COVID-19 risk stratification algorithms based on sTREM-1 and IL-6 in emergency department

Quantitative SARS-CoV-2 RT-PCR and Bronchoalveolar Cytokine Concentrations Redefine the COVID-19 Phenotypes in Critically Ill Patients

RATIONALE

Recent studies suggest that both hypo- and hyperinflammatory acute respiratory distress syndrome (ARDS) phenotypes characterize severe COVID-19-related pneumonia. The role of lung Severe Acute Respiratory Syndrome - Coronavirus 2 (SARS-CoV-2) viral load in contributing to these phenotypes remains unknown.

OBJECTIVES

To redefine COVID-19 ARDS phenotypes when considering quantitative SARS-CoV-2 RT-PCR in the bronchoalveolar lavage of intubated patients. To compare the relevance of deep respiratory samples versus plasma in linking the immune response and the quantitative viral loads.

METHODS

Eligible subjects were adults diagnosed with COVID-19 ARDS who required mechanical ventilation and underwent bronchoscopy. We recorded the immune response in the bronchoalveolar lavage and plasma and the quantitative SARS-CoV-2 RT-PCR in the bronchoalveolar lavage. Hierarchical clustering on principal components was applied separately on the 2 compartments' datasets. Baseline characteristics were compared between clusters.

MEASUREMENTS AND RESULTS

Twenty subjects were enrolled between August 2020 and March 2021. Subjects underwent bronchoscopy on average 3.6 days after intubation. All subjects were treated with dexamethasone prior to bronchoscopy, 11 of 20 (55.6%) received remdesivir and 1 of 20 (5%) received tocilizumab. Adding viral load information to the classic 2-cluster model of ARDS revealed a new cluster characterized by hypoinflammatory responses and high viral load in 23.1% of the cohort. Hyperinflammatory ARDS was noted in 15.4% of subjects. Bronchoalveolar lavage clusters were more stable compared to plasma.

CONCLUSIONS

We identified a unique group of critically ill subjects with COVID-19 ARDS who exhibit hypoinflammatory responses but high viral loads in the lower airways. These clusters may warrant different treatment approaches to improve clinical outcomes.

Innovative strategies for the surveillance, prevention, and management of pediatric infections applied to low-income settings

INTRODUCTION

Infectious diseases still cause a significant burden of morbidity and mortality among children in low- and middle-income countries (LMICs). There are ample opportunities for innovation in surveillance, prevention, and management, with the ultimate goal of improving survival.

AREAS COVERED

This review discusses the current status in the use and development of innovative strategies for pediatric infectious diseases in LMICs by focusing on surveillance, diagnosis, prevention, and management. Topics covered are: Minimally Invasive Tissue Sampling as a technique to accurately ascertain the cause of death; Genetic Surveillance to trace the pathogen genomic diversity and emergence of resistance; Artificial Intelligence as a multidisciplinary tool; Portable noninvasive imaging methods; and Prognostic Biomarkers to triage and risk stratify pediatric patients.

EXPERT OPINION

To overcome the specific hurdles in child health for LMICs, some innovative strategies appear at the forefront of research. If the development of these next-generation tools remains focused on accessibility, sustainability and capacity building, reshaping epidemiological surveillance, diagnosis, and treatment in LMICs, can become a reality and result in a significant public health impact. Their integration with existing healthcare infrastructures may revolutionize disease detection and surveillance, and improve child health and survival.

sTREM-1: A Biomarker of Mortality in Severe Malaria Impacted by Acute Kidney Injury

BACKGROUND

Malaria is an important cause of mortality in African children. Identification of biomarkers to identify children at risk of mortality has the potential to improve outcomes.

METHODS

We evaluated 11 biomarkers of host response in 592 children with severe malaria. The primary outcome was biomarker performance for predicting mortality. Biomarkers were evaluated using receiver operating characteristic (ROC) curve analysis comparing the area under the ROC curve (AUROC).

RESULTS

Mortality was 7.3% among children in the study with 72% of deaths occurring within 24 hours of admission. Among the candidate biomarkers, soluble triggering receptor expressed on myeloid cells 1 (sTREM-1) had the highest AUROC (0.78 [95% confidence interval, .70-.86]), outperforming several other biomarkers including C-reactive protein and procalcitonin. sTREM-1 was the top-performing biomarker across prespecified subgroups (malaria definition, site, sex, nutritional status, age). Using established cutoffs, we evaluated mortality across sTREM-1 risk zones. Among children with acute kidney injury, 39.9% of children with a critical-risk sTREM-1 result had an indication for dialysis. When evaluated relative to a disease severity score, sTREM-1 improved mortality prediction (difference in AUROC, P = .016).

CONCLUSIONS

sTREM-1 is a promising biomarker to guide rational allocation of clinical resources and should be integrated into clinical decision support algorithms, particularly when acute kidney injury is suspected.

Novel subtypes of severe COVID-19 respiratory failure based on biological heterogeneity: a secondary analysis of a randomized controlled trial

BACKGROUND

Despite evidence associating inflammatory biomarkers with worse outcomes in hospitalized adults with COVID-19, trials of immunomodulatory therapies have met with mixed results, likely due in part to biological heterogeneity of participants. Latent class analysis (LCA) of clinical and protein biomarker data has identified two subtypes of non-COVID acute respiratory distress syndrome (ARDS) with different clinical outcomes and treatment responses. We studied biological heterogeneity and clinical outcomes in a multi-institutional platform randomized controlled trial of adults with severe COVID-19 hypoxemic respiratory failure (I-SPY COVID).

METHODS

Clinical and plasma protein biomarker data were analyzed from 400 trial participants enrolled from September 2020 until October 2021 with severe COVID-19 requiring ≥ 6 L/min supplemental oxygen. Seventeen hypothesis-directed protein biomarkers were measured at enrollment using multiplex Luminex panels or single analyte enzyme linked immunoassay methods (ELISA). Biomarkers and clinical variables were used to test for latent subtypes and longitudinal biomarker changes by subtype were explored. A validated parsimonious model using interleukin-8, bicarbonate, and protein C was used for comparison with non-COVID hyper- and hypo-inflammatory ARDS subtypes.

RESULTS

Average participant age was 60 ± 14 years; 67% were male, and 28-day mortality was 25%. At trial enrollment, 85% of participants required high flow oxygen or non-invasive ventilation, and 97% were receiving dexamethasone. Several biomarkers of inflammation (IL-6, IL-8, IL-10, sTNFR-1, TREM-1), epithelial injury (sRAGE), and endothelial injury (Ang-1, thrombomodulin) were associated with 28- and 60-day mortality. Two latent subtypes were identified. Subtype 2 (27% of participants) was characterized by persistent derangements in biomarkers of inflammation, endothelial and epithelial injury, and disordered coagulation and had twice the mortality rate compared with Subtype 1. Only one person was classified as hyper-inflammatory using the previously validated non-COVID ARDS model.

CONCLUSIONS

We discovered evidence of two novel biological subtypes of severe COVID-19 with significantly different clinical outcomes. These subtypes differed from previously established hyper- and hypo-inflammatory non-COVID subtypes of ARDS. Biological heterogeneity may explain inconsistent findings from trials of hospitalized patients with COVID-19 and guide treatment approaches.

Triggering receptor expressed on myeloid cells-1 in sepsis, and current insights into clinical studies

Triggering receptor expressed on myeloid cells-1 (TREM-1) is a pattern recognition receptor and plays a critical role in the immune response. TREM-1 activation leads to the production and release of proinflammatory cytokines, chemokines, as well as its own expression and circulating levels of the cleaved soluble extracellular portion of TREM-1 (sTREM-1). Because patients with sepsis and septic shock show elevated sTREM-1 levels, TREM-1 has attracted attention as an important contributor to the inadequate immune response in this often-deadly condition. Since 2001, when the first blockade of TREM-1 in sepsis was performed, many potential TREM-1 inhibitors have been established in animal models. However, only one of them, nangibotide, has entered clinical trials, which have yielded promising data for future treatment of sepsis, septic shock, and other inflammatory disease such as COVID-19. This review discusses the TREM-1 pathway and important ligands, and highlights the development of novel inhibitors as well as their clinical potential for targeted treatment of various inflammatory conditions.

