Allergic asthma biomarkers using systems approaches

Particles in Exhaled Air (PExA): Clinical Uses and Future Implications

Access to distal airway samples to assess respiratory diseases is not straightforward and requires invasive procedures such as bronchoscopy and bronchoalveolar lavage. The particles in exhaled air (PExA) device provides a non-invasive means of assessing small airways; it captures distal airway particles (PEx) sized around 0.5-7 μm and contains particles of respiratory tract lining fluid (RTLF) that originate during airway closure and opening. The PExA device can count particles and measure particle mass according to their size. The PEx particles can be analysed for metabolites on various analytical platforms to quantitatively measure targeted and untargeted lung specific markers of inflammation. As such, the measurement of distal airway components may help to evaluate acute and chronic inflammatory conditions such as asthma, chronic obstructive pulmonary disease, acute respiratory distress syndrome, and more recently, acute viral infections such as COVID-19. PExA may provide an alternative to traditional methods of airway sampling, such as induced sputum, tracheal aspirate, or bronchoalveolar lavage. The measurement of specific biomarkers of airway inflammation obtained directly from the RTLF by PExA enables a more accurate and comprehensive understanding of pathophysiological changes at the molecular level in patients with acute and chronic lung diseases.

Trends in asthma among adults in the United States, National Health and Nutrition Examination Survey 2005 to 2018

BACKGROUND

Asthma is a common chronic disease in American adults. The prevalence of asthma has varied over time, but there are few studies on the long-term trend of asthma in American adults.

OBJECTIVE

To describe the prevalence and trend of asthma in American adults from 2005 to 2018 and analyze the risk factors for asthma.

METHODS

Data collection was performed from National Health and Nutrition Examination Survey 2005 to 2018. The unweighted number and weighted percentages of normal participants and patients with asthma and the trends of asthma were calculated. Weighted univariate logistic regression was used to analyze the risk factors for asthma.

RESULTS

A total of 39,601 adults were included in this study. From 2005 to 2018, the overall prevalence of asthma in American adults was 8.41%, whereas that in young, middle-aged, and elderly adults was 8.30%, 8.70%, and 7.92%, respectively. The estimated prevalence of asthma in the overall adults and young adults increased with time (P for trend = .03, difference = 0.023 and P for trend = .007, difference = 0.060, respectively), and the estimated prevalence of middle-aged and elderly adults remained stable with time (P for trend = .33, difference = 0.015 and P for trend = .80, difference = -0.024, respectively).

CONCLUSION

Asthma in American adults was on the rise. Female sex, non-Hispanic Blacks, individuals with low annual household income, active smokers, obese patients, patients with hypertension, patients with diabetes, and individuals with positive asthma family history were associated with a higher risk for developing asthma.

An Integrated View of Virus-Triggered Cellular Plasticity Using Boolean Networks

Virus-related mortality and morbidity are due to cell/tissue damage caused by replicative pressure and resource exhaustion, e.g., HBV or HIV; exaggerated immune responses, e.g., SARS-CoV-2; and cancer, e.g., EBV or HPV. In this context, oncogenic and other types of viruses drive genetic and epigenetic changes that expand the tumorigenic program, including modifications to the ability of cancer cells to migrate. The best-characterized group of changes is collectively known as the epithelial–mesenchymal transition, or EMT. This is a complex phenomenon classically described using biochemistry, cell biology and genetics. However, these methods require enormous, often slow, efforts to identify and validate novel therapeutic targets. Systems biology can complement and accelerate discoveries in this field. One example of such an approach is Boolean networks, which make complex biological problems tractable by modeling data (“nodes”) connected by logical operators. Here, we focus on virus-induced cellular plasticity and cell reprogramming in mammals, and how Boolean networks could provide novel insights into the ability of some viruses to trigger uncontrolled cell proliferation and EMT, two key hallmarks of cancer.

The application of proteomics in the diagnosis and treatment of bronchial asthma

Bronchial asthma is a common chronic inflammatory disease of the airways. Although its pathogenic mechanism remains unknown, it is influenced by both genetic and environmental factors. The emergence and application of proteomic technologies can help to facilitate analysis of the changes in transcription factors, inflammatory mediators, chemokines, cytokines, and cell apoptosis-and proliferation-related proteins in the pathological processes of asthma. Proteomic technologies can unearth prospects and theoretical bases for improved understanding of the biological mechanism of asthma and effective identification of diagnostic and therapeutic targets.

