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

A Chemical Structure and Machine Learning Approach to Assess the Potential Bioactivity of Endogenous Metabolites and Their Association with Early Childhood Systemic Inflammation

Metabolomics has gained much attention due to its potential to reveal molecular disease mechanisms and present viable biomarkers. This work uses a panel of untargeted serum metabolomes from 602 children from the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 517 chemical compounds curated using automated procedures. We created a filtering method for the quantified metabolites using predicted quantitative structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines. The metabolites measured in the children's serums are predicted to affect specific targeted models, known for their significance in inflammation, immune function, and health outcomes. The targets from Tox21 have been used as targets with quantitative structure-activity relationships (QSARs). They were trained for ~7000 structures, saved as models, and then applied to the annotated metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation.

Serum Metabolomics Reveals Metabolomic Profile and Potential Biomarkers in Asthma

PURPOSE

Asthma is a highly heterogeneous disease. Metabolomics plays a pivotal role in the pathogenesis and development of asthma. The main aims of our study were to explore the underlying mechanism of asthma and to identify novel biomarkers through metabolomics approach.

METHODS

Serum samples from 102 asthmatic patients and 18 healthy controls were collected and analyzed using liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) system. Multivariate analysis and weighted gene co-expression network analysis (WGCNA) were performed to explore asthma-associated metabolomics profile and metabolites. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used for pathway enrichment analysis. Subsequently, 2 selected serum hub metabolites, myristoleic acid and dodecanoylcarnitine, were replicated in a validation cohort using ultra-high performance LC-MS/MS system (UHPLC-MS/MS).

RESULTS

Distinct metabolomics profile of asthma was revealed by multivariate analysis. Then, 116 overlapped asthma-associated metabolites between multivariate analysis and WGCNA, including 12 hub metabolites, were identified. Clinical features-associated hub metabolites were also identified by WGCNA. Among 116 asthma-associated metabolites, Sphingolipid metabolism and valine, leucine and isoleucine biosynthesis were revealed by KEGG analysis. Furthermore, serum myristoleic acid and dodecanoylcarnitine were significantly higher in asthmatic patients than in healthy controls in validation cohort. Additionally, serum myristoleic acid and dodecanoylcarnitine demonstrated high sensitivities and specificities in predicting asthma.

CONCLUSIONS

Collectively, asthmatic patients showed a unique serum metabolome. Sphingolipid metabolism and valine, leucine and isoleucine biosynthesis were involved in the pathogenesis of asthma. Furthermore, our results suggest the promising values of serum myristoleic acid and dodecanoylcarnitine for asthma diagnosis in adults.

Urinary metabolomic profiles uncover metabolic pathways in children with asthma

OBJECTIVE

The prevalence of asthma has gradually increased worldwide in recent years, which has made asthma a global public health problem. However, due to its complexity and heterogeneity, there are a few academic debates on the pathogenic mechanism of asthma. The study of the pathogenesis of asthma through metabolomics has become a new research direction. We aim to uncover the metabolic pathway of children with asthma.

METHODS

Liquid chromatography (LC)-mass spectrometry (MS)-based metabolomic analysis was conducted to compare urine metabolic profiles between asthmatic children (n = 30) and healthy controls (n = 10).

RESULTS

Orthogonal projections to latent structures-discrimination analysis (OPLS-DA) showed that there were significant differences in metabolism between the asthma group and the control group with three different metabolites screened out, including traumatic acid, dodecanedioic acid, and glucobrassicin, and the levels of traumatic acid and dodecanedioic acid in the urine samples of asthmatic children were lower than those of healthy controls therein. Pathway enrichment analysis of differentially abundant metabolites suggested that α-linolenic acid metabolism was an asthma-related pathway.

CONCLUSIONS

This study suggests that there are significant metabolic differences in the urine of asthmatic children and healthy controls, and α-linolenic acid metabolic pathways may be involved in the pathogenesis of asthma.

S100A4 reprofiles lipid metabolism in mast cells via RAGE and PPAR-γ signaling pathway

S100A4 is implicated in metabolic reprogramming across various cell types and is known to propel the progression of numerous diseases including allergies. Nonetheless, the influence of S100A4 on mast cell metabolic reprogramming during allergic disorders remains unexplored. Utilizing a mast cell line (C57), cells were treated with recombinant mouse S100A4 protein, with or without a PPAR-γ agonist (ROSI) or a RAGE inhibitor (FPS-ZM1). Subsequent assessments were conducted for mast cell activation and lipid metabolism. S100A4 induced mast cell activation and the release of inflammatory mediators, concurrently altering molecules involved in lipid metabolism and glycolysis over time. Furthermore, S100A4 stimulation resulted in cellular oxidative stress and mitochondrial dysfunction. Alterations in the levels of pivotal molecules within the RAGE/Src/JAK2/STAT3/PPAR-γ and NF-κB signaling pathways were noted during this stimulation, which were partially counteracted by ROSI or FPS-ZMI. Additionally, a trend of metabolic alterations was identified in patients with allergic asthma who exhibited elevated serum S100A4 levels. Correlation analysis unveiled a positive association between serum S100A4 and serum IgE, implying an indirect association with asthma. Collectively, our findings suggest that S100A4 regulates the lipid-metabolic reprogramming of mast cells, potentially via the RAGE and PPAR-γ-involved signaling pathway, offering a novel perspective in the disease management in patients with allergic disorders.

