NMR metabolomic analysis of exhaled breath condensate of asthmatic patients at two different temperatures

Biomarkers in exhaled breath condensate as fingerprints of asthma, chronic obstructive pulmonary disease and asthma-chronic obstructive pulmonary disease overlap: a critical review

Asthma, chronic obstructive pulmonary disease (COPD) and asthma-COPD overlap are the third leading cause of mortality around the world. They share some common features, which can lead to misdiagnosis. To properly manage these conditions, reliable markers for early and accurate diagnosis are needed. Over the past 20 years, many molecules have been investigated in the exhaled breath condensate to better understand inflammation pathways and mechanisms related to these disorders. Recently, more advanced techniques, such as sensitive metabolomic and proteomic profiling, have been used to obtain a more comprehensive understanding. This article reviews the use of targeted and untargeted metabolomic methodology to study asthma, COPD and asthma-COPD overlap.

Immune Metabolism in TH2 Responses: New Opportunities to Improve Allergy Treatment - Disease-Specific Findings (Part 1)

PURPOSE OF REVIEW

Recent high-level publications have shown an intricate connection between immune effector function and the metabolic state of the respective cells. In the last years, studies have begun analyzing the metabolic changes associated with allergies. As the first part of a two-article series, this review will briefly summarize the basics of immune metabolism and then focus on the recently published studies on metabolic changes observed in allergic patients.

RECENT FINDINGS

In the last 3 years, immune-metabolic research in allergology had a clear focus on asthma with some studies also reporting findings in food allergy and atopic dermatitis. Current results suggest asthma to be associated with a shift in cellular metabolism towards increased aerobic glycolysis (Warburg metabolism), while also displaying substantial changes in fatty acid- and amino acid metabolism (depending on investigated patient collective, asthma phenotype, and disease severity). Understanding immune-metabolic changes in allergies will allow us to (I) better understand allergic disease pathology and (II) modulate immune-metabolic pathways to improve allergy treatment.

Sputum Metabolomic Profiling Reveals Metabolic Pathways and Signatures Associated With Inflammatory Phenotypes in Patients With Asthma

Purpose

The molecular links between metabolism and inflammation that drive different inflammatory phenotypes in asthma are poorly understood. We aimed to identify the metabolic signatures and underlying molecular pathways of different inflammatory asthma phenotypes.

Methods

In the discovery set (n = 119), untargeted ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was applied to characterize the induced sputum metabolic profiles of asthmatic patients with different inflammatory phenotypes using orthogonal partial least-squares discriminant analysis (OPLS-DA), and pathway topology enrichment analysis. In the validation set (n = 114), differential metabolites were selected to perform targeted quantification. Correlations between targeted metabolites and clinical indices in asthmatic patients were analyzed. Logistic and negative binomial regression models were established to assess the association between metabolites and severe asthma exacerbations.

Results

Seventy-seven differential metabolites were identified in the discovery set. Pathway topology analysis uncovered that histidine metabolism, glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, linoleic acid metabolism as well as phenylalanine, tyrosine and tryptophan biosynthesis were involved in the pathogenesis of different asthma phenotypes. In the validation set, 24 targeted quantification metabolites were significantly expressed between asthma inflammatory phenotypes. Finally, adenosine 5′-monophosphate (adjusted relative risk [adj RR] = 1.000; 95% confidence interval [CI] = 1.000–1.000; P = 0.050), allantoin (adj RR = 1.000; 95% CI = 1.000–1.000; P = 0.043) and nicotinamide (adj RR = 1.001; 95% CI = 1.000–1.002; P = 0.021) were demonstrated to predict severe asthma exacerbation rates.

Conclusions

Different inflammatory asthma phenotypes have specific metabolic profiles in induced sputum. The potential metabolic signatures may identify therapeutic targets in different inflammatory asthma phenotypes.

Segmental Bronchial Allergen Challenge Elicits Distinct Metabolic Phenotypes in Allergic Asthma

Asthma is a complex syndrome associated with episodic decompensations provoked by aeroallergen exposures. The underlying pathophysiological states driving exacerbations are latent in the resting state and do not adequately inform biomarker-driven therapy. A better understanding of the pathophysiological pathways driving allergic exacerbations is needed. We hypothesized that disease-associated pathways could be identified in humans by unbiased metabolomics of bronchoalveolar fluid (BALF) during the peak inflammatory response provoked by a bronchial allergen challenge. We analyzed BALF metabolites in samples from 12 volunteers who underwent segmental bronchial antigen provocation (SBP-Ag). Metabolites were quantified using liquid chromatography-tandem mass spectrometry (LC–MS/MS) followed by pathway analysis and correlation with airway inflammation. SBP-Ag induced statistically significant changes in 549 features that mapped to 72 uniquely identified metabolites. From these features, two distinct inducible metabolic phenotypes were identified by the principal component analysis, partitioning around medoids (PAM) and k-means clustering. Ten index metabolites were identified that informed the presence of asthma-relevant pathways, including unsaturated fatty acid production/metabolism, mitochondrial beta oxidation of unsaturated fatty acid, and bile acid metabolism. Pathways were validated using proteomics in eosinophils. A segmental bronchial allergen challenge induces distinct metabolic responses in humans, providing insight into pathogenic and protective endotypes in allergic asthma.

