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

An Extensively Hydrolyzed Formula Supplemented with Two Human Milk Oligosaccharides Modifies the Fecal Microbiome and Metabolome in Infants with Cow's Milk Protein Allergy

Cow's milk protein allergy (CMPA) is a prevalent food allergy among infants and young children. We conducted a randomized, multicenter intervention study involving 194 non-breastfed infants with CMPA until 12 months of age (clinical trial registration: NCT03085134). One exploratory objective was to assess the effects of a whey-based extensively hydrolyzed formula (EHF) supplemented with 2'-fucosyllactose (2'-FL) and lacto-N-neotetraose (LNnT) on the fecal microbiome and metabolome in this population. Thus, fecal samples were collected at baseline, 1 and 3 months from enrollment, as well as at 12 months of age. Human milk oligosaccharides (HMO) supplementation led to the enrichment of bifidobacteria in the gut microbiome and delayed the shift of the microbiome composition toward an adult-like pattern. We identified specific HMO-mediated changes in fecal amino acid degradation and bile acid conjugation, particularly in infants commencing the HMO-supplemented formula before the age of three months. Thus, HMO supplementation partially corrected the dysbiosis commonly observed in infants with CMPA. Further investigation is necessary to determine the clinical significance of these findings in terms of a reduced incidence of respiratory infections and other potential health benefits.

Genomic, Epigenomic, Transcriptomic, Proteomic and Metabolomic Approaches in Atopic Dermatitis

Atopic dermatitis (AD) is a chronic inflammatory skin disease with a high prevalence in the developed countries. It is associated with atopic and non-atopic diseases, and its close correlation with atopic comorbidities has been genetically demonstrated. One of the main roles of genetic studies is to comprehend the defects of the cutaneous barrier due to filaggrin deficit and epidermal spongiosis. Recently, epigenetic studies started to analyze the influence of the environmental factors on gene expression. The epigenome is considered to be a superior second code that controls the genome, which includes alterations of the chromatin. The epigenetic changes do not alter the genetic code, however, changes in the chromatin structure could activate or inhibit the transcription process of certain genes and consequently, the translation process of the new mRNA into a polypeptide chain. In-depth analysis of the transcriptomic, metabolomic and proteomic studies allow to unravel detailed mechanisms that cause AD. The extracellular space and lipid metabolism are associated with AD that is independent of the filaggrin expression. On the other hand, around 45 proteins are considered as the principal components in the atopic skin. Moreover, genetic studies based on the disrupted cutaneous barrier can lead to the development of new treatments targeting the cutaneous barrier or cutaneous inflammation. Unfortunately, at present, there are no target therapies that focus on the epigenetic process of AD. However, in the future, miR-143 could be an important objective for new therapies, as it targets the miR-335:SOX axis, thereby restoring the miR-335 expression, and repairing the cutaneous barrier defects.

Association of Metabolites, Nutrients, and Toxins in Maternal and Cord Serum with Asthma, IgE, SPT, FeNO, and Lung Function in Offspring

The role of metabolites, nutrients, and toxins (MNTs) in sera at the end of pregnancy and of their association with offspring respiratory and allergic disorders is underexplored. Untargeted approaches detecting a variety of compounds, known and unknown, are limited. In this cohort study, we first aimed at discovering associations of MNTs in grandmaternal (F0) serum with asthma, immunoglobulin E, skin prick tests, exhaled nitric oxide, and lung function parameters in their parental (F1) offspring. Second, for replication, we tested the identified associations of MNTs with disorders in their grandchildren (F2-offspring) based on F2 cord serum. The statistical analyses were sex-stratified. Using liquid chromatography/high-resolution mass spectrometry in F0, we detected signals for 2286 negative-ion lipids, 59 positive-ion lipids, and 6331 polar MNTs. Nine MNTs (one unknown MNT) discovered in F0-F1 and replicated in F2 showed higher risks of respiratory/allergic outcomes. Twelve MNTs (four unknowns) constituted a potential protection in F1 and F2. We recognized MNTs not yet considered candidates for respiratory/allergic outcomes: a phthalate plasticizer, an antihistamine, a bile acid metabolite, tryptophan metabolites, a hemiterpenoid glycoside, triacylglycerols, hypoxanthine, and polyphenol syringic acid. The findings suggest that MNTs are aspirants for clinical trials to prevent adverse respiratory/allergic outcomes.

Gut microbiota derived bile acid metabolites maintain the homeostasis of gut and systemic immunity

Bile acids (BAs) as cholesterol-derived molecules play an essential role in some physiological processes such as nutrient absorption, glucose homeostasis and regulation of energy expenditure. They are synthesized in the liver as primary BAs such as cholic acid (CA), chenodeoxycholic acid (CDCA) and conjugated forms. A variety of secondary BAs such as deoxycholic acid (DCA) and lithocholic acid (LCA) and their derivatives is synthesized in the intestine through the involvement of various microorganisms. In addition to essential physiological functions, BAs and their metabolites are also involved in the differentiation and functions of innate and adaptive immune cells such as macrophages (Macs), dendritic cells (DCs), myeloid derived suppressive cells (MDSCs), regulatory T cells (Treg), Breg cells, T helper (Th)17 cells, CD4 Th1 and Th2 cells, CD8 cells, B cells and NKT cells. Dysregulation of the BAs and their metabolites also affects development of some diseases such as inflammatory bowel diseases. We here summarize recent advances in how BAs and their metabolites maintain gut and systemic homeostasis, including the metabolism of the BAs and their derivatives, the role of BAs and their metabolites in the differentiation and function of immune cells, and the effects of BAs and their metabolites on immune-associated disorders.

Serum metabolomic analyses reveal the potential metabolic biomarkers for prediction of amatoxin poisoning

Amatoxin poisoning leads to over 90% of deaths in mushroom poisoning. The objective of present study was to identify the potential metabolic biomarkers for early diagnosis of amatoxin poisoning. Serum samples were collected from 61 patients with amatoxin poisoning and 61 healthy controls. An untargeted metabolomics analysis was performed using the ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS/MS). Multivariate statistical analysis revealed that the patients with amatoxin poisoning could be clearly separated from healthy controls on the basis of their metabolic fingerprints. There were 33 differential metabolites including 15 metabolites up-regulated metabolites and 18 down-regulated metabolites in patients with amatoxin poisoning compared to healthy controls. These metabolites mainly enriched in the lipid metabolism and amino acid metabolism pathways, such as Glycerophospholipid metabolism, Sphingolipid metabolism, Phenylalanine tyrosine and typtophan biosynthesis, Tyrosine metabolism, Arginine and proline metabolism, which may serve important roles in the amatoxin poisoning. Among the differential metabolites, a total of 8 significant metabolic markers were identified for discriminating patients with amatoxin poisoning from healthy controls, including Glycochenodeoxycholate-3-sulfate (GCDCA-S), 11-Oxo-androsterone glucuronide, Neomenthol-glucuronide, Dehydroisoandrosterone 3-glucuronide, Glucose 6-phosphate (G6P), Lanthionine ketimine, Glycerophosphocholine (GPC) and Nicotinamide ribotide, which achieved satisfactory diagnostic accuracy (AUC>0.8) in both discovery and validation cohorts. Strikingly, the Pearson's correlation analysis indicated that 11-Oxo-androsterone glucuronide, G6P and GCDCA-S were positively correlated with the liver injury induced by amatoxin poisoning. The findings of the current study may provide insight into the pathological mechanism of amatoxin poisoning and screened out the reliable metabolic biomarkers to contribute the clinical early diagnosis of amatoxin poisoning.

