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1.
Cell Reports Medicine ; : 100560, 2022.
Article in English | ScienceDirect | ID: covidwho-1706398

ABSTRACT

Summary Most patients infected with SARS-CoV-2 (COVID-19) experience mild, non-specific symptoms, but several develop severe symptoms associated with an excessive inflammatory response. Elevated plasma concentrations of soluble urokinase plasminogen activator receptor (suPAR) provide early warning of progression to severe respiratory failure (SRF) or death, but access to suPAR testing may be limited. The Severe COvid Prediction Estimate (SCOPE) score, derived from C-reactive protein, D-dimers, interleukin-6, and ferritin circulating concentrations among patients not receiving non-invasive or invasive mechanical ventilation during the SAVE-MORE study, offers comparable predictive accuracy for progression to SRF or death within 14 days as suPAR ≥6 ng/ml (area under receiver operator characteristic curve, 0.81 for both). SCOPE score is validated in two similar independent cohorts. SCOPE score 6 or more is an alternative to suPAR for predicting progression to SRF or death within 14 days of hospital admission for pneumonia, and it can be used to guide treatment decisions.

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-320779

ABSTRACT

Purpose: Recent publications on the probable role of heparin-binding protein (HBP) as a biomarker in sepsis prompted us to investigate its diagnostic and prognostic performance in severe COVID-19 Methods: HBP and IL-6 were measured by immunoassays at admission and on day 7 in 178 patients with pneumonia by SARS-CoV-2. Patients were classified into non-sepsis and sepsis as per the Sepsis-3 definitions and were followed-up for the development of severe respiratory failure (SRF) and for outcome. Results were confirmed by multivariate analyses. Results: HBP was significantly higher in patients classified as having sepsis and was negatively associated with the oxygenation ratio and positively associated with creatinine and lactate. Logistic regression analysis evidenced admission HBP more than 18 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for the development of SRP. Their integration prognosticated SRF with respective sensitivity, specificity, positive predictive value and negative predictive 59.1%, 96.3%, 83.9% and 87.8%. Cox regression analysis evidenced admission HBP more than 35 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for 28-day mortality. Their integration prognosticated 28-day mortality with respective sensitivity, specificity, positive predictive value and negative predictive 69.2%, 92.7%, 42.9% and 97.5%. HBP remained unchanged over-time course. Conclusion: A prediction score of the disposition of patients with COVID-19 is proposed taking into consideration admission levels of IL-6 and HBP. Using different cut-offs the score may predict the likelihood for SRF and for 28-day outcome.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-294791

