Metabolomics applied to urine samples in childhood asthma; differentiation between asthma phenotypes and identification of relevant metabolites

Urine metabolomics signature reveals novel determinants of adrenal suppression in children taking inhaled corticosteroids to control asthma symptoms

BACKGROUND

Asthma is routinely treated with inhaled corticosteroids (ICS). Asthma patients on ICS are at increased risk of adrenal suppression, a potentially serious effect of long-term glucocorticoid exposure; however, this relationship is poorly understood. Therefore, this study aims to identify metabolite biomarkers related to adrenal suppression in asthma patients taking ICS.

METHODS

A total of 571 urine metabolites from 200 children with asthma on ICS in the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort were profiled. Samples were grouped by peak plasma cortisol measurement as adrenal sufficient (>350 nmol/L) or insufficient (≤350 nmol/L) (outcome). Regression and discriminant-based statistical models combined with network analyses were utilized to assess relationships between metabolites and the outcome. Finally, prioritized metabolites were validated using data from an ancillary study of the Childhood Asthma Management (CAMP) cohort with similar characteristics to PASS.

RESULTS

Ninety metabolites were significantly associated with adrenal suppression, of which 57 also could discriminate adrenal status. While 26 metabolites (primarily steroids) were present at lower levels in the adrenal insufficient patients, 14 were significantly elevated in this group; the top metabolite, mannitol/sorbitol, was previously associated with asthma exacerbations. Network analyses identified unique clusters of metabolites related to steroids, fatty acid oxidation, and nucleoside metabolism, respectively. Four metabolites including urocanic acid, acetylcarnitine, uracil, and sorbitol were validated in CAMP cohort for adrenal suppression.

CONCLUSIONS

Urinary metabolites differ among asthma patients on ICS, by adrenal status. While steroid metabolites were reduced in patients with poor adrenal function, our findings also implicate previously unreported metabolites involved in amino acid, lipid, and nucleoside metabolism.

Pharmacometabolomics of Asthma as a Road Map to Precision Medicine

Pharmacometabolomics applies the principles of metabolomics to therapeutics in order to elucidate the biological mechanisms underlying the variation in responses to drugs between groups and individuals. Asthma is associated with broad systemic effects and heterogeneity in treatment response and as such is ideally suited to pharmacometabolomics. In this chapter, we discuss the state of the emerging field of asthma pharmacometabolomics, with a particular focus on studies of steroids, bronchodilators, and leukotriene inhibitors. We also consider those studies concerned with subtyping cases to better understand the pharmacology of those groups and those looking to leverage pharmacometabolomics for asthma prevention. We finish with a discussion of the challenges and opportunities of asthma pharmacometabolomics and reflect upon where this field must go next in order to realize its precision medicine potential.

Metabolic Changes and Their Associations with Selected Nutrients Intake in the Group of Workers Exposed to Arsenic

Arsenic (As) exposure causes numerous adverse health effects, which can be reduced by the nutrients involved in the metabolism of iAs (inorganic As). This study was carried out on two groups of copper-smelting workers: WN, workers with a urinary total arsenic (tAs) concentration within the norm (n = 75), and WH, workers with a urinary tAs concentration above the norm (n = 41). This study aimed to analyze the association between the intake level of the nutrients involved in iAs metabolism and the signal intensity of the metabolites that were affected by iAs exposure. An untargeted metabolomics analysis was carried out on urine samples using liquid chromatography-mass spectrometry, and the intake of the nutrients was analyzed based on 3-day dietary records. Compared with the WN group, five pathways (the metabolism of amino acids, carbohydrates, glycans, vitamins, and nucleotides) with twenty-five putatively annotated metabolites were found to be increased in the WH group. In the WN group, the intake of nutrients (methionine; vitamins B2, B6, and B12; folate; and zinc) was negatively associated with six metabolites (cytosine, D-glucuronic acid, N-acetyl-D-glucosamine, pyroglutamic acid, uridine, and urocanic acid), whereas in the WH group, it was associated with five metabolites (D-glucuronic acid, L-glutamic acid, N-acetyl-D-glucosamine, N-acetylneuraminic acid, and uridine). Furthermore, in the WH group, positive associations between methionine, folate, and zinc intake and the signal intensity of succinic acid and 3-mercaptolactic acid were observed. These results highlight the need to educate the participants about the intake level of the nutrients involved in iAs metabolism and may contribute to further considerations with respect to the formulation of dietary recommendations for people exposed to iAs.