A novel temperature-controlled open source microcontroller based sampler for collection of exhaled breath condensate in point-of-care diagnostics

Exhaled breath condensate (EBC) is an attractive, non-invasive sample for clinical diagnostics. During EBC collection, its composition is influenced by the collection temperature, a factor that is often not thoroughly monitored and controlled. In this study, we assembled a novel, simple, portable, and inexpensive device for EBC collection, able to maintain a stable temperature at any value between -7 °C and +12 °C. The temperature was controlled using a microcontroller and a thermoelectric cooler that was employed to cool the aluminum block holding the glass tube or the polypropylene syringe. The performance of the novel sampler was compared with the passively cooled RTube™ and a simple EBC sampler, in which the temperature was steadily increasing during sampling. The developed sampler was able to maintain a stable temperature within ±1 °C. To investigate the influence of different sampling temperatures (i.e., +12, -7, -80 °C) on the analyte content in EBC, inorganic ions and organic acids were analyzed by capillary electrophoresis with a capacitively coupled contactless conductivity detector. It was shown that the concentration of metabolites decreased significantly with decreasing temperature. The portability and the ability to keep a stable temperature during EBC sampling makes the developed sampler suitable for point-of-care diagnostics.

Potential Metabolic Biomarkers in Adult Asthmatics

Asthma is the most common chronic airway inflammation, with multiple phenotypes caused by complicated interactions of genetic, epigenetic, and environmental factors. To date, various determinants have been suggested for asthma pathogenesis by a new technology termed omics, including genomics, transcriptomics, proteomics, and metabolomics. In particular, the systematic analysis of all metabolites in a biological system, such as carbohydrates, amino acids, and lipids, has helped identify a novel pathway related to complex diseases. These metabolites are involved in the regulation of hypermethylation, response to hypoxia, and immune reactions in the pathogenesis of asthma. Among them, lipid metabolism has been suggested to be related to lung dysfunction in mild-to-moderate asthma. Sphingolipid metabolites are an important mediator contributing to airway inflammation in obese asthma and aspirin-exacerbated respiratory disease. Although how these molecular variants impact the disease has not been completely determined, identification of new causative factors may possibly lead to more-personalized and precise pathway-specific approaches for better diagnosis and treatment of asthma. In this review, perspectives of metabolites related to asthma and clinical implications have been highlighted according to various phenotypes.

Application of Metabolomics in Pediatric Asthma: Prediction, Diagnosis and Personalized Treatment

Asthma in children remains a significant public health challenge affecting 5–20% of children in Europe and is associated with increased morbidity and societal healthcare costs. The high variation in asthma incidence among countries may be attributed to differences in genetic susceptibility and environmental factors. This respiratory disorder is described as a heterogeneous syndrome of multiple clinical manifestations (phenotypes) with varying degrees of severity and airway hyper-responsiveness, which is based on patient symptoms, lung function and response to pharmacotherapy. However, an accurate diagnosis is often difficult due to diversities in clinical presentation. Therefore, identifying early diagnostic biomarkers and improving the monitoring of airway dysfunction and inflammatory through non-invasive methods are key goals in successful pediatric asthma management. Given that asthma is caused by the interaction between genes and environmental factors, an emerging approach, metabolomics—the systematic analysis of small molecules—can provide more insight into asthma pathophysiological mechanisms, enable the identification of early biomarkers and targeted personalized therapies, thus reducing disease burden and societal cost. The purpose of this review is to present evidence on the utility of metabolomics in pediatric asthma through the analysis of intermediate metabolites of biochemical pathways that involve carbohydrates, amino acids, lipids, organic acids and nucleotides and discuss their potential application in clinical practice. Also, current challenges on the integration of metabolomics in pediatric asthma management and needed next steps are critically discussed.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Metabolomic differences of exhaled breath condensate among children with and without asthma

BACKGROUND

There remains an unmet need in objective tests for diagnosing asthma in children. The objective of this study was to investigate the potential of metabolomic profiles of exhaled breath condensate (EBC) to discriminate stable asthma in Asian children in the community.

METHODS

One hundred and sixty-five Asian children (92 stable asthma and 73 non-asthmatic controls) participating in a population-based cohort were enrolled and divided into training and validation sets. Nuclear magnetic resonance-based metabolomic profiles of EBC samples were analyzed by using orthogonal partial least squares discriminant analysis.

RESULTS

EBC metabolomic signature (lactate, formate, butyrate, and isobutyrate) had an area under the receiver operator characteristic curve (AUC) of 0.826 in discriminating children with and without asthma in the training set, which significantly outperformed FeNO (AUC = 0.574; P < .001) and FEV₁ /FVC % predicted (AUC = 0.569; P < .001). The AUC for EBC metabolomic signature was 0.745 in the validation set, which was slightly but not significantly lower than in the testing set (P = .282). We further extrapolated two potentially involved metabolic pathways, including pyruvate (P = 1.67 × 10^-3 ; impact: 0.14) and methane (P = 1.89 × 10^-3 ; impact: 0.15), as the most likely divergent metabolisms between children with and without asthma.

CONCLUSION

This study provided evidence supporting the role of EBC metabolomic signature to discriminate stable asthma in Asian children in the community, with a discriminative property outperforming conventional clinical tests such as FeNO or spirometry.

