Case study observational research: inflammatory cytokines in the bronchial epithelial lining fluid of COVID-19 patients with acute hypoxemic respiratory failure

BACKGROUND

In this study, the concentrations of inflammatory cytokines were measured in the bronchial epithelial lining fluid (ELF) and plasma in patients with acute hypoxemic respiratory failure (AHRF) secondary to severe coronavirus disease 2019 (COVID-19).

METHODS

We comprehensively analyzed the concentrations of 25 cytokines in the ELF and plasma of 27 COVID-19 AHRF patients. ELF was collected using the bronchial microsampling method through an endotracheal tube just after patients were intubated for mechanical ventilation.

RESULTS

Compared with those in healthy volunteers, the concentrations of interleukin (IL)-6 (median 27.6 pmol/L), IL-8 (1045.1 pmol/L), IL-17A (0.8 pmol/L), IL-25 (1.5 pmol/L), and IL-31 (42.3 pmol/L) were significantly greater in the ELF of COVID-19 patients than in that of volunteers. The concentrations of MCP-1 and MIP-1β were significantly greater in the plasma of COVID-19 patients than in that of volunteers. The ELF/plasma ratio of IL-8 was the highest among the 25 cytokines, with a median of 737, and the ELF/plasma ratio of IL-6 (median: 218), IL-1β (202), IL-31 (169), MCP-1 (81), MIP-1β (55), and TNF-α (47) were lower.

CONCLUSIONS

The ELF concentrations of IL-6, IL-8, IL-17A, IL-25, and IL-31 were significantly increased in COVID-19 patients. Although high levels of MIP-1 and MIP-1β were also detected in the blood samples collected simultaneously with the ELF samples, the results indicated that lung inflammation was highly compartmentalized. Our study demonstrated that a comprehensive analysis of cytokines in the ELF is a feasible approach for understanding lung inflammation and systemic interactions in patients with severe pneumonia.

Application of Proteomics in Sarcoidosis

Sarcoidosis is a multisystem disease with heterogeneity in manifestations and outcomes. System-level studies leveraging "omics" technologies are expected to define mechanisms contributing to sarcoidosis heterogeneous manifestations and course. With improvements in mass spectrometry (MS) and bioinformatics, it is possible to study protein abundance for a large number of proteins simultaneously. Contemporary fast-scanning MS enables the acquisition of spectral data for deep coverage of the proteins with data-dependent or data-independent acquisition MS modes. Studies leveraging MS-based proteomics in sarcoidosis have characterized BAL fluid (BALF), alveolar macrophages, plasma, and exosomes. These studies identified several differentially expressed proteins, including protocadherin-2 precursor, annexin A2, pulmonary surfactant A2, complement factors C3, vitamin-D-binding protein, cystatin B, and amyloid P, comparing subjects with sarcoidosis with control subjects. Other studies identified ceruloplasmin, complement factors B, C3, and 1, and others with differential abundance in sarcoidosis compared with other interstitial lung diseases. Using quantitative proteomics, most recent studies found differences in PI3K/Akt/mTOR, MAP kinase, pluripotency-associated transcriptional factor, and hypoxia response pathways. Other studies identified increased clathrin-mediated endocytosis and Fcγ receptor-mediated phagocytosis pathways in sarcoidosis alveolar macrophages. Although studies in mixed BAL and blood cells or plasma are limited, some of the changes in lung compartment are detected in the blood cells and plasma. We review proteomics for sarcoidosis with a focus on the existing MS data acquisition strategies, bioinformatics for spectral data analysis to infer protein identity and quantity, unique aspects about biospecimen collection and processing for lung-related proteomics, and proteomics studies conducted to date in sarcoidosis.

Serum Krebs von den Lungen-6 level in the disease progression and treatment of Mycobacterium avium complex lung disease

BACKGROUND AND OBJECTIVE

The lack of useful biomarkers reflecting the disease state limits the management of Mycobacterium avium complex lung disease (MAC-LD). We clarified the associations between serum KL-6 level, disease progression and treatment response.

METHODS

Resected lung tissues from MAC-LD patients were immunostained for KL-6. We compared serum KL-6 levels between MAC-LD and healthy control or bronchiectasis patients without nontuberculous mycobacterial lung disease (NTM-LD). Serum KL-6 level was assessed in a prospective observational study at Keio University Hospital between May 2012 and May 2016. We investigated associations between serum KL-6 level and disease progression and treatment response in patients untreated for MAC-LD on registration (n = 187).