Untargeted Fecal Metabolomic Analyses across an Industrialization Gradient Reveal Shared Metabolites and Impact of Industrialization on Fecal Microbiome-Metabolome Interactions

The metabolome is a central determinant of human phenotypes and includes the plethora of small molecules produced by host and microbiome or taken up from exogenous sources. However, studies of the metabolome have so far focused predominantly on urban, industrialized populations. Through an untargeted metabolomic analysis of 90 fecal samples from human individuals from Africa and the Americas-the birthplace and the last continental expansion of our species, respectively-we characterized a shared human fecal metabolome. The majority of detected metabolite features were ubiquitous across populations, despite any geographic, dietary, or behavioral differences. Such shared metabolite features included hyocholic acid and cholesterol. However, any characterization of the shared human fecal metabolome is insufficient without exploring the influence of industrialization. Here, we show chemical differences along an industrialization gradient, where the degree of industrialization correlates with metabolomic changes. We identified differential metabolite features such as amino acid-conjugated bile acids and urobilin as major metabolic correlates of these behavioral shifts. Additionally, coanalyses with over 5,000 publicly available human fecal samples and cooccurrence probability analyses with the gut microbiome highlight connections between the human fecal metabolome and gut microbiome. Our results indicate that industrialization significantly influences the human fecal metabolome, but diverse human lifestyles and behavior still maintain a shared human fecal metabolome. This study represents the first characterization of the shared human fecal metabolome through untargeted analyses of populations along an industrialization gradient. IMPORTANCE As the world becomes increasingly industrialized, understanding the biological consequences of these lifestyle shifts and what it means for past, present, and future human health is critical. Indeed, industrialization is associated with rises in allergic and autoimmune health conditions and reduced microbial diversity. Exploring these health effects on a chemical level requires consideration of human lifestyle diversity, but understanding the significance of any differences also requires knowledge of what molecular components are shared between human groups. Our study reveals the key chemistry of the human gut as defined by varied industrialization-based differences and ubiquitous shared features. Ultimately, these novel findings extend our knowledge of human molecular biology, especially as it is influenced by lifestyle and behavior, and provide steps toward understanding how human biology has changed over our species' history.

The metabolomic differential plasma profile between dialysates. Pursuing to understand the mechanisms of citrate dialysate clinical benefits

Background: Currently, bicarbonate-based dialysate needs a buffer to prevent precipitation of bicarbonate salts with the bivalent cations, and acetate at 3-4 mmol/L is the most used. However, citrate is being postulated as a preferred option because of its association with better clinical results by poorly understood mechanisms. In that sense, this hypothesis-generating study aims to identify potential metabolites that could biologically explain these improvements found in patients using citrate dialysate. Methods: A unicentric, cross-over, prospective untargeted metabolomics study was designed to analyze the differences between two dialysates only differing in their buffer, one containing 4 mmol/L of acetate (AD) and the other 1 mmol/L of citrate (CD). Blood samples were collected in four moments (i.e., pre-, mid-, post-, and 30-min-post-dialysis) and analyzed in an untargeted metabolomics approach based on UPLC-Q-ToF mass spectrometry. Results: The 31 most discriminant metabolomic variables from the plasma samples of the 21 participants screened by their potential clinical implications show that, after dialysis with CD, some uremic toxins appear to be better cleared, the lysine degradation pathway is affected, and branched-chain amino acids post-dialysis levels are 9-10 times higher than with AD; and, on its part, dialysis with AD affects acylcarnitine clearance. Conclusion: Although most metabolic changes seen in this study could be attributable to the dialysis treatment itself, this study successfully identifies some metabolic variables that differ between CD and AD, which raise new hypotheses that may unveil the mechanisms involved in the clinical improvements observed with citrate in future research.

Biomarkers of Mycoplasma pneumoniae pneumonia in children by urine metabolomics based on Q Exactive liquid chromatography/tandem mass spectrometry

RATIONALE

Mycoplasma pneumoniae has become one of the common pathogens causing pediatric respiratory infections. In clinical diagnosis, throat swabs are very difficult to obtain from children, and there is a possibility of false positive results; hence, there are few clinically available diagnostic methods.

