Expression of Surfactant Protein D Distinguishes Severe Pandemic Influenza A(H1N1) from Coronavirus Disease 2019

Multicentric investigations of the role in the disease severity of accelerated phospholipid changes in COVID-19 patient airway

CONTEXT

The changes in host membrane phospholipids are crucial in airway infection pathogenesis. Phospholipase A2 hydrolyzes host cell membranes, producing lyso-phospholipids and free fatty acids, including arachidonic acid (AA), which contributes significantly to lung inflammation.

AIM

Follow these changes and their evolution from day 1, day 3 to day 7 in airway aspirates of 89 patients with COVID-19-associated acute respiratory distress syndrome and examine whether they correlate with the severity of the disease. The patients were recruited in three French intensive care units. The analysis was conducted from admission to the intensive care unit until the end of the first week of mechanical ventilation.

RESULTS

In the airway aspirates, we found significant increases in the levels of host cell phospholipids, including phosphatidyl-serine and phosphatidyl-ethanolamine, and their corresponding lyso-phospholipids. This was accompanied by increased levels of AA and its inflammatory metabolite prostaglandin E2 (PGE2). Additionally, enhanced levels of ceramides, sphingomyelin, and free cholesterol were observed in these aspirates. These lipids are known to be involved in cell death and/or apoptosis, whereas free cholesterol plays a role in virus entry and replication in host cells. However, there were no significant changes in the levels of dipalmitoyl-phosphatidylcholine, the major surfactant phospholipid. A correlation analysis revealed an association between mortality risk and levels of AA and PGE2, as well as host cell phospholipids.

CONCLUSION

Our findings indicate a correlation between heightened cellular phospholipid modifications and variations in AA and PGE2 with the severity of the disease in patients. Nevertheless, there is no indication of surfactant alteration in the initial phases of the illness.

Surfactant protein D (SP-D) as a biomarker of SARS-CoV-2 infection

Background

Surfactant protein-D (SP-D) is a lung-resident protein that has emerged as a potential biomarker for COVID-19. Previous investigations on acute respiratory distress syndrome patients demonstrated a significant increment of SP-D serum levels in pathological conditions. Since SP-D is not physiologically permeable to alveoli-capillary membrane and poorly expressed by other tissues, this enhancement is likely due to an impairment of the pulmonary barrier caused by prolonged inflammation.

Methods

A retrospective study on a relatively large cohort of patients of Hospital Pio XI of Desio was conducted to assess differences of the hematic SP-D concentrations among COVID-19 patients and healthy donors and if SP-D levels resulted a risk factor for disease severity and mortality.

Results

The first analysis, using an ANOVA-model, showed a significant difference in the mean of log SP-D levels between COVID-19 patients and healthy donors. Significant variations were also found between dead vs survived patients. Results confirm that SP-D concentrations were significantly higher for both hospitalized COVID-19 and dead patients, with threshold values of 150 and 250 ng/mL, respectively. Further analysis conducted with Logistic Mixed models, highlighted that higher SP-D levels at admission and increasing differences among follow-up and admission values resulted the strongest significant risk factors of mortality (model predictive accuracy, AUC = 0.844).

Conclusions

The results indicate that SP-D can be a predictive marker of COVID-19 disease and its outcome. Considering its prognostic value in terms of mortality, the early detection of SP-D levels and its follow-up in hospitalized patients should be considered to direct the therapeutic intervention.

Dynamic Monitoring of Serum Protein in Acute Respiratory Distress Syndrome Based on Artificial Neural Network

Acute respiratory distress syndrome (ARDS) is one of the more serious diseases in human lung disease. Reducing its incidence rate is an important task in current clinical research. Dynamic monitoring of serum protein in patients will help to achieve the early diagnosis and treatment of ARDS. In this study, a protein monitoring model based on artificial neural network is proposed. First, surface enhanced laser desorption ionization time-of-flight mass spectrometry is used for protein detection, and then BP neural network is used for protein classification and content analysis. In the experimental analysis, serum samples from patients with acute respiratory distress syndrome in our hospital from November 2020 to August 2021 were selected for experimental testing. The experimental results show that the serum protein monitoring model based on BP neural network has low error and high convergence ability and can monitor individual protein in protein monitoring, and the area under the ROC curve in diagnostic performance reaches 0.854. The above results show that the artificial neural network has a good effect on the dynamic monitoring of serum protein in acute respiratory distress syndrome, and the diagnostic performance evaluation can reach 0.854, which has the ability to significantly improve the clinical diagnosis and treatment of acute respiratory distress syndrome.

