Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters (preprint)

Background: Almost two years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted, nor new tests identified to improve the prediction and management of SARS-CoV-2 infection. Methods: Retrospective observational analysis of the predictive performance of clinical parameters and laboratory tests in hospitalised patients with COVID-19. Outcomes were 28-day survival and maximal severity in a cohort of 1,579 patients and two validation cohorts of 598 and 434 patients. A pilot study conducted in a patient subgroup measured 17 cytokines and 27 lymphocyte phenotypes to explore additional predictive laboratory tests. Findings: 1) Despite a strong association of 22 clinical and laboratory variables with the outcomes, their joint prediction power was limited due to redundancy. 2) Eight variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the statistical predictive power. 3) The interpretation of clinical and laboratory variables was improved by grouping them in categories. 4) Age and organ damage-related tests were the best predictors of survival, and inflammatory-related tests were the best predictors of severity. 5) The pilot study identified several immunological tests (including chemokine ligand 10, chemokine ligand 2, and interleukin 1 receptor antagonist), that performed better than currently used tests. Conclusions: Currently used tests for clinical management of COVID 19 patients are of limited value due to redundancy, as all measure aspects of two major processes: inflammation, and organ damage. There are no independent predictors based on the quality of the nascent adaptive immune response. Understanding the limitations of current tests would improve their interpretation and simplify clinical management protocols. A systematic search for better biomarkers is urgent and feasible.

Soluble angiotensin-converting enzyme 2 as a prognostic biomarker for disease progression in patients infected with SARS-CoV-2 (preprint)

Background: There is a need for better prediction of disease severity in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Soluble angiotensin-converting enzyme 2 (sACE2) arises from shedding of membrane ACE2 (mACE2) that is known to be a receptor for the spike protein of SARS-CoV-2; however, its value as a biomarker for disease severity is unknown. This study evaluated the predictive value of sACE2 in the context of other known biomarkers of inflammation and tissue damage (C-reactive protein [CRP], growth/differentiation factor-15 [GDF-15], interleukin-6 [IL-6], and soluble fms-like tyrosine kinase-1 [sFlt-1]) in patients with and without SARS-CoV-2 with different clinical outcomes. Methods: For univariate analyses, median differences between biomarker levels were calculated for the following patient groups classified according to clinical outcome: reverse transcription polymerase chain reaction (RT-PCR)-confirmed SARS-CoV-2 positive (Groups 1 - 4); RT-PCR-confirmed SARS-CoV-2 negative following previous SARS-CoV-2 infection (Groups 5 and 6); and RT-PCR-confirmed SARS-CoV-2 negative controls (Group 7). Results: Median levels of CRP, GDF-15, IL-6, and sFlt-1 were significantly higher in patients with SARS-CoV-2 who were admitted to hospital compared with patients who were discharged (all p<0.001), whereas levels of sACE2 were significantly lower (p<0.001). Receiver operating characteristic curve analysis of sACE2 provided cut-offs for the prediction of hospital admission of [≤]0.05 ng/mL (positive predictive value: 89.1%) and [≥]0.42 ng/mL (negative predictive value: 84.0%). Conclusion: These findings support further investigation of sACE2, either as a single biomarker or as part of a panel, to predict hospitalisation risk and disease severity in patients infected with SARS-CoV-2.

Recovery of serum testosterone levels is an accurate predictor of survival from COVID-19 in male patients (preprint)

Infection with SARS-CoV-2 portends a broad range of outcomes, from a majority of asymptomatic cases or mild clinical courses to a lethal disease. Robust correlates of severe COVID-19 include old age, male sex, poverty and co-morbidities such as obesity, diabetes or cardiovascular disease. A precise knowledge is still lacking of the molecular and biological mechanisms that may explain the association of severe disease with male sex. Here, we show that testosterone trajectories are highly accurate individual predictors (AUC of ROC = 0.928, p < 0.0001) of survival in male COVID-19 patients. Longitudinal determinations of blood levels of luteinizing hormone (LH) and androstenedione suggest an early modest inhibition of the central LH-androgen biosynthesis axis in a majority of patients, followed by either full recovery in survivors or a peripheral failure in lethal cases. Moreover, failure to reinstate physiological testosterone levels was associated with evidence of impaired T helper differentiation and decrease of non-classical monocytes. The strong association of recovery or failure to reinstate testosterone levels with survival or death from COVID-19 in male patients is suggestive of a significant role of testosterone status in the immune responses to COVID-19.