METHODS

In this study, Q Exactive liquid chromatography/tandem mass spectrometry was used to analyze the metabolites in the urine of healthy children (HC) and M. pneumoniae pneumonia in children (MPPC) patients. A multivariate statistical analysis was performed to screen the differential metabolites. Based on the HMDB and KEGG, the possible metabolic pathways subject to biological alteration were identified.

RESULTS

Compared with HC, 73 different metabolites in MPPC patients disrupted nine metabolic pathways through different change trends; after integrating various parameters, 20 significantly different metabolites were identified as MPPC potential biomarkers. Through the above two analysis modes, acetylphosphate and 2,5-dioxopentanoate were both screened out and used as potential biomarkers for the early diagnosis of MPPC for the first time.

CONCLUSIONS

The characterization of 20 potential biomarkers provides a scientific basis for predicting and diagnosing MPPC. This article further indicates that urine metabolic profiling has great potential in diagnosing MPPC and can effectively prevent the disease from causing further deterioration.

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.

A Systematic Review of Metabolic Alterations Underlying IgE-Mediated Food Allergy in Children

SCOPE

Immunoglobulin E-mediated food allergies (IgE-FA) are characterized by an ever-increasing prevalence, currently reaching up to 10.4% of children in the European Union. Metabolomics has the potential to provide a deeper understanding of the pathogenic mechanisms behind IgE-FA.

METHODS AND RESULTS

In this work, literature is systematically searched using Web of Science, PubMed, Scopus, and Embase, from January 2010 until May 2021, including human and animal metabolomic studies on multiple biofluids (urine, blood, feces). In total, 15 studies on IgE-FA are retained and a dataset of 277 potential biomarkers is compiled for in-depth pathway mapping. Decreased indoleamine 2,3-dioxygenase-1 (IDO- 1) activity is hypothesized due to altered plasma levels of tryptophan and its metabolites in IgE-FA children. In feces of children prior to IgE-FA, aberrant metabolization of sphingolipids and histidine is noted. Decreased fecal levels of (branched) short chain fatty acids ((B)SCFAs) compel a shift towards aerobic glycolysis and suggest dysbiosis, associated with an immune system shift towards T-helper 2 (Th2) responses. During animal anaphylaxis, a similar switch towards glycolysis is observed, combined with increased ketogenic pathways. Additionally, altered histidine, purine, pyrimidine, and lipid pathways are observed.

CONCLUSION

To conclude, this work confirms the unprecedented opportunities of metabolomics and supports the in-depth pathophysiological qualification in the quest towards improved diagnostic and prognostic biomarkers for IgE-FA.

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other “phenotypes” of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma–COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.

Untargeted serum metabolomics and tryptophan metabolism profiling in type 2 diabetic patients with diabetic glomerulopathy

Diabetic glomerulopathy (DG) remains the prevalent microvascular complication and leading cause of shortened lifespan in type-2 diabetes mellitus (T2DM) despite improvement in hyperglycemia control. Considering the pivotal role of kidney in metabolism, using untargeted metabolomic techniques to globally delineate the serum metabolite profiles will help advance understanding pathogenetic underpinnings of renal biopsy-confirmed DG from the perspective of metabolism specifically. Fourteen pathologically diagnosed DG patients secondary to T2DM and 14 age- and gender-matched healthy controls (HCs) were recruited for study. We employed mass spectrometry-based untargeted metabolomic methods to reveal the metabolite profiles of serum samples collected from all included subjects. We identified a total of 334 and 397 metabolites in positive and negative ion mode respectively. One hundred and eighty-two important differential metabolites whose variable importance in projection (VIP) > 1 and p value <0.05 were selected and annotated to metabolic pathways. KEGG pathway enrichment analysis revealed tryptophan metabolism enriched most significantly. Among the tryptophan derivatives, L-tryptophan (L-Trp) and serotonin were relatively accumulated in DGs compared with HCs, while 5-hydroxyindoleacetic acid (5-HIAA) and indole-3-acetamide were depleted. Correlation analysis showed serotonin and L-Trp are negatively correlated with 24 h urine protein and glycosylated hemoglobin (Ghb). To exclude the interference of preexisting T2DM on DG exacerbation, we selected 5-HIAA and 3-(3-hydroxyphenyl) propionic acid (3-OHPPA) which are not correlated with Ghb and analyzed their correlation relationship with crucial renal indices. We found 3-OHPPA is positively correlated with urine total protein and creatinine ratio (T/Cr) and 24 h urine protein, 5-HIAA is positively correlated with serum creatinine and urea.