Hospital trajectories and early predictors of clinical outcomes differ between SARS-CoV-2 and influenza pneumonia

BACKGROUND

A comparison of pneumonias due to SARS-CoV-2 and influenza, in terms of clinical course and predictors of outcomes, might inform prognosis and resource management. We aimed to compare clinical course and outcome predictors in SARS-CoV-2 and influenza pneumonia using multi-state modelling and supervised machine learning on clinical data among hospitalised patients.

METHODS

This multicenter retrospective cohort study of patients hospitalised with SARS-CoV-2 (March-December 2020) or influenza (Jan 2015-March 2020) pneumonia had the composite of hospital mortality and hospice discharge as the primary outcome. Multi-state models compared differences in oxygenation/ventilatory utilisation between pneumonias longitudinally throughout hospitalisation. Differences in predictors of outcome were modelled using supervised machine learning classifiers.

FINDINGS

Among 2,529 hospitalisations with SARS-CoV-2 and 2,256 with influenza pneumonia, the primary outcome occurred in 21% and 9%, respectively. Multi-state models differentiated oxygen requirement progression between viruses, with SARS-CoV-2 manifesting rapidly-escalating early hypoxemia. Highly contributory classifier variables for the primary outcome differed substantially between viruses.

INTERPRETATION

SARS-CoV-2 and influenza pneumonia differ in presentation, hospital course, and outcome predictors. These pathogen-specific differential responses in viral pneumonias suggest distinct management approaches should be investigated.

FUNDING

This project was supported by NIH/NCATS UL1 TR002345, NIH/NCATS KL2 TR002346 (PGL), the Doris Duke Charitable Foundation grant 2015215 (PGL), NIH/NHLBI R35 HL140026 (CSC), and a Big Ideas Award from the BJC HealthCare and Washington University School of Medicine Healthcare Innovation Lab and NIH/NIGMS R35 GM142992 (PS).

SP-A binding to the SARS-CoV-2 spike protein using hybrid quantum and classical in silico modeling and molecular pruning by Quantum Approximate Optimization Algorithm (QAOA) Based MaxCut with ZDOCK

The pulmonary surfactant protein A (SP-A) is a constitutively expressed immune-protective collagenous lectin (collectin) in the lung. It binds to the cell membrane of immune cells and opsonizes infectious agents such as bacteria, fungi, and viruses through glycoprotein binding. SARS-CoV-2 enters airway epithelial cells by ligating the Angiotensin Converting Enzyme 2 (ACE2) receptor on the cell surface using its Spike glycoprotein (S protein). We hypothesized that SP-A binds to the SARS-CoV-2 S protein and this binding interferes with ACE2 ligation. To study this hypothesis, we used a hybrid quantum and classical in silico modeling technique that utilized protein graph pruning. This graph pruning technique determines the best binding sites between amino acid chains by utilizing the Quantum Approximate Optimization Algorithm (QAOA)-based MaxCut (QAOA-MaxCut) program on a Near Intermediate Scale Quantum (NISQ) device. In this, the angles between every neighboring three atoms were Fourier-transformed into microwave frequencies and sent to a quantum chip that identified the chemically irrelevant atoms to eliminate based on their chemical topology. We confirmed that the remaining residues contained all the potential binding sites in the molecules by the Universal Protein Resource (UniProt) database. QAOA-MaxCut was compared with GROMACS with T-REMD using AMBER, OPLS, and CHARMM force fields to determine the differences in preparing a protein structure docking, as well as with Goemans-Williamson, the best classical algorithm for MaxCut. The relative binding affinity of potential interactions between the pruned protein chain residues of SP-A and SARS-CoV-2 S proteins was assessed by the ZDOCK program. Our data indicate that SP-A could ligate the S protein with a similar affinity to the ACE2-Spike binding. Interestingly, however, the results suggest that the most tightly-bound SP-A binding site is localized to the S2 chain, in the fusion region of the SARS-CoV-2 S protein, that is responsible for cell entry Based on these findings we speculate that SP-A may not directly compete with ACE2 for the binding site on the S protein, but interferes with viral entry to the cell by hindering necessary conformational changes or the fusion process.

The Tip of the Spear: Emergency Medicine and Missouri's Response to the COVID-19 Pandemic

The COVID-19 pandemic provided the specialty of emergency medicine the opportunity to showcase what many knew all along: emergency physicians (EP) are well suited to deal with the unknown and can quickly adapt even with incomplete or limited information and resources. Emergency physicians in Missouri served in integral positions locally, nationally and internationally. Missouri EPs published numerous manuscripts on topics from basic science to clinical care. Device innovation also occurred with the development of protective devices for health care workers. As we approach the three-year mark of the COVID-19 pandemic, the burden of clinical care still weighs heavily on EPs. Each wave of the pandemic has brought challenges and spurred EPs to innovate in new ways. As Michigan EP Brian Zink, MD once said "Anyone, Anything, Anytime". These words correctly sum up emergency medicine. When others hesitated to care for COVID-19 patients, EPs stepped up despite uncertainty and risks to their own health. Emergency medicine has led the way and continues to innovate and push the envelope of emergency care.