Pi-Pa-Run-Fei-Tang alleviates lung injury by modulating IL-6/JAK2/STAT3/IL-17 and PI3K/AKT/NF-κB signaling pathway and balancing Th17 and Treg in murine model of OVA-induced asthma

ETHNOPHARMACOLOGICAL RELEVANCE

Pi-Pa-Run-Fei-Tang (PPRFT) is an empirical TCM prescription for treating asthma. However, the underlying mechanisms of PPRFT in asthma treatment have yet to be elucidated. Recent advances have revealed that some natural components could ameliorate asthma injury by affecting host metabolism. Untargeted metabolomics can be used to better understand the biological mechanisms underlying asthma development and identify early biomarkers that can help advance treatment.

AIM OF THE STUDY

The aim of this study was to verification the efficacy of PPRFT in the treatment of asthma and to preliminarily explore its mechanism.

MATERIALS AND METHODS

A mouse asthma model was built by OVA induction. Inflammatory cell in BALF was counted. The level of IL-6, IL-1β, and TNF-α in BALF were measured. The levels of IgE in the serum and EPO, NO, SOD, GSH-Px, and MDA in the lung tissue were measured. Furthermore, pathological damage to the lung tissues was detected to evaluate the protective effects of PPRFT. The serum metabolomic profiles of PPRFT in asthmatic mice were determined by GC-MS. The regulatory effects on mechanism pathways of PPRFT in asthmatic mice were explored via immunohistochemical staining and western blotting analysis.

RESULTS

PPRFT displayed lung-protective effects through decreasing oxidative stress, airway inflammation, and lung tissue damage in OVA-induced mice, which was demonstrated by decreasing inflammatory cell levels, IL-6, IL-1β, and TNF-α levels in BALF, and IgE levels in serum, decreasing EPO, NO, and MDA levels in lung tissue, elevating SOD and GSH-Px levels in lung tissue and lung histopathological changes. In addition, PPRFT could regulate the imbalance in Th17/Treg cell ratios, suppress RORγt, and increase the expression of IL-10 and Foxp3 in the lung. Moreover, PPRFT treatment led to decreased expression of IL-6, p-JAK2/Jak2, p-STAT3/STAT3, IL-17, NF-κB, p-AKT/AKT, and p-PI3K/PI3K. Serum metabolomics analysis revealed that 35 metabolites were significantly different among different groups. Pathway enrichment analysis indicated that 31 pathways were involved. Moreover, correlation analysis and metabolic pathway analysis identified three key metabolic pathways: galactose metabolism; tricarboxylic acid cycle; and glycine, serine, and threonine metabolism.

CONCLUSION

This research indicated that PPRFT treatment not only attenuates the clinical symptoms of asthma but is also involved in regulating serum metabolism. The anti-asthmatic activity of PPRFT may be associated with the regulatory effects of IL-6/JAK2/STAT3/IL-17 and PI3K/AKT/NF-κB mechanistic pathways.

A Metabolites Merging Strategy (MMS): Harmonization to Enable Studies' Intercomparison

Metabolomics encounters challenges in cross-study comparisons due to diverse metabolite nomenclature and reporting practices. To bridge this gap, we introduce the Metabolites Merging Strategy (MMS), offering a systematic framework to harmonize multiple metabolite datasets for enhanced interstudy comparability. MMS has three steps. Step 1: Translation and merging of the different datasets by employing InChIKeys for data integration, encompassing the translation of metabolite names (if needed). Followed by Step 2: Attributes' retrieval from the InChIkey, including descriptors of name (title name from PubChem and RefMet name from Metabolomics Workbench), and chemical properties (molecular weight and molecular formula), both systematic (InChI, InChIKey, SMILES) and non-systematic identifiers (PubChem, CheBI, HMDB, KEGG, LipidMaps, DrugBank, Bin ID and CAS number), and their ontology. Finally, a meticulous three-step curation process is used to rectify disparities for conjugated base/acid compounds (optional step), missing attributes, and synonym checking (duplicated information). The MMS procedure is exemplified through a case study of urinary asthma metabolites, where MMS facilitated the identification of significant pathways hidden when no dataset merging strategy was followed. This study highlights the need for standardized and unified metabolite datasets to enhance the reproducibility and comparability of metabolomics studies.