Associations of maternal and infant metabolomes with immune maturation and allergy development at 12 months in the Swedish NICE-cohort

Allergic diseases are the most common chronic diseases in childrenin the Western world, but little is know about what factors influence immune maturation and allergy development. We therefore aimed to associate infant and maternal metabolomes to T- and B-cell subpopulations and allergy diagnosis. We performed liquid chromatography-mass spectrometry based untargeted metabolomics on blood plasma from mothers (third trimester, n = 605; delivery, n = 558) and from the umbilical cord (n = 366). The measured metabolomes were associated to T- and B-cell subpopulations up to 4 months after delivery and to doctor´s diagnosed eczema, food allergy and asthma at one year of age using random forest analysis. Maternal and cord plasma at delivery could predict the number of CD24+CD38low memory B-cells (p = 0.033, n = 26 and p = 0.009, n = 22), but future allergy status could not be distinguished from any of the three measured metabolomes. Replication of previous literature findings showed hypoxanthine to be upregulated in the umbilical cord of children with subsequent asthma. This exploratory study suggests foetal immune programming occuring during pregnancy as the metabolomic profiles of mothers and infants at delivery related to infants' B-cell maturation.

Characteristics and Mechanisms of a Sphingolipid-associated Childhood Asthma Endotype

Rationale: A link among sphingolipids, 17q21 genetic variants, and childhood asthma has been suggested, but the underlying mechanisms and characteristics of such an asthma endotype remain to be elucidated.Objectives: To study the sphingolipid-associated childhood asthma endotype using multiomic data.Methods: We used untargeted liquid chromatography-mass spectrometry plasma metabolomic profiles at the ages of 6 months and 6 years from more than 500 children in the COPSAC₂₀₁₀ (Copenhagen Prospective Studies on Asthma in Childhood) birth cohort focusing on sphingolipids, and we integrated the 17q21 genotype and nasal gene expression of SPT (serine palmitoyl-CoA transferase) (i.e., the rate-limiting enzyme in de novo sphingolipid synthesis) in relation to asthma development and lung function traits from infancy until the age 6 years. Replication was sought in the independent VDAART (Vitamin D Antenatal Asthma Reduction Trial) cohort.Measurements and Main Results: Lower concentrations of ceramides and sphingomyelins at the age of 6 months were associated with an increased risk of developing asthma before age 3, which was also observed in VDAART. At the age of 6 years, lower concentrations of key phosphosphingolipids (e.g., sphinganine-1-phosphate) were associated with increased airway resistance. This relationship was dependent on the 17q21 genotype and nasal SPT gene expression, with significant interactions occurring between the genotype and the phosphosphingolipid concentrations and between the genotype and SPT expression, in which lower phosphosphingolipid concentrations and reduced SPT expression were associated with increasing numbers of at-risk alleles. However, the findings did not pass the false discovery rate threshold of <0.05.Conclusions: This exploratory study suggests the existence of a childhood asthma endotype with early onset and increased airway resistance that is characterized by reduced sphingolipid concentrations, which are associated with 17q21 genetic variants and expression of the SPT enzyme.

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

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

The Metabolomics of Childhood Atopic Diseases: A Comprehensive Pathway-Specific Review

Asthma, allergic rhinitis, food allergy, and atopic dermatitis are common childhood diseases with several different underlying mechanisms, i.e., endotypes of disease. Metabolomics has the potential to identify disease endotypes, which could beneficially promote personalized prevention and treatment. Here, we summarize the findings from metabolomics studies of children with atopic diseases focusing on tyrosine and tryptophan metabolism, lipids (particularly, sphingolipids), polyunsaturated fatty acids, microbially derived metabolites (particularly, short-chain fatty acids), and bile acids. We included 25 studies: 23 examined asthma or wheezing, five examined allergy endpoints, and two focused on atopic dermatitis. Of the 25 studies, 20 reported findings in the pathways of interest with findings for asthma in all pathways and for allergy and atopic dermatitis in most pathways except tyrosine metabolism and short-chain fatty acids, respectively. Particularly, tyrosine, 3-hydroxyphenylacetic acid, N-acetyltyrosine, tryptophan, indolelactic acid, 5-hydroxyindoleacetic acid, p-Cresol sulfate, taurocholic acid, taurochenodeoxycholic acid, glycohyocholic acid, glycocholic acid, and docosapentaenoate n-6 were identified in at least two studies. This pathway-specific review provides a comprehensive overview of the existing evidence from metabolomics studies of childhood atopic diseases. The altered metabolic pathways uncover some of the underlying biochemical mechanisms leading to these common childhood disorders, which may become of potential value in clinical practice.