NMR Profiling of Exhaled Breath Condensate Defines Different Metabolic Phenotypes of Non-Cystic Fibrosis Bronchiectasis

Nuclear-magnetic-resonance (NMR) profiling of exhaled breath condensate (EBC) provides insights into the pathophysiology of bronchiectasis by identifying specific biomarkers. We evaluated whether NMR-based metabolomics discriminates the EBC-derived metabolic phenotypes (“metabotypes”) of 41 patients with non-cystic fibrosis (nCF) bronchiectasis of various etiology [24 subjects with Primary Ciliary Dyskinesia (PCD); 17 patients with bronchiectasis not associated with PCD (nCF/nPCD)], who were compared to 17 healthy subjects (HS). NMR was used for EBC profiling, and Orthogonal Projections to Latent Structures with partial least-squares discriminant analysis (OPLS-DA) was used as a classifier. The results were validated by using the EBC from 17 PCD patients not included in the primary analysis. Different statistical models were built, which compared nCF/nPCD and HS, PCD and HS, all classes (nCF/nPCD-PCD-HS), and, finally, PCD and nCF/nPCD. In the PCD-nCF/nPCD model, four statistically significant metabolites were able to discriminate between the two groups, with only a minor reduction of the quality parameters. In particular, for nCF/nPCD, acetone/acetoin and methanol increased by 21% and 18%, respectively. In PCD patients, ethanol and lactate increased by 25% and 28%, respectively. They are all related to lung inflammation as methanol is found in the exhaled breath of lung cancer patients, acetone/acetoin produce toxic ROS that damage lung tissue in CF, and lactate is observed in acute inflammation. Interestingly, a high concentration of ethanol hampers cilia beating and can be associated with the genetic defect of PCD. Model validation with 17 PCD samples not included in the primary analysis correctly predicted all samples. Our results indicate that NMR of EBC discriminates nCF/nPCD and PCD bronchiectasis patients from HS, and patients with nCF/nPCD from those with PCD. The metabolites responsible for between-group separation identified specific metabotypes, which characterize bronchiectasis of a different etiology.

The influence of active and passive air humidification on exhaled breath condensate volume

Exhaled breath condensate (EBC) is safely collected in mechanically ventilated (MV) patients, but there are no guidelines regarding humidification of inhaled air during EBC collection. We investigated the influence of active and passive air humidification on EBC volumes obtained from MV patients. We collected 29 EBC samples from 21 critically ill MV patients with one condition of active humidification and four different conditions of non-humidification; 19 samples from 19 surgical MV patients with passive humidification and two samples from artificial lungs MV with active humidification. The main outcome was the obtained EBC volume per 100 L exhaled air. When collected with different conditions of non-humidification, mean [95% CI] EBC volumes did not differ significantly (1.35 [1.23; 1.46] versus 1.16 [1.05; 1.28] versus 1.27 [1.13; 1.41] versus 1.17 [1.00; 1.33] mL/100 L, p=0.114). EBC volumes were higher with active humidification than with non-humidification (2.05 [1.91; 2.19] versus 1.25 [1.17; 1.32] mL/100 L, p<0.001). The volume difference between these corresponded to the EBC volume obtained from artificial lungs (0.81 [0.62; 0.99] versus 0.89 mL/100 L, p=0.287). EBC volumes were lower for surgical MV patients with passive humidification compared to critically ill MV patients with non-humidification (0.55 [0.47; 0.63] versus 1.25 [1.17; 1.32] mL/100 L, p<0.001). While active humidification increases EBC volumes, passive humidification decreases EBC volumes and possibly influences EBC composition by other mechanisms. We propose that EBC should be collected from MV patients without air humidification to improve reproducibility and comparability across studies, and that humidification conditions should always be reported.

Characterization of exhaled breath condensate (EBC) non-exchangeable hydrogen functional types and lung function of wildland firefighters

Inhalation of smoke is shown to be associated with adverse respiratory outcomes in firefighters. Due to invasiveness of procedures to obtain airways lining fluid, the immediate responses of the target organ (i.e. lung) are secondarily assessed through biomarkers in blood and urine. The objective of this study was to identify changes in metabolic profile of exhaled breath condensate (EBC) and lung function of firefighters exposed to wildfires smoke. A total of 29 subjects were studied over 16 events; 14 of these subjects provided cross-shift EBC samples. The predominant types of non-exchangeable hydrogen in EBC were saturated oxygenated hydrogen, aliphatic alkyl and allylic. Non-exchangeable allylic and oxygenated hydrogen concentrations decreased in post-exposure EBC samples. Longer exposures were correlated with increased abundance of oxidized carbon in ketones, acids and esters. Post-exposure lung function declines (forced expiratory volume in 1 s (FEV₁): 0.08 l, forced vital capacity (FVC): 0.07 l, FEV₁/FVC: 0.03 l, peak expiratory flow (PEF): 0.39 l s^-1) indicated airways inflammation. They were related to exposure intensity (FEV₁ and FVC) and exposure duration (PEF). This study showed that EBC characterization of non-exchangeable hydrogen types by NMR may provide insights on EBC molecular compositions in response to smoke inhalation and facilitate targeted analysis to identify specific biomarkers.

Metabolic Dysfunction and Asthma: Current Perspectives

The increasing knowledge of the mechanisms involved in metabolism is shifting the paradigms by which the pathophysiology of many pulmonary diseases is understood. Metabolic dysfunction is recognized in obesity-associated asthma, but other metabolic conditions have been shown to be independently related to asthma. Novel insights have also recently been brought by metabolomics in this filed. The purpose of this review is to discuss current perspectives regarding metabolic dysfunction in asthma, from obesity-related asthma to other metabolic conditions and the role of current pharmacological therapeutic strategies and lifestyle interventions. Obesity is a well-recognized risk factor for asthma across the lifespan, which is generally associated with poorer response to current available treatments, rendering a more severe, refractory disease status. Besides the epidemiological and clinical link, untargeted metabolomics studies have recently supported the obesity-associated asthma phenotype at the molecular level. Not only obesity-related, but also other aspects of metabolic dysregulation can be independently linked to asthma. These include hyperinsulinemia, dyslipidemia and hypertension, which need to be taken into account, even in the non-obese patient. Untargeted metabolomics studies have further highlighted several other metabolic pathways that can be altered in asthma, namely regarding oxidative stress and systemic inflammation, and also suggesting the importance of microbiota in asthma pathogenesis. Considering the reduced response to corticosteroids, other pharmacologic treatments have been shown to be effective regardless of body mass index. Non-pharmacologic treatments (namely weight reduction and dietary changes) may bring substantial benefit to the asthmatic patient. Taken together, this evidence points towards the need to improve our knowledge in this filed and, in particular, to address the influence of environmental factors in metabolic dysfunction and asthma development. Personalized medicine is definitely needed to optimize treatment, including a holistic view of the asthmatic patient in order to set accurate pharmacologic therapy together with dietary, physical exercise and lifestyle interventions.

