ABSTRACT
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
ABSTRACT
BackgroundThere 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. MethodsFor 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). ResultsMedian 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%). ConclusionThese 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. HIGHLIGHTSNoelia Diaz Troyano: Noy-Lee-ah Dee-az Tro-yah-no Better prediction of disease severity in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is needed. We measured soluble angiotensin-converting enzyme 2 (soluble ACE2) and other biomarkers of inflammation and tissue damage in patients recruited from Vall dHebron University Hospital, with and without SARS-CoV-2 and with different clinical outcomes. Levels of soluble ACE2 were significantly lower in patients with SARS-CoV-2 who had the most severe clinical outcome in all comparisons. These findings support a protective role for soluble ACE2 in SARS-CoV-2 infection and warrant further investigation of soluble ACE2 as a biomarker for disease severity in patients with SARS-CoV-2.
ABSTRACT
Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic [~]0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.
ABSTRACT
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.
ABSTRACT
BackgroundRespiratory failure is a key feature of severe Covid-19 and a critical driver of mortality, but for reasons poorly defined affects less than 10% of SARS-CoV-2 infected patients. MethodsWe included 1,980 patients with Covid-19 respiratory failure at seven centers in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe (Milan, Monza, Madrid, San Sebastian and Barcelona) for a genome-wide association analysis. After quality control and exclusion of population outliers, 835 patients and 1,255 population-derived controls from Italy, and 775 patients and 950 controls from Spain were included in the final analysis. In total we analyzed 8,582,968 single-nucleotide polymorphisms (SNPs) and conducted a meta-analysis of both case-control panels. ResultsWe detected cross-replicating associations with rs11385942 at chromosome 3p21.31 and rs657152 at 9q34, which were genome-wide significant (P<5x10-8) in the meta-analysis of both study panels, odds ratio [OR], 1.77; 95% confidence interval [CI], 1.48 to 2.11; P=1.14x10-10 and OR 1.32 (95% CI, 1.20 to 1.47; P=4.95x10-8), respectively. Among six genes at 3p21.31, SLC6A20 encodes a known interaction partner with angiotensin converting enzyme 2 (ACE2). The association signal at 9q34 was located at the ABO blood group locus and a blood-group-specific analysis showed higher risk for A-positive individuals (OR=1.45, 95% CI, 1.20 to 1.75, P=1.48x10-4) and a protective effect for blood group O (OR=0.65, 95% CI, 0.53 to 0.79, P=1.06x10-5). ConclusionsWe herein report the first robust genetic susceptibility loci for the development of respiratory failure in Covid-19. Identified variants may help guide targeted exploration of severe Covid-19 pathophysiology.
ABSTRACT
The SARS-CoV-2 spike (S) protein, the viral mediator for binding and entry into the host cell, has sparked great interest as a target for vaccine development and treatments with neutralizing antibodies. Initial data suggest that the virus has low mutation rates, but its large genome could facilitate recombination, insertions, and deletions, as has been described in other coronaviruses. Here, we deep-sequenced the complete SARS-CoV-2 S gene from 18 patients (10 with mild and 8 with severe COVID-19), and found that the virus accumulates deletions upstream and very close to the S1/S2 cleavage site, generating a frameshift with appearance of a stop codon. These deletions were found in a small percentage of the viral quasispecies (2.2%) in samples from all the mild and only half the severe COVID-19 patients. Our results suggest that the virus may generate free S1 protein released to the circulation. We propose that natural selection has favored a "Dont burn down the house" strategy, in which free S1 protein may compete with viral particles for the ACE2 receptor, thus reducing the severity of the infection and tissue damage without losing transmission capability.