Interleukin-62/lymphocyte as a proposed predictive index for COVID-19 patients treated with monoclonal antibodies

In a convenience sample of 93 patients treated with monoclonal antibodies (moAbs) against SARS-CoV-2, the interleukin-62/lymphocyte count ratio (IL-62/LC) was able to predict clinical worsening both in early stages of COVID-19 and in oxygen-requiring patients. Moreover, we analysed 18 most at-risk patients with asymptomatic or mild disease treated with both moAbs and antiviral treatment and found that only 2 had clinical progression, while patients with a similar risk were reported to have an unfavourable outcome in most cases from recent data. In only one of our 18 patients, clinical progression was attributable to COVID-19, and in the other cases, clinical progression was observed despite IL-62/LC being above the risk cut-off. In conclusion, IL-62/LC may be a valuable method to identify patients requiring more aggressive treatments both in earlier and later stages of the disease; however, most at-risk patients can be protected from clinical worsening by combining moAbs and antivirals, even if levels of the IL-62/LC biomarker are lower than the risk cut-off.

Validation of sTREM-1 and IL-6 based algorithms for outcome prediction of COVID-19

BACKGROUND

A prospective observational cohort study of COVID-19 patients in a single Emergency Department (ED) showed that sTREM-1- and IL-6-based algorithms were highly predictive of adverse outcome (Van Singer et al. J Allergy Clin Immunol 2021). We aim to validate the performance of these algorithms at ED presentation.

METHODS

This multicentric prospective observational study of PCR-confirmed COVID-19 adult patients was conducted in the ED of three Swiss hospitals. Data of the three centers were retrospectively completed and merged. We determined the predictive accuracy of the sTREM-1-based algorithm for 30-day intubation/mortality. We also determined the performance of the IL-6-based algorithm using data from one center for 30-day oxygen requirement.

RESULTS

373 patients were included in the validation cohort, 139 (37%) in Lausanne, 93 (25%) in St.Gallen and 141 (38%) in EOC. Overall, 18% (93/373) patients died or were intubated by day 30. In Lausanne, 66% (92/139) patients required oxygen by day 30. The predictive accuracy of sTREM-1 and IL-6 were similar compared to the derivation cohort. The sTREM-1-based algorithm confirmed excellent sensitivity (90% versus 100% in the derivation cohort) and negative predictive value (94% versus 100%) for 30-day intubation/mortality. The IL-6-based algorithm performance was acceptable with a sensitivity of 85% versus 98% in the derivation cohort and a negative predictive value of 60% versus 92%.

CONCLUSION

The sTREM-1 algorithm demonstrated good reproducibility. A prospective randomized controlled trial, comparing outcomes with and without the algorithm, is necessary to assess its safety and impact on hospital and ICU admission rates. The IL-6 algorithm showed acceptable validity in a single center and need additional validation before widespread implementation.

The biology of TREM receptors

Triggering receptors expressed on myeloid cells (TREMs) encompass a family of cell-surface receptors chiefly expressed by granulocytes, monocytes and tissue macrophages. These receptors have been implicated in inflammation, neurodegenerative diseases, bone remodelling, metabolic syndrome, atherosclerosis and cancer. Here, I review the structure, ligands, signalling modes and functions of TREMs in humans and mice and discuss the challenges that remain in understanding TREM biology.

Soluble TREM-1 plasma concentration predicts poor outcome in COVID-19 patients

BACKGROUND

The immuno-receptor Triggering Expressed on Myeloid cells-1 (TREM-1) is activated during bacterial infectious diseases, where it amplifies the inflammatory response. Small studies suggest that TREM-1 could be involved in viral infections, including COVID-19. We here aim to decipher whether plasma concentration of the soluble form of TREM-1 (sTREM-1) could predict the outcome of hospitalized COVID-19 patients.

METHODS

We conducted a multicentre prospective observational study in 3 university hospitals in France. Consecutive hospitalized patients with confirmed infection with SARS-CoV-2 were enrolled. Plasma concentration of sTREM-1 was measured on admission and then at days 4, 6, 8, 14, 21, and 28 in patients admitted into an ICU (ICU cohort: ICUC) or 3 times a week for patients hospitalized in a medical ward (Conventional Cohort: ConvC). Clinical and biological data were prospectively recorded and patients were followed-up for 90 days. For medical ward patients, the outcome was deemed complicated in case of requirement of increased oxygen supply > 5 L/min, transfer to an ICU, or death. For Intensive Care Unit (ICU) patients, complicated outcome was defined by death in the ICU.

RESULTS

Plasma concentration of sTREM-1 at inclusion was higher in ICU patients (n = 269) than in medical ward patients (n = 562) (224 pg/mL (IQR 144-320) vs 147 pg/mL (76-249), p < 0.0001), and higher in patients with a complicated outcome in both cohorts: 178 (94-300) vs 135 pg/mL (70-220), p < 0.0001 in the ward patients, and 342 (288-532) vs 206 pg/mL (134-291), p < 0.0001 in the ICU patients. Elevated sTREM-1 baseline concentration was an independent predictor of complicated outcomes (Hazard Ratio (HR) = 1.5 (1.1-2.1), p = 0.02 in ward patients; HR = 3.8 (1.8-8.0), p = 0.0003 in ICU patients). An sTREM-1 plasma concentration of 224 pg/mL had a sensitivity of 42%, and a specificity of 76% in the ConvC for complicated outcome. In the ICUC, a 287 pg/mL cutoff had a sensitivity of 78%, and a specificity of 74% for death. The sTREM-1 concentrations increased over time in the ConvC patients with a complicated outcome (p = 0.017), but not in the ICUC patients.

CONCLUSIONS

In COVID-19 patients, plasma concentration of sTREM-1 is an independent predictor of the outcome, although its positive and negative likelihood ratio are not good enough to guide clinical decision as a standalone marker.

Defining the role of host biomarkers in the diagnosis and prognosis of the severity of childhood pneumonia: a prospective cohort study

Reliable tools to inform outpatient management of childhood pneumonia in resource-limited settings are needed. We investigated the value added by biomarkers of the host infection response to the performance of the Liverpool quick Sequential Organ Failure Assessment score (LqSOFA), for triage of children presenting with pneumonia to a primary care clinic in a refugee camp on the Thailand-Myanmar border. 900 consecutive presentations of children aged ≤ 24 months meeting WHO pneumonia criteria were included. The primary outcome was receipt of supplemental oxygen. We compared discrimination of a clinical risk score (LqSOFA) to markers of endothelial injury (Ang-1, Ang-2, sFlt-1), immune activation (CHI3L1, IP-10, IL-1ra, IL-6, IL-8, IL-10, sTNFR-1, sTREM-1), and inflammation (CRP, PCT), and quantified the net benefit of including biomarkers alongside LqSOFA. We evaluated the differential contribution of LqSOFA and host biomarkers to the diagnosis and prognosis of pneumonia severity. 49/900 (5.4%) presentations met the primary outcome. Discrimination of LqSOFA and Ang-2, the best performing biomarker, were comparable (AUC 0.82 [95% CI 0.76-0.88] and 0.81 [95% CI 0.74-0.87] respectively). Combining Ang-2 with LqSOFA improved discrimination (AUC 0.91; 95% CI 0.87-0.94; p < 0.001), and resulted in greater net benefit, with 10-30% fewer children who required oxygen supplementation incorrectly identified as safe for community-based management. Ang-2 had greater prognostic utility than LqSOFA to identify children requiring supplemental oxygen later in their illness course. Combining Ang-2 and LqSOFA could guide referrals of childhood pneumonia from resource-limited community settings. Further work on test development and integration into patient triage is required.