Comparing the Cytokine Storms of COVID-19 and Pandemic Influenza

Emerging respiratory viruses are major health threats due to their potential to cause massive outbreaks. Over the past 2 years, the coronavirus disease 2019 (COVID-19) pandemic has caused millions of cases of severe infection and deaths worldwide. Although natural and vaccine-induced protective immune mechanisms against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been increasingly identified, the factors that determine morbimortality are less clear. Comparing the immune signatures of COVID-19 and other severe respiratory infections such as the pandemic influenza might help dissipate current controversies about the origin of their severe manifestations. As such, identifying homologies in the immunopathology of both diseases could provide targets for immunotherapy directed to block shared pathogenic mechanisms. Meanwhile, finding unique characteristics that differentiate each infection could shed light on specific immune alterations exploitable for diagnostic and individualized therapeutics for each case. In this study, we summarize immunopathological aspects of COVID-19 and pandemic influenza from the perspective of cytokine storms as the driving force underlying morbidity. Thereby, we analyze similarities and differences in the cytokine profiles of both infections, aiming to bring forward those molecules more attractive for translational medicine and drug development.

Mechanistic Understanding of Lung Inflammation: Recent Advances and Emerging Techniques

Acute respiratory distress syndrome (ARDS) is a life-threatening lung injury characterized by an acute inflammatory response in the lung parenchyma. Hence, it is considered as the most appropriate clinical syndrome to study pathogenic mechanisms of lung inflammation. ARDS is associated with increased morbidity and mortality in the intensive care unit (ICU), while no effective pharmacological treatment exists. It is very important therefore to fully characterize the underlying pathobiology and the related mechanisms, in order to develop novel therapeutic approaches. In vivo and in vitro models are important pre-clinical tools in biological and medical research in the mechanistic and pathological understanding of the majority of diseases. In this review, we will present data from selected experimental models of lung injury/acute lung inflammation, which have been based on clinical disorders that can lead to the development of ARDS and related inflammatory lung processes in humans, including ventilation-induced lung injury (VILI), sepsis, ischemia/reperfusion, smoke, acid aspiration, radiation, transfusion-related acute lung injury (TRALI), influenza, Streptococcus (S.) pneumoniae and coronaviruses infection. Data from the corresponding clinical conditions will also be presented. The mechanisms related to lung inflammation that will be covered are oxidative stress, neutrophil extracellular traps, mitogen-activated protein kinase (MAPK) pathways, surfactant, and water and ion channels. Finally, we will present a brief overview of emerging techniques in the field of omics research that have been applied to ARDS research, encompassing genomics, transcriptomics, proteomics, and metabolomics, which may recognize factors to help stratify ICU patients at risk, predict their prognosis, and possibly, serve as more specific therapeutic targets.

Differential Leukocyte Expression of IFITM1 and IFITM3 in Patients with Severe Pandemic Influenza A(H1N1) and COVID-19

Interferon-induced transmembrane (IFITM) proteins mediate protection against enveloped viruses by blocking membrane fusion at endosomes. IFITM1 and IFITM3 are crucial for protection against influenza, and various single nucleotide polymorphisms altering their function have been linked to disease susceptibility. However, bulk IFITM1 and IFITM3 mRNA expression dynamics and their correlation with clinical outcomes have not been extensively addressed in patients with respiratory infections. In this study, we evaluated the expression of IFITM1 and IFITM3 in peripheral leukocytes from healthy controls and individuals with severe pandemic influenza A(H1N1) or coronavirus disease 2019 (COVID-19). Comparisons between participants grouped according to their clinical characteristics, underlying disease, and outcomes showed that the downregulation of IFITM1 was a distinctive characteristic of severe pandemic influenza A(H1N1) that correlated with outcomes, including mortality. Conversely, increased IFITM3 expression was a common feature of severe pandemic influenza A(H1N1) and COVID-19. Using a high-dose murine model of infection, we confirmed not only the downregulation of IFITM1 but also of IFITM3 in the lungs of mice with severe influenza, as opposed to humans. Analyses in the comparative cohort also indicate the possible participation of IFITM3 in COVID-19. Our results add to the evidence supporting a protective function of IFITM proteins against viral respiratory infections in humans.

Surfactant protein D: A useful biomarker for distinguishing COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases

Introduction

Computed tomography is useful for the diagnosis of coronavirus disease (COVID‐19) pneumonia. However, many types of interstitial lung diseases and even bacterial pneumonia can show abnormal chest shadows that are indistinguishable from those observed in COVID‐19 pneumonia. Thus, it is necessary to identify useful biomarkers that can efficiently distinguish COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases. Herein, we investigated the usefulness of serum Krebs von den Lungen 6 (KL‐6) and surfactant protein D (SP‐D) for identifying patients with COVID‐19 pneumonia among patients with abnormal chest shadows consistent with COVID‐19 pneumonia.