RESULTS

The KL-6⁺ alveolar type 2 cell population in the lung and serum KL-6 level were significantly higher in MAC-LD patients than in controls. Serum KL-6 level in bronchiectasis patients without NTM-LD showed no significant increase. Of the 187 patients who did not receive treatment on registration, 53 experienced disease progression requiring treatment. Multivariable Cox analysis revealed that the serum KL-6 level (aHR: 1.18, P = 0.005), positive acid-fast bacilli smear (aHR: 2.64, P = 0.001) and cavitary lesions (aHR: 3.01, P < 0.001) were significantly associated with disease progression. The change in serum KL-6 (ΔKL-6) was significantly higher in the disease progression group; it decreased post-treatment, reflecting the negative sputum culture conversion.

CONCLUSION

Serum KL-6 level is associated with disease progression and treatment response. Longitudinal assessment combined with AFB smear status and presence of cavitary lesions may aid MAC-LD management.

What did we learn from multiple omics studies in asthma?

More than a decade has passed since the finalization of the Human Genome Project. Omics technologies made a huge leap from trendy and very expensive to routinely executed and relatively cheap assays. Simultaneously, we understood that omics is not a panacea for every problem in the area of human health and personalized medicine. Whilst in some areas of research omics showed immediate results, in other fields, including asthma, it only allowed us to identify the incredibly complicated molecular processes. Along with their possibilities, omics technologies also bring many issues connected to sample collection, analyses and interpretation. It is often impossible to separate the intrinsic imperfection of omics from asthma heterogeneity. Still, many insights and directions from applied omics were acquired-presumable phenotypic clusters of patients, plausible biomarkers and potential pathways involved. Omics technologies develop rapidly, bringing improvements also to asthma research. These improvements, together with our growing understanding of asthma subphenotypes and underlying cellular processes, will likely play a role in asthma management strategies.

Absorption of Nasal and Bronchial Fluids: Precision Sampling of the Human Respiratory Mucosa and Laboratory Processing of Samples

The methods of nasal absorption (NA) and bronchial absorption (BA) use synthetic absorptive matrices (SAM) to absorb the mucosal lining fluid (MLF) of the human respiratory tract. NA is a non-invasive technique which absorbs fluid from the inferior turbinate, and causes minimal discomfort. NA has yielded reproducible results with the ability to frequently repeat sampling of the upper airway.

By comparison, alternative methods of sampling the respiratory mucosa, such as nasopharyngeal aspiration (NPA) and conventional swabbing, are more invasive and may result in greater data variability. Other methods have limitations, for instance, biopsies and bronchial procedures are invasive, sputum contains many dead and dying cells and requires liquefaction, exhaled breath condensate (EBC) contains water and saliva, and lavage samples are dilute and variable.

BA can be performed through the working channel of a bronchoscope in clinic. Sampling is well tolerated and can be conducted at multiple sites in the airway. BA results in MLF samples being less dilute than bronchoalveolar lavage (BAL) samples.

This article demonstrates the techniques of NA and BA, as well as the laboratory processing of the resulting samples, which can be tailored to the desired downstream biomarker being measured. These absorption techniques are useful alternatives to the conventional sampling techniques used in clinical respiratory research.

Napsin A levels in epithelial lining fluid as a diagnostic biomarker of primary lung adenocarcinoma

BACKGROUND

It is crucial to develop novel diagnostic approaches for determining if peripheral lung nodules are malignant, as such nodules are frequently detected due to the increased use of chest computed tomography scans. To this end, we evaluated levels of napsin A in epithelial lining fluid (ELF), since napsin A has been reported to be an immunohistochemical biomarker for histological diagnosis of primary lung adenocarcinoma.

METHODS

In consecutive patients with indeterminate peripheral lung nodules, ELF samples were obtained using a bronchoscopic microsampling (BMS) technique. The levels of napsin A and carcinoembryonic antigen (CEA) in ELF at the nodule site were compared with those at the contralateral site. A final diagnosis of primary lung adenocarcinoma was established by surgical resection.

RESULTS

We performed BMS in 43 consecutive patients. Among patients with primary lung adenocarcinoma, the napsin A levels in ELF at the nodule site were markedly higher than those at the contralateral site, while there were no significant differences in CEA levels. Furthermore, in 18 patients who were undiagnosed by bronchoscopy and finally diagnosed by surgery, the napsin A levels in ELF at the nodule site were identically significantly higher than those at the contralateral site. In patients with non-adenocarcinoma, there were no differences in napsin A levels in ELF. The area under the receiver operator characteristic curve for identifying primary lung adenocarcinoma was 0.840 for napsin A and 0.542 for CEA.