Point-of-care pancreatic stone protein measurement in critically ill COVID-19 patients

INTRODUCTION

Pancreatic stone protein (PSP) is a novel biomarker that is reported to be increased in pneumonia and acute conditions. The primary aim of this study was to prospectively study plasma levels of PSP in a COVID-19 intensive care unit (ICU) population to determine how well PSP performed as a marker of mortality in comparison to other plasma biomarkers, such as C reactive protein (CRP) and procalcitonin (PCT).

METHODS

We collected clinical data and blood samples from COVID-19 ICU patients at the time of admission (T0), 72 h later (T1), five days later (T2), and finally, seven days later. The PSP plasma level was measured with a point-of-care system; PCT and CRP levels were measured simultaneously with laboratory tests. The inclusion criteria were being a critical COVID-19 ICU patient requiring ventilatory mechanical assistance.

RESULTS

We enrolled 21 patients and evaluated 80 blood samples; we found an increase in PSP plasma levels according to mixed model analysis over time (p < 0.001), with higher levels found in the nonsurvivor population (p < 0.001). Plasma PSP levels achieved a statistically significant result in terms of the AUROC, with a value higher than 0.7 at T0, T1, T2, and T3. The overall AUROC of PSP was 0.8271 (CI (0.73-0.93), p < 0.001). These results were not observed for CRP and PCT.

CONCLUSION

These first results suggest the potential advantages of monitoring PSP plasma levels through point-of-care technology, which could be useful in the absence of a specific COVID-19 biomarker. Additional data are needed to confirm these results.

Comparison of C-reactive protein with distinct hyperinflammatory biomarkers in association with COVID-19 severity, mortality and SARS-CoV-2 variants

C-reactive protein (CRP) has been one of the most investigated inflammatory-biomarkers during the ongoing COVID-19 pandemics caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The severe outcome among patients with SARS-CoV-2 infection is closely related to the cytokine storm and the hyperinflammation responsible for the acute respiratory distress syndrome and multiple organ failure. It still remains a challenge to determine which of the hyperinflammatory biomarkers and cytokines are the best predictors for disease severity and mortality in COVID-19 patients. Therefore, we evaluated and compared the outcome prediction efficiencies between CRP, the recently reported inflammatory modulators (suPAR, sTREM-1, HGF), and the classical biomarkers (MCP-1, IL-1β, IL-6, NLR, PLR, ESR, ferritin, fibrinogen, and LDH) in patients confirmed with SARS-CoV-2 infection at hospital admission. Notably, patients with severe disease had higher serum levels of CRP, suPAR, sTREM-1, HGF and classical biomarkers compared to the mild and moderate cases. Our data also identified CRP, among all investigated analytes, to best discriminate between severe and non-severe forms of disease, while LDH, sTREM-1 and HGF proved to be excellent mortality predictors in COVID-19 patients. Importantly, suPAR emerged as a key molecule in characterizing the Delta variant infections.

Evaluation of the efficacy and safety of TREM-1 inhibition with nangibotide in patients with COVID-19 receiving respiratory support: the ESSENTIAL randomised, double-blind trial

Background

Activation of the TREM-1 pathway is associated with outcome in life threatening COVID-19. Data suggest that modulation of this pathway with nangibotide, a TREM-1 modulator may improve survival in TREM-1 activated patients (identified using the biomarker sTREM-1).

Methods

Phase 2 double-blind randomized controlled trial assessing efficacy, safety, and optimum treatment population of nangibotide (1.0 mg/kg/h) compared to placebo. Patients aged 18–75 years were eligible within 7 days of SARS-CoV-2 documentation and within 48 h of the onset of invasive or non-invasive respiratory support because of COVID-19-related ARDS. Patients were included from September 2020 to April 2022, with a pause in recruitment between January and August 2021. Primary outcome was the improvement in clinical status defined by a seven-point ordinal scale in the overall population with a planned sensitivity analysis in the subgroup of patients with a sTREM-1 level above the median value at baseline (high sTREM-1 group). Secondary endpoints included safety and all-cause 28-day and day 60 mortality. The study was registered in EudraCT (2020-001504-42) and ClinicalTrials.gov (NCT04429334).

Findings

The study was stopped after 220 patients had been recruited. Of them, 219 were included in the mITT analysis. Nangibotide therapy was associated with an improved clinical status at day 28. Fifty-two (52.0%) of patients had improved in the placebo group compared to 77 (64.7%) of the nangibotide treated population, an odds ratio (95% CI) for improvement of 1.79 (1.02–3.14), p = 0.043. In the high sTREM-1 population, 18 (32.7%) of placebo patients had improved by day 28 compared to 26 (48.1%) of treated patients, an odds ratio (95% CI) of 2.17 (0.96–4.90), p = 0.063 was observed. In the overall population, 28 (28.0%) of placebo treated patients were not alive at the day 28 visit compared to 19 (16.0%) of nangibotide treated patients, an absolute improvement (95% CI) in all-cause mortality at day 28, adjusted for baseline clinical status of 12.1% (1.18–23.05). In the high sTREM-1 population (n = 109), 23 (41.8%) of patients in the placebo group and 12 (22.2%) of patients in the nangibotide group were not alive at day 28, an adjusted absolute reduction in mortality of 19.9% (2.78–36.98). The rate of treatment emergent adverse events was similar in both placebo and nangibotide treated patients.

Interpretation

Whilst the study was stopped early due to low recruitment rate, the ESSENTIAL study demonstrated that TREM-1 modulation with nangibotide is safe in COVID-19, and results in a consistent pattern of improved clinical status and mortality compared to placebo. The relationship between sTREM-1 and both risk of death and treatment response merits further evaluation of nangibotide using precision medicine approaches in life threatening viral pneumonitis.

Funding

The study was sponsored by Inotrem SA.

A quantitative systems pharmacology model of the pathophysiology and treatment of COVID-19 predicts optimal timing of pharmacological interventions

A quantitative systems pharmacology (QSP) model of the pathogenesis and treatment of SARS-CoV-2 infection can streamline and accelerate the development of novel medicines to treat COVID-19. Simulation of clinical trials allows in silico exploration of the uncertainties of clinical trial design and can rapidly inform their protocols. We previously published a preliminary model of the immune response to SARS-CoV-2 infection. To further our understanding of COVID-19 and treatment, we significantly updated the model by matching a curated dataset spanning viral load and immune responses in plasma and lung. We identified a population of parameter sets to generate heterogeneity in pathophysiology and treatment and tested this model against published reports from interventional SARS-CoV-2 targeting mAb and antiviral trials. Upon generation and selection of a virtual population, we match both the placebo and treated responses in viral load in these trials. We extended the model to predict the rate of hospitalization or death within a population. Via comparison of the in silico predictions with clinical data, we hypothesize that the immune response to virus is log-linear over a wide range of viral load. To validate this approach, we show the model matches a published subgroup analysis, sorted by baseline viral load, of patients treated with neutralizing Abs. By simulating intervention at different time points post infection, the model predicts efficacy is not sensitive to interventions within five days of symptom onset, but efficacy is dramatically reduced if more than five days pass post symptom onset prior to treatment.

