Serum metabolomics reveals pathways and biomarkers associated with asthma pathogenesis

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.

Urinary Metabolomic Profiling Reveals Biological Pathways and Predictive Signatures Associated with Childhood Asthma

Background

Despite considerable efforts, the pathogenic mechanisms of asthma are still incompletely understood, due to its heterogeneous nature. However, metabolomics can offer a global view of a biological system, making it a valuable tool for further elucidation of mechanisms and biomarker discovery in asthma.

Methods

GC-MS-based metabolomic analysis was conducted for comparison of urine metabolic profiles between asthmatic children (n=30) and healthy controls (n=30).

Results

An orthogonal projections to latent structures discriminant-analysis model revealed a clear separation of the asthma and control groups (R ² _x =0.137, R ² _y =0.947, Q ²=0.82). A total of 20 differential metabolites were identified as discriminant factors, of which eleven were significantly increased and nine decreased in the asthma group compared to the control group. Pathway-enrichment analysis based on these differential metabolites indicated that sphingolipid metabolism, protein biosynthesis, and citric acid cycle were strongly associated with asthma. Among the identified metabolites, 2-hydroxybutanoic acid showed excellent discriminatory performance for distinguishing asthma from healthy controls, with an AUC of 0.969.

Conclusion

Our study revealed significant changes in the urine metabolome of asthma patients. Several perturbed pathways (eg, sphingolipid metabolism and citric acid cycle) may be related to asthma pathogenesis, and 2-hydroxybutanoic acid could serve as a potential biomarker for asthma diagnosis.

Effects of different stocking densities on tracheal barrier function and its metabolic changes in finishing broilers

In the present study, we evaluated the effects of various stocking densities on the tracheal barrier and plasma metabolic profiles of finishing broilers. We randomly assigned 1,440 Lingnan Yellow feathered broilers (age 22 d) to 5 different stocking density groups (8 m-2, 10 m-2, 12 m-2, 14 m-2, and 16 m-2). Each of these consisted of 3 replicates. The interleukin (IL)-1β and IL-10 concentrations were substantially higher in the 16 m-2 treatment group than they were in the 8 m-2 and 10 m-2 treatment groups (P < 0.05). Nevertheless, IL-4 did not significantly differ among the 5 treatments (P > 0.05). The tracheal mucosae of the birds in the 16 m-2 group (high stocking density, HSD) were considerably thicker than those for the birds in the 10 m-2 group (control, CSD). Relative to CSD, the claudin1 expression level was lower, and the muc2 and caspase3 expression levels were higher for HSD. Compared with CSD, 10 metabolites were significantly upregulated (P < 0.05), and 7 were significantly downregulated (P < 0.05) in HSD. Most of these putative diagnostic biomarkers were implicated in matter biosynthesis and energy metabolism. A metabolic pathway analysis revealed that the most relevant and critical biomarkers were pentose and glucuronate interconversions and the pentose phosphate pathway. Activation of the aforementioned pathways may partially counteract the adverse effects of the stress induced by high stocking density. This work helped improve our understanding of the harmful effects of high stocking density on the tracheal barrier and identified 2 metabolic pathways that might be associated with high stocking density-induced metabolic disorders in broilers.

Integration of metagenomics-metabolomics reveals specific signatures and functions of airway microbiota in mite-sensitized childhood asthma

BACKGROUND

Childhood asthma is a multifactorial inflammatory condition of the airways, associated with specific changes in respiratory microbiome and circulating metabolome.

METHODS

To explore the functional capacity of asthmatic microbiome and its intricate connection with the host, we performed shotgun sequencing of airway microbiome and untargeted metabolomics profiling of serum samples in a cohort of children with mite-sensitized asthma and non-asthmatic controls.

RESULTS

We observed higher gene counts and sample-to-sample dissimilarities in asthmatic microbiomes, indicating a more heterogeneous community structure and functionality among the cases than in controls. Moreover, we identified airway microbial species linked to changes in circulating metabolites and IgE responses of the host, including a positive correlation between Prevotella sp oral taxon 306 and dimethylglycine that were both decreased in patients. Several control-enriched species (Eubacterium sulci, Prevotella pallens, and Prevotella sp oral taxon 306) were inversely correlated with total and allergen-specific IgE levels. Genes related to microbial carbohydrate, amino acid, and lipid metabolism were differentially enriched, suggesting that changes in microbial metabolism may contribute to respiratory health in asthmatics. Pathway modules relevant to allergic responses were differentially abundant in asthmatic microbiome, such as enrichments for biofilm formation by Pseudomonas aeruginosa, membrane trafficking, histidine metabolism, and glycosaminoglycan degradation, and depletions for polycyclic aromatic hydrocarbon degradation. Further, we identified metagenomic and metabolomic markers (eg, Eubacterium sulci) to discriminate cases from the non-asthmatic controls.

CONCLUSIONS

Our dual-omics data reveal the connections between respiratory microbes and circulating metabolites perturbed in mite-sensitized pediatric asthma, which may be of etiological and diagnostic implications.

Metabolomics analysis of bronchoalveolar lavage fluid samples in horses with naturally-occurring asthma and experimentally-induced airway inflammation

The present work characterized the metabolomic profile of bronchoalveolar lavage fluid (BALF) in healthy horses, experimentally-induced airway inflammation by lipopolysaccharide (LPS) nebulization, and naturally-occurring asthma (n = 3 in each group). All animals underwent clinical and upper airway endoscopic examinations, and bronchoalveolar lavage. BALF supernatant samples were subjected to metabolic analysis based on gas chromatography-mass spectrometry (GC-MS). Overall, 67 peaks were obtained from BALF GC-MS analysis, corresponding to 53 metabolites which were categorized according to chemical class, such as organic acids, fatty acids, nucleosides or their derivatives, amino acids, peptides or their derivatives, carbohydrates, and other compounds. Our results showed that the airway inflammation induction model with LPS produced the same pattern of metabolite changes as in horses with naturally occurring asthma. Metabolic pathway analysis was done by means of Fisher's exact test, for detection of metabolites over-represented in asthma affected-horses and LPS-induced airway inflammation as compared with healthy horses. The most significant altered metabolic pathways were fatty acid biosynthesis, galactose metabolism and citrate cycle. These results suggest that the airway inflammation induction model with LPS is a good study model for asthma-affected horses, due to the similarity of the profile of inflammatory cells (specifically neutrophils) and similar metabolic alterations found in BALF that occur during the inflammatory process of the airways. Further research may increase understanding of metabolomics disturbances and their significance in the pathogenesis of equine asthma.