CONCLUSION

Evaluation of napsin A levels in ELF may be useful for distinguishing primary lung adenocarcinoma.

Transcriptomics, proteomics and metabolomics driven biomarker discovery in COPD: an update

INTRODUCTION

Diagnosis of chronic obstructive pulmonary disease (COPD), characterized by progressive irreversible airflow limitation, remains a challenge. Lack of sensitive diagnostic markers and alternative treatments have limited patients' survival rate. Herein, we provide for clinicians and scientists a comprehensive review on the various omics platforms used to investigate COPD.

AREAS COVERED

This review consists of articles from PubMed (2009-2016) as well as views of the contributing authors. The review highlights the need for COPD biomarker identification and also provides an update on promising candidate markers identified in various biological fluids using omics technologies. Expert commentary: The multi-omics approach holds promise for the development of robust early stage COPD diagnostic markers, screening of high-risk population, and also improved prognosis which could lead to personalized medicine in future. Various factors regulating an omics study including sample size, control selection, disease phenotyping, usage of complementary techniques and result replication in omics-based research are outlined.

Asthma and COPD proteomics: current approaches and future directions

Although asthma and chronic obstructive pulmonary disease COPD represent the two most common chronic respiratory diseases worldwide, the mechanisms underlying their pathobiology need to be further elucidated. Presently, differentiation of asthma and COPD are largely based on clinical and lung function parameters. However, the complexity of these multifactorial diseases may lead to misclassification and to inappropriate management strategies. Recently, tremendous progress in MS has extended the sensitivity, accuracy, and speed of analysis, enabling the identification of thousands of proteins per experiment. Beyond identification, MS has also greatly implemented quantitation issues allowing to assess qualitative-quantitative differences in protein profiles of different samples, in particular diseased versus normal. Herein, we provide a summary of recent proteomics-based investigations in the field of asthma/COPD, highlighting major issues related to sampling and processing procedures for proteomic analyses of specific airway and parenchymal specimens (induced sputum, exhaled breath condensate, epithelial lining fluid, bronchoalveolar and nasal lavage fluid), as well as blood-derived specimen (plasma and serum). Within such a context, together with current difficulties and limitations mainly due to lack of general standardization in preanalytical sampling procedure, our discussion will focus on the challenges and possible benefits of proteomic studies in phenotypic stratification of asthma and COPD.

Application of clinical proteomics in acute respiratory distress syndrome

Acute Respiratory Distress Syndrome (ARDS) is a devastating cause of hypoxic respiratory failure, which continues to have high mortality. It is expected that a comprehensive systems- level approach will identify global and complex changes that contribute to the development of ARDS and subsequent repair of the damaged lung. In the last decade, powerful genome-wide analytical and informatics tools have been developed, that have provided valuable insights into the mechanisms of complex diseases such as ARDS. These tools include the rapid and precise measure of gene expression at the proteomic level. This article reviews the contemporary proteomics platforms that are available for comprehensive studies in ARDS. The challenges of various biofluids that could be investigated and some of the studies performed are also discussed.

Susceptibility to COPD: differential proteomic profiling after acute smoking

Cigarette smoking is the main risk factor for COPD (Chronic Obstructive Pulmonary Disease), yet only a subset of smokers develops COPD. Family members of patients with severe early-onset COPD have an increased risk to develop COPD and are therefore defined as “susceptible individuals”. Here we perform unbiased analyses of proteomic profiles to assess how “susceptible individuals” differ from age-matched “non-susceptible individuals” in response to cigarette smoking. Epithelial lining fluid (ELF) was collected at baseline and 24 hours after smoking 3 cigarettes in young individuals susceptible or non-susceptible to develop COPD and older subjects with established COPD. Controls at baseline were older healthy smoking and non-smoking individuals. Five samples per group were pooled and analysed by stable isotope labelling (iTRAQ) in duplicate. Six proteins were selected and validated by ELISA or immunohistochemistry. After smoking, 23 proteins increased or decreased in young susceptible individuals, 7 in young non-susceptible individuals, and 13 in COPD in the first experiment; 23 proteins increased or decreased in young susceptible individuals, 32 in young non-susceptible individuals, and 11 in COPD in the second experiment. SerpinB3 and Uteroglobin decreased after acute smoke exposure in young non-susceptible individuals exclusively, whereas Peroxiredoxin I, S100A9, S100A8, ALDH3A1 (Aldehyde dehydrogenase 3A1) decreased both in young susceptible and non-susceptible individuals, changes being significantly different between groups for Uteroglobin with iTRAQ and for Serpin B3 with iTRAQ and ELISA measures. Peroxiredoxin I, SerpinB3 and ALDH3A1 increased in COPD patients after smoking. We conclude that smoking induces a differential protein response in ELF of susceptible and non-susceptible young individuals, which differs from patients with established COPD. This is the first study applying unbiased proteomic profiling to unravel the underlying mechanisms that induce COPD. Our data suggest that SerpinB3 and Uteroglobin could be interesting proteins in understanding the processes leading to COPD.