Prognostic accuracy of biomarkers of immune and endothelial activation in Mozambican children hospitalized with pneumonia

Pneumonia is a leading cause of child mortality. However, currently we lack simple, objective, and accurate risk-stratification tools for pediatric pneumonia. Here we test the hypothesis that measuring biomarkers of immune and endothelial activation in children with pneumonia may facilitate the identification of those at risk of death. We recruited children <10 years old fulfilling WHO criteria for pneumonia and admitted to the Manhiça District Hospital (Mozambique) from 2010 to 2014. We measured plasma levels of IL-6, IL-8, Angpt-2, sTREM-1, sFlt-1, sTNFR1, PCT, and CRP at admission, and assessed their prognostic accuracy for in-hospital, 28-day, and 90-day mortality. Healthy community controls, within same age strata and location, were also assessed. All biomarkers were significantly elevated in 472 pneumonia cases versus 80 controls (p<0.001). IL-8, sFlt-1, and sTREM-1 were associated with in-hospital mortality (p<0.001) and showed the best discrimination with AUROCs of 0.877 (95% CI: 0.782 to 0.972), 0.832 (95% CI: 0.729 to 0.935) and 0.822 (95% CI: 0.735 to 0.908), respectively. Their performance was superior to CRP, PCT, oxygen saturation, and clinical severity scores. IL-8, sFlt-1, and sTREM-1 remained good predictors of 28-day and 90-day mortality. These findings suggest that measuring IL-8, sFlt-1, or sTREM-1 at hospital presentation can guide risk-stratification of children with pneumonia, which could enable prioritized care to improve survival and resource allocation.

Circulating sTREM-1 as a predictive biomarker of pediatric multisystemic inflammatory syndrome (MIS-C)

The exacerbation of the inflammatory response caused by SARS-CoV-2 in adults promotes the production of soluble mediators that could act as diagnostic and prognostic biomarkers for COVID-19. Among the potential biomarkers, the soluble triggering receptor expressed on myeloid cell-1 (sTREM-1) has been described as a predictor of inflammation severity. The aim was to evaluate sTREM-1 and cytokine serum concentrations in pediatric patients during the acute and convalescent phases of COVID-19. This was a prospective study that included 53 children/adolescents with acute COVID-19 (Acute-CoV group); 54 who recovered from COVID-19 (Post-CoV group) and 54 controls (Control group). Preexisting chronic conditions were present in the three groups, which were defined as follows: immunological diseases, neurological disorders, and renal and hepatic failures. The three groups were matched by age, sex, and similar preexisting chronic conditions. No differences in sTREM-1 levels were detected among the groups or when the groups were separately analyzed by preexisting chronic conditions. However, sTREM-1 analysis in the seven multisystemic inflammatory syndrome children (MIS-C) within the Acute-Cov group showed that sTREM-1 concentrations were higher in MIS-C vs non-MIS-C acute patients. Then, the receiver operating curve analysis (ROC) performed with MIS-C acute patients revealed a significant AUC of 0.870, and the sTREM-1 cutoff value of > 5781 pg/mL yielded a sensitivity of 71.4 % and a specificity of 91.3 % for disease severity, and patients with sTREM-1 levels above this cutoff presented an elevated risk for MIS-C development in 22.85-fold (OR = 22.85 [95 % CI 1.64-317.5], p = 0.02). The cytokine analyses in the acute phase revealed that IL-6, IL-8, and IL-10 concentrations were elevated regardless of whether the patient developed MIS-C, and those levels decreased in the convalescent phase, even when compared with controls. Spearman correlation analysis generated positive indexes between sTREM-1 and IL-12 and TNF-α concentrations, only within the Acute-CoV group. Our findings revealed that sTREM-1 in pediatric patients has good predictive accuracy as an early screening tool for surveillance of MIS-C cases, even in patients with chronic underlying conditions.

Association of SARS-CoV-2 nucleocapsid viral antigen and the receptor for advanced glycation end products with development of severe disease in patients presenting to the emergency department with COVID-19

Introduction

There remains a need to better identify patients at highest risk for developing severe Coronavirus Disease 2019 (COVID-19) as additional waves of the pandemic continue to impact hospital systems. We sought to characterize the association of receptor for advanced glycation end products (RAGE), SARS-CoV-2 nucleocapsid viral antigen, and a panel of thromboinflammatory biomarkers with development of severe disease in patients presenting to the emergency department with symptomatic COVID-19.

Methods

Blood samples were collected on arrival from 77 patients with symptomatic COVID-19, and plasma levels of thromboinflammatory biomarkers were measured.

Results

Differences in biomarkers between those who did and did not develop severe disease or death 7 days after presentation were analyzed. After adjustment for multiple comparisons, RAGE, SARS-CoV-2 nucleocapsid viral antigen, interleukin (IL)-6, IL-10 and tumor necrosis factor receptor (TNFR)-1 were significantly elevated in the group who developed severe disease (all p<0.05). In a multivariable regression model, RAGE and SARS-CoV-2 nucleocapsid viral antigen remained significant risk factors for development of severe disease (both p<0.05), and each had sensitivity and specificity >80% on cut-point analysis.

Discussion

Elevated RAGE and SARS-CoV-2 nucleocapsid viral antigen on emergency department presentation are strongly associated with development of severe disease at 7 days. These findings are of clinical relevance for patient prognostication and triage as hospital systems continue to be overwhelmed. Further studies are warranted to determine the feasibility and utility of point-of care measurements of these biomarkers in the emergency department setting to improve patient prognostication and triage.

The CDR3 region as the major driver of TREM-1 interaction with its ligands, an in silico characterization

The triggering receptor expressed on myeloid cells-1 (TREM-1) is a pattern recognition receptor heavily investigated in infectious and non-infectious diseases. Because of its role in amplifying inflammation, TREM-1 has been explored as a diagnostic/prognostic biomarker. Further, as the receptor has been implicated in the pathophysiology of several diseases, therapies aiming at modulating its activity represent a promising strategy to constrain uncontrolled inflammatory or infectious diseases. Despite this, several aspects concerning its interaction with ligands and activation process, remain unclear. Although many molecules have been suggested as TREM-1 ligands, only five have been confirmed to interact with the receptor: actin, eCIRP, HMGB1, Hsp70 and PGLYRP1. However, the domains involved in the interaction between the receptor and these proteins are not clarified yet. Therefore, here we used in silico approaches to investigate the putative binding domains in the receptor, using hot spots analysis, molecular docking and molecular dynamics simulations between TREM-1 and its five known ligands. Our results indicated the complementarity-determining regions (CDRs) of the receptor as the main mediators of antigen recognition, especially the CDR3 loop. We believe that our study could be used as structural basis for the elucidation of TREM-1's recognition process, and may be useful for prospective in silico and biological investigations exploring the receptor in different contexts.

A biomarker assay to risk-stratify patients with symptoms of respiratory tract infection

BACKGROUND

Patients who present to an emergency department (ED) with respiratory symptoms are often conservatively triaged in favour of hospitalisation. We sought to determine if an inflammatory biomarker panel that identifies the host response better predicts hospitalisation in order to improve the precision of clinical decision making in the ED.

METHODS

From April 2020 to March 2021, plasma samples of 641 patients with symptoms of respiratory illness were collected from EDs in an international multicentre study: Canada (n=310), Italy (n=131) and Brazil (n=200). Patients were followed prospectively for 28 days. Subgroup analysis was conducted on confirmed coronavirus disease 2019 (COVID-19) patients (n=245). An inflammatory profile was determined using a rapid, 50-min, biomarker panel (RALI-Dx (Rapid Acute Lung Injury Diagnostic)), which measures interleukin (IL)-6, IL-8, IL-10, soluble tumour necrosis factor receptor 1 (sTNFR1) and soluble triggering receptor expressed on myeloid cells 1 (sTREM1).