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.

Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans

The unabated global increase of allergic patients leads to an unmet need for rapid and inexpensive tools for the diagnosis of allergies and for monitoring the outcome of allergen-specific immunotherapy (SIT). In this proof-of-concept study, we investigated the potential of Fourier-Transform Infrared (FTIR) spectroscopy, a high-resolution and cost-efficient biophotonic method with high throughput capacities, to detect characteristic alterations in serum samples of healthy, allergic, and SIT-treated mice and humans. To this end, we used experimental models of ovalbumin (OVA)-induced allergic airway inflammation and allergen-specific tolerance induction in BALB/c mice. Serum collected before and at the end of the experiment was subjected to FTIR spectroscopy. As shown by our study, FTIR spectroscopy, combined with deep learning, can discriminate serum from healthy, allergic, and tolerized mice, which correlated with immunological data. Furthermore, to test the suitability of this biophotonic method for clinical diagnostics, serum samples from human patients were analyzed by FTIR spectroscopy. In line with the results from the mouse models, machine learning-assisted FTIR spectroscopy allowed to discriminate sera obtained from healthy, allergic, and SIT-treated humans, thereby demonstrating its potential for rapid diagnosis of allergy and clinical therapeutic monitoring of allergic patients.

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.

Metabolomic fingerprinting and systemic inflammatory profiling of asthma COPD overlap (ACO)

Background

Asthma-COPD overlap (ACO) refers to a group of poorly studied and characterised patients reporting with disease presentations of both asthma and COPD, thereby making both diagnosis and treatment challenging for the clinicians. They exhibit a higher burden in terms of both mortality and morbidity in comparison to patients with only asthma or COPD. The pathophysiology of the disease and its existence as a unique disease entity remains unclear. The present study aims to determine whether ACO has a distinct metabolic and immunological mediator profile in comparison to asthma and COPD.

Methods

Global metabolomic profiling using two different groups of patients [discovery (D) and validation (V)] were conducted. Serum samples obtained from moderate and severe asthma [n = 34(D); n = 32(V)], moderate and severe COPD [n = 30(D); 32(V)], ACO patients [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using gas chromatography mass spectrometry (GC-MS). Multiplexed analysis of 25 immunological markers (IFN-γ (interferon gamma), TNF-α (tumor necrosis factor alpha), IL-12p70 (interleukin 12p70), IL-2, IL-4, IL-5, IL-13, IL-10, IL-1α, IL-1β, TGF-β (transforming growth factor), IL-6, IL-17E, IL-21, IL-23, eotaxin, GM-CSF (granulocyte macrophage-colony stimulating factor), IFN-α (interferon alpha), IL-18, NGAL (neutrophil gelatinase-associated lipocalin), periostin, TSLP (thymic stromal lymphopoietin), MCP-1 (monocyte chemoattractant protein- 1), YKL-40 (chitinase 3 like 1) and IL-8) was also performed in the discovery cohort.

Results

Eleven metabolites [serine, threonine, ethanolamine, glucose, cholesterol, 2-palmitoylglycerol, stearic acid, lactic acid, linoleic acid, D-mannose and succinic acid] were found to be significantly altered in ACO as compared with asthma and COPD. The levels and expression trends were successfully validated in a fresh cohort of subjects. Thirteen immunological mediators including TNFα, IL-1β, IL-17E, GM-CSF, IL-18, NGAL, IL-5, IL-10, MCP-1, YKL-40, IFN-γ, IL-6 and TGF-β showed distinct expression patterns in ACO. These markers and metabolites exhibited significant correlation with each other and also with lung function parameters.

Conclusions

The energy metabolites, cholesterol and fatty acids correlated significantly with the immunological mediators, suggesting existence of a possible link between the inflammatory status of these patients and impaired metabolism. The present findings could be possibly extended to better define the ACO diagnostic criteria, management and tailoring therapies exclusively for the disease.

Linking endotypes to omics profiles in difficult-to-control asthma using the diagnostic Chinese medicine syndrome differentiation algorithm

Objective: Patients with difficult-to-control asthma have difficulty breathing almost all of the time, even leading to life-threatening asthma attacks. However, only few diagnostic markers for this disease have been identified. We aimed to take advantage of unique Chinese medicine theories for phenotypic classification and to explore molecular signatures in difficult-to-control asthma. Methods: The Chinese medicine syndrome differentiation algorithm (CMSDA) is a syndrome-scoring classification method based on the Chinese medicine overall observation theory. Patients with difficult-to-control asthma were classified into Cold- and Hot-pattern groups according to the CMSDA. DNA methylation and metabolomic profiles were obtained using Infinium Human Methylation 450 BeadChip and gas chromatography-mass spectrometer. Subsequently, an integrated bioinformatics analysis was performed to compare those two patterns and identify Cold/Hot-associated candidates, followed by functional validation studies. Results: A total of 20 patients with difficult-to-control asthma were enrolled in the study. Ten were grouped as Cold and 10 as Hot according to the CMSDA. We identified distinct whole-genome DNA methylation and metabolomic profiles between Cold- and Hot-pattern groups. ALDH3A1 gene exhibited variations in the DNA methylation probe cg10791966, while two metabolic pathways were associated with those two patterns. Conclusions: Our study introduced a novel diagnostic classification approach, the CMSDA, for difficult-to-control asthma. This is an alternative way to categorize diverse syndromes and link endotypes with omics profiles of this disease. ALDH3A1 might be a potential biomarker for precision diagnosis of difficult-to-control asthma.