A chemical structure and machine learning approach to assess the potential bioactivity of endogenous metabolites and their association with early-childhood hs-CRP levels

Metabolomics has gained much attraction due to its potential to reveal molecular disease mechanisms and present viable biomarkers. In this work we used a panel of untargeted serum metabolomes in 602 childhood patients of the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 493 chemical compounds curated using automated procedures. Using predicted quantitative-structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines, we created a filtering method for the vast number of quantified metabolites. The metabolites measured in children's serums used here have predicted potential against the chosen target modelled targets. The targets from Tox21 have been used with quantitative structure-activity relationships (QSARs) and were trained for ~7000 structures, saved as models, and then applied to 493 metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation. The significant metabolites were reported.

Metabolomics Applied to Pediatric Asthma: What Have We Learnt in the Past 10 Years?

Background: Asthma is the most common chronic condition in children. It is a complex non-communicable disease resulting from the interaction of genetic and environmental factors and characterized by heterogeneous underlying molecular mechanisms. Metabolomics, as with the other omic sciences, thanks to the joint use of high-throughput technologies and sophisticated multivariate statistical methods, provides an unbiased approach to study the biochemical-metabolic processes underlying asthma. The aim of this narrative review is the analysis of the metabolomic studies in pediatric asthma published in the past 10 years, focusing on the prediction of asthma development, endotype characterization and pharmaco-metabolomics. Methods: A total of 43 relevant published studies were identified searching the MEDLINE/Pubmed database, using the following terms: "asthma" AND "metabolomics". The following filters were applied: language (English), age of study subjects (0-18 years), and publication date (last 10 years). Results and Conclusions: Several studies were identified within the three areas of interest described in the aim, and some of them likely have the potential to influence our clinical approach in the future. Nonetheless, further studies are needed to validate the findings and to assess the role of the proposed biomarkers as possible diagnostic or prognostic tools to be used in clinical practice.

Metabolomics in diabetes mellitus: clinical insight

INTRODUCTION

Diabetes Mellitus (DM) is a chronic heterogeneous metabolic disorder characterized by hyperglycemia due to the destruction of insulin-producing pancreatic β cells and/or insulin resistance. It is now considered a global epidemic disease associated with serious threats to a patient's life. Understanding the metabolic pathways involved in disease pathogenesis and progression is important and would improve prevention and management strategies. Metabolomics is an emerging field of research that offers valuable insights into the metabolic perturbation associated with metabolic diseases, including DM.

AREA COVERED

Herein, we discussed the metabolomics in type 1 and 2 DM research, including its contribution to understanding disease pathogenesis and identifying potential novel biomarkers clinically useful for disease screening, monitoring, and prognosis. In addition, we highlighted the metabolic changes associated with treatment effects, including insulin and different anti-diabetic medications.

EXPERT OPINION

By analyzing the metabolome, the metabolic disturbances involved in T1DM and T2DM can be explored, enhancing our understanding of the disease progression and potentially leading to novel clinical diagnostic and effective new therapeutic approaches. In addition, identifying specific metabolites would be potential clinical biomarkers for predicting the disease and thus preventing and managing hyperglycemia and its complications.

Online breath analysis with SESI/HRMS for metabolic signatures in children with allergic asthma

Introduction: There is a need to improve the diagnosis and management of pediatric asthma. Breath analysis aims to address this by non-invasively assessing altered metabolism and disease-associated processes. Our goal was to identify exhaled metabolic signatures that distinguish children with allergic asthma from healthy controls using secondary electrospray ionization high-resolution mass spectrometry (SESI/HRMS) in a cross-sectional observational study.

Methods: Breath analysis was performed with SESI/HRMS. Significant differentially expressed mass-to-charge features in breath were extracted using the empirical Bayes moderated t-statistics test. Corresponding molecules were putatively annotated by tandem mass spectrometry database matching and pathway analysis.

Results: 48 allergic asthmatics and 56 healthy controls were included in the study. Among 375 significant mass-to-charge features, 134 were putatively identified. Many of these could be grouped to metabolites of common pathways or chemical families. We found several pathways that are well-represented by the significant metabolites, for example, lysine degradation elevated and two arginine pathways downregulated in the asthmatic group. Assessing the ability of breath profiles to classify samples as asthmatic or healthy with supervised machine learning in a 10 times repeated 10-fold cross-validation revealed an area under the receiver operating characteristic curve of 0.83.

Discussion: For the first time, a large number of breath-derived metabolites that discriminate children with allergic asthma from healthy controls were identified by online breath analysis. Many are linked to well-described metabolic pathways and chemical families involved in pathophysiological processes of asthma. Furthermore, a subset of these volatile organic compounds showed high potential for clinical diagnostic applications.

