Metabolic interactions in asthma

Farraia, Mariana; Rufo, João Cavaleiro; Paciência, Inês; Mendes, Francisca de Castro; Delgado, Luís; Boechat, José Laerte; Moreira, André

doi:10.23822/eurannaci.1764-1489.101

Cited by 10 publications

(7 citation statements)

References 55 publications

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“…Other metabolites significantly altered in UC patients are arginine, which is related to the nitric oxide (NO) pathway 38,41‐44 ; and leucine, associated with the activation of mTORC1 pathways responsible for T cells activation, proliferation and differentiation 45 …”

Section: Discussionmentioning

confidence: 99%

“…Other metabolites significantly altered in UC patients are arginine, which is related to the nitric oxide (NO) pathway 38,[41][42][43][44] ; and leucine, associated with the activation of mTORC1 pathways responsible for T cells activation, proliferation and differentiation. 45 Furthermore, proteomic analysis reveal that UC patients seems to have an increased pro-inflammatory T cell response, which is also supported but the changes in S1P and leucine abovementioned.…”

Section: Discussionmentioning

confidence: 99%

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

Delgado-Dolset

Obeso

Rodríguez-Coira

et al. 2021

Allergy

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

Delgado-Dolset

Obeso

Rodríguez-Coira

et al. 2021

Allergy

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“…[1,[3][4][5][6] This metabolome, governed by the interaction of a person's genetics with diet, environmental factors, and the gut microbiome, provides the closest representation of the functional phenotype, thus giving insights into metabolic changes in health and disease. [2,[7][8][9] So far, metabolomic fingerprinting has emerged as a powerful technique to uncover biologically relevant biomarkers and pathway alterations, contributing to a variety of complex diseases, including obesity, diabetes, inflammatory bowel diseases, and a variety of cancers. [3,[10][11][12][13] In this regard, the analysis of the metabolome provides unprecedented opportunities in the quest for biomarkers of IgE-mediated allergic diseases.…”

Section: Introductionmentioning

confidence: 99%

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

Paepe

Gijseghem

Spiegeleer

et al. 2021

Molecular Nutrition Food Res

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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.

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“…In summary, metabolomics can discriminate between healthy individuals and patients with bronchial asthma. Globally, the most frequently identified metabolites, although with differences across studies, have involved energy homeostasis, lipid metabolism, tricarboxylic acid cycle, oxidative stress, hypoxia-associated molecules and various metabolites associated with immunoinflammatory processes that may be relevant to the underlying immunopathology of asthma [ 49 , 93 , 94 ]. Most of these affected metabolic pathways are concordant with the fact that asthma is a chronic, inflammatory disease, which requires changes in energy supply and possibly also metabolic reprogramming, namely in immune cells involved in the process.…”

Section: Main Metabolomic Signatures and Their Potential Implications In Adult Asthmamentioning

confidence: 99%

“…The reproducibility of metabolomics signatures in asthma may also be checked by comparing results between children and adult studies, since finding similar results will strengthen the possible relevance of detected changes. In fact, several studies in children and in adults have coincided in the main metabolites, at least regarding discrimination between asthma and a healthy state [ 32 , 64 , 88 , 92 , 94 ]. However, comparative studies regarding the capacity to discriminate between asthma inflammatory and/or clinical phenotypes are necessary, although the previously mentioned study by Abdel-Aziz [ 113 ], which showed the capacity of eNose metabolomics in exhaled breath to predict an atopic asthma phenotype in adults and children, is a good example of reproducibility.…”

Section: Reproducibility and Stability Of Asthma-related Metabolic Signatures: Of Validation Cohorts Time Stability Age Sex And Other Facmentioning

confidence: 99%

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

et al. 2021

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

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Metabolic interactions in asthma

Cited by 10 publications

References 55 publications

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

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

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

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

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