ABSTRACT

Most patients infected with SARS-CoV-2 (COVID-19) experience mild, non-specific symptoms, but several develop severe symptoms associated with an excessive inflammatory response. Elevated plasma concentrations of soluble urokinase plasminogen activator receptor (suPAR) provide early warning of progression to severe respiratory failure (SRF) or death, but access to suPAR testing may be limited. The Severe COvid Prediction Estimate (SCOPE) score, derived from C-reactive protein, D-dimer, interleukin-6, and ferritin circulating concentrations at hospitalization during the SAVE-MORE study, offers comparable predictive accuracy for progression to SRF or death within 14 days as suPAR ≥6 ng/ml (area under receiver operator characteristic curve, 0.81 for both). SCOPE score was validated against an independent dataset from the SAVE study. The SCOPE score is an alternative to suPAR for predicting progression to SRF or death within 14 days of hospital admission for pneumonia, and it can be used to guide treatment decisions.<br><br>Funding: The study was funded in part by the Hellenic Institute for the Study of Sepsis and by Swedish Orphan Biovitrum. The Hellenic Institute for the Study of Sepsis is the Sponsor of the SAVE and SAVE-MORE studies.<br><br>Declaration of Interests:E. J. Giamarellos-Bourboulis has received honoraria from Abbott CH, bioMérieux, Brahms GmbH, GSK, InflaRx GmbH, Sobi and XBiotech Inc;independent educational grants from Abbott CH, AxisShield, bioMérieux Inc, InflaRx GmbH, Johnson & Johnson, MSD, Sobi and XBiotech Inc.;and funding from the Horizon2020 Marie-Curie Project European Sepsis Academy (granted to the National and Kapodistrian University of Athens), and the Horizon 2020 European Grants ImmunoSep and RISKinCOVID (granted to the Hellenic Institute for the Study of Sepsis). G. Poulakou has received independent educational grants from Pfizer, MSD, Angelini, and Biorad. H. Milionis reports receiving honoraria, consulting fees and non-financial support from healthcare companies, including Amgen, Angelini, Bayer, Mylan, MSD, Pfizer, and Servier. L. Dagna had received consultation honoraria from SOBI. M. Bassetti has received funds for research grants and/or advisor/consultant and/or speaker/chairman from Angelini, Astellas, Bayer, Biomerieux, Cidara, Cipla, Gilead, Menarini, MSD, Pfizer, Roche, Shionogi and Nabriva. P. Panagopoulos has received honoraria from GILEAD Sciences, Janssen, and MSD. G. N. Dalekos is an advisor or lecturer for Ipsen, Pfizer, Genkyotex, Novartis, Sobi, received research grants from Abbvie, Gilead and has served as PI in studies for Abbvie, Novartis, Gilead, Novo Nordisk, Genkyotex, Regulus Therapeutics Inc, Tiziana Life Sciences, Bayer, Astellas, Pfizer, Amyndas Pharmaceuticals, CymaBay Therapeutics Inc., Sobi and Intercept Pharmaceuticals. M. G. Netea is supported by an ERC Advanced Grant (#833247) and a Spinoza grant of the Netherlands Organization for Scientific Research. Hes is a scientific founder of TTxD and he has received independent educational grants from TTxD, GSK, Ono Pharma and ViiV HealthCare. The other authors do not have any competing interest to declare.<br><br>Ethics Approval Statement: The SAVE protocol was approved by the National Ethics Committee of Greece (approval 38/20) and National Organization for Medicines approval (ISO 28/20). The SAVE-MORE protocol was approved by the National Ethics Committee of Greece (approval 161/20) and by the Ethics Committee of the National Institute for Infectious Diseases Lazzaro Spallanzani, IRCCS, in Rome (1 February 2021).<br><br>Trial Registration: The SAVE study was prospectively registered prior to enrolling the first patient (EudraCT number 2020-001466-11;ClinicalTrials.gov identifier NCT04357366). The SAVE-MORE study was prospectively registered (EudraCT no. 2020-005828-11;ClinicalTrials.gov identifier NCT04680949). Written informed consent was provided by all patients prior to enrollment.

4.
J Innate Immun ; : 1-11, 2021 Dec 01.
Article in English | MEDLINE | ID: covidwho-1546612

ABSTRACT

BACKGROUND: Macrophage activation-like syndrome (MALS) and complex immune dysregulation (CID) often underlie acute respiratory distress (ARDS) in COVID-19. We aimed to investigate the effect of personalized immunotherapy on clinical improvement of critical COVID-19. METHODS: In this open-label prospective trial, 102 patients with ARDS by SARS-CoV-2 were screened for MALS (ferritin >4,420 ng/mL) and CID (ferritin ≤4,420 ng/mL and low human leukocyte antigen (HLA)-DR expression on CD14-monocytes). Patients with MALS or CID with increased aminotransferases received intravenous anakinra; those with CID and normal aminotransferases received tocilizumab. The primary outcome was ≥25% decrease in the Sequential Organ Failure Assessment (SOFA) score and/or 50% increase in the respiratory ratio by day 8; 28-day mortality, change of SOFA score by day 28, serum biomarkers, and cytokine production by mononuclear cells were secondary endpoints. RESULTS: The primary study endpoint was met in 58.3% of anakinra-treated patients and in 33.3% of tocilizumab-treated patients (p: 0.01). Most patients in both groups received dexamethasone as standard of care. No differences were found in secondary outcomes, mortality, and SOFA score changes. Ferritin decreased among anakinra-treated patients; interleukin-6, soluble urokinase plasminogen activator receptor, and HLA-DR expression increased among tocilizumab-treated patients. Survivors by day 28 who received anakinra were distributed to lower severity levels of the WHO clinical progression scale. Greater incidence of secondary infections was found with tocilizumab treatment. CONCLUSION: Immune assessment resulted in favorable anakinra responses among critically ill patients with COVID-19 and features of MALS.

