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Background Methods Results Conclusions The pathological mechanism of the gastrointestinal forms of food allergies is less understood in comparison to other clinical phenotypes, such as asthma and anaphylaxis Importantly, high‐IgE levels are a poor prognostic factor in gastrointestinal allergies.This study investigated how high‐IgE levels influence the development of intestinal inflammation and the metabolome in allergic enteritis (AE), using IgE knock‐in (IgEki) mice expressing high levels of IgE. In addition, correlation of the altered metabolome with gut microbiome was analysed.Ovalbumin‐sensitized and egg‐white diet‐fed (OVA/EW) BALB/c WT mice developed moderate AE, whereas OVA/EW IgEki mice induced more aggravated intestinal inflammation with enhanced eosinophil accumulation. Untargeted metabolomics detected the increased levels of N‐tau‐methylhistamine and 2,3‐butanediol, and reduced levels of butyric acid in faeces and/or sera of OVA/EW IgEki mice, which was accompanied with reduced Clostridium and increased Lactobacillus at the genus level. Non‐sensitized and egg‐white diet‐fed (NC/EW) WT mice did not exhibit any signs of AE, whereas NC/EW IgEki mice developed marginal degrees of AE. Compared to NC/EW WT mice, enhanced levels of lysophospholipids, sphinganine and sphingosine were detected in serum and faecal samples of NC/EW IgEki mice. In addition, several associations of altered metabolome with gut microbiome—for example Akkermansia with lysophosphatidylserine—were detected.Our results suggest that high‐IgE levels alter intestinal and systemic levels of endogenous and microbiota‐associated metabolites in experimental AE. This study contributes to deepening the knowledge of molecular mechanisms for the development of AE and provides clues to advance diagnostic and therapeutic strategies of allergic diseases. [ABSTRACT FROM AUTHOR]

Allergy, diet, metabolome, metabolomics, microbiota, serum Keywords: allergy; diet; metabolome; metabolomics; microbiota; serum EN allergy diet metabolome metabolomics microbiota serum 2306 2308 3 07/02/21 20210701 NES 210701 INTRODUCTION Metabolomics is the science focused on the study of the metabolism in living organisms.1 Their aim is to measure the metabolites that are the intermediate and final molecules of the biological processes. [Extracted from the article]

Background: Mechanisms causing the onset and perpetuation of inflammation in severe allergic patients remain unknown. Our previous studies suggested that severe allergic inflammation is linked to platelet dysfunction. Methods: Platelet‐rich plasma (PRP) and platelet‐poor plasma (PPP) samples were obtained by platelet‐apheresis from severe (n = 7) and mild (n = 10) allergic patients and nonallergic subjects (n = 9) to perform platelet lipidomics by liquid chromatography coupled to mass spectrometry (LC–MS) and RNA‐seq analysis. Significant metabolites and transcripts were used to identify compromised biological pathways in the severe phenotype. Platelet and inflammation‐related proteins were quantified by Luminex. Results: Platelets from severe allergic patients were characterized by high levels of ceramides, phosphoinositols, phosphocholines, and sphingomyelins. In contrast, they showed a decrease in eicosanoid precursor levels. Biological pathway analysis performed with the significant lipids revealed the alteration of phospholipases, calcium‐dependent events, and linolenic metabolism. RNAseq confirmed mRNA overexpression of genes related to platelet activation and arachidonic acid metabolism in the severe phenotypes. Pathway analysis indicated the alteration of NOD, MAPK, TLR, TNF, and IL‐17 pathways in the severe phenotype. P‐Selectin and IL‐17AF proteins were increased in the severe phenotype. Conclusions: This study demonstrates that platelet lipid, mRNA, and protein content is different according to allergy severity. These findings suggest that platelet load is a potential source of biomarkers and a new chance for therapeutic targets in severe inflammatory pathologies. [ABSTRACT FROM AUTHOR]

Allergic diseases are allergen‐induced immunological disorders characterized by the development of type 2 immunity and IgE responses. The prevalence of allergic diseases has been on the rise alike cardiovascular disease (CVD), which affects arteries of different organs such as the heart, the kidney and the brain. The underlying cause of CVD is often atherosclerosis, a disease distinguished by endothelial dysfunction, fibrofatty material accumulation in the intima of the artery wall, smooth muscle cell proliferation, and Th1 inflammation. The opposed T‐cell identity of allergy and atherosclerosis implies an atheroprotective role for Th2 cells by counteracting Th1 responses. Yet, the clinical association between allergic disease and CVD argues against it. Within, we review different phases of allergic pathology, basic immunological mechanisms of atherosclerosis and the clinical association between allergic diseases (particularly asthma, atopic dermatitis, allergic rhinitis and food allergy) and CVD. Then, we discuss putative atherogenic mechanisms of type 2 immunity and allergic inflammation including acute allergic reactions (IgE, IgG1, mast cells, macrophages and allergic mediators such as vasoactive components, growth factors and those derived from the complement, contact and coagulation systems) and late phase inflammation (Th2 cells, eosinophils, type 2 innate‐like lymphoid cells, alarmins, IL‐4, IL‐5, IL‐9, IL‐13 and IL‐17). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 (1H‐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. [ABSTRACT FROM AUTHOR]