Metabolic profiling of organic and fatty acids in chronic and autoimmune diseases

Metabolomics is a powerful tool of omics that permits the simultaneous identification of metabolic perturbations in several autoimmune and chronic diseases. Several parameters can affect a metabolic profile, from the population characteristics to the selection of the analytical method. In the current chapter, we summarize the main analytical methods and results of the metabolic profiling of fatty and organic acids performed in human metabolomic studies for asthma, COPD, psoriasis and Hashimoto's thyroiditis. We discuss the most significant metabolic alterations associated with these diseases, after comparison of either a single patient's group with healthy controls or several patient's subgroups of different disease severity and phenotype with healthy controls or of a patient's group before and after treatment. Finally, we present critical metabolic patterns that are associated with each disease and their potency for the unraveling of disease pathogenesis, prediction, diagnosis, patient stratification and treatment selection.

Alterations in Serum-Free Amino Acid Profiles in Childhood Asthma

Asthma often begins in childhood, although making an early diagnosis is difficult. Clinical manifestations, the exclusion of other causes of bronchial obstruction, and responsiveness to anti-inflammatory therapy are the main tool of diagnosis. However, novel, precise, and functional biochemical markers are needed in the differentiation of asthma phenotypes, endotypes, and creating personalized therapy. The aim of the study was to search for metabolomic-based asthma biomarkers among free amino acids (AAs). A wide panel of serum-free AAs in asthmatic children, covering both proteinogenic and non-proteinogenic AAs, were analyzed. The examination included two groups of individuals between 3 and 18 years old: asthmatic children and the control group consisted of children with neither asthma nor allergies. High-performance liquid chromatography combined with tandem mass spectrometry (LC-MS/MS technique) was used for AA measurements. The data were analyzed by applying uni- and multivariate statistical tests. The obtained results indicate the decreased serum concentration of taurine, L-valine, DL-β-aminoisobutyric acid, and increased levels of ƴ-amino-n-butyric acid and L-arginine in asthmatic children when compared to controls. The altered concentration of these AAs can testify to their role in the pathogenesis of childhood asthma. The authors' results should contribute to the future introduction of new diagnostic markers into clinical practice.

Metabolomics of Exhaled Breath Condensate by Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry: A Methodological Approach

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Respiratory diseases present a very high prevalence in the general population, with an increase in morbidity, mortality and health-care expenses worldwide. They are complex and heterogeneous pathologies that may present different pathological facets in different subjects, often with personal evolution. Therefore, there is a need to identify patients with similar characteristics, prognosis or treatment, defining the so-called phenotype, but also to mark specific differences within each phenotype, defining the endotypes.

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Biomarkers are very useful to study respiratory phenotypes and endotypes. Metabolomics, one of the recently introduced “omics”, is becoming a leading technique for biomarker discovery. For the airways, metabolomics appears to be well suited as the respiratory tract offers a natural matrix, the Exhaled Breath Condensate (EBC), in which several biomarkers can be measured. In this review, we will discuss the main methodological issues related to the application of Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) to EBC metabolomics for investigating respiratory diseases.

Metabolomic Analysis Reveals Distinct Profiles in the Plasma and Urine Associated with IgE Reactions in Childhood Asthma

Several metabolomics studies have identified altered metabolic pathways that are related to asthma. However, an integrative analysis of the metabolic responses across blood and urine for a comprehensive framework of asthma in early childhood remains lacking. Fifty-four age-matched children with asthma (n = 28) and healthy controls (n = 26) were enrolled. Metabolome analysis of the plasma and urine samples was performed using ¹H-nuclear magnetic resonance (NMR) spectroscopy coupled with partial least-squares discriminant analysis (PLS-DA). Integrated analysis of blood and urine metabolic profiling related to IgE reactions for childhood asthma was investigated. A significantly higher plasma histidine level was found, in parallel with lower urinary 1-methylnicotinamide and trimethylamine N-oxide (TMAO) levels, in children with asthma compared to healthy controls. Compared to children without allergic sensitization, 11 (92%) plasma metabolites and 8 (80%) urinary metabolites were found to be significantly different in children with IgE and food sensitization respectively. There were significant correlations between the plasma 3-hydroxybutyric acid and excreted volumes of the hydroxy acids, which were strongly correlated to plasma leucine and valine levels. Urine N-phenylacetylglycine, a microbial-host co-metabolite, was strongly correlated with total serum and food allergen-specific IgE levels. Plasma pyruvate and urine valine, leucine, and isoleucine degradation metabolisms were significantly associated with allergic sensitization for childhood asthma. In conclusion, blood and urine metabolome reflect different metabolic pathways in allergic reactions. Plasma pyruvate metabolism to acetic acid appears to be associated with serum IgE production, whereas urine branched-chain amino acid metabolism primarily reflects food allergic reactions against allergies.

Untargeted metabolomic profiling identifies disease-specific signatures in food allergy and asthma

BACKGROUND

Food allergy (FA) affects an increasing proportion of children for reasons that remain obscure. Novel disease biomarkers and curative treatment options are strongly needed.

