A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study.

BACKGROUND: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. METHODS: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. RESULTS: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. CONCLUSIONS: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.

High SARS-CoV-2 Viral Load and Low CCL5 Expression Levels in the Upper Respiratory Tract Are Associated With COVID-19 Severity.

Mucosal immune response in the upper respiratory tract is crucial for initial control of viral replication, clearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and progression of coronavirus disease 2019 (COVID-19). We analyzed SARS-CoV-2 RNA load and expression of selected immune genes in the upper respiratory tract (nasopharynx) of 255 SARS-CoV-2-infected patients and evaluated their association with severe COVID-19. SARS-CoV-2 replication in nasopharyngeal mucosa induces expression of several innate immune genes. High SARS-CoV-2 viral load and low CCL5 expression levels were associated with intensive care unit admission or death, although CCL5 was the best predictor of COVID-19 severity.

Low anti-SARS-CoV-2 S antibody levels predict increased mortality and dissemination of viral components in the blood of critical COVID-19 patients.

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.

Digital PCR applications for the diagnosis and management of infection in critical care medicine.

Infection (either community acquired or nosocomial) is a major cause of morbidity and mortality in critical care medicine. Sepsis is present in up to 30% of all ICU patients. A large fraction of sepsis cases is driven by severe community acquired pneumonia (sCAP), which incidence has dramatically increased during COVID-19 pandemics. A frequent complication of ICU patients is ventilator associated pneumonia (VAP), which affects 10-25% of all ventilated patients, and bloodstream infections (BSIs), affecting about 10% of patients. Management of these severe infections poses several challenges, including early diagnosis, severity stratification, prognosis assessment or treatment guidance. Digital PCR (dPCR) is a next-generation PCR method that offers a number of technical advantages to face these challenges: it is less affected than real time PCR by the presence of PCR inhibitors leading to higher sensitivity. In addition, dPCR offers high reproducibility, and provides absolute quantification without the need for a standard curve. In this article we reviewed the existing evidence on the applications of dPCR to the management of infection in critical care medicine. We included thirty-two articles involving critically ill patients. Twenty-three articles focused on the amplification of microbial genes: (1) four articles approached bacterial identification in blood or plasma; (2) one article used dPCR for fungal identification in blood; (3) another article focused on bacterial and fungal identification in other clinical samples; (4) three articles used dPCR for viral identification; (5) twelve articles quantified microbial burden by dPCR to assess severity, prognosis and treatment guidance; (6) two articles used dPCR to determine microbial ecology in ICU patients. The remaining nine articles used dPCR to profile host responses to infection, two of them for severity stratification in sepsis, four focused to improve diagnosis of this disease, one for detecting sCAP, one for detecting VAP, and finally one aimed to predict progression of COVID-19. This review evidences the potential of dPCR as a useful tool that could contribute to improve the detection and clinical management of infection in critical care medicine.

A host transcriptomic signature for identification of respiratory viral infections in the community.

BACKGROUND: Fever-7 is a test evaluating host mRNA expression levels of IFI27, JUP, LAX, HK3, TNIP1, GPAA1 and CTSB in blood able to detect viral infections. This test has been validated mostly in hospital settings. Here we have evaluated Fever-7 to identify the presence of respiratory viral infections in a Community Health Center. METHODS: A prospective study was conducted in the "Servicio de Urgencias de Atención Primaria" in Salamanca, Spain. Patients with clinical signs of respiratory infection and at least one point in the National Early Warning Score were recruited. Fever-7 mRNAs were profiled on a Nanostring nCounter® SPRINT instrument from blood collected upon patient enrolment. Viral diagnosis was performed on nasopharyngeal aspirates (NPAs) using the Biofire-RP2 panel. RESULTS: A respiratory virus was detected in the NPAs of 66 of the 100 patients enrolled. Median National Early Warning Score was 7 in the group with no virus detected and 6.5 in the group with a respiratory viral infection (P > .05). The Fever-7 score yielded an overall AUC of 0.81 to predict a positive viral syndromic test. The optimal operating point for the Fever-7 score yielded a sensitivity of 82% with a specificity of 71%. Multivariate analysis showed that Fever-7 was a robust marker of viral infection independently of age, sex, major comorbidities and disease severity at presentation (OR [CI95%], 3.73 [2.14-6.51], P < .001). CONCLUSIONS: Fever-7 is a promising host immune mRNA signature for the early identification of a respiratory viral infection in the community.

Comparison of real-time and droplet digital PCR to detect and quantify SARS-CoV-2 RNA in plasma.

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.

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients.

BACKGROUND: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. METHODS: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. RESULTS: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). CONCLUSIONS: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation.