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.

EBC metabolomics for asthma severity

Asthma is a heterogeneous disease with diverse severity and represents a considerable socio-economic burden. Exhaled Breath Condensate (EBC) is a biofluid directly obtained from the airway lining fluid non-invasively. We attempted to discriminate severe from mild-to-moderate asthma using EBC metabolomics based on both NMR and UHPLC-MS techniques. 36 patients were included in this study (15 patients with severe and 21 with mild-to-moderate asthma). EBC was collected and analyzed using both NMR and UHPLC-MS techniques for possible metabolites. Using PLS and oPLS analysis for the UHPLC-MS data, no metabolite was found to be sufficient for the discrimination of asthma severity. However, when another PLS-regression model was applied five metabolites were found to discriminate severe from mild-to-moderate asthma. Amino-acid lysine was the only metabolite that discriminated the two study groups using NMR data (p= 0.04, t-test with Welch's correction, AUC 0.66). EBC is an easily available biofluid which directly represents the lower airways but difficult-to-use for metabolomic analysis. Our study presents some encouraging findings for the discrimination of asthma severity subgroups using EBC metabolomics but more well-designed studies with a higher number of patients need to be conducted.

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.

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry

BACKGROUND

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR.

AIM OF REVIEW

This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

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.

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.

Neonatal Urine Metabolic Profiling and Development of Childhood Asthma

Urine metabolomics case-control studies of childhood asthma have demonstrated a discriminative ability. Here, we investigated whether urine metabolic profiles from healthy neonates were associated with the development of asthma in childhood. Untargeted metabolomics by liquid chromatography-mass spectrometry was applied to urine samples collected at age 4 weeks in 171 and 161 healthy neonates born from mothers with asthma from the COPSAC2000 and COPSAC2010 cohorts, respectively, where persistent wheeze/asthma was prospectively diagnosed using a symptom-based algorithm. Univariate and multivariate analyses were applied to investigate differences in metabolic profiles between children who developed asthma and healthy children. Univariate analysis showed 63 and 87 metabolites (q-value < 0.15) in COPSAC2000 and COPSAC2010, respectively, which is promising for discriminating between asthmatic and healthy children. Of those, 14 metabolites were common among the two cohorts. Multivariate random forest and projection to latent structures discriminant analyses confirmed the discriminatory capacity of the metabolic profiles in both cohorts with estimated errors in prediction equal to 35% and AUCpred > 0.60. Database search enabled annotation of three discriminative features: a glucoronidated compound (steroid), 3-hydroxytetradecanedioic acid (fatty acid), and taurochenodeoxycholate-3-sulfate (bile acid). The urine metabolomics profiles from healthy neonates were associated with the development of childhood asthma, but further research is needed to understand underlying metabolic pathways.

Metabolomics toward personalized medicine

Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes. Over the last decade, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Most diseases result in signature metabolic profiles that reflect the sums of external and internal cellular activities. Metabolomics has a major role in clinical practice as it represents >95% of the workload in clinical laboratories worldwide. Many of these metabolites require different analytical platforms, such as Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), and Ultra Performance Liquid Chromatography (UPLC), while many clinically relevant metabolites are still not routinely amenable to detection using currently available assays. Combining metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. This comprehensive approach will represent a major step forward toward providing precision medical care, in which individual is accounted for variability in genes, environment, and personal lifestyle. In this review, we compare and evaluate the metabolomics strategies and studies that focus on the discovery of biomarkers that have "personalized" diagnostic, prognostic, and therapeutic value, validated for monitoring disease progression and responses to various management regimens.