Proteomic analysis of the asthmatic airway

Proteomic investigations in general utilize varied technologies for sample preparation, separations, quantification, protein identification, and biological rationalization. Their applications range from pure discovery and mechanistic studies to biomarker discovery/verification/validation. In each specific case, the analytical strategy to be implemented is tailored to the type of sample that serves as the target of the investigations. Proteomic investigations take into consideration sample complexity, the cellular heterogeneity (particularly from tissues), the potential dynamic range of the protein and peptide abundance within the sample, the likelihood of posttranslational modifications (PTM), and other important factors that might influence the final output of the study. We describe the sample types typically used for proteomic investigations into the biology of asthma and review the most recent related publications with special attention to those that deal with the unique airway samples such as bronchoalveolar lavage fluids (BALF), epithelial lining fluid and cells (ELF), induced sputum (IS), and exhaled breath condensate (EBC). Finally, we describe the newest proteomics approaches to sample preparation of the unique airway samples, BALF and IS.

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Glycoproteomic identification of galectin-3 and -8 ligands in bronchoalveolar lavage of mild asthmatics and healthy subjects

BACKGROUND

Galectins, a family of small carbohydrate binding proteins, have been implicated in regulation of inflammatory reactions, including asthma and fibrosis in the lungs. Galectins are found in cells of the airways and in airway secretions, but their glycoprotein ligands there have only been studied to a very limited extent.

METHODS

Bronchoalveolar lavage (BAL) fluid from mild asthmatics and healthy volunteers were fractionated by affinity chromatography on the immobilized galectins. Total (10-30 μg) and galectin bound (~1-10 μg) protein fractions were identified, quantified and compared using shot-gun proteomics and spectral counts.

RESULTS

About 175 proteins were identified in unfractionated BAL-fluid, and about 100 bound galectin-3 and 60 bound galectin-8. These included plasma glycoproteins, and typical airway proteins such as SP-A2, PIGR and SP-B. The concentration of galectin-binding proteins was 100-300 times higher than the concentration of galectins in BAL.

CONCLUSION

The low relative concentration of galectins in BAL makes it likely that functional interactions with glycoproteins occur at sites rich in galectin, such as cells of the airways, rather than the extracellular fluid itself. The profile of galectin bound proteins differed between samples from asthma patients and healthy subjects and correlated with the presence of fibroblasts or eosinophils. This included appearance of a specific galectin-8-binding glycoform of haptoglobin, previously shown to be increased in serum in other inflammatory conditions.

GENERAL SIGNIFICANCE

It is technically feasible to identify galectin-binding glycoproteins in low concentration patient samples such as BAL-fluid, to generate biomedically interesting results. This article is part of a Special Issue entitled Glycoproteomics.

Proteomics of epithelial lining fluid obtained by bronchoscopic microprobe sampling

Epithelial lining fluid (ELF) forms a thin fluid layer that covers the mucosa of the alveoli, the small airways, and the large airways. Since it constitutes the first barrier between the lung and the outer world, it is an interesting target for proteomics studies that focus on lung disease. Bronchoscopic microprobe (BMP) sampling of ELF uses small probes with an absorptive tip that are introduced bronchoscopically. In contrast to other methods used so far for the collection of biofluids from the lung (e.g., bronchoalveolar lavage fluid, induced sputum), this technique has the advantage that ELF is not diluted and contains high concentrations of biomolecules. In addition, the investigated location in the tracheobronchial tree is well defined, and there is no contamination with oropharyngeal bacteria or saliva. Despite occasional blood contamination of the probes by scratching the mucosa of the airways, the proteomic analysis of microprobe-sampled ELF opens new possibilities for research in lung diseases. Our work focuses particularly on the induction and progression of cigarette smoke-induced Chronic Obstructive Pulmonary Disease (COPD). In this chapter, we describe the practical aspects of sampling ELF followed by a detailed description of proteomics analysis by LC-MS/MS after protein separation by SDS-PAGE and in-gel digestion. As an example, we apply this proteomic platform to the identification and quantification of proteins in ELF from COPD patients and healthy subjects.