MR- proADM to detect specific types of organ failure in infection.

BACKGROUND: Following the SEPSIS-3 consensus, detection of organ failure as assessed by the SOFA (Sequential Organ Failure Assessment) score, is mandatory to detect sepsis. Calculating SOFA outside of the Intensive Care Unit (ICU) is challenging. The alternative in this scenario, the quick SOFA, is very specific but less sensible. Biomarkers could help to detect the presence of organ failure secondary to infection either in ICU and non-ICU settings. MATERIALS AND METHODS: We evaluated the ability of four biomarkers (C-Reactive protein (CRP), lactate, mid-regional proadrenomedullin (MR-proADM) and procalcitonin (PCT)) to detect each kind of organ failure considered in the SOFA in 213 patients with infection, sepsis or septic shock, by using multivariate regression analysis and calculation of the area under the receiver operating curve (AUROC). RESULTS: In the multivariate analysis, MR-proADM was an independent predictor of five different failures (respiratory, coagulation, cardiovascular, neurological and renal). In turn, lactate predicted three (coagulation, cardiovascular and neurological) and PCT two (cardiovascular and renal). CRP did not predict any of the individual components of SOFA. The highest AUROCs were those of MR-proADM and PCT to detect cardiovascular (AUROC, CI95%): MR-proADM (0.82 [0.76-0.88]), PCT (0.81 [0.75-0.87] (P < .05) and renal failure: MR-proADM (0.87 [0.82-0.92]), PCT (0.81 [0.75-0.86]), (P < .05). None of the biomarkers tested was able to detect hepatic failure. CONCLUSIONS: In patients with infection, MR-proADM was the biomarker detecting the largest number of SOFA score components, with the exception of hepatic failure.

A DNA Vaccine Delivery Platform Based on Elastin-Like Recombinamer Nanosystems for Rift Valley Fever Virus.

This work analyzes the immunogenicity of six genetically engineered constructs based on elastin-like recombinamers (ELRs) fused to the Gn glycoprotein from Rift Valley fever virus (RVFV). Upon transfection, all constructs showed no effect on cell viability. While fusion constructs including ELR blocks containing hydrophobic amino acids (alanine or isoleucine) did not increase the expression of viral Gn in eukaryotic cells, glutamic acid- or valine-rich fusion proteins showed enhanced expression levels compared with the constructs encoding the viral antigen alone. However, in vivo DNA plasmid immunization assays determined that the more hydrophobic constructs reduced viremia levels after RVFV challenge to a higher extent than glutamic- or valine-rich encoding plasmids and were better inducers of cellular immunity as judged by in vitro restimulation experiments. Although the Gn-ELR fusion constructs did not surpass the protective efficacy of a plasmid vaccine expressing nonfused Gn, our results warrant further experiments directed to take advantage of the immunomodulatory potential of ELR biomaterials for improving vaccines against infectious diseases.

Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19.

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.

Quantification of Immune Dysregulation by Next-generation Polymerase Chain Reaction to Improve Sepsis Diagnosis in Surgical Patients.

OBJECTIVES: To quantify immunological dysfunction in surgical patients with presence/absence of sepsis using a droplet digital polymerase chain reaction (ddPCR) transcriptomic analysis. The study also aims to evaluate this approach for improving identification of sepsis in these patients. BACKGROUND: Immune dysregulation is a central event in sepsis. Quantification of the expression of immunological genes participating in the pathogenesis of sepsis could represent a new avenue to improve its diagnosis. METHODS: Expression of 6 neutrophil protease genes (MMP8, OLFM4, LCN2/NGAL, LTF, PRTN3, MPO) and also of 5 genes involved in the immunological synapse (HLA-DRA, CD40LG, CD3E, CD28, ICOS) was quantified in blood from 101 surgical patients with sepsis, 53 uninfected surgical patients, and 16 blood donors by using ddPCR. Areas under receiver operating characteristic curves (AUROC) and multivariate regression analysis were employed to test individual genes and gene ratios to identify sepsis, in comparison with procalcitonin. RESULTS: Sepsis-induced overexpression of neutrophil protease genes and depressed expression of immunological synapse genes. MMP8/HLA-DRA, LCN2/HLA-DRA outperformed procalcitonin in differentiating between patients with sepsis and surgical controls in the AUROC analysis: LCN2/HLA-DRA: 0.90 (0.85-0.96), MMP8/HLA-DRA: 0.89 (0.84-0.95), procalcitonin: 0.80 (0.73-0.88) (AUROC, confidence interval 95%), and also in the multivariate analysis: LCN2/HLA-DRA: 8.57 (2.25-32.62); MMP8/HLA-DRA: 8.03 (2.10-30.76), procalcitonin: 4.20 (1.15-15.43) [odds ratio (confidence interval 95%)]. Gene expression levels of HLA-DRA were an independent marker of hospital mortality. CONCLUSIONS: Quantifying the transcriptomic ratios MMP8/HLA-DRA, LCN2/HLA-DRA by ddPCR is a promising approach to improve sepsis diagnosis in surgical patients.