Intriguing pH-modulated Luminescence Chameleon System based on Postsynthetic Modified Dual-emitting Eu3+@Mn-MOF and Its Application for Histidine Chemosensor

Due to the disruption by other nonanalyte factors, single-emission probes have been limited in complicated detecting systems. In this work, a pH-modulated luminescence chameleon system based on lanthanide-based MOF (Eu³⁺@Mn-MOF), with stable structure and miraculous dual-emitting fluorescent properties, was synthesized by a postsynthetic modification (PSM) strategy of a simple hydrothermal and agitation method. Amazingly, not only can the Eu³⁺@Mn-MOF emit a broad emission at 500 nm attributed to the ligand-based fluorescence emission but it can also exhibit the characteristic emission of Eu³⁺ ions responding to the antenna effect. Moreover, the Eu³⁺@Mn-MOF displays an interesting luminescence color transition between acidic and basic solutions. Inspired by this phenomenon, a pH-modulated luminescence chameleon system was first constructed and employed to detect histidine, a kind of basic amino acid for a variety of biological matters, causing a unique fluorescence signal of the ratio-dependent color to change from yellow to light pink which differs from the color change of other water-soluble amino acids. Therefore, Eu³⁺@Mn-MOF can be as a practical pH-modulated luminescence chameleon system chemsensor for sensing histidine with low detection limit, high sensitivity, and rapid sensing time. In conclusion, the postsynthetic modified Eu³⁺@Mn-MOF has outstanding applications in the fields of chemical detection and human health.

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.

Integration of transcriptomics, proteomics and metabolomics identifies biomarkers for pulmonary injury by polyhexamethylene guanidine phosphate (PHMG-p), a humidifier disinfectant, in rats

Polyhexamethylene guanidine phosphate (PHMG-p) was used as a humidifier disinfectant in Korea. PHMG induced severe pulmonary fibrosis in Koreans. The objective of this study was to elucidate mechanism of pulmonary toxicity caused by PHMG-p in rats using multi-omics analysis. Wistar rats were intratracheally instilled with PHMG-p by single (1.5 mg/kg) administration or 4-week (0.1 mg/kg, 2 times/week) repeated administration. Histopathologic examination was performed with hematoxylin and eosin staining. Alveolar macrophage aggregation and granulomatous inflammation were observed in rats treated with single dose of PHMG-p. Pulmonary fibrosis, chronic inflammation, bronchiol-alveolar fibrosis, and metaplasia of squamous cell were observed in repeated dose group. Next generation sequencing (NGS) was performed for transcriptome profiling after mRNA isolation from bronchiol-alveoli. Bronchiol-alveoli proteomic profiling was performed using an Orbitrap Q-exactive mass spectrometer. Serum and urinary metabolites were determined using 1H-NMR. Among 418 differentially expressed genes (DEGs) and 67 differentially expressed proteins (DEPs), changes of 16 mRNA levels were significantly correlated with changes of their protein levels in both single and repeated dose groups. Remarkable biological processes represented by both DEGs and DEPs were defense response, inflammatory response, response to stress, and immune response. Arginase 1 (Arg1) and lipocalin 2 (Lcn2) were identified to be major regulators for PHMG-p-induced pulmonary toxicity based on merged analysis using DEGs and DEPs. In metabolomics study, 52 metabolites (VIP > 0.5) were determined in serum and urine of single and repeated-dose groups. Glutamate and choline were selected as major metabolites. They were found to be major factors affecting inflammatory response in association with DEGs and DEPs. Arg1 and Lcn2 were suggested to be major gene and protein related to pulmonary damage by PHMG-p while serum or urinary glutamate and choline were endogenous metabolites related to pulmonary damage by PHMG-p.

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.

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.

Priorities for future research into asthma diagnostic tools: A PAN-EU consensus exercise from the European asthma research innovation partnership (EARIP)

The diagnosis of asthma is currently based on clinical history, physical examination and lung function, and to date, there are no accurate objective tests either to confirm the diagnosis or to discriminate between different types of asthma. This consensus exercise reviews the state of the art in asthma diagnosis to identify opportunities for future investment based on the likelihood of their successful development, potential for widespread adoption and their perceived impact on asthma patients. Using a two-stage e-Delphi process and a summarizing workshop, a group of European asthma experts including health professionals, researchers, people with asthma and industry representatives ranked the potential impact of research investment in each technique or tool for asthma diagnosis and monitoring. After a systematic review of the literature, 21 statements were extracted and were subject of the two-stage Delphi process. Eleven statements were scored 3 or more and were further discussed and ranked in a face-to-face workshop. The three most important diagnostic/predictive tools ranked were as follows: "New biological markers of asthma (eg genomics, proteomics and metabolomics) as a tool for diagnosis and/or monitoring," "Prediction of future asthma in preschool children with reasonable accuracy" and "Tools to measure volatile organic compounds (VOCs) in exhaled breath."

Metabolomic signatures of asthma-COPD overlap (ACO) are different from asthma and COPD

INTRODUCTION

Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease without any clear diagnostic or therapeutic guidelines. The pathophysiology of the disease, its characteristic features, and existence as a unique disease entity remains unclear. Individuals with ACO have a faster lung function decline, more frequent exacerbations, and worse quality of life than those with COPD or asthma alone.

OBJECTIVES

The present study aims to determine whether ACO has a distinct metabolic profile in comparison to asthma and COPD.

