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.

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.

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.

Functional profile, homing and residency of protective T cell immune responses against SARS-CoV-2 (preprint)

Considering that SARS-CoV-2 interacts with the host at the respiratory tract mucosal interface, T cells strategically placed within these surfaces, namely resident memory T cells, will be essential to limit viral spread and disease. Importantly, these cells are mostly non-recirculating, which reduces the window of opportunity to examine circulating lymphocytes in blood as they home to the lung parenchyma. Here, we demonstrate that viral specific T cells can migrate and establish in the lung as resident memory T cells, being detectable beyond 7 months in convalescent COVID-19 patients. Moreover, focusing on the acute phase of the infection, we identified virus-specific T cell responses in blood with functional, migratory and apoptotic patterns modulated by viral proteins and associated with clinical outcome. Our study highlights IL-10 secretion by virus-specific T cells associated to a better outcome and the persistence of resident memory T cells as key players for future protection against SARS-CoV-2 infection.

Nasopharyngeal microbial communities of patients infected with SARS-COV-2 that developed COVID-19. (preprint)

BackgroundSARS-CoV-2 is an RNA virus causing COVID-19. The clinical characteristics and epidemiology of COVID-19 have been extensively investigated, however studies focused on the patients microbiota are still lacking. In this study, we investigated the nasopharyngeal microbiome composition of patients who developed different severity levels of COVID-19. We performed Rdna-SSU (16S) sequencing from nasopharyngeal swab samples obtained from SARS-CoV-2 positive (56) and negative (18) patients in the province of Alicante (Spain) in their first visit to the hospital. Positive SARS-CoV-2 patients were observed and later categorized in mild (symptomatic without hospitalization), moderate (hospitalization) and severe (admission to ICU). We compared the microbiome diversity and OTU composition among severity groups using Similarity Percentage (SIMPER) analysis and Maaslin2. We also built bacterial co-abundance networks for each group using Fastpar. ResultsStatistical analysis indicated differences in the nasopharyngeal microbiome of COVID19 patients. 62 OTUs were found exclusively in SARS-CoV-2 positive patients, mostly classified as members of the phylum Bacteroidetes (18) and Firmicutes (25). OTUs classified as Prevotella were found to be significantly more abundant in patients that developed more severe COVID-19. Furthemore, co-abundance analysis indicated a loss of network complexity among samples from patients that later developed more severe symptoms. ConclusionsOur preliminary study shows that the nasopharyngeal microbiome of COVID-19 patients showed differences in the composition of specific OTUs and complexity of co-abundance networks. These microbes with differential abundances among groups could serve as biomarkers for COVID-19 severity. Nevertheless, further studies with larger sample sizes should be conducted to validate these results. IMPORTANCEThis work has studied the microbiota of the nasopharyngeal tract in COVID19 patients using advanced techniques of molecular microbiology. Diverse microorganisms, most of which are harmless or even beneficial to the host, colonize the nasopharyngeal tract. These microorganisms are the microbiota, and they are present in every people. However, changes in this microbiota could be related to different diseases as cancer, gastrointestinal pathologies or even COVID19. This study has been performed to investigate the microbiota from patients with COVID19, in order to determinate its implication in the pathology severity. The results obtained showed that it is possible that several specific microorganisms are present only in patients with severe COVID19. These data, could be used as a prognostic biomarker to early detect whose patients will develop a severe COVID19 and improve their clinical management.