Cytokine Hemoadsorption As Rescue Therapy for Critically Ill Patients with SARS-CoV-2 Pneumonia with Severe Respiratory Failure and Hypercytokinemia (preprint)

Background : A dysregulated inflammatory response, known as “cytokine storm”, plays an important role in the pathophysiology of coronavirus 2019 disease (COVID-19). There is a subgroup of patients who develop a hyperinflammatory response with severe respiratory failure and organ dysfunction with high mortality. Identifying these patients is outstanding as they could benefit from specific therapies, such as cytokine removal by hemoadsorption. Methods: Single-center, observational and prospective study of critically ill patients with SARS-CoV-2 pneumonia, severe acute respiratory failure and hypercytokinemia. All patients received cytokine hemoadsorption using Cytosorb® (Cytosorbents Europe, Berlin, Germany). The indication for treatment was acute respiratory failure, inadequate prone response, and hypercytokinemia. Results : A total of 343 patients were admitted to the ICU due to SARS-Cov-2 infection between March 3, 2020, to June 22, 2020. Of these, six patients [5 (83.3%) men; mean age 57 (10.5) years; SOFA 5 (1.4); mean Acute Physiology And Chronic Health Evaluation (APACHE) II score 19.5 (6)] underwent hemoadsorption with Cytosorb®. All patients fulfilled the Berlin criteria for severe acute respiratory distress syndrome (ARDS), underwent prone positioning, and were on mechanical ventilation for 15.2 (7.2) days. One session of 16 (9.0) hours duration was performed. IL-6 levels were significantly reduced [(pre- hemoadsorption levels 17.367 (4.539– 22.532) pg/ml; post-hemoadsorption levels 2.403 (917 – 3.724) pg/ml, p = 0.043], and improvements in oxygenation were observed [pre-hemoadsorption PaO 2 /FiO 2 ratio was 103 (18.4), post- hemoadsorption PaO2/FiO2 ratio was 222 (20.9), p = 0.029]. We documented the clinical improvement and rapid reversal of organ dysfunction [pre-hemoadsorption Sequential Organ Failure Assessment (SOFA) score 9 (4.7); post- hemoadsorption SOFA score 7.7 (5.4), p = 0.046]. Inflammatory markers (C-reactive protein, D-dimer, and ferritin) also improved significantly. Mean ICU stay was 17.2 (8.0) days. ICU and in-hospital mortality was 33.7%. Conclusions : In our cohort, patients with SARS-CoV-2 pneumonia and severe acute respiratory failure and hypercytokinemia who received cytokine hemoadsorption, an important reduction in IL-6 levels and improvements in oxygenation and SOFA score were observed.

Immunophenotyping and machine learning identify distinct immunotypes that predict COVID-19 clinical severity (preprint)

Quantitative or qualitative differences in immunity may drive and predict clinical severity in COVID-19. We therefore measured modules of serum pro-inflammatory, anti-inflammatory and anti-viral cytokines in combination with the anti-SARS-CoV-2 antibody response in COVID-19 patients admitted to tertiary care. Using machine learning and employing unsupervised hierarchical clustering, agnostic to severity, we identified three distinct immunotypes that were shown post-clustering to predict very different clinical courses such as clinical improvement or clinical deterioration. Immunotypes did not associate chronologically with disease duration but rather reflect variations in the nature and kinetics of individual patient’s immune response. Here we demonstrate that immunophenotyping can stratify patients to high and low risk clinical subtypes, with distinct cytokine and antibody profiles, that can predict severity progression and guide personalized therapy.

T-cell responses as a correlate of COVID-19 vaccination. A pilot study in Health Care Workers. (preprint)

Background: Clinical trials on the different vaccines to SARS-CoV-2 have demonstrated protection efficacy, but it is urgent to assess the levels of protection generated with real-world data, especially in individuals professionally exposed. Measuring T-cell responses may complement antibody tests currently in use as correlates of protection but there are not validated T-cell responses applicable to large number of samples. Objective: To assess the feasibility of using T-cell responses to SARS-CoV-2 S peptides by commercially available whole blood interferon-gamma release assays (IGRA) as a correlate of protection. Patients: Twenty health care workers before and after vaccination. Methods: Antibody test to SARS-CoV-2 N and S proteins in parallel with one IGRA assay and two detection techniques than can be automated. Results: IGRA test detected T-cell responses in naturally exposed and vaccinated HCW already after first vaccination dose. the correlation by the two detection methods, CLIA and ELISA, very high (R>0.9) and sensitivity and specificity ranged between 100 and 86% and 100-73% respectively. Even though there was a very high concordance between antibody and the IGRA assay in the ability to detect immune response to SARS-CoV-2 there was a relatively low quantitative correlation. In the small group primed by natural infection, one vaccine dose was sufficient to reach immune response plateau. IGRA was positive in one Ig (S) antibody negative vaccinated immunosuppressed HCW illustrating another advantage of the IGRA test. Conclusion: Whole blood IGRA tests amenable to automation, as the one here reported, constitute a promising additional tool for measuring the state of the immune response to SARS-CoV-2; they are applicable to large number of samples and may become valuable correlates of protection to COVID-19, particularly for vulnerable groups at risk of being re-exposed to infection, as are health care workers.