OBJECTIVE

We sought to apply untargeted metabolomic profiling to identify pathogenic mechanisms and candidate disease biomarkers in patients with FA.

METHODS

Mass spectrometry-based untargeted metabolomic profiling was performed on serum samples of children with either FA alone, asthma alone, or both FA and asthma, as well as healthy pediatric control subjects.

RESULTS

In this pilot study patients with FA exhibited a disease-specific metabolomic signature compared with both control subjects and asthmatic patients. In particular, FA was uniquely associated with a marked decrease in sphingolipid levels, as well as levels of a number of other lipid metabolites, in the face of normal frequencies of circulating natural killer T cells. Specific comparison of patients with FA and asthmatic patients revealed differences in the microbiota-sensitive aromatic amino acid and secondary bile acid metabolism. Children with both FA and asthma exhibited a metabolomic profile that aligned with that of FA alone but not asthma. Among children with FA, the history of severe systemic reactions and the presence of multiple FAs were associated with changes in levels of tryptophan metabolites, eicosanoids, plasmalogens, and fatty acids.

CONCLUSIONS

Children with FA have a disease-specific metabolomic profile that is informative of disease mechanisms and severity and that dominates in the presence of asthma. Lower levels of sphingolipids and ceramides and other metabolomic alterations observed in children with FA might reflect the interplay between an altered microbiota and immune cell subsets in the gut.

Four amino acids as serum biomarkers for anti-asthma effects in the ovalbumin-induced asthma mouse model treated with extract of Asparagus cochinchinensis

The butanol extract of Asparagus cochinchinensis roots fermented with Weissella cibaria (BAW) effectively prevents inflammation and remodeling of airway in the ovalbumin (OVA)-induced asthma model. To characterize biomarkers that can predict the anti-asthmatic effects induced by BAW treatment, we measured the alteration of endogenous metabolites in the serum of OVA-induced asthma mice after administration of low concentration BAW (BAWLo, 250 mg/kg) and high concentration BAW (BAWHi, 500 mg/kg) using ¹H nuclear magnetic resonance (¹H-NMR) spectral data. The number of immune cells and serum concentration of IgE as well as thickness of the respiratory epithelium and infiltration of inflammatory cells in the airway significantly recovered in the OVA+BAW treated group as compared to the OVA+Vehicle treated group. In the metabolic profile analysis, the pattern recognition showed completely separate clustering of serum analysis parameters between the OVA+Vehicle and OVA+BAW treated groups. Of the total endogenous metabolites, 19 metabolites were upregulated or downregulated in the OVA+Vehicle treated group as compared to the Control treated group. However, only 4 amino acids (alanine, glycine, methionine and tryptophan) were significantly recovered after BAWLo and BAWHi treatment. This study provides the first results pertaining to metabolic changes in the asthma model mice treated with OVA+BAW. Additionally, these findings show that 4 metabolites can be used as one of biomarkers to predict the anti-asthmatic effects.

Exhaled breath condensate biomarkers for lung cancer

Lung cancer is the main cause of cancer incidence and mortality worldwide and the identification of clinically useful biomarkers for lung cancer detection at both early and metastatic stage is a pressing medical need. Although many improvements have been made in the treatment and in the early screening of this cancer, most diagnosis are made at a late stage, when a lot of genetic and epigenetic changes have occurred. A promising source of biomarkers reflective of the pathogenesis of lung cancer is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules such as DNAs, RNAs, proteins, metabolites and volatile compounds are present in EBC, and their presence/absence or their variation in concentrations can be used as biomarkers. The aims of this review are to briefly describe exhaled breath composition, firstly, and then to document some of the EBC candidate biomarkers for lung cancer by dividing them according to their origin (genome, transcriptome, epigenome, metabolome, proteome and microbiota) in order to demonstrate the potential use of EBC as a helpful tool in cancer diagnostics, molecular profiling, therapy monitoring and screening of high risk individuals.

Multiomics Data Triangulation for Asthma Candidate Biomarkers and Precision Medicine

Asthma is a common complex disorder and has been subject to intensive omics research for disease susceptibility and therapeutic innovation. Candidate biomarkers of asthma and its precision treatment demand that they stand the test of multiomics data triangulation before they can be prioritized for clinical applications. We classified the biomarkers of asthma after a search of the literature and based on whether or not a given biomarker candidate is reported in multiple omics platforms and methodologies, using PubMed and Web of Science, we identified omics studies of asthma conducted on diverse platforms using keywords, such as asthma, genomics, metabolomics, and epigenomics. We extracted data about asthma candidate biomarkers from 73 articles and developed a catalog of 190 potential asthma biomarkers (167 human, 23 animal data), comprising DNA loci, transcripts, proteins, metabolites, epimutations, and noncoding RNAs. The data were sorted according to 13 omics types: genomics, epigenomics, transcriptomics, proteomics, interactomics, metabolomics, ncRNAomics, glycomics, lipidomics, environmental omics, pharmacogenomics, phenomics, and integrative omics. Importantly, we found that 10 candidate biomarkers were apparent in at least two or more omics levels, thus promising potential for further biomarker research and development and precision medicine applications. This multiomics catalog reported herein for the first time contributes to future decision-making on prioritization of biomarkers and validation efforts for precision medicine in asthma. The findings may also facilitate meta-analyses and integrative omics studies in the future.

