A proteomic survival predictor for COVID-19 patients in intensive care.

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care.

Cenicriviroc for the treatment of COVID-19: first interim results of a randomised, placebo-controlled, investigator-initiated, double-blind phase II trial.

OBJECTIVES: C-C-chemokine receptors (CCRs) are expressed on a variety of immune cells and play an important role in many immune processes, particularly leukocyte migration. Comprehensive preclinical research demonstrated CCR2/CCR5-dependent pathways as pivotal for the pathophysiology of severe COVID-19. Here we report human data on use of a chemokine receptor inhibitor in patients with COVID-19. METHODS: Interim results of a 2:1 randomised, placebo-controlled, investigator-initiated trial on the CCR2/CCR5-inhibitor Cenicriviroc (CVC) 150 mg BID orally for 28 d in hospitalised patients with moderate to severe COVID-19 are reported. The primary endpoint is the subject's responder status defined by achieving grade 1 or 2 on the 7-point ordinal scale of clinical improvement on day 15. RESULTS: Of the 30 patients randomised, 18 were assigned to receive CVC and 12 to placebo. Efficient CCR2- and CCR5 inhibition was demonstrated through CCL2 and CCL4 elevation in CVC-treated patients (485% and 80% increase on day 3 compared to the baseline, respectively). In the modified intention-to-treat population, 82.4% of patients (14/17) in the CVC group met the primary endpoint, as did 91.7% (11/12) in the placebo group (OR = 0.5, 95% CI = 0.04-3.41). One patient treated with CVC died of progressive acute respiratory distress syndrome, and the remaining had a favourable outcome. Overall, treatment with CVC was well tolerated, with most adverse events being grade I or II and resolving spontaneously. CONCLUSIONS: Our interim analysis provides proof-of-concept data on CVC for COVID-19 patients as an intervention to inhibit CCR2/CCR5. Further studies are warranted to assess its clinical efficacy.

Functional limitations 12 months after SARS-CoV-2 infection correlate with initial disease severity: An observational study of cardiopulmonary exercise capacity testing in COVID-19 convalescents.

BACKGROUND: Cardiopulmonary Exercise Testing (CPET) provides a comprehensive assessment of pulmonary, cardiovascular and musculosceletal function. Reduced CPET performance could be an indicator for chronic morbidity after COVID-19. METHODS: Patients ≥18 years with confirmed PCR positive SARS-CoV-2 infection were offered to participate in a prospective observational study of clinical course and outcomes of COVID-19. 54 patients completed CPET, questionnaires on respiratory quality of life and performed pulmonary function tests 12 months after SARS-CoV-2 infection. RESULTS: At 12 months after SARS-CoV-2 infection, 46.3% of participants had a peak performance and 33.3% a peak oxygen uptake of <80% of the predicted values, respectively. Further impairments were observed in diffusion capacity and ventilatory efficiency. Functional limitations were particularly pronounced in patients after invasive mechanical ventilation and extracorporeal membrane oxygenation treatment. Ventilatory capacity was reduced <80% of predicted values in 55.6% of participants, independent from initial clinical severity. Patient reported dyspnea and respiratory quality of life after COVID-19 correlated with CPET performance and parameters of gas exchange. Risk factors for reduced CPET performance 12 months after COVID-19 were prior intensive care treatment (OR 5.58, p = 0.004), SGRQ outcome >25 points (OR 3.48, p = 0.03) and reduced DLCO (OR 3.01, p = 0.054). CONCLUSIONS: Functional limitations causing chronic morbidity in COVID-19 survivors persist over 12 months after SARS-CoV-2 infection. These limitations were particularly seen in parameters of overall performance and gas exchange resulting from muscular deconditioning and lung parenchymal changes. Patient reported reduced respiratory quality of life was a risk factor for adverse CPET performance.

Severity of respiratory failure and computed chest tomography in acute COVID-19 correlates with pulmonary function and respiratory symptoms after infection with SARS-CoV-2: An observational longitudinal study over 12 months.

