1. Investigación

Chronic rhinosinusitis (CRS) is a clinical syndrome defined by typical sinonasal symptoms persisting for at least 12weeks. CRS is divided into two distinct phenotypes, CRS with nasal polyps (CRSwNP) and without (CRSsNP). The aim of the review is to provide an update on the current knowledge in CRS endotypes. The prevailing hypothesis regarding the pathogenesis of CRS suggests that dysfunctional interactions between the host and environmental stressors at the mucosal surface drive the diverse inflammatory mechanisms. Genetic and epigenetic variations in the mucosal immune system are believed to play a significant role in the pathomechanisms of CRS. Various environmental agents (such as microbes and irritants) have been implicated in CRS. In a healthy state, the sinonasal mucosa acts as a barrier, modulating environmental stimulation and mounting appropriate immune responses against pathogens with minimal tissue damage. Different endotypes may exist based on the specific mechanistic pathways driving the chronic tissue inflammation of CRS. There is a need to understand endotypes in order to better predict, diagnose, and treat CRS. This literature review provides an update on the role of the endotypes in CRS and the limitations of endotyping CRS in clinical practice. Understanding of the pathogenesis and optimal management of CRS has progressed significantly in the last decades; however, there still are several unmet needs in endotype research.

The diagnosis of mast cell activation syndrome (MCAS) is defined by 3 criteria: (1) typical clinical signs and symptoms of acute, recurrent (episodic), and systemic mast cell activation (MCA); (2) increase in tryptase level to >20% + 2 ng/mL within 1-4 hours after onset of the acute crisis; and (3) response of MCA symptoms to antimediator therapy. Classification of MCAS requires highly sensitive and specific methodological approaches for the assessment of clonal bone marrow mast cells at low frequencies. The Spanish Network on Mastocytosis score has been used successfully as a predictive model for selecting MCAS candidates for bone marrow studies based on a high probability of an underlying clonal mast cell disorder. In this article, we propose a diagnostic algorithm and focus on the practical evaluation and management of patients with suspected MCAS.

Background: The clinical burden of influenza is increasing worldwide. Aging, immunosuppression, and underlying respiratory illness are determinants of poor clinical outcomes, including greater mortality. Bac- terial infections seem to be the main reason. Updated information on the role of bacterial infection as the cause of complications would be of value in improving the prognosis of patients with influenza. Methods: A systematic review and meta-analysis were performed by using the PubMed repository using keywords like: Influenza, H1N1, Streptococcus pneumoniae , bacterial coinfection, secondary coinfection, bacterial complications in pneumonia, and seasonal influenza. Only articles written in English were in- cluded in publications from 2010 to 2020. The analyses were conducted following the preferred reporting items for systematic review and meta-analyses guidelines. The results were independently validated using a TrinetX database cohort of roughly 4 million patients. Results: We included 135 studies that contained data from 48,259 patients hospitalized with influenza of any age. Bacterial infections were diagnosed in 5391 (11.2%). Streptococcus pneumoniae (30.7%) and Staphylococcus aureus (30.4%) were the most frequent microorganisms, followed by Haemophilus influenzae (7.1%) and Pseudomonas aeruginosa (5.9%). The random-effects model of the meta-analysis indicated that bacterial infections posed a 3.4-fold increased risk of death compared with influenza infection alone. Unexpectedly, asthma was protective (odds ratio 0.8). Conclusion: Bacterial infections diagnosed in 11.2% of patients with influenza increase 3.4-fold the mor- tality risk. S. pneumoniae, S. aureus, H. influenzae , and P. aeruginosa account for nearly 75% of the cases. Earlier diagnosis and use of antibiotics should improve outcomes in this population.

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.

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.

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.

The purpose of this Special Issue is to provide evidence of the utility of metabolomics in asthma (pediatric and adult), and to show their potential application in clinical practice. Moreover, current challenges in integrating metabolomics in asthma management are also critically presented

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.

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, placebocontrolled, 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.

Progressive knowledge of allergenic structures resulted in a broad availability of allergenic molecules for diagnosis. Component resolved diagnosis allowed a better understanding of patient sensitization patterns, facilitating allergen immunotherapy decisions. In parallel to the discovery of allergenic molecules, there was a progressive development of a regulation framework that affected both in vitro diagnostics and Allergen Immunotherapy products. With a progressive understanding of underlying mechanisms associated to Allergen immunotherapy and an increasing experience of application of molecular diagnosis in daily life, we focus in analyzing the evidencesof the value provided by molecular allergology in daily clinical practice, with a focus on Allergen Immunotherapy decisions.