Systems biology and big data in asthma and allergy: recent discoveries and emerging challenges

Asthma is a common condition caused by immune and respiratory dysfunction, and it is often linked to allergy. A systems perspective may prove helpful in unravelling the complexity of asthma and allergy. Our aim is to give an overview of systems biology approaches used in allergy and asthma research. Specifically, we describe recent "omic"-level findings, and examine how these findings have been systematically integrated to generate further insight.Current research suggests that allergy is driven by genetic and epigenetic factors, in concert with environmental factors such as microbiome and diet, leading to early-life disturbance in immunological development and disruption of balance within key immuno-inflammatory pathways. Variation in inherited susceptibility and exposures causes heterogeneity in manifestations of asthma and other allergic diseases. Machine learning approaches are being used to explore this heterogeneity, and to probe the pathophysiological patterns or "endotypes" that correlate with subphenotypes of asthma and allergy. Mathematical models are being built based on genomic, transcriptomic and proteomic data to predict or discriminate disease phenotypes, and to describe the biomolecular networks behind asthma.The use of systems biology in allergy and asthma research is rapidly growing, and has so far yielded fruitful results. However, the scale and multidisciplinary nature of this research means that it is accompanied by new challenges. Ultimately, it is hoped that systems medicine, with its integration of omics data into clinical practice, can pave the way to more precise, personalised and effective management of asthma.

Pilot-Scale Study Of Human Plasma Proteomics Identifies ApoE And IL33 As Markers In Atopic Asthma

Background

The pathobiology of atopic asthma is complex and the symptoms similar to other respiratory diseases. As such, identification of biomarkers of atopic asthma is of prime importance for better diagnosis and control of the disease.

Objectives

We sought to study the changes in plasma proteome and cytokine-expression profile across healthy and atopic asthmatics for identifying biomarkers and exploring aberrant pathways for atopic asthma.

Methods

A pilot-scale study in humans was performed to identify differentially expressed proteins in blood plasma of healthy controls (n=5) and treatment-naïve atopic asthma patients (n=5) using quantitative label-free liquid chromatography-tandem mass spectrometry proteomics and ELISA.

Results

Mass spectrometry-based proteomic analysis revealed ApoE to be significantly downregulated in atopic asthmatics compared to healthy volunteers. Decreased expression of ApoE in atopic asthmatics was validated by immunoblotting (50.74% decrease). Comparison with atopic asthmatics and COPD patients showed that ApoE was decreased (36.33%) in atopic asthma compared to COPD. IL33 was significantly upregulated in atopic asthmatics compared to healthy subjects (3.84-fold).

Conclusion

ApoE was downregulated and IL33 upregulated in atopic asthma patients compared to healthy volunteers. These two proteins' profiles were distinct in atopic asthma from healthy and COPD plasma samples. Differential expression of these proteins could serve as a probable candidate for a two-protein classifier-based prognostic biomarker of atopic asthma.

Biomarkers associated with disease severity in allergic and nonallergic asthma

Asthma is a complex, chronic respiratory disease with a wide clinical spectrum. Use of high-throughput technologies has generated a great deal of data that require validation. In this work the objective was to validate molecular biomarkers related to asthmatic disease types in peripheral blood samples and define their relationship with disease severity. With this purpose, ninety-four previously described genes were analyzed by qRT-PCR in 30 healthy control (HC) subjects, 30 patients with nonallergic asthma (NA), 30 with allergic asthma (AA), and 14 patients with allergy (rhinitis) but without asthma (AR). RNA was extracted from peripheral blood mononuclear cells (PBMCs) using the TRIzol method. After data normalization, principal component analysis (PCA) was performed, and multiple approaches were used to test for differential gene expression. Relevance was defined by RQ (relative quantification) and corrected P value (<0.05). Protein levels of IL-8 and MSR1 were determined by ELISA and Western blot, respectively. PCA showed 4 gene expression clusters that correlated with the 4 clinical phenotypes. Analysis of differential gene expression between clinical groups and HCs revealed 26 statistically relevant genes in NA and 69 in AA. Protein interaction analysis revealed IL-8 to be a central protein. Average levels of IL-8 were higher in the asthma patients' sera (NA: 452.28±357.72, AA: 327.46±377pg/ml) than in HCs (286.09±179.10), but without reaching statistical significance. Nine genes, especially MSR1, were strongly associated with severe NA. In conclusion, several molecular biomarkers of asthma have been defined, some of which could be useful for the diagnosis or prognosis of disease severity.