Application of Metabolomics in Obesity-Related Childhood Asthma Subtyping: A Narrative Scoping Review

Obesity-related asthma is a heterogeneous childhood asthma phenotype with rising prevalence. Observational studies identify early-life obesity or weight gain as risk factors for childhood asthma development. The reverse association is also described, children with asthma have a higher risk of being obese. Obese children with asthma have poor symptom control and an increased number of asthma attacks compared to non-obese children with asthma. Clinical trials have also identified that a proportion of obese children with asthma do not respond as well to usual treatment (e.g., inhaled corticosteroids). The heterogeneity of obesity-related asthma phenotypes may be attributable to different underlying pathogenetic mechanisms. Although few childhood obesity-related asthma endotypes have been described, our knowledge in this field is incomplete. An evolving analytical profiling technique, metabolomics, has the potential to link individuals' genetic backgrounds and environmental exposures (e.g., diet) to disease endotypes. This will ultimately help define clinically relevant obesity-related childhood asthma subtypes that respond better to targeted treatment. However, there are challenges related to this approach. The current narrative scoping review summarizes the evidence for metabolomics contributing to asthma subtyping in obese children, highlights the challenges associated with the implementation of this approach, and identifies gaps in research.

The Role of Pericytes in Regulation of Innate and Adaptive Immunity

Pericytes are perivascular multipotent cells wrapping microvascular capillaries, where they support vasculature functioning, participate in tissue regeneration, and regulate blood flow. However, recent evidence suggests that in addition to traditionally credited structural function, pericytes also manifest immune properties. In this review, we summarise recent data regarding pericytes' response to different pro-inflammatory stimuli and their involvement in innate immune responses through expression of pattern-recognition receptors. Moreover, pericytes express various adhesion molecules, thus regulating trafficking of immune cells across vessel walls. Additionally, the role of pericytes in modulation of adaptive immunity is discussed. Finally, recent reports have suggested that the interaction with cancer cells evokes immunosuppression function in pericytes, thus facilitating immune evasion and facilitating cancer proliferation and metastasis. However, such complex and multi-faceted cross-talks of pericytes with immune cells also suggest a number of potential pericyte-based therapeutic methods and techniques for cancer immunotherapy and treatment of autoimmune and auto-inflammatory disorders.

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.

Extracellular vesicles isolated from hyperuricemia patients might aggravate airway inflammation of COPD via senescence-associated pathway

BACKGROUNDS

Chronic obstructive pulmonary disease (COPD) is a major health issue resulting in significant mortality worldwide. Due to the high heterogeneity and unclear pathogenesis, the management and therapy of COPD are still challenging until now. Elevated serum uric acid(SUA) levels seem to be associated with the inflammatory level in patients with COPD. However, the underlying mechanism is not yet clearly established. In the current research, we aim to elucidate the effect of high SUA levels on airway inflammation among COPD patients.

METHODS

Through bioinformatic analysis, the common potential key genes were determined in both COPD and hyperuricemia (HUA) patients. A total of 68 COPD patients aged 50-75-year were included in the study, and their clinical parameters, including baseline characteristics, lung function test, as well as blood chemistry test were recorded. These parameters were then compared between the COPD patients with and without HUA. Hematoxylin & Eosin (HE), immunofluorescence (IF), and Masson trichrome staining were performed to demonstrate the pathological changes in the lung tissues. Furthermore, we isolated extracellular vesicles (EVs) from plasma, sputum, and bronchoalveolar lavage fluid (BALF) samples and detected the expression of inflammatory factor (Interleukin-6 (IL-6), IL-8 and COPD related proteases (antitrypsin and elastase) between two groups. Additionally, we treated the human bronchial epithelial (HBE) cells with cigarette smoke extract (CSE), and EVs were derived from the plasma in vitro experiments. The critical pathway involving the relationship between COPD and HUA was eventually validated based on the results of RNA sequencing (RNA-seq) and western blot (WB).

RESULTS

In the study, the COPD patients co-existing with HUA were found to have more loss of pulmonary function compared with those COPD patients without HUA. The lung tissue samples of patients who had co-existing COPD and HUA indicated greater inflammatory cell infiltration, more severe airway destruction and even fibrosis. Furthermore, the high SUA level could exacerbate the progress of airway inflammation in COPD through the transfer of EVs. In vitro experiments, we determined that EVs isolated from plasma, sputum, and BALF played pivotal roles in the CSE-induced inflammation of HBE. The EVs in HUA patients might exacerbate both systemic inflammation and airway inflammatory response via the senescence-related pathway.

CONCLUSION

The pulmonary function and clinical indicators of COPD patients with HUA were worse than those without HUA, which may be caused by the increased airway inflammatory response through the EVs in the patient's peripheral blood. Moreover, it might mediate the EVs via senescence-related pathways in COPD patients with HUA.

