Metabolomics analysis identifies different metabotypes of asthma severity

ORMDL3 and allergic asthma: From physiology to pathology

There is a strong genetic component to asthma, and numerous genome-wide association studies have identified ORM1 (yeast)-like protein 3 (ORMDL3) as a gene associated with asthma susceptibility. However, how ORMDL3 contributes to asthma pathogenesis and its physiologic functions is not well understood and a matter of great debate. This rostrum describes recent advances and new insights in understanding of the multifaceted functions of ORMDL3 in patients with allergic asthma. We also suggest a potential unifying paradigm and discuss molecular mechanisms for the pathologic functions of ORMDL3 in asthma related to its evolutionarily conserved role in regulation of sphingolipid homeostasis. Finally, we briefly survey the utility of sphingolipid metabolites as potential biomarkers for allergic asthma.

Understanding Asthma Phenotypes, Endotypes, and Mechanisms of Disease

The model of asthma as a single entity has now been replaced by a much more complex biological network of distinct and interrelating inflammatory pathways. The term asthma is now considered an umbrella diagnosis for several diseases with distinct mechanistic pathways (endotypes) and variable clinical presentations (phenotypes). The precise definition of these endotypes is central to asthma management due to inherent therapeutic and prognostic implications. This review presents the molecular mechanisms behind the heterogeneity of airway inflammation in asthmatic patients. Asthma endotypes may be broadly regarded as type 2 (T2) high or T2-low. Several biologic agents have been approved for T2-high asthma, with numerous other therapeutics that are incipient and similarly targeted at specific molecular mechanisms. Collectively, these advances have shifted existing paradigms in the approach to asthma to tailor novel therapies.

Filtering procedures for untargeted LC-MS metabolomics data

Background

Untargeted metabolomics datasets contain large proportions of uninformative features that can impede subsequent statistical analysis such as biomarker discovery and metabolic pathway analysis. Thus, there is a need for versatile and data-adaptive methods for filtering data prior to investigating the underlying biological phenomena. Here, we propose a data-adaptive pipeline for filtering metabolomics data that are generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Our data-adaptive pipeline includes novel methods for filtering features based on blank samples, proportions of missing values, and estimated intra-class correlation coefficients.

Results

Using metabolomics datasets that were generated in our laboratory from samples of human blood, as well as two public LC-MS datasets, we compared our data-adaptive filtering method with traditional methods that rely on non-method specific thresholds. The data-adaptive approach outperformed traditional approaches in terms of removing noisy features and retaining high quality, biologically informative ones. The R code for running the data-adaptive filtering method is provided at https://github.com/courtneyschiffman/Metabolomics-Filtering.

Conclusions

Our proposed data-adaptive filtering pipeline is intuitive and effectively removes uninformative features from untargeted metabolomics datasets. It is particularly relevant for interrogation of biological phenomena in data derived from complex matrices associated with biospecimens.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2871-9) contains supplementary material, which is available to authorized users.

Asthma phenotypes and associated comorbidities in a large cohort of adolescents in Israel

Objectives: Asthma is a multifactorial, heterogeneous, complex and common chronic respiratory disease driven by diverse mechanisms. Although asthma presents various clinical forms with different levels of severity, it is unclear whether asthma severities are a consequence of disease management or varied etiologies. We sought to investigate this question.Methods: This article presents a cross-sectional study of 113,671 Israeli adolescents. Univariate and multivariable logistic regression models were performed to analyze the independent associations between mild asthma and moderate-to-severe asthma phenotypes and coexistent medical conditions within each gender separately. Hierarchical clustering of the odds ratios of the diverse statistically significant medical conditions associated with asthma severity-gender groups was also performed. We focused on the allergic and neurological-cognitive-mental disorders.Results: Among males, two associations were common to both asthma groups (atopic dermatitis and allergic rhinitis), five unique to mild asthma (urticaria/angioedema, Hymenoptera/bee allergies, allergic conjunctivitis, epilepsy and migraine) and two unique to moderate-to-severe asthma (learning disabilities and ADD/ADHD (Attention-deficit disorder/Attention-deficit/hyperactivity disorder)). Among females, two associations were common to both clinical asthma groups (allergic rhinitis and urticaria/angioedema), and five unique to moderate-to-severe asthma (atopic dermatitis, learning disabilities, ADD/ADHD, anxiety/mood disorders and migraine). Allergic rhinitis was the only condition to be associated with all four groups. Learning disabilities and ADD/ADHD were only associated with moderate-to-severe asthma (but not with mild asthma), in both males and females. Hierarchical clustering analysis uncovered two prominent clusters, separating mild from moderate-to-severe asthma.Conclusions: The differences between mild and moderate-to-severe asthma enhance asthma phenotype characterization, with respect to comorbidities, and indicate varied etiologies.