5.
Nature ; 594(7862): 265-270, 2021 06.
Article in English | MEDLINE | ID: covidwho-1246377

ABSTRACT

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.


Subject(s)
Blockchain , Clinical Decision-Making/methods , Confidentiality , Datasets as Topic , Machine Learning , Precision Medicine/methods , COVID-19/diagnosis , COVID-19/epidemiology , Disease Outbreaks , Female , Humans , Leukemia/diagnosis , Leukemia/pathology , Leukocytes/pathology , Lung Diseases/diagnosis , Machine Learning/trends , Male , Software , Tuberculosis/diagnosis
6.
Elife ; 102021 03 08.
Article in English | MEDLINE | ID: covidwho-1121691

ABSTRACT

Background: It was studied if early suPAR-guided anakinra treatment can prevent severe respiratory failure (SRF) of COVID-19. Methods: A total of 130 patients with suPAR ≥6 ng/ml were assigned to subcutaneous anakinra 100 mg once daily for 10 days. Primary outcome was SRF incidence by day 14 defined as any respiratory ratio below 150 mmHg necessitating mechanical or non-invasive ventilation. Main secondary outcomes were 30-day mortality and inflammatory mediators; 28-day WHO-CPS was explored. Propensity-matched standard-of care comparators were studied. Results: 22.3% with anakinra treatment and 59.2% comparators (hazard ratio, 0.30; 95% CI, 0.20-0.46) progressed into SRF; 30-day mortality was 11.5% and 22.3% respectively (hazard ratio 0.49; 95% CI 0.25-0.97). Anakinra was associated with decrease in circulating interleukin (IL)-6, sCD163 and sIL2-R; IL-10/IL-6 ratio on day 7 was inversely associated with SOFA score; patients were allocated to less severe WHO-CPS strata. Conclusions: Early suPAR-guided anakinra decreased SRF and restored the pro-/anti-inflammatory balance. Funding: This study was funded by the Hellenic Institute for the Study of Sepsis, Technomar Shipping Inc, Swedish Orphan Biovitrum, and the Horizon 2020 Framework Programme. Clinical trial number: NCT04357366.


People infected with the SARS-CoV-2 virus, which causes COVID-19, can develop severe respiratory failure and require a ventilator to keep breathing, but this does not happen to every infected individual. Measuring a blood protein called suPAR (soluble urokinase plasminogen activator receptor) may help identify patients at the greatest risk of developing severe respiratory failure and requiring a ventilator. Previous investigations have suggested that measuring suPAR can identify pneumonia patients at highest risk for developing respiratory failure. The protein can be measured by taking a blood sample, and its levels provide a snapshot of how the body's immune system is reacting to infection, and of how it may respond to treatment. Anakinra is a drug that forms part of a class of medications called interleukin antagonists. It is commonly prescribed alone or in combination with other medications to reduce pain and swelling associated with rheumatoid arthritis. Kyriazopoulou et al. investigated whether treating COVID-19 patients who had developed pneumonia with anakinra could prevent the use of a ventilator and lower the risk of death. The findings show that treating COVID-19 patients with an injection of 100 milligrams of anakinra for ten days may be an effective approach because the drug combats inflammation. Kyriazopoulou et al. examined various markers of the immune response and discovered that anakinra was able to improve immune function, protecting a significant number of patients from going on a ventilator. The drug was also found to be safe and cause no significant adverse side effects. Administering anakinra decreased of the risk of progression into severe respiratory failure by 70%, and reduced death rates significantly. These results suggest that it may be beneficial to use suPAR as an early biomarker for identifying those individuals at highest risk for severe respiratory failure, and then treat them with anakinra. While the findings are promising, they must be validated in larger studies.