Multi-omics profiling approach in food allergy

The prevalence of food allergy (FA) among children is increasing, affecting nearly 8% of children, and FA is the most common cause of anaphylaxis and anaphylaxis-related emergency department visits in children. Importantly, FA is a complex, multi-system, multifactorial disease mediated by food-specific immunoglobulin E (IgE) and type 2 immune responses and involving environmental and genetic factors and gene-environment interactions. Early exposure to external and internal environmental factors largely influences the development of immune responses to allergens. Genetic factors and gene-environment interactions have established roles in the FA pathophysiology. To improve diagnosis and identification of FA therapeutic targets, high-throughput omics approaches have emerged and been applied over the past decades to screen for potential FA biomarkers, such as genes, transcripts, proteins, and metabolites. In this article, we provide an overview of the current status of FA omics studies, namely genomic, transcriptomic, epigenomic, proteomic, exposomic, and metabolomic. The current development of multi-omics integration of FA studies is also briefly discussed. As individual omics technologies only provide limited information on the multi-system biological processes of FA, integration of population-based multi-omics data and clinical data may lead to robust biomarker discovery that could translate into advances in disease management and clinical care and ultimately lead to precision medicine approaches.

The combination of machine learning and untargeted metabolomics identifies the lipid metabolism -related gene CH25H as a potential biomarker in asthma

BACKGROUND

Lipids, significant signaling molecules, regulate a multitude of cellular responses and biological pathways in asthma which are closely associated with disease onset and progression. However, the characteristic lipid genes and metabolites in asthma remain to be explored. It is also necessary to further investigate the role of lipid molecules in asthma based on high-throughput data.

OBJECTIVE

To explore the biomarkers and molecular mechanisms associated with lipid metabolism in asthma.

METHODS

In this study, we selected three mouse-derived datasets and one human dataset (GSE41665, GSE41667, GSE3184 and GSE67472) from the GEO database. Five machine learning algorithms, LASSO, SVM-RFE, Boruta, XGBoost and RF, were used to identify core gene. Additionally, we used non-negative matrix breakdown (NMF) clustering to identify two lipid molecular subgroups and constructed a lipid metabolism score by principal component analysis (PCA) to differentiate the subtypes. Finally, Western blot confirmed the altered expression levels of core genes in OVA (ovalbumin) and HDM+LPS (house dust mite+lipopolysaccharide) stimulated and challenged BALB/c mice, respectively. Results of non-targeted metabolomics revealed multiple differentially expressed metabolites in the plasma of OVA-induced asthmatic mice.

RESULTS

Cholesterol 25-hydroxylase (CH25H) was finally localized as a core lipid metabolism gene in asthma and was verified to be highly expressed in two mouse models of asthma. Five-gene lipid metabolism constructed from CYP2E1, CH25H, PTGES, ALOX15 and ME1 was able to distinguish the subtypes effectively. The results of non-targeted metabolomics showed that most of the aberrantly expressed metabolites in the plasma of asthmatic mice were lipids, such as LPC 16:0, LPC 18:1 and LPA 18:1.

CONCLUSION

Our findings imply that the lipid-related gene CH25H may be a useful biomarker in the diagnosis of asthma.

Advances and potential of omics studies for understanding the development of food allergy

The prevalence of food allergy continues to rise globally, carrying with it substantial safety, economic, and emotional burdens. Although preventative strategies do exist, the heterogeneity of allergy trajectories and clinical phenotypes has made it difficult to identify patients who would benefit from these strategies. Therefore, further studies investigating the molecular mechanisms that differentiate these trajectories are needed. Large-scale omics studies have identified key insights into the molecular mechanisms for many different diseases, however the application of these technologies to uncover the drivers of food allergy development is in its infancy. Here we review the use of omics approaches in food allergy and highlight key gaps in knowledge for applying these technologies for the characterization of food allergy development.

Untargeted, High-Resolution Metabolomics in Pediatric Eosinophilic Esophagitis

BACKGROUND/OBJECTIVES

Eosinophilic esophagitis (EoE) is an inflammatory disease of unclear etiology. The aim of this study was to use untargeted plasma metabolomics to identify metabolic pathway alterations associated with EoE to better understand the pathophysiology.

METHODS

This prospective, case-control study included 72 children, aged 1-17 years, undergoing clinically indicated upper endoscopy (14 diagnosed with EoE and 58 controls). Fasting plasma samples were analyzed for metabolomics by high-resolution dual-chromatography mass spectrometry. Analysis was performed on sex-matched groups at a 2:1 ratio. Significant differences among the plasma metabolite features between children with and without EoE were determined using multivariate regression analysis and were annotated with a network-based algorithm. Subsequent pathway enrichment analysis was performed.

RESULTS

Patients with EoE had a higher proportion of atopic disease (85.7% vs 50%, P = 0.019) and any allergies (100% vs 57.1%, P = 0.0005). Analysis of the dual chromatography features resulted in a total of 918 metabolites that differentiated EoE and controls. Glycerophospholipid metabolism was significantly enriched with the greatest number of differentiating metabolites and overall pathway enrichment ( P < 0.01). Multiple amino and fatty acid pathways including linoleic acid were also enriched, as well as pyridoxine metabolism ( P < 0.01).

CONCLUSIONS

In this pilot study, we found differences in metabolites involved in glycerophospholipid and inflammation pathways in pediatric patients with EoE using untargeted metabolomics, as well as overlap with amino acid metabolome alterations found in atopic disease.

Metabolomics of asthma, COPD, and asthma-COPD overlap: an overview

The two common progressive lung diseases, asthma and chronic obstructive pulmonary disease (COPD), are the leading causes of morbidity and mortality worldwide. Asthma-COPD overlap, referred to as ACO, is another complex pulmonary disease that manifests itself with features of both asthma and COPD. The disease has no clear diagnostic or therapeutic guidelines, thereby making both diagnosis and treatment challenging. Though a number of studies on ACO have been documented, gaps in knowledge regarding the pathophysiologic mechanism of this disorder exist. Addressing this issue is an urgent need for improved diagnostic and therapeutic management of the disease. Metabolomics, an increasingly popular technique, reveals the pathogenesis of complex diseases and holds promise in biomarker discovery. This comprehensive narrative review, comprising 99 original research articles in the last five years (2017-2022), summarizes the scientific advances in terms of metabolic alterations in patients with asthma, COPD, and ACO. The analytical tools, nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS), commonly used to study the expression of the metabolome, are discussed. Challenges frequently encountered during metabolite identification and quality assessment are highlighted. Bridging the gap between phenotype and metabotype is envisioned in the future.

Early-life fecal metabolomics of food allergy

BACKGROUND

Intestinal microenvironmental perturbations may increase food allergy risk. We hypothesize that children with clinical food allergy, those with food sensitization, and healthy children can be differentiated by intestinal metabolites in the first years of life.

METHODS

In this ancillary analysis of the Vitamin D Antenatal Asthma Reduction Trial (VDAART), we performed untargeted metabolomic profiling in 824 stool samples collected at ages 3-6 months, 1 year and 3 years. Subjects included 23 with clinical food allergy at age 3 and/or 6 years, 151 with food sensitization but no clinical food allergy, and 220 controls. We identified modules of correlated, functionally related metabolites and sought associations of metabolite modules and individual metabolites with food allergy/sensitization using regression models.