Clinical metabolomics of exhaled breath condensate in chronic respiratory diseases

Chronic respiratory diseases (CRDs) are complex multifactorial disorders involving the airways and other lung structures. The development of reliable markers for an early and accurate diagnosis, including disease phenotype, and prediction of the response and/or adherence to treatment prescribed are essential points for the correct management of CRDs. Beside the traditional techniques to detect biomarkers, "omics" sciences have stimulated interest in clinical field as they could potentially improve the study of disease phenotype. Perturbations in a variety of metabolic and signaling pathways could contribute an understanding of CRDs pathogenesis. In particular, metabolomics provides powerful tools to map biological perturbations and their relationship with disease pathogenesis. The exhaled breath condensate (EBC) is a natural matrix of the respiratory tract, and is well suited for metabolomics studies. In this article, we review the current state of metabolomics methodology applied to EBC in the study of CRDs.

Non-volatile compounds in exhaled breath condensate: review of methodological aspects

In contrast to bronchial and nasal lavages, the analysis of exhaled breath condensate (EBC) is a promising, simple, non-invasive, repeatable, and diagnostic method for studying the composition of airway lining fluid with the potential to assess lung inflammation, exacerbations, and disease severity, and to monitor the effectiveness of treatment regimens. Recent investigations have revealed the potential applications of EBC analysis in systemic diseases. In this review, we highlight the analytical studies conducted on non-volatile compounds/biomarkers in EBC. In contrast to other related articles, this review is classified on the basis of analytical techniques and includes almost all the applied methods and their methodological limitations for quantification of non-volatile compounds in EBC samples, providing a guideline for further researches. The studies were identified by searching the SCOPUS database with the keywords "biomarkers," "non-volatile compounds," "determination method," and "EBC."

Serum lipidomics in diagnostics of sarcoidosis

The aim of this study was to determine the use of the lipid profile of patients with sarcoidosis and compare it with healthy subjects. We assume that lipid profile of serum in sarcoidosis differs from the lipid profile of control subjects. Serum was collected from 14 patients with II stage of sarcoidosis and 14 control subjects (healthy volunteers). Proton NMR spectroscopy combined with discriminant analyses, OPLS-DA (orthogonal partial least squares projections to latent structures discriminant analysis), was used. Thirty four NMR signals of lipid compounds were selected. OPLS-DA model consisted of three components and very good explain the data and also predict the data. Discriminant analysis correctly classified patients according to their groups for 92.9% of sarcoidose and 100% of control. From multivariate discriminant analysis we obtain a list of potentialbiomarkers which are statistically significant and which separate one class from another. These biomarkers are statistically significant, but not necessarily biochemically significant. They may have biochemical significance and they may be the biomarkers we are interested in, however, this must be established through extensive testing. Presented method allows distinguishing between healthy subject and sarcoidosis patients. (Sarcoidosis Vasc Diffuse Lung Dis 2018; 35: 150-153).

Gas chromatography-time of flight/mass spectrometry-based metabonomics of changes in the urinary metabolic profile in osteoarthritic rats

The aim of the present study was to explore changes in the urinary metabolic spectrum in rats with knee osteoarthritis, using gas chromatography-time of flight/mass spectrometry (GC-TOF/MS) to determine the metabonomic disease pathogenesis. Sprague-Dawley rats were randomly divided into the control and model groups (n=8/group), and 20 µl of 4% papain and 0.03 M L-cysteine was injected into the right knee on days 1, 3 and 7 to establish the knee osteoarthritis model. Following 14 days, urine was collected over 12 h and cartilage ultrastructural damage was assessed by hematoxylin-eosin staining. GC-TOF/MS, combined with principal component analysis, partial least squares discriminant modeling and orthogonal partial least squares discriminant modeling, was used to analyze the changes in the metabolic spectrum trajectory and to identify potential biomarkers and their related metabolic pathways. Compared with the control group, the synovial cell lining of the knee joint exhibited proliferation, inflammatory cell infiltration and collagen fiber hyperplasia in the knee osteoarthritis group. A total of 23 potential biomarkers were identified, including alanine, α-ketoglutarate, asparagine, maltose and glutamine. Furthermore, metabolomic pathogenesis of osteoarthritis may be related to disorders of amino acid metabolism, energy metabolism, fatty acid metabolism, vitamin B₆ metabolism and nucleic acid metabolism.

Allergic asthma: an overview of metabolomic strategies leading to the identification of biomarkers in the field

Allergic asthma is a prominent disease especially during childhood. Indoor allergens, in general, and particularly house dust mites (HDM) are the most prevalent sensitizers associated with allergic asthma. Available data show that 65-130 million people are mite-sensitized world-wide and as many as 50% of these are asthmatic. In fact, sensitization to HDM in the first years of life can produce devastating effects on pulmonary function leading to asthmatic syndromes that can be fatal. To date, there has been considerable research into the pathological pathways and structural changes associated with allergic asthma. However, limitations related to the disease heterogeneity and a lack of knowledge into its pathophysiology have impeded the generation of valuable data needed to appropriately phenotype patients and, subsequently, treat this disease. Here, we report a systematic and integral analysis of the disease, from airway remodelling to the immune response taking place throughout the disease stages. We present an overview of metabolomics, the management of complex multifactorial diseases through the analysis of all possible metabolites in a biological sample, obtaining a global interpretation of biological systems. Special interest is placed on the challenges to obtain biological samples and the methodological aspects to acquire relevant information, focusing on the identification of novel biomarkers associated with specific phenotypes of allergic asthma. We also present an overview of the metabolites cited in the literature, which have been related to inflammation and immune response in asthma and other allergy-related diseases.

Metabolic changes of different high-resolution computed tomography phenotypes of COPD after budesonide-formoterol treatment

BACKGROUND

Metabolomics is the global unbiased analysis of all the small-molecule metabolites within a biological system. Metabolic profiling of different high-resolution computed tomography (HRCT) phenotypes of COPD patients before and after treatment may identify discriminatory metabolites that can serve as biomarkers and therapeutic agents.