METHODS

Two different groups of patients were recruited as discovery (D) and validation (V) cohorts. Serum samples obtained from moderate and severe asthma patients diagnosed as per GINA guidelines [n = 34(D); n = 32(V)], moderate and severe COPD cases identified by GOLD guidelines [n = 30(D); 32(V)], ACO patients diagnosed by joint GOLD and GINA guidelines [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using nuclear magnetic resonance (NMR) spectrometry.

RESULTS

Multivariate and univariate analysis indicated that 12 metabolites [lipid, isoleucine, N-acetylglycoproteins (NAG), valine, glutamate, citric acid, glucose, L-leucine, lysine, asparagine, phenylalanine and histidine] were dysregulated in ACO patients when compared with both asthma and COPD. These metabolites were further validated in a fresh cohort of patients, which again exhibited a similar expression pattern.

CONCLUSIONS

Our findings suggest that ACO has an enhanced energy and metabolic burden associated with it as compared to asthma and COPD. It is anticipated that our results will stimulate researchers to further explore ACO and unravel the pathophysiological complexities associated with the disease.

Development of a new quantification method for organic acids in urine as potential biomarkers for respiratory illness

Asthma and chronic obstructive pulmonary disease (COPD) are common respiratory disorders that have similar clinical presentation and misdiagnosis may lead to improper treatment. There is a need for a better, non-invasive test for the differentiation of asthma and COPD. In this study, we developed a new validated LC-MS/MS method for 17 urinary organic acids that could serve as potential biomarkers. Human urine samples were collected from adults with asthma or COPD. LC-MS/MS was performed using the differential isotope labeling approach. 4-(Dimethylamino) phenacyl bromide (DmPA) was used for derivatization using two different carbon isotopes, allowing for the formation of internal standard for each metabolite. Gradient elution was employed on a C₁₈ column while the LC-MS/MS operated in the multiple reaction monitoring mode (MRM). Regulatory guidelines were used for method validation. Partial Least Squares Discriminative Analysis (PLS-DA) was applied to the log-transformed values of metabolites in each group of asthma and COPD subjects. Full validation in targeted metabolomics is scarce with usually limited number of metabolites, unlike fit-for-purpose approach. Due to the endogenous nature of the metabolites, numerous challenges were encountered during method development and validation, such as the lactic acid interference from the surrounding environment. The required specificity, accuracy and precision was successfully achieved. The method was fully validated, ensuring robustness and reproducibility when analyzing patient samples. The method was applied to analyze human urine samples and PLS-DA analysis showed differentiation of asthma and COPD subjects (R2 0.89, Q2 0.68). As targeted metabolomics is expanding to the clinical sphere, more validated methods/strategies are needed. Our work will expand the current knowledge-base regarding targeted metabolomics.

The Study of Dried Ginger and Linggan Wuwei Jiangxin Decoction Treatment of Cold Asthma Rats Using GC-MS Based Metabolomics

Dried ginger is the monarch drug in Linggan Wuwei Jiangxin (LGWWJX) decoction, which is used to treat cold asthma. The purpose of this study was to investigate and compare the effects of dried ginger and LGWWJX decoction for treatment of cold asthma rats at the metabolomics level using gas chromatography–mass spectrometry (GC–MS). OVA and ice water-induced cold asthma were induced in SD rats. The effects of dried ginger and LGWWJX decoction were evaluated by general morphological observation, hematoxylin and eosin staining, inflammatory cell count, IgE, IL-4, IFN-γ quantitation, and visceral index. GC-MS-based metabolomics was performed and analyzed using multivariate statistical analysis. Biomarker identification, pathway analysis, correlations between identified biomarker, and efficacy indices were performed. The results showed that dried ginger and LGWWJX decoction had obvious effects on cold asthma rats. Thirty-seven metabolites (15 in serum and 22 in urine) associated with cold asthma were identified. These metabolites were mainly carbohydrates, fatty acids and their products, organic acids, and others. Seven pathways were identified by MetaboAnalyst 4.0 metabolic pathway analysis. After intervention with dried ginger and LGWWJX decoction, the majority of altered metabolites and metabolic pathways returned to control levels. LGWWJX decoction regulated more metabolites of carbohydrates and fatty acids, which contribute to energy metabolism and oxidative stress in cold asthma, than dried ginger. We concluded that dried ginger and LGWWJX decoction both were effective for treatment of cold asthma. LGWWJX decoction was more effective than dried ginger for treatment of cold asthma. This study evaluated the effects of dried ginger and LGWWJX decoction on cold asthma at the metabolomics level. It provides a reference for the research on the compatibility of Chinese Medicine.

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.

Multi-omics analysis points to altered platelet functions in severe food-associated respiratory allergy

BACKGROUND

Prevalence and severity of allergic diseases have increased worldwide. To date, respiratory allergy phenotypes are not fully characterized and, along with inflammation progression, treatment is increasingly complex and expensive. Profilin sensitization constitutes a good model to study the progression of allergic inflammation. Our aim was to identify the underlying mechanisms and the associated biomarkers of this progression, focusing on severe phenotypes, using transcriptomics and metabolomics.

METHODS

Twenty-five subjects were included in the study. Plasma samples were analyzed using gas and liquid chromatography coupled to mass spectrometry (GC-MS and LC-MS, respectively). Individuals were classified in four groups-"nonallergic," "mild," "moderate," and "severe"-based on their clinical history, their response to an oral challenge test with profilin, and after a refinement using a mathematical metabolomic model. PBMCs were used for microarray analysis.

RESULTS

We found a set of transcripts and metabolites that were specific for the "severe" phenotype. By metabolomics, a decrease in carbohydrates and pyruvate and an increase in lactate were detected, suggesting aerobic glycolysis. Other metabolites were incremented in "severe" group: lysophospholipids, sphingosine-1-phosphate, sphinganine-1-phosphate, and lauric, myristic, palmitic, and oleic fatty acids. On the other hand, carnitines were decreased along severity. Significant transcripts in the "severe" group were found to be downregulated and were associated with platelet functions, protein synthesis, histone modification, and fatty acid metabolism.