Role of transient receptor potential cation channel subfamily V member 1 (TRPV1) on ozone-exacerbated allergic asthma in mice

Around the globe, worsening air pollution is spawning major public health and environmental concerns, especially in the poorest and most populous cities. As a major secondary air pollutant, ozone is a potential risk factor for exacerbated asthma, although the underlying mechanisms remain uncertain. In this study, we aim to investigate the role of ozone on asthma exacerbation using a classic asthmatic model with allergic airway inflammation by treating Balb/c mice with ovalbumin (OVA). Our study shows ozone exposure significantly exacerbated OVA-induced asthmatic phenotypes, including serum immunoglobulin, Th cytokines, inflammatory cell counts, mucus production, airway remodeling, and airway hyper-responsiveness (AHR). Interestingly, expression of transient receptor potential cation channel subfamily V member1 (TRPV1) was also significantly elevated in ozone-exacerbated asthmatic mice and that treatment with TRPV1 antagonist effectively suppressed AHR, airway inflammation and remodeling. The underlying mechanisms of these effects may be associated with suppression of neuropeptide calcitonin gene-related peptide (CGRP) and thymic stromal lymphopoietin (TSLP), an epithelial cell-derived cytokine. Base on the role of TRPV1 in allergic asthma, this study further revealed that inhibition of TRPV1 by TRPV1 antagonist has significant anti-inflammatory effects on ozone-induced asthma exacerbation in this study. Induction of TRPV1 expression may be an important mechanism underlying the increased risks for asthma after exposure to environmental pollutants.

Metabolomics in chronic lung diseases

Chronic lung diseases represent a significant global burden. Their increasing incidence and complexity render a comprehensive, multidisciplinary and personalized approach to each patient, critically important. Most recently, unique biochemical pathways and disease markers have been identified through large-scale metabolomic studies. Metabolomics is the study of metabolic pathways and the measurement of unique biomolecules in a living system. Analysing samples from different compartments such as bronchoalveolar lavage fluid (BALF) and plasma has proven useful for the characterization of a number of pathological conditions and offers promise as a clinical tool. For example, several studies using mass spectrometry (MS) have shown alterations in the sphingolipid metabolism of chronic obstructive pulmonary disease (COPD) sufferers. In this article, we present a practical review of the application of metabolomics to the study of chronic lung diseases (CLD): COPD, idiopathic pulmonary fibrosis (IPF) and asthma. The insights, which the analytical strategies employed in metabolomics, have provided to the dissection of the biochemistry of CLD and future clinical biomarkers are explored.

Altered metabolites in guinea pigs with allergic asthma after acupoint sticking therapy: New insights from a metabolomics approach

BACKGROUND

Clinical evidence gathered in Chinese communities suggested that acupoint sticking therapy could be an alternative treatment for asthma-related diseases. However, its underlying mechanism is still poorly understood.

AIM/HYPOTHESIS

In this study, we aimed to investigate the mechanism of the anti-inflammatory effect of acupoint sticking application with 'Treatment of Winter Disease in Summer' (TWDS) prescription by using metabolomics.

METHODS

Allergic asthma in guinea pig was sensitized and challenged by ovalbumin (OVA). Histopathological evaluation of the lung tissue was performed by hematoxylin and eosin (H&E) staining and Masson's trichrome staining. The levels of Th2 cytokine and IgE level in serum were measured using enzyme-linked immunoassay (ELISA). The mRNA expression levels of IL-4, IL-5, IL-13 and orosomucoid-like 3 (ORMDL3) were measured using quantitative reverse transcription polymerase chain reaction (RT-qPCR). Proteins of NF-κB signaling pathway were measured using western blot. The serum metabolomics profiles were obtained by using ultra-performance liquid chromatography combined with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOF-MS).