PATIENTS AND METHODS

1H nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomics was performed on a discovery set of plasma samples from 50 patients with stable COPD. Patients were assigned into two groups on the basis of HRCT findings including phenotype E (n=22) and phenotype M (n=28). After budesonide-formoterol treatment (160/4.5 µg ×2 inhalations twice daily for 3 months), clinical characteristics and metabolites were then compared between phenotype E pretreatment and posttreatment, phenotype M pretreatment and posttreatment, phenotype E pretreatment and phenotype M pretreatment, and phenotype E posttreatment and phenotype M posttreatment.

RESULTS

Inhaled budesonide-formoterol therapy for both phenotype E (emphysema without bronchial wall thickening) and phenotype M (emphysema with bronchial wall thickening) was effective. However, phenotype E and phenotype M were different in response to therapy. Patients with phenotype M in response to therapeutic effects were significantly greater compared with phenotype E. Certain metabolites were identified, which were closely related to the treatment and phenotype. Metabolic changes in phenotype E or phenotype M after treatment may be involved with adenosine diphosphate (ADP), guanosine, choline, malonate, tyrosine, glycine, proline, l-alanine, l-valine, l-threonine leucine, uridine, pyruvic acid, acetone and metabolism disturbance. Metabolic differences between phenotype E and phenotype M in pretreatment and posttreatment covered glycine, d-glucose, pyruvic acid, succinate, lactate, proline, l-valine and leucine.

CONCLUSION

Bronchial wall thickening in COPD may be an indicator for predicting the better response to the treatment with bronchodilator and corticosteroid. The identification of metabolic alterations provides new insights into different HRCT phenotypes and therapeutic assessment of COPD.

New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report

This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

Metabolomic profiling of lung function in Costa-Rican children with asthma

BACKGROUND

The development of novel therapeutics and treatment regimens for the management of asthma is hindered by an incomplete understanding of its heterogeneous nature and pathophysiology. Metabolomics can provide an integrated and global profile of a biological system in a dysregulated state, making it a valuable tool to identify biomarkers along the disease development pathway and to understand the biological mechanisms driving that pathway.

METHODS

Liquid chromatography-mass spectrometry metabolomic profiling was conducted on plasma samples provided at recruitment for 380 children with asthma from the 'Genetic Epidemiology of Asthma in Costa Rica Cohort'. Metabolites associated with three clinical characteristics of asthma severity (i) airway hyper-responsiveness (AHR) (ii) percent-predicted forced expiratory volume in one second/forced vital capacity ratio (FEV₁/FVC), and (iii) FEV₁/FVC post-bronchodilator were identified and their discriminatory ability assessed. Metabolite set enrichment analyses was applied to explore the biology underlying these relationships.

RESULTS

AHR was associated (p<0.05) with 91 of 574 metabolites (15.9%), FEV₁/FVC pre-bronchodilator with 102(17.8%), and FEV₁/FVC post-bronchodilator with 155 (27.0%). The findings suggest that these characteristics capture some common and some distinct phenotypic aspects of lung function; glycerophospholipid, linoleic acid and pyrimidine metabolism were common to all three characteristics. The corresponding metabolomic profiles showed moderate but robust discriminatory ability.

CONCLUSIONS

The results confirm the existence of an asthma severity metabolome. However, differences in the metabolomic profiles of the three lung function characteristics studied, suggest that refinement of both phenotype classification and metabolite selection should be a priority as the field of asthma metabolomics progresses.

A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research

The application of metabolomics to biological samples has been a key focus in systems biology research, which is aimed at the development of rapid diagnostic methods and the creation of personalized medicine. More recently, there has been a strong focus towards this approach applied to non-invasively acquired samples, such as saliva and exhaled breath. The analysis of these biological samples, in conjunction with other sample types and traditional diagnostic tests, has resulted in faster and more reliable characterization of a range of health disorders and diseases. As the sampling process involved in collecting exhaled breath and saliva is non-intrusive as well as comparatively low-cost and uses a series of widely accepted methods, it provides researchers with easy access to the metabolites secreted by the human body. Owing to its accuracy and rapid nature, metabolomic analysis of saliva and breath (known as salivaomics and breathomics, respectively) is a rapidly growing field and has shown potential to be effective in detecting and diagnosing the early stages of numerous diseases and infections in preclinical studies. This review discusses the various collection and analyses methods currently applied in two of the least used non-invasive sample types in metabolomics, specifically their application in salivaomics and breathomics research. Some of the salient research completed in this field to date is also assessed and discussed in order to provide a basis to advocate their use and possible future scientific directions.

Asthma Metabolomics and the Potential for Integrative Omics in Research and the Clinic

Asthma is a complex disease well-suited to metabolomic profiling, both for the development of novel biomarkers and for the improved understanding of pathophysiology. In this review, we summarize the 21 existing metabolomic studies of asthma in humans, all of which reported significant findings and concluded that individual metabolites and metabolomic profiles measured in exhaled breath condensate, urine, plasma, and serum could identify people with asthma and asthma phenotypes with high discriminatory ability. There was considerable consistency across the studies in terms of the reported biomarkers, regardless of biospecimen, profiling technology, and population age. In particular, acetate, adenosine, alanine, hippurate, succinate, threonine, and trans-aconitate, and pathways relating to hypoxia response, oxidative stress, immunity, inflammation, lipid metabolism and the tricarboxylic acid cycle were all identified as significant in at least two studies. There were also a number of nonreplicated results; however, the literature is not yet sufficiently developed to determine whether these represent spurious findings or reflect the substantial heterogeneity and limited statistical power in the studies and their methods to date. This review highlights the need for additional asthma metabolomic studies to explore these issues, and, further, the need for standardized methods in the way these studies are conducted. We conclude by discussing the potential of translation of these metabolomic findings into clinically useful biomarkers and the crucial role that integrated omics is likely to play in this endeavor.