RESULTS

RALI-Dx biomarkers were significantly elevated in patients who required hospitalisation across all three sites. A machine learning algorithm that was applied to predict hospitalisation using RALI-Dx biomarkers had a mean±sd area under the receiver operating characteristic curve of 76±6% (Canada), 84±4% (Italy) and 86±3% (Brazil). Model performance was 82±3% for COVID-19 patients and 87±7% for patients with a confirmed pneumonia diagnosis.

CONCLUSIONS

The rapid diagnostic biomarker panel accurately identified the need for inpatient care in patients presenting with respiratory symptoms, including COVID-19. The RALI-Dx test is broadly and easily applicable across many jurisdictions, and represents an important diagnostic adjunct to advance ED decision-making protocols.

Facilitating Safe Discharge Through Predicting Disease Progression in Moderate Coronavirus Disease 2019 (COVID-19): A Prospective Cohort Study to Develop and Validate a Clinical Prediction Model in Resource-Limited Settings

BACKGROUND

In locations where few people have received coronavirus disease 2019 (COVID-19) vaccines, health systems remain vulnerable to surges in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Tools to identify patients suitable for community-based management are urgently needed.

METHODS

We prospectively recruited adults presenting to 2 hospitals in India with moderate symptoms of laboratory-confirmed COVID-19 to develop and validate a clinical prediction model to rule out progression to supplemental oxygen requirement. The primary outcome was defined as any of the following: SpO2 < 94%; respiratory rate > 30 BPM; SpO2/FiO2 < 400; or death. We specified a priori that each model would contain three clinical parameters (age, sex, and SpO2) and 1 of 7 shortlisted biochemical biomarkers measurable using commercially available rapid tests (C-reactive protein [CRP], D-dimer, interleukin 6 [IL-6], neutrophil-to-lymphocyte ratio [NLR], procalcitonin [PCT], soluble triggering receptor expressed on myeloid cell-1 [sTREM-1], or soluble urokinase plasminogen activator receptor [suPAR]), to ensure the models would be suitable for resource-limited settings. We evaluated discrimination, calibration, and clinical utility of the models in a held-out temporal external validation cohort.

RESULTS

In total, 426 participants were recruited, of whom 89 (21.0%) met the primary outcome; 257 participants comprised the development cohort, and 166 comprised the validation cohort. The 3 models containing NLR, suPAR, or IL-6 demonstrated promising discrimination (c-statistics: 0.72-0.74) and calibration (calibration slopes: 1.01-1.05) in the validation cohort and provided greater utility than a model containing the clinical parameters alone.

CONCLUSIONS

We present 3 clinical prediction models that could help clinicians identify patients with moderate COVID-19 suitable for community-based management. The models are readily implementable and of particular relevance for locations with limited resources.

N-Terminal Peptide of PGLYRP1/Tag7 Is a Novel Ligand for TREM-1 Receptor

An investigation of innate immunity receptors sheds light on the mechanisms of inflammation and associated immune reactions. One of the key immune regulators is the TREM-1 receptor, which is involved in both inflammation and antitumor immune response. In this article, we have obtained a new ligand for the TREM-1 receptor. The peptide, named N3, is a part of the innate immune protein PGLYRP1/Tag7. It is responsible for activating the TREM-1 signaling pathway. Here, we have demonstrated that the N3 peptide acts like other TREM-1 receptor ligands: its binding results in a mild inflammation response and appearance of cytotoxic lymphocytes. We have shown that cytotoxic populations of lymphocytes in N3 peptide-treated PBMCs are similar to those treated with Tag7 or Hsp70. We also determined the part of the N3 peptide responsible for binding to TREM-1. The resulting peptide (N9) consists of nine amino acids and can be considered as a potential peptide that blocks TREM-1 signaling.

What we know and still ignore on COVID-19 immune pathogenesis and a proposal based on the experience of allergic disorders

The coronavirus disease 2019 (COVID-19) pandemic started in March 2020 and caused over 5 million confirmed deaths worldwide as far August 2021. We have been recently overwhelmed by a wide literature on how the immune system recognizes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and contributes to COVID-19 pathogenesis. Although originally considered a respiratory viral disease, COVID-19 is now recognized as a far more complex, multi-organ-, immuno-mediated-, and mostly heterogeneous disorder. Though efficient innate and adaptive immunity may control infection, when the patient fails to mount an adequate immune response at the start, or in advanced disease, a high innate-induced inflammation can lead to different clinical outcomes through heterogeneous compensatory mechanisms. The variability of viral load and persistence, the genetic alterations of virus-driven receptors/signaling pathways and the plasticity of innate and adaptive responses may all account for the extreme heterogeneity of pathogenesis and clinical patterns. As recently applied to some inflammatory disorders as asthma, rhinosinusitis with polyposis, and atopic dermatitis, herein we suggest defining different endo-types and the related phenotypes along COVID-19. Patients should be stratified for evolving symptoms and tightly monitored for surrogate biomarkers of innate and adaptive immunity. This would allow to preventively identify each endo-type (and its related phenotype) and to treat patients precisely with agents targeting pathogenic mechanisms.

Cardiovascular signatures of COVID-19 predict mortality and identify barrier stabilizing therapies

Background

Endothelial cell (EC) activation, endotheliitis, vascular permeability, and thrombosis have been observed in patients with severe coronavirus disease 2019 (COVID-19), indicating that the vasculature is affected during the acute stages of SARS-CoV-2 infection. It remains unknown whether circulating vascular markers are sufficient to predict clinical outcomes, are unique to COVID-19, and if vascular permeability can be therapeutically targeted.

Methods

Prospectively evaluating the prevalence of circulating inflammatory, cardiac, and EC activation markers as well as developing a microRNA atlas in 241 unvaccinated patients with suspected SARS-CoV-2 infection allowed for prognostic value assessment using a Random Forest model machine learning approach. Subsequent ex vivo experiments assessed EC permeability responses to patient plasma and were used to uncover modulated gene regulatory networks from which rational therapeutic design was inferred.

Findings

Multiple inflammatory and EC activation biomarkers were associated with mortality in COVID-19 patients and in severity-matched SARS-CoV-2-negative patients, while dysregulation of specific microRNAs at presentation was specific for poor COVID-19-related outcomes and revealed disease-relevant pathways. Integrating the datasets using a machine learning approach further enhanced clinical risk prediction for in-hospital mortality. Exposure of ECs to COVID-19 patient plasma resulted in severity-specific gene expression responses and EC barrier dysfunction, which was ameliorated using angiopoietin-1 mimetic or recombinant Slit2-N.

Interpretation

Integration of multi-omics data identified microRNA and vascular biomarkers prognostic of in-hospital mortality in COVID-19 patients and revealed that vascular stabilizing therapies should be explored as a treatment for endothelial dysfunction in COVID-19, and other severe diseases where endothelial dysfunction has a central role in pathogenesis.

Funding Information

This work was directly supported by grant funding from the Ted Rogers Center for Heart Research, Toronto, Ontario, Canada and the Peter Munk Cardiac Center, Toronto, Ontario, Canada.

Blood myxovirus resistance protein-1 measurement in the diagnostic work-up of suspected COVID-19 infection in the emergency department

INTRODUCTION

Myxovirus resistance protein 1 (MxA) is a biomarker that is elevated in patients with viral infections. The goal of this study was to evaluate the diagnostic value of MxA in diagnosing COVID-19 infections in the emergency department (ED) patients.

METHODS

This was a single-center prospective observational cohort study including patients with a suspected COVID-19 infection. The primary outcome of this study was a confirmed COVID-19 infection by RT-PCR test. MxA was assessed using an enzyme immunoassay on whole blood and receiver operating chart and area under the curve (AUC) analysis was conducted. Sensitivity, specificity, negative predictive value, and positive predictive value of MxA on diagnosing COVID-19 at the optimal cut-off of MxA was determined.