RESULTS

The overall results confirmed that AST with TWDS prescription had a significant protective effect against OVA-induced allergic asthma in guinea pig. This treatment not only attenuated airway inflammation and collagen deposition in the airway, but also decreased the levels of IL-4, IL-5, IL-13 and IgE in serum. In addition, metabolomics results indicated that metabolisms of phospholipid, sphingolipid, purine, amino acid and level of epinephrine were restored back to the normal control level. Moreover, results of the gene expression of ORMDL3 in lung tissues indicated that AST using TWDS could alter the sphingolipid metabolism. Further western blotting analysis also showed that its anti-inflammatory mechanism was by decreasing the phosphorylation of p65 and IκB.

CONCLUSION

The study demonstrated that metabolomics provides a better understanding of the actions of TWDS acupoint sticking therapy on OVA-induced allergic asthma.

Urine metabolic profiles in paediatric asthma

BACKGROUND AND OBJECTIVE

Asthma is a global problem and complex disease suited for metabolomic profiling. This study explored the candidate biomarkers specific to paediatric asthma and provided insights into asthmatic pathophysiology.

METHODS

Children (aged 6-11 years) meeting the criteria for healthy control (n = 29), uncontrolled asthma (n = 37) or controlled asthma (n = 43) were enrolled. Gas chromatography-mass spectrometry was performed on urine samples of the patients to explore the different types of metabolite profile in paediatric asthma. Additionally, we employed a comprehensive strategy to elucidate the relationship between significant metabolites and asthma-related genes.

RESULTS

We identified 51 differential metabolites mainly related to dysfunctional amino acid, carbohydrate and purine metabolism. A combination of eight candidate metabolites, including uric acid, stearic acid, threitol, acetylgalactosamine, heptadecanoic acid, aspartic acid, xanthosine and hypoxanthine (adjusted P < 0.05 and fold-change >1.5 or <0.67), showed excellent discriminatory performance for the presence of asthma and the differentiation of poor-controlled or well-controlled asthma, and area under the curve values were >0.97 across groups. Enrichment analysis based on these targets revealed that the Fc receptor, intracellular steroid hormone receptor signalling pathway, DNA damage and fibroblast proliferation were involved in inflammation, immunity and stress-related biological progression of paediatric asthma.

CONCLUSION

Metabolomic analysis of patient urine combined with network-biology approaches allowed discrimination of asthma profiles and subtypes according to the metabolic patterns. The results provided insight into the potential mechanism of paediatric asthma.

Genomic Predictors of Asthma Phenotypes and Treatment Response

Asthma is a complex respiratory disease considered as the most common chronic condition in children. A large genetic contribution to asthma susceptibility is predicted by the clustering of asthma and allergy symptoms among relatives and the large disease heritability estimated from twin studies, ranging from 55 to 90%. Genetic basis of asthma has been extensively investigated in the past 40 years using linkage analysis and candidate-gene association studies. However, the development of dense arrays for polymorphism genotyping has enabled the transition toward genome-wide association studies (GWAS), which have led the discovery of several unanticipated asthma genes in the last 11 years. Despite this, currently known risk variants identified using many thousand samples from distinct ethnicities only explain a small proportion of asthma heritability. This review examines the main findings of the last 2 years in genomic studies of asthma using GWAS and admixture mapping studies, as well as the direction of studies fostering integrative perspectives involving omics data. Additionally, we discuss the need for assessing the whole spectrum of genetic variation in association studies of asthma susceptibility, severity, and treatment response in order to further improve our knowledge of asthma genes and predictive biomarkers. Leveraging the individual's genetic information will allow a better understanding of asthma pathogenesis and will facilitate the transition toward a more precise diagnosis and treatment.