Composed endotypes to guide antibiotic discontinuation in sepsis.

Overuse of empiric antibiotic therapy in the ICU is responsible for promoting the dissemination of multidrug-resistant (MDR) bacteria. Shortened antibiotic treatment duration could contribute to palliating the emergence of MDR. Uncertainty about patient evolution is a major concern for deciding to stop antibiotics. Biomarkers could represent a complementary tool to identify those patients for whom antibiotic treatment could be safely discontinued. The biomarker most extensively studied to guide antibiotic withdrawal is procalcitonin (PCT), but its real impact on decreasing the duration of antibiotic treatment is a matter of controversy. Combining biomarkers to rule out complicated outcomes in sepsis patients could represent a better option. Some candidate biomarkers, including mid-regional proadrenomedullin, the percentage of human leukocyte antigen DR (HLA-DR)-positive monocytes, means of fluorescence intensities of HLA-DR on monocytes, interleukin-7 receptor expression levels, immunoglobulin M levels in the serum or the absence of increased proteolysis, have already demonstrated the potential to exclude the risk of progression to septic shock, nosocomial infections, and mortality when tested along the sepsis course. Other promising biomarkers to rule out complicated outcomes are neutrophil protease activity, the adaptive/coagulopathic signatures identified by whole transcriptome analysis by Sweeney et al., and the SRS1 signature identified by Davenport et al. In conclusion, there are a number of promising biomarkers involved in proteolytic, vascular, immunological, and coagulation alterations that could be useful to build composed endotypes to predict uncomplicated outcomes in sepsis. These endotypes could help to identify patients deserving the discontinuation of antibiotics.

Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters.

OBJECTIVES: To find and validate generalizable sepsis subtypes using data-driven clustering. DESIGN: We used advanced informatics techniques to pool data from 14 bacterial sepsis transcriptomic datasets from eight different countries (n = 700). SETTING: Retrospective analysis. SUBJECTS: Persons admitted to the hospital with bacterial sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A unified clustering analysis across 14 discovery datasets revealed three subtypes, which, based on functional analysis, we termed "Inflammopathic, Adaptive, and Coagulopathic." We then validated these subtypes in nine independent datasets from five different countries (n = 600). In both discovery and validation data, the Adaptive subtype is associated with a lower clinical severity and lower mortality rate, and the Coagulopathic subtype is associated with higher mortality and clinical coagulopathy. Further, these clusters are statistically associated with clusters derived by others in independent single sepsis cohorts. CONCLUSIONS: The three sepsis subtypes may represent a unifying framework for understanding the molecular heterogeneity of the sepsis syndrome. Further study could potentially enable a precision medicine approach of matching novel immunomodulatory therapies with septic patients most likely to benefit.

Postbooster Antibodies from Humans as Source of Diphtheria Antitoxin.

Diphtheria antitoxin for therapeutic use is in limited supply. A potential source might be affinity-purified antibodies originally derived from plasma of adults who received a booster dose of a vaccine containing diphtheria toxoid. These antibodies might be useful for treating even severe cases of diphtheria.

The original sins of clinical trials with intravenous immunoglobulins in sepsis.

Intravenous immunoglobulins (IVIGs) have not yet demonstrated robust evidence in the benefit for treatment of sepsis. In spite of multiple clinical trials performed with IVIG in sepsis, it remains an experimental therapy for this severe condition. Nonetheless, these trials do not address a number of potential confounding factors, concerning both the patient and the IVIG preparations, which could greatly affect the final result. To name a few, endogenous levels of immunoglobulin isotypes and subclasses are not assessed prior to treatment. The presence/absence of patient antibodies against the microorganism(s) causing sepsis is not evaluated. The accuracy of antibiotic prescription is not included as an adjusting variable. The degree of patient immunosuppression (previous or induced by sepsis) is not documented. In turn, the concentration and antimicrobial specificities of the antibodies contained in the batches of IVIG are not assessed. Neither the pharmacokinetics of IVIG nor its potential immunomodulatory effects are evaluated. In addition, the concept of 'window of opportunity' for IVIG administration following diagnosis of sepsis is not considered. In conclusion, addressing these factors could help to individualise treatment with IVIG for sepsis, which could enhance the opportunities of this drug to show benefits in terms of survival in this severe condition.