INTRODUCTION: Prospective and longitudinal data on pulmonary injury over one year after acute coronavirus disease 2019 (COVID-19) are sparse. We aim to determine reductions in pulmonary function and respiratory related quality of life up to 12 months after acute COVID-19. METHODS: Patients with acute COVID-19 were enrolled into an ongoing single-centre, prospective observational study and prospectively examined 6 weeks, 3, 6 and 12 months after onset of COVID-19 symptoms. Chest CT-scans, pulmonary function and symptoms assessed by St. Georges Respiratory Questionnaire were used to evaluate respiratory limitations. Patients were stratified according to severity of acute COVID-19. RESULTS: Median age of all patients was 57 years, 37.8% were female. Higher age, male sex and higher BMI were associated with acute-COVID-19 severity (p < 0.0001, 0.001 and 0.004 respectively). Also, pulmonary restriction and reduced carbon monoxide diffusion capacity was associated with disease severity. In patients with restriction and impaired diffusion capacity, FVC improved over 12 months from 61.32 to 71.82, TLC from 68.92 to 76.95, DLCO from 60.18 to 68.98 and KCO from 81.28 to 87.80 (percent predicted values; p = 0.002, 0.045, 0.0002 and 0.0005). The CT-score of lung involvement in the acute phase was associated with restriction and reduction in diffusion capacity in follow-up. Respiratory symptoms improved for patients in higher severity groups during follow-up, but not for patients with initially mild disease. CONCLUSION: Severity of respiratory failure during COVID-19 correlates with the degree of pulmonary function impairment and respiratory quality of life in the year after acute infection.

A time-resolved proteomic and prognostic map of COVID-19.

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.

CD169/SIGLEC1 is expressed on circulating monocytes in COVID-19 and expression levels are associated with disease severity.

Coronavirus disease 2019 (COVID-19) is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Type I interferons are important in the defense of viral infections. Recently, neutralizing IgG auto-antibodies against type I interferons were found in patients with severe COVID-19 infection. Here, we analyzed expression of CD169/SIGLEC1, a well described downstream molecule in interferon signaling, and found increased monocytic CD169/SIGLEC1 expression levels in patients with mild, acute COVID-19, compared to patients with severe disease. We recommend further clinical studies to evaluate the value of CD169/SIGLEC1 expression in patients with COVID-19 with or without auto-antibodies against type I interferons.

Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19).

PURPOSE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global health emergency. Pa-COVID-19 aims to provide comprehensive data on clinical course, pathophysiology, immunology and outcome of COVID-19, to identify prognostic biomarkers, clinical scores, and therapeutic targets for improved clinical management and preventive interventions. METHODS: Pa-COVID-19 is a prospective observational cohort study of patients with confirmed SARS-CoV-2 infection treated at Charité - Universitätsmedizin Berlin. We collect data on epidemiology, demography, medical history, symptoms, clinical course, and pathogen testing and treatment. Systematic, serial blood sampling will allow deep molecular and immunological phenotyping, transcriptomic profiling, and comprehensive biobanking. Longitudinal data and sample collection during hospitalization will be supplemented by long-term follow-up. RESULTS: Outcome measures include the WHO clinical ordinal scale on day 15 and clinical, functional, and health-related quality-of-life assessments at discharge and during follow-up. We developed a scalable dataset to (i) suit national standards of care, (ii) facilitate comprehensive data collection in medical care facilities with varying resources, and (iii) allow for rapid implementation of interventional trials based on the standardized study design and data collection. We propose this scalable protocol as blueprint for harmonized data collection and deep phenotyping in COVID-19 in Germany. CONCLUSION: We established a basic platform for harmonized, scalable data collection, pathophysiological analysis, and deep phenotyping of COVID-19, which enables rapid generation of evidence for improved medical care and identification of candidate therapeutic and preventive strategies. The electronic database accredited for interventional trials allows fast trial implementation for candidate therapeutic agents. TRIAL REGISTRATION: Registered at the German registry for clinical studies (DRKS00021688).