Urinary organic acids as biomarkers in the assessment of pulmonary function in children with asthma

Childhood asthma prevalence continues to rise despite advancements in prevention and medical management strategies. The purpose of this study was to investigate correlations between urinary organic acids and pulmonary diagnostic tests, asthma control in Greek asthmatic children. We hypothesized that urinary organic acids are positively associated with poor pulmonary function in children with asthma. Seventy-two children, 5 to 12 years old with asthma were recruited from a pediatric asthma clinic in Athens, Greece. Pulmonary function was assessed using spirometry and exhaled nitric oxide analysis. Asthma control was measured qualitatively using the Asthma Control Questionnaire. Targeted metabolomic analysis of 34 urinary organic acids in children was conducted by gas chromatography-mass spectrometry. A statistically significant difference between girls and boys was found for asthma control score (P = .02), lactic acid (P = .03), but not for any other organic acids (P > .05). Statistically significant correlations were found between lactic acid and Forced Expiratory Volume in 1 second (FEV₁) (P = .02), Forced Vital Capacity (FVC) (P = .03); 4- hydroxyphenylacetic acid and FEV₁ (P = .01), FVC (P = .01); 5-hydroxyindoleacetic acid and FEV₁/FVC (P = .03), eNO (P = .05); glycolic acid with Peak Expiratory Flow (PEF) (P = .03); and malic acid with asthma control (P = .02). In conclusion, metabolomics was used to determine correlations between urinary organic acids and conventional pulmonary diagnostic tests in Greek asthmatic children. Metabolomics could be a promising approach for asthma research and in detection of novel biomarkers for asthma monitoring and therapeutic targets for childhood asthma. This study contributes towards a better understanding of the biochemical pathways involved in 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.

A review of metabolomics approaches and their application in identifying causal pathways of childhood asthma

Because asthma is a disease that results from host-environment interactions, an approach that allows assessment of the effect of the environment on the host is needed to understand the disease. Metabolomics has appealing potential as an application to study pathways to childhood asthma development. The objective of this review is to provide an overview of metabolomics methods and their application to understanding host-environment pathways in asthma development. We reviewed recent literature on advances in metabolomics and their application to study pathways to childhood asthma development. We highlight the (1) potential of metabolomics in understanding the pathogenesis of disease and the discovery of biomarkers; (2) choice of metabolomics techniques, biospecimen handling, and data analysis; (3) application to studying the role of the environment on asthma development; (4) review of metabolomics applied to the outcome of asthma; (5) recommendations for application of metabolomics-based -omics data integration in understanding disease pathogenesis; and (6) limitations. In conclusion, metabolomics allows use of biospecimens to identify useful biomarkers and pathways involved in disease development and subsequently to inform a greater understanding of disease pathogenesis and endotypes and prediction of the clinical course of childhood asthma phenotypes.

Metabolic profiling of asthma in mice and the interventional effects of SPA using liquid chromatography and Q-TOF mass spectrometry

Asthma is a chronic inflammatory lung disease that leads to 250 000 deaths annually. There is a need to better understand asthma by identifying new pathogenic molecules. We conducted a liquid-chromatography time-of-flight mass spectrometry (LC-Q-TOF-MS)-based metabolomics study to test for asthma and investigate the interventional mechanisms of surfactant protein A (SPA) in OVA-induced asthma mice. The results revealed that asthma disturbed 32 metabolites in 9 metabolic pathways. After SPA treatment, the metabolomics profile found in asthma was significantly reversed, shifting much closer to that of the control group, indicating that SPA has therapeutic effects against asthma. Metabolomic pathway analysis by the ingenuity pathway analysis demonstrated that several pathways including fatty acid metabolism, lipid metabolism, and purine metabolism were significantly altered in asthma. This study offers new methodologies for the understanding of asthma and the mechanisms of SPA in treating asthma.

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.

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.

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.

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.

Sample normalization methods in quantitative metabolomics

To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts.

Molecular phenotyping and biomarker development: are we on our way towards targeted therapy for severe asthma?