Air pollution, metabolites and respiratory health across the life-course

Previous studies have explored the relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and the associated mechanisms have not been reviewed from a life-course perspective. Here, we provide a narrative review summarising recent evidence on the associations of metabolic profiles with air pollution exposure and lung function in children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analysing air pollution-related metabolic profiles and 16 studies analysing lung function-related metabolic profiles. A wide range of metabolites were associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general population and with respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers the potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many studies suffer from small sample sizes, cross-sectional designs, a preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools for healthy living in urbAN Settings (EXPANSE) project aims to address some of these shortcomings by combining biospecimens from large European cohorts and harmonised air pollution exposure and exposome data.

Proline metabolism reprogramming of trained macrophages induced by early respiratory infection combined with allergen sensitization contributes to development of allergic asthma in childhood of mice

Background

Infants with respiratory syncytial virus (RSV)-associated bronchiolitis are at increased risk of childhood asthma. Recent studies demonstrated that certain infections induce innate immune memory (also termed trained immunity), especially in macrophages, to respond more strongly to future stimuli with broad specificity, involving in human inflammatory diseases. Metabolic reprogramming increases the capacity of the innate immune cells to respond to a secondary stimulation, is a crucial step for the induction of trained immunity. We hypothesize that specific metabolic reprogramming of lung trained macrophages induced by neonatal respiratory infection is crucial for childhood allergic asthma.

Objective

To address the role of metabolic reprogramming in lung trained macrophages induced by respiratory virus infection in allergic asthma.

Methods

Neonatal mice were infected and sensitized by the natural rodent pathogen Pneumonia virus of mice (PVM), a mouse equivalent strain of human RSV, combined with ovalbumin (OVA). Lung CD11b⁺ macrophages in the memory phase were re-stimulated to investigate trained immunity and metabonomics. Adoptive transfer, metabolic inhibitor and restore experiments were used to explore the role of specific metabolic reprogramming in childhood allergic asthma.

Results

PVM infection combined with OVA sensitization in neonatal mice resulted in non-Th2 (Th1/Th17) type allergic asthma following OVA challenge in childhood of mice. Lung CD11b⁺ macrophages in the memory phage increased, and showed enhanced inflammatory responses following re-stimulation, suggesting trained macrophages. Adoptive transfer of the trained macrophages mediated the allergic asthma in childhood. The trained macrophages showed metabolic reprogramming after re-stimulation. Notably, proline biosynthesis remarkably increased. Inhibition of proline biosynthesis suppressed the development of the trained macrophages as well as the Th1/Th17 type allergic asthma, while supplement of proline recovered the trained macrophages as well as the allergic asthma.

Conclusion

Proline metabolism reprogramming of trained macrophages induced by early respiratory infection combined with allergen sensitization contributes to development of allergic asthma in childhood. Proline metabolism could be a well target for prevention of allergic asthma in childhood.

Uncovering the effects and mechanism of Danggui Shaoyao San intervention on primary dysmenorrhea by serum metabolomics approach

Danggui Shaoyao San (DSS) is a well-known prescription for relieving primary dysmenorrhea (PD) of women in China. However, its pharmacological mechanism has not been thoroughly uncovered. Here, an integrative UPLC-Q-TOF-MS-based serum metabolomics approach coupled with multivariate data analysis has been proposed to investigate the effects and mechanism of DSS on estradiol benzoate and oxytocin-induced PD rats. 31 potential biomarkers of PD were screened and identified, mainly involving phenylalanine, tyrosine and tryptophan biosynthesis, glycerophospholipid metabolism, primary bile acid biosynthesis, and the occurrence of PD could destroy biological homeostasis in vivo by monitoring these pathways. After DSS treatment, 18 identified different metabolites were restored to the nomal state in varying degrees and could be potential biomarkers contributing to the treatment of DSS. These findings implyed that DSS exhibited a therapeutic effect on PD rats through regulating multiple abnormal pathways. Of note, this study discovered some potential biomarkers related to PD for the first time, such as L-tyrosine, glycocholic acid, citric acid, palmitoylcarnitine, cholesterol. It preliminarily proved the pathophysiology of PD and action mechanisms of DSS on PD, and provided a novel insight into the effectiveness of DSS on PD.

Metabolomics of bronchoalveolar lavage in children with persistent wheezing

Background

Recent studies have demonstrated the important role of metabolomics in the pathogenesis of asthma. However, the role of lung metabolomics in childhood persistent wheezing (PW) or wheezing recurrence remains poorly understood.

Methods

In this prospective observational study, we performed a liquid chromatography/mass spectrometry-based metabolomic survey on bronchoalveolar lavage samples collected from 30 children with PW and 30 age-matched infants (control group). A 2-year follow-up study on these PW children was conducted.