CONCLUSION

We have found evidence that points to the association of severe allergic inflammation with platelet functions alteration, together with reduced protein synthesis, and switch of immune cells to aerobic glycolysis.

Partial Least Squares Discriminant Analysis and Bayesian Networks for Metabolomic Prediction of Childhood Asthma

To explore novel methods for the analysis of metabolomics data, we compared the ability of Partial Least Squares Discriminant Analysis (PLS-DA) and Bayesian networks (BN) to build predictive plasma metabolite models of age three asthma status in 411 three year olds (n = 59 cases and 352 controls) from the Vitamin D Antenatal Asthma Reduction Trial (VDAART) study. The standard PLS-DA approach had impressive accuracy for the prediction of age three asthma with an Area Under the Curve Convex Hull (AUCCH) of 81%. However, a permutation test indicated the possibility of overfitting. In contrast, a predictive Bayesian network including 42 metabolites had a significantly higher AUCCH of 92.1% (p for difference < 0.001), with no evidence that this accuracy was due to overfitting. Both models provided biologically informative insights into asthma; in particular, a role for dysregulated arginine metabolism and several exogenous metabolites that deserve further investigation as potential causative agents. As the BN model outperformed the PLS-DA model in both accuracy and decreased risk of overfitting, it may therefore represent a viable alternative to typical analytical approaches for the investigation of metabolomics data.

1H-NMR-based metabolic profiling of healthy individuals and high-resolution CT-classified phenotypes of COPD with treatment of tiotropium bromide

Background

Heterogeneity of COPD results in different therapeutic effects for different patients receiving the same treatment. COPD patients need to be individually treated according to their own characteristics. The purpose of this study was to explore the differences in different CT phenotypic COPD by molecular metabolites through the use of metabolomics.

Methods

According to the characteristics of CT imaging, 42 COPD patients were grouped into phenotype E (n=20) or phenotype M (n=24). Each COPD patient received tiotropium bromide powder for inhalation for a therapeutic period of 3 months. All subjects were assigned into phenotype E in pre-therapy (EB, n=20), phenotype E in post-therapy (EA, n=20), phenotype M in pre-therapy (MB, n=22), phenotype M in post-therapy (MA, n=22), or normal control (N, n=24). The method of metabolomics based on ¹H nuclear magnetic resonance (¹H-NMR) was used to compare the changes in serum metabolites between COPD patients and normal controls and between different phenotypes of COPD patients in pre- and post-therapy.

Results

Patients with COPD phenotype E responded better to tiotropium bromide than patients with COPD phenotype M in terms of pulmonary function and COPD assessment test scores. There were differences in metabolites in COPD patients vs normal control people. Differences were also observed between different COPD phenotypic patients receiving the treatment in comparison with those who did not receive treatment. The changes of metabolites involved lactate, phenylalanine, fructose, glycine, asparagine, citric acid, pyruvic acid, proline, acetone, ornithine, lipid, pyridoxine, maltose, betaine, lipoprotein, and so on. These identified metabolites covered the metabolic pathways of amino acids, carbohydrates, lipids, genetic materials, and vitamin.

Conclusion

The efficacy of tiotropium bromide on COPD phenotype E is better than that of phenotype M. Metabolites detected by ¹H-NMR metabolomics have potentialities of differentiation of COPD and healthy people, discrimination of different COPD phenotypes, and giving insight into the individualized treatment of COPD.

Metabolomics of tracheal wash samples and exhaled breath condensates in healthy horses and horses affected by equine asthma

The present work characterized the metabolomic profile of tracheal wash (TW) and exhaled breath condensate (EBC) in healthy horses and horses with respiratory disease. Six asthma-affected horses (group A) and six healthy controls (group H) underwent clinical, endoscopic and cytologic examinations of upper airways to confirm the active phase of asthma. TW and EBC samples were collected from each animal and investigated by proton nuclear magnetic resonance (¹H-NMR) metabolomic analysis. A total of ten out of 38 metabolites found in the TW were significantly different between the groups (p < 0.05). Higher concentrations of histamine and oxidant agents, such as glutamate, valine, leucine and isoleucine, as well as lower levels of ascorbate, methylamine, dimethylamine and O-phosphocholine, were found in group A compared to group H. Eight metabolites were found in equine EBC, namely methanol, ethanol, formate, trimethylamine, acetone, acetate, lactate and butanone, previously observed also in human EBC. Despite the fact that this was a pilot study, the results showed that the metabolomic analysis of TW and EBC has the potentiality to serve as a basis for diagnostic tools in horses with asthma.

Quantitative determination of potential urine biomarkers of respiratory illnesses using new targeted metabolomic approach

