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1.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327173

ABSTRACT

Initial symptoms of COVID-19 infection depend on viral replication, while hyperinflammation is a hallmark of critical illness and may drive severe pneumonia and death. Among the mechanisms potentially involved in the hyperinflammatory state, we focused on the unfolded protein response, because the IRE1α-XBP1 branch can be activated as result of the endoplasmic reticulum stress produced by the overwhelming synthesis of viral components and synergizes with Toll-like receptor signaling to induce cytokine expression. Viral RNA may trigger the IRE1α-XBP1 branch via TLR7/8 activation and like TLR2 and TLR4 may underpin cytokine expression trough XBP1 splicing (sXBP1). The expression of IL1B, IL6, and TNF mRNA in bronchoalveolar aspirates (BAAs) were higher in COVID-19 patients under mechanical ventilation and intubation who showed sXBP1. The scrutiny of monocytic/macrophagic markers during active infection showed a reduction of those involved in antigen presentation and survival, as well as the IFN stimulated gene MX1. These changes reverted after infection tests turned negative. In contrast, the expression of the mRNA of the serine protease TMPRSS2 involved in S protein priming showed a high expression during active infection. TLR8 mRNA showed an overwhelming expression as compared to TLR7 mRNA, which suggests the presence of monocyte-derived dendritic cells (MDDCs). In vitro experiments in MDDCs activated with ssRNA40, a positive-sense, single-stranded RNA (+ssRNA) like SARS-CoV-2 RNA, induced sXBP1 and the expression of IL-1β, IL-6, and TNFα at mRNA and protein levels. These responses were blunted by the IRE1α ribonuclease inhibitor MKC8866. Given the analogies between the results observed in BAAs and the effects induced by +ssRNA in MDDCs, IRE1α ribonuclease inhibition might be a druggable target in severe COVID-19 disease.

2.
J Intern Med ; 291(2): 232-240, 2022 02.
Article in English | MEDLINE | ID: covidwho-1455598

ABSTRACT

BACKGROUND: Anti-SARS-CoV-2 S antibodies prevent viral replication. Critically ill COVID-19 patients show viral material in plasma, associated with a dysregulated host response. If these antibodies influence survival and viral dissemination in ICU-COVID patients is unknown. PATIENTS/METHODS: We studied the impact of anti-SARS-CoV-2 S antibodies levels on survival, viral RNA-load in plasma, and N-antigenaemia in 92 COVID-19 patients over ICU admission. RESULTS: Frequency of N-antigenaemia was >2.5-fold higher in absence of antibodies. Antibodies correlated inversely with viral RNA-load in plasma, representing a protective factor against mortality (adjusted HR [CI 95%], p): (S IgM [AUC ≥ 60]: 0.44 [0.22; 0.88], 0.020); (S IgG [AUC ≥ 237]: 0.31 [0.16; 0.61], <0.001). Viral RNA-load in plasma and N-antigenaemia predicted increased mortality: (N1-viral load [≥2.156 copies/ml]: 2.25 [1.16; 4.36], 0.016); (N-antigenaemia: 2.45 [1.27; 4.69], 0.007). CONCLUSIONS: Low anti-SARS-CoV-2 S antibody levels predict mortality in critical COVID-19. Our findings support that these antibodies contribute to prevent systemic dissemination of SARS-CoV-2.