Results

Children with PW showed a distinct characterization of respiratory metabolome compared with control group. Children with PW had higher abundances of choline, oleamide, nepetalactam, butyrylcarnitine, l-palmitoylcarnitine, palmitoylethanolamide, and various phosphatidylcholines. The glycerophospholipid metabolism pathway was the most relevant pathway involving in PW pathophysiologic process. Additionally, different gender, prematurity, and systemic corticoids use demonstrated a greater impact in airway metabolite compositions. Furthermore, for PW children with recurrence during the follow-up period, children who were born prematurely had an increased abundance of butyrylcarnitine relative to those who were carried to term.

Conclusions

This study suggests that the alterations of lung metabolites could be associated with the development of wheezing, and this early alteration could also be correlated with wheezing recurrence later in life.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02087-6.

Metabolomic Profiling of Samples from Pediatric Asthma Patients Unveils Deficient Nutrients in African Americans

Plasma metabolomics represents a potentially powerful approach to understand the biochemical mechanisms of nutrition and metabolism in asthma. This study aims to acquire knowledge on plasma metabolites in asthma, which may provide avenues for nutrition therapy, as well as explanations for the observed effects in existing therapies. This study investigated 249 metabolites from 18 metabolite groups in a large cohort of African American population, including 602 pediatric patients with asthma and 593 controls, using a nuclear magnetic resonance (NMR) metabolomics platform. Decreased levels of citrate, ketone bodies, and two amino acids histidine (His) and glutamine (Gln), were observed in asthma cases compared to controls. Metabolites for lipid metabolism lost significance after controlling for comorbid obesity. For the first time, this study depicts a broad panorama of lipid metabolism and nutrition in asthma. Supplementation or augmentation of nutrients that are deficient may be beneficial for asthma care.

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Asthma is a major health issue in African Americans

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Metabolomics represents a powerful approach to understand the metabolism in asthma

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We observed decreased citrate, ketone bodies, and amino acids in the plasma

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Supplementation of nutrients that are deficient may be beneficial for asthma care

Metabolomics analysis reveals molecular linkages for the impact of vitamin D on childhood allergic airway diseases

BACKGROUND

Several studies have reported the relevance between serum vitamin D and allergic immunoglobulin E (IgE) responses and atopic diseases. However, a metabolomics-based approach to the impacts of vitamin D on allergic reactions remains unclear.

METHODS

A total of 111 children completed a 3-year follow-up were enrolled and classified based on longitudinal vitamin D status (≥ 30 ng/ml, n = 54; 20-29.9 ng/ml, n = 41; <20 ng/ml, n = 16). Urinary metabolomic profiling was performed using ¹ H-Nuclear magnetic resonance (NMR) spectroscopy at age 3. Integrative analyses of their associations related to vitamin D levels, atopic indices, and allergies were performed, and their roles in functional metabolic pathways were also assessed.

RESULTS

Six and five metabolites were identified to be significantly associated with vitamin D status and atopic diseases, respectively (FDR-adjusted p-value <.05). A further correlation analysis revealed that vitamin D-associated 3-hydroxyisobutyric acid and glutamine were positively correlated with atopic disease-associated succinic acid and alanine, respectively. Furthermore, hippuric acid was negatively correlated with atopic disease-associated formic acid, which was positively correlated with vitamin D level (p < .01). Absolute eosinophil count (AEC) was positively correlated with serum D. pteronyssinus- and D. farinae-specific IgE level (p < .01) but negatively correlated with vitamin D level (p < .05). Amino acid metabolisms were significantly associated with vitamin D related to childhood allergies.

CONCLUSION

Integrative metabolomic analysis provides the link of vitamin D-associated metabolites with the gut microbiome and immunoallergic reactions related to childhood allergies.

Plasma Metabolomic Alterations Induced by COVID-19 Vaccination Reveal Putative Biomarkers Reflecting the Immune Response

Vaccination is currently the most effective strategy for the mitigation of the COVID-19 pandemic. mRNA vaccines trigger the immune system to produce neutralizing antibodies (NAbs) against SARS-CoV-2 spike proteins. However, the underlying molecular processes affecting immune response after vaccination remain poorly understood, while there is significant heterogeneity in the immune response among individuals. Metabolomics have often been used to provide a deeper understanding of immune cell responses, but in the context of COVID-19 vaccination such data are scarce. Mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR)-based metabolomics were used to provide insights based on the baseline metabolic profile and metabolic alterations induced after mRNA vaccination in paired blood plasma samples collected and analysed before the first and second vaccination and at 3 months post first dose. Based on the level of NAbs just before the second dose, two groups, "low" and "high" responders, were defined. Distinct plasma metabolic profiles were observed in relation to the level of immune response, highlighting the role of amino acid metabolism and the lipid profile as predictive markers of response to vaccination. Furthermore, levels of plasma ceramides along with certain amino acids could emerge as predictive biomarkers of response and severity of inflammation.