The diagnosis of asthma and chronic obstructive pulmonary disease (COPD) can be challenging due to the overlap in their clinical presentations in some patients. There is a need for a more objective clinical test that can be routinely used in primary care settings. Through an untargeted ¹H NMR urine metabolomic approach, we identified a set of endogenous metabolites as potential biomarkers for the differentiation of asthma and COPD. A subset of these potential biomarkers contains 7 highly polar metabolites of diverse physicochemical properties. To the best of our knowledge, there is no liquid chromatography-tandem mass spectrometry (LC-MS/MS) method that evaluated more than two of the target metabolites in a single analytical run. The target metabolites belong to the families of monosaccharides, organic acids, amino acids, quaternary ammonium compounds and nucleic acids, rendering hydrophilic interaction liquid chromatography (HILIC) an ideal technology for their quantification. Since a clinical decision is to be made from patients data, a fully validated analytical method is required for biomarker validation. Method validation for endogenous metabolites is a daunting task since current guidelines were designed for exogenous compounds. As such, innovative approaches were adopted to meet the validation requirements. Herein, we describe a sensitive HILIC-MS/MS method for the quantification of the 7 endogenous urinary metabolites. Detection was achieved in the multiple reaction monitoring (MRM) mode with polarity switching, using quadrupole-linear ion trap instrument (QTRAP 6500) as well as single ion monitoring in the negative-ion mode. The method was fully validated according to the regulatory guidelines. Linearity was established between 6 and 21000 ng/mL and quality control samples demonstrated acceptable intra- and inter-day accuracy (85.7%-112%), intra- and inter-day precision (CV% <11.5%) as well as stability under various storage and sample processing conditions. To illustrate the method's applicability, the validated method was applied to the analysis of a small set of urine samples collected from asthma and COPD patients. Preliminary modelling of separation was generated using partial least square discriminant analysis (R² 0.752 and Q² 0.57). The adequate separation between patient samples confirms the diagnostic potential of these target metabolites as a proof-of-concept for the differentiation between asthma and COPD. However, more patient urine samples are needed in order to increase the statistical power of the analytical model.

Serum Metabolomics Analysis of Asthma in Different Inflammatory Phenotypes: A Cross-Sectional Study in Northeast China

BACKGROUND AND OBJECTIVE

Asthma as a chronic heterogeneous disease seriously affects the quality of life. Incorrect identification for its clinical phenotypes lead to a huge waste of medical resources. Metabolomic technique as a novel approach to explore the pathogenesis of diseases have not been used to study asthma based on their clear defined inflammatory phenotypes. This study is aimed to distinguish the divergent metabolic profile in different asthma phenotypes and clarify the pathogenesis of them.

METHODS

Participants including eosinophilic asthmatics (EA, n=13), noneosinophilic asthmatics (NEA, n=16), and healthy controls (HC, n=15) were enrolled. A global profile of untargeted serum metabolomics was identified with Ultra Performance Liquid Chromatography-Mass Spectrometry technique.

RESULTS

Multivariate analysis was performed and showed a clear distinction between EA, NEA, and HC. A total of 18 different metabolites were recognized between the three groups based on OPLS-DA model and involved in 10 perturbed metabolic pathways. Glycerophospholipid metabolism, retinol metabolism, and sphingolipid metabolism were identified as the most significant changed three pathways (impact > 0.1 and -log(P) > 4) between the phenotypes.

CONCLUSIONS

We showed that the different inflammatory phenotypes of asthma involve the immune regulation, energy, and nutrients metabolism. The clarified metabolic profile contributes to understanding the pathophysiology of asthma phenotypes and optimizing the therapeutic strategy against asthma heterogeneity.

Longitudinal urinary metabolomic profiling reveals metabolites for asthma development in early childhood

BACKGROUND

Several metabolites and altered metabolic pathways have been reported to be associated with asthma. However, longitudinal analysis of the dynamics of metabolites contributing to the development of asthma has not yet been fully clarified.

METHODS

We sought to identify the metabolic mechanisms underlying asthma development in early childhood. Thirty children with asthma and paired healthy controls from a prospective birth cohort were enrolled. Time series analysis of urinary metabolites collected at ages 1, 2, 3, and 4 years was assessed using ¹ H nuclear magnetic resonance (NMR) spectroscopy coupled with partial least squares discriminant analysis (PLS-DA). Metabolites identified were studied in relation to changes over time in a linear mixed model for repeated measures.

RESULTS

A total of 172 urine samples collected from the enrolled children were analyzed. Urinary metabolomics identified four metabolites significantly associated with childhood asthma development, with longitudinal analysis. Among them, dimethylamine, a metabolite produced by intestinal bacteria, appeared to shift from higher to lower level during asthma development. A persistent lower level of 1-methylnicotinamide and allantoin was found in children with asthma, with a peak difference at age 3 years (P = .032 and P = .021, respectively). Furthermore, a significant inverse correlation was found between allantoin and house dust mite sensitization (Spearman's r = -.297 P = .035).

CONCLUSIONS

Longitudinal urinary metabolomic profiling provides a link of microbe-environment interactions in the development of childhood asthma. 1-Methylnicotinamide and allantoin may participate in allergic reactions in response to allergen exposure, potentially serving as specific biomarkers for asthma.

Plasma metabolite profiles in children with current asthma

BACKGROUND

Identifying metabolomic profiles of children with asthma has the potential to increase understanding of asthma pathophysiology.

OBJECTIVE

To identify differences in plasma metabolites between children with and without current asthma at mid-childhood.

METHODS

We used untargeted mass spectrometry to measure plasma metabolites in 237 children (46 current asthma cases and 191 controls) in Project Viva, a birth cohort from eastern Massachusetts, USA. Current asthma was assessed at mid-childhood (mean age 8.0 years). The ability of a broad spectrum metabolic profile to distinguish between cases and controls was assessed using partial least squares discriminant analysis. We used logistic regression models to identify individual metabolites that were differentially abundant by case-control status. We tested significant metabolites for replication in 411 children from the VDAART clinical trial.

RESULTS

There was no evidence of a systematic difference in the metabolome of children reporting current asthma vs. healthy controls according to partial least squares discriminant analysis. However, several metabolites were associated with odds of current asthma at a nominally significant threshold (P < .05), including a metabolite of nicotinamide (N1-Methyl-2-pyridone-5-carboxamide (Odds Ratio (OR) = 2.8 (95% CI 1.1-8.0)), a pyrimidine metabolite (5,6-dihydrothymine (OR = 0.4 (95% CI 0.2-0.9)), bile constituents (biliverdin (OR = 0.4 (95%CI 0.1-0.9), taurocholate (OR = 2.0 (95% CI 1.2-3.4)), two peptides likely derived from fibrinopeptide A (ORs from 1.6 to 1.7), and a gut microbiome metabolite (p-cresol sulphate OR = 0.5 (95% CI 0.2-0.9)). The associations for N1-Methyl-2-pyridone-5-carboxamide and p-cresol sulphate replicated in the independent VDAART population (one-sided P values = .03-.04).