RESULTS

Several modules of functionally related intestinal metabolites were reduced among subjects with food allergy, including bile acids at ages 3-6 months and 1 year, amino acids at age 3-6 months, steroid hormones at 1 year, and sphingolipids at age 3 years. One module primarily containing diacylglycerols was increased in those with food allergy at age 3-6 months. Fecal caffeine metabolites at age 3-6 months, likely derived from breast milk, were increased in those with food allergy and/or sensitization (beta = 5.9, 95% CI 1.0-10.8, p = .02) and were inversely correlated with fecal bile acids and bilirubin metabolites, though maternal plasma caffeine levels were not associated with food allergy and/or sensitization.

CONCLUSIONS

Several classes of bioactive fecal metabolites are associated with food allergy and/or sensitization including bile acids, steroid hormones, sphingolipids, and caffeine metabolites.

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

Microbiome Therapeutics for Food Allergy

The prevalence of food allergies continues to rise, and with limited existing therapeutic options there is a growing need for new and innovative treatments. Food allergies are, in a large part, related to environmental influences on immune tolerance in early life, and represent a significant therapeutic challenge. An expanding body of evidence on molecular mechanisms in murine models and microbiome associations in humans have highlighted the critical role of gut dysbiosis in the pathogenesis of food allergies. As such, the gut microbiome is a rational target for novel strategies aimed at preventing and treating food allergies, and new methods of modifying the gastrointestinal microbiome to combat immune dysregulation represent promising avenues for translation to future clinical practice. In this review, we discuss the intersection between the gut microbiome and the development of food allergies, with particular focus on microbiome therapeutic strategies. These emerging microbiome approaches to food allergies are subject to continued investigation and include dietary interventions, pre- and probiotics, microbiota metabolism-based interventions, and targeted live biotherapeutics. This exciting frontier may reveal disease-modifying food allergy treatments, and deserves careful study through ongoing clinical trials.

Immunomodulation by foods and microbes: Unravelling the molecular tango

Metabolic health and immune function are intimately connected via diet and the microbiota. Nearly 90% of all immune cells in the body are associated with the gastrointestinal tract and these immune cells are continuously exposed to a wide range of microbes and microbial-derived compounds, with important systemic ramifications. Microbial dysbiosis has consistently been observed in patients with atopic dermatitis, food allergy and asthma and the molecular mechanisms linking changes in microbial populations with disease risk and disease endotypes are being intensively investigated. The discovery of novel bacterial metabolites that impact immune function is at the forefront of host-microbe research. Co-evolution of microbial communities within their hosts has resulted in intertwined metabolic pathways that affect physiological and pathological processes. However, recent dietary and lifestyle changes are thought to negatively influence interactions between microbes and their host. This review provides an overview of some of the critical metabolite-receptor interactions that have been recently described, which may underpin the immunomodulatory effects of the microbiota, and are of relevance for allergy, asthma and infectious diseases.

Study on potential markers for diagnosis of renal cell carcinoma by serum untargeted metabolomics based on UPLC-MS/MS

Objective: Renal cell carcinoma (RCC) is the most common malignancy of the kidney. However, there is no reliable biomarker with high sensitivity and specificity for diagnosis and differential diagnosis. This study aims to analyze serum metabolite profile of patients with RCC and screen for potential diagnostic biomarkers. Methods: Forty-five healthy controls (HC), 40 patients with benign kidney tumor (BKT) and 46 patients with RCC were enrolled in this study. Serum metabolites were detected by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and then subjected to multivariate statistical analysis, metabolic pathway analysis and diagnostic performance evaluation. Results: The changes of glycerophospholipid metabolism, phosphatidylinositol signaling system, glycerolipid metabolism, d-glutamine and d-glutamate metabolism, galactose metabolism, and folate biosynthesis were observed in RCC group. Two hundred and forty differential metabolites were screened between RCC and HC groups, and 64 differential metabolites were screened between RCC and BKT groups. Among them, 4 differential metabolites, including 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, lysophosphatidylcholine (LPC) 19:2, and γ-Aminobutyryl-lysine (an amino acid metabolite), were of high clinical value not only in the diagnosis of RCC (RCC group vs. HC group; AUC = 0.990, 0.916, 0.909, and 0.962; Sensitivity = 97.73%, 97.73%, 93.18%, and 86.36%; Specificity = 100.00%, 73.33%, 80.00%, and 95.56%), but also in the differential diagnosis of benign and malignant kidney tumors (RCC group vs. BKT group; AUC = 0.989, 0.941, 0.845 and 0.981; Sensitivity = 93.33%, 93.33%, 77.27% and 93.33%; Specificity = 100.00%, 84.21%, 78.38% and 92.11%). Conclusion: The occurrence of RCC may involve changes in multiple metabolic pathways. The 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, LPC 19:2 and γ-Aminobutyryl-lysine may be potential biomarkers for the diagnosis or differential diagnosis of RCC.

Urine metabolomics and microbiome analyses reveal the mechanism of anti-tuberculosis drug-induced liver injury, as assessed for causality using the updated RUCAM: A prospective study

Background

Anti-tuberculosis drug-induced liver injury (ATB-DILI) is one of the most common adverse reactions that brings great difficulties to the treatment of tuberculosis. Thus, early identification of individuals at risk for ATB-DILI is urgent. We conducted a prospective cohort study to analyze the urinary metabolic and microbial profiles of patients with ATB-DILI before drug administration. And machine learning method was used to perform prediction model for ATB-DILI based on metabolomics, microbiome and clinical data.

Methods

A total of 74 new TB patients treated with standard first-line anti-TB treatment regimens were enrolled from West China Hospital of Sichuan University. Only patients with an updated RUCAM score of 6 or more were accepted in this study. Nontargeted metabolomics and microbiome analyses were performed on urine samples prior to anti-tuberculosis drug ingestion to screen the differential metabolites and microbes between the ATB-DILI group and the non-ATB-DILI group. Integrating electronic medical records, metabolomics, and microbiome data, four machine learning methods was used, including random forest algorithm, artificial neural network, support vector machine with the linear kernel and radial basis function kernel.

Results

Of all included patients, 69 patients completed follow-up, with 16 (23.19%) patients developing ATB-DILI after antituberculosis treatment. Finally, 14 ATB-DILI patients and 30 age- and sex-matched non-ATB-DILI patients were subjected to urinary metabolomic and microbiome analysis. A total of 28 major differential metabolites were screened out, involving bile secretion, nicotinate and nicotinamide metabolism, tryptophan metabolism, ABC transporters, etc. Negativicoccus and Actinotignum were upregulated in the ATB-DILI group. Multivariate analysis also showed significant metabolic and microbial differences between the non-ATB-DILI and severe ATB-DILI groups. Finally, the four models showed high accuracy in predicting ATB-DILI, with the area under the curve of more than 0.85 for the training set and 1 for the validation set.

Conclusion

This study characterized the metabolic and microbial profile of ATB-DILI risk individuals before drug ingestion for the first time. Metabolomic and microbiome characteristics in patient urine before anti-tuberculosis drug ingestion may predict the risk of liver injury after ingesting anti-tuberculosis drugs. Machine learning algorithms provides a new way to predict the occurrence of ATB-DILI among tuberculosis patients.

Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury

Background: Anti-tuberculosis drug-induced liver injury (ATB-DILI) is an adverse reaction with a high incidence and the greatest impact on tuberculosis treatment. However, there is a lack of effective biomarkers for the early prediction of ATB-DILI. Herein, this study uses UPLC‒MS/MS to reveal the plasma metabolic profile and lipid profile of ATB-DILI patients before drug administration and screen new biomarkers for predicting ATB-DILI. Methods: A total of 60 TB patients were enrolled, and plasma was collected before antituberculosis drug administration. The untargeted metabolomics and lipidomics analyses were performed using UPLC‒MS/MS, and the high-resolution mass spectrometer Q Exactive was used for data acquisition in both positive and negative ion modes. The random forest package of R software was used for data screening and model building. Results: A total of 60 TB patients, including 30 ATB-DILI patients and 30 non-ATB-DILI subjects, were enrolled. There were no significant differences between the ATB-DILI and control groups in age, sex, smoking, drinking or body mass index (p > 0.05). Twenty-two differential metabolites were selected. According to KEGG pathway analysis, 9 significantly enriched metabolic pathways were found, and both drug metabolism-other enzymes and niacin and nicotinamide metabolic pathways were found in both positive and negative ion models. A total of 7 differential lipid molecules were identified between the two groups. Ferroptosis and biosynthesis of unsaturated fatty acids were involved in the occurrence of ATB-DILI. Random forest analysis showed that the model built with the top 30 important variables had an area under the ROC curve of 0.79 (0.65-0.93) for the training set and 0.79 (0.55-1.00) for the validation set. Conclusion: This study demonstrated that potential markers for the early prediction of ATB-DILI can be found through plasma metabolomics and lipidomics. The random forest model showed good clinical predictive value for ATB-DILI.

Food allergy, mechanisms, diagnosis and treatment: Innovation through a multi-targeted approach

The incidence of food allergy (FA) has continued to rise over the last several decades, posing significant burdens on health and quality of life. Significant strides into the advancement of FA diagnosis, prevention, and treatment have been made in recent years. In an effort to lower reliance on resource-intensive food challenges, the field has continued work toward the development of highly sensitive and specific assays capable of high-throughput analysis to assist in the diagnosis FA. In looking toward early infancy as a critical period in the development of allergy or acquisition of tolerance, evidence has increasingly suggested that early intervention via the early introduction of food allergens and maintenance of skin barrier function may decrease the risk of FA. As such, large-scale investigations are underway evaluating infant feeding and the impact of emollient and steroid use in infants with dry skin for the prevention of allergy. On the other end of the spectrum, the past few years have been witness to an explosive increase in clinical trials of novel and innovative therapeutic strategies aimed at the treatment of FA in those whom the disease has already manifested. A milestone in the field, 2020 marked the approval of the first drug, oral peanut allergen, for the indication of peanut allergy. With a foundation of promising data supporting the safety and efficacy of single- and multi-allergen oral immunotherapy, current efforts have turned toward the use of probiotics, biologic agents, and modified allergens to optimize and improve upon existing paradigms. Through these advancements, the field hopes to gain footing in the ongoing battle against FA.

Omics technologies in allergy and asthma research: An EAACI position paper

Allergic diseases and asthma are heterogenous chronic inflammatory conditions with several distinct complex endotypes. Both environmental and genetic factors can influence the development and progression of allergy. Complex pathogenetic pathways observed in allergic disorders present a challenge in patient management and successful targeted treatment strategies. The increasing availability of high-throughput omics technologies, such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics allows studying biochemical systems and pathophysiological processes underlying allergic responses. Additionally, omics techniques present clinical applicability by functional identification and validation of biomarkers. Therefore, finding molecules or patterns characteristic for distinct immune-inflammatory endotypes, can subsequently influence its development, progression, and treatment. There is a great potential to further increase the effectiveness of single omics approaches by integrating them with other omics, and nonomics data. Systems biology aims to simultaneously and longitudinally understand multiple layers of a complex and multifactorial disease, such as allergy, or asthma by integrating several, separated data sets and generating a complete molecular profile of the condition. With the use of sophisticated biostatistics and machine learning techniques, these approaches provide in-depth insight into individual biological systems and will allow efficient and customized healthcare approaches, called precision medicine. In this EAACI Position Paper, the Task Force "Omics technologies in allergic research" broadly reviewed current advances and applicability of omics techniques in allergic diseases and asthma research, with a focus on methodology and data analysis, aiming to provide researchers (basic and clinical) with a desk reference in the field. The potential of omics strategies in understanding disease pathophysiology and key tools to reach unmet needs in allergy precision medicine, such as successful patients' stratification, accurate disease prognosis, and prediction of treatment efficacy and successful prevention measures are highlighted.

Biomarkers in oral immunotherapy

Food allergy (FA) is a global health problem that affects a large population, and thus effective treatment is highly desirable. Oral immunotherapy (OIT) has been showing reasonable efficacy and favorable safety in most FA subjects. Dependable biomarkers are needed for treatment assessment and outcome prediction during OIT. Several immunological indicators have been used as biomarkers in OIT, such as skin prick tests, basophil and mast cell reactivity, T cell and B cell responses, allergen-specific antibody levels, and cytokines. Other novel indicators also could be potential biomarkers. In this review, we discuss and assess the application of various immunological indicators as biomarkers for OIT.

Research Progress on the Correlation between the Intestinal Microbiota and Food Allergy

The increasing incidence of food allergy is becoming a substantial public health concern. Increasing evidence suggests that alterations in the composition of the intestinal microbiota play a part in the development of food allergy. Additionally, the application of probiotics to correct gut microbiota imbalances and regulate food allergy has become a research hotspot. However, the mechanism by which the gut microbiota regulates food allergy and the efficacy of probiotics are still in the preliminary exploration stage, and there are no clear and specific conclusions. The aim of this review is to provide information regarding the immune mechanism underlying food allergy, the correlation between the intestinal microbiota and food allergy, a detailed description of causation, and mechanisms by which the intestinal microbiota regulates food allergy. Subsequently, we highlight how probiotics modulate the gut microbiome–immune axis to alleviate food allergy. This study will contribute to the dovetailing of bacterial therapeutics with immune system in allergic individuals to prevent food allergy and ameliorate food allergy symptoms.

Limosilactobacillus reuteri Attenuates Atopic Dermatitis via Changes in Gut Bacteria and Indole Derivatives from Tryptophan Metabolism

Gut bacteria are closely associated with the development of atopic dermatitis (AD) due to their immunoregulatory function. Indole derivatives, produced by gut bacteria metabolizing tryptophan, are ligands to activate the aryl hydrocarbon receptor (AHR), which plays a critical role in attenuating AD symptoms. Limosilactobacillus reuteri, a producer of indole derivatives, regulates mucosal immunity via activating the AHR signaling pathway. However, the effective substance and mechanism of L. reuteri in the amelioration of AD remain to be elucidated. In this research, we found that L. reuteri DYNDL22M62 significantly improved AD-like symptoms in mice by suppressing IgE levels and the expressions of thymic stromal lymphopoietin (TSLP), IL-4, and IL-5. L. reuteri DYNDL22M62 induced an increase in the production of indole lactic acid (ILA) and indole propionic acid (IPA) via targeted tryptophan metabolic analysis and the expression of AHR in mice. Furthermore, L. reuteri DYNDL22M62 increased the proportions of Romboutsia and Ruminococcaceae NK4A214 group, which were positively related to ILA, but decreased Dubosiella, which was negatively related to IPA. Collectively, L. reuteri DYNDL22M62 with the role of modulating gut bacteria and the production of indole derivatives may attenuate AD via activating AHR in mice.

Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles

Asthma is ranked among the most common chronic conditions and has become a significant public health issue due to the recent and rapid increase in its prevalence. Investigations into the underlying genetic factors predict a heritable component for its incidence, estimated between 35% and 90% of causation. Despite the application of large-scale genome-wide association studies (GWAS) and admixture mapping approaches, the proportion of variants identified accounts for less than 15% of the observed heritability of the disease. The discrepancy between the predicted heritable component of disease and the proportion of heritability mapped to the currently identified susceptibility loci has been termed the ‘missing heritability problem.’ Here, we examine recent studies involving both the analysis of genetically encoded features that contribute to asthma and also the role of non-encoded heritable characteristics, including epigenetic, environmental, and developmental aspects of disease. The importance of vertical maternal microbiome transfer and the influence of maternal immune factors on fetal conditioning in the inheritance of disease are also discussed. In order to highlight the broad array of biological inputs that contribute to the sum of heritable risk factors associated with allergic disease incidence that, together, contribute to the induction of a pro-atopic state. Currently, there is a need to develop in-depth models of asthma risk factors to overcome the limitations encountered in the interpretation of GWAS results in isolation, which have resulted in the missing heritability problem. Hence, multiomics analyses need to be established considering genetic, epigenetic, and functional data to create a true systems biology-based approach for analyzing the regulatory pathways that underlie the inheritance of asthma and to develop accurate risk profiles for disease.

Metabolomics in asthma: A platform for discovery

Asthma, characterized by airway hyperresponsiveness, inflammation and remodeling, is a chronic airway disease with complex etiology. Severe asthma is characterized by frequent exacerbations and poor therapeutic response to conventional asthma therapy. A clear understanding of cellular and molecular mechanisms of asthma is critical for the discovery of novel targets for optimal therapeutic control of asthma. Metabolomics is emerging as a powerful tool to elucidate novel disease mechanisms in a variety of diseases. In this review, we summarize the current status of knowledge in asthma metabolomics at systemic and cellular levels. The findings demonstrate that various metabolic pathways, related to energy metabolism, macromolecular biosynthesis and redox signaling, are differentially modulated in asthma. Airway smooth muscle cell plays pivotal roles in asthma by contributing to airway hyperreactivity, inflammatory mediator release and remodeling. We posit that metabolomic profiling of airway structural cells, including airway smooth muscle cells, will shed light on molecular mechanisms of asthma and airway hyperresponsiveness and help identify novel therapeutic targets.

Understanding uncontrolled severe allergic asthma by integration of omic and clinical data

BACKGROUND

Asthma is a complex, multifactorial disease often linked with sensitization to house dust mites (HDM). There is a subset of patients that does not respond to available treatments, who present a higher number of exacerbations and a worse quality of life. To understand the mechanisms of poor asthma control and disease severity, we aim to elucidate the metabolic and immunologic routes underlying this specific phenotype and the associated clinical features.

METHODS

Eighty-seven patients with a clinical history of asthma were recruited and stratified in 4 groups according to their response to treatment: corticosteroid-controlled (ICS), immunotherapy-controlled (IT), biologicals-controlled (BIO) or uncontrolled (UC). Serum samples were analysed by metabolomics and proteomics; and classifiers were built using machine-learning algorithms.

RESULTS

Metabolomic analysis showed that ICS and UC groups cluster separately from one another and display the highest number of significantly different metabolites among all comparisons. Metabolite identification and pathway enrichment analysis highlighted increased levels of lysophospholipids related to inflammatory pathways in the UC patients. Likewise, 8 proteins were either upregulated (CCL13, ARG1, IL15 and TNFRSF12A) or downregulated (sCD4, CCL19 and IFNγ) in UC patients compared to ICS, suggesting a significant activation of T cells in these patients. Finally, the machine-learning model built including metabolomic and clinical data was able to classify the patients with an 87.5% accuracy.

CONCLUSIONS

UC patients display a unique fingerprint characterized by inflammatory-related metabolites and proteins, suggesting a pro-inflammatory environment. Moreover, the integration of clinical and experimental data led to a deeper understanding of the mechanisms underlying UC phenotype.

IgE-Mediated food allergy: Current diagnostic modalities and novel biomarkers with robust potential

Food allergy (FA) is a serious public health issue afflicting millions of people globally, with an estimated prevalence ranging from 1-10%. Management of FA is challenging due to overly restrictive diets and the lack of diagnostic approaches with high accuracy and prediction. Although measurement of serum-specific antibodies combined with patient medical history and skin prick test is a useful diagnostic tool, it is still an imprecise predictor of clinical reactivity with a high false-positive rate. The double-blind placebo-controlled food challenge represents the gold standard for FA diagnosis; however, it requires large healthcare and involves the risk of acute onset of allergic reactions. Improvement in our understanding of the molecular mechanism underlying allergic disease pathology, development of omics-based methods, and advances in bioinformatics have boosted the generation of a number of robust diagnostic biomarkers of FA. In this review, we discuss how traditional diagnostic modalities guide appropriate diagnosis and management of FA in clinical practice, as well as uncover the potential of the latest biomarkers for the diagnosis, monitoring, and prediction of FA. We also raise perspectives for precise and targeted medical intervention to fill the gap in the diagnosis of FA.

Lipid Ligands and Allergenic LTPs: Redefining the Paradigm of the Protein-Centered Vision in Allergy

Lipid Transfer Proteins (LTPs) have been described as one of the most prevalent and cross-reactive allergen families in the general population. They are widely distributed among the plant kingdom, as well as in different plant organs ranging from pollen to fruits. Thus, they can initiate allergic reactions with very different outcomes, such as asthma and food allergy. Several mouse models have been developed to unravel the mechanisms that lead LTPs to promote such strong sensitization patterns. Interestingly, the union of certain ligands can strengthen the allergenic capacity of LTPs, suggesting that not only is the protein relevant in the sensitization process, but also the ligands that LTPs carry in their cavity. In fact, different LTPs with pro-allergenic capacity have been shown to transport similar ligands, thus positioning lipids in a central role during the first stages of the allergic response. Here, we offer the latest advances in the use of experimental animals to study the topic, remarking differences among them and providing future researchers a tool to choose the most suitable model to achieve their goals. Also, recent results derived from metabolomic studies in humans are included, highlighting how allergic diseases alter the lipidic metabolism toward a pathogenic state in the individual. Altogether, this review offers a comprehensive body of work that sums up the background evidence supporting the role of lipids as modulators of allergic diseases. Studying the role of lipids during allergic sensitization might broaden our understanding of the molecular events leading to tolerance breakdown in the epithelium, thus helping us to understand how allergy is initiated and established in the individuals.

Association Between Breastmilk Microbiota and Food Allergy in Infants

Regulating the composition of human breastmilk has the potential to prevent allergic diseases early in life. The composition of breastmilk is complex, comprising varying levels of oligosaccharides, immunoactive molecules, vitamins, metabolites, and microbes. Although several studies have examined the relationship between different components of breastmilk and infant food allergies, few have investigated the relationship between microorganisms in breastmilk and infant food allergy. In the present study, we selected 135 healthy pregnant women and their full-term newborns from a cohort of 202 mother-infant pairs. Among them, 69 infants were exclusively breastfed until 6 mo after birth. At follow-up, 11 of the 69 infants developed a food allergy in infancy while 22 showed no signs of allergy. Thirty-three breastmilk samples were collected within 1 mo after delivery, and 123 infant fecal samples were collected at five time points following their birth. These samples were analyzed using microbial 16S rRNA gene sequencing. The abundance and evenness of the milk microbiota and the number of differential bacteria were higher in the breastmilk samples from the non-allergy group than in those from the food allergy group. The non-allergy group showed relatively high abundance of Bifidobacterium, Akkermansia, Clostridium IV, Clostridium XIVa, Veillonella, and butyrate-producing bacteria such as Fusobacterium, Lachnospiraceae incertae sedis, Roseburia, and Ruminococcus. In contrast, the abundance of Proteobacteria, Acinetobacter, and Pseudomonas in breastmilk was higher in the food allergy group. A comparison of the changes in dominant differential breastmilk microbiota in the intestinal flora of the two groups of infants over time revealed that the changes in Bifidobacterium abundance were consistent with those in the breastmilk flora. Functional pathway prediction of breastmilk microflora showed that the enhancement of the metabolic pathways of tyrosine, tryptophan, and fatty acids was significantly different between the groups. We suggest that changes in the breastmilk microbiota can influence the development of food allergies. Breastmilk contains several microbes that have protective effects against food allergies, both by influencing the colonization of intestinal microbiota and by producing butyrate. This study may provide new ideas for improving infant health through early intervention with probiotics.

