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.

Allergic asthma is a prominent disease especially during childhood. Indoor allergens, in general, and particularly house dust mites (HDM) are the most prevalent sensitizers associated with allergic asthma. Available data show that 65–130 million people are mite-sensitized world-wide and as many as 50% of these are asthmatic. In fact, sensitization to HDM in the first years of life can produce devastating effects on pulmonary function leading to asthmatic syndromes that can be fatal. To date, there has been considerable research into the pathological pathways and structural changes associated with allergic asthma. However, limitations related to the disease heterogeneity and a lack of knowledge into its pathophysiology have impeded the generation of valuable data needed to appropriately phenotype patients and, subsequently, treat this disease. Here, we report a systematic and integral analysis of the disease, from airway remodelling to the immune response taking place throughout the disease stages. We present an overview of metabolomics, the management of complex multifactorial diseases through the analysis of all possible metabolites in a biological sample, obtaining a global interpretation of biological systems. Special interest is placed on the challenges to obtain biological samples and the methodological aspects to acquire relevant information, focusing on the identification of novel biomarkers associated with specific phenotypes of allergic asthma. We also present an overview of the metabolites cited in the literature, which have been related to inflammation and immune response in asthma and other allergy-related diseases.

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.

Allergic diseases, such as respiratory, cutaneous, and food allergy, have dramatically increased in prevalence over the last few decades. Recent research points to a central role of the microbiome, which is highly influenced by multiple environmental and dietary factors. It is well established that the microbiome can modulate the immune response, from cellular development to organ and tissue formation exerting its effects through multiple interactions with both the innate and acquired branches of the immune system. It has been described at some extent changes in environment and nutrition produce dysbiosis in the gut but also in the skin, and lung microbiome, inducing qualitative and quantitative changes in composition and metabolic activity. Here, we review the potential role of the skin, respiratory, and gastrointestinal tract (GIT) microbiomes in allergic diseases. In the GIT, the microbiome has been proven to be important in developing either effector or tolerant responses to different antigens by balancing the activities of Th1 and Th2 cells. In the lung, the microbiome may play a role in driving asthma endotype polarization, by adjusting the balance between Th2 and Th17 patterns. Bacterial dysbiosis is associated with chronic inflammatory disorders of the skin, such as atopic dermatitis and psoriasis. Thus, the microbiome can be considered a therapeutical target for treating inflammatory diseases, such as allergy. Despite some limitations, interventions with probiotics, prebiotics, and/or synbiotics seem promising for the development of a preventive therapy by restoring altered microbiome functionality, or as an adjuvant in specific immunotherapy.

Background: In areas of high exposure to grass pollen, allergic patients are frequently sensitized to profilin, and some experience severe profilin-mediated food-induced reactions. This specific population of patients is ideal to study the relationship between respiratory and food allergies. Objective: We sought to determine the role of oral mucosal epithelial barrier integrity in profilin-mediated allergic reactions. Methods: Thirty-eight patients with profilin allergy stratified into mild or severe according to their clinical history and response to a profilin challenge test and 6 nonallergic subjects were recruited. Oral mucosal biopsies were used for measurement of CD11c, CD3, CD4, tryptase, claudin-1, occludin, E-cadherin, and vascular endothelial growth factor A levels; Masson trichrome staining; and POSTN, IL33, TPSAB, TPSB, and CMA gene expression analysis by using quantitative RT-PCR. Blood samples were used for basophil activation tests. Results: Distinct features of the group with severe allergy included the following: (1) impaired epithelial integrity with reduced expression of claudin-1, occludin, and E-cadherin and decreased numbers of epithelial cells, which is indicative of acanthosis, higher collagen deposition, and angiogenesis; (2) inflammatory immune response in the mucosa, with an increased number of CD11c1 and CD41 infiltrates and increased expression of the cytokine genes POSTN and IL33; and (3) a 10-fold increased sensitivity of basophils to profilin. Conclusions: Patients with profilin allergy present with significant damage to the oral mucosal epithelial barrier, which might allow profilin penetration into the oral mucosa and induction of local inflammation. Additionally, severely allergic patients presented with increased sensitivity of effector cells. (J Allergy Clin Immunol 2019;143:681-90.)

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