Study of the metabolomic relationship between lung cancer and chronic obstructive pulmonary disease based on direct infusion mass spectrometry

The high prevalence of lung cancer (LC) has triggered the search of biomarkers for early diagnosis of this disease. For this purpose the study of metabolic changes related to the development of lung cancer could provide interesting information about its early diagnosis. In this sense, chronic obstructive pulmonary disease (COPD), a disease associated with tumor development, is a comorbidity that increases the risk of onset and progression of lung neoplasia and has also to be considered in the study of pathology related to lung cancer. This work develop a metabolomic approach based on direct infusion mass spectrometry using a hybrid triple quadrupole-time of flight mass spectrometer (DI-ESI-QqQ-TOF-MS) in order to identify altered metabolites from serum of LC and COPD patients and evaluate its relationship and implication in the progression of LC. This methodology has been applied to 30 serum samples from LC, 30 healthy patients used as controls (HC) and 30 serum samples from COPD to found altered metabolites from both LC and COPD diseases. In addition, some metabolic differences and similarities were found in Pulmonary Emphysema and Chronic Bronchitis patients. On the other hand, altered metabolites were studied in different stages of LC (II, III and IV) to evaluate the perturbation of them throughout the progression of disease. The sample treatment consisted of the extraction of polar and non-polar metabolites from serum that was later infused into the mass spectrometer using an electrospray ionization source in positive and negative mode. Partial least squares discriminant analysis (PLS-DA) allowed a classification between LC, HC and COPD groups in all acquisition modes. A total of 35 altered and common metabolites between LC and COPD, including amino acids, fatty acids, lysophospholipids, phospholipids and triacylglycerides were identified, being alanine, aspartate and glutamate metabolism the most altered. Finally, ROC curves were applied to the dataset and metabolites with AUC value higher than 0.70 were considered as relevant in the progression of LC.

OnPLS-Based Multi-Block Data Integration: A Multivariate Approach to Interrogating Biological Interactions in Asthma

Integration of multiomics data remains a key challenge in fulfilling the potential of comprehensive systems biology. Multiple-block orthogonal projections to latent structures (OnPLS) is a projection method that simultaneously models multiple data matrices, reducing feature space without relying on a priori biological knowledge. In order to improve the interpretability of OnPLS models, the associated multi-block variable influence on orthogonal projections (MB-VIOP) method is used to identify variables with the highest contribution to the model. This study combined OnPLS and MB-VIOP with interactive visualization methods to interrogate an exemplar multiomics study, using a subset of 22 individuals from an asthma cohort. Joint data structure in six data blocks was assessed: transcriptomics; metabolomics; targeted assays for sphingolipids, oxylipins, and fatty acids; and a clinical block including lung function, immune cell differentials, and cytokines. The model identified seven components, two of which had contributions from all blocks (globally joint structure) and five that had contributions from two to five blocks (locally joint structure). Components 1 and 2 were the most informative, identifying differences between healthy controls and asthmatics and a disease–sex interaction, respectively. The interactions between features selected by MB-VIOP were visualized using chord plots, yielding putative novel insights into asthma disease pathogenesis, the effects of asthma treatment, and biological roles of uncharacterized genes. For example, the gene ATP6 V1G1, which has been implicated in osteoporosis, correlated with metabolites that are dysregulated by inhaled corticoid steroids (ICS), providing insight into the mechanisms underlying bone density loss in asthma patients taking ICS. These results show the potential for OnPLS, combined with MB-VIOP variable selection and interaction visualization techniques, to generate hypotheses from multiomics studies and inform biology.

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.

Sphingolipids and their enigmatic role in asthma

Asthma is defined as a chronic inflammatory condition in the lung and is characterized by episodic shortness of breath with expiratory wheezing and cough. Asthma is a serious public health concern globally with an estimated incidence over 300 million. Asthma is a complex disease in that it manifests as disease of gene and environmental interactions. Sphingolipids are a unique class of lipids involved in a host of biological functions ranging from serving as key cellular membrane lipids to acting as critical signaling molecules. To date sphingolipids have been studied across various human conditions ranging from neurological disorders to cancer to infection to autoimmunity. This review will focus on the role of sphingolipids in asthma development and pathology with particular focus on the role of mast cell sphingolipid biology.