Method

This was a retrospective cohort study of consecutive patients who underwent evaluation of serum KL‐6 and SP‐D at a single center from February 2019 to December 2020. A total of 54 patients with COVID‐19 pneumonia and 65 patients with COVID‐19 pneumonia‐like diseases were enrolled in this study from the source population. Serum KL‐6 and SP‐D levels in both groups were analyzed.

Result

The serum levels of KL‐6 and SP‐D in patients with COVID‐19 pneumonia were significantly lower than those in patients with COVID‐19 pneumonia‐like disease (median [interquartile range]: 208.5 [157.5–368.5] U/ml vs. 430 [284.5–768.5] U/ml, p < 0.0001 and 24.7 [8.6–51.0] ng/ml vs. 141 [63.7–243.5] ng/ml, p < 0.0001, respectively). According to receiver operating characteristic (ROC) analysis, the areas under the ROC curves (95% confidence intervals) of serum KL‐6 and SP‐D levels for distinguishing COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases were 0.761 (0.675–0.847) and 0.874 (0.812–0.936), respectively. The area under the ROC curve of serum SP‐D was significantly larger than that of serum KL‐6 (p = 0.0213), suggesting that serum SP‐D can more efficiently distinguish COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases.

Conclusion

Serum SP‐D is a promising biomarker for distinguishing COVID‐19 pneumonia from COVID‐19 pneumonia‐like diseases. Serum SP‐D can be useful for the management of patients with abnormal chest shadow mimicking COVID‐19 pneumonia.

Endothelial Dysfunction through Oxidatively Generated Epigenetic Mark in Respiratory Viral Infections

The bronchial vascular endothelial network plays important roles in pulmonary pathology during respiratory viral infections, including respiratory syncytial virus (RSV), influenza A(H1N1) and importantly SARS-Cov-2. All of these infections can be severe and even lethal in patients with underlying risk factors.A major obstacle in disease prevention is the lack of appropriate efficacious vaccine(s) due to continuous changes in the encoding capacity of the viral genome, exuberant responsiveness of the host immune system and lack of effective antiviral drugs. Current management of these severe respiratory viral infections is limited to supportive clinical care. The primary cause of morbidity and mortality is respiratory failure, partially due to endothelial pulmonary complications, including edema. The latter is induced by the loss of alveolar epithelium integrity and by pathological changes in the endothelial vascular network that regulates blood flow, blood fluidity, exchange of fluids, electrolytes, various macromolecules and responses to signals triggered by oxygenation, and controls trafficking of leukocyte immune cells. This overview outlines the latest understanding of the implications of pulmonary vascular endothelium involvement in respiratory distress syndrome secondary to viral infections. In addition, the roles of infection-induced cytokines, growth factors, and epigenetic reprogramming in endothelial permeability, as well as emerging treatment options to decrease disease burden, are discussed.

The Role of Pulmonary Surfactants in the Treatment of Acute Respiratory Distress Syndrome in COVID-19

Lung alveolar type-II (AT-II) cells produce pulmonary surfactant (PS), consisting of proteins and lipids. The lipids in PS are primarily responsible for reducing the air-fluid surface tension inside the alveoli of the lungs and to prevent atelectasis. The proteins are of two types: hydrophilic and hydrophobic. Hydrophilic surfactants are primarily responsible for opsonisation, thereby protecting the lungs from microbial and environmental contaminants. Hydrophobic surfactants are primarily responsible for respiratory function. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) enters the lungs through ACE-2 receptors on lungs and replicates in AT-II cells leading to the etiology of Coronavirus disease - 2019 (COVID-19). The SARS-CoV-2 virus damages the AT-II cells and results in decreased production of PS. The clinical symptoms of acute respiratory distress syndrome (ARDS) in COVID-19 patients are like those of neonatal respiratory distress syndrome (NRDS). The PS treatment is first-line treatment option for NRDS and found to be well tolerated in ARDS patients with inconclusive efficacy. Over the past 70°years, a lot of research is underway to produce natural/synthetic PS and developing systems for delivering PS directly to the lungs, in addition to finding the association between PS levels and respiratory illnesses. In the present COVID-19 pandemic situation, the scientific community all over the world is searching for the effective therapeutic options to improve the clinical outcomes. With a strong scientific and evidence-based background on role of PS in lung homeostasis and infection, few clinical trials were initiated to evaluate the functions of PS in COVID-19. Here, we connect the data on PS with reference to pulmonary physiology and infection with its possible therapeutic benefit in COVID-19 patients.