Proteomic determinants of disease, mortality and sequelae in COVID-19 patients requiring invasive mechanical ventilation

Introduction: The molecular mechanisms linked to the pathology of severe COVID-19 and its outcomes are poorly described. Aim(s): To analyze the proteomic profile of bronchial aspirates (BAS) samples from critically ill COVID-19 patients in order to identify factors associated with the disease and its prognosis. Method(s): Multicenter study including 74 critically ill non-COVID-19 and COVID-19 patients. BAS was obtained by bronchoaspiration after invasive mechanical ventilation (IMV) initiation. Proximity extension assay (PEA) technology was used for proteomic profiling. Random forest (RF) statistical models were used to predict the variable importance. Result(s): After adjusting for confounding factors, CST5, NADK, SRPK2 and TGF-alpha showed differences between COVID-19 and non-COVID-19 patients. Reduced levels of ENTPD2 and PTN were observed in non-survivors, even after adjustment. AGR2, NQO2, IL-1alpha, OSM and TRAIL, were the top five strongest predictors for ICU mortality and were used to build a prediction model. PTN (HR=4.00) ENTPD2 (HR=2.14) and the prediction model (HR=6.25) were associated with higher risk of death. In survivors, FCRL1, NTF4 and THOP1 correlated with lung function (DLCO levels) 3-months after hospital discharge. Similar findings were observed for Flt3L and THOP1 and radiological features (TSS). The proteins identified are expressed in immune and non-immune lung cells. A poor control of viral infectivity and an inappropriate reparative response seems to be linked to the disease and fatal outcomes, respectively. Conclusion(s): In critically ill COVID-19 patients, specific proteomic profiles are associated with the pathology, mortality and lung sequelae.

Proteomic profiling of severe lung diffusion impairment in the recovery stage of COVID-19-induced ARDS

Background: Around 80% of patients who developed COVID-19-driven ARDS present lung ailment. There is a lack of knowledge of the mechanisms that mediate the pulmonary outcomes. Aim(s): To characterize the factors linked to diffusion impairment in survivors of severe COVID-19. Method(s): Prospective cohort study including 87 COVID-19-induced ARDS survivors. A complete pulmonary evaluation was performed 3 months after hospital discharge. 364 proteins were quantified using the proximity extension assay (PEA). Partial least square-discriminant analysis (PLS-DA) and random forest (RF) were used for multivariable analyses. Result(s): Moderate to severe diffusion impairment (DLCO<60% predicted) was observed in the 30% of the cohort. 15 proteins were differentially detected [false discovery rate (FDR)<0.05] in the univariate analysis. Pleiotrophin showed the highest differences (fold change=2.22 and FDR=0.001). In continuous analysis, proteins were inversely and independently associated with DLCO, and in some cases showed a robust dose-response relationship. PLS-DA and RF identified proteomic profiles related to the severity of diffusion capacity. Clusters identified were enriched in mediators of cell proliferation and differentiation, tissue remodeling, angiogenesis, coagulation, inflammation, immune response and fibrosis. Proteins are expressed in immune and non-immune lung cells. Conclusion(s): In survivors of COVID-19-driven ARDS, lung dysfunction is linked to plasma factors involved in injury and repair mechanisms. The host proteomic profile provides a novel understanding of post-acute sequelae and may be source of therapeutic strategies and biomarkers.

Risk models for predicting in-hospital mortality from COVID-19 pneumonia in the elderly

Objective. To compare the prognostic value of 3 severity scales: the Pneumonia Severity Index (PSI), the CURB-65 pneumonia severity score, and the Severity Community-Acquired Pneumonia (SCAP) score. To build a new predictive model for in-hospital mortality in patients over the age of 75 years admitted with pneumonia due to the coronavirus disease 2019 (COVID-19). Methods. Retrospective study of patients older than 75 years admitted from the emergency department for COVID-19 pneumonia between March 12 and April 27, 2020. We recorded demographic (age, sex, living in a care facility or not), clinical (symptoms, comorbidities, Charlson Comorbidity Index [CCI]), and analytical (serum biochemistry, blood gases, blood count, and coagulation factors) variables. A risk model was constructed, and the ability of the 3 scales to predict all-cause in-hospital mortality was compared. Results. We included 186 patients with a median age of 85 years (interquartile range, 80-89 years);44.1% were men. Mortality was 47.3%. The areas under the receiver operating characteristic curves (AUCs) were as follows for each tool: PSI, 0.74 (95% CI, 0.64-0.82);CURB-65 score, 0.71 (95% CI, 0.62-0.79);and SCAP score, 0.72 (95% CI, 0.63-0.81). Risk factors included in the model were the presence or absence of symptoms (cough, dyspnea), the CCI, and analytical findings (aspartate aminotransferase, potassium, urea, and lactate dehydrogenase. The AUC for the model was 0.81 (95% CI, 0.73-0.88). Conclusions. This study shows that the predictive power of the PSI for mortality is moderate and perceptibly higher than the CURB-65 and SCAP scores. We propose a new predictive model for mortality that offers significantly better performance than any of the 3 scales compared. However, our model must undergo external validation.

