the two subphenotypes, patients in the subphenotype 2 had higher ICU mortality compared with the subphenotype 1 (18/42 [43%] vs 17/74 [23%]; p = 0.03).

CONCLUSIONS

One third of critically ill patients with Middle East respiratory syndrome severe acute respiratory infection and non-Middle East respiratory syndrome severe acute respiratory infection demonstrated a subphenotype characterized by increased proinflammatory cytokines, consistent with cytokine storm. Further research is needed to examine whether immunomodulators have differential effects based on inflammatory subphenotypes.

Can SARS-CoV-2 Virus Use Multiple Receptors to Enter Host Cells?

The occurrence of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for coronavirus disease 2019 (COVD-19), represents a catastrophic threat to global health. Protruding from the viral surface is a densely glycosylated spike (S) protein, which engages angiotensin-converting enzyme 2 (ACE2) to mediate host cell entry. However, studies have reported viral susceptibility in intra- and extrapulmonary immune and non-immune cells lacking ACE2, suggesting that the S protein may exploit additional receptors for infection. Studies have demonstrated interactions between S protein and innate immune system, including C-lectin type receptors (CLR), toll-like receptors (TLR) and neuropilin-1 (NRP1), and the non-immune receptor glucose regulated protein 78 (GRP78). Recognition of carbohydrate moieties clustered on the surface of the S protein may drive receptor-dependent internalization, accentuate severe immunopathological inflammation, and allow for systemic spread of infection, independent of ACE2. Furthermore, targeting TLRs, CLRs, and other receptors (Ezrin and dipeptidyl peptidase-4) that do not directly engage SARS-CoV-2 S protein, but may contribute to augmented anti-viral immunity and viral clearance, may represent therapeutic targets against COVID-19.

Case Report: Inflammation and Endothelial Injury Profiling of COVID-19 Pediatric Multisystem Inflammatory Syndrome (MIS-C)

Introduction: COVID-19 is associated with a novel multi-system inflammatory syndrome that shares some characteristics with Kawasaki's Disease. The syndrome manifestation is delayed relative to COVID-19 onset, with a spectrum of clinical severity. Clinical signs may include persistent fever, gastrointestinal symptoms, cardiac inflammation and/or shock. Case Presentation: We measured 59 inflammatory and endothelial injury plasma analytes in an adolescent girl that presented with malaise, fever, cough, strawberry tongue and jaundice. Her COVID-19 status was positive with detection of 2 SARS-CoV-2 viral genes using polymerase chain reaction. She was treated with intravenous immunoglobulin prior to blood draw, but our plasma measurements suggested a unique analyte expression pattern associated with inflammation, endothelial injury and microvascular glycocalyx degradation. Conclusions: COVID-19 is associated with a multi-system inflammatory syndrome and a unique inflammatory and endothelial injury signature. Summary: Analyte markers of inflammation and endothelial cell injury might serve as putative biomarkers and/or be investigated further as potential therapeutic targets.