Advances in proximal fluid proteomics for disease biomarker discovery

Although serum/plasma has been the preferred source for identification of disease biomarkers, these efforts have been met with little success, in large part due the relatively small number of highly abundant proteins that render the reliable detection of low abundant disease-related proteins challenging due to the expansive dynamic range of concentration of proteins in this sample. Proximal fluid, the fluid derived from the extracellular milieu of tissues, contains a large repertoire of shed and secreted proteins that are likely to be present at higher concentrations relative to plasma/serum. It is hypothesized that many, if not all, proximal fluid proteins exchange with peripheral circulation, which has provided significant motivation for utilizing proximal fluids as a primary sample source for protein biomarker discovery. The present review highlights recent advances in proximal fluid proteomics, including the various protocols utilized to harvest proximal fluids along with detailing the results from mass spectrometry- and antibody-based analyses.

[Variation in protein expression depending on the severity of sleep apnoea-hypopnoea syndrome]

OBJECTIVE

A prospective study with a consecutive sample and a control group to determine whether protein expression in patients with sleep apnoea-hypopnoea syndrome (SAHS) is different from that of the control group (IAH < or =5).

PATIENTS AND METHODS

A total of 32 patients aged between 35 and 60 years who had a polysomnograph performed were included. Patients with an acute or chronic were excluded. The first dimension of the proteomic study was carried out on IPG strips (18cm, pH 4-7) and the second on SDS-PAGE gels in triplicate for each group. The gels were stained with SYPRO-Ruby (Bio-Rad((R))), the images obtained with an FX-Imager laser scanner and the spots were analysed using ProteomWeaver v. 4.0 (Bio-Rad((R))) software. Significant changes between the gels were analysed by replicates and separately, being considered a significant change if the relative intensity of the spots was three times higher or lower than that of the control and if it was observed in 2 of the 3 replicates of each group, with a coefficient of variation of <20%.

RESULTS

The patients were divided into 8 subjects per group (control, mild, moderate and severe). The comparison of the gels showed significant differences between the control group and the 3 clinical groups, with significant over-expression being observed in 3 spots, and under-expression in 7 spots in the control group.

CONCLUSION

There are significant changes in protein expression between a control group and patients in different stages of disease. The proteomic study can identify biomarkers associated with the diagnosis and severity of the SAHS.

Induced sputum: a window to lung pathology

Sputum is recognized as a sampling method for the monitoring and assessment of chronic lung diseases such as asthma, COPD (chronic obstructive pulmonary disease) and cystic fibrosis. Sputum samples the central airways and its protein components (e.g. mucins and cytokines), cellular components (e.g. eosinophils and neutrophils) and microbiological components (e.g. viruses and bacteria) can be used as markers of disease severity, exacerbation, susceptibility or progression. This paper describes the basic constituents of induced sputum and how these influence the quantification and identification of novel biomarkers of chronic lung diseases using techniques such as proteomics.

Alterations in the human lung proteome with lipopolysaccharide

Background

Recombinant human activated protein C (rhAPC) is associated with improved survival in high-risk patients with severe sepsis; however, the effects of both lipopolysaccharide (LPS) and rhAPC on the bronchoalveolar lavage fluid (BALF) proteome are unknown.

Methods

Using differential in gel electrophoresis (DIGE) we identified changes in the BALF proteome from 10 healthy volunteers given intrapulmonary LPS in one lobe and saline in another lobe. Subjects were randomized to pretreatment with saline or rhAPC.

Results

An average of 255 protein spots were detected in each proteome. We found 31 spots corresponding to 8 proteins that displayed abundance increased or decreased at least 2-fold after LPS. Proteins that decreased after LPS included surfactant protein A, immunoglobulin J chain, fibrinogen-γ, α₁-antitrypsin, immunoglobulin, and α₂-HS-glycoprotein. Haptoglobin increased after LPS-treatment. Treatment with rhAPC was associated with a larger relative decrease in immunoglobulin J chain, fibrinogen-γ, α₁-antitrypsin, and α₂-HS-glycoprotein.

Conclusion

Intrapulmonary LPS was associated with specific protein changes suggesting that the lung response to LPS is more than just a loss of integrity in the alveolar epithelial barrier; however, pretreatment with rhAPC resulted in minor changes in relative BALF protein abundance consistent with its lack of affect in ALI and milder forms of sepsis.