Circulating micrornas as biomarkers of COVID-19 severity

RATIONALE: The identification of minimally invasive and easily-accessible biomarkers to support the management of coronavirus disease 2019 (COVID-19) in hospitalized patients constitutes a hot topic in clinical research. MicroRNAs (miRNAs) have been proposed as clinical indicators to assist in medical decision-making. Here, we aimed to examine the circulating miRNA profile of hospitalized COVID-19 patients and to evaluate its potential as a source of biomarkers for the management of the disease. METHODS: Observational, prospective and multicenter study which included 84 patients with a positive nasopharyngeal swab PCR test for SARS-CoV-2, recruited during the first pandemic wave in Spain (March-May 2020). Patients were stratified according to disease severity: hospitalized patients admitted to the clinical wards without requiring critical care (n = 47) and hospitalized patients admitted to the ICU (n = 37). An additional study considering ICU non-survivors (n=17) and survivors (n = 20) was performed. Expression profiling of 41 miRNAs was performed in plasma samples using RT-qPCR. The panel included miRNAs associated with: i) immune/inflammatory response;ii) lung damage;iii) respiratory viral infections;iv) myocardial damage;v) coagulation. Quality control was performed using spike-ins and hemolysis tests. Predictive models were constructed using a variable selection process based on LASSO regression. RESULTS: Ten circulating miRNAs were deregulated in ICU compared to ward patients. LASSO analysis identified a signature of three miRNAs that displayed an optimal discrimination ability to distinguish between ICU and ward patients (AUC = 0.88) (Figure 1A). Among ICU patients, six miRNAs were downregulated when comparing nonsurvivors to survivors. A signature based on two miRNAs was found to be a relevant predictor of mortality during ICU stay (AUC = 0.84) (Figure 1B). The discrimination potential of the miRNA signature was higher than the observed for clinical laboratory parameters such as leukocyte counts (including neutrophil count, lymphocyte count and the neutrophil-tolymphocyte ratio), CRP or D-dimer (maximum AUC for these variables = 0.76). CONCLUSIONS: The severity of COVID-19 impacts on the circulating miRNA profile. The results suggest the potential usefulness of the circulating miRNA signature for the management of the disease over contemporaneous tests, at least in ICU patients.

Pulmonary function and radiological features in survivors of critical COVID-19: A 3-month prospective cohort

Background More than 20% of hospitalized patients with coronavirus disease 2019 (COVID-19) develop acute respiratory distress syndrome (ARDS) requiring intensive care unit (ICU) admission. The long-term respiratory sequelae in ICU survivors remain unclear. Aim: To perform a detailed characterization of the long-term pulmonary sequelae in critical COVID-19 survivors. Study Design and Methods Consecutive patients with COVID-19 requiring ICU admission were recruited and evaluated 3 months after hospitalization discharge. The follow-up comprised symptom and quality of life, anxiety and depression questionnaires, pulmonary function tests, exercise test (6-minute walking test (6MWT)) and chest computed tomography (CT). Results 125 ICU patients with ARDS secondary to COVID-19 were recruited between March and June 2020. At the 3-month follow-up, 62 patients were available for pulmonary evaluation. The most frequent symptoms were dyspnea (46.7%), and cough (34.4%). Eighty-two percent of patients showed a lung diffusing capacity of less than 80%. The mean distance in the 6MWT was 401±93 mts. CT scans were abnormal in 70.2% of patients, showing reticular lesions in 49.1% and fibrotic patterns in 21.1%. Patients with more severe alterations on chest CT had worse pulmonary function and presented more degrees of desaturation in the 6MWT. Factors associated with the severity of lung damage on chest CT were age and prone position during the ICU stay. Interpretation Pulmonary structural abnormalities and functional impairment are highly prevalent in surviving ICU patients with ARDS secondary to COVID-19 3 months after hospital discharge. Pulmonary evaluation should be considered for all critical COVID-19 survivors 3 months post discharge.