Gut Microbiome and Metabolomics Profiles of Allergic and Non-Allergic Childhood Asthma

Purpose

This study aimed to investigate the characteristics of gut bacteria and the derived metabolites among allergic asthmatic children, non-allergic asthmatic children and healthy children without asthma.

Methods

Fecal samples were collected from 57 participants, including 20 healthy children, 27 allergic asthmatic children, and 10 non-allergic asthmatic children. 16S rRNA gene sequencing was conducted for analyzing gut bacterial compositions and untargeted metabolomics was used to analyze the alterations of gut microbe-derived metabolites. The associations between gut bacterial compositions and metabolites were analyzed by the method of Spearman correlation.

Results

The results showed that the compositions and metabolites of gut microbiome were altered both in allergic and non-allergic asthmatics compared with healthy controls. Chao1 (p = 0.025) index reflected a higher bacterial richness and Simpson (p = 0.024) index showed a lower diversity in asthma group. PERMANOVA analysis showed significant differences among the three groups based on unweighted UniFrac distance (p = 0.001). Both allergic and non-allergic asthmatics showed a higher relative abundance of Proteobacteria and a lower relative abundance of genera from Clostridia. More bacteria were altered in non-allergic asthmatics compared with allergic asthmatics. Metabolomics analysis identified that 42 metabolites were significantly associated with allergic asthma, and 58 metabolites were significantly associated with non-allergic asthma (multiple linear regression, p < 0.05). Histamine was 4 folds up-regulated only in the non-allergic asthma group. The relative abundance of Candidatus Accumulib was significantly correlated with the upregulation of histamine. The relative abundance of genera from Clostridia was significantly correlated with the downregulation of lipid and tryptophan metabolism.

Conclusion

The altered gut microbes was associated with the mechanism of asthma attack through metabolites in allergic and non-allergic asthma group, respectively. The result suggested that gut microbiome had an impact on the development of both allergic and non-allergic asthma. The distinct gut microbiome and microbiome-derived metabolites in non-allergic asthma children suggested that gut microbiome might play a critical role in modulation of asthma phenotype.

Untargeted Metabolomic Profiling Reveals Changes in Gut Microbiota and Mechanisms of Its Regulation of Allergy in OVA-Sensitive BALB/c Mice

Gut microbiota plays an important role in the regulation of food allergy. However, the interactions between the gut flora and immune system are not well studied. Here, we obtained ovalbumin (OVA)-sensitive BALB/c mice, combined with serum untargeted metabolomics to investigate the mechanisms of the interactions. The serum metabolomics results showed that 17 serum metabolites were downregulated, enriched in the aminoacyl-tRNA biosynthesis pathway, whereas indole-3-propionic acid (IPA) was increased. Six operational taxonomic units (OTUs) at the family level were altered and correlated with immune endpoints. Combined metabolomic and microbiomic analyses revealed that IPA levels were correlated with differential bacterial OTUs and a positive correlation with Treg in splenic lymphocytes. These results suggest that the regulatory effects of intestinal flora on allergic responses may be achieved by metabolizing tryptophan to produce indole derivatives and the aminoacyl-tRNA biosynthesis pathway. The formation of OVA tolerance in mice may be related to the enrichment of Peptostreptococcaceae, Ruminococcaceae, and Lactobacillaceae.

Airway Microbiome and Serum Metabolomics Analysis Identify Differential Candidate Biomarkers in Allergic Rhinitis

Allergic rhinitis (AR) is a common heterogeneous chronic disease with a high prevalence and a complex pathogenesis influenced by numerous factors, involving a combination of genetic and environmental factors. To gain insight into the pathogenesis of AR and to identity diagnostic biomarkers, we combined systems biology approach to analyze microbiome and serum composition. We collected inferior turbinate swabs and serum samples to study the microbiome and serum metabolome of 28 patients with allergic rhinitis and 15 healthy individuals. We sequenced the V3 and V4 regions of the 16S rDNA gene from the upper respiratory samples. Metabolomics was used to examine serum samples. Finally, we combined differential microbiota and differential metabolites to find potential biomarkers. We found no significant differences in diversity between the disease and control groups, but changes in the structure of the microbiota. Compared to the HC group, the AR group showed a significantly higher abundance of 1 phylum (Actinobacteria) and 7 genera (Klebsiella, Prevotella and Staphylococcus, etc.) and a significantly lower abundance of 1 genus (Pelomonas). Serum metabolomics revealed 26 different metabolites (Prostaglandin D2, 20-Hydroxy-leukotriene B4 and Linoleic acid, etc.) and 16 disrupted metabolic pathways (Linoleic acid metabolism, Arachidonic acid metabolism and Tryptophan metabolism, etc.). The combined respiratory microbiome and serum metabolomics datasets showed a degree of correlation reflecting the influence of the microbiome on metabolic activity. Our results show that microbiome and metabolomics analyses provide important candidate biomarkers, and in particular, differential genera in the microbiome have also been validated by random forest prediction models. Differential microbes and differential metabolites have the potential to be used as biomarkers for the diagnosis of allergic rhinitis.

Fetal lipidome and incident risk of food allergy: A prospective birth cohort study

BACKGROUND

Lipids are proposed to be important in developing adaptive immunity and allergy. However, studies to date reported inconsistent findings.

OBJECTIVE

To examine newborn lipidome (a comprehensive profiling of circulating lipid metabolites) on child's risk of developing food allergy (FA). The maternal-cord joint effects of lipid metabolites on FA development were also investigated.

METHODS

This study included 647 mother-child pairs from the Boston Birth Cohort and analyzed 202 lipid metabolites in cord plasma profiled by liquid chromatography tandem mass spectrometry. FA was defined based on standard clinical criteria. Logistic regression was applied to examine the relationships between individual metabolites and risk of FA.

RESULTS

Of the 647 children, 61 developed FA. Cord triacylglycerols of long carbon chains and multiple double bonds were significantly associated with decreased risk of FA. These associations were comparable across strata of pertinent maternal and child covariates, and were independent of maternal triacylglycerols when assessed simultaneously. Besides, cord and maternal triacylglycerols had an additive effect in association with risk of FA: Children having high (≥Median) C56:8 triacylglycerol levels in both cord and maternal plasma were at the lowest risk of developing FA (OR = 0.24, 95% CI = 0.10-0.56, p = .001), compared to those having low levels in both cord and maternal plasma.

CONCLUSION

This is the first birth cohort study to link altered cord plasma lipidome with future risk of development FA during childhood. It calls for further investigation on triacylglycerols of long carbon chains and multiple double bonds as potential novel predictive biomarkers and therapeutic targets for FA.