CONCLUSIONS AND CLINICAL RELEVANCE

Current asthma is nominally associated with altered levels of several metabolites, including metabolites in the nicotinamide pathway, and a bacterial metabolite derived from the gut microbiome.

Increased urinary l-histidine in patients with asthma-COPD overlap: a pilot study

Purpose

Asthma-COPD overlap (ACO) is heterogeneous in nature and requires a unified diagnostic approach. We investigated the urinary levels of l-histidine, a precursor of histamine related to inflammatory responses, as a new candidate biomarker for diagnosing this condition.

Patients and methods

We performed a prospective multicenter cohort study with retrospective analysis of 107 patients, who were divided into three groups: asthma, COPD, and ACO, according to the Spanish guidelines algorithm. Urinary l-histidine levels were measured using liquid chromatography-mass spectrometry. High-resolution metabolomic analysis, coupled with liquid chromatography-mass spectrometry and followed by multivariate statistical analysis, was performed on urine samples to discriminate between the metabolic profiles of the groups.

Results

Urinary l-histidine levels were significantly higher in patients with ACO than in those with asthma or COPD, but the subgroups of ACO, classified according to disease origin, did not differ significantly. High urinary l-histidine level was a significant factor for the diagnosis of ACO even after adjusting for age, sex, and smoking amount. Among patients with airflow obstruction, the urinary l-histidine levels were elevated in patients with a documented history of asthma before the age of 40 years or bronchodilator responsiveness ≥400 mL; bronchodilator responsiveness ≥200 mL of forced expiratory volume in 1 second and exceeding baseline values by 12% on two or more visits; blood eosinophil count ≥300 cells·mm^-3; and frequent exacerbations (P < 0.05).

Conclusion

Urinary l-histidine could be a potential biomarker for ACO, regardless of the diversity of diagnostic definitions used.

Application of Metabolomics in Lung Research

Advancements in omics technologies have increased our potential to evaluate molecular changes in a rapid and comprehensive manner. This is especially true in mass spectrometry-based metabolomics where improvements, including ease of use, in high-performance liquid chromatography (HPLC), column chemistries, instruments, software, and molecular databases, have advanced the field considerably. Applications of this relatively new omics technology in clinical research include discovering disease biomarkers, finding new drug targets, and elucidating disease mechanisms. Here we describe a typical clinical metabolomics workflow, which includes the following steps: (1) extraction of metabolites from the lung, plasma, bronchoalveolar lavage, or cells; (2) sample analysis via liquid chromatography-mass spectrometry; and (3) data analysis using commercial and freely available software packages. Overall, the methods delineated here can help investigators use metabolomics to discovery novel biomarkers and to understand lung diseases.

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.

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 study for monitoring of biomarkers in mouse plasma with asthma by gas chromatography-mass spectrometry

Asthma is a multifaceted chronic disease caused by an alteration of various genetic and environmental factors that is increasing in incidence worldwide. However, the biochemical mechanisms regarding asthma are not completely understood. Thus, we performed of metabolomic study for understanding of the biochemical events by monitoring of altered metabolism and biomarkers in asthma. In mice plasma, 27 amino acids(AAs), 24 fatty acids(FAs) and 17 organic acids(OAs) were determined by ethoxycarbonyl(EOC)/methoxime(MO)/tert-butyldimethylsilyl(TBDMS) derivatives with GC-MS. Their percentage composition normalized to the corresponding mean levels of control group. They then plotted as star symbol patterns for visual monitoring of altered metabolism, which were characteristic and readily distinguishable in control and asthma groups. The Mann-Whitney test revealed 25 metabolites, including eight AAs, nine FAs and eight OAs, which were significantly different (p<0.05), and orthogonal partial least-squares-discriminant analysis revealed a clear separation of the two groups. In classification analysis, palmitic acid and methionine were the main metabolites for discrimination between asthma and the control followed by pipecolic, lactic, α-ketoglutaric, and linoleic acids for high classification accuracy as potential biomarkers. These explain the metabolic disturbance in asthma for AAs and FAs including intermediate OAs related to the energy metabolism in the TCA cycle.

Development of a validated LC- MS/MS method for the quantification of 19 endogenous asthma/COPD potential urinary biomarkers

Obstructive airways inflammatory diseases sometimes show overlapping symptoms that hinder their early and correct diagnosis. Current clinical tests are tedious and are of inadequate specificity in special population such as the elderly and children. Therefore, we are developing tandem mass spectrometric (MS/MS) methods for targeted analysis of urine biomarkers. Recently, proton-nuclear magnetic resonance (¹H-NMR) analysis proposed 50 urinary metabolites as potential diagnostic biomarkers among asthma and chronic obstructive pulmonary disease (COPD) patients. Metabolites are divided into 3 groups based on chemical nature. For group 1 (amines and phenols, 19 urinary metabolites), we developed and validated a high performance liquid chromatographic (HPLC)-MS/MS method using differential isotope labeling (DIL) with dansyl chloride. Method development included the optimization of the derivatization reaction, the MS/MS conditions, and the chromatographic separation. Linearity varied from 2 to 4800 ng/mL and the use of ¹³C₂-labeled derivatives allowed for the correction of matrix effects as well as the unambiguous confirmation of the identity of each metabolite in the presence of interfering isomers in urine. Despite the challenges associated with method validation, the method was fully validated as per the food and drug administration (FDA) and the European medicines agency (EMA) recommendations. Validation criteria included linearity, precision, accuracy, dilution integrity, selectivity, carryover, and stability. Challenges in selectivity experiments included the isotopic contributions of the analyte towards its internal standard (IS), that was addressed via the optimization of the IS concentration. In addition, incurred sample analysis was performed to ensure that results from patient samples are accurate and reliable. The method was robust and reproducible and is currently being applied in a cohort of asthma and COPD patient urine samples for biomarker discovery purposes.