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.

Toll-Like Receptor 7/8 Ligand, S28463, Suppresses Ascaris suum-induced Allergic Asthma in Nonhuman Primates

S28463 (S28), a ligand for Toll-like receptor 7/8, has been shown to have antiinflammatory properties in rodent models of allergic asthma. The principle goal of this study was to assess whether these antiinflammatory effects can also be observed in a nonhuman primate (NHP) model of allergic asthma. NHPs were sensitized then challenged with natural allergen, Ascaris suum extract. The animals were treated with S28 orally before each allergen challenge. The protective effect of S28 in NHPs was assessed by measuring various asthma-related phenotypes. We also characterized the metabolomic and proteomic signatures of the lung environment and plasma to identify markers associated with the disease and treatment. Our data demonstrate that clinically relevant parameters, such as wheal and flare response, blood IgE levels, recruitment of white blood cells to the bronchoalveolar space, and lung responsiveness, are decreased in the S28-treated allergic NHPs compared with nontreated allergic NHPs. Furthermore, we also identified markers that can distinguish allergic from nonallergic or allergic and drug-treated NHPs, such as metabolites, phosphocreatine and glutathione, in the plasma and BAL fluid, respectively; and inflammatory cytokines, IL-5 and IL-13, in the bronchoalveolar lavage fluid. Our preclinical study demonstrates that S28 has potential as a treatment for allergic asthma in primate species closely related to humans. Combined with our previous findings, we demonstrate that S28 is effective in different models of asthma and in different species, and has the antiinflammatory properties clinically relevant for the treatment of allergic asthma.

Serum metabolic profiling identified a distinct metabolic signature in patients with idiopathic pulmonary fibrosis - a potential biomarker role for LysoPC

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a lethal lung disease of unknown etiology. Patients present loss of lung function, dyspnea and dry cough. Diagnosis requires compatible radiologic imaging and, in undetermined cases, invasive procedures such as bronchoscopy and surgical lung biopsy. The pathophysiological mechanisms of IPF are not completely understood. Lung injury with abnormal alveolar epithelial repair is thought to be a major cause for activation of profibrotic pathways in IPF. Metabolic signatures might indicate pathological pathways involved in disease development and progression. Reliable serum biomarker would help to improve both diagnostic approach and monitoring of drug effects.

METHOD

The global metabolic profiles measured by ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) of ten stable IPF patients were compared to the ones of ten healthy participants. The results were validated in an additional study of eleven IPF patients and ten healthy controls.

RESULTS

We discovered 10 discriminative metabolic features using multivariate and univariate statistical analysis. Among them, we identified one metabolite at a retention time of 9.59 min that was two times more abundant in the serum of IPF patients compared to healthy participants. Based on its ion pattern, a lysophosphatidylcholine (LysoPC) was proposed. LysoPC is a precursor of lysophosphatidic acid (LPA) - a known mediator for lung fibrosis with its pathway currently being evaluated as new therapeutic drug target for IPF and other fibrotic diseases.

CONCLUSIONS

We identified a LysoPC by UHPLC-HRMS as potential biomarker in serum of patients with IPF. Further validation studies in a larger cohort are necessary to determine its role in IPF.

TRIAL REGISTRATION

Serum samples from IPF patients have been obtained within the clinical trial NCT02173145 at baseline and from the idiopathic interstitial pneumonia (IIP) cohort study. The study was approved by the Swiss Ethics Committee, Bern (KEK 002/14 and 246/15 or PB_2016-01524).

Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies

BACKGROUND

Quality assurance (QA) and quality control (QC) are two quality management processes that are integral to the success of metabolomics including their application for the acquisition of high quality data in any high-throughput analytical chemistry laboratory. QA defines all the planned and systematic activities implemented before samples are collected, to provide confidence that a subsequent analytical process will fulfil predetermined requirements for quality. QC can be defined as the operational techniques and activities used to measure and report these quality requirements after data acquisition.

AIM OF REVIEW

This tutorial review will guide the reader through the use of system suitability and QC samples, why these samples should be applied and how the quality of data can be reported.

