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

BackgroundAlmost 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. MethodsRetrospective 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. Findings1) 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. ConclusionsCurrently used tests for clinical management of COVID-19 patients are of limited predictive 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. This study was funded by Instituto de Salud Carlos III, Madrid, Spain, grants COV20/00416, Cov20/00654 and COV20/00388 to R.P-B, ATS and JBM respectively and co-financed by the European Regional Development Fund (ERDF). DA-S is recipient of a doctoral fellowship from the Vall dHebron Research Institute, Barcelona, Spain. ASM was supported by a postdoctoral grant "Juan Rodes" (JR18/00022) from Instituto de Salud Carlos III through the Ministry of Economy and Competitiveness, Spain

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

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

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 patients 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.

BackgroundIt is crucial to assess the levels of protection generated by natural infection or SARS-CoV-2 vaccines, mainly in individuals professionally exposed and in vulnerable groups. Measuring T-cell responses may complement antibody tests currently in use as correlates of protection. Our aim was to assess the feasibility of a validated assay of T-cell responses. MethodsTwenty health-care-workers (HCW) were included. Antibody test to SARS-CoV-2 N and S-proteins in parallel with a commercially available whole-blood-interferon-gamma-release-assay (IGRA) to S-peptides and two detection methods, CLIA and ELISA were determined. ResultsIGRA test detected T-cell responses in naturally exposed and vaccinated HCW already after first vaccination dose. The correlation by the two detection methods was very high (R>0.8) and sensitivity and specificity ranged between 100 and 86% and 100-73% respectively. Even though there was a very high concordance between specific antibody levels 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, with Ig(S) antibody negative vaccinated immunosuppressed HCW illustrating another advantage of the IGRA-test. ConclusionWhole-blood-IGRA-tests amenable to automation and constitutes 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 a valuable correlate 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

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 remaining detectable up to 10 months after initial infection. 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.