Developing a framework for assessing chemical respiratory sensitization: A workshop report

Respiratory tract sensitization can have significant acute and chronic health implications. While induction of respiratory sensitization is widely recognized for some chemicals, validated standard methods or frameworks for identifying and characterizing the hazard are not available. A workshop on assessment of respiratory sensitization was held to discuss the current state of science for identification and characterization of respiratory sensitizer hazard, identify information facilitating development of validated standard methods and frameworks, and consider the regulatory and practical risk management needs. Participants agreed on a predominant Th2 immunological mechanism and several steps in respiratory sensitization. Some overlapping cellular events in respiratory and skin sensitization are well understood, but full mechanism(s) remain unavailable. Progress on non-animal approaches to skin sensitization testing, ranging from in vitro systems, -omics, in silico profiling, and structural profiling were acknowledged. Addressing both induction and elicitation phases remains challenging. Participants identified lack of a unifying dose metric as increasing the difficulty of interpreting dosimetry across exposures. A number of research needs were identified, including an agreed list of respiratory sensitizers and other asthmagens, distinguishing between adverse effects from immune-mediated versus non-immunological mechanisms. A number of themes emerged from the discussion regarding future testing strategies, particularly the need for a tiered framework respiratory sensitizer assessment. These workshop present a basis for moving towards a weight-of-evidence assessment.

Soluble CD93 as a Novel Biomarker in Asthma Exacerbation

Asthma research is shifting from studying symptoms and lung functions to the narrow-focus cellular profiles protein analysis, biomarkers, and genetic markers. The transmembrane glycoprotein CD93 is involved in endothelial cell migration, angiogenesis, leukocytes extravasation, apoptosis, innate immunity and inflammation. Relationships between the serum level of soluble CD93 (sCD93) and acute myocardial infarction/premature MI/inflammatory arthritis/skin sclerosis have recently been reported. We hypothesized that sCD93 would be elevated during the acute phase of asthma. We measured the serum level of sCD93 in 57 patients with asthma exacerbation and 57 age-and gender-matched healthy controls. Additionally, sCD93 was reassessed at the time of discharge from the hospital. Clinical characteristics and peak expiratory flow (PEF) of the patients were assessed. The primary outcome was the comparison of serum level of sCD93 between asthmatics and healthy subjects. The sCD93 values ranged from 128 to 789 ng/mL in asthmatics (345.83±115.81) and from 31 to 289 ng/mL in control subjects (169.46±62.43). The difference between the 2 groups was statistically significant (P<0.001). The association between sCD93 and asthma remained significant after adjusting for age, sex, and BMI. The differences between asthmatics and controls remained significant on the last day of hospital stay. The association between sCD93 and PEF was not significant. In conclusion, the serum level of soluble CD93 is increased in patients with asthma exacerbation. It also showed that serum levels of sCD93 decreased with treatment of asthma attack. The clinical usefulness of determination of sCD93 as a biomarker of asthma requires further studies.

[Biomarkers in asthma]

Identifying new biomarkers in asthma is attractive but requires assessing their relevance and their reliability to clinical practice. Beyond fashion, the improvement in identification of new candidate biomarkers benefited of scientific and biologic progresses, biobanks and platforms robustly backed on longitudinal cohorts and registries. Paradoxically, the main issue is now to stress up the good question, in other words to correctly characterize the unmet needs in asthma that might benefit of a biomarker. Chronicity, variability, weakness of diagnostic tools and the heterogeneity of the disease are features of asthma claiming for identifying new biomarkers. Unmet needs in asthma encompass areas such as diagnosis, prognosis, management and follow-up, therapeutic guidance and phenotypic/endotypic identification. FEV1 is an available biomarker largely tested in asthma worth in most of these areas. Albeit, mandatory features required for a new biomarker to emerge, pro/con debates on those already existing and currently used methods for identifying new ones are worth explorations. We reviewed and summarized the current literature focusing biomarkers in asthma.