KEY SCIENTIFIC CONCEPTS OF REVIEW

System suitability samples are applied to assess the operation and lack of contamination of the analytical platform prior to sample analysis. Isotopically-labelled internal standards are applied to assess system stability for each sample analysed. Pooled QC samples are applied to condition the analytical platform, perform intra-study reproducibility measurements (QC) and to correct mathematically for systematic errors. Standard reference materials and long-term reference QC samples are applied for inter-study and inter-laboratory assessment of data.

Asthma severity and heterogeneity: Insights from prevalence trends and associated demographic variables and anthropometric indices among Israeli adolescents

OBJECTIVES

While asthma presents various clinical forms with different levels of severity, it is unclear whether asthma severities are a consequence of disease management or varied etiologies. We sought to investigate this question.

METHODS

This paper presents a cross-sectional study of 113,671 Israeli adolescents. Prevalence rates of mild and moderate-to-severe asthma over a 24-year period were calculated and multivariate regression models (outcomes: different asthma severity, reference: subjects without asthma) were performed to analyze associations with anthropometric indices and socio-demographic variables, in males and females separately.

RESULTS

The prevalence of mild asthma increased until birth years 1976-1980 and then steadily decreased. In contrast, the prevalence of moderate-to-severe asthma was relatively stable until birth years 1976-1980, then rose steeply until 1986-1990 and subsequently plateaued in the early 1990s. Obesity was positively associated with both mild and moderate-to-severe asthma in males (Odds Ratio (OR) [95%CIs]: 1.61 [1.37-1.89] and 1.63 [1.34-1.98], respectively) and females (1.54 [1.10-2.16] and 1.54 [1.20-1.98], respectively). Family size greater than three siblings was negatively associated with both mild and moderate-to-severe asthma in males (0.62 [0.56-0.68] and 0.59 [0.52-0.68]) and females (0.71 [0.60-0.83] and 0.73 [0.63-0.83]). In contrast, in males, underweight was only associated with mild asthma (1.54 [1.22-1.94]) but not with moderate-to-severe asthma. In females, overweight was only associated with moderate-to-severe asthma (1.21 [1.00-1.46]) and rural residence was only associated with mild asthma (1.26 [1.09-1.47]).

CONCLUSIONS

The differences between mild and moderate-to-severe asthma enhance asthma phenotype characterization, with respect to secular trends and associated variables, and indicate varied etiologies.

Arginine metabolic endotypes related to asthma severity

Aims

Arginine metabolism via inducible nitric oxide synthase (iNOS) and arginase 2 (ARG2) is higher in asthmatics than in healthy individuals. We hypothesized that a sub-phenotype of asthma might be defined by the magnitude of arginine metabolism categorized on the basis of high and low fraction of exhaled nitric oxide (F_ENO).

Methods

To test this hypothesis, asthmatics (n = 52) were compared to healthy controls (n = 51) for levels of F_ENO, serum arginase activity, and airway epithelial expression of iNOS and ARG2 proteins, in relation to clinical parameters of asthma inflammation and airway reactivity. In parallel, bronchial epithelial cells were evaluated for metabolic effects of iNOS and ARG2 expression in vitro.

Results

Asthmatics with high F_ENO (≥ 35 ppb; 44% of asthmatics) had higher expression of iNOS (P = 0.04) and ARG2 (P = 0.05) in the airway, indicating F_ENO is a marker of the high arginine metabolic endotype. High F_ENO asthmatics had the lowest FEV₁% (P < 0.001), FEV₁/FVC (P = 0.0002) and PC₂₀ (P < 0.001) as compared to low F_ENO asthmatics or healthy controls. Low F_ENO asthmatics had near normal iNOS and ARG2 expression (both P > 0.05), and significantly higher PC₂₀ (P < 0.001) as compared to high F_ENO asthmatics. In vitro studies to evaluate metabolic effects showed that iNOS overexpression and iNOS+ARG2 co-expression in a human bronchial epithelial cell line led to greater reliance on glycolysis with higher rate of pyruvate going to lactate.

Conclusions

The high F_ENO phenotype represents a large portion of the asthma population, and is typified by greater arginine metabolism and more severe and reactive asthma.

