SARS-CoV-2 viremia precedes an IL6 response in severe COVID-19 patients: results of a longitudinal prospective cohort (preprint)

Background: Interleukin 6 (IL6) levels and SARS-CoV-2 viremia have been correlated with COVID-19 severity. The association over time between them has not been assessed in a prospective cohort. Our aim was to evaluate the relationship between SARS-CoV-2 viremia and time evolution of IL6 levels in a COVID-19 prospective cohort. Methods: Secondary analysis from a prospective cohort including COVID-19 hospitalized patients from Hospital Universitario La Princesa between November 2020 and January 2021. Serial plasma samples were collected from admission until discharge. Viral load was quantified by Real-Time Polymerase Chain Reaction and IL6 levels with an enzyme immunoassay. To represent the evolution over time of both variables we used the graphic command twoway of Stata. Results: A total of 57 patients were recruited, with median age of 63 years (IQR [53-81]), 61.4% male and 68.4% caucasian. The peak of viremia appeared shortly after symptom onset in patients with persistent viremia (more than 1 sample with >1.3 log10 copies/ml) and also in those with at least one IL6>30 pg/ml, followed by a progressive increase in IL6 around 10 days later. Persistent viremia in the first week of hospitalization was associated with higher levels of IL6. Both IL6 and SARS-CoV-2 viral load were higher in males, with a quicker increase with age. Conclusions: In those patients with worse outcomes, an early peak of SARS-CoV-2 viral load precedes an increase in IL6 levels. Monitoring SARS-CoV-2 viral load during the first week after symptom onset may be helpful to predict disease severity in COVID-19 patients.

Detection of SARS-Cov-2 RNA in serum is associated with increased mortality risk in hospitalized COVID-19 patients. (preprint)

BackgroundCOVID-19 has overloaded national health services worldwide. Thus, early identification of patients at risk of poor outcomes is critical. Our objective was to analyse SARS-CoV-2 RNA detection in serum as a severity biomarker in COVID-19. Methods and FindingsRetrospective observational study including 193 patients admitted for COVID-19. Detection of SARS-CoV-2 RNA in serum (CoVemia) was performed with samples collected at 48-72 hours of admission by two techniques from Roche and Thermo Fischer Scientific (TFS). Main outcome variables were mortality and need for ICU admission during hospitalization for COVID-19. CoVemia was detected in 50-60% of patients depending on technique. The correlation of Ct in serum between both techniques was good (intraclass correlation coefficient: 0.612; p < 0.001). Patients with CoVemia were older (p = 0.006), had poorer baseline oxygenation (PaO2/FiO2; p < 0.001), more severe lymphopenia (p < 0.001) and higher LDH (p < 0.001), IL-6 (p = 0.021), C-reactive protein (CRP; p = 0.022) and procalcitonin (p = 0.002) serum levels. We defined "relevant CoVemia" when detection Ct was < 34 with Roche and < 31 for TFS. These thresholds had 95% sensitivity and 35 % specificity. Relevant CoVemia predicted death during hospitalization (OR 9.2 [3.8 - 22.6] for Roche, OR 10.3 [3.6 - 29.3] for TFS; p < 0.001). Cox regression models, adjusted by age, sex and Charlson index, identified increased LDH serum levels and relevant CoVemia (HR = 9.87 [4.13-23.57] for TFS viremia and HR = 7.09 [3.3-14.82] for Roche viremia) as the best markers to predict mortality. ConclusionsCoVemia assessment at admission is the most useful biomarker for predicting mortality in COVID-19 patients. CoVemia is highly reproducible with two different techniques (TFS and Roche), has a good consistency with other severity biomarkers for COVID-19 and better predictive accuracy. AUTHOR SUMMARYCOVID-19 shows a very heterogeneous clinical picture. In addition, it has overloaded national health services worldwide. Therefore, early identification of patients with poor prognosis is critical to improve the use of limited health resources. In this work, we evaluated whether baseline SARS-CoV2 RNA detection in blood (CoVemia) is associated with worse outcomes. We studied almost 200 patients admitted to our hospital and about 50-60% of them showed positive CoVemia. Patients with positive CoVemia were older and had more severe disease; CoVemia was also more frequent in patients requiring admission to the ICU. Moreover, we defined "relevant CoVemia", as the amount of viral load that better predicted mortality obtaining 95% sensitivity and 35% specificity. In addition, relevant CoVemia was a better predictor than other biomarkers such as LDH, lymphocyte count, interleukin-6, and indexes used in ICU such as qSOFA and CURB65. In summary, detection of CoVemia is the best biomarker to predict death in COVID-19 patients. Furthermore, it is easy to be implemented and is reproducible with two techniques (Roche and Thermo Fisher Scientific) that are currently used for diagnosis in nasopharyngeal swabs samples.

In vivo structure and dynamics of the RNA genome of SARS-Cov-2 (preprint)

The SARS-CoV-2 coronavirus, which causes the COVID-19 pandemic, is one of the largest positive strand RNA viruses. Here we developed a simplified SPLASH assay and comprehensively mapped the in vivo RNA-RNA interactome of SARS-CoV-2 RNA during the viral life cycle. We observed canonical and alternative structures including 3-UTR and 5-UTR, frameshifting element (FSE) pseudoknot and genome cyclization in cells and in virions. We provide direct evidence of interactions between Transcription Regulating Sequences (TRS-L and TRS-Bs), which facilitate discontinuous transcription. In addition, we reveal alternative short and long distance arches around FSE, forming a "high-order pseudoknot" embedding FSE, which might help ribosome stalling at frameshift sites. More importantly, we found that within virions, while SARS-CoV-2 genome RNA undergoes intensive compaction, genome cyclization is weakened and genome domains remain stable. Our data provides a structural basis for the regulation of replication, discontinuous transcription and translational frameshifting, describes dynamics of RNA structures during life cycle of SARS-CoV-2, and will help to develop antiviral strategies.

Differential Redistribution of Activated Monocyte and Dendritic Cell Subsets to the Lung Associates with Severity of COVID-19 (preprint)

The SARS-CoV-2 is responsible for the pandemic COVID-19 in infected individuals, who can either exhibit mild symptoms or progress towards a life-threatening acute respiratory distress syndrome (ARDS). It is known that exacerbated inflammation and dysregulated immune responses involving T and myeloid cells occur in COVID-19 patients with severe clinical progression. However, the differential contribution of specific subsets of dendritic cells and monocytes to ARDS is still poorly understood. In addition, the role of CD8+ T cells present in the lung of COVID-19 patients and relevant for viral control has not been characterized. With the aim to improve the knowledge in this area, we developed a cross-sectional study, in which we have studied the frequencies and activation profiles of dendritic cells and monocytes present in the blood of COVID-19 patients with different clinical severity in comparison with healthy control individuals. Furthermore, these subpopulations and their association with antiviral effector CD8+ T cell subsets were also characterized in lung infiltrates from critical COVID-19 patients. Collectively, our results suggest that inflammatory transitional and non-classical monocytes preferentially migrate from blood to lungs in patients with severe COVID-19. CD1c+ conventional dendritic cells also followed this pattern, whereas CD141+ conventional and CD123hi plasmacytoid dendritic cells were depleted from blood but were absent in the lungs. Thus, this study increases the knowledge on the pathogenesis of COVID-19 disease and could be useful for the design of therapeutic strategies to fight SARS-CoV-2 infection.