RESULTS

In 2021, 100 patients were included. Of these patients, 77 patients had COVID-19 infection and 23 were non-COVID-19. Median MxA level was significantly higher (p < .001) in COVID-19 patients compared to non-COVID-19 patients, respectively 1933 and 0.1 ng/ml. The AUC of MxA on a confirmed COVID-19 infection was 0.941 (95% CI: 0.867-1.000). The optimal cut-off point of MxA was 252 ng/ml. At this cut-off point, the sensitivity of MxA on a confirmed COVID-19 infection was 94% (95% CI: 85%-98%) and the specificity was 91% (95% CI: 72%-99%).

CONCLUSION

MxA accurately distinguishes COVID-19 infections from bacterial infections and noninfectious diagnoses in the ED in patients with a suspected COVID-19 infection. If the results can be validated, MxA could improve the diagnostic workup and patient flow in the ED.

Role of triggering receptor expressed on myeloid cells-1 (TREM-1) in COVID-19 and other viral pneumonias: a systematic review and meta-analysis of clinical studies

Background

Triggering receptor expressed on myeloid cells-1 (TREM-1) has emerged as an important inflammatory marker of immune response associated with severity and mortality outcomes in infection diseases, including viral pneumonias.

Aim

(1) To evaluate the expression of TREM-1 in patients with COVID-19 and other viral pneumonias compared to healthy individuals; and (2) to analyze the levels of these biomarkers according to disease severity.

Materials and methods

This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. Searches were performed in PubMed, Scopus, Embase, and Google Scholar. Studies were considered eligible if they were observational studies that provided data on the levels of TREM-1 in humans with viral pneumonia compared to healthy controls. The results of the meta-analysis were expressed as standardized mean difference (SMD) and an effect size of 0.8 was considered a large effect. A subgroup analysis was performed according to the disease severity.

Results

Seven studies were included in this systematic review. Four studies included patients with COVID-19 and three analyzed patients with different viruses. The meta-analysis was performed only with patients with COVID-19, which showed increased levels of soluble form of TREM-1 (sTREM-1) among patients with COVID-19 compared to healthy controls (SMD 1.53; 95% CI 0.53–2.52; p < 0.01). No differences were found between patients with mild-to-moderate COVID-19 and healthy controls, but higher levels of sTREM-1 were shown among patients with severe COVID-19 (SMD 1.83; 95% CI 0.77–2.88; p < 0.01). All three studies including patients with other viral pneumonias showed that TREM-1 levels were significantly elevated in infected patients compared with controls.

Conclusion

These findings may provide evidence on the pro-inflammatory role of TREM-1 in these infections, contributing to the inflammatory profile and disease progression.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10787-022-00972-6.

Ofeleein i mi Vlaptin-Volume II: Immunity Following Infection or mRNA Vaccination, Drug Therapies and Non-Pharmacological Management at Post-Two Years SARS-CoV-2 Pandemic

The persistence of the coronavirus disease 2019 (COVID-19) pandemic has triggered research into limiting transmission, morbidity and mortality, thus warranting a comprehensive approach to guide balanced healthcare policies with respect to people's physical and mental health. The mainstay priority during COVID-19 is to achieve widespread immunity, which could be established through natural contact or vaccination. Deep knowledge of the immune response combined with recent specific data indicates the potential inferiority of induced immunity against infection. Moreover, the prevention of transmission has been founded on general non-pharmacological measures of protection, albeit debate exists considering their efficacy and, among other issues, their socio-psychological burden. The second line of defense is engaged after infection and is supported by a plethora of studied agents, such as antibiotics, steroids and non-steroid anti-inflammatory drugs, antiviral medications and other biological agents that have been proposed, though variability in terms of benefits and adverse events has not allowed distinct solutions, albeit certain treatments might have a role in prevention and/or treatment of the disease. This narrative review summarizes the existing literature on the advantages and weaknesses of current COVID-19 management measures, thus underlining the necessity of acting based on the classical principle of "ofeleein i mi vlaptin", that is, to help or not to harm.

New Discovery of Myeloid-Derived Suppressor Cell's Tale on Viral Infection and COVID-19

Myeloid-derived suppressor cells (MDSCs) are generated under biological stress such as cancer, inflammatory tissue damage, and viral infection. In recent years, with occurrence of global infectious diseases, new discovery on MDSCs functions has been significantly expanded during viral infection and COVID-19. For a successful viral infection, pathogens viruses develop immune evasion strategies to avoid immune recognition. Numerous viruses induce the differentiation and expansion of MDSCs in order to suppress host immune responses including natural killer cells, antigen presenting cells, and T-cells. Moreover, MDSCs play an important role in regulation of immunopathogenesis by balancing viral infection and tissue damage. In this review article, we describe the overview of immunomodulation and genetic regulation of MDSCs during viral infection in the animal model and human studies. In addition, we include up-to-date review of role of MDSCs in SARS-CoV-2 infection and COVID-19. Finally, we discuss potential therapeutics targeting MDSCs.

Clinical sign and biomarker-based algorithm to identify bacterial pneumonia among outpatients with lower respiratory tract infection in Tanzania

BACKGROUND

Inappropriate antibiotics use in lower respiratory tract infections (LRTI) is a major contributor to resistance. We aimed to design an algorithm based on clinical signs and host biomarkers to identify bacterial community-acquired pneumonia (CAP) among patients with LRTI.

METHODS

Participants with LRTI were selected in a prospective cohort of febrile (≥ 38 °C) adults presenting to outpatient clinics in Dar es Salaam. Participants underwent chest X-ray, multiplex PCR for respiratory pathogens, and measurements of 13 biomarkers. We evaluated the predictive accuracy of clinical signs and biomarkers using logistic regression and classification and regression tree analysis.

RESULTS

Of 110 patients with LRTI, 17 had bacterial CAP. Procalcitonin (PCT), interleukin-6 (IL-6) and soluble triggering receptor expressed by myeloid cells-1 (sTREM-1) showed an excellent predictive accuracy to identify bacterial CAP (AUROC 0.88, 95%CI 0.78-0.98; 0.84, 0.72-0.99; 0.83, 0.74-0.92, respectively). Combining respiratory rate with PCT or IL-6 significantly improved the model compared to respiratory rate alone (p = 0.006, p = 0.033, respectively). An algorithm with respiratory rate (≥ 32/min) and PCT (≥ 0.25 μg/L) had 94% sensitivity and 82% specificity.

CONCLUSIONS

PCT, IL-6 and sTREM-1 had an excellent predictive accuracy in differentiating bacterial CAP from other LRTIs. An algorithm combining respiratory rate and PCT displayed even better performance in this sub-Sahara African setting.

Interleukin-6 in SARS-CoV-2 induced disease: Interactions and therapeutic applications

Interleukin-6 (IL-6) is a multi-tasking cytokine that represents high activity in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and cancer. High concentration of this pleiotropic cytokine accounts for hyperinflammation and cytokine storm, and is related to multi-organ failure in patients with SARS-CoV-2 induced disease. IL-6 promotes lymphopenia and increases C-reactive protein (CRP) in such cases. However, blockade of IL-6 is not a full-proof of complete response. Hypoxia, hypoxemia, aberrant angiogenesis and chronic inflammation are inter-related events occurring as a response to the SARS-CoV-2 stimulatory effect on high IL-6 activity. Taking both pro- and anti-inflammatory activities will make complex targeting IL-6 in patient with SARS-CoV-2 induced disease. The aim of this review was to discuss about interactions occurring within the body of patients with SARS-CoV-2 induced disease who are representing high IL-6 levels, and to determine whether IL-6 inhibition therapy is effective for such patients or not. We also address the interactions and targeted therapies in cancer patients who also have SARS-CoV-2 induced disease.