Subject(s)
Antibodies, Viral/blood , Antigens, Viral/blood , COVID-19 , COVID-19/immunology , COVID-19/mortality , Critical Illness , Humans , RNA, Viral/blood , SARS-CoV-2
3.
Eur J Clin Invest ; 51(6): e13501, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1054522

ABSTRACT

BACKGROUND: The presence of SARS-CoV-2 RNA in plasma has been linked to disease severity and mortality. We compared RT-qPCR to droplet digital PCR (ddPCR) to detect SARS-CoV-2 RNA in plasma from COVID-19 patients (mild, moderate, and critical disease). METHODS: The presence/concentration of SARS-CoV-2 RNA in plasma was compared in three groups of COVID-19 patients (30 outpatients, 30 ward patients and 30 ICU patients) using both RT-qPCR and ddPCR. Plasma was obtained in the first 24h following admission, and RNA was extracted using eMAG. ddPCR was performed using Bio-Rad SARS-CoV-2 detection kit, and RT-qPCR was performed using GeneFinder™ COVID-19 Plus RealAmp Kit. Statistical analysis was performed using Statistical Package for the Social Science. RESULTS: SARS-CoV-2 RNA was detected, using ddPCR and RT-qPCR, in 91% and 87% of ICU patients, 27% and 23% of ward patients and 3% and 3% of outpatients. The concordance of the results obtained by both methods was excellent (Cohen's kappa index = 0.953). RT-qPCR was able to detect 34/36 (94.4%) patients positive for viral RNA in plasma by ddPCR. Viral RNA load was higher in ICU patients compared with the other groups (P < .001), by both ddPCR and RT-qPCR. AUC analysis revealed Ct values (RT-qPCR) and viral RNA load values (ddPCR) can similarly differentiate between patients admitted to wards and to the ICU (AUC of 0.90 and 0.89, respectively). CONCLUSION: Both methods yielded similar prevalence of RNAemia between groups, with ICU patients showing the highest (>85%). RT-qPCR was as useful as ddPCR to detect and quantify SARS-CoV-2 RNAemia in plasma.


Subject(s)
COVID-19/blood , RNA, Viral/blood , Real-Time Polymerase Chain Reaction/methods , Aged , Ambulatory Care , Female , Humans , Intensive Care Units , Male , Middle Aged , Patients' Rooms , Polymerase Chain Reaction/methods , SARS-CoV-2/genetics , Severity of Illness Index
4.
Crit Care ; 24(1): 691, 2020 12 14.
Article in English | MEDLINE | ID: covidwho-977684

ABSTRACT

BACKGROUND: COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. METHODS: A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. RESULTS: The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p < 0.001). Critical patients had higher viral RNA loads in plasma than non-critically ill patients, with non-survivors showing the highest values. When outpatients and ward patients were compared, viral RNAemia did not show significant associations in the multivariate analysis. In contrast, when ward patients were compared with ICU patients, both viral RNAemia and viral RNA load in plasma were associated with critical illness (OR [CI 95%], p): RNAemia (3.92 [1.183-12.968], 0.025), viral RNA load (N1) (1.962 [1.244-3.096], 0.004); viral RNA load (N2) (2.229 [1.382-3.595], 0.001). Viral RNA load in plasma correlated with higher levels of chemokines (CXCL10, CCL2), biomarkers indicative of a systemic inflammatory response (IL-6, CRP, ferritin), activation of NK cells (IL-15), endothelial dysfunction (VCAM-1, angiopoietin-2, ICAM-1), coagulation activation (D-Dimer and INR), tissue damage (LDH, GPT), neutrophil response (neutrophils counts, myeloperoxidase, GM-CSF) and immunodepression (PD-L1, IL-10, lymphopenia and monocytopenia). CONCLUSIONS: SARS-CoV-2 RNAemia and viral RNA load in plasma are associated with critical illness in COVID-19. Viral RNA load in plasma correlates with key signatures of dysregulated host responses, suggesting a major role of uncontrolled viral replication in the pathogenesis of this disease.


Subject(s)
COVID-19/complications , RNA, Viral/analysis , Viral Load/immunology , Adult , Aged , Biomarkers/analysis , Biomarkers/blood , COVID-19/blood , Chi-Square Distribution , Critical Illness , Female , Humans , Male , Middle Aged , Multivariate Analysis , Polymerase Chain Reaction/methods , RNA, Viral/blood , Statistics, Nonparametric
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