Although different phenotypes of severe asthma can be identified, all are characterized by common symptoms. Due to their heterogeneity, they exhibit differences in pathogenesis, etiology and clinical responses to therapeutic approaches. The identification of distinct molecular phenotypes to define severe asthmatic patients will allow us to better understand the pathophysiology of the disease and thus to more precisely target the treatment for each patient. To achieve this goal, a systematic search for new, reliable and stable biomarkers specific for each phenotype is essential. This review focuses on the current known molecular phenotypes of severe asthma and highlights the need for biomarkers that could (either alone or in combination) be predictive of the treatment outcome.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

Biomarkers and severe asthma: a critical appraisal

Severe asthma (SA) is a clinically and etiologically heterogeneous respiratory disease which affects among 5–10 % of asthmatic patients. Despite high-dose therapy, a large patients percentage is not fully controlled and has a poor quality of life. In this review, we describe the biomarkers actually known in scientific literature and used in clinical practice for SA assessment and management: neutrophils, eosinophils, periostin, fractional exhaled nitric oxide, exhaled breath condensate and galectins. Moreover, we give an overview on clinical and biological features characterizing severe asthma, paying special attention to the potential use of these ones as reliable markers. We finally underline the need to define different biomarkers panels to select patients affected by severe asthma for specific and personalized therapeutic approach.

The metabolomics of asthma control: a promising link between genetics and disease

Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative "omics" approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), - using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites-monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.

Urinary proteomics and metabolomics in the diagnosis of pediatric disorders

Proteomics is the study of structures and functions of proteins, while metabolomics is the study of small-molecule metabolites in the cells, tissues, and organs of the organism. Proteomic technologies have wide applications in medical field. The current revolution in proteomics has led to the discovery of several new protein markers for various disorders. Urinary proteomics and metabolomics have also evolved in the recent years, for the diagnosis of both renal and nonrenal disorders. The urinary proteome varies in normal and abnormal conditions. Different techniques are employed for the analysis of pediatric urinary proteome, the commonest being MS. Before introduction into clinical use, there is the need for careful standardization. Available data suggest that there are differences in urinary proteome between adult and pediatric populations. It is noted that infant urine contains proteins involved in translation and transcription, cellular growth, and metabolic processes, which are not predominant in adult urine. Available data on urinary proteomic and metabolomic profile in common pediatric disorders are also reviewed here.

Metabolomics study on serum of allergic bronchial asthma rabbits treated by Recuperating Lung decoction

This study found seven biological markers in the Recuperating Lung decoction, which intervenes in the mechanism of asthma.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.

Functional interpretation of metabolomics data as a new method for predicting long-term side effects: treatment of atopic dermatitis in infants

Topical steroids are used for the treatment of primary atopic dermatitis (AD); however, their associated risk of serious complications is great due to the presence of vulnerable lesions in young children with AD. Topical calcineurin inhibitors (TCIs) are steroid-free, anti-inflammatory agents used for topical AD therapy. However, their use is prohibited in infants <2 years of age because of their carcinogenic potential. We conducted a randomized, double-blind trial to evaluate the efficacy of TCIs as a secondary AD treatment for children <2 years of age by comparing 1% pimecrolimus cream with 0.05% desonide cream. We performed urinary metabolomics to predict long-term side effects. The 1% pimecrolimus cream displayed similar efficacy and exceptional safety compared with the 0.05% desonide cream. Metabolomics-based long-term toxicity tests effectively predicted long-term side effects using short-term clinical models. This applicable method for the functional interpretation of metabolomics data sets the foundation for future studies involving the prediction of the toxicity and systemic reactions caused by long-term medication administration.

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

Exhaled breath condensate (EBC) collection is a noninvasive method to investigate lung diseases. EBC is usually collected with commercial/custom-made condensers, but the optimal condensing temperature is often unknown. As such, the physical and chemical properties of exhaled metabolites should be considered when setting the temperature, therefore requiring validation and standardization of the collecting procedure. EBC is frequently used in nuclear magnetic resonance (NMR)-based metabolomics, which unambiguously recognizes different pulmonary pathological states. Here we applied NMR-based metabolomics to asthmatic and healthy EBC samples collected with two commercial condensers operating at -27.3 and -4.8 °C. Thirty-five mild asthmatic patients and 35 healthy subjects were included in the study, while blind validation was obtained from 20 asthmatic and 20 healthy different subjects not included in the primary analysis. We initially analyzed the samples separately and assessed the within-day, between-day, and technical repeatabilities. Next, samples were interchanged, and, finally, all samples were analyzed together, disregarding the condensing temperature. Partial least-squares discriminant analysis of NMR spectra correctly classified samples, without any influence from the temperature. Input variables were either integral bucket areas (spectral bucketing) or metabolite concentrations (targeted profiling). We always obtained strong regression models (95%), with high average-quality parameters for spectral profiling (R(2) = 0.84 and Q(2) = 0.78) and targeted profiling (R(2) = 0.91 and Q(2) = 0.87). In particular, although targeted profiling clustering is better than spectral profiling, all models reproduced the relative metabolite variations responsible for class differentiation. This warrants that cross comparisons are reliable and that NMR-based metabolomics could attenuate some specific problems linked to standardization of EBC collection.

