SARS-CoV-2 infection impairs NK cell functions via activation of the LLT1-CD161 axis.

Introduction: Natural killer (NK) cells plays a pivotal role in the control of viral infections, and their function depend on the balance between their activating and inhibitory receptors. The immune dysregulation observed in COVID-19 patients was previously associated with downregulation of NK cell numbers and function, yet the mechanism of inhibition of NK cell functions and the interplay between infected cells and NK cells remain largely unknown. Methods: In this study we show that SARS-CoV-2 infection of airway epithelial cells can directly influence NK cell phenotype and functions in the infection microenvironment. NK cells were co-cultured with SARS-CoV-2 infected epithelial cells, in a direct contact with A549ACE2/TMPRSS2 cell line or in a microenvironment of the infection in a 3D ex vivo human airway epithelium (HAE) model and NK cell surface expression of a set of most important receptors (CD16, NKG2D, NKp46, DNAM-1, NKG2C, CD161, NKG2A, TIM-3, TIGIT, and PD-1) was analyzed. Results: We observed a selective, in both utilized experimental models, significant downregulation the proportion of CD161 (NKR-P1A or KLRB1) expressing NK cells, and its expression level, which was followed by a significant impairment of NK cells cytotoxicity level against K562 cells. What is more, we confirmed that SARS-CoV-2 infection upregulates the expression of the ligand for CD161 receptor, lectin-like transcript 1 (LLT1, CLEC2D or OCIL), on infected epithelial cells. LLT1 protein can be also detected not only in supernatants of SARS-CoV-2 infected A549ACE2/TMPRSS2 cells and HAE basolateral medium, but also in serum of COVID-19 patients. Finally, we proved that soluble LLT1 protein treatment of NK cells significantly reduces i) the proportion of CD161+ NK cells, ii) the ability of NK cells to control SARS-CoV-2 infection in A549ACE2/TMPRSS2 cells and iii) the production of granzyme B by NK cells and their cytotoxicity capacity, yet not degranulation level. Conclusion: We propose a novel mechanism of SARS-CoV-2 inhibition of NK cell functions via activation of the LLT1-CD161 axis.

The value of lung ultrasound in COVID-19 pneumonia, verified by high resolution computed tomography assessed by artificial intelligence.

BACKGROUND: Lung ultrasound (LUS) is an increasingly popular imaging method in clinical practice. It became particularly important during the COVID-19 pandemic due to its mobility and ease of use compared to high-resolution computed tomography (HRCT). The objective of this study was to assess the value of LUS in quantifying the degree of lung involvement and in discrimination of lesion types in the course of COVID-19 pneumonia as compared to HRCT analyzed by the artificial intelligence (AI). METHODS: This was a prospective observational study including adult patients hospitalized due to COVID-19 in whom initial HRCT and LUS were performed with an interval < 72 h. HRCT assessment was performed automatically by AI. We evaluated the correlations between the inflammation volume assessed both in LUS and HRCT, between LUS results and the HRCT structure of inflammation, and between LUS and the laboratory markers of inflammation. Additionally we compared the LUS results in subgroups depending on the respiratory failure throughout the hospitalization. RESULTS: Study group comprised 65 patients, median 63 years old. For both lungs, the median LUS score was 19 (IQR-interquartile range 11-24) and the median CT score was 22 (IQR 16-26). Strong correlations were found between LUS and CT scores (for both lungs r = 0.75), and between LUS score and percentage inflammation volume (PIV) (r = 0.69). The correlations remained significant, if weakened, for individual lung lobes. The correlations between LUS score and the value of the percentage consolidation volume (PCV) divided by percentage ground glass volume (PGV), were weak or not significant. We found significant correlation between LUS score and C-reactive protein (r = 0.55), and between LUS score and interleukin 6 (r = 0.39). LUS score was significantly higher in subgroups with more severe respiratory failure. CONCLUSIONS: LUS can be regarded as an accurate method to evaluate the extent of COVID-19 pneumonia and as a promising tool to estimate its clinical severity. Evaluation of LUS in the assessment of the structure of inflammation, requires further studies in the course of the disease. TRIAL REGISTRATION: The study has been preregistered 13 Aug 2020 on clinicaltrials.gov with the number NCT04513210.

Course of fatigue among patients previously hospitalised due to COVID-19.

INTRODUCTION: Discrepancies exist regarding the clinical course and prognostic factors for post-COVID fatigue. Therefore, our aim was to assess the timely course of fatigue and its possible predictors in patients previously hospitalised due to SARS-CoV-2 infection. MATERIAL AND METHODS: Patients and employees of the University Hospital in Krakow were assessed with the use of a validated neuropsychological questionnaire. Included were participants aged 18 or more, previously hospitalised due to COVID-19, who completed questionnaires only once > 3 months after the onset of infection. Individuals were retrospectively asked about the presence of eight symptoms of chronic fatigue syndrome at four timepoints: before COVID-19, within 0-4 weeks, 4-12 weeks, and > 12 weeks post-infection. RESULTS: We enrolled 204 patients [40.2% women, median age 58 (46-66) years] evaluated after a median of 187 (156-220) days from the first positive nasal swab test for SARS-CoV-2. The most common comorbidities were hypertension (44.61%), obesity (36.27%), smoking (28.43%), and hypercholesterolemia (21.08%); none of the patients required mechanical ventilation during hospitalisation. Before COVID-19, 43.62% of patients reported at least one symptom of chronic fatigue. Within 4, 4-12, and > 12 weeks after COVID-19, the prevalence of chronic fatigue was 76.96%, 75.49%, and 66.17%, respectively (all p < 0.001). The frequency of chronic fatigue symptoms decreased within > 12 weeks following the onset of infection but did not return to baseline values, except for self-reported lymph node enlargement. In a multivariable linear regression model, the number of fatigue symptoms was predicted by female sex [ß 0.25 (0.12; 0.39), p < 0.001 and 0.26 (0.13; 0.39), p < 0.001 for weeks 0-12 and > 12, respectively], and age [for < 4 weeks, ß -0.12 (-0.28; -0.01), p = 0.029]. CONCLUSIONS: Most patients previously hospitalised due to COVID-19 suffer from fatigue > 12 weeks after infection onset. The presence of fatigue is predicted by female sex and - only for the acute phase - age.