Metabolomics analysis identifies different metabotypes of asthma severity

In this study, we sought to determine whether asthma has a metabolic profile and whether this profile is related to disease severity.We characterised the serum from 22 healthy individuals and 54 asthmatics (12 mild, 20 moderate, 22 severe) using liquid chromatography-high-resolution mass spectrometry-based metabolomics. Selected metabolites were confirmed by targeted mass spectrometry assays of eicosanoids, sphingolipids and free fatty acids.We conclusively identified 66 metabolites; 15 were significantly altered with asthma (p≤0.05). Levels of dehydroepiandrosterone sulfate, cortisone, cortisol, prolylhydroxyproline, pipecolate and N-palmitoyltaurine correlated significantly (p<0.05) with inhaled corticosteroid dose, and were further shifted in individuals treated with oral corticosteroids. Oleoylethanolamide increased with asthma severity independently of steroid treatment (p<0.001). Multivariate analysis revealed two patterns: 1) a mean difference between controls and patients with mild asthma (p=0.025), and 2) a mean difference between patients with severe asthma and all other groups (p=1.7×10^-4). Metabolic shifts in mild asthma, relative to controls, were associated with exogenous metabolites (e.g. dietary lipids), while those in moderate and severe asthma (e.g. oleoylethanolamide, sphingosine-1-phosphate, N-palmitoyltaurine) were postulated to be involved in activating the transient receptor potential vanilloid type 1 (TRPV1) receptor, driving TRPV1-dependent pathogenesis in asthma.Our findings suggest that asthma is characterised by a modest systemic metabolic shift in a disease severity-dependent manner, and that steroid treatment significantly affects metabolism.

The Effect of Chinese Herbal Medicine Formula mKG on Allergic Asthma by Regulating Lung and Plasma Metabolic Alternations

Asthma is a chronic inflammatory disorder of the airway and is characterized by airway remodeling, hyperresponsiveness, and shortness of breath. Modified Kushen Gancao Formula (mKG), derived from traditional Chinese herbal medicines (TCM), has been demonstrated to have good therapeutic effects on experimental allergic asthma. However, its anti-asthma mechanism remains currently unknown. In the present work, metabolomics studies of biochemical changes in the lung tissue and plasma of ovalbumin (OVA)-induced allergic asthma mice with mKG treatment were performed using ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). Partial least squares–discriminate analysis (PLS−DA) indicated that the metabolic perturbation induced by OVA was reduced after mKG treatment. A total of twenty-four metabolites involved in seven metabolic pathways were identified as potential biomarkers in the development of allergic asthma. Among them, myristic acid (L3 or P2), sphinganine (L6 or P4), and lysoPC(15:0) (L12 or P16) were detected both in lung tissue and plasma. Additionally, l-acetylcarnitine (L1), thromboxane B2 (L2), 10-HDoHE (L10), and 5-HETE (L11) were first reported to be potential biomarkers associated with allergic asthma. The treatment of mKG mediated all of those potential biomarkers except lysoPC(15:0) (P16). The anti-asthma mechanism of mKG can be achieved through the comprehensive regulation of multiple perturbed biomarkers and metabolic pathways.

Metabolomics for the masses: The future of metabolomics in a personalized world

Current clinical practices focus on a small number of biochemical directly related to the pathophysiology with patients and thus only describe a very limited metabolome of a patient and fail to consider the interations of these small molecules. This lack of extended information may prevent clinicians from making the best possible therapeutic interventions in sufficient time to improve patient care. Various post-genomics '('omic)' approaches have been used for therapeutic interventions previously. Metabolomics now a well-established'omics approach, has been widely adopted as a novel approach for biomarker discovery and in tandem with genomics (especially SNPs and GWAS) has the potential for providing systemic understanding of the underlying causes of pathology. In this review, we discuss the relevance of metabolomics approaches in clinical sciences and its potential for biomarker discovery which may help guide clinical interventions. Although a powerful and potentially high throughput approach for biomarker discovery at the molecular level, true translation of metabolomics into clinics is an extremely slow process. Quicker adaptation of biomarkers discovered using metabolomics can be possible with novel portable and wearable technologies aided by clever data mining, as well as deep learning and artificial intelligence; we shall also discuss this with an eye to the future of precision medicine where metabolomics can be delivered to the masses.

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.

The metabolomics of psoriatic disease

Metabolomics is an emerging new "omics" field involving the systematic analysis of the metabolites in a biologic system. These metabolites provide a molecular snapshot of cellular activity and are thus important for understanding the functional changes in metabolic pathways that drive disease. Recently, metabolomics has been used to study the local and systemic metabolic changes in psoriasis and its cardiometabolic comorbidities. Such studies have revealed novel insights into disease pathogenesis and suggest new biochemical signatures that may be used as a marker of psoriatic disease. This review will discuss common strategies in metabolomics analysis, current findings in the metabolomics of psoriasis, and emerging trends in psoriatic metabolomics.

Metabolomics reveal the protective effect of Farfarae Flos against asthma using an OVA-induced rat model

A ¹H NMR based metabolomics approach combined with biochemical assay and histopathological inspection has been employed to study the protective effect of PEFF against asthma on a rat model.

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.

Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches

BACKGROUND

The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods.

METHODS

We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry.

RESULTS

A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40-50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p < 0.001 after Bonferroni correction). Moreover, a combination of 2-isopropylmalic acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second).

CONCLUSIONS

By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that serum metabolomics may represent a diagnostic tool for asthma and may be helpful for distinguishing asthma phenotypes.