Background: Several studies have shown a correlation between an altered metabolome and respiratory allergies. The epithelial barrier hypothesis proposes that an epithelial barrier dysfunction can result in allergic diseases development. Der p 1 allergen from house dust mite is a renowned epithelial barrier disruptor and allergy initiator due to its cysteine-protease activity. Here, we compared the metabolic profile of the bronchial epithelium exposed or not to Der p 1 during barrier establishment to understand its active role in allergy development. Methods: Calu-3 cells were cultivated in air-liquid interface cultures and exposed to either Der p 1 or Ole e 1 allergens during barrier establishment. The comparative metabolomics analysis of apical and basolateral media were performed using liquid chromatography and capillary electrophoresis both coupled to mass spectrometry. Results: We showed that epithelial barrier disruption by Der p 1 was associated with a specific metabolic profile, which was highly dependent on the state of the epithelium at the time of contact. Moreover, an apical-basolateral distribution of the metabolites was also observed, indicating a compartmentalization of the response with differential metabolic patterns. A number of metabolites were changed by Der p 1, mainly related to amino acids metabolism, such as L-arginine, L-kynurenine and L-methionine. Conclusion: This work is the first report on the metabolic response in human bronchial epithelial cells associated with cysteine-protease Der p 1 activity, which could contribute to allergy development. Moreover, it supports a reformulated epithelial barrier hypothesis that might help to explain allergies and their increasing prevalence. [ABSTRACT FROM AUTHOR]

Background: Sublingual allergen‐specific immunotherapy (SLIT) intervention improves the control of grass pollen allergy by maintaining allergen tolerance after cessation. Despite its widespread use, little is known about systemic effects and kinetics associated to SLIT, as well as the influence of the patient sensitization phenotype (Mono‐ or Poly‐sensitized). In this quest, omics sciences could help to gain new insights to understand SLIT effects. Methods: 47 grass‐pollen‐allergic patients were enrolled in a double‐blind, placebo‐controlled, multicenter trial using GRAZAX® during 2 years. Immunological assays (sIgE, sIgG4, and ISAC) were carried out to 31 patients who finished the trial. Additionally, serum and PBMCs samples were analyzed by metabolomics and transcriptomics, respectively. Based on their sensitization level, 22 patients were allocated in Mono‐ or Poly‐sensitized groups, excluding patients allergic to epithelia. Individuals were compared based on their treatment (Active/Placebo) and sensitization level (Mono/Poly). Results: Kinetics of serological changes agreed with those previously described. At two years of SLIT, there are scarce systemic changes that could be associated to improvement in systemic inflammation. Poly‐sensitized patients presented a higher inflammation at inclusion, while Mono‐sensitized patients presented a reduced activity of mast cells and phagocytes as an effect of the treatment. Conclusions: The most relevant systemic change detected after two years of SLIT was the desensitization of effector cells, which was only detected in Mono‐sensitized patients. This change may be related to the clinical improvement, as previously reported, and, together with the other results, may explain why clinical effect is lost if SLIT is discontinued at this point. [ABSTRACT FROM AUTHOR]

Background: Prevalence and severity of allergic diseases have increased worldwide. To date, respiratory allergy phenotypes are not fully characterized and, along with inflammation progression, treatment is increasingly complex and expensive. Profilin sensitization constitutes a good model to study the progression of allergic inflammation. Our aim was to identify the underlying mechanisms and the associated biomarkers of this progression, focusing on severe phenotypes, using transcriptomics and metabolomics. Methods: Twenty‐five subjects were included in the study. Plasma samples were analyzed using gas and liquid chromatography coupled to mass spectrometry (GC‐MS and LC‐MS, respectively). Individuals were classified in four groups—"nonallergic," "mild," "moderate," and "severe"—based on their clinical history, their response to an oral challenge test with profilin, and after a refinement using a mathematical metabolomic model. PBMCs were used for microarray analysis. Results: We found a set of transcripts and metabolites that were specific for the "severe" phenotype. By metabolomics, a decrease in carbohydrates and pyruvate and an increase in lactate were detected, suggesting aerobic glycolysis. Other metabolites were incremented in "severe" group: lysophospholipids, sphingosine‐1‐phosphate, sphinganine‐1‐phosphate, and lauric, myristic, palmitic, and oleic fatty acids. On the other hand, carnitines were decreased along severity. Significant transcripts in the "severe" group were found to be downregulated and were associated with platelet functions, protein synthesis, histone modification, and fatty acid metabolism. Conclusion: We have found evidence that points to the association of severe allergic inflammation with platelet functions alteration, together with reduced protein synthesis, and switch of immune cells to aerobic glycolysis. Altered energy metabolism is connected to the immune cell activation. Sphingolipid metabolism variations and downregulation of platelet‐related transcripts in severe allergic patients point to an alteration of platelet functions. Multiple lipid membrane mediators including lysophosphatidylcholines (LPC), lysophosphoserines (LPS), and lysophosphoetanolamines (LPE) were found increased in severe allergic patients. [ABSTRACT FROM AUTHOR]