Subject(s)
Anti-Inflammatory Agents/administration & dosage , COVID-19/drug therapy , Interleukin 1 Receptor Antagonist Protein/administration & dosage , Respiratory Insufficiency/prevention & control , Aged , Aged, 80 and over , Antigens, CD/blood , Antigens, Differentiation, Myelomonocytic/blood , COVID-19/mortality , Female , Humans , Incidence , Injections, Subcutaneous , Interleukin-10/blood , Interleukin-6/blood , Male , Middle Aged , Receptors, Cell Surface/blood , Receptors, Urokinase Plasminogen Activator/blood , Receptors, Urokinase Plasminogen Activator/metabolism , Respiration, Artificial , Respiratory Insufficiency/epidemiology , SARS-CoV-2 , Standard of Care , Treatment Outcome
7.
Eur J Clin Microbiol Infect Dis ; 40(7): 1405-1412, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1053011

ABSTRACT

Recent publications on the probable role of heparin-binding protein (HBP) as a biomarker in sepsis prompted us to investigate its diagnostic and prognostic performance in severe COVID-19. HBP and IL-6 were measured by immunoassays at admission and on day 7 in 178 patients with pneumonia by SARS-CoV-2. Patients were classified into non-sepsis and sepsis as per the Sepsis-3 definitions and were followed up for the development of severe respiratory failure (SRF) and for outcome. Results were confirmed by multivariate analyses. HBP was significantly higher in patients classified as having sepsis and was negatively associated with the oxygenation ratio and positively associated with creatinine and lactate. Logistic regression analysis evidenced admission HBP more than 18 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for the development of SRP. Their integration prognosticated SRF with respective sensitivity, specificity, positive predictive value, and negative predictive 59.1%, 96.3%, 83.9%, and 87.8%. Cox regression analysis evidenced admission HBP more than 35 ng/ml and IL-6 more than 30 pg/ml as independent risk factors for 28-day mortality. Their integration prognosticated 28-day mortality with respective sensitivity, specificity, positive predictive value, and negative predictive value 69.2%, 92.7%, 42.9%, and 97.5%. HBP remained unchanged over-time course. A prediction score of the disposition of patients with COVID-19 is proposed taking into consideration admission levels of IL-6 and HBP. Using different cut-offs, the score may predict the likelihood for SRF and for 28-day outcome.


Subject(s)
Antimicrobial Cationic Peptides/blood , COVID-19/blood , Interleukin-6/blood , Respiratory Insufficiency/blood , Adult , Biomarkers/blood , Blood Proteins , COVID-19/diagnosis , COVID-19/mortality , COVID-19/physiopathology , Female , Humans , Male , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Pneumonia, Viral/mortality , Pneumonia, Viral/physiopathology , Predictive Value of Tests , Prognosis , Respiratory Insufficiency/diagnosis , Respiratory Insufficiency/mortality , Respiratory Insufficiency/physiopathology , SARS-CoV-2/isolation & purification , Sepsis/blood , Sepsis/diagnosis , Sepsis/mortality , Sepsis/physiopathology
8.
Genome Med ; 13(1): 7, 2021 01 13.
Article in English | MEDLINE | ID: covidwho-1027902

ABSTRACT

BACKGROUND: The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS: In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS: Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS: Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.


Subject(s)
COVID-19/pathology , Neutrophils/metabolism , Transcriptome , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/virology , Case-Control Studies , Down-Regulation , Drug Repositioning , Humans , Neutrophils/cytology , Neutrophils/immunology , Phenotype , Principal Component Analysis , RNA/blood , RNA/chemistry , RNA/metabolism , Sequence Analysis, RNA , Severity of Illness Index , Up-Regulation
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