Systems biology of asthma and allergic diseases: a multiscale approach

Systems biology is an approach to understanding living systems that focuses on modeling diverse types of high-dimensional interactions to develop a more comprehensive understanding of complex phenotypes manifested by the system. High-throughput molecular, cellular, and physiologic profiling of populations is coupled with bioinformatic and computational techniques to identify new functional roles for genes, regulatory elements, and metabolites in the context of the molecular networks that define biological processes associated with system physiology. Given the complexity and heterogeneity of asthma and allergic diseases, a systems biology approach is attractive, as it has the potential to model the myriad connections and interdependencies between genetic predisposition, environmental perturbations, regulatory intermediaries, and molecular sequelae that ultimately lead to diverse disease phenotypes and treatment responses across individuals. The increasing availability of high-throughput technologies has enabled system-wide profiling of the genome, transcriptome, epigenome, microbiome, and metabolome, providing fodder for systems biology approaches to examine asthma and allergy at a more holistic level. In this article we review the technologies and approaches for system-wide profiling, as well as their more recent applications to asthma and allergy. We discuss approaches for integrating multiscale data through network analyses and provide perspective on how individually captured health profiles will contribute to more accurate systems biology views of asthma and allergy.

The metabolomics of airway diseases, including COPD, asthma and cystic fibrosis

Chronic obstructive pulmonary disease (COPD), asthma and cystic fibrosis (CF) are characterized by airway obstruction and an inflammatory process. Reaching early diagnosis and discrimination of subtypes of these respiratory diseases are quite a challenging task than other chronic illnesses. Metabolomics is the study of metabolic pathways and the measurement of unique biochemical molecules generated in a living system. In the last decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. In this article, we review the current state of the metabolomics of COPD, asthma and CF with a focus on the different methods and instrumentation being used for the discovery of biomarkers in research and translation into clinic as diagnostic aids for the choice of patient-specific therapies.

Metabolomics Reveals Inflammatory-Linked Pulmonary Metabolic Alterations in a Murine Model of House Dust Mite-Induced Allergic Asthma

Although the house dust mite (HDM) is a major environmental aeroallergen that promotes the pathogenesis and severity of allergic asthma, it remains elusive if HDM exposures can induce global metabolism aberrations during allergic airway inflammation. Using an integrated gas and liquid chromatography mass spectrometry-based metabolomics and multiplex cytokine profile analysis, metabolic alterations and cytokine changes were investigated in the bronchoalveolar lavage fluid (BALF), serum, and lung tissues in experimental HDM-induced allergic asthma. Allergic pulmonary HDM exposures lead to pronounced eosinophilia, neutrophilia, and increases in inflammatory cytokines. Metabolomics analysis of the BALF, serum, and lung tissues revealed distinctive compartmental metabolic signatures, which included depleted carbohydrates, increased energy metabolites, and consistent losses of sterols and phosphatidylcholines. Pearson correlation analysis uncovered strong associations between specific metabolic alterations and inflammatory cells and cytokines, linking altered pulmonary metabolism to allergic airway inflammation. The clinically prescribed glucocorticoid prednisolone could modulate airway inflammation but was ineffective against the reversal of many HDM-induced metabolic alterations. Collectively, metabolomics reveal comprehensive pulmonary metabolic signatures in HDM-induced allergic asthma, with specific alterations in carbohydrates, lipids, sterols, and energy metabolic pathways. Altered pulmonary metabolism may be a major underlying molecular feature involved during HDM-induced allergic airway inflammation, linked to inflammatory cells and cytokines changes.

Potential of metabolomics in preclinical and clinical drug development

Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development.