Short overview on metabolomics approach to study pathophysiology of oxidative stress in cancer

Association of oxidative stress with carcinogenesis is well known, but not understood well, as is pathophysiology of oxidative stress generated during different types of anti-cancer treatments. Moreover, recent findings indicate that cancer associated lipid peroxidation might eventually help defending adjacent nonmalignant cells from cancer invasion. Therefore, untargeted metabolomics studies designed for advanced translational and clinical studies are needed to understand the existing paradoxes in oncology, including those related to controversial usage of antioxidants aiming to prevent or treat cancer. In this short review we have tried to put emphasis on the importance of pathophysiology of oxidative stress and lipid peroxidation in cancer development in relation to metabolic adaptation of particular types of cancer allowing us to conclude that adaptation to oxidative stress is one of the main driving forces of cancer pathophysiology. With the help of metabolomics many novel findings are being achieved thus encouraging further scientific breakthroughs. Combined with targeted qualitative and quantitative methods, especially immunochemistry, further research might reveal bio-signatures of individual patients and respective malignant diseases, leading to individualized treatment approach, according to the concepts of modern integrative medicine.

Metabolomics analysis identifies sex-associated metabotypes of oxidative stress and the autotaxin-lysoPA axis in COPD

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and a leading cause of mortality and morbidity worldwide. The aim of this study was to investigate the sex dependency of circulating metabolic profiles in COPD.

Serum from healthy never-smokers (healthy), smokers with normal lung function (smokers), and smokers with COPD (COPD; Global Initiative for Chronic Obstructive Lung Disease stages I–II/A–B) from the Karolinska COSMIC cohort (n=116) was analysed using our nontargeted liquid chromatography–high resolution mass spectrometry metabolomics platform.

Pathway analyses revealed that several altered metabolites are involved in oxidative stress. Supervised multivariate modelling showed significant classification of smokers from COPD (p=2.8×10⁻⁷). Sex stratification indicated that the separation was driven by females (p=2.4×10⁻⁷) relative to males (p=4.0×10⁻⁴). Significantly altered metabolites were confirmed quantitatively using targeted metabolomics. Multivariate modelling of targeted metabolomics data confirmed enhanced metabolic dysregulation in females with COPD (p=3.0×10⁻³) relative to males (p=0.10). The autotaxin products lysoPA (16:0) and lysoPA (18:2) correlated with lung function (forced expiratory volume in 1 s) in males with COPD (r=0.86; p<0.0001), but not females (r=0.44; p=0.15), potentially related to observed dysregulation of the miR-29 family in the lung.

These findings highlight the role of oxidative stress in COPD, and suggest that sex-enhanced dysregulation in oxidative stress, and potentially the autotaxin–lysoPA axis, are associated with disease mechanisms and/or prevalence.

Oxidative stress and the autotaxin–lysoPA axis evidence sex-associated metabotypes in the serum of COPD patientshttp://ow.ly/kAeE309MpdI

A review of blood sample handling and pre-processing for metabolomics studies

Metabolomics has been found to be applicable to a wide range of clinical studies, bringing a new era for improving clinical diagnostics, early disease detection, therapy prediction and treatment efficiency monitoring. A major challenge in metabolomics, particularly untargeted studies, is the extremely diverse and complex nature of biological specimens. Despite great advances in the field there still exist fundamental needs for considering pre-analytical variability that can introduce bias to the subsequent analytical process and decrease the reliability of the results and moreover confound final research outcomes. Many researchers are mainly focused on the instrumental aspects of the biomarker discovery process, and sample related variables sometimes seem to be overlooked. To bridge the gap, critical information and standardized protocols regarding experimental design and sample handling and pre-processing are highly desired. Characterization of a range variation among sample collection methods is necessary to prevent results misinterpretation and to ensure that observed differences are not due to an experimental bias caused by inconsistencies in sample processing. Herein, a systematic discussion of pre-analytical variables affecting metabolomics studies based on blood derived samples is performed. Furthermore, we provide a set of recommendations concerning experimental design, collection, pre-processing procedures and storage conditions as a practical review that can guide and serve for the standardization of protocols and reduction of undesirable variation.