Metabolomics Signatures and Subsequent Maternal Health among Mothers with a Congenital Heart Defect-Affected Pregnancy

Congenital heart defects (CHDs) are the most prevalent and serious of all birth defects in the United States. However, little is known about the impact of CHD-affected pregnancies on subsequent maternal health. Thus, there is a need to characterize the metabolic alterations associated with CHD-affected pregnancies. Fifty-six plasma samples were identified from post-partum women who participated in the National Birth Defects Prevention Study between 1997 and 2011 and had (1) unaffected control offspring (n = 18), (2) offspring with tetralogy of Fallot (ToF, n = 22), or (3) hypoplastic left heart syndrome (HLHS, n = 16) in this pilot study. Absolute concentrations of 408 metabolites using the AbsoluteIDQ^® p400 HR Kit (Biocrates) were evaluated among case and control mothers. Twenty-six samples were randomly selected from above as technical repeats. Analysis of covariance (ANCOVA) and logistic regression models were used to identify significant metabolites after controlling for the maternal age at delivery and body mass index. The receiver operating characteristic (ROC) curve and area-under-the-curve (AUC) are reported to evaluate the performance of significant metabolites. Overall, there were nine significant metabolites (p < 0.05) identified in HLHS case mothers and 30 significant metabolites in ToF case mothers. Statistically significant metabolites were further evaluated using ROC curve analyses with PC (34:1), two sphingolipids SM (31:1), SM (42:2), and PC-O (40:4) elevated in HLHS cases; while LPC (18:2), two triglycerides: TG (44:1), TG (46:2), and LPC (20:3) decreased in ToF; and cholesterol esters CE (22:6) were elevated among ToF case mothers. The metabolites identified in the study may have profound structural and functional implications involved in cellular signaling and suggest the need for postpartum dietary supplementation among women who gave birth to CHD offspring.

Visualizing the knowledge domains and research trends of childhood asthma: A scientometric analysis with CiteSpace

BACKGROUND

Asthma is one of the most common chronic diseases in children globally. In recent decades, advances have been made in understanding the mechanism, diagnosis, treatment and management for childhood asthma, but few studies have explored its knowledge structure and future interests comprehensively.

OBJECTIVE

This scientometric study aims to understand the research status and emerging trends of childhood asthma.

METHODS

CiteSpace (version 5.8.R3) was used to demonstrate national and institutional collaborations in childhood asthma, analyze research subjects and journal distribution, review research keywords and their clusters, as well as detect research bursts.

RESULTS

A total of 14,340 publications related to childhood asthma were extracted from Web of Science (core database) during January 2011 to December 2021. The results showed that academic activities of childhood asthma had increased steadily in the last decade. Most of the research was conducted by developed countries while China, as a developing country, was also actively engaged in this field. In addition to subjects of allergy and immunology, both public health aspects and ecological environmental impacts on the disease were emphasized recently in this research field. Keywords clustering analysis indicated that research on asthma management and atopy was constantly updated and became the two major research focuses recently, as a significant shift in research hotspots from etiology and diagnosis to atopic march and asthma management was identified. Subgroup analysis for childhood asthma management and atopy suggested that caregiver- or physician-based education and interventions were emerging directions for asthma management, and that asthma should be carefully studied in the context of atopy, together with other allergic diseases.

CONCLUSIONS

This study presented a comprehensive and systematic overview of the research status of childhood asthma, provided clues to future research directions, and highlighted two significant research trends of asthma management and atopy in this field.

Perinatal origins of chronic lung disease: mechanisms-prevention-therapy-sphingolipid metabolism and the genetic and perinatal origins of childhood asthma

Childhood asthma derives from complex host-environment interactions occurring in the perinatal and infant period, a critical time for lung development. Sphingolipids are bioactive molecules consistently implicated in the pathogenesis of childhood asthma. Genome wide association studies (GWAS) initially identified a link between alleles within the 17q21 asthma-susceptibility locus, childhood asthma, and overexpression of the ORMDL sphingolipid biosynthesis regulator 3 (ORMDL3), an inhibitor of de novo sphingolipid synthesis. Subsequent studies of pediatric asthma offer strong evidence that these asthma-risk alleles correlate with early-life aberrancies of sphingolipid homeostasis and asthma. Relationships between sphingolipid metabolism and asthma-related risk factors, including maternal obesity and respiratory viral infections, are currently under investigation. This review will summarize how these perinatal and early life exposures can synergize with 17q21 asthma risk alleles to exacerbate disruptions of sphingolipid homeostasis and drive asthma pathogenesis.