Mucosal Mast Cells as Key Effector Cells in Food Allergies

Mucosal mast cells (MMCs) localized in the intestinal mucosa play a key role in the development of IgE-mediated food allergies. Recent advances have revealed that MMCs are a distinctly different population from connective tissue mast cells localized in skin and other connective tissues. MMCs are inducible and transient cells that arise from bone marrow-derived mast cell progenitors, and their numbers increase rapidly during mucosal allergic inflammation. However, the mechanism of the dramatic expansion of MMCs and their cell functions are not well understood. Here, we review recent findings on the mechanisms of MMC differentiation and expansion, and we discuss the potential for the inducers of differentiation and expansion to serve as targets for food allergy therapy. In addition, we also discuss the mechanism by which oral immunotherapy, a promising treatment for food allergy patients, induces unresponsiveness to food allergens and the roles of MMCs in this process. Research focusing on MMCs should provide useful information for understanding the underlying mechanisms of food allergies in order to further advance the treatment of food allergies.

FLEXiGUT: Rationale for exposomics associations with chronic low-grade gut inflammation

FLEXiGUT is the first large-scale exposomics study focused on chronic low-grade inflammation. It aims to characterize human life course environmental exposure to assess and validate its impact on gut inflammation and related biological processes and diseases. The cumulative influences of environmental and food contaminants throughout the lifespan on certain biological responses related to chronic gut inflammation will be investigated in two Flemish prospective cohorts, namely the "ENVIRONAGE birth cohort", which provides follow-up from gestation to early childhood, and the "Flemish Gut Flora Project longitudinal cohort", a cohort of adults. The exposome will be characterised through biomonitoring of legacy and emerging contaminants, mycotoxins and markers of air pollution, by analysing the available metadata on nutrition, location and activity, and by applying state-of-the-art -omics techniques, including metagenomics, metabolomics and DNA adductomics, as well as the assessment of telomere length and measurement of inflammatory markers, to encompass both exposure and effect. Associations between exposures and health outcomes will be uncovered using an integrated -omics data analysis framework comprising data exploration, pre-processing, dimensionality reduction and data mining, combined with machine learning-based pathway analysis approaches. This is expected to lead to a more profound insight in mechanisms underlying disease progression (e.g. metabolic disorders, food allergies, gastrointestinal cancers) and/or accelerated biological ageing.

Metabolomic profiling revealed altered lipid metabolite levels in childhood food allergy

BACKGROUND

The pathophysiology of childhood food allergy (FA) and its natural history are poorly understood. Clarification of the underlying mechanism may help identify novel biomarkers and strategies for clinical intervention in children with FA.

OBJECTIVE

This study aimed to identify metabolites associated with the development and resolution of FA.

METHODS

The metabolomic profiles of 20 children with FA and 20 healthy controls were assessed by liquid chromatography-tandem mass spectrometry. Comparative analysis was performed to identify metabolites associated with FA and FA resolution. For subjects with FA, serum samples were collected at the time of diagnosis and after resolution to identify the changes in metabolite levels. The selected metabolites were then quantified in a quantification cohort to validate the results. Finally, genome-wide association analysis of the metabolite levels was performed.

RESULTS

The study demonstrated a significantly higher level of sphingolipid metabolites and a lower level of acylcarnitine metabolites in children with FA than those in healthy controls. At diagnosis, subjects with resolving FA had a significantly high level of omega-3 metabolites and a low level of platelet-activating factors compared to persistent FA. However, the level of omega-3 metabolites decreased in children with resolving FA but increased in children with persistent FA during the same time. The quantification data of omega-3-derived resolvins, platelet-activating factor, and platelet-activating factor acetylhydrolase activity further supported these results.

CONCLUSION

The lipid metabolite profile is closely related to childhood FA and FA resolution. This study suggests potential predictive biomarkers and provides insight into the mechanisms underlying childhood FA.

Adjunctive Probiotics Alleviates Asthmatic Symptoms via Modulating the Gut Microbiome and Serum Metabolome

Asthma is a multifactorial disorder, and microbial dysbiosis enhances lung inflammation and asthma-related symptoms. Probiotics have shown anti-inflammatory effects and could regulate the gut-lung axis. Thus, a 3-month randomized, double-blind, and placebo-controlled human trial was performed to investigate the adjunctive efficacy of probiotics in managing asthma. Fifty-five asthmatic patients were randomly assigned to a probiotic group (n = 29; received Bifidobacterium lactis Probio-M8 powder and Symbicort Turbuhaler) and a placebo group (n = 26; received placebo and Symbicort Turbuhaler), and all 55 subjects provided details of their clinical history and demographic data. However, only 31 patients donated a complete set of fecal and blood samples at all three time points for further analysis. Compared with those of the placebo group, co-administering Probio-M8 with Symbicort Turbuhaler significantly decreased the fractional exhaled nitric oxide level at day 30 (P = 0.049) and improved the asthma control test score at the end of the intervention (P = 0.023). More importantly, the level of alveolar nitric oxide concentration decreased significantly among the probiotic receivers at day 30 (P = 0.038), and the symptom relief effect was even more obvious at day 90 (P = 0.001). Probiotic co-administration increased the resilience of the gut microbiome, which was reflected by only minor fluctuations in the gut microbiome diversity (P > 0.05, probiotic receivers; P < 0.05, placebo receivers). Additionally, the probiotic receivers showed significantly changes in some species-level genome bins (SGBs), namely, increases in potentially beneficial species Bifidobacterium animalis, Bifidobacterium longum, and Prevotella sp. CAG and decreases in Parabacteroides distasonis and Clostridiales bacterium (P < 0.05). Compared with that of the placebo group, the gut metabolic potential of probiotic receivers exhibited increased levels of predicted microbial bioactive metabolites (linoleoyl ethanolamide, adrenergic acid, erythronic acid) and serum metabolites (5-dodecenoic acid, tryptophan, sphingomyelin) during/after intervention. Collectively, our results suggested that co-administering Probio-M8 synergized with conventional therapy to alleviate diseases associated with the gut-lung axis, like asthma, possibly via activating multiple anti-inflammatory pathways. IMPORTANCE The human gut microbiota has a potential effect on the pathogenesis of asthma and is closely related to the disease phenotype. Our trial has demonstrated that co-administering Probio-M8 synergized with conventional therapy to alleviate asthma symptoms. The findings of the present study provide new insights into the pathogenesis and treatment of asthma, mechanisms of novel therapeutic strategies, and application of probiotics-based therapy.

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.

Untargeted Metabolomic Profiling of Cuprizone-Induced Demyelination in Mouse Corpus Callosum by UPLC-Orbitrap/MS Reveals Potential Metabolic Biomarkers of CNS Demyelination Disorders