Advances in clinical outcomes: what we have learned during the COVID-19 pandemic

Our understanding of risk factors and interventions influencing outcomes from coronavirus disease 2019 (COVID-19) has continued to evolve, revealing advances emerging from hypotheses formed at the start of the pandemic. Epidemiologic studies have shown that asthma control, rather than a diagnosis of asthma, is a determinant of COVID-19 severity. Clinical outcomes in patients with primary immunodeficiencies, even in those with impaired cellular immunity, are variable. IL-6 has emerged as a reliable biomarker of COVID-19 severity, and large clinical trials have shown the potential for improving outcomes through inhibition of IL-6 signaling in some patients. Studies of genetic risk factors for severe COVID-19 have also revealed the importance of interferon homeostasis in the defense against severe acute respiratory syndrome coronavirus 2. Because COVID-19 vaccines constitute the primary tool for ending this pandemic, strategies have been developed to address potential allergic and immune-mediated reactions. Here, we discuss advances in our understanding of COVID-19 risk factors and outcomes within the context of allergic and immunologic mechanisms.

Plasma Soluble CD14 Subtype Levels Are Associated With Clinical Outcomes in Critically Ill Subjects With Coronavirus Disease 2019

IMPORTANCE

In bacterial sepsis, CD14 and its N-terminal fragment (soluble CD14 subtype, "Presepsin") have been characterized as markers of innate immune responses and emerging evidence has linked both to coronavirus disease 2019 pathophysiology.

OBJECTIVES

Our aim was to determine the relationship between the soluble form of CD14 and soluble CD14 subtype plasma levels, coronavirus disease 2019 status, and coronavirus disease 2019-related outcomes.

DESIGN

A prospective cohort study.

SETTING

ICUs in three tertiary hospitals in Seattle, WA.

PARTICIPANTS

Two-hundred four critically ill patients under investigation for coronavirus disease 2019.

MAIN OUTCOMES AND MEASURES

We measured plasma soluble CD14 and soluble CD14 subtype levels in samples collected upon admission. We tested for associations between biomarker levels and coronavirus disease 2019 status. We stratified by coronavirus disease 2019 status and tested for associations between biomarker levels and outcomes.

RESULTS

Among 204 patients, 102 patients had coronavirus disease 2019 and 102 patients did not. In both groups, the most common ICU admission diagnosis was respiratory failure or pneumonia and proportions receiving respiratory support at admission were similar. In regression analyses adjusting for age, sex, race/ethnicity, steroid therapy, comorbidities, and severity of illness, soluble CD14 subtype was 54% lower in coronavirus disease 2019 than noncoronavirus disease 2019 patients (fold difference, 0.46; 95% CI, 0.28-0.77; p = 0.003). In contrast to soluble CD14 subtype, soluble CD14 levels did not differ between coronavirus disease 2019 and noncoronavirus disease 2019 patients. In both coronavirus disease 2019 and noncoronavirus disease 2019, in analyses adjusting for age, sex, race/ethnicity, steroid therapy, and comorbidities, higher soluble CD14 subtype levels were associated with death (coronavirus disease 2019: adjusted relative risk, 1.21; 95% CI, 1.06-1.39; p = 0.006 and noncoronavirus disease 2019: adjusted relative risk, 1.19; 95% CI, 1.03-1.38; p = 0.017), shock, and fewer ventilator-free days. In coronavirus disease 2019 only, an increase in soluble CD14 subtype was associated with severe acute kidney injury (adjusted relative risk, 1.23; 95% CI, 1.05-1.44; p = 0.013).

CONCLUSIONS

Higher plasma soluble CD14 subtype is associated with worse clinical outcomes in critically ill patients irrespective of coronavirus disease 2019 status though soluble CD14 subtype levels were lower in coronavirus disease 2019 patients than noncoronavirus disease 2019 patients. Soluble CD14 subtype levels may have prognostic utility in coronavirus disease 2019.

sTREM-1 Predicts Disease Severity and Mortality in COVID-19 Patients: Involvement of Peripheral Blood Leukocytes and MMP-8 Activity

Uncontrolled inflammatory responses play a critical role in coronavirus disease (COVID-19). In this context, because the triggering-receptor expressed on myeloid cells-1 (TREM-1) is considered an intrinsic amplifier of inflammatory signals, this study investigated the role of soluble TREM-1 (sTREM-1) as a biomarker of the severity and mortality of COVID-19. Based on their clinical scores, we enrolled COVID-19 positive patients (n = 237) classified into mild, moderate, severe, and critical groups. Clinical data and patient characteristics were obtained from medical records, and their plasma inflammatory mediator profiles were evaluated with immunoassays. Plasma levels of sTREM-1 were significantly higher among patients with severe disease compared to all other groups. Additionally, levels of sTREM-1 showed a significant positive correlation with other inflammatory parameters, such as IL-6, IL-10, IL-8, and neutrophil counts, and a significant negative correlation was observed with lymphocyte counts. Most interestingly, sTREM-1 was found to be a strong predictive biomarker of the severity of COVID-19 and was related to the worst outcome and death. Systemic levels of sTREM-1 were significantly correlated with the expression of matrix metalloproteinases (MMP)-8, which can release TREM-1 from the surface of peripheral blood cells. Our findings indicated that quantification of sTREM-1 could be used as a predictive tool for disease outcome, thus improving the timing of clinical and pharmacological interventions in patients with COVID-19.

Protein PGLYRP1/Tag7 Peptides Decrease the Proinflammatory Response in Human Blood Cells and Mouse Model of Diffuse Alveolar Damage of Lung through Blockage of the TREM-1 and TNFR1 Receptors

Infection caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) in many cases is accompanied by the release of a large amount of proinflammatory cytokines in an event known as "cytokine storm", which is associated with severe coronavirus disease 2019 (COVID-19) cases and high mortality. The excessive production of proinflammatory cytokines is linked, inter alia, to the enhanced activity of receptors capable of recognizing the conservative regions of pathogens and cell debris, namely TLRs, TREM-1 and TNFR1. Here we report that peptides derived from innate immunity protein Tag7 inhibit activation of TREM-1 and TNFR1 receptors during acute inflammation. Peptides from the N-terminal fragment of Tag7 bind only to TREM-1, while peptides from the C-terminal fragment interact solely with TNFR1. Selected peptides are capable of inhibiting the production of proinflammatory cytokines both in peripheral blood mononuclear cells (PBMCs) from healthy donors and in vivo in the mouse model of acute lung injury (ALI) by diffuse alveolar damage (DAD). Treatment with peptides significantly decreases the infiltration of mononuclear cells to lungs in animals with DAD. Our findings suggest that Tag7-derived peptides might be beneficial in terms of the therapy or prevention of acute lung injury, e.g., for treating COVID-19 patients with severe pulmonary lesions.

Utility of P-SEP, sTREM-1 and suPAR as Novel Sepsis Biomarkers in SARS-CoV-2 Infection

The coronavirus disease 2019 is a highly contagious viral infection caused by SARS-CoV-2 virus, member of coronaviridae family. It causes life threatening complications due to complexity and rapid onset course of the disease. Early identification of high-risk patients who require close monitoring and aggressive treatment remains challengeable till date. Novel biomarkers which help to identify high risk patients at the early stage is high priority. Objective of this review to find utility of P-SEP, sTREM-1 and suPAR for diagnosis, risk stratification and prognosis of SARS-CoV-2 infected cases. Soluble receptors like, P-SEP, sTREM-1 and suPAR have been involved in immune regulation in SARS-CoV-2 infection and elevate more in severe cases. A comprehensive research of databases like PubMed, EMBASE, CNKI and Web of Science was performed for relevant studies. A total of nine out of fifteen research literature in initial screening were included for this review. Interestingly all studies have reported high levels of P-SEP, sTREM-1 and suPAR in SARS-CoV-2 infected cases and the biomarkers positively correlated with severity of infection. This implies that P-SEP, sTREM-1 and suPAR can be implemented as surrogate marker in blood profile for early diagnosis, risk stratification and prognosis in SARS-CoV-2 for better management in Indian population at the current situation.