Predictive models for personalized asthma attacks based on patient's biosignals and environmental factors: a systematic review

BACKGROUND

Asthma is a chronic disease that exacerbates due to various risk factors, including the patient's biosignals and environmental conditions. It is affecting on average 7% of the world population. Preventing an asthma attack is the main challenge for asthma patients, which requires keeping track of any risk factor that can cause a seizure. Many researchers developed asthma attacks prediction models that used various asthma biosignals and environmental factors. These predictive models can help asthmatic patients predict asthma attacks in advance, and thus preventive measures can be taken. This paper introduces a review of these models to evaluate the used methods, model's performance, and determine the need to improve research in this field.

METHOD

A systematic review was conducted for the research articles introducing asthma attack prediction models for children and adults. We searched the PubMed, ScienceDirect, Springer, and IEEE databases from January 2000 to December 2020. The search includes the prediction models that used biosignal, environmental, and both risk factors. The research article's quality was assessed and scored based on two checklists, the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) and the Critical Appraisal Skills Programme clinical prediction rule checklist (CASP). The highest scored articles were selected to review.

RESULT

From 1068 research articles we reviewed, we found that most of the studies used asthma biosignal factors only for prediction, few of the studies used environmental factors, and limited studies used both of these factors. Fifteen different asthma attack predictive models were selected for this review. we found that most of the studies used traditional prediction methods, like Support Vector Machine and regression. We have identified the pros and cons of the reviewed asthma attack prediction models and propose solutions to advance the studies in this field.

CONCLUSION

Asthma attack predictive models become more significant when using both patient's biosignal and environmental factors. There is a lack of utilizing advanced machine learning methods, like deep learning techniques. Besides, there is a need to build smart healthcare systems that provide patients with decision-making systems to identify risk and visualize high-risk regions.

Metabolomics, Microbiota, and In Vivo and In Vitro Biomarkers in Type 2 Severe Asthma: A Perspective Review

Precision medicine refers to the tailoring of therapeutic strategies to the individual characteristics of each patient; thus, it could be a new approach for the management of severe asthma that considers individual variability in genes, environmental exposure, and lifestyle. Precision medicine would also assist physicians in choosing the right treatment, the best timing of administration, consequently trying to maximize drug efficacy, and, possibly, reducing adverse events. Metabolomics is the systematic study of low molecular weight (bio)chemicals in a given biological system and offers a powerful approach to biomarker discovery and elucidating disease mechanisms. In this point of view, metabolomics could play a key role in targeting precision medicine.

Metabolomics, Microbiota, and In Vivo and In Vitro Biomarkers in Type 2 Severe Asthma: A Perspective Review

Precision medicine refers to the tailoring of therapeutic strategies to the individual characteristics of each patient; thus, it could be a new approach for the management of severe asthma that considers individual variability in genes, environmental exposure, and lifestyle. Precision medicine would also assist physicians in choosing the right treatment, the best timing of administration, consequently trying to maximize drug efficacy, and, possibly, reducing adverse events. Metabolomics is the systematic study of low molecular weight (bio)chemicals in a given biological system and offers a powerful approach to biomarker discovery and elucidating disease mechanisms. In this point of view, metabolomics could play a key role in targeting precision medicine.

Inhaled corticosteroids' effects on biomarkers in exhaled breath condensate and blood in patients newly diagnosed with asthma who smoke

OBJECTIVE

Exposure to cigarette smoke complicates the treatment and management of asthma through a variety of inflammatory effects. This study aimed to investigate the differences between newly diagnosed cases of asthma in smokers and nonsmokers in terms of localized and systemic biomarkers following treatment with inhaled corticosteroids (ICS) or ICS in combination with a long-acting β2 agonist (LABA).

METHODS

Specimens of exhaled breath condensate (EBC) from newly diagnosed patients with asthma were used to quantify inflammation in the airways, while blood samples were used to assess systemic inflammation. In both samples, the levels of IL-6, LTB4, LTD4, and 8-isoprostane were measured and these were repeated after 3 months of treatment with ICS or ICS + LABA.

RESULTS

Of the 20 patients, 10 (50%) were nonsmokers with asthma (NSA) and 10 (50%) smokers with asthma (SA). There was no statistically significant difference in the blood or EBC levels of IL-6, LTB4, LTD4, or 8-isoprostane between the groups prior to treatment. Only the decrease in 8-isoprostane level in the EBC samples was found to be significantly greater in the NSA group after treatment (for smokers, the change was 2.91 ± 23.22, while for nonsmokers it was -22.72 ± 33.12, p = 0.022). Post-treatment asthma control was significantly better in the NSA group (p = 0.033).

CONCLUSION

Monitoring the alterations in 8-isoprostane levels in EBC in patients with asthma who smoke may be helpful in deciding on therapeutic management and switching treatments. Asthma control was better in nonsmokers than in smokers.

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.

Metabolomics in the Identification of Biomarkers of Asthma

Asthma is a major non-communicable disease characterized by recurrent attacks of breathlessness and wheezing [...].