Identifying a biomarker network for corticosteroid resistance in asthma from bronchoalveolar lavage samples

Corticosteroid resistance (CR) is a major barrier to the effective treatment of severe asthma. Hence, a better understanding of the molecular mechanisms involved in this condition is a priority. Network analysis is an emerging strategy to explore this complex heterogeneous disorder at system level to identify a small own network for CR in asthma. Gene expression profile of GSE7368 from bronchoalveolar lavage (BAL) of CR in subjects with asthma was downloaded from the gene expression omnibus (GEO) database and compared to BAL of corticosteroid-sensitive (CS) patients. DEGs were identified by the Limma package in R language. In addition, DEGs were mapped to STRING to acquire protein-protein interaction (PPI) pairs. Topological properties of PPI network were calculated by Centiscape, ClusterOne and BINGO. Subsequently, text-mining tools were applied to design one own cell signalling for CR in asthma. Thirty-five PPI networks were obtained; including a major network consisted of 370 nodes, connected by 777 edges. After topological analysis, a minor PPI network composed by 48 nodes was indentified, which is composed by most relevant nodes of major PPI network. In this subnetwork, several receptors (EGFR, EGR1, ESR2, PGR), transcription factors (MYC, JAK), cytokines (IL8, IL6, IL1B), one chemokine (CXCL1), one kinase (SRC) and one cyclooxygenase (PTGS2) were described to be associated with inflammatory environment and steroid resistance in asthma. We suggest a biomarker network composed by 48 nodes that could be potentially explored with diagnostic or therapeutic use.

Bom m 9 from Bombyx mori is a novel protein related to asthma

The silkworm (Bombyx mori) can cause severe IgE-mediated allergic disease, however, the mechanism remains unclear. The aim of this study was to investigate the immunologic mechanism by which silkworms induce allergy. Whole silkworm pupa proteins were separated by SDS-PAGE and 2-D PAGE. Then, IgE-binding proteins were detected by immunoblotting with sera of patients having an allergy to Bombyx mori. After tryptic digestion, the peptides of IgE-binding proteins were analyzed by matrix-assisted laser desorption ionization tandem time-of-flight mass spectrometry or tandem mass spectrometry. Database searches were used to identify allergens in silkworm pupa, after which Bom m 9 was to construct an asthma model. Thus, in the current study, a mouse asthma model was constructed with Bom m 9.

Modeling Pulmonary Disease Pathways Using Recombinant Adeno-Associated Virus 6.2

Viral vectors have been applied successfully to generate disease-related animal models and to functionally characterize target genes in vivo. However, broader application is still limited by complex vector production, biosafety requirements, and vector-mediated immunogenic responses, possibly interfering with disease-relevant pathways. Here, we describe adeno-associated virus (AAV) variant 6.2 as an ideal vector for lung delivery in mice, overcoming most of the aforementioned limitations. In a proof-of-concept study using AAV6.2 vectors expressing IL-13 and transforming growth factor-β1 (TGF-β1), we were able to induce hallmarks of severe asthma and pulmonary fibrosis, respectively. Phenotypic characterization and deep sequencing analysis of the AAV-IL-13 asthma model revealed a characteristic disease signature. Furthermore, suitability of the model for compound testing was also demonstrated by pharmacological intervention studies using an anti-IL-13 antibody and dexamethasone. Similarly, the AAV-TGF-β1 fibrosis model showed several disease-like pathophenotypes monitored by micro-computed tomography imaging and lung function measurement. Most importantly, analyses using stuffer control vectors demonstrated that in contrast to a common adenovirus-5 vector, AAV6.2 vectors did not induce any measurable inflammation and therefore carry a lower risk of altering relevant readouts. In conclusion, we propose AAV6.2 as an ideal vector system for the functional characterization of target genes in the context of pulmonary diseases in mice.

Transition from identity to bioactivity-guided proteomics for biomarker discovery with focus on the PF2D platform

Proteomic strategies provide a valuable tool kit to identify proteins involved in diseases. With recent progress in MS technology, high throughput proteomics has accelerated protein identification for potential biomarkers. Numerous biomarker candidates have been identified in several diseases, and many are common among pathologies. An overall strategy that could complement and strengthen the search for biomarkers is combining protein identity with biological outcomes. This review describes an emerging framework of bridging bioactivity to protein identity, exploring the possibility that some biomarkers will have a mechanistic role in the disease process. A review of pulmonary, cardiovascular, and CNS biomarkers will be discussed to demonstrate the utility of combining bioactivity with identification as a means to not only find meaningful biomarkers, but also to uncover functional mediators of disease.

Protein and microRNA biomarkers from lavage, urine, and serum in military personnel evaluated for dyspnea

Background

We have identified candidate protein and microRNA (miRNA) biomarkers for dyspnea by studying serum, lavage fluid, and urine from military personnel who reported serious respiratory symptoms after they were deployed to Iraq or Afghanistan.