A simple prognostic score based on troponin and presepsin for COVID-19 patients admitted to the emergency department: a single-center pilot study

BACKGROUND

The need to determine prognostic factors that can predict a particularly severe or, conversely, the benign course of COVID-19 is particularly perceived in the Emergency Department (ED), considering the scarcity of resources for a conspicuous mass of patients. The aim of our study was to identify some predictors for 30-day mortality among some clinical, laboratory, and ultrasound variables in a COVID-19 patients population.

METHODS

Prospective single-center pilot study conducted in an ED of a University Hospital. A consecutive sample of confirmed COVID-19 patients with acute respiratory failure was enrolled from March 8th to April 15th, 2020.

RESULTS

143 patients were enrolled. Deceased patients (n = 65) were older (81 vs. 61 years, p <0.001), and they had more frequently a history of heart disease, neurological disease, or chronic obstructive pulmonary disease (p-values = 0.026, 0.025, and 0.034, respectively) than survived patients. Troponin I and presepsin had a significant correlation with a worse outcome. Troponin achieved a sensitivity of 77% and a specificity of 82% for a cut-off value of 27.6 ng/L. The presepsin achieved a sensitivity of 54% and a specificity of 92% for a cut-off value of 871 pg/mL.

CONCLUSION

In a population of COVID-19 patients with acute respiratory failure in an ED, presepsin and troponin I are accurate predictors of 30-day mortality. Presepsin is highly specific and could permit the early identification of patients who could benefit from more intensive care as soon as they enter the ED. Further validation studies are needed to confirm this result.

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review

The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions.

Increased sTREM-1 plasma concentrations are associated with poor clinical outcomes in patients with COVID-19

Patients with sepsis display increased concentrations of sTREM-1 (soluble Triggering Receptor Expressed on Myeloid cells 1), and a phase II clinical trial focusing on TREM-1 modulation is ongoing. We investigated whether sTREM-1 circulating concentrations are associated with the outcome of patients with coronavirus disease 2019 (COVID-19) to assess the role of this pathway in COVID-19. This observational study was performed in two independent cohorts of patients with COVID-19. Plasma concentrations of sTREM-1 were assessed after ICU admission (pilot cohort) or after COVID-19 diagnosis (validation cohort). Routine laboratory and clinical parameters were collected from electronic patient files. Results showed sTREM-1 plasma concentrations were significantly elevated in patients with COVID-19 (161 [129-196] pg/ml) compared to healthy controls (104 [75-124] pg/ml; P<0.001). Patients with severe COVID-19 needing ICU admission displayed even higher sTREM-1 concentrations compared to less severely ill COVID-19 patients receiving clinical ward-based care (235 [176-319] pg/ml and 195 [139-283] pg/ml, respectively, P = 0.017). In addition, higher sTREM-1 plasma concentrations were observed in patients who did not survive the infection (326 [207-445] pg/ml) compared to survivors (199 [142-278] pg/ml, P<0.001). Survival analyses indicated that patients with higher sTREM-1 concentrations are at higher risk for death (hazard ratio = 3.3, 95%CI: 1.4-7.8). In conclusion, plasma sTREM-1 concentrations are elevated in patients with COVID-19, relate to disease severity, and discriminate between survivors and non-survivors. This suggests that the TREM-1 pathway is involved in the inflammatory reaction and the disease course of COVID-19, and therefore may be considered as a therapeutic target in severely ill patients with COVID-19.

Endothelial, Immunothrombotic, and Inflammatory Biomarkers in the Risk of Mortality in Critically Ill COVID-19 Patients: The Role of Dexamethasone

Endothelial dysfunction, coagulation and inflammation biomarkers are increasingly emerging as prognostic markers of poor outcomes and mortality in severe and critical COVID-19. However, the effect of dexamethasone has not been investigated on these biomarkers. Hence, we studied potential prognostic biomarkers of mortality in critically ill COVID-19 patients who had either received or not dexamethasone. Biomarker serum levels were measured on intensive care unit (ICU) admission (within 24 h) in 37 dexamethasone-free and 29 COVID-19 patients who had received the first dose (6 mg) of dexamethasone. Receiver operating characteristic (ROC) curves were generated to assess their value in ICU mortality prediction, while Kaplan-Meier analysis was used to explore associations between biomarkers and survival. In the dexamethasone-free COVID-19 ICU patients, non-survivors had considerably higher levels of various endothelial, immunothrombotic and inflammatory biomarkers. In the cohort who had received one dexamethasone dose, non-survivors had higher ICU admission levels of only soluble (s) vascular cell adhesion molecule-1 (VCAM-1), soluble urokinase-type plasminogen activator receptor (suPAR) and presepsin. As determined from the generated ROC curves, sVCAM-1, suPAR and presepsin could still be reliable prognostic ICU mortality biomarkers, following dexamethasone administration (0.7 < AUC < 0.9). Moreover, the Kaplan-Meier survival analysis showed that patients with higher than the median values for sVCAM-1 or suPAR exhibited a greater mortality risk than patients with lower values (Log-Rank test, p < 0.01). In our single-center study, sVCAM-1, suPAR and presepsin appear to be valuable prognostic biomarkers in assessing ICU mortality risk in COVID-19 patients, even following dexamethasone administration.

Myeloid-Derived Suppressor Cells as a Potential Biomarker and Therapeutic Target in COVID-19

Clinical presentations of COVID-19 are highly variable, yet the precise mechanisms that govern the pathophysiology of different disease courses remain poorly defined. Across the spectrum of disease severity, COVID-19 impairs both innate and adaptive host immune responses by activating innate immune cell recruitment, while resulting in low lymphocyte counts. Recently, several reports have shown that patients with severe COVID-19 exhibit a dysregulated myeloid cell compartment, with increased myeloid-derived suppressor cells (MDSCs) correlating with disease severity. MDSCs, in turn, promote virus survival by suppressing T-cell responses and driving a highly pro-inflammatory state through the secretion of various mediators of immune activation. Here, we summarize the evidence on MDSCs and myeloid cell dysregulation in COVID-19 infection and discuss the potential of MDSCs as biomarkers and therapeutic targets in COVID-19 pneumonia and associated disease.

Can biomarkers of extracellular matrix remodelling and wound healing be used to identify high risk patients infected with SARS-CoV-2?: lessons learned from pulmonary fibrosis

Pulmonary fibrosis has been identified as a main factor leading to pulmonary dysfunction and poor quality of life in post-recovery Severe Acute Respiratory Syndrome (SARS) survivor’s consequent to SARS-Cov-2 infection. Thus there is an urgent medical need for identification of readily available biomarkers that in patients with SARS-Cov-2 infection are able to; (1) identify patients in most need of medical care prior to admittance to an intensive care unit (ICU), and; (2) identify patients post-infection at risk of developing persistent fibrosis of lungs with subsequent impaired quality of life and increased morbidity and mortality. An intense amount of research have focused on wound healing and Extracellular Matrix (ECM) remodelling of the lungs related to lung function decline in pulmonary fibrosis (PF). A range of non-invasive serological biomarkers, reflecting tissue remodelling, and fibrosis have been shown to predict risk of acute exacerbations, lung function decline and mortality in PF and other interstitial lung diseases (Sand et al. in Respir Res 19:82, 2018). We suggest that lessons learned from such PF studies of the pathological processes leading to lung function decline could be used to better identify patients infected with SARS-Co-V2 at most risk of acute deterioration or persistent fibrotic damage of the lung and could consequently be used to guide treatment decisions.