1. Investigación

Background: The pathological mechanism of the gastrointestinal forms of food aller-gies is less understood in comparison to other clinical phenotypes, such as asthmaand anaphylaxis Importantly, high-IgE levels are a poor prognostic factor in gastroin-testinal allergies.Methods: This study investigated how high-IgE levels influence the development ofintestinal 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 me-tabolome with gut microbiome was analysed.Results: Ovalbumin-sensitized and egg-white diet-fed (OVA/EW) BALB/c WT micedeveloped moderate AE, whereas OVA/EW IgEki mice induced more aggravated in-testinal inflammation with enhanced eosinophil accumulation. Untargeted metabo-lomics 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, whichwas 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 anysigns of AE, whereas NC/EW IgEki mice developed marginal degrees of AE. Comparedto NC/EW WT mice, enhanced levels of lysophospholipids, sphinganine and sphin-gosine were detected in serum and faecal samples of NC/EW IgEki mice. In addi-tion, several associations of altered metabolome with gut microbiome—for exampleAkkermansia with lysophosphatidylserine—were detected.Conclusions: Our results suggest that high-IgE levels alter intestinal and systemic levelsof endogenous and microbiota-associated metabolites in experimental AE. This studycontributes to deepening the knowledge of molecular mechanisms for the developmentof AE and provides clues to advance diagnostic and therapeutic strategies of allergicdiseases

The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by persistent symptoms associated to the development of nasal polyps. To this day, the molecular mechanisms involved are still not well defined. However, it has been suggested that a sustained inflammation as allergy is involved in its onset. In this exploratory study, the aim was to investigate the effect of the allergic status in the development of CRSwNP. To achieve this, we recruited 22 patients with CRSwNP and classified them in non-allergic and allergic using ImmunoCAP ISAC molecular diagnosis. Plasma samples were analyzed using liquid chromatography coupled to mass spectrometry (LC-MS). Subsequently, significant metabolites from plasma that were commercially available were then analyzed by targeted analysis in some nasal polyps. Additionally, nasal polyp and nasal mucosa samples were examined for eosinophils, neutrophils, CD3+ and CD11c+ cells, as well as collagen deposition and goblet cell hyperplasia. We found that 9 out of the 22 patients were sensitized to some aeroallergens (named as allergic CRSwNP). The other 13 patients had no sensitizations (non-allergic CRSwNP). Regarding metabolomics, bilirubin, cortisol, lysophosphatidylcholines (LPCs) 16:0, 18:0 and 20:4 and lysophosphatidylinositol (LPI) 20:4, which are usually related to a sustained allergic inflammation, were unexpectedly increased in plasma of non-allergic CRSwNP compared to allergic CRSwNP. LPC 16:0, LPC 18:0 and LPI 20:4 followed the same trend in nasal polyp as they did in plasma. Comparison of nasal polyps with nasal mucosa showed a significant increase in eosinophils (p < 0.001) and neutrophils (p < 0.01) in allergic CRSwNP. There were more eosinophils in polyps of non-allergic CRSwNP than in their nasal mucosa (p < 0.01). Polyps from non-allergic CRSwNP had less eosinophils than the polyps of allergic CRSwNP (p < 0.05) and reduced amounts of collagen compared to their nasal mucosa (p < 0.001). Our data suggests that there is a systemic inflammatory response associated to CRSwNP in the absence of allergy, which could be accountable for the nasal polyp development. Allergic CRSwNP presented a higher number of eosinophils in nasal polyps, suggesting that eosinophilia might be connected to the development of nasal polyps in this phenotype.

In the last decades have emerged new technological platforms that allow evaluation of genes, transcripts, proteins, or metabolites of a living being, so-called omics sciences. More importantly, new technics for their integration have provided access to a complete set of information of the current conditions and features of a specific biological sample in a precise moment. Thus, omic sciences are now considered an essential tool for patient stratification in base to their severity, to understand disease progression and to identify new biomarkers. Severe patients, that are out of control, provide an excellent model to understand disease evolution and to identify new intervention and biomarkers strategies. Here we discuss the use of metabolomics to understand severity in allergic diseases in a strategy that opens new insights as well as identify new biological systems relevant for allergy progression. Metabolomics strategies are based in parallel evaluation of different allergy severity models by mean of untargeted analysis that allows the identification of potential biomarkers. Overlapping of different biomarkers in multiple models, provides information of general as well as specific biological systems involved in each model. Later a selected panel of biomarkers will be used in a target method to explore the diagnosis potential to stratify allergic patients.