Multiple sclerosis (MS) is a neurodegenerative disorder characterized by periodic neuronal demyelination, which leads to a range of symptoms and eventually to disability. The goal of this research was to use UPLC-Orbitrap/MS to identify validated biomarkers and explore the metabolic mechanisms of MS in mice. Thirty-two C57BL/6 male mice were randomized into two groups that were fed either normal food or 0.2% CPZ for 11 weeks. The mouse demyelination model was assessed by LFB and the expression of MBP by immunofluorescence and immunohistochemistry. The metabolites of the corpus callosum were quantified using UPLC-Orbitrap/MS. The mouse pole climbing experiment was used to assess coordination ability. Multivariate statistical analysis was adopted for screening differential metabolites, and the ingenuity pathway analysis (IPA) was used to reveal the metabolite interaction network. We successfully established the demyelination model. The CPZ group slowly lost weight and showed an increased pole climbing time during feeding compared to the CON group. A total of 81 metabolites (VIP > 1 and P < 0.05) were determined to be enriched in 24 metabolic pathways; 41 metabolites were markedly increased, while 40 metabolites were markedly decreased in the CPZ group. The IPA results revealed that these 81 biomarker metabolites were associated with neuregulin signaling, PI3K-AKT signaling, mTOR signaling, and ERK/MAPK signaling. KEGG pathway analysis showed that two significantly different metabolic pathways were enriched, namely, the glycerophospholipid and sphingolipid metabolic pathways, comprising a total of nine biomarkers. Receiver operating characteristic analysis showed that the metabolites (e.g., PE (16 : 0/22 : 6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), PC (18 : 0/22 : 4(7Z, 10Z, 13Z, 16Z)), cytidine 5′-diphosphocholine, PS (18 : 0/22 : 6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), glycerol 3-phosphate, SM (d18 : 0/16 : 1(9Z)), Cer (d18:1/18 : 0), galabiosylceramide (d18:1/18 : 0), and GlcCer (d18:1/18 : 0)) have good discrimination ability for the CPZ group. In conclusion, the differential metabolites have great potential to serve as biomarkers of demyelinating diseases. In addition, we identified metabolic pathways associated with CPZ-induced demyelination pathogenesis, which provided a new perspective for understanding the relationship between metabolites and CNS demyelination pathogenesis.

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.

Nitroalkene fatty acids modulate bile acid metabolism and lung function in obese asthma

Bile acid profiles are altered in obese individuals with asthma. Thus, we sought to better understand how obesity-related systemic changes contribute to lung pathophysiology. We also test the therapeutic potential of nitro-oleic acid (NO₂-OA), a regulator of metabolic and inflammatory signaling pathways, to mitigate allergen and obesity-induced lung function decline in a murine model of asthma. Bile acids were measured in the plasma of healthy subjects and individuals with asthma and serum and lung tissue of mice with and without allergic airway disease (AAD). Lung function, indices of inflammation and hepatic bile acid enzyme expression were measured in obese mice with house dust mite-induced AAD treated with vehicle or NO₂-OA. Serum levels of glycocholic acid and glycoursodeoxycholic acid clinically correlate with body mass index and airway hyperreactivity whereas murine levels of β-muricholic acid and tauro-β-muricholic acid were significantly increased and positively correlated with impaired lung function in obese mice with AAD. NO₂-OA reduced murine bile acid levels by modulating hepatic expression of bile acid synthesis enzymes, with a concomitant reduction in small airway resistance and tissue elastance. Bile acids correlate to body mass index and lung function decline and the signaling actions of nitroalkenes can limit AAD by modulating bile acid metabolism, revealing a potential pharmacologic approach to improving the current standard of care.

Research Progress of Metabolomics in Asthma

Asthma is a highly heterogeneous disease, but the pathogenesis of asthma is still unclear. It is well known that the airway inflammatory immune response is the pathological basis of asthma. Metabolomics is a systems biology method to analyze the difference of low molecular weight metabolites (<1.5 kDa) and explore the relationship between metabolic small molecules and pathophysiological changes of the organisms. The functional interdependence between immune response and metabolic regulation is one of the cores of the body's steady-state regulation, and its dysfunction will lead to a series of metabolic disorders. The signal transduction effect of specific metabolites may affect the occurrence of the airway inflammatory immune response, which may be closely related to the pathogenesis of asthma. Emerging metabolomic analysis may provide insights into the pathogenesis and diagnosis of asthma. The review aims to analyze the changes of metabolites in blood/serum/plasma, urine, lung tissue, and exhaled breath condensate (EBC) samples, and further reveals the potential pathogenesis of asthma according to the disordered metabolic pathways.

Characterization of anaphylaxis reveals different metabolic changes depending on severity and triggers

BACKGROUND

Despite the increasing incidence of anaphylaxis, its underlying molecular mechanisms and biomarkers for appropriate diagnosis remain undetermined. The rapid onset and potentially fatal outcome in the absence of managed treatment prevent its study. Up today, there are still no known biomarkers that allow an unequivocal diagnosis. Therefore, the aim of this study was to explore metabolic changes in patients suffering anaphylactic reactions depending on the trigger (food and/or drug) and severity (moderate and severe) in a real-life set-up.

METHODS

Eighteen episodes of anaphylaxis, one per patient, were analysed. Sera were collected during the acute phase (T1), the recovery phase (T2) and around 2-3 months after the anaphylactic reaction (T0: basal state). Reactions were classified following an exhaustive allergological evaluation for severity and trigger. Sera samples were analysed using untargeted metabolomics combining liquid chromatography coupled to mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (¹ H-NMR).

RESULTS

'Food T1 vs T2' and 'moderate T1 vs T2' anaphylaxis comparisons showed clear metabolic patterns during the onset of an anaphylactic reaction, which differed from those induced by drugs, food + drug or severe anaphylaxis. Moreover, the model of food anaphylaxis was able to distinguish the well-characterized IgE (antibiotics) from non-IgE-mediated anaphylaxis (nonsteroidal anti-inflammatory drugs), suggesting a differential metabolic pathway associated with the mechanism of action. Metabolic differences between 'moderate vs severe' at the acute phase T1 and at basal state T0 were studied. Among the altered metabolites, glucose, lipids, cortisol, betaine and oleamide were observed altered.

CONCLUSIONS

The results of this exploratory study provide the first evidence that different anaphylactic triggers or severity induce differential metabolic changes along time or at specific time-point, respectively. Besides, the basal status T0 might identify high-risk patients, thus opening new ways to understand, diagnose and treat anaphylaxis.

Altered IgA Response to Gut Bacteria Is Associated with Childhood Asthma in Peru

Alterations in gut microbiota in early life have been associated with the development of asthma; however, the role of gut bacteria or the IgA response to gut bacteria in school-aged children with asthma is unclear. To address this question, we profiled the microbial populations in fecal and nasal swab samples by 16S rRNA sequencing from 40 asthma and 40 control children aged 9-17 y from Peru. Clinical history and laboratory evaluation of asthma and allergy were obtained. Fecal samples were analyzed by flow cytometry and sorted into IgA+ and IgA- subsets for 16S rRNA sequencing. We found that the fecal or nasal microbial 16S rRNA diversity and frequency of IgA+ fecal bacteria did not differ between children with or without asthma. However, the α diversity of fecal IgA+ bacteria was decreased in asthma compared with control. Machine learning analysis of fecal bacterial IgA-enrichment data revealed loss of IgA binding to the Blautia, Ruminococcus, and Lachnospiraceae taxa in children with asthma compared with controls. In addition, this loss of IgA binding was associated with worse asthma control (Asthma Control Test) and increased odds of severe as opposed to mild to moderate asthma. Thus, despite little to no change in the microbiota, children with asthma exhibit an altered host IgA response to gut bacteria compared with control participants. Notably, the signature of altered IgA responses is loss of IgA binding, in particular to members of Clostridia spp., which is associated with greater severity of asthma.

Microbiota and human allergic diseases: the company we keep

Environmental, maternal and early life microbial/immune networks program human developmental trajectories and health outcomes and strongly modify allergic disease risk. The effects of environmental microbiota are illustrated by the 'farm effect' (the protection against asthma and allergy conferred by growing up on a traditional farm) and other natural experiments in populations exposed to microbe-rich environments. The role of gut microbiome maturation in the asthma/allergy trajectory is demonstrated by the most recent farm studies, which identified microbial metabolites specifically associated with asthma protection, and studies in other cohorts, which defined dynamic microbial community profiles associated with allergic disease phenotypes. Current and future studies in germ-free mice associated with gut microbiota from human disease states are providing novel mechanistic insights into the role of microbiota in shaping immune function and allergic disease susceptibility.