Methods

Forty-seven soldiers with the complaint of dyspnea who enrolled in the STudy of Active Duty Military Personnel for Environmental Dust Exposure (STAMPEDE) underwent comprehensive pulmonary evaluations at the San Antonio Military Medical Center. The evaluation included fiber-optic bronchoscopy with bronchoalveolar lavage. The clinical findings from the STAMPEDE subjects pointed to seven general underlying diagnoses or findings including airway hyperreactivity, asthma, low diffusivity of carbon monoxide, and abnormal cell counts. The largest category was undiagnosed. As an exploratory study, not a classification study, we profiled proteins or miRNAs in lavage fluid, serum, or urine in this group to look for any underlying molecular patterns that might lead to biomarkers. Proteins in lavage fluid and urine were identified by accurate mass tag (database-driven) proteomics methods while miRNAs were profiled by a hybridization assay applied to serum, urine, and lavage fluid.

Results

Over seventy differentially expressed proteins were reliably identified both from lavage and from urine in forty-eight dyspnea subjects compared to fifteen controls with no known lung disorder. Six of these proteins were detected both in urine and lavage. One group of subjects was distinguished from controls by expressing a characteristic group of proteins. A related group of dyspnea subjects expressed a unique group of miRNAs that included one miRNA that was differentially overexpressed in all three fluids studied. The levels of several miRNAs also showed modest but direct associations with several standard clinical measures of lung health such as forced vital capacity or gas exchange efficiency.

Conclusions

Candidate proteins and miRNAs associated with the general diagnosis of dyspnea have been identified in subjects with differing medical diagnoses. Since these markers can be measured in readily obtained clinical samples, further studies are possible that test the value of these findings in more formal classification or case–control studies in much larger cohorts of subjects with specific lung diseases such as asthma, emphysema, or some other well-defined lung disease.

Montelukast-induced adverse drug reactions: a review of case reports in the literature

BACKGROUND

Montelukast, a leucotriene receptor antagonist, binds the cysteinyl leucotriene type 1 receptor. Montelukast is commonly prescribed to asthma patients as add-on therapy to inhaled corticosteroids. Several clinical trials emphasized that montelukast can be considered a safe drug. However, recent evidence reconsidered the benefit/risk ratio of the use of montelukast for both paediatric and adult patients.

SUMMARY

The present review analyzed the previous published case reports regarding montelukast-induced adverse drug reactions (ADRs). They included agitation, anxiety, depression, sleep disturbance, hallucinations, suicidal thinking and suicidality, tremor, dizziness, drowsiness, neuropathies and seizures. The immune system can be involved, in particular, cases of Churg-Strauss syndrome have been published. Furthermore, it can induce hypersensitivity reactions, including anaphylaxis and eosinophilic infiltration. In addition, hepatobiliary, pancreatic and uropoietic disorders have been observed. Some of these cases are characterized by severe prognosis (i.e. neurological deficit and fatal hepatotoxicity). Key Message: The use of montelukast can be burdened by several ADRs, of which physicians should be aware in their clinical practice. A better understanding of the mechanisms causing ADRs after using montelukast could help researchers and clinicians in defining a risk-reduction strategy aimed to lessen montelukast toxicity. More accurate epidemiological studies, in order to discover risk factors favouring montelukast-associated ADRs, are demanded.

Systems biology approaches to understanding Epithelial Mesenchymal Transition (EMT) in mucosal remodeling and signaling in asthma

A pathological hallmark of asthma is chronic injury and repair, producing dysfunction of the epithelial barrier function. In this setting, increased oxidative stress, growth factor- and cytokine stimulation, together with extracellular matrix contact produces transcriptional reprogramming of the epithelial cell. This process results in epithelial-mesenchymal transition (EMT), a cellular state associated with loss of epithelial polarity, expression of mesenchymal markers, enhanced mobility and extracellular matrix remodeling. As a result, the cellular biology of the EMT state produces characteristic changes seen in severe, refractory asthma: myofibroblast expansion, epithelial trans-differentiation and subepithelial fibrosis. EMT also induces profound changes in epithelial responsiveness that affects innate immune signaling that may have impact on the adaptive immune response and effectiveness of glucocorticoid therapy in severe asthma. We discuss how this complex phenotype is beginning to be understood using systems biology-level approaches through perturbations coupled with high throughput profiling and computational modeling. Understanding the distinct changes induced by EMT at the systems level may provide translational strategies to reverse the altered signaling and physiology of refractory asthma.