Noninvasive Recognition and Biomarkers of Early Allergic Asthma in Cats Using Multivariate Statistical Analysis of NMR Spectra of Exhaled Breath Condensate

Asthma is prevalent in children and cats, and needs means of noninvasive diagnosis. We sought to distinguish noninvasively the differences in 53 cats before and soon after induction of allergic asthma, using NMR spectra of exhaled breath condensate (EBC). Statistical pattern recognition was improved considerably by preprocessing the spectra with probabilistic quotient normalization and glog transformation. Classification of the 106 preprocessed spectra by principal component analysis and partial least squares with discriminant analysis (PLS-DA) appears to be impaired by variances unrelated to eosinophilic asthma. By filtering out confounding variances, orthogonal signal correction (OSC) PLS-DA greatly improved the separation of the healthy and early asthmatic states, attaining 94% specificity and 94% sensitivity in predictions. OSC enhancement of multi-level PLS-DA boosted the specificity of the prediction to 100%. OSC-PLS-DA of the normalized spectra suggest the most promising biomarkers of allergic asthma in cats to include increased acetone, metabolite(s) with overlapped NMR peaks near 5.8 ppm, and a hydroxyphenyl-containing metabolite, as well as decreased phthalate. Acetone is elevated in the EBC of 74% of the cats with early asthma. The noninvasive detection of early experimental asthma, biomarkers in EBC, and metabolic perturbation invite further investigation of the diagnostic potential in humans.

Coexistence of obesity and asthma determines a distinct respiratory metabolic phenotype

BACKGROUND

Epidemiologic and clinical evidence supports the existence of an obesity-related asthma phenotype. No distinct pathophysiologic elements or specific biomarkers have been identified thus far, but increased oxidative stress has been reported.

OBJECTIVE

We aimed at verifying whether metabolomics of exhaled breath condensate from obese asthmatic (OA) patients, lean asthmatic (LA) patients, and obese nonasthmatic (ONA) subjects could recognize specific and statistically validated biomarkers for a separate "asthma-obesity" respiratory metabolic phenotype, here defined as "metabotype."

METHODS

Twenty-five OA patients, 30 ONA subjects, and 30 mild-to-moderate LA age-matched patients participated in a cross-sectional study. Nuclear magnetic resonance (NMR) profiles were analyzed by using partial least-squares discriminant analysis, and the results were validated with an independent patient set.

RESULTS

From NMR profiles, we obtained strong regression models that distinguished OA patients from ONA subjects (quality parameters: goodness-of-fit parameter [R²] = 0.81 and goodness-of-prediction parameter [Q²] = 0.79), as well as OA patients from LA patients (R² = 0.91 and Q² = 0.89). The all-classes comparison (R² = 0.86 and Q² = 0.83) indicated that OA patients possess a respiratory metabolic profile fully divergent from those obtained in the other patient groups. We also identified specific biomarkers for between-class separation, which are independent from clinical bias. They are involved in the methane, pyruvate, and glyoxylate and dicarboxylate metabolic pathways.

CONCLUSIONS

NMR-based metabolomics indicates that OA patients are characterized by a respiratory metabolic fingerprint fully different from that of patients independently affected by asthma or obesity. Such a phenotypic difference strongly suggests unique pathophysiologic pathways involved in the pathogenesis of asthma in adult obese subjects. Furthermore, the OA metabotype could define a strategy for patient stratification based on unbiased biomarkers, with important diagnostic and therapeutic implications.

Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine

"Omics" sciences have been developed to provide a holistic point of view of biology and to better understand the complexity of an organism as a whole. These systems biology approaches can be examined at different levels, starting from the most fundamental, i.e., the genome, and finishing with the most functional, i.e., the metabolome. Similar to how genomics is applied to the exploration of DNA, metabolomics is the qualitative and quantitative study of metabolites. This emerging field is clearly linked to genomics, transcriptomics, and proteomics. In addition, metabolomics provides a unique and direct vision of the functional outcome of an organism's activities that are required for it to survive, grow, and respond to internal and external stimuli or stress, e.g., pathologies and drugs. The links between metabolic changes, patient phenotype, physiological and/or pathological status, and treatment are now well established and have opened a new area for the application of metabolomics in the drug discovery process and in personalized medicine.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.

Metabolic alterations in the sera of Chinese patients with mild persistent asthma: a GC-MS-based metabolomics analysis

AIM

To character the specific metabolomics profiles in the sera of Chinese patients with mild persistent asthma and to explore potential metabolic biomarkers.

METHODS

Seventeen Chinese patients with mild persistent asthma and age- and sex-matched healthy controls were enrolled. Serum samples were collected, and serum metabolites were analyzed using GC-MS coupled with a series of multivariate statistical analyses.

RESULTS

Clear intergroup separations existed between the asthmatic patients and control subjects. A list of differential metabolites and several top altered metabolic pathways were identified. The levels of succinate (an intermediate in tricarboxylic acid cycle) and inosine were highly upregulated in the asthmatic patients, suggesting a greater effort to breathe during exacerbation and hypoxic stress due to asthma. Other differential metabolites, such as 3,4-dihydroxybenzoic acid and phenylalanine, were also identified. Furthermore, the differential metabolites possessed higher values of area under the ROC curve (AUC), suggesting an excellent clinical ability for the prediction of asthma.

CONCLUSION

Metabolic activity is significantly altered in the sera of Chinese patients with mild persistent asthma. The data might be helpful for